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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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n=++this.pendingBackendInitId,a=r.then(s=>n<this.pendingBackendInitId?!1:(this.registry[e]=s,this.pendingBackendInit=null,!0)).catch(s=>(n<this.pendingBackendInitId||(this.pendingBackendInit=null,Cs(`Initialization of backend ${e} failed`),Cs(s.stack||s.message)),!1));return this.pendingBackendInit=a,{success:a,asyncInit:!0}}else return this.registry[e]=r,{success:!0,asyncInit:!1}}catch(r){return Cs(`Initialization of backend ${e} failed`),Cs(r.stack||r.message),{success:!1,asyncInit:!1}}}removeBackend(e){if(!(e in this.registryFactory))throw new Error(`${e} backend not found in registry`);this.backendName===e&&this.pendingBackendInit!=null&&this.pendingBackendInitId++,e in this.registry&&(this.disposeRegisteredKernels(e),this.registry[e].dispose(),delete this.registry[e]),delete this.registryFactory[e],this.backendName===e&&(this.pendingBackendInit=null,this.backendName=null,this.backendInstance=null)}getSortedBackends(){if(Object.keys(this.registryFactory).length===0)throw new 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Error("When calling with two arguments, the 2nd argument to tidy() must be a function");r=e}let n;return this.scopedRun(()=>this.startScope(r),()=>this.endScope(n),()=>(n=t(),n instanceof Promise&&console.error("Cannot return a Promise inside of tidy."),n))}scopedRun(e,t,r){e();try{let n=r();return t(),n}catch(n){throw t(),n}}nextTensorId(){return Cg.nextTensorId++}nextVariableId(){return Cg.nextVariableId++}clone(e){let t=B.runKernel(fi,{x:e}),r={x:e},n=s=>({x:()=>{let i="float32",o={x:s},l={dtype:i};return B.runKernel(Qs,o,l)}}),a=[];return this.addTapeNode(this.state.activeScope.name,r,[t],n,a,{}),t}runKernel(e,t,r){if(this.backendName==null&&this.backend,N0(e,this.backendName)==null)throw new Error(`Kernel '${e}' not registered for backend '${this.backendName}'`);return this.runKernelFunc({kernelName:e,inputs:t,attrs:r})}shouldCheckForMemLeaks(){return this.ENV.getBool("IS_TEST")}checkKernelForMemLeak(e,t,r){let n=this.backend.numDataIds(),a=0;r.forEach(o=>{a+=o.dtype==="complex64"?3:1});let s=this.state.numDataMovesStack[this.state.numDataMovesStack.length-1],i=n-t-a-s;if(i>0)throw new Error(`Backend '${this.backendName}' has an internal memory leak (${i} data ids) after running '${e}'`)}runKernelFunc(e){let t,r=[],n=this.isTapeOn(),a=this.state.numBytes,s=this.state.numTensors;this.shouldCheckForMemLeaks()&&this.state.numDataMovesStack.push(0);let i;this.backendName==null&&this.backend;let o,l=pg(e)?e.kernelName:this.state.activeScope!=null?this.state.activeScope.name:"";if(pg(e)){let{kernelName:c,inputs:m,attrs:f}=e;this.backendName==null&&this.backend;let g=N0(c,this.backendName);_(g!=null,()=>`Cannot find registered kernel '${c}' for backend '${this.backendName}'`),i=()=>{let y=this.backend.numDataIds();o=g.kernelFunc({inputs:m,attrs:f,backend:this.backend});let A=Array.isArray(o)?o:[o];this.shouldCheckForMemLeaks()&&this.checkKernelForMemLeak(c,y,A);let x=A.map(b=>b.rank!=null?b:this.makeTensorFromTensorInfo(b));if(n){let b=this.getTensorsForGradient(c,m,x);r=this.saveTensorsForBackwardMode(b)}return x}}else{let{forwardFunc:c}=e,m=f=>{!n||(r=f.map(g=>this.keep(this.clone(g))))};i=()=>{let f=this.backend.numDataIds();o=this.tidy(()=>c(this.backend,m));let g=Array.isArray(o)?o:[o];return this.shouldCheckForMemLeaks()&&this.checkKernelForMemLeak(l,f,g),g}}let{inputs:u,attrs:d}=e,h=pg(e)?null:e.backwardsFunc,p;return this.scopedRun(()=>this.state.kernelDepth++,()=>this.state.kernelDepth--,()=>{!this.ENV.getBool("DEBUG")&&!this.state.profiling?t=i():(p=this.profiler.profileKernel(l,u,()=>i()),this.ENV.getBool("DEBUG")&&this.profiler.logKernelProfile(p),t=p.outputs)}),n&&this.addTapeNode(l,u,t,h,r,d),this.state.profiling&&this.state.activeProfile.kernels.push({name:l,bytesAdded:this.state.numBytes-a,totalBytesSnapshot:this.state.numBytes,tensorsAdded:this.state.numTensors-s,totalTensorsSnapshot:this.state.numTensors,inputShapes:Object.keys(u).map(c=>u[c]!=null?u[c].shape:null),outputShapes:t.map(c=>c.shape),kernelTimeMs:p.timeMs,extraInfo:p.extraInfo}),Array.isArray(o)?t:t[0]}saveTensorsForBackwardMode(e){return e.map(t=>this.keep(this.clone(t)))}getTensorsForGradient(e,t,r){let n=Ig(e);if(n!=null){let a=n.inputsToSave||[],s=n.outputsToSave||[],i;n.saveAllInputs?(_(Array.isArray(t),()=>"saveAllInputs is true, expected inputs to be an array."),i=Object.keys(t).map(l=>t[l])):i=a.map(l=>t[l]);let o=r.filter((l,u)=>s[u]);return i.concat(o)}return[]}makeTensor(e,t,r,n){if(e==null)throw new Error("Values passed to engine.makeTensor() are null");r=r||"float32",n=n||this.backend;let a=e;r==="string"&&Ts(e[0])&&(a=e.map(o=>vh(o)));let s=n.write(a,t,r),i=new nt(t,r,s,this.nextTensorId());if(this.trackTensor(i,n),r==="string"){let o=this.state.tensorInfo.get(s),l=D7(a);this.state.numBytes+=l-o.bytes,o.bytes=l}return i}makeTensorFromDataId(e,t,r,n){r=r||"float32";let a={dataId:e,shape:t,dtype:r};return this.makeTensorFromTensorInfo(a,n)}makeTensorFromTensorInfo(e,t){let{dataId:r,shape:n,dtype:a}=e,s=new nt(n,a,r,this.nextTensorId());return this.trackTensor(s,t),s}makeVariable(e,t=!0,r,n){r=r||this.nextVariableId().toString(),n!=null&&n!==e.dtype&&(e=e.cast(n));let a=new Hp(e,t,r,this.nextTensorId());if(this.state.registeredVariables[a.name]!=null)throw new Error(`Variable with name ${a.name} was already registered`);return this.state.registeredVariables[a.name]=a,this.incRef(a,this.backend),a}trackTensor(e,t){this.state.numTensors++,e.dtype==="string"&&this.state.numStringTensors++;let r=0;e.dtype!=="complex64"&&e.dtype!=="string"&&(r=e.size*kg(e.dtype)),this.state.numBytes+=r,this.state.tensorInfo.has(e.dataId)||(this.state.numDataBuffers++,this.state.tensorInfo.set(e.dataId,{backend:t||this.backend,dtype:e.dtype,shape:e.shape,bytes:r})),e instanceof Hp||this.track(e)}incRef(e,t){this.trackTensor(e,t),this.backend.incRef(e.dataId)}removeDataId(e,t){this.state.tensorInfo.has(e)&&this.state.tensorInfo.get(e).backend===t&&(this.state.tensorInfo.delete(e),this.state.numDataBuffers--)}disposeTensor(e){if(!this.state.tensorInfo.has(e.dataId))return;let t=this.state.tensorInfo.get(e.dataId);if(this.state.numTensors--,e.dtype==="string"&&(this.state.numStringTensors--,this.state.numBytes-=t.bytes),e.dtype!=="complex64"&&e.dtype!=="string"){let r=e.size*kg(e.dtype);this.state.numBytes-=r}t.backend.disposeData(e.dataId)&&this.removeDataId(e.dataId,t.backend)}disposeVariables(){for(let e in this.state.registeredVariables){let t=this.state.registeredVariables[e];this.disposeVariable(t)}}disposeVariable(e){this.disposeTensor(e),this.state.registeredVariables[e.name]!=null&&delete this.state.registeredVariables[e.name]}memory(){let e=this.backend.memory();return e.numTensors=this.state.numTensors,e.numDataBuffers=this.state.numDataBuffers,e.numBytes=this.state.numBytes,this.state.numStringTensors>0&&(e.unreliable=!0,e.reasons==null&&(e.reasons=[]),e.reasons.push("Memory usage by string tensors is approximate (2 bytes per character)")),e}async profile(e){this.state.profiling=!0;let t=this.state.numBytes,r=this.state.numTensors;this.state.activeProfile.kernels=[],this.state.activeProfile.result=await e(),this.state.profiling=!1,this.state.activeProfile.peakBytes=Math.max(...this.state.activeProfile.kernels.map(n=>n.totalBytesSnapshot)),this.state.activeProfile.newBytes=this.state.numBytes-t,this.state.activeProfile.newTensors=this.state.numTensors-r;for(let n of this.state.activeProfile.kernels)n.kernelTimeMs=await n.kernelTimeMs,n.extraInfo=await n.extraInfo;return this.state.activeProfile}isTapeOn(){return this.state.gradientDepth>0&&this.state.kernelDepth===0}addTapeNode(e,t,r,n,a,s){let i={id:this.state.nextTapeNodeId++,kernelName:e,inputs:t,outputs:r,saved:a},o=Ig(e);o!=null&&(n=o.gradFunc),n!=null&&(i.gradient=l=>(l=l.map((u,d)=>{if(u==null){let h=r[d],p=of(h.size,h.dtype);return this.makeTensor(p,h.shape,h.dtype)}return u}),n(l.length>1?l:l[0],a,s))),this.state.activeTape.push(i)}keep(e){return e.kept=!0,e}startTape(){this.state.gradientDepth===0&&(this.state.activeTape=[]),this.state.gradientDepth++}endTape(){this.state.gradientDepth--}startScope(e){let t={track:[],name:"unnamed scope",id:this.state.nextScopeId++};e&&(t.name=e),this.state.scopeStack.push(t),this.state.activeScope=t}endScope(e){let t=Ey(e),r=new Set(t.map(a=>a.id));for(let a=0;a<this.state.activeScope.track.length;a++){let s=this.state.activeScope.track[a];!s.kept&&!r.has(s.id)&&s.dispose()}let n=this.state.scopeStack.pop();this.state.activeScope=this.state.scopeStack.length===0?null:this.state.scopeStack[this.state.scopeStack.length-1],t.forEach(a=>{!a.kept&&a.scopeId===n.id&&this.track(a)})}gradients(e,t,r,n=!1){if(_(t.length>0,()=>"gradients() received an empty list of xs."),r!=null&&r.dtype!=="float32")throw new Error(`dy must have 'float32' dtype, but has '${r.dtype}'`);let a=this.scopedRun(()=>this.startTape(),()=>this.endTape(),()=>this.tidy("forward",e));_(a instanceof nt,()=>"The result y returned by f() must be a tensor.");let s=cM(this.state.activeTape,t,a);if(!n&&s.length===0&&t.length>0)throw new Error("Cannot compute gradient of y=f(x) with respect to x. 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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)}};sm.className="Adamax";Ui(sm);var Fh=class extends ns{constructor(e){super(),this.learningRate=e,this.setLearningRate(e)}applyGradients(e){(Array.isArray(e)?e.map(t=>t.name):Object.keys(e)).forEach((t,r)=>{let n=Array.isArray(e)?e[r].tensor:e[t];if(n==null)return;let a=B.registeredVariables[t];X(()=>{let s=le(L(this.c,n),a);a.assign(s)})}),this.incrementIterations()}setLearningRate(e){this.learningRate=e,this.c!=null&&this.c.dispose(),this.c=mr(Se(-e))}dispose(){this.c.dispose()}async getWeights(){return[await this.saveIterations()]}async setWeights(e){if(e=await this.extractIterations(e),e.length!==0)throw new Error("SGD optimizer does 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YD(e,t){let r=e[0].length;e.forEach((a,s)=>{_(a.length===r,()=>`Error in concat${r}D: rank of tensors[${s}] must be the same as the rank of the rest (${r})`)}),_(t>=0&&t<r,()=>`Error in concat${r}D: axis must be between 0 and ${r-1}.`);let n=e[0];e.forEach((a,s)=>{for(let i=0;i<r;i++)_(i===t||a[i]===n[i],()=>`Error in concat${r}D: Shape of tensors[${s}] (${a}) does not match the shape of the rest (${n}) along the non-concatenated axis ${s}.`)})}function JD(e,t){let r=e[0].slice();for(let n=1;n<e.length;n++)r[t]+=e[n][t];return r}var E3=30;function QD(e){return e<=E3?e:S0(e,Math.floor(Math.sqrt(e)))}function eL(e,t,r){let n=r*(typeof e=="number"?e:e[0]),a=t*(typeof e=="number"?e:e[1]);return[n,a]}function tL(e,t,r,n=!0){let a=[];if(n)a=a.concat(t.slice(0)),a.push(e[0]/r),a=a.concat(e.slice(1));else{a=a.concat(e[0]);let s=t.length;for(let i=0;i<s;++i)a=a.concat([e[i+1]/t[i],t[i]]);a=a.concat(e.slice(s+1))}return a}function rL(e,t,r=!0){let n=[];if(r){n.push(t);for(let 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t={};return t.className="linear",t.config={},Ag(t)}if(typeof e=="string"){let t={};return t.className=e,t.config={},Ag(t)}else return e instanceof ln?e:Ag(e)}function e5(e){if(e!=null&&typeof e!="object")throw new Error(`Argument to L1L2 regularizer's constructor is expected to be an object, but received: ${e}`)}var Qw=class extends ue.Serializable{},Lh=class extends Qw{constructor(e){super(),e5(e),this.l1=e==null||e.l1==null?.01:e.l1,this.l2=e==null||e.l2==null?.01:e.l2,this.hasL1=this.l1!==0,this.hasL2=this.l2!==0}apply(e){return X(()=>{let t=Ot([1]);return this.hasL1&&(t=le(t,ke(L(this.l1,ar(e))))),this.hasL2&&(t=le(t,ke(L(this.l2,Oh(e))))),U(t,[])})}getConfig(){return{l1:this.l1,l2:this.l2}}static fromConfig(e,t){return new e({l1:t.l1,l2:t.l2})}};Lh.className="L1L2";ue.registerClass(Lh);function jU(e){return e5(e),new Lh({l1:e!=null?e.l1:null,l2:0})}function HU(e){return e5(e),new Lh({l2:e!=null?e.l2:null,l1:0})}var S4={l1l2:"L1L2"};function bt(e){return R3(e)}function C4(e,t={}){return _h(e,ue.SerializationMap.getMap().classNameMap,t,"regularizer")}function Ft(e){if(e==null)return null;if(typeof e=="string"){let t={className:e in S4?S4[e]:e,config:{}};return C4(t)}else return e instanceof Qw?e:C4(e)}var t5=class extends st{constructor(e){super(e==null?{}:e),this.supportsMasking=!0,e!=null&&(this.maxValue=e.maxValue)}call(e,t){e=je(e);let r=Da(e);return this.maxValue!=null&&(r=fn(r,0,this.maxValue)),r}computeOutputShape(e){return e}getConfig(){let e={maxValue:this.maxValue},t=super.getConfig();return Object.assign(e,t),e}};t5.className="ReLU";ue.registerClass(t5);var r5=class extends st{constructor(e){super(e==null?{}:e),this.DEFAULT_ALPHA=.3,e==null&&(e={}),this.alpha=e.alpha==null?this.DEFAULT_ALPHA:e.alpha}call(e,t){let r=je(e);return Bf(r,this.alpha)}computeOutputShape(e){return e}getConfig(){let e={alpha:this.alpha},t=super.getConfig();return Object.assign(e,t),e}};r5.className="LeakyReLU";ue.registerClass(r5);var n5=class extends st{constructor(e){if(super(e==null?{}:e),this.DEFAULT_ALPHA_INITIALIZER="zeros",e==null&&(e={}),this.supportsMasking=!0,this.alphaInitializer=Mt(e.alphaInitializer||this.DEFAULT_ALPHA_INITIALIZER),this.alphaRegularizer=Ft(e.alphaRegularizer),this.alphaConstraint=lr(e.alphaConstraint),e.sharedAxes==null)this.sharedAxes=null;else if(Array.isArray(e.sharedAxes))this.sharedAxes=e.sharedAxes;else if(typeof e.sharedAxes=="number")this.sharedAxes=[e.sharedAxes];else throw new q(`Expected sharedAxes to be a number or an array of numbers, but got ${e.sharedAxes}`)}build(e){e=mt(e);let t=e.slice(1);if(this.sharedAxes!=null)for(let n of this.sharedAxes)t[n-1]=1;this.alpha=this.addWeight("alpha",t,"float32",this.alphaInitializer,this.alphaRegularizer,!0,this.alphaConstraint);let r={};if(this.sharedAxes!=null)for(let n=1;n<e.length;++n)r[n]=e[n];this.inputSpec=[new Zt({ndim:e.length,axes:r})],this.built=!0}call(e,t){return e=je(e),qf(e,this.alpha.read())}getConfig(){let e={alphaInitializer:zt(this.alphaInitializer),alphaRegularizer:bt(this.alphaRegularizer),alphaConstraint:or(this.alphaConstraint),sharedAxes:this.sharedAxes},t=super.getConfig();return Object.assign(e,t),e}};n5.className="PReLU";ue.registerClass(n5);var a5=class extends st{constructor(e){if(super(e==null?{}:e),this.DEFAULT_ALPHA=1,e==null&&(e={}),e.alpha!=null&&e.alpha!==this.DEFAULT_ALPHA)throw new Ve(`Non-default alpha value (${e.alpha}) is not supported by the ELU layer yet.`);this.alpha=e.alpha==null?this.DEFAULT_ALPHA:e.alpha}call(e,t){let r=je(e);return Eh(r)}computeOutputShape(e){return e}getConfig(){let e={alpha:this.alpha},t=super.getConfig();return Object.assign(e,t),e}};a5.className="ELU";ue.registerClass(a5);var s5=class extends st{constructor(e){super(e==null?{}:e),this.DEFAULT_THETA=1,e==null&&(e={}),this.theta=e.theta==null?this.DEFAULT_THETA:e.theta}call(e,t){let r=je(e);return L(r,me(gn(r,this.theta),"float32"))}computeOutputShape(e){return e}getConfig(){let e={theta:this.theta},t=super.getConfig();return Object.assign(e,t),e}};s5.className="ThresholdedReLU";ue.registerClass(s5);var i5=class extends st{constructor(e){super(e==null?{}:e),this.DEFAULT_AXIS=1,e==null&&(e={}),this.softmax=new Q3().apply,this.axis=e.axis==null?this.DEFAULT_AXIS:e.axis}call(e,t){let r=je(e);return this.softmax(r,this.axis)}computeOutputShape(e){return e}getConfig(){let e={axis:this.axis},t=super.getConfig();return Object.assign(e,t),e}};i5.className="Softmax";ue.registerClass(i5);function ku(e,t,r){if(typeof e=="number")return Oo(e,t);if(e.length!==t)throw new q(`The ${r} argument must be an integer or tuple of ${t} integers. 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q(`conv3dWithBias expects input to be of rank 4 or 5, but received ${e.rank}.`);if(t.rank!==4&&t.rank!==5)throw new q(`conv3dWithBias expects kernel to be of rank 4 or 5, but received ${e.rank}.`);let o=e8(e,s);if(a==="causal")throw new Ve("The support for CAUSAL padding mode in conv3dWithBias is not implemented yet.");return o=e3(o,t,n,a==="same"?"same":"valid","NDHWC",i),r!=null&&(o=va(o,r)),s==="channelsFirst"&&(o=tt(o,[0,4,1,2,3])),o})}var l5=class extends st{constructor(e,t){if(super(t),this.bias=null,this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_BIAS_INITIALIZER="zeros",l5.verifyArgs(t),this.rank=e,gr(this.rank,"rank"),this.rank!==1&&this.rank!==2&&this.rank!==3)throw new Ve(`Convolution layer for rank other than 1, 2, or 3 (${this.rank}) is not implemented 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if(this.dilationRate.length!==2)throw new q(`dilationRate must be a number or array of two numbers for 2D convolution, but received ${JSON.stringify(this.dilationRate)}`)}else if(this.rank===3){if(typeof this.dilationRate=="number")this.dilationRate=[this.dilationRate,this.dilationRate,this.dilationRate];else if(this.dilationRate.length!==3)throw new q(`dilationRate must be a number or array of three numbers for 3D convolution, but received ${JSON.stringify(this.dilationRate)}`)}}static verifyArgs(e){if(Na("kernelSize"in e,"required key 'kernelSize' not in config"),typeof e.kernelSize!="number"&&!M3(e.kernelSize,"number",1,3))throw new q(`BaseConv expects config.kernelSize to be number or number[] with length 1, 2, or 3, but received ${JSON.stringify(e.kernelSize)}.`)}getConfig(){let e={kernelSize:this.kernelSize,strides:this.strides,padding:this.padding,dataFormat:this.dataFormat,dilationRate:this.dilationRate,activation:Us(this.activation),useBias:this.useBias,biasInitializer:zt(this.biasInitializer),biasRegularizer:bt(this.biasRegularizer),activityRegularizer:bt(this.activityRegularizer),biasConstraint:or(this.biasConstraint)},t=super.getConfig();return Object.assign(e,t),e}},Bh=class extends l5{constructor(e,t){super(e,t),this.kernel=null,Bh.verifyArgs(t),this.filters=t.filters,gr(this.filters,"filters"),this.kernelInitializer=Mt(t.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.kernelConstraint=lr(t.kernelConstraint),this.kernelRegularizer=Ft(t.kernelRegularizer)}build(e){e=mt(e);let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null)throw new q(`The channel dimension of the input should be defined. 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Found `None`.");let r=e[t],n=this.kernelSize.concat([this.filters,r]);this.kernel=this.addWeight("kernel",n,"float32",this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[new Zt({ndim:4,axes:{[t]:r}})],this.built=!0}call(e,t){return X(()=>{let r=je(e);if(r.shape.length!==4)throw new q(`Conv2DTranspose.call() expects input tensor to be rank-4, but received a tensor of rank-${r.shape.length}`);let n=r.shape,a=n[0],s,i;this.dataFormat==="channelsFirst"?(s=2,i=3):(s=1,i=2);let o=n[s],l=n[i],u=this.kernelSize[0],d=this.kernelSize[1],h=this.strides[0],p=this.strides[1],c=Ea(o,h,u,this.padding),m=Ea(l,p,d,this.padding),f=[a,c,m,this.filters];this.dataFormat!=="channelsLast"&&(r=tt(r,[0,2,3,1]));let g=Qy(r,this.kernel.read(),f,this.strides,this.padding);return this.dataFormat!=="channelsLast"&&(g=tt(g,[0,3,1,2])),this.bias!=null&&(g=va(g,this.bias.read(),this.dataFormat)),this.activation!=null&&(g=this.activation.apply(g)),g})}computeOutputShape(e){e=mt(e);let t=e.slice(),r,n,a;this.dataFormat==="channelsFirst"?(r=1,n=2,a=3):(r=3,n=1,a=2);let s=this.kernelSize[0],i=this.kernelSize[1],o=this.strides[0],l=this.strides[1];return t[r]=this.filters,t[n]=Ea(t[n],o,s,this.padding),t[a]=Ea(t[a],l,i,this.padding),t}getConfig(){let e=super.getConfig();return delete e.dilationRate,e}};u5.className="Conv2DTranspose";ue.registerClass(u5);var d5=class extends km{constructor(e){if(super(e),this.inputSpec=[new Zt({ndim:5})],this.padding!=="same"&&this.padding!=="valid")throw new q(`Conv3DTranspose currently supports only padding modes 'same' and 'valid', but received padding mode ${this.padding}`)}build(e){if(e=mt(e),e.length!==5)throw new q("Input should have rank 5; Received input shape: "+JSON.stringify(e));let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null)throw new q("The channel dimension of the inputs should be defined. Found `None`.");let r=e[t],n=this.kernelSize.concat([this.filters,r]);this.kernel=this.addWeight("kernel",n,"float32",this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[new Zt({ndim:5,axes:{[t]:r}})],this.built=!0}call(e,t){return X(()=>{let r=je(e);if(r.shape.length!==5)throw new q(`Conv3DTranspose.call() expects input tensor to be rank-4, but received a tensor of rank-${r.shape.length}`);let n=r.shape,a=n[0],s,i,o;this.dataFormat==="channelsFirst"?(o=2,s=3,i=4):(o=1,s=2,i=3);let l=n[o],u=n[s],d=n[i],h=this.kernelSize[0],p=this.kernelSize[1],c=this.kernelSize[2],m=this.strides[0],f=this.strides[1],g=this.strides[2],y=Ea(l,m,h,this.padding),A=Ea(u,f,p,this.padding),x=Ea(d,g,c,this.padding),b=[a,y,A,x,this.filters];this.dataFormat!=="channelsLast"&&(r=tt(r,[0,2,3,4,1]));let w=ov(r,this.kernel.read(),b,this.strides,this.padding);return this.dataFormat!=="channelsLast"&&(w=tt(w,[0,4,1,2,3])),this.bias!==null&&(w=va(w,this.bias.read(),this.dataFormat)),this.activation!==null&&(w=this.activation.apply(w)),w})}computeOutputShape(e){e=mt(e);let t=e.slice(),r,n,a,s;this.dataFormat==="channelsFirst"?(r=1,n=2,a=3,s=4):(r=4,n=1,a=2,s=3);let i=this.kernelSize[0],o=this.kernelSize[1],l=this.kernelSize[2],u=this.strides[0],d=this.strides[1],h=this.strides[2];return t[r]=this.filters,t[n]=Ea(t[n],u,i,this.padding),t[a]=Ea(t[a],d,o,this.padding),t[s]=Ea(t[s],h,l,this.padding),t}getConfig(){let e=super.getConfig();return delete e.dilationRate,e}};d5.className="Conv3DTranspose";ue.registerClass(d5);var n8=class extends Bh{constructor(e,t){if(super(e,t),this.DEFAULT_DEPTHWISE_INITIALIZER="glorotUniform",this.DEFAULT_POINTWISE_INITIALIZER="glorotUniform",this.depthwiseKernel=null,this.pointwiseKernel=null,t.filters==null)throw new q("The `filters` configuration field is required by SeparableConv, but is unspecified.");if(t.kernelInitializer!=null||t.kernelRegularizer!=null||t.kernelConstraint!=null)throw new q("Fields kernelInitializer, kernelRegularizer and kernelConstraint are invalid for SeparableConv2D. Use depthwiseInitializer, depthwiseRegularizer, depthwiseConstraint, pointwiseInitializer, pointwiseRegularizer and pointwiseConstraint instead.");if(t.padding!=null&&t.padding!=="same"&&t.padding!=="valid")throw new q(`SeparableConv${this.rank}D supports only padding modes: 'same' and 'valid', but received ${JSON.stringify(t.padding)}`);this.depthMultiplier=t.depthMultiplier==null?1:t.depthMultiplier,this.depthwiseInitializer=Mt(t.depthwiseInitializer||this.DEFAULT_DEPTHWISE_INITIALIZER),this.depthwiseRegularizer=Ft(t.depthwiseRegularizer),this.depthwiseConstraint=lr(t.depthwiseConstraint),this.pointwiseInitializer=Mt(t.depthwiseInitializer||this.DEFAULT_POINTWISE_INITIALIZER),this.pointwiseRegularizer=Ft(t.pointwiseRegularizer),this.pointwiseConstraint=lr(t.pointwiseConstraint)}build(e){if(e=mt(e),e.length<this.rank+2)throw new q(`Inputs to SeparableConv${this.rank}D should have rank ${this.rank+2}, but received input shape: ${JSON.stringify(e)}`);let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null||e[t]<0)throw new q(`The channel dimension of the inputs should be defined, but found ${JSON.stringify(e[t])}`);let r=e[t],n=this.kernelSize.concat([r,this.depthMultiplier]),a=[];for(let i=0;i<this.rank;++i)a.push(1);a.push(r*this.depthMultiplier,this.filters);let s=!0;this.depthwiseKernel=this.addWeight("depthwise_kernel",n,"float32",this.depthwiseInitializer,this.depthwiseRegularizer,s,this.depthwiseConstraint),this.pointwiseKernel=this.addWeight("pointwise_kernel",a,"float32",this.pointwiseInitializer,this.pointwiseRegularizer,s,this.pointwiseConstraint),this.useBias?this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,s,this.biasConstraint):this.bias=null,this.inputSpec=[new Zt({ndim:this.rank+2,axes:{[t]:r}})],this.built=!0}call(e,t){return X(()=>{e=je(e);let r;if(this.rank===1)throw new Ve("1D separable convolution is not implemented yet.");return this.rank===2&&(this.dataFormat==="channelsFirst"&&(e=tt(e,[0,2,3,1])),r=Mv(e,this.depthwiseKernel.read(),this.pointwiseKernel.read(),this.strides,this.padding,this.dilationRate,"NHWC")),this.useBias&&(r=va(r,this.bias.read(),this.dataFormat)),this.activation!=null&&(r=this.activation.apply(r)),this.dataFormat==="channelsFirst"&&(r=tt(r,[0,3,1,2])),r})}getConfig(){let e=super.getConfig();return delete e.rank,delete e.kernelInitializer,delete e.kernelRegularizer,delete e.kernelConstraint,e.depthwiseInitializer=zt(this.depthwiseInitializer),e.pointwiseInitializer=zt(this.pointwiseInitializer),e.depthwiseRegularizer=bt(this.depthwiseRegularizer),e.pointwiseRegularizer=bt(this.pointwiseRegularizer),e.depthwiseConstraint=or(this.depthwiseConstraint),e.pointwiseConstraint=or(this.pointwiseConstraint),e}};n8.className="SeparableConv";var p5=class extends n8{constructor(e){super(2,e)}};p5.className="SeparableConv2D";ue.registerClass(p5);var a8=class extends Bh{constructor(e){super(1,e),a8.verifyArgs(e),this.inputSpec=[{ndim:3}]}getConfig(){let e=super.getConfig();return delete e.rank,delete e.dataFormat,e}static verifyArgs(e){if(typeof e.kernelSize!="number"&&!M3(e.kernelSize,"number",1,1))throw new q(`Conv1D expects config.kernelSize to be number or number[] with length 1, but received ${JSON.stringify(e.kernelSize)}.`)}},h5=a8;h5.className="Conv1D";ue.registerClass(h5);var c5=class extends st{constructor(e){super(e),typeof e.cropping=="number"?this.cropping=[[e.cropping,e.cropping],[e.cropping,e.cropping]]:typeof e.cropping[0]=="number"?this.cropping=[[e.cropping[0],e.cropping[0]],[e.cropping[1],e.cropping[1]]]:this.cropping=e.cropping,this.dataFormat=e.dataFormat===void 0?"channelsLast":e.dataFormat,this.inputSpec=[{ndim:4}]}computeOutputShape(e){return this.dataFormat==="channelsFirst"?[e[0],e[1],e[2]-this.cropping[0][0]-this.cropping[0][1],e[3]-this.cropping[1][0]-this.cropping[1][1]]:[e[0],e[1]-this.cropping[0][0]-this.cropping[0][1],e[2]-this.cropping[1][0]-this.cropping[1][1],e[3]]}call(e,t){return X(()=>{if(e=je(e),this.dataFormat==="channelsLast"){let r=n0(e,this.cropping[0][0],e.shape[1]-this.cropping[0][0]-this.cropping[0][1],2);return n0(r,this.cropping[1][0],e.shape[2]-this.cropping[1][1]-this.cropping[1][0],3)}else{let r=n0(e,this.cropping[0][0],e.shape[2]-this.cropping[0][0]-this.cropping[0][1],3);return n0(r,this.cropping[1][0],e.shape[3]-this.cropping[1][1]-this.cropping[1][0],4)}})}getConfig(){let e={cropping:this.cropping,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}};c5.className="Cropping2D";ue.registerClass(c5);var f5=class extends st{constructor(e){super(e),this.DEFAULT_SIZE=[2,2],this.inputSpec=[{ndim:4}],this.size=e.size==null?this.DEFAULT_SIZE:e.size,this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,jt(this.dataFormat),this.interpolation=e.interpolation==null?"nearest":e.interpolation,eB(this.interpolation)}computeOutputShape(e){if(this.dataFormat==="channelsFirst"){let t=e[2]==null?null:this.size[0]*e[2],r=e[3]==null?null:this.size[1]*e[3];return[e[0],e[1],t,r]}else{let t=e[1]==null?null:this.size[0]*e[1],r=e[2]==null?null:this.size[1]*e[2];return[e[0],t,r,e[3]]}}call(e,t){return X(()=>{let r=je(e),n=r.shape;if(this.dataFormat==="channelsFirst"){r=tt(r,[0,2,3,1]);let a=this.size[0]*n[2],s=this.size[1]*n[3],i=this.interpolation==="nearest"?Ie.resizeNearestNeighbor(r,[a,s]):Ie.resizeBilinear(r,[a,s]);return tt(i,[0,3,1,2])}else{let a=this.size[0]*n[1],s=this.size[1]*n[2];return this.interpolation==="nearest"?Ie.resizeNearestNeighbor(r,[a,s]):Ie.resizeBilinear(r,[a,s])}})}getConfig(){let e={size:this.size,dataFormat:this.dataFormat,interpolation:this.interpolation},t=super.getConfig();return Object.assign(e,t),e}};f5.className="UpSampling2D";ue.registerClass(f5);function KU(e,t,r=[1,1],n="valid",a,s){return X(()=>{a==null&&(a=Aa()),jt(a);let i=o5(e,a);if(e.rank!==4)throw new q(`Input for depthwiseConv2d is required to be 4-D, but is instead ${e.rank}-D`);if(t.rank!==4)throw new q(`depthwiseKernel is required to be 4-D, but is instead ${t.rank}-D`);return i=Nh(i,t,r,n==="same"?"same":"valid","NHWC",s),a==="channelsFirst"&&(i=tt(i,[0,3,1,2])),i})}var m5=class extends l5{constructor(e){super(2,e),this.depthwiseKernel=null,this.depthMultiplier=e.depthMultiplier==null?1:e.depthMultiplier,this.depthwiseInitializer=Mt(e.depthwiseInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.depthwiseConstraint=lr(e.depthwiseConstraint),this.depthwiseRegularizer=Ft(e.depthwiseRegularizer)}build(e){if(e=mt(e),e.length<4)throw new q(`Inputs to DepthwiseConv2D should have rank 4. Received input shape: ${JSON.stringify(e)}.`);let t=this.dataFormat==="channelsFirst"?1:3;if(e[t]==null||e[t]<0)throw new q(`The channel dimension of the inputs to DepthwiseConv2D should be defined, but is not (${e[t]}).`);let r=e[t],n=[this.kernelSize[0],this.kernelSize[1],r,this.depthMultiplier];this.depthwiseKernel=this.addWeight("depthwise_kernel",n,null,this.depthwiseInitializer,this.depthwiseRegularizer,!0,this.depthwiseConstraint),this.useBias?this.bias=this.addWeight("bias",[r*this.depthMultiplier],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint):this.bias=null,this.built=!0}call(e,t){return X(()=>{e=je(e);let r=KU(e,this.depthwiseKernel.read(),this.strides,this.padding,this.dataFormat,null);return this.useBias&&(r=va(r,this.bias.read(),this.dataFormat)),this.activation!=null&&(r=this.activation.apply(r)),r})}computeOutputShape(e){e=mt(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],r=this.dataFormat==="channelsFirst"?e[3]:e[2],n=this.dataFormat==="channelsFirst"?e[1]*this.depthMultiplier:e[3]*this.depthMultiplier,a=ma(t,this.kernelSize[0],this.padding,this.strides[0]),s=ma(r,this.kernelSize[1],this.padding,this.strides[1]);return this.dataFormat==="channelsFirst"?[e[0],n,a,s]:[e[0],a,s,n]}getConfig(){let e=super.getConfig();return e.depthMultiplier=this.depthMultiplier,e.depthwiseInitializer=zt(this.depthwiseInitializer),e.depthwiseRegularizer=bt(this.depthwiseRegularizer),e.depthwiseConstraint=or(this.depthwiseRegularizer),e}};m5.className="DepthwiseConv2D";ue.registerClass(m5);function s8(e,t,r,n){if(Array.isArray(e)){if(t!=null||r!=null)throw new q("When inputs is an array, neither initialState or constants should be provided");n!=null&&(r=e.slice(e.length-n,e.length),e=e.slice(0,e.length-n)),e.length>1&&(t=e.slice(1,e.length)),e=e[0]}function a(s){return s==null||Array.isArray(s)?s:[s]}return t=a(t),r=a(r),{inputs:e,initialState:t,constants:r}}function i8(e,t,r,n=!1,a,s,i=!1,o=!1){return X(()=>{let l=t.shape.length;if(l<3)throw new q(`Input should be at least 3D, but is ${l}D.`);let u=[1,0].concat(ya(2,l));if(t=tt(t,u),s!=null)throw new Ve("The rnn() functoin of the deeplearn.js backend does not support constants yet.");i&&console.warn("Backend rnn(): the unroll = true option is not applicable to the imperative deeplearn.js backend."),a!=null&&(a=me(me(a,"bool"),"float32"),a.rank===l-1&&(a=Kt(a,-1)),a=tt(a,u)),n&&(t=Pn(t,0),a!=null&&(a=Pn(a,0)));let d=[],h,p=r,c=t.shape[0],m=an(t),f;a!=null&&(f=an(a));for(let y=0;y<c;++y){let A=m[y],x=X(()=>e(A,p));if(a==null)h=x[0],p=x[1];else{let b=X(()=>{let w=f[y],I=ce(_n(w),w),T=le(L(x[0],w),L(p[0],I)),E=p.map((R,O)=>le(L(x[1][O],w),L(R,I)));return{output:T,newStates:E}});h=b.output,p=b.newStates}o&&d.push(h)}let g;return o&&(g=ur(d,1)),[h,g,p]})}var o8=class extends st{constructor(e){super(e);let t;if(e.cell==null)throw new q("cell property is missing for the constructor of RNN.");if(Array.isArray(e.cell)?t=new Cm({cells:e.cell}):t=e.cell,t.stateSize==null)throw new q("The RNN cell should have an attribute `stateSize` (tuple of integers, one integer per RNN state).");this.cell=t,this.returnSequences=e.returnSequences==null?!1:e.returnSequences,this.returnState=e.returnState==null?!1:e.returnState,this.goBackwards=e.goBackwards==null?!1:e.goBackwards,this._stateful=e.stateful==null?!1:e.stateful,this.unroll=e.unroll==null?!1:e.unroll,this.supportsMasking=!0,this.inputSpec=[new Zt({ndim:3})],this.stateSpec=null,this.states_=null,this.numConstants=null,this.keptStates=[]}getStates(){if(this.states_==null){let e=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1;return ya(0,e).map(t=>null)}else return this.states_}setStates(e){this.states_=e}computeOutputShape(e){Wg(e)&&(e=e[0]),e=e;let t=this.cell.stateSize;Array.isArray(t)||(t=[t]);let r=t[0],n;if(this.returnSequences?n=[e[0],e[1],r]:n=[e[0],r],this.returnState){let a=[];for(let s of t)a.push([e[0],s]);return[n].concat(a)}else return n}computeMask(e,t){return X(()=>{Array.isArray(t)&&(t=t[0]);let r=this.returnSequences?t:null;if(this.returnState){let n=this.states.map(a=>null);return[r].concat(n)}else return r})}get states(){if(this.states_==null){let e=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1,t=[];for(let r=0;r<e;++r)t.push(null);return t}else return this.states_}set states(e){this.states_=e}build(e){if(this.numConstants!=null)throw new Ve("Constants support is not implemented in RNN yet.");Wg(e)&&(e=e[0]),e=e;let t=this.stateful?e[0]:null,r=e.slice(2);this.inputSpec[0]=new Zt({shape:[t,null,...r]});let n=[e[0]].concat(e.slice(2));this.cell.build(n);let a;if(Array.isArray(this.cell.stateSize)?a=this.cell.stateSize:a=[this.cell.stateSize],this.stateSpec!=null){if(!v.arraysEqual(this.stateSpec.map(s=>s.shape[s.shape.length-1]),a))throw new q(`An initialState was passed that is not compatible with cell.stateSize. Received stateSpec=${this.stateSpec}; However cell.stateSize is ${this.cell.stateSize}`)}else this.stateSpec=a.map(s=>new Zt({shape:[null,s]}));this.stateful&&this.resetStates()}resetStates(e,t=!1){X(()=>{if(!this.stateful)throw new Ga("Cannot call resetStates() on an RNN Layer that is not stateful.");let r=this.inputSpec[0].shape[0];if(r==null)throw new q("If an RNN is stateful, it needs to know its batch size. Specify the batch size of your input tensors: \n- If using a Sequential model, specify the batch size by passing a `batchInputShape` option to your first layer.\n- If using the functional API, specify the batch size by passing a `batchShape` option to your Input layer.");if(this.states_==null)Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(n=>Ot([r,n])):this.states_=[Ot([r,this.cell.stateSize])];else if(e==null)te(this.states_),this.keptStates!=null&&(te(this.keptStates),this.keptStates=[]),Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(n=>Ot([r,n])):this.states_[0]=Ot([r,this.cell.stateSize]);else{if(Array.isArray(e)||(e=[e]),e.length!==this.states_.length)throw new q(`Layer ${this.name} expects ${this.states_.length} state(s), but it received ${e.length} state value(s). Input received: ${e}`);t===!0?this.keptStates.push(this.states_.slice()):te(this.states_);for(let n=0;n<this.states_.length;++n){let a=e[n],s=Array.isArray(this.cell.stateSize)?this.cell.stateSize[n]:this.cell.stateSize,i=[r,s];if(!v.arraysEqual(a.shape,i))throw new q(`State ${n} is incompatible with layer ${this.name}: expected shape=${i}, received shape=${a.shape}`);this.states_[n]=a}}this.states_=this.states_.map(n=>mr(n.clone()))})}apply(e,t){let r=t==null?null:t.initialState,n=t==null?null:t.constants;t==null&&(t={});let a=s8(e,r,n,this.numConstants);e=a.inputs,r=a.initialState,n=a.constants;let s=[],i=[];if(r!=null){t.initialState=r,s=s.concat(r),this.stateSpec=[];for(let o of r)this.stateSpec.push(new Zt({shape:o.shape}));i=i.concat(this.stateSpec)}if(n!=null&&(t.constants=n,s=s.concat(n),this.numConstants=n.length),s[0]instanceof pa){let o=[e].concat(s),l=this.inputSpec.concat(i),u=this.inputSpec;this.inputSpec=l;let d=super.apply(o,t);return this.inputSpec=u,d}else return super.apply(e,t)}call(e,t){return X(()=>{let r=t==null?null:t.mask,n=t==null?null:t.training,a=t==null?null:t.initialState;e=je(e),a==null&&(this.stateful?a=this.states_:a=this.getInitialState(e));let s=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1;if(a.length!==s)throw new q(`RNN Layer has ${s} state(s) but was passed ${a.length} initial state(s).`);this.unroll&&console.warn("Ignoring unroll = true for RNN layer, due to imperative backend.");let i={training:n},o=i8((p,c)=>{let m=this.cell.call([p].concat(c),i);return[m[0],m.slice(1)]},e,a,this.goBackwards,r,null,this.unroll,this.returnSequences),l=o[0],u=o[1],d=o[2];this.stateful&&this.resetStates(d,n);let h=this.returnSequences?u:l;return this.returnState?[h].concat(d):h})}getInitialState(e){return X(()=>{let t=Ot(e.shape);return t=ke(t,[1,2]),t=Ph(t),Array.isArray(this.cell.stateSize)?this.cell.stateSize.map(r=>r>1?Lg(t,[1,r]):t):this.cell.stateSize>1?[Lg(t,[1,this.cell.stateSize])]:[t]})}get trainableWeights(){return this.trainable?this.cell.trainableWeights:[]}get nonTrainableWeights(){return this.trainable?this.cell.nonTrainableWeights:this.cell.weights}setFastWeightInitDuringBuild(e){super.setFastWeightInitDuringBuild(e),this.cell!=null&&this.cell.setFastWeightInitDuringBuild(e)}getConfig(){let e=super.getConfig(),t={returnSequences:this.returnSequences,returnState:this.returnState,goBackwards:this.goBackwards,stateful:this.stateful,unroll:this.unroll};this.numConstants!=null&&(t.numConstants=this.numConstants);let r=this.cell.getConfig();return this.getClassName()===o8.className&&(t.cell={className:this.cell.getClassName(),config:r}),{...r,...e,...t}}static fromConfig(e,t,r={}){let n=t.cell,a=fa(n,r);return new e(Object.assign(t,{cell:a}))}},as=o8;as.className="RNN";ue.registerClass(as);var Wh=class extends st{},Im=class extends Wh{constructor(e){super(e),this.DEFAULT_ACTIVATION="tanh",this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_RECURRENT_INITIALIZER="orthogonal",this.DEFAULT_BIAS_INITIALIZER="zeros",this.units=e.units,gr(this.units,"units"),this.activation=Gs(e.activation==null?this.DEFAULT_ACTIVATION:e.activation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=Mt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=Mt(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=Mt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelRegularizer=Ft(e.kernelRegularizer),this.recurrentRegularizer=Ft(e.recurrentRegularizer),this.biasRegularizer=Ft(e.biasRegularizer),this.kernelConstraint=lr(e.kernelConstraint),this.recurrentConstraint=lr(e.recurrentConstraint),this.biasConstraint=lr(e.biasConstraint),this.dropout=Fu([1,Vs([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=Fu([1,Vs([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.dropoutFunc=e.dropoutFunc,this.stateSize=this.units,this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){e=mt(e),this.kernel=this.addWeight("kernel",[e[e.length-1],this.units],null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.recurrentKernel=this.addWeight("recurrent_kernel",[this.units,this.units],null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint),this.useBias?this.bias=this.addWeight("bias",[this.units],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint):this.bias=null,this.built=!0}call(e,t){return X(()=>{if(e=e,e.length!==2)throw new q(`SimpleRNNCell expects 2 input Tensors, got ${e.length}.`);let r=e[1];e=e[0];let n=t.training==null?!1:t.training;0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=js({ones:()=>_n(e),rate:this.dropout,training:n,dropoutFunc:this.dropoutFunc})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=js({ones:()=>_n(r),rate:this.recurrentDropout,training:n,dropoutFunc:this.dropoutFunc}));let a,s=this.dropoutMask,i=this.recurrentDropoutMask;s!=null?a=$a(L(e,s),this.kernel.read()):a=$a(e,this.kernel.read()),this.bias!=null&&(a=va(a,this.bias.read())),i!=null&&(r=L(r,i));let o=le(a,$a(r,this.recurrentKernel.read()));return this.activation!=null&&(o=this.activation.apply(o)),[o,o]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:Us(this.activation),useBias:this.useBias,kernelInitializer:zt(this.kernelInitializer),recurrentInitializer:zt(this.recurrentInitializer),biasInitializer:zt(this.biasInitializer),kernelRegularizer:bt(this.kernelRegularizer),recurrentRegularizer:bt(this.recurrentRegularizer),biasRegularizer:bt(this.biasRegularizer),activityRegularizer:bt(this.activityRegularizer),kernelConstraint:or(this.kernelConstraint),recurrentConstraint:or(this.recurrentConstraint),biasConstraint:or(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout};return{...e,...t}}};Im.className="SimpleRNNCell";ue.registerClass(Im);var g5=class extends as{constructor(e){e.cell=new Im(e),super(e)}call(e,t){return X(()=>{this.cell.dropoutMask!=null&&(te(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(te(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let r=t==null?null:t.mask,n=t==null?null:t.training,a=t==null?null:t.initialState;return super.call(e,{mask:r,training:n,initialState:a})})}static fromConfig(e,t){return new e(t)}};g5.className="SimpleRNN";ue.registerClass(g5);var Sm=class extends Wh{constructor(e){if(super(e),this.DEFAULT_ACTIVATION="tanh",this.DEFAULT_RECURRENT_ACTIVATION="hardSigmoid",this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_RECURRENT_INITIALIZER="orthogonal",this.DEFAULT_BIAS_INITIALIZER="zeros",e.resetAfter)throw new q("GRUCell does not support reset_after parameter set to true.");this.units=e.units,gr(this.units,"units"),this.activation=Gs(e.activation===void 0?this.DEFAULT_ACTIVATION:e.activation),this.recurrentActivation=Gs(e.recurrentActivation===void 0?this.DEFAULT_RECURRENT_ACTIVATION:e.recurrentActivation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=Mt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=Mt(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=Mt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelRegularizer=Ft(e.kernelRegularizer),this.recurrentRegularizer=Ft(e.recurrentRegularizer),this.biasRegularizer=Ft(e.biasRegularizer),this.kernelConstraint=lr(e.kernelConstraint),this.recurrentConstraint=lr(e.recurrentConstraint),this.biasConstraint=lr(e.biasConstraint),this.dropout=Fu([1,Vs([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=Fu([1,Vs([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.dropoutFunc=e.dropoutFunc,this.implementation=e.implementation,this.stateSize=this.units,this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){e=mt(e);let t=e[e.length-1];this.kernel=this.addWeight("kernel",[t,this.units*3],null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.recurrentKernel=this.addWeight("recurrent_kernel",[this.units,this.units*3],null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint),this.useBias?this.bias=this.addWeight("bias",[this.units*3],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint):this.bias=null,this.built=!0}call(e,t){return X(()=>{if(e=e,e.length!==2)throw new q(`GRUCell expects 2 input Tensors (inputs, h, c), got ${e.length}.`);let r=t.training==null?!1:t.training,n=e[1];e=e[0],0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=js({ones:()=>_n(e),rate:this.dropout,training:r,count:3,dropoutFunc:this.dropoutFunc})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=js({ones:()=>_n(n),rate:this.recurrentDropout,training:r,count:3,dropoutFunc:this.dropoutFunc}));let a=this.dropoutMask,s=this.recurrentDropoutMask,i,o,l;0<this.dropout&&this.dropout<1&&(e=L(e,a[0]));let u=$a(e,this.kernel.read());this.useBias&&(u=va(u,this.bias.read())),0<this.recurrentDropout&&this.recurrentDropout<1&&(n=L(n,s[0]));let d=this.recurrentKernel.read(),[h,p]=Yt(d,[2*this.units,this.units],d.rank-1),c=$a(n,h),[m,f,g]=Yt(u,3,u.rank-1),[y,A]=Yt(c,2,c.rank-1);i=this.recurrentActivation.apply(le(m,y)),o=this.recurrentActivation.apply(le(f,A));let x=$a(L(o,n),p);l=this.activation.apply(le(g,x));let b=le(L(i,n),L(le(1,$t(i)),l));return[b,b]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:Us(this.activation),recurrentActivation:Us(this.recurrentActivation),useBias:this.useBias,kernelInitializer:zt(this.kernelInitializer),recurrentInitializer:zt(this.recurrentInitializer),biasInitializer:zt(this.biasInitializer),kernelRegularizer:bt(this.kernelRegularizer),recurrentRegularizer:bt(this.recurrentRegularizer),biasRegularizer:bt(this.biasRegularizer),activityRegularizer:bt(this.activityRegularizer),kernelConstraint:or(this.kernelConstraint),recurrentConstraint:or(this.recurrentConstraint),biasConstraint:or(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation,resetAfter:!1};return{...e,...t}}};Sm.className="GRUCell";ue.registerClass(Sm);var y5=class extends as{constructor(e){e.implementation===0&&console.warn("`implementation=0` has been deprecated, and now defaults to `implementation=1`. Please update your layer call."),e.cell=new Sm(e),super(e)}call(e,t){return X(()=>{this.cell.dropoutMask!=null&&(te(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(te(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let r=t==null?null:t.mask,n=t==null?null:t.training,a=t==null?null:t.initialState;return super.call(e,{mask:r,training:n,initialState:a})})}static fromConfig(e,t){return t.implmentation===0&&(t.implementation=1),new e(t)}};y5.className="GRU";ue.registerClass(y5);var Vh=class extends Wh{constructor(e){super(e),this.DEFAULT_ACTIVATION="tanh",this.DEFAULT_RECURRENT_ACTIVATION="hardSigmoid",this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_RECURRENT_INITIALIZER="orthogonal",this.DEFAULT_BIAS_INITIALIZER="zeros",this.units=e.units,gr(this.units,"units"),this.activation=Gs(e.activation===void 0?this.DEFAULT_ACTIVATION:e.activation),this.recurrentActivation=Gs(e.recurrentActivation===void 0?this.DEFAULT_RECURRENT_ACTIVATION:e.recurrentActivation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=Mt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=Mt(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=Mt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.unitForgetBias=e.unitForgetBias,this.kernelRegularizer=Ft(e.kernelRegularizer),this.recurrentRegularizer=Ft(e.recurrentRegularizer),this.biasRegularizer=Ft(e.biasRegularizer),this.kernelConstraint=lr(e.kernelConstraint),this.recurrentConstraint=lr(e.recurrentConstraint),this.biasConstraint=lr(e.biasConstraint),this.dropout=Fu([1,Vs([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=Fu([1,Vs([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.dropoutFunc=e.dropoutFunc,this.implementation=e.implementation,this.stateSize=[this.units,this.units],this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){var t;e=mt(e);let r=e[e.length-1];this.kernel=this.addWeight("kernel",[r,this.units*4],null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.recurrentKernel=this.addWeight("recurrent_kernel",[this.units,this.units*4],null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint);let n;if(this.useBias){if(this.unitForgetBias){let a=this.biasInitializer,s=this.units;n=new(t=class extends Zn{apply(i,o){let l=a.apply([s]),u=new pm().apply([s]),d=a.apply([s*2]);return s4(s4(l,u),d)}},t.className="CustomInit",t)}else n=this.biasInitializer;this.bias=this.addWeight("bias",[this.units*4],null,n,this.biasRegularizer,!0,this.biasConstraint)}else this.bias=null;this.built=!0}call(e,t){return X(()=>{let r=t.training==null?!1:t.training;if(e=e,e.length!==3)throw new q(`LSTMCell expects 3 input Tensors (inputs, h, c), got ${e.length}.`);let n=e[1],a=e[2];e=e[0],0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=js({ones:()=>_n(e),rate:this.dropout,training:r,count:4,dropoutFunc:this.dropoutFunc})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=js({ones:()=>_n(n),rate:this.recurrentDropout,training:r,count:4,dropoutFunc:this.dropoutFunc}));let s=this.dropoutMask,i=this.recurrentDropoutMask,o,l,u,d;0<this.dropout&&this.dropout<1&&(e=L(e,s[0]));let h=$a(e,this.kernel.read());0<this.recurrentDropout&&this.recurrentDropout<1&&(n=L(n,i[0])),h=le(h,$a(n,this.recurrentKernel.read())),this.useBias&&(h=va(h,this.bias.read()));let[p,c,m,f]=Yt(h,4,h.rank-1);o=this.recurrentActivation.apply(p),l=this.recurrentActivation.apply(c),u=le(L(l,a),L(o,this.activation.apply(m))),d=this.recurrentActivation.apply(f);let g=L(d,this.activation.apply(u));return[g,g,u]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:Us(this.activation),recurrentActivation:Us(this.recurrentActivation),useBias:this.useBias,kernelInitializer:zt(this.kernelInitializer),recurrentInitializer:zt(this.recurrentInitializer),biasInitializer:zt(this.biasInitializer),unitForgetBias:this.unitForgetBias,kernelRegularizer:bt(this.kernelRegularizer),recurrentRegularizer:bt(this.recurrentRegularizer),biasRegularizer:bt(this.biasRegularizer),activityRegularizer:bt(this.activityRegularizer),kernelConstraint:or(this.kernelConstraint),recurrentConstraint:or(this.recurrentConstraint),biasConstraint:or(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation};return{...e,...t}}};Vh.className="LSTMCell";ue.registerClass(Vh);var A5=class extends as{constructor(e){e.implementation===0&&console.warn("`implementation=0` has been deprecated, and now defaults to `implementation=1`. Please update your layer call."),e.cell=new Vh(e),super(e)}call(e,t){return X(()=>{this.cell.dropoutMask!=null&&(te(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(te(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let r=t==null?null:t.mask,n=t==null?null:t.training,a=t==null?null:t.initialState;return super.call(e,{mask:r,training:n,initialState:a})})}static fromConfig(e,t){return t.implmentation===0&&(t.implementation=1),new e(t)}};A5.className="LSTM";ue.registerClass(A5);var Cm=class extends Wh{constructor(e){super(e),this.cells=e.cells}get stateSize(){let e=[];for(let t of this.cells.slice().reverse())Array.isArray(t.stateSize)?e.push(...t.stateSize):e.push(t.stateSize);return e}call(e,t){return X(()=>{e=e;let r=e.slice(1),n=[];for(let i of this.cells.slice().reverse())Array.isArray(i.stateSize)?n.push(r.splice(0,i.stateSize.length)):n.push(r.splice(0,1));n.reverse();let a=[],s;for(let i=0;i<this.cells.length;++i){let o=this.cells[i];r=n[i],i===0?s=[e[0]].concat(r):s=[s[0]].concat(r),s=o.call(s,t),a.push(s.slice(1))}r=[];for(let i of a.slice().reverse())r.push(...i);return[s[0]].concat(r)})}build(e){Wg(e)&&(e=e[0]),e=e;let t;this.cells.forEach((r,n)=>{No(`RNNCell_${n}`,()=>{r.build(e),Array.isArray(r.stateSize)?t=r.stateSize[0]:t=r.stateSize,e=[e[0],t]})}),this.built=!0}getConfig(){let e=super.getConfig(),t=n=>({className:n.getClassName(),config:n.getConfig()}),r={cells:this.cells.map(t)};return{...e,...r}}static fromConfig(e,t,r={}){let n=[];for(let a of t.cells)n.push(fa(a,r));return new e({cells:n})}get trainableWeights(){if(!this.trainable)return[];let e=[];for(let t of this.cells)e.push(...t.trainableWeights);return e}get nonTrainableWeights(){let e=[];for(let t of this.cells)e.push(...t.nonTrainableWeights);if(!this.trainable){let t=[];for(let r of this.cells)t.push(...r.trainableWeights);return t.concat(e)}return e}getWeights(){let e=[];for(let t of this.cells)e.push(...t.weights);return Vg(e)}setWeights(e){let t=[];for(let r of this.cells){let n=r.weights.length,a=e.splice(n);for(let s=0;s<r.weights.length;++s)t.push([r.weights[s],a[s]])}B3(t)}};Cm.className="StackedRNNCells";ue.registerClass(Cm);function js(e){let{ones:t,rate:r,training:n=!1,count:a=1,dropoutFunc:s}=e,i=()=>s!=null?s(t(),r):cw(t(),r),o=()=>zh(i,t,n);return!a||a<=1?mr(o().clone()):Array(a).fill(void 0).map(o).map(l=>mr(l.clone()))}var l8=class extends as{constructor(e){if(e.unroll)throw new Ve("Unrolling is not possible with convolutional RNNs.");if(Array.isArray(e.cell))throw new Ve("It is not possible at the moment to stack convolutional cells.");super(e),this.inputSpec=[new Zt({ndim:5})]}call(e,t){return X(()=>{if(this.cell.dropoutMask!=null&&(te(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(te(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null),t&&t.constants)throw new q("ConvRNN2D cell does not support constants");let r=t==null?null:t.mask,n=t==null?null:t.training,a=t==null?null:t.initialState;return super.call(e,{mask:r,training:n,initialState:a})})}computeOutputShape(e){let t=this.computeSingleOutputShape(e);return this.returnSequences||(t=[t[0],...t.slice(2)]),this.returnState&&(t=[t,...Array(2).fill([e[0],...t.slice(-3)])]),t}getInitialState(e){return X(()=>{let{stateSize:t}=this.cell,r=e.shape,n=this.computeSingleOutputShape(r),a=[n[0],...n.slice(2)],s=Ot(a);return Array.isArray(t)?Array(t.length).fill(s):[s]})}resetStates(e,t=!1){X(()=>{if(!this.stateful)throw new Ga("Cannot call resetStates() on an RNN Layer that is not stateful.");let r=this.inputSpec[0].shape,n=this.computeSingleOutputShape(r),a=[n[0],...n.slice(2)];if(r[0]==null)throw new q("If an RNN is stateful, it needs to know its batch size. Specify the batch size of your input tensors: \n- If using a Sequential model, specify the batch size by passing a `batchInputShape` option to your first layer.\n- If using the functional API, specify the batch size by passing a `batchShape` option to your Input layer.");if(this.getStates()==null)Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(()=>Ot(a)):this.states_=[Ot(a)];else if(e==null)te(this.states_),this.keptStates!=null&&(te(this.keptStates),this.keptStates=[]),Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(()=>Ot(a)):this.states_[0]=Ot(a);else{if(Array.isArray(e)||(e=[e]),e.length!==this.states_.length)throw new q(`Layer ${this.name} expects ${this.states_.length} state(s), but it received ${e.length} state value(s). Input received: ${e}`);t?this.keptStates.push(this.states_.slice()):te(this.states_);for(let s=0;s<this.states_.length;++s){let i=e[s],o=a;if(!v.arraysEqual(i.shape,o))throw new q(`State ${s} is incompatible with layer ${this.name}: expected shape=${o}, received shape=${i.shape}`);this.states_[s]=i}}this.states_=this.states_.map(s=>mr(s.clone()))})}computeSingleOutputShape(e){let{dataFormat:t,filters:r,kernelSize:n,padding:a,strides:s,dilationRate:i}=this.cell,o=t==="channelsFirst",l=e[o?3:2],u=e[o?4:3],d=ma(l,n[0],a,s[0],i[0]),h=ma(u,n[1],a,s[1],i[1]);return[...e.slice(0,2),...o?[r,d,h]:[d,h,r]]}};l8.className="ConvRNN2D";var Tm=class extends Vh{constructor(e){let{filters:t,kernelSize:r,strides:n,padding:a,dataFormat:s,dilationRate:i}=e;super({...e,units:t}),this.filters=t,gr(this.filters,"filters"),this.kernelSize=ku(r,2,"kernelSize"),this.kernelSize.forEach(o=>gr(o,"kernelSize")),this.strides=ku(n||1,2,"strides"),this.strides.forEach(o=>gr(o,"strides")),this.padding=a||"valid",Ln(this.padding),this.dataFormat=s||"channelsLast",jt(this.dataFormat),this.dilationRate=ku(i||1,2,"dilationRate"),this.dilationRate.forEach(o=>gr(o,"dilationRate"))}build(e){var t;e=mt(e);let r=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[r]==null)throw new q(`The channel dimension of the input should be defined. Found ${e[r]}`);let n=e[r],a=4,s=this.kernelSize.concat([n,this.filters*a]);this.kernel=this.addWeight("kernel",s,null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint);let i=this.kernelSize.concat([this.filters,this.filters*a]);if(this.recurrentKernel=this.addWeight("recurrent_kernel",i,null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint),this.useBias){let o;if(this.unitForgetBias){let l=this.biasInitializer,u=this.filters;o=new(t=class extends Zn{apply(d,h){let p=l.apply([u]),c=cn([u]),m=l.apply([u*2]);return $3([p,c,m])}},t.className="CustomInit",t)}else o=this.biasInitializer;this.bias=this.addWeight("bias",[this.filters*a],null,o,this.biasRegularizer,!0,this.biasConstraint)}this.built=!0}call(e,t){return X(()=>{if(e.length!==3)throw new q(`ConvLSTM2DCell expects 3 input Tensors (inputs, h, c), got ${e.length}.`);let r=t.training||!1,n=e[0],a=e[1],s=e[2],i=4;0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=js({ones:()=>_n(n),rate:this.dropout,training:r,count:i,dropoutFunc:this.dropoutFunc}));let o=this.dropoutMask,l=(V,re,Q)=>!re||!re[Q]?V:L(re[Q],V),u=l(n,o,0),d=l(n,o,1),h=l(n,o,2),p=l(n,o,3);0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=js({ones:()=>_n(a),rate:this.recurrentDropout,training:r,count:i,dropoutFunc:this.dropoutFunc}));let c=this.recurrentDropoutMask,m=l(a,c,0),f=l(a,c,1),g=l(a,c,2),y=l(a,c,3),A=3,[x,b,w,I]=Yt(this.kernel.read(),i,A),[T,E,R,O]=this.useBias?Yt(this.bias.read(),i):[null,null,null,null];u=this.inputConv(u,x,T,this.padding),d=this.inputConv(d,b,E,this.padding),h=this.inputConv(h,w,R,this.padding),p=this.inputConv(p,I,O,this.padding);let[M,S,P,z]=Yt(this.recurrentKernel.read(),i,A);m=this.recurrentConv(m,M),f=this.recurrentConv(f,S),g=this.recurrentConv(g,P),y=this.recurrentConv(y,z);let j=this.recurrentActivation.apply(le(u,m)),K=this.recurrentActivation.apply(le(d,f)),D=le(L(K,s),L(j,this.activation.apply(le(h,g)))),Y=L(this.recurrentActivation.apply(le(p,y)),this.activation.apply(D));return[Y,Y,D]})}getConfig(){let{units:e,...t}=super.getConfig(),r={filters:this.filters,kernelSize:this.kernelSize,padding:this.padding,dataFormat:this.dataFormat,dilationRate:this.dilationRate,strides:this.strides};return{...t,...r}}inputConv(e,t,r,n){let a=Ds(e,t,this.strides,n||"valid",this.dataFormat==="channelsFirst"?"NCHW":"NHWC",this.dilationRate);return r?va(a,r,this.dataFormat):a}recurrentConv(e,t){return Ds(e,t,1,"same",this.dataFormat==="channelsFirst"?"NCHW":"NHWC")}};Tm.className="ConvLSTM2DCell";ue.registerClass(Tm);var x5=class extends l8{constructor(e){let t=new Tm(e);super({...e,cell:t})}static fromConfig(e,t){return new e(t)}};x5.className="ConvLSTM2D";ue.registerClass(x5);var Nm=class extends st{constructor(e){super(e),this.rate=Math.max(Math.min(e.rate,1),0),this.noiseShape=e.noiseShape,this.seed=e.seed,this.supportsMasking=!0}getNoiseShape(e){if(this.noiseShape==null)return this.noiseShape;let t=e.shape,r=[];for(let n=0;n<this.noiseShape.length;++n)r.push(this.noiseShape[n]==null?t[n]:this.noiseShape[n]);return r}call(e,t){return X(()=>{this.invokeCallHook(e,t);let r=je(e);if(0<this.rate&&this.rate<1){let n=t.training==null?!1:t.training,a=this.getNoiseShape(r);return zh(()=>cw(r,this.rate,a,this.seed),()=>r,n)}return e})}getConfig(){let e={rate:this.rate,noiseShape:this.noiseShape,seed:this.seed},t=super.getConfig();return Object.assign(e,t),e}dispose(){return super.dispose()}};Nm.className="Dropout";ue.registerClass(Nm);var b5=class extends Nm{constructor(e){super(e),this.inputSpec=[{ndim:3}]}getNoiseShape(e){let t=e.shape;return[t[0],1,t[2]]}};b5.className="SpatialDropout1D";ue.registerClass(b5);var v5=class extends st{constructor(e){if(super(e),this.activation=null,this.useBias=!0,this.kernel=null,this.bias=null,this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_BIAS_INITIALIZER="zeros",e.batchInputShape==null&&e.inputShape==null&&e.inputDim!=null){let t=null;e.batchSize!=null&&(t=e.batchSize),this.batchInputShape=[t,e.inputDim]}this.units=e.units,gr(this.units,"units"),this.activation=Gs(e.activation),e.useBias!=null&&(this.useBias=e.useBias),this.kernelInitializer=Mt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.biasInitializer=Mt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelConstraint=lr(e.kernelConstraint),this.biasConstraint=lr(e.biasConstraint),this.kernelRegularizer=Ft(e.kernelRegularizer),this.biasRegularizer=Ft(e.biasRegularizer),this.activityRegularizer=Ft(e.activityRegularizer),this.supportsMasking=!0,this.inputSpec=[{minNDim:2}]}build(e){e=mt(e);let t=e[e.length-1];this.kernel==null&&(this.kernel=this.addWeight("kernel",[t,this.units],null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.units],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint))),this.inputSpec=[{minNDim:2,axes:{[-1]:t}}],this.built=!0}computeOutputShape(e){e=mt(e);let t=e.slice();return t[t.length-1]=this.units,t}call(e,t){return X(()=>{this.invokeCallHook(e,t);let r=je(e),n=iw(this.activation.getClassName()),a;return n!=null?a=$a(r,this.kernel.read(),n,this.bias?this.bias.read():null):(a=$a(r,this.kernel.read()),this.bias!=null&&(a=va(a,this.bias.read())),this.activation!=null&&(a=this.activation.apply(a))),a})}getConfig(){let e={units:this.units,activation:Us(this.activation),useBias:this.useBias,kernelInitializer:zt(this.kernelInitializer),biasInitializer:zt(this.biasInitializer),kernelRegularizer:bt(this.kernelRegularizer),biasRegularizer:bt(this.biasRegularizer),activityRegularizer:bt(this.activityRegularizer),kernelConstraint:or(this.kernelConstraint),biasConstraint:or(this.biasConstraint)},t=super.getConfig();return Object.assign(e,t),e}};v5.className="Dense";ue.registerClass(v5);var w5=class extends st{constructor(e){e=e||{},super(e),this.inputSpec=[{minNDim:3}],this.dataFormat=e.dataFormat}computeOutputShape(e){e=mt(e);for(let t of e.slice(1))if(t==null)throw new q(`The shape of the input to "Flatten" is not fully defined (got ${e.slice(1)}). 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X(()=>(e=je(e),aB(e,this.n)))}getConfig(){let e={n:this.n},t=super.getConfig();return Object.assign(e,t),e}};I5.className="RepeatVector";ue.registerClass(I5);var S5=class extends st{constructor(e){super(e),this.targetShape=e.targetShape;for(let t=0;t<this.targetShape.length;++t)this.isUnknown(this.targetShape[t])&&(this.targetShape[t]=null)}isUnknown(e){return e<0||e==null}fixUnknownDimension(e,t){let r="Total size of new array must be unchanged.",n=t.slice(),a=1,s=null;for(let o=0;o<n.length;++o){let l=n[o];if(this.isUnknown(l))if(s===null)s=o;else throw new q("Can only specifiy one unknown dimension.");else a*=l}let i=Ms(e);if(s!==null){if(a===0||i%a!==0)throw new q(r);n[s]=i/a}else if(i!==a)throw new q(r);return n}computeOutputShape(e){let t=!1;for(let r=0;r<e.length;++r)if(this.isUnknown(e[r])){t=!0;break}return t?e.slice(0,1).concat(this.targetShape):e.slice(0,1).concat(this.fixUnknownDimension(e.slice(1),this.targetShape))}call(e,t){return X(()=>{this.invokeCallHook(e,t);let r=je(e),n=r.shape,a=n.slice(0,1).concat(this.fixUnknownDimension(n.slice(1),this.targetShape));return U(r,a)})}getConfig(){let e={targetShape:this.targetShape},t=super.getConfig();return Object.assign(e,t),e}};S5.className="Reshape";ue.registerClass(S5);var C5=class extends st{constructor(e){if(super(e),e.dims==null)throw new Error("Required configuration field `dims` is missing during Permute constructor call.");if(!Array.isArray(e.dims))throw new Error(`Permute constructor requires \`dims\` to be an Array, but received ${e.dims} instead.`);let t=ya(1,e.dims.length+1);if(!v.arraysEqual(e.dims.slice().sort(),t))throw new Error("Invalid permutation `dims`: "+JSON.stringify(e.dims)+" `dims` must contain consecutive integers starting from 1.");this.dims=e.dims,this.dimsIncludingBatch=[0].concat(this.dims),this.inputSpec=[new Zt({ndim:this.dims.length+1})]}computeOutputShape(e){e=mt(e);let t=e.slice();return this.dims.forEach((r,n)=>{t[n+1]=e[r]}),t}call(e,t){return tt(je(e),this.dimsIncludingBatch)}getConfig(){let e={dims:this.dims},t=super.getConfig();return Object.assign(e,t),e}};C5.className="Permute";ue.registerClass(C5);var T5=class extends st{constructor(e){super(e==null?{}:e),this.supportsMasking=!0,e!=null?this.maskValue=e.maskValue==null?0:e.maskValue:this.maskValue=0}computeOutputShape(e){return e}getConfig(){let e=super.getConfig(),t={maskValue:this.maskValue};return Object.assign(t,e),t}computeMask(e,t){let r=je(e),n=-1;return F0(Mu(r,this.maskValue),n)}call(e,t){return X(()=>{this.invokeCallHook(e,t);let r=je(e),n=-1,a=!0,s=F0(Mu(r,this.maskValue),n,a);return L(r,me(s,r.dtype))})}};T5.className="Masking";ue.registerClass(T5);var N5=class extends st{constructor(e){if(super(e),this.embeddings=null,this.DEFAULT_EMBEDDINGS_INITIALIZER="randomUniform",e.batchInputShape==null&&e.inputShape==null){let t=null;e.batchSize!=null&&(t=e.batchSize),e.inputLength==null?this.batchInputShape=[t,null]:this.batchInputShape=[t].concat(Tt(e.inputLength))}this.inputDim=e.inputDim,gr(this.inputDim,"inputDim"),this.outputDim=e.outputDim,gr(this.outputDim,"outputDim"),this.embeddingsInitializer=Mt(e.embeddingsInitializer||this.DEFAULT_EMBEDDINGS_INITIALIZER),this.embeddingsRegularizer=Ft(e.embeddingsRegularizer),this.activityRegularizer=Ft(e.activityRegularizer),this.embeddingsConstraint=lr(e.embeddingsConstraint),this.maskZero=e.maskZero,this.supportsMasking=e.maskZero,this.inputLength=e.inputLength}build(e){this.embeddings=this.addWeight("embeddings",[this.inputDim,this.outputDim],this.dtype,this.embeddingsInitializer,this.embeddingsRegularizer,!0,this.embeddingsConstraint),this.built=!0}warnOnIncompatibleInputShape(e){}computeMask(e,t){return X(()=>this.maskZero?(e=je(e),Mu(e,at(e))):null)}computeOutputShape(e){if(e=mt(e),this.inputLength==null)return[...e,this.outputDim];let t=Tt(this.inputLength);if(t.length!==e.length-1)throw new q(`"inputLength" is ${this.inputLength}, but received input shape has shape ${e}`);{let r=0;for(let n=0;n<t.length;++n){let a=t[n],s=e[n+1];if(a!=null&&s!=null&&a!==s)throw new q(`"inputLength" is ${this.inputLength}, but received input shape has shape ${e}`);a==null&&(t[r]=s),r++}}return[e[0],...t,this.outputDim]}call(e,t){return X(()=>{this.invokeCallHook(e,t);let r=je(e);r.dtype!=="int32"&&(r=um(r,"int32"));let n=hw(this.embeddings.read(),U(r,[r.size]));return U(n,mt(this.computeOutputShape(r.shape)))})}getConfig(){let e={inputDim:this.inputDim,outputDim:this.outputDim,embeddingsInitializer:zt(this.embeddingsInitializer),embeddingsRegularizer:bt(this.embeddingsRegularizer),activityRegularizer:bt(this.activityRegularizer),embeddingsConstraint:or(this.embeddingsConstraint),maskZero:this.maskZero,inputLength:this.inputLength},t=super.getConfig();return Object.assign(e,t),e}};N5.className="Embedding";ue.registerClass(N5);var Ol=class extends st{constructor(e){super(e||{}),this.supportsMasking=!0}mergeFunction(e){throw new Ve}computeElementwiseOpOutputShape(e,t){if(e==null||t==null)return null;if(e.length<t.length)return this.computeElementwiseOpOutputShape(t,e);if(t.length===0)return e;let r=e.slice(0,e.length-t.length);for(let n=0;n<t.length;++n){let a=e[e.length-t.length+n],s=t[n];if(a==null||s==null||a<0||s<0)r.push(null);else if(a===1)r.push(s);else if(s===1)r.push(a);else{if(a!==s)throw new q("Operands could not be broadcast together with shapes "+JSON.stringify(e)+" "+JSON.stringify(t));r.push(a)}}return r}build(e){if(Array.isArray(e)&&!Array.isArray(e[0])&&(e=[mt(e)]),e=e,e.length<2)throw new q(`A merge layer should be called on an Array of at least 2 inputs. 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e={axis:this.axis},t=super.getConfig();return Object.assign(e,t),e}};_5.className="Concatenate";ue.registerClass(_5);function Ip(e,t){for(;e<0;)e+=t;return e}function ZU(e,t,r){if(e.shape.length>3||t.shape.length>3)throw new Ve("batchDot is not implemented for tensors of 4D or higher rank yet");if(v.assert(e.shape.length>=2,()=>`batchDot requires the rank of x to be >= 2, but got ${e.shape.length}`),v.assert(e.shape.length>=2,()=>`batchDot requires the rank of y to be >= 2, but got ${t.shape.length}`),typeof r=="number"&&(r=[r,r]),e.dtype==="complex64"||t.dtype==="complex64")throw new Ve("batchDot is not implemented for complex64-type Tensors yet.");let n=e.shape.length,a=t.shape.length;r==null&&(r=[n-1,a-2]);let s=r;return X(()=>{let i;if(n>a){i=n-a;let l=[];for(let u=0;u<i;++u)l.push(1);t=U(t,t.shape.concat(l))}else if(a>n){i=a-n;let l=[];for(let u=0;u<i;++u)l.push(1);e=U(e,e.shape.concat(l))}else i=0;let o;if(e.shape.length===2&&t.shape.length===2)s[0]===s[1]?o=ke(L(e,t),s[0]):o=ke(L(tt(e,[1,0]),t),s[1]);else{let l=s[0]!==e.shape.length-1,u=s[1]===t.shape.length-1;o=Ye(e,t,l,u)}if(i>0){let l;n>a?l=n+a-3:l=n-1;let u=[];for(let d=l;d<l+i;++d)u.push(d);o=et(o,u)}return o.shape.length===1&&(o=Kt(o,1)),o})}var P5=class extends Ol{constructor(e){super(e),this.axes=e.axes,this.normalize=e.normalize==null?!1:e.normalize,this.supportsMasking=!0,this.reshapeRequired=!1}build(e){v.assert(Array.isArray(e)&&e.length===2&&Array.isArray(e[0])&&Array.isArray(e[1]),()=>"A `Dot` layer should be called on a list of exactly 2 inputs.");let t=e[0],r=e[1];if(t.length>3||r.length>3)throw new Ve("Dot layer does not support tensors of 4D or higher rank yet.");let n=this.interpretAxes(t,r);if(t[n[0]]!==r[n[1]])throw new q(`Dimension incompatibility: ${t[n[0]]} !== ${r[n[1]]}`)}mergeFunction(e){if(e.length!==2)throw new q(`A \`Dot\` layer must be called on exactly 2 inputs, but received ${e.length} input(s).`);let t=e[0],r=e[1],n;return Array.isArray(this.axes)?n=this.axes.map((a,s)=>Ip(a,e[s].shape.length)):n=[Ip(this.axes,t.shape.length),Ip(this.axes,r.shape.length)],this.normalize&&(t=B0(t,n[0]),r=B0(r,n[1])),ZU(t,r,n)}interpretAxes(e,t){let r;return Array.isArray(this.axes)?r=this.axes:r=[Ip(this.axes,e.length),Ip(this.axes,t.length)],r}computeOutputShape(e){v.assert(Array.isArray(e)&&e.length===2&&Array.isArray(e[0])&&Array.isArray(e[1]),()=>"A `Dot` layer should be called on a list of exactly 2 inputs.");let t=e[0].slice(),r=e[1].slice();if(t.length>3||r.length>3)throw new Ve("Dot layer does not support tensors of 4D or higher rank yet.");let n=this.interpretAxes(t,r);t.splice(n[0],1),r.splice(n[1],1),r.splice(0,1);let a=t.concat(r);return a.length===1&&a.push(1),a}computeMask(e,t){return null}getConfig(){let e={axes:this.axes,normalize:this.normalize},t=super.getConfig();return Object.assign(e,t),e}};P5.className="Dot";ue.registerClass(P5);var O5=class extends st{constructor(e){super(e),this.supportsMasking=!0,this.stddev=e.stddev}computeOutputShape(e){return e}getConfig(){let e=super.getConfig(),t={stddev:this.stddev};return Object.assign(t,e),t}call(e,t){return X(()=>{this.invokeCallHook(e,t);let r=je(e);return zh(()=>le(dm(r.shape,0,this.stddev),r),()=>r,t.training||!1)})}};O5.className="GaussianNoise";ue.registerClass(O5);var z5=class extends st{constructor(e){super(e),this.supportsMasking=!0,this.rate=e.rate}computeOutputShape(e){return e}getConfig(){let e=super.getConfig(),t={rate:this.rate};return Object.assign(t,e),t}call(e,t){return X(()=>{this.invokeCallHook(e,t);let r=je(e);return this.rate>0&&this.rate<1?zh(()=>{let n=Math.sqrt(this.rate/(1-this.rate));return L(r,dm(r.shape,1,n))},()=>r,t.training||!1):r})}};z5.className="GaussianDropout";ue.registerClass(z5);var D5=class extends st{constructor(e){super(e),this.supportsMasking=!0,this.rate=e.rate,this.noiseShape=e.noiseShape}_getNoiseShape(e){return this.noiseShape||je(e).shape}computeOutputShape(e){return e}getConfig(){let e=super.getConfig(),t={rate:this.rate};return Object.assign(t,e),t}call(e,t){return X(()=>{if(this.rate<1&&this.rate>0){let r=this._getNoiseShape(e);return zh(()=>{let n=je(e),a=1.6732632423543772,s=1.0507009873554805,i=-a*s,o=Ml(vd(r),this.rate);o=um(o,"float32");let l=((1-this.rate)*(1+this.rate*i**2))**-.5,u=-l*i*this.rate,d=le(L(n,o),L(le(o,-1),i));return le(L(d,l),u)},()=>je(e),t.training||!1)}return e})}};D5.className="AlphaDropout";ue.registerClass(D5);function Jp(e,t,r,n,a,s=.001){let i;if(e.rank===2)i=J6(e,t,r,n,a,s);else if(e.rank===3)i=Q6(e,t,r,n,a,s);else if(e.rank===4)i=ev(e,t,r,n,a,s);else throw new Ve(`batchNormalization is not implemented for array of rank ${e.rank} yet`);return i}function YU(e,t,r,n,a=.001){return X(()=>{let s=jf(e,n),i=s.mean,o=s.variance;return[Jp(e,i,o,r,t,a),i,o]})}function JU(e,t,r,n,a=.001){return X(()=>{let s=jf(e,n),i=s.mean,o=s.variance,l=[];for(let c of ya(0,e.rank))n.indexOf(c)!==-1?l.push(1):l.push(e.shape[c]);let u=U(i,l),d=U(o,l),h=t==null?null:U(t,l),p=r==null?null:U(r,l);return[Jp(e,u,d,p,h,a),i,o]})}function QU(e,t,r,n,a=.001){return v.arraysEqual(n.slice().sort(),ya(0,e.rank-1))?YU(e,t,r,n,a):JU(e,t,r,n,a)}var L5=class extends st{constructor(e){e==null&&(e={}),super(e),this.supportsMasking=!0,this.axis=e.axis==null?-1:e.axis,this.momentum=e.momentum==null?.99:e.momentum,this.epsilon=e.epsilon==null?.001:e.epsilon,this.center=e.center==null?!0:e.center,this.scale=e.scale==null?!0:e.scale,this.betaInitializer=Mt(e.betaInitializer||"zeros"),this.gammaInitializer=Mt(e.gammaInitializer||"ones"),this.movingMeanInitializer=Mt(e.movingMeanInitializer||"zeros"),this.movingVarianceInitializer=Mt(e.movingVarianceInitializer||"ones"),this.betaConstraint=lr(e.betaConstraint),this.gammaConstraint=lr(e.gammaConstraint),this.betaRegularizer=Ft(e.betaRegularizer),this.gammaRegularizer=Ft(e.gammaRegularizer)}build(e){e=mt(e);let t=this.axis>=0?this.axis:this.axis+e.length,r=e[t];if(r==null)throw new q(`Axis ${t} of input tensor should have a defined dimension but the layer received an input with shape ${JSON.stringify(e)}.`);this.inputSpec=[new Zt({ndim:e.length,axes:{[t]:r}})];let n=[r];this.scale&&(this.gamma=this.addWeight("gamma",n,null,this.gammaInitializer,this.gammaRegularizer,!0,this.gammaConstraint)),this.center&&(this.beta=this.addWeight("beta",n,null,this.betaInitializer,this.betaRegularizer,!0,this.betaConstraint)),this.movingMean=this.addWeight("moving_mean",n,null,this.movingMeanInitializer,null,!1),this.movingVariance=this.addWeight("moving_variance",n,null,this.movingVarianceInitializer,null,!1),this.built=!0}call(e,t){return X(()=>{let r=t.training==null?!1:t.training,n=je(e),a=n.shape,s=a.length,i=ya(0,s),o=this.axis>=0?this.axis:this.axis+s;i.splice(o,1);let l=Oo(1,s);l[o]=a[o];let u=i.slice();u.sort();let d=!v.arraysEqual(u,ya(0,s).slice(0,s-1)),h=()=>{if(d){let 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e={axis:this.axis,momentum:this.momentum,epsilon:this.epsilon,center:this.center,scale:this.scale,betaInitializer:zt(this.betaInitializer),gammaInitializer:zt(this.gammaInitializer),movingMeanInitializer:zt(this.movingMeanInitializer),movingVarianceInitializer:zt(this.movingVarianceInitializer),betaRegularizer:bt(this.betaRegularizer),gammaRegularizer:bt(this.gammaRegularizer),betaConstraint:or(this.betaConstraint),gammaConstraint:or(this.gammaConstraint)},t=super.getConfig();return Object.assign(e,t),e}};L5.className="BatchNormalization";ue.registerClass(L5);var B5=class extends st{constructor(e){if(e==null&&(e={}),super(e),this.axis=e.axis==null?-1:e.axis,typeof this.axis=="number"){if(!Number.isInteger(this.axis))throw new Error(`Expected axis to be an integer, but received ${this.axis}`)}else if(Array.isArray(this.axis)){for(let t of this.axis)if(!Number.isInteger(t))throw new Error(`Expected axis to be an array of integers, but received ${JSON.stringify(this.axis)}`)}else throw new Error(`Expected axis to be an integer or an array of integers, but received ${JSON.stringify(this.axis)}`);this.epsilon=e.epsilon==null?.001:e.epsilon,this.center=e.center==null?!0:e.center,this.scale=e.scale==null?!0:e.scale,this.betaInitializer=Mt(e.betaInitializer||"zeros"),this.gammaInitializer=Mt(e.gammaInitializer||"ones"),this.betaRegularizer=Ft(e.betaRegularizer),this.gammaRegularizer=Ft(e.gammaRegularizer),this.supportsMasking=!0}build(e){e=mt(e);let t=e.length;typeof this.axis=="number"&&(this.axis=[this.axis]);for(let a=0;a<this.axis.length;++a)this.axis[a]<0&&(this.axis[a]+=t);for(let a of this.axis)if(a<0||a>=t)throw new Error(`Invalid axis: ${a}`);if(this.axis.length!==Rs(this.axis).length)throw new Error(`Found duplicate axes in: ${this.axis}`);let r=this.axis.map(a=>e[a]),n=!0;this.scale?this.gamma=this.addWeight("gamma",r,"float32",this.gammaInitializer,this.gammaRegularizer,n):this.gamma=null,this.center?this.beta=this.addWeight("beta",r,"float32",this.betaInitializer,this.betaRegularizer,n):this.beta=null,this.built=!0}call(e,t){let r=je(e),n=r.shape,a=n.length;return X(()=>{let{mean:s,variance:i}=jf(r,this.axis,!0),o=Oo(1,a);for(let c of this.axis)o[c]=n[c];let l=c=>c!=null&&c.shape.length!==a?U(c,o):c,u=this.scale?l(this.gamma.read()):null,d=this.center?l(this.beta.read()):null,h=[],p=[];for(let c=0;c<a;++c)this.axis.indexOf(c)!==-1?(h.push(n[c]),p.push(1)):(h.push(1),p.push(n[c]));return s=Gn(s,h),i=Gn(i,h),u!=null&&(u=Gn(u,p)),d!=null&&(d=Gn(d,p)),Jp(r,s,i,d,u,this.epsilon)})}getConfig(){let e={axis:this.axis,epsilon:this.epsilon,center:this.center,scale:this.scale,betaInitializer:zt(this.betaInitializer),gammaInitializer:zt(this.gammaInitializer),betaRegularizer:bt(this.betaRegularizer),gammaRegularizer:bt(this.gammaRegularizer)},t=super.getConfig();return Object.assign(e,t),e}};B5.className="LayerNormalization";ue.registerClass(B5);function eG(e,t,r){return X(()=>{if(e.rank!==4)throw new q(`temporalPadding expects input tensor to be 4-D, but received a ${e.rank}-D tensor.`);if(t==null&&(t=[[1,1],[1,1]]),t.length!==2||t[0].length!==2||t[1].length!==2)throw new q("spatial2dPadding expects `padding` to be an Array of two Arrays, each of which is an Array of two integers.");if(r==null&&(r=Aa()),r!=="channelsLast"&&r!=="channelsFirst")throw new q(`Unknown data format: ${r}. 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s==="max"?i=Gf(e,t,r,o):i=Of(e,t,r,o),a==="channelsFirst"&&(i=tt(i,[0,3,1,2])),i})}function u8(e,t,r,n,a,s){return X(()=>{jt(a),lw(s),Ln(n),r==null&&(r=[1,1,1]),n==null&&(n="valid"),a==null&&(a=Aa()),s==null&&(s="max"),e=e8(e,a);let i,o=n==="same"?"same":"valid";return s==="max"?i=d3(e,t,r,o):i=Ky(e,t,r,o),a==="channelsFirst"&&(i=tt(i,[0,4,1,2,3])),i})}var d8=class extends st{constructor(e){if(e.poolSize==null&&(e.poolSize=2),super(e),typeof e.poolSize=="number")this.poolSize=[e.poolSize];else if(Array.isArray(e.poolSize)&&e.poolSize.length===1&&typeof e.poolSize[0]=="number")this.poolSize=e.poolSize;else throw new q(`poolSize for 1D convolutional layer must be a number or an Array of a single number, but received ${JSON.stringify(e.poolSize)}`);if(gr(this.poolSize,"poolSize"),e.strides==null)this.strides=this.poolSize;else if(typeof e.strides=="number")this.strides=[e.strides];else if(Array.isArray(e.strides)&&e.strides.length===1&&typeof e.strides[0]=="number")this.strides=e.strides;else throw new q(`strides for 1D convolutional layer must be a number or an Array of a single number, but received ${JSON.stringify(e.strides)}`);gr(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,Ln(this.padding),this.inputSpec=[new Zt({ndim:3})]}computeOutputShape(e){e=mt(e);let t=ma(e[1],this.poolSize[0],this.padding,this.strides[0]);return[e[0],t,e[2]]}call(e,t){return X(()=>{this.invokeCallHook(e,t),e=Ph(je(e),2);let r=this.poolingFunction(je(e),[this.poolSize[0],1],[this.strides[0],1],this.padding,"channelsLast");return et(r,[2])})}getConfig(){let e={poolSize:this.poolSize,padding:this.padding,strides:this.strides},t=super.getConfig();return Object.assign(e,t),e}},V5=class extends d8{constructor(e){super(e)}poolingFunction(e,t,r,n,a){return jt(a),Ln(n),Em(e,t,r,n,a,"max")}};V5.className="MaxPooling1D";ue.registerClass(V5);var U5=class extends d8{constructor(e){super(e)}poolingFunction(e,t,r,n,a){return jt(a),Ln(n),Em(e,t,r,n,a,"avg")}};U5.className="AveragePooling1D";ue.registerClass(U5);var p8=class extends st{constructor(e){if(e.poolSize==null&&(e.poolSize=[2,2]),super(e),this.poolSize=Array.isArray(e.poolSize)?e.poolSize:[e.poolSize,e.poolSize],e.strides==null)this.strides=this.poolSize;else if(Array.isArray(e.strides)){if(e.strides.length!==2)throw new q(`If the strides property of a 2D pooling layer is an Array, it is expected to have a length of 2, but received length ${e.strides.length}.`);this.strides=e.strides}else this.strides=[e.strides,e.strides];gr(this.poolSize,"poolSize"),gr(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,jt(this.dataFormat),Ln(this.padding),this.inputSpec=[new Zt({ndim:4})]}computeOutputShape(e){e=mt(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],r=this.dataFormat==="channelsFirst"?e[3]:e[2];return t=ma(t,this.poolSize[0],this.padding,this.strides[0]),r=ma(r,this.poolSize[1],this.padding,this.strides[1]),this.dataFormat==="channelsFirst"?[e[0],e[1],t,r]:[e[0],t,r,e[3]]}call(e,t){return X(()=>(this.invokeCallHook(e,t),this.poolingFunction(je(e),this.poolSize,this.strides,this.padding,this.dataFormat)))}getConfig(){let e={poolSize:this.poolSize,padding:this.padding,strides:this.strides,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}},G5=class extends p8{constructor(e){super(e)}poolingFunction(e,t,r,n,a){return jt(a),Ln(n),Em(e,t,r,n,a,"max")}};G5.className="MaxPooling2D";ue.registerClass(G5);var j5=class extends p8{constructor(e){super(e)}poolingFunction(e,t,r,n,a){return jt(a),Ln(n),Em(e,t,r,n,a,"avg")}};j5.className="AveragePooling2D";ue.registerClass(j5);var h8=class extends st{constructor(e){if(e.poolSize==null&&(e.poolSize=[2,2,2]),super(e),this.poolSize=Array.isArray(e.poolSize)?e.poolSize:[e.poolSize,e.poolSize,e.poolSize],e.strides==null)this.strides=this.poolSize;else if(Array.isArray(e.strides)){if(e.strides.length!==3)throw new q(`If the strides property of a 3D pooling layer is an Array, it is expected to have a length of 3, but received length ${e.strides.length}.`);this.strides=e.strides}else this.strides=[e.strides,e.strides,e.strides];gr(this.poolSize,"poolSize"),gr(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,jt(this.dataFormat),Ln(this.padding),this.inputSpec=[new Zt({ndim:5})]}computeOutputShape(e){e=mt(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],r=this.dataFormat==="channelsFirst"?e[3]:e[2],n=this.dataFormat==="channelsFirst"?e[4]:e[3];return 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EH(e,t,r){let{usedNodes:n,inputs:a}=r,s=[],i=Object.keys(a).map(d=>pn(d)[0]).map(d=>e.nodes[d]),o=e.initNodes;i.forEach(d=>{n.has(d.name)&&s.push(d)}),e.weights.forEach(d=>{n.has(d.name)&&s.push(d)}),o!=null&&o.forEach(d=>{n.has(d.name)&&s.push(d)});let l=new Set,u=[];for(;s.length>0;){let d=s.pop();l.add(d.name),t[d.name]||u.push(d),d.children.forEach(h=>{!l.has(h.name)&&n.has(h.name)&&h.inputs.every(p=>l.has(p.name))&&s.push(h)})}return u}var RH=["Switch","Merge","Enter","Exit","NextIteration","StatelessIf","StatelessWhile","if","While"],MH=["NonMaxSuppressionV2","NonMaxSuppressionV3","NonMaxSuppressionV5","Where"],$H=["HashTable","HashTableV2","LookupTableImport","LookupTableImportV2","LookupTableFind","LookupTableFindV2","LookupTableSize","LookupTableSizeV2"];function X8(e){return RH.indexOf(e.op)>=0}function FH(e){return MH.indexOf(e.op)>=0}function _H(e){return $H.indexOf(e.op)>=0}var iy=class{constructor(e,t){this.graph=e,this.parent=t,this.compiledMap=new Map,this._weightMap={},this.SEPERATOR=",",this._functions={},this._functionExecutorMap={},this.intermediateTensors={},this.keepTensorForDebug=!1,this._outputs=e.outputs,this._inputs=e.inputs,this._initNodes=e.initNodes,this._signature=e.signature,this._functions=e.functions,e.functions!=null&&Object.keys(e.functions).forEach(r=>{this._functionExecutorMap[r]=new iy(e.functions[r],this)})}get weightIds(){return this.parent?this.parent.weightIds:this._weightIds}get functionExecutorMap(){return this.parent?this.parent.functionExecutorMap:this._functionExecutorMap}get weightMap(){return this.parent?this.parent.weightMap:this._weightMap}set weightMap(e){let t=Object.keys(e).map(r=>e[r].map(n=>n.id));this._weightIds=[].concat(...t),this._weightMap=e}set resourceManager(e){this._resourceManager=e}get inputs(){return this._inputs.map(e=>({name:e.name,shape:e.attrParams.shape?e.attrParams.shape.value:void 0,dtype:e.attrParams.dtype?e.attrParams.dtype.value:void 0}))}get outputs(){return 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Please use model.executeAsync() instead. Alternatively, to avoid the dynamic ops, specify the inputs [${s}]`);if(n.length>0){let i=t.map(l=>l.name),o=Object.keys(e);throw new Error(`Cannot compute the outputs [${i}] from the provided inputs [${o}]. Missing the following inputs: [${n}]`)}return EH(this.graph,this.weightMap,r)}execute(e,t){e=this.mapInputs(e);let r=Object.keys(e).sort();this.checkInputs(e),this.checkInputShapeAndType(e),t=this.mapOutputs(t),this.checkOutputs(t);let n=r.map(d=>this.graph.nodes[pn(d)[0]]),a=t.map(d=>pn(d)[0]),s=a.map(d=>this.graph.nodes[d]);this.resetIntermediateTensors(),s.length===0&&(s=this._outputs);let i=this.getCompilationKey(n,s),o=this.compiledMap.get(i);o==null&&(o=this.compile(e,s),this.compiledMap.set(i,o));let l={},u={};return X(()=>{let d=new P4(this.weightMap,l,u,this.functionExecutorMap),h={...this.weightMap};Object.keys(e).forEach(m=>{let[f,g]=pn(m),y=[];y[g]=e[m],h[f]=y});let p=this.getFrozenTensorIds(h),c={};for(let m=0;m<o.length;m++){let f=o[m];if(!h[f.name]){let g=_4(f,h,d,this._resourceManager);if(v.isPromise(g))throw new Error(`The execution of the op '${f.op}' returned a promise. 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this.upstream.next()}},rq=class extends xr{constructor(e,t){super(),this.upstream=e,this.maxCount=t,this.count=0}summary(){return`${this.upstream.summary()} -> Take`}async next(){return this.count++>=this.maxCount?{value:null,done:!0}:this.upstream.next()}},nq=class extends xr{constructor(e,t,r=!0){super(),this.upstream=e,this.batchSize=t,this.enableSmallLastBatch=r,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> RowMajorBatch`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){let e=[];for(;e.length<this.batchSize;){let t=await this.upstream.next();if(t.done)return this.enableSmallLastBatch&&e.length>0?{value:e,done:!1}:{value:null,done:!0};e.push(t.value)}return{value:e,done:!1}}},aq=class extends xr{constructor(e,t){super(),this.upstream=e,this.predicate=t,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> Filter`}async 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this.upstream.next()}catch(e){if(!this.handler(e))return{value:null,done:!0}}}},z4=class extends xr{constructor(e,t){super(),this.upstream=e,this.transform=t}summary(){return`${this.upstream.summary()} -> AsyncMap`}async next(){let e=await this.upstream.next();if(e.done)return{value:null,done:!0};let t=ha.getTensorsInContainer(e.value),r=await this.transform(e.value),n=ha.getTensorsInContainer(r);for(let a of t)ha.isTensorInList(a,n)||a.dispose();return{value:r,done:!1}}},iA=class extends xr{constructor(){super(),this.outputQueue=new tk,this.lastRead=Promise.resolve({value:null,done:!1})}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){for(;this.outputQueue.length()===0;)if(!await this.pump())return{value:null,done:!0};return{value:this.outputQueue.shift(),done:!1}}},oq=class extends iA{constructor(e,t){super(),this.upstream=e,this.transform=t}summary(){return`${this.upstream.summary()} -> Flatmap`}async pump(){let e=await this.upstream.next();if(e.done)return!1;let t=ha.getTensorsInContainer(e.value),r=this.transform(e.value),n=ha.getTensorsInContainer(r);this.outputQueue.pushAll(r);for(let a of t)ha.isTensorInList(a,n)||a.dispose();return!0}},nk=class extends xr{constructor(e,t){super(),this.baseErrorHandler=t,this.lastRead=null,this.iterator=null,this.moreIterators=e}summary(){return"TODO: fill in upstream of chained summaries -> Chained"}async next(){return this.lastRead=this.readFromChain(this.lastRead),this.lastRead}async readFromChain(e){if(await e,this.iterator==null){let r=await this.moreIterators.next();if(r.done)return{value:null,done:!0};this.iterator=r.value,this.baseErrorHandler!=null&&(this.iterator=this.iterator.handleErrors(this.baseErrorHandler))}let t=await this.iterator.next();return t.done?(this.iterator=null,this.readFromChain(e)):t}},ak=(e=>(e[e.FAIL=0]="FAIL",e[e.SHORTEST=1]="SHORTEST",e[e.LONGEST=2]="LONGEST",e))(ak||{}),lq=class extends xr{constructor(e,t=0){super(),this.iterators=e,this.mismatchMode=t,this.count=0,this.currentPromise=null}summary(){return"{TODO: fill in upstream of zip summaries} -> Zip"}async nextState(e){await e;let t=0,r=0;function n(s){return s instanceof xr?{value:s.next().then(i=>(t++,i.done&&r++,i.value)),recurse:!1}:{value:null,recurse:!0}}let a=await J8(this.iterators,n);if(t===r)return{value:null,done:!0};if(r>0)switch(this.mismatchMode){case 0:throw new Error(`Zipped streams should have the same length. Mismatched at element ${this.count}.`);case 1:return{value:null,done:!0};case 2:default:}return this.count++,{value:a,done:!1}}async next(){return this.currentPromise=this.nextState(this.currentPromise),this.currentPromise}},sk=class extends xr{constructor(e,t){super(),this.upstream=e,this.bufferSize=t,this.buffer=new Q8(t)}summary(){return`${this.upstream.summary()} -> Prefetch`}refill(){for(;!this.buffer.isFull();){let e=this.upstream.next();this.buffer.push(e)}}next(){return this.refill(),this.buffer.shift()}},uq=class extends sk{constructor(e,t,r){super(e,t),this.upstream=e,this.windowSize=t,this.upstreamExhausted=!1,this.random=UH.alea(r||v.now().toString()),this.lastRead=Promise.resolve({value:null,done:!1})}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}randomInt(e){return Math.floor(this.random()*e)}chooseIndex(){return this.randomInt(this.buffer.length())}async serialNext(){for(this.upstreamExhausted||this.refill();!this.buffer.isEmpty();){let e=this.chooseIndex(),t=await this.buffer.shuffleExcise(e);if(t.done)this.upstreamExhausted=!0;else return this.refill(),t}return{value:null,done:!0}}},Cd=class{constructor(){this.size=null}batch(e,t=!0){let r=this;v.assert(e>0,()=>`batchSize needs to be positive, but it is
${e}`);let n;return this.size===1/0||this.size==null?n=this.size:t?n=Math.ceil(this.size/e):n=Math.floor(this.size/e),dn(async()=>(await r.iterator()).columnMajorBatch(e,t,hq),n)}concatenate(e){let t=this,r;return this.size===1/0||e.size===1/0?r=1/0:this.size!=null&&e.size!=null?r=this.size+e.size:r=null,dn(async()=>(await t.iterator()).concatenate(await e.iterator()),r)}filter(e){let t=this,r;return this.size===1/0?r=1/0:r=null,dn(async()=>(await t.iterator()).filter(n=>X(()=>e(n))),r)}async forEachAsync(e){return(await this.iterator()).forEachAsync(e)}map(e){let t=this;return dn(async()=>(await t.iterator()).map(r=>X(()=>e(r))),this.size)}mapAsync(e){let t=this;return dn(async()=>(await t.iterator()).mapAsync(e),this.size)}prefetch(e){if(e==null)throw new RangeError("`Dataset.prefetch()` requires bufferSize to be specified.");let t=this;return dn(async()=>(await t.iterator()).prefetch(e),this.size)}repeat(e){let t=this,r;return this.size!=null&&e>0?r=this.size*e:e===0?r=0:this.size!=null&&(e===void 0||e<0)?r=1/0:r=null,dn(async()=>{let n=sA(async()=>({value:await t.iterator(),done:!1}));return ZH(n.take(e))},r)}skip(e){let t=this,r;return this.size!=null&&e>=0&&this.size>=e?r=this.size-e:this.size!=null&&(this.size<e||e===void 0||e<0)?r=0:r=null,dn(async()=>(await t.iterator()).skip(e),r)}shuffle(e,t,r=!0){if(e==null||e<0)throw this.size==null?new RangeError("`Dataset.shuffle()` requires bufferSize to be specified."):new RangeError(`\`Dataset.shuffle()\` requires bufferSize to be specified. If your data fits in main memory (for regular JS objects), and/or GPU memory (for \`tf.Tensor\`s), consider setting bufferSize to the dataset size (${this.size} elements)`);let n=this,a=VH.alea(t||v.now().toString());return dn(async()=>{let s=a.int32();return r&&(s+=a.int32()),(await n.iterator()).shuffle(e,s.toString())},this.size)}take(e){let t=this,r;return this.size!=null&&this.size>e?r=e:this.size!=null&&this.size<=e?r=this.size:r=null,dn(async()=>(await t.iterator()).take(e),r)}async toArray(){if(this.size===1/0)throw new Error("Can not convert infinite data stream to array.");return(await this.iterator()).toArray()}async toArrayForTest(){if(this.size===1/0)throw new Error("Can not convert infinite data stream to array.");return(await this.iterator()).toArrayForTest()}};Cd.MAX_BUFFER_SIZE=1e4;function dn(e,t=null){return new class extends Cd{constructor(){super(...arguments),this.size=t}async iterator(){return e()}}}function dq(e){return dn(async()=>rk(e),e.length)}function pq(e){if(!Ou(e))throw new Error("The argument to zip() must be an object or array.");let t;if(Array.isArray(e))for(let r=0;r<e.length;r++)t=t==null?e[r].size:Math.min(t,e[r].size);else if(e instanceof Object)for(let r in e)t=t==null?e[r].size:Math.min(t,e[r].size);return dn(async()=>{let r=await J8(e,n=>{if(n instanceof Cd)return{value:n.iterator(),recurse:!1};if(Ou(n))return{value:null,recurse:!0};throw new Error("Leaves of the structure passed to zip() must be Datasets, not primitives.")});return YH(r,1)},t)}function hq(e){if(e===null)return null;let t=e[0];return HH(t)?{value:cq(e),recurse:!1}:{value:null,recurse:!0}}function cq(e){if(e.length===0)throw new Error("Can't make a batch of zero elements.");return e[0]instanceof nt?ur(e):ft(e)}var ik=class extends Cd{constructor(e){super(),this.input=e}async iterator(){return(await this.input.iterator()).decodeUTF8().split(`
`).map(e=>(e.endsWith("\r")&&(e=e.slice(0,-1)),e))}},i0='"',Cp=Symbol("out"),D4=Symbol("field"),o0=Symbol("quote"),bg=Symbol("quoteafterquote"),L4=Symbol("quoteinquote"),ok=class extends Cd{constructor(e,t){super(),this.input=e,this.hasHeader=!0,this.fullColumnNames=null,this.columnNamesValidated=!1,this.columnConfigs=null,this.configuredColumnsOnly=!1,this.delimiter=",",this.delimWhitespace=!1,this.base=new ik(e),t||(t={}),this.hasHeader=t.hasHeader!==!1,this.fullColumnNames=t.columnNames,this.columnConfigs=t.columnConfigs,this.configuredColumnsOnly=t.configuredColumnsOnly,t.delimWhitespace?(v.assert(t.delimiter==null,()=>"Delimiter should not be provided when delimWhitespace is true."),this.delimWhitespace=!0,this.delimiter=" "):this.delimiter=t.delimiter?t.delimiter:","}async columnNames(){return this.columnNamesValidated||await this.setColumnNames(),this.configuredColumnsOnly?Object.keys(this.columnConfigs):this.fullColumnNames}async setColumnNames(){let e=await this.maybeReadHeaderLine();if(!this.fullColumnNames&&!e)throw new Error("Column names must be provided if there is no header line.");this.fullColumnNames&&e&&v.assert(e.length===this.fullColumnNames.length,()=>"The length of provided columnNames ("+this.fullColumnNames.length.toString()+") does not match the length of the header line read from file ("+e.length.toString()+")."),this.fullColumnNames||(this.fullColumnNames=e);let t=this.fullColumnNames.reduce((n,a)=>(n[a]=n[a]+1||1,n),{}),r=Object.keys(t).filter(n=>t[n]>1);if(v.assert(r.length===0,()=>"Duplicate column names found: "+r.toString()),this.columnConfigs){for(let n of Object.keys(this.columnConfigs))if(this.fullColumnNames.indexOf(n)===-1)throw new Error('The key "'+n+'" provided in columnConfigs does not match any of the column names ('+this.fullColumnNames.toString()+").")}this.columnNamesValidated=!0}async maybeReadHeaderLine(){if(this.hasHeader){let e=await(await this.base.iterator()).next();if(e.done)throw new Error("No data was found for CSV parsing.");let t=e.value;return this.parseRow(t,!1)}else return null}async iterator(){this.columnNamesValidated||await this.setColumnNames();let e=await this.base.iterator();return this.hasHeader&&(e=e.skip(1)),e.map(t=>this.makeDataElement(t))}makeDataElement(e){let t=this.parseRow(e),r={},n={};for(let a=0;a<this.fullColumnNames.length;a++){let s=this.fullColumnNames[a],i=this.columnConfigs?this.columnConfigs[s]:null;if(!(this.configuredColumnsOnly&&!i)){let o=t[a],l=null;if(o==="")if(i&&i.default!==void 0)l=i.default;else{if(i&&(i.required||i.isLabel))throw new Error(`Required column ${s} is empty in this line: ${e}`);l=void 0}else{let u=Number(o);if(isNaN(u))i&&i.dtype==="bool"?l=this.getBoolean(o):l=o;else if(!i||!i.dtype)l=u;else switch(i.dtype){case"float32":l=u;break;case"int32":l=Math.floor(u);break;case"bool":l=this.getBoolean(o);break;default:l=u}}i&&i.isLabel?n[s]=l:r[s]=l}}return Object.keys(n).length===0?r:{xs:r,ys:n}}getBoolean(e){return e==="1"||e.toLowerCase()==="true"?1:0}parseRow(e,t=!0){let r=[],n=0,a=e.length,s=Cp;for(let i=0;i<a;i++)switch(s){case Cp:switch(e.charAt(i)){case i0:n=i+1,s=o0;break;case this.delimiter:if(n=i+1,this.delimiter===" "&&this.delimWhitespace)break;r.push(""),s=Cp;break;default:s=D4,n=i;break}break;case D4:switch(e.charAt(i)){case this.delimiter:r.push(e.substring(n,i)),s=Cp,n=i+1;break;default:}break;case o0:switch(e.charAt(i)){case i0:s=bg;break;default:}break;case bg:switch(e.charAt(i)){case this.delimiter:r.push(e.substring(n,i-1)),s=Cp,n=i+1;break;case i0:s=o0;break;default:s=L4;break}break;case L4:switch(e.charAt(i)){case i0:s=o0;break;default:}break;default:}if(s===bg?r.push(e.substring(n,a-1)):r.push(e.substring(n)),t&&r.length!==this.fullColumnNames.length)throw new Error(`Invalid row in csv file. Should have ${this.fullColumnNames.length} elements in a row, but got ${r}`);return r}},lk=class extends xr{constructor(e){super(),this.microphoneConfig=e,this.isClosed=!1,this.fftSize=e.fftSize||1024;let t=Math.log2(this.fftSize);if(this.fftSize<0||t<4||t>14||!Number.isInteger(t))throw new Error(`Invalid fftSize: it must be a power of 2 between 2 to 4 and 2 to 14, but got ${this.fftSize}`);if(this.numFrames=e.numFramesPerSpectrogram||43,this.sampleRateHz=e.sampleRateHz,this.columnTruncateLength=e.columnTruncateLength||this.fftSize,this.audioTrackConstraints=e.audioTrackConstraints,this.smoothingTimeConstant=e.smoothingTimeConstant||0,this.includeSpectrogram=e.includeSpectrogram!==!1,this.includeWaveform=e.includeWaveform===!0,!this.includeSpectrogram&&!this.includeWaveform)throw new Error("Both includeSpectrogram and includeWaveform are false. At least one type of data should be returned.")}summary(){return"microphone"}static async create(e={}){if(!Z().get("IS_BROWSER"))throw new Error("microphone API is only supported in browser environment.");let t=new lk(e);return await t.start(),t}async start(){try{this.stream=await navigator.mediaDevices.getUserMedia({audio:this.audioTrackConstraints==null?!0:this.audioTrackConstraints,video:!1})}catch(r){throw new Error(`Error thrown while initializing video stream: ${r.message}`)}if(!this.stream)throw new Error("Could not obtain audio from microphone.");let e=window.AudioContext||window.webkitAudioContext;if(this.audioContext=new e,!this.sampleRateHz)this.sampleRateHz=this.audioContext.sampleRate;else if(this.audioContext.sampleRate!==this.sampleRateHz)throw new Error(`Mismatch in sampling rate: Expected: ${this.sampleRateHz}; Actual: ${this.audioContext.sampleRate}`);let t=this.audioContext.createMediaStreamSource(this.stream);this.analyser=this.audioContext.createAnalyser(),this.analyser.fftSize=this.fftSize*2,this.analyser.smoothingTimeConstant=this.smoothingTimeConstant,t.connect(this.analyser),this.freqData=new Float32Array(this.fftSize),this.timeData=new Float32Array(this.fftSize)}async next(){if(this.isClosed)return{value:null,done:!0};let e,t,r=await this.getAudioData();if(this.includeSpectrogram){let n=this.flattenQueue(r.freqDataQueue);e=this.getTensorFromAudioDataArray(n,[this.numFrames,this.columnTruncateLength,1])}if(this.includeWaveform){let n=this.flattenQueue(r.timeDataQueue);t=this.getTensorFromAudioDataArray(n,[this.numFrames*this.fftSize,1])}return{value:{spectrogram:e,waveform:t},done:!1}}async capture(){return(await this.next()).value}async getAudioData(){let e=[],t=[],r=0;return new Promise(n=>{let a=setInterval(()=>{this.includeSpectrogram&&(this.analyser.getFloatFrequencyData(this.freqData),this.freqData[0]===-1/0&&n({freqDataQueue:e,timeDataQueue:t}),e.push(this.freqData.slice(0,this.columnTruncateLength))),this.includeWaveform&&(this.analyser.getFloatTimeDomainData(this.timeData),t.push(this.timeData.slice())),++r===this.numFrames&&(clearInterval(a),n({freqDataQueue:e,timeDataQueue:t}))},this.fftSize/this.sampleRateHz*1e3)})}stop(){this.isClosed||(this.isClosed=!0,this.analyser.disconnect(),this.audioContext.close(),this.stream!=null&&this.stream.getTracks().length>0&&this.stream.getTracks()[0].stop())}toArray(){throw new Error("Can not convert infinite audio stream to array.")}getSampleRate(){return this.sampleRateHz}flattenQueue(e){let t=e[0].length,r=new Float32Array(e.length*t);return e.forEach((n,a)=>r.set(n,a*t)),r}getTensorFromAudioDataArray(e,t){let r=new Float32Array(v.sizeFromShape(t));return r.set(e,r.length-e.length),ft(r,t)}},uk=class extends xr{constructor(e,t){if(super(),this.webcamVideoElement=e,this.webcamConfig=t,this.isClosed=!0,this.resize=!1,this.needToResize())if(this.resize=!0,this.cropSize=[this.webcamConfig.resizeHeight,this.webcamConfig.resizeWidth],this.cropBoxInd=Nt([0],"int32"),this.webcamConfig.centerCrop){let r=this.webcamConfig.resizeWidth*1/this.webcamVideoElement.width,n=this.webcamConfig.resizeHeight*1/this.webcamVideoElement.height,a=(1-r)/2,s=(1-n)/2,i=a+r,o=n+s;this.cropBox=ca([s,a,o,i],[1,4])}else this.cropBox=ca([0,0,1,1],[1,4])}summary(){return"webcam"}static async create(e,t={}){if(!Z().get("IS_BROWSER"))throw new Error("tf.data.webcam is only supported in browser environment.");if(!e){if(e=document.createElement("video"),!t.resizeWidth||!t.resizeHeight)throw new Error("Please provide webcam video element, or resizeWidth and resizeHeight to create a hidden video element.");e.width=t.resizeWidth,e.height=t.resizeHeight}let r=new uk(e,t);return await r.start(),r}async start(){this.webcamConfig.facingMode&&v.assert(this.webcamConfig.facingMode==="user"||this.webcamConfig.facingMode==="environment",()=>`Invalid webcam facing mode: ${this.webcamConfig.facingMode}. Please provide 'user' or 'environment'`);try{this.stream=await navigator.mediaDevices.getUserMedia({video:{deviceId:this.webcamConfig.deviceId,facingMode:this.webcamConfig.facingMode?this.webcamConfig.facingMode:"user",width:this.webcamVideoElement.width,height:this.webcamVideoElement.height}})}catch(e){throw e.message=`Error thrown while initializing video stream: ${e.message}`,e}if(!this.stream)throw new Error("Could not obtain video from webcam.");try{this.webcamVideoElement.srcObject=this.stream}catch(e){console.log(e),this.webcamVideoElement.src=window.URL.createObjectURL(this.stream)}return this.webcamVideoElement.play(),this.isClosed=!1,new Promise(e=>{this.webcamVideoElement.onloadedmetadata=()=>{e()}})}async next(){if(this.isClosed)return{value:null,done:!0};let e;try{e=Dn.fromPixels(this.webcamVideoElement)}catch(t){throw new Error(`Error thrown converting video to pixels: ${JSON.stringify(t)}`)}if(this.resize)try{return{value:this.cropAndResizeFrame(e),done:!1}}catch(t){throw new Error(`Error thrown cropping the video: ${t.message}`)}finally{e.dispose()}else return{value:e,done:!1}}needToResize(){return!!(this.webcamConfig.resizeWidth&&this.webcamConfig.resizeHeight&&(this.webcamVideoElement.width!==this.webcamConfig.resizeWidth||this.webcamVideoElement.height!==this.webcamConfig.resizeHeight))}cropAndResizeFrame(e){return X(()=>{let t=Kt(me(e,"float32"),0),r;r=Ie.cropAndResize(t,this.cropBox,this.cropBoxInd,this.cropSize,"bilinear");let n=r.shape;return U(r,n.slice(1))})}async capture(){return(await this.next()).value}stop(){this.stream.getTracks().forEach(e=>e.stop());try{this.webcamVideoElement.srcObject=null}catch(e){console.log(e),this.webcamVideoElement.src=null}this.isClosed=!0}toArray(){throw new Error("Can not convert infinite video stream to array.")}},dk=class{},pk=class extends xr{split(e){return new fq(this,e)}},fq=class extends pk{constructor(e,t){super(),this.upstream=e,this.impl=new mq(e,t)}summary(){return this.impl.summary()}async next(){return this.impl.next()}},mq=class extends iA{constructor(e,t){super(),this.upstream=e,this.separator=t,this.carryover=""}summary(){return`${this.upstream.summary()} -> Split('${this.separator}')`}async pump(){let e=await this.upstream.next();if(e.done)return this.carryover===""?!1:(this.outputQueue.push(this.carryover),this.carryover="",!0);let t=e.value.split(this.separator);t[0]=this.carryover+t[0];for(let r of t.slice(0,-1))this.outputQueue.push(r);return this.carryover=t[t.length-1],!0}},gq=class extends xr{decodeUTF8(){return new yq(this)}},yq=class extends pk{constructor(e){super(),this.upstream=e,this.impl=new Aq(e)}summary(){return this.impl.summary()}async next(){return this.impl.next()}},Aq=class extends iA{constructor(e){if(super(),this.upstream=e,Z().get("IS_BROWSER"))this.decoder=new TextDecoder("utf-8");else{let{StringDecoder:t}=M7();this.decoder=new t("utf8")}}summary(){return`${this.upstream.summary()} -> Utf8`}async pump(){let e=await this.upstream.next(),t;if(e.done)return!1;t=e.value;let r;return Z().get("IS_BROWSER")?r=this.decoder.decode(t,{stream:!0}):r=this.decoder.write(Buffer.from(t.buffer)),this.outputQueue.push(r),!0}},hk=class extends gq{constructor(e,t={}){super(),this.file=e,this.options=t,v.assert(e instanceof Uint8Array||(Z().get("IS_BROWSER")?e instanceof File||e instanceof Blob:!1),()=>"FileChunkIterator only supports File, Blob and Uint8Array right now."),this.offset=t.offset||0,this.chunkSize=t.chunkSize||1024*1024}summary(){return`FileChunks ${this.file}`}async next(){return this.offset>=(this.file instanceof Uint8Array?this.file.byteLength:this.file.size)?{value:null,done:!0}:{value:await new Promise((e,t)=>{let r=this.offset+this.chunkSize;if(this.file instanceof Uint8Array)e(new Uint8Array(this.file.slice(this.offset,r)));else{let n=new FileReader;n.onload=s=>{let i=n.result;if(i instanceof ArrayBuffer&&(i=new Uint8Array(i)),!(i instanceof Uint8Array))return t(new TypeError("FileReader returned unknown type."));e(i)},n.onabort=s=>t(new Error("Aborted")),n.onerror=s=>t(new Error(s.type));let a=this.file.slice(this.offset,r);n.readAsArrayBuffer(a)}this.offset=r}),done:!1}}};async function xq(e,t={},r){let n,a;typeof e=="string"?n=e:(n=e.url,a=bq(e));let s=await(r||v.fetch)(n,a);if(s.ok){let i=new Uint8Array(await s.arrayBuffer());return new hk(i,t)}else throw new Error(s.statusText)}var bq=e=>({method:e.method,headers:e.headers,body:e.body,mode:e.mode,credentials:e.credentials,cache:e.cache,redirect:e.redirect,referrer:e.referrer,integrity:e.integrity});function ck(e){return typeof e=="string"&&e.slice(0,7)==="file://"}var fk=class extends dk{constructor(e,t={}){super(),this.input=e,this.options=t}async iterator(){if(ck(this.input)&&Z().get("IS_NODE")){let e=ky();this.input=e.readFileSync(this.input.slice(7))}return new hk(this.input,this.options)}},mk=class extends dk{constructor(e,t={}){super(),this.url=e,this.fileOptions=t}async iterator(){return ck(this.url)?new fk(this.url,this.fileOptions).iterator():xq(this.url,this.fileOptions)}};function vq(e,t={}){return new ok(new mk(e),t)}function wq(e){let t=sA(e);return dn(async()=>t)}function kq(e){return dn(async()=>{let t=await e();return sA(()=>t.next())})}async function Iq(e,t){return uk.create(e,t)}async function Sq(e){return lk.create(e)}var Cq="0.0.0";function Ce(e,t){Array.isArray(e)||(e=[e]),e.forEach(r=>{r!=null&&v.assert(r.dtype!=="complex64",()=>`${t} does not support complex64 tensors in the CPU backend.`)})}var Tq=Kn.whereImpl,gk=class extends Wu{constructor(){super(),this.blockSize=48,this.firstUse=!0,this.data=new rh(this,Xt())}nextDataId(){return gk.nextDataId++}write(e,t,r){this.firstUse&&(this.firstUse=!1,Z().get("IS_NODE")&&C.warn(`
============================
Hi, looks like you are running TensorFlow.js in Node.js. To speed things up dramatically, install our node backend, visit https://github.com/tensorflow/tfjs-node for more details.
============================`));let n={id:this.nextDataId()};return this.data.set(n,{values:e,dtype:r,refCount:1}),n}makeTensorInfo(e,t,r){let n;if(t==="string"&&r!=null&&r.length>0&&v.isString(r[0])){let a=r.map(s=>v.encodeString(s));n=this.write(a,e,t)}else n=this.write(r,e,t);return{dataId:n,shape:e,dtype:t}}refCount(e){return this.data.has(e)?this.data.get(e).refCount:0}incRef(e){let t=this.data.get(e);t.refCount++}decRef(e){if(this.data.has(e)){let t=this.data.get(e);t.refCount--}}move(e,t,r,n,a){this.data.set(e,{values:t,dtype:n,refCount:a})}numDataIds(){return this.data.numDataIds()}async read(e){return this.readSync(e)}readSync(e){let{dtype:t,complexTensorInfos:r}=this.data.get(e);if(t==="complex64"){let n=this.readSync(r.real.dataId),a=this.readSync(r.imag.dataId);return C.mergeRealAndImagArrays(n,a)}return this.data.get(e).values}bufferSync(e){let t=this.readSync(e.dataId);if(e.dtype==="string")try{let r=t.map(n=>v.decodeString(n));return Le(e.shape,e.dtype,r)}catch(r){throw new Error("Failed to decode encoded string bytes into utf-8")}return Le(e.shape,e.dtype,t)}makeOutput(e,t,r){return Xt().makeTensorFromTensorInfo(this.makeTensorInfo(t,r,e),this)}disposeData(e,t=!1){if(this.data.has(e)){if(this.data.get(e).refCount--,!t&&this.data.get(e).refCount>0)return!1;let{complexTensorInfos:r}=this.data.get(e);r!=null&&(this.disposeData(r.real.dataId,!0),this.disposeData(r.imag.dataId,!0)),this.data.delete(e)}return!0}disposeIntermediateTensorInfo(e){this.disposeData(e.dataId)}async time(e){let t=v.now();return e(),{kernelMs:v.now()-t}}memory(){return{unreliable:!0,reasons:["The reported memory is an upper bound. 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ae=J*l-y,de=ae;for(;de<0;)de+=h;let be=Math.min(a.inWidth,m+ae),ve=ie+J*E,Ee=A,Me=0,De=0;for(let Ke=j;Ke<K;Ke+=u){let ot=M+Ke*n[1];for(let pt=re;pt<Q;pt+=d){let ht=ot+pt*n[2];for(let Fe=de;Fe<be;Fe+=h){let wt=ht+Fe*n[3],At=e[wt+S];if(s==="max"&&At>Ee?Ee=At:s==="avg"&&(Me+=At,De++),isNaN(Ee))break}if(isNaN(Ee))break}if(isNaN(Ee))break}let We=ve+S;b[We]=s==="avg"?Me/De:Ee}}}}return x}function uK(e,t){let r=Le(t.outShape,"int32"),n=t.strideDepth,a=t.strideHeight,s=t.strideWidth,i=t.dilationDepth,o=t.dilationHeight,l=t.dilationWidth,u=t.effectiveFilterDepth,d=t.effectiveFilterHeight,h=t.effectiveFilterWidth,p=t.padInfo.front,c=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 A=y*n-p,x=A;for(;x<0;)x+=i;let b=Math.min(t.inDepth,u+A);for(let w=0;w<t.outHeight;++w){let I=w*a-c,T=I;for(;T<0;)T+=o;let E=Math.min(t.inHeight,d+I);for(let R=0;R<t.outWidth;++R){let O=R*s-m,M=O;for(;M<0;)M+=l;let S=Math.min(t.inWidth,h+O),P=Number.NEGATIVE_INFINITY,z=-1;for(let j=x;j<b;j+=i){let K=j-A;for(let D=T;D<E;D+=o){let Y=D-I;for(let V=M;V<S;V+=l){let re=V-O,Q=e.get(f,j,D,V,g);Q>=P&&(P=Q,z=K*d*h+Y*d+re)}}}r.set(z,f,y,w,R,g)}}}return r}function dK(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t;Ce(a,"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. 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d=C.computePool3DInfo(s.shape,i,o,1,l,u),h=d.strideDepth,p=d.strideHeight,c=d.strideWidth,m=d.filterDepth,f=d.filterHeight,g=d.filterWidth,y=d.dilationDepth,A=d.dilationHeight,x=d.dilationWidth,b=d.effectiveFilterDepth,w=d.effectiveFilterHeight,I=d.effectiveFilterWidth,T=b-1-d.padInfo.front,E=I-1-d.padInfo.left,R=w-1-d.padInfo.top,O=Le(s.shape,"float32"),M=1/(m*f*g),S=r.bufferSync(a);for(let P=0;P<d.batchSize;++P)for(let z=0;z<d.inChannels;++z)for(let j=0;j<d.inDepth;++j)for(let K=0;K<d.inHeight;++K)for(let D=0;D<d.inWidth;++D){let Y=j-T,V=K-R,re=D-E,Q=0;for(let ie=0;ie<b;ie+=y){let J=(Y+ie)/h;if(!(J<0||J>=d.outDepth||Math.floor(J)!==J))for(let ae=0;ae<w;ae+=A){let de=(V+ae)/p;if(!(de<0||de>=d.outHeight||Math.floor(de)!==de))for(let be=0;be<I;be+=x){let ve=(re+be)/c;ve<0||ve>=d.outWidth||Math.floor(ve)!==ve||(Q+=S.get(P,J,de,ve,z))}}}O.set(Q*M,P,j,K,D,z)}return r.makeTensorInfo(O.shape,O.dtype,O.values)}var mK={kernelName:uf,backendName:"cpu",kernelFunc:fK};function gK(e){let{inputs:t,backend:r,attrs:n}=e,{dy:a,input:s}=t,i=s;Ce([a,s],"avgPoolGrad");let{filterSize:o,strides:l,pad:u}=n,d=C.computePool2DInfo(i.shape,o,l,1,u),h=d.strideHeight,p=d.strideWidth,c=d.filterHeight,m=d.filterWidth,f=d.dilationHeight,g=d.dilationWidth,y=d.effectiveFilterHeight,A=d.effectiveFilterWidth,x=A-1-d.padInfo.left,b=y-1-d.padInfo.top,w=Le(i.shape,"float32"),I=1/(c*m),T=r.data.get(a.dataId).values,E=Le(a.shape,"float32",T);for(let R=0;R<d.batchSize;++R)for(let O=0;O<d.inChannels;++O)for(let M=0;M<d.inHeight;++M)for(let S=0;S<d.inWidth;++S){let P=M-b,z=S-x,j=0;for(let K=0;K<y;K+=f){let D=(P+K)/h;if(!(D<0||D>=d.outHeight||Math.floor(D)!==D))for(let Y=0;Y<A;Y+=g){let V=(z+Y)/p;V<0||V>=d.outWidth||Math.floor(V)!==V||(j+=E.get(R,D,V,O))}}w.set(j*I,R,M,S,O)}return r.makeTensorInfo(w.shape,w.dtype,w.values)}var yK={kernelName:lf,backendName:"cpu",kernelFunc:gK};function AK(e){let{inputs:t,backend:r,attrs:n}=e,{x:a,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."),Ce([a,o,l,s,i],"batchNorm");let{varianceEpsilon:u}=n;u==null&&(u=.001);let d=r.data.get(a.dataId).values,h=r.data.get(o.dataId).values,p=r.data.get(l.dataId).values,c=s?r.data.get(s.dataId).values:new Float32Array([1]),m=i?r.data.get(i.dataId).values:new Float32Array([0]),f=new Float32Array(d.length),g=m.length,y=c.length,A=p.length,x=h.length,b=0,w=0,I=0,T=0;for(let E=0;E<d.length;++E)f[E]=m[b++]+(d[E]-h[w++])*c[I++]/Math.sqrt(p[T++]+u),b>=g&&(b=0),w>=x&&(w=0),I>=y&&(I=0),T>=A&&(T=0);return r.makeTensorInfo(a.shape,a.dtype,f)}var xK={kernelName:hi,backendName:"cpu",kernelFunc:AK};function bK(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{blockShape:s,crops:i}=n;Ce([a],"batchToSpaceND");let o=s.reduce((y,A)=>y*A),l=C.getReshaped(a.shape,s,o),u=C.getPermuted(l.length,s.length),d=C.getReshapedPermuted(a.shape,s,o),h=C.getSliceBeginCoords(i,s.length),p=C.getSliceSize(d,i,s.length),c=Ct({inputs:{x:a},backend:r,attrs:{shape:l}}),m=on({inputs:{x:c},backend:r,attrs:{perm:u}}),f=Ct({inputs:{x:m},backend:r,attrs:{shape:d}}),g=Do({inputs:{x:f},backend:r,attrs:{begin:h,size:p}});return r.disposeIntermediateTensorInfo(c),r.disposeIntermediateTensorInfo(m),r.disposeIntermediateTensorInfo(f),g}var vK={kernelName:jo,backendName:"cpu",kernelFunc:bK};function wK(e){let{inputs:t,backend:r,attrs:n}=e,{x:a,weights:s}=t,{size:i}=n,o=r.data.get(a.dataId).values,l=r.data.get(s.dataId).values,u=uA(o,l,s.dtype,s.shape,i);return r.makeTensorInfo([i],s.dtype,u)}var kK={kernelName:df,backendName:"cpu",kernelFunc:wK};function IK(e){let{inputs:t,backend:r}=e,{s0:n,s1:a}=t,s=r.data.get(n.dataId).values,i=r.data.get(a.dataId).values,o=C.assertAndGetBroadcastShape(Array.from(s),Array.from(i));return r.makeTensorInfo([o.length],"int32",Int32Array.from(o))}var SK={kernelName:pf,backendName:"cpu",kernelFunc:IK},CK=gt(Qa,(e,t)=>{let r=t;return e>r.clipValueMax?r.clipValueMax:e<r.clipValueMin?r.clipValueMin:e}),TK={kernelName:Qa,backendName:"cpu",kernelFunc:CK},NK=e=>{let{x:t}=e.inputs,r=e.backend,n=new Float32Array(v.sizeFromShape(t.shape)),a=r.data.get(t.dataId),s=a.complexTensorInfos.real,i=a.complexTensorInfos.imag,o=r.data.get(s.dataId).values,l=r.data.get(i.dataId).values;for(let u=0;u<o.length;u++){let d=o[u],h=l[u];n[u]=Math.hypot(d,h)}return r.makeOutput(n,t.shape,"float32")},EK={kernelName:sh,backendName:"cpu",kernelFunc:NK};function Du(e){let{inputs:t,backend:r}=e,{input:n}=t,a=r.data.get(n.dataId).complexTensorInfos.imag,s=r.data.get(a.dataId).values;return r.makeTensorInfo(a.shape,a.dtype,s)}var RK={kernelName:uh,backendName:"cpu",kernelFunc:Du};function Lu(e){let{inputs:t,backend:r,attrs:n}=e,{axis:a}=n,s=v.parseAxisParam(a,t[0].shape)[0],i=C.computeOutShape(t.map(f=>f.shape),s);if(v.sizeFromShape(i)===0)return r.makeTensorInfo(i,t[0].dtype,[]);let o=t.filter(f=>v.sizeFromShape(f.shape)>0);if(o.length===1)return Oa({inputs:{x:o[0]},backend:r});let l=o.map(f=>f.shape);if(C.assertParamsConsistent(l,s),o[0].dtype==="complex64"){let f=o.map(b=>zo({inputs:{input:b},backend:r})),g=o.map(b=>Du({inputs:{input:b},backend:r})),y=Lu({inputs:f,backend:r,attrs:{axis:s}}),A=Lu({inputs:g,backend:r,attrs:{axis:s}}),x=hn({inputs:{real:y,imag:A},backend:r});return f.forEach(b=>r.disposeIntermediateTensorInfo(b)),g.forEach(b=>r.disposeIntermediateTensorInfo(b)),r.disposeIntermediateTensorInfo(y),r.disposeIntermediateTensorInfo(A),x}let u=o.map(f=>{let g=v.sizeFromShape(f.shape.slice(s));return Ct({inputs:{x:f},backend:r,attrs:{shape:[-1,g]}})}),d=u.map(f=>({vals:r.data.get(f.dataId).values,shape:f.shape}));i=C.computeOutShape(u.map(f=>f.shape),1);let h=u[0].shape[0]===1,p=dA(d,i,t[0].dtype,h),c=C.computeOutShape(o.map(f=>f.shape),s),m=r.makeTensorInfo(c,t[0].dtype,p);return u.forEach(f=>r.disposeIntermediateTensorInfo(f)),m}var MK={kernelName:Ho,backendName:"cpu",kernelFunc:Lu};function u9(e){let{inputs:t,backend:r,attrs:n}=e,{x:a,filter:s}=t,{strides:i,pad:o,dataFormat:l,dilations:u,dimRoundingMode:d}=n;Ce([a,s],"conv2d");let h=C.convertConv2DDataFormat(l),p=C.computeConv2DInfo(a.shape,s.shape,i,u,o,d,!1,h),c=p.filterHeight,m=p.filterWidth,f=p.dilationHeight,g=p.dilationWidth,y=p.padInfo.left,A=p.padInfo.top,x=p.dataFormat==="channelsLast",b=new ir(p.outShape,a.dtype),w=v.computeStrides(a.shape),I=v.computeStrides(s.shape),T=w[0],E=x?w[1]:w[2],R=x?w[2]:1,O=x?1:w[1],M=b.strides[0],S=x?b.strides[1]:b.strides[2],P=x?b.strides[2]:1,z=x?1:b.strides[1],j=r.data.get(a.dataId).values,K=r.data.get(s.dataId).values,D=b.values;for(let Y=0;Y<p.batchSize;++Y){let V=Y*T,re=Y*M;for(let Q=0;Q<p.outHeight;++Q){let ie=re+Q*S,J=Q*p.strideHeight-A;for(let ae=0;ae<c;++ae){let de=J+ae*f;if(de<0||de>=p.inHeight)continue;let be=ae*I[0],ve=V+de*E;for(let Ee=0;Ee<p.outWidth;++Ee){let Me=ie+Ee*P,De=Ee*p.strideWidth-y;for(let We=0;We<m;++We){let Ke=De+We*g;if(Ke<0||Ke>=p.inWidth)continue;let ot=be+We*I[1],pt=ve+Ke*R,ht=ot;for(let Fe=0;Fe<p.inChannels;++Fe){let wt=j[pt+Fe*O];for(let At=0;At<p.outChannels;++At)D[Me+At*z]+=wt*K[ht+At];ht+=p.outChannels}}}}}}return r.makeTensorInfo(b.shape,b.dtype,D)}var $K={kernelName:ti,backendName:"cpu",kernelFunc:u9};function FK(e){let{inputs:t,backend:r,attrs:n}=e,{x:a,dy:s}=t,{strides:i,pad:o,dataFormat:l,dimRoundingMode:u,filterShape:d}=n;Ce([a,s],"conv2dBackpropFilter");let h=C.convertConv2DDataFormat(l),p=C.computeConv2DInfo(a.shape,d,i,1,o,u,!1,h),{strideHeight:c,strideWidth:m,filterHeight:f,filterWidth:g}=p,y=p.dataFormat==="channelsLast",A=new ir(p.filterShape,"float32"),x=p.padInfo.left,b=p.padInfo.top,w=r.data.get(a.dataId).values,I=r.data.get(s.dataId).values,T=new ir(a.shape,a.dtype,w),E=new ir(s.shape,s.dtype,I);for(let R=0;R<f;++R){let O=Math.max(0,Math.ceil((b-R)/c)),M=Math.min(p.outHeight,(p.inHeight+b-R)/c);for(let S=0;S<g;++S){let P=Math.max(0,Math.ceil((x-S)/m)),z=Math.min(p.outWidth,(p.inWidth+x-S)/m);for(let j=0;j<p.inChannels;++j)for(let K=0;K<p.outChannels;++K){let D=0;for(let Y=0;Y<p.batchSize;++Y)for(let V=O;V<M;++V){let re=R+V*c-b;for(let Q=P;Q<z;++Q){let ie=S+Q*m-x;y?D+=T.get(Y,re,ie,j)*E.get(Y,V,Q,K):D+=T.get(Y,j,re,ie)*E.get(Y,K,V,Q)}}A.set(D,R,S,j,K)}}}return r.makeTensorInfo(A.shape,A.dtype,A.values)}var _K={kernelName:hf,backendName:"cpu",kernelFunc:FK};function PK(e){let{inputs:t,backend:r,attrs:n}=e,{dy:a,filter:s}=t,{inputShape:i,strides:o,pad:l,dataFormat:u,dimRoundingMode:d}=n;Ce([a,s],"conv2dBackpropInput");let h=v.computeStrides(s.shape),p=v.computeStrides(a.shape),c=C.convertConv2DDataFormat(u),m=C.computeConv2DInfo(i,s.shape,o,1,l,d,!1,c),f=new ir(m.inShape,"float32"),g=f.values,y=r.data.get(a.dataId).values,A=r.data.get(s.dataId).values,[x,b,w]=h,{batchSize:I,filterHeight:T,filterWidth:E,inChannels:R,inHeight:O,inWidth:M,outChannels:S,outHeight:P,outWidth:z,strideHeight:j,strideWidth:K}=m;c=m.dataFormat;let D=T-1-m.padInfo.top,Y=E-1-m.padInfo.left,V=c==="channelsLast",re=f.strides[0],Q=V?f.strides[1]:f.strides[2],ie=V?f.strides[2]:1,J=V?1:f.strides[1],ae=p[0],de=V?p[1]:p[2],be=V?p[2]:1,ve=V?1:p[1];for(let Ee=0;Ee<I;++Ee)for(let Me=0;Me<R;++Me)for(let De=0;De<O;++De){let We=De-D,Ke=Math.max(0,Math.ceil(We/j)),ot=Math.min(P,(T+We)/j);for(let pt=0;pt<M;++pt){let ht=pt-Y,Fe=Math.max(0,Math.ceil(ht/K)),wt=Math.min(z,(E+ht)/K),At=0;for(let hr=Ke;hr<ot;++hr){let Qr=hr*j-We;for(let rr=Fe;rr<wt;++rr){let cr=rr*K-ht,ta=ae*Ee+de*hr+be*rr,en=x*(T-1-Qr)+b*(E-1-cr)+w*Me;for(let nr=0;nr<S;++nr){let kn=y[ta+ve*nr],In=A[en+nr];At+=kn*In}}}let _r=re*Ee+Q*De+ie*pt+J*Me;g[_r]=At}}return r.makeTensorInfo(f.shape,f.dtype,f.values)}var OK={kernelName:ri,backendName:"cpu",kernelFunc:PK};function zK(e){let{inputs:t,backend:r,attrs:n}=e,{x:a,filter:s}=t,{strides:i,pad:o,dilations:l}=n;Ce([a,s],"conv3d");let u=C.computeConv3DInfo(a.shape,s.shape,i,l,o),{filterDepth:d,filterHeight:h,filterWidth:p,dilationDepth:c,dilationHeight:m,dilationWidth:f,padInfo:g}=u,y=g.front,A=g.left,x=g.top,b=new ir(u.outShape,a.dtype),w=r.data.get(a.dataId).values,I=r.data.get(s.dataId).values,T=b.values,E=v.computeStrides(a.shape),R=v.computeStrides(s.shape);for(let O=0;O<u.batchSize;++O){let M=O*E[0],S=O*b.strides[0];for(let P=0;P<u.outDepth;++P){let z=S+P*b.strides[1],j=P*u.strideDepth-y;for(let K=0;K<d;++K){let D=j+K*c;if(D<0||D>=u.inDepth)continue;let Y=K*R[0],V=M+D*E[1];for(let re=0;re<u.outHeight;++re){let Q=z+re*b.strides[2],ie=re*u.strideHeight-x;for(let J=0;J<h;++J){let ae=ie+J*m;if(ae<0||ae>=u.inHeight)continue;let de=Y+J*R[1],be=V+ae*E[2];for(let ve=0;ve<u.outWidth;++ve){let Ee=Q+ve*u.outChannels,Me=ve*u.strideWidth-A;for(let De=0;De<p;++De){let We=Me+De*f;if(We<0||We>=u.inWidth)continue;let Ke=de+De*R[2],ot=be+We*u.inChannels,pt=Ke;for(let ht=0;ht<u.inChannels;++ht){let Fe=w[ot+ht];for(let wt=0;wt<u.outChannels;++wt)T[Ee+wt]+=Fe*I[pt+wt];pt+=u.outChannels}}}}}}}}return r.makeTensorInfo(b.shape,b.dtype,b.values)}var DK={kernelName:ih,backendName:"cpu",kernelFunc:zK};function LK(e){let{inputs:t,backend:r,attrs:n}=e,{x:a,dy:s}=t,{strides:i,pad:o,filterShape:l}=n;Ce([a,s],"conv3dBackpropFilterV2");let u=v.computeStrides(a.shape),d=v.computeStrides(s.shape),h=C.computeConv3DInfo(a.shape,l,i,1,o),p=h.strideDepth,c=h.strideHeight,m=h.strideWidth,f=h.filterDepth,g=h.filterHeight,y=h.filterWidth,A=new ir(h.filterShape,"float32"),x=A.values,[b,w,I,T]=A.strides,E=r.data.get(s.dataId).values,[R,O,M,S]=d,P=r.data.get(a.dataId).values,[z,j,K,D]=u,Y=h.padInfo.front,V=h.padInfo.left,re=h.padInfo.top;for(let Q=0;Q<f;++Q){let ie=Math.max(0,Math.ceil((Y-Q)/p)),J=Math.min(h.outDepth,(h.inDepth+Y-Q)/p),ae=Q*b;for(let de=0;de<g;++de){let be=Math.max(0,Math.ceil((re-de)/c)),ve=Math.min(h.outHeight,(h.inHeight+re-de)/c),Ee=de*w+ae;for(let Me=0;Me<y;++Me){let De=Math.max(0,Math.ceil((V-Me)/m)),We=Math.min(h.outWidth,(h.inWidth+V-Me)/m),Ke=Me*I+Ee;for(let ot=0;ot<h.inChannels;++ot){let pt=ot*T+Ke;for(let ht=0;ht<h.outChannels;++ht){let Fe=0;for(let wt=0;wt<h.batchSize;++wt){let At=wt*z,_r=wt*R;for(let hr=ie;hr<J;++hr){let Qr=(Q+hr*p-Y)*j+At,rr=hr*O+_r;for(let cr=be;cr<ve;++cr){let ta=(de+cr*c-re)*K+Qr,en=cr*M+rr;for(let nr=De;nr<We;++nr){let kn=(Me+nr*m-V)*D+ta,In=nr*S+en;Fe+=P[kn+ot]*E[In+ht]}}}}x[pt+ht]=Fe}}}}}return r.makeTensorInfo(A.shape,A.dtype,A.values)}var BK={kernelName:cf,backendName:"cpu",kernelFunc:LK};function WK(e){let{inputs:t,backend:r,attrs:n}=e,{dy:a,filter:s}=t,{pad:i,strides:o,inputShape:l}=n;Ce([a],"conv3dBackpropInputV2");let u=v.computeStrides(a.shape),d=v.computeStrides(s.shape),h=C.computeConv3DInfo(l,s.shape,o,1,i),p=new ir(h.inShape,"float32"),c=p.values,[m,f,g,y]=p.strides,A=r.data.get(a.dataId).values,[x,b,w,I]=u,T=r.data.get(s.dataId).values,[E,R,O,M]=d,{batchSize:S,filterDepth:P,filterHeight:z,filterWidth:j,inChannels:K,inDepth:D,inHeight:Y,inWidth:V,outChannels:re,outDepth:Q,outHeight:ie,outWidth:J,strideDepth:ae,strideHeight:de,strideWidth:be}=h,ve=P-1-h.padInfo.front,Ee=z-1-h.padInfo.top,Me=j-1-h.padInfo.left;for(let De=0;De<S;++De)for(let We=0;We<K;++We)for(let Ke=0;Ke<D;++Ke){let ot=Ke-ve,pt=Math.max(0,Math.ceil(ot/ae)),ht=Math.min(Q,(P+ot)/ae);for(let Fe=0;Fe<Y;++Fe){let wt=Fe-Ee,At=Math.max(0,Math.ceil(wt/de)),_r=Math.min(ie,(z+wt)/de);for(let hr=0;hr<V;++hr){let Qr=hr-Me,rr=Math.max(0,Math.ceil(Qr/be)),cr=Math.min(J,(j+Qr)/be),ta=0;for(let en=pt;en<ht;++en){let nr=en*ae-ot;for(let kn=At;kn<_r;++kn){let In=kn*de-wt;for(let gs=rr;gs<cr;++gs){let oo=gs*be-Qr,gc=x*De+b*en+w*kn+I*gs,ys=E*(P-1-nr)+R*(z-1-In)+O*(j-1-oo)+M*We;for(let Ua=0;Ua<re;++Ua){let lp=A[gc+Ua],Jl=T[ys+Ua];ta+=lp*Jl}}}}c[m*De+f*Ke+g*Fe+y*hr+We]=ta}}}return r.makeTensorInfo(p.shape,p.dtype,p.values)}var VK={kernelName:ff,backendName:"cpu",kernelFunc:WK},UK=gt(ni,e=>Math.cos(e)),GK={kernelName:ni,backendName:"cpu",kernelFunc:UK},jK=gt(ai,e=>Math.cosh(e)),HK={kernelName:ai,backendName:"cpu",kernelFunc:jK};function qK(e){let{inputs:t,backend:r,attrs:n}=e,{image:a,boxes:s,boxInd:i}=t,{cropSize:o,method:l,extrapolationValue:u}=n,[d,h,p,c]=a.shape,m=s.shape[0],[f,g]=o,y=Le([m,f,g,c],"float32"),A=r.data.get(s.dataId).values,x=r.data.get(i.dataId).values,b=r.data.get(a.dataId).values,w=v.computeStrides(a.shape),I=v.computeStrides(y.shape);for(let T=0;T<m;T++){let E=T*4,R=A[E],O=A[E+1],M=A[E+2],S=A[E+3],P=x[T];if(P>=d)continue;let z=f>1?(M-R)*(h-1)/(f-1):0,j=g>1?(S-O)*(p-1)/(g-1):0;for(let K=0;K<f;K++){let D=f>1?R*(h-1)+K*z:.5*(R+M)*(h-1);if(D<0||D>h-1){for(let Y=0;Y<g;Y++)for(let V=0;V<c;V++){let re=V+Y*I[2]+K*I[1]+T*I[0];y.values[re]=u}continue}if(l==="bilinear"){let Y=Math.floor(D),V=Math.ceil(D),re=D-Y;for(let Q=0;Q<g;Q++){let ie=g>1?O*(p-1)+Q*j:.5*(O+S)*(p-1);if(ie<0||ie>p-1){for(let be=0;be<c;be++){let ve=be+Q*I[2]+K*I[1]+T*I[0];y.values[ve]=u}continue}let J=Math.floor(ie),ae=Math.ceil(ie),de=ie-J;for(let be=0;be<c;be++){let ve=be+J*w[2]+Y*w[1]+P*w[0],Ee=b[ve];ve=be+ae*w[2]+Y*w[1]+P*w[0];let Me=b[ve];ve=be+J*w[2]+V*w[1]+P*w[0];let De=b[ve];ve=be+ae*w[2]+V*w[1]+P*w[0];let We=b[ve],Ke=Ee+(Me-Ee)*de,ot=De+(We-De)*de;ve=be+Q*I[2]+K*I[1]+T*I[0],y.values[ve]=Ke+(ot-Ke)*re}}}else for(let Y=0;Y<g;++Y){let V=g>1?O*(p-1)+Y*j:.5*(O+S)*(p-1);if(V<0||V>p-1){for(let ie=0;ie<c;ie++){let J=ie+Y*I[2]+K*I[1]+T*I[0];y.values[J]=u}continue}let re=Math.round(V),Q=Math.round(D);for(let ie=0;ie<c;ie++){let J=ie+re*w[2]+Q*w[1]+P*w[0],ae=ie+Y*I[2]+K*I[1]+T*I[0];y.values[ae]=b[J]}}}}return r.makeTensorInfo(y.shape,y.dtype,y.values)}var XK={kernelName:Xo,backendName:"cpu",kernelFunc:qK};function KK(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{axis:s,exclusive:i,reverse:o}=n;Ce(a,"cumprod");let l=C.getAxesPermutation([s],a.shape.length),u=a;l!=null&&(u=on({inputs:{x:a},backend:r,attrs:{perm:l}}));let d=C.getInnerMostAxes(1,a.shape.length)[0];if(d!==u.shape.length-1)throw new Error(`backend.cumprod in CPU expects an inner-most axis=${u.shape.length-1} but got axis=${d}`);let h=Tr(u.dtype,"int32"),p=v.makeOnesTypedArray(v.sizeFromShape(u.shape),h),c=r.data.get(u.dataId).values,m=u.shape[u.shape.length-1],f=o?(y,A)=>y+m-A-1:(y,A)=>y+A;for(let y=0;y<c.length;y+=m)for(let A=0;A<m;A++){let x=f(y,A);if(A===0)p[x]=i?1:c[x];else{let b=f(y,A-1);p[x]=i?c[b]*p[b]:c[x]*p[b]}}let g=r.makeTensorInfo(u.shape,h,p);if(l!=null){let y=C.getUndoAxesPermutation(l),A=on({inputs:{x:g},backend:r,attrs:{perm:y}});return r.disposeIntermediateTensorInfo(g),r.disposeIntermediateTensorInfo(u),A}return g}var ZK={kernelName:qo,backendName:"cpu",kernelFunc:KK};function YK(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{axis:s,exclusive:i,reverse:o}=n;Ce(a,"cumsum");let l=C.getAxesPermutation([s],a.shape.length),u=a;l!=null&&(u=on({inputs:{x:a},backend:r,attrs:{perm:l}}));let d=C.getInnerMostAxes(1,a.shape.length)[0];if(d!==u.shape.length-1)throw new Error(`backend.cumsum in CPU expects an inner-most axis=${u.shape.length-1} but got axis=${d}`);let h=Tr(u.dtype,"int32"),p=v.makeZerosTypedArray(v.sizeFromShape(u.shape),h),c=r.data.get(u.dataId).values,m=u.shape[u.shape.length-1],f=o?(y,A)=>y+m-A-1:(y,A)=>y+A;for(let y=0;y<c.length;y+=m)for(let A=0;A<m;A++){let x=f(y,A);if(A===0)p[x]=i?0:c[x];else{let b=f(y,A-1);p[x]=i?c[b]+p[b]:c[x]+p[b]}}let g=r.makeTensorInfo(u.shape,h,p);if(l!=null){let y=C.getUndoAxesPermutation(l),A=on({inputs:{x:g},backend:r,attrs:{perm:y}});return r.disposeIntermediateTensorInfo(g),r.disposeIntermediateTensorInfo(u),A}return g}var JK={kernelName:si,backendName:"cpu",kernelFunc:YK};function QK(e){let{inputs:t,backend:r,attrs:n}=e,{x:a,weights:s}=t,{size:i,binaryOutput:o}=n;if(a.shape.length===1){let l=r.data.get(a.dataId).values,u=r.data.get(s.dataId).values,d=uA(l,u,s.dtype,s.shape,i);return r.makeTensorInfo([i],s.dtype,d)}else if(a.shape.length===2){let l=r.bufferSync(a),u=r.bufferSync(s),d=xk(l,u,i,o);return r.makeTensorInfo(d.shape,s.dtype,d.values)}throw new Error(`Error in denseBincount: input must be at most rank 2, but got rank${a.shape.length}.`)}var eZ={kernelName:mf,backendName:"cpu",kernelFunc:QK};function tZ(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{blockSize:s,dataFormat:i}=n;v.assert(i==="NHWC",()=>`Only NHWC dataFormat supported on CPU for depthToSpace. Got ${i}`);let o=a.shape[0],l=a.shape[1],u=a.shape[2],d=a.shape[3],h=l*s,p=u*s,c=d/(s*s),m=r.data.get(a.dataId).values,f=new Float32Array(o*h*p*c),g=0;for(let y=0;y<o;++y)for(let A=0;A<h;++A){let x=Math.floor(A/s),b=A%s;for(let w=0;w<p;++w){let I=Math.floor(w/s),T=w%s,E=(b*s+T)*c;for(let R=0;R<c;++R){let O=R+E+d*(I+u*(x+l*y));f[g++]=m[O]}}}return r.makeTensorInfo([o,h,p,c],a.dtype,f)}var rZ={kernelName:Ko,backendName:"cpu",kernelFunc:tZ};function d9(e){let{inputs:t,backend:r,attrs:n}=e,{x:a,filter:s}=t,{strides:i,pad:o,dilations:l,dimRoundingMode:u}=n;Ce([a,s],"depthwiseConv2DNative");let d=v.computeStrides(a.shape),h=v.computeStrides(s.shape),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(a.shape,s.shape,i,p,o,u,!0),{filterHeight:m,filterWidth:f,dilationHeight:g,dilationWidth:y,padInfo:A}=c,x=A.left,b=A.top,w=c.outChannels/c.inChannels,I=new ir(c.outShape,a.dtype),T=r.data.get(a.dataId).values,E=r.data.get(s.dataId).values,R=I.values;for(let O=0;O<c.batchSize;++O){let M=O*d[0],S=O*I.strides[0];for(let P=0;P<c.outHeight;++P){let z=S+P*I.strides[1],j=P*c.strideHeight-b;for(let K=0;K<m;++K){let D=j+K*g;if(D<0||D>=c.inHeight)continue;let Y=K*h[0],V=M+D*d[1];for(let re=0;re<c.outWidth;++re){let Q=z+re*I.strides[2],ie=re*c.strideWidth-x;for(let J=0;J<f;++J){let ae=ie+J*y;if(ae<0||ae>=c.inWidth)continue;let de=Y+J*h[1],be=V+ae*c.inChannels,ve=Q,Ee=de;for(let Me=0;Me<c.inChannels;++Me){let De=T[be+Me];for(let We=0;We<w;++We)R[ve+We]+=De*E[Ee+We];ve+=w,Ee+=w}}}}}}return r.makeTensorInfo(I.shape,I.dtype,I.values)}var nZ={kernelName:ii,backendName:"cpu",kernelFunc:d9};function aZ(e){let{inputs:t,backend:r,attrs:n}=e,{x:a,dy:s}=t,{strides:i,dilations:o,pad:l,dimRoundingMode:u,filterShape:d}=n;Ce([a,s],"depthwiseConv2dNativeBackpropFilter");let h=C.computeConv2DInfo(a.shape,d,i,o,l,u,!0),{strideHeight:p,strideWidth:c,filterHeight:m,filterWidth:f}=h,g=new ir(h.filterShape,"float32"),y=h.padInfo.left,A=h.padInfo.top,x=h.outChannels/h.inChannels,b=r.data.get(a.dataId).values,w=new ir(a.shape,a.dtype,b),I=r.data.get(s.dataId).values,T=new ir(s.shape,s.dtype,I);for(let E=0;E<m;++E){let R=Math.max(0,Math.ceil((A-E)/p)),O=Math.min(h.outHeight,(h.inHeight+A-E)/p);for(let M=0;M<f;++M){let S=Math.max(0,Math.ceil((y-M)/c)),P=Math.min(h.outWidth,(h.inWidth+y-M)/c);for(let z=0;z<h.outChannels;++z){let j=Math.trunc(z/x),K=z%x,D=0;for(let Y=0;Y<h.batchSize;++Y)for(let V=R;V<O;++V){let re=E+V*p-A;for(let Q=S;Q<P;++Q){let ie=M+Q*c-y;D+=w.get(Y,re,ie,j)*T.get(Y,V,Q,z)}}g.set(D,E,M,j,K)}}}return r.makeTensorInfo(g.shape,g.dtype,g.values)}var 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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",r="varying",n="varying",a="texture2D",s="gl_FragColor",i="",o=`
#define isnan(value) isnan_custom(value)
bool isnan_custom(float val) {
return (val > 0. || val < 1. || val == 0.) ? false : true;
}
bvec4 isnan_custom(vec4 val) {
return bvec4(isnan(val.x), isnan(val.y), isnan(val.z), isnan(val.w));
}
`,l=`
uniform float INFINITY;
bool isinf(float val) {
return abs(val) == INFINITY;
}
bvec4 isinf(vec4 val) {
return equal(abs(val), vec4(INFINITY));
}
`,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:r,varyingFs:n,texture2D:a,output:s,defineOutput:i,defineSpecialNaN:o,defineSpecialInf:l,defineRound:u}}function zl(e,t,r="index"){let n=v.computeStrides(t);return n.map((a,s)=>{let i=`int ${e[s]} = ${r} / ${a}`,o=s===n.length-1?`int ${e[s+1]} = ${r} - ${e[s]} * ${a}`:`index -= ${e[s]} * ${a}`;return`${i}; ${o};`}).join("")}function Fm(e,t,r="index"){let n=v.computeStrides(t);return n.map((a,s)=>{let i=`int ${e[s]} = ${r} / outShapeStrides[${s}]`,o=s===n.length-1?`int ${e[s+1]} = ${r} - ${e[s]} * outShapeStrides[${s}]`:`index -= ${e[s]} * outShapeStrides[${s}]`;return`${i}; ${o};`}).join("")}function JQ(e,t){let r=e.length,n=e.map(s=>`${t}[${s}]`),a=new Array(r-1);a[r-2]=n[r-1];for(let s=r-3;s>=0;--s)a[s]=`(${a[s+1]} * ${n[s+1]})`;return a}function QQ(e,t,r="index"){let n=e.map((s,i)=>i),a=JQ(n,t);return a.map((s,i)=>{let o=`int ${e[i]} = ${r} / ${a[i]}`,l=i===a.length-1?`int ${e[i+1]} = ${r} - ${e[i]} * ${a[i]}`:`index -= ${e[i]} * ${a[i]}`;return`${o}; ${l};`}).join("")}function vA(e){let t=v.computeStrides(e).map(r=>r.toString());return`
int getFlatIndex(ivec3 coords) {
return coords.x * ${t[0]} + coords.y * ${t[1]} + coords.z;
}
`}function wA(){return`
int getFlatIndex(ivec3 coords) {
return coords.x * outShapeStrides[0] + coords.y * outShapeStrides[1] + coords.z;
}
`}var V9=`
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:U9}=C;function eee(e,t,r){let n=[];if(e.forEach(p=>{let c=v.sizeFromShape(p.shapeInfo.logicalShape);if(p.shapeInfo.isUniform?n.push(`uniform float ${p.name}${c>1?`[${c}]`:""};`):(n.push(`uniform sampler2D ${p.name};`),n.push(`uniform int offset${p.name};`)),r.enableShapeUniforms){let{uniformShape:m}=kA(r.packedInputs,p.shapeInfo.logicalShape,p.shapeInfo.texShape);switch(m.length){case 1:n.push(`uniform int ${p.name}Shape;`);break;case 2:n.push(`uniform ivec2 ${p.name}Shape;`);break;case 3:n.push(`uniform ivec3 ${p.name}Shape;`);break;case 4:n.push(`uniform ivec4 ${p.name}Shape;`);break;default:break}n.push(`uniform ivec2 ${p.name}TexShape;`)}}),r.enableShapeUniforms){switch(t.logicalShape.length){case 1:n.push("uniform int outShape;");break;case 2:n.push("uniform ivec2 outShape;"),n.push("uniform int outShapeStrides;");break;case 3:n.push("uniform ivec3 outShape;"),n.push("uniform ivec2 outShapeStrides;");break;case 4:n.push("uniform ivec4 outShape;"),n.push("uniform ivec3 outShapeStrides;");break;default:break}n.push("uniform ivec2 outTexShape;")}r.customUniforms&&r.customUniforms.forEach(p=>{n.push(`uniform ${p.type} ${p.name}${p.arrayIndex?`[${p.arrayIndex}]`:""};`)});let a=n.join(`
`),s=e.map(p=>tee(p,t,r.packedInputs,r.enableShapeUniforms)).join(`
`),i=t.texShape,o=qr(),l=aee(o),u,d,h=oee(o);return t.isPacked?(u=ree(t.logicalShape,i,r.enableShapeUniforms),d=iee(o)):(u=nee(t.logicalShape,i,r.enableShapeUniforms),d=see(o)),r.packedInputs&&(h+=pee),[h,l,d,a,u,s,r.userCode].join(`
`)}function Rd(e,t=!1){let r=e.shapeInfo.logicalShape;switch(r.length){case 0:return kee(e,t);case 1:return See(e,t);case 2:return Tee(e,t);case 3:return Eee(e,t);case 4:return Mee(e,t);case 5:return $ee(e);case 6:return Fee(e);default:throw new Error(`${r.length}-D input sampling is not yet supported`)}}function G9(e,t){switch(e.shapeInfo.logicalShape.length){case 0:return wee(e);case 1:return Iee(e,t);case 2:return Cee(e,t);case 3:return Nee(e,t);default:return Ree(e,t)}}function tee(e,t,r=!1,n){let a="";r?a+=G9(e,n):a+=Rd(e,n);let s=e.shapeInfo.logicalShape,i=t.logicalShape;return s.length<=i.length&&(r?a+=_ee(e,t):a+=Pee(e,t)),a}function ree(e,t,r){switch(e.length){case 0:return j9();case 1:return hee(e,t,r);case 2:return bee(e,t,r);case 3:return fee(e,t,r);default:return gee(e,t,r)}}function nee(e,t,r){switch(e.length){case 0:return j9();case 1:return cee(e,t,r);case 2:return vee(e,t,r);case 3:return mee(e,t,r);case 4:return yee(e,t,r);case 5:return Aee(e,t);case 6:return xee(e,t);default:throw new Error(`${e.length}-D output sampling is not yet supported`)}}function aee(e){return`
float sampleTexture(sampler2D textureSampler, vec2 uv) {
return ${e.texture2D}(textureSampler, uv).r;
}
`}function see(e){return`
void setOutput(float val) {
${e.output} = vec4(val, 0, 0, 0);
}
`}function iee(e){return`
void setOutput(vec4 val) {
${e.output} = val;
}
`}function oee(e){return`${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);
}
${lee}
${uee}
${dee}
`}var lee=`
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);
}
`,uee=`
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);
}
`,dee=`
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);
}
`,pee=`
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 j9(){return`
int getOutputCoords() {
return 0;
}
`}function hee(e,t,r){let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)];return n[0]===1?r?`
int getOutputCoords() {
return 2 * int(resultUV.x * ceil(float(outTexShape[1]) / 2.0));
}
`:`
int getOutputCoords() {
return 2 * int(resultUV.x * ${n[1]}.0);
}
`:n[1]===1?r?`
int getOutputCoords() {
return 2 * int(resultUV.y * ceil(float(outTexShape[0]) / 2.0));
}
`:`
int getOutputCoords() {
return 2 * int(resultUV.y * ${n[0]}.0);
}
`:r?`
int getOutputCoords() {
ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(packedTexShape[0], packedTexShape[1]));
return 2 * (resTexRC.x * packedTexShape[1] + resTexRC.y);
}
`:`
int getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${n[0]}, ${n[1]}));
return 2 * (resTexRC.x * ${n[1]} + resTexRC.y);
}
`}function cee(e,t,r){return t[0]===1?r?`
int getOutputCoords() {
return int(resultUV.x * float(outTexShape[1]));
}
`:`
int getOutputCoords() {
return int(resultUV.x * ${t[1]}.0);
}
`:t[1]===1?r?`
int getOutputCoords() {
return int(resultUV.y * float(outTexShape[0]));
}
`:`
int getOutputCoords() {
return int(resultUV.y * ${t[0]}.0);
}
`:r?`
int getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(outTexShape[0], outTexShape[1]));
return resTexRC.x * outTexShape[1] + resTexRC.y;
}
`:`
int getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${t[0]}, ${t[1]}));
return resTexRC.x * ${t[1]} + resTexRC.y;
}
`}function fee(e,t,r){if(r)return`
ivec3 getOutputCoords() {
ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));
int texelsInLogicalRow = int(ceil(float(outShape[2]) / 2.0));
int texelsInBatch = texelsInLogicalRow * int(ceil(float(outShape[1]) / 2.0));
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(packedTexShape[0], packedTexShape[1]));
int index = resTexRC.x * packedTexShape[1] + resTexRC.y;
int b = index / texelsInBatch;
index -= b * texelsInBatch;
int r = 2 * (index / texelsInLogicalRow);
int c = imod(index, texelsInLogicalRow) * 2;
return ivec3(b, r, c);
}
`;let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)],a=Math.ceil(e[2]/2),s=a*Math.ceil(e[1]/2);return`
ivec3 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${n[0]}, ${n[1]}));
int index = resTexRC.x * ${n[1]} + resTexRC.y;
int b = index / ${s};
index -= b * ${s};
int r = 2 * (index / ${a});
int c = imod(index, ${a}) * 2;
return ivec3(b, r, c);
}
`}function mee(e,t,r){if(r)return`
ivec3 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(outTexShape[0], outTexShape[1]));
int index = resTexRC.x * outTexShape[1] + resTexRC.y;
${Fm(["r","c","d"],e)}
return ivec3(r, c, d);
}
`;let n=zl(["r","c","d"],e);return`
ivec3 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${t[0]}, ${t[1]}));
int index = resTexRC.x * ${t[1]} + resTexRC.y;
${n}
return ivec3(r, c, d);
}
`}function gee(e,t,r){if(r)return`
ivec4 getOutputCoords() {
ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(packedTexShape[0], packedTexShape[1]));
int index = resTexRC.x * packedTexShape[1] + resTexRC.y;
int texelsInLogicalRow = int(ceil(float(outShape[3]) / 2.0));
int texelsInBatch = texelsInLogicalRow * int(ceil(float(outShape[2]) / 2.0));
int texelsInBatchN = texelsInBatch * outShape[1];
int b2 = index / texelsInBatchN;
index -= b2 * texelsInBatchN;
int b = index / texelsInBatch;
index -= b * texelsInBatch;
int r = 2 * (index / texelsInLogicalRow);
int c = imod(index, texelsInLogicalRow) * 2;
return ivec4(b2, b, r, c);
}
`;let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)],a=Math.ceil(e[e.length-1]/2),s=a*Math.ceil(e[e.length-2]/2),i=s,o="",l="b, r, c";for(let u=2;u<e.length-1;u++)i*=e[e.length-u-1],o=`
int b${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 / ${a});
int c = imod(index, ${a}) * 2;
return ivec${e.length}(${l});
}
`}function yee(e,t,r){if(r)return`
ivec4 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(outTexShape[0], outTexShape[1]));
int index = resTexRC.x * outTexShape[1] + resTexRC.y;
${Fm(["r","c","d","d2"],e)}
return ivec4(r, c, d, d2);
}
`;let n=zl(["r","c","d","d2"],e);return`
ivec4 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${t[0]}, ${t[1]}));
int index = resTexRC.x * ${t[1]} + resTexRC.y;
${n}
return ivec4(r, c, d, d2);
}
`}function Aee(e,t){let r=zl(["r","c","d","d2","d3"],e);return`
ivec5 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx * vec2(${t[0]},
${t[1]}));
int index = resTexRC.x * ${t[1]} + resTexRC.y;
${r}
ivec5 outShape = ivec5(r, c, d, d2, d3);
return outShape;
}
`}function xee(e,t){let r=zl(["r","c","d","d2","d3","d4"],e);return`
ivec6 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${t[0]}, ${t[1]}));
int index = resTexRC.x * ${t[1]} + resTexRC.y;
${r}
ivec6 result = ivec6(r, c, d, d2, d3, d4);
return result;
}
`}function bee(e,t,r){let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)];if(v.arraysEqual(e,t))return r?`
ivec2 getOutputCoords() {
ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));
return 2 * ivec2(resultUV.yx * vec2(packedTexShape[0], packedTexShape[1]));
}
`:`
ivec2 getOutputCoords() {
return 2 * ivec2(resultUV.yx * vec2(${n[0]}, ${n[1]}));
}
`;let a=Math.ceil(e[1]/2);return r?`
ivec2 getOutputCoords() {
ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));
int texelsInLogicalRow = int(ceil(float(outShape[1]) / 2.0));
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(packedTexShape[0], packedTexShape[1]));
int index = resTexRC.x * packedTexShape[1] + resTexRC.y;
int r = 2 * (index / texelsInLogicalRow);
int c = imod(index, texelsInLogicalRow) * 2;
return ivec2(r, c);
}
`:`
ivec2 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${n[0]}, ${n[1]}));
int index = resTexRC.x * ${n[1]} + resTexRC.y;
int r = 2 * (index / ${a});
int c = imod(index, ${a}) * 2;
return ivec2(r, c);
}
`}function vee(e,t,r){return v.arraysEqual(e,t)?r?`
ivec2 getOutputCoords() {
return ivec2(resultUV.yx * vec2(outTexShape[0], outTexShape[1]));
}
`:`
ivec2 getOutputCoords() {
return ivec2(resultUV.yx * vec2(${t[0]}, ${t[1]}));
}
`:e[1]===1?r?`
ivec2 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(outTexShape[0], outTexShape[1]));
int index = resTexRC.x * outTexShape[1] + resTexRC.y;
return ivec2(index, 0);
}
`:`
ivec2 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${t[0]}, ${t[1]}));
int index = resTexRC.x * ${t[1]} + resTexRC.y;
return ivec2(index, 0);
}
`:e[0]===1?r?`
ivec2 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(outTexShape[0], outTexShape[1]));
int index = resTexRC.x * outTexShape[1] + resTexRC.y;
return ivec2(0, index);
}
`:`
ivec2 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${t[0]}, ${t[1]}));
int index = resTexRC.x * ${t[1]} + resTexRC.y;
return ivec2(0, index);
}
`:r?`
ivec2 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(outTexShape[0], outTexShape[1]));
int index = resTexRC.x * outTexShape[1] + resTexRC.y;
int r = index / outShape[1];
int c = index - r * outShape[1];
return ivec2(r, c);
}
`:`
ivec2 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${t[0]}, ${t[1]}));
int index = resTexRC.x * ${t[1]} + resTexRC.y;
int r = index / ${e[1]};
int c = index - r * ${e[1]};
return ivec2(r, c);
}
`}function Dl(e){return`offset${e}`}function wee(e){let t=e.name,r="get"+t.charAt(0).toUpperCase()+t.slice(1),n=qr();return`
vec4 ${r}() {
return ${n.texture2D}(${t}, halfCR);
}
`}function kee(e,t){let r=e.name,n="get"+r.charAt(0).toUpperCase()+r.slice(1);if(e.shapeInfo.isUniform)return`float ${n}() {return ${r};}`;let[a,s]=e.shapeInfo.texShape;if(a===1&&s===1)return`
float ${n}() {
return sampleTexture(${r}, halfCR);
}
`;let i=Dl(r);if(t)return`
float ${n}() {
vec2 uv = uvFromFlat(${r}TexShape[0], ${r}TexShape[1], ${i});
return sampleTexture(${r}, uv);
}
`;let[o,l]=e.shapeInfo.texShape;return`
float ${n}() {
vec2 uv = uvFromFlat(${o}, ${l}, ${i});
return sampleTexture(${r}, uv);
}
`}function Iee(e,t){let r=e.name,n="get"+r.charAt(0).toUpperCase()+r.slice(1),a=e.shapeInfo.texShape,s=qr();if(t)return`
vec4 ${n}(int index) {
ivec2 packedTexShape = ivec2(ceil(float(${r}TexShape[0]) / 2.0), ceil(float(${r}TexShape[1]) / 2.0));
vec2 uv = packedUVfrom1D(
packedTexShape[0], packedTexShape[1], index);
return ${s.texture2D}(${r}, uv);
}
`;let i=[Math.ceil(a[0]/2),Math.ceil(a[1]/2)];return`
vec4 ${n}(int index) {
vec2 uv = packedUVfrom1D(
${i[0]}, ${i[1]}, index);
return ${s.texture2D}(${r}, uv);
}
`}function See(e,t){let r=e.name,n="get"+r.charAt(0).toUpperCase()+r.slice(1);if(e.shapeInfo.isUniform)return`
float ${n}(int index) {
${Md(e)}
}
`;let a=e.shapeInfo.texShape,s=a[0],i=a[1];if(i===1&&s===1)return`
float ${n}(int index) {
return sampleTexture(${r}, halfCR);
}
`;let o=Dl(r);return i===1?t?`
float ${n}(int index) {
vec2 uv = vec2(0.5, (float(index + ${o}) + 0.5) / float(${r}TexShape[0]));
return sampleTexture(${r}, uv);
}
`:`
float ${n}(int index) {
vec2 uv = vec2(0.5, (float(index + ${o}) + 0.5) / ${s}.0);
return sampleTexture(${r}, uv);
}
`:s===1?t?`
float ${n}(int index) {
vec2 uv = vec2((float(index + ${o}) + 0.5) / float(${r}TexShape[1]), 0.5);
return sampleTexture(${r}, uv);
}
`:`
float ${n}(int index) {
vec2 uv = vec2((float(index + ${o}) + 0.5) / ${i}.0, 0.5);
return sampleTexture(${r}, uv);
}
`:t?`
float ${n}(int index) {
vec2 uv = uvFromFlat(${r}TexShape[0], ${r}TexShape[1], index + ${o});
return sampleTexture(${r}, uv);
}
`:`
float ${n}(int index) {
vec2 uv = uvFromFlat(${s}, ${i}, index + ${o});
return sampleTexture(${r}, uv);
}
`}function Cee(e,t){let r=e.shapeInfo.logicalShape,n=e.name,a="get"+n.charAt(0).toUpperCase()+n.slice(1),s=e.shapeInfo.texShape,i=s[0],o=s[1],l=qr();if(s!=null&&v.arraysEqual(r,s))return t?`
vec4 ${a}(int row, int col) {
vec2 uv = (vec2(col, row) + halfCR) / vec2(${n}TexShape[1], ${n}TexShape[0]);
return ${l.texture2D}(${n}, uv);
}
`:`
vec4 ${a}(int row, int col) {
vec2 uv = (vec2(col, row) + halfCR) / vec2(${o}.0, ${i}.0);
return ${l.texture2D}(${n}, uv);
}
`;if(t)return`
vec4 ${a}(int row, int col) {
ivec2 packedTexShape = ivec2(ceil(float(${n}TexShape[0]) / 2.0), ceil(float(${n}TexShape[1]) / 2.0));
int valuesPerRow = int(ceil(float(${n}Shape[1]) / 2.0));
vec2 uv = packedUVfrom2D(valuesPerRow, packedTexShape[0], packedTexShape[1], row, col);
return ${l.texture2D}(${n}, uv);
}
`;let u=[Math.ceil(s[0]/2),Math.ceil(s[1]/2)],d=Math.ceil(r[1]/2);return`
vec4 ${a}(int row, int col) {
vec2 uv = packedUVfrom2D(${d}, ${u[0]}, ${u[1]}, row, col);
return ${l.texture2D}(${n}, uv);
}
`}function Tee(e,t){let r=e.shapeInfo.logicalShape,n=e.name,a="get"+n.charAt(0).toUpperCase()+n.slice(1),s=e.shapeInfo.texShape;if(s!=null&&v.arraysEqual(r,s)){if(t)return`
float ${a}(int row, int col) {
vec2 uv = (vec2(col, row) + halfCR) / vec2(${n}TexShape[1], ${n}TexShape[0]);
return sampleTexture(${n}, uv);
}
`;let p=s[0],c=s[1];return`
float ${a}(int row, int col) {
vec2 uv = (vec2(col, row) + halfCR) / vec2(${c}.0, ${p}.0);
return sampleTexture(${n}, uv);
}
`}let{newShape:i,keptDims:o}=v.squeezeShape(r),l=i;if(l.length<r.length){let p=$d(e,l),c=["row","col"];return`
${Rd(p,t)}
float ${a}(int row, int col) {
return ${a}(${Fd(c,o)});
}
`}if(e.shapeInfo.isUniform)return`
float ${a}(int row, int col) {
int index = round(dot(vec2(row, col), vec2(${r[1]}, 1)));
${Md(e)}
}
`;let u=s[0],d=s[1],h=Dl(n);return d===1?t?`
float ${a}(int row, int col) {
float index = dot(vec3(row, col, ${h}), vec3(${n}Shape[1], 1, 1));
vec2 uv = vec2(0.5, (index + 0.5) / float(${n}TexShape[0]));
return sampleTexture(${n}, uv);
}
`:`
float ${a}(int row, int col) {
float index = dot(vec3(row, col, ${h}), vec3(${r[1]}, 1, 1));
vec2 uv = vec2(0.5, (index + 0.5) / ${u}.0);
return sampleTexture(${n}, uv);
}
`:u===1?t?`
float ${a}(int row, int col) {
float index = dot(vec3(row, col, ${h}), vec3(${n}Shape[1], 1, 1));
vec2 uv = vec2((index + 0.5) / float(${n}TexShape[1]), 0.5);
return sampleTexture(${n}, uv);
}
`:`
float ${a}(int row, int col) {
float index = dot(vec3(row, col, ${h}), vec3(${r[1]}, 1, 1));
vec2 uv = vec2((index + 0.5) / ${d}.0, 0.5);
return sampleTexture(${n}, uv);
}
`:t?`
float ${a}(int row, int col) {
// Explicitly use integer operations as dot() only works on floats.
int index = row * ${n}Shape[1] + col + ${h};
vec2 uv = uvFromFlat(${n}TexShape[0], ${n}TexShape[1], index);
return sampleTexture(${n}, uv);
}
`:`
float ${a}(int row, int col) {
// Explicitly use integer operations as dot() only works on floats.
int index = row * ${r[1]} + col + ${h};
vec2 uv = uvFromFlat(${u}, ${d}, index);
return sampleTexture(${n}, uv);
}
`}function Nee(e,t){let r=e.shapeInfo.logicalShape,n=e.name,a="get"+n.charAt(0).toUpperCase()+n.slice(1),s=e.shapeInfo.texShape,i=[Math.ceil(s[0]/2),Math.ceil(s[1]/2)];if(r[0]===1){let p=r.slice(1),c=[1,2],m=$d(e,p),f=["b","row","col"];return`
${G9(m,t)}
vec4 ${a}(int b, int row, int col) {
return ${a}(${Fd(f,c)});
}
`}let o=qr();if(t)return`
vec4 ${a}(int b, int row, int col) {
ivec2 packedTexShape = ivec2(ceil(float(${n}TexShape[0]) / 2.0), ceil(float(${n}TexShape[1]) / 2.0));
int valuesPerRow = int(ceil(float(${n}Shape[2]) / 2.0));
int texelsInBatch = valuesPerRow * int(ceil(float(${n}Shape[1]) / 2.0));
vec2 uv = packedUVfrom3D(
packedTexShape[0], packedTexShape[1], texelsInBatch, valuesPerRow, b, row, col);
return ${o.texture2D}(${n}, uv);
}
`;let l=i[0],u=i[1],d=Math.ceil(r[2]/2),h=d*Math.ceil(r[1]/2);return`
vec4 ${a}(int b, int row, int col) {
vec2 uv = packedUVfrom3D(
${l}, ${u}, ${h}, ${d}, b, row, col);
return ${o.texture2D}(${n}, uv);
}
`}function Eee(e,t){let r=e.shapeInfo.logicalShape,n=e.name,a="get"+n.charAt(0).toUpperCase()+n.slice(1),s=r[1]*r[2],i=r[2],{newShape:o,keptDims:l}=v.squeezeShape(r),u=o;if(u.length<r.length){let f=$d(e,u),g=["row","col","depth"];return`
${Rd(f,t)}
float ${a}(int row, int col, int depth) {
return ${a}(${Fd(g,l)});
}
`}if(e.shapeInfo.isUniform)return`
float ${a}(int row, int col, int depth) {
int index = round(dot(vec3(row, col, depth),
vec3(${s}, ${i}, 1)));
${Md(e)}
}
`;let d=e.shapeInfo.texShape,h=d[0],p=d[1],c=e.shapeInfo.flatOffset;if(p===s&&c==null)return t?`
float ${a}(int row, int col, int depth) {
int stride1 = ${n}Shape[2];
float texR = float(row);
float texC = dot(vec2(col, depth), vec2(stride1, 1));
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${n}TexShape[1], ${n}TexShape[0]);
return sampleTexture(${n}, uv);
}
`:`
float ${a}(int row, int col, int depth) {
float texR = float(row);
float texC = dot(vec2(col, depth), vec2(${i}, 1));
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${p}.0, ${h}.0);
return sampleTexture(${n}, uv);
}
`;if(p===i&&c==null)return t?`
float ${a}(int row, int col, int depth) {
float texR = dot(vec2(row, col), vec2(${n}Shape[1], 1));
float texC = float(depth);
vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${n}TexShape[1], ${n}TexShape[0]);
return sampleTexture(${n}, uv);
}
`:`
float ${a}(int row, int col, int depth) {
float texR = dot(vec2(row, col), vec2(${r[1]}, 1));
float texC = float(depth);
vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${p}.0, ${h}.0);
return sampleTexture(${n}, uv);
}
`;let m=Dl(n);return t?`
float ${a}(int row, int col, int depth) {
// Explicitly use integer operations as dot() only works on floats.
int stride0 = ${n}Shape[1] * ${n}Shape[2];
int stride1 = ${n}Shape[2];
int index = row * ${s} + col * ${i} + depth + ${m};
vec2 uv = uvFromFlat(${n}TexShape[0], ${n}TexShape[1], index);
return sampleTexture(${n}, uv);
}
`:`
float ${a}(int row, int col, int depth) {
// Explicitly use integer operations as dot() only works on floats.
int index = row * ${s} + col * ${i} + depth + ${m};
vec2 uv = uvFromFlat(${h}, ${p}, index);
return sampleTexture(${n}, uv);
}
`}function Ree(e,t){let r=e.name,n="get"+r.charAt(0).toUpperCase()+r.slice(1),a=qr();if(t)return`
vec4 ${n}(int b2, int b, int row, int col) {
int valuesPerRow = int(ceil(float(${r}Shape[3]) / 2.0));
int texelsInBatch = valuesPerRow * int(ceil(float(${r}Shape[2]) / 2.0));
int index = b * texelsInBatch + (row / 2) * valuesPerRow + (col / 2);
texelsInBatch *= ${r}Shape[1];
index = b2 * texelsInBatch + index;
ivec2 packedTexShape = ivec2(ceil(float(${r}TexShape[0]) / 2.0), ceil(float(${r}TexShape[1]) / 2.0));
int texR = index / packedTexShape[1];
int texC = index - texR * packedTexShape[1];
vec2 uv = (vec2(texC, texR) + halfCR) / vec2(packedTexShape[1], packedTexShape[0]); return ${a.texture2D}(${r}, uv);
}
`;let s=e.shapeInfo.logicalShape,i=s.length,o=e.shapeInfo.texShape,l=[Math.ceil(o[0]/2),Math.ceil(o[1]/2)],u=l[0],d=l[1],h=Math.ceil(s[i-1]/2),p=h*Math.ceil(s[i-2]/2),c="int b, int row, int col",m=`b * ${p} + (row / 2) * ${h} + (col / 2)`;for(let f=2;f<i-1;f++)c=`int b${f}, `+c,p*=s[i-f-1],m=`b${f} * ${p} + `+m;return`
vec4 ${n}(${c}) {
int index = ${m};
int texR = index / ${d};
int texC = index - texR * ${d};
vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${d}, ${u});
return ${a.texture2D}(${r}, uv);
}
`}function Mee(e,t){let r=e.shapeInfo.logicalShape,n=e.name,a="get"+n.charAt(0).toUpperCase()+n.slice(1),s=r[3],i=r[2]*s,o=r[1]*i,{newShape:l,keptDims:u}=v.squeezeShape(r);if(l.length<r.length){let A=$d(e,l),x=["row","col","depth","depth2"];return`
${Rd(A,t)}
float ${a}(int row, int col, int depth, int depth2) {
return ${a}(${Fd(x,u)});
}
`}if(e.shapeInfo.isUniform)return`
float ${a}(int row, int col, int depth, int depth2) {
int index = round(dot(vec4(row, col, depth, depth2),
vec4(${o}, ${i}, ${s}, 1)));
${Md(e)}
}
`;let d=e.shapeInfo.flatOffset,h=e.shapeInfo.texShape,p=h[0],c=h[1],m=`int stride2 = ${n}Shape[3];`,f=`int stride1 = ${n}Shape[2] * stride2;`,g=`int stride0 = ${n}Shape[1] * stride1;`;if(c===o&&d==null)return t?`
float ${a}(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 ${a}(int row, int col, int depth, int depth2) {
float texR = float(row);
float texC =
dot(vec3(col, depth, depth2),
vec3(${i}, ${s}, 1));
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${c}.0, ${p}.0);
return sampleTexture(${n}, uv);
}
`;if(c===s&&d==null)return t?`
float ${a}(int row, int col, int depth, int depth2) {
float texR = dot(vec3(row, col, depth),
vec3(${n}Shape[1] * ${n}Shape[2], ${n}Shape[2], 1));
float texC = float(depth2);
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${n}TexShape[1], ${n}TexShape[0]);
return sampleTexture(${n}, uv);
}
`:`
float ${a}(int row, int col, int depth, int depth2) {
float texR = dot(vec3(row, col, depth),
vec3(${r[1]*r[2]}, ${r[2]}, 1));
float texC = float(depth2);
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${c}.0, ${p}.0);
return sampleTexture(${n}, uv);
}
`;let y=Dl(n);return t?`
float ${a}(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 ${a}(int row, int col, int depth, int depth2) {
// Explicitly use integer operations as dot() only works on floats.
int index = row * ${o} + col * ${i} +
depth * ${s} + depth2;
vec2 uv = uvFromFlat(${p}, ${c}, index + ${y});
return sampleTexture(${n}, uv);
}
`}function $ee(e){let t=e.shapeInfo.logicalShape,r=e.name,n="get"+r.charAt(0).toUpperCase()+r.slice(1),a=t[4],s=t[3]*a,i=t[2]*s,o=t[1]*i,{newShape:l,keptDims:u}=v.squeezeShape(t);if(l.length<t.length){let f=$d(e,l),g=["row","col","depth","depth2","depth3"];return`
${Rd(f)}
float ${n}(int row, int col, int depth, int depth2, int depth3) {
return ${n}(${Fd(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}, ${a})) +
depth3;
${Md(e)}
}
`;let d=e.shapeInfo.flatOffset,h=e.shapeInfo.texShape,p=h[0],c=h[1];if(c===o&&d==null)return`
float ${n}(int row, int col, int depth, int depth2, int depth3) {
int texR = row;
float texC = dot(vec4(col, depth, depth2, depth3),
vec4(${i}, ${s}, ${a}, 1));
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${c}.0, ${p}.0);
return sampleTexture(${r}, uv);
}
`;if(c===a&&d==null)return`
float ${n}(int row, int col, int depth, int depth2, int depth3) {
float texR = dot(
vec4(row, col, depth, depth2),
vec4(${t[1]*t[2]*t[3]},
${t[2]*t[3]}, ${t[3]}, 1));
int texC = depth3;
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${c}.0, ${p}.0);
return sampleTexture(${r}, uv);
}
`;let m=Dl(r);return`
float ${n}(int row, int col, int depth, int depth2, int depth3) {
// Explicitly use integer operations as dot() only works on floats.
int index = row * ${o} + col * ${i} + depth * ${s} +
depth2 * ${a} + depth3 + ${m};
vec2 uv = uvFromFlat(${p}, ${c}, index);
return sampleTexture(${r}, uv);
}
`}function Fee(e){let t=e.shapeInfo.logicalShape,r=e.name,n="get"+r.charAt(0).toUpperCase()+r.slice(1),{newShape:a,keptDims:s}=v.squeezeShape(t);if(a.length<t.length){let g=$d(e,a),y=["row","col","depth","depth2","depth3","depth4"];return`
${Rd(g)}
float ${n}(int row, int col, int depth,
int depth2, int depth3, int depth4) {
return ${n}(${Fd(y,s)});
}
`}let i=t[5],o=t[4]*i,l=t[3]*o,u=t[2]*l,d=t[1]*u;if(e.shapeInfo.isUniform)return`
float ${n}(int row, int col, int depth,
int depth2, int depth3, int depth4) {
int index = round(dot(
vec4(row, col, depth, depth2),
vec4(${d}, ${u}, ${l}, ${o})) +
dot(
vec2(depth3, depth4),
vec2(${i}, 1)));
${Md(e)}
}
`;let h=e.shapeInfo.flatOffset,p=e.shapeInfo.texShape,c=p[0],m=p[1];if(m===d&&h==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, ${c}.0);
return sampleTexture(${r}, uv);
}
`;if(m===i&&h==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, ${c}.0);
return sampleTexture(${r}, uv);
}
`;let f=Dl(r);return`
float ${n}(int row, int col, int depth,
int depth2, int depth3, int depth4) {
// Explicitly use integer operations as dot() only works on floats.
int index = row * ${d} + col * ${u} + depth * ${l} +
depth2 * ${o} + depth3 * ${i} + depth4 + ${f};
vec2 uv = uvFromFlat(${c}, ${m}, index);
return sampleTexture(${r}, uv);
}
`}function Md(e){let t=e.name,r=v.sizeFromShape(e.shapeInfo.logicalShape);return r<2?`return ${t};`:`
for (int i = 0; i < ${r}; i++) {
if (i == index) {
return ${t}[i];
}
}
`}function _ee(e,t){let r=e.name,n=r.charAt(0).toUpperCase()+r.slice(1),a="get"+n+"AtOutCoords",s=e.shapeInfo.logicalShape.length,i=t.logicalShape.length,o=U9(e.shapeInfo.logicalShape,t.logicalShape),l=vt(i),u=i-s,d,h=["x","y","z","w","u","v"];s===0?d="":i<2&&o.length>=1?d="coords = 0;":d=o.map(g=>`coords.${h[g+u]} = 0;`).join(`
`);let p="";i<2&&s>0?p="coords":p=e.shapeInfo.logicalShape.map((g,y)=>`coords.${h[y+u]}`).join(", ");let c="return outputValue;",m=v.sizeFromShape(e.shapeInfo.logicalShape)===1,f=v.sizeFromShape(t.logicalShape)===1;if(s===1&&!m&&!f)c=`
return vec4(outputValue.xy, outputValue.xy);
`;else if(m&&!f)i===1?c=`
return vec4(outputValue.x, outputValue.x, 0., 0.);
`:c=`
return vec4(outputValue.x);
`;else if(o.length){let g=s-2,y=s-1;o.indexOf(g)>-1&&o.indexOf(y)>-1?c="return vec4(outputValue.x);":o.indexOf(g)>-1?c="return vec4(outputValue.x, outputValue.y, outputValue.x, outputValue.y);":o.indexOf(y)>-1&&(c="return vec4(outputValue.xx, outputValue.zz);")}return`
vec4 ${a}() {
${l} coords = getOutputCoords();
${d}
vec4 outputValue = get${n}(${p});
${c}
}
`}function Pee(e,t){let r=e.name,n=r.charAt(0).toUpperCase()+r.slice(1),a="get"+n+"AtOutCoords",s=t.texShape,i=e.shapeInfo.texShape,o=e.shapeInfo.logicalShape.length,l=t.logicalShape.length;if(!e.shapeInfo.isUniform&&o===l&&e.shapeInfo.flatOffset==null&&v.arraysEqual(i,s))return`
float ${a}() {
return sampleTexture(${r}, resultUV);
}
`;let u=vt(l),d=U9(e.shapeInfo.logicalShape,t.logicalShape),h=l-o,p,c=["x","y","z","w","u","v"];o===0?p="":l<2&&d.length>=1?p="coords = 0;":p=d.map(f=>`coords.${c[f+h]} = 0;`).join(`
`);let m="";return l<2&&o>0?m="coords":m=e.shapeInfo.logicalShape.map((f,g)=>`coords.${c[g+h]}`).join(", "),`
float ${a}() {
${u} coords = getOutputCoords();
${p}
return get${n}(${m});
}
`}function vt(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 kA(e,t,r){let{newShape:n,keptDims:a}=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,r)&&n.length<s||i;return{useSqueezeShape:l,uniformShape:l?o:t,keptDims:a}}function $d(e,t){let r=JSON.parse(JSON.stringify(e));return r.shapeInfo.logicalShape=t,r}function Fd(e,t){return t.map(r=>e[r]).join(", ")}function Oee(e,t,r,n){let a=r.map((d,h)=>{let p={logicalShape:d.shape,texShape:d.isUniform?null:d.texData.texShape,isUniform:d.isUniform,isPacked:d.isUniform?!1:d.texData.isPacked,flatOffset:null};return d.texData!=null&&d.texData.slice!=null&&d.texData.slice.flatOffset>0&&(p.flatOffset=d.texData.slice.flatOffset),{name:t.variableNames[h],shapeInfo:p}}),s=a.map(d=>d.shapeInfo),i={logicalShape:n.shape,texShape:n.texData.texShape,isUniform:!1,isPacked:n.texData.isPacked,flatOffset:null},o=eee(a,i,t),l=v9(e.gl,o),u=e.createProgram(l);return Z().get("ENGINE_COMPILE_ONLY")?{program:t,fragmentShader:l,source:o,webGLProgram:u,inShapeInfos:s,outShapeInfo:i,uniformLocations:null,customUniformLocations:null,infLoc:null,nanLoc:null,inShapesLocations:null,inTexShapesLocations:null,outShapeLocation:null,outShapeStridesLocation:null,outTexShapeLocation:null}:{program:t,fragmentShader:l,source:o,webGLProgram:u,inShapeInfos:s,outShapeInfo:i,...H9(e,t,u)}}function H9(e,t,r){let n={},a={},s={},i=[],o,l,u,d=null,h=null;h=e.getUniformLocation(r,"NAN",!1),Z().getNumber("WEBGL_VERSION")===1&&(d=e.getUniformLocation(r,"INFINITY",!1));let p=!1;for(let c=0;c<t.variableNames.length;c++){let m=t.variableNames[c];n[m]=e.getUniformLocation(r,m,p),n[`offset${m}`]=e.getUniformLocation(r,`offset${m}`,p),t.enableShapeUniforms&&(a[`${m}Shape`]=e.getUniformLocation(r,`${m}Shape`,p),s[`${m}TexShape`]=e.getUniformLocation(r,`${m}TexShape`,p))}return t.enableShapeUniforms&&(o=e.getUniformLocation(r,"outShape",p),u=e.getUniformLocation(r,"outShapeStrides",p),l=e.getUniformLocation(r,"outTexShape",p)),t.customUniforms&&t.customUniforms.forEach((c,m)=>{i[m]=e.getUniformLocation(r,c.name,p)}),{uniformLocations:n,customUniformLocations:i,infLoc:d,nanLoc:h,inShapesLocations:a,inTexShapesLocations:s,outShapeLocation:o,outShapeStridesLocation:u,outTexShapeLocation:l}}function V4(e,t){if(e.length!==t.length)throw Error(`Binary was compiled with ${e.length} inputs, but was executed with ${t.length} inputs`);e.forEach((r,n)=>{let a=r.logicalShape,s=t[n],i=s.shape;if(!v.arraysEqual(a,i))throw Error(`Binary was compiled with different shapes than the current args. Shapes ${a} and ${i} must match`);if(r.isUniform&&s.isUniform)return;let o=r.texShape,l=s.isUniform?null:s.texData.texShape;if(!v.arraysEqual(o,l))throw Error(`Binary was compiled with different texture shapes than the current args. Shape ${o} and ${l} must match`)})}function zee(e,t,r,n,a){t.program.enableShapeUniforms||(V4(t.inShapeInfos,r),V4([t.outShapeInfo],[n]));let s=n.texData.texture,i=n.texData.texShape;n.texData.isPacked?e.setOutputPackedMatrixTexture(s.texture,i[0],i[1]):e.setOutputMatrixTexture(s.texture,i[0],i[1]),e.setProgram(t.webGLProgram),Z().getNumber("WEBGL_VERSION")===1&&t.infLoc!==null&&e.gl.uniform1f(t.infLoc,1/0),t.nanLoc!==null&&e.gl.uniform1f(t.nanLoc,NaN),r.forEach((l,u)=>{let d=t.program.variableNames[u],h=t.uniformLocations[d],p=t.uniformLocations[`offset${d}`],c=t.inShapesLocations[`${d}Shape`],m=t.inTexShapesLocations[`${d}TexShape`];if(c){let{uniformShape:f}=kA(t.program.packedInputs,l.shape,l.texData.texShape);switch(f.length){case 1:e.gl.uniform1iv(c,new Int32Array(f));break;case 2:e.gl.uniform2iv(c,new Int32Array(f));break;case 3:e.gl.uniform3iv(c,new Int32Array(f));break;case 4:e.gl.uniform4iv(c,new Int32Array(f));break;default:break}}if(m&&e.gl.uniform2i(m,l.texData.texShape[0],l.texData.texShape[1]),h!=null){if(l.isUniform){if(v.sizeFromShape(l.shape)<2)e.gl.uniform1f(h,l.uniformValues[0]);else{let f=l.uniformValues;f instanceof Float32Array||(f=new Float32Array(f)),e.gl.uniform1fv(h,f)}return}l.texData.slice!=null&&p!=null&&e.gl.uniform1i(p,l.texData.slice.flatOffset),e.setInputMatrixTexture(l.texData.texture.texture,h,u)}});let o=t.outShapeLocation;if(o)switch(n.shape.length){case 1:e.gl.uniform1iv(o,new Int32Array(n.shape));break;case 2:e.gl.uniform2iv(o,new Int32Array(n.shape));break;case 3:e.gl.uniform3iv(o,new Int32Array(n.shape));break;case 4:e.gl.uniform4iv(o,new Int32Array(n.shape));break;default:break}if(t.outShapeStridesLocation){let l=v.computeStrides(n.shape);switch(n.shape.length){case 2:e.gl.uniform1iv(t.outShapeStridesLocation,new Int32Array(l));break;case 3:e.gl.uniform2iv(t.outShapeStridesLocation,new Int32Array(l));break;case 4:e.gl.uniform3iv(t.outShapeStridesLocation,new Int32Array(l));break;default:break}}t.outTexShapeLocation&&e.gl.uniform2i(t.outTexShapeLocation,n.texData.texShape[0],n.texData.texShape[1]),t.program.customUniforms&&a&&t.program.customUniforms.forEach((l,u)=>{let d=t.customUniformLocations[u],h=a[u];if(l.type==="float")e.gl.uniform1fv(d,h);else if(l.type==="vec2")e.gl.uniform2fv(d,h);else if(l.type==="vec3")e.gl.uniform3fv(d,h);else if(l.type==="vec4")e.gl.uniform4fv(d,h);else if(l.type==="int")e.gl.uniform1iv(d,h);else if(l.type==="ivec2")e.gl.uniform2iv(d,h);else if(l.type==="ivec3")e.gl.uniform3iv(d,h);else if(l.type==="ivec4")e.gl.uniform4iv(d,h);else throw Error(`uniform type ${l.type} is not supported yet.`)}),e.executeProgram()}function Dee(e,t,r){let n="";t.concat(r).forEach(i=>{let o=i.texData!=null&&i.texData.slice!=null&&i.texData.slice.flatOffset>0;if(e.enableShapeUniforms&&!i.isUniform){let l=i.texData.texShape,{useSqueezeShape:u,uniformShape:d,keptDims:h}=kA(e.packedInputs,i.shape,l),p="",c="",m="";if(d.length===1&&e.packedInputs){let w=[Math.ceil(l[0]/2),Math.ceil(l[1]/2)];p=`${w[0]>1}_${w[1]>1}`}else if(d.length===2&&!e.packedInputs)c=`${d[0]>1}_${d[1]>1}`;else if(d.length>2&&!e.packedInputs){let w=v.computeStrides(d);m=`${w[0]===l[1]}_${w[w.length-1]===l[1]}`}let f=i.shape.length,g=d.length===2&&v.arraysEqual(i.shape,l),y=v.sizeFromShape(i.shape)===1,A=C.getBroadcastDims(i.shape,r.shape),x=!e.packedInputs&&f===r.shape.length&&v.arraysEqual(l,r.texData.texShape),b=e.packedInputs||d.length>2?"":`${l[0]>1}_${l[1]>1}`;n+=`${f}_${x}_${u?h:""}_${d.length}_${y}_${A}_${g}_${p}_${c}_${m}_${b}_${o}`}else{let l=i.isUniform?"uniform":i.texData.texShape;n+=`${i.shape}_${l}_${o}`}});let a=e.userCode,s=e.constructor.name;return s+="_"+n+"_"+a+`${Z().getNumber("WEBGL_VERSION")}`,s}function un(e){return Z().getBool("WEBGL_USE_SHAPES_UNIFORMS")&&e<=4}var Lee=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outPackingScheme=0,this.customUniforms=[{name:"texShape",type:"ivec2"}];let t=qr();this.outputShape=e,this.enableShapeUniforms=un(this.outputShape.length),this.userCode=`
ivec3 outCoordsFromFlatIndex(int index) {
${this.enableShapeUniforms?Fm(["r","c","d"],e):zl(["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;
}
`}},Bee=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outPackingScheme=0,this.customUniforms=[{name:"texShape",type:"ivec2"}];let t=qr();this.outputShape=e,this.enableShapeUniforms=un(this.outputShape.length),this.userCode=`
ivec3 outCoordsFromFlatIndex(int index) {
${this.enableShapeUniforms?Fm(["r","c","d"],e):zl(["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;
}
`}},Wee=class{constructor(e){this.variableNames=["A"],this.outTexUsage=3;let t=qr();this.outputShape=e,this.userCode=`
${V9}
void main() {
float x = getAAtOutCoords();
${t.output} = encode_float(x);
}
`}},Vee=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outTexUsage=3;let t=qr();this.outputShape=e,this.userCode=`
${V9}
void main() {
ivec3 coords = getOutputCoords();
float x = getChannel(getAAtOutCoords(), vec2(coords.y, coords.z));
${t.output} = encode_float(x);
}
`}},Uee=class{constructor(e,t=!1){this.variableNames=["A"],this.customUniforms=[{name:"texShape",type:"ivec2"}];let r=qr();this.outputShape=e,this.enableShapeUniforms=un(this.outputShape.length);let n="result";t&&(n="floor(result * 255. + 0.5)"),this.userCode=`
${this.enableShapeUniforms?wA():vA(e)}
void main() {
ivec3 coords = getOutputCoords();
int flatIndex = getFlatIndex(coords);
int offset = imod(flatIndex, 4);
flatIndex = idiv(flatIndex, 4, 1.);
int r = flatIndex / texShape[1];
int c = imod(flatIndex, texShape[1]);
vec2 uv = (vec2(c, r) + halfCR) / vec2(texShape[1], texShape[0]);
vec4 values = ${r.texture2D}(A, uv);
float result;
if(offset == 0) {
result = values[0];
} else if(offset == 1) {
result = values[1];
} else if(offset == 2) {
result = values[2];
} else {
result = values[3];
}
${r.output} = vec4(${n}, 0., 0., 0.);
}
`}},Gee=class{constructor(e,t=!1){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.customUniforms=[{name:"texShape",type:"ivec2"}];let r=qr();this.outputShape=e,this.enableShapeUniforms=un(this.outputShape.length);let n="",a="result";t&&(a="floor(result * 255. + 0.5)");for(let s=0;s<=1;s++)for(let i=0;i<=1;i++){let o=s*2+i;n+=`
localCoords = coords;
if(localCoords[2] + ${i} < ${this.enableShapeUniforms?"outShape[2]":`${e[2]}`}) {
localCoords[2] += ${i};
if (localCoords[1] + ${s} < ${this.enableShapeUniforms?"outShape[1]":`${e[1]}`}) {
localCoords[1] += ${s};
flatIndex = getFlatIndex(localCoords);
offset = imod(flatIndex, 4);
flatIndex = idiv(flatIndex, 4, 1.);
int r = flatIndex / texShape[1];
int c = imod(flatIndex, texShape[1]);
vec2 uv = (vec2(c, r) + halfCR) / vec2(texShape[1], texShape[0]);
values = ${r.texture2D}(A, uv);
if (offset == 0) {
result[${o}] = values[0];
} else if (offset == 1) {
result[${o}] = values[1];
} else if (offset == 2) {
result[${o}] = values[2];
} else {
result[${o}] = values[3];
}
}
}
`}this.userCode=`
${this.enableShapeUniforms?wA():vA(e)}
void main() {
ivec3 coords = getOutputCoords();
vec4 result = vec4(0.);
int flatIndex, r, c, offset;
ivec3 localCoords;
vec2 uv;
vec4 values;
${n}
${r.output} = ${a};
}
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${t.attribute} vec3 clipSpacePos;
${t.attribute} vec2 uv;
${t.varyingVs} vec2 resultUV;
void main() {
gl_Position = vec4(clipSpacePos, 1);
resultUV = uv;
}`;return b9(e,r)}function K9(e){let t=new Float32Array([-1,1,0,0,1,-1,-1,0,0,0,1,1,0,1,1,1,-1,0,1,0]);return I9(e,t)}function Z9(e){let t=new Uint16Array([0,1,2,2,1,3]);return S9(e,t)}function Hh(e,t,r,n,a,s){T9(t,r);let i=C9(e),o=e.TEXTURE_2D;return we(e,()=>e.bindTexture(o,i)),we(e,()=>e.texParameteri(o,e.TEXTURE_WRAP_S,e.CLAMP_TO_EDGE)),we(e,()=>e.texParameteri(o,e.TEXTURE_WRAP_T,e.CLAMP_TO_EDGE)),we(e,()=>e.texParameteri(o,e.TEXTURE_MIN_FILTER,e.NEAREST)),we(e,()=>e.texParameteri(o,e.TEXTURE_MAG_FILTER,e.NEAREST)),Z().getNumber("WEBGL_VERSION")===1?we(e,()=>e.texImage2D(o,0,n,t,r,0,a,s,null)):we(e,()=>e.texStorage2D(o,1,n,t,r)),we(e,()=>e.bindTexture(e.TEXTURE_2D,null)),{texture:i,texShape:[r,t]}}function IA(e){return e.internalFormatFloat}function Y9(e,t,r,n){let[a,s]=jh(t,r);return Hh(e,a,s,IA(n),n.textureFormatFloat,e.FLOAT)}function SA(e){return e.internalFormatHalfFloat}function J9(e,t,r,n){let[a,s]=jh(t,r);return 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$te=class{constructor(e){if(this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outputShape=e,this.rank=e.length,this.enableShapeUniforms=un(this.outputShape.length),this.rank===0)this.userCode=`
void main() {
setOutput(vec4(getA(), 0., 0., 0.));
}
`;else{let t=Br("rc",this.rank),r=vt(this.rank),n=this.getOutOfBoundsCondition(t),a=this.getSetup(t),s=this.getOutput(t);this.userCode=`
void main() {
${r} rc = getOutputCoords();
if(${n}) {
setOutput(vec4(0));
} else {
${a}
setOutput(vec4(${s}));
}
}
`}}getSourceCoordsArr(e){let t=[];for(let r=0;r<=1;r++)for(let n=0;n<=1;n++){let a=`${r===0?"r":"rp1"}, ${n===0?"c":"cp1"}`;for(let s=2;s<this.rank;s++)a=`${e[e.length-1-s]},`+a;t.push(a)}return t}getOutOfBoundsCondition(e){if(this.rank===1)return`rc > ${this.enableShapeUniforms?"outShape":this.outputShape[0]}`;let t="";for(let r=this.rank-2;r<this.rank;r++)t+=`${e[r]} >= ${this.enableShapeUniforms?`outShape[${r}]`:this.outputShape[r]}`,r<this.rank-1&&(t+="||");return t}getSetup(e){if(this.rank===1)return"";let t=e.slice(-2),r=this.enableShapeUniforms?`outShape[${this.rank} - 1]`:this.outputShape[this.rank-1],n=this.enableShapeUniforms?`outShape[${this.rank} - 2]`:this.outputShape[this.rank-2];return`
int r = ${t[0]};
int c = ${t[1]};
int rp1 = r + 1;
int cp1 = c + 1;
bool cEdge = cp1 >= ${r};
bool rEdge = rp1 >= ${n};
`}getOutput(e){let t=this.getSourceCoordsArr(e);return this.rank===1?`getA(rc), (rc + 1 >= ${this.enableShapeUniforms?"outShape":this.outputShape[0]} ? 0. : getA(rc + 1)), 0, 0`:`getA(${t[0]}),
cEdge ? 0. : getA(${t[1]}),
rEdge ? 0. : getA(${t[2]}),
rEdge || cEdge ? 0. : getA(${t[3]})`}},fI=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"inputShape",type:"ivec3"}],this.outputShape=e,this.enableShapeUniforms=un(this.outputShape.length);let r="";for(let n=0;n<4;n++){let a="thisRC = rc;";n%2===1&&(a+="thisRC.z += 1;"),n>1&&(a+="thisRC.y += 1;"),r+=`
${a}
${n>0?"if(thisRC.y < rows && thisRC.z < cols){":""}
int flatIndex = getFlatIndex(thisRC);
ivec3 inputRC = inputCoordsFromReshapedOutCoords(flatIndex);
vec2 inputRCInnerDims = vec2(float(inputRC.y),float(inputRC.z));
result[${n}] =
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${n>0?"}":""}
`}this.userCode=`
${Fte(t,this.enableShapeUniforms)}
${this.enableShapeUniforms?wA():vA(e)}
void main() {
ivec3 rc = getOutputCoords();
vec4 result = vec4(0.);
ivec3 thisRC;
int rows = ${this.enableShapeUniforms?"outShape[1]":e[1]};
int cols = ${this.enableShapeUniforms?"outShape[2]":e[2]};
${r}
setOutput(result);
}
`}};function Fte(e,t){return`
ivec3 inputCoordsFromReshapedOutCoords(int index) {
${t?QQ(["r","c","d"],"inputShape"):zl(["r","c","d"],e)}
return ivec3(r, c, d);
}
`}var _te=class{constructor(e){this.gpgpu=e,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0,this.freeTextures={},this.logEnabled=!1,this.usedTextures={}}acquireTexture(e,t,r){let n=G4(t,r),a=j4(e,n,r);a in this.freeTextures||(this.freeTextures[a]=[]),a in this.usedTextures||(this.usedTextures[a]=[]);let s=U4(e,n,this.gpgpu.gl,this.gpgpu.textureConfig,r);if(this.freeTextures[a].length>0){this.numFreeTextures--,this.numUsedTextures++,this._numBytesFree-=s,this.log();let o=this.freeTextures[a].shift();return this.usedTextures[a].push(o),o}let i;return n===3?i=this.gpgpu.createPackedMatrixTexture(e[0],e[1]):n===4?i=this.gpgpu.createFloat16PackedMatrixTexture(e[0],e[1]):n===1?i=this.gpgpu.createFloat32MatrixTexture(e[0],e[1]):n===0?i=this.gpgpu.createFloat16MatrixTexture(e[0],e[1]):n===2&&(i=this.gpgpu.createUnsignedBytesMatrixTexture(e[0],e[1])),this.usedTextures[a].push(i),this.numUsedTextures++,this._numBytesAllocated+=s,this.log(),i}releaseTexture(e,t,r,n){if(this.freeTextures==null)return;let a=G4(r,n),s=j4(t,a,n);s in this.freeTextures||(this.freeTextures[s]=[]);let i=U4(t,a,this.gpgpu.gl,this.gpgpu.textureConfig,n),o=Z().get("WEBGL_DELETE_TEXTURE_THRESHOLD");o!==-1&&this._numBytesAllocated>o?(this.gpgpu.deleteMatrixTexture(e.texture),this._numBytesAllocated-=i):(this.freeTextures[s].push(e),this.numFreeTextures++,this._numBytesFree+=i),this.numUsedTextures--;let l=this.usedTextures[s],u=l.indexOf(e);if(u<0)throw new Error("Cannot release a texture that was never provided by this texture manager");l.splice(u,1),this.log()}log(){if(!this.logEnabled)return;let e=this.numFreeTextures+this.numUsedTextures;console.log("Free/Used",`${this.numFreeTextures} / ${this.numUsedTextures}`,`(${e})`);let t=this._numBytesFree/this._numBytesAllocated;console.log(`Bytes allocated: ${this._numBytesAllocated}`),console.log(`Bytes unused: ${this._numBytesFree} (${Math.round(100*t)}%)`)}get numBytesAllocated(){return this._numBytesAllocated}get numBytesFree(){return this._numBytesFree}getNumUsedTextures(){return this.numUsedTextures}getNumFreeTextures(){return this.numFreeTextures}dispose(){if(this.freeTextures!=null){for(let e in this.freeTextures)this.freeTextures[e].forEach(t=>{this.gpgpu.deleteMatrixTexture(t.texture)});for(let e in this.usedTextures)this.usedTextures[e].forEach(t=>{this.gpgpu.deleteMatrixTexture(t.texture)});this.freeTextures=null,this.usedTextures=null,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0}}};function Pte(e,t){let r=e;if(t===r.R32F)return 4;if(t===r.R16F)return 2;if(t===r.RGBA32F||t===e.RGBA)return 16;if(t===r.RGBA16F)return 8;if(t===r.RGBA8)return 4;throw new Error(`Unknown internal format ${t}`)}function U4(e,t,r,n,a){let s=Ote(t,n),i;if(a){let[l,u]=Nd(e[0],e[1]);i=l*u}else{let[l,u]=jh(e[0],e[1]);i=l*u}let o=Pte(r,s);return i*o}function Ote(e,t){switch(e){case 3:return TA(t);case 4:return NA(t);case 1:return IA(t);case 0:return SA(t);case 2:return CA(t);default:throw new Error(`Unknown physical texture type ${e}`)}}function zte(e){return Z().getBool("WEBGL_RENDER_FLOAT32_ENABLED")?e?3:1:e?4:0}function G4(e,t){if(e===1)return 3;if(e===0||e==null)return zte(t);if(e===3||e===2)return 2;throw new Error(`Unknown logical texture type ${e}`)}function j4(e,t,r){return`${e[0]}_${e[1]}_${t}_${r}`}var Xa=class{constructor(e,t){this.variableNames=["A"],this.outputShape=e,this.enableShapeUniforms=un(this.outputShape.length),this.userCode=`
float unaryOperation(float x) {
${t}
}
void main() {
float x = getAAtOutCoords();
float y = unaryOperation(x);
setOutput(y);
}
`}},Yn="if (isnan(x)) return x;",Dte="return x;",H4="return abs(x);",Lte="return (x >= 0.0) ? x : (exp(x) - 1.0);",Bte=Yn+`
return (x < 0.0) ? 0.0 : x;
`,Wte=Yn+`
return (x < 0.0) ? 0.0 : min(6.0, x);
`,hu="return x;",Vte="return 1.0 / (1.0 + exp(-1.0 * x));",Ute="return x;",Gte=`
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;
`,jte=`
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;
`,Hte=`
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;
`,qte="return 1.0 / (1.0 + exp(-1.0 * x));",Co=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.enableShapeUniforms=un(this.outputShape.length),this.userCode=`
vec4 unaryOperation(vec4 x) {
${t}
}
void main() {
vec4 x = getAAtOutCoords();
vec4 y = unaryOperation(x);
setOutput(y);
}
`}},Xte=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outputShape=e,this.enableShapeUniforms=un(this.outputShape.length);let t=e.length,r=Br("rc",t),n=vt(t),a=Mte(t,r),s=r.slice(-2),i=t<=1?"rc":`vec2(${s.join(",")})`;this.userCode=`
void main() {
${n} rc = getOutputCoords();
vec4 packedInput = getA(${a});
setOutput(getChannel(packedInput, ${i}));
}
`}},Kte=Kn.whereImpl,Zte=1e-7,Yte=1e-4,wg={};function Jte(e){return e in wg||(wg[e]={}),wg[e]}var Qte=Z().getNumber("CPU_HANDOFF_SIZE_THRESHOLD"),ere=600;function tre(){return Z().global.screen==null?1024:Z().global.screen.height*Z().global.screen.width*window.devicePixelRatio*ere/1024/1024}var mI=class extends Wu{constructor(e){if(super(),this.pendingRead=new WeakMap,this.pendingDisposal=new WeakSet,this.dataRefCount=new WeakMap,this.numBytesInGPU=0,this.uploadWaitMs=0,this.downloadWaitMs=0,this.lastGlFlushTime=0,this.warnedAboutMemory=!1,this.pendingDeletes=0,this.disposed=!1,!Z().getBool("HAS_WEBGL"))throw new Error("WebGL is not supported on this device");let t;if(e!=null){if(e instanceof Iu)t=e;else{let r=xa(Z().getNumber("WEBGL_VERSION"),e);t=new Iu(r)}this.binaryCache={},this.gpgpuCreatedLocally=!1}else{let r=xa(Z().getNumber("WEBGL_VERSION"));t=new Iu(r),this.binaryCache=Jte(Z().getNumber("WEBGL_VERSION")),this.gpgpuCreatedLocally=!0}this.gpgpu=t,this.canvas=this.gpgpu.gl.canvas,this.textureManager=new _te(this.gpgpu),this.numMBBeforeWarning=tre(),this.texData=new rh(this,Xt())}nextDataId(){return mI.nextDataId++}numDataIds(){return this.texData.numDataIds()-this.pendingDeletes}write(e,t,r){if((Z().getBool("WEBGL_CHECK_NUMERICAL_PROBLEMS")||Z().getBool("DEBUG"))&&this.checkNumericalProblems(e),r==="complex64"&&e!=null)throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");let n={id:this.nextDataId()};return this.texData.set(n,{shape:t,dtype:r,values:e,usage:1,refCount:1}),n}refCount(e){return this.texData.has(e)?this.texData.get(e).refCount:0}incRef(e){let t=this.texData.get(e);t.refCount++}decRef(e){if(this.texData.has(e)){let t=this.texData.get(e);t.refCount--}}move(e,t,r,n,a){if(Z().getBool("DEBUG")&&this.checkNumericalProblems(t),n==="complex64")throw new Error("Cannot write to a complex64 dtype. 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Consider enabling float32 rendering: 'tf.env().set('WEBGL_RENDER_FLOAT32_ENABLED', true);'`):Error(`The value ${r} cannot be represented on this device.`)}}getValuesFromTexture(e){let{shape:t,dtype:r,isPacked:n}=this.texData.get(e),a=v.sizeFromShape(t);if(Z().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")){let h=this.decode(e),p=this.texData.get(h.dataId),c=this.gpgpu.downloadMatrixFromPackedTexture(p.texture.texture,...l0(t)).subarray(0,a);return this.disposeIntermediateTensorInfo(h),c}let s=Z().getBool("WEBGL_PACK")&&n===!0,i=s?y0(t):t,o=s?new Vee(i):new Wee(i),l=this.runWebGLProgram(o,[{shape:i,dtype:r,dataId:e}],"float32"),u=this.texData.get(l.dataId),d=this.gpgpu.downloadByteEncodedFloatMatrixFromOutputTexture(u.texture.texture,u.texShape[0],u.texShape[1]).subarray(0,a);return this.disposeIntermediateTensorInfo(l),d}timerAvailable(){return Z().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0}time(e){let t=this.activeTimers,r=[],n=!1;this.programTimersStack==null?(this.programTimersStack=r,n=!0):this.activeTimers.push(r),this.activeTimers=r,e();let a=v.flatten(this.activeTimers.map(o=>o.query)).filter(o=>o!=null),s=v.flatten(this.activeTimers.map(o=>o.name)).filter(o=>o!=null);this.activeTimers=t,n&&(this.programTimersStack=null);let i={uploadWaitMs:this.uploadWaitMs,downloadWaitMs:this.downloadWaitMs,kernelMs:null,wallMs:null};return(async()=>{if(Z().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0){let o=await Promise.all(a);i.kernelMs=v.sum(o),i.getExtraProfileInfo=()=>o.map((l,u)=>({name:s[u],ms:l})).map(l=>`${l.name}: ${l.ms}`).join(", ")}else i.kernelMs={error:"WebGL query timers are not supported in this environment."};return this.uploadWaitMs=0,this.downloadWaitMs=0,i})()}memory(){return{unreliable:!1,numBytesInGPU:this.numBytesInGPU,numBytesInGPUAllocated:this.textureManager.numBytesAllocated,numBytesInGPUFree:this.textureManager.numBytesFree}}startTimer(){return Z().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?this.gpgpu.beginQuery():{startMs:v.now(),endMs:null}}endTimer(e){return Z().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?(this.gpgpu.endQuery(),e):(e.endMs=v.now(),e)}async getQueryTime(e){if(Z().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0)return this.gpgpu.waitForQueryAndGetTime(e);let t=e;return t.endMs-t.startMs}disposeData(e,t=!1){if(this.pendingDisposal.has(e))return!1;if(!this.texData.has(e))return!0;if(t?this.texData.get(e).refCount=0:this.texData.get(e).refCount--,!t&&this.texData.get(e).refCount>0)return!1;if(this.pendingRead.has(e))return this.pendingDisposal.add(e),this.pendingDeletes++,!1;this.releaseGPUData(e);let{complexTensorInfos:r}=this.texData.get(e);return r!=null&&(this.disposeData(r.real.dataId,t),this.disposeData(r.imag.dataId,t)),this.texData.delete(e),!0}releaseGPUData(e){let{texture:t,dtype:r,texShape:n,usage:a,isPacked:s,slice:i}=this.texData.get(e),o=i&&i.origDataId||e,l=this.dataRefCount.get(o);l>1?this.dataRefCount.set(o,l-1):(this.dataRefCount.delete(o),t!=null&&(this.numBytesInGPU-=this.computeBytes(n,r),this.textureManager.releaseTexture(t,n,a,s)));let u=this.texData.get(e);u.texture=null,u.texShape=null,u.isPacked=!1,u.slice=null}getTexture(e){return this.uploadToGPU(e),this.texData.get(e).texture.texture}getDataInfo(e){return this.texData.get(e)}shouldExecuteOnCPU(e,t=Qte){return Z().getBool("WEBGL_CPU_FORWARD")&&e.every(r=>this.texData.get(r.dataId).texture==null&&v.sizeFromShape(r.shape)<t)}getGPGPUContext(){return this.gpgpu}where(e){C.warn("tf.where() in webgl locks the UI thread. Call tf.whereAsync() instead");let t=e.dataSync();return Kte(e.shape,t)}packedUnaryOp(e,t,r){let n=new Co(e.shape,t),a=this.compileAndRun(n,[e],r);return Xt().makeTensorFromTensorInfo(a)}abs(e){if(this.shouldExecuteOnCPU([e])&&e.dtype!=="complex64"){let n=pI(this.texData.get(e.dataId).values);return this.makeOutput(e.shape,e.dtype,n)}if(Z().getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(e,H4,e.dtype);let t=new Xa(e.shape,H4),r=this.compileAndRun(t,[e]);return Xt().makeTensorFromTensorInfo(r)}makeTensorInfo(e,t,r){let n;if(t==="string"&&r!=null&&r.length>0&&v.isString(r[0])){let a=r.map(s=>v.encodeString(s));n=this.write(a,e,t)}else n=this.write(r,e,t);return this.texData.get(n).usage=null,{dataId:n,shape:e,dtype:t}}makeOutput(e,t,r){return Xt().makeTensorFromTensorInfo(this.makeTensorInfo(e,t,r),this)}unpackTensor(e){let t=new Xte(e.shape);return this.runWebGLProgram(t,[e],e.dtype)}packTensor(e){let t=new $te(e.shape),r=!0;return this.runWebGLProgram(t,[e],e.dtype,null,r)}packedReshape(e,t){let r=[Lo(e.shape),...Bo(e.shape)],n={dtype:e.dtype,shape:r,dataId:e.dataId},a=[Lo(t),...Bo(t)],s=new fI(a,r),i=!0,o=[r],l=this.runWebGLProgram(s,[n],e.dtype,o,i);return{dataId:l.dataId,shape:t,dtype:l.dtype}}decode(e,t){let r=this.texData.get(e),{isPacked:n,shape:a,dtype:s}=r;if(t!=null){let h=v.sizeFromShape(a),p=t[0]*t[1]*4;v.assert(h<=p,()=>"customTexShape is too small. Row * Column * 4 should be equal or larger than the size of the tensor data.")}let i=y0(a),o;n?o=new Bee(i):o=new Lee(i);let l=!0,u=[t!=null?t:l0(i)],d=this.runWebGLProgram(o,[{shape:i,dtype:s,dataId:e}],s,u,l,t);return{dtype:s,shape:a,dataId:d.dataId}}runWebGLProgram(e,t,r,n,a=!1,s){let i=this.makeTensorInfo(e.outputShape,r),o=this.texData.get(i.dataId);if(e.packedOutput&&(o.isPacked=!0),e.outPackingScheme===0){let g=s!=null?s:l0(e.outputShape);o.texShape=g.map(y=>y*2)}if(e.outTexUsage!=null&&(o.usage=e.outTexUsage),v.sizeFromShape(i.shape)===0)return o.values=v.getTypedArrayFromDType(i.dtype,0),i;let l=[],u=t.map(g=>{if(g.dtype==="complex64")throw new Error("GPGPUProgram does not support complex64 input. For complex64 dtypes, please separate the program into real and imaginary parts.");let y=this.texData.get(g.dataId);if(y.texture==null){if(!e.packedInputs&&v.sizeFromShape(g.shape)<=Z().getNumber("WEBGL_SIZE_UPLOAD_UNIFORM"))return{shape:g.shape,texData:null,isUniform:!0,uniformValues:y.values};e.packedInputs&&(y.isPacked=!0,y.shape=g.shape)}if(this.uploadToGPU(g.dataId),!!y.isPacked!=!!e.packedInputs)g=y.isPacked?this.unpackTensor(g):this.packTensor(g),l.push(g),y=this.texData.get(g.dataId);else if(y.isPacked&&!Qp(y.shape,g.shape)){let A=g,x=g.shape;g.shape=y.shape,g=this.packedReshape(g,x),l.push(g),y=this.texData.get(g.dataId),A.shape=x}return{shape:g.shape,texData:y,isUniform:!1}});this.uploadToGPU(i.dataId);let d={shape:i.shape,texData:o,isUniform:!1},h=Dee(e,u,d),p=this.getAndSaveBinary(h,()=>Oee(this.gpgpu,e,u,d)),c=this.activeTimers!=null,m;c&&(m=this.startTimer()),Z().get("ENGINE_COMPILE_ONLY")||zee(this.gpgpu,p,u,d,n),l.forEach(g=>this.disposeIntermediateTensorInfo(g)),c&&(m=this.endTimer(m),this.activeTimers.push({name:e.constructor.name,query:this.getQueryTime(m)}));let f=Z().get("WEBGL_FLUSH_THRESHOLD");if(f>0){let g=v.now();g-this.lastGlFlushTime>f&&(this.gpgpu.gl.flush(),this.lastGlFlushTime=g)}if(!Z().getBool("WEBGL_LAZILY_UNPACK")&&o.isPacked&&a===!1){let g=this.unpackTensor(i);return this.disposeIntermediateTensorInfo(i),g}return i}compileAndRun(e,t,r,n,a=!1){return r=r||t[0].dtype,this.runWebGLProgram(e,t,r,n,a)}getAndSaveBinary(e,t){return e in this.binaryCache||(this.binaryCache[e]=t()),this.binaryCache[e]}getTextureManager(){return this.textureManager}dispose(){this.disposed||(Z().getBool("IS_TEST")||Object.keys(this.binaryCache).forEach(e=>{this.gpgpu.deleteProgram(this.binaryCache[e].webGLProgram),delete this.binaryCache[e]}),this.textureManager.dispose(),this.canvas!=null&&typeof HTMLCanvasElement!="undefined"&&this.canvas instanceof HTMLCanvasElement?this.canvas.remove():this.canvas=null,this.gpgpuCreatedLocally&&(this.gpgpu.program=null,this.gpgpu.dispose()),this.disposed=!0)}floatPrecision(){return this.floatPrecisionValue==null&&(this.floatPrecisionValue=X(()=>{if(!Z().get("WEBGL_RENDER_FLOAT32_ENABLED")){let e=Z().getBool("DEBUG");Z().set("DEBUG",!1);let t=this.abs(Se(1e-8)).dataSync()[0];if(Z().set("DEBUG",e),t>0)return 32}return 16})),this.floatPrecisionValue}epsilon(){return this.floatPrecision()===32?Zte:Yte}uploadToGPU(e){let t=this.texData.get(e),{shape:r,dtype:n,values:a,texture:s,usage:i,isPacked:o}=t;if(s!=null)return;let l=this.activeTimers!=null,u;l&&(u=v.now());let 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this.releaseGPUData(e),t!=null&&(r.values=rre(t,n)),r.values}acquireTexture(e,t,r,n){if(this.numBytesInGPU+=this.computeBytes(e,r),!this.warnedAboutMemory&&this.numBytesInGPU>this.numMBBeforeWarning*1024*1024){let a=(this.numBytesInGPU/1024/1024).toFixed(2);this.warnedAboutMemory=!0,console.warn(`High memory usage in GPU: ${a} MB, most likely due to a memory leak`)}return this.textureManager.acquireTexture(e,t,n)}computeBytes(e,t){return e[0]*e[1]*v.bytesPerElement(t)}checkCompileCompletion(){for(let[,e]of Object.entries(this.binaryCache))this.checkCompletion_(e)}async checkCompileCompletionAsync(){let e=[];if(this.gpgpu.parallelCompilationExtension){for(let[,t]of Object.entries(this.binaryCache))e.push(this.checkCompletionAsync_(t));return Promise.all(e)}else{for(let[,t]of Object.entries(this.binaryCache)){let r=new Promise(n=>{try{this.checkCompletion_(t),n(!0)}catch(a){throw a}});e.push(r)}return Promise.all(e)}}async checkCompletionAsync_(e){return this.gpgpu.gl.getProgramParameter(e.webGLProgram,this.gpgpu.parallelCompilationExtension.COMPLETION_STATUS_KHR)?this.checkCompletion_(e):(await N3(),this.checkCompletionAsync_(e))}checkCompletion_(e){if(this.gpgpu.gl.getProgramParameter(e.webGLProgram,this.gpgpu.gl.LINK_STATUS)===!1)throw console.log(this.gpgpu.gl.getProgramInfoLog(e.webGLProgram)),this.gpgpu.gl.getShaderParameter(e.fragmentShader,this.gpgpu.gl.COMPILE_STATUS)===!1?(bA(e.source,this.gpgpu.gl.getShaderInfoLog(e.fragmentShader)),new Error("Failed to compile fragment shader.")):new Error("Failed to link vertex and fragment shaders.");return!0}getUniformLocations(){for(let[,e]of Object.entries(this.binaryCache)){let{uniformLocations:t,customUniformLocations:r,infLoc:n,nanLoc:a,inShapesLocations:s,inTexShapesLocations:i,outShapeLocation:o,outShapeStridesLocation:l,outTexShapeLocation:u}=H9(this.gpgpu,e.program,e.webGLProgram);e.uniformLocations=t,e.customUniformLocations=r,e.infLoc=n,e.nanLoc=a,e.inShapesLocations=s,e.inTexShapesLocations=i,e.outShapeLocation=o,e.outShapeStridesLocation=l,e.outTexShapeLocation=u}}},qh=mI;qh.nextDataId=0;function rre(e,t){if(t==="float32"||t==="complex64")return e;if(t==="int32"||t==="bool"){let r=t==="int32"?new Int32Array(e.length):new Uint8Array(e.length);for(let n=0;n<r.length;++n)r[n]=Math.round(e[n]);return r}else throw new Error(`Unknown dtype ${t}`)}var nre="0.0.0";function gI(){Z().set("WEBGL_FORCE_F16_TEXTURES",!0)}kh.isBrowser()&&El("webgl",()=>new qh,2);var are={forceHalfFloat:gI},yI=`
if (isnan(a)) return a;
if (isnan(b)) return b;
`,Bu=class{constructor(e,t,r){this.variableNames=["A","B"],this.outputShape=C.assertAndGetBroadcastShape(t,r),this.enableShapeUniforms=un(this.outputShape.length),this.userCode=`
float binaryOperation(float a, float b) {
${e}
}
void main() {
float a = getAAtOutCoords();
float b = getBAtOutCoords();
setOutput(binaryOperation(a, b));
}
`}},_m=`
result.r = isNaN.r > 0. ? NAN : result.r;
result.g = isNaN.g > 0. ? NAN : result.g;
result.b = isNaN.b > 0. ? NAN : result.b;
result.a = isNaN.a > 0. ? NAN : result.a;
`,Xh=class{constructor(e,t,r,n=!1){this.variableNames=["A","B"],this.supportsBroadcasting=!0,this.packedInputs=!0,this.packedOutput=!0,this.outputShape=C.assertAndGetBroadcastShape(t,r);let a=this.outputShape.length;this.enableShapeUniforms=un(a);let s="";if(n)if(a===0||v.sizeFromShape(this.outputShape)===1)s=`
result.y = 0.;
result.z = 0.;
result.w = 0.;
`;else if(s=`
${vt(a)} coords = getOutputCoords();
`,a===1)this.enableShapeUniforms?s+=`
result.y = (coords + 1) >= outShape ? 0. : result.y;
result.z = 0.;
result.w = 0.;
`:s+=`
result.y = (coords + 1) >= ${this.outputShape[0]} ? 0. : result.y;
result.z = 0.;
result.w = 0.;
`;else{let i=Br("coords",a);this.enableShapeUniforms?s+=`
bool nextRowOutOfBounds =
(${i[a-2]} + 1) >= outShape[${a} - 2];
bool nextColOutOfBounds =
(${i[a-1]} + 1) >= outShape[${a} - 1];
result.y = nextColOutOfBounds ? 0. : result.y;
result.z = nextRowOutOfBounds ? 0. : result.z;
result.w = nextColOutOfBounds || nextRowOutOfBounds ? 0. : result.w;
`:s+=`
bool nextRowOutOfBounds =
(${i[a-2]} + 1) >= ${this.outputShape[a-2]};
bool nextColOutOfBounds =
(${i[a-1]} + 1) >= ${this.outputShape[a-1]};
result.y = nextColOutOfBounds ? 0. : result.y;
result.z = nextRowOutOfBounds ? 0. : result.z;
result.w = nextColOutOfBounds || nextRowOutOfBounds ? 0. : result.w;
`}this.userCode=`
vec4 binaryOperation(vec4 a, vec4 b) {
${e}
}
void main() {
vec4 a = getAAtOutCoords();
vec4 b = getBAtOutCoords();
vec4 result = binaryOperation(a, b);
${s}
setOutput(result);
}
`}};function mn(e){let{inputs:t,backend:r}=e,{x:n}=t;return r.incRef(n.dataId),{dataId:n.dataId,shape:n.shape,dtype:n.dtype}}var sre={kernelName:fi,backendName:"webgl",kernelFunc:mn};function ji(e){let{inputs:t,backend:r}=e,{real:n,imag:a}=t,s=r.makeTensorInfo(n.shape,"complex64"),i=r.texData.get(s.dataId),o=mn({inputs:{x:n},backend:r}),l=mn({inputs:{x:a},backend:r});return i.complexTensorInfos={real:o,imag:l},s}var ire={kernelName:ah,backendName:"webgl",kernelFunc:ji},AI="return (a < 0.) ? b * a : a;",xI=`
vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));
return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);
`;function ore(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{alpha:s}=n,i=r.makeTensorInfo([],"float32",v.createScalarValue(s,"float32")),o=Z().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new Xh(xI,a.shape,i.shape):new Bu(AI,a.shape,i.shape),l=r.runWebGLProgram(o,[a,i],"float32");return r.disposeIntermediateTensorInfo(i),l}var lre={kernelName:mi,backendName:"webgl",kernelFunc:ore},bI="return (a < 0.) ? b * a : a;",vI=`
vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));
return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);
`;function ure(e){let{inputs:t,backend:r}=e,{x:n,alpha:a}=t,s=Z().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new Xh(vI,n.shape,a.shape):new Bu(bI,n.shape,a.shape);return r.runWebGLProgram(s,[n,a],"float32")}var dre={kernelName:Ti,backendName:"webgl",kernelFunc:ure},_d="if (isnan(x)) return x;",pre=`
if (isnan(a)) return a;
if (isnan(b)) return b;
`,hre=`
result.r = isNaN.r > 0. ? NAN : result.r;
result.g = isNaN.g > 0. ? NAN : result.g;
result.b = isNaN.b > 0. ? NAN : result.b;
result.a = isNaN.a > 0. ? NAN : result.a;
`;function it({opSnippet:e,packedOpSnippet:t,cpuKernelImpl:r,dtype:n}){return({inputs:a,backend:s})=>{let{x:i}=a,o=s,l=n||i.dtype;if(o.shouldExecuteOnCPU([i])&&r!=null){let h=o.texData.get(i.dataId),p=r(h.values,l);return o.makeTensorInfo(i.shape,l,p)}let u=Z().getBool("WEBGL_PACK_UNARY_OPERATIONS")&&t!=null,d;return u?d=new Co(i.shape,t):d=new Xa(i.shape,e),o.runWebGLProgram(d,[i],l)}}function vr({opSnippet:e,packedOpSnippet:t,checkOutOfBounds:r=!1,supportsComplex:n=!1,cpuKernelImpl:a,dtype:s}){return({inputs:i,backend:o})=>{let{a:l,b:u}=i,d=o;if(n&&l.dtype==="complex64"){let m=d.texData.get(l.dataId),f=d.texData.get(u.dataId),[g,y]=[[m.complexTensorInfos.real,f.complexTensorInfos.real],[m.complexTensorInfos.imag,f.complexTensorInfos.imag]].map(x=>{let[b,w]=x,I={dataId:b.dataId,dtype:b.dtype,shape:l.shape},T={dataId:w.dataId,dtype:w.dtype,shape:u.shape},E=new Bu(e,l.shape,u.shape);return d.runWebGLProgram(E,[I,T],Tr(b.dtype,w.dtype))}),A=ji({inputs:{real:g,imag:y},backend:d});return d.disposeIntermediateTensorInfo(g),d.disposeIntermediateTensorInfo(y),A}let h=s||Tr(l.dtype,u.dtype);if((l.dtype==="string"||u.dtype==="string"||d.shouldExecuteOnCPU([l,u]))&&a!=null){let m=d.texData.get(l.dataId).values,f=d.texData.get(u.dataId).values,g=l.dtype==="string"?C.fromUint8ToStringArray(m):m,y=l.dtype==="string"?C.fromUint8ToStringArray(f):f,[A,x]=a(l.shape,u.shape,g,y,h),b=d.makeTensorInfo(x,h),w=d.texData.get(b.dataId);return w.values=A,b}let p=Z().getBool("WEBGL_PACK_BINARY_OPERATIONS")&&t!=null,c;return p?c=new Xh(t,l.shape,u.shape,r):c=new Bu(e,l.shape,u.shape),d.runWebGLProgram(c,[l,u],h)}}function Pm(e,t=!1){if(e==="linear")return t?Ute:Dte;if(e==="relu")return t?jte:Bte;if(e==="elu")return t?Gte:Lte;if(e==="relu6")return t?Hte:Wte;if(e==="prelu")return t?vI:bI;if(e==="leakyrelu")return t?xI:AI;if(e==="sigmoid")return t?qte:Vte;throw new Error(`Activation ${e} has not been implemented for the WebGL backend.`)}var wI=class{constructor(e,t,r,n=!1,a=!1,s=!1,i=null,o=!1,l=!1){this.variableNames=["matrixA","matrixB"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=r,this.enableShapeUniforms=un(this.outputShape.length);let u=n?e[1]:e[2],d=Math.ceil(u/2),h=n?"i * 2, rc.y":"rc.y, i * 2",p=a?"rc.z, i * 2":"i * 2, rc.z",c=n?["a.xxyy","a.zzww"]:["a.xxzz","a.yyww"],m=a?["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 A="rc.x",x="rc.x";e[0]<t[0]?A=`int(min(float(rc.x), ${e[0]-1}.))`:t[0]<e[0]&&(x=`int(min(float(rc.x), ${t[0]-1}.))`),this.userCode=`
${f}
// Don't use uniform for sharedDimensionPacked for performance.
const float sharedDimension = ${d}.0;
vec4 dot2x2ARowBCol(ivec3 rc) {
vec4 result = vec4(0);
for (int i = 0; i < ${d}; i++) {
int batchA = ${A};
int batchB = ${x};
vec4 a = getMatrixA(batchA, ${h});
vec4 b = getMatrixB(batchB, ${p});
// These swizzled products need to be separately added.
// See: https://github.com/tensorflow/tfjs/issues/1735
result += (${c[0]} * ${m[0]});
result += (${c[1]} * ${m[1]});
}
return result;
}
void main() {
ivec3 rc = getOutputCoords();
vec4 result = dot2x2ARowBCol(rc);
${y}
${g}
setOutput(result);
}
`}},q4={REAL:"return areal * breal - aimag * bimag;",IMAG:"return areal * bimag + aimag * breal;"},X4=class{constructor(e,t,r){this.variableNames=["AReal","AImag","BReal","BImag"],this.outputShape=C.assertAndGetBroadcastShape(t,r),this.userCode=`
float binaryOpComplex(
float areal, float aimag, float breal, float bimag) {
${e}
}
void main() {
float areal = getARealAtOutCoords();
float aimag = getAImagAtOutCoords();
float breal = getBRealAtOutCoords();
float bimag = getBImagAtOutCoords();
setOutput(binaryOpComplex(areal, aimag, breal, bimag));
}
`}},K4="return a * b;";function RA(e){let{inputs:t,backend:r}=e,{a:n,b:a}=t,s=C.upcastType(n.dtype,a.dtype);if(n.dtype==="complex64"){let o=r.texData.get(n.dataId),l=r.texData.get(a.dataId),u=new X4(q4.REAL,n.shape,a.shape),d=new X4(q4.IMAG,n.shape,a.shape),h=[{dataId:o.complexTensorInfos.real.dataId,dtype:o.complexTensorInfos.real.dtype,shape:n.shape},{dataId:o.complexTensorInfos.imag.dataId,dtype:o.complexTensorInfos.imag.dtype,shape:n.shape},{dataId:l.complexTensorInfos.real.dataId,dtype:l.complexTensorInfos.real.dtype,shape:a.shape},{dataId:l.complexTensorInfos.imag.dataId,dtype:l.complexTensorInfos.imag.dtype,shape:a.shape}],p=r.runWebGLProgram(u,h,"float32"),c=r.runWebGLProgram(d,h,"float32"),m=ji({inputs:{real:p,imag:c},backend:r});return r.disposeIntermediateTensorInfo(p),r.disposeIntermediateTensorInfo(c),m}if(r.shouldExecuteOnCPU([n,a])){let o=r.texData.get(n.dataId),l=r.texData.get(a.dataId),[u,d]=pte(n.shape,a.shape,o.values,l.values,s),h=r.makeTensorInfo(d,s),p=r.texData.get(h.dataId);return p.values=u,h}let i;return Z().getBool("WEBGL_PACK_BINARY_OPERATIONS")?i=new Xh(K4,n.shape,a.shape):i=new Bu(K4,n.shape,a.shape),r.runWebGLProgram(i,[n,a],s)}var cre={kernelName:Ii,backendName:"webgl",kernelFunc:RA};function fre(e,t,r){let n=[Lo(e.shape),...Bo(e.shape)],a={dtype:e.dtype,shape:n,dataId:e.dataId},s=[Lo(t),...Bo(t)],i=new fI(s,n),o=!0,l=[n],u=r.runWebGLProgram(i,[a],e.dtype,l,o);return{dataId:u.dataId,shape:t,dtype:u.dtype}}function Ae(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{shape:s}=n,i=r,o=v.sizeFromShape(a.shape),l=v.inferFromImplicitShape(s,o),u=v.sizeFromShape(l);v.assert(o===u,()=>`The new shape (${l}) has ${u} elements and the old shape (${a.shape}) has ${o} elements. The new shape and old shape must have the same number of elements.`);let d=i.texData.get(a.dataId);return d.isPacked&&!Qp(a.shape,l)&&!(d.texture!==null&&Qp(d.shape,l))?fre(a,l,i):(i.incRef(a.dataId),{dataId:a.dataId,shape:l,dtype:a.dtype})}var mre={kernelName:cl,backendName:"webgl",kernelFunc:Ae},Z4=class{constructor(e,t){this.variableNames=["x"];let{windowSize:r,batchSize:n,inSize:a,outSize:s}=e;this.outputShape=[n,s];let i=Math.floor(r/4)*4,o=r%4,l="sumValue += dot(values, ones);";if(t!=null){let d=1/t;l=`sumValue += dot(values * ${v.isInt(d)?d.toPrecision(2):d}, ones);`}let u="";a%r>0&&(u=`
if (inIdx < 0 || inIdx >= ${a}) {
return 0.0;
}
`),this.userCode=`
const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);
float getValue(int batch, int inIdx) {
${u}
return getX(batch, inIdx);
}
void main() {
ivec2 coords = getOutputCoords();
int batch = coords[0];
int outIdx = coords[1];
int inOffset = outIdx * ${r};
float sumValue = 0.0;
for (int i = 0; i < ${i}; i += 4) {
int inIdx = inOffset + i;
vec4 values = vec4(
getValue(batch, inIdx),
getValue(batch, inIdx + 1),
getValue(batch, inIdx + 2),
getValue(batch, inIdx + 3)
);
${l}
}
int inIdx = inOffset + ${i};
if (${o===1}) {
vec4 values = vec4(getValue(batch, inIdx), 0.0, 0.0, 0.0);
${l}
} else if (${o===2}) {
vec4 values = vec4(
getValue(batch, inIdx),
getValue(batch, inIdx + 1), 0.0, 0.0);
${l}
} else if (${o===3}) {
vec4 values = vec4(
getValue(batch, inIdx),
getValue(batch, inIdx + 1),
getValue(batch, inIdx + 2), 0.0);
${l}
}
setOutput(sumValue);
}
`}},gre=class{constructor(e,t){this.variableNames=["x"];let{windowSize:r,batchSize:n,inSize:a,outSize:s}=e;this.outputShape=[n,s];let i="0.0",o="";t==="prod"?i="1.0":t==="min"?(i="1.0 / 1e-20",o="min"):t==="max"&&(i="-1.0 / 1e-20",o="max");let l=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="sum"?l="sumValue":t==="prod"?l="prodValue":t==="all"?l="allValue":t==="any"&&(l="anyValue");let u=Math.floor(r/4)*4,d=r%4,h=`
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);
}
}
}
`,p="vec4";t==="all"?(i="1.0",h=`
bool reducedAllValue = all(values);
float floatedReducedAllValue = float(reducedAllValue);
allValue = float(allValue >= 1.0 && floatedReducedAllValue >= 1.0);
`,p="bvec4"):t==="any"&&(i="0.0",h=`
bool reducedAnyValue = any(values);
float floatedReducedAnyValue = float(reducedAnyValue);
anyValue = float(anyValue >= 1.0 || floatedReducedAnyValue >= 1.0);
`,p="bvec4");let c="";a%r>0&&(c=`
if (inIdx < 0 || inIdx >= ${a}) {
return initializationValue;
}
`),this.userCode=`
const float initializationValue = ${i};
const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);
float getValue(int batch, int inIdx) {
${c}
return getX(batch, inIdx);
}
void main() {
ivec2 coords = getOutputCoords();
int batch = coords[0];
int outIdx = coords[1];
int inOffset = outIdx * ${r};
vec4 minMaxValue = vec4(${i});
float prodValue = 1.0;
float sumValue = 0.0;
float allValue = 1.0;
float anyValue = 0.0;
for (int i = 0; i < ${u}; i += 4) {
int inIdx = inOffset + i;
${p} values = ${p}(
getValue(batch, inIdx),
getValue(batch, inIdx + 1),
getValue(batch, inIdx + 2),
getValue(batch, inIdx + 3)
);
${h}
}
int inIdx = inOffset + ${u};
if (${d===1}) {
${p} values = ${p}(
getValue(batch, inIdx),
initializationValue,
initializationValue,
initializationValue
);
${h}
} else if (${d===2}) {
${p} values = ${p}(
getValue(batch, inIdx),
getValue(batch, inIdx + 1),
initializationValue,
initializationValue
);
${h}
} else if (${d===3}) {
${p} values = ${p}(
getValue(batch, inIdx),
getValue(batch, inIdx + 1),
getValue(batch, inIdx + 2),
initializationValue
);
${h}
}
setOutput(${l});
}
`}};function yre(e){let t=[];for(;t.length===0||t[t.length-1].outSize!==1;){let r=t.length?t[t.length-1].outSize:e[1],n=C.computeOptimalWindowSize(r);t.push({inSize:r,windowSize:n,outSize:Math.ceil(r/n)})}return t}function Ll(e,t,r,n){let a=yre(e.shape),s=e;for(let i=0;i<a.length;i++){let{inSize:o,windowSize:l,outSize:u}=a[i],d,h;r==="mean"?d=i===0?new Z4({windowSize:l,inSize:o,batchSize:e.shape[0],outSize:u},o):new Z4({windowSize:l,inSize:o,batchSize:e.shape[0],outSize:u}):d=new gre({windowSize:l,inSize:o,batchSize:e.shape[0],outSize:u},r),h=s,s=n.runWebGLProgram(d,[s],t),h.dataId!==e.dataId&&n.disposeIntermediateTensorInfo(h)}return s}var Are=class{constructor(e,t){this.variableNames=["A"];let r=new Array(e.length);for(let s=0;s<r.length;s++)r[s]=e[t[s]];this.outputShape=r,this.rank=r.length;let n=vt(this.rank),a=xre(t);this.userCode=`
void main() {
${n} resRC = getOutputCoords();
setOutput(getA(${a}));
}
`}};function xre(e){let t=e.length;if(t>6)throw Error(`Transpose for rank ${t} is not yet supported`);let r=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u","resRC.v"],n=new Array(t);for(let a=0;a<e.length;a++)n[e[a]]=r[a];return n.join()}var bre=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0;let r=new Array(e.length);for(let u=0;u<r.length;u++)r[u]=e[t[u]];if(this.outputShape=r,this.rank=r.length,this.rank>6)throw Error(`Packed transpose for rank ${this.rank} is not yet supported.`);let n=vt(this.rank),a=cI("rc",this.rank),s=new Array(this.rank);for(let u=0;u<t.length;u++)s[t[u]]=a[u];let i=`vec2(${s.slice(-2).join()})`,o=`++${a[this.rank-1]} < ${r[this.rank-1]}`,l=`getChannel(getA(${s.join()}), ${i})`;this.userCode=`
void main() {
${n} rc = getOutputCoords();
vec4 result = vec4(0.);
result[0] = ${l};
if(${o}) {
result[1] = ${l};
}
--${a[this.rank-1]};
if(++${a[this.rank-2]} < ${r[this.rank-2]}) {
result[2] = ${l};
if(${o}) {
result[3] = ${l};
}
}
setOutput(result);
}
`}};function Om(e,t,r){let n=Z().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new bre(e.shape,t):new Are(e.shape,t);return r.runWebGLProgram(n,[e],e.dtype)}function vre(e,t,r,n){let a=t,s=e.shape.length,i=v.parseAxisParam(a,e.shape),o=i,l=C.getAxesPermutation(o,s),u=l!=null,d=e;u&&(d=Om(e,l,n),o=C.getInnerMostAxes(o.length,s)),C.assertAxesAreInnerMostDims("sum",o,s);let[h,p]=C.computeOutAndReduceShapes(d.shape,o),c=h;r&&(c=C.expandShapeToKeepDim(h,i));let m=v.sizeFromShape(p),f=v.sizeFromShape(e.shape)/m,g=Ae({inputs:{x:d},attrs:{shape:[f,m]},backend:n}),y=wh(e.dtype),A=Ll(g,y,"sum",n),x=Ae({inputs:{x:A},attrs:{shape:c},backend:n});return n.disposeIntermediateTensorInfo(g),n.disposeIntermediateTensorInfo(A),u&&n.disposeIntermediateTensorInfo(d),x}function zm(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{axis:s,keepDims:i}=n;return vre(a,s,i,r)}var wre={kernelName:Oi,backendName:"webgl",kernelFunc:zm};function Ur(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{perm:s}=n,i=r,o=a.shape.length,l=new Array(o);for(let d=0;d<l.length;d++)l[d]=a.shape[s[d]];let u;if(i.shouldExecuteOnCPU([a])){let d=i.texData.get(a.dataId).values,h=EA(d,a.shape,a.dtype,s,l);u=i.makeTensorInfo(l,a.dtype);let p=i.texData.get(u.dataId);p.values=h}else u=Om(a,s,i);return u}var kre={kernelName:Ma,backendName:"webgl",kernelFunc:Ur},kI=1e3;function J0({a:e,b:t,transposeA:r,transposeB:n,backend:a,bias:s=null,preluActivationWeights:i=null,leakyreluAlpha:o=0,activation:l=null}){let u=e.shape.length,d=t.shape.length,h=r?e.shape[u-2]:e.shape[u-1],p=n?t.shape[d-1]:t.shape[d-2],c=r?e.shape[u-1]:e.shape[u-2],m=n?t.shape[d-2]:t.shape[d-1],f=e.shape.slice(0,-2),g=t.shape.slice(0,-2),y=v.sizeFromShape(f),A=v.sizeFromShape(g),x=Rl.assertAndGetBroadcastShape(e.shape.slice(0,-2),t.shape.slice(0,-2)).concat([c,m]);v.assert(h===p,()=>`Error in matMul: inner shapes (${h}) and (${p}) of Tensors with shapes ${e.shape} and ${t.shape} and transposeA=${r} and transposeB=${n} must match.`);let b=r?[y,h,c]:[y,c,h],w=n?[A,m,p]:[A,p,m],I=Ae({inputs:{x:e},backend:a,attrs:{shape:b}}),T=Ae({inputs:{x:t},backend:a,attrs:{shape:w}}),E=[I,T],R=Math.max(y,A),O=r?I.shape[1]:I.shape[2],M=s!=null,S=i!=null,P=l==="leakyrelu",z=l!=null?Pm(l,!0):null,j=M||S||P||z!=null,K;if((c===1||m===1)&&O>kI&&j===!1){let Y=I,V=T;r&&(Y=Ur({inputs:{x:I},backend:a,attrs:{perm:[0,2,1]}}),E.push(Y)),n&&(V=Ur({inputs:{x:T},backend:a,attrs:{perm:[0,2,1]}}),E.push(V));let re=m!==1,Q=m===1,ie=Y;re&&(ie=Ae({inputs:{x:Y},backend:a,attrs:{shape:[R,O,1]}}),E.push(ie));let J=m===1?2:1,ae=V;Q&&(ae=Ae({inputs:{x:V},backend:a,attrs:{shape:[R,1,O]}}),E.push(ae));let de=RA({inputs:{a:ie,b:ae},backend:a});K=zm({inputs:{x:de},backend:a,attrs:{axis:J,keepDims:!0}}),E.push(de)}else{let Y=Tr(e.dtype,t.dtype),V=new wI(b,w,[R,c,m],r,n,M,z,S,P),re=[I,T];if(s!=null&&re.push(s),S&&re.push(i),P){let Q=a.makeTensorInfo([],"float32",v.createScalarValue(o,"float32"));re.push(Q),E.push(Q)}K=a.runWebGLProgram(V,re,Y)}let D=Ae({inputs:{x:K},backend:a,attrs:{shape:x}});E.push(K);for(let Y of E)a.disposeIntermediateTensorInfo(Y);return D}function Ire(e){let{inputs:t,backend:r,attrs:n}=e,{a,b:s,bias:i,preluActivationWeights:o}=t,{transposeA:l,transposeB:u,activation:d,leakyreluAlpha:h}=n;return J0({a,b:s,transposeA:l,transposeB:u,backend:r,bias:i,preluActivationWeights:o,leakyreluAlpha:h,activation:d})}var Sre={kernelName:_s,backendName:"webgl",kernelFunc:Ire},Y4="return abs(x);";function Cre(e){let{inputs:t,backend:r}=e,{x:n}=t;if(r.shouldExecuteOnCPU([n])&&n.dtype!=="complex64"){let s=r.texData.get(n.dataId),i=pI(s.values);return r.makeTensorInfo(n.shape,n.dtype,i)}let a;return Z().getBool("WEBGL_PACK_UNARY_OPERATIONS")?a=new Co(n.shape,Y4):a=new Xa(n.shape,Y4),r.runWebGLProgram(a,[n],n.dtype)}var Tre={kernelName:Go,backendName:"webgl",kernelFunc:Cre},Nre=Yn+`
if (abs(x) > 1.) {
return NAN;
}
return acos(x);
`,Ere=it({opSnippet:Nre}),Rre={kernelName:Uu,backendName:"webgl",kernelFunc:Ere},Mre=Yn+`
if (x < 1.0) return NAN;
return log(x + sqrt(x * x - 1.0));`,$re=it({opSnippet:Mre}),Fre={kernelName:Gu,backendName:"webgl",kernelFunc:$re},J4="return a + b;",_re=vr({opSnippet:J4,packedOpSnippet:J4,supportsComplex:!0,cpuKernelImpl:Hee}),Pre={kernelName:Ja,backendName:"webgl",kernelFunc:_re},Ore=class{constructor(e,t){this.outputShape=[],this.outputShape=e,this.variableNames=t.map((a,s)=>`T${s}`);let r=[];this.variableNames.forEach(a=>{r.push(`float v${a} = get${a}AtOutCoords();`)});let n=this.variableNames.map(a=>`v${a}`).join(" + ");this.userCode=`
void main() {
${r.join(`
`)}
float result = ${n};
setOutput(result);
}
`}},zre=class{constructor(e,t){this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.variableNames=t.map((a,s)=>`T${s}`);let r=[];this.variableNames.forEach(a=>{r.push(`vec4 v${a} = get${a}AtOutCoords();`)});let n=this.variableNames.map(a=>`v${a}`).join(" + ");this.userCode=`
void main() {
${r.join(`
`)}
vec4 result = ${n};
setOutput(result);
}
`}};function b0(e){let{inputs:t,backend:r}=e,n=t;if(n.length===1)return mn({inputs:{x:n[0]},backend:r});if(n.length>Z().get("WEBGL_MAX_TEXTURES_IN_SHADER")){let o=Math.floor(n.length/2),l=b0({inputs:n.slice(0,o),backend:r}),u=b0({inputs:n.slice(o),backend:r});return b0({inputs:[l,u],backend:r})}let a=n.map(o=>o.dtype).reduce((o,l)=>Tr(o,l)),s=n.map(o=>o.shape),i=Z().getBool("WEBGL_PACK")?new zre(n[0].shape,s):new Ore(n[0].shape,s);return r.runWebGLProgram(i,n,a)}var Dre={kernelName:Ks,backendName:"webgl",kernelFunc:b0};function Lre(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{axis:s,keepDims:i}=n,o=a.shape.length,l=v.parseAxisParam(s,a.shape),u=l,d=C.getAxesPermutation(u,o),h=a;d!=null&&(h=Ur({inputs:{x:a},backend:r,attrs:{perm:d}}),u=C.getInnerMostAxes(u.length,o)),C.assertAxesAreInnerMostDims("all",u,o);let[p,c]=C.computeOutAndReduceShapes(h.shape,u),m=v.sizeFromShape(c),f=Ae({inputs:{x:h},backend:r,attrs:{shape:[-1,m]}}),g=Ll(f,f.dtype,"all",r),y;if(i){let A=C.expandShapeToKeepDim(p,l);y=Ae({inputs:{x:g},backend:r,attrs:{shape:A}})}else y=Ae({inputs:{x:g},backend:r,attrs:{shape:p}});return r.disposeIntermediateTensorInfo(f),r.disposeIntermediateTensorInfo(g),d!=null&&r.disposeIntermediateTensorInfo(h),y}var Bre={kernelName:ju,backendName:"webgl",kernelFunc:Lre};function Wre(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{axis:s,keepDims:i}=n,o=a.shape.length,l=v.parseAxisParam(s,a.shape),u=l,d=C.getAxesPermutation(u,o),h=a;d!=null&&(h=Ur({inputs:{x:a},backend:r,attrs:{perm:d}}),u=C.getInnerMostAxes(u.length,o)),C.assertAxesAreInnerMostDims("any",u,o);let[p,c]=C.computeOutAndReduceShapes(h.shape,u),m=v.sizeFromShape(c),f=Ae({inputs:{x:h},backend:r,attrs:{shape:[-1,m]}}),g=Ll(f,f.dtype,"any",r),y;if(i){let A=C.expandShapeToKeepDim(p,l);y=Ae({inputs:{x:g},backend:r,attrs:{shape:A}})}else y=Ae({inputs:{x:g},backend:r,attrs:{shape:p}});return r.disposeIntermediateTensorInfo(f),r.disposeIntermediateTensorInfo(g),d!=null&&r.disposeIntermediateTensorInfo(h),y}var Vre={kernelName:Hu,backendName:"webgl",kernelFunc:Wre},Ure=class{constructor(e,t,r){this.variableNames=["A"];let{windowSize:n,batchSize:a,outSize:s}=e;r||this.variableNames.push("bestIndicesA"),this.outputShape=[a,s];let i=t==="max"?">":"<",o=r?"inOffset + i;":"round(getBestIndicesA(batch, inOffset + i));";this.userCode=`
void main() {
ivec2 coords = getOutputCoords();
int batch = coords[0];
int outIdx = coords[1];
int inOffset = outIdx * ${n};
int bestIndex = inOffset;
float bestValue = getA(batch, bestIndex);
for (int i = 0; i < ${n}; i++) {
int inIdx = ${o};
float candidate = getA(batch, inIdx);
if (candidate ${i} bestValue) {
bestValue = candidate;
bestIndex = inIdx;
}
}
setOutput(float(bestIndex));
}
`}},Gre=class{constructor(e,t,r,n){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,v.assert(e.length>2,()=>`Packed arg${r.charAt(0).toUpperCase()+r.slice(1)} supports only inputs with rank above 2.`);let a=e[e.length-1],s=Math.ceil(a/t);this.outputShape=e.slice(0,-1),s>1&&this.outputShape.push(s),n||this.variableNames.push("bestIndicesA");let i=this.outputShape,o=i.length,l=vt(o),u=Br("coords",o),d,h;if(s===1){h=o+1;let T=vt(h);d=`
${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 h=o,d=`
${l} sourceLocR = coords;
++${u[o-1]};
${l} sourceLocG = coords;
++${u[o-2]};
${l} sourceLocA = coords;
--${u[o-1]};
${l} sourceLocB = coords;
--${u[o-2]};`;let p=["x","y","z","w","u","v"].slice(0,h),c="."+p[h-1],m=p.map(T=>"int "+T),f=Br("sourceLocR",h-1).concat("inIdx.r"),g=Br("sourceLocG",h-1).concat("inIdx.g"),y=Br("sourceLocB",h-1).concat("inIdx.b"),A=Br("sourceLocA",h-1).concat("inIdx.a"),x=r==="max"?"greaterThan":"lessThan",b=n?"":`
inIdx = round(vec4(getBestIndicesAChannel(${f.join()}),
getBestIndicesAChannel(${g.join()}),
getBestIndicesAChannel(${y.join()}),
getBestIndicesAChannel(${A.join()})));`,w=`vec4(
getAChannel(${f.join()}),
hasNextCol ? getAChannel(${g.join()}) : 0.,
hasNextRow ? getAChannel(${y.join()}) : 0.,
hasNextRow && hasNextCol ? getAChannel(${A.join()}) : 0.)`,I=n?"":`
float getBestIndicesAChannel(${m.join()}) {
return getChannel(getBestIndicesA(${p.join()}),
vec2(${p.slice(-2).join()}));
}`;this.userCode=`
float getAChannel(${m.join()}) {
return getChannel(getA(${p.join()}),
vec2(${p.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};
${d}
ivec4 srcIdx = ivec4(sourceLocR${c}, sourceLocG${c},
sourceLocB${c}, sourceLocA${c}) * ${t};
ivec4 inIdx = srcIdx;
vec4 bestIndex = vec4(inIdx);
vec4 bestValue = ${w};
for (int i = 0; i < ${t}; i++) {
inIdx = srcIdx;
${b}
vec4 candidate = ${w};
bvec4 nan = isnan(candidate);
bvec4 replace = bvec4(
vec4(${x}(candidate, bestValue)) * (vec4(1.0) - vec4(nan)));
bestValue = vec4(replace.x ? candidate.x : bestValue.x,
replace.y ? candidate.y : bestValue.y,
replace.z ? candidate.z : bestValue.z,
replace.w ? candidate.w : bestValue.w);
bestIndex = mix(bestIndex, vec4(inIdx), vec4(replace));
srcIdx++;
}
setOutput(bestIndex);
}
`}};function II(e,t,r,n=null){let a=t.shape[0],s=t.shape[1];n!=null&&(a=n.shape[0],s=n.shape[1]);let i=C.computeOptimalWindowSize(s),o={windowSize:i,inSize:s,batchSize:a,outSize:Math.ceil(s/i)},l=new Ure(o,r,n==null),u=[t];n!=null&&u.push(n);let d=e.runWebGLProgram(l,u,"int32");if(d.shape[1]===1)return d;let h=II(e,t,r,d);return e.disposeIntermediateTensorInfo(d),h}function SI(e,t,r,n=null){let a=n!=null?n.shape:t.shape,s=a[a.length-1],i=C.computeOptimalWindowSize(s),o=new Gre(a,i,r,n==null),l=n==null?[t]:[t,n],u=e.runWebGLProgram(o,l,"int32");if(u.shape.length===t.shape.length){let d=SI(e,t,r,u);return e.disposeIntermediateTensorInfo(u),d}return u}function CI(e,t,r,n){let a=[r];if(C.assertAxesAreInnerMostDims("arg"+n.charAt(0).toUpperCase()+n.slice(1),a,t.shape.length),!Z().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,d]=C.computeOutAndReduceShapes(l.shape,a),h=v.sizeFromShape(d),p=Ae({inputs:{x:l},backend:e,attrs:{shape:[-1,h]}});s.push(p);let c=II(e,p,n);s.push(c);let m=Ae({inputs:{x:c},backend:e,attrs:{shape:u}});return s.forEach(f=>e.disposeIntermediateTensorInfo(f)),m}return SI(e,t,n)}function jre(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{axis:s}=n,i=v.parseAxisParam(s,a.shape),o=C.getAxesPermutation(i,a.shape.length),l=a,u=[];o!=null&&(l=Ur({inputs:{x:a},backend:r,attrs:{perm:o}}),u.push(l),i=C.getInnerMostAxes(i.length,l.shape.length)),C.assertAxesAreInnerMostDims("argMax",[i[0]],l.shape.length);let d=CI(r,l,i[0],"max");return u.forEach(h=>r.disposeIntermediateTensorInfo(h)),d}var Hre={kernelName:Zs,backendName:"webgl",kernelFunc:jre};function qre(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{axis:s}=n,i=v.parseAxisParam(s,a.shape),o=C.getAxesPermutation(i,a.shape.length),l=a,u=[];o!=null&&(l=Ur({inputs:{x:a},backend:r,attrs:{perm:o}}),u.push(l),i=C.getInnerMostAxes(i.length,l.shape.length)),C.assertAxesAreInnerMostDims("argMin",[i[0]],l.shape.length);let d=CI(r,l,i[0],"min");return u.forEach(h=>r.disposeIntermediateTensorInfo(h)),d}var Xre={kernelName:qu,backendName:"webgl",kernelFunc:qre},Kre=Yn+`
if (abs(x) > 1.) {
return NAN;
}
return asin(x);
`,Zre=it({opSnippet:Kre}),Yre={kernelName:Xu,backendName:"webgl",kernelFunc:Zre},Jre=Yn+"return log(x + sqrt(x * x + 1.0));",Qre=it({opSnippet:Jre}),ene={kernelName:Ku,backendName:"webgl",kernelFunc:Qre},tne=Yn+`
return atan(x);
`,rne=it({opSnippet:tne}),nne={kernelName:Zu,backendName:"webgl",kernelFunc:rne},ane=pre+`
return atan(a, b);
`,sne=`
vec4 result = atan(a, b);
vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
`+hre+`
return result;
`,ine=vr({opSnippet:ane,packedOpSnippet:sne}),one={kernelName:Ju,backendName:"webgl",kernelFunc:ine},lne=Yn+`
if ((x < -1.0) || (x > 1.0)) return NAN;
return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,une=it({opSnippet:lne}),dne={kernelName:Yu,backendName:"webgl",kernelFunc:une},eh=class{constructor(e,t,r,n=!1,a=!1){if(this.variableNames=["x"],t==="avg"&&r)throw new Error("Cannot compute positions for average pool.");let s=e.filterWidth,i=e.strideHeight,o=e.strideWidth,l=e.dilationHeight,u=e.dilationWidth,d=e.effectiveFilterHeight,h=e.effectiveFilterWidth,p=e.padInfo.top,c=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) * ${e.inChannels} + d`,y="0.0";if(m||(y="-1.0 / 1e-20"),r){let T=">=";this.userCode=`
const ivec2 strides = ivec2(${i}, ${o});
const ivec2 pads = ivec2(${p}, ${c});
void main() {
ivec4 coords = getOutputCoords();
int batch = coords[0];
int d = coords[3];
ivec2 xRCCorner = coords.yz * strides - pads;
int xRCorner = xRCCorner.x;
int xCCorner = xRCCorner.y;
// max/min x(?, ?, d) to get y(yR, yC, d).
// ? = to be determined
float minMaxValue = 0.0;
float minMaxValueFound = 0.0;
int minMaxPosition = 0;
float avgValue = 0.0;
for (int wR = 0; wR < ${d};
wR += ${l}) {
int xR = xRCorner + wR;
if (xR < 0 || xR >= ${e.inHeight}) {
continue;
}
for (int wC = 0; wC < ${h};
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?a?f:g:`wR * ${h} + wC`};
}
}
}
setOutput(float(minMaxPosition));
}
`;return}let A="max",x=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="avg"&&(x="avgValue / count");let b=Math.floor(s/4)*4,w=s%4,I=`
if (${m}) {
avgValue += dot(values, ones);
} else {
minMaxValue = ${A}(values, minMaxValue);
}
`;this.userCode=`
const ivec2 strides = ivec2(${i}, ${o});
const ivec2 pads = ivec2(${p}, ${c});
const float initializationValue = ${y};
const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);
float count = 0.0;
float getValue(int batch, int xR, int xC, int d) {
if (xC < 0 || xC >= ${e.inWidth}) {
return initializationValue;
}
count += 1.0;
return getX(batch, xR, xC, d);
}
void main() {
ivec4 coords = getOutputCoords();
int batch = coords[0];
int d = coords[3];
ivec2 xRCCorner = coords.yz * strides - pads;
int xRCorner = xRCCorner.x;
int xCCorner = xRCCorner.y;
// max/min x(?, ?, d) to get y(yR, yC, d).
// ? = to be determined
vec4 minMaxValue = vec4(${y});
float avgValue = 0.0;
count = 0.0;
for (int wR = 0; wR < ${d};
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
);
${I}
}
}
setOutput(${x});
}
`}},MA=class{constructor(e,t,r,n=!1,a=!1){if(this.variableNames=["x"],t==="avg"&&r)throw new Error("Cannot compute positions for average pool.");let s=e.filterWidth,i=e.strideDepth,o=e.strideHeight,l=e.strideWidth,u=e.dilationDepth,d=e.dilationHeight,h=e.dilationWidth,p=e.effectiveFilterDepth,c=e.effectiveFilterHeight,m=e.effectiveFilterWidth,f=e.padInfo.front,g=e.padInfo.top,y=e.padInfo.left;this.outputShape=e.outShape;let A=t==="avg",x="0.0";if(A||(x="-1.0 / 1e-20"),r){let R=">=";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 < ${p};
wD += ${u}) {
int xD = xDCorner + wD;
if (xD < 0 || xD >= ${e.inDepth}) {
continue;
}
for (int wR = 0; wR < ${c};
wR += ${d}) {
int xR = xRCorner + wR;
if (xR < 0 || xR >= ${e.inHeight}) {
continue;
}
for (int wC = 0; wC < ${m};
wC += ${h}) {
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 ${R} currMinMaxValue) {
minMaxValue = value;
minMaxValueFound = 1.0;
minMaxPosition = ${n?a?`(((batch * ${e.inDepth} + xD) * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + ch`:`((xD * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + ch`:`wD * ${c} * ${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 / count");let I=Math.floor(s/4)*4,T=s%4,E=`
if (${A}) {
avgValue += dot(values, ones);
} else {
minMaxValue = ${b}(values, minMaxValue);
}
`;this.userCode=`
const ivec3 strides =
ivec3(${i}, ${o}, ${l});
const ivec3 pads = ivec3(${f}, ${g}, ${y});
const float initializationValue = ${x};
const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);
float count = 0.0;
float getValue(int batch, int xD, int xR, int xC, int ch) {
if (xC < 0 || xC >= ${e.inWidth}) {
return initializationValue;
}
count += 1.0;
return getX(batch, xD, xR, xC, ch);
}
void main() {
ivec5 coords = getOutputCoords();
int batch = coords.x;
int ch = coords.u;
ivec3 xCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;
int xDCorner = xCorner.x;
int xRCorner = xCorner.y;
int xCCorner = xCorner.z;
// max/min x(?, ?, ?, d) to get y(yD, yR, yC, ch).
// ? = to be determined
vec4 minMaxValue = vec4(${x});
float avgValue = 0.0;
count = 0.0;
for (int wD = 0; wD < ${p};
wD += ${u}) {
int xD = xDCorner + wD;
if (xD < 0 || xD >= ${e.inDepth}) {
continue;
}
for (int wR = 0; wR < ${c};
wR += ${d}) {
int xR = xRCorner + wR;
if (xR < 0 || xR >= ${e.inHeight}) {
continue;
}
for (int wC = 0; wC < ${I}; wC += 4) {
int xC = xCCorner + wC * ${h};
vec4 values = vec4(
getValue(batch, xD, xR, xC, ch),
getValue(batch, xD, xR, xC + ${h}, ch),
getValue(batch, xD, xR, xC + 2 * ${h}, ch),
getValue(batch, xD, xR, xC + 3 * ${h}, ch)
);
${E}
}
int xC = xCCorner + ${I};
if (${T===1}) {
vec4 values = vec4(
getValue(batch, xD, xR, xC, ch),
initializationValue,
initializationValue,
initializationValue
);
${E}
} else if (${T===2}) {
vec4 values = vec4(
getValue(batch, xD, xR, xC, ch),
getValue(batch, xD, xR, xC + ${h}, ch),
initializationValue,
initializationValue
);
${E}
} else if (${T===3}) {
vec4 values = vec4(
getValue(batch, xD, xR, xC, ch),
getValue(batch, xD, xR, xC + ${h}, ch),
getValue(batch, xD, xR, xC + 2 * ${h}, ch),
initializationValue
);
${E}
}
}
setOutput(${w});
}
}
`}};function pne(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t;Ed(a,"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 d=C.computePool2DInfo(a.shape,s,i,u,o,l);if(d.filterWidth===1&&d.filterHeight===1&&v.arraysEqual(d.inShape,d.outShape))return mn({inputs:{x:a},backend:r});let h=new eh(d,"avg",!1);return r.runWebGLProgram(h,[a],"float32")}var hne={kernelName:Ys,backendName:"webgl",kernelFunc:pne};function cne(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{filterSize:s,strides:i,pad:o,dimRoundingMode:l,dataFormat:u}=n,d=[1,1,1],h=C.computePool3DInfo(a.shape,s,i,d,o,l,u),p=new MA(h,"avg",!1);return r.runWebGLProgram(p,[a],"float32")}var fne={kernelName:nh,backendName:"webgl",kernelFunc:cne},mne=class{constructor(e){this.variableNames=["dy"],this.outputShape=e.inShape;let t=e.filterHeight,r=e.filterWidth,n=e.strideHeight,a=e.strideWidth,s=e.dilationHeight,i=e.dilationWidth,o=e.effectiveFilterHeight,l=e.effectiveFilterWidth,u=o-1-e.padInfo.top,d=l-1-e.padInfo.left,h=1/(t*r);this.userCode=`
const ivec2 pads = ivec2(${u}, ${d});
const float avgMultiplier = float(${h});
void main() {
ivec4 coords = getOutputCoords();
int b = coords[0];
int d = coords[3];
ivec2 dyRCCorner = coords.yz - pads;
int dyRCorner = dyRCCorner.x;
int dyCCorner = dyRCCorner.y;
// Convolve dy(?, ?, d) with pos mask(:, :, d) to get dx(xR, xC, d).
// ? = to be determined. : = across all values in that axis.
float dotProd = 0.0;
for (int wR = 0; wR < ${o};
wR += ${s}) {
float dyR = float(dyRCorner + wR) / ${n}.0;
if (dyR < 0.0 || dyR >= ${e.outHeight}.0 || fract(dyR) > 0.0) {
continue;
}
int idyR = int(dyR);
for (int wC = 0; wC < ${l};
wC+= ${i}) {
float dyC = float(dyCCorner + wC) / ${a}.0;
if (dyC < 0.0 || dyC >= ${e.outWidth}.0 ||
fract(dyC) > 0.0) {
continue;
}
int idyC = int(dyC);
float dyValue = getDy(b, idyR, idyC, d);
dotProd += dyValue * avgMultiplier;
}
}
setOutput(dotProd);
}
`}},gne=class{constructor(e){this.variableNames=["dy"],this.outputShape=e.inShape;let t=e.filterDepth,r=e.filterHeight,n=e.filterWidth,a=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=e.dilationDepth,l=e.dilationHeight,u=e.dilationWidth,d=e.effectiveFilterDepth,h=e.effectiveFilterHeight,p=e.effectiveFilterWidth,c=d-1-e.padInfo.front,m=h-1-e.padInfo.top,f=p-1-e.padInfo.left,g=1/(t*r*n);this.userCode=`
const ivec3 pads = ivec3(${c}, ${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 < ${d};
wD += ${o}) {
float dyD = float(dyDCorner + wD) / ${a}.0;
if (dyD < 0.0 || dyD >= ${e.outDepth}.0 || fract(dyD) > 0.0) {
continue;
}
int idyD = int(dyD);
for (int wR = 0; wR < ${h};
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 < ${p};
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 yne(e){let{inputs:t,backend:r,attrs:n}=e,{dy:a,input:s}=t,i=s,{filterSize:o,strides:l,pad:u,dimRoundingMode:d}=n,h=[1,1,1],p=C.computePool3DInfo(i.shape,o,l,h,u,d),c=new gne(p);return r.runWebGLProgram(c,[a],i.dtype)}var Ane={kernelName:uf,backendName:"webgl",kernelFunc:yne};function xne(e){let{inputs:t,backend:r,attrs:n}=e,{dy:a,input:s}=t,i=s;Ed([a,s],"avgPoolGrad");let{filterSize:o,strides:l,pad:u}=n,d=C.computePool2DInfo(i.shape,o,l,1,u),h=new mne(d);return r.runWebGLProgram(h,[a],i.dtype)}var bne={kernelName:lf,backendName:"webgl",kernelFunc:xne};function vne(e){let{inputs:t,backend:r,attrs:n}=e,{a,b:s}=t,{transposeA:i,transposeB:o}=n;return J0({a,b:s,transposeA:i,transposeB:o,backend:r})}var wne={kernelName:Js,backendName:"webgl",kernelFunc:vne},kne=class{constructor(e,t,r,n,a,s){this.outputShape=[],this.variableNames=["x","mean","variance"],C.assertAndGetBroadcastShape(e,t),C.assertAndGetBroadcastShape(e,r);let i="0.0";n!=null&&(C.assertAndGetBroadcastShape(e,n),this.variableNames.push("offset"),i="getOffsetAtOutCoords()");let o="1.0";a!=null&&(C.assertAndGetBroadcastShape(e,a),this.variableNames.push("scale"),o="getScaleAtOutCoords()"),this.outputShape=e,this.userCode=`
void main() {
float x = getXAtOutCoords();
float mean = getMeanAtOutCoords();
float variance = getVarianceAtOutCoords();
float offset = ${i};
float scale = ${o};
float inv = scale * inversesqrt(variance + float(${s}));
setOutput(dot(vec3(x, -mean, offset), vec3(inv, inv, 1)));
}
`}},Ine=class{constructor(e,t,r,n,a,s){this.packedInputs=!0,this.packedOutput=!0,this.variableNames=["x","mean","variance"],C.assertAndGetBroadcastShape(e,t),C.assertAndGetBroadcastShape(e,r);let i="vec4(0.0)";n!=null&&(C.assertAndGetBroadcastShape(e,n),this.variableNames.push("offset"),i="getOffsetAtOutCoords()");let o="vec4(1.0)";a!=null&&(C.assertAndGetBroadcastShape(e,a),this.variableNames.push("scale"),o="getScaleAtOutCoords()"),this.outputShape=e,this.userCode=`
void main() {
vec4 offset = ${i};
vec4 scale = ${o};
vec4 x = getXAtOutCoords();
vec4 mean = getMeanAtOutCoords();
vec4 variance = getVarianceAtOutCoords();
vec4 inv = scale * inversesqrt(variance + vec4(${s}));
setOutput((x - mean) * inv + offset);
}
`}},Sne=({inputs:e,backend:t,attrs:r})=>{let{x:n,mean:a,variance:s,offset:i,scale:o}=e;v.assert(a.shape.length===s.shape.length,()=>"Batch normalization gradient requires mean and variance to have equal ranks."),v.assert(i==null||a.shape.length===i.shape.length,()=>"Batch normalization gradient requires mean and offset to have equal ranks."),v.assert(o==null||a.shape.length===o.shape.length,()=>"Batch normalization gradient requires mean and scale to have equal ranks.");let{varianceEpsilon:l}=r;l==null&&(l=.001);let u=[n,a,s],d=null;i!=null&&(d=i.shape,u.push(i));let h=null;o!=null&&(h=o.shape,u.push(o));let p=Z().getBool("WEBGL_PACK_NORMALIZATION")?new Ine(n.shape,a.shape,s.shape,d,h,l):new kne(n.shape,a.shape,s.shape,d,h,l);return t.runWebGLProgram(p,u,u[0].dtype)},Cne={kernelName:hi,backendName:"webgl",kernelFunc:Sne},Tne=class{constructor(e){this.variableNames=["source"],this.outputShape=e,this.rank=e.length;let t=vt(this.rank);this.customUniforms=[{name:"start",arrayIndex:this.rank,type:"int"}];let r=Nne(this.rank),n,a=e.map((s,i)=>`sourceLoc.${cy[i]} = start[${i}] + coords.${cy[i]};`);n=`
${t} sourceLoc;
${t} coords = getOutputCoords();
${a.join(`
`)}
`,this.userCode=`
void main() {
${n}
setOutput(getSource(${r}));
}
`}},cy=["x","y","z","w","u","v"];function Nne(e){if(e===1)return"sourceLoc";if(e<=6)return cy.slice(0,e).map(t=>"sourceLoc."+t).join(",");throw Error(`Slicing for rank ${e} is not yet supported`)}var Ene=class{constructor(e){this.variableNames=["source"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.rank=e.length,this.customUniforms=[{name:"start",arrayIndex:this.rank,type:"int"}];let t=vt(this.rank),r=Br("coords",this.rank),n=Br("sourceLoc",this.rank),a=this.rank===1?"sourceLoc":`vec2(${n.slice(-2).join()})`,s=`getChannel(getSource(${n.join()}), ${a})`,i=`
result.x = ${s};
if (++${r[this.rank-1]} < ${e[this.rank-1]}) {
++${n[this.rank-1]};
result.y = ${s};
--${n[this.rank-1]};
}
`,o=this.rank===1?"":`
--${r[this.rank-1]};
if (++${r[this.rank-2]} < ${e[this.rank-2]}) {
++${n[this.rank-2]};
result.z = ${s};
if (++${r[this.rank-1]} < ${e[this.rank-1]}) {
++${n[this.rank-1]};
result.w = ${s};
}
}
`,l=this.rank<=4?`sourceLoc = coords +
${t}(${e.map((u,d)=>`start[${d}]`).join()});`:e.map((u,d)=>`${n[d]} = ${r[d]} + start[${d}];`).join(`
`);this.userCode=`
void main() {
${t} coords = getOutputCoords();
${t} sourceLoc;
${l}
vec4 result = vec4(0.);
${i}
${o}
setOutput(result);
}
`}};function Rne(e,t,r,n){let a=n.texData.get(e.dataId),s=n.makeTensorInfo(r,e.dtype),i=n.texData.get(s.dataId);Object.assign(i,a),i.refCount=1,i.shape=r,i.dtype=e.dtype;let o=Dt.computeFlatOffset(t,v.computeStrides(e.shape));a.slice&&(o+=a.slice.flatOffset),i.slice={flatOffset:o,origDataId:a.slice&&a.slice.origDataId||e.dataId};let l=n.dataRefCount.get(i.slice.origDataId)||1;return n.dataRefCount.set(i.slice.origDataId,l+1),s}function Pd(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{begin:s,size:i}=n,[o,l]=Dt.parseSliceParams(a,s,i);if(Dt.assertParamsValid(a,o,l),v.sizeFromShape(l)===0)return r.makeTensorInfo(l,a.dtype,[]);if(r.shouldExecuteOnCPU([a])||a.dtype==="string"){let h=r.texData.get(a.dataId),p=xte(h.values,o,l,a.shape,a.dtype);return r.makeTensorInfo(l,a.dtype,p)}let{isPacked:u}=r.texData.get(a.dataId),d=Dt.isSliceContinous(a.shape,o,l);if(u||!d){let h=Z().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new Ene(l):new Tne(l),p=[o];return r.runWebGLProgram(h,[a],a.dtype,p)}return r.uploadToGPU(a.dataId),Rne(a,o,l,r)}var Mne={kernelName:Al,backendName:"webgl",kernelFunc:Pd},$ne=e=>{let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{blockShape:s,crops:i}=n;v.assert(a.shape.length<=4,()=>"batchToSpaceND for rank > 4 with a WebGL backend not implemented yet");let o=s.reduce((A,x)=>A*x),l=C.getReshaped(a.shape,s,o),u=C.getPermuted(l.length,s.length),d=C.getReshapedPermuted(a.shape,s,o),h=C.getSliceBeginCoords(i,s.length),p=C.getSliceSize(d,i,s.length),c=[],m=Ae({inputs:{x:a},backend:r,attrs:{shape:l}}),f=Ur({inputs:{x:m},backend:r,attrs:{perm:u}}),g=Ae({inputs:{x:f},backend:r,attrs:{shape:d}}),y=Pd({inputs:{x:g},backend:r,attrs:{begin:h,size:p}});return c.push(m),c.push(f),c.push(g),c.forEach(A=>r.disposeIntermediateTensorInfo(A)),y},Fne={kernelName:jo,backendName:"webgl",kernelFunc:$ne};function _ne(e){let{inputs:t,backend:r,attrs:n}=e,{x:a,weights:s}=t,{size:i}=n,o=r.readSync(a.dataId),l=r.readSync(s.dataId),u=dI(o,l,s.dtype,s.shape,i);return r.makeTensorInfo([i],s.dtype,u)}var Pne={kernelName:df,backendName:"webgl",kernelFunc:_ne};function One(e){let{inputs:t,backend:r}=e,{s0:n,s1:a}=t,s=r.readSync(n.dataId),i=r.readSync(a.dataId),o=C.assertAndGetBroadcastShape(Array.from(s),Array.from(i));return r.makeTensorInfo([o.length],"int32",Int32Array.from(o))}var zne={kernelName:pf,backendName:"webgl",kernelFunc:One},Dne="return float(a != b);",TI=vr({opSnippet:Dne,cpuKernelImpl:cte,dtype:"bool"}),Lne={kernelName:ol,backendName:"webgl",kernelFunc:TI};function Kh(e){let{inputs:t,backend:r}=e,{input:n}=t,a=r.texData.get(n.dataId);return mn({inputs:{x:a.complexTensorInfos.real},backend:r})}var Bne={kernelName:ch,backendName:"webgl",kernelFunc:Kh},Wne="return float(int(x));";function Vne(e,t){let r=new Xa(e.shape,Wne),n=t.runWebGLProgram(r,[e],"int32");return{dataId:n.dataId,shape:n.shape,dtype:n.dtype}}function fy(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{dtype:s}=n;if(s==="complex64"){if(a.dtype==="complex64")return mn({inputs:{x:a},backend:r});let i=Ot(a.shape),o=fy({inputs:{x:a},backend:r,attrs:{dtype:"float32"}}),l=ji({inputs:{real:o,imag:i},backend:r});return i.dispose(),r.disposeIntermediateTensorInfo(o),l}if(a.dtype==="complex64"){let i=Kh({inputs:{input:a},backend:r}),o=fy({inputs:{x:i},backend:r,attrs:{dtype:s}});return r.disposeIntermediateTensorInfo(i),o}if(!v.hasEncodingLoss(a.dtype,s)){let i=mn({inputs:{x:a},backend:r});return{dataId:i.dataId,shape:i.shape,dtype:s}}if(s==="int32")return Vne(a,r);if(s==="bool"){let i=r.makeTensorInfo([],"bool",v.getTypedArrayFromDType("bool",1)),o=TI({inputs:{a,b:i},backend:r});return r.disposeIntermediateTensorInfo(i),o}throw new Error(`Error in Cast: failed to cast ${a.dtype} to ${s}`)}var Une={kernelName:Qs,backendName:"webgl",kernelFunc:fy},Q4="return ceil(x);",Gne=it({opSnippet:Q4,packedOpSnippet:Q4,cpuKernelImpl:Xee}),jne={kernelName:ei,backendName:"webgl",kernelFunc:Gne},Hne=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));
}
`}},qne=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 Xne(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{clipValueMin:s,clipValueMax:i}=n,o;Z().getBool("WEBGL_PACK_CLIP")?o=new qne(a.shape):o=new Hne(a.shape);let l=[[s],[i]];return r.runWebGLProgram(o,[a],a.dtype,l)}var Kne={kernelName:Qa,backendName:"webgl",kernelFunc:Xne},Zne=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 e7(e,t){return{dataId:t.dataId,dtype:t.dtype,shape:e.shape}}function Yne(e){let{inputs:t,backend:r}=e,{x:n}=t,a=r.texData.get(n.dataId),s=new Zne(n.shape),i=[e7(n,a.complexTensorInfos.real),e7(n,a.complexTensorInfos.imag)];return r.runWebGLProgram(s,i,i[0].dtype)}var Jne={kernelName:sh,backendName:"webgl",kernelFunc:Yne},Qne=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 r=[`if (yC < ${t[0]}) setOutput(getT0(yR, yC));`];for(let s=1;s<t.length;s++){let i=t[s-1];r.push(`else if (yC < ${t[s]}) setOutput(getT${s}(yR, yC-${i}));`)}let n=t.length,a=t[t.length-1];r.push(`else setOutput(getT${n}(yR, yC-${a}));`),this.userCode=`
void main() {
ivec2 coords = getOutputCoords();
int yR = coords.x;
int yC = coords.y;
${r.join(`
`)}
}
`}},eae=class{constructor(e,t){this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[],this.outputShape=C.computeOutShape(e,t);let r=this.outputShape,n=r.length,a=vt(n),s=Br("coords",n),i=["x","y","z","w","u","v"].slice(0,n);this.variableNames=e.map((m,f)=>`T${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),d=i.join(),h=`if (${l} < ${o[0]}) {
return getChannel(
getT0(${d}), vec2(${u.join()}));
}`;for(let m=1;m<o.length;m++){let f=o[m-1];h+=`
if (${l} < ${o[m]} && ${l} >= ${o[m-1]}) {
return getChannel(
getT${m}(${d0(i,l,f)}),
vec2(${d0(u,l,f)}));
}`}let p=o.length,c=o[o.length-1];h+=`
return getChannel(
getT${p}(${d0(i,l,c)}),
vec2(${d0(u,l,c)}));`,this.userCode=`
float getValue(${i.map(m=>"int "+m)}) {
${h}
}
void main() {
${a} coords = getOutputCoords();
vec4 result = vec4(getValue(${s}), 0., 0., 0.);
${s[n-1]} = ${s[n-1]} + 1;
if (${s[n-1]} < ${r[n-1]}) {
result.g = getValue(${s});
}
${s[n-2]} = ${s[n-2]} + 1;
if (${s[n-2]} < ${r[n-2]}) {
result.a = getValue(${s});
}
${s[n-1]} = ${s[n-1]} - 1;
if (${s[n-2]} < ${r[n-2]} &&
${s[n-1]} < ${r[n-1]}) {
result.b = getValue(${s});
}
setOutput(result);
}
`}};function d0(e,t,r){let n=e.indexOf(t);return e.map((a,s)=>s===n?`${a} - ${r}`:a).join()}function Dm(e){let{inputs:t,backend:r}=e,{input:n}=t,a=r.texData.get(n.dataId);return mn({inputs:{x:a.complexTensorInfos.imag},backend:r})}var tae={kernelName:uh,backendName:"webgl",kernelFunc:Dm};function Au(e,t,r){let n=e[0].dtype;if(n==="complex64"){let d=e.map(f=>Kh({inputs:{input:f},backend:r})),h=e.map(f=>Dm({inputs:{input:f},backend:r})),p=Au(d,t,r),c=Au(h,t,r),m=ji({inputs:{real:p,imag:c},backend:r});return d.forEach(f=>r.disposeIntermediateTensorInfo(f)),h.forEach(f=>r.disposeIntermediateTensorInfo(f)),r.disposeIntermediateTensorInfo(p),r.disposeIntermediateTensorInfo(c),m}let a=r.shouldExecuteOnCPU(e);if(n==="string"&&(a=!0),a){let d=e.map(y=>{let A=v.sizeFromShape(y.shape.slice(t));return Ae({inputs:{x:y},backend:r,attrs:{shape:[-1,A]}})}),h=d.map(y=>({vals:r.readSync(y.dataId),shape:y.shape})),p=C.computeOutShape(d.map(y=>y.shape),1),c=d[0].shape[0]===1,m=Kee(h,p,n,c),f=C.computeOutShape(e.map(y=>y.shape),t),g=r.makeTensorInfo(f,n,m);return d.forEach(y=>r.disposeIntermediateTensorInfo(y)),g}if(e.length>Z().getNumber("WEBGL_MAX_TEXTURES_IN_SHADER")){let d=Math.floor(e.length/2),h=Au(e.slice(0,d),t,r),p=Au(e.slice(d),t,r),c=Au([h,p],t,r);return r.disposeIntermediateTensorInfo(h),r.disposeIntermediateTensorInfo(p),c}if(Z().getBool("WEBGL_PACK_ARRAY_OPERATIONS")&&e[0].shape.length>1){let d=new eae(e.map(h=>h.shape),t);return r.runWebGLProgram(d,e,n)}let{tensors2D:s,outShape:i}=rae(e,t,r),o=new Qne(s.map(d=>d.shape)),l=r.runWebGLProgram(o,s,n);s.forEach(d=>r.disposeIntermediateTensorInfo(d));let u=Ae({inputs:{x:l},attrs:{shape:i},backend:r});return r.disposeIntermediateTensorInfo(l),u}function rae(e,t,r){let n=C.computeOutShape(e.map(a=>a.shape),t);return{tensors2D:e.map(a=>Ae({inputs:{x:a},attrs:{shape:[-1,v.sizeFromShape(a.shape.slice(t))]},backend:r})),outShape:n}}function NI(e){let{inputs:t,backend:r,attrs:n}=e,{axis:a}=n,s=v.parseAxisParam(a,t[0].shape)[0],i=C.computeOutShape(t.map(u=>u.shape),s);if(v.sizeFromShape(i)===0)return r.makeTensorInfo(i,t[0].dtype,[]);let o=t.filter(u=>v.sizeFromShape(u.shape)>0);if(o.length===1)return mn({inputs:{x:o[0]},backend:r});let l=o.map(u=>u.shape);return C.assertParamsConsistent(l,s),Au(o,s,r)}var nae={kernelName:Ho,backendName:"webgl",kernelFunc:NI},EI=class{constructor(e,t=!1,r=null,n=!1,a=!1){this.variableNames=["x","W"],this.outputShape=e.outShape;let s=e.padInfo.top,i=e.padInfo.left,o=e.strideHeight,l=e.strideWidth,u=e.dilationHeight,d=e.dilationWidth,h=e.filterHeight,p=e.filterWidth,c=Math.floor(e.inChannels/4)*4,m=e.inChannels%4,f=e.dataFormat==="channelsLast",g=f?1:2,y=f?2:3,A=f?3:1,x="",b="";r&&(n?x=`float activation(float a) {
float b = getPreluActivationWeightsAtOutCoords();
${r}
}`:a?x=`float activation(float a) {
float b = getLeakyreluAlphaAtOutCoords();
${r}
}`:x=`
float activation(float x) {
${r}
}
`,b="result = activation(result);");let w=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),n&&this.variableNames.push("preluActivationWeights"),a&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
${x}
const ivec2 strides = ivec2(${o}, ${l});
const ivec2 pads = ivec2(${s}, ${i});
void main() {
ivec4 coords = getOutputCoords();
int batch = coords[0];
int d2 = coords[${A}];
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 < ${h}; wR++) {
int xR = xRCorner + wR * ${u};
if (xR < 0 || xR >= ${e.inHeight}) {
continue;
}
for (int wC = 0; wC < ${p}; wC++) {
int xC = xCCorner + wC * ${d};
if (xC < 0 || xC >= ${e.inWidth}) {
continue;
}
for (int d1 = 0; d1 < ${c}; d1 += 4) {
vec4 wValues = vec4(
getW(wR, wC, d1, d2),
getW(wR, wC, d1 + 1, d2),
getW(wR, wC, d1 + 2, d2),
getW(wR, wC, d1 + 3, d2)
);
if (${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, ${c}) *
getW(wR, wC, ${c}, d2);
} else {
dotProd +=
getX(batch, ${c}, xR, xC) *
getW(wR, wC, ${c}, d2);
}
} else if (${m===2}) {
vec2 wValues = vec2(
getW(wR, wC, ${c}, d2),
getW(wR, wC, ${c} + 1, d2)
);
if (${f}) {
vec2 xValues = vec2(
getX(batch, xR, xC, ${c}),
getX(batch, xR, xC, ${c} + 1)
);
dotProd += dot(xValues, wValues);
} else {
vec2 xValues = vec2(
getX(batch, ${c}, xR, xC),
getX(batch, ${c} + 1, xR, xC)
);
dotProd += dot(xValues, wValues);
}
} else if (${m===3}) {
vec3 wValues = vec3(
getW(wR, wC, ${c}, d2),
getW(wR, wC, ${c} + 1, d2),
getW(wR, wC, ${c} + 2, d2)
);
if (${f}) {
vec3 xValues = vec3(
getX(batch, xR, xC, ${c}),
getX(batch, xR, xC, ${c} + 1),
getX(batch, xR, xC, ${c} + 2)
);
dotProd += dot(xValues, wValues);
} else {
vec3 xValues = vec3(
getX(batch, ${c}, xR, xC),
getX(batch, ${c} + 1, xR, xC),
getX(batch, ${c} + 2, xR, xC)
);
dotProd += dot(xValues, wValues);
}
}
}
}
float result = dotProd;
${w}
${b}
setOutput(result);
}
`}},aae=class{constructor(e){this.variableNames=["x","W"],this.outputShape=e.outShape;let t=e.padInfo.front,r=e.padInfo.top,n=e.padInfo.left,a=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=e.dilationDepth,l=e.dilationHeight,u=e.dilationWidth,d=e.filterDepth,h=e.filterHeight,p=e.filterWidth,c=Math.floor(e.inChannels/4)*4,m=e.inChannels%4;this.userCode=`
const ivec3 strides = ivec3(${a}, ${s}, ${i});
const ivec3 pads = ivec3(${t}, ${r}, ${n});
void main() {
ivec5 coords = getOutputCoords();
int batch = coords.x;
int d2 = coords.u;
ivec3 xFRCCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;
int xFCorner = xFRCCorner.x;
int xRCorner = xFRCCorner.y;
int xCCorner = xFRCCorner.z;
// Convolve x(?, ?, ?, d1) with w(:, :, :, d1, d2) to get
// y(yF, yR, yC, d2). ? = to be determined. : = across all
// values in that axis.
float dotProd = 0.0;
for (int wF = 0; wF < ${d}; wF++) {
int xF = xFCorner + wF * ${o};
if (xF < 0 || xF >= ${e.inDepth}) {
continue;
}
for (int wR = 0; wR < ${h}; wR++) {
int xR = xRCorner + wR * ${l};
if (xR < 0 || xR >= ${e.inHeight}) {
continue;
}
for (int wC = 0; wC < ${p}; wC++) {
int xC = xCCorner + wC * ${u};
if (xC < 0 || xC >= ${e.inWidth}) {
continue;
}
for (int d1 = 0; d1 < ${c}; d1 += 4) {
vec4 xValues = vec4(
getX(batch, xF, xR, xC, d1),
getX(batch, xF, xR, xC, d1 + 1),
getX(batch, xF, xR, xC, d1 + 2),
getX(batch, xF, xR, xC, d1 + 3)
);
vec4 wValues = vec4(
getW(wF, wR, wC, d1, d2),
getW(wF, wR, wC, d1 + 1, d2),
getW(wF, wR, wC, d1 + 2, d2),
getW(wF, wR, wC, d1 + 3, d2)
);
dotProd += dot(xValues, wValues);
}
if (${m===1}) {
dotProd +=
getX(batch, xF, xR, xC, ${c}) *
getW(wF, wR, wC, ${c}, d2);
} else if (${m===2}) {
vec2 xValues = vec2(
getX(batch, xF, xR, xC, ${c}),
getX(batch, xF, xR, xC, ${c} + 1)
);
vec2 wValues = vec2(
getW(wF, wR, wC, ${c}, d2),
getW(wF, wR, wC, ${c} + 1, d2)
);
dotProd += dot(xValues, wValues);
} else if (${m===3}) {
vec3 xValues = vec3(
getX(batch, xF, xR, xC, ${c}),
getX(batch, xF, xR, xC, ${c} + 1),
getX(batch, xF, xR, xC, ${c} + 2)
);
vec3 wValues = vec3(
getW(wF, wR, wC, ${c}, d2),
getW(wF, wR, wC, ${c} + 1, d2),
getW(wF, wR, wC, ${c} + 2, d2)
);
dotProd += dot(xValues, wValues);
}
}
}
}
setOutput(dotProd);
}
`}},sae=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=un(this.outputShape.length);let{dataFormat:r}=t,n=qr(),a=r==="channelsLast",s=a?1:2,i=a?2:3,o=this.enableShapeUniforms?"if(blockIndex < outShape[2] && pos < outShape[1]) {":`if(blockIndex < ${e[2]} && pos < ${e[1]}) {`,l="";for(let u=0;u<=1;u++)for(let d=0;d<=1;d++)l+=`
blockIndex = rc.z + ${d};
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[${i}] && d1 >= 0) {
ch = imod(pos, inChannels);
if (${a}) {
innerDims = vec2(d1, ch);
result[${u*2+d}] = getChannel(
getA(rc.x, d0, int(innerDims.x),
int(innerDims.y)), innerDims);
} else {
innerDims = vec2(d0, d1);
result[${u*2+d}] = 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 Q0(e,t){let r=e.length;return r>=3?t?[...e.slice(0,-3),e[r-3]*e[r-2],e[r-1]]:[...e.slice(0,-3),e[r-3],e[r-2]*e[r-1]]:!t&&r===1&&e[0]>1?[e[0],1]:null}function RI({x:e,filter:t,convInfo:r,backend:n,bias:a=null,preluActivationWeights:s=null,leakyreluAlpha:i=0,activation:o=null}){let l=e.shape,u=n.texData.get(e.dataId),d=r.inChannels,h=l[0]*l[1]*l[2],p=r.outChannels,c=r.dataFormat==="channelsLast",m=!1,f=!1,g,y=[];if(s!=null){let A=Q0(s.shape,c);A!=null&&(s=Ae({inputs:{x:s},backend:n,attrs:{shape:A}}),y.push(s))}if(a!=null){let A=Q0(a.shape,c);A!=null&&(a=Ae({inputs:{x:a},backend:n,attrs:{shape:A}}),y.push(a))}if(!((h===1||p===1)&&d>kI)&&u.isPacked&&c&&u.texture!=null&&l[2]%2!==0&&v.arraysEqual(u.shape.slice(-3),l.slice(-3))){let A=l[0]*l[1]*(l[2]+1),x={dataId:e.dataId,shape:[1,A,r.inChannels],dtype:e.dtype},b=u.shape;u.shape=u.shape.slice(),u.shape[u.shape.length-2]++,v.assert(Qp(u.shape,x.shape),()=>`packed reshape ${u.shape} to ${x.shape} isn't free`);let w=Ae({inputs:{x:t},backend:n,attrs:{shape:[1,r.inChannels,r.outChannels]}});y.push(w);let I=J0({a:x,b:w,backend:n,transposeA:m,transposeB:f,bias:a,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=r.outShape,g=mn({inputs:{x:I},backend:n}),g.shape=r.outShape,y.push(I)}else{let A=r.outHeight*r.outWidth,x=Ae({inputs:{x:e},backend:n,attrs:{shape:c?[r.batchSize,A,r.inChannels]:[r.batchSize,r.inChannels,A]}}),b=Ae({inputs:{x:t},backend:n,attrs:{shape:[1,r.inChannels,r.outChannels]}}),w=J0({a:c?x:b,b:c?b:x,transposeA:!c,transposeB:f,backend:n,bias:a,activation:o,preluActivationWeights:s,leakyreluAlpha:i});g=Ae({inputs:{x:w},backend:n,attrs:{shape:r.outShape}}),y.push(x),y.push(b),y.push(w)}for(let A of y)n.disposeIntermediateTensorInfo(A);return g}function MI({x:e,filter:t,convInfo:r,backend:n,bias:a=null,preluActivationWeights:s=null,leakyreluAlpha:i=0,activation:o=null}){let{filterWidth:l,filterHeight:u,inChannels:d,outWidth:h,outHeight:p,dataFormat:c}=r,m=c==="channelsLast",f=l*u*d,g=p*h,y=[r.batchSize,f,g],A=!0,x=!1,b=[];if(s!=null){let Y=Q0(s.shape,m);Y!=null&&(s=Ae({inputs:{x:s},backend:n,attrs:{shape:Y}}),b.push(s))}if(a!=null){let Y=Q0(a.shape,m);Y!=null&&(a=Ae({inputs:{x:a},backend:n,attrs:{shape:Y}}),b.push(a))}let w=Ae({inputs:{x:t},backend:n,attrs:{shape:[1,f,v.sizeFromShape(t.shape)/f]}});b.push(w);let I=new sae(y,r),T=[e.shape,[r.padInfo.top,r.padInfo.left],[r.strideHeight,r.strideWidth],[r.dilationHeight,r.dilationWidth],[r.inChannels],[r.filterWidth*r.inChannels],[r.outWidth]],E=n.runWebGLProgram(I,[e],"float32",T),R=Ae({inputs:{x:E},backend:n,attrs:{shape:y}});b.push(E),b.push(R);let O=a!=null,M=s!=null,S=o==="leakyrelu",P=o?Pm(o,!0):null,z=new wI(m?R.shape:w.shape,m?w.shape:R.shape,m?[r.batchSize,g,r.outChannels]:[r.batchSize,r.outChannels,g],A,x,O,P,M,S),j=m?[R,w]:[w,R];if(a&&j.push(a),M&&j.push(s),S){let Y=n.makeTensorInfo([],"float32",v.createScalarValue(i,"float32"));j.push(Y),b.push(Y)}let K=n.runWebGLProgram(z,j,"float32"),D=Ae({inputs:{x:K},backend:n,attrs:{shape:r.outShape}});b.push(K);for(let Y of b)n.disposeIntermediateTensorInfo(Y);return D}function iae(e){let{inputs:t,backend:r,attrs:n}=e,{x:a,filter:s}=t,{strides:i,pad:o,dataFormat:l,dilations:u,dimRoundingMode:d}=n,h=C.convertConv2DDataFormat(l),p=C.computeConv2DInfo(a.shape,s.shape,i,u,o,d,!1,h),c;if(p.filterHeight===1&&p.filterWidth===1&&p.dilationHeight===1&&p.dilationWidth===1&&p.strideHeight===1&&p.strideWidth===1&&(p.padInfo.type==="SAME"||p.padInfo.type==="VALID"))c=RI({x:a,filter:s,convInfo:p,backend:r});else if(Z().getBool("WEBGL_CONV_IM2COL"))c=MI({x:a,filter:s,convInfo:p,backend:r});else{let f=new EI(p);c=r.runWebGLProgram(f,[a,s],"float32")}let m=Ae({inputs:{x:c},backend:r,attrs:{shape:p.outShape}});return r.disposeIntermediateTensorInfo(c),m}var oae={kernelName:ti,backendName:"webgl",kernelFunc:iae},lae=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideHeight,r=e.strideWidth,n=e.padInfo.top,a=e.padInfo.left,s=e.dataFormat==="channelsLast";this.userCode=`
void main() {
ivec4 coords = getOutputCoords();
int wR = coords.x;
int wC = coords.y;
int d1 = coords.z;
int d2 = coords.w;
// Convolve x(?, ?, d1) with dy(:, :, d2) to get dw(wR, wC, d1, d2).
// ? = to be determined. : = across all values in that axis.
float dotProd = 0.0;
for (int b = 0; b < ${e.batchSize}; b++) {
for (int yR = 0; yR < ${e.outHeight}; yR++) {
int xR = wR + yR * ${t} - ${n};
if (xR < 0 || xR >= ${e.inHeight}) {
continue;
}
for (int yC = 0; yC < ${e.outWidth}; yC++) {
int xC = wC + yC * ${r} - ${a};
if (xC < 0 || xC >= ${e.inWidth}) {
continue;
}
if (${s}) {
float dyValue = getDy(b, yR, yC, d2);
float xValue = getX(b, xR, xC, d1);
dotProd += (xValue * dyValue);
} else {
float dyValue = getDy(b, d2, yR, yC);
float xValue = getX(b, d1, xR, xC);
dotProd += (xValue * dyValue);
}
}
}
}
setOutput(dotProd);
}
`}},uae=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterHeight,r=e.filterWidth,n=e.strideHeight,a=e.strideWidth,s=e.dataFormat==="channelsLast",i=t-1-e.padInfo.top,o=r-1-e.padInfo.left,l=s?1:2,u=s?2:3,d=s?3:1;this.userCode=`
const ivec2 pads = ivec2(${i}, ${o});
void main() {
ivec4 coords = getOutputCoords();
int batch = coords[0];
int d1 = coords[${d}];
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 < ${r}; wC++) {
float dyC = float(dyCCorner + wC) / ${a}.0;
if (dyC < 0.0 || dyC >= ${e.outWidth}.0 ||
fract(dyC) > 0.0) {
continue;
}
int idyC = int(dyC);
int wCPerm = ${r} - 1 - wC;
for (int d2 = 0; d2 < ${e.outChannels}; d2++) {
if (${s}) {
float xValue = getDy(batch, idyR, idyC, d2);
float wValue = getW(wRPerm, wCPerm, d1, d2);
dotProd += xValue * wValue;
} else {
float xValue = getDy(batch, d2, idyR, idyC);
float wValue = getW(wRPerm, wCPerm, d1, d2);
dotProd += xValue * wValue;
}
}
}
}
setOutput(dotProd);
}
`}},dae=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideDepth,r=e.strideHeight,n=e.strideWidth,a=e.padInfo.front,s=e.padInfo.top,i=e.padInfo.left;this.userCode=`
void main() {
ivec5 coords = getOutputCoords();
int wF = coords.x;
int wR = coords.y;
int wC = coords.z;
int d1 = coords.w;
int d2 = coords.u;
float dotProd = 0.0;
for (int b = 0; b < ${e.batchSize}; b++) {
for (int yF = 0; yF < ${e.outDepth}; yF++) {
int xF = wF + yF * ${t} - ${a};
if (xF < 0 || xF >= ${e.inDepth}) {
continue;
}
for (int yR = 0; yR < ${e.outHeight}; yR++) {
int xR = wR + yR * ${r} - ${s};
if (xR < 0 || xR >= ${e.inHeight}) {
continue;
}
for (int yC = 0; yC < ${e.outWidth}; yC++) {
int xC = wC + yC * ${n} - ${i};
if (xC < 0 || xC >= ${e.inWidth}) {
continue;
}
float dyValue = getDy(b, yF, yR, yC, d2);
float xValue = getX(b, xF, xR, xC, d1);
dotProd += (xValue * dyValue);
}
}
}
}
setOutput(dotProd);
}
`}},pae=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterDepth,r=e.filterHeight,n=e.filterWidth,a=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=t-1-e.padInfo.front,l=r-1-e.padInfo.top,u=n-1-e.padInfo.left;this.userCode=`
const ivec3 pads = ivec3(${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) / ${a}.0;
if (dyF < 0.0 || dyF >= ${e.outDepth}.0 || fract(dyF) > 0.0) {
continue;
}
int idyF = int(dyF);
int wFPerm = ${t} - 1 - wF;
for (int wR = 0; wR < ${r}; wR++) {
float dyR = float(dyRCorner + wR) / ${s}.0;
if (dyR < 0.0 || dyR >= ${e.outHeight}.0 ||
fract(dyR) > 0.0) {
continue;
}
int idyR = int(dyR);
int wRPerm = ${r} - 1 - wR;
for (int wC = 0; wC < ${n}; wC++) {
float dyC = float(dyCCorner + wC) / ${i}.0;
if (dyC < 0.0 || dyC >= ${e.outWidth}.0 ||
fract(dyC) > 0.0) {
continue;
}
int idyC = int(dyC);
int wCPerm = ${n} - 1 - wC;
for (int d2 = 0; d2 < ${e.outChannels}; d2++) {
float xValue = getDy(batch, idyF, idyR, idyC, d2);
float wValue = getW(wFPerm, wRPerm, wCPerm, d1, d2);
dotProd += xValue * wValue;
}
}
}
}
setOutput(dotProd);
}
`}};function hae(e){let{inputs:t,backend:r,attrs:n}=e,{x:a,dy:s}=t,{strides:i,pad:o,dataFormat:l,dimRoundingMode:u,filterShape:d}=n,h=C.convertConv2DDataFormat(l),p=C.computeConv2DInfo(a.shape,d,i,1,o,u,!1,h),c=new lae(p);return r.runWebGLProgram(c,[a,s],"float32")}var cae={kernelName:hf,backendName:"webgl",kernelFunc:hae};function fae(e){let{inputs:t,backend:r,attrs:n}=e,{dy:a,filter:s}=t,{inputShape:i,strides:o,pad:l,dataFormat:u,dimRoundingMode:d}=n,h=C.convertConv2DDataFormat(u),p=C.computeConv2DInfo(i,s.shape,o,1,l,d,!1,h),c=new uae(p);return r.runWebGLProgram(c,[a,s],"float32")}var mae={kernelName:ri,backendName:"webgl",kernelFunc:fae};function gae(e){let{inputs:t,backend:r,attrs:n}=e,{x:a,filter:s}=t,{strides:i,pad:o,dilations:l}=n,u=C.computeConv3DInfo(a.shape,s.shape,i,l,o),d=new aae(u);return r.runWebGLProgram(d,[a,s],"float32")}var yae={kernelName:ih,backendName:"webgl",kernelFunc:gae};function Aae(e){let{inputs:t,backend:r,attrs:n}=e,{x:a,dy:s}=t,{strides:i,pad:o,filterShape:l}=n,u=C.computeConv3DInfo(a.shape,l,i,1,o),d=new dae(u);return r.runWebGLProgram(d,[a,s],"float32")}var xae={kernelName:cf,backendName:"webgl",kernelFunc:Aae};function bae(e){let{inputs:t,backend:r,attrs:n}=e,{dy:a,filter:s}=t,{pad:i,strides:o,inputShape:l}=n,u=C.computeConv3DInfo(l,s.shape,o,1,i),d=new pae(u);return r.runWebGLProgram(d,[a,s],"float32")}var vae={kernelName:ff,backendName:"webgl",kernelFunc:bae},wae=_d+`
return cos(x);
`,kae=it({opSnippet:wae}),Iae={kernelName:ni,backendName:"webgl",kernelFunc:kae},Sae=`
float e2x = exp(-x);
return (e2x + 1.0 / e2x) / 2.0;
`,Cae=it({opSnippet:Sae}),Tae={kernelName:ai,backendName:"webgl",kernelFunc:Cae},Nae=class{constructor(e,t,r,n,a){this.variableNames=["Image","Boxes","BoxInd"],this.outputShape=[];let[s,i,o,l]=e,[u]=t,[d,h]=r;this.outputShape=[u,d,h,l];let p=n==="bilinear"?1:0,[c,m]=[`${i-1}.0`,`${o-1}.0`],[f,g,y]=d>1?[`${(i-1)/(d-1)}`,"(y2-y1) * height_ratio",`y1*${c} + float(y)*(height_scale)`]:["0.0","0.0",`0.5 * (y1+y2) * ${c}`],[A,x,b]=h>1?[`${(o-1)/(h-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(${A});
void main() {
ivec4 coords = getOutputCoords();
int b = coords[0];
int y = coords[1];
int x = coords[2];
int d = coords[3];
// get box vals
float y1 = getBoxes(b,0);
float x1 = getBoxes(b,1);
float y2 = getBoxes(b,2);
float x2 = getBoxes(b,3);
// get image in batch index
int bInd = round(getBoxInd(b));
if(bInd < 0 || bInd >= ${s}) {
return;
}
float height_scale = ${g};
float width_scale = ${x};
float in_y = ${y};
if( in_y < 0.0 || in_y > ${c} ) {
setOutput(float(${a}));
return;
}
float in_x = ${b};
if( in_x < 0.0 || in_x > ${m} ) {
setOutput(float(${a}));
return;
}
vec2 sourceFracIndexCR = vec2(in_x,in_y);
if(${p} == 1) {
// Compute the four integer indices.
ivec2 sourceFloorCR = ivec2(sourceFracIndexCR);
ivec2 sourceCeilCR = ivec2(ceil(sourceFracIndexCR));
float topLeft = getImage(b, sourceFloorCR.y, sourceFloorCR.x, d);
float bottomLeft = getImage(b, sourceCeilCR.y, sourceFloorCR.x, d);
float topRight = getImage(b, sourceFloorCR.y, sourceCeilCR.x, d);
float bottomRight = getImage(b, sourceCeilCR.y, sourceCeilCR.x, d);
vec2 fracCR = sourceFracIndexCR - vec2(sourceFloorCR);
float top = topLeft + (topRight - topLeft) * fracCR.x;
float bottom = bottomLeft + (bottomRight - bottomLeft) * fracCR.x;
float newValue = top + (bottom - top) * fracCR.y;
setOutput(newValue);
} else {
// Compute the coordinators of nearest neighbor point.
ivec2 sourceNearestCR = ivec2(floor(
sourceFracIndexCR + vec2(0.5,0.5)));
float newValue = getImage(b, sourceNearestCR.y, sourceNearestCR.x, d);
setOutput(newValue);
}
}
`}},Eae=e=>{let{inputs:t,backend:r,attrs:n}=e,{image:a,boxes:s,boxInd:i}=t,{cropSize:o,method:l,extrapolationValue:u}=n,d=new Nae(a.shape,s.shape,o,l,u);return r.runWebGLProgram(d,[a,s,i],"float32")},Rae={kernelName:Xo,backendName:"webgl",kernelFunc:Eae},t7=class{constructor(e,t,r,n){this.op=e,this.outputShape=t,this.variableNames=["x"],this.customUniforms=[{name:"index",type:"float"}];let a=this.outputShape.length,s=this.op==="*"?"1.0":"0.0",i=r?s:`getX(${r7(a,"coords",this.op)})`,o=this.outputShape[this.outputShape.length-1],l="",u="";r?(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() {
${vt(a)} coords = getOutputCoords();
int end = ${n7(a,"coords",this.op)};
float val = ${i};
int pow2 = int(pow(2.0, index));
if (${l}) {
int idx = ${u};
${n7(a,"coords",this.op)} = idx;
val ${this.op}= getX(${r7(a,"coords",this.op)});
}
setOutput(val);
}
`}};function r7(e,t,r){if(e===1)return`${t}`;if(e===2)return`${t}.x, ${t}.y`;if(e===3)return`${t}.x, ${t}.y, ${t}.z`;if(e===4)return`${t}.x, ${t}.y, ${t}.z, ${t}.w`;throw new Error(`Cumulative ${r} for rank ${e} is not yet supported`)}function n7(e,t,r){if(e===1)return`${t}`;if(e===2)return`${t}.y`;if(e===3)return`${t}.z`;if(e===4)return`${t}.w`;throw new Error(`Cumulative ${r} for rank ${e} is not yet supported`)}function $I(e,t,r,n,a,s){let i=t.shape.length,o=C.getAxesPermutation([n],i),l=t;o!=null&&(l=Ur({inputs:{x:t},backend:r,attrs:{perm:o}}));let u=C.getInnerMostAxes(1,i)[0];if(u!==i-1)throw new Error(`WebGL cumprod shader expects an inner-most axis=${t.shape.length-1} but got axis=${n}`);let d=l.shape[u],h=mn({inputs:{x:l},backend:r});for(let p=0;p<=Math.ceil(Math.log2(d))-1;p++){let c=new t7(e,l.shape,!1,s),m=[[p]],f=h;h=r.runWebGLProgram(c,[h],h.dtype,m),r.disposeIntermediateTensorInfo(f)}if(a){let p=new t7(e,l.shape,a,s),c=h;h=r.runWebGLProgram(p,[h],h.dtype),r.disposeIntermediateTensorInfo(c)}if(o!=null){let p=C.getUndoAxesPermutation(o),c=Ur({inputs:{x:h},backend:r,attrs:{perm:p}});return r.disposeIntermediateTensorInfo(h),r.disposeIntermediateTensorInfo(l),c}return h}function Mae(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{axis:s,exclusive:i,reverse:o}=n;return $I("*",a,r,s,i,o)}var $ae={kernelName:qo,backendName:"webgl",kernelFunc:Mae};function Fae(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{axis:s,exclusive:i,reverse:o}=n;return $I("+",a,r,s,i,o)}var _ae={kernelName:si,backendName:"webgl",kernelFunc:Fae};function Pae(e){let{inputs:t,backend:r,attrs:n}=e,{x:a,weights:s}=t,{size:i,binaryOutput:o}=n;if(a.shape.length===1){let l=r.readSync(a.dataId),u=r.readSync(s.dataId),d=dI(l,u,s.dtype,s.shape,i);return r.makeTensorInfo([i],s.dtype,d)}else if(a.shape.length===2){let l=r.bufferSync(a),u=r.bufferSync(s),d=qee(l,u,i,o);return r.makeTensorInfo(d.shape,s.dtype,d.values)}throw new Error(`Error in denseBincount: input must be at most rank 2, but got rank${a.shape.length}.`)}var Oae={kernelName:mf,backendName:"webgl",kernelFunc:Pae},zae=class{constructor(e,t,r){this.variableNames=["x"],this.outputShape=[],this.outputShape=e,this.blockSize=t,this.dataFormat=r,this.userCode=`
void main() {
ivec4 coords = getOutputCoords();
int b = coords[0];
int h = ${this.getHeightCoordString()};
int w = ${this.getWidthCoordString()};
int d = ${this.getDepthCoordString()};
int in_h = h / ${t};
int offset_h = imod(h, ${t});
int in_w = w / ${t};
int offset_w = imod(w, ${t});
int offset_d = (offset_h * ${t} + offset_w) *
${this.getOutputDepthSize()};
int in_d = d + offset_d;
float result = ${this.getInputSamplingString()};
setOutput(result);
}
`}getHeightCoordString(){return this.dataFormat==="NHWC"?"coords[1]":"coords[2]"}getWidthCoordString(){return this.dataFormat==="NHWC"?"coords[2]":"coords[3]"}getDepthCoordString(){return this.dataFormat==="NHWC"?"coords[3]":"coords[1]"}getOutputDepthSize(){return this.dataFormat==="NHWC"?this.outputShape[3]:this.outputShape[1]}getInputSamplingString(){return this.dataFormat==="NHWC"?"getX(b, in_h, in_w, in_d)":"getX(b, in_d, in_h, in_w)"}};function Dae(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{blockSize:s,dataFormat:i}=n,o=a.shape[0],l=i==="NHWC"?a.shape[1]:a.shape[2],u=i==="NHWC"?a.shape[2]:a.shape[3],d=i==="NHWC"?a.shape[3]:a.shape[1],h=l*s,p=u*s,c=d/(s*s),m=i==="NHWC"?[o,h,p,c]:[o,c,h,p],f=new zae(m,s,i);return r.runWebGLProgram(f,[a],a.dtype)}var Lae={kernelName:Ko,backendName:"webgl",kernelFunc:Dae},FI=class{constructor(e,t=!1,r=null,n=!1,a=!1){this.variableNames=["x","W"],this.customUniforms=[{name:"pads",type:"ivec2"},{name:"strides",type:"ivec2"},{name:"dilations",type:"ivec2"},{name:"inDims",type:"ivec2"}],this.outputShape=e.outShape,this.enableShapeUniforms=un(this.outputShape.length);let s=e.filterHeight,i=e.filterWidth,o=e.outChannels/e.inChannels,l="",u="";r&&(n?l=`float activation(float a) {
float b = getPreluActivationWeightsAtOutCoords();
${r}
}`:a?l=`float activation(float a) {
float b = getLeakyreluAlphaAtOutCoords();
${r}
}`:l=`
float activation(float x) {
${r}
}
`,u="result = activation(result);");let d=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),n&&this.variableNames.push("preluActivationWeights"),a&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
${l}
void main() {
ivec4 coords = getOutputCoords();
int batch = coords.x;
ivec2 xRCCorner = coords.yz * strides - pads;
int d2 = coords.w;
int d1 = d2 / ${o};
int q = d2 - d1 * ${o};
int xRCorner = xRCCorner.x;
int xCCorner = xRCCorner.y;
// Convolve x(?, ?, d1) with w(:, :, d1, q) to get y(yR, yC, d2).
// ? = to be determined. : = across all values in that axis.
float dotProd = 0.0;
// TO DO(dsmilkov): Flatten the two for loops and vec4 the operations.
for (int wR = 0; wR < ${s}; wR++) {
int xR = xRCorner + wR * dilations[0];
if (xR < 0 || xR >= inDims[0]) {
continue;
}
for (int wC = 0; wC < ${i}; wC++) {
int xC = xCCorner + wC * dilations[1];
if (xC < 0 || xC >= inDims[1]) {
continue;
}
float xVal = getX(batch, xR, xC, d1);
float wVal = getW(wR, wC, d1, q);
dotProd += xVal * wVal;
}
}
float result = dotProd;
${d}
${u}
setOutput(result);
}
`}},_I=class{constructor(e,t=!1,r=null,n=!1,a=!1){this.variableNames=["x","W"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"pads",type:"ivec2"},{name:"strides",type:"ivec2"},{name:"dilations",type:"ivec2"},{name:"inDims",type:"ivec2"}],this.outputShape=e.outShape,this.enableShapeUniforms=un(this.outputShape.length);let s=e.outChannels/e.inChannels,i=e.padInfo.left,o=e.strideWidth,l=e.dilationWidth,u=e.filterHeight,d=e.filterWidth,h=d,p=`
int xR; int xC; int xCOffset;
vec4 wTexel; vec4 previous; vec4 final;`;for(let g=0;g<d;g++)p+=`
vec4 xTexelC${g*2};
int xTexelC${g*2}Ready;
vec4 xTexelC${g*2+1};
int xTexelC${g*2+1}Ready;
vec4 xC${g};`;p+=`
for (int r = 0; r < ${u}; r++) {
`;for(let g=0;g<d;g++)p+=`
xTexelC${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);`;p+=`
xR = xRCorner + r * dilations[0];
if (xR >=0 && xR < inDims[0]) {
`;for(let g=0;g<(h+1)/2;g++){let y=g*2;if(p+=`
xC = xCCorner + ${y*l};
`,o===1){if(y<d&&(i%2===1?(p+=`
xCOffset = xC + 1;
if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${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${y}Ready = 1;
}
`,l===1&&y>0?p+=`
xC${y} = vec4(xTexelC${y-2}.zw, xTexelC${y}.xy);
`:p+=`
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);
}
`):p+=`
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<d)){let A=i%2===0?v.nearestLargerEven(l):l;l%2===0&&i%2===1||l%2!==0&&i%2!==1?(p+=`
xCOffset = xC + imod(pads[1], 2) + ${A};
if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${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${y+1}Ready = 1;
}
`,l>1&&(p+=`
xCOffset -= 2;
if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${y}Ready == 0) {
xTexelC${y} = getX(batch, xR, xCOffset, d1);
xTexelC${y}Ready = 1;
}
`),p+=`
xC${y+1} = vec4(xTexelC${y}.zw, xTexelC${y+1}.xy);
`):A===1?p+=`
xC${y+1} = xTexelC${y};
`:p+=`
xCOffset = xC + ${A};
if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${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${y+1};
`}}else y<d&&(i%2===1?(p+=`
xCOffset = xC + 1 - strides[1];
if(xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${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<d&&(p+=`
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);
`)):(p+=`
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${y+1}.xy);
`,y+1<d&&(p+=`
xC${y+1} = vec4(xTexelC${y}.zw, xTexelC${y+1}.zw);
`)));y<d&&(p+=`
wTexel = getW(r, ${y}, d1, q);
dotProd += xC${y} * vec4(wTexel.xz, wTexel.xz);
`,y+1<d&&(p+=`
wTexel = getW(r, ${y+1}, d1, q);
dotProd += xC${y+1} * vec4(wTexel.xz, wTexel.xz);
`))}p+=`
}
`,p+=`
}
`;let c="",m="";r&&(n?c=`vec4 activation(vec4 a) {
vec4 b = getPreluActivationWeightsAtOutCoords();
${r}
}`:a?c=`vec4 activation(vec4 a) {
vec4 b = getLeakyreluAlphaAtOutCoords();
${r}
}`:c=`vec4 activation(vec4 x) {
${r}
}`,m="result = activation(result);");let f=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),n&&this.variableNames.push("preluActivationWeights"),a&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
${c}
void main() {
ivec4 coords = getOutputCoords();
int batch = coords.x;
ivec2 xRCCorner = coords.yz * strides - pads;
int d2 = coords.w;
int d1 = d2 / ${s};
int q = d2 - d1 * ${s};
int xRCorner = xRCCorner.x;
int xCCorner = xRCCorner.y;
//intialize dotProd with a small epsilon seems to reduce GPU accuracy loss.
vec4 dotProd = vec4(0.000000000000001);
${p}
vec4 result = dotProd - vec4(0.000000000000001);
${f}
${m}
setOutput(result);
}
`}};function Bae(e){let{inputs:t,backend:r,attrs:n}=e,{x:a,filter:s}=t,{strides:i,pad:o,dilations:l,dimRoundingMode:u}=n,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(a.shape,s.shape,i,d,o,u,!0),p;Z().getBool("WEBGL_PACK_DEPTHWISECONV")&&h.strideWidth<=2&&h.outChannels/h.inChannels===1?p=new _I(h):p=new FI(h);let c=[[h.padInfo.top,h.padInfo.left],[h.strideHeight,h.strideWidth],[h.dilationHeight,h.dilationWidth],[h.inHeight,h.inWidth]];return r.runWebGLProgram(p,[a,s],"float32",c)}var Wae={kernelName:ii,backendName:"webgl",kernelFunc:Bae},Vae=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideHeight,r=e.strideWidth,n=e.padInfo.top,a=e.padInfo.left,s=e.outChannels/e.inChannels;this.userCode=`
void main() {
ivec4 coords = getOutputCoords();
int wR = coords.x;
int wC = coords.y;
int d1 = coords.z;
int dm = coords.w;
int d2 = d1 * ${s} + dm;
float dotProd = 0.0;
// TO DO: Vec4 over the batch size
for (int b = 0; b < ${e.batchSize}; b++) {
for (int yR = 0; yR < ${e.outHeight}; yR++) {
int xR = wR + yR * ${t} - ${n};
if (xR < 0 || xR >= ${e.inHeight}) {
continue;
}
for (int yC = 0; yC < ${e.outWidth}; yC++) {
int xC = wC + yC * ${r} - ${a};
if (xC < 0 || xC >= ${e.inWidth}) {
continue;
}
float dyValue = getDy(b, yR, yC, d2);
float xValue = getX(b, xR, xC, d1);
dotProd += (xValue * dyValue);
}
}
}
setOutput(dotProd);
}
`}},Uae=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterHeight,r=e.filterWidth,n=e.strideHeight,a=e.strideWidth,s=t-1-e.padInfo.top,i=r-1-e.padInfo.left,o=e.outChannels/e.inChannels;this.userCode=`
const ivec2 pads = ivec2(${s}, ${i});
void main() {
ivec4 coords = getOutputCoords();
int batch = coords[0];
int d1 = coords[3];
ivec2 dyCorner = coords.yz - pads;
int dyRCorner = dyCorner.x;
int dyCCorner = dyCorner.y;
float dotProd = 0.0;
for (int wR = 0; wR < ${t}; wR++) {
float dyR = float(dyRCorner + wR) / ${n}.0;
if (dyR < 0.0 || dyR >= ${e.outHeight}.0 || fract(dyR) > 0.0) {
continue;
}
int idyR = int(dyR);
int wRPerm = ${t} - 1 - wR;
for (int wC = 0; wC < ${r}; wC++) {
float dyC = float(dyCCorner + wC) / ${a}.0;
if (dyC < 0.0 || dyC >= ${e.outWidth}.0 ||
fract(dyC) > 0.0) {
continue;
}
int idyC = int(dyC);
int wCPerm = ${r} - 1 - wC;
// TO DO: Vec4 over the channelMul
for (int dm = 0; dm < ${o}; dm++) {
int d2 = d1 * ${o} + dm;
float xValue = getDy(batch, idyR, idyC, d2);
float wValue = getW(wRPerm, wCPerm, d1, dm);
dotProd += xValue * wValue;
}
}
}
setOutput(dotProd);
}
`}};function Gae(e){let{inputs:t,backend:r,attrs:n}=e,{x:a,dy:s}=t,{strides:i,dilations:o,pad:l,dimRoundingMode:u,filterShape:d}=n,h=C.computeConv2DInfo(a.shape,d,i,o,l,u,!0),p=new Vae(h);return r.runWebGLProgram(p,[a,s],"float32")}var jae={kernelName:gf,backendName:"webgl",kernelFunc:Gae};function Hae(e){let{inputs:t,backend:r,attrs:n}=e,{dy:a,filter:s}=t,{strides:i,dilations:o,pad:l,dimRoundingMode:u,inputShape:d}=n,h=C.computeConv2DInfo(d,s.shape,i,o,l,u,!0),p=new Uae(h);return r.runWebGLProgram(p,[a,s],"float32")}var qae={kernelName:yf,backendName:"webgl",kernelFunc:Hae},Xae=class{constructor(e){this.variableNames=["X"],this.outputShape=[e,e],this.userCode=`
void main() {
ivec2 coords = getOutputCoords();
float val = coords[0] == coords[1] ? getX(coords[0]) : 0.0;
setOutput(val);
}
`}};function Kae(e){let{inputs:t,backend:r}=e,{x:n}=t,a=[...n.shape,...n.shape],s=v.sizeFromShape(n.shape),i=Ae({inputs:{x:n},backend:r,attrs:{shape:[s]}}),o=new Xae(s),l=r.runWebGLProgram(o,[i],i.dtype),u=Ae({inputs:{x:l},backend:r,attrs:{shape:a}});return r.disposeIntermediateTensorInfo(i),r.disposeIntermediateTensorInfo(l),u}var Zae={kernelName:Af,backendName:"webgl",kernelFunc:Kae},Yae=class{constructor(e){this.variableNames=["x","W"],this.outputShape=e.outShape;let{inHeight:t,inWidth:r,padInfo:n,strideHeight:a,strideWidth:s,filterHeight:i,filterWidth:o,dilationHeight:l,dilationWidth:u}=e,{top:d,left:h}=n;this.userCode=`
const ivec2 strides = ivec2(${a}, ${s});
const ivec2 pads = ivec2(${d}, ${h});
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 < ${r}) {
float xVal = getX(batch, hIn, wIn, d1);
float wVal = getW(h, w, d1);
float val = xVal + wVal;
if (val > curVal) {
curVal = val;
}
}
}
}
}
float result = curVal;
setOutput(result);
}
`}};function Jae(e){let{inputs:t,backend:r,attrs:n}=e,{x:a,filter:s}=t,{strides:i,pad:o,dilations:l}=n,u=C.computeDilation2DInfo(a.shape,s.shape,i,o,"NHWC",l),d,h=new Yae(u);d=r.runWebGLProgram(h,[a,s],"float32");let p=Ae({inputs:{x:d},backend:r,attrs:{shape:u.outShape}});return r.disposeIntermediateTensorInfo(d),p}var Qae={kernelName:oh,backendName:"webgl",kernelFunc:Jae};function ese(e){let{inputs:t,backend:r,attrs:n}=e,{equation:a}=n,s=t,{allDims:i,summedDims:o,idDims:l}=C.decodeEinsumEquation(a,s.length);C.checkEinsumDimSizes(i.length,l,s);let{path:u,steps:d}=C.getEinsumComputePath(o,l),h=d.length,p=null,c=i.length,m=[];for(let f=0;f<h;++f){for(let g of d[f]){let{permutationIndices:y,expandDims:A}=C.getEinsumPermutation(c,l[g]),x;C.isIdentityPermutation(y)?x=s[g]:(x=Ur({inputs:{x:s[g]},backend:r,attrs:{perm:y}}),m.push(x));let b=x.shape.slice();for(let w=0;w<A.length;++w)b.splice(A[w],0,1);v.arraysEqual(x.shape,b)||(x=Ae({inputs:{x},backend:r,attrs:{shape:b}}),m.push(x)),p===null?p=x:(p=RA({inputs:{a:x,b:p},backend:r}),m.push(p))}f<h-1&&(u[f]>=0&&(p=zm({inputs:{x:p},backend:r,attrs:{axis:u[f]-(i.length-c),keepDims:!1}}),m.push(p)),c--)}for(let f of m)f!==p&&r.disposeIntermediateTensorInfo(f);return p}var tse={kernelName:lh,backendName:"webgl",kernelFunc:ese},rse="return (x >= 0.0) ? x : (exp(x) - 1.0);",nse=`
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;
`,ase=it({opSnippet:rse,packedOpSnippet:nse}),sse={kernelName:li,backendName:"webgl",kernelFunc:ase},ise="return (b >= 1.0) ? a : a * (b + 1.0);",ose=`
vec4 bGTEZero = vec4(greaterThanEqual(b, vec4(0.)));
return (bGTEZero * a) + ((vec4(1.0) - bGTEZero) * (a * (b + vec4(1.0))));
`,lse=e=>{let{inputs:t,backend:r}=e,{dy:n,y:a}=t,s=Z().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new Xh(ose,n.shape,a.shape):new Bu(ise,n.shape,a.shape);return r.runWebGLProgram(s,[n,a],n.dtype)},use={kernelName:xf,backendName:"webgl",kernelFunc:lse},dse=`
return vec4(equal(a, b));
`,pse="return float(a == b);",hse=vr({opSnippet:pse,packedOpSnippet:dse,dtype:"bool",cpuKernelImpl:Zee}),cse={kernelName:Zo,backendName:"webgl",kernelFunc:hse},fse=`
// 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 = ${C.ERF_A5};
float sign = sign(x);
x = abs(x);
float t = 1.0 / (1.0 + p * x);
return sign * (1.0 - (((((a5*t + a4)*t) + a3)*t + a2)*t + a1)*t*exp(-x*x));
`,mse=it({opSnippet:fse}),gse={kernelName:Qu,backendName:"webgl",kernelFunc:mse},yse=_d+`
return exp(x);
`,Ase=`
vec4 result = exp(x);
bvec4 isNaN = isnan(x);
result.r = isNaN.r ? x.r : result.r;
result.g = isNaN.g ? x.g : result.g;
result.b = isNaN.b ? x.b : result.b;
result.a = isNaN.a ? x.a : result.a;
return result;
`,PI=it({opSnippet:yse,packedOpSnippet:Ase,cpuKernelImpl:Yee,dtype:"float32"}),xse={kernelName:ui,backendName:"webgl",kernelFunc:PI};function my(e){let{inputs:t,attrs:r,backend:n}=e,{dim:a}=r,{input:s}=t,i=s.shape.length,o=s.shape.slice(),l=a;return a<0&&(v.assert(-(i+1)<=a,()=>`Axis must be in the interval [${-(i+1)}, ${i}]`),l=i+a+1),o.splice(l,0,1),Ae({inputs:{x:s},backend:n,attrs:{shape:o}})}var bse={kernelName:Yo,backendName:"webgl",kernelFunc:my},a7="return exp(x) - 1.0;",vse=it({opSnippet:a7,packedOpSnippet:a7,cpuKernelImpl:Jee}),wse={kernelName:Jo,backendName:"webgl",kernelFunc:vse},s7=class{constructor(e,t,r){this.variableNames=["real","imag"];let n=t[1];this.outputShape=t;let a=r?`2.0 * ${Math.PI}`:`-2.0 * ${Math.PI}`,s=r?`${n}.0`:"1.0",i;if(e==="real")i="return real * expR - imag * expI;";else if(e==="imag")i="return real * expI + imag * expR;";else throw new Error(`FFT component must be either "real" or "imag", got ${e}.`);this.userCode=`
const float exponentMultiplier = ${a};
float unaryOpComplex(float real, float expR, float imag, float expI) {
${i}
}
float mulMatDFT(int batch, int index) {
float indexRatio = float(index) / float(${n});
float exponentMultiplierTimesIndexRatio =
exponentMultiplier * indexRatio;
float result = 0.0;
for (int i = 0; i < ${n}; i++) {
// x = (-2|2 * PI / N) * index * i;
float x = exponentMultiplierTimesIndexRatio * float(i);
float expR = cos(x);
float expI = sin(x);
float real = getReal(batch, i);
float imag = getImag(batch, i);
result +=
unaryOpComplex(real, expR, imag, expI) / ${s};
}
return result;
}
void main() {
ivec2 coords = getOutputCoords();
setOutput(mulMatDFT(coords[0], coords[1]));
}
`}};function OI(e,t,r){let n=r.texData.get(e.dataId),a=v.sizeFromShape(e.shape),s=e.shape[e.shape.length-1],i=a/s,o=Ae({inputs:{x:e},backend:r,attrs:{shape:[i,s]}}),l=o.shape,u=new s7("real",l,t),d=new s7("imag",l,t),h=[{dataId:n.complexTensorInfos.real.dataId,dtype:n.complexTensorInfos.real.dtype,shape:l},{dataId:n.complexTensorInfos.imag.dataId,dtype:n.complexTensorInfos.imag.dtype,shape:l}],p=r.runWebGLProgram(u,h,"float32"),c=r.runWebGLProgram(d,h,"float32"),m=ji({inputs:{real:p,imag:c},backend:r});r.disposeIntermediateTensorInfo(p),r.disposeIntermediateTensorInfo(c);let f=Ae({inputs:{x:m},backend:r,attrs:{shape:e.shape}});return r.disposeIntermediateTensorInfo(o),r.disposeIntermediateTensorInfo(m),f}function kse(e){let{inputs:t,backend:r}=e,{input:n}=t;return OI(n,!1,r)}var Ise={kernelName:bf,backendName:"webgl",kernelFunc:kse},Sse=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 Zh(e){let{backend:t,attrs:r}=e,{shape:n,value:a}=r,{dtype:s}=r;if(s=s||v.inferDtype(a),s==="string"){let i=v.getArrayFromDType(s,v.sizeFromShape(n));return i.fill(a),t.makeTensorInfo(n,s,i)}else{let i=new Sse(n,a),o=[[a]];return t.runWebGLProgram(i,[],s,o)}}var Cse={kernelName:ed,backendName:"webgl",kernelFunc:Zh},Tse=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 < ${t}) {
outputValue = getImage(coords[0], coords[1], coordX, coords[3]);
} else {
outputValue = getImage(coords[0], coords[1], coords[2], coords[3]);
}
setOutput(outputValue);
}
`}},Nse={kernelName:Qo,backendName:"webgl",kernelFunc:({inputs:e,backend:t})=>{let{image:r}=e,n=t,a=new Tse(r.shape);return n.runWebGLProgram(a,[r],r.dtype)}},i7="return floor(x);",Ese=it({opSnippet:i7,packedOpSnippet:i7,cpuKernelImpl:Qee}),Rse={kernelName:di,backendName:"webgl",kernelFunc:Ese},Mse=`
float s = sign(a) * sign(b);
int ia = round(a);
int ib = round(b);
if (ib != 0) {
// Windows (D3D) wants guaranteed non-zero int division at compile-time.
return float(idiv(ia, ib, s));
} else {
return NAN;
}
`,$se=`
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);
`,Fse=vr({opSnippet:Mse,packedOpSnippet:$se,dtype:"int32"}),_se={kernelName:pi,backendName:"webgl",kernelFunc:Fse},Pse=class{constructor(e){this.variableNames=["A"];let t=qr(),[r,n]=e;this.outputShape=e,this.userCode=`
void main() {
ivec3 coords = getOutputCoords();
int texR = coords[0];
int texC = coords[1];
int depth = coords[2];
vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${n}.0, ${r}.0);
vec4 values = ${t.texture2D}(A, uv);
float value;
if (depth == 0) {
value = values.r;
} else if (depth == 1) {
value = values.g;
} else if (depth == 2) {
value = values.b;
} else if (depth == 3) {
value = values.a;
}
setOutput(floor(value * 255.0 + 0.5));
}
`}},Ose=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0;let t=qr(),[r,n]=e;this.outputShape=e,this.userCode=`
void main() {
ivec3 coords = getOutputCoords();
int texR = coords[0];
int texC = coords[1];
int depth = coords[2];
vec4 result = vec4(0.);
for(int row=0; row<=1; row++) {
for(int col=0; col<=1; col++) {
texC = coords[1] + row;
depth = coords[2] + col;
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${n}.0, ${r}.0);
vec4 values = ${t.texture2D}(A, uv);
float value;
if (depth == 0) {
value = values.r;
} else if (depth == 1) {
value = values.g;
} else if (depth == 2) {
value = values.b;
} else if (depth == 3) {
value = values.a;
}
result[row * 2 + col] = floor(value * 255.0 + 0.5);
}
}
${t.output} = result;
}
`}},zse={kernelName:Up,backendName:"webgl",kernelFunc:Dse},cu;function Dse(e){let{inputs:t,backend:r,attrs:n}=e,{pixels:a}=t,{numChannels:s}=n,i=typeof HTMLVideoElement!="undefined"&&a instanceof HTMLVideoElement,o=typeof HTMLImageElement!="undefined"&&a instanceof HTMLImageElement,[l,u]=i?[a.videoWidth,a.videoHeight]:[a.width,a.height],d=[u,l],h=[u,l,s];(o||i)&&(cu==null&&(cu=document.createElement("canvas").getContext("2d")),cu.canvas.width=l,cu.canvas.height=u,cu.drawImage(a,0,0,l,u),a=cu.canvas);let p=r.makeTensorInfo(d,"int32");r.texData.get(p.dataId).usage=2,r.gpgpu.uploadPixelDataToTexture(r.getTexture(p.dataId),a);let c=Z().getBool("WEBGL_PACK")?new Ose(h):new Pse(h),m=r.runWebGLProgram(c,[p],"int32");return r.disposeData(p.dataId),m}function Lse(e){let{inputs:t,backend:r,attrs:n}=e,{x:a,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:u,dataFormat:d,dilations:h,dimRoundingMode:p,activation:c,leakyreluAlpha:m}=n,f=C.convertConv2DDataFormat(d),g=C.computeConv2DInfo(a.shape,s.shape,l,h,u,p,!1,f),y,A=[];if(g.filterHeight===1&&g.filterWidth===1&&g.dilationHeight===1&&g.dilationWidth===1&&g.strideHeight===1&&g.strideWidth===1&&(g.padInfo.type==="SAME"||g.padInfo.type==="VALID"))y=RI({x:a,filter:s,convInfo:g,backend:r,bias:i,activation:c,preluActivationWeights:o,leakyreluAlpha:m});else if(Z().getBool("WEBGL_CONV_IM2COL"))y=MI({x:a,filter:s,convInfo:g,backend:r,bias:i,activation:c,preluActivationWeights:o,leakyreluAlpha:m});else{let b=i!=null,w=o!=null,I=c==="leakyrelu",T=c?Pm(c,!1):null,E=new EI(g,b,T,w,I),R=[a,s],O=(M,S)=>{if(S==="NCHW"&&M.shape.length===1&&M.shape[0]!==1){let P=Ae({inputs:{x:M},backend:r,attrs:{shape:[M.shape[0],1,1]}});return A.push(P),P}return M};if(b&&R.push(O(i,d)),w&&R.push(O(o,d)),I){let M=r.makeTensorInfo([],"float32",v.createScalarValue(m,"float32"));R.push(M),A.push(M)}y=r.runWebGLProgram(E,R,"float32")}let x=Ae({inputs:{x:y},backend:r,attrs:{shape:g.outShape}});return A.push(y),A.forEach(b=>r.disposeIntermediateTensorInfo(b)),x}var Bse={kernelName:Ps,backendName:"webgl",kernelFunc:Lse};function Wse(e){let{inputs:t,backend:r,attrs:n}=e,{x:a,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:u,dilations:d,dimRoundingMode:h,activation:p,leakyreluAlpha:c}=n,m=[],f=d;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(a.shape,s.shape,l,f,u,h,!0),y=Z().getBool("WEBGL_PACK_DEPTHWISECONV")&&g.strideWidth<=2&&g.outChannels/g.inChannels===1,A=p?Pm(p,y):null,x=[a,s],b=i!=null,w=o!=null,I=p==="leakyrelu";if(b&&x.push(i),w&&x.push(o),I){let O=r.makeTensorInfo([],"float32",v.createScalarValue(c,"float32"));x.push(O),m.push(O)}let T;y?T=new _I(g,b,A,w,I):T=new FI(g,b,A,w,I);let E=[[g.padInfo.top,g.padInfo.left],[g.strideHeight,g.strideWidth],[g.dilationHeight,g.dilationWidth],[g.inHeight,g.inWidth]],R=r.runWebGLProgram(T,x,"float32",E);return m.forEach(O=>r.disposeIntermediateTensorInfo(O)),R}var Vse={kernelName:Os,backendName:"webgl",kernelFunc:Wse},Use=class{constructor(e,t,r){this.sliceDim=e,this.strides=t,this.variableNames=["x","indices"],this.outputShape=r;let n=vt(t.length),a=vt(r.length),s=this.sliceDim>1?"strides[j]":"strides";this.userCode=`
${n} strides = ${n}(${this.strides});
void main() {
${a} coords = getOutputCoords();
int flattenIndex = 0;
for (int j = 0; j < ${this.sliceDim}; j++) {
int index = round(getIndices(coords[0], j));
flattenIndex += index * ${s};
}
setOutput(getX(flattenIndex, coords[1]));
}
`}};function Gse(e){let{inputs:t,backend:r}=e,{params:n,indices:a}=t,s=a.shape,i=s[s.length-1],o=v.sizeFromShape(n.shape),[l,u,d,h]=C.prepareAndValidate(n,a),p=Ae({inputs:{x:a},backend:r,attrs:{shape:[u,i]}}),c=Ae({inputs:{x:n},backend:r,attrs:{shape:[v.sizeFromShape(n.shape)/d,d]}});if(r.shouldExecuteOnCPU([n,a])||n.dtype==="string"){let y=r.readSync(a.dataId),A=r.bufferSync(n),x=ete(y,A,n.dtype,u,i,d,h,n.shape,o);return r.makeTensorInfo(l,n.dtype,x.values)}let m=new Use(i,h,[u,d]),f=r.runWebGLProgram(m,[c,p],c.dtype),g=Ae({inputs:{x:f},backend:r,attrs:{shape:l}});return r.disposeIntermediateTensorInfo(p),r.disposeIntermediateTensorInfo(c),r.disposeIntermediateTensorInfo(f),g}var jse={kernelName:tl,backendName:"webgl",kernelFunc:Gse},Hse=class{constructor(e,t){this.variableNames=["A","indices"],this.outputShape=t,this.rank=t.length;let r=vt(this.rank),n=qse(e,2);this.userCode=`
void main() {
${r} resRC = getOutputCoords();
int index = int(getIndices(resRC.x, resRC.z));
float inBounds = (index >= 0) && (index < ${e[2]}) ? 1.0 : 0.0;
setOutput(inBounds * getA(${n}));
}
`}};function qse(e,t){let r=["resRC.x","resRC.y","resRC.z","resRC.w"],n=[];for(let a=0;a<e.length;a++)a===2?n.push("index"):n.push(`${r[a]}`);return n.join()}function zI(e){let{inputs:t,backend:r,attrs:n}=e,{x:a,indices:s}=t,{axis:i,batchDims:o}=n,l=v.parseAxisParam(i,a.shape)[0];if(Z().get("DEBUG")){let A=r.readSync(s.dataId),x=a.shape[l];for(let b=0;b<A.length;++b){let w=A[b];v.assert(w<=x-1&&w>=0,()=>`GatherV2: the index value ${w} is not in [0, ${x-1}]`)}}let u=C.segment_util.collectGatherOpShapeInfo(a,s,l,o),d=v.sizeFromShape(s.shape),h=[],p=Ae({inputs:{x:a},backend:r,attrs:{shape:[u.batchSize,u.outerSize,u.dimSize,u.sliceSize]}}),c=Ae({inputs:{x:s},backend:r,attrs:{shape:[u.batchSize,d/u.batchSize]}});h.push(p),h.push(c);let m=[u.batchSize,u.outerSize,d/u.batchSize,u.sliceSize];if(r.shouldExecuteOnCPU([a,s])||a.dtype==="string"){let A=r.bufferSync(c),x=r.bufferSync(p),b=tte(x,A,m);return h.forEach(w=>r.disposeIntermediateTensorInfo(w)),r.makeTensorInfo(u.outputShape,b.dtype,b.values)}let f=new Hse(p.shape,m),g=r.runWebGLProgram(f,[p,c],p.dtype);h.push(g);let y=Ae({inputs:{x:g},backend:r,attrs:{shape:u.outputShape}});return h.forEach(A=>r.disposeIntermediateTensorInfo(A)),y}var Xse={kernelName:el,backendName:"webgl",kernelFunc:zI},Kse="return float(a > b);",Zse=`
return vec4(greaterThan(a, b));
`,Yse=vr({opSnippet:Kse,packedOpSnippet:Zse,cpuKernelImpl:rte,dtype:"bool"}),Jse={kernelName:rl,backendName:"webgl",kernelFunc:Yse},Qse="return float(a >= b);",eie=`
return vec4(greaterThanEqual(a, b));
`,tie=vr({opSnippet:Qse,packedOpSnippet:eie,dtype:"bool",cpuKernelImpl:nte}),rie={kernelName:ci,backendName:"webgl",kernelFunc:tie};function nie(e){let{inputs:t,backend:r}=e,{input:n}=t;return OI(n,!0,r)}var aie={kernelName:vf,backendName:"webgl",kernelFunc:nie},sie="return float(!isnan(x) && !isinf(x));",iie=it({opSnippet:sie,dtype:"bool"}),oie={kernelName:td,backendName:"webgl",kernelFunc:iie},lie="return float(isinf(x));",uie=it({opSnippet:lie,dtype:"bool"}),die={kernelName:rd,backendName:"webgl",kernelFunc:uie},pie="return float(isnan(x));",hie=it({opSnippet:pie,dtype:"bool"}),cie={kernelName:nd,backendName:"webgl",kernelFunc:hie},fie="return float(a < b);",mie=`
return vec4(lessThan(a, b));
`,gie=vr({opSnippet:fie,packedOpSnippet:mie,cpuKernelImpl:ate,dtype:"bool"}),yie={kernelName:nl,backendName:"webgl",kernelFunc:gie},Aie="return float(a <= b);",xie=`
return vec4(lessThanEqual(a, b));
`,bie=vr({opSnippet:Aie,packedOpSnippet:xie,cpuKernelImpl:ste,dtype:"bool"}),vie={kernelName:al,backendName:"webgl",kernelFunc:bie};function wie(e){let{backend:t,attrs:r}=e,{start:n,stop:a,num:s}=r,i=ite(n,a,s);return t.makeTensorInfo([i.length],"float32",i)}var kie={kernelName:wf,backendName:"webgl",kernelFunc:wie},Iie=_d+`
return x < 0.0 ? 0./0. : log(x);
`,Sie=`
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;
`,Cie=it({opSnippet:Iie,packedOpSnippet:Sie,cpuKernelImpl:ote}),Tie={kernelName:gi,backendName:"webgl",kernelFunc:Cie},Nie=_d+`
return log(1.0 + x);
`,Eie=it({opSnippet:Nie}),Rie={kernelName:ad,backendName:"webgl",kernelFunc:Eie},Mie="return float(a >= 1.0 && b >= 1.0);",$ie=`
return vec4(
vec4(greaterThanEqual(a, vec4(1.0))) *
vec4(greaterThanEqual(b, vec4(1.0))));
`,Fie=vr({opSnippet:Mie,packedOpSnippet:$ie,dtype:"bool"}),_ie={kernelName:sl,backendName:"webgl",kernelFunc:Fie},Pie="return float(!(x >= 1.0));",Oie=it({opSnippet:Pie}),zie={kernelName:sd,backendName:"webgl",kernelFunc:Oie},Die="return float(a >= 1.0 || b >= 1.0);",Lie=`
return min(
vec4(greaterThanEqual(a, vec4(1.0))) +
vec4(greaterThanEqual(b, vec4(1.0))),
vec4(1.0));
`,Bie=vr({opSnippet:Die,packedOpSnippet:Lie,dtype:"bool"}),Wie={kernelName:dh,backendName:"webgl",kernelFunc:Bie},Vie=class{constructor(e,t,r,n,a){this.variableNames=["x"],this.outputShape=[];let s=t,i=e[3]-1;this.outputShape=e;let o,l=`float(${r}) + float(${n}) * sum`;a===.5?o=`inversesqrt(${l})`:a===1?o=`1.0/(${l})`:o=`exp(log(${l}) * float(-${a}));`,this.userCode=`
void main() {
ivec4 coords = getOutputCoords();
int b = coords[0];
int r = coords[1];
int c = coords[2];
int d = coords[3];
float x = getX(b, r, c, d);
float sum = 0.0;
for (int j = -${s}; j <= ${s}; j++) {
int idx = d + j;
if (idx >= 0 && idx <= ${i}) {
float z = getX(b, r, c, idx);
sum += z * z;
}
}
float val = x * ${o};
setOutput(val);
}
`}},Uie=class{constructor(e,t,r,n,a){this.variableNames=["x"],this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0;let s=t,i=e[3]-1;this.outputShape=e;let o,l=`float(${r}) + float(${n}) * sum`;a===.5?o=`inversesqrt(${l})`:a===1?o=`1.0/(${l})`:o=`exp(log(${l}) * float(-${a}));`,this.userCode=`
void main() {
ivec4 coords = getOutputCoords();
int b = coords.x;
int r = coords.y;
int c = coords.z;
int d = coords.w;
bool hasNextCol = d < ${this.outputShape[3]};
bool hasNextRow = c < ${this.outputShape[2]};
vec4 sum = vec4(0.);
vec4 xFragAtOutputCoords = getX(b, r, c, d);
vec4 xAtOutputCoords = vec4(
getChannel(xFragAtOutputCoords, vec2(c, d)),
hasNextCol ?
getChannel(xFragAtOutputCoords, vec2(c, d + 1)) : 0.0,
hasNextRow ?
getChannel(xFragAtOutputCoords , vec2(c + 1, d)) : 0.0,
(hasNextRow && hasNextCol) ?
getChannel(xFragAtOutputCoords, vec2(c + 1, d + 1)) : 0.0
);
int firstChannel = d - ${s};
vec2 cache = vec2(0.);
if(firstChannel >= 0){
vec4 firstChannelFrag = getX(b, r, c, firstChannel);
cache.x = getChannel(firstChannelFrag, vec2(c, firstChannel));
if(hasNextRow){
cache.y = getChannel(firstChannelFrag, vec2(c + 1, firstChannel));
}
}
ivec2 depth = ivec2(d, d + 1);
for (int j = - ${s}; j <= ${s}; j++) {
ivec2 idx = depth + j;
bvec2 aboveLowerBound = greaterThanEqual(idx, ivec2(0));
bvec2 belowUpperBound = lessThanEqual(idx, ivec2(${i}));
bool depthInRange = aboveLowerBound.x && belowUpperBound.x;
bool depthPlusOneInRange = aboveLowerBound.y && belowUpperBound.y;
if(depthInRange || depthPlusOneInRange){
vec4 z = vec4(0.);
vec4 xFragAtCurrentDepth;
z.xz = cache.xy;
if(depthPlusOneInRange && hasNextCol){
xFragAtCurrentDepth = idx.y != d ?
getX(b, r, c, idx.y) : xFragAtOutputCoords;
z.y = getChannel(xFragAtCurrentDepth, vec2(c, idx.y));
if(hasNextRow){
z.w = getChannel(xFragAtCurrentDepth, vec2(c + 1, idx.y));
}
}
cache.xy = z.yw;
sum += z * z;
}
}
vec4 result = xAtOutputCoords * ${o};
setOutput(result);
}
`}},Gie=e=>{let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{depthRadius:s,bias:i,alpha:o,beta:l}=n,u=Z().getBool("WEBGL_PACK_NORMALIZATION")?new Uie(a.shape,s,i,o,l):new Vie(a.shape,s,i,o,l);return r.runWebGLProgram(u,[a],a.dtype)},jie={kernelName:ph,backendName:"webgl",kernelFunc:Gie},Hie=class{constructor(e,t,r,n,a){this.variableNames=["inputImage","outputImage","dy"],this.outputShape=[],this.outputShape=e,this.depth=e[3],this.depthRadius=t,this.bias=r,this.alpha=n,this.beta=a,this.userCode=`
void main() {
ivec4 coords = getOutputCoords();
int b = coords[0];
int r = coords[1];
int c = coords[2];
float result = 0.0;
for (int d = 0; d < ${this.depth}; ++d) {
int depthBegin = int(max(0.0, float(d - ${t})));
int depthEnd = int(min(float(${this.depth}),
float(d + ${t} + 1)));
const int MIN_DEPTH_BEGIN = 0;
const int MAX_DEPTH_END = ${this.depth};
float norm = 0.0;
for (int k = MIN_DEPTH_BEGIN; k < MAX_DEPTH_END; ++k) {
if (k < depthBegin){
continue;
}
else if (k >= depthBegin && k < depthEnd) {
norm += getInputImage(b, r, c, k) * getInputImage(b, r, c, k);
}
else {
break;
}
}
norm = float(${n}) * norm + float(${r});
for(int k = MIN_DEPTH_BEGIN; k < MAX_DEPTH_END; ++k){
if (k < depthBegin){
continue;
}
else if (k >= depthBegin && k < depthEnd){
float dyi = -2.0 * float(${n})
* float(${a})
* getInputImage(b ,r ,c, k) * getOutputImage(b, r, c, d)
/ norm;
if (k == d) {
dyi += pow(norm, -1.0 * ${a});
}
if (k == coords[3]) {
dyi *= getDy(b, r, c, d);
result += dyi;
}
}
else {
break;
}
}
}
setOutput(result);
}
`}},qie=e=>{let{inputs:t,backend:r,attrs:n}=e,{x:a,y:s,dy:i}=t,{depthRadius:o,bias:l,alpha:u,beta:d}=n,h=new Hie(a.shape,o,l,u,d);return r.runWebGLProgram(h,[a,s,i],a.dtype)},Xie={kernelName:kf,backendName:"webgl",kernelFunc:qie};function Kie(e,t,r,n){let a=v.sizeFromShape(t),s=v.sizeFromShape(e.shape)/a,i=Ae({inputs:{x:e},attrs:{shape:[s,a]},backend:n}),o=Ll(i,e.dtype,"max",n),l=Ae({inputs:{x:o},attrs:{shape:r},backend:n});return n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(o),l}function DI(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{reductionIndices:s,keepDims:i}=n,o=a.shape.length,l=v.parseAxisParam(s,a.shape),u=l,d=C.getAxesPermutation(u,o),h=d!=null,p=r.shouldExecuteOnCPU([a]),c=a;if(h){if(p){let A=r.texData.get(c.dataId).values,x=new Array(o);for(let I=0;I<x.length;I++)x[I]=a.shape[d[I]];let b=EA(A,a.shape,a.dtype,d,x);c=r.makeTensorInfo(x,a.dtype);let w=r.texData.get(c.dataId);w.values=b}else c=Om(a,d,r);u=C.getInnerMostAxes(u.length,o)}C.assertAxesAreInnerMostDims("max",u,o);let[m,f]=C.computeOutAndReduceShapes(c.shape,u),g=m;i&&(g=C.expandShapeToKeepDim(m,l));let y;if(p){let A=r.texData.get(c.dataId).values,x=lte(A,v.sizeFromShape(f),g,a.dtype);y=r.makeTensorInfo(g,a.dtype);let b=r.texData.get(y.dataId);b.values=x}else y=Kie(c,f,g,r);return h&&r.disposeIntermediateTensorInfo(c),y}var Zie={kernelName:yi,backendName:"webgl",kernelFunc:DI},Yie=yI+`
return max(a, b);
`,Jie=`
vec4 result = vec4(max(a, b));
vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
`+_m+`
return result;
`,Qie=vr({opSnippet:Yie,packedOpSnippet:Jie,cpuKernelImpl:ute}),eoe={kernelName:Ai,backendName:"webgl",kernelFunc:Qie};function toe(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t;Ed(a,"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 d=C.computePool2DInfo(a.shape,s,i,u,o,l);if(d.filterWidth===1&&d.filterHeight===1&&v.arraysEqual(d.inShape,d.outShape))return mn({inputs:{x:a},backend:r});let h=new eh(d,"max",!1);return r.runWebGLProgram(h,[a],a.dtype)}var roe={kernelName:xi,backendName:"webgl",kernelFunc:toe};function noe(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{filterSize:s,strides:i,pad:o,dataFormat:l,dimRoundingMode:u}=n,d=[1,1,1],h=C.computePool3DInfo(a.shape,s,i,d,o,u,l),p=new MA(h,"max",!1);return r.runWebGLProgram(p,[a],a.dtype)}var aoe={kernelName:hh,backendName:"webgl",kernelFunc:noe},soe=class{constructor(e){this.variableNames=["dy","maxPos"],this.outputShape=e.inShape;let t=e.strideHeight,r=e.strideWidth,n=e.dilationHeight,a=e.effectiveFilterHeight,s=e.effectiveFilterWidth,i=a-1-e.padInfo.top,o=s-1-e.padInfo.left,l=a*s-1;this.userCode=`
const ivec2 pads = ivec2(${i}, ${o});
void main() {
ivec4 coords = getOutputCoords();
int b = coords[0];
int d = coords[3];
ivec2 dyRCCorner = coords.yz - pads;
int dyRCorner = dyRCCorner.x;
int dyCCorner = dyRCCorner.y;
// Convolve dy(?, ?, d) with pos mask(:, :, d) to get dx(xR, xC, d).
// ? = to be determined. : = across all values in that axis.
float dotProd = 0.0;
for (int wR = 0; wR < ${a};
wR += ${n}) {
float dyR = float(dyRCorner + wR) / ${t}.0;
if (dyR < 0.0 || dyR >= ${e.outHeight}.0 || fract(dyR) > 0.0) {
continue;
}
int idyR = int(dyR);
for (int wC = 0; wC < ${s}; wC++) {
float dyC = float(dyCCorner + wC) / ${r}.0;
if (dyC < 0.0 || dyC >= ${e.outWidth}.0 ||
fract(dyC) > 0.0) {
continue;
}
int idyC = int(dyC);
float dyValue = getDy(b, idyR, idyC, d);
int maxPosValue = ${l} - int(getMaxPos(b, idyR, idyC, d));
// Get the current value, check it against the value from the
// position matrix.
int curPosValue = wR * ${s} + wC;
float mask = float(maxPosValue == curPosValue ? 1.0 : 0.0);
dotProd += dyValue * mask;
}
}
setOutput(dotProd);
}
`}},ioe=class{constructor(e){this.variableNames=["dy","maxPos"],this.outputShape=e.inShape;let t=e.strideDepth,r=e.strideHeight,n=e.strideWidth,a=e.dilationDepth,s=e.dilationHeight,i=e.dilationWidth,o=e.effectiveFilterDepth,l=e.effectiveFilterHeight,u=e.effectiveFilterWidth,d=o-1-e.padInfo.front,h=l-1-e.padInfo.top,p=u-1-e.padInfo.left,c=o*l*u-1;this.userCode=`
const ivec3 pads = ivec3(${d}, ${h}, ${p});
void main() {
ivec5 coords = getOutputCoords();
int batch = coords.x;
int ch = coords.u;
ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads;
int dyDCorner = dyCorner.x;
int dyRCorner = dyCorner.y;
int dyCCorner = dyCorner.z;
// Convolve dy(?, ?, ?, ch) with pos mask(:, :, :, d) to get
// dx(xD, xR, xC, ch).
// ? = to be determined. : = across all values in that axis.
float dotProd = 0.0;
for (int wD = 0; wD < ${o};
wD += ${a}) {
float dyD = float(dyDCorner + wD) / ${t}.0;
if (dyD < 0.0 || dyD >= ${e.outDepth}.0 || fract(dyD) > 0.0) {
continue;
}
int idyD = int(dyD);
for (int wR = 0; wR < ${l};
wR += ${s}) {
float dyR = float(dyRCorner + wR) / ${r}.0;
if (dyR < 0.0 || dyR >= ${e.outHeight}.0 ||
fract(dyR) > 0.0) {
continue;
}
int idyR = int(dyR);
for (int wC = 0; wC < ${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 = ${c} -
int(getMaxPos(batch, idyD, idyR, idyC, ch));
// Get the current value, check it against the value from the
// position matrix.
int curPosValue =
wD * ${l} * ${u} +
wR * ${u} + wC;
float mask = float(maxPosValue == curPosValue ? 1.0 : 0.0);
dotProd += dyValue * mask;
}
}
}
setOutput(dotProd);
}
`}};function ooe(e){let{inputs:t,backend:r,attrs:n}=e,{dy:a,input:s}=t,i=s,{filterSize:o,strides:l,pad:u,dimRoundingMode:d}=n,h=[1,1,1],p=C.computePool3DInfo(i.shape,o,l,h,u,d),c=new MA(p,"max",!0),m=r.runWebGLProgram(c,[i],i.dtype),f=new ioe(p),g=r.runWebGLProgram(f,[a,m],i.dtype);return r.disposeIntermediateTensorInfo(m),g}var loe={kernelName:Sf,backendName:"webgl",kernelFunc:ooe};function uoe(e){let{inputs:t,backend:r,attrs:n}=e,{dy:a,input:s,output:i}=t,o=s;Ed([s,i],"maxPoolGrad");let{filterSize:l,strides:u,pad:d,dimRoundingMode:h}=n,p=C.computePool2DInfo(o.shape,l,u,1,d,h),c=!0,m=new eh(p,"max",c),f=r.runWebGLProgram(m,[o],o.dtype),g=new soe(p),y=r.runWebGLProgram(g,[a,f],o.dtype);return r.disposeIntermediateTensorInfo(f),y}var doe={kernelName:If,backendName:"webgl",kernelFunc:uoe};function poe(e,t,r,n){let a=new eh(r,"max",!1),s=n.runWebGLProgram(a,[e],"float32");a=new eh(r,"max",!0,!0,t);let i=n.runWebGLProgram(a,[e],"float32");return[s,i]}var hoe={kernelName:Cf,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:r})=>{let{x:n}=e,{filterSize:a,strides:s,pad:i,includeBatchInIndex:o}=t,l=r;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 d=C.computePool2DInfo(n.shape,a,s,u,i),[h,p]=poe(n,o,d,l);return[h,p]}};function coe(e,t,r,n){let a=v.sizeFromShape(t),s=v.sizeFromShape(e.shape)/a,i=Ae({inputs:{x:e},attrs:{shape:[s,a]},backend:n}),o=Ll(i,"float32","mean",n),l=Ae({inputs:{x:o},attrs:{shape:r},backend:n});return n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(o),l}var foe={kernelName:bi,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:r})=>{let{x:n}=e,{keepDims:a,axis:s}=t,i=r,o=n.shape.length,l=v.parseAxisParam(s,n.shape),u=l,d=C.getAxesPermutation(u,o),h=d!=null,p=i.shouldExecuteOnCPU([n]),c=[],m=n;if(h){if(p){let x=i.texData.get(m.dataId).values,b=new Array(o);for(let T=0;T<b.length;T++)b[T]=n.shape[d[T]];let w=EA(x,n.shape,n.dtype,d,b);m=i.makeTensorInfo(b,n.dtype);let I=i.texData.get(m.dataId);I.values=w}else m=Om(n,d,i);c.push(m),u=C.getInnerMostAxes(u.length,o)}C.assertAxesAreInnerMostDims("sum",u,o);let[f,g]=C.computeOutAndReduceShapes(m.shape,u),y=f;a&&(y=C.expandShapeToKeepDim(f,l));let A=coe(m,g,y,i);for(let x of c)i.disposeIntermediateTensorInfo(x);return A}};function moe(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{axis:s,keepDims:i}=n,o=a.shape.length,l=v.parseAxisParam(s,a.shape),u=l,d=C.getAxesPermutation(u,o),h=a;d!=null&&(h=Ur({inputs:{x:a},backend:r,attrs:{perm:d}}),u=C.getInnerMostAxes(u.length,a.shape.length)),C.assertAxesAreInnerMostDims("min",u,o);let[p,c]=C.computeOutAndReduceShapes(h.shape,u),m=v.sizeFromShape(c),f=Ae({inputs:{x:h},backend:r,attrs:{shape:[-1,m]}}),g=Ll(f,f.dtype,"min",r),y;if(i){let A=C.expandShapeToKeepDim(p,l);y=Ae({inputs:{x:g},backend:r,attrs:{shape:A}})}else y=Ae({inputs:{x:g},backend:r,attrs:{shape:p}});return r.disposeIntermediateTensorInfo(f),r.disposeIntermediateTensorInfo(g),d!=null&&r.disposeIntermediateTensorInfo(h),y}var goe={kernelName:vi,backendName:"webgl",kernelFunc:moe},yoe=yI+`
return min(a, b);
`,Aoe=`
vec4 result = vec4(min(a, b));
vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
`+_m+`
return result;
`,xoe=vr({opSnippet:yoe,packedOpSnippet:Aoe,cpuKernelImpl:dte}),boe={kernelName:wi,backendName:"webgl",kernelFunc:xoe},voe=class{constructor(e,t,r){this.variableNames=["x"],this.outputShape=t.map((u,d)=>u[0]+e[d]+u[1]);let n=e.length,a=vt(n),s=t.map(u=>u[0]).join(","),i=t.map((u,d)=>u[0]+e[d]).join(","),o=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,n),l=r==="reflect"?0:1;if(n===1){this.userCode=`
int start = ${s};
int end = ${i};
void main() {
int outC = getOutputCoords();
if (outC < start) {
outC = start * 2 - outC - ${l};
} else if(outC >= end) {
outC = (end - 1) * 2 - outC + ${l};
}
setOutput(getX(outC - start));
}
`;return}this.userCode=`
${a} start = ${a}(${s});
${a} end = ${a}(${i});
void main() {
${a} outC = getOutputCoords();
for (int i = 0; i < ${n}; i++) {
if (outC[i] < start[i]) {
outC[i] = start[i] * 2 - outC[i] - ${l};
} else if(outC[i] >= end[i]) {
outC[i] = (end[i] - 1) * 2 - outC[i] + ${l};
}
}
${a} coords = outC - start;
setOutput(getX(${o}));
}
`}},woe=class{constructor(e,t,r){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t.map((c,m)=>c[0]+e[m]+c[1]);let n=e.length,a=vt(n),s=t.map(c=>c[0]).join(","),i=t.map((c,m)=>c[0]+e[m]).join(","),o=Br("rc",n),l=Br("source",n),u=`${o[n-1]} < ${this.outputShape[n-1]}`,d=n===1?"source":`vec2(${l.slice(-2).join()})`,h=r==="reflect"?0:1,p="";if(n===1){let c=`
${a} source = rc;
if (source < start) {
source = start * 2 - source - ${h};
} else if (source >= end) {
source = (end - 1) * 2 - source + ${h};
}
source -= start;
`;p=`
${a} rc = outputLoc;
${c}
result[0] = getChannel(getX(${l.join()}), ${d});
${o[n-1]} += 1;
if(${u}) {
${c}
result[1] = getChannel(getX(${l.join()}), ${d});
}
`}else{let c=`
${a} source = rc;
${a} lt = ${a}(lessThan(source, start));
${a} gte = ${a}(greaterThanEqual(source, end));
${a} orig = 1 - (lt + gte);
source = orig * source +
lt * (start * 2 - source - ${h}) +
gte * ((end - 1) * 2 - source + ${h});
source -= start;
`;p=`
${a} rc = outputLoc;
${c}
result[0] = getChannel(getX(${l.join()}), ${d});
${o[n-1]} += 1;
if(${u}) {
${c}
result[1] = getChannel(getX(${l.join()}), ${d});
}
rc = outputLoc;
${o[n-2]} += 1;
if(${o[n-2]} < ${this.outputShape[n-2]}) {
${c}
result[2] = getChannel(getX(${l.join()}), ${d});
${o[n-1]} += 1;
if(${u}) {
${c}
result[3] = getChannel(getX(${l.join()}), ${d});
}
}
`}this.userCode=`
const ${a} start = ${a}(${s});
const ${a} end = ${a}(${i});
void main() {
${a} outputLoc = getOutputCoords();
vec4 result = vec4(0.);
${p}
setOutput(result);
}
`}},koe=({inputs:e,backend:t,attrs:r})=>{let{x:n}=e,{paddings:a,mode:s}=r,i=Z().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new woe(n.shape,a,s):new voe(n.shape,a,s);return t.runWebGLProgram(i,[n],n.dtype)},Ioe={kernelName:ki,backendName:"webgl",kernelFunc:koe},Soe=`if (b == 0.0) return NAN;
return mod(a, b);`,Coe=`
vec4 result = mod(a, b);
vec4 isNaN = vec4(equal(b, vec4(0.0)));
`+_m+`
return result;
`,Toe=vr({opSnippet:Soe,packedOpSnippet:Coe}),Noe={kernelName:id,backendName:"webgl",kernelFunc:Toe},Eoe=class{constructor(e,t,r){this.variableNames=["probs"],this.customUniforms=[{name:"seed",type:"float"}],this.outputShape=[e,r],this.userCode=`
void main() {
ivec2 coords = getOutputCoords();
int batch = coords[0];
float r = random(seed);
float cdf = 0.0;
for (int i = 0; i < ${t-1}; i++) {
cdf += getProbs(batch, i);
if (r < cdf) {
setOutput(float(i));
return;
}
}
// If no other event happened, last event happened.
setOutput(float(${t-1}));
}
`}},Roe=`
if (a == b) {
return 1.0;
};
return a / b;`,Moe=`
// 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;
`,LI=vr({opSnippet:Roe,packedOpSnippet:Moe,checkOutOfBounds:!0}),$oe={kernelName:oi,backendName:"webgl",kernelFunc:LI},o7="return a - b;",BI=vr({opSnippet:o7,packedOpSnippet:o7,supportsComplex:!0,cpuKernelImpl:Tte}),Foe={kernelName:Li,backendName:"webgl",kernelFunc:BI};function WI(e){let{inputs:t,backend:r,attrs:n}=e,{logits:a}=t,{dim:s}=n,i=v.parseAxisParam([s],a.shape),o=DI({inputs:{x:a},backend:r,attrs:{reductionIndices:i,keepDims:!1}}),l=C.expandShapeToKeepDim(o.shape,i),u=Ae({inputs:{x:o},backend:r,attrs:{shape:l}}),d=BI({inputs:{a,b:u},backend:r}),h=PI({inputs:{x:d},backend:r}),p=zm({inputs:{x:h},backend:r,attrs:{axis:i,keepDims:!1}}),c=Ae({inputs:{x:p},backend:r,attrs:{shape:l}}),m=LI({inputs:{a:h,b:c},backend:r});return r.disposeIntermediateTensorInfo(o),r.disposeIntermediateTensorInfo(u),r.disposeIntermediateTensorInfo(d),r.disposeIntermediateTensorInfo(h),r.disposeIntermediateTensorInfo(p),r.disposeIntermediateTensorInfo(c),m}var _oe={kernelName:zi,backendName:"webgl",kernelFunc:WI};function Poe(e){let{inputs:t,backend:r,attrs:n}=e,{logits:a}=t,{numSamples:s,seed:i,normalized:o}=n,l=o?a:WI({inputs:{logits:a},backend:r,attrs:{dim:a.shape.length-1}}),u=l.shape[0],d=l.shape[1],h=new Eoe(u,d,s),p=[[i]],c=r.runWebGLProgram(h,[l],"int32",p);return o||r.disposeIntermediateTensorInfo(l),c}var Ooe={kernelName:Tf,backendName:"webgl",kernelFunc:Poe},zoe=Yn+`
return -x;
`,Doe=`
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 Loe(e){let{inputs:t,backend:r}=e,{x:n}=t;if(r.shouldExecuteOnCPU([n])){let s=r.texData.get(n.dataId),[i,o]=hte(s.values,n.shape,n.dtype);return r.makeTensorInfo(o,n.dtype,i)}let a;return Z().getBool("WEBGL_PACK_UNARY_OPERATIONS")?a=new Co(n.shape,Doe):a=new Xa(n.shape,zoe),r.runWebGLProgram(a,[n],n.dtype)}var Boe={kernelName:il,backendName:"webgl",kernelFunc:Loe},Woe=Kn.nonMaxSuppressionV3Impl;function Voe(e){C.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:r,attrs:n}=e,{boxes:a,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l}=n,u=r.readSync(a.dataId),d=r.readSync(s.dataId),{selectedIndices:h}=Woe(u,d,i,o,l);return r.makeTensorInfo([h.length],"int32",new Int32Array(h))}var Uoe={kernelName:ll,backendName:"webgl",kernelFunc:Voe},Goe=Kn.nonMaxSuppressionV4Impl;function joe(e){C.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:r,attrs:n}=e,{boxes:a,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l,padToMaxOutputSize:u}=n,d=r.readSync(a.dataId),h=r.readSync(s.dataId),{selectedIndices:p,validOutputs:c}=Goe(d,h,i,o,l,u);return[r.makeTensorInfo([p.length],"int32",new Int32Array(p)),r.makeTensorInfo([],"int32",new Int32Array([c]))]}var Hoe={kernelName:od,backendName:"webgl",kernelFunc:joe},qoe=Kn.nonMaxSuppressionV5Impl;function Xoe(e){C.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:r,attrs:n}=e,{boxes:a,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l,softNmsSigma:u}=n,d=r.readSync(a.dataId),h=r.readSync(s.dataId),p=i,c=o,m=l,f=u,{selectedIndices:g,selectedScores:y}=qoe(d,h,p,c,m,f);return[r.makeTensorInfo([g.length],"int32",new Int32Array(g)),r.makeTensorInfo([y.length],"float32",new Float32Array(y))]}var Koe={kernelName:ul,backendName:"webgl",kernelFunc:Xoe},Zoe=class{constructor(e,t,r,n){this.variableNames=["indices"],this.outputShape=[e,t],this.userCode=`
void main() {
ivec2 coords = getOutputCoords();
int index = round(getIndices(coords.x));
setOutput(mix(float(${n}), float(${r}),
float(index == coords.y)));
}
`}},Yoe=e=>{let{inputs:t,backend:r,attrs:n}=e,{indices:a}=t,{depth:s,onValue:i,offValue:o}=n,l=v.sizeFromShape(a.shape),u=new Zoe(l,s,i,o),d=Ae({inputs:{x:a},backend:r,attrs:{shape:[l]}}),h=r.runWebGLProgram(u,[d],a.dtype);r.disposeIntermediateTensorInfo(d);let p=[...a.shape,s],c=Ae({inputs:{x:h},backend:r,attrs:{shape:p}});return r.disposeIntermediateTensorInfo(h),c},Joe={kernelName:pl,backendName:"webgl",kernelFunc:Yoe};function ef(e){let{inputs:t,backend:r}=e,{x:n}=t;if(n.dtype==="complex64"){let a=Kh({inputs:{input:n},backend:r}),s=ef({inputs:{x:a},backend:r}),i=Dm({inputs:{input:n},backend:r}),o=ef({inputs:{x:i},backend:r}),l=ji({inputs:{real:s,imag:o},backend:r});return r.disposeIntermediateTensorInfo(a),r.disposeIntermediateTensorInfo(s),r.disposeIntermediateTensorInfo(i),r.disposeIntermediateTensorInfo(o),l}else return Zh({attrs:{shape:n.shape,dtype:n.dtype,value:n.dtype==="string"?"":0},backend:r})}var Qoe={kernelName:Tl,backendName:"webgl",kernelFunc:ef};function VI(e){let{inputs:t,backend:r}=e,{x:n}=t;if(n.dtype==="string")throw new Error("onesLike is not supported under string dtype");if(n.dtype==="complex64"){let a=Kh({inputs:{input:n},backend:r}),s=VI({inputs:{x:a},backend:r}),i=Dm({inputs:{input:n},backend:r}),o=ef({inputs:{x:i},backend:r}),l=ji({inputs:{real:s,imag:o},backend:r});return r.disposeIntermediateTensorInfo(a),r.disposeIntermediateTensorInfo(s),r.disposeIntermediateTensorInfo(i),r.disposeIntermediateTensorInfo(o),l}else return Zh({attrs:{shape:n.shape,dtype:n.dtype,value:1},backend:r})}var ele={kernelName:dl,backendName:"webgl",kernelFunc:VI};function tle(e){let{inputs:t,backend:r,attrs:n}=e,{axis:a}=n;if(t.length===1)return my({inputs:{input:t[0]},backend:r,attrs:{dim:a}});let s=t[0].shape,i=t[0].dtype;t.forEach(d=>{v.assertShapesMatch(s,d.shape,"All tensors passed to stack must have matching shapes"),v.assert(i===d.dtype,()=>"All tensors passed to stack must have matching dtypes")});let o=[],l=t.map(d=>{let h=my({inputs:{input:d},backend:r,attrs:{dim:a}});return o.push(h),h}),u=NI({inputs:l,backend:r,attrs:{axis:a}});return o.forEach(d=>r.disposeIntermediateTensorInfo(d)),u}var rle={kernelName:hl,backendName:"webgl",kernelFunc:tle},nle=class{constructor(e,t,r){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,a=vt(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=`
${a} start = ${a}(${s});
${a} end = ${a}(${i});
void main() {
${a} outC = getOutputCoords();
if (any(lessThan(outC, start)) || any(greaterThanEqual(outC, end))) {
setOutput(value);
} else {
${a} coords = outC - start;
setOutput(getX(${o}));
}
}
`}},ale=class{constructor(e,t,r){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,a=vt(n),s=t.map(m=>m[0]).join(","),i=t.map((m,f)=>m[0]+e[f]).join(","),o=Br("rc",n),l=Br("source",n),u=`${o[n-1]} < ${this.outputShape[n-1]}`,d=n===1?"source":`vec2(${l.slice(-2).join()})`,h=[`${a} rc = outputLoc;`,`${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}) {`],p=n===1?"rc < start || rc >= end":"any(lessThan(rc, start)) || any(greaterThanEqual(rc, end))",c="";for(let m=0,f=n===1?2:4;m<f;m++)c+=`
${h[m]}
if (${p}) {
result[${m}] = float(value);
} else {
${a} source = rc - start;
result[${m}] = getChannel(getX(${l.join()}), ${d});
}
`;c+=n===1?"} ":"}}",this.userCode=`
const ${a} start = ${a}(${s});
const ${a} end = ${a}(${i});
void main() {
${a} outputLoc = getOutputCoords();
vec4 result = vec4(0.);
${c}
setOutput(result);
}
`}},UI=e=>{let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{paddings:s,constantValue:i}=n;if(v.sizeFromShape(a.shape)===0){let u=s.map((d,h)=>d[0]+a.shape[h]+d[1]);return Zh({backend:r,attrs:{shape:u,value:i,dtype:a.dtype}})}let o=Z().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new ale(a.shape,s,i):new nle(a.shape,s,i),l=[[i]];return r.runWebGLProgram(o,[a],a.dtype,l)},sle={kernelName:Si,backendName:"webgl",kernelFunc:UI},ile=`
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);
`,ole=`
// 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;
vec4 isNaN = vec4(lessThan(a, vec4(0.0))) * vec4(lessThan(floor(b), b));
`+_m+`
return result;
`,lle=vr({opSnippet:ile,packedOpSnippet:ole}),ule={kernelName:Ci,backendName:"webgl",kernelFunc:lle};function dle(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{axis:s,keepDims:i}=n,o=a.shape.length,l=[],u=v.parseAxisParam(s,a.shape),d=u,h=C.getAxesPermutation(d,o),p=a;h!=null&&(p=Ur({inputs:{x:a},backend:r,attrs:{perm:h}}),d=C.getInnerMostAxes(d.length,o),l.push(p)),C.assertAxesAreInnerMostDims("prod",d,o);let c;if(r.shouldExecuteOnCPU([p])){let m=r.texData.get(p.dataId).values,{outVals:f,outShape:g,outDtype:y}=fte(p.shape,p.dtype,m,d);c=r.makeTensorInfo(g,y,f)}else{let[m,f]=C.computeOutAndReduceShapes(p.shape,d),g=v.sizeFromShape(f),y=Ae({inputs:{x:p},backend:r,attrs:{shape:[-1,g]}}),A=wh(a.dtype),x=Ll(y,A,"prod",r);c=Ae({inputs:{x},backend:r,attrs:{shape:m}}),l.push(y),l.push(x)}if(i){l.push(c);let m=C.expandShapeToKeepDim(c.shape,u);c=Ae({inputs:{x:c},backend:r,attrs:{shape:m}})}return l.forEach(m=>r.disposeIntermediateTensorInfo(m)),c}var ple={kernelName:Ni,backendName:"webgl",kernelFunc:dle},GI=e=>{let{backend:t,attrs:r}=e,{start:n,stop:a,step:s,dtype:i}=r,o=mte(n,a,s,i);return t.makeTensorInfo([o.length],i,o)},hle={kernelName:ld,backendName:"webgl",kernelFunc:GI},cle="return 1.0 / x;",fle=it({opSnippet:cle}),mle={kernelName:ud,backendName:"webgl",kernelFunc:fle},gle=Yn+`
return (x < 0.0) ? 0.0 : x;
`,yle=`
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;
`,Ale=it({opSnippet:gle,packedOpSnippet:yle}),xle={kernelName:Ei,backendName:"webgl",kernelFunc:Ale},ble=Yn+`
return (x < 0.0) ? 0.0 : min(6.0, x);
`,vle=`
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;
`,wle=it({opSnippet:ble,packedOpSnippet:vle}),kle={kernelName:Mi,backendName:"webgl",kernelFunc:wle},Ile=class{constructor(e,t,r,n,a){this.variableNames=["A"],this.outputShape=[];let[s,i,o,l]=e;this.outputShape=[s,t,r,l];let u=[n&&t>1?i-1:i,n&&r>1?o-1:o],d=[n&&t>1?t-1:t,n&&r>1?r-1:r],h;a?h="(vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC - vec2(0.5)":h="vec2(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
const vec2 effectiveInputOverOutputRatioRC = vec2(
${u[0]/d[0]},
${u[1]/d[1]});
const vec2 inputShapeRC = vec2(${i}.0, ${o}.0);
void main() {
ivec4 coords = getOutputCoords();
int b = coords[0];
int d = coords[3];
ivec2 yRC = coords.yz;
// Fractional source index.
vec2 sourceFracIndexRC = ${h};
// Compute the 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);
}
`}},Sle=class{constructor(e,t,r,n,a){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[];let[s,i,o,l]=e;this.outputShape=[s,t,r,l];let u=[n&&t>1?i-1:i,n&&r>1?o-1:o],d=[n&&t>1?t-1:t,n&&r>1?r-1:r],h;a?h="(vec3(yRC) + vec3(0.5)) * effectiveInputOverOutputRatioRC - vec3(0.5)":h="vec3(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
const vec3 effectiveInputOverOutputRatioRC = vec3(
${u[0]/d[0]},
${u[1]/d[1]},
${u[1]/d[1]});
const vec3 inputShapeRC = vec3(${i}.0, ${o}.0,
${o}.0);
float getAValue(int b, int r, int c, int d) {
return getChannel(getA(b, r, c, d), vec2(c, d));
}
void main() {
ivec4 coords = getOutputCoords();
int b = coords[0];
int d = coords[3];
// Calculate values for next column in yRC.z.
ivec3 yRC = coords.yzz + ivec3(0, 0, 1);
// Fractional source index.
vec3 sourceFracIndexRC = ${h};
// Compute the four integer indices.
ivec3 sourceFloorRC = ivec3(max(sourceFracIndexRC, vec3(0.0)));
ivec3 sourceCeilRC = ivec3(
min(inputShapeRC - 1.0, ceil(sourceFracIndexRC)));
// Should we calculate next column and row elements in 2x2 packed cell.
bool hasNextCol = d < ${l-1};
bool hasNextRow = coords.z < ${r-1};
// In parallel, construct four corners for all four components in
// packed 2x2 cell.
vec4 topLeft = vec4(
getAValue(b, sourceFloorRC.x, sourceFloorRC.y, d),
hasNextCol ? getAValue(b, sourceFloorRC.x, sourceFloorRC.y, d + 1)
: 0.0,
hasNextRow ? getAValue(b, sourceFloorRC.x, sourceFloorRC.z, d)
: 0.0,
(hasNextRow && hasNextCol) ?
getAValue(b, sourceFloorRC.x, sourceFloorRC.z, d + 1) : 0.0);
vec4 bottomLeft = vec4(
getAValue(b, sourceCeilRC.x, sourceFloorRC.y, d),
hasNextCol ? getAValue(b, sourceCeilRC.x, sourceFloorRC.y, d + 1)
: 0.0,
hasNextRow ? getAValue(b, sourceCeilRC.x, sourceFloorRC.z, d)
: 0.0,
(hasNextRow && hasNextCol) ?
getAValue(b, sourceCeilRC.x, sourceFloorRC.z, d + 1) : 0.0);
vec4 topRight = vec4(
getAValue(b, sourceFloorRC.x, sourceCeilRC.y, d),
hasNextCol ? getAValue(b, sourceFloorRC.x, sourceCeilRC.y, d + 1)
: 0.0,
hasNextRow ? getAValue(b, sourceFloorRC.x, sourceCeilRC.z, d)
: 0.0,
(hasNextRow && hasNextCol) ?
getAValue(b, sourceFloorRC.x, sourceCeilRC.z, d + 1) : 0.0);
vec4 bottomRight = vec4(
getAValue(b, sourceCeilRC.x, sourceCeilRC.y, d),
hasNextCol ? getAValue(b, sourceCeilRC.x, sourceCeilRC.y, d + 1)
: 0.0,
hasNextRow ? getAValue(b, sourceCeilRC.x, sourceCeilRC.z, d)
: 0.0,
(hasNextRow && hasNextCol) ?
getAValue(b, sourceCeilRC.x, sourceCeilRC.z, d + 1) : 0.0);
vec3 fracRC = sourceFracIndexRC - vec3(sourceFloorRC);
vec4 top = mix(topLeft, topRight, fracRC.yyzz);
vec4 bottom = mix(bottomLeft, bottomRight, fracRC.yyzz);
vec4 newValue = mix(top, bottom, fracRC.x);
setOutput(newValue);
}
`}};function Cle(e){let{inputs:t,backend:r,attrs:n}=e,{images:a}=t,{alignCorners:s,halfPixelCenters:i,size:o}=n,[l,u]=o,d=Z().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new Sle(a.shape,l,u,s,i):new Ile(a.shape,l,u,s,i);return r.runWebGLProgram(d,[a],"float32")}var Tle={kernelName:Ri,backendName:"webgl",kernelFunc:Cle},Nle=class{constructor(e,t,r){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t;let[,n,a]=t,[,s,i]=e,o=[r&&s>1?n-1:n,r&&i>1?a-1:a],l=[r&&s>1?s-1:s,r&&i>1?i-1:i],u=o[0]/l[0],d=o[1]/l[1],h=1/u,p=1/d,c=Math.ceil(h)*2+2,m=Math.ceil(p)*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(${d});
const float invHeightScale = float(${h});
const float invWidthScale = float(${p});
const int winHeight = int(${c});
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), ${a-1}.0));
float dxCLerp = dxC - float(leftDxCIndex);
float inverseDxCLerp = 1.0 - dxCLerp;
if (r == topDxRIndex && c == leftDxCIndex) {
// topLeft
accumulator +=
getDy(b, dyR, dyC, d) * inverseDxRLerp * inverseDxCLerp;
}
if (r == topDxRIndex && c == rightDxCIndex) {
// topRight
accumulator += getDy(b, dyR, dyC, d) * inverseDxRLerp * dxCLerp;
}
if (r == bottomDxRIndex && c == leftDxCIndex) {
// bottomLeft
accumulator += getDy(b, dyR, dyC, d) * dxRLerp * inverseDxCLerp;
}
if (r == bottomDxRIndex && c == rightDxCIndex) {
// bottomRight
accumulator += getDy(b, dyR, dyC, d) * dxRLerp * dxCLerp;
}
}
}
// End loop over dy
setOutput(accumulator);
}
`}};function Ele(e){let{inputs:t,backend:r,attrs:n}=e,{images:a,dy:s}=t,{alignCorners:i}=n,o=new Nle(s.shape,a.shape,i);return r.runWebGLProgram(o,[s],s.dtype)}var Rle={kernelName:Ef,backendName:"webgl",kernelFunc:Ele},Mle=class{constructor(e,t,r,n,a){this.variableNames=["A"],this.outputShape=[];let[s,i,o,l]=e;this.outputShape=[s,t,r,l];let u=[n&&t>1?i-1:i,n&&r>1?o-1:o],d=[n&&t>1?t-1:t,n&&r>1?r-1:r],h=n?"0.5":"0.0",p;a?p="max((vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC, vec2(0.0))":p="vec2(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
const vec2 effectiveInputOverOutputRatioRC = vec2(
${u[0]/d[0]},
${u[1]/d[1]});
const vec2 inputShapeRC = vec2(${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 = ${p};
// Compute the coordinators of nearest neighbor point.
ivec2 sourceNearestRC = ivec2(
min(inputShapeRC - 1.0, floor(sourceFracIndexRC + ${h})));
float newValue = getA(b, sourceNearestRC.x, sourceNearestRC.y, d);
setOutput(newValue);
}
`}},$le=class{constructor(e,t,r,n,a){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[];let[s,i,o,l]=e;this.outputShape=[s,t,r,l];let u=[n&&t>1?i-1:i,n&&r>1?o-1:o],d=[n&&t>1?t-1:t,n&&r>1?r-1:r],h=n?"0.5":"0.0",p;a?p="max((vec3(yRC) + vec3(0.5)) * effectiveInputOverOutputRatioRC, vec3(0.0))":p="vec3(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
const vec3 effectiveInputOverOutputRatioRC = vec3(
${u[0]/d[0]},
${u[1]/d[1]},
${u[1]/d[1]});
const vec3 inputShapeRC = vec3(${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 = ${p};
// Compute the coordinators of nearest neighbor point.
ivec3 sourceNearestRC = ivec3(
min(inputShapeRC - 1.0, floor(sourceFracIndexRC + ${h})));
// Should we calculate next column and row elements in 2x2 packed cell.
bool hasNextCol = d < ${l-1};
bool hasNextRow = coords.z < ${r-1};
vec4 newValue = vec4(
getAValue(b, sourceNearestRC.x, sourceNearestRC.y, d),
hasNextCol ? getAValue(b, sourceNearestRC.x, sourceNearestRC.y, d + 1)
: 0.0,
hasNextRow ? getAValue(b, sourceNearestRC.x, sourceNearestRC.z, d)
: 0.0,
(hasNextRow && hasNextCol) ?
getAValue(b, sourceNearestRC.x, sourceNearestRC.z, d + 1) : 0.0);
setOutput(newValue);
}
`}};function Fle(e){let{inputs:t,backend:r,attrs:n}=e,{images:a}=t,{alignCorners:s,halfPixelCenters:i,size:o}=n,[l,u]=o,d=Z().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new $le(a.shape,l,u,s,i):new Mle(a.shape,l,u,s,i);return r.runWebGLProgram(d,[a],a.dtype)}var _le={kernelName:dd,backendName:"webgl",kernelFunc:Fle},Ple=class{constructor(e,t,r){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t;let[,n,a]=t,[,s,i]=e,o=[r&&s>1?n-1:n,r&&i>1?a-1:a],l=[r&&s>1?s-1:s,r&&i>1?i-1:i],u=o[0]/l[0],d=o[1]/l[1],h=1/u,p=1/d,c=Math.ceil(h)*2+2,m=Math.ceil(p)*2+2;this.userCode=`
void main() {
ivec4 coords = getOutputCoords();
int b = coords[0];
int d = coords[3];
int r = coords[1];
int c = coords[2];
float accumulator = 0.0;
const float heightScale = float(${u});
const float widthScale = float(${d});
const float invHeightScale = float(${h});
const float invWidthScale = float(${p});
const int winHeight = int(${c});
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),
${r} ? float(round(sourceFracRow)) :
float(floor(sourceFracRow))));
int sourceNearestCol = int(min(
float(int(${a}) - 1),
${r} ? float(round(sourceFracCol)) :
float(floor(sourceFracCol))));
if (r == sourceNearestRow && c == sourceNearestCol) {
accumulator += getDy(b, dyR, dyC, d);
}
}
}
// End loop over dy
setOutput(accumulator);
}
`}};function Ole(e){let{inputs:t,backend:r,attrs:n}=e,{images:a,dy:s}=t,{alignCorners:i}=n,o=new Ple(s.shape,a.shape,i);return r.runWebGLProgram(o,[s],s.dtype)}var zle={kernelName:Nf,backendName:"webgl",kernelFunc:Ole},Dle=class{constructor(e,t){this.variableNames=["x"];let r=e.length;if(r>4)throw new Error(`WebGL backend: Reverse of rank-${r} tensor is not yet supported`);if(this.outputShape=e,r===1){this.userCode=`
void main() {
int coord = getOutputCoords();
setOutput(getX(${e[0]} - coord - 1));
}
`;return}let n=i=>t.indexOf(i)!==-1&&e[i]!==1?`${e[i]} - coords[${i}] - 1`:`coords[${i}]`,a=e.map((i,o)=>n(o)).join(","),s=vt(r);this.userCode=`
void main() {
${s} coords = getOutputCoords();
setOutput(getX(${a}));
}
`}},Lle=class{constructor(e,t){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0;let r=e.length;if(r>4)throw new Error(`WebGL backend: Reverse of rank-${r} tensor is not yet supported`);this.outputShape=e;let n=Br("rc",r),a=`${n[r-1]} + 1 < ${this.outputShape[r-1]}`,s=`${n[r-2]} + 1 < ${this.outputShape[r-2]}`,i=vt(r);r===1?this.userCode=`
void main(){
int rc = getOutputCoords();
vec4 result = vec4(0.);
result.r = getChannel(getX(${e[0]} - rc - 1),
${e[0]} - rc - 1);
if(${a}){
result.g = getChannel(getX(${e[0]} - (rc + 1) - 1),
${e[0]} - (rc + 1) - 1);
}
setOutput(result);
}
`:this.userCode=`
void main() {
${i} rc = getOutputCoords();
vec4 result = vec4(0.);
result.r = ${o(n.slice())};
if(${a}){
result.g = ${l(n.slice())};
}
if(${s}) {
result.b = ${u(n.slice())};
if(${a}) {
result.a = ${d(n.slice())};
}
}
setOutput(result);
}
`;function o(c){return h(c)}function l(c){return c[r-1]="("+c[r-1]+" + 1)",h(c)}function u(c){return c[r-2]="("+c[r-2]+" + 1)",h(c)}function d(c){return c[r-1]="("+c[r-1]+" + 1)",c[r-2]="("+c[r-2]+" + 1)",h(c)}function h(c){let m=e.map((y,A)=>p(A,c)),f=m.join(","),g=m.slice(-2).join(",");return`getChannel(getX(${f}), vec2(${g}))`}function p(c,m){return t.indexOf(c)!==-1&&e[c]!==1?`${e[c]} - ${m[c]} - 1`:`${m[c]}`}}};function Ble(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{dims:s}=n,i=a.shape.length,o=v.parseAxisParam(s,a.shape);if(i===0)return mn({inputs:{x:a},backend:r});let l=Z().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new Lle(a.shape,o):new Dle(a.shape,o);return r.runWebGLProgram(l,[a],a.dtype)}var Wle={kernelName:fl,backendName:"webgl",kernelFunc:Ble},Vle=class{constructor(e,t){this.variableNames=["Image"],this.outputShape=[],this.customUniforms=[{name:"params",type:"vec4"}];let r=e[1],n=e[2];this.outputShape=e;let a="";typeof t=="number"?a=`float outputValue = ${t.toFixed(2)};`:a=`
vec3 fill = vec3(${t.join(",")});
float outputValue = fill[coords[3]];`,this.userCode=`
void main() {
ivec4 coords = getOutputCoords();
int x = coords[2];
int y = coords[1];
float coordXFloat = (float(x) - params[0]) * params[3] -
(float(y) - params[1]) * params[2];
float coordYFloat = (float(x) - params[0]) * params[2] +
(float(y) - params[1]) * params[3];
int coordX = int(round(coordXFloat + params[0]));
int coordY = int(round(coordYFloat + params[1]));
${a}
if(coordX >= 0 && coordX < ${n} && coordY >= 0 && coordY < ${r}) {
outputValue = getImage(coords[0], coordY, coordX, coords[3]);
}
setOutput(outputValue);
}
`}},Ule={kernelName:Nl,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:r})=>{let{image:n}=e,{radians:a,fillValue:s,center:i}=t,o=r,l=new Vle(n.shape,s),[u,d]=C.getImageCenter(i,n.shape[1],n.shape[2]),h=[[u,d,Math.sin(a),Math.cos(a)]];return o.runWebGLProgram(l,[n],n.dtype,h)}},Gle=`
// OpenGL ES does not support round function.
// The algorithm is based on banker's rounding.
float base = floor(x);
if ((x - base) < 0.5) {
return floor(x);
} else if ((x - base) > 0.5) {
return ceil(x);
} else {
if (mod(base, 2.0) == 0.0) {
return base;
} else {
return base + 1.0;
}
}
`,jle=it({opSnippet:Gle}),Hle={kernelName:ml,backendName:"webgl",kernelFunc:jle},qle="return inversesqrt(x);",Xle=it({opSnippet:qle,cpuKernelImpl:gte}),Kle={kernelName:$i,backendName:"webgl",kernelFunc:Xle},jI=class{constructor(e,t,r,n,a,s,i=!0){this.variableNames=["updates","indices","defaultValue"],this.outputShape=s;let o=vt(a.length),l=vt(s.length),u="";r===1?u="i":r===2&&(u="i, j");let d=`getIndices(${u})`,h="";n===1?h="i":n===2&&(h="i, coords[1]");let p=`getUpdates(${h})`,c=t>1?"strides[j]":"strides";this.userCode=`
${o} strides = ${o}(${a});
void main() {
${l} coords = getOutputCoords();
float sum = 0.0;
bool found = false;
for (int i = 0; i < ${e}; i++) {
int flattenedIndex = 0;
for (int j = 0; j < ${t}; j++) {
int index = round(${d});
flattenedIndex += index * ${c};
}
if (flattenedIndex == coords[0]) {
sum += ${p};
found = true;
}
}
setOutput(mix(getDefaultValue(), sum, float(found)));
}
`}};function Zle(e){let{inputs:t,backend:r,attrs:n}=e,{indices:a,updates:s}=t,{shape:i}=n,{sliceRank:o,numUpdates:l,sliceSize:u,strides:d,outputSize:h}=C.calculateShapes(s,a,i),p=[h/u,u];if(h===0)return r.makeTensorInfo(i,a.dtype);let c=Ae({inputs:{x:a},backend:r,attrs:{shape:[l,o]}}),m=Ae({inputs:{x:s},backend:r,attrs:{shape:[l,u]}}),f=r.makeTensorInfo([],"float32",new Float32Array([0])),g=new jI(l,o,c.shape.length,m.shape.length,d,p),y=r.runWebGLProgram(g,[m,c,f],m.dtype),A=Ae({inputs:{x:y},backend:r,attrs:{shape:i}});return r.disposeIntermediateTensorInfo(c),r.disposeIntermediateTensorInfo(m),r.disposeIntermediateTensorInfo(y),r.disposeIntermediateTensorInfo(f),A}var Yle={kernelName:gl,backendName:"webgl",kernelFunc:Zle},Jle=class{constructor(e,t,r,n){this.variableNames=["sortedSequence","values"],this.customUniforms=[{name:"numInputs",type:"int"}],this.outputShape=[e,r];let a="while (left < right) {",s=`for (int i = 0; i < ${Math.ceil(Math.log2(t+1))}; ++i) { if (left >= right) break;`,i=Z().getNumber("WEBGL_VERSION")===2?a:s,o=n==="left"?"<":"<=";this.userCode=`
int findBound(int batch, float value) {
int left = 0;
int right = numInputs;
int mid;
${i}
mid = (left + right) / 2;
if (getSortedSequence(batch, mid) ${o} value) {
left = mid + 1;
} else {
right = mid;
}
}
return right;
}
void main() {
ivec2 coords = getOutputCoords();
int batch = coords[0];
int valueIndex = coords[1];
float value = getValues(batch, valueIndex);
setOutput(float(findBound(batch, value)));
}
`}};function Qle(e){let{inputs:t,backend:r,attrs:n}=e,{sortedSequence:a,values:s}=t,{side:i}=n,o=new Jle(a.shape[0],a.shape[1],s.shape[1],i),l=[[a.shape[1]]];return r.runWebGLProgram(o,[a,s],"int32",l)}var eue={kernelName:Rf,backendName:"webgl",kernelFunc:Qle},tue=class{constructor(e,t,r){this.variableNames=["c","a","b"],this.outputShape=t;let n,a;if(r>4)throw Error(`Where for rank ${r} is not yet supported`);if(r===1)a="resRC",n="resRC";else{let i=["resRC.x","resRC.y","resRC.z","resRC.w"],o=[],l=[];for(let u=0;u<t.length;u++)l.push(`${i[u]}`),u<e&&o.push(`${i[u]}`);n=o.join(),a=l.join()}let s=vt(r);this.userCode=`
void main() {
${s} resRC = getOutputCoords();
float cVal = getC(${n});
if (cVal >= 1.0) {
setOutput(getA(${a}));
} else {
setOutput(getB(${a}));
}
}
`}};function rue(e){let{inputs:t,backend:r}=e,{condition:n,t:a,e:s}=t,i=new tue(n.shape.length,a.shape,a.shape.length);return r.runWebGLProgram(i,[n,a,s],Tr(a.dtype,s.dtype))}var nue={kernelName:yl,backendName:"webgl",kernelFunc:rue},aue=`
// 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);
`,sue=it({opSnippet:aue}),iue={kernelName:pd,backendName:"webgl",kernelFunc:sue},oue=_d+`
return 1.0 / (1.0 + exp(-1.0 * x));
`,lue=`
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;
`,uue=it({opSnippet:oue,packedOpSnippet:lue,cpuKernelImpl:Ate}),due={kernelName:_i,backendName:"webgl",kernelFunc:uue},pue=`
if (isnan(x)) { return 0.0; }
return sign(x);
`,hue=it({opSnippet:pue}),cue={kernelName:hd,backendName:"webgl",kernelFunc:hue},fue=_d+`
return sin(x);
`,mue=it({opSnippet:fue}),gue={kernelName:Fi,backendName:"webgl",kernelFunc:mue},yue=`
float e2x = exp(x);
return (e2x - 1.0 / e2x) / 2.0;
`,Aue=it({opSnippet:yue}),xue={kernelName:xl,backendName:"webgl",kernelFunc:Aue},bue=`
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;
`,vue=it({opSnippet:bue}),wue={kernelName:cd,backendName:"webgl",kernelFunc:vue},kue=e=>{let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{blockShape:s,paddings:i}=n;v.assert(a.shape.length<=4,()=>"spaceToBatchND for rank > 4 with a WebGL backend not implemented yet");let o=s.reduce((y,A)=>y*A),l=[[0,0]];l.push(...i);for(let y=1+s.length;y<a.shape.length;++y)l.push([0,0]);let u=[],d=UI({inputs:{x:a},backend:r,attrs:{paddings:l,constantValue:0}}),h=C.getReshaped(d.shape,s,o,!1),p=C.getPermuted(h.length,s.length,!1),c=C.getReshapedPermuted(d.shape,s,o,!1),m=Ae({inputs:{x:d},backend:r,attrs:{shape:h}}),f=Ur({inputs:{x:m},backend:r,attrs:{perm:p}}),g=Ae({inputs:{x:f},backend:r,attrs:{shape:c}});return u.push(d),u.push(m),u.push(f),u.forEach(y=>r.disposeIntermediateTensorInfo(y)),g},Iue={kernelName:bl,backendName:"webgl",kernelFunc:kue};function Sue(e){let{inputs:t,backend:r}=e,{indices:n,values:a,denseShape:s,defaultValue:i}=t;if(s.shape.length!==1)throw new Error(`Dense shape must be a vector, saw:
${s.shape}`);if(n.shape.length!==2)throw new Error(`Indices must be a matrix, saw:
${n.shape}`);if(a.shape.length!==1)throw new Error(`Values must be a vector, saw:
${a.shape}`);if(i.shape.length!==0)throw new Error(`Default value must be a scalar, saw:
${i.shape}`);let o=r.readSync(n.dataId),l=r.readSync(a.dataId),u=r.readSync(s.dataId),d=r.readSync(i.dataId)[0],[h,p,c,m,f]=bte(o,n.shape,n.dtype,l,a.dtype,u,d);return[r.makeTensorInfo(p,n.dtype,h),r.makeTensorInfo([p[0]],a.dtype,c),r.makeTensorInfo([m.length],"bool",new Uint8Array(m.map(g=>Number(g)))),r.makeTensorInfo([f.length],n.dtype,new Int32Array(f))]}var Cue={kernelName:fh,backendName:"webgl",kernelFunc:Sue};function Tue(e){let{inputs:t,backend:r}=e,{inputIndices:n,inputShape:a,newShape:s}=t;if(n.shape.length!==2)throw new Error(`Input indices should be a matrix but received shape ${n.shape}`);if(a.shape.length!==1)throw new Error(`Input shape should be a vector but received shape ${a.shape}`);if(s.shape.length!==1)throw new Error(`Target shape should be a vector but received shape ${s.shape}`);let i=Array.from(r.readSync(a.dataId)),o=r.readSync(n.dataId),l=Array.from(r.readSync(s.dataId)),[u,d,h]=vte(o,n.shape,n.dtype,i,l);return[r.makeTensorInfo(d,n.dtype,u),r.makeTensorInfo([h.length],s.dtype,new Int32Array(h))]}var Nue={kernelName:fd,backendName:"webgl",kernelFunc:Tue};function Eue(e){let{inputs:t,backend:r}=e,{data:n,indices:a,segmentIds:s}=t;if(n.shape.length<1)throw new Error("Data should be at least 1 dimensional but received scalar");if(a.shape.length!==1)throw new Error(`Indices should be a vector but received shape
${a.shape}`);if(s.shape.length!==1)throw new Error(`Segment ids should be a vector but received shape
${s.shape}`);let i=r.readSync(n.dataId),o=r.readSync(a.dataId),l=r.readSync(s.dataId),[u,d]=hI(i,n.shape,n.dtype,o,l,!0);return r.makeTensorInfo(d,n.dtype,u)}var Rue={kernelName:mh,backendName:"webgl",kernelFunc:Eue};function Mue(e){let{inputs:t,backend:r}=e,{data:n,indices:a,segmentIds:s}=t;if(n.shape.length<1)throw new Error("Data should be at least 1 dimensional but received scalar");if(a.shape.length!==1)throw new Error(`Indices should be a vector but received shape
${a.shape}`);if(s.shape.length!==1)throw new Error(`Segment ids should be a vector but received shape
${s.shape}`);let i=r.readSync(n.dataId),o=r.readSync(a.dataId),l=r.readSync(s.dataId),[u,d]=hI(i,n.shape,n.dtype,o,l);return r.makeTensorInfo(d,n.dtype,u)}var $ue={kernelName:gh,backendName:"webgl",kernelFunc:Mue};function Fue(e){let{inputs:t,backend:r,attrs:n}=e,{sparseIndices:a,sparseValues:s,defaultValue:i}=t,{outputShape:o}=n,{sliceRank:l,numUpdates:u,sliceSize:d,strides:h,outputSize:p}=C.calculateShapes(s,a,o),c=!1;if(s.dtype==="string"){let y=r.bufferSync(a),A=r.bufferSync(s),x=v.decodeString(r.readSync(i.dataId)[0]),b=yte(y,A,o,p,d,u,l,h,x,c);return r.makeTensorInfo(o,b.dtype,b.values)}let m=new jI(u,l,a.shape.length,s.shape.length,h,[p,1],c),f=r.runWebGLProgram(m,[s,a,i],s.dtype),g=Ae({inputs:{x:f},backend:r,attrs:{shape:o}});return r.disposeIntermediateTensorInfo(f),g}var _ue={kernelName:yh,backendName:"webgl",kernelFunc:Fue};function Pue(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{numOrSizeSplits:s,axis:i}=n,o=v.parseAxisParam(i,a.shape)[0],l=C.prepareSplitSize(a,s,o),u=a.shape.length,d=new Array(u).fill(0),h=a.shape.slice();return l.map(p=>{let c=[...h];c[o]=p;let m=Pd({inputs:{x:a},backend:r,attrs:{begin:d,size:c}});return d[o]+=p,m})}var Oue={kernelName:vl,backendName:"webgl",kernelFunc:Pue},l7="return sqrt(x);",zue=it({opSnippet:l7,packedOpSnippet:l7,cpuKernelImpl:wte}),Due={kernelName:Pi,backendName:"webgl",kernelFunc:zue},Lue="return x * x;",Bue=it({opSnippet:Lue}),Wue={kernelName:md,backendName:"webgl",kernelFunc:Bue},u7="return (a - b) * (a - b);",Vue=vr({opSnippet:u7,packedOpSnippet:u7}),Uue={kernelName:Di,backendName:"webgl",kernelFunc:Vue};function Gue({inputs:e,attrs:t,backend:r}){let{x:n}=e,a=Yn+`
return x > 0.0 ? 1.0 : float(${t.alpha});
`,s=new Xa(n.shape,a);return r.runWebGLProgram(s,[n],n.dtype)}var jue={kernelName:Wi,backendName:"webgl",kernelFunc:Gue},Hue=class{constructor(e,t,r){this.variableNames=["x"],this.outputShape=r;let n=r.length,a=vt(r.length),s=vt(r.length),i="";if(n===1)i="coords * strides + begin";else{let o=0;i=r.map((l,u)=>(o++,r.length===1?`coords * strides[${u}] + begin[${u}]`:`coords[${o-1}] * strides[${u}] + begin[${u}]`)).join(",")}this.userCode=`
${a} begin = ${a}(${e});
${a} strides = ${a}(${t});
void main() {
${s} coords = getOutputCoords();
setOutput(getX(${i}));
}
`}};function que(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{begin:s,end:i,strides:o,beginMask:l,endMask:u,ellipsisMask:d,newAxisMask:h,shrinkAxisMask:p}=n,{finalShapeSparse:c,finalShape:m,isIdentity:f,sliceDim0:g,isSimpleSlice:y,begin:A,end:x,strides:b}=Dt.sliceInfo(a.shape,s,i,o,l,u,d,h,p),w;if(f)w=Ae({inputs:{x:a},backend:r,attrs:{shape:m}});else if(g||y){v.assert(a.shape.length>=1,()=>`Input must have rank at least 1, got: ${a.shape.length}`);let T=Dt.computeOutShape(A,x,b),E=Pd({inputs:{x:a},backend:r,attrs:{begin:A,size:T}});w=Ae({inputs:{x:E},backend:r,attrs:{shape:m}}),r.disposeIntermediateTensorInfo(E)}else if(r.shouldExecuteOnCPU([a])){let T=r.readSync(a.dataId),E=Le(a.shape,a.dtype,T),R=kte(c,E,b,A);w=r.makeTensorInfo(m,a.dtype,R.values)}else{let T=new Hue(A,b,c);w=r.runWebGLProgram(T,[a],a.dtype)}let I=Ae({inputs:{x:w},backend:r,attrs:{shape:m}});return r.disposeIntermediateTensorInfo(w),I}var Xue={kernelName:wl,backendName:"webgl",kernelFunc:que};function Kue(e){let{inputs:t,backend:r,attrs:n}=e,{separator:a,nGramWidths:s,leftPad:i,rightPad:o,padWidth:l,preserveShortSequences:u}=n,{data:d,dataSplits:h}=t,p=r.readSync(d.dataId),c=r.readSync(h.dataId),[m,f]=Ite(p,c,a,s,i,o,l,u);return[r.makeTensorInfo([m.length],"string",m),r.makeTensorInfo(h.shape,"int32",f)]}var Zue={kernelName:Ah,backendName:"webgl",kernelFunc:Kue};function Yue(e){let{inputs:t,backend:r,attrs:n}=e,{skipEmpty:a}=n,{input:s,delimiter:i}=t;if(s.dtype!=="string")throw new Error("Input must be of datatype string");if(s.shape.length!==1)throw new Error(`Input must be a vector, got shape: ${s.shape}`);if(i.shape.length!==0)throw new Error(`Delimiter must be a scalar, got shape: ${i.shape}`);let o=r.readSync(s.dataId),l=r.readSync(i.dataId)[0],[u,d,h]=Ste(o,l,a),p=d.length;return[r.makeTensorInfo([p,2],"int32",u),r.makeTensorInfo([p],"string",d),r.makeTensorInfo([2],"int32",new Int32Array(h))]}var Jue={kernelName:Mf,backendName:"webgl",kernelFunc:Yue};function Que(e){let{inputs:t,backend:r,attrs:n}=e,{numBuckets:a}=n,{input:s}=t;if(s.dtype!=="string")throw new Error("Input must be of datatype string");if(a<=0)throw new Error("Number of buckets must be at least 1");let i=r.readSync(s.dataId),o=Cte(i,a);return r.makeTensorInfo(s.shape,"int32",o)}var ede={kernelName:$f,backendName:"webgl",kernelFunc:Que},tde="return tan(x);",rde=it({opSnippet:tde}),nde={kernelName:kl,backendName:"webgl",kernelFunc:rde},ade=`
float e2x = exp(-2.0 * abs(x));
return sign(x) * (1.0 - e2x) / (1.0 + e2x);
`,sde=it({opSnippet:ade}),ide={kernelName:Bi,backendName:"webgl",kernelFunc:sde},ode=class{constructor(e,t){this.variableNames=["A"];let r=new Array(e.length);for(let s=0;s<r.length;s++)r[s]=e[s]*t[s];this.outputShape=r,this.rank=r.length;let n=vt(this.rank),a=lde(e);this.userCode=`
void main() {
${n} resRC = getOutputCoords();
setOutput(getA(${a}));
}
`}};function lde(e){let t=e.length;if(t>5)throw Error(`Tile for rank ${t} is not yet supported`);if(t===1)return`imod(resRC, ${e[0]})`;let r=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u"],n=[];for(let a=0;a<e.length;a++)n.push(`imod(${r[a]}, ${e[a]})`);return n.join()}function HI(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{reps:s}=n;if(a.dtype==="string"||a.shape.length>5){let o=r.readSync(a.dataId),l=a.dtype==="string"?o.map(h=>v.decodeString(h)):o,u=Le(a.shape,a.dtype,l),d=Nte(u,s);return r.makeTensorInfo(d.shape,d.dtype,d.values)}let i=new ode(a.shape,s);return r.runWebGLProgram(i,[a],a.dtype)}var ude={kernelName:es,backendName:"webgl",kernelFunc:HI},dde=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));
}
}
`}},pde=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 go(e,t){t!==null&&e.disposeIntermediateTensorInfo(t)}function d7(e){let t=1;for(;t<e;)t*=2;return t}function hde(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{k:s,sorted:i}=n,o=Z().getNumber("TOPK_LAST_DIM_CPU_HANDOFF_SIZE_THRESHOLD"),l=Z().getNumber("TOPK_K_CPU_HANDOFF_THRESHOLD"),u=a.shape,d=u[u.length-1];if(r.shouldExecuteOnCPU([a])||d<o||s>l){let R=r.readSync(a.dataId),[O,M]=Ete(R,u,a.dtype,s,i);return[r.makeTensorInfo(O.shape,O.dtype,O.values),r.makeTensorInfo(M.shape,M.dtype,M.values)]}if(s===0)return u[u.length-1]=0,[r.makeTensorInfo(u,a.dtype,[]),r.makeTensorInfo(u,"int32",[])];if(d===1)return[a,Zh({attrs:{shape:u,dtype:"int32",value:0},backend:r})];let h=r.texData.get(a.dataId),p=h!==null&&h.isPacked,c=p?r.unpackTensor(a):a,m=v.sizeFromShape(u)/d,f=Ae({inputs:{x:c},attrs:{shape:[m,d]},backend:r});p&&go(r,c);let g=d7(s),y=d7(d),A=null,x=()=>A===null?[f,f]:[f,A],b=(R,O,M)=>{let S=x(),P=new dde(M),z=[[d],[A===null?1:0],[Number.NEGATIVE_INFINITY],[R],[O]],j=A;A=r.runWebGLProgram(P,S,"int32",z),go(r,j)};for(let R=1;R<g;R*=2){let O=R*2;for(let M=R;M>=1;M/=2)b(O,M,[m,y])}for(let R=y;R>g;R/=2){let O=x(),M=new pde([m,R/2]),S=[[d],[A===null?1:0],[g]],P=A;A=r.runWebGLProgram(M,O,"int32",S),go(r,P);let z=g/2,j=z*2;for(let K=z;K>=1;K/=2)b(j,K,A.shape)}let w=A;A=Pd({inputs:{x:A},backend:r,attrs:{begin:0,size:[m,s]}}),go(r,w);let I=zI({inputs:{x:f,indices:A},backend:r,attrs:{axis:1,batchDims:1}});go(r,f);let T=u.slice(0,-1);T.push(s),w=A,A=Ae({inputs:{x:A},attrs:{shape:T},backend:r}),go(r,w);let E=I;return I=Ae({inputs:{x:I},attrs:{shape:T},backend:r}),go(r,E),[I,A]}var cde={kernelName:Il,backendName:"webgl",kernelFunc:hde},fde=class{constructor(e,t,r,n,a,s){this.variableNames=["Image","Transforms"],this.outputShape=s;let i=r==="nearest"?1:2,o;switch(n){case"constant":o=1;break;case"reflect":o=2;break;case"wrap":o=3;break;case"nearest":o=4;break;default:o=1;break}this.userCode=`
float mapCoord(float outCoord, float len) {
float inCoord = outCoord;
if(${o} == 2) {
if (inCoord < 0.0) {
if (len <= 1.0) {
inCoord = 0.0;
} else {
float sz2 = 2.0 * len;
if (inCoord < sz2) {
inCoord = sz2 * float(int(float(-inCoord / sz2))) +
inCoord;
}
inCoord = inCoord < -len ? inCoord + sz2 : -inCoord - 1.0;
}
} else if (inCoord > len - 1.0) {
if (len <= 1.0) {
inCoord = 0.0;
} else {
float sz2 = 2.0 * len;
inCoord -= sz2 * float(int(float(inCoord / sz2)));
if (inCoord >= len) {
inCoord = sz2 - inCoord - 1.0;
}
}
}
return clamp(inCoord, 0.0, len - 1.0);
} else if (${o} == 3) {
if (inCoord < 0.0) {
if (len <= 1.0) {
inCoord = 0.0;
} else {
float sz = len - 1.0;
inCoord += len * (float(int(float(-inCoord / sz))) + 1.0);
}
} else if (inCoord > len - 1.0) {
if (len <= 1.0) {
inCoord = 0.0;
} else {
float sz = len - 1.0;
inCoord -= len * float(int(float(inCoord / sz)));
}
}
return clamp(inCoord, 0.0, len - 1.0);
} else if (${o} == 4) {
return clamp(outCoord, 0.0, len - 1.0);
} else {
return outCoord;
}
}
float readWithFillValue(int batch, int coordY, int coordX,
int channel) {
float outputValue;
if (0 <= coordY && coordY < ${e} && 0 <= coordX && coordX < ${t}) {
outputValue = getImage(batch, coordY, coordX, channel);
} else {
outputValue = float(${a});
}
return outputValue;
}
void main() {
ivec4 coords = getOutputCoords();
float outputValue;
int batch = coords[0];
int x = coords[2];
int y = coords[1];
int channel = coords[3];
float xf = float(x);
float yf = float(y);
float a1 = getTransforms(batch, 0);
float a2 = getTransforms(batch, 1);
float a3 = getTransforms(batch, 2);
float b1 = getTransforms(batch, 3);
float b2 = getTransforms(batch, 4);
float b3 = getTransforms(batch, 5);
float c1 = getTransforms(batch, 6);
float c2 = getTransforms(batch, 7);
float projection = c1 * xf + c2 * yf + 1.0;
if (projection == 0.0) {
outputValue = float(${a});
} else {
float inX = (a1 * xf + a2 * yf + a3) / projection;
float inY = (b1 * xf + b2 * yf + b3) / projection;
float mapX = mapCoord(inX, float(${t}));
float mapY = mapCoord(inY, float(${e}));
if (${i} == 1) {
int coordY = int(round(mapY));
int coordX = int(round(mapX));
outputValue = readWithFillValue(batch, coordY, coordX,
channel);
} else {
float yFloor = floor(mapY);
float xFloor = floor(mapX);
float yCeil = yFloor + 1.0;
float xCeil = xFloor + 1.0;
float valueYFloor = (xCeil - mapX) *
readWithFillValue(batch, int(yFloor), int(xFloor), channel) +
(mapX - xFloor) *
readWithFillValue(batch, int(yFloor), int(xCeil), channel);
float valueYCeil = (xCeil - mapX) *
readWithFillValue(batch, int(yCeil), int(xFloor), channel) +
(mapX - xFloor) *
readWithFillValue(batch, int(yCeil), int(xCeil), channel);
outputValue = (yCeil - mapY) * valueYFloor +
(mapY - yFloor) * valueYCeil;
}
}
setOutput(outputValue);
}
`}};function mde(e){let{inputs:t,backend:r,attrs:n}=e,{image:a,transforms:s}=t,{interpolation:i,fillMode:o,fillValue:l,outputShape:u}=n,[d,h,p,c]=a.shape,[m,f]=u!=null?u:[h,p],g=[d,m,f,c],y=new fde(h,p,i,o,l,g);return r.runWebGLProgram(y,[a,s],"float32")}var gde={kernelName:Sl,backendName:"webgl",kernelFunc:mde};function yde(e){let{inputs:t,attrs:r,backend:n}=e,{axis:a}=r,{x:s}=t;Ed(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}=Rte(i,a,s.shape,s.dtype);return[n.makeTensorInfo(l,s.dtype,o),n.makeTensorInfo([u.length],"int32",u)]}var Ade={kernelName:Ff,backendName:"webgl",kernelFunc:yde};function xde(e){let{inputs:t,backend:r,attrs:n}=e,{value:a}=t,{axis:s}=n;s<0&&(s+=a.shape.length);let i=a,o=i.shape.length,l=a.shape[s],u=new Array(o-1),d=0;for(let f=0;f<o;f++)f!==s&&(u[d++]=i.shape[f]);let h=[],p=new Array(o).fill(0),c=i.shape.slice();c[s]=1;let m=new Array(l);for(let f=0;f<m.length;f++){p[s]=f;let g=Pd({inputs:{x:i},backend:r,attrs:{begin:p,size:c}}),y=Ae({inputs:{x:g},backend:r,attrs:{shape:u}});m[f]=y,h.push(g)}return h.forEach(f=>r.disposeIntermediateTensorInfo(f)),m}var bde={kernelName:Cl,backendName:"webgl",kernelFunc:xde},vde=class{constructor(e,t){this.variableNames=["x","segmentIds"];let r=e.windowSize,n=e.batchSize,a=e.inSize,s=e.numSegments,i=s*Math.ceil(a/r);this.outputShape=[n,i];let o="0.0",l="sumValue",u=Math.floor(r/4)*4,d=r%4,h=`
sumValue += dot(values, segFilter);
`,p="";a%r>0&&(p=`
if (inIdx < 0 || inIdx >= ${a}) {
return initializationValue;
}
`);let c="";a%r>0&&(c=`
if (inIdx < 0 || inIdx >= ${a}) {
return -1.0;
}
`),this.userCode=`
const float initializationValue = ${o};
float getValue(int batch, int inIdx) {
${p}
return getX(batch, inIdx);
}
float getSegmentIdAtIndex(int inIdx) {
${c}
return getSegmentIds(inIdx);
}
void main() {
ivec2 coords = getOutputCoords();
int batch = coords[0];
int outIdx = coords[1];
int inOffset = int(floor(float(outIdx) / float(
${s})) * float(${r}));
int currentSeg = int(mod(float(outIdx), float(${s})));
float sumValue = 0.0;
for (int i = 0; i < ${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
);
${h}
}
int inIdx = inOffset + ${u};
if (${d===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
);
${h}
} else if (${d===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
);
${h}
} else if (${d===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
);
${h}
}
setOutput(${l});
}
`}};function wde(e){let{inputs:t,backend:r,attrs:n}=e,{x:a,segmentIds:s}=t,{numSegments:i}=n,o=a.shape.length,l=[],u=0,d=C.getAxesPermutation([u],o),h=a;d!=null&&(h=Ur({inputs:{x:a},backend:r,attrs:{perm:d}}),l.push(h),u=C.getInnerMostAxes(1,o)[0]);let p=C.segment_util.computeOutShape(h.shape,u,i),c=v.sizeFromShape([h.shape[u]]),m=Ae({inputs:{x:h},backend:r,attrs:{shape:[-1,c]}});l.push(m);let f=wh(a.dtype),g=(b,w,I,T,E)=>{let R=b.shape[0],O=b.shape[1],M=C.segment_util.segOpComputeOptimalWindowSize(O,E),S={windowSize:M,inSize:O,batchSize:R,numSegments:E},P=new vde(S,w),z=r.compileAndRun(P,[b,I],T);if(l.push(z),z.shape[1]===E)return z;let j=GI({backend:r,attrs:{start:0,stop:E,step:1,dtype:"float32"}}),K=HI({inputs:{x:j},backend:r,attrs:{reps:[O/M]}});return l.push(j),l.push(K),g(z,w,K,T,E)},y=g(m,"unsortedSegmentSum",s,f,i),A=Ae({inputs:{x:y},backend:r,attrs:{shape:p}}),x=A;if(d!=null){l.push(A);let b=C.getUndoAxesPermutation(d);x=Ur({inputs:{x},backend:r,attrs:{perm:b}})}return l.forEach(b=>r.disposeIntermediateTensorInfo(b)),x}var kde={kernelName:xh,backendName:"webgl",kernelFunc:wde},Ide=[Sre,Tre,Rre,Fre,Pre,Dre,Bre,Vre,Hre,Xre,Yre,ene,nne,one,dne,hne,fne,Ane,bne,wne,Cne,Fne,Pne,zne,Une,jne,Kne,ire,Jne,nae,oae,cae,mae,yae,xae,vae,Iae,Tae,Rae,$ae,_ae,Oae,Lae,Wae,jae,qae,Zae,Qae,tse,sse,use,cse,gse,xse,bse,wse,Ise,Cse,Nse,Rse,_se,zse,Bse,Vse,jse,Xse,Jse,rie,sre,aie,tae,oie,die,cie,lre,yie,vie,kie,Tie,Rie,_ie,zie,Wie,jie,Xie,Zie,eoe,roe,aoe,loe,doe,hoe,foe,goe,boe,Ioe,Noe,Ooe,cre,Boe,Uoe,Hoe,Koe,Lne,Joe,ele,rle,sle,ule,dre,ple,hle,Bne,$oe,mle,xle,kle,mre,Tle,Rle,_le,zle,Wle,Ule,Hle,Kle,Yle,eue,nue,iue,due,cue,gue,xue,Mne,_oe,wue,Iue,Cue,Nue,Rue,$ue,_ue,Oue,Due,Wue,Uue,jue,Xue,Zue,Jue,ede,Foe,wre,nde,ide,ude,cde,gde,kre,Ade,bde,kde,Qoe];for(let e of Ide)qn(e);var Hi=Z();Hi.registerFlag("WEBGPU_DEFERRED_SUBMIT_BATCH_SIZE",()=>15);Hi.registerFlag("WEBGPU_CPU_FORWARD",()=>!0);Hi.registerFlag("WEBGPU_MATMUL_WORK_PER_THREAD",()=>4);Hi.registerFlag("WEBGPU_USE_NAIVE_CONV2D_TRANSPOSE",()=>!1);Hi.registerFlag("WEBGPU_USE_LOW_POWER_GPU",()=>!1);Hi.registerFlag("WEBGPU_CPU_HANDOFF_SIZE_THRESHOLD",()=>1e3);Hi.registerFlag("WEBGPU_USE_PROFILE_TOOL",()=>!1);Hi.registerFlag("WEBGPU_USE_IMPORT",()=>!1);var Sde="return a + b;",Cde="return areal * breal - aimag * bimag;",Tde="return areal * bimag + aimag * breal;",Nde="return a / b;",Ede="return a * b;",Rde="return (a - b) * (a - b);",Mde="return a - b;",$de="return f32(a == b);",Fde="return vec4<f32>(a == b);",_de="return f32(a > b);",Pde="return vec4<f32>(a > b);",Ode="return f32(a >= b);",zde="return vec4<f32>(a >= b);",Dde="return f32(a < b);",Lde="return vec4<f32>(a < b);",Bde="return f32(a <= b);",Wde="return vec4<f32>(a <= b);",Vde="return f32(f32(a) >= 1.0 && f32(b) >= 1.0);",Ude=`return (vec4<f32>(a >= vec4<f32>(1.0)) *
vec4<f32>(b >= vec4<f32>(1.0)));`,Gde=`
if (isnan(a)) { return a; }
if (isnan(b)) { return b; }
`,qI=`
if (isNaN.r) {
resultTemp.r = uniforms.NAN;
}
if (isNaN.g) {
resultTemp.g = uniforms.NAN;
}
if (isNaN.b) {
resultTemp.b = uniforms.NAN;
}
if (isNaN.a) {
resultTemp.a = uniforms.NAN;
}
`,jde=`
let s = sign(a) * sign(b);
let ia = i32(round(a));
let ib = i32(round(b));
return f32(idiv(ia, ib, s));
`,Hde=`
let ia = vec4<i32>(round(a));
let ib = vec4<i32>(round(b));
let cond = ib != vec4<i32>(0);
var resultTemp = vec4<i32>(0);
let s = sign(a) * sign(b);
// Windows (D3D) wants guaranteed non-zero int division at compile-time.
if (cond[0]) {
resultTemp[0] = idiv(ia[0], ib[0], s[0]);
}
if (cond[1]) {
resultTemp[1] = idiv(ia[1], ib[1], s[1]);
}
if (cond[2]) {
resultTemp[2] = idiv(ia[2], ib[2], s[2]);
}
if (cond[3]) {
resultTemp[3] = idiv(ia[3], ib[3], s[3]);
}
return vec4<f32>(resultTemp);
`,qde="return f32(a != b);",Xde="return vec4<f32>(a != b);",Kde=`
if(a < 0.0 && floor(b) < b) {
return uniforms.NAN;
}
if (b == 0.0) {
return 1.0;
}
if (round(abs(b) % 2.0) != 1.0) {
return pow(abs(a), b);
}
return sign(a) * pow(abs(a), b);
`,Zde=`
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;
${qI}
return resultTemp;
`,Yde="if (a < 0.0) { return b * a; } return a;",Jde=`
let aLessThanZero = vec4<f32>(a < vec4<f32>(0.0));
return (aLessThanZero * (b * a)) + ((vec4<f32>(1.0) - aLessThanZero) * a);
`;function p7(e,t){let r=t?qI:Gde;return t?`
var resultTemp = vec4<f32>(${e}(a, b));
let isNaN = isnanVec4(a) | isnanVec4(b);
`+r+`
return resultTemp;
`:r+`
return ${e}(a, b);
`}function Yh(e,t){switch(e){case 0:return Ede;case 1:return Sde;case 2:return Mde;case 3:return Nde;case 4:return t?Fde:$de;case 5:return t?Pde:_de;case 6:return t?zde:Ode;case 7:return t?Lde:Dde;case 8:return t?Wde:Bde;case 9:return t?Ude:Vde;case 10:return t?Xde:qde;case 11:return Rde;case 12:return t?Hde:jde;case 14:return t?Jde:Yde;case 15:return p7("max",t);case 16:return p7("min",t);case 13:return t?Zde:Kde;case 17:return Cde;case 18:return Tde;default:throw new Error(`BinaryType ${e} is not implemented!`)}}var Qde="return abs(a);",epe="return ceil(a);",tpe="return cos(a);",rpe=`
let e2x = exp(-a);
return (e2x + 1.0 / e2x) / 2.0;
`,npe="return exp(a) - 1.0;",ape="if (a >= 0.0) { return a; } return (exp(a) - 1.0);",spe=`
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;
`,ipe="return exp(a);",ope="return floor(a);",lpe="return a;",upe=`if (a < 0.0) { return 1.0/0.0; }
return log(a);`,dpe="return f32(!(a >= 1.0));",ppe="return -a;",hpe="if (a < 0.0) { return uniforms.alpha * a; } return a;",cpe=`
let aLessThanZero = vec4<f32>(a < vec4<f32>(0.0));
return (aLessThanZero * (uniforms.alpha * a)) + ((vec4<f32>(1.0) - aLessThanZero) * a);
`,fpe="return select(a, 0.0, a < 0.0);",mpe="return clamp(a, 0.0, 6.0);",gpe="return clamp(a, vec4<f32>(0.0, 0.0, 0.0, 0.0), vec4<f32>(6.0, 6.0, 6.0, 6.0));",ype=`
return select(a, vec4<f32>(0.0), a < vec4<f32>(0.0));
`,Ape="return 1.0/sqrt(a);",xpe="return 1.0 / (1.0 + exp(-1.0 * a));",bpe="return sin(a);",vpe=`
let e2x = exp(a);
return (e2x - 1.0 / e2x) / 2.0;
`,wpe="return sqrt(a);",kpe="return a * a;",Ipe=`
let e2x = exp(-2.0 * abs(a));
return sign(a) * (1.0 - e2x) / (1.0 + e2x);
`,Spe="return f32(i32((a)));";function xo(e,t){switch(e){case 0:return Qde;case 2:return tpe;case 3:return rpe;case 1:return epe;case 4:return t?spe:ape;case 5:return ipe;case 6:return npe;case 7:return ope;case 8:return lpe;case 9:return upe;case 10:return dpe;case 11:return ppe;case 14:return t?cpe:hpe;case 12:return t?ype:fpe;case 13:return t?gpe:mpe;case 15:return Ape;case 18:return xpe;case 16:return bpe;case 17:return vpe;case 19:return wpe;case 20:return kpe;case 21:return Ipe;case 22:return Spe;default:throw new Error(`BinaryType ${e} is not implemented!`)}}function qi(e,t=!1){if(e===null)return null;if(e==="linear")return xo(8);if(e==="relu")return xo(12,t);if(e==="elu")return xo(4,t);if(e==="relu6")return xo(13,t);if(e==="prelu")return Yh(14,t);if(e==="sigmoid")return xo(18,t);if(e==="leakyrelu")return xo(14,t);throw new Error(`Activation ${e} has not been implemented for the WebGPU backend.`)}function Cpe(e,t){if(Math.max(...e)>3)throw new Error("Cannot symbolically compute strides for rank > 4 tensor.");let r=e.length,n=e.map(s=>`${t}[${s}]`),a=new Array(r-1);a[r-2]=n[r-1];for(let s=r-3;s>=0;--s)a[s]=`(${a[s+1]} * ${n[s+1]})`;return a}function Ar(e){if(e<=1)return"i32";if(e===2)return"vec2<i32>";if(e===3)return"vec3<i32>";if(e===4)return"vec4<i32>";if(e===5)return"vec5";if(e===6)return"vec6";throw Error(`GPU for rank ${e} is not yet supported`)}function $s(e){if(e===0)return"x";if(e===1)return"y";if(e===2)return"z";if(e===3)return"w";if(e===4)return"u";if(e===5)return"v";throw Error(`Index ${e} is not yet supported`)}function v0(e,t){return e==="float32"?t?"vec4<f32>":"f32":e==="int32"||e==="bool"?t?"vec4<i32>":"i32":e}function $A(){return`
@stage(compute) @workgroup_size(workGroupSizeX, workGroupSizeY, workGroupSizeZ)
`}function Od(){return`
${$A()}
fn main(@builtin(local_invocation_id) LocalId : vec3<u32>,
@builtin(global_invocation_id) GlobalId : vec3<u32>,
@builtin(num_workgroups) NumWorkgroups: vec3<u32>) {
localId = LocalId;
globalId = GlobalId;
numWorkgroups = NumWorkgroups;
`}function rt(){return`
${Od()}
let index = getGlobalIndex();
`}function Tpe(e,t,r,n=!1){let a=[];if(a.push(`
let workGroupSizeX = ${r.workGroupSize[0]}u;
let workGroupSizeY = ${r.workGroupSize[1]}u;
let workGroupSizeZ = ${r.workGroupSize[2]}u;
var<private> localId: vec3<u32>;
var<private> globalId: vec3<u32>;
var<private> numWorkgroups: vec3<u32>;
// Only used when the y/z dimension of workgroup size is 1.
fn getGlobalIndex() -> i32 {
${r.dispatch[1]===1&&r.dispatch[2]===1?" return i32(globalId.x);":` let localInvocationIndex = localId.z * workGroupSizeX * workGroupSizeY +
localId.y * workGroupSizeX + localId.x;
let workGroupID = (globalId - localId)/vec3<u32>(
workGroupSizeX, workGroupSizeY, workGroupSizeZ);
return i32((workGroupID.z * numWorkgroups.x * numWorkgroups.y +
workGroupID.y * numWorkgroups.x + workGroupID.x) *
(workGroupSizeX * workGroupSizeY * workGroupSizeZ) +
localInvocationIndex);
`}
}
`),n===!0)return a.push(`
struct Uniform {
size : i32,
numChannels : i32,
outShapeStrides : vec2<i32>,
dispatchSize : vec3<u32>,
};
@group(0) @binding(0) var<storage, write> result: array<${v0(t.dtype,r.isVec4)}>;
@group(0) @binding(2) var<uniform> uniforms: Uniform;
`),[h7,a.join(`
`),c7(t.shape),r.getUserCode()].join(`
`);let s=!1,i=!1,o="struct Uniforms { NAN : f32, ";r.variableNames.forEach((m,f)=>{let g=Ar(e[f].shape.length);(g==="vec5"||g==="vec6")&&(i=!0),(s||i)&&(o+="@align(16) "),s=i,o+=`${m.charAt(0).toLowerCase()+m.slice(1)}Shape : ${g}, `});let l=Ar(t.shape.length);i=l==="vec5"||l==="vec6",(s||i)&&(o+="@align(16) "),s=i,o+=`outShape : ${l}, `;let u=t.shape.length-1,d=Ar(u);i=d==="vec5"||d==="vec6",(s||i)&&(o+="@align(16) "),s=i,o+=`
outShapeStrides: ${d}, `,r.size&&(s&&(o+="@align(16) "),s=!1,o+="size : i32, "),r.uniforms&&(s&&(o+="@align(16) "),o+=r.uniforms),o+="};",a.push(o),r.atomic?a.push(`
@group(0) @binding(0) var<storage, read_write> result: array<atomic<i32>>;
`):a.push(`
@group(0) @binding(0) var<storage, write> result: array<${v0(t.dtype,r.isVec4)}>;
`),r.variableNames.forEach((m,f)=>{a.push(`
@group(0) @binding(${1+f}) var<storage, read> ${m}: array<${r.variableTypes?r.variableTypes[f]:v0(e[f].dtype,r.isVec4)}>;
`)}),o!==""&&a.push(`
@group(0) @binding(${1+r.variableNames.length}) var<uniform> uniforms: Uniforms;
`);let[h,p]=Fpe(t.shape,r.dispatchLayout),c=[h7,a.join(`
`),c7(t.shape),h,Npe(t.shape.length)];if(r.atomic||c.push(Epe(t.shape,t.dtype,r.isVec4)),p===t.shape.length){let m=e.map((f,g)=>Rpe(f,t.shape,r.variableTypes?r.variableTypes[g]==="vec4<f32>":r.isVec4,r.dispatchLayout.x.length===t.shape.length)).join(`
`);c.push(m)}return c.push(r.getUserCode()),c.join(`
`)}var h7=`
struct vec5 {x: i32, y: i32, z: i32, w: i32, u: i32};
struct vec6 {x: i32, y: i32, z: i32, w: i32, u: i32, v: i32};
// Checks whether coordinates lie within the bounds of the shape.
fn coordsInBounds2D(coord : vec2<i32>, shape : vec2<i32>) -> bool {
return all(coord >= vec2<i32>(0)) && all(coord < shape);
}
fn coordsInBounds3D(coord : vec3<i32>, shape : vec3<i32>) -> bool {
return all(coord >= vec3<i32>(0)) && all(coord < shape);
}
fn coordsInBounds4D(coord : vec4<i32>, shape : vec4<i32>) -> bool {
return all(coord >= vec4<i32>(0)) && all(coord < shape);
}
fn getIndexFromCoords1D(coord : i32, shape : i32) -> i32 {
return coord;
}
fn getIndexFromCoords2D(coords : vec2<i32>, shape : vec2<i32>) -> i32 {
return dot(coords, vec2<i32>(shape.y, 1));
}
fn getIndexFromCoords3D(coords : vec3<i32>, shape : vec3<i32>) -> i32 {
return dot(coords, vec3<i32>(shape.y * shape.z, shape.z, 1));
}
fn getIndexFromCoords4D(coords : vec4<i32>, shape : vec4<i32>) -> i32 {
return dot(coords, vec4<i32>(
shape.y * shape.z * shape.w, shape.z * shape.w, shape.w, 1));
}
fn getIndexFromCoords5D(coords : vec5, shape : vec5) -> i32 {
let shapeStrides: vec5 = vec5(shape.y * shape.z * shape.w * shape.u, shape.z * shape.w * shape.u, shape.w * shape.u, shape.u, 1);
return coords.x*shapeStrides.x + coords.y*shapeStrides.y + coords.z*shapeStrides.z + coords.w*shapeStrides.w + coords.u*shapeStrides.u;
}
fn getIndexFromCoords6D(coords : vec6, shape : vec6) -> i32 {
let shapeStrides: vec6 = vec6(shape.y * shape.z * shape.w * shape.u * shape.v, shape.z * shape.w * shape.u * shape.v, shape.w * shape.u * shape.v, shape.u * shape.v, shape.v, 1);
return coords.x*shapeStrides.x + coords.y*shapeStrides.y + coords.z*shapeStrides.z + coords.w*shapeStrides.w + coords.u*shapeStrides.u + coords.v*shapeStrides.v;
}
fn idiv(a: i32, b: i32, sign: f32) -> i32 {
var res: i32 = a / b;
let mod: i32 = a % b;
if (sign < 0. && mod != 0) {
res = res - 1;
}
return res;
}
// NaN defination in IEEE 754-1985 is :
// - sign = either 0 or 1.
// - biased exponent = all 1 bits.
// - fraction = anything except all 0 bits (since all 0 bits represents infinity).
// https://en.wikipedia.org/wiki/IEEE_754-1985#Representation_of_non-numbers
fn isnan(val: f32) -> bool {
let floatToUint: u32 = bitcast<u32>(val);
return (floatToUint & 0x7fffffffu) > 0x7f800000u;
}
fn isnanVec4(val : vec4<f32>) -> vec4<bool> {
return vec4<bool>(isnan(val[0]), isnan(val[1]), isnan(val[2]), isnan(val[3]));
}
`;function Npe(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 Epe(e,t,r){let n=e.length,a=v0(t,r),s;if(r?s=`fn setOutputAtIndex(flatIndex : i32, value : vec4<f32>) {
result[flatIndex] = ${a}(value);
}
fn setOutputAtIndexI32(flatIndex : i32, value : vec4<i32>) {
result[flatIndex] = ${a}(value);
}`:s=`fn setOutputAtIndex(flatIndex : i32, value : f32) {
result[flatIndex] = ${a}(value);
}
fn setOutputAtIndexI32(flatIndex : i32, value : i32) {
result[flatIndex] = ${a}(value);
}`,n>=2){let i=["d0","d1","d2","d3","d4","d5"].slice(0,n),o=Ar(n);r?s+=`
fn setOutputAtCoords(${i.map(l=>`${l} : i32`).join(", ")}, value : vec4<f32>) {
let flatIndex = getOutputIndexFromCoords(${o}(${i.join(", ")}));
setOutputAtIndex(flatIndex / 4, value);
}
fn setOutputAtCoordsI32(${i.map(l=>`${l} : i32`).join(", ")}, value : vec4<i32>) {
let flatIndex = getOutputIndexFromCoords(${o}(${i.join(", ")}));
setOutputAtIndexI32(flatIndex / 4, value);
}
`:s+=`
fn setOutputAtCoords(${i.map(l=>`${l} : i32`).join(", ")}, value : f32) {
let flatIndex = getOutputIndexFromCoords(${o}(${i.join(", ")}));
setOutputAtIndex(flatIndex, value);
}
fn setOutputAtCoordsI32(${i.map(l=>`${l} : i32`).join(", ")}, value : i32) {
let flatIndex = getOutputIndexFromCoords(${o}(${i.join(", ")}));
setOutputAtIndexI32(flatIndex, value);
}
`}return s}function Rpe(e,t,r,n){let a=Mpe(e,r);return e.shape.length<=t.length&&(a+=$pe(e,t,r,n)),a}function Mpe(e,t){let r=e.name,n=e.shape.length,a=Ar(n),s="get"+r.charAt(0).toUpperCase()+r.slice(1),i=["d0","d1","d2","d3","d4","d5"].slice(0,n),o=i.map(d=>`${d} : i32`).join(", ");if(n<1)return t?`
fn ${s}() -> vec4<f32> {
return vec4<f32>(${r}[0]);
}
`:`
fn ${s}() ->f32 {
return f32(${r}[0]);
}
`;let l=`uniforms.${r.charAt(0).toLowerCase()+r.slice(1)}Shape`,u=`${n}D`;return n===0&&(u="1D"),t?`
fn ${s}(${o}) -> vec4<f32> {
return vec4<f32>(${r}[getIndexFromCoords${u}(${a}(${i.join(",")}),
${l}) / 4]);
}
`:`
fn ${s}(${o}) -> f32 {
return f32(${r}[getIndexFromCoords${u}(${a}(${i.join(",")}),
${l})]);
}
`}function $pe(e,t,r,n){let a=e.name,s=a.charAt(0).toUpperCase()+a.slice(1),i="get"+s+"ByOutput",o=e.shape.length,l=t.length,u=Ar(l);if(v.arraysEqual(e.shape,t)&&n)return r?`
fn ${i}Index(globalIndex : i32) -> vec4<f32> {
return vec4<f32>(${a}[globalIndex]);
}
fn ${i}Coords(coords : ${u}) -> vec4<f32> {
return vec4<f32>(${a}[${l>1?"getOutputIndexFromCoords(coords)":"coords"} / 4]);
}
`:`
fn ${i}Index(globalIndex : i32) -> f32 {
return f32(${a}[globalIndex]);
}
fn ${i}Coords(coords : ${u}) -> f32 {
return f32(${a}[${l>1?"getOutputIndexFromCoords(coords)":"coords"}]);
}
`;let d=C.getBroadcastDims(e.shape,t),h=l-o,p="";if(o===0)return r?`
fn ${i}Index(globalIndex : i32) -> vec4<f32> {
return get${s}();
}
fn ${i}Coords(coords : ${u}) -> vec4<f32> {
return get${s}();
}
`:`
fn ${i}Index(globalIndex : i32) -> f32{
return get${s}();
}
fn ${i}Coords(coords : ${u}) -> f32{
return get${s}();
}
`;l<2&&d.length>=1?p="coords = 0;":p=d.map(g=>`coords.${$s(g+h)} = 0;`).join(`
`);let c="";if(l<2&&o>0)c="coords";else if(l>1){let g=Ar(o),y=e.shape.map((A,x)=>`coords.${$s(x+h)}`).join(", ");c=`${g}(${y})`}else c="coords";let m=`uniforms.${a.charAt(0).toLowerCase()+a.slice(1)}Shape`,f=`${o}D`;return r?`
fn ${i}Index(globalIndex : i32) -> vec4<f32> {
var coords = getCoordsFromIndex(globalIndex);
${p}
return ${a}[getIndexFromCoords${f}(${c}, ${m}) / 4];
}
fn ${i}Coords(coordsIn : ${u}) -> vec4<f32> {
var coords = coordsIn;
${p}
return ${a}[getIndexFromCoords${f}(${c}, ${m}) / 4];
}
`:`
fn ${i}Index(globalIndex : i32) -> f32 {
var coords = getCoordsFromIndex(globalIndex);
${p}
return f32(${a}[getIndexFromCoords${f}(${c}, ${m})]);
}
fn ${i}Coords(coordsIn : ${u}) -> f32 {
var coords = coordsIn;
${p}
return f32(${a}[getIndexFromCoords${f}(${c}, ${m})]);
}
`}function Fpe(e,t){let{x:r,y:n=[],z:a=[]}=t,s=e.length;if(r.length===s)return[`fn getOutputCoords() -> ${Ar(s)}{
let globalIndex = getGlobalIndex();
return getCoordsFromIndex(globalIndex);
}
`,s];let i="",o=[r,n,a],l=0;for(let p=0;p<o.length;p++){let c=o[p];if(c.length!==0)if(l+=c.length,c.length===1)i+=`let d${c[0]} = i32(globalId[${p}]);`;else{let m=Cpe(c,"uniforms.outShape");i+=`var index${p} = i32(globalId[${p}]);`;for(let f=0;f<m.length;f++)i+=`let d${c[f]} = index${p} / ${m[f]};`,f===m.length-1?i+=`let d${c[f+1]} = index${p} - d${c[f]} * ${m[f]};`:i+=`index${p} = index${p} - d${c[f]} * ${m[f]};`}}let u=[];for(let p=0;p<l;p++)u.push(`d${p}`);let d=Ar(l),h=`fn getOutputCoords() -> ${d} {
${i}
`;return u.length===0?h+=`return ${d}(0); }`:h+=`return ${d}(${u.join(",")}); }`,[h,l]}function c7(e){let t=e.length;if(t<=1)return"fn getCoordsFromIndex(index : i32) -> i32 { return index; }";let r=v.computeStrides(e),n=Ar(t),a=[];for(let i=0;i<t;i++)a.push(`d${i}`);if(r.length===1)return` fn getCoordsFromIndex(index : i32) -> vec2<i32> {
let d0 = index / uniforms.outShapeStrides; let d1 = index - d0 * uniforms.outShapeStrides;
return vec2<i32>(d0, d1);
}`;let s;return s="var index2 = index;"+r.map((i,o)=>{let l=`let ${a[o]} = index2 / uniforms.outShapeStrides.${$s(o)}`,u=o===r.length-1?`let ${a[o+1]} = index2 - ${a[o]} * uniforms.outShapeStrides.${$s(o)}`:`index2 = index2 - ${a[o]} * uniforms.outShapeStrides.${$s(o)}`;return`${l}; ${u};`}).join(""),`
fn getCoordsFromIndex(index : i32) -> ${n} {
${s}
return ${n}(${a.join(",")});
}
`}var XI={};Be(XI,{ArrayBufferToTypedArray:()=>ZI,GPUBytesPerElement:()=>w0,computeDispatch:()=>ze,computeWorkGroupSizeForConv2d:()=>FA,computeWorkGroupSizeForMatMul:()=>KI,computeWorkPerThreadForConv2d:()=>_A,flatDispatchLayout:()=>Je,isWebGPUSupported:()=>PA,tilesFitEvenlyIntoShape:()=>th});var Ro=e=>{let t=1;for(let r=0;r<e.length;r++)t*=e[r];return t};function th(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((r,n)=>r%e[n]===0)}function ze(e,t,r=[1,1,1],n=[1,1,1]){let[a,s,i]=[Math.ceil(Ro(e.x.map(o=>t[o]))/(r[0]*n[0])),e.y?Math.ceil(Ro(e.y.map(o=>t[o]))/(r[1]*n[1])):1,e.z?Math.ceil(Ro(e.z.map(o=>t[o]))/(r[2]*n[2])):1];return[a,s,i]}function FA(e,t){let r=Ro(e.x.map(a=>t[a])),n=Ro(e.y.map(a=>t[a]));return r<=4?[4,16,1]:n<=4?[16,4,1]:[16,16,1]}function KI(e,t,r){return e===1?[32,1,1]:r===1?[1,32,1]:[8,8,1]}function _A(e,t){let r=Ro(e.x.map(a=>t[a])),n=Ro(e.y.map(a=>t[a]));return r<=4?[1,2,1]:n<=4?[2,1,1]:[2,2,1]}function Je(e){return{x:e.map((t,r)=>r)}}function w0(e){if(e==="float32"||e==="int32"||e==="bool"||e==="string")return 4;if(e==="complex64")return 8;throw new Error(`Unknown dtype ${e}`)}function ZI(e,t){if(t==="float32")return new Float32Array(e);if(t==="int32")return new Int32Array(e);if(t==="bool"||t==="string")return Uint8Array.from(new Int32Array(e));throw new Error(`Unknown dtype ${t}`)}function PA(){return(typeof window!="undefined"||typeof WorkerGlobalScope!="undefined")&&!!navigator.gpu}function YI(e,t,r,n,a=4){return v.assert((n%4===0||n%3===0)&&e[0]===4&&(a===3||a===4),()=>`tileInner must be divisible by 4|3. ColPerThread must be 4.
innerElementSize must be 3|4.`),`
var<workgroup> mm_Asub : array<array<vec${a}<f32>, ${n/a}>, ${t}>;
var<workgroup> mm_Bsub : array<array<vec4<f32>, ${r/e[0]}>, ${n}>;
let RowPerThread = ${e[1]};
let ColPerThread = ${e[0]};
let InnerElementSize = ${a};
let TileInner = ${n};
${Od()}
let tileRow = ${t===1?"0":"i32(localId.y) * RowPerThread"};
let tileCol = i32(localId.x);
let globalRow = ${t===1?"0":"i32(globalId.y) * RowPerThread"};
let globalCol = i32(globalId.x);
let numTiles = (uniforms.dimInner - 1) / TileInner + 1;
var acc: array<vec4<f32>, RowPerThread>;
var BCached : array<vec4<f32>, 4>;
// Loop over shared dimension.
var globalColA = tileCol;
let RowPerThreadB = TileInner / i32(workGroupSizeY);
let tileRowB = i32(localId.y) * RowPerThreadB;
for (var t = 0; t < numTiles; t = t + 1) {
// Load one tile of A into local memory.
for (var innerRow = 0; innerRow < RowPerThread; innerRow = innerRow + 1) {
let inputRow = tileRow + innerRow;
let inputCol = tileCol;
mm_Asub[inputRow][inputCol] = mm_readA(globalRow + innerRow, globalColA, globalId);
}
globalColA = globalColA + TileInner / InnerElementSize;
// Load one tile of B into local memory.
for (var innerRow = 0; innerRow < RowPerThreadB; innerRow = innerRow + 1) {
let inputRow = tileRowB + innerRow;
let inputCol = tileCol;
mm_Bsub[inputRow][inputCol] = mm_readB(t * TileInner + inputRow, globalCol, globalId);
}
workgroupBarrier();
// Compute acc values for a single thread.
for (var k = 0; k < TileInner / InnerElementSize; k = k + 1) {
BCached[0] = mm_Bsub[k * InnerElementSize][tileCol];
BCached[1] = mm_Bsub[k * InnerElementSize + 1][tileCol];
BCached[2] = mm_Bsub[k * InnerElementSize + 2][tileCol];
${a===3?"":"BCached[3] = mm_Bsub[k * InnerElementSize + 3][tileCol];"}
for (var i = 0; i < RowPerThread; i = i + 1) {
let ACached = mm_Asub[tileRow + i][k];
acc[i] = BCached[0] * ACached.x + acc[i];
acc[i] = BCached[1] * ACached.y + acc[i];
acc[i] = BCached[2] * ACached.z + acc[i];
${a===3?"":"acc[i] = BCached[3] * ACached.w + acc[i];"}
}
}
workgroupBarrier();
}
for (var innerRow = 0; innerRow < RowPerThread; innerRow = innerRow + 1) {
mm_write(globalRow + innerRow,
globalCol,
acc[innerRow], globalId);
}
}`}var _pe=class{constructor(e,t,r,n,a,s=null,i=null,o=null){this.variableNames=["A","B"],this.uniforms="dimAOuter : i32, dimBOuter : i32, dimInner : i32,",this.workGroupSize=[8,8,1],this.isVec4=!0,this.outputShape=t,this.dispatchLayout={x:[2],y:[1],z:[0]},t[1]===1?this.elementsPerThread=[4,1,1]:this.elementsPerThread=[4,4,1],this.dispatch=ze(this.dispatchLayout,this.outputShape,this.workGroupSize,this.elementsPerThread);let l=s!=null,u=o!=null;l&&this.variableNames.push("bias"),u&&this.variableNames.push("preluActivationWeights"),this.tileAOuter=t[1]===1?1:this.workGroupSize[1]*this.elementsPerThread[1],this.tileBOuter=this.workGroupSize[0]*this.elementsPerThread[0],this.tileInner=this.tileBOuter,this.aShape=e,this.addBias=l,this.activation=i,this.hasPreluActivationWeights=u,this.batchAEqualOne=n,this.batchBEqualOne=a,[this.fitA,this.fitB]=this.getShapeFit(),this.shaderKey=`matMulPackedVec4_${this.activation}_${this.fitA}_${this.fitB}_${this.elementsPerThread}_${this.batchAEqualOne}_${this.batchBEqualOne}`}getShapeFit(){let e=this.aShape[2],t=this.outputShape[2],r=[this.outputShape[0],e,t],n=[this.tileAOuter,this.tileInner],a=[this.tileInner,this.tileBOuter];return[th(n,this.aShape.slice(1)),th(a,r.slice(1))]}getUserCode(){let e=this.fitA?"return A[batch * batchASize + row * uniforms.dimInner / 4 + col]":`if (coordsInBounds2D(vec2<i32>(row, col * 4), vec2<i32>(uniforms.dimAOuter, uniforms.dimInner))) {
return A[batch * batchASize + row * uniforms.dimInner / 4 + col];
}
return vec4<f32>(0.0)`,t=this.fitB?"return B[batch * batchBSize + row * uniforms.dimBOuter / 4 + col]":`if(coordsInBounds2D(vec2<i32>(row, col * 4), vec2<i32>(uniforms.dimInner, uniforms.dimBOuter))) {
return B[batch * batchBSize + row * uniforms.dimBOuter / 4 + col];
}
return vec4<f32>(0.0)`,r="",n="";if(this.activation){let s=qi(this.activation,this.isVec4);this.hasPreluActivationWeights?r=`fn activation(a : vec4<f32>, outCoord : vec3<i32>) -> vec4<f32> {
let b = getPreluActivationWeightsByOutputCoords(outCoord);
${s}
}`:r=`
fn activation(a : vec4<f32>, outCoord : vec3<i32>) -> vec4<f32> {
${s}
}`,n="value = activation(value, outCoord);"}let a=this.addBias?"value = value + getBiasByOutputCoords(outCoord);":"";return`
${r}
fn mm_readA(row : i32, col : i32, globalId : vec3<u32>) -> vec4<f32> {
${this.batchAEqualOne?`
let batchASize = 0;
let batch = 0;
`:`
let batchASize = uniforms.aShape[1] * uniforms.aShape[2] / 4;
let batch = i32(globalId.z);
`}
${e};
}
fn mm_readB(row : i32, col : i32, globalId : vec3<u32>) -> vec4<f32> {
${this.batchBEqualOne?`
let batchBSize = 0;
let batch = 0;
`:`
let batchBSize = uniforms.bShape[1] * uniforms.bShape[2] / 4;
let batch = i32(globalId.z);
`}
${t};
}
fn mm_write(row : i32, col : i32, valueIn : vec4<f32>, globalId : vec3<u32>) {
if (row < uniforms.aShape[1] && col * 4 < uniforms.bShape[2])
{
var value = valueIn;
let batch = i32(globalId.z);
let outCoord = vec3<i32>(batch, row, col * 4);
${a}
${n}
setOutputAtCoords(outCoord[0], outCoord[1], outCoord[2], value);
}
}
${YI(this.elementsPerThread,this.tileAOuter,this.tileBOuter,this.tileInner)}
`}},Ppe=e=>e?`
mm_Asub[inputRow][inputCol] = mm_readA(
t * TileInner + inputRow,
globalRowStart + inputCol, globalId);
`:`
mm_Asub[inputRow][inputCol] = mm_readA(
globalRowStart + inputRow,
t * TileInner + inputCol, globalId);
`,Ope=e=>e?"let ACached = mm_Asub[k][tileRow + innerRow];":"let ACached = mm_Asub[tileRow + innerRow][k];";function OA(e,t,r=!1,n=32){let a=e[1]*t[1],s=e[0]*t[0],i=r?a:n,o=r?n:a;v.assert(o%t[1]===0&&i%t[0]===0&&n%t[1]===0,()=>`tileAHight ${o} must be divisible by workGroupSize[1]${t[1]}, tileAWidth ${i} must be divisible by workGroupSize[0]${t[0]}, tileInner ${n} must be divisible by workGroupSize[1]${t[1]}`);let l=o/t[1],u=i/t[0],d=n/t[1];return`
var<workgroup> mm_Asub : array<array<f32, ${i}>, ${o}>;
var<workgroup> mm_Bsub : array<array<f32, ${s}>, ${n}>;
let RowPerThread = ${e[1]};
let ColPerThread = ${e[0]};
let TileInner = ${n};
@stage(compute) @workgroup_size(workGroupSizeX, workGroupSizeY, workGroupSizeZ)
fn main(@builtin(local_invocation_id) LocalId : vec3<u32>,
@builtin(global_invocation_id) GlobalId : vec3<u32>,
@builtin(num_workgroups) NumWorkgroups: vec3<u32>,
@builtin(workgroup_id) workgroupId: vec3<u32>) {
localId = LocalId;
globalId = GlobalId;
numWorkgroups = NumWorkgroups;
let tileRow = i32(localId.y) * RowPerThread;
let tileCol = i32(localId.x) * ColPerThread;
let globalRow = i32(globalId.y) * RowPerThread;
let globalCol = i32(globalId.x) * ColPerThread;
let globalRowStart = i32(workgroupId.y) * ${a};
let numTiles = (uniforms.dimInner - 1) / TileInner + 1;
var acc : array<array<f32, ColPerThread>, RowPerThread>;
// Without this initialization strange values show up in acc.
for (var innerRow = 0; innerRow < RowPerThread; innerRow = innerRow + 1) {
for (var innerCol = 0; innerCol < ColPerThread; innerCol = innerCol + 1) {
acc[innerRow][innerCol] = 0.0;
}
}
let tileRowA = i32(localId.y) * ${l};
let tileColA = i32(localId.x) * ${u};
let tileRowB = i32(localId.y) * ${d};
// Loop over shared dimension.
for (var t = 0; t < numTiles; t = t + 1) {
// Load one tile of A into local memory.
for (var innerRow = 0; innerRow < ${l}; innerRow = innerRow + 1) {
for (var innerCol = 0; innerCol < ${u}; innerCol = innerCol + 1) {
let inputRow = tileRowA + innerRow;
let inputCol = tileColA + innerCol;
${Ppe(r)}
}
}
// Load one tile of B into local memory.
for (var innerRow = 0; innerRow < ${d}; innerRow = innerRow + 1) {
for (var innerCol = 0; innerCol < ColPerThread; innerCol = innerCol + 1) {
let inputRow = tileRowB + innerRow;
let inputCol = tileCol + innerCol;
mm_Bsub[inputRow][inputCol] = mm_readB(
t * ${n} + inputRow,
globalCol + innerCol, globalId);
}
}
workgroupBarrier();
// Compute acc values for a single thread.
var BCached : array<f32, ColPerThread>;
for (var k = 0; k < TileInner; k = k + 1) {
for (var inner = 0; inner < ColPerThread; inner = inner + 1) {
BCached[inner] = mm_Bsub[k][tileCol + inner];
}
for (var innerRow = 0; innerRow < RowPerThread; innerRow = innerRow + 1) {
${Ope(r)}
for (var innerCol = 0; innerCol < ColPerThread; innerCol = innerCol + 1) {
acc[innerRow][innerCol] = acc[innerRow][innerCol] + ACached * BCached[innerCol];
}
}
}
workgroupBarrier();
}
for (var innerRow = 0; innerRow < RowPerThread; innerRow = innerRow + 1) {
for (var innerCol = 0; innerCol < ColPerThread; innerCol = innerCol + 1) {
if ((globalCol + innerCol) < uniforms.dimBOuter &&
(globalRow + innerRow) < uniforms.dimAOuter) {
mm_write(globalRow + innerRow,
globalCol + innerCol,
acc[innerRow][innerCol], globalId);
}
}
}
}
`}var zpe=e=>e?`
mm_readA(colA, globalRow, globalId),
mm_readA(colA + 1, globalRow, globalId),
mm_readA(colA + 2, globalRow, globalId),
mm_readA(colA + 3, globalRow, globalId)
`:`
mm_readA(globalRow, colA, globalId),
mm_readA(globalRow, colA + 1, globalId),
mm_readA(globalRow, colA + 2, globalId),
mm_readA(globalRow, colA + 3, globalId)
`;function Dpe(e,t=!1){return v.assert(e[1]===1&&e[2]===1,()=>`A linear work group size is required. But got ${e}.`),`
let TileSize = ${e[0]*4};
var<workgroup> mm_Asub : array<vec4<f32>, ${e[0]}>;
${Od()}
let tileCol = i32(localId.x);
let globalCol = i32(globalId.x);
let globalRow = i32(globalId.y);
let numTiles = (uniforms.dimInner - 1) / TileSize + 1;
// Without this initialization strange values show up in acc.
var acc = 0.0;
// Loop over shared dimension.
for (var t = 0; t < numTiles; t = t + 1) {
// Load one tile of A into local memory.
let colA = t * TileSize + tileCol * 4;
mm_Asub[tileCol] = vec4<f32>(${zpe(t)});
workgroupBarrier();
// Compute acc values for a single thread.
for (var k = 0; k < TileSize / 4; k = k + 1) {
let rowB = t * TileSize + k * 4;
let BCached = vec4<f32>(mm_readB(rowB, globalCol, globalId),
mm_readB(rowB + 1, globalCol, globalId),
mm_readB(rowB + 2, globalCol, globalId),
mm_readB(rowB + 3, globalCol, globalId));
let ACached = mm_Asub[k];
acc = acc + dot(ACached, BCached);
}
workgroupBarrier();
}
if (globalRow < uniforms.dimAOuter && globalCol < uniforms.dimBOuter) {
mm_write(globalRow, globalCol, acc, globalId);
}
}
`}var Lpe=class{constructor(e,t,r,n,a,s=!1,i=!1,o=null,l=null,u=null){this.variableNames=["A","B"],this.uniforms="dimAOuter : i32, dimBOuter : i32, dimInner : i32,",this.workGroupSize=[16,16,1],this.outputShape=t,this.dispatchLayout={x:[2],y:[1],z:[0]};let d=s?e[1]:e[2];this.workGroupSize=KI(t[1],d,t[2]),(t[1]===1||t[2]===1)&&(r=1),this.dispatch=ze(this.dispatchLayout,this.outputShape,this.workGroupSize,[r,r,1]),v.arraysEqual(this.dispatch,[1,1,1])&&(r=1,this.dispatch=ze(this.dispatchLayout,this.outputShape,this.workGroupSize,[r,r,1]));let h=o!=null,p=u!=null;h&&this.variableNames.push("bias"),p&&this.variableNames.push("preluActivationWeights"),this.workPerThread=r,this.transposeA=s,this.transposeB=i,this.addBias=h,this.activation=l,this.hasPreluActivationWeights=p,this.batchAEqualOne=n,this.batchBEqualOne=a,[this.fitAOuter,this.fitBOuter,this.fitInner]=this.getShapeFit(t[1],t[2],d),this.shaderKey=`matMulPacked_${this.workPerThread}_${s}_${i}_${this.activation}_${this.fitAOuter}_${this.fitBOuter}_${this.fitInner}_${this.outputShape[1]>1}_${this.batchAEqualOne}_${this.batchBEqualOne}`}getShapeFit(e,t,r){let n=this.workGroupSize[1]*this.workPerThread,a=this.workGroupSize[0]*this.workPerThread;this.tileInner=32,this.outputShape[1]===1&&(this.tileInner=this.workGroupSize[0]*4);let s=e%n===0,i=t%a===0,o=r%this.tileInner===0;return[s,i,o]}getUserCode(){let e=this.fitAOuter&&this.fitInner?"return A[batch * batchASize + row * uniforms.aShape[2] + col];":`
if(row < uniforms.aShape[1] && col < uniforms.aShape[2]) {
return A[batch * batchASize + row * uniforms.aShape[2] + col];
}
return 0.0;
`,t;this.transposeB===!1?t="return B[batch * batchBSize + row * uniforms.dimBOuter + col];":t="return B[batch * batchBSize + col * uniforms.dimInner + row];";let r="",n="";if(this.activation){let s=qi(this.activation,!1);this.hasPreluActivationWeights?r=`fn activation(a : f32, outCoord : vec3<i32>) -> f32 {
let b = getPreluActivationWeightsByOutputCoords(outCoord);
${s}
}`:r=`
fn activation(a : f32, outCoord : vec3<i32>) -> f32 {
${s}
}
`,n="value = activation(value, outCoord);"}let a=this.addBias?"value = value + getBiasByOutputCoords(outCoord);":"";return`
${r}
fn mm_readA(row : i32, col : i32, globalId : vec3<u32>) -> f32 {
${this.batchAEqualOne?`
let batch = 0;
let batchASize = 0;
`:`
let batch = i32(globalId.z);
let batchASize = uniforms.aShape[1] * uniforms.aShape[2];
`}
${e}
}
fn mm_readB(row : i32, col : i32, globalId : vec3<u32>) -> f32 {
${this.batchBEqualOne?`
let batch = 0;
let batchBSize = 0;
`:`
let batch = i32(globalId.z);
let batchBSize = uniforms.bShape[1] * uniforms.bShape[2];
`}
${t}
}
fn mm_write(row : i32, col : i32, valueIn : f32, globalId : vec3<u32>) {
var value = valueIn;
let batch = i32(globalId.z);
let outCoord = vec3<i32>(batch, row, col);
${a}
${n}
setOutputAtCoords(batch, row, col, value);
}
${this.outputShape[1]>1?OA([this.workPerThread,this.workPerThread,1],this.workGroupSize,this.transposeA,this.tileInner):Dpe(this.workGroupSize,this.transposeA)}
`}};function Bpe(){return`
var<workgroup> sumValues : array<f32, workGroupSizeX>;
${Od()}
let coords = getOutputCoords();
let batch = coords[0];
let row = coords[1];
let col = coords[2];
var sum = 0.0;
let Length = uniforms.dimInner;
for (var k = i32(localId.x); k < Length; k = k + i32(workGroupSizeX)) {
let dataA = mm_readA(batch, row, k);
let dataB = mm_readB(batch, k, col);
sum = sum + dataA * dataB;
}
sumValues[localId.x] = sum;
workgroupBarrier();
for(var currentSize = workGroupSizeX / 2u; currentSize > 1u;
currentSize = currentSize / 2u) {
if (localId.x < currentSize)
{
sumValues[localId.x] = sumValues[localId.x] + sumValues[localId.x + currentSize];
}
workgroupBarrier();
}
if (localId.x == 0u) {
sum = sumValues[0] + sumValues[1];
mm_write(batch, row, col, sum);
}
}
`}var Wpe=class{constructor(e,t,r,n=!1,a=!1,s=null,i=null,o=null){this.variableNames=["A","B"],this.uniforms="dimAOuter : i32, dimBOuter : i32, dimInner : i32,",this.workGroupSize=[256,1,1],this.outputShape=e,this.dispatchLayout={x:[],y:[1,2],z:[0]},this.dispatch=ze(this.dispatchLayout,this.outputShape,this.workGroupSize);let l=s!=null,u=o!=null;l&&this.variableNames.push("bias"),u&&this.variableNames.push("preluActivationWeights"),this.transposeA=n,this.transposeB=a,this.addBias=l,this.activation=i,this.hasPreluActivationWeights=u,this.batchAEqualOne=t,this.batchBEqualOne=r,this.shaderKey=`matMulReduce_${this.activation}_${n}_${a}_${this.batchAEqualOne}_${this.batchBEqualOne}`}getUserCode(){let e;this.transposeA===!1?e="return f32(A[batch * batchASize + row * uniforms.dimInner + col]);":e="return f32(A[batch * batchASize + col * uniforms.dimAOuter + row]);";let t;this.transposeB===!1?t="return f32(B[batch * batchBSize + row * uniforms.dimBOuter + col]);":t="return f32(B[batch * batchBSize + col * uniforms.dimInner + row]);";let r="",n="";if(this.activation){let s=qi(this.activation,!1);this.hasPreluActivationWeights?r=`fn activation(a : f32, outCoord : vec3<i32>) -> f32 {
let b = getPreluActivationWeightsByOutputCoords(outCoord);
${s}
}`:r=`
fn activation(a : f32, outCoord : vec3<i32>) -> f32 {
${s}
}
`,n="value = activation(value, outCoord);"}let a=this.addBias?"value = value + getBiasByOutputCoords(outCoord);":"";return`
${r}
fn mm_readA(batchIn: i32, row : i32, col : i32) -> f32 {
${this.batchAEqualOne?`
let batchASize = 0;
let batch = 0;
`:`
let batchASize = uniforms.aShape[1] * uniforms.aShape[2];
let batch = batchIn;
`}
${e}
}
fn mm_readB(batchIn: i32, row : i32, col : i32) -> f32 {
${this.batchBEqualOne?`
let batch = 0;
let batchBSize = 0;
`:`
let batch = batchIn;
let batchBSize = uniforms.bShape[1] * uniforms.bShape[2];
`}
${t}
}
fn mm_write(batch: i32, row : i32, col : i32, valueIn : f32) {
var value = valueIn;
let outCoord = vec3<i32>(batch, row, col);
${a}
${n}
setOutputAtCoords(batch, row, col, value);
}
${Bpe()}
`}};function Vpe(e){let t=e[1]/2,r=e[0],n=t>r?t:r;return`
var<workgroup> mm_Asub1 : array<array<f32, ${n}>, ${t}>;
var<workgroup> mm_Bsub1 : array<array<f32, ${r}>, ${n}>;
var<workgroup> mm_Asub2 : array<array<f32, ${n}>, ${t}>;
var<workgroup> mm_Bsub2 : array<array<f32, ${r}>, ${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.
// Introduces two shared memory buffers, some logical threads could handle
// arithmetic operations and others handle IO operations between barrier api,
// makes ALUs and load/store units work simultaneously, could improves
// the performance.
${Od()}
let tileRow = i32(localId.y);
let tileCol = i32(localId.x);
let globalRow = i32(globalId.y);
let globalCol = i32(globalId.x);
// uniforms.dimInner should be greater than 0.
let numTiles = (uniforms.dimInner - 1) / ${n} + 1;
var acc = 0.0;
var globalColA = tileCol;
var globalRowB = tileRow;
for (var t = 0; t < numTiles; t = t + 1) {
if (t == 0) {
if (tileRow < ${t}) {
// Load one tile of A and B into local memory.
// globalRow is always greater than or equal tileRow.
mm_Asub1[tileRow][tileCol] =
mm_readA((globalRow - tileRow) / 2 + tileRow, globalColA, globalId);
globalColA = globalColA + ${n};
mm_Bsub1[tileRow][tileCol] = mm_readB(globalRowB, globalCol, globalId);
globalRowB = globalRowB + ${n};
}
} else {
if (tileRow < ${t}) {
// Load one tile of A and B into local memory.
// globalRow is always greater than or equal tileRow.
mm_Asub1[tileRow][tileCol] =
mm_readA((globalRow - tileRow) / 2 + tileRow, globalColA, globalId);
globalColA = globalColA + ${n};
mm_Bsub1[tileRow][tileCol] = mm_readB(globalRowB, globalCol, globalId);
globalRowB = globalRowB + ${n};
} else {
// Compute acc values for a single thread.
for (var k = 0; k < ${n}; k = k + 1) {
let subRow = tileRow - ${t};
if (subRow < 0) {
continue;
}
acc = acc + mm_Asub2[subRow][k] * mm_Bsub2[k][tileCol];
}
}
}
workgroupBarrier();
if (t != 0) {
t = t + 1;
}
if (t < numTiles) {
if (tileRow < ${t}) {
// Load one tile of A and B into local memory.
// globalRow is always greater than or equal tileRow.
mm_Asub2[tileRow][tileCol] =
mm_readA((globalRow - tileRow) / 2 + tileRow, globalColA, globalId);
globalColA = globalColA + ${n};
mm_Bsub2[tileRow][tileCol] = mm_readB(globalRowB, globalCol, globalId);
globalRowB = globalRowB + ${n};
} else {
// Compute acc values for a single thread.
for (var k = 0; k < ${n}; k = k + 1) {
let subRow = tileRow - ${t};
if (subRow < 0) {
continue;
}
acc = acc + mm_Asub1[subRow][k] * mm_Bsub1[k][tileCol];
}
}
}
workgroupBarrier();
}
let writeCol = (globalRow - tileRow) / 2 + tileRow - ${t};
if (tileRow >= ${t} && writeCol >= 0) {
mm_write(writeCol, globalCol, acc, globalId);
}
}
`}var Upe=class{constructor(e,t,r,n=null,a=null,s=null){this.variableNames=["A","B"],this.uniforms="dimAOuter : i32, dimBOuter : i32, dimInner : i32,",this.workGroupSize=[8,16,1],v.assert(e[1]<=16||t[2]<=16,()=>"This program can be only used when A width or B Height are small"),this.outputShape=r,this.dispatchLayout={x:[2],y:[1],z:[0]},this.dispatch=[Math.ceil(r[2]/this.workGroupSize[0]),Math.ceil(r[1]*2/this.workGroupSize[1]),r[0]];let i=n!=null;i&&this.variableNames.push("bias");let o=s!=null;o&&this.variableNames.push("preluActivationWeights"),this.addBias=i,this.activation=a,this.hasPreluActivationWeights=o,this.batchAEqualOne=e[0]===1,this.batchBEqualOne=t[0]===1,this.shaderKey=`matMulSmallOutputSize_${this.activation}_${this.batchAEqualOne}_${this.batchBEqualOne}`}getUserCode(){let e=`if (coordsInBounds2D(vec2<i32>(row, col), vec2<i32>(uniforms.dimAOuter, uniforms.dimInner))) {
return A[batch * batchASize + row * uniforms.dimInner + col];
}
return 0.0;`,t=`if (coordsInBounds2D(vec2<i32>(row, col), vec2<i32>(uniforms.dimInner, uniforms.dimBOuter))) {
return B[batch * batchBSize + row * uniforms.dimBOuter + col];
}
return 0.0;`,r="",n="";if(this.activation){let s=qi(this.activation,!1);this.hasPreluActivationWeights?r=`fn activation(a : f32, outCoord : vec3<i32>) -> f32 {
let b = getPreluActivationWeightsByOutputCoords(outCoord);
${s}
}`:r=`fn activation(a : f32, outCoord : vec3<i32>) -> f32 {
${s}
}`,n="value = activation(value, outCoord);"}let a=this.addBias?"value = value + getBiasByOutputCoords(outCoord);":"";return`
${r}
fn mm_readA(row : i32, col : i32, globalId : vec3<u32>) -> f32 {
${this.batchAEqualOne?`
let batch = 0;
let batchASize = 0;
`:`
let batchASize = uniforms.aShape[1] * uniforms.aShape[2];
let batch = i32(globalId.z);
`}
${e}
}
fn mm_readB(row : i32, col : i32, globalId : vec3<u32>) -> f32 {
${this.batchBEqualOne?`
let batch = 0;
let batchBSize = 0;
`:`
let batch = i32(globalId.z);
let batchBSize = uniforms.bShape[1] * uniforms.bShape[2];
`}
${t}
}
fn mm_write(row : i32, col : i32, valueIn : f32, globalId : vec3<u32>) {
if (coordsInBounds2D(vec2<i32>(row, col), vec2<i32>(uniforms.dimAOuter, uniforms.dimBOuter))) {
let batch = i32(globalId.z);
let outCoord = vec3<i32>(batch, row, col);
var value = valueIn;
${a}
${n}
setOutputAtCoords(batch, row, col, value);
}
}
${Vpe(this.workGroupSize)}
`}};function qe(e){let{inputs:t,attrs:r}=e,{x:n}=t,{shape:a}=r,s=v.sizeFromShape(n.shape),i=v.inferFromImplicitShape(a,s),o=v.sizeFromShape(i);return v.assert(s===o,()=>`The new shape (${i}) has ${o} elements and the old shape (${n.shape}) has ${s} elements. The new shape and old shape must have the same number of elements.`),e.backend.incRef(n.dataId),{dataId:n.dataId,shape:i,dtype:n.dtype}}var Gpe={kernelName:cl,backendName:"webgpu",kernelFunc:qe};function zA({a:e,b:t,transposeA:r,transposeB:n,backend:a,bias:s=null,preluActivationWeights:i=null,leakyreluAlpha:o=0,activation:l=null}){let u=e.shape.length,d=t.shape.length,h=r?e.shape[u-2]:e.shape[u-1],p=n?t.shape[d-1]:t.shape[d-2],c=r?e.shape[u-1]:e.shape[u-2],m=n?t.shape[d-2]:t.shape[d-1],f=e.shape.slice(0,-2),g=t.shape.slice(0,-2),y=v.sizeFromShape(f),A=v.sizeFromShape(g),x=Rl.assertAndGetBroadcastShape(e.shape.slice(0,-2),t.shape.slice(0,-2)).concat([c,m]);v.assert(h===p,()=>`Error in matMul: inner shapes (${h}) and (${p}) of Tensors with shapes ${e.shape} and ${t.shape} and transposeA=${r} and transposeB=${n} must match.`);let b=r?[y,h,c]:[y,c,h],w=n?[A,m,p]:[A,p,m],I=qe({inputs:{x:e},backend:a,attrs:{shape:b}}),T=qe({inputs:{x:t},backend:a,attrs:{shape:w}}),E=[I,T],R=Math.max(y,A),O=y===1,M=A===1,S=h%4===0&&m%4===0&&!r&&!n,P;c*m<=32?P=new Wpe([R,c,m],O,M,r,n,s,l,i):!r&&!n&&(c<=16&&(m<=512||p>=2*m)||m<=16&&(c<=512||h>=2*c))?P=new Upe(b,w,[R,c,m],s,l,i):S?P=new _pe(b,[R,c,m],Z().get("WEBGPU_MATMUL_WORK_PER_THREAD"),O,M,s,l,i):P=new Lpe(b,[R,c,m],Z().get("WEBGPU_MATMUL_WORK_PER_THREAD"),O,M,r,n,s,l,i);let z=[I,T];s&&z.push(s),i&&z.push(i);let j=[{type:"int32",data:[c]},{type:"int32",data:[m]},{type:"int32",data:[h]}];l==="leakyrelu"&&(j.push({type:"float32",data:[o]}),P.uniforms+=" alpha : f32,");let K=a.runWebGPUProgram(P,z,e.dtype,j),D=qe({inputs:{x:K},backend:a,attrs:{shape:x}});E.push(K);for(let Y of E)a.disposeData(Y.dataId);return D}function jpe(e){let{inputs:t,backend:r,attrs:n}=e,{a,b:s,bias:i,preluActivationWeights:o}=t,{transposeA:l,transposeB:u,activation:d,leakyreluAlpha:h}=n;return zA({a,b:s,transposeA:l,transposeB:u,backend:r,bias:i,preluActivationWeights:o,leakyreluAlpha:h,activation:d})}var Hpe={kernelName:_s,backendName:"webgpu",kernelFunc:jpe},f7=class{constructor(e,t,r){this.variableNames=["AReal","AImag","BReal","BImag"],this.workGroupSize=[128,1,1],this.size=!0,this.outputShape=C.assertAndGetBroadcastShape(t,r),this.dispatchLayout=Je(this.outputShape),this.dispatch=ze(this.dispatchLayout,this.outputShape,this.workGroupSize),this.shaderKey=`binaryOpComplex_${e}`,this.op=e}getUserCode(){return`
fn binaryOpComplex(
areal : f32, aimag : f32, breal : f32, bimag : f32) -> f32 {
${Yh(this.op,!1)}
}
${rt()}
if(index < uniforms.size) {
let areal = getARealByOutputIndex(index);
let aimag = getAImagByOutputIndex(index);
let breal = getBRealByOutputIndex(index);
let bimag = getBImagByOutputIndex(index);
setOutputAtIndex(index, binaryOpComplex(areal, aimag, breal, bimag));
}
}
`}},qpe=class{constructor(e,t,r,n){this.variableNames=["A","B"],this.size=!0;let a=256;this.workGroupSize=[a,1,1],this.outputShape=C.assertAndGetBroadcastShape(t,r),this.dispatchLayout=Je(this.outputShape),this.lastDimensionSize=n?r[0]:t[0],this.lastDimensionSize<256?this.workPerThread=1:this.lastDimensionSize<512?this.workPerThread=2:this.workPerThread=4,this.dispatch=ze(this.dispatchLayout,this.outputShape,this.workGroupSize,[this.workPerThread,1,1]),this.useSharedMemoryWithB=n,this.op=e,this.shaderKey=`binaryShared_${e}_${this.lastDimensionSize}_${this.useSharedMemoryWithB}`}getUserCode(){let e=this.lastDimensionSize>1?`coords[${this.outputShape.length-1}]`:"0",t=this.useSharedMemoryWithB?`let a = getAByOutputCoords(coords);
let b = sharedBuf[${e}];`:`let a = sharedBuf[${e}];
let b = getBByOutputCoords(coords);`;return`
fn binaryOperation(a : f32, b : f32) -> f32 {
${Yh(this.op,!1)}
}
var<workgroup> sharedBuf : array<f32, ${this.lastDimensionSize}>;
${rt()}
// Fill in the shared memory buffer. Here we need a loop to make sure
// that all data in A|B are uploaded when |sharedMemorySize| is larger
// than work group size.
for(var localIndex = i32(localId.x); localIndex < ${this.lastDimensionSize}; localIndex = localIndex + ${this.workGroupSize[0]}) {
sharedBuf[localIndex] = f32(${this.useSharedMemoryWithB?"B":"A"}[localIndex]);
}
workgroupBarrier();
for(var i = 0; i < ${this.workPerThread}; i = i + 1) {
let flatIndex = index * ${this.workPerThread} + i;
if(flatIndex < uniforms.size) {
let coords = getCoordsFromIndex(flatIndex);
${t}
setOutputAtIndex(flatIndex, binaryOperation(a, b));
}
}
}
`}},Xpe=class{constructor(e,t,r){this.variableNames=["A","B"],this.workPerThread=4,this.isVec4=!0,this.size=!0;let n=128;this.workGroupSize=[n,1,1],this.outputShape=C.assertAndGetBroadcastShape(t,r),this.dispatchLayout=Je(this.outputShape),this.dispatch=ze(this.dispatchLayout,this.outputShape,this.workGroupSize,[this.workPerThread,1,1]),this.op=e,this.shaderKey=`binaryVec4_${e}`}getUserCode(){return`
fn binaryOperation(a : vec4<f32>, b : vec4<f32>) -> vec4<f32> {
${Yh(this.op,this.isVec4)}
}
${rt()}
if (index < uniforms.size) {
let a = getAByOutputIndex(index);
let b = getBByOutputIndex(index);
setOutputAtIndex(index, binaryOperation(a, b));
}
}
`}},JI=class{constructor(e,t,r){this.variableNames=["A","B"],this.size=!0;let n=128;this.workGroupSize=[n,1,1],this.outputShape=C.assertAndGetBroadcastShape(t,r),this.dispatchLayout=Je(this.outputShape),this.dispatch=ze(this.dispatchLayout,this.outputShape,this.workGroupSize),this.shaderKey=`binary_${e}`,this.op=e}getUserCode(){return`
fn binaryOperation(a : f32, b : f32) -> f32 {
${Yh(this.op,!1)}
}
${rt()}
if (index < uniforms.size) {
let a = getAByOutputIndex(index);
let b = getBByOutputIndex(index);
setOutputAtIndex(index, binaryOperation(a, b));
}
}
`}};function m7(e,t,r){if(v.arraysEqual(t,r)&&v.sizeFromShape(t)%4===0)return new Xpe(e,t,r);let n=t.length===1&&r.length>1&&t[0]<1024,a=r.length===1&&t.length>1&&r[0]<1024;return n||a?new qpe(e,t,r,a):new JI(e,t,r)}function On(e){let{inputs:t}=e,{x:r}=t;return e.backend.incRef(r.dataId),{dataId:r.dataId,shape:r.shape,dtype:r.dtype}}var Kpe={kernelName:fi,backendName:"webgpu",kernelFunc:On};function zd(e){let{inputs:t,backend:r}=e,{real:n,imag:a}=t,s=r.makeTensorInfo(n.shape,"complex64"),i=r.tensorMap.get(s.dataId),o=On({inputs:{x:n},backend:r}),l=On({inputs:{x:a},backend:r});return i.complexTensorInfos={real:o,imag:l},s}var Zpe={kernelName:ah,backendName:"webgpu",kernelFunc:zd},Jh=class{constructor(e,t){this.variableNames=["A"],this.size=!0;let r=128;this.workGroupSize=[r,1,1],this.outputShape=e,this.dispatchLayout=Je(this.outputShape),this.dispatch=ze(this.dispatchLayout,this.outputShape,this.workGroupSize),this.op=t,this.shaderKey=`unary_${t}`}getUserCode(){return`
fn unaryOperation(a : f32) -> f32 {
${xo(this.op,!1)}
}
${rt()}
if (index < uniforms.size) {
let a = getAByOutputIndex(index);
setOutputAtIndex(index, unaryOperation(a));
}
}
`}};function wr({opType:e,cpuKernelImpl:t,dtype:r}){return({inputs:n,backend:a})=>{let{x:s}=n,i=a,o=r||s.dtype;if(i.shouldExecuteOnCPU([s])&&t!=null){let u=i.tensorMap.get(s.dataId),d=t(u.values,o);return i.makeTensorInfo(s.shape,o,d)}let l=new Jh(s.shape,e);return i.runWebGPUProgram(l,[s],o)}}function Xr({opSnippet:e,cpuKernelImpl:t,supportsComplex:r=!1,dtype:n}){return({inputs:a,backend:s})=>{let{a:i,b:o}=a,l=s;if(r&&i.dtype==="complex64"){let h=l.tensorMap.get(i.dataId),p=l.tensorMap.get(o.dataId),c,m;if(e!==0)[c,m]=[[h.complexTensorInfos.real,p.complexTensorInfos.real],[h.complexTensorInfos.imag,p.complexTensorInfos.imag]].map(g=>{let[y,A]=g,x={dataId:y.dataId,dtype:y.dtype,shape:i.shape},b={dataId:A.dataId,dtype:A.dtype,shape:o.shape},w=m7(e,i.shape,o.shape);return l.runWebGPUProgram(w,[x,b],Tr(y.dtype,A.dtype))});else{let g=new f7(17,i.shape,o.shape),y=new f7(18,i.shape,o.shape),A=[{dataId:h.complexTensorInfos.real.dataId,dtype:h.complexTensorInfos.real.dtype,shape:i.shape},{dataId:h.complexTensorInfos.imag.dataId,dtype:h.complexTensorInfos.imag.dtype,shape:i.shape},{dataId:p.complexTensorInfos.real.dataId,dtype:p.complexTensorInfos.real.dtype,shape:o.shape},{dataId:p.complexTensorInfos.imag.dataId,dtype:p.complexTensorInfos.imag.dtype,shape:o.shape}];c=l.runWebGPUProgram(g,A,"float32"),m=l.runWebGPUProgram(y,A,"float32")}let f=zd({inputs:{real:c,imag:m},backend:l});return l.disposeData(c.dataId),l.disposeData(m.dataId),f}let u=n||Tr(i.dtype,o.dtype);if((i.dtype==="string"||o.dtype==="string"||l.shouldExecuteOnCPU([i,o]))&&t!=null){let h=l.tensorMap.get(i.dataId).values,p=l.tensorMap.get(o.dataId).values,c=i.dtype==="string"?C.fromUint8ToStringArray(h):h,m=i.dtype==="string"?C.fromUint8ToStringArray(p):p,[f,g]=t(i.shape,o.shape,c,m,u);return l.makeTensorInfo(g,u,f)}let d=m7(e,i.shape,o.shape);return l.runWebGPUProgram(d,[i,o],u)}}var{addImpl:Ype,ceilImpl:Jpe,concatImpl:Qpe,equalImpl:ehe,expImpl:the,expm1Impl:rhe,floorImpl:nhe,gatherNdImpl:ahe,gatherV2Impl:she,greaterEqualImpl:ihe,greaterImpl:ohe,lessEqualImpl:lhe,lessImpl:uhe,logImpl:dhe,maxImpl:phe,maximumImpl:hhe,minimumImpl:che,multiplyImpl:fhe,negImpl:mhe,notEqualImpl:ghe,prodImpl:yhe,rangeImpl:Ahe,rsqrtImpl:xhe,scatterImpl:bhe,simpleAbsImpl:vhe,sliceImpl:whe,stridedSliceImpl:khe,stringNGramsImpl:Ihe,subImpl:She,tileImpl:Che,topKImpl:The,transposeImpl:Nhe,uniqueImpl:iAe}=Rm,Ehe=wr({opType:0,cpuKernelImpl:vhe}),Rhe={kernelName:Go,backendName:"webgpu",kernelFunc:Ehe},Mhe=Xr({opSnippet:1,cpuKernelImpl:Ype,supportsComplex:!0}),$he={kernelName:Ja,backendName:"webgpu",kernelFunc:Mhe},Fhe=class{constructor(e){this.workPerThread=4,this.workGroupSize=[64,1,1],this.size=!0,this.outputShape=e[0],this.variableNames=e.map((t,r)=>`T${r}`),this.dispatchLayout=Je(this.outputShape),this.dispatch=ze(this.dispatchLayout,this.outputShape,this.workGroupSize,[this.workPerThread,1,1]),this.shaderKey="addN"}getUserCode(){let e=[];this.variableNames.forEach(r=>{e.push(`let v${r} = get${r}ByOutputCoords(coords);`)});let t=this.variableNames.map(r=>`v${r}`).join(" + ");return`
${rt()}
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, ${t});
}
}
}
`}};function _he(e){let{inputs:t,backend:r}=e,n=t;if(n.length===1)return On({inputs:{x:n[0]},backend:r});let a=n.map(o=>o.dtype).reduce((o,l)=>Tr(o,l)),s=n.map(o=>o.shape),i=new Fhe(s);return r.runWebGPUProgram(i,n,a)}var Phe={kernelName:Ks,backendName:"webgpu",kernelFunc:_he},QI=class{constructor(e,t,r){this.workGroupSize=[64,1,1],this.variableNames=["x"],this.uniforms="infinityValue : f32,",this.size=!0;let n=[t];C.assertAxesAreInnerMostDims("arg"+r.charAt(0).toUpperCase()+r.slice(1),n,e.length),this.op=r==="min"?"<":">";let[a]=C.computeOutAndReduceShapes(e,n);this.outputShape=a.length===0?[1]:a,this.dispatchLayout=Je(this.outputShape),this.dispatch=ze(this.dispatchLayout,this.outputShape,[1,1,1]),this.inputShape=e,this.shaderKey=`argMinMax${this.op}`}getUserCode(){let e=`
var<workgroup> xBestIndices : array<i32, ${this.workGroupSize[0]}>;
var<workgroup> xBestValues : array<f32, ${this.workGroupSize[0]}>;
`,t=()=>this.inputShape.length===1?"uniforms.xShape":`uniforms.xShape.${$s(this.inputShape.length-1)}`,r=()=>{let n="";if(this.outputShape.length===1)this.inputShape.length!==1&&(n+="outputCoords,");else for(let a=0;a<this.outputShape.length;a++)n+=`outputCoords.${$s(a)},`;return n};return`
fn DIV_CEIL(a : u32, b : u32) -> u32 {
return ((a - 1u) / b + 1u);
}
${e}
${rt()}
let outputIndex = index / i32(workGroupSizeX);
let reduceLength = ${t()};
var bestIndex = i32(localId.x);
var bestValue = uniforms.infinityValue;
let outputCoords = getCoordsFromIndex(outputIndex);
for (var k = i32(localId.x); k < reduceLength && outputIndex < uniforms.size;
k = k + i32(workGroupSizeX)) {
let candidate = getX(${r()} k);
if (!isnan(candidate) && candidate ${this.op} bestValue) {
bestValue = candidate;
bestIndex = k;
}
}
xBestValues[localId.x] = bestValue;
xBestIndices[localId.x] = bestIndex;
workgroupBarrier();
var reduceSize = min(u32(reduceLength), workGroupSizeX);
for (var currentSize = reduceSize / 2u; reduceSize > 1u;
currentSize = reduceSize / 2u) {
let interval = DIV_CEIL(reduceSize, 2u);
if (localId.x < currentSize) {
let candidate = xBestValues[localId.x + interval];
if (candidate ${this.op} bestValue) {
bestValue = candidate;
xBestValues[localId.x] = bestValue;
xBestIndices[localId.x] = xBestIndices[localId.x + interval];
}
}
reduceSize = interval;
workgroupBarrier();
}
if (localId.x == 0u && outputIndex < uniforms.size) {
setOutputAtIndexI32(outputIndex, xBestIndices[localId.x]);
}
}
`}},Ohe=class{constructor(e,t){this.variableNames=["A"],this.workGroupSize=[16,16,1];let r=new Array(e.length);for(let n=0;n<r.length;n++)r[n]=e[t[n]];this.outputShape=r,this.dispatchLayout={x:[0],y:[1]},this.dispatch=ze(this.dispatchLayout,this.outputShape,this.workGroupSize,[1,1,1]),this.shaderKey="transposeShared"}getUserCode(){return`
let TILE_DIM = ${this.workGroupSize[0]};
var<workgroup> tile : array<array<f32, ${this.workGroupSize[0]+1}>, ${this.workGroupSize[0]}>;
${$A()}
fn main(@builtin(local_invocation_id) localId : vec3<u32>,
@builtin(workgroup_id) workgroupId : vec3<u32>) {
var x = i32(workgroupId.x) * TILE_DIM + i32(localId.x);
var y = i32(workgroupId.y) * TILE_DIM + i32(localId.y);
let width = uniforms.outShape[0];
let height = uniforms.outShape[1];
if (x < width && y < height) {
tile[localId.y][localId.x] = A[y * width + x];
}
workgroupBarrier();
x = i32(workgroupId.y) * TILE_DIM + i32(localId.x);
y = i32(workgroupId.x) * TILE_DIM + i32(localId.y);
if (x < height && y < width) {
setOutputAtIndex((y * height + x), tile[localId.x]
[localId.y]);
}
}
`}},zhe=class{constructor(e,t){this.variableNames=["A"],this.workPerThread=4,this.workGroupSize=[64,1,1],this.size=!0;let r=new Array(e.length);for(let n=0;n<r.length;n++)r[n]=e[t[n]];this.outputShape=r,this.dispatchLayout=Je(this.outputShape),this.dispatch=ze(this.dispatchLayout,this.outputShape,this.workGroupSize,[this.workPerThread,1,1]),this.newDim=t,this.shaderKey=`transpose_${t}`}getUserCode(){let e=Ar(this.outputShape.length),t=Dhe(this.newDim);return`
${rt()}
for(var i = 0; i < ${this.workPerThread}; i = i + 1) {
let flatIndex = index * ${this.workPerThread} + i;
if(flatIndex < uniforms.size) {
let resRC = getCoordsFromIndex(flatIndex);
setOutputAtIndex(flatIndex, A[getIndexFromCoords${this.outputShape.length}D(
${e}(${t}), uniforms.aShape)]);
}
}
}
`}};function Dhe(e){let t=e.length;if(t>6)throw Error(`Transpose for rank ${t} is not yet supported`);let r=new Array(t);for(let n=0;n<e.length;n++)r[e[n]]=`resRC.${$s(n)}`;return r.join()}function Ya(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{perm:s}=n,i=r,o=a.shape.length,l=new Array(o);for(let d=0;d<l.length;d++)l[d]=a.shape[s[d]];if(r.shouldExecuteOnCPU([a])){let d=i.tensorMap.get(a.dataId).values,h=Nhe(d,a.shape,a.dtype,s,l);return r.makeTensorInfo(l,a.dtype,h)}if(a.shape.length===2&&v.arraysEqual(s,[1,0])){let d=new Ohe(a.shape,s);return i.runWebGPUProgram(d,[a],a.dtype)}let u=new zhe(a.shape,s);return i.runWebGPUProgram(u,[a],a.dtype)}var Lhe={kernelName:Ma,backendName:"webgpu",kernelFunc:Ya};function Bhe(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{axis:s}=n,i=v.parseAxisParam(s,a.shape),o=C.getAxesPermutation(i,a.shape.length),l=a,u=[];o!=null&&(l=Ya({inputs:{x:a},backend:r,attrs:{perm:o}}),u.push(l),i=C.getInnerMostAxes(i.length,l.shape.length)),C.assertAxesAreInnerMostDims("argMax",[i[0]],l.shape.length);let d=new QI(l.shape,i[0],"max"),h=[{type:"float32",data:[Number.NEGATIVE_INFINITY]}],p=r.runWebGPUProgram(d,[l],"int32",h);return u.forEach(c=>r.disposeData(c.dataId)),p}var Whe={kernelName:Zs,backendName:"webgpu",kernelFunc:Bhe};function Vhe(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{axis:s}=n,i=v.parseAxisParam(s,a.shape),o=C.getAxesPermutation(i,a.shape.length),l=a,u=[];o!=null&&(l=Ya({inputs:{x:a},backend:r,attrs:{perm:o}}),u.push(l),i=C.getInnerMostAxes(i.length,l.shape.length)),C.assertAxesAreInnerMostDims("argMin",[i[0]],l.shape.length);let d=new QI(l.shape,i[0],"min"),h=[{type:"float32",data:[Number.POSITIVE_INFINITY]}],p=r.runWebGPUProgram(d,[l],"int32",h);return u.forEach(c=>r.disposeData(c.dataId)),p}var Uhe={kernelName:qu,backendName:"webgpu",kernelFunc:Vhe},eS=class{constructor(e,t){this.variableNames=["x"],this.uniforms="stride : vec2<i32>, pad : vec2<i32>, dilation : vec2<i32>, convDims : vec2<i32>, filterDims : vec2<i32>,",this.workGroupSize=[128,1,1],this.size=!0,this.outputShape=e.outShape,this.dispatchLayout=Je(this.outputShape),this.dispatch=ze(this.dispatchLayout,this.outputShape,this.workGroupSize),this.shaderKey=`pool2D_${t}`,this.poolType=t}getUserCode(){let e="resultValue = max(value, resultValue);";this.poolType==="avg"&&(e="resultValue = resultValue + value; count = count + 1.0;");let t="resultValue";return this.poolType==="avg"&&(t="resultValue / count"),`
${rt()}
if (index < uniforms.size) {
let coords = getCoordsFromIndex(index);
let batch = coords[0];
let xRCCorner = vec2<i32>(coords.yz) * uniforms.stride - uniforms.pad;
let xRCorner = xRCCorner.x;
let xCCorner = xRCCorner.y;
var resultValue = ${this.poolType==="avg"?"0.0":"-1.0 / pow(10.0, -20.0)"};
var count = 0.0;
for (var wR = 0; wR < uniforms.filterDims.x; wR = wR + uniforms.dilation.x) {
let xR = xRCorner + wR;
if (xR < 0 || xR >= uniforms.convDims.x) {
continue;
}
for (var wC = 0; wC < uniforms.filterDims.y; wC = wC + uniforms.dilation.y) {
let xC = xCCorner + wC;
if (xC < 0 || xC >= uniforms.convDims.y) {
continue;
}
let value = getX(batch, xR, xC, coords[3]);
${e}
}
}
setOutputAtIndex(index, ${t});
}
}
`}},tS=class{constructor(e){this.variableNames=["x"],this.uniforms="stride : vec2<i32>,",this.workGroupSize=[256,1,1],this.size=!0,this.outputShape=e.outShape,this.dispatchLayout=Je(this.outputShape),this.dispatch=ze(this.dispatchLayout,this.outputShape,this.workGroupSize),this.shaderKey="poolWithFilterSizeEqualsOne"}getUserCode(){return`
${rt()}
if (index < uniforms.size) {
let coords = getCoordsFromIndex(index);
let batch = coords[0];
let d = coords[3];
let xRCCorner = coords.yz * uniforms.stride;
let xRCorner = xRCCorner.x;
let xCCorner = xRCCorner.y;
let value = getX(batch, xRCorner, xCCorner, d);
setOutputAtIndex(index, value);
}
}
`}};function Ghe(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{filterSize:s,strides:i,pad:o,dimRoundingMode:l}=n,u=1,d=C.computePool2DInfo(a.shape,s,i,u,o,l);if(d.filterWidth===1&&d.filterHeight===1&&v.arraysEqual(d.inShape,d.outShape))return On({inputs:{x:a},backend:r});let h,p=[{type:"int32",data:[d.strideHeight,d.strideWidth]}];return d.filterHeight===1&&d.filterWidth===1?h=new tS(d):(h=new eS(d,"avg"),p.push({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]})),r.runWebGPUProgram(h,[a],a.dtype,p)}var jhe={kernelName:Ys,backendName:"webgpu",kernelFunc:Ghe};function Hhe(e){let{inputs:t,backend:r,attrs:n}=e,{a,b:s}=t,{transposeA:i,transposeB:o}=n;return zA({a,b:s,transposeA:i,transposeB:o,backend:r})}var qhe={kernelName:Js,backendName:"webgpu",kernelFunc:Hhe},Xhe=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=Je(this.outputShape),this.dispatch=ze(this.dispatchLayout,this.outputShape,this.workGroupSize,[this.workPerThread,1,1]),this.start=e,this.uniforms=`start : ${Ar(e.length)}, `,this.shaderKey="slice"}getUserCode(){let e=Ar(this.rank),t=Khe(this.rank),r;return this.start.length===1?r=this.outputShape.map((n,a)=>"sourceLoc = uniforms.start + coords;"):r=this.outputShape.map((n,a)=>`sourceLoc.${gy[a]} = uniforms.start[${a}] + coords.${gy[a]};`),`
${rt()}
if (index < uniforms.size) {
var sourceLoc : ${e};
let coords = getCoordsFromIndex(index);
${r.join(`
`)}
setOutputAtIndex(index, getSource(${t}));
}
}
`}},gy=["x","y","z","w","u","v"];function Khe(e){if(e===1)return"sourceLoc";if(e<=6)return gy.slice(0,e).map(t=>`sourceLoc.${t}`).join(",");throw Error(`Slicing for rank ${e} is not yet supported`)}function Dd(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{begin:s,size:i}=n,[o,l]=Dt.parseSliceParams(a,s,i);if(Dt.assertParamsValid(a,o,l),r.shouldExecuteOnCPU([a])||a.dtype==="string"){let h=r.tensorMap.get(a.dataId),p=whe(h.values,o,l,a.shape,a.dtype);return r.makeTensorInfo(l,a.dtype,p)}if(v.sizeFromShape(l)===0)return r.makeTensorInfo(l,a.dtype,[]);let u=new Xhe(o,l),d=[{type:"int32",data:o}];return r.runWebGPUProgram(u,[a],a.dtype,d)}var Zhe={kernelName:Al,backendName:"webgpu",kernelFunc:Dd},Yhe=e=>{let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{blockShape:s,crops:i}=n;v.assert(a.shape.length<=4,()=>"batchToSpaceND for rank > 4 with a WebGPU backend not implemented yet");let o=s.reduce((A,x)=>A*x),l=C.getReshaped(a.shape,s,o),u=C.getPermuted(l.length,s.length),d=C.getReshapedPermuted(a.shape,s,o),h=C.getSliceBeginCoords(i,s.length),p=C.getSliceSize(d,i,s.length),c=[],m=qe({inputs:{x:a},backend:r,attrs:{shape:l}}),f=Ya({inputs:{x:m},backend:r,attrs:{perm:u}}),g=qe({inputs:{x:f},backend:r,attrs:{shape:d}}),y=Dd({inputs:{x:g},backend:r,attrs:{begin:h,size:p}});return c.push(m),c.push(f),c.push(g),c.forEach(A=>r.disposeData(A.dataId)),y},Jhe={kernelName:jo,backendName:"webgpu",kernelFunc:Yhe},rS=Xr({opSnippet:10,dtype:"bool",cpuKernelImpl:ghe}),Qhe={kernelName:ol,backendName:"webgpu",kernelFunc:rS};function Qh(e){let{inputs:t,backend:r}=e,{input:n}=t,a=r.tensorMap.get(n.dataId);return On({inputs:{x:a.complexTensorInfos.real},backend:r})}var ece={kernelName:ch,backendName:"webgpu",kernelFunc:Qh};function tce(e,t){let r=new Jh(e.shape,22),n=t.runWebGPUProgram(r,[e],"int32");return{dataId:n.dataId,shape:n.shape,dtype:n.dtype}}function yy(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{dtype:s}=n;if(s==="complex64"){if(a.dtype==="complex64")return On({inputs:{x:a},backend:r});let i=Ot(a.shape),o=yy({inputs:{x:a},backend:r,attrs:{dtype:"float32"}}),l=zd({inputs:{real:o,imag:i},backend:r});return i.dispose(),r.disposeData(o.dataId),l}if(a.dtype==="complex64"){let i=Qh({inputs:{input:a},backend:r}),o=yy({inputs:{x:i},backend:r,attrs:{dtype:s}});return r.disposeData(i.dataId),o}if(!v.hasEncodingLoss(a.dtype,s)){let i=On({inputs:{x:a},backend:r});return{dataId:i.dataId,shape:i.shape,dtype:s}}if(s==="int32")return tce(a,r);if(s==="bool"){let i=r.makeTensorInfo([],"bool",v.getTypedArrayFromDType("bool",1)),o=rS({inputs:{a,b:i},backend:r});return r.disposeData(i.dataId),o}throw new Error(`Error in Cast: failed to cast ${a.dtype} to ${s}`)}var rce={kernelName:Qs,backendName:"webgpu",kernelFunc:yy},nce=wr({opType:1,cpuKernelImpl:Jpe}),ace={kernelName:ei,backendName:"webgpu",kernelFunc:nce},sce=class{constructor(e){this.variableNames=["A"],this.uniforms="minVal : f32, maxVal : f32,",this.workPerThread=4,this.workGroupSize=[64,1,1],this.isVec4=!0,this.size=!0,this.outputShape=e,this.dispatchLayout=Je(this.outputShape),this.dispatch=ze(this.dispatchLayout,this.outputShape,this.workGroupSize,[this.workPerThread,1,1]),this.shaderKey="clipVec4"}getUserCode(){return`
${rt()}
if(index < uniforms.size) {
let value = getAByOutputIndex(index);
var clampedValue : vec4<f32>;
for (var i = 0; i < 4; i = i + 1) {
if (isnan(value[i])) {
clampedValue[i] = value[i];
} else {
clampedValue[i] = clamp(value[i], uniforms.minVal, uniforms.maxVal);
}
}
setOutputAtIndex(index, clampedValue);
}
}
`}},ice=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=Je(this.outputShape),this.dispatch=ze(this.dispatchLayout,this.outputShape,this.workGroupSize),this.shaderKey="clip"}getUserCode(){return`
${rt()}
if(index < uniforms.size) {
let value = getAByOutputIndex(index);
if (isnan(value)) {
setOutputAtIndex(index, value);
return;
}
setOutputAtIndex(index, clamp(value, uniforms.minVal, uniforms.maxVal));
}
}
`}};function oce(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{clipValueMin:s,clipValueMax:i}=n,o,l=[{type:"float32",data:[s]},{type:"float32",data:[i]}];return v.sizeFromShape(a.shape)%4===0?o=new sce(a.shape):o=new ice(a.shape),r.runWebGPUProgram(o,[a],a.dtype,l)}var lce={kernelName:Qa,backendName:"webgpu",kernelFunc:oce},uce=class{constructor(e){this.uniforms="",this.workPerThread=4,this.workGroupSize=[64,1,1],this.size=!0,this.outputShape=C.computeOutShape(e,1),this.variableNames=e.map((t,r)=>`T${r}`),this.dispatchLayout=Je(this.outputShape),this.dispatch=ze(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,r=this.offsetLength-1;e.push(`else { setOutputAtCoords(coords.x, coords.y, getT${t}(yR, yC - uniforms.offset${r})); }`)}else e.push("setOutputAtCoords(coords.x, coords.y, getT0(yR, yC));");return`
${rt()}
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 Lm(e){let{inputs:t,backend:r}=e,{input:n}=t,a=r.tensorMap.get(n.dataId);return On({inputs:{x:a.complexTensorInfos.imag},backend:r})}var dce={kernelName:uh,backendName:"webgpu",kernelFunc:Lm};function Ay(e,t,r){let n=e[0].dtype;if(n==="complex64"){let c=e.map(A=>Qh({inputs:{input:A},backend:r})),m=e.map(A=>Lm({inputs:{input:A},backend:r})),f=Ay(c,t,r),g=Ay(m,t,r),y=zd({inputs:{real:f,imag:g},backend:r});return c.forEach(A=>r.disposeData(A.dataId)),m.forEach(A=>r.disposeData(A.dataId)),r.disposeData(f.dataId),r.disposeData(g.dataId),y}let a=r.shouldExecuteOnCPU(e);if(n==="string"&&(a=!0),a){let c=e.map(b=>{let w=v.sizeFromShape(b.shape.slice(t));return qe({inputs:{x:b},backend:r,attrs:{shape:[-1,w]}})}),m=c.map(b=>({vals:r.readSync(b.dataId),shape:b.shape})),f=C.computeOutShape(c.map(b=>b.shape),1),g=c[0].shape[0]===1,y=Qpe(m,f,n,g),A=C.computeOutShape(e.map(b=>b.shape),t),x=r.makeTensorInfo(A,n,y);return c.forEach(b=>r.disposeData(b.dataId)),x}let{tensors2D:s,outShape:i}=pce(e,t,r),o=s.map(c=>c.shape),l=new uce(o),u=[],d=new Array(o.length-1);if(d.length>0){d[0]=o[0][1],u.push({type:"int32",data:[d[0]]});for(let c=1;c<d.length;c++)d[c]=d[c-1]+o[c][1],u.push({type:"int32",data:[d[c]]})}let h=r.runWebGPUProgram(l,s,s[0].dtype,u);s.forEach(c=>r.disposeData(c.dataId));let p=qe({inputs:{x:h},backend:r,attrs:{shape:i}});return r.disposeData(h.dataId),p}function pce(e,t,r){let n=C.computeOutShape(e.map(a=>a.shape),t);return{tensors2D:e.map(a=>qe({inputs:{x:a},backend:r,attrs:{shape:[v.sizeFromShape(a.shape.slice(0,t)),v.sizeFromShape(a.shape.slice(t))]}})),outShape:n}}function nS(e){let{inputs:t,backend:r,attrs:n}=e,{axis:a}=n,s=v.parseAxisParam(a,t[0].shape)[0],i=C.computeOutShape(t.map(u=>u.shape),s);if(v.sizeFromShape(i)===0)return r.makeTensorInfo(i,t[0].dtype,[]);let o=t.filter(u=>v.sizeFromShape(u.shape)>0);if(o.length===1)return On({inputs:{x:o[0]},backend:r});let l=o.map(u=>u.shape);return C.assertParamsConsistent(l,s),Ay(o,s,r)}var hce={kernelName:Ho,backendName:"webgpu",kernelFunc:nS},cce=class{constructor(e,t=!1,r=null,n=!1){this.variableNames=["x","W"],this.uniforms=`filterDims : vec2<i32>, pad : vec2<i32>, stride : vec2<i32>, dilation : vec2<i32>,
dimAOuter : i32, dimBOuter : i32, dimInner : i32,`,this.workGroupSize=[8,8,1],this.isVec4=!0,this.outputShape=e.outShape,v.assert(e.dataFormat==="channelsLast",()=>"TODO: NCHW is unimplemented"),this.dispatchLayout={x:[3],y:[1,2],z:[0]},this.outputShape[1]===1?this.elementsPerThread=[4,1,1]:this.elementsPerThread=[4,4,1],this.dispatch=ze(this.dispatchLayout,this.outputShape,this.workGroupSize,this.elementsPerThread),this.convInfo=e,this.addBias=t,this.activation=r,this.hasPreluActivationWeights=n,this.innerElementSize=this.convInfo.inChannels%4===0?4:3,this.innerElementSize===3?this.variableTypes=["f32","vec4<f32>"]:this.variableTypes=["vec4<f32>","vec4<f32>"],this.addBias&&(this.variableNames.push("bias"),this.variableTypes.push("vec4<f32>")),this.hasPreluActivationWeights&&(this.variableNames.push("preluActivationWeights"),this.variableTypes.push("vec4<f32>")),this.tileAOuter=this.outputShape[1]===1?1:this.workGroupSize[1]*this.elementsPerThread[1],this.tileBOuter=this.workGroupSize[0]*this.elementsPerThread[0],this.tileInner=this.workGroupSize[0]*this.innerElementSize,[this.fitA,this.fitB]=this.getShapeFit(),this.shaderKey=`conv2DMMVec4_${this.activation}_${this.fitA}_${this.fitB}_${this.elementsPerThread}_${this.innerElementSize}`}getShapeFit(){let e=[this.tileAOuter,this.tileInner],t=[this.tileInner,this.tileBOuter],r=this.outputShape[1]*this.outputShape[2],n=this.outputShape[3],a=this.convInfo.filterHeight*this.convInfo.filterWidth*this.convInfo.inChannels;return[th(e,[r,a]),th(t,[a,n])]}getUserCode(){let e=YI(this.elementsPerThread,this.tileAOuter,this.tileBOuter,this.tileInner,this.innerElementSize),t=`let outRow = r / uniforms.outShape[2];
let outCol = r % uniforms.outShape[2];
let WRow = c / (uniforms.filterDims[1] * uniforms.xShape[3]);
let WCol = c / uniforms.xShape[3] % uniforms.filterDims[1];
let inChCoord = c % uniforms.xShape[3];
let xRow = outRow * uniforms.stride[0] + uniforms.dilation[0] * WRow - uniforms.pad[0];
let xCol = outCol * uniforms.stride[1] + uniforms.dilation[1] * WCol - uniforms.pad[1];
var resData = vec${this.innerElementSize}<f32>(0.0);
// The bounds checking is always needed since we use it to pad zero for
// the 'same' padding type.
if (xRow >= 0 && xRow < uniforms.xShape[1] && xCol >= 0 && xCol < uniforms.xShape[2]) {
var coord = vec4<i32>(
batch,
xRow,
xCol,
inChCoord);
let xIndex = getIndexFromCoords4D(coord, uniforms.xShape);
${this.innerElementSize===3?"resData = vec3<f32>(x[xIndex], x[xIndex + 1], x[xIndex + 2]);":"resData = x[xIndex / 4];"}
}
return resData;`,r=this.fitA?`${t}`:`if (r < uniforms.dimAOuter && c < uniforms.dimInner) {
${t}
}
return vec${this.innerElementSize}<f32>(0.0);
`,n=this.fitB?"return W[row * uniforms.dimBOuter / 4 + col];":`if(coordsInBounds2D(vec2<i32>(row, col * 4), vec2<i32>(uniforms.dimInner, uniforms.dimBOuter))) {
return W[row * uniforms.dimBOuter / 4 + col];
}
return vec4<f32>(0.0);
`,a="",s="";if(this.activation){let o=qi(this.activation,this.isVec4);this.hasPreluActivationWeights?a=`fn activation(a : vec4<f32>, outCoord : vec4<i32>) -> vec4<f32> {
let b = getPreluActivationWeightsByOutputCoords(outCoord);
${o}
}`:a=`
fn activation(a : vec4<f32>, outCoord : vec4<i32>) -> vec4<f32> {
${o}
}`,s="value = activation(value, outCoord);"}let i=this.addBias?"value = value + getBiasByOutputCoords(outCoord);":"";return`
${a}
fn mm_readA(row : i32, col : i32, globalId : vec3<u32>) -> vec${this.innerElementSize}<f32> {
let r = row;
let c = col * ${this.innerElementSize};
var batch = i32(globalId.z);
${r}
}
fn mm_readB(row : i32, col : i32, globalId : vec3<u32>) -> vec4<f32> {
${n}
}
fn mm_write(row : i32, col : i32, valueInput : vec4<f32>, globalId : vec3<u32>) {
var batch = i32(globalId.z);
var value = valueInput;
if (row < uniforms.dimAOuter && col * 4 < uniforms.dimBOuter)
{
let outCoord = vec4<i32>(
batch,
row / uniforms.outShape[2],
row % uniforms.outShape[2],
col * 4);
${i}
${s}
setOutputAtCoords(outCoord[0], outCoord[1], outCoord[2], outCoord[3],
value);
}
}
${e}
`}},fce=class{constructor(e,t,r,n,a=!1,s=null,i=!1){this.variableNames=["x","W"],this.uniforms="filterDims : vec2<i32>, pad : vec2<i32>, stride : vec2<i32>, dilation : vec2<i32>, dimAOuter : i32, dimBOuter : i32, dimInner : i32,",this.outputShape=e.outShape,this.isChannelsLast=e.dataFormat==="channelsLast",this.dispatchLayout=this.isChannelsLast?{x:[3],y:[1,2],z:[0]}:{x:[2,3],y:[1],z:[0]},this.workGroupSize=FA(this.dispatchLayout,this.outputShape),this.elementsPerThread=_A(this.dispatchLayout,this.outputShape),this.dispatch=ze(this.dispatchLayout,this.outputShape,this.workGroupSize,this.elementsPerThread),a&&this.variableNames.push("bias"),i&&this.variableNames.push("preluActivationWeights"),this.addBias=a,this.activation=s,this.hasPreluActivationWeights=i;let o=this.workGroupSize[1]*this.elementsPerThread[1],l=this.workGroupSize[0]*this.elementsPerThread[0];this.tileInner=32,this.fitAOuter=t%o===0,this.fitBOuter=r%l===0,this.fitInner=n%this.tileInner===0,this.shaderKey=`conv2DMM_${this.elementsPerThread}_${this.activation}}_${this.fitAOuter}_${this.fitBOuter}_${this.fitInner}_${this.isChannelsLast}`}getUserCode(){let e=this.isChannelsLast?`
let coord = vec4<i32>(batch, xRow, xCol, xCh);
`:`
let coord = vec4<i32>(batch, xCh, xRow, xCol);
`,t=this.isChannelsLast?`
let outCoord = vec4<i32>(
batch,
row / outWidth,
row % outWidth,
col);
`:`
let outCoord = vec4<i32>(
batch,
row,
col / outWidth,
col % outWidth);
`,r=OA(this.elementsPerThread,this.workGroupSize,!this.isChannelsLast,this.tileInner),n=this.isChannelsLast?"row":"col",a=this.isChannelsLast?"col":"row",s=`
let inChannels = uniforms.wShape[2];
let outWidth = ${this.isChannelsLast?"uniforms.outShape[2]":"uniforms.outShape[3]"};
let outRow = ${n} / outWidth;
let outCol = ${n} % outWidth;
let WRow = ${a} / (uniforms.filterDims[1] * inChannels);
let WCol = ${a} / inChannels % uniforms.filterDims[1];
let xRow = outRow * uniforms.stride[0] + uniforms.dilation[0] * WRow - uniforms.pad[0];
let xCol = outCol * uniforms.stride[1] + uniforms.dilation[1] * WCol - uniforms.pad[1];
let xCh = ${a} % inChannels;
${e}
// The bounds checking is always needed since we use it to pad zero for the
// 'same' padding type.
if(coordsInBounds4D(coord, uniforms.xShape)) {
return x[getIndexFromCoords4D(coord, uniforms.xShape)];
}
return 0.0;`,i=this.isChannelsLast?this.fitAOuter&&this.fitInner?`${s}`:`if (row < uniforms.dimAOuter && col < uniforms.dimInner) {
${s}
}
return 0.0;`:this.fitInner&&this.fitBOuter?`${s}`:`if (row < uniforms.dimInner && col < uniforms.dimBOuter) {
${s}
}
return 0.0;`,o="return W[row * uniforms.wShape[3] + col];",l="",u="";if(this.activation){let h=qi(this.activation,!1);this.hasPreluActivationWeights?l=`fn activation(a: f32, outCoord : vec4<i32>) -> f32 {
let b = getPreluActivationWeightsByOutputCoords(outCoord);
${h}
}`:l=`
fn activation(a : f32, outCoord : vec4<i32>) -> f32 {
${h}
}
`,u="value = activation(value, outCoord);"}let d=this.addBias?"value = value + getBiasByOutputCoords(outCoord);":"";return`
${l}
fn mm_readA(row : i32, col : i32, globalId : vec3<u32>) -> f32 {
var batch = i32(globalId.z);
${this.isChannelsLast?i:o}
}
fn mm_readB(row : i32, col : i32, globalId : vec3<u32>) -> f32 {
var batch = i32(globalId.z);
${this.isChannelsLast?o:i}
}
fn mm_write(row : i32, col : i32, valueInput : f32, globalId : vec3<u32>) {
var batch = i32(globalId.z);
var value = valueInput;
let outWidth = ${this.isChannelsLast?"uniforms.outShape[2]":"uniforms.outShape[3]"};
${t}
${d}
${u}
result[getIndexFromCoords4D(outCoord, uniforms.outShape)] = value;
}
${r}
`}};function g7(e,t){let r=e.length;return r>=3?t?[...e.slice(0,-3),e[r-3]*e[r-2],e[r-1]]:[...e.slice(0,-3),e[r-3],e[r-2]*e[r-1]]:!t&&r===1&&e[0]>1?[e[0],1]:null}function mce({x:e,filter:t,convInfo:r,backend:n,bias:a=null,preluActivationWeights:s=null,leakyreluAlpha:i=0,activation:o=null}){let l=r.dataFormat==="channelsLast",u=!l,d=!1,h=l&&r.filterHeight===r.inHeight&&r.filterWidth===r.inWidth&&r.padInfo.type==="VALID",p=[],c,m;if(h){let y=r.inHeight*r.inWidth*r.inChannels;c=qe({inputs:{x:e},backend:n,attrs:{shape:[1,r.batchSize,y]}}),m=qe({inputs:{x:t},backend:n,attrs:{shape:[1,y,r.outChannels]}})}else c=qe({inputs:{x:e},backend:n,attrs:{shape:l?[r.batchSize,r.inHeight*r.inWidth,r.inChannels]:[r.batchSize,r.inChannels,r.inHeight*r.inWidth]}}),m=qe({inputs:{x:t},backend:n,attrs:{shape:[1,r.inChannels,r.outChannels]}});if(p.push(c),p.push(m),s!=null){let y=g7(s.shape,l);y!=null&&(s=qe({inputs:{x:s},backend:n,attrs:{shape:y}}),p.push(s))}if(a!=null){let y=g7(a.shape,l);y!=null&&(a=qe({inputs:{x:a},backend:n,attrs:{shape:y}}),p.push(a))}let f=zA({a:l?c:m,b:l?m:c,transposeA:u,transposeB:d,backend:n,bias:a,activation:o,preluActivationWeights:s,leakyreluAlpha:i}),g=qe({inputs:{x:f},backend:n,attrs:{shape:r.outShape}});p.push(f);for(let y of p)n.disposeData(y.dataId);return g}function aS({x:e,filter:t,convInfo:r,backend:n,bias:a=null,preluActivationWeights:s=null,leakyreluAlpha:i=0,activation:o=null}){let l=a!=null,u=s!=null,d=r.dataFormat==="channelsLast",h;if(d&&r.filterHeight===r.inHeight&&r.filterWidth===r.inWidth&&r.padInfo.type==="VALID"||r.filterHeight===1&&r.filterWidth===1&&r.dilationHeight===1&&r.dilationWidth===1&&r.strideHeight===1&&r.strideWidth===1&&(r.padInfo.type==="SAME"||r.padInfo.type==="VALID"))return mce({x:e,filter:t,convInfo:r,backend:n,bias:a,activation:o,preluActivationWeights:s,leakyreluAlpha:i});let p=(r.inChannels%4===0||r.inChannels%3===0)&&r.outChannels%4===0&&d,c=d?r.outHeight*r.outWidth:r.outChannels,m=d?r.outChannels:r.outHeight*r.outWidth,f=r.filterHeight*r.filterWidth*r.inChannels,g=[r.padInfo.top,r.padInfo.left],y=[{type:"int32",data:[r.filterHeight,r.filterWidth]},{type:"int32",data:[...g]},{type:"int32",data:[r.strideHeight,r.strideWidth]},{type:"int32",data:[r.dilationHeight,r.dilationWidth]},{type:"int32",data:[c]},{type:"int32",data:[m]},{type:"int32",data:[f]}];p?h=new cce(r,l,o,u):h=new fce(r,c,m,f,l,o,u);let A=[],x=[e,t];l&&(!d&&a.shape.length===1&&(a=qe({inputs:{x:a},backend:n,attrs:{shape:[a.shape[0],1,1]}}),A.push(a)),x.push(a)),u&&(!d&&s.shape.length===1&&(s=qe({inputs:{x:s},backend:n,attrs:{shape:[s.shape[0],1,1]}}),A.push(s)),x.push(s)),o==="leakyrelu"&&(y.push({type:"float32",data:[i]}),h.uniforms+=" alpha : f32,");let b=n.runWebGPUProgram(h,x,e.dtype,y);for(let w of A)n.disposeData(w.dataId);return b}function gce(e){let{inputs:t,attrs:r,backend:n}=e,{x:a,filter:s}=t,{strides:i,pad:o,dataFormat:l,dilations:u,dimRoundingMode:d}=r,h=C.convertConv2DDataFormat(l),p=C.computeConv2DInfo(a.shape,s.shape,i,u,o,d,!1,h);return aS({x:a,filter:s,convInfo:p,backend:n})}var yce={kernelName:ti,backendName:"webgpu",kernelFunc:gce},Ace=class{constructor(e){this.variableNames=["x","W"],this.uniforms="filterDims : vec2<i32>, pads : vec2<i32>, stride : vec2<i32>, outBackprop : vec4<i32>, dimAOuter : i32, dimBOuter : i32, dimInner : i32,",this.outputShape=e.inShape,v.assert(e.dataFormat==="channelsLast",()=>"TODO: NCHW is unimplemented"),this.dispatchLayout={x:[3],y:[1,2],z:[0]},this.workGroupSize=FA(this.dispatchLayout,this.outputShape),this.elementsPerThread=_A(this.dispatchLayout,this.outputShape),this.dispatch=ze(this.dispatchLayout,this.outputShape,this.workGroupSize,this.elementsPerThread),this.shaderKey=`conv2DDerInputMM_${this.elementsPerThread}`}getUserCode(){return`
fn mm_readA(row : i32, col : i32, globalId : vec3<u32>) -> f32 {
var batch = i32(globalId.z);
if (row < uniforms.dimAOuter && col < uniforms.dimInner) {
let outRow = row / uniforms.outShape[2];
let outCol = row % uniforms.outShape[2];
let WRow = col / (uniforms.filterDims[1] * uniforms.outBackprop[3]);
let WCol = col / uniforms.outBackprop[3] % uniforms.filterDims[1];
let xR = f32(outRow - uniforms.pads[0] + WRow) / f32(uniforms.stride[0]);
let xC = f32(outCol - uniforms.pads[1] + WCol) / f32(uniforms.stride[1]);
if (xR < 0.0 || xR >= f32(uniforms.outBackprop[1]) || fract(xR) > 0.0) {
return 0.0;
}
if (xC < 0.0 || xC >= f32(uniforms.outBackprop[2]) || fract(xC) > 0.0) {
return 0.0;
}
let coord = vec4<i32>(
batch,
i32(xR),
i32(xC),
col % uniforms.outBackprop[3]);
return x[getIndexFromCoords4D(coord, uniforms.xShape)];
}
return 0.0;
}
fn mm_readB(row : i32, col : i32, globalId : vec3<u32>) -> f32 {
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 coord = vec4<i32>(coordX, coordY, col,
row % uniforms.outBackprop[3]);
return W[getIndexFromCoords4D(coord, uniforms.wShape)];
}
return 0.0;
}
fn mm_write(row : i32, col : i32, valueInput : f32, globalId : vec3<u32>) {
var batch = i32(globalId.z);
var value = valueInput;
let outCoord = vec4<i32>(
batch,
row / uniforms.outShape[2],
row % uniforms.outShape[2],
col);
result[getIndexFromCoords4D(outCoord, uniforms.outShape)] = value;
}
${OA(this.elementsPerThread,this.workGroupSize)}
`}},xce=class{constructor(e){this.variableNames=["dy","W"],this.uniforms="filterDims : vec2<i32>, pads : vec2<i32>, stride : vec2<i32>, outBackprop : vec4<i32>,",this.workGroupSize=[64,1,1],this.size=!0,this.outputShape=e.inShape,this.dispatchLayout=Je(this.outputShape),this.dispatch=ze(this.dispatchLayout,this.outputShape,this.workGroupSize),this.isChannelsLast=e.dataFormat==="channelsLast",this.shaderKey=`conv2DDerInput_${this.isChannelsLast}`}getUserCode(){let e=this.isChannelsLast?1:2,t=this.isChannelsLast?2:3,r=this.isChannelsLast?3:1;return`
${rt()} {
if(index < uniforms.size) {
let coords = getCoordsFromIndex(index);
let batch = coords[0];
let d1 = coords[${r}];
let dyCorner = vec2<i32>(coords[${e}]), coords[${t}]) - uniforms.pads;
let dyRCorner = dyCorner.x;
let dyCCorner = dyCorner.y;
// Convolve dy(?, ?, d2) with w(:, :, d1, d2) to compute dx(xR, xC, d1).
// ? = to be determined. : = across all values in that axis.
var dotProd = 0.0;
for (var wR = 0; wR < uniforms.filterDims.x; wR = wR + 1) {
let dyR = (f32(dyRCorner) + f32(wR)) / f32(uniforms.stride.x);
let wRPerm = uniforms.filterDims.x - 1 - wR;
if (dyR < 0.0 || dyR >= f32(uniforms.outBackprop[1]) || fract(dyR) > 0.0 ||
wRPerm < 0) {
continue;
}
let idyR = dyR;
for (var wC = 0; wC < uniforms.filterDims.y; wC = wC + 1) {
let dyC = (f32(dyCCorner) + f32(wC)) / f32(uniforms.stride.y);
let wCPerm = uniforms.filterDims.y - 1 - wC;
if (dyC < 0.0 || dyC >= f32(uniforms.outBackprop[2]) ||
fract(dyC) > 0.0 || wCPerm < 0) {
continue;
}
let idyC = dyC;
for (var d2 = 0; d2 < uniforms.outBackprop[3]; d2 = d2 + 1) {
if (${this.isChannelsLast}) {
let xValue = getDy(batch, idyR, idyC, d2);
let wValue = getW(wRPerm, wCPerm, d1, d2);
dotProd = dotProd + xValue * wValue;
} else {
let xValue = getDy(batch, d2, idyR, idyC);
let wValue = getW(wRPerm, wCPerm, d1, d2);
dotProd = dotProd + xValue * wValue;
}
}
}
}
setOutputAtIndex(index, dotProd);
}
}
`}};function bce(e){let{inputs:t,backend:r,attrs:n}=e,{dy:a,filter:s}=t,{inputShape:i,strides:o,pad:l,dataFormat:u,dimRoundingMode:d}=n,h=C.convertConv2DDataFormat(u),p=C.computeConv2DInfo(i,s.shape,o,1,l,d,!1,h),c=[{type:"int32",data:[p.filterHeight,p.filterWidth]},{type:"int32",data:[p.filterHeight-1-p.padInfo.top,p.filterWidth-1-p.padInfo.left]},{type:"int32",data:[p.strideHeight,p.strideWidth]},{type:"int32",data:[p.batchSize,p.outHeight,p.outWidth,p.outChannels]}],m;if(Z().getBool("WEBGPU_USE_NAIVE_CONV2D_TRANSPOSE"))m=new xce(p);else{m=new Ace(p);let f=p.inShape[1]*p.inShape[2],g=p.inShape[3],y=p.filterHeight*p.filterWidth*p.outChannels;c.push({type:"uint32",data:[f]},{type:"uint32",data:[g]},{type:"uint32",data:[y]})}return r.runWebGPUProgram(m,[a,s],"float32",c)}var vce={kernelName:ri,backendName:"webgpu",kernelFunc:bce},wce=wr({opType:2}),kce={kernelName:ni,backendName:"webgpu",kernelFunc:wce},Ice=wr({opType:3}),Sce={kernelName:ai,backendName:"webgpu",kernelFunc:Ice},Cce=class{constructor(e,t,r,n){this.variableNames=["Image","Boxes","BoxInd"],this.uniforms="extrapolationValue : f32,",this.workGroupSize=[64,1,1],this.size=!0;let[a]=t;this.outputShape=[a,r[0],r[1],e],this.dispatchLayout=Je(this.outputShape),this.dispatch=ze(this.dispatchLayout,this.outputShape,this.workGroupSize),this.methodId=n==="bilinear"?1:0,this.cropHeightBiggerThan1=this.outputShape[1]>1,this.cropWidthBiggerThan1=this.outputShape[2]>1,this.shaderKey=`cropAndResize_${this.methodId}_${this.cropHeightBiggerThan1}_${this.cropWidthBiggerThan1}`}getUserCode(){let[e,t]=["f32(uniforms.imageShape[1] - 1)","f32(uniforms.imageShape[2] - 1)"],[r,n,a]=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`
${rt()}
if (index < uniforms.size) {
let coords = getCoordsFromIndex(index);
let height_ratio = f32(${r});
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 = ${a};
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);
}
}
}
`}},Tce=e=>{let{inputs:t,backend:r,attrs:n}=e,{image:a,boxes:s,boxInd:i}=t,{cropSize:o,method:l,extrapolationValue:u}=n,d=new Cce(a.shape[3],s.shape,o,l),h=[{type:"float32",data:[u]}];return r.runWebGPUProgram(d,[a,s,i],"float32",h)},Nce={kernelName:Xo,backendName:"webgpu",kernelFunc:Tce},y7=class{constructor(e,t,r,n){this.variableNames=["x"],this.uniforms="index : f32,",this.size=!0;let a=128;this.workGroupSize=[a,1,1],this.outputShape=t,this.dispatchLayout=Je(this.outputShape),this.dispatch=ze(this.dispatchLayout,this.outputShape,this.workGroupSize),this.exclusive=r,this.reverse=n,this.op=e,this.shaderKey=`cum_${this.op}_${this.exclusive}_${this.reverse}`}getUserCode(){let e=this.outputShape.length,t=this.op==="*"?"1.0":"0.0",r=this.exclusive?t:`getX(${A7(e,"coords",this.op)})`,n=this.outputShape[this.outputShape.length-1],a="",s="";return this.exclusive?(a=this.reverse?`end != ${n-1}`:"end != 0",s=this.reverse?"end + 1":"end - 1"):(a=this.reverse?`end + pow2 < ${n}`:"end >= pow2",s=this.reverse?"end + pow2":"end - pow2"),`
${rt()}
if (index < uniforms.size) {
var coords = getCoordsFromIndex(index);
let end = ${x7(e,"coords",this.op)};
var val = ${r};
let pow2 = i32(pow(2.0, uniforms.index));
if (${a}) {
let idx = ${s};
${x7(e,"coords",this.op)} = idx;
val ${this.op}= getX(${A7(e,"coords",this.op)});
}
setOutputAtIndex(index, val);
}
}
`}};function A7(e,t,r){if(e===1)return`${t}`;if(e===2)return`${t}.x, ${t}.y`;if(e===3)return`${t}.x, ${t}.y, ${t}.z`;if(e===4)return`${t}.x, ${t}.y, ${t}.z, ${t}.w`;throw Error(`Cumulative ${r} for rank ${e} is not yet supported`)}function x7(e,t,r){if(e===1)return`${t}`;if(e===2)return`${t}.y`;if(e===3)return`${t}.z`;if(e===4)return`${t}.w`;throw Error(`Cumulative ${r} for rank ${e} is not yet supported`)}function sS(e,t,r,n,a,s){let i=t.shape.length,o=C.getAxesPermutation([n],i),l=t;o!=null&&(l=Ya({inputs:{x:t},backend:r,attrs:{perm:o}}));let u=C.getInnerMostAxes(1,i)[0];if(u!==i-1)throw new Error(`WebGPU cumprod shader expects an inner-most axis=${t.shape.length-1} but got axis=${n}`);let d=l.shape[u],h=On({inputs:{x:l},backend:r});for(let p=0;p<=Math.ceil(Math.log2(d))-1;p++){let c=new y7(e,l.shape,!1,s),m=h,f=[{type:"float32",data:[p]}];h=r.runWebGPUProgram(c,[h],h.dtype,f),r.disposeData(m.dataId)}if(a){let p=new y7(e,l.shape,a,s),c=h,m=[{type:"float32",data:[0]}];h=r.runWebGPUProgram(p,[h],h.dtype,m),r.disposeData(c.dataId)}if(o!=null){let p=C.getUndoAxesPermutation(o),c=Ya({inputs:{x:h},backend:r,attrs:{perm:p}});return r.disposeData(h.dataId),r.disposeData(l.dataId),c}return h}function Ece(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{axis:s,exclusive:i,reverse:o}=n;return sS("*",a,r,s,i,o)}var Rce={kernelName:qo,backendName:"webgpu",kernelFunc:Ece};function Mce(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{axis:s,exclusive:i,reverse:o}=n;return sS("+",a,r,s,i,o)}var $ce={kernelName:si,backendName:"webgpu",kernelFunc:Mce},Fce=class{constructor(e,t){this.variableNames=["x"],this.workGroupSize=[64,1,1],this.size=!0,this.uniforms="blockSize : i32,",this.outputShape=e,this.dispatchLayout=Je(this.outputShape),this.dispatch=ze(this.dispatchLayout,this.outputShape,this.workGroupSize),this.shaderKey=`depthToSpace_${t}`,this.dataFormat=t}getUserCode(){return`
${rt()}
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 = ${this.getInputSamplingString()};
setOutputAtIndex(index, rlt);
}
}`}getHeightCoordString(){return this.dataFormat==="NHWC"?"coords[1]":"coords[2]"}getWidthCoordString(){return this.dataFormat==="NHWC"?"coords[2]":"coords[3]"}getDepthCoordString(){return this.dataFormat==="NHWC"?"coords[3]":"coords[1]"}getOutputDepthSize(){return this.dataFormat==="NHWC"?"uniforms.outShape[3]":"uniforms.outShape[1]"}getInputSamplingString(){return this.dataFormat==="NHWC"?"getX(b, in_h, in_w, in_d)":"getX(b, in_d, in_h, in_w)"}};function _ce(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{blockSize:s,dataFormat:i}=n,o=a.shape[0],l=i==="NHWC"?a.shape[1]:a.shape[2],u=i==="NHWC"?a.shape[2]:a.shape[3],d=i==="NHWC"?a.shape[3]:a.shape[1],h=l*s,p=u*s,c=d/(s*s),m=i==="NHWC"?[o,h,p,c]:[o,c,h,p],f=[{type:"int32",data:[s]}],g=new Fce(m,i);return r.runWebGPUProgram(g,[a],a.dtype,f)}var Pce={kernelName:Ko,backendName:"webgpu",kernelFunc:_ce},iS=class{constructor(e,t=!1,r=null,n=!1){this.variableNames=["x","W"],this.uniforms="pad : vec2<i32>, stride : vec2<i32>, dilation : vec2<i32>, inDims : vec2<i32>,",this.workGroupSize=[4,4,4],this.isVec4=!0,this.outputShape=e.outShape,this.dispatchLayout={x:[0,1],y:[2],z:[3]},this.dispatch=ze(this.dispatchLayout,this.outputShape,this.workGroupSize,[1,4,4]),v.assert(e.dataFormat==="channelsLast",()=>"TODO: NCHW is unimplemented"),t&&this.variableNames.push("bias"),n&&this.variableNames.push("preluActivationWeights"),this.convInfo=e,this.addBias=t,this.activation=r,this.hasPreluActivation=n,this.shaderKey=`depthwise3x3_${r}`}getUserCode(){let e="",t="";if(this.activation){let n=qi(this.activation,this.isVec4);this.hasPreluActivation?e=`fn activation(a : vec4<f32>, outCoord : vec4<i32>) -> vec4<f32> {
let b = getPreluActivationWeightsByOutputCoords(outCoord);
${n}
}`:e=`
fn activation(a : vec4<f32>, outCoord : vec4<i32>) -> vec4<f32> {
${n}
}
`,t="dotProd[i] = activation(dotProd[i], coords);"}let r=this.addBias?"dotProd[i] = dotProd[i] + getBiasByOutputCoords(coords);":"";return`
${e}
${$A()}
fn main(@builtin(global_invocation_id) globalId: vec3<u32>) {
let batch = 0;
let r = i32(globalId.x);
let c = i32(globalId.y) * 4;
let d2 = i32(globalId.z) * 4;
let xRCCorner = vec2<i32>(r, c) * uniforms.stride - uniforms.pad;
let d1 = d2;
let q = 0;
let xRCorner = xRCCorner.x;
let xCCorner = xRCCorner.y;
var wVals : array<vec4<f32>, 9>;
wVals[0] = getW(0, 0, d1, q);
wVals[1] = getW(0, 1, d1, q);
wVals[2] = getW(0, 2, d1, q);
wVals[3] = getW(1, 0, d1, q);
wVals[4] = getW(1, 1, d1, q);
wVals[5] = getW(1, 2, d1, q);
wVals[6] = getW(2, 0, d1, q);
wVals[7] = getW(2, 1, d1, q);
wVals[8] = getW(2, 2, d1, q);
var xVals : array<array<vec4<f32>, 6>, 3>;
for (var wR = 0; wR < 3; wR = wR + 1) {
let xR = xRCorner + wR * uniforms.dilation[0];
for (var wC = 0; wC < 6; wC = wC + 1) {
let xC = xCCorner + wC * uniforms.dilation[1];
if (xR < 0 || xR >= uniforms.inDims[0] || xC < 0 || xC >= uniforms.inDims[1]) {
xVals[wR][wC] = vec4<f32>(0.0);
} else {
xVals[wR][wC] = getX(batch, xR, xC, d1);
}
}
}
var dotProd : array<vec4<f32>, 4>;
dotProd[0] = vec4<f32>(0.0);
dotProd[1] = vec4<f32>(0.0);
dotProd[2] = vec4<f32>(0.0);
dotProd[3] = vec4<f32>(0.0);
for (var wR = 0; wR < 3; wR = wR + 1) {
for (var wC = 0; wC < 3; wC = wC + 1) {
let indexW = wR * 3 + wC;
dotProd[0] = dotProd[0] + xVals[wR][0 + wC] * wVals[indexW];
dotProd[1] = dotProd[1] + xVals[wR][1 + wC] * wVals[indexW];
dotProd[2] = dotProd[2] + xVals[wR][2 + wC] * wVals[indexW];
dotProd[3] = dotProd[3] + xVals[wR][3 + wC] * wVals[indexW];
}
}
for (var i = 0; i < 4; i = i + 1) {
let coords = vec4<i32>(batch, r, c + i, d2);
if (coordsInBounds4D(coords, uniforms.outShape)) {
${r}
${t}
setOutputAtCoords(coords[0], coords[1], coords[2], coords[3], dotProd[i]);
}
}
}
`}},oS=class{constructor(e,t=!1,r=null,n=!1){this.variableNames=["x","W"],this.uniforms=`pad : vec2<i32>, stride : vec2<i32>, dilation : vec2<i32>,
inDims : vec2<i32>, filterHeight : i32, filterWidth : i32,
channelMul : i32,`,this.workGroupSize=[256,1,1],this.outputShape=e.outShape,this.dispatchLayout=Je(this.outputShape),this.dispatch=ze(this.dispatchLayout,this.outputShape,this.workGroupSize),v.assert(e.dataFormat==="channelsLast",()=>"TODO: NCHW is unimplemented"),t&&this.variableNames.push("bias"),n&&this.variableNames.push("preluActivationWeights"),this.convInfo=e,this.addBias=t,this.activation=r,this.hasPreluActivation=n,this.shaderKey=`depthwise_${this.activation}`}getUserCode(){let e="",t="";if(this.activation){let n=qi(this.activation,!1);this.hasPreluActivation?e=`fn activation(a : f32, outCoord : vec4<i32>) -> f32 {
let b = getPreluActivationWeightsByOutputCoords(outCoord);
${n}
}`:e=`
fn activation(a : f32, outCoord : vec4<i32>) -> f32 {
${n}
}
`,t="dotProd = activation(dotProd, coords);"}let r=this.addBias?"dotProd = dotProd + getBiasByOutputCoords(coords);":"";return`
${e}
fn writeResult(batch : i32, row : i32, col : i32, chan : i32,
value : f32) {
let coord = vec4<i32>(batch, row, col, chan);
if (coordsInBounds4D(coord, uniforms.outShape)) {
setOutputAtCoords(batch, row, col, chan, value);
}
}
${Od()}
let coords = getOutputCoords();
let batch = coords[0];
let xRCCorner = vec2<i32>(coords.yz) * uniforms.stride - uniforms.pad;
let d2 = coords[3];
let d1 = d2 / uniforms.channelMul;
let q = d2 - d1 * uniforms.channelMul;
let inputRowStart = xRCCorner.x;
let inputColStart = xRCCorner.y;
let inputRowEnd = inputRowStart + uniforms.filterHeight *
uniforms.dilation[0];
let inputColEnd = inputColStart + uniforms.filterWidth *
uniforms.dilation[1];
// Convolve x(?, ?, d1) with w(:, :, d1, q) to get y(yR, yC, d2).
// ? = to be determined. : = across all values in that axis.
var dotProd = 0.0;
// Extract if checking out of for loop for performance.
if (inputRowStart >= 0 && inputColStart >= 0 &&
inputRowEnd < uniforms.inDims[0] &&
inputColEnd < uniforms.inDims[1]) {
// Here using a constant value |this.convInfo.filterHeight| instead
// of uniform value is in order to loop unrolling.
for (var wR = 0; wR < uniforms.filterHeight; wR = wR + 1) {
let xR = inputRowStart + wR * uniforms.dilation[0];
for (var wC = 0; wC < uniforms.filterWidth; wC = wC + 1) {
let xC = inputColStart + wC * uniforms.dilation[1];
let xVal = getX(batch, xR, xC, d1);
let wVal = getW(wR, wC, d1, q);
dotProd = dotProd + xVal * wVal;
}
}
} else {
for (var wR = 0; wR < uniforms.filterHeight; wR = wR + 1) {
let xR = inputRowStart + wR * uniforms.dilation[0];
if (xR < 0 || xR >= uniforms.inDims[0]) {
continue;
}
for (var wC = 0; wC < uniforms.filterWidth; wC = wC + 1) {
let xC = inputColStart + wC * uniforms.dilation[1];
if (xC < 0 || xC >= uniforms.inDims[1]) {
continue;
}
let xVal = getX(batch, xR, xC, d1);
let wVal = getW(wR, wC, d1, q);
dotProd = dotProd + xVal * wVal;
}
}
}
${r}
${t}
writeResult(batch, coords[1], coords[2], d2, dotProd);
}
`}};function Oce(e){let{inputs:t,backend:r,attrs:n}=e,{x:a,filter:s}=t,{strides:i,pad:o,dilations:l,dimRoundingMode:u}=n,d=l;d==null&&(d=[1,1]);let h=C.computeConv2DInfo(a.shape,s.shape,i,d,o,u,!0),p=[{type:"int32",data:[h.padInfo.top,h.padInfo.left]},{type:"int32",data:[h.strideHeight,h.strideWidth]},{type:"int32",data:[h.dilationHeight,h.dilationWidth]},{type:"int32",data:[h.inHeight,h.inWidth]}],c;return h.batchSize===1&&h.inHeight===h.outHeight&&h.inWidth===h.outWidth&&h.strideHeight===1&&h.strideWidth===1&&h.filterHeight===h.filterWidth&&h.inChannels===h.outChannels&&h.dilationHeight===1&&h.dilationWidth===1&&h.filterHeight===3&&h.inChannels%4===0?c=new iS(h):(c=new oS(h),p.push({type:"int32",data:[h.filterHeight]},{type:"int32",data:[h.filterWidth]},{type:"int32",data:[h.outChannels/h.inChannels]})),r.runWebGPUProgram(c,[a,s],a.dtype,p)}var zce={kernelName:ii,backendName:"webgpu",kernelFunc:Oce},lS=Xr({opSnippet:0,cpuKernelImpl:fhe,supportsComplex:!0}),Dce={kernelName:Ii,backendName:"webgpu",kernelFunc:lS},Lce=class{constructor(e,t){this.workGroupSize=[64,1,1],this.variableNames=["x"],this.uniforms="reduceSize : i32,",this.size=!0,this.inputShape=[e.batchSize,e.inSize];let[r]=C.computeOutAndReduceShapes(this.inputShape,[1]);this.outputShape=r.length===0?[1]:r,this.dispatchLayout=Je(this.outputShape),this.dispatch=ze(this.dispatchLayout,this.outputShape,[1,1,1]),this.reduceType=t,this.shaderKey=`reduce_${t}`}getUserCode(){let e="",t="0.0";this.reduceType==="min"||this.reduceType==="max"?(e=`
if (isnan(candidate)) {
bestValue = uniforms.NAN;
} else if (!isnan(bestValue) && candidate ${this.reduceType==="min"?"<":">"} bestValue)
{ bestValue = candidate; }`,t="f32(x[offset])"):this.reduceType==="sum"||this.reduceType==="mean"?e=" bestValue = bestValue + candidate; ":this.reduceType==="prod"&&(e=" bestValue = bestValue * candidate; ",t="1.0");let r=this.reduceType==="mean"?"setOutputAtIndex(outputIndex, bestValue / f32(uniforms.reduceSize));":"setOutputAtIndex(outputIndex, bestValue);";return`
fn DIV_CEIL(a : u32, b : u32) -> u32 {
return ((a - 1u) / b + 1u);
}
${`
var<workgroup> xBestValues : array<f32, ${this.workGroupSize[0]}>;
`}
fn getOffset(outputIndex : i32) -> i32 {
let outputCoords = getCoordsFromIndex(outputIndex);
let offset = ${this.outputShape.length===1?"outputCoords":"outputCoords[0]"} * uniforms.reduceSize;
return offset;
}
${rt()}
let outputIndex = index / i32(workGroupSizeX);
let offset = getOffset(outputIndex);
var bestValue = ${t};
let Length = uniforms.reduceSize;
let WorkPerThread = DIV_CEIL(u32(Length), workGroupSizeX);
for (var k = i32(localId.x); k < Length && outputIndex < uniforms.size;
k = k + i32(workGroupSizeX)) {
let candidate = f32(x[offset + k]);
${e}
}
xBestValues[localId.x] = bestValue;
workgroupBarrier();
var reduceSize = min(u32(Length), workGroupSizeX);
for (var currentSize = reduceSize / 2u; reduceSize > 1u;
currentSize = reduceSize / 2u) {
let interval = DIV_CEIL(reduceSize, 2u);
if (localId.x < currentSize) {
let candidate = xBestValues[localId.x + interval];
${e}
xBestValues[localId.x] = bestValue;
}
reduceSize = interval;
workgroupBarrier();
}
if (localId.x == 0u && outputIndex < uniforms.size) {
${r}
}
}
`}};function ec(e,t,r,n,a){let s=e.shape.length,i=[],o=v.parseAxisParam(t,e.shape),l=o,u=C.getAxesPermutation(l,s),d=e;u!=null&&(d=Ya({inputs:{x:e},attrs:{perm:u},backend:a}),l=C.getInnerMostAxes(l.length,s),i.push(d)),C.assertAxesAreInnerMostDims(n,l,s);let[h,p]=C.computeOutAndReduceShapes(d.shape,l),c=h;r&&(c=C.expandShapeToKeepDim(h,o));let m;if((n==="max"||n==="prod")&&a.shouldExecuteOnCPU([d])){let f=a.tensorMap.get(d.dataId).values;switch(n){case"max":let g=phe(f,v.sizeFromShape(p),c,e.dtype);m=a.makeTensorInfo(c,e.dtype,g);break;case"prod":let{outVals:y,outShape:A,outDtype:x}=yhe(d.shape,d.dtype,f,l);m=a.makeTensorInfo(A,x,y);break;default:throw new Error(`${n} CPU implementation is not yet supported.`)}}else{let f=v.sizeFromShape(p),g=v.sizeFromShape(d.shape)/f,y={windowSize:f,inSize:f,batchSize:g,outSize:1},A=n==="mean"?"float32":wh(e.dtype),x=[{type:"int32",data:[f]}],b=new Lce(y,n),w=a.runWebGPUProgram(b,[d],A,x);i.push(w),m=qe({inputs:{x:w},attrs:{shape:c},backend:a})}return i.forEach(f=>a.disposeData(f.dataId)),m}function DA(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{axis:s,keepDims:i}=n;return ec(a,s,i,"sum",r)}var Bce={kernelName:Oi,backendName:"webgpu",kernelFunc:DA};function Wce(e){let{inputs:t,backend:r,attrs:n}=e,{equation:a}=n,s=t,{allDims:i,summedDims:o,idDims:l}=C.decodeEinsumEquation(a,s.length);C.checkEinsumDimSizes(i.length,l,s);let{path:u,steps:d}=C.getEinsumComputePath(o,l),h=d.length,p=null,c=i.length,m=[];for(let f=0;f<h;++f){for(let g of d[f]){let{permutationIndices:y,expandDims:A}=C.getEinsumPermutation(c,l[g]),x;C.isIdentityPermutation(y)?x=s[g]:(x=Ya({inputs:{x:s[g]},backend:r,attrs:{perm:y}}),m.push(x));let b=x.shape.slice();for(let w=0;w<A.length;++w)b.splice(A[w],0,1);v.arraysEqual(x.shape,b)||(x=qe({inputs:{x},backend:r,attrs:{shape:b}}),m.push(x)),p===null?p=x:(p=lS({inputs:{a:x,b:p},backend:r}),m.push(p))}f<h-1&&(u[f]>=0&&(p=DA({inputs:{x:p},backend:r,attrs:{axis:u[f]-(i.length-c),keepDims:!1}}),m.push(p)),c--)}for(let f of m)f!==p&&r.disposeData(f.dataId);return p}var Vce={kernelName:lh,backendName:"webgpu",kernelFunc:Wce},Uce=wr({opType:4}),Gce={kernelName:li,backendName:"webgpu",kernelFunc:Uce},jce=Xr({opSnippet:4,dtype:"bool",cpuKernelImpl:ehe}),Hce={kernelName:Zo,backendName:"webgpu",kernelFunc:jce},uS=wr({opType:5,cpuKernelImpl:the,dtype:"float32"}),qce={kernelName:ui,backendName:"webgpu",kernelFunc:uS};function xy(e){let{inputs:t,attrs:r,backend:n}=e,{dim:a}=r,{input:s}=t,i=s.shape.length,o=s.shape.slice(),l=a;return a<0&&(v.assert(-(i+1)<=a,()=>`Axis must be in the interval [${-(i+1)}, ${i}]`),l=i+a+1),o.splice(l,0,1),qe({inputs:{x:s},backend:n,attrs:{shape:o}})}var Xce={kernelName:Yo,backendName:"webgpu",kernelFunc:xy},Kce=wr({opType:6,cpuKernelImpl:rhe}),Zce={kernelName:Jo,backendName:"webgpu",kernelFunc:Kce},Yce=class{constructor(e){this.variableNames=[],this.outputShape=[],this.uniforms="value : f32,",this.workGroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=Je(this.outputShape),this.dispatch=ze(this.dispatchLayout,this.outputShape,this.workGroupSize),this.shaderKey="fill"}getUserCode(){return`
${rt()}
if (index < uniforms.size) {
setOutputAtIndex(index, uniforms.value);
}
}
`}};function Ld(e){let{backend:t,attrs:r}=e,{shape:n,value:a}=r,{dtype:s}=r;if(s=s||v.inferDtype(a),s==="string"){let i=v.getArrayFromDType(s,v.sizeFromShape(n));return i.fill(a),t.makeTensorInfo(n,s,i)}else{let i=new Yce(n),o=[{type:"float32",data:[a]}];return t.runWebGPUProgram(i,[],s,o)}}var Jce={kernelName:ed,backendName:"webgpu",kernelFunc:Ld},Qce=class{constructor(e){this.outputShape=[],this.variableNames=["x"],this.workGroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=Je(this.outputShape),this.dispatch=ze(this.dispatchLayout,this.outputShape,this.workGroupSize),this.shaderKey="flipLeftRight"}getUserCode(){return`
${rt()}
if (index < uniforms.size) {
let coords = getCoordsFromIndex(index);
let coordX = uniforms.xShape[2] - coords[2] - 1;
let outputValue = getX(coords[0], coords[1], coordX, coords[3]);
setOutputAtIndex(index, outputValue);
}
}
`}},e0e={kernelName:Qo,backendName:"webgpu",kernelFunc:({inputs:e,backend:t})=>{let{image:r}=e,n=t,a=new Qce(r.shape);return n.runWebGPUProgram(a,[r],r.dtype)}},t0e=wr({opType:7,cpuKernelImpl:nhe}),r0e={kernelName:di,backendName:"webgpu",kernelFunc:t0e},n0e=Xr({opSnippet:12,dtype:"int32"}),a0e={kernelName:pi,backendName:"webgpu",kernelFunc:n0e},s0e=class{constructor(e,t=!1){this.outputShape=[0],this.variableNames=[],this.workGroupSize=[256,1,1],this.outputShape=e,this.dispatchLayout=Je(this.outputShape),this.dispatch=ze(this.dispatchLayout,this.outputShape,this.workGroupSize),this.useImport=t,this.shaderKey=`fromPixels_${this.useImport}`}getUserCode(){let e=this.useImport?"textureLoad(src, vec2<i32>(coords.yx));":"textureLoad(src, vec2<i32>(coords.yx), 0)";return`
@binding(1) @group(0) var src: ${this.useImport?"texture_external":"texture_2d<f32>"};
${rt()}
let flatIndexBase = index * uniforms.numChannels;
for (var i = 0; i < uniforms.numChannels; i = i + 1) {
let flatIndex = flatIndexBase + i;
if (flatIndex < uniforms.size) {
let coords = getCoordsFromIndex(flatIndexBase);
let values = ${e};
result[flatIndex] = i32(floor(255.0 * values[i]));
}
}
}
`}},i0e={kernelName:Up,backendName:"webgpu",kernelFunc:o0e},fu;function o0e(e){let{inputs:t,backend:r,attrs:n}=e,{pixels:a}=t,{numChannels:s}=n;if(a==null)throw new Error("pixels passed to tf.browser.fromPixels() can not be null");let i=typeof HTMLVideoElement!="undefined"&&a instanceof HTMLVideoElement,o=typeof HTMLImageElement!="undefined"&&a instanceof HTMLImageElement,l=typeof HTMLCanvasElement!="undefined"&&a instanceof HTMLCanvasElement||typeof OffscreenCanvas!="undefined"&&a instanceof OffscreenCanvas,u=typeof ImageBitmap!="undefined"&&a instanceof ImageBitmap,[d,h]=i?[a.videoWidth,a.videoHeight]:[a.width,a.height],p=[h,d,s];if(Z().getBool("WEBGPU_USE_IMPORT")&&i)return b7({externalImage:a,backend:r,attrs:n,outShape:p,useImport:!0});if((i||o)&&(fu==null&&(fu=document.createElement("canvas").getContext("2d")),fu.canvas.width=d,fu.canvas.height=h,fu.drawImage(a,0,0,d,h),a=fu.canvas),u||l||i||o)return b7({externalImage:a,backend:r,attrs:n,outShape:p,useImport:!1});let c=a.data,m=c;if(s!=null&&s!==4){m=new Uint8Array(a.width*a.height*s);let y=c.length,A=0;for(let x=0;x<y;x++)x%4<s&&(m[A++]=c[x])}let f=r.makeTensorInfo(p,"int32"),g=r.tensorMap.get(f.dataId);return g.values=new Int32Array(m),r.maybeReleaseBuffer(f.dataId),r.uploadToGPU(f.dataId),f}function b7(e){let{externalImage:t,backend:r,attrs:n,outShape:a,useImport:s}=e,{numChannels:i}=n,o=v.sizeFromShape(a),l=v.computeStrides(a),u=new s0e(a,s),d=[{type:"uint32",data:[o]},{type:"uint32",data:[i]},{type:"uint32",data:[...l]},{type:"uint32",data:[...u.dispatch]}];return r.runFromPixelsProgram(u,a,d,s,t)}var l0e=class{constructor(e,t,r,n,a){this.uniforms="varianceEpsilon : f32,",this.workGroupSize=[128,1,1],this.size=!0,this.variableNames=["x","mean","variance"],C.assertAndGetBroadcastShape(e,t),C.assertAndGetBroadcastShape(e,r),this.outputShape=e,this.dispatchLayout=Je(this.outputShape),this.dispatch=ze(this.dispatchLayout,this.outputShape,this.workGroupSize),n!=null&&(C.assertAndGetBroadcastShape(e,n),this.variableNames.push("offset")),a!=null&&(C.assertAndGetBroadcastShape(e,a),this.variableNames.push("scale")),this.offsetShape=n,this.scaleShape=a,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)"),`
${rt()}
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)));
}
}
`}},u0e={kernelName:hi,backendName:"webgpu",kernelFunc:({inputs:e,attrs:t,backend:r})=>{let{x:n,scale:a,offset:s,mean:i,variance:o}=e,{varianceEpsilon:l}=t,u=r,d=[n,i,o],h=null;s!=null&&(h=s.shape,d.push(s));let p=null;a!=null&&(p=a.shape,d.push(a));let c=new l0e(n.shape,i.shape,o.shape,h,p),m=[{type:"float32",data:[l]}];return u.runWebGPUProgram(c,d,n.dtype,m)}};function d0e(e){let{inputs:t,backend:r,attrs:n}=e,{x:a,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:u,dataFormat:d,dilations:h,dimRoundingMode:p,activation:c,leakyreluAlpha:m}=n,f=C.convertConv2DDataFormat(d),g=C.computeConv2DInfo(a.shape,s.shape,l,h,u,p,!1,f);return aS({x:a,filter:s,convInfo:g,backend:r,bias:i,preluActivationWeights:o,leakyreluAlpha:m,activation:c})}var p0e={kernelName:Ps,backendName:"webgpu",kernelFunc:d0e};function h0e(e){let{inputs:t,backend:r,attrs:n}=e,{x:a,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:u,dilations:d,dimRoundingMode:h,activation:p,leakyreluAlpha:c}=n,m=d;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(a.shape,s.shape,l,m,u,h,!0),g=[a,s],y=i!=null,A=o!=null;y&&g.push(i),A&&g.push(o);let x=[{type:"int32",data:[f.padInfo.top,f.padInfo.left]},{type:"int32",data:[f.strideHeight,f.strideWidth]},{type:"int32",data:[f.dilationHeight,f.dilationWidth]},{type:"int32",data:[f.inHeight,f.inWidth]}],b;return f.batchSize===1&&f.inHeight===f.outHeight&&f.inWidth===f.outWidth&&f.strideHeight===1&&f.strideWidth===1&&f.filterHeight===f.filterWidth&&f.inChannels===f.outChannels&&f.dilationHeight===1&&f.dilationWidth===1&&f.filterHeight===3&&f.inChannels%4===0?b=new iS(f,y,p,A):(b=new oS(f,y,p,A),x.push({type:"int32",data:[f.filterHeight]},{type:"int32",data:[f.filterWidth]},{type:"int32",data:[f.outChannels/f.inChannels]})),p==="leakyrelu"&&(x.push({type:"float32",data:[c]}),b.uniforms+=" alpha : f32,"),r.runWebGPUProgram(b,g,"float32",x)}var c0e={kernelName:Os,backendName:"webgpu",kernelFunc:h0e},f0e=class{constructor(e,t){this.variableNames=["A","indices"],this.workGroupSize=[64,1,1],this.size=!0,this.outputShape=t,this.dispatchLayout=Je(this.outputShape),this.dispatch=ze(this.dispatchLayout,this.outputShape,this.workGroupSize),this.shaderKey=`gathernd_${e}`,this.sliceDim=e,this.uniforms=`sliceDim : i32, strides : ${Ar(e)},`}getUserCode(){let e;return this.sliceDim>1?e="uniforms.strides[j]":e="uniforms.strides",`
${rt()}
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 m0e(e){let{inputs:t,backend:r}=e,{params:n,indices:a}=t,s=a.shape,i=s[s.length-1],o=v.sizeFromShape(n.shape),[l,u,d,h]=C.prepareAndValidate(n,a),p=qe({inputs:{x:a},backend:r,attrs:{shape:[u,i]}}),c=qe({inputs:{x:n},backend:r,attrs:{shape:[v.sizeFromShape(n.shape)/d,d]}});if(r.shouldExecuteOnCPU([n,a])||n.dtype==="string"){let A=r.readSync(a.dataId),x=r.bufferSync(n),b=ahe(A,x,n.dtype,u,i,d,h,n.shape,o);return r.makeTensorInfo(l,n.dtype,b.values)}let m=new f0e(i,[u,d]),f=[{type:"int32",data:[i]},{type:"int32",data:h}],g=r.runWebGPUProgram(m,[c,p],c.dtype,f),y=qe({inputs:{x:g},backend:r,attrs:{shape:l}});return r.disposeData(p.dataId),r.disposeData(c.dataId),r.disposeData(g.dataId),y}var g0e={kernelName:tl,backendName:"webgpu",kernelFunc:m0e},y0e=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=Je(this.outputShape),this.dispatch=ze(this.dispatchLayout,this.outputShape,this.workGroupSize),this.shaderKey="gather"}getUserCode(){let e=A0e(this.aShape);return`
${rt()}
if (index < uniforms.size) {
let resRC = getCoordsFromIndex(index);
let indexZ = i32(getIndices(resRC.x, resRC.z));
let inBounds = select(0.0, 1.0, indexZ >= 0 && indexZ < uniforms.aShape[2]);
setOutputAtIndex(index, inBounds * getA(${e}));
}
}
`}};function A0e(e){let t=["resRC.x","resRC.y","resRC.z","resRC.w"],r=[];for(let n=0;n<e.length;n++)n===2?r.push("indexZ"):r.push(`${t[n]}`);return r.join()}function dS(e){let{inputs:t,backend:r,attrs:n}=e,{x:a,indices:s}=t,{axis:i,batchDims:o}=n,l=v.parseAxisParam(i,a.shape)[0],u=C.segment_util.collectGatherOpShapeInfo(a,s,l,o),d=v.sizeFromShape(s.shape),h=[],p=qe({inputs:{x:a},backend:r,attrs:{shape:[u.batchSize,u.outerSize,u.dimSize,u.sliceSize]}}),c=qe({inputs:{x:s},backend:r,attrs:{shape:[u.batchSize,d/u.batchSize]}});h.push(p),h.push(c);let m=[u.batchSize,u.outerSize,d/u.batchSize,u.sliceSize];if(r.shouldExecuteOnCPU([a,s])){let A=r.tensorMap.get(c.dataId).values,x=Le(c.shape,c.dtype,A),b=r.tensorMap.get(p.dataId).values,w=Le(p.shape,p.dtype,b),I=she(w,x,m);return h.forEach(T=>r.disposeData(T.dataId)),r.makeTensorInfo(u.outputShape,I.dtype,I.values)}let f=new y0e(p.shape,m),g=r.runWebGPUProgram(f,[p,c],p.dtype);h.push(g);let y=qe({inputs:{x:g},backend:r,attrs:{shape:u.outputShape}});return h.forEach(A=>r.disposeData(A.dataId)),y}var x0e={kernelName:el,backendName:"webgpu",kernelFunc:dS},b0e=Xr({opSnippet:5,cpuKernelImpl:ohe,dtype:"bool"}),v0e={kernelName:rl,backendName:"webgpu",kernelFunc:b0e},w0e=Xr({opSnippet:6,dtype:"bool",cpuKernelImpl:ihe}),k0e={kernelName:ci,backendName:"webgpu",kernelFunc:w0e};function I0e(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{alpha:s}=n,i=[{type:"float32",data:[s]}],o=new Jh(a.shape,14);return o.uniforms="alpha : f32,",r.runWebGPUProgram(o,[a],"float32",i)}var S0e={kernelName:mi,backendName:"webgpu",kernelFunc:I0e},C0e=Xr({opSnippet:7,dtype:"bool",cpuKernelImpl:uhe}),T0e={kernelName:nl,backendName:"webgpu",kernelFunc:C0e},N0e=Xr({opSnippet:8,dtype:"bool",cpuKernelImpl:lhe}),E0e={kernelName:al,backendName:"webgpu",kernelFunc:N0e},R0e=wr({opType:9,cpuKernelImpl:dhe}),M0e={kernelName:gi,backendName:"webgpu",kernelFunc:R0e},$0e=Xr({opSnippet:9,dtype:"bool"}),F0e={kernelName:sl,backendName:"webgpu",kernelFunc:$0e},_0e=wr({opType:10}),P0e={kernelName:sd,backendName:"webgpu",kernelFunc:_0e};function pS(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{reductionIndices:s,keepDims:i}=n;return ec(a,s,i,"max",r)}var O0e={kernelName:yi,backendName:"webgpu",kernelFunc:pS},z0e=Xr({opSnippet:15,cpuKernelImpl:hhe}),D0e={kernelName:Ai,backendName:"webgpu",kernelFunc:z0e};function L0e(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{filterSize:s,strides:i,pad:o,dimRoundingMode:l}=n,u=1,d=C.computePool2DInfo(a.shape,s,i,u,o,l),h,p=[];if(d.filterHeight===1&&d.filterWidth===1){if(v.arraysEqual(d.inShape,d.outShape))return On({inputs:{x:a},backend:r});h=new tS(d),p.push({type:"int32",data:[d.strideHeight,d.strideWidth]})}else h=new eS(d,"max"),p.push({type:"int32",data:[d.strideHeight,d.strideWidth]},{type:"int32",data:[d.padInfo.top,d.padInfo.left]},{type:"int32",data:[d.dilationHeight,d.dilationWidth]},{type:"int32",data:[d.inHeight,d.inWidth]},{type:"int32",data:[d.effectiveFilterHeight,d.effectiveFilterWidth]});return r.runWebGPUProgram(h,[a],a.dtype,p)}var B0e={kernelName:xi,backendName:"webgpu",kernelFunc:L0e};function W0e(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{keepDims:s,axis:i}=n;return ec(a,i,s,"mean",r)}var V0e={kernelName:bi,backendName:"webgpu",kernelFunc:W0e};function U0e(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{axis:s,keepDims:i}=n;return ec(a,s,i,"min",r)}var G0e={kernelName:vi,backendName:"webgpu",kernelFunc:U0e},j0e=Xr({opSnippet:16,cpuKernelImpl:che}),H0e={kernelName:wi,backendName:"webgpu",kernelFunc:j0e},q0e=class{constructor(e,t,r){this.uniforms="",this.variableNames=["x"],this.workGroupSize=[64,1,1],this.size=!0,this.outputShape=t.map((n,a)=>n[0]+e[a]+n[1]),this.dispatchLayout=Je(this.outputShape),this.dispatch=ze(this.dispatchLayout,this.outputShape,this.workGroupSize),this.xShape=e,t.map((n,a)=>{this.uniforms+=` pad${a} : vec2<i32>,`}),this.offset=r==="reflect"?0:1,this.shaderKey=`mirrorPad_${r}`}getUserCode(){let e=this.xShape.length,t=this.xShape.map((l,u)=>`uniforms.pad${u}[0]`).join(","),r=this.xShape.map((l,u)=>`uniforms.pad${u}[0] + uniforms.xShape${e>1?`[${u}]`:""}`).join(","),n=e===1?"start":"start[i]",a=e===1?"end":"end[i]",s=e===1?"outC":"outC[i]",i=Ar(e),o=e>1?["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,e):"coords";return`
${rt()}
if (index < uniforms.size) {
let start = ${i}(${t});
let end = ${i}(${r});
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} >= ${a}) {
${s} = (${a} - 1) * 2 - ${s} + ${this.offset};
}
}
let coords = outC - start;
setOutputAtIndex(index, getX(${o}));
}
}
`}},X0e={kernelName:ki,backendName:"webgpu",kernelFunc:({inputs:e,attrs:t,backend:r})=>{let{x:n}=e,{paddings:a,mode:s}=t,i=r,o=a.map(u=>({type:"int32",data:[u[0],u[1]]})),l=new q0e(n.shape,a,s);return i.runWebGPUProgram(l,[n],n.dtype,o)}};function K0e(e){let{inputs:t,backend:r}=e,{x:n}=t;if(r.shouldExecuteOnCPU([n])){let s=r.tensorMap.get(n.dataId),[i,o]=mhe(s.values,n.shape,n.dtype);return r.makeTensorInfo(o,n.dtype,i)}let a=new Jh(n.shape,11);return r.runWebGPUProgram(a,[n],n.dtype)}var Z0e={kernelName:il,backendName:"webgpu",kernelFunc:K0e};function Y0e(e){console.warn("tf.nonMaxSuppression() in webgpu locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:r,attrs:n}=e,{boxes:a,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l}=n,u=r.readSync(a.dataId),d=r.readSync(s.dataId),{selectedIndices:h}=Kn.nonMaxSuppressionV3Impl(u,d,i,o,l);return r.makeTensorInfo([h.length],"int32",new Int32Array(h))}var J0e={kernelName:ll,backendName:"webgpu",kernelFunc:Y0e};function Q0e(e){console.warn("tf.nonMaxSuppression() in webgpu locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:r,attrs:n}=e,{boxes:a,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l,softNmsSigma:u}=n,d=r.readSync(a.dataId),h=r.readSync(s.dataId),p=i,c=o,m=l,f=u,{selectedIndices:g,selectedScores:y}=Kn.nonMaxSuppressionV5Impl(d,h,p,c,m,f);return[r.makeTensorInfo([g.length],"int32",new Int32Array(g)),r.makeTensorInfo([y.length],"float32",new Float32Array(y))]}var efe={kernelName:ul,backendName:"webgpu",kernelFunc:Q0e};function tf(e){let{inputs:t,backend:r}=e,{x:n}=t;if(n.dtype==="complex64"){let a=Qh({inputs:{input:n},backend:r}),s=tf({inputs:{x:a},backend:r}),i=Lm({inputs:{input:n},backend:r}),o=tf({inputs:{x:i},backend:r}),l=zd({inputs:{real:s,imag:o},backend:r});return r.disposeData(a.dataId),r.disposeData(s.dataId),r.disposeData(i.dataId),r.disposeData(o.dataId),l}else return Ld({attrs:{shape:n.shape,dtype:n.dtype,value:n.dtype==="string"?"":0},backend:r})}var tfe={kernelName:Tl,backendName:"webgpu",kernelFunc:tf};function hS(e){let{inputs:t,backend:r}=e,{x:n}=t;if(n.dtype==="string")throw new Error("onesLike is not supported under string dtype");if(n.dtype==="complex64"){let a=Qh({inputs:{input:n},backend:r}),s=hS({inputs:{x:a},backend:r}),i=Lm({inputs:{input:n},backend:r}),o=tf({inputs:{x:i},backend:r}),l=zd({inputs:{real:s,imag:o},backend:r});return r.disposeData(a.dataId),r.disposeData(s.dataId),r.disposeData(i.dataId),r.disposeData(o.dataId),l}else return Ld({attrs:{shape:n.shape,dtype:n.dtype,value:1},backend:r})}var rfe={kernelName:dl,backendName:"webgpu",kernelFunc:hS};function nfe(e){let{inputs:t,backend:r,attrs:n}=e,{axis:a}=n;if(t.length===1)return xy({inputs:{input:t[0]},backend:r,attrs:{dim:a}});let s=t[0].shape,i=t[0].dtype;t.forEach(d=>{v.assertShapesMatch(s,d.shape,"All tensors passed to stack must have matching shapes"),v.assert(i===d.dtype,()=>"All tensors passed to stack must have matching dtypes")});let o=[],l=t.map(d=>{let h=xy({inputs:{input:d},backend:r,attrs:{dim:a}});return o.push(h),h}),u=nS({inputs:l,backend:r,attrs:{axis:a}});return o.forEach(d=>r.disposeData(d.dataId)),u}var afe={kernelName:hl,backendName:"webgpu",kernelFunc:nfe},sfe=class{constructor(e,t){this.variableNames=["x"],this.uniforms="constantValue : f32,",this.workGroupSize=[64,1,1],this.size=!0,this.outputShape=t.map((r,n)=>r[0]+e[n]+r[1]),this.dispatchLayout=Je(this.outputShape),this.dispatch=ze(this.dispatchLayout,this.outputShape,this.workGroupSize),t.map((r,n)=>{this.uniforms+=` pad${n} : vec2<i32>,`}),this.xShape=e,this.shaderKey="pad"}getUserCode(){let e=this.xShape.length,t=Ar(e),r=this.xShape.map((u,d)=>`uniforms.pad${d}[0]`).join(","),n=this.xShape.map((u,d)=>`uniforms.pad${d}[0] + uniforms.xShape${e>1?`[${d}]`:""}`).join(","),a=e>1?`${t}(${r})`:`${r}`,s=e>1?`${t}(${n})`:`${n}`,i=e>1?"any(outC < start)":"outC < start",o=e>1?"any(outC >= end)":"outC >= end",l=e>1?["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,e):"coords";return`
${rt()}
if (index < uniforms.size) {
let start = ${a};
let end = ${s};
let outC = getCoordsFromIndex(index);
if (${i} || ${o}) {
setOutputAtIndex(index, uniforms.constantValue);
} else {
let coords = outC - start;
setOutputAtIndex(index, getX(${l}));
}
}
}
`}},cS=e=>{let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{paddings:s,constantValue:i}=n;if(s.every(u=>v.arraysEqual(u,[0,0])))return On({inputs:{x:a},backend:r});if(v.sizeFromShape(a.shape)===0){let u=s.map((d,h)=>d[0]+a.shape[h]+d[1]);return Ld({backend:r,attrs:{shape:u,value:i,dtype:a.dtype}})}let o=[{type:"float32",data:[i]}];s.map(u=>o.push({type:"int32",data:[u[0],u[1]]}));let l=new sfe(a.shape,s);return r.runWebGPUProgram(l,[a],a.dtype,o)},ife={kernelName:Si,backendName:"webgpu",kernelFunc:cS},ofe=Xr({opSnippet:13}),lfe={kernelName:Ci,backendName:"webgpu",kernelFunc:ofe};function ufe(e){let{inputs:t,backend:r}=e,{x:n,alpha:a}=t,s=new JI(14,n.shape,a.shape);return r.runWebGPUProgram(s,[n,a],"float32")}var dfe={kernelName:Ti,backendName:"webgpu",kernelFunc:ufe};function pfe(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{axis:s,keepDims:i}=n;return ec(a,s,i,"prod",r)}var hfe={kernelName:Ni,backendName:"webgpu",kernelFunc:pfe},cfe=e=>{let{backend:t,attrs:r}=e,{start:n,stop:a,step:s,dtype:i}=r,o=Ahe(n,a,s,i);return t.makeTensorInfo([o.length],i,o)},ffe={kernelName:ld,backendName:"webgpu",kernelFunc:cfe},fS=Xr({opSnippet:3}),mfe={kernelName:oi,backendName:"webgpu",kernelFunc:fS},gfe=wr({opType:12}),yfe={kernelName:Ei,backendName:"webgpu",kernelFunc:gfe},Afe=wr({opType:13}),xfe={kernelName:Mi,backendName:"webgpu",kernelFunc:Afe},bfe=class{constructor(e,t,r){this.variableNames=["x"],this.uniforms="adjustHeightWidth : vec2<f32>, halfPixelCenters : f32,",this.workGroupSize=[64,1,1],this.size=!0,this.outputShape=[e[0],t,r,e[3]],this.dispatchLayout=Je(this.outputShape),this.dispatch=ze(this.dispatchLayout,this.outputShape,this.workGroupSize),this.shaderKey="resizeBilinear"}getUserCode(){return`
${rt()}
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 vfe(e){let{inputs:t,backend:r,attrs:n}=e,{images:a}=t,{alignCorners:s,size:i,halfPixelCenters:o}=n,[l,u]=i,d=s&&l>1?1:0,h=s&&u>1?1:0,p=[{type:"float32",data:[d,h]},{type:"float32",data:[o?.5:0]}],c=new bfe(a.shape,l,u);return r.runWebGPUProgram(c,[a],"float32",p)}var wfe={kernelName:Ri,backendName:"webgpu",kernelFunc:vfe},kfe=class{constructor(e,t,r,n){this.variableNames=["x"],this.uniforms="adjustHeightWidth : vec2<f32>, roundBase : f32,",this.workGroupSize=[64,1,1],this.size=!0,this.outputShape=[e[0],t,r,e[3]],this.dispatchLayout=Je(this.outputShape),this.dispatch=ze(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",`
${rt()}
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 Ife(e){let{inputs:t,backend:r,attrs:n}=e,{images:a}=t,{alignCorners:s,halfPixelCenters:i,size:o}=n,[l,u]=o,d=s&&l>1?1:0,h=s&&u>1?1:0,p=[{type:"float32",data:[d,h]},{type:"float32",data:[s?.5:0]}],c=new kfe(a.shape,l,u,i);return r.runWebGPUProgram(c,[a],a.dtype,p)}var Sfe={kernelName:dd,backendName:"webgpu",kernelFunc:Ife},Cfe=class{constructor(e,t){this.outputShape=[],this.variableNames=["x"],this.workGroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=Je(this.outputShape),this.dispatch=ze(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`
${rt()}
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));
${this.fillSnippet}
if(coordX >= 0 && coordX < uniforms.xShape[2] && coordY >= 0 &&
coordY < uniforms.xShape[1]) {
outputValue = getX(coords[0], coordY, coordX, coords[3]);
}
setOutputAtIndex(index, outputValue);
}
}
`}},Tfe={kernelName:Nl,backendName:"webgpu",kernelFunc:({inputs:e,attrs:t,backend:r})=>{let{image:n}=e,{radians:a,fillValue:s,center:i}=t,o=r,l=new Cfe(n.shape,s),[u,d]=C.getImageCenter(i,n.shape[1],n.shape[2]),h=[{type:"float32",data:[u]},{type:"float32",data:[d]},{type:"float32",data:[Math.sin(a)]},{type:"float32",data:[Math.cos(a)]}];return typeof s=="number"?h.push({type:"float32",data:[Number.parseFloat(s.toFixed(2))]}):h.push({type:"float32",data:s}),o.runWebGPUProgram(l,[n],n.dtype,h)}},Nfe=wr({opType:15,cpuKernelImpl:xhe}),Efe={kernelName:$i,backendName:"webgpu",kernelFunc:Nfe},Rfe=class{constructor(e,t,r,n,a,s,i){this.variableNames=["updates","indices"],this.workGroupSize=[64,1,1],this.atomic=!0,this.outputShape=s,this.type=i,this.dispatchLayout=Je(e),this.dispatch=ze(this.dispatchLayout,e,this.workGroupSize),this.sliceDimGreaterThanOne=t>1,this.shaderKey=`scatter_${r}_${n}_${this.sliceDimGreaterThanOne}_${i}`;let o=Ar(a.length);this.uniforms=`sliceDim : i32, strides: ${o}, size: i32,`,this.updatesRank=n,this.indicesRank=r}getUserCode(){let e="";this.indicesRank===1?e="coords[0]":this.indicesRank===2&&(e="coords[0], j");let t=`getIndices(${e})`,r=this.sliceDimGreaterThanOne?"uniforms.strides[j]":"uniforms.strides",n="",a="",s="";this.updatesRank===1?(n="coords[0]",a="flattenedIndex",s=`
fn getUpdatesCoordsFromFlatIndex(index : i32) -> i32 {
return index;
}
`):this.updatesRank===2&&(n="coords[0], coords[1]",a="vec2<i32>(flattenedIndex, coords[1])",s=`
fn getUpdatesCoordsFromFlatIndex(index : i32) -> vec2<i32> {
let d0 = index / uniforms.updatesShape[1];
let d1 = index - d0 * uniforms.updatesShape[1];
return vec2<i32>(d0, d1);
}
`);let i=`getUpdates(${n})`,o=this.type==="int32"?"atomicAdd(&(result[flatIndex]), i32(updateValue));":`
var assumed = atomicLoad(&(result[flatIndex]));
var success = 0;
for (; success == 0;) {
let new = bitcast<f32>(assumed) + updateValue;
let newI32 = bitcast<i32>(new);
let resValue = atomicCompareExchangeWeak(&(result[flatIndex]), assumed, newI32);
assumed = resValue[0];
success = resValue[1];
}
`;return`
${s}
${rt()}
if (index < uniforms.size) {
let coords = getUpdatesCoordsFromFlatIndex(index);
var flattenedIndex = 0;
for (var j = 0; j < uniforms.sliceDim; j = j + 1) {
let indexInside = i32(round(${t}));
flattenedIndex = flattenedIndex + indexInside * ${r};
}
let updateValue = ${i};
let flatIndex = getOutputIndexFromCoords(${a});
${o}
}
}`}};function Mfe(e){let{inputs:t,backend:r,attrs:n}=e,{indices:a,updates:s}=t,{shape:i}=n,{sliceRank:o,numUpdates:l,sliceSize:u,strides:d,outputSize:h}=C.calculateShapes(s,a,i),p=[h/u,u];if(h===0)return r.makeTensorInfo(i,a.dtype);let c=qe({inputs:{x:a},backend:r,attrs:{shape:[l,o]}}),m=qe({inputs:{x:s},backend:r,attrs:{shape:[l,u]}}),f=m.dtype,g=Ld({backend:r,attrs:{shape:p,value:0,dtype:f}}),y=v.sizeFromShape(m.shape),A=[{type:"int32",data:[o]},{type:"int32",data:d},{type:"int32",data:[y]}],x=new Rfe(m.shape,o,c.shape.length,m.shape.length,d,p,f),b=r.runWebGPUProgram(x,[m,c],f,A,g),w=qe({inputs:{x:b},backend:r,attrs:{shape:i}});return r.disposeData(c.dataId),r.disposeData(m.dataId),r.disposeData(b.dataId),w}var $fe={kernelName:gl,backendName:"webgpu",kernelFunc:Mfe},Ffe=class{constructor(e,t,r){this.variableNames=["c","a","b"],this.workGroupSize=[64,1,1],this.size=!0,this.outputShape=t,this.dispatchLayout=Je(this.outputShape),this.dispatch=ze(this.dispatchLayout,this.outputShape,this.workGroupSize),this.cRank=e,this.rank=r,this.shaderKey="select"}getUserCode(){let e,t;if(this.rank>4)throw Error(`Where for rank ${this.rank} is not yet supported`);if(this.rank===1)t="resRC",e="resRC";else{let r=["resRC.x","resRC.y","resRC.z","resRC.w"],n=[],a=[];for(let s=0;s<this.outputShape.length;s++)a.push(`${r[s]}`),s<this.cRank&&n.push(`${r[s]}`);e=n.join(),t=a.join()}return`
${rt()}
if (index < uniforms.size) {
let resRC = getCoordsFromIndex(index);
let cVal = getC(${e});
if (cVal >= 1.0) {
setOutputAtIndex(index, getA(${t}));
} else {
setOutputAtIndex(index, getB(${t}));
}
}
}
`}};function _fe(e){let{inputs:t,backend:r}=e,{condition:n,t:a,e:s}=t,i=new Ffe(n.shape.length,a.shape,a.shape.length);return r.runWebGPUProgram(i,[n,a,s],Tr(a.dtype,s.dtype))}var Pfe={kernelName:yl,backendName:"webgpu",kernelFunc:_fe},Ofe=wr({opType:18}),zfe={kernelName:_i,backendName:"webgpu",kernelFunc:Ofe},Dfe=wr({opType:16}),Lfe={kernelName:Fi,backendName:"webgpu",kernelFunc:Dfe},Bfe=wr({opType:17}),Wfe={kernelName:xl,backendName:"webgpu",kernelFunc:Bfe},mS=Xr({opSnippet:2,cpuKernelImpl:She,supportsComplex:!0}),Vfe={kernelName:Li,backendName:"webgpu",kernelFunc:mS};function Ufe(e){let{inputs:t,backend:r,attrs:n}=e,{logits:a}=t,{dim:s}=n,i=v.parseAxisParam([s],a.shape),o=pS({inputs:{x:a},backend:r,attrs:{reductionIndices:i,keepDims:!1}}),l=C.expandShapeToKeepDim(o.shape,i),u=qe({inputs:{x:o},backend:r,attrs:{shape:l}}),d=mS({inputs:{a,b:u},backend:r}),h=uS({inputs:{x:d},backend:r}),p=DA({inputs:{x:h},backend:r,attrs:{axis:i,keepDims:!1}}),c=qe({inputs:{x:p},backend:r,attrs:{shape:l}}),m=fS({inputs:{a:h,b:c},backend:r});return r.disposeData(o.dataId),r.disposeData(u.dataId),r.disposeData(d.dataId),r.disposeData(h.dataId),r.disposeData(p.dataId),r.disposeData(c.dataId),m}var Gfe={kernelName:zi,backendName:"webgpu",kernelFunc:Ufe},jfe=e=>{let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{blockShape:s,paddings:i}=n;v.assert(a.shape.length<=4,()=>"spaceToBatchND for rank > 4 with a WebGPU backend not implemented yet");let o=s.reduce((y,A)=>y*A),l=[[0,0]];l.push(...i);for(let y=1+s.length;y<a.shape.length;++y)l.push([0,0]);let u=[],d=cS({inputs:{x:a},backend:r,attrs:{paddings:l,constantValue:0}}),h=C.getReshaped(d.shape,s,o,!1),p=C.getPermuted(h.length,s.length,!1),c=C.getReshapedPermuted(d.shape,s,o,!1),m=qe({inputs:{x:d},backend:r,attrs:{shape:h}}),f=Ya({inputs:{x:m},backend:r,attrs:{perm:p}}),g=qe({inputs:{x:f},backend:r,attrs:{shape:c}});return u.push(d),u.push(m),u.push(f),u.forEach(y=>r.disposeData(y.dataId)),g},Hfe={kernelName:bl,backendName:"webgpu",kernelFunc:jfe},qfe=class{constructor(e,t,r,n,a,s,i=!0){this.variableNames=["updates","indices","defaultValue"],this.workGroupSize=[64,1,1],this.workPerThread=4,this.size=!0,this.outputShape=s,this.dispatchLayout=Je(this.outputShape),this.dispatch=ze(this.dispatchLayout,this.outputShape,this.workGroupSize,[this.workPerThread,1,1]);let o=t>1;this.shaderKey=`scatter_${r}_${n}_${o}`;let l=Ar(a.length);this.uniforms=`updateSize : i32, sliceDim : i32, strides: ${l},`;let u="";r===1?u="i":r===2&&(u="i, j"),this.indicesSnippet=`getIndices(${u})`;let d="";n===1?d="i":n===2&&(d="i, coords[1]"),this.updatesSnippet=`getUpdates(${d})`,this.strideString=o?"uniforms.strides[j]":"uniforms.strides"}getUserCode(){return`
${rt()}
let globalIndex = index * ${this.workPerThread};
if (globalIndex < uniforms.size) {
var sum = vec4<f32>(0.0);
var found = vec4<bool>(false);
for (var i = 0; i < uniforms.updateSize; i = i + 1) {
var flattenedIndex = 0;
for (var j = 0; j < uniforms.sliceDim; j = j + 1) {
let indexInside = i32(round(${this.indicesSnippet}));
flattenedIndex = flattenedIndex + indexInside * ${this.strideString};
}
for (var innerIndex = 0; innerIndex < ${this.workPerThread}; innerIndex = innerIndex + 1) {
let curIndex = globalIndex + innerIndex;
let coords = getCoordsFromIndex(curIndex);
if (flattenedIndex == coords[0]) {
sum[innerIndex] = sum[innerIndex] + ${this.updatesSnippet};
found[innerIndex] = true;
}
}
}
for (var innerIndex = 0; innerIndex < ${this.workPerThread}; innerIndex = innerIndex + 1) {
let curIndex = globalIndex + innerIndex;
if (curIndex < uniforms.size)
{
setOutputAtIndex(curIndex, mix(getDefaultValue(), sum[innerIndex], f32(found[innerIndex])));
}
}
}
}`}};function Xfe(e){let{inputs:t,backend:r,attrs:n}=e,{sparseIndices:a,sparseValues:s,defaultValue:i}=t,{outputShape:o}=n,{sliceRank:l,numUpdates:u,sliceSize:d,strides:h,outputSize:p}=C.calculateShapes(s,a,o),c=!1;if(s.dtype==="string"){let A=r.bufferSync(a),x=r.bufferSync(s),b=v.decodeString(r.readSync(i.dataId)[0]),w=bhe(A,x,o,p,d,u,l,h,b,c);return r.makeTensorInfo(o,w.dtype,w.values)}let m=[{type:"int32",data:[u]},{type:"int32",data:[l]},{type:"int32",data:h}],f=new qfe(u,l,a.shape.length,s.shape.length,h,[p,1],c),g=r.runWebGPUProgram(f,[s,a,i],s.dtype,m),y=qe({inputs:{x:g},backend:r,attrs:{shape:o}});return r.disposeData(g.dataId),y}var Kfe={kernelName:yh,backendName:"webgpu",kernelFunc:Xfe};function Zfe(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{numOrSizeSplits:s,axis:i}=n,o=v.parseAxisParam(i,a.shape)[0],l=C.prepareSplitSize(a,s,o),u=a.shape.length,d=new Array(u).fill(0),h=a.shape.slice();return l.map(p=>{let c=[...h];c[o]=p;let m=Dd({inputs:{x:a},backend:r,attrs:{begin:d,size:c}});return d[o]+=p,m})}var Yfe={kernelName:vl,backendName:"webgpu",kernelFunc:Zfe},Jfe=wr({opType:19}),Qfe={kernelName:Pi,backendName:"webgpu",kernelFunc:Jfe},eme={kernelName:md,backendName:"webgpu",kernelFunc:({inputs:e,backend:t})=>{let{x:r}=e,n=t,a=new Jh(r.shape,20);return n.runWebGPUProgram(a,[r],r.dtype)}},tme=Xr({opSnippet:11}),rme={kernelName:Di,backendName:"webgpu",kernelFunc:tme},nme=class{constructor(e){this.variableNames=["x"],this.workPerThread=1,this.workGroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=Je(this.outputShape),this.dispatch=ze(this.dispatchLayout,this.outputShape,this.workGroupSize,[this.workPerThread,1,1]);let t=Ar(this.outputShape.length);this.uniforms=`begin : ${t}, strides : ${t}, `,this.shaderKey="stridedSlice"}getUserCode(){let e=this.outputShape.length,t="";if(e===1)t="coords * uniforms.strides + uniforms.begin";else{let r=0;t=this.outputShape.map((n,a)=>(r++,this.outputShape.length===1?`coords * uniforms.strides[${a}] + uniforms.begin[${a}]`:`coords[${r-1}] * uniforms.strides[${a}] + uniforms.begin[${a}]`)).join(",")}return`
${rt()}
if (index < uniforms.size) {
let coords = getCoordsFromIndex(index);
setOutputAtIndex(index, getX(${t}));
}
}
`}};function ame(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{begin:s,end:i,strides:o,beginMask:l,endMask:u,ellipsisMask:d,newAxisMask:h,shrinkAxisMask:p}=n,{finalShapeSparse:c,finalShape:m,isIdentity:f,sliceDim0:g,isSimpleSlice:y,begin:A,end:x,strides:b}=Dt.sliceInfo(a.shape,s,i,o,l,u,d,h,p),w;if(f)w=qe({inputs:{x:a},backend:r,attrs:{shape:m}});else if(g||y){v.assert(a.shape.length>=1,()=>`Input must have rank at least 1, got: ${a.shape.length}`);let I=Dt.computeOutShape(A,x,b),T=Dd({inputs:{x:a},backend:r,attrs:{begin:A,size:I}});w=qe({inputs:{x:T},backend:r,attrs:{shape:m}}),r.disposeData(T.dataId)}else if(r.shouldExecuteOnCPU([a])){let I=r.readSync(a.dataId),T=Le(a.shape,a.dtype,I),E=khe(c,T,b,A);w=r.makeTensorInfo(m,a.dtype,E.values)}else{let I=new nme(c),T=[{type:"int32",data:A},{type:"int32",data:b}],E=r.runWebGPUProgram(I,[a],a.dtype,T);w=qe({inputs:{x:E},backend:r,attrs:{shape:m}}),r.disposeData(E.dataId)}return w}var sme={kernelName:wl,backendName:"webgpu",kernelFunc:ame};function ime(e){let{inputs:t,backend:r,attrs:n}=e,{separator:a,nGramWidths:s,leftPad:i,rightPad:o,padWidth:l,preserveShortSequences:u}=n,{data:d,dataSplits:h}=t,p=r.readSync(d.dataId),c=r.readSync(h.dataId),[m,f]=Ihe(p,c,a,s,i,o,l,u);return[r.makeTensorInfo([m.length],"string",m),r.makeTensorInfo(h.shape,"int32",f)]}var ome={kernelName:Ah,backendName:"webgpu",kernelFunc:ime},lme=wr({opType:21}),ume={kernelName:Bi,backendName:"webgpu",kernelFunc:lme},dme=class{constructor(e,t){this.variableNames=["A"],this.workGroupSize=[64,1,1],this.size=!0;let r=new Array(e.length);for(let n=0;n<r.length;n++)r[n]=e[n]*t[n];this.outputShape=r,this.dispatchLayout=Je(this.outputShape),this.dispatch=ze(this.dispatchLayout,this.outputShape,this.workGroupSize),this.rank=this.outputShape.length,this.shaderKey="tile"}getUserCode(){let e=pme(this.rank,"uniforms.");return`
${rt()}
if (index < uniforms.size) {
let resRC = getCoordsFromIndex(index);
setOutputAtIndex(index, getA(${e}));
}
}
`}};function pme(e,t=""){if(e>=5)throw Error(`Tile for rank ${e} is not yet supported`);if(e===1)return`(resRC % ${t}aShape)`;let r=["resRC.x","resRC.y","resRC.z","resRC.w"],n=[];for(let a=0;a<e;a++)n.push(`(${r[a]} % ${t}aShape[${a}])`);return n.join()}function hme(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{reps:s}=n;if(r.shouldExecuteOnCPU([a])||a.dtype==="string"||a.shape.length>=5){let o=r.readSync(a.dataId),l=a.dtype==="string"?o.map(h=>v.decodeString(h)):o,u=Le(a.shape,a.dtype,l),d=Che(u,s);return r.makeTensorInfo(d.shape,d.dtype,d.values)}let i=new dme(a.shape,s);return r.runWebGPUProgram(i,[a],a.dtype)}var cme={kernelName:es,backendName:"webgpu",kernelFunc:hme},fme=class{constructor(e){this.variableNames=["x","indices"],this.workGroupSize=[256,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=Je(this.outputShape),this.dispatch=ze(this.dispatchLayout,this.outputShape,this.workGroupSize),this.uniforms=`inputSize : i32, firstPass : i32, negativeInf : f32,
dir : i32, inc : i32,`,this.shaderKey="swap"}getUserCode(){return`
${rt()}
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));
}
}
}
`}},mme=class{constructor(e){this.variableNames=["x","indices"],this.workGroupSize=[256,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=Je(this.outputShape),this.dispatch=ze(this.dispatchLayout,this.outputShape,this.workGroupSize),this.uniforms="inputSize : i32, firstPass : i32, k : i32,",this.shaderKey="merge"}getUserCode(){return`
${rt()}
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 mu(e,t){t!==null&&e.disposeData(t.dataId)}function v7(e){let t=1;for(;t<e;)t*=2;return t}function gme(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{k:s,sorted:i}=n,o=a.shape,l=o[o.length-1];if(r.shouldExecuteOnCPU([a])){let b=r.readSync(a.dataId),[w,I]=The(b,o,a.dtype,s,i);return[r.makeTensorInfo(w.shape,w.dtype,w.values),r.makeTensorInfo(I.shape,I.dtype,I.values)]}if(s===0)return o[o.length-1]=0,[r.makeTensorInfo(o,a.dtype,[]),r.makeTensorInfo(o,"int32",[])];if(l===1)return[a,Ld({attrs:{shape:o,dtype:"int32",value:0},backend:r})];let u=v.sizeFromShape(o)/l,d=qe({inputs:{x:a},attrs:{shape:[u,l]},backend:r}),h=v7(s),p=v7(l),c=null,m=()=>c===null?[d,d]:[d,c],f=(b,w,I)=>{let T=m(),E=new fme(I),R=[{type:"int32",data:[l]},{type:"int32",data:[c===null?1:0]},{type:"float32",data:[Number.NEGATIVE_INFINITY]},{type:"int32",data:[b]},{type:"int32",data:[w]}],O=c;c=r.runWebGPUProgram(E,T,"int32",R),mu(r,O)};for(let b=1;b<h;b*=2){let w=b*2;for(let I=b;I>=1;I/=2)f(w,I,[u,p])}for(let b=p;b>h;b/=2){let w=m(),I=new mme([u,b/2]),T=[{type:"int32",data:[l]},{type:"int32",data:[c===null?1:0]},{type:"int32",data:[h]}],E=c;c=r.runWebGPUProgram(I,w,"int32",T),mu(r,E);let R=h/2,O=R*2;for(let M=R;M>=1;M/=2)f(O,M,c.shape)}let g=c;c=Dd({inputs:{x:c},backend:r,attrs:{begin:0,size:[u,s]}}),mu(r,g);let y=dS({inputs:{x:d,indices:c},backend:r,attrs:{axis:1,batchDims:1}});mu(r,d);let A=o.slice(0,-1);A.push(s),g=c,c=qe({inputs:{x:c},attrs:{shape:A},backend:r}),mu(r,g);let x=y;return y=qe({inputs:{x:y},attrs:{shape:A},backend:r}),mu(r,x),[y,c]}var yme={kernelName:Il,backendName:"webgpu",kernelFunc:gme},Ame=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=Je(this.outputShape),this.dispatch=ze(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;
}
${rt()}
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 xme(e){let{inputs:t,backend:r,attrs:n}=e,{image:a,transforms:s}=t,{interpolation:i,fillMode:o,fillValue:l,outputShape:u}=n,[d,h,p,c]=a.shape,[m,f]=u!=null?u:[h,p],g=[d,m,f,c],y=new Ame(g),A=i==="nearest"?1:2,x;switch(o){case"constant":x=1;break;case"reflect":x=2;break;case"wrap":x=3;break;case"nearest":x=4;break;default:x=1;break}let b=[{type:"int32",data:[A]},{type:"int32",data:[x]},{type:"float32",data:[l]}];return r.runWebGPUProgram(y,[a,s],"float32",b)}var bme={kernelName:Sl,backendName:"webgpu",kernelFunc:xme};function vme(e){let{inputs:t,backend:r,attrs:n}=e,{value:a}=t,{axis:s}=n;s<0&&(s+=a.shape.length);let i=a,o=i.shape.length,l=a.shape[s],u=new Array(o-1),d=0;for(let f=0;f<o;f++)f!==s&&(u[d++]=i.shape[f]);let h=[],p=new Array(o).fill(0),c=i.shape.slice();c[s]=1;let m=new Array(l);for(let f=0;f<m.length;f++){p[s]=f;let g=Dd({inputs:{x:i},backend:r,attrs:{begin:p,size:c}}),y=qe({inputs:{x:g},backend:r,attrs:{shape:u}});m[f]=y,h.push(g)}return h.forEach(f=>r.disposeData(f.dataId)),m}var wme={kernelName:Cl,backendName:"webgpu",kernelFunc:vme},kme=[Hpe,Rhe,$he,Phe,Whe,Uhe,jhe,qhe,Jhe,rce,ace,lce,Zpe,hce,yce,vce,kce,Sce,Nce,Rce,$ce,Pce,zce,Vce,Gce,Hce,qce,Xce,Zce,Jce,e0e,i0e,r0e,a0e,u0e,p0e,c0e,g0e,x0e,v0e,k0e,Kpe,dce,S0e,T0e,E0e,M0e,F0e,P0e,O0e,D0e,B0e,V0e,G0e,H0e,X0e,Dce,Z0e,J0e,efe,Qhe,rfe,afe,ife,lfe,dfe,hfe,ffe,ece,mfe,yfe,xfe,Gpe,wfe,Sfe,Tfe,Efe,$fe,Pfe,zfe,Lfe,Wfe,Zhe,sme,ome,Gfe,Hfe,Kfe,Yfe,Qfe,eme,rme,Vfe,Bce,ume,cme,yme,bme,Lhe,wme,tfe];for(let e of kme)qn(e);var Ime=class{constructor(e){this.device=e,this.numUsedBuffers=0,this.numFreeBuffers=0,this.freeBuffers=new Map,this.usedBuffers=new Map,this.numBytesUsed=0,this.numBytesAllocated=0}acquireUploadBuffer(e,t){return this.acquireBuffer(e,t,!0)}acquireBuffer(e,t,r=!1){let n=w7(e,t);if(this.freeBuffers.has(n)||this.freeBuffers.set(n,[]),this.usedBuffers.has(n)||this.usedBuffers.set(n,[]),this.numBytesUsed+=e,this.numUsedBuffers++,this.freeBuffers.get(n).length>0){this.numFreeBuffers--;let s=this.freeBuffers.get(n).shift();return this.usedBuffers.get(n).push(s),s}this.numBytesAllocated+=e;let a=this.device.createBuffer({mappedAtCreation:r,size:e,usage:t});return this.usedBuffers.get(n).push(a),a}releaseBuffer(e,t,r){if(this.freeBuffers.size===0)return;let n=w7(t,r);this.freeBuffers.has(n)||this.freeBuffers.set(n,[]),this.freeBuffers.get(n).push(e),this.numFreeBuffers++,this.numUsedBuffers--;let a=this.usedBuffers.get(n),s=a.indexOf(e);if(s<0)throw new Error("Cannot release a buffer that was never provided by this buffer manager");a.splice(s,1),this.numBytesUsed-=t}releaseUploadBuffer(e,t,r){e.mapAsync(GPUMapMode.WRITE).then(()=>{this.releaseBuffer(e,t,r)},n=>{})}getNumUsedBuffers(){return this.numUsedBuffers}getNumFreeBuffers(){return this.numFreeBuffers}dispose(){this.freeBuffers.forEach((e,t)=>{e.forEach(r=>{r.destroy()})}),this.usedBuffers.forEach((e,t)=>{e.forEach(r=>{r.destroy()})}),this.freeBuffers=new Map,this.usedBuffers=new Map,this.numUsedBuffers=0,this.numFreeBuffers=0,this.numBytesUsed=0,this.numBytesAllocated=0}};function w7(e,t){return`${e}_${t}`}var Sme=class{constructor(e){this.device=e,this.numUsedTextures=0,this.numFreeTextures=0,this.freeTextures=new Map,this.usedTextures=new Map,this.numBytesUsed=0,this.numBytesAllocated=0}acquireTexture(e,t,r,n){let a=I7(r),s=e*t*a,i=k7(e,t,r,n);if(this.freeTextures.has(i)||this.freeTextures.set(i,[]),this.usedTextures.has(i)||this.usedTextures.set(i,[]),this.numBytesUsed+=s,this.numUsedTextures++,this.freeTextures.get(i).length>0){this.numFreeTextures--;let l=this.freeTextures.get(i).shift();return this.usedTextures.get(i).push(l),l}this.numBytesAllocated+=s;let o=this.device.createTexture({size:[e,t],format:r,usage:n});return this.usedTextures.get(i).push(o),o}releaseTexture(e,t,r,n,a){if(this.freeTextures.size===0)return;let s=k7(t,r,n,a);this.freeTextures.has(s)||this.freeTextures.set(s,[]),this.freeTextures.get(s).push(e),this.numFreeTextures++,this.numUsedTextures--;let i=this.usedTextures.get(s),o=i.indexOf(e);if(o<0)throw new Error("Cannot release a texture that was never provided by this texture manager");i.splice(o,1);let l=I7(n),u=t*r*l;this.numBytesUsed-=u}getNumUsedTextures(){return this.numUsedTextures}getNumFreeTextures(){return this.numFreeTextures}dispose(){this.freeTextures.forEach((e,t)=>{e.forEach(r=>{r.destroy()})}),this.usedTextures.forEach((e,t)=>{e.forEach(r=>{r.destroy()})}),this.freeTextures=new Map,this.usedTextures=new Map,this.numUsedTextures=0,this.numFreeTextures=0,this.numBytesUsed=0,this.numBytesAllocated=0}};function k7(e,t,r,n){return`${e}_${t}_${r}_${n}`}function I7(e){if(e==="rgba8unorm")return 16;throw new Error(`${e} is not supported!`)}var Cme=(e,t,r,n,a)=>{let s=[n,...r];return a&&s.push(a),e.createBindGroup({layout:t,entries:s.map((i,o)=>({binding:o,resource:i}))})},S7=(e,t,r,n,a,s=!1)=>{let i={dtype:a.dtype,shape:a.shape},o=Tpe(n,i,t,s),l=e.createShaderModule({code:o,label:t.constructor.name});return e.createComputePipeline({layout:r,compute:{module:l,entryPoint:"main"},label:t.constructor.name})};function C7(e,t,r=[],n="",a=""){let s=e.dispatch[1]===1&&e.dispatch[2]===1?"flatDispatch":"";return e.shaderKey+"_"+(e.workGroupSize?e.workGroupSize.join(","):"")+t.map(i=>i.length).join(",")+r.join(",")+e.variableNames.join(",")+n+a+s}var Tme=Z().getNumber("WEBGPU_CPU_HANDOFF_SIZE_THRESHOLD"),T7=(e,t)=>{let r=e.limits.maxComputeWorkgroupsPerDimension,n=t.dispatchLayout,a=t.dispatch;if(a.every(i=>i<=r))return a;v.assert(a[0]>r&&n.y===void 0&&n.z===void 0,()=>"Dispatch size exceeds WebGPU limits in Y or Z dimension.");let s=Math.ceil(Math.sqrt(a[0]));return s>r?(s=Math.ceil(Math.cbrt(a[0])),v.assert(s<=r,()=>"Total dispatch size exceeds WebGPU maximum."),[s,s,s]):[s,s,1]},gS=class extends Wu{constructor(e,t=!1){if(super(),this.commandQueueOwnedIds=new WeakSet,this.tensorDisposalQueue=[],this.uniformDisposalQueue=[],this.stagingDisposalQueue=[],this.textureDisposalQueue=[],this.disposed=!1,this.uploadWaitMs=0,this.downloadWaitMs=0,this.dispatchNumberInEncoder=0,this.fromPixelTextureLayout=null,this.fromPixelImportTextureLayout=null,!PA())throw new Error("WebGPU is not supported on this device");this.layoutCache={},this.pipelineCache={},this.device=e,this.queue=e.queue,this.currentCommandEncoder=null,this.currentComputePass=null,this.supportTimeQuery=t,this.bufferManager=new Ime(this.device),this.textureManager=new Sme(this.device),this.tensorMap=new rh(this,Xt()),this.supportTimeQuery&&(this.querySet=this.device.createQuerySet({type:"timestamp",count:2})),Z().getBool("WEBGPU_USE_PROFILE_TOOL")&&(this.dummyCanvas=document.createElement("canvas"),this.dummyCanvas.width=1,this.dummyCanvas.height=1,this.dummyContext=this.dummyCanvas.getContext("webgpu"),this.dummyContext.configure({device:e,format:"bgra8unorm"}),document.body.appendChild(this.dummyCanvas))}nextDataId(){return gS.nextDataId++}floatPrecision(){return 32}defaultGpuBufferUsage(){return GPUBufferUsage.STORAGE|GPUBufferUsage.COPY_SRC|GPUBufferUsage.COPY_DST}flushDisposalQueue(){this.tensorDisposalQueue.forEach(e=>{this.maybeReleaseBuffer(e),this.tensorMap.delete(e)}),this.uniformDisposalQueue.forEach(e=>this.bufferManager.releaseBuffer(e.buffer,e.byteSize,e.usage)),this.stagingDisposalQueue.forEach(e=>this.bufferManager.releaseUploadBuffer(e.buffer,e.byteSize,e.usage)),this.textureDisposalQueue.forEach(e=>this.textureManager.releaseTexture(e.texture,e.width,e.height,e.format,e.usage)),this.tensorDisposalQueue=[],this.uniformDisposalQueue=[],this.stagingDisposalQueue=[],this.textureDisposalQueue=[]}disposeData(e,t=!1){if(this.tensorMap.has(e)){let r=this.tensorMap.get(e);if(r.refCount--,!t&&r.refCount>0)return!1;if(this.commandQueueOwnedIds.has(e))return this.tensorDisposalQueue.push(e),!1;this.maybeReleaseBuffer(e);let{complexTensorInfos:n}=this.tensorMap.get(e);n!=null&&(this.disposeData(n.real.dataId,!0),this.disposeData(n.imag.dataId,!0)),this.tensorMap.delete(e)}return!0}memory(){return{numBytesInGPU:this.bufferManager.numBytesUsed,numBytesAllocatedInGPU:this.bufferManager.numBytesAllocated,unreliable:!1}}getBufferManager(){return this.bufferManager}getTextureManager(){return this.textureManager}acquireBuffer(e,t=this.defaultGpuBufferUsage()){return this.bufferManager.acquireBuffer(e,t)}maybeReleaseBuffer(e){let t=this.tensorMap.get(e);t!=null&&t.bufferInfo.buffer!=null&&(this.bufferManager.releaseBuffer(t.bufferInfo.buffer,t.bufferInfo.byteSize,t.bufferInfo.usage),t.bufferInfo.buffer=null)}refCount(e){return this.tensorMap.has(e)?this.tensorMap.get(e).refCount:0}incRef(e){let t=this.tensorMap.get(e);t.refCount++}decRef(e){if(this.tensorMap.has(e)){let t=this.tensorMap.get(e);t.refCount--}}write(e,t,r){if(r==="complex64"&&e!=null)throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");let n={id:this.nextDataId()},a=v.sizeFromShape(t)*w0(r);return this.tensorMap.set(n,{dtype:r,shape:t,values:e,bufferInfo:{byteSize:a,usage:this.defaultGpuBufferUsage()},refCount:1}),n}move(e,t,r,n,a){if(n==="complex64")throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");let s=v.sizeFromShape(r)*w0(n);this.tensorMap.set(e,{dtype:n,shape:r,values:t,bufferInfo:{byteSize:s,usage:this.defaultGpuBufferUsage()},refCount:a})}submitQueue(){this.ensureComputePassEnded(),this.queue.submit([this.currentCommandEncoder.finish()]),this.currentCommandEncoder=null,this.dispatchNumberInEncoder=0,this.commandQueueOwnedIds=new WeakSet,this.flushDisposalQueue()}getBuffer(e){return this.uploadToGPU(e),this.tensorMap.get(e).bufferInfo.buffer}ensureCommandEncoderReady(){this.currentCommandEncoder||(this.currentCommandEncoder=this.device.createCommandEncoder())}ensureComputePassEnded(){this.currentComputePass&&(this.currentComputePass.end(),this.currentComputePass=null)}getComputePass(){return this.currentComputePass||(this.currentComputePass=this.currentCommandEncoder.beginComputePass()),this.currentComputePass}async getBufferData(e,t){let r=this.acquireBuffer(t,GPUBufferUsage.COPY_DST|GPUBufferUsage.MAP_READ);this.ensureCommandEncoderReady(),this.ensureComputePassEnded(),this.currentCommandEncoder.copyBufferToBuffer(e,0,r,0,t),this.submitQueue(),await r.mapAsync(GPUMapMode.READ);let n=r.getMappedRange().slice(0);return r.unmap(),r!=null&&this.bufferManager.releaseBuffer(r,t,GPUBufferUsage.COPY_DST|GPUBufferUsage.MAP_READ),Z().getBool("WEBGPU_USE_PROFILE_TOOL")&&(v.assert(this.dummyContext!==void 0,()=>"Fail to get context for profiling tool"),this.dummyContext.getCurrentTexture()),n}convertAndCacheOnCPU(e,t){let r=this.tensorMap.get(e);return this.maybeReleaseBuffer(e),r.values=t,r.values}readSync(e){let t=this.tensorMap.get(e),{values:r}=t;if(r==null)throw new Error("WebGPU readSync is only available for CPU-resident tensors.");return r}async read(e){if(!this.tensorMap.has(e))throw new Error(`Tensor ${e} was not registered!`);let t=this.tensorMap.get(e),{values:r}=t;if(r!=null)return this.convertAndCacheOnCPU(e,r);let n;if(t.dtype==="complex64"){let a=await Promise.all([this.read(t.complexTensorInfos.real.dataId),this.read(t.complexTensorInfos.imag.dataId)]),s=a[0],i=a[1];n=C.mergeRealAndImagArrays(s,i)}else{let a=t.values!=null?t.values:await this.getBufferData(t.bufferInfo.buffer,t.bufferInfo.byteSize);n=ZI(a,t.dtype)}return this.convertAndCacheOnCPU(e,n),n}readToGPU(e){let t=this.tensorMap.get(e),{values:r,dtype:n,shape:a,bufferInfo:s}=t;if(n==="complex64")throw new Error("Does not support reading buffer for complex64 dtype.");if(s.buffer==null)throw r!=null?new Error("Data is not on GPU but on CPU."):new Error("There is no data on GPU or CPU.");let i=v.sizeFromShape(a)*w0(n),o=this.acquireBuffer(i);this.ensureCommandEncoderReady(),this.ensureComputePassEnded(),this.currentCommandEncoder.copyBufferToBuffer(s.buffer,0,o,0,i),this.submitQueue();let l=this.makeTensorInfo(a,n),u=Xt().makeTensorFromTensorInfo(l),d=this.tensorMap.get(l.dataId);return d.bufferInfo.buffer=o,{tensorRef:u,buffer:o,bufSize:i}}bufferSync(e){let t=this.readSync(e.dataId);if(e.dtype==="string")try{let r=t.map(n=>v.decodeString(n));return Le(e.shape,e.dtype,r)}catch(r){throw new Error("Failed to decode encoded string bytes into utf-8")}return Le(e.shape,e.dtype,t)}async time(e){let t=this.activeTimers,r=[],n=!1;this.programTimersStack==null?(this.programTimersStack=r,n=!0):this.activeTimers.push(r),this.activeTimers=r,e();let a=v.flatten(this.activeTimers.map(l=>l.query)).filter(l=>l!=null),s=v.flatten(this.activeTimers.map(l=>l.name)).filter(l=>l!=null);this.activeTimers=t,n&&(this.programTimersStack=null);let i={uploadWaitMs:this.uploadWaitMs,downloadWaitMs:this.downloadWaitMs,kernelMs:null,wallMs:null},o=await Promise.all(a);return i.kernelMs=v.sum(o),i.getExtraProfileInfo=()=>o.map((l,u)=>({name:s[u],ms:l})).map(l=>`${l.name}: ${l.ms}`).join(", "),this.uploadWaitMs=0,this.downloadWaitMs=0,i}getAndSavePipeline(e,t){return e in this.pipelineCache||(this.pipelineCache[e]=t()),this.pipelineCache[e]}makeTensorInfo(e,t,r){let n;if(t==="string"&&r!=null&&r.length>0&&v.isString(r[0])){let a=r.map(s=>v.encodeString(s));n=this.write(a,e,t)}else n=this.write(r,e,t);return{dataId:n,shape:e,dtype:t}}tensorToBinding(e){if(!e)return null;let t=this.tensorMap.get(e.dataId);return{offset:0,size:t.bufferInfo.byteSize,buffer:t.bufferInfo.buffer}}async getQueryTime(e){return this.supportTimeQuery?this.getTimeFromQuerySet(e):0}uploadToGPU(e){let t=this.tensorMap.get(e);if(t.bufferInfo.buffer==null&&(t.bufferInfo.buffer=this.acquireBuffer(t.bufferInfo.byteSize),t.values)){let r=this.bufferManager.acquireUploadBuffer(t.bufferInfo.byteSize,GPUBufferUsage.MAP_WRITE|GPUBufferUsage.COPY_SRC),n=r.getMappedRange();t.dtype==="int32"||t.dtype==="bool"?new Int32Array(n).set(t.values):new Float32Array(n).set(t.values),r.unmap(),this.ensureCommandEncoderReady(),this.ensureComputePassEnded(),this.currentCommandEncoder.copyBufferToBuffer(r,0,t.bufferInfo.buffer,0,t.bufferInfo.byteSize);let a={byteSize:t.bufferInfo.byteSize,usage:GPUBufferUsage.MAP_WRITE|GPUBufferUsage.COPY_SRC,buffer:r};this.stagingDisposalQueue.push(a)}}makeUniforms(e){let t=0,r=0,n=[];e.forEach(o=>{o.data.length===0&&(o.data=[1]);let l;switch(o.data.length){case 1:l=4;break;case 2:l=8;break;case 3:l=16;break;case 4:l=16;break;case 5:l=16;break;case 6:l=16;break;default:v.assert(!1,()=>`Unsupported ${o.data.length}D shape`)}(r===5||r===6)&&(l=16),t=Math.ceil(t/l)*l,r=o.data.length,n.push(t),t+=o.data.length*4});let a=new ArrayBuffer(t);e.forEach((o,l)=>{let u=n[l];o.type==="int32"?new Int32Array(a,u,o.data.length).set(o.data):o.type==="uint32"?new Uint32Array(a,u,o.data.length).set(o.data):new Float32Array(a,u,o.data.length).set(o.data)});let s=this.acquireBuffer(t,GPUBufferUsage.COPY_DST|GPUBufferUsage.UNIFORM);this.queue.writeBuffer(s,0,a,0,t);let i={byteSize:t,usage:GPUBufferUsage.COPY_DST|GPUBufferUsage.UNIFORM,buffer:s};return this.uniformDisposalQueue.push(i),{offset:0,size:t,buffer:s}}createLayout(e){let t=[];t.push({binding:0,visibility:GPUShaderStage.COMPUTE,buffer:{type:"storage"}});for(let a=0;a<e;a++)t.push({binding:a+1,visibility:GPUShaderStage.COMPUTE,buffer:{type:"read-only-storage"}});t.push({binding:e+1,visibility:GPUShaderStage.COMPUTE,buffer:{type:"uniform"}});let r=this.device.createBindGroupLayout({entries:t}),n=this.device.createPipelineLayout({bindGroupLayouts:[r]});return{bindGroupLayout:r,pipelineLayout:n}}getCachedOrCreateLayout(e){return e in this.layoutCache||(this.layoutCache[e]=this.createLayout(e)),this.layoutCache[e]}runWebGPUProgram(e,t,r,n,a){if(!a){if(a=this.makeTensorInfo(e.outputShape,r),v.sizeFromShape(a.shape)===0){let I=this.tensorMap.get(a.dataId);return I.values=v.getTypedArrayFromDType(a.dtype,0),a}this.uploadToGPU(a.dataId)}e.dispatch=T7(this.device,e);let s=[{type:"float32",data:[NaN]}],i=t.concat(a).map(I=>I.shape),o="int32";i.map(I=>{s.push({type:o,data:I})});let l=v.computeStrides(a.shape);if(s.push({type:o,data:l}),e.size){let I=v.sizeFromShape(e.outputShape);s.push({type:o,data:[e.isVec4?I/4:I]})}n&&(s=[...s,...n]);let u=this.makeUniforms(s),d=t.map((I,T)=>{if(I.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(I.dataId),{dtype:this.tensorMap.get(I.dataId).dtype,shape:I.shape,name:e.variableNames[T]}}),h=d.map(I=>I.dtype).concat(a.dtype),p=d.map(I=>C.getBroadcastDims(I.shape,a.shape)),c=d.map(I=>v.arraysEqual(I.shape,a.shape)).join("_"),m=p.map(I=>I.join("_")).join(";"),f=C7(e,i,h,m,c),{bindGroupLayout:g,pipelineLayout:y}=this.getCachedOrCreateLayout(e.variableNames.length),A=this.getAndSavePipeline(f,()=>S7(this.device,e,y,d,a)),x=this.activeTimers!=null,b=Cme(this.device,g,t.map(I=>this.tensorToBinding(I)),this.tensorToBinding(a),u);this.ensureCommandEncoderReady();let w=this.getComputePass();return x&&this.supportTimeQuery&&w.writeTimestamp(this.querySet,0),w.setPipeline(A),w.setBindGroup(0,b),w.dispatchWorkgroups(e.dispatch[0],e.dispatch[1],e.dispatch[2]),x&&this.supportTimeQuery&&w.writeTimestamp(this.querySet,1),this.dispatchNumberInEncoder++,t.forEach(I=>{this.commandQueueOwnedIds.add(I.dataId)}),this.commandQueueOwnedIds.add(a.dataId),Z().get("WEBGPU_DEFERRED_SUBMIT_BATCH_SIZE")<=this.dispatchNumberInEncoder&&this.submitQueue(),x&&this.activeTimers.push({name:e.constructor.name,query:this.getQueryTime(this.querySet)}),a}getFromPixelTextureLayout(e){return e?(this.fromPixelImportTextureLayout===null&&(this.fromPixelImportTextureLayout=this.createFromPixelTextureLayout(!0)),this.fromPixelImportTextureLayout):(this.fromPixelTextureLayout===null&&(this.fromPixelTextureLayout=this.createFromPixelTextureLayout(!1)),this.fromPixelTextureLayout)}createFromPixelTextureLayout(e){let t=[];t.push({binding:0,visibility:GPUShaderStage.COMPUTE,buffer:{type:"storage"}}),e?t.push({binding:1,visibility:GPUShaderStage.COMPUTE,externalTexture:{}}):t.push({binding:1,visibility:GPUShaderStage.COMPUTE,texture:{}}),t.push({binding:2,visibility:GPUShaderStage.COMPUTE,buffer:{}});let r=this.device.createBindGroupLayout({entries:t}),n=this.device.createPipelineLayout({bindGroupLayouts:[r]});return{bindGroupLayout:r,pipelineLayout:n}}copyExternalImageToTexture(e,t){let r=GPUTextureUsage.COPY_DST|GPUTextureUsage.RENDER_ATTACHMENT|GPUTextureUsage.TEXTURE_BINDING,n="rgba8unorm",a=this.textureManager.acquireTexture(t[1],t[0],n,r),s=a.createView();this.queue.copyExternalImageToTexture({source:e},{texture:a},[t[1],t[0]]);let i={width:t[1],height:t[0],format:n,usage:r,texture:a};return this.textureDisposalQueue.push(i),s}runFromPixelsProgram(e,t,r,n,a){e.dispatch=T7(this.device,e);let s=this.makeTensorInfo(t,"int32");if(v.sizeFromShape(s.shape)===0){let f=this.tensorMap.get(s.dataId);return f.values=v.getTypedArrayFromDType(s.dtype,0),s}this.uploadToGPU(s.dataId);let i=C7(e,[s.shape]),o=this.getFromPixelTextureLayout(n),l=this.getAndSavePipeline(i,()=>S7(this.device,e,o.pipelineLayout,[],s,!0)),u;if(n){let f={source:a};u=this.device.importExternalTexture(f)}else u=this.copyExternalImageToTexture(a,s.shape);let d=this.tensorToBinding(s),h=this.makeUniforms(r),p=this.device.createBindGroup({layout:o.bindGroupLayout,entries:[{binding:0,resource:{buffer:d.buffer}},{binding:1,resource:u},{binding:2,resource:{buffer:h.buffer}}]});this.ensureCommandEncoderReady();let c=this.getComputePass(),m=this.activeTimers!=null;return m&&this.supportTimeQuery&&c.writeTimestamp(this.querySet,0),c.setPipeline(l),c.setBindGroup(0,p),c.dispatchWorkgroups(e.dispatch[0],e.dispatch[1],e.dispatch[2]),m&&this.supportTimeQuery&&c.writeTimestamp(this.querySet,1),this.commandQueueOwnedIds.add(s.dataId),this.dispatchNumberInEncoder++,Z().get("WEBGPU_DEFERRED_SUBMIT_BATCH_SIZE")<=this.dispatchNumberInEncoder&&this.submitQueue(),m&&this.activeTimers.push({name:e.constructor.name,query:this.getQueryTime(this.querySet)}),s}async getTimeFromQuerySet(e){let t=this.acquireBuffer(16,GPUBufferUsage.COPY_SRC|GPUBufferUsage.QUERY_RESOLVE),r=this.acquireBuffer(16,GPUBufferUsage.MAP_READ|GPUBufferUsage.COPY_DST);this.ensureCommandEncoderReady(),this.ensureComputePassEnded(),this.currentCommandEncoder.resolveQuerySet(e,0,2,t,0),this.currentCommandEncoder.copyBufferToBuffer(t,0,r,0,16),this.submitQueue(),await r.mapAsync(GPUMapMode.READ);let n=new BigUint64Array(r.getMappedRange()),a=Number(n[1]-n[0]);return r.unmap(),this.bufferManager.releaseBuffer(r,16,GPUBufferUsage.MAP_READ|GPUBufferUsage.COPY_DST),this.bufferManager.releaseBuffer(t,16,GPUBufferUsage.COPY_SRC|GPUBufferUsage.QUERY_RESOLVE),a/1e6}shouldExecuteOnCPU(e,t=Tme){return Z().getBool("WEBGPU_CPU_FORWARD")&&e.every(r=>this.tensorMap.get(r.dataId).bufferInfo.buffer==null&&v.sizeFromShape(r.shape)<t)}numDataIds(){return this.tensorMap.numDataIds()-this.tensorDisposalQueue.length}dispose(){this.disposed||(this.bufferManager.dispose(),this.textureManager.dispose(),this.disposed=!0)}},LA=gS;LA.nextDataId=0;var yS={};Be(yS,{WebGPUBackend:()=>LA,webgpu_util:()=>XI});PA()&&El("webgpu",async()=>{Z().set("CHECK_COMPUTATION_FOR_ERRORS",!1);let e={powerPreference:Z().get("WEBGPU_USE_LOW_POWER_GPU")?"low-power":"high-performance"},t=await navigator.gpu.requestAdapter(e),r=t.limits,n={},a=t.features.has("timestamp-query");n.requiredLimits={maxComputeWorkgroupStorageSize:r.maxComputeWorkgroupStorageSize,maxComputeWorkgroupsPerDimension:r.maxComputeWorkgroupsPerDimension},a?n.requiredFeatures=["timestamp-query"]:console.warn("This device doesn't support timestamp-query extension. Start Chrome browser with flag --disable-dawn-features=disallow_unsafe_apis then try again. Or zero will shown for the kernel time when profiling mode isenabled. Using performance.now is not workable for webgpu sinceit doesn't support synchronously to read data from GPU.");let s=await t.requestDevice(n);return new LA(s,a)},3);var Ut=(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",e))(Ut||{}),Bm=(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",e))(Bm||{}),AS;function Nme(e){AS=e.wasm.cwrap(_s,null,["number","array","number","number","array","number","number","number","number","number","number","number","number"])}function Eme(e){let{inputs:t,backend:r,attrs:n}=e,{a,b:s,bias:i,preluActivationWeights:o}=t;if(a.dtype!=="float32"||s.dtype!=="float32")throw new Error("_FusedMatMul for non non-float32 tensors not yet supported.");let{transposeA:l,transposeB:u,activation:d,leakyreluAlpha:h}=n,p=r.dataIdMap.get(a.dataId).id,c=r.dataIdMap.get(s.dataId).id,m=0;if(i!=null){let E=r.dataIdMap.get(i.dataId);if(E.shape.length!==1)throw new Error(`_FusedMatMul only supports rank-1 bias but got rank ${E.shape.length}.`);m=E.id}let f=o==null?0:r.dataIdMap.get(o.dataId).id,g=Bm[d];if(g==null)throw new Error(`${d} activation not yet supported for FusedConv2D in the wasm backend.`);let y=l?a.shape[2]:a.shape[1],A=u?s.shape[1]:s.shape[2],x=Rl.assertAndGetBroadcastShape(a.shape.slice(0,-2),s.shape.slice(0,-2)),b=r.makeOutput([...x,y,A],a.dtype),w=r.dataIdMap.get(b.dataId).id,I=new Uint8Array(new Int32Array(a.shape).buffer),T=new Uint8Array(new Int32Array(s.shape).buffer);return AS(p,I,a.shape.length,c,T,s.shape.length,l,u,g,m,f,h||0,w),b}var Rme={kernelName:_s,backendName:"wasm",setupFunc:Nme,kernelFunc:Eme};function kr(e,t){let r;function n(s){r=s.wasm.cwrap(e,null,["number","number","number"])}function 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_me(e){xS=e.wasm.cwrap(Ks,null,["array","number","number","number"])}function Pme(e){let{inputs:t,backend:r}=e,n=r.makeOutput(t[0].shape,t[0].dtype);if(v.sizeFromShape(n.shape)===0)return n;let a=t.map(o=>r.dataIdMap.get(o.dataId).id),s=new Uint8Array(new Int32Array(a).buffer),i=r.dataIdMap.get(n.dataId).id;return xS(s,a.length,Ut[n.dtype],i),n}var Ome={kernelName:Ks,backendName:"wasm",setupFunc:_me,kernelFunc:Pme};function Wm(e){let{inputs:{x:t},backend:r}=e,n=r.makeOutput(t.shape,t.dtype),a=r.typedArrayFromHeap(t);return r.typedArrayFromHeap(n).set(a),n}var zme={kernelName:fi,backendName:"wasm",kernelFunc:Wm},bS;function Dme(e){bS=e.wasm.cwrap(Ma,null,["number","array","number","number","number","array","number"])}function qs(e){let{inputs:t,backend:r,attrs:n}=e,[a,s]=Bme(t.x.shape,n.perm),i=!0;for(let m=0;m<s.length;m++)s[m]!==m&&(i=!1);let o=Lme(t.x.shape,n.perm),l={dataId:t.x.dataId,shape:a,dtype:t.x.dtype};if(i){let m=Wm({inputs:t,backend:r});return m.shape=o,m}let u=r.makeOutput(o,l.dtype),d=r.dataIdMap.get(l.dataId).id,h=r.dataIdMap.get(u.dataId).id,p=new Uint8Array(new Int32Array(s).buffer),c=new Uint8Array(new Int32Array(l.shape).buffer);return bS(d,c,l.shape.length,Ut[l.dtype],h,p,s.length),u}function Lme(e,t){let r=new Array(e.length);for(let n=0;n<r.length;n++)r[n]=e[t[n]];return r}function Bme(e,t){let r=[],n=[];for(let a=0;a<e.length;++a)e[a]!==1&&r.push(e[a]),e[t[a]]!==1&&n.push(t[a]);for(let a=0;a<n.length;++a){let s=-1;for(let i=0;i<n.length;++i)n[i]>=a&&(s===-1||n[s]>n[i])&&(s=i);n[s]=a}return[r,n]}var Wme={kernelName:Ma,backendName:"wasm",kernelFunc:qs,setupFunc:Dme};function Xi(e,t,r){let n=e.shape,a=e.shape.length,s=v.parseAxisParam(t,n),i=s,o=C.getAxesPermutation(i,a),l=null,u=!1;if(o!=null){let d=new Array(a);for(let p=0;p<d.length;p++)d[p]=n[o[p]];i=C.getInnerMostAxes(i.length,a),l=qs({inputs:{x:e},attrs:{perm:o},backend:r});let h=r.dataIdMap.get(e.dataId).id;r.dataIdMap.get(l.dataId).id!==h&&(u=!0)}return{transposed:l,originalAxes:s,axes:i,inputWasTransposed:u}}var vS;function Vme(e){vS=e.wasm.cwrap(ju,null,["number, number, number"])}function Ume(e){let{backend:t,inputs:r,attrs:n}=e,{axis:a,keepDims:s}=n,{x:i}=r,o=t.dataIdMap.get(i.dataId).id,l=i,{transposed:u,axes:d,originalAxes:h,inputWasTransposed:p}=Xi(i,a,t);if(p){let A=t.dataIdMap.get(u.dataId).id;l=u,o=A}let c=l.shape.length;C.assertAxesAreInnerMostDims("all",d,c);let[m,f]=C.computeOutAndReduceShapes(l.shape,d),g=v.sizeFromShape(f),y=t.makeOutput(m,i.dtype);if(v.sizeFromShape(l.shape)!==0){let A=t.dataIdMap.get(y.dataId).id;vS(o,g,A)}if(p&&t.disposeData(u.dataId),s){let A=C.expandShapeToKeepDim(y.shape,h);y.shape=A}return y}var Gme={kernelName:ju,backendName:"wasm",setupFunc:Vme,kernelFunc:Ume},wS;function jme(e){wS=e.wasm.cwrap(Hu,null,["number, number, number"])}function Hme(e){let{backend:t,inputs:r,attrs:n}=e,{axis:a,keepDims:s}=n,{x:i}=r,o=t.dataIdMap.get(i.dataId).id,l=i,{transposed:u,axes:d,originalAxes:h,inputWasTransposed:p}=Xi(i,a,t);if(p){let A=t.dataIdMap.get(u.dataId).id;l=u,o=A}let c=l.shape.length;C.assertAxesAreInnerMostDims("any",d,c);let[m,f]=C.computeOutAndReduceShapes(l.shape,d),g=v.sizeFromShape(f),y=t.makeOutput(m,i.dtype);if(v.sizeFromShape(l.shape)!==0){let A=t.dataIdMap.get(y.dataId).id;wS(o,g,A)}if(p&&t.disposeData(u.dataId),s){let A=C.expandShapeToKeepDim(y.shape,h);y.shape=A}return y}var qme={kernelName:Hu,backendName:"wasm",setupFunc:jme,kernelFunc:Hme},kS;function Xme(e){kS=e.wasm.cwrap(Zs,null,["number","number","number","number","number"])}function Kme(e){let{backend:t,inputs:r,attrs:n}=e,{axis:a}=n,{x:s}=r,i=t.dataIdMap.get(s.dataId).id,o=i,l=s,{transposed:u,axes:d,inputWasTransposed:h}=Xi(s,a,t);if(h){let y=t.dataIdMap.get(u.dataId).id;y!==i&&(l=u,o=y)}let p=l.shape.slice(0,-1),c=t.makeOutput(p,"int32"),m=t.dataIdMap.get(c.dataId).id,f=v.sizeFromShape(c.shape),g=l.shape[d[0]];return kS(o,Ut[l.dtype],f,g,m),h&&t.disposeData(u.dataId),c}var Zme={kernelName:Zs,backendName:"wasm",kernelFunc:Kme,setupFunc:Xme},IS;function Yme(e){IS=e.wasm.cwrap(Ys,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function Jme(e){let{inputs:t,attrs:r,backend:n}=e,a=t.x,s=n.dataIdMap.get(a.dataId).id,{filterSize:i,strides:o,pad:l,dimRoundingMode:u}=r,d=C.computePool2DInfo(a.shape,i,o,1,l,u),h=d.filterHeight,p=d.filterWidth,c=d.padInfo.top,m=d.padInfo.right,f=d.padInfo.bottom,g=d.padInfo.left,y=d.strideHeight,A=d.strideWidth,x=d.inChannels;if(d.dataFormat!=="channelsLast")throw new Error(`wasm backend does not support dataFormat:'${d.dataFormat}'. Please use 'channelsLast'.`);if(d.dilationWidth!==1||d.dilationHeight!==1)throw new Error(`was backend only supports average pooling with dilation = [1, 1], got [${d.dilationHeight}, ${d.dilationWidth}].`);let b=n.makeOutput(d.outShape,"float32"),w=n.dataIdMap.get(b.dataId).id;return IS(s,a.shape[0],a.shape[1],a.shape[2],h,p,c,m,f,g,y,A,x,w),b}var Qme={kernelName:Ys,backendName:"wasm",setupFunc:Yme,kernelFunc:Jme};function nn(e){let{inputs:t,attrs:r}=e,{x:n}=t,{shape:a}=r,s=v.sizeFromShape(n.shape),i=v.inferFromImplicitShape(a,s);return v.assert(s===v.sizeFromShape(i),()=>`new shape: ${i}, old shape: ${n.shape}. 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t.dtype==="string"?h.stringBytes=l.slice(m,m+v.sizeFromShape(i)):a.typedArrayFromHeap(u).set(l.subarray(m,m+v.sizeFromShape(i))),u}if(t.dtype==="string"){let m=X0(l,s,i,t.shape,t.dtype);return h.stringBytes=m,u}let p=a.typedArrayFromHeap(u),c=t.shape.length;if(c===2)a1e(l,d[0],p,s,i);else if(c===3)s1e(l,d[0],d[1],p,s,i);else if(c===4)i1e(l,d[0],d[1],d[2],p,s,i);else{let m=X0(l,s,i,t.shape,t.dtype);p.set(m)}return u}function a1e(e,t,r,n,a){let s=0,i=n[0],o=n[1],l=i+a[0];for(let u=i;u<l;u++){let d=u*t+o;r.set(e.subarray(d,d+a[1]),s),s+=a[1]}}function s1e(e,t,r,n,a,s){let i=0,o=a[0],l=a[1],u=a[2],d=o+s[0],h=l+s[1];for(let p=o;p<d;p++)for(let c=l;c<h;c++){let m=p*t+c*r+u;n.set(e.subarray(m,m+s[2]),i),i+=s[2]}}function i1e(e,t,r,n,a,s,i){let o=0,l=s[0],u=s[1],d=s[2],h=l+i[0],p=u+i[1],c=d+i[2],m=s[3];for(let f=l;f<h;f++)for(let g=u;g<p;g++)for(let y=d;y<c;y++){let A=f*t+g*r+y*n+m;a.set(e.subarray(A,A+i[3]),o),o+=i[3]}}var o1e={kernelName:Al,backendName:"wasm",kernelFunc:Wo};function l1e(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{blockShape:s,crops:i}=n,o=s.reduce((y,A)=>y*A),l=C.getReshaped(a.shape,s,o),u=C.getPermuted(l.length,s.length),d=C.getReshapedPermuted(a.shape,s,o),h=C.getSliceBeginCoords(i,s.length),p=C.getSliceSize(d,i,s.length),c=nn({inputs:{x:a},backend:r,attrs:{shape:l}}),m=qs({inputs:{x:c},backend:r,attrs:{perm:u}}),f=nn({inputs:{x:m},backend:r,attrs:{shape:d}}),g=Wo({inputs:{x:f},backend:r,attrs:{begin:h,size:p}});return r.disposeData(c.dataId),r.disposeData(m.dataId),r.disposeData(c.dataId),g}var u1e={kernelName:jo,backendName:"wasm",kernelFunc:l1e};function tc(e){let{inputs:{x:t},attrs:{dtype:r},backend:n}=e,a=n.makeOutput(t.shape,r),s=n.typedArrayFromHeap(t);return n.typedArrayFromHeap(a).set(s),a}var d1e={kernelName:Qs,backendName:"wasm",kernelFunc:tc},p1e=kr(ei),CS;function h1e(e){CS=e.wasm.cwrap(Qa,null,["number","number","number","number"])}function c1e(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{clipValueMin:s,clipValueMax:i}=n,o=r.dataIdMap.get(a.dataId).id,l=r.makeOutput(a.shape,a.dtype),u=r.dataIdMap.get(l.dataId).id;return CS(o,s,i,u),l}var f1e={kernelName:Qa,backendName:"wasm",setupFunc:h1e,kernelFunc:c1e};function TS(e){let{inputs:t,backend:r}=e,n=v.parseAxisParam(e.attrs.axis,t[0].shape)[0],a=C.computeOutShape(t.map(c=>c.shape),n),s=t.filter(c=>v.sizeFromShape(c.shape)>0);if(s.length===1)return Wm({inputs:{x:s[0]},backend:r});let i=r.makeOutput(a,t[0].dtype);if(v.sizeFromShape(a)===0)return i;let o=s.map(c=>c.shape);if(C.assertParamsConsistent(o,n),s[0].dtype==="string"){let c=s.map(x=>{let b=v.sizeFromShape(x.shape.slice(n));return nn({inputs:{x},backend:r,attrs:{shape:[-1,b]}})}),m=c.map(x=>({vals:r.readSync(x.dataId),shape:x.shape}));a=C.computeOutShape(c.map(x=>x.shape),1);let f=c[0].shape[0]===1,g=dA(m,a,t[0].dtype,f),y=C.computeOutShape(s.map(x=>x.shape),n);i.shape=y;let A=r.dataIdMap.get(i.dataId);return A.stringBytes=C.fromStringArrayToUint8(g),c.forEach(x=>r.disposeData(x.dataId)),i}let l=v.sizeFromShape(s[0].shape.slice(0,n)),u=0,d=s.map(c=>{let m=v.sizeFromShape(c.shape.slice(n));return u+=m,m}),h=s.map(c=>r.typedArrayFromHeap(c)),p=r.typedArrayFromHeap(i);for(let c=0;c<l;c++){let m=c*u;for(let f=0;f<h.length;f++){let g=d[f],y=c*g,A=h[f].subarray(y,y+g);p.set(A,m),m+=g}}return i}var m1e={kernelName:Ho,backendName:"wasm",kernelFunc:TS},NS;function g1e(e){NS=e.wasm.cwrap(ti,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function y1e(e){let{inputs:t,attrs:r,backend:n}=e,{x:a,filter:s}=t,i=n.dataIdMap.get(a.dataId).id,o=n.dataIdMap.get(s.dataId).id,{strides:l,dilations:u,pad:d,dimRoundingMode:h,dataFormat:p}=r,c=C.convertConv2DDataFormat(p),m=C.computeConv2DInfo(a.shape,s.shape,l,u,d,h,!1,c),f=m.filterHeight,g=m.filterWidth,y=m.padInfo.top,A=m.padInfo.right,x=m.padInfo.bottom,b=m.padInfo.left,w=m.dilationHeight,I=m.dilationWidth,T=m.strideHeight,E=m.strideWidth,R=m.inChannels,O=m.outChannels,M=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"),P=n.dataIdMap.get(S.dataId).id;return NS(i,a.shape[0],a.shape[1],a.shape[2],o,f,g,y,A,x,b,M,w,I,T,E,R,O,P),S}var A1e={kernelName:ti,backendName:"wasm",setupFunc:g1e,kernelFunc:y1e},ES;function x1e(e){ES=e.wasm.cwrap(ri,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 b1e(e){let{backend:t,inputs:r,attrs:n}=e,{dy:a,filter:s}=r,{strides:i,pad:o,dataFormat:l,dimRoundingMode:u,inputShape:d}=n,h=1,p=C.convertConv2DDataFormat(l),c=C.computeConv2DInfo(d,s.shape,i,h,o,u,!1,p),{batchSize:m,filterHeight:f,filterWidth:g,inChannels:y,inHeight:A,inWidth:x,outChannels:b,outHeight:w,outWidth:I,strideHeight:T,strideWidth:E}=c,R=f-1-c.padInfo.top,O=g-1-c.padInfo.left,M=c.dataFormat==="channelsLast",S=v.computeStrides(c.inShape),P=v.computeStrides(a.shape),[z,j,K]=v.computeStrides(s.shape),D=S[0],Y=M?S[1]:S[2],V=M?S[2]:1,re=M?1:S[1],Q=P[0],ie=M?P[1]:P[2],J=M?P[2]:1,ae=M?1:P[1],de=t.makeOutput(c.inShape,"float32"),be=t.dataIdMap.get(de.dataId).id,ve=t.dataIdMap.get(a.dataId).id,Ee=t.dataIdMap.get(s.dataId).id;return ES(ve,Ee,m,f,g,A,x,y,w,I,b,T,E,R,O,z,j,K,D,Y,V,re,Q,ie,J,ae,be),de}var v1e={kernelName:ri,backendName:"wasm",setupFunc:x1e,kernelFunc:b1e},w1e=kr(ni),k1e=kr(ai),RS=(e=>(e[e.bilinear=0]="bilinear",e[e.nearest=1]="nearest",e))(RS||{}),MS;function I1e(e){MS=e.wasm.cwrap(Xo,null,["number","number","number","number","array","number","number","number","number","number"])}function S1e(e){let{backend:t,inputs:r,attrs:n}=e,{method:a,extrapolationValue:s,cropSize:i}=n,{image:o,boxes:l,boxInd:u}=r,d=l.shape[0],[h,p]=i,c=[d,h,p,o.shape[3]],m=t.dataIdMap.get(o.dataId),f;o.dtype!=="float32"&&(f=tc({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,A=t.dataIdMap.get(u.dataId).id,x=t.makeOutput(c,"float32"),b=t.dataIdMap.get(x.dataId).id,w=new Uint8Array(new Int32Array(o.shape).buffer);return MS(g,y,A,d,w,h,p,RS[a],s,b),f!=null&&t.disposeData(f.dataId),x}var C1e={kernelName:Xo,backendName:"wasm",setupFunc:I1e,kernelFunc:S1e},$S;function T1e(e){$S=e.wasm.cwrap(qo,null,["number","number","number","number","number","number"])}function N1e(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{axis:s,exclusive:i,reverse:o}=n,l=a.shape.length;v.assert(a.dtype==="float32"||a.dtype==="int32",()=>`cumprod does not support ${a.dtype} tensors in the WASM backend`);let u=C.getAxesPermutation([s],l),d=a;u!==null&&(d=qs({inputs:{x:a},attrs:{perm:u},backend:r}));let h=C.getInnerMostAxes(1,l)[0];C.assertAxesAreInnerMostDims("cumprod",[h],l);let p=r.makeOutput(d.shape,d.dtype),c=d.shape[h],m=r.dataIdMap.get(d.dataId).id,f=r.dataIdMap.get(p.dataId).id;$S(m,i?1:0,o?1:0,c,f,Ut[a.dtype]);let g=p;if(u!==null){let y=C.getUndoAxesPermutation(u);g=qs({inputs:{x:p},attrs:{perm:y},backend:r}),r.disposeData(d.dataId),r.disposeData(p.dataId)}return g}var E1e={kernelName:qo,backendName:"wasm",setupFunc:T1e,kernelFunc:N1e},FS;function R1e(e){FS=e.wasm.cwrap(si,null,["number","number","number","number","number","number"])}function M1e(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{axis:s,exclusive:i,reverse:o}=n,l=a.shape.length;v.assert(a.dtype==="float32"||a.dtype==="int32",()=>`cumsum does not support ${a.dtype} tensors in the WASM backend`);let u=C.getAxesPermutation([s],l),d=a;u!==null&&(d=qs({inputs:{x:a},attrs:{perm:u},backend:r}));let h=C.getInnerMostAxes(1,l)[0];C.assertAxesAreInnerMostDims("cumsum",[h],l);let p=r.makeOutput(d.shape,d.dtype),c=d.shape[h],m=r.dataIdMap.get(d.dataId).id,f=r.dataIdMap.get(p.dataId).id;FS(m,i?1:0,o?1:0,c,f,Ut[a.dtype]);let g=p;if(u!==null){let y=C.getUndoAxesPermutation(u);g=qs({inputs:{x:p},attrs:{perm:y},backend:r}),r.disposeData(d.dataId),r.disposeData(p.dataId)}return g}var $1e={kernelName:si,backendName:"wasm",setupFunc:R1e,kernelFunc:M1e},_S;function F1e(e){_S=e.wasm.cwrap(Ko,null,["number","number","number","array","number","array","array","number","number"])}function _1e(e){let{backend:t,inputs:r,attrs:n}=e,{x:a}=r,{blockSize:s,dataFormat:i}=n,o=a.shape[0],l=i==="NHWC"?a.shape[1]:a.shape[2],u=i==="NHWC"?a.shape[2]:a.shape[3],d=i==="NHWC"?a.shape[3]:a.shape[1],h=l*s,p=u*s,c=d/(s*s),m=i==="NHWC"?[o,h,p,c]:[o,c,h,p],f=t.makeOutput(m,"float32"),g=t.dataIdMap.get(a.dataId).id,y=new Uint8Array(new Int32Array(v.computeStrides(a.shape)).buffer),A=new Uint8Array(new Int32Array(m).buffer),x=new Uint8Array(new Int32Array(v.computeStrides(m)).buffer),b=t.dataIdMap.get(f.dataId).id;return _S(g,s,i==="NHWC"?1:0,y,a.shape.length-1,A,x,m.length,b),f}var P1e={kernelName:Ko,backendName:"wasm",setupFunc:F1e,kernelFunc:_1e},PS;function O1e(e){PS=e.wasm.cwrap(ii,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function z1e(e){let{inputs:t,attrs:r,backend:n}=e,{x:a,filter:s}=t,i=n.dataIdMap.get(a.dataId).id,o=n.dataIdMap.get(s.dataId).id,{strides:l,dilations:u,pad:d,dimRoundingMode:h}=r,p=u==null?[1,1]:u,c=C.computeConv2DInfo(a.shape,s.shape,l,p,d,h,!0),m=c.filterHeight,f=c.filterWidth,g=c.padInfo.top,y=c.padInfo.right,A=c.padInfo.bottom,x=c.padInfo.left,b=c.dilationHeight,w=c.dilationWidth,I=c.strideHeight,T=c.strideWidth,E=c.inChannels,R=c.outChannels,O=c.padInfo.type==="SAME"?1:0;if(c.dataFormat!=="channelsLast")throw new Error(`wasm backend DepthwiseConv2dNative does not support dataFormat:'${c.dataFormat}'. Please use 'channelsLast'.`);let M=n.makeOutput(c.outShape,"float32"),S=n.dataIdMap.get(M.dataId).id;return PS(i,a.shape[0],a.shape[1],a.shape[2],o,m,f,g,y,A,x,O,b,w,I,T,E,R,S),M}var D1e={kernelName:ii,backendName:"wasm",setupFunc:O1e,kernelFunc:z1e},L1e=kr(li),B1e=!1,W1e=Kr(Zo,B1e,"bool"),V1e=kr(ui,"float32");function by(e){let{inputs:t,attrs:r,backend:n}=e,{input:a}=t,{dim:s}=r,i=a.shape.length,o=a.shape.slice(),l=s;return s<0&&(v.assert(-(i+1)<=s,()=>`Axis must be in the interval [${-(i+1)}, ${i}]`),l=i+s+1),o.splice(l,0,1),nn({inputs:{x:a},backend:n,attrs:{shape:o}})}var U1e={kernelName:Yo,backendName:"wasm",kernelFunc:by};function OS(e){let{attrs:{shape:t,value:r,dtype:n},backend:a}=e,s=a.makeOutput(t,n);return a.typedArrayFromHeap(s).fill(r),s}var G1e={kernelName:ed,backendName:"wasm",kernelFunc:OS},zS;function j1e(e){zS=e.wasm.cwrap(Qo,null,["number","number","number","number","number","number"])}function H1e(e){let{inputs:t,backend:r}=e,{image:n}=t,a=r.makeOutput(n.shape,n.dtype),s=r.dataIdMap.get(n.dataId).id,i=r.dataIdMap.get(a.dataId).id,[o,l,u,d]=n.shape;return zS(s,o,l,u,d,i),a}var q1e={kernelName:Qo,backendName:"wasm",kernelFunc:H1e,setupFunc:j1e},X1e=kr(di),K1e=!1,Z1e=Kr(pi,K1e),DS;function Y1e(e){DS=e.wasm.cwrap(hi,null,["number","number","number","number","number","number","number"])}function J1e(e){let{backend:t,inputs:r,attrs:n}=e,{varianceEpsilon:a}=n,{x:s,mean:i,variance:o,offset:l,scale:u}=r,d=t.dataIdMap.get(s.dataId).id,h=t.dataIdMap.get(i.dataId).id,p=t.dataIdMap.get(o.dataId).id,c=l!=null?t.dataIdMap.get(l.dataId).id:0,m=u!=null?t.dataIdMap.get(u.dataId).id:0,f=t.makeOutput(s.shape,s.dtype);if(v.sizeFromShape(s.shape)===0)return f;let g=t.dataIdMap.get(f.dataId).id;return DS(d,h,p,c,m,a,g),f}var Q1e={kernelName:hi,backendName:"wasm",setupFunc:Y1e,kernelFunc:J1e},LS;function e2e(e){LS=e.wasm.cwrap(Ps,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function t2e(e){let{inputs:t,attrs:r,backend:n}=e,{x:a,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:u,dilations:d,dataFormat:h,dimRoundingMode:p,activation:c,leakyreluAlpha:m}=r,f=C.computeConv2DInfo(a.shape,s.shape,l,d,u,p),g=Bm[c];if(g==null)throw new Error(`${c} activation not yet supported for FusedConv2D in the wasm backend.`);let y=n.dataIdMap.get(a.dataId).id,A=n.dataIdMap.get(s.dataId).id,x=f.outChannels,b=0;if(i!=null){let J=n.dataIdMap.get(i.dataId);if(J.shape.length!==1)throw new Error(`FusedConv2D only supports rank-1 bias but got rank ${J.shape.length}.`);if(J.shape[0]!==x)throw new Error(`FusedConv2D bias shape (${J.shape}) does not match the number of output channels (${x})`);b=J.id}let w=f.filterHeight,I=f.filterWidth,T=f.padInfo.top,E=f.padInfo.right,R=f.padInfo.bottom,O=f.padInfo.left,M=f.dilationHeight,S=f.dilationWidth,P=f.strideHeight,z=f.strideWidth,j=f.inChannels,K=f.padInfo.type==="SAME"?1:0,D=f.batchSize,Y=f.inHeight,V=f.inWidth;if(h!=="NHWC")throw new Error(`wasm backend FusedConv2D does not support dataFormat:'${h}'. Please use 'NHWC'.`);let re=n.makeOutput(f.outShape,"float32"),Q=n.dataIdMap.get(re.dataId).id,ie=o==null?0:n.dataIdMap.get(o.dataId).id;return LS(y,D,Y,V,A,w,I,b,T,E,R,O,K,M,S,P,z,j,x,g,ie,m||0,Q),re}var r2e={kernelName:Ps,backendName:"wasm",setupFunc:e2e,kernelFunc:t2e},BS;function n2e(e){BS=e.wasm.cwrap(Os,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 a2e(e){let{inputs:t,attrs:r,backend:n}=e,{x:a,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:u,dilations:d,dataFormat:h,dimRoundingMode:p,activation:c,leakyreluAlpha:m}=r,f=C.computeConv2DInfo(a.shape,s.shape,l,d,u,p,!0),g=Bm[c];if(g==null)throw new Error(`${c} activation not yet supported for FusedDepthwiseConv2D in the wasm backend.`);let y=n.dataIdMap.get(a.dataId).id,A=n.dataIdMap.get(s.dataId).id,x=f.outChannels,b=0;if(i!=null){let J=n.dataIdMap.get(i.dataId);if(J.shape.length!==1)throw new Error(`FusedDepthwiseConv2D only supports rank-1 bias but got rank ${J.shape.length}.`);if(J.shape[0]!==x)throw new Error(`FusedDepthwiseConv2D bias shape (${J.shape}) does not match the number of output channels (${x})`);b=J.id}let w=f.filterHeight,I=f.filterWidth,T=f.padInfo.top,E=f.padInfo.right,R=f.padInfo.bottom,O=f.padInfo.left,M=f.dilationHeight,S=f.dilationWidth,P=f.strideHeight,z=f.strideWidth,j=f.inChannels,K=f.padInfo.type==="SAME"?1:0,D=f.batchSize,Y=f.inHeight,V=f.inWidth;if(h!=="NHWC")throw new Error(`wasm backend FusedDepthwiseConv2D does not support dataFormat:'${h}'. Please use 'NHWC'.`);let re=n.makeOutput(f.outShape,"float32"),Q=n.dataIdMap.get(re.dataId).id,ie=o==null?0:n.dataIdMap.get(o.dataId).id;return BS(y,D,Y,V,A,w,I,b,T,E,R,O,K,M,S,P,z,j,x,g,ie,m||0,Q),re}var s2e={kernelName:Os,backendName:"wasm",setupFunc:n2e,kernelFunc:a2e},WS;function i2e(e){WS=e.wasm.cwrap(tl,null,["number","number","number","number","number","number","array","number"])}function o2e(e){let{backend:t,inputs:r}=e,{params:n,indices:a}=r,[s,i,o,l]=By.prepareAndValidate(n,a),u=t.makeOutput(s,n.dtype);if(i===0)return u;let d=a.shape,h=d[d.length-1],p=t.dataIdMap.get(n.dataId).id,c=t.dataIdMap.get(a.dataId).id,m=new Uint8Array(new Int32Array(l).buffer),f=t.dataIdMap.get(u.dataId).id;return WS(p,Ut[n.dtype],c,i,h,o,m,f),u}var l2e={kernelName:tl,backendName:"wasm",setupFunc:i2e,kernelFunc:o2e},VS;function u2e(e){VS=e.wasm.cwrap("Gather",null,["number","number","array","number","number","number","array","number"])}function d2e(e){let{backend:t,inputs:r,attrs:n}=e,{x:a,indices:s}=r,{axis:i,batchDims:o}=n,l=v.parseAxisParam(i,a.shape)[0],u=t.readSync(s.dataId),d=a.shape[l];for(let T=0;T<u.length;++T){let E=u[T];v.assert(E<=d-1&&E>=0,()=>`GatherV2: the index value ${E} is not in [0, ${d-1}]`)}let h=C.segment_util.collectGatherOpShapeInfo(a,s,l,o),p=nn({inputs:{x:a},attrs:{shape:[h.batchSize,h.outerSize,h.dimSize,h.sliceSize]},backend:t}),c=v.sizeFromShape(s.shape),m=nn({inputs:{x:s},attrs:{shape:[h.batchSize,c/h.batchSize]},backend:t}),f=[h.batchSize,h.outerSize,c/h.batchSize,h.sliceSize],g=t.makeOutput(f,a.dtype);if(v.sizeFromShape(a.shape)===0)return g;let y=p.shape.length-1,A=t.dataIdMap.get(p.dataId).id,x=t.dataIdMap.get(m.dataId).id,b=t.dataIdMap.get(g.dataId).id,w=new Uint8Array(new Int32Array(v.computeStrides(p.shape)).buffer),I=new Uint8Array(new Int32Array(v.computeStrides(f)).buffer);return VS(A,Ut[a.dtype],w,y,x,h.batchSize,I,b),t.disposeData(p.dataId),t.disposeData(m.dataId),g.shape=h.outputShape,g}var p2e={kernelName:el,backendName:"wasm",setupFunc:u2e,kernelFunc:d2e},h2e=!1,c2e=Kr(rl,h2e,"bool"),f2e=!1,m2e=Kr(ci,f2e,"bool"),US;function g2e(e){US=e.wasm.cwrap(mi,null,["number","number","number","number"])}function y2e(e){let{inputs:{x:t},attrs:{alpha:r},backend:n}=e,a=n.dataIdMap.get(t.dataId).id,s=n.makeOutput(t.shape,"float32");if(v.sizeFromShape(t.shape)!==0){let i=n.dataIdMap.get(s.dataId).id;US(a,Ut[t.dtype],r,i)}return s}var A2e={kernelName:mi,backendName:"wasm",setupFunc:g2e,kernelFunc:y2e},x2e=!1,b2e=Kr(nl,x2e,"bool"),v2e=!1,w2e=Kr(al,v2e,"bool"),k2e=kr(gi),I2e=!1,S2e=Kr(sl,I2e,"bool"),GS;function C2e(e){GS=e.wasm.cwrap(yi,null,["number","number","number","number"])}function T2e(e){let{backend:t,inputs:r,attrs:n}=e,{reductionIndices:a,keepDims:s}=n,{x:i}=r,o=t.dataIdMap.get(i.dataId).id,l=i,{transposed:u,axes:d,originalAxes:h,inputWasTransposed:p}=Xi(i,a,t);if(p){let A=t.dataIdMap.get(u.dataId).id;l=u,o=A}let c=l.shape.length;C.assertAxesAreInnerMostDims("max",d,c);let[m,f]=C.computeOutAndReduceShapes(l.shape,d),g=v.sizeFromShape(f),y=t.makeOutput(m,i.dtype);if(v.sizeFromShape(l.shape)!==0){let A=t.dataIdMap.get(y.dataId).id;GS(o,Ut[i.dtype],g,A)}if(p&&t.disposeData(u.dataId),s){let A=C.expandShapeToKeepDim(y.shape,h);y.shape=A}return y}var N2e={kernelName:yi,backendName:"wasm",setupFunc:C2e,kernelFunc:T2e},E2e=!1,R2e=Kr(Ai,E2e),jS;function M2e(e){jS=e.wasm.cwrap(xi,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function $2e(e){let{inputs:t,attrs:r,backend:n}=e,a=t.x,s=n.dataIdMap.get(a.dataId).id;v.assert(a.dtype==="float32",()=>`Error in MaxPool: only float32 input is supported. Got ${a.dtype}.`);let{filterSize:i,strides:o,pad:l,dimRoundingMode:u}=r,d=C.computePool2DInfo(a.shape,i,o,1,l,u),h=d.filterHeight,p=d.filterWidth,c=d.padInfo.top,m=d.padInfo.right,f=d.padInfo.bottom,g=d.padInfo.left,y=d.dilationHeight,A=d.dilationWidth,x=d.strideHeight,b=d.strideWidth,w=d.inChannels,I=d.outChannels;if(d.dataFormat!=="channelsLast")throw new Error(`wasm backend does not support dataFormat:'${d.dataFormat}'. Please use 'channelsLast'.`);let T=n.makeOutput(d.outShape,"float32"),E=n.dataIdMap.get(T.dataId).id;return jS(s,a.shape[0],a.shape[1],a.shape[2],h,p,c,m,f,g,y,A,x,b,w,I,E),T}var F2e={kernelName:xi,backendName:"wasm",setupFunc:M2e,kernelFunc:$2e},HS;function _2e(e){HS=e.wasm.cwrap(bi,null,["number, number, number"])}function P2e(e){let{backend:t,inputs:r,attrs:n}=e,{axis:a,keepDims:s}=n,{x:i}=r,o=t.dataIdMap.get(i.dataId).id,l=o,u=i,{transposed:d,axes:h,originalAxes:p,inputWasTransposed:c}=Xi(i,a,t),m=h;if(c){let b=t.dataIdMap.get(d.dataId).id;b!==o&&(u=d,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),A=u;u.dtype!=="float32"&&(A=tc({backend:t,inputs:{x:u},attrs:{dtype:"float32"}}),l=t.dataIdMap.get(A.dataId).id);let x=t.makeOutput(f,"float32");if(v.sizeFromShape(u.shape)!==0){let b=t.dataIdMap.get(x.dataId).id;HS(l,y,b)}if(c&&t.disposeData(d.dataId),s){let b=C.expandShapeToKeepDim(x.shape,p);x.shape=b}return u.dtype!=="float32"&&t.disposeData(A.dataId),x}var O2e={kernelName:bi,backendName:"wasm",setupFunc:_2e,kernelFunc:P2e},qS;function z2e(e){qS=e.wasm.cwrap(vi,null,["number","number","number","number"])}function D2e(e){let{backend:t,inputs:r,attrs:n}=e,{axis:a,keepDims:s}=n,{x:i}=r,o=t.dataIdMap.get(i.dataId).id,l=o,u=i,{transposed:d,axes:h,originalAxes:p,inputWasTransposed:c}=Xi(i,a,t);if(c){let x=t.dataIdMap.get(d.dataId).id;x!==o&&(u=d,l=x)}let m=u.shape.length;C.assertAxesAreInnerMostDims("min",h,m);let[f,g]=C.computeOutAndReduceShapes(u.shape,h),y=v.sizeFromShape(g),A=t.makeOutput(f,u.dtype);if(v.sizeFromShape(u.shape)!==0){let x=t.dataIdMap.get(A.dataId).id;qS(l,Ut[i.dtype],y,x)}if(c&&t.disposeData(d.dataId),s){let x=C.expandShapeToKeepDim(A.shape,p);A.shape=x}return A}var L2e={kernelName:vi,backendName:"wasm",setupFunc:z2e,kernelFunc:D2e},B2e=!1,W2e=Kr(wi,B2e),XS=(e=>(e[e.reflect=0]="reflect",e[e.symmetric=1]="symmetric",e))(XS||{}),KS;function V2e(e){KS=e.wasm.cwrap(ki,null,["number","array","number","number","array","array","number","number"])}function U2e(e){let{inputs:{x:t},backend:r,attrs:{paddings:n,mode:a}}=e,s=n.map((m,f)=>m[0]+t.shape[f]+m[1]),i=r.dataIdMap.get(t.dataId).id,o=r.makeOutput(s,t.dtype),l=r.dataIdMap.get(o.dataId).id,u=new Uint8Array(new Int32Array(t.shape).buffer),d=n.map(m=>m[0]),h=n.map(m=>m[1]),p=new Uint8Array(new Int32Array(d).buffer),c=new Uint8Array(new Int32Array(h).buffer);return KS(i,u,t.shape.length,Ut[t.dtype],p,c,XS[a],l),o}var G2e={kernelName:ki,backendName:"wasm",kernelFunc:U2e,setupFunc:V2e},j2e=!0,H2e=Kr(Ii,j2e),q2e=kr(il);function BA(e,t){let r=new Int32Array(e.wasm.HEAPU8.buffer,t,4),n=r[0],a=r[1],s=r[2],i=r[3];return e.wasm._free(t),{pSelectedIndices:n,selectedSize:a,pSelectedScores:s,pValidOutputs:i}}var ZS;function X2e(e){ZS=e.wasm.cwrap(ll,"number",["number","number","number","number","number"])}function K2e(e){let{backend:t,inputs:r,attrs:n}=e,{iouThreshold:a,maxOutputSize:s,scoreThreshold:i}=n,{boxes:o,scores:l}=r,u=t.dataIdMap.get(o.dataId).id,d=t.dataIdMap.get(l.dataId).id,h=ZS(u,d,s,a,i),{pSelectedIndices:p,selectedSize:c,pSelectedScores:m,pValidOutputs:f}=BA(t,h);return t.wasm._free(m),t.wasm._free(f),t.makeOutput([c],"int32",p)}var Z2e={kernelName:ll,backendName:"wasm",setupFunc:X2e,kernelFunc:K2e},YS;function Y2e(e){YS=e.wasm.cwrap(od,"number",["number","number","number","number","number","bool"])}function J2e(e){let{backend:t,inputs:r,attrs:n}=e,{iouThreshold:a,maxOutputSize:s,scoreThreshold:i,padToMaxOutputSize:o}=n,{boxes:l,scores:u}=r,d=t.dataIdMap.get(l.dataId).id,h=t.dataIdMap.get(u.dataId).id,p=YS(d,h,s,a,i,o),{pSelectedIndices:c,selectedSize:m,pSelectedScores:f,pValidOutputs:g}=BA(t,p);t.wasm._free(f);let 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pge={kernelName:hl,backendName:"wasm",kernelFunc:dge},eC;function hge(e){eC=e.wasm.cwrap(Si,null,["number","array","number","number","array","array","number","number"])}function cge(e){let{inputs:{x:t},backend:r,attrs:{paddings:n,constantValue:a}}=e,s=n.map((m,f)=>m[0]+t.shape[f]+m[1]);if(v.sizeFromShape(t.shape)===0)return OS({backend:r,attrs:{shape:s,value:a,dtype:t.dtype}});let i=r.dataIdMap.get(t.dataId).id,o=r.makeOutput(s,t.dtype),l=r.dataIdMap.get(o.dataId).id,u=new Uint8Array(new Int32Array(t.shape).buffer),d=n.map(m=>m[0]),h=n.map(m=>m[1]),p=new Uint8Array(new Int32Array(d).buffer),c=new Uint8Array(new Int32Array(h).buffer);return eC(i,u,t.shape.length,Ut[t.dtype],p,c,a,l),o}var tC={kernelName:Si,backendName:"wasm",kernelFunc:cge,setupFunc:hge},fge=!1,mge=Kr(Ci,fge),rC;function gge(e){rC=e.wasm.cwrap(Ti,null,["number","number","number"])}function 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Kge(e){dC=e.wasm.cwrap(zi,null,["number","number","number","number"])}function Zge(e){let{backend:t,inputs:{logits:r},attrs:{dim:n}}=e,a=t.dataIdMap.get(r.dataId).id,s=t.makeOutput(r.shape,r.dtype),i=t.dataIdMap.get(s.dataId).id,o=r.shape[n],l=v.sizeFromShape(r.shape)/o;return v.sizeFromShape(s.shape)===0||dC(a,i,o,l),s}var Yge={kernelName:zi,backendName:"wasm",setupFunc:Kge,kernelFunc:Zge};function Jge(e){let{inputs:t,backend:r,attrs:n}=e,{x:a}=t,{blockShape:s,paddings:i}=n,o=v.sizeFromShape(s),l=[[0,0]];l.push(...i);for(let g=1+s.length;g<a.shape.length;++g)l.push([0,0]);let u=tC.kernelFunc({inputs:{x:a},backend:r,attrs:{paddings:l,constantValue:0}}),d=C.getReshaped(u.shape,s,o,!1),h=C.getPermuted(d.length,s.length,!1),p=C.getReshapedPermuted(u.shape,s,o,!1),c=nn({inputs:{x:u},backend:r,attrs:{shape:d}}),m=qs({inputs:{x:c},backend:r,attrs:{perm:h}}),f=nn({inputs:{x:m},backend:r,attrs:{shape:p}});return r.disposeData(u.dataId),r.disposeData(c.dataId),r.disposeData(m.dataId),f}var Qge={kernelName:bl,backendName:"wasm",kernelFunc:Jge},pC;function eye(e){pC=e.wasm.cwrap("SparseFillEmptyRows","number",["number","number","number","number","number","number","number","number","number","number","number","number"])}function tye(e){let{backend:t,inputs:r}=e,{indices:n,values:a,denseShape:s,defaultValue:i}=r,o=n.shape[0],l=n.shape[1],u=t.readSync(s.dataId)[0],d=[o+u,l],h=t.dataIdMap.get(n.dataId).id,p=t.dataIdMap.get(a.dataId).id,c=t.dataIdMap.get(i.dataId).id,m=t.makeOutput(d,n.dtype),f=t.dataIdMap.get(m.dataId).id,g=t.makeOutput(d.slice(0,1),a.dtype),y=t.dataIdMap.get(g.dataId).id,A=t.makeOutput([u],"bool"),x=t.dataIdMap.get(A.dataId).id,b=t.makeOutput([o],n.dtype),w=t.dataIdMap.get(b.dataId).id,I=t.makeOutput([4],"int32"),T=t.dataIdMap.get(I.dataId).id,E=pC(h,p,Ut[a.dtype],o,u,l,c,f,y,x,w,T),R=t.readSync(I.dataId),O;switch(R[0]){case 1:{O=C.getSparseFillEmptyRowsIndicesDenseShapeMismatch(R[1]);break}case 2:{O=C.getSparseFillEmptyRowsNegativeIndexErrorMessage(R[1],R[2]);break}case 3:O=C.getSparseFillEmptyRowsOutOfRangeIndexErrorMessage(R[1],R[2],R[3]);break;default:O=""}if(t.disposeData(I.dataId),O)throw t.disposeData(m.dataId),t.disposeData(g.dataId),t.disposeData(A.dataId),t.disposeData(b.dataId),new Error(O);let M=m,S=g;return E!==d[0]&&(M=Wo({inputs:{x:m},attrs:{begin:0,size:[E,l]},backend:t}),S=Wo({inputs:{x:g},attrs:{begin:0,size:E},backend:t}),t.disposeData(m.dataId),t.disposeData(g.dataId)),[M,S,A,b]}var rye={kernelName:fh,backendName:"wasm",setupFunc:eye,kernelFunc:tye},hC;function nye(e){hC=e.wasm.cwrap(fd,null,["number","number","number","number","number","number","number"])}function aye(e){let{backend:t,inputs:r}=e,{inputIndices:n,inputShape:a,newShape:s}=r;if(n.shape.length!==2)throw new Error(`Input indices should be a matrix but received shape
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A=r.readSync(g.dataId),x;switch(A[0]){case 0:{x=C.getSparseSegmentReductionNegativeSegmentIdsErrorMessage();break}case 1:{x=C.getSparseSegmentReductionNonIncreasingSegmentIdsErrorMessage();break}case 2:x=C.getSparseSegmentReductionSegmentIdOutOfRangeErrorMessage(A[1],A[2]);break;case 3:x=C.getSparseSegmentReductionIndicesOutOfRangeErrorMessage(A[1],A[2],A[3]);break;default:x=""}if(r.disposeData(g.dataId),x)throw r.disposeData(m.dataId),new Error(x);return m}function iye(e){return mC(e,!0)}var oye={kernelName:mh,backendName:"wasm",setupFunc:fC,kernelFunc:iye};function lye(e){return mC(e,!1)}var uye={kernelName:gh,backendName:"wasm",setupFunc:fC,kernelFunc:lye};function dye(e){let{inputs:t,attrs:r,backend:n}=e,{x:a}=t,{numOrSizeSplits:s,axis:i}=r,o=v.parseAxisParam(i,a.shape)[0],l=C.prepareSplitSize(a,s,o),u=new Array(a.shape.length).fill(0),d=a.shape.slice();return l.map(h=>{let p=[...d];p[o]=h;let c=Wo({inputs:{x:a},attrs:{begin:u,size:p},backend:n});return u[o]+=h,c})}var pye={kernelName:vl,backendName:"wasm",kernelFunc:dye},hye=kr(Pi),cye=kr(md),fye=!0,mye=Kr(Di,fye),gC;function gye(e){gC=e.wasm.cwrap(Wi,null,["number","number","number","number"])}function yye(e){let{backend:t,inputs:r,attrs:n}=e,{alpha:a}=n,{x:s}=r,i=t.dataIdMap.get(s.dataId).id,o=t.makeOutput(s.shape,s.dtype),l=t.dataIdMap.get(o.dataId).id;return gC(i,a,Ut[s.dtype],l),o}var Aye={kernelName:Wi,backendName:"wasm",setupFunc:gye,kernelFunc:yye},yC;function xye(e){yC=e.wasm.cwrap(wl,null,["number","array","number","array","array","array","array","array","number","number"])}function bye(e){let{backend:t,inputs:r,attrs:n}=e,{x:a}=r,{begin:s,end:i,strides:o,beginMask:l,endMask:u,ellipsisMask:d,newAxisMask:h,shrinkAxisMask:p}=n,{finalShapeSparse:c,finalShape:m,isIdentity:f,sliceDim0:g,isSimpleSlice:y,begin:A,end:x,strides:b}=Dt.sliceInfo(a.shape,s,i,o,l,u,d,h,p),w;if(f)w=nn({inputs:{x:a},backend:t,attrs:{shape:m}});else if(g||y){v.assert(a.shape.length>=1,()=>`Input must have rank at least 1, 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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 SC=`
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];
}
`,CC=`
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;
}
`,TC=`
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);
}
`,NC=`
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;
}
`,EC=`
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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Vd=e=>[Math.abs(e.endPoint[0]-e.startPoint[0]),Math.abs(e.endPoint[1]-e.startPoint[1])],Xm=e=>[e.startPoint[0]+(e.endPoint[0]-e.startPoint[0])/2,e.startPoint[1]+(e.endPoint[1]-e.startPoint[1])/2,1],Km=(e,t)=>e?[Math.trunc(Math.max(0,e.startPoint[0])),Math.trunc(Math.max(0,e.startPoint[1])),Math.trunc(Math.min(t.shape[2]||0,e.endPoint[0])-Math.max(0,e.startPoint[0])),Math.trunc(Math.min(t.shape[1]||0,e.endPoint[1])-Math.max(0,e.startPoint[1]))]:[0,0,0,0],Zm=(e,t)=>e?[e.startPoint[0]/(t.shape[2]||0),e.startPoint[1]/(t.shape[1]||0),(e.endPoint[0]-e.startPoint[0])/(t.shape[2]||0),(e.endPoint[1]-e.startPoint[1])/(t.shape[1]||0)]:[0,0,0,0],QC=(e,t)=>{let r=[e.startPoint[0]*t[0],e.startPoint[1]*t[1]],n=[e.endPoint[0]*t[0],e.endPoint[1]*t[1]];return{startPoint:r,endPoint:n,landmarks:e.landmarks,confidence:e.confidence}},ix=(e,t,r)=>{let n=t.shape[1],a=t.shape[2],s=[e.startPoint[1]/n,e.startPoint[0]/a,e.endPoint[1]/n,e.endPoint[0]/a],i=Ie.cropAndResize(t,[s],[0],r),o=pe(i,Qe.tf255);return te(i),o},Ym=(e,t)=>{let r=Xm(e),n=Vd(e),a=[t*n[0]/2,t*n[1]/2];return{startPoint:[r[0]-a[0],r[1]-a[1]],endPoint:[r[0]+a[0],r[1]+a[1]],landmarks:e.landmarks,confidence:e.confidence}},Jm=e=>{let t=Xm(e),r=Vd(e),n=Math.max(...r)/2;return{startPoint:[Math.round(t[0]-n),Math.round(t[1]-n)],endPoint:[Math.round(t[0]+n),Math.round(t[1]+n)],landmarks:e.landmarks,confidence:e.confidence}},eT=e=>{let t=e.map(n=>n[0]),r=e.map(n=>n[1]);return{startPoint:[Math.min(...t),Math.min(...r)],endPoint:[Math.max(...t),Math.max(...r)],landmarks:e}},ox=[[1,0,0],[0,1,0],[0,0,1]],b3e=e=>e-2*Math.PI*Math.floor((e+Math.PI)/(2*Math.PI)),v3e=(e,t)=>b3e(Math.PI/2-Math.atan2(-(t[1]-e[1]),t[0]-e[0]));var YC=(e,t)=>[[1,0,e],[0,1,t],[0,0,1]],Vl=(e,t)=>{let r=0;for(let n=0;n<e.length;n++)r+=e[n]*t[n];return r},w3e=(e,t)=>{let r=[];for(let n=0;n<e.length;n++)r.push(e[n][t]);return r},JC=(e,t)=>{let r=[],n=e.length;for(let a=0;a<n;a++){r.push([]);for(let s=0;s<n;s++)r[a].push(Vl(e[a],w3e(t,s)))}return r},tT=(e,t)=>{let r=Math.cos(e),n=Math.sin(e),a=[[r,-n,0],[n,r,0],[0,0,1]],s=YC(t[0],t[1]),i=JC(s,a),o=YC(-t[0],-t[1]);return JC(i,o)},k3e=e=>{let t=[[e[0][0],e[1][0]],[e[0][1],e[1][1]]],r=[e[0][2],e[1][2]],n=[-Vl(t[0],r),-Vl(t[1],r)];return[t[0].concat(n[0]),t[1].concat(n[1]),[0,0,1]]},I3e=(e,t)=>[Vl(e,t[0]),Vl(e,t[1])];function rT(e){let t=e===192?{strides:[4],anchors:[1]}:{strides:[e/16,e/8],anchors:[2,6]},r=[];for(let n=0;n<t.strides.length;n++){let a=t.strides[n],s=Math.floor((e+a-1)/a),i=Math.floor((e+a-1)/a),o=t.anchors[n];for(let l=0;l<s;l++){let u=a*(l+.5);for(let d=0;d<i;d++){let h=a*(d+.5);for(let p=0;p<o;p++)r.push([h,u])}}}return r}function nT(e,t,r,n,a){let s=Vd(t),i=e.map(c=>[s[0]/a*(c[0]-a/2),s[1]/a*(c[1]-a/2),c[2]||0]),o=r&&r!==0&&Math.abs(r)>.2,l=o?tT(r,[0,0]):ox,u=o?i.map(c=>[...I3e(c,l),c[2]]):i,d=o?k3e(n):ox,h=Xm(t),p=[Vl(h,d[0]),Vl(h,d[1])];return u.map(c=>[Math.trunc(c[0]+p[0]),Math.trunc(c[1]+p[1]),Math.trunc(c[2]||0)])}function aT(e,t,r,n){let a=t.landmarks.length>=nx.count?nx.symmetryLine:Bl.symmetryLine,s=0,i=ox,o;if(e&&he.kernels.includes("rotatewithoffset"))if(s=v3e(t.landmarks[a[0]],t.landmarks[a[1]]),s&&s!==0&&Math.abs(s)>.2){let u=Xm(t),d=[u[0]/r.shape[2],u[1]/r.shape[1]],h=Ie.rotateWithOffset(r,s,0,d);i=tT(-s,u),o=ix(t,h,[n,n]),te(h)}else o=ix(t,r,[n,n]);else o=ix(t,r,[n,n]);return[s,i,o]}var S3e=e=>{let t=e.map(n=>n[0]),r=e.map(n=>n[1]);return[Math.min(...t)+(Math.max(...t)-Math.min(...t))/2,Math.min(...r)+(Math.max(...r)-Math.min(...r))/2]},sT=(e,t)=>{let r=S3e(e),n=Vd(t);return{startPoint:[r[0]-n[0]/2,r[1]-n[1]/2],endPoint:[r[0]+n[0]/2,r[1]+n[1]/2]}};var iT=6,C3e=1.4,La,oT=null,Zi=0,sc=null,Ud=()=>Zi;async function lT(e){var t;return he.initial&&(La=null),La?e.debug&&se("cached model:",La.modelUrl):La=await Ge((t=e.face.detector)==null?void 0:t.modelPath),Zi=La.inputs[0].shape?La.inputs[0].shape[2]:0,sc=Se(Zi,"int32"),oT=ca(rT(Zi)),La}function T3e(e){let t={};t.boxStarts=_e(e,[0,1],[-1,2]),t.centers=le(t.boxStarts,oT),t.boxSizes=_e(e,[0,3],[-1,2]),t.boxSizesNormalized=pe(t.boxSizes,sc),t.centersNormalized=pe(t.centers,sc),t.halfBoxSize=pe(t.boxSizesNormalized,Qe.tf2),t.starts=ce(t.centersNormalized,t.halfBoxSize),t.ends=le(t.centersNormalized,t.halfBoxSize),t.startNormalized=L(t.starts,sc),t.endNormalized=L(t.ends,sc);let r=yd([t.startNormalized,t.endNormalized],1);return Object.keys(t).forEach(n=>te(t[n])),r}async function uT(e,t){var o,l,u,d;if(!e||e.isDisposedInternal||e.shape.length!==4||e.shape[1]<1||e.shape[2]<1)return[];let r={};r.resized=Ie.resizeBilinear(e,[Zi,Zi]),r.div=pe(r.resized,Qe.tf127),r.normalized=ce(r.div,Qe.tf05);let n=La==null?void 0:La.execute(r.normalized);if(Array.isArray(n)&&n.length>2){let h=n.sort((p,c)=>p.size-c.size);r.concat384=St([h[0],h[2]],2),r.concat512=St([h[1],h[3]],2),r.concat=St([r.concat512,r.concat384],1),r.batch=et(r.concat,0)}else Array.isArray(n)?r.batch=et(n[0]):r.batch=et(n);te(n),r.boxes=T3e(r.batch),r.logits=_e(r.batch,[0,0],[-1,1]),r.sigmoid=Cr(r.logits),r.scores=et(r.sigmoid),r.nms=await Ie.nonMaxSuppressionAsync(r.boxes,r.scores,((o=t.face.detector)==null?void 0:o.maxDetected)||0,((l=t.face.detector)==null?void 0:l.iouThreshold)||0,((u=t.face.detector)==null?void 0:u.minConfidence)||0);let a=await r.nms.array(),s=[],i=await r.scores.data();for(let h=0;h<a.length;h++){let p=i[a[h]];if(p>(((d=t.face.detector)==null?void 0:d.minConfidence)||0)){let c={};c.bbox=_e(r.boxes,[a[h],0],[1,-1]),c.slice=_e(r.batch,[a[h],iT-1],[1,-1]),c.squeeze=et(c.slice),c.landmarks=U(c.squeeze,[iT,-1]);let m=await c.bbox.data(),f={startPoint:[m[0],m[1]],endPoint:[m[2],m[3]],landmarks:await c.landmarks.array(),confidence:p},g=QC(f,[(e.shape[2]||0)/Zi,(e.shape[1]||0)/Zi]),y=Ym(g,t.face.scale||C3e),A=Jm(y);s.push(A),Object.keys(c).forEach(x=>te(c[x]))}}return Object.keys(r).forEach(h=>te(r[h])),s}var Qm={};vs(Qm,{connected:()=>dx,kpt:()=>ux});var ux=["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"],dx={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 pT=224,N3e,E3e=5,e1=[8,16,32,32,32];async function hT(){let e=[],t=0;for(;t<E3e;){let r=0,n=t;for(;n<e1.length&&e1[n]===e1[t];)r+=2,n++;let a=e1[t],s=Math.ceil(pT/a),i=Math.ceil(pT/a);for(let o=0;o<s;++o)for(let l=0;l<i;++l)for(let u=0;u<r;++u)e.push({x:(l+.5)/i,y:(o+.5)/s});t=n}N3e={x:Nt(e.map(r=>r.x)),y:Nt(e.map(r=>r.y))}}function ls(e,t=[1,1]){let r=[e.map(o=>o[0]),e.map(o=>o[1])],n=[Math.min(...r[0]),Math.min(...r[1])],a=[Math.max(...r[0]),Math.max(...r[1])],s=[n[0],n[1],a[0]-n[0],a[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 cT(e,t=[1,1]){let r=[e.map(u=>u[0]),e.map(u=>u[1])],n=[Math.min(...r[0]),Math.min(...r[1])],a=[Math.max(...r[0]),Math.max(...r[1])],s=[(n[0]+a[0])/2,(n[1]+a[1])/2],i=Math.max(s[0]-n[0],s[1]-n[1],-s[0]+a[0],-s[1]+a[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 t1(e,t){let r=[e[2]*t,e[3]*t];return[e[0]-(r[0]-e[2])/2,e[1]-(r[1]-e[3])/2,r[0],r[1]]}var gT={initial:!0},An={detector:null,landmarks:null},Gd={detector:[224,224],landmarks:[256,256]},px=Number.MAX_SAFE_INTEGER,M3e={landmarks:["ld_3d","activation_segmentation","activation_heatmap","world_3d","output_poseflag"],detector:[]},n1=null,ic,Yi=[[0,0],[0,0],[0,0],[0,0]],fT=0,mT=e=>1-1/(1+Math.exp(e));async function yT(e){if(gT.initial&&(An.detector=null),!An.detector&&e.body.detector&&e.body.detector.modelPath){An.detector=await Ge(e.body.detector.modelPath);let t=Object.values(An.detector.modelSignature.inputs);Gd.detector[0]=Array.isArray(t)?parseInt(t[0].tensorShape.dim[1].size):0,Gd.detector[1]=Array.isArray(t)?parseInt(t[0].tensorShape.dim[2].size):0}else e.debug&&An.detector&&se("cached model:",An.detector.modelUrl);return await hT(),An.detector}async function AT(e){if(gT.initial&&(An.landmarks=null),An.landmarks)e.debug&&se("cached model:",An.landmarks.modelUrl);else{An.landmarks=await Ge(e.body.modelPath);let t=Object.values(An.landmarks.modelSignature.inputs);Gd.landmarks[0]=Array.isArray(t)?parseInt(t[0].tensorShape.dim[1].size):0,Gd.landmarks[1]=Array.isArray(t)?parseInt(t[0].tensorShape.dim[2].size):0}return An.landmarks}async function $3e(e,t){let r={};if(!e.shape||!e.shape[1]||!e.shape[2])return e;let n;if(ic&&(r.cropped=Ie.cropAndResize(e,[ic],[0],[e.shape[1],e.shape[2]])),e.shape[1]!==e.shape[2]){let a=[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],s=[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];Yi=[[0,0],a,s,[0,0]],r.pad=Xn(r.cropped||e,Yi),r.resize=Ie.resizeBilinear(r.pad,[t,t]),n=pe(r.resize,Qe.tf255)}else e.shape[1]!==t?(r.resize=Ie.resizeBilinear(r.cropped||e,[t,t]),n=pe(r.resize,Qe.tf255)):n=pe(r.cropped||e,Qe.tf255);return Object.keys(r).forEach(a=>te(r[a])),n}function F3e(e,t){for(let r of e)r.position=[Math.trunc(r.position[0]*(t[0]+Yi[2][0]+Yi[2][1])/t[0]-Yi[2][0]),Math.trunc(r.position[1]*(t[1]+Yi[1][0]+Yi[1][1])/t[1]-Yi[1][0]),r.position[2]],r.positionRaw=[r.position[0]/t[0],r.position[1]/t[1],2*r.position[2]/(t[0]+t[1])];if(ic)for(let r of e)r.positionRaw=[r.positionRaw[0]+ic[1],r.positionRaw[1]+ic[0],r.positionRaw[2]],r.position=[Math.trunc(r.positionRaw[0]*t[0]),Math.trunc(r.positionRaw[1]*t[1]),r.positionRaw[2]];return e}async function _3e(e){let t=e.find(o=>o.part==="leftPalm"),r=e.find(o=>o.part==="leftWrist"),n=e.find(o=>o.part==="leftIndex");t.position[2]=((r.position[2]||0)+(n.position[2]||0))/2;let a=e.find(o=>o.part==="rightPalm"),s=e.find(o=>o.part==="rightWrist"),i=e.find(o=>o.part==="rightIndex");a.position[2]=((s.position[2]||0)+(i.position[2]||0))/2}async function P3e(e,t,r){var m;let n={};[n.ld,n.segmentation,n.heatmap,n.world,n.poseflag]=(m=An.landmarks)==null?void 0:m.execute(e,M3e.landmarks);let a=(await n.poseflag.data())[0],s=await n.ld.data(),i=await n.world.data();Object.keys(n).forEach(f=>te(n[f]));let o=[],l=5;for(let f=0;f<s.length/l;f++){let g=mT(s[l*f+3]),y=mT(s[l*f+4]),A=Math.trunc(100*g*y*a)/100,x=[s[l*f+0]/Gd.landmarks[0],s[l*f+1]/Gd.landmarks[1],s[l*f+2]+0],b=[Math.trunc(r[0]*x[0]),Math.trunc(r[1]*x[1]),x[2]],w=[i[l*f+0],i[l*f+1],i[l*f+2]+0];o.push({part:ux[f],positionRaw:x,position:b,distance:w,score:A})}if(a<(t.body.minConfidence||0))return null;_3e(o);let u=F3e(o,r),d=u.map(f=>f.position),h=ls(d,[r[0],r[1]]),p={};for(let[f,g]of Object.entries(dx)){let y=[];for(let A=0;A<g.length-1;A++){let x=u.find(w=>w.part===g[A]),b=u.find(w=>w.part===g[A+1]);x&&b&&y.push([x.position,b.position])}p[f]=y}return{id:0,score:Math.trunc(100*a)/100,box:h.box,boxRaw:h.boxRaw,keypoints:u,annotations:p}}async function hx(e,t){let r=[e.shape[2]||0,e.shape[1]||0],n=(t.body.skipTime||0)>oe()-fT,a=px<(t.body.skipFrames||0);if(t.skipAllowed&&n&&a&&n1!==null)px++;else{let s={};s.landmarks=await $3e(e,256),n1=await P3e(s.landmarks,t,r),Object.keys(s).forEach(i=>te(s[i])),fT=oe(),px=0}return n1?[n1]:[]}var jd=[{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 meter"},{class:14,label:"bench"},{class:15,label:"bird"},{class:16,label:"cat"},{class:17,label:"dog"},{class:18,label:"horse"},{class:19,label:"sheep"},{class:20,label:"cow"},{class:21,label:"elephant"},{class:22,label:"bear"},{class:23,label:"zebra"},{class:24,label:"giraffe"},{class:25,label:"backpack"},{class:26,label:"umbrella"},{class:27,label:"handbag"},{class:28,label:"tie"},{class:29,label:"suitcase"},{class:30,label:"frisbee"},{class:31,label:"skis"},{class:32,label:"snowboard"},{class:33,label:"sports ball"},{class:34,label:"kite"},{class:35,label:"baseball bat"},{class:36,label:"baseball glove"},{class:37,label:"skateboard"},{class:38,label:"surfboard"},{class:39,label:"tennis racket"},{class:40,label:"bottle"},{class:41,label:"wine glass"},{class:42,label:"cup"},{class:43,label:"fork"},{class:44,label:"knife"},{class:45,label:"spoon"},{class:46,label:"bowl"},{class:47,label:"banana"},{class:48,label:"apple"},{class:49,label:"sandwich"},{class:50,label:"orange"},{class:51,label:"broccoli"},{class:52,label:"carrot"},{class:53,label:"hot dog"},{class:54,label:"pizza"},{class:55,label:"donut"},{class:56,label:"cake"},{class:57,label:"chair"},{class:58,label:"couch"},{class:59,label:"potted plant"},{class:60,label:"bed"},{class:61,label:"dining table"},{class:62,label:"toilet"},{class:63,label:"tv"},{class:64,label:"laptop"},{class:65,label:"mouse"},{class:66,label:"remote"},{class:67,label:"keyboard"},{class:68,label:"cell phone"},{class:69,label:"microwave"},{class:70,label:"oven"},{class:71,label:"toaster"},{class:72,label:"sink"},{class:73,label:"refrigerator"},{class:74,label:"book"},{class:75,label:"clock"},{class:76,label:"vase"},{class:77,label:"scissors"},{class:78,label:"teddy bear"},{class:79,label:"hair drier"},{class:80,label:"toothbrush"}];var us,Ul=0,cx=[],bT=0,fx=Number.MAX_SAFE_INTEGER;async function vT(e){if(he.initial&&(us=null),us)e.debug&&se("cached model:",us.modelUrl);else{us=await Ge(e.object.modelPath);let t=Object.values(us.modelSignature.inputs);Ul=Array.isArray(t)?parseInt(t[0].tensorShape.dim[2].size):0}return us}async function O3e(e,t,r){if(!e)return[];let n={},a=[],s=await e.array();n.squeeze=et(e);let i=Yt(n.squeeze,6,1);n.stack=ur([i[1],i[0],i[3],i[2]],1),n.boxes=et(n.stack),n.scores=et(i[4]),n.classes=et(i[5]),te([e,...i]),n.nms=await Ie.nonMaxSuppressionAsync(n.boxes,n.scores,r.object.maxDetected,r.object.iouThreshold,r.object.minConfidence||0);let o=await n.nms.data(),l=0;for(let u of Array.from(o)){let d=Math.trunc(100*s[0][u][4])/100,h=s[0][u][5],p=jd[h].label,[c,m]=[s[0][u][0]/Ul,s[0][u][1]/Ul],f=[c,m,s[0][u][2]/Ul-c,s[0][u][3]/Ul-m],g=[Math.trunc(f[0]*t[0]),Math.trunc(f[1]*t[1]),Math.trunc(f[2]*t[0]),Math.trunc(f[3]*t[1])];a.push({id:l++,score:d,class:h,label:p,box:g,boxRaw:f})}return Object.keys(n).forEach(u=>te(n[u])),a}async function mx(e,t){let r=(t.object.skipTime||0)>oe()-bT,n=fx<(t.object.skipFrames||0);return t.skipAllowed&&r&&n&&cx.length>0?(fx++,cx):(fx=0,new Promise(async a=>{let s=[e.shape[2]||0,e.shape[1]||0],i=Ie.resizeBilinear(e,[Ul,Ul]),o=t.object.enabled?us==null?void 0:us.execute(i,["tower_0/detections"]):null;bT=oe(),te(i);let l=await O3e(o,s,t);cx=l,a(l)}))}var a1={};vs(a1,{connected:()=>yx,kpt:()=>gx});var gx=["head","neck","rightShoulder","rightElbow","rightWrist","chest","leftShoulder","leftElbow","leftWrist","bodyCenter","rightHip","rightKnee","rightAnkle","leftHip","leftKnee","leftAnkle"],yx={leftLeg:["leftHip","leftKnee","leftAnkle"],rightLeg:["rightHip","rightKnee","rightAnkle"],torso:["leftShoulder","rightShoulder","rightHip","leftHip","leftShoulder"],leftArm:["leftShoulder","leftElbow","leftWrist"],rightArm:["rightShoulder","rightElbow","rightWrist"],head:[]};var Rr,kT=0,Yr={id:0,keypoints:[],box:[0,0,0,0],boxRaw:[0,0,0,0],score:0,annotations:{}},Ax=Number.MAX_SAFE_INTEGER;async function IT(e){return he.initial&&(Rr=null),Rr?e.debug&&se("cached model:",Rr.modelUrl):Rr=await Ge(e.body.modelPath),Rr}async function z3e(e,t){let[r,n]=e.shape,a=U(e,[n*r]),s=yr(a,0),i=(await s.data())[0];if(te([a,s]),i>t){let o=Rn(a,0),l=bd(o,r),u=(await l.data())[0],d=pe(o,Se(r,"int32")),h=(await d.data())[0];return te([l,d]),[u,h,i]}return[0,0,i]}async function xx(e,t){let r=(t.body.skipTime||0)>oe()-kT,n=Ax<(t.body.skipFrames||0);return t.skipAllowed&&r&&n&&Object.keys(Yr.keypoints).length>0?(Ax++,[Yr]):(Ax=0,new Promise(async a=>{var h;let s=X(()=>{if(!(Rr!=null&&Rr.inputs[0].shape))return null;let p=Ie.resizeBilinear(e,[Rr.inputs[0].shape[2],Rr.inputs[0].shape[1]],!1),c=L(p,Qe.tf2);return ce(c,Qe.tf1)}),i;if(t.body.enabled&&(i=Rr==null?void 0:Rr.execute(s)),kT=oe(),te(s),i){Yr.keypoints.length=0;let p=i.squeeze();te(i);let c=p.unstack(2);te(p);for(let m=0;m<c.length;m++){let[f,g,y]=await z3e(c[m],t.body.minConfidence);y>(((h=t.body)==null?void 0:h.minConfidence)||0)&&Yr.keypoints.push({score:Math.round(100*y)/100,part:gx[m],positionRaw:[f/Rr.inputs[0].shape[2],g/Rr.inputs[0].shape[1]],position:[Math.round(e.shape[2]*f/Rr.inputs[0].shape[2]),Math.round(e.shape[1]*g/Rr.inputs[0].shape[1])]})}c.forEach(m=>te(m))}Yr.score=Yr.keypoints.reduce((p,c)=>c.score>p?c.score:p,0);let o=Yr.keypoints.map(p=>p.position[0]),l=Yr.keypoints.map(p=>p.position[1]);Yr.box=[Math.min(...o),Math.min(...l),Math.max(...o)-Math.min(...o),Math.max(...l)-Math.min(...l)];let u=Yr.keypoints.map(p=>p.positionRaw[0]),d=Yr.keypoints.map(p=>p.positionRaw[1]);Yr.boxRaw=[Math.min(...u),Math.min(...d),Math.max(...u)-Math.min(...u),Math.max(...d)-Math.min(...d)];for(let[p,c]of Object.entries(yx)){let m=[];for(let f=0;f<c.length-1;f++){let g=Yr.keypoints.find(A=>A.part===c[f]),y=Yr.keypoints.find(A=>A.part===c[f+1]);g&&y&&g.score>(t.body.minConfidence||0)&&y.score>(t.body.minConfidence||0)&&m.push([g.position,y.position])}Yr.annotations[p]=m}a([Yr])}))}var D3e=["angry","disgust","fear","happy","sad","surprise","neutral"],Bn,s1=[],CT=0,TT=0,bx=Number.MAX_SAFE_INTEGER;async function NT(e){var t;return he.initial&&(Bn=null),Bn?e.debug&&se("cached model:",Bn.modelUrl):Bn=await Ge((t=e.face.emotion)==null?void 0:t.modelPath),Bn}async function vx(e,t,r,n){var i,o;if(!Bn)return[];let a=bx<(((i=t.face.emotion)==null?void 0:i.skipFrames)||0),s=(((o=t.face.emotion)==null?void 0:o.skipTime)||0)>oe()-TT;return t.skipAllowed&&s&&a&&CT===n&&s1[r]&&s1[r].length>0?(bx++,s1[r]):(bx=0,new Promise(async l=>{var d,h;let u=[];if((d=t.face.emotion)!=null&&d.enabled){let p={},c=Bn!=null&&Bn.inputs[0].shape?Bn.inputs[0].shape[2]:0;p.resize=Ie.resizeBilinear(e,[c,c],!1),p.channels=L(p.resize,Qe.rgb),p.grayscale=ke(p.channels,3,!0),p.grayscaleSub=ce(p.grayscale,Qe.tf05),p.grayscaleMul=L(p.grayscaleSub,Qe.tf2),p.emotion=Bn==null?void 0:Bn.execute(p.grayscaleMul),TT=oe();let m=await p.emotion.data();for(let f=0;f<m.length;f++)m[f]>(((h=t.face.emotion)==null?void 0:h.minConfidence)||0)&&u.push({score:Math.min(.99,Math.trunc(100*m[f])/100),emotion:D3e[f]});u.sort((f,g)=>g.score-f.score),Object.keys(p).forEach(f=>te(p[f]))}s1[r]=u,CT=n,l(u)}))}var xn,wx=[],RT=0,MT=0,$T=Number.MAX_SAFE_INTEGER;async function FT(e){return he.initial&&(xn=null),xn?e.debug&&se("cached model:",xn.modelUrl):xn=await Ge(e.face.mobilefacenet.modelPath),xn}async function kx(e,t,r,n){var i,o;if(!xn)return[];let a=$T<(((i=t.face.embedding)==null?void 0:i.skipFrames)||0),s=(((o=t.face.embedding)==null?void 0:o.skipTime)||0)>oe()-MT;return t.skipAllowed&&s&&a&&RT===n&&wx[r]?($T++,wx[r]):new Promise(async l=>{var d;let u=[];if(((d=t.face.embedding)==null?void 0:d.enabled)&&(xn==null?void 0:xn.inputs[0].shape)){let h={};h.crop=Ie.resizeBilinear(e,[xn.inputs[0].shape[2],xn.inputs[0].shape[1]],!1),h.data=xn==null?void 0:xn.execute(h.crop);let p=await h.data.data();u=Array.from(p)}wx[r]=u,RT=n,MT=oe(),l(u)})}var ds,Ji=0,L3e=2.3,Ix=ea.leftEyeLower0,Sx=ea.rightEyeLower0,Hd={leftBounds:[Ix[0],Ix[Ix.length-1]],rightBounds:[Sx[0],Sx[Sx.length-1]]},qd={upperCenter:3,lowerCenter:4,index:71,numCoordinates:76};async function DT(e){var t;return he.initial&&(ds=null),ds?e.debug&&se("cached model:",ds.modelUrl):ds=await Ge((t=e.face.iris)==null?void 0:t.modelPath),Ji=ds.inputs[0].shape?ds.inputs[0].shape[2]:0,Ji===-1&&(Ji=64),ds}function i1(e,t,r,n){for(let a=0;a<ax.length;a++){let{key:s,indices:i}=ax[a],o=ea[`${r}${s}`];if(!n||n.includes(s))for(let l=0;l<i.length;l++){let u=i[l];e[o[l]]=[t[u][0],t[u][1],(t[u][2]+e[o[l]][2])/2]}}}var B3e=e=>{let t=e[Hd.leftBounds[0]][2],r=e[Hd.rightBounds[0]][2];return t-r},PT=(e,t,r,n,a,s=!1)=>{let i=Jm(Ym(eT([e[r],e[n]]),L3e)),o=Vd(i),l=Ie.cropAndResize(t,[[i.startPoint[1]/a,i.startPoint[0]/a,i.endPoint[1]/a,i.endPoint[0]/a]],[0],[Ji,Ji]);if(s&&he.kernels.includes("flipleftright")){let u=Ie.flipLeftRight(l);te(l),l=u}return{box:i,boxSize:o,crop:l}},OT=(e,t,r,n=!1)=>{let a=[];for(let s=0;s<qd.numCoordinates;s++){let i=e[s*3],o=e[s*3+1],l=e[s*3+2];a.push([(n?1-i/Ji:i/Ji)*r[0]+t.startPoint[0],o/Ji*r[1]+t.startPoint[1],l])}return{rawCoords:a,iris:a.slice(qd.index)}},zT=(e,t,r)=>{let n=e[ea[`${r}EyeUpper0`][qd.upperCenter]][2],a=e[ea[`${r}EyeLower0`][qd.lowerCenter]][2],s=(n+a)/2;return t.map((i,o)=>{let l=s;return o===2?l=n:o===4&&(l=a),[i[0],i[1],l]})};async function LT(e,t,r,n){if(!ds)return r.debug&&se("face mesh iris detection requested, but model is not loaded"),e;let{box:a,boxSize:s,crop:i}=PT(e,t,Hd.leftBounds[0],Hd.leftBounds[1],n,!0),{box:o,boxSize:l,crop:u}=PT(e,t,Hd.rightBounds[0],Hd.rightBounds[1],n,!0),d=St([i,u]);te(i),te(u);let h=ds.execute(d);te(d);let p=await h.data();te(h);let c=p.slice(0,qd.numCoordinates*3),{rawCoords:m,iris:f}=OT(c,a,s,!0),g=p.slice(qd.numCoordinates*3),{rawCoords:y,iris:A}=OT(g,o,l,!1),x=B3e(e);Math.abs(x)<30?(i1(e,m,"left",null),i1(e,y,"right",null)):x<1?i1(e,m,"left",["EyeUpper0","EyeLower0"]):i1(e,y,"right",["EyeUpper0","EyeLower0"]);let b=zT(e,f,"left"),w=zT(e,A,"right");return e.concat(b).concat(w)}var W3e=[[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]],V3e=[[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]],U3e=[[276,283],[283,282],[282,295],[295,285],[300,293],[293,334],[334,296],[296,336]],G3e=[[474,475],[475,476],[476,477],[477,474]],j3e=[[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]],H3e=[[46,53],[53,52],[52,65],[65,55],[70,63],[63,105],[105,66],[66,107]],q3e=[[469,470],[470,471],[471,472],[472,469]],X3e=[[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 Qi(e){let t=e.map(r=>r[0]);return t.push(e[e.length-1][1]),t}var K3e={lips:Qi(W3e),leftEye:Qi(V3e),leftEyebrow:Qi(U3e),leftIris:Qi(G3e),rightEye:Qi(j3e),rightEyebrow:Qi(H3e),rightIris:Qi(q3e),faceOval:Qi(X3e)},Z3e=Object.entries(K3e).map(([e,t])=>t.map(r=>[r,e])).flat(),Hwe=new Map(Z3e),oc=[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],jl=[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];async function VT(e,t){let r={lips:t.filter(s=>s.size===160)[0].dataSync(),irisL:t.filter(s=>s.size===10)[0].dataSync(),eyeL:t.filter(s=>s.size===142)[0].dataSync(),irisR:t.filter(s=>s.size===10)[1].dataSync(),eyeR:t.filter(s=>s.size===142)[1].dataSync()},n=Gl.reduce((s,i)=>s+=e[i][2],0)/Gl.length;for(let s=0;s<r.irisL.length/2;s++)e.push([r.irisL[2*s+0],r.irisL[2*s+1],n]);let a=jl.reduce((s,i)=>s+=e[i][2],0)/jl.length;for(let s=0;s<r.irisR.length/2;s++)e.push([r.irisR[2*s+0],r.irisR[2*s+1],a]);for(let s=0;s<r.eyeL.length/2;s++)e[Gl[s]]=[r.eyeL[2*s+0],r.eyeL[2*s+1],e[Gl[s]][2]];for(let s=0;s<r.eyeR.length/2;s++)e[jl[s]]=[r.eyeR[2*s+0],r.eyeR[2*s+1],e[jl[s]][2]];for(let s=0;s<r.lips.length/2;s++)e[oc[s]]=[r.lips[2*s+0],r.lips[2*s+1],e[oc[s]][2]];return e}var Ba={boxes:[],skipped:Number.MAX_SAFE_INTEGER,timestamp:0},Mr=null,Hl=0;async function UT(e,t){var o,l,u,d,h,p,c,m,f,g,y;let r=(((o=t.face.detector)==null?void 0:o.skipTime)||0)>oe()-Ba.timestamp,n=Ba.skipped<(((l=t.face.detector)==null?void 0:l.skipFrames)||0);!t.skipAllowed||!r||!n||Ba.boxes.length===0?(Ba.boxes=await uT(e,t),Ba.timestamp=oe(),Ba.skipped=0):Ba.skipped++;let a=[],s=[],i=0;for(let A=0;A<Ba.boxes.length;A++){let x=Ba.boxes[A],b=0,w,I={id:i++,mesh:[],meshRaw:[],box:[0,0,0,0],boxRaw:[0,0,0,0],score:0,boxScore:0,faceScore:0,annotations:{}};if([b,w,I.tensor]=aT((u=t.face.detector)==null?void 0:u.rotation,x,e,(d=t.face.mesh)!=null&&d.enabled?Hl:Ud()),(h=t==null?void 0:t.filter)!=null&&h.equalization){let T=await Vm(I.tensor);te(I.tensor),I.tensor=T}if(I.boxScore=Math.round(100*x.confidence)/100,(p=t.face.mesh)!=null&&p.enabled)if(!Mr)t.debug&&se("face mesh detection requested, but model is not loaded");else{let T=Mr.execute(I.tensor),E=T.find(P=>P.shape[P.shape.length-1]===1),R=T.find(P=>P.shape[P.shape.length-1]===1404),O=E.dataSync();I.faceScore=Math.round(100*O[0])/100;let M=U(R,[-1,3]),S=await M.array();if(I.faceScore<(((c=t.face.detector)==null?void 0:c.minConfidence)||1)){if(x.confidence=I.faceScore,(m=t.face.mesh)!=null&&m.keepInvalid){I.box=Km(x,e),I.boxRaw=Zm(x,e),I.score=I.boxScore,I.mesh=x.landmarks.map(P=>[(x.startPoint[0]+x.endPoint[0])/2+(x.endPoint[0]+x.startPoint[0])*P[0]/Ud(),(x.startPoint[1]+x.endPoint[1])/2+(x.endPoint[1]+x.startPoint[1])*P[1]/Ud()]),I.meshRaw=I.mesh.map(P=>[P[0]/(e.shape[2]||0),P[1]/(e.shape[1]||0),(P[2]||0)/Hl]);for(let P of Object.keys(Bl))I.annotations[P]=[I.mesh[Bl[P]]]}}else{(f=t.face.attention)!=null&&f.enabled?S=await VT(S,T):(g=t.face.iris)!=null&&g.enabled&&(S=await LT(S,I.tensor,t,Hl)),I.mesh=nT(S,x,b,w,Hl),I.meshRaw=I.mesh.map(z=>[z[0]/(e.shape[2]||0),z[1]/(e.shape[1]||0),(z[2]||0)/Hl]);for(let z of Object.keys(ea))I.annotations[z]=ea[z].map(j=>I.mesh[j]);I.score=I.faceScore;let P={...sT(I.mesh,x),confidence:x.confidence,landmarks:x.landmarks};I.box=Km(P,e),I.boxRaw=Zm(P,e),s.push(P)}te([...T,M])}else{I.box=Km(x,e),I.boxRaw=Zm(x,e),I.score=I.boxScore,I.mesh=x.landmarks.map(T=>[(x.startPoint[0]+x.endPoint[0])/2+(x.endPoint[0]+x.startPoint[0])*T[0]/Ud(),(x.startPoint[1]+x.endPoint[1])/2+(x.endPoint[1]+x.startPoint[1])*T[1]/Ud()]),I.meshRaw=I.mesh.map(T=>[T[0]/(e.shape[2]||0),T[1]/(e.shape[1]||0),(T[2]||0)/Hl]);for(let T of Object.keys(Bl))I.annotations[T]=[I.mesh[Bl[T]]]}I.score>(((y=t.face.detector)==null?void 0:y.minConfidence)||1)?a.push(I):te(I.tensor)}return Ba.boxes=s,a}async function GT(e){var t,r,n,a,s,i;return he.initial&&(Mr=null),((r=(t=e==null?void 0:e.face)==null?void 0:t.attention)==null?void 0:r.enabled)&&(Mr==null?void 0:Mr.signature)&&Object.keys(((n=Mr==null?void 0:Mr.signature)==null?void 0:n.outputs)||{}).length<6&&(Mr=null),Mr?e.debug&&se("cached model:",Mr.modelUrl):(a=e.face.attention)!=null&&a.enabled?Mr=await 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n={};n.reshape=U(t,[-1,7,2]),n.div=pe(n.reshape,this.inputSizeTensor),n.landmarks=le(n.div,this.anchors[r]);let a=L(n.landmarks,this.inputSizeTensor);return Object.keys(n).forEach(s=>te(n[s])),a}async predict(t,r){let n={};n.resize=Ie.resizeBilinear(t,[this.inputSize,this.inputSize]),n.div=pe(n.resize,Qe.tf127),n.image=ce(n.div,Qe.tf1),n.batched=this.model.execute(n.image),n.predictions=et(n.batched),n.slice=_e(n.predictions,[0,0],[-1,1]),n.sigmoid=Cr(n.slice),n.scores=et(n.sigmoid);let a=await n.scores.data();n.boxes=_e(n.predictions,[0,1],[-1,4]),n.norm=this.normalizeBoxes(n.boxes),n.nms=await Ie.nonMaxSuppressionAsync(n.norm,n.scores,3*r.hand.maxDetected,r.hand.iouThreshold,r.hand.minConfidence);let s=await n.nms.array(),i=[];for(let o of s){let l={};l.box=_e(n.norm,[o,0],[1,-1]),l.slice=_e(n.predictions,[o,5],[1,14]),l.norm=this.normalizeLandmarks(l.slice,o),l.palmLandmarks=U(l.norm,[-1,2]);let u=await l.box.data(),d=u.slice(0,2),h=u.slice(2,4),p=await l.palmLandmarks.array(),c={startPoint:d,endPoint:h,palmLandmarks:p,confidence:a[o]},m=QT(c,[t.shape[2]/this.inputSize,t.shape[1]/this.inputSize]);i.push(m),Object.keys(l).forEach(f=>te(l[f]))}return Object.keys(n).forEach(o=>te(n[o])),i}};var r5e=5,aN=1.65,sN=[0,5,9,13,17,1,2],n5e=0,a5e=2,iN=0,h1=class{constructor(t,r){fe(this,"handDetector");fe(this,"handPoseModel");fe(this,"inputSize");fe(this,"storedBoxes");fe(this,"skipped");fe(this,"detectedHands");this.handDetector=t,this.handPoseModel=r,this.inputSize=this.handPoseModel&&this.handPoseModel.inputs[0].shape?this.handPoseModel.inputs[0].shape[2]:0,this.storedBoxes=[],this.skipped=Number.MAX_SAFE_INTEGER,this.detectedHands=0}calculateLandmarksBoundingBox(t){let r=t.map(i=>i[0]),n=t.map(i=>i[1]),a=[Math.min(...r),Math.min(...n)],s=[Math.max(...r),Math.max(...n)];return{startPoint:a,endPoint:s}}getBoxForPalmLandmarks(t,r){let n=t.map(s=>$x([...s,1],r)),a=this.calculateLandmarksBoundingBox(n);return u1(d1(a),r5e)}getBoxForHandLandmarks(t){let r=this.calculateLandmarksBoundingBox(t),n=u1(d1(r),aN);n.palmLandmarks=[];for(let a=0;a<sN.length;a++)n.palmLandmarks.push(t[sN[a]].slice(0,2));return n}transformRawCoords(t,r,n,a){let s=l1(r),i=[s[0]/this.inputSize,s[1]/this.inputSize,(s[0]+s[1])/this.inputSize/2],o=t.map(c=>[i[0]*(c[0]-this.inputSize/2),i[1]*(c[1]-this.inputSize/2),i[2]*c[2]]),l=Mx(n,[0,0]),u=o.map(c=>[...$x(c,l),c[2]]),d=tN(a),h=[...lc(r),1],p=[eo(h,d[0]),eo(h,d[1])];return u.map(c=>[Math.trunc(c[0]+p[0]),Math.trunc(c[1]+p[1]),Math.trunc(c[2])])}async estimateHands(t,r){let n=!1,a,s=(r.hand.skipTime||0)>oe()-iN,i=this.skipped<(r.hand.skipFrames||0);r.skipAllowed&&s&&i&&(a=await this.handDetector.predict(t,r),this.skipped=0),r.skipAllowed&&this.skipped++,a&&a.length>0&&(a.length!==this.detectedHands&&this.detectedHands!==r.hand.maxDetected||!r.hand.landmarks)&&(this.detectedHands=0,this.storedBoxes=[...a],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(r.hand.landmarks){let d=r.hand.rotation?eN(u.palmLandmarks[n5e],u.palmLandmarks[a5e]):0,h=lc(u),p=[h[0]/t.shape[2],h[1]/t.shape[1]],c=r.hand.rotation&&he.kernels.includes("rotatewithoffset")?Ie.rotateWithOffset(t,d,0,p):t.clone(),m=Mx(-d,h),f=n?this.getBoxForPalmLandmarks(u.palmLandmarks,m):u,g=JT(f,c,[this.inputSize,this.inputSize]),y=pe(g,Qe.tf255);te(g),te(c);let[A,x]=this.handPoseModel.execute(y);iN=oe(),te(y);let b=(await A.data())[0];if(te(A),b>=r.hand.minConfidence/4){let w=U(x,[-1,3]),I=await w.array();te(x),te(w);let T=this.transformRawCoords(I,f,d,m),E=this.getBoxForHandLandmarks(T);this.storedBoxes[l]={...E,confidence:b};let R={landmarks:T,confidence:b,boxConfidence:u.confidence,fingerConfidence:b,box:{topLeft:E.startPoint,bottomRight:E.endPoint}};o.push(R)}else this.storedBoxes[l]=null;te(x)}else{let d=u1(d1(u),aN),h={confidence:u.confidence,boxConfidence:u.confidence,fingerConfidence:0,box:{topLeft:d.startPoint,bottomRight:d.endPoint},landmarks:[]};o.push(h)}}return this.storedBoxes=this.storedBoxes.filter(l=>l!==null),this.detectedHands=o.length,o.length>r.hand.maxDetected&&(o.length=r.hand.maxDetected),o}};var Jr={thumb:0,index:1,middle:2,ring:3,pinky:4,all:[0,1,2,3,4],nameMapping:{0:"thumb",1:"index",2:"middle",3:"ring",4:"pinky"},pointsMapping:{0:[[0,1],[1,2],[2,3],[3,4]],1:[[0,5],[5,6],[6,7],[7,8]],2:[[0,9],[9,10],[10,11],[11,12]],3:[[0,13],[13,14],[14,15],[15,16]],4:[[0,17],[17,18],[18,19],[19,20]]},getName:e=>Jr.nameMapping[e],getPoints:e=>Jr.pointsMapping[e]},ro={none:0,half:1,full:2,nameMapping:{0:"none",1:"half",2:"full"},getName:e=>ro.nameMapping[e]},Bt={verticalUp:0,verticalDown:1,horizontalLeft:2,horizontalRight:3,diagonalUpRight:4,diagonalUpLeft:5,diagonalDownRight:6,diagonalDownLeft:7,nameMapping:{0:"verticalUp",1:"verticalDown",2:"horizontalLeft",3:"horizontalRight",4:"diagonalUpRight",5:"diagonalUpLeft",6:"diagonalDownRight",7:"diagonalDownLeft"},getName:e=>Bt.nameMapping[e]},to=class{constructor(t){fe(this,"name");fe(this,"curls");fe(this,"directions");fe(this,"weights");fe(this,"weightsRelative");this.name=t,this.curls={},this.directions={},this.weights=[1,1,1,1,1],this.weightsRelative=[1,1,1,1,1]}curl(t,r,n){typeof this.curls[t]=="undefined"&&(this.curls[t]=[]),this.curls[t].push([r,n])}direction(t,r,n){this.directions[t]||(this.directions[t]=[]),this.directions[t].push([r,n])}weight(t,r){this.weights[t]=r;let n=this.weights.reduce((a,s)=>a+s,0);this.weightsRelative=this.weights.map(a=>a*5/n)}matchAgainst(t,r){let n=0;for(let a in t){let s=t[a],i=this.curls[a];if(typeof i=="undefined"){n+=this.weightsRelative[a];continue}for(let[o,l]of i)if(s===o){n+=l*this.weightsRelative[a];break}}for(let a in r){let s=r[a],i=this.directions[a];if(typeof i=="undefined"){n+=this.weightsRelative[a];continue}for(let[o,l]of i)if(s===o){n+=l*this.weightsRelative[a];break}}return n/10}};var{thumb:wa,index:ps,middle:hs,ring:ql,pinky:Xl}=Jr,{none:ka,half:i5e,full:Ia}=ro,{verticalUp:Xd,verticalDown:o8e,horizontalLeft:Fx,horizontalRight:o5e,diagonalUpRight:l5e,diagonalUpLeft:Kd,diagonalDownRight:l8e,diagonalDownLeft:u8e}=Bt,no=new to("thumbs up");no.curl(wa,ka,1);no.direction(wa,Xd,1);no.direction(wa,Kd,.25);no.direction(wa,l5e,.25);for(let e of[Jr.index,Jr.middle,Jr.ring,Jr.pinky])no.curl(e,Ia,1),no.direction(e,Fx,1),no.direction(e,o5e,1);var tr=new to("victory");tr.curl(wa,i5e,.5);tr.curl(wa,ka,.5);tr.direction(wa,Xd,1);tr.direction(wa,Kd,1);tr.curl(ps,ka,1);tr.direction(ps,Xd,.75);tr.direction(ps,Kd,1);tr.curl(hs,ka,1);tr.direction(hs,Xd,1);tr.direction(hs,Kd,.75);tr.curl(ql,Ia,1);tr.direction(ql,Xd,.2);tr.direction(ql,Kd,1);tr.direction(ql,Fx,.2);tr.curl(Xl,Ia,1);tr.direction(Xl,Xd,.2);tr.direction(Xl,Kd,1);tr.direction(Xl,Fx,.2);tr.weight(ps,2);tr.weight(hs,2);var ao=new to("point");ao.curl(wa,Ia,1);ao.curl(ps,ka,.5);ao.curl(hs,Ia,.5);ao.curl(ql,Ia,.5);ao.curl(Xl,Ia,.5);ao.weight(ps,2);ao.weight(hs,2);var so=new to("middle finger");so.curl(wa,ka,1);so.curl(ps,Ia,.5);so.curl(hs,Ia,.5);so.curl(ql,Ia,.5);so.curl(Xl,Ia,.5);so.weight(ps,2);so.weight(hs,2);var Zd=new to("open palm");Zd.curl(wa,ka,.75);Zd.curl(ps,ka,.75);Zd.curl(hs,ka,.75);Zd.curl(ql,ka,.75);Zd.curl(Xl,ka,.75);var oN=[no,tr,ao,so,Zd];var u5e=.7,Kl={HALF_CURL_START_LIMIT:60,NO_CURL_START_LIMIT:130,DISTANCE_VOTE_POWER:1.1,SINGLE_ANGLE_VOTE_POWER:.9,TOTAL_ANGLE_VOTE_POWER:1.6};function lN(e,t,r,n){let a=(t-n)/(e-r),s=Math.atan(a)*180/Math.PI;return s<=0?s=-s:s>0&&(s=180-s),s}function dN(e,t){if(!e||!t)return[0,0];let r=lN(e[0],e[1],t[0],t[1]);if(e.length===2)return r;let n=lN(e[1],e[2],t[1],t[2]);return[r,n]}function uN(e,t=1){let r=0,n=0,a=0;return e>=75&&e<=105?r=1*t:e>=25&&e<=155?n=1*t:a=1*t,[r,n,a]}function d5e(e,t,r){let n=e[0]-t[0],a=e[0]-r[0],s=t[0]-r[0],i=e[1]-t[1],o=e[1]-r[1],l=t[1]-r[1],u=e[2]-t[2],d=e[2]-r[2],h=t[2]-r[2],p=Math.sqrt(n*n+i*i+u*u),c=Math.sqrt(a*a+o*o+d*d),m=Math.sqrt(s*s+l*l+h*h),f=(m*m+p*p-c*c)/(2*m*p);f>1?f=1:f<-1&&(f=-1);let g=Math.acos(f);g=57.2958*g%180;let y;return g>Kl.NO_CURL_START_LIMIT?y=ro.none:g>Kl.HALF_CURL_START_LIMIT?y=ro.half:y=ro.full,y}function pN(e,t,r,n){let a;return n===Math.abs(e)?e>0?a=Bt.horizontalLeft:a=Bt.horizontalRight:n===Math.abs(t)?t>0?a=Bt.horizontalLeft:a=Bt.horizontalRight:r>0?a=Bt.horizontalLeft:a=Bt.horizontalRight,a}function hN(e,t,r,n){let a;return n===Math.abs(e)?e<0?a=Bt.verticalDown:a=Bt.verticalUp:n===Math.abs(t)?t<0?a=Bt.verticalDown:a=Bt.verticalUp:r<0?a=Bt.verticalDown:a=Bt.verticalUp,a}function p5e(e,t,r,n,a,s,i,o){let l,u=hN(e,t,r,n),d=pN(a,s,i,o);return u===Bt.verticalUp?d===Bt.horizontalLeft?l=Bt.diagonalUpLeft:l=Bt.diagonalUpRight:d===Bt.horizontalLeft?l=Bt.diagonalDownLeft:l=Bt.diagonalDownRight,l}function h5e(e,t,r,n){let a=e[0]-t[0],s=e[0]-r[0],i=t[0]-r[0],o=e[1]-t[1],l=e[1]-r[1],u=t[1]-r[1],d=Math.max(Math.abs(a),Math.abs(s),Math.abs(i)),h=Math.max(Math.abs(o),Math.abs(l),Math.abs(u)),p=0,c=0,m=0,f=h/(d+1e-5);f>1.5?p+=Kl.DISTANCE_VOTE_POWER:f>.66?c+=Kl.DISTANCE_VOTE_POWER:m+=Kl.DISTANCE_VOTE_POWER;let g=Math.sqrt(a*a+o*o),y=Math.sqrt(s*s+l*l),A=Math.sqrt(i*i+u*u),x=Math.max(g,y,A),b=e[0],w=e[1],I=r[0],T=r[1];x===g?(I=r[0],T=r[1]):x===A&&(b=t[0],w=t[1]);let O=dN([b,w],[I,T]),M=uN(O,Kl.TOTAL_ANGLE_VOTE_POWER);p+=M[0],c+=M[1],m+=M[2];for(let P of n){let z=uN(P,Kl.SINGLE_ANGLE_VOTE_POWER);p+=z[0],c+=z[1],m+=z[2]}let S;return p===Math.max(p,c,m)?S=hN(l,o,u,h):m===Math.max(c,m)?S=pN(s,a,i,d):S=p5e(l,o,u,h,s,a,i,d),S}function cN(e){let t=[],r=[],n=[],a=[];if(!e)return{curls:n,directions:a};for(let s of Jr.all){let i=Jr.getPoints(s),o=[],l=[];for(let u of i){let d=e[u[0]],h=e[u[1]],p=dN(d,h),c=p[0],m=p[1];o.push(c),l.push(m)}t.push(o),r.push(l)}for(let s of Jr.all){let i=s===Jr.thumb?1:0,o=Jr.getPoints(s),l=e[o[i][0]],u=e[o[i+1][1]],d=e[o[3][1]],h=d5e(l,u,d),p=h5e(l,u,d,t[s].slice(i));n[s]=h,a[s]=p}return{curls:n,directions:a}}function c1(e){if(!e||e.length===0)return null;let t=cN(e),r={};for(let n of Jr.all)r[Jr.getName(n)]={curl:ro.getName(t.curls[n]),direction:Bt.getName(t.directions[n])};return r}function fN(e){let t=[];if(!e||e.length===0)return t;let r=cN(e);for(let n of oN){let a=n.matchAgainst(r.curls,r.directions);a>=u5e&&t.push({name:n.name,confidence:a})}return t}var mN={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]},Yd,Jd,gN;async function Px(e,t){let r=await gN.estimateHands(e,t);if(!r)return[];let n=[];for(let a=0;a<r.length;a++){let s={};if(r[a].landmarks)for(let d of Object.keys(mN))s[d]=mN[d].map(h=>r[a].landmarks[h]);let i=r[a].landmarks,o=[Number.MAX_SAFE_INTEGER,Number.MAX_SAFE_INTEGER,0,0],l=[0,0,0,0];if(i&&i.length>0){for(let d of i)d[0]<o[0]&&(o[0]=d[0]),d[1]<o[1]&&(o[1]=d[1]),d[0]>o[2]&&(o[2]=d[0]),d[1]>o[3]&&(o[3]=d[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=r[a].box?[Math.trunc(Math.max(0,r[a].box.topLeft[0])),Math.trunc(Math.max(0,r[a].box.topLeft[1])),Math.trunc(Math.min(e.shape[2]||0,r[a].box.bottomRight[0])-Math.max(0,r[a].box.topLeft[0])),Math.trunc(Math.min(e.shape[1]||0,r[a].box.bottomRight[1])-Math.max(0,r[a].box.topLeft[1]))]:[0,0,0,0],l=[r[a].box.topLeft[0]/(e.shape[2]||0),r[a].box.topLeft[1]/(e.shape[1]||0),(r[a].box.bottomRight[0]-r[a].box.topLeft[0])/(e.shape[2]||0),(r[a].box.bottomRight[1]-r[a].box.topLeft[1])/(e.shape[1]||0)];let u=c1(i);n.push({id:a,score:Math.round(100*r[a].confidence)/100,boxScore:Math.round(100*r[a].boxConfidence)/100,fingerScore:Math.round(100*r[a].fingerConfidence)/100,label:"hand",box:o,boxRaw:l,keypoints:i,annotations:s,landmarks:u})}return n}async function Ox(e){var r,n;he.initial&&(Yd=null,Jd=null),!Yd||!Jd?[Yd,Jd]=await Promise.all([e.hand.enabled?Ge((r=e.hand.detector)==null?void 0:r.modelPath):null,e.hand.landmarks?Ge((n=e.hand.skeleton)==null?void 0:n.modelPath):null]):(e.debug&&se("cached model:",Yd.modelUrl),e.debug&&se("cached model:",Jd.modelUrl));let t=new p1(Yd);return gN=new h1(t,Jd),[Yd,Jd]}var pr=[null,null],c5e=["StatefulPartitionedCall/Postprocessor/Slice","StatefulPartitionedCall/Postprocessor/ExpandDims_1"],io=[[0,0],[0,0]],f5e=["hand","fist","pinch","point","face","tip","pinchtip"],AN=4,xN=1.6,m5e=512,g5e=1.4,f1=Number.MAX_SAFE_INTEGER,zx=0,cs=[0,0],Ht={boxes:[],hands:[]},bN={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 vN(e){var t;if(he.initial&&(pr[0]=null),pr[0])e.debug&&se("cached model:",pr[0].modelUrl);else{m1(["tensorlistreserve","enter","tensorlistfromtensor","merge","loopcond","switch","exit","tensorliststack","nextiteration","tensorlistsetitem","tensorlistgetitem","reciprocal","shape","split","where"],e),pr[0]=await Ge((t=e.hand.detector)==null?void 0:t.modelPath);let r=Object.values(pr[0].modelSignature.inputs);io[0][0]=Array.isArray(r)?parseInt(r[0].tensorShape.dim[1].size):0,io[0][1]=Array.isArray(r)?parseInt(r[0].tensorShape.dim[2].size):0}return pr[0]}async function wN(e){var t;if(he.initial&&(pr[1]=null),pr[1])e.debug&&se("cached model:",pr[1].modelUrl);else{pr[1]=await Ge((t=e.hand.skeleton)==null?void 0:t.modelPath);let r=Object.values(pr[1].modelSignature.inputs);io[1][0]=Array.isArray(r)?parseInt(r[0].tensorShape.dim[1].size):0,io[1][1]=Array.isArray(r)?parseInt(r[0].tensorShape.dim[2].size):0}return pr[1]}async function y5e(e,t){let r=[];if(!e||!pr[0])return r;let n={},a=(e.shape[2]||1)/(e.shape[1]||1),s=Math.min(Math.round((e.shape[1]||0)/8)*8,m5e),i=Math.round(s*a/8)*8;n.resize=Ie.resizeBilinear(e,[s,i]),n.cast=me(n.resize,"int32"),[n.rawScores,n.rawBoxes]=await pr[0].executeAsync(n.cast,c5e),n.boxes=et(n.rawBoxes,[0,2]),n.scores=et(n.rawScores,[0]);let o=an(n.scores,1);te(o[AN]),o.splice(AN,1),n.filtered=ur(o,1),te(o),n.max=yr(n.filtered,1),n.argmax=Rn(n.filtered,1);let l=0;n.nms=await Ie.nonMaxSuppressionAsync(n.boxes,n.max,(t.hand.maxDetected||0)+1,t.hand.iouThreshold||0,t.hand.minConfidence||1);let u=await n.nms.data(),d=await n.max.data(),h=await n.argmax.data();for(let p of Array.from(u)){let c=_e(n.boxes,p,1),m=await c.data();te(c);let f=[m[1],m[0],m[3]-m[1],m[2]-m[0]],g=t1(f,g5e),y=[Math.trunc(f[0]*cs[0]),Math.trunc(f[1]*cs[1]),Math.trunc(f[2]*cs[0]),Math.trunc(f[3]*cs[1])],A=d[p],x=f5e[h[p]],b={id:l++,score:A,box:y,boxRaw:g,label:x};r.push(b)}return Object.keys(n).forEach(p=>te(n[p])),r.sort((p,c)=>c.score-p.score),r.length>(t.hand.maxDetected||1)&&(r.length=t.hand.maxDetected||1),r}async function Dx(e,t,r){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&&pr[1]&&r.hand.landmarks&&t.score>(r.hand.minConfidence||0)){let a={},s=[t.boxRaw[1],t.boxRaw[0],t.boxRaw[3]+t.boxRaw[1],t.boxRaw[2]+t.boxRaw[0]];a.crop=Ie.cropAndResize(e,[s],[0],[io[1][0],io[1][1]],"bilinear"),a.div=pe(a.crop,Qe.tf255),[a.score,a.keypoints]=pr[1].execute(a.div,["Identity_1","Identity"]);let i=(await a.score.data())[0],o=(100-Math.trunc(100/(1+Math.exp(i))))/100;if(o>=(r.hand.minConfidence||0)){n.fingerScore=o,a.reshaped=U(a.keypoints,[-1,3]);let d=(await a.reshaped.array()).map(h=>[h[0]/io[1][1],h[1]/io[1][0],h[2]||0]).map(h=>[h[0]*t.boxRaw[2],h[1]*t.boxRaw[3],h[2]||0]);n.keypoints=d.map(h=>[cs[0]*(h[0]+t.boxRaw[0]),cs[1]*(h[1]+t.boxRaw[1]),h[2]||0]),n.landmarks=c1(n.keypoints);for(let h of Object.keys(bN))n.annotations[h]=bN[h].map(p=>n.landmarks&&n.keypoints[p]?n.keypoints[p]:null)}Object.keys(a).forEach(l=>te(a[l]))}return n}async function Lx(e,t){var a,s;if(!pr[0]||!pr[1]||!((a=pr[0])!=null&&a.inputs[0].shape)||!((s=pr[1])!=null&&s.inputs[0].shape))return[];cs=[e.shape[2]||0,e.shape[1]||0],f1++;let r=(t.hand.skipTime||0)>oe()-zx,n=f1<(t.hand.skipFrames||0);return t.skipAllowed&&r&&n?Ht.hands:new Promise(async i=>{let o=3*(t.hand.skipTime||0)>oe()-zx,l=f1<3*(t.hand.skipFrames||0);t.skipAllowed&&Ht.hands.length===t.hand.maxDetected?Ht.hands=await Promise.all(Ht.boxes.map(d=>Dx(e,d,t))):t.skipAllowed&&o&&l&&Ht.hands.length>0?Ht.hands=await Promise.all(Ht.boxes.map(d=>Dx(e,d,t))):(Ht.boxes=await y5e(e,t),zx=oe(),Ht.hands=await Promise.all(Ht.boxes.map(d=>Dx(e,d,t))),f1=0);let u=[...Ht.boxes];if(Ht.boxes.length=0,t.cacheSensitivity>0)for(let d=0;d<Ht.hands.length;d++){let h=cT(Ht.hands[d].keypoints,cs);if(h.box[2]/(e.shape[2]||1)>.05&&h.box[3]/(e.shape[1]||1)>.05&&Ht.hands[d].fingerScore&&Ht.hands[d].fingerScore>(t.hand.minConfidence||0)){let p=t1(h.box,xN),c=t1(h.boxRaw,xN);Ht.boxes.push({...u[d],box:p,boxRaw:c})}}for(let d=0;d<Ht.hands.length;d++){let h=ls(Ht.hands[d].keypoints,cs);Ht.hands[d].box=h.box,Ht.hands[d].boxRaw=h.boxRaw}i(Ht.hands)})}var $r,g1=[],Bx=Number.MAX_SAFE_INTEGER,IN=0,SN=0;async function CN(e){var t;return he.initial&&($r=null),$r?e.debug&&se("cached model:",$r.modelUrl):$r=await Ge((t=e.face.liveness)==null?void 0:t.modelPath),$r}async function Wx(e,t,r,n){var i,o;if(!$r)return 0;let a=(((i=t.face.liveness)==null?void 0:i.skipTime)||0)>oe()-SN,s=Bx<(((o=t.face.liveness)==null?void 0:o.skipFrames)||0);return t.skipAllowed&&a&&s&&IN===n&&g1[r]?(Bx++,g1[r]):(Bx=0,new Promise(async l=>{let u=Ie.resizeBilinear(e,[$r!=null&&$r.inputs[0].shape?$r.inputs[0].shape[2]:0,$r!=null&&$r.inputs[0].shape?$r.inputs[0].shape[1]:0],!1),d=$r==null?void 0:$r.execute(u),h=(await d.data())[0];g1[r]=Math.round(100*h)/100,IN=n,SN=oe(),te([u,d]),l(g1[r])}))}var uc={};vs(uc,{connected:()=>A1,horizontal:()=>Vx,kpt:()=>y1,relative:()=>Gx,vertical:()=>Ux});var y1=["nose","leftEye","rightEye","leftEar","rightEar","leftShoulder","rightShoulder","leftElbow","rightElbow","leftWrist","rightWrist","leftHip","rightHip","leftKnee","rightKnee","leftAnkle","rightAnkle"],Vx=[["leftEye","rightEye"],["leftEar","rightEar"],["leftShoulder","rightShoulder"],["leftElbow","rightElbow"],["leftWrist","rightWrist"],["leftHip","rightHip"],["leftKnee","rightKnee"],["leftAnkle","rightAnkle"]],Ux=[["leftKnee","leftShoulder"],["rightKnee","rightShoulder"],["leftAnkle","leftKnee"],["rightAnkle","rightKnee"]],Gx=[[["leftHip","rightHip"],["leftShoulder","rightShoulder"]],[["leftElbow","rightElbow"],["leftShoulder","rightShoulder"]]],A1={leftLeg:["leftHip","leftKnee","leftAnkle"],rightLeg:["rightHip","rightKnee","rightAnkle"],torso:["leftShoulder","rightShoulder","rightHip","leftHip","leftShoulder"],leftArm:["leftShoulder","leftElbow","leftWrist"],rightArm:["rightShoulder","rightElbow","rightWrist"],head:[]};var NN=.005,vn={keypoints:[],padding:[[0,0],[0,0],[0,0],[0,0]]};function jx(e){for(let t of Vx){let r=e.keypoints.findIndex(a=>a.part===t[0]),n=e.keypoints.findIndex(a=>a.part===t[1]);if(e.keypoints[r]&&e.keypoints[n]&&e.keypoints[r].position[0]<e.keypoints[n].position[0]){let a=e.keypoints[r];e.keypoints[r]=e.keypoints[n],e.keypoints[n]=a}}for(let t of Ux){let r=e.keypoints.findIndex(a=>a&&a.part===t[0]),n=e.keypoints.findIndex(a=>a&&a.part===t[1]);e.keypoints[r]&&e.keypoints[n]&&e.keypoints[r].position[1]<e.keypoints[n].position[1]&&e.keypoints.splice(r,1)}for(let[t,r]of Gx){let n=e.keypoints.findIndex(u=>u&&u.part===t[0]),a=e.keypoints.findIndex(u=>u&&u.part===t[1]),s=e.keypoints.findIndex(u=>u&&u.part===r[0]),i=e.keypoints.findIndex(u=>u&&u.part===r[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[a]?[Math.abs(e.keypoints[i].position[0]-e.keypoints[a].position[0]),Math.abs(e.keypoints[s].position[0]-e.keypoints[a].position[0])]:[0,0];if(o[0]>o[1]||l[0]>l[1]){let u=e.keypoints[n];e.keypoints[n]=e.keypoints[a],e.keypoints[a]=u}}}function EN(e){for(let t=0;t<e.length;t++)if(e[t]&&vn.keypoints[t]){let r=[Math.abs(e[t].positionRaw[0]-vn.keypoints[t].positionRaw[0]),Math.abs(e[t].positionRaw[1]-vn.keypoints[t].positionRaw[1])];r[0]<NN&&r[1]<NN?e[t]=vn.keypoints[t]:vn.keypoints[t]=e[t]}else vn.keypoints[t]=e[t];return e}function RN(e,t){let r={};if(!e.shape||!e.shape[1]||!e.shape[2])return 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p=s[3*h+2];if(p>t.body.minConfidence){let c=[s[3*h+1],s[3*h+0]];o.push({part:y1[h],score:Math.round(100*p)/100,positionRaw:c,position:[Math.round((r.shape[2]||0)*c[0]),Math.round((r.shape[1]||0)*c[1])]})}}let l=ls(o.map(h=>h.position),[r.shape[2],r.shape[1]]),u={};for(let[h,p]of Object.entries(A1)){let c=[];for(let m=0;m<p.length-1;m++){let f=o.find(y=>y.part===p[m]),g=o.find(y=>y.part===p[m+1]);f&&g&&f.score>(t.body.minConfidence||0)&&g.score>(t.body.minConfidence||0)&&c.push([f.position,g.position])}u[h]=c}let d={id:a,score:i,box:l.box,boxRaw:l.boxRaw,keypoints:[...o],annotations:u};jx(d),n.push(d)}}return n.sort((a,s)=>s.score-a.score),n.length>t.body.maxDetected&&(n.length=t.body.maxDetected),n}async function qx(e,t){if(!wn||!(wn!=null&&wn.inputs[0].shape))return[];t.skipAllowed||(Zl.boxes.length=0),Hx++;let r=(t.body.skipTime||0)>oe()-Zl.last,n=Hx<(t.body.skipFrames||0);return t.skipAllowed&&r&&n?Zl.bodies:new Promise(async a=>{let s={};Hx=0,s.input=RN(e,x1),s.res=wn==null?void 0:wn.execute(s.input),Zl.last=oe();let i=await s.res.array();Zl.bodies=s.res.shape[2]===17?await x5e(i,t,e):await b5e(i,t,e);for(let o of Zl.bodies)MN(o,[e.shape[2]||1,e.shape[1]||1]),EN(o.keypoints);Object.keys(s).forEach(o=>te(s[o])),a(Zl.bodies)})}var Qd,b1=[],_N=0,Xx=Number.MAX_SAFE_INTEGER,w1=0,v1=2.5;async function PN(e){if(!Qd||he.initial){Qd=await Ge(e.object.modelPath);let t=Object.values(Qd.modelSignature.inputs);w1=Array.isArray(t)?parseInt(t[0].tensorShape.dim[2].size):0}else e.debug&&se("cached model:",Qd.modelUrl);return Qd}async function v5e(e,t,r){let n=0,a=[];for(let l of[1,2,4])X(async()=>{let u=l*13,d=et(e.find(f=>f.shape[1]===u**2&&(f.shape[2]||0)===jd.length)),h=et(e.find(f=>f.shape[1]===u**2&&(f.shape[2]||0)<jd.length)),c=await h.reshape([-1,4,h.shape[1]/4]).argMax(2).array(),m=await d.array();for(let f=0;f<d.shape[0];f++)for(let g=0;g<d.shape[1];g++){let y=m[f][g];if(y>(r.object.minConfidence||0)&&g!==61){let A=(.5+Math.trunc(f%u))/u,x=(.5+Math.trunc(f/u))/u,b=c[f].map(S=>S*(u/l/w1)),[w,I]=[A-v1/l*b[0],x-v1/l*b[1]],[T,E]=[A+v1/l*b[2]-w,x+v1/l*b[3]-I],R=[w,I,T,E];R=R.map(S=>Math.max(0,Math.min(S,1)));let O=[R[0]*t[0],R[1]*t[1],R[2]*t[0],R[3]*t[1]],M={id:n++,score:Math.round(100*y)/100,class:g+1,label:jd[g].label,box:O.map(S=>Math.trunc(S)),boxRaw:R};a.push(M)}}});e.forEach(l=>te(l));let s=a.map(l=>[l.boxRaw[1],l.boxRaw[0],l.boxRaw[3],l.boxRaw[2]]),i=a.map(l=>l.score),o=[];if(s&&s.length>0){let l=await Ie.nonMaxSuppressionAsync(s,i,r.object.maxDetected,r.object.iouThreshold,r.object.minConfidence);o=await l.data(),te(l)}return a=a.filter((l,u)=>o.includes(u)).sort((l,u)=>u.score-l.score),a}async function Kx(e,t){let r=(t.object.skipTime||0)>oe()-_N,n=Xx<(t.object.skipFrames||0);return t.skipAllowed&&r&&n&&b1.length>0?(Xx++,b1):(Xx=0,!he.kernels.includes("mod")||!he.kernels.includes("sparsetodense")?b1:new Promise(async a=>{let 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r=Math.abs(e.annotations.leftEyeIris[3][0]-e.annotations.leftEyeIris[1][0])/2,n=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],r,n,0,0,2*Math.PI),t.stroke(),dt.fillPolygons&&(t.fillStyle=dt.useDepth?"rgba(255, 255, 200, 0.3)":dt.color,t.fill())}if(e.annotations&&e.annotations.rightEyeIris&&e.annotations.rightEyeIris[0]){t.strokeStyle=dt.useDepth?"rgba(255, 200, 255, 0.3)":dt.color,t.beginPath();let r=Math.abs(e.annotations.rightEyeIris[3][0]-e.annotations.rightEyeIris[1][0])/2,n=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],r,n,0,0,2*Math.PI),t.stroke(),dt.fillPolygons&&(t.fillStyle=dt.useDepth?"rgba(255, 255, 200, 0.3)":dt.color,t.fill())}}function z5e(e,t){var r;if(dt.drawGaze&&((r=e.rotation)==null?void 0:r.angle)&&typeof Path2D!="undefined"){t.strokeStyle="pink";let n=e.box[0]+e.box[2]/2-e.box[3]*Yl(e.rotation.angle.yaw)/90,a=e.box[1]+e.box[3]/2+e.box[2]*Yl(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]},
${e.box[0]+e.box[2]/2} ${e.box[1]+e.box[3]}
`),i=new Path2D(`
M ${e.box[0]} ${e.box[1]+e.box[3]/2}
C
${e.box[0]} ${a},
${e.box[0]+e.box[2]} ${a},
${e.box[0]+e.box[2]} ${e.box[1]+e.box[3]/2}
`);t.stroke(i),t.stroke(s)}}function D5e(e,t){var r,n,a,s;if(dt.drawGaze&&((n=(r=e.rotation)==null?void 0:r.gaze)==null?void 0:n.strength)&&((s=(a=e.rotation)==null?void 0:a.gaze)==null?void 0:s.bearing)&&e.annotations.leftEyeIris&&e.annotations.rightEyeIris&&e.annotations.leftEyeIris[0]&&e.annotations.rightEyeIris[0]){t.strokeStyle="pink",t.fillStyle="pink";let i=[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]];ib(t,[e.annotations.leftEyeIris[0][0],e.annotations.leftEyeIris[0][1]],[i[0],i[1]],4);let o=[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]];ib(t,[e.annotations.rightEyeIris[0][0],e.annotations.rightEyeIris[0][1]],[o[0],o[1]],4)}}function L5e(e,t){if(dt.drawPolygons&&e.mesh.length>=468){t.lineWidth=1;for(let r=0;r<Wl.length/3;r++){let n=[Wl[r*3+0],Wl[r*3+1],Wl[r*3+2]].map(a=>e.mesh[a]);sb(t,n,dt)}O5e(e,t)}}function B5e(e,t){if(dt.drawPoints&&e.mesh.length>=468)for(let r=0;r<e.mesh.length;r++)ms(t,e.mesh[r][0],e.mesh[r][1],e.mesh[r][2],dt),dt.drawAttention&&(oc.includes(r)&&ms(t,e.mesh[r][0],e.mesh[r][1],e.mesh[r][2]+127,dt),Gl.includes(r)&&ms(t,e.mesh[r][0],e.mesh[r][1],e.mesh[r][2]-127,dt),jl.includes(r)&&ms(t,e.mesh[r][0],e.mesh[r][1],e.mesh[r][2]-127,dt))}function W5e(e,t){dt.drawBoxes&&Va(t,e.box[0],e.box[1],e.box[2],e.box[3],dt)}async function tp(e,t,r){if(dt=Gt(Fr,r),!t||!e)return;let n=Wn(e);if(!!n){n.font=dt.font,n.strokeStyle=dt.color,n.fillStyle=dt.color;for(let a of t)W5e(a,n),P5e(a,n),a.mesh&&a.mesh.length>0&&(B5e(a,n),L5e(a,n),z5e(a,n),D5e(a,n))}}async function rp(e,t,r){var s;let n=Gt(Fr,r);if(!t||!e)return;let a=Wn(e);if(!!a){a.lineJoin="round";for(let i=0;i<t.length;i++){if(a.strokeStyle=n.color,a.fillStyle=n.color,a.lineWidth=n.lineWidth,a.font=n.font,n.drawBoxes&&t[i].box&&((s=t[i].box)==null?void 0:s.length)===4&&(Va(a,t[i].box[0],t[i].box[1],t[i].box[2],t[i].box[3],n),n.drawLabels&&(n.shadowColor&&n.shadowColor!==""&&(a.fillStyle=n.shadowColor,a.fillText(`body ${100*t[i].score}%`,t[i].box[0]+3,1+t[i].box[1]+n.lineHeight,t[i].box[2])),a.fillStyle=n.labelColor,a.fillText(`body ${100*t[i].score}%`,t[i].box[0]+2,0+t[i].box[1]+n.lineHeight,t[i].box[2]))),n.drawPoints&&t[i].keypoints)for(let o=0;o<t[i].keypoints.length;o++)!t[i].keypoints[o].score||t[i].keypoints[o].score===0||(a.fillStyle=fs(t[i].keypoints[o].position[2],n),ms(a,t[i].keypoints[o].position[0],t[i].keypoints[o].position[1],0,n));if(n.drawLabels&&t[i].keypoints){a.font=n.font;for(let o of t[i].keypoints)!o.score||o.score===0||(a.fillStyle=fs(o.position[2],n),a.fillText(`${o.part} ${Math.trunc(100*o.score)}%`,o.position[0]+4,o.position[1]+4))}if(n.drawPolygons&&t[i].keypoints&&t[i].annotations)for(let o of Object.values(t[i].annotations))for(let l of o)KN(a,l,n)}}}async function np(e,t,r){let n=Gt(Fr,r);if(!t||!e)return;let a=Wn(e);if(!!a){a.lineJoin="round",a.font=n.font;for(let s of t){if(n.drawBoxes&&(a.strokeStyle=n.color,a.fillStyle=n.color,Va(a,s.box[0],s.box[1],s.box[2],s.box[3],n),n.drawLabels&&(n.shadowColor&&n.shadowColor!==""&&(a.fillStyle=n.shadowColor,a.fillText(`hand:${Math.trunc(100*s.score)}%`,s.box[0]+3,1+s.box[1]+n.lineHeight,s.box[2])),a.fillStyle=n.labelColor,a.fillText(`hand:${Math.trunc(100*s.score)}%`,s.box[0]+2,0+s.box[1]+n.lineHeight,s.box[2])),a.stroke()),n.drawPoints&&s.keypoints&&s.keypoints.length>0)for(let i of s.keypoints)a.fillStyle=fs(i[2],n),ms(a,i[0],i[1],0,n);if(n.drawLabels&&s.annotations){let i=(o,l)=>{if(!o||o.length===0||!o[0])return;let u=o[o.length-1][2]||-256;a.fillStyle=fs(u,n),a.fillText(l,o[o.length-1][0]+4,o[o.length-1][1]+4)};a.font=n.font,i(s.annotations.index,"index"),i(s.annotations.middle,"middle"),i(s.annotations.ring,"ring"),i(s.annotations.pinky,"pinky"),i(s.annotations.thumb,"thumb"),i(s.annotations.palm,"palm")}if(n.drawPolygons&&s.annotations){let i=o=>{if(!(!o||o.length===0||!o[0]))for(let l=0;l<o.length;l++){a.beginPath();let u=o[l][2]||0;a.strokeStyle=fs(l*u,n),a.moveTo(o[l>0?l-1:0][0],o[l>0?l-1:0][1]),a.lineTo(o[l][0],o[l][1]),a.stroke()}};a.lineWidth=n.lineWidth,i(s.annotations.index),i(s.annotations.middle),i(s.annotations.ring),i(s.annotations.pinky),i(s.annotations.thumb)}}}}async function ap(e,t,r){let n=Gt(Fr,r);if(!t||!e)return;let a=Wn(e);if(!!a){a.lineJoin="round",a.font=n.font;for(let s of t)if(n.drawBoxes){if(a.strokeStyle=n.color,a.fillStyle=n.color,Va(a,s.box[0],s.box[1],s.box[2],s.box[3],n),n.drawLabels){let i=`${s.label} 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ea.silhouette)a.push({x:(e.mesh[i][0]-e.box[0])/e.box[2],y:(e.mesh[i][1]-e.box[1])/e.box[3]});ip&&ip>0&&(a=a.map(i=>({x:i.x>.5?i.x+ip:i.x-ip,y:i.y>.5?i.y+ip:i.y-ip})));for(let i=0;i<t;i++)for(let o=0;o<r;o++)V5e(i/t,o/t,a)||(n.set(hb*n.get(0,o,i,0),0,o,i,0),n.set(hb*n.get(0,o,i,1),0,o,i,1),n.set(hb*n.get(0,o,i,2),0,o,i,2));let s=n.toTensor();return te(n),s}var G5e=e=>{let t=(h,p)=>Math.atan2(h[1]-p[1],h[0]-p[0]);if(!e.annotations.rightEyeIris||!e.annotations.leftEyeIris)return{bearing:0,strength:0};let r=[0,-.1],n=1,a=(e.mesh[33][2]||0)>(e.mesh[263][2]||0),s=a?e.mesh[473]:e.mesh[468],i=a?[(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=a?[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]-r[0],n*(s[1]-i[1])/o[1]-r[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}},YN=(e,t)=>{let r=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],A=f[1]-g[1],x=f[2]-g[2];return[y,A,x]},a=(f,g)=>{let y=f[1]*g[2]-f[2]*g[1],A=f[2]*g[0]-f[0]*g[2],x=f[0]*g[1]-f[1]*g[0];return[y,A,x]},s=f=>{let[g,y,A,x,b,w,I,T,E]=f,R,O,M;return x<1?x>-1?(M=Math.asin(x),O=Math.atan2(-I,g),R=Math.atan2(-w,b)):(M=-Math.PI/2,O=-Math.atan2(T,E),R=0):(M=Math.PI/2,O=Math.atan2(T,E),R=0),isNaN(R)&&(R=0),isNaN(O)&&(O=0),isNaN(M)&&(M=0),{pitch:2*-R,yaw:2*-O,roll:2*-M}},i=e.meshRaw;if(!i||i.length<300)return{angle:{pitch:0,yaw:0,roll:0},matrix:[1,0,0,0,1,0,0,0,1],gaze:{bearing:0,strength:0}};let o=Math.max(e.boxRaw[2]*t[0],e.boxRaw[3]*t[1])/1.5,l=[i[10],i[152],i[234],i[454]].map(f=>[f[0]*t[0]/o,f[1]*t[1]/o,f[2]]),u=r(n(l[1],l[0])),d=r(n(l[3],l[2])),h=r(a(d,u));d=a(u,h);let p=[d[0],d[1],d[2],u[0],u[1],u[2],h[0],h[1],h[2]],c=s(p),m=i.length===478?G5e(e):{bearing:0,strength:0};return{angle:c,matrix:p,gaze:m}};var cb=async(e,t)=>{var c,m,f,g,y,A,x,b,w,I,T,E,R,O,M,S,P,z,j,K,D,Y;let r=oe(),n,a,s,i,o,l,u,d,h=[];e.state="run:face";let p=await UT(t,e.config);if(e.performance.face=he.perfadd?(e.performance.face||0)+Math.trunc(oe()-r):Math.trunc(oe()-r),!t.shape||t.shape.length!==4)return[];if(!p)return[];for(let V=0;V<p.length;V++){if(e.analyze("Get Face"),!p[V].tensor||p[V].tensor.isDisposedInternal){se("Face object is disposed:",p[V].tensor);continue}if((c=e.config.face.detector)!=null&&c.mask){let ae=await ZN(p[V]);te(p[V].tensor),p[V].tensor=ae}let re=p[V].mesh&&p[V].mesh.length>200?YN(p[V],[t.shape[2],t.shape[1]]):null;e.analyze("Start Emotion:"),e.config.async?i=(m=e.config.face.emotion)!=null&&m.enabled?vx(p[V].tensor||ft([]),e.config,V,p.length):[]:(e.state="run:emotion",r=oe(),i=(f=e.config.face.emotion)!=null&&f.enabled?await vx(p[V].tensor||ft([]),e.config,V,p.length):[],e.performance.emotion=he.perfadd?(e.performance.emotion||0)+Math.trunc(oe()-r):Math.trunc(oe()-r)),e.analyze("End Emotion:"),e.analyze("Start AntiSpoof:"),e.config.async?l=(g=e.config.face.antispoof)!=null&&g.enabled?rx(p[V].tensor||ft([]),e.config,V,p.length):0:(e.state="run:antispoof",r=oe(),l=(y=e.config.face.antispoof)!=null&&y.enabled?await rx(p[V].tensor||ft([]),e.config,V,p.length):0,e.performance.antispoof=he.perfadd?(e.performance.antispoof||0)+Math.trunc(oe()-r):Math.trunc(oe()-r)),e.analyze("End AntiSpoof:"),e.analyze("Start Liveness:"),e.config.async?u=(A=e.config.face.liveness)!=null&&A.enabled?Wx(p[V].tensor||ft([]),e.config,V,p.length):0:(e.state="run:liveness",r=oe(),u=(x=e.config.face.liveness)!=null&&x.enabled?await Wx(p[V].tensor||ft([]),e.config,V,p.length):0,e.performance.liveness=he.perfadd?(e.performance.antispoof||0)+Math.trunc(oe()-r):Math.trunc(oe()-r)),e.analyze("End Liveness:"),e.analyze("Start GEAR:"),e.config.async?a=(b=e.config.face.gear)!=null&&b.enabled?KA(p[V].tensor||ft([]),e.config,V,p.length):null:(e.state="run:gear",r=oe(),a=(w=e.config.face.gear)!=null&&w.enabled?await KA(p[V].tensor||ft([]),e.config,V,p.length):null,e.performance.gear=Math.trunc(oe()-r)),e.analyze("End GEAR:"),e.analyze("Start SSRNet:"),e.config.async?(n=(I=e.config.face.ssrnet)!=null&&I.enabled?YA(p[V].tensor||ft([]),e.config,V,p.length):null,s=(T=e.config.face.ssrnet)!=null&&T.enabled?ex(p[V].tensor||ft([]),e.config,V,p.length):null):(e.state="run:ssrnet",r=oe(),n=(E=e.config.face.ssrnet)!=null&&E.enabled?await YA(p[V].tensor||ft([]),e.config,V,p.length):null,s=(R=e.config.face.ssrnet)!=null&&R.enabled?await ex(p[V].tensor||ft([]),e.config,V,p.length):null,e.performance.ssrnet=Math.trunc(oe()-r)),e.analyze("End SSRNet:"),e.analyze("Start MobileFaceNet:"),e.config.async?o=(O=e.config.face.mobilefacenet)!=null&&O.enabled?kx(p[V].tensor||ft([]),e.config,V,p.length):null:(e.state="run:mobilefacenet",r=oe(),o=(M=e.config.face.mobilefacenet)!=null&&M.enabled?await kx(p[V].tensor||ft([]),e.config,V,p.length):null,e.performance.mobilefacenet=Math.trunc(oe()-r)),e.analyze("End MobileFaceNet:"),e.analyze("Start Description:"),e.config.async?d=(S=e.config.face.description)!=null&&S.enabled?Ex(p[V].tensor||ft([]),e.config,V,p.length):null:(e.state="run:description",r=oe(),d=(P=e.config.face.description)!=null&&P.enabled?await Ex(p[V].tensor||ft([]),e.config,V,p.length):null,e.performance.description=he.perfadd?(e.performance.description||0)+Math.trunc(oe()-r):Math.trunc(oe()-r)),e.analyze("End Description:"),e.config.async&&([n,s,i,o,d,a,l,u]=await Promise.all([n,s,i,o,d,a,l,u])),e.analyze("Finish Face:"),((z=e.config.face.ssrnet)==null?void 0:z.enabled)&&n&&s&&(d={...d,age:n.age,gender:s.gender,genderScore:s.genderScore}),((j=e.config.face.gear)==null?void 0:j.enabled)&&a&&(d={...d,age:a.age,gender:a.gender,genderScore:a.genderScore,race:a.race}),((K=e.config.face.mobilefacenet)==null?void 0:K.enabled)&&o&&(d.descriptor=o),(D=e.config.face.iris)!=null&&D.enabled;let Q=p[V].annotations&&p[V].annotations.leftEyeIris&&p[V].annotations.leftEyeIris[0]&&p[V].annotations.rightEyeIris&&p[V].annotations.rightEyeIris[0]&&p[V].annotations.leftEyeIris.length>0&&p[V].annotations.rightEyeIris.length>0&&p[V].annotations.leftEyeIris[0]!==null&&p[V].annotations.rightEyeIris[0]!==null?Math.max(Math.abs(p[V].annotations.leftEyeIris[3][0]-p[V].annotations.leftEyeIris[1][0]),Math.abs(p[V].annotations.rightEyeIris[4][1]-p[V].annotations.rightEyeIris[2][1]))/t.shape[2]:0,ie=(Y=e.config.face.detector)!=null&&Y.return?et(p[V].tensor):null;te(p[V].tensor),p[V].tensor&&delete p[V].tensor;let J={...p[V],id:V};d!=null&&d.age&&(J.age=d.age),d!=null&&d.gender&&(J.gender=d.gender),d!=null&&d.genderScore&&(J.genderScore=d==null?void 0:d.genderScore),d!=null&&d.descriptor&&(J.embedding=d==null?void 0:d.descriptor),d!=null&&d.race&&(J.race=d==null?void 0:d.race),i&&(J.emotion=i),l&&(J.real=l),u&&(J.live=u),Q&&Q!==0&&(J.iris=Math.trunc(500/Q/11.7)/100),re&&(J.rotation=re),ie&&(J.tensor=ie),h.push(J),e.analyze("End Face")}return e.analyze("End FaceMesh:"),e.config.async&&(e.performance.face&&delete e.performance.face,e.performance.age&&delete e.performance.age,e.performance.gender&&delete e.performance.gender,e.performance.emotion&&delete e.performance.emotion),h};var JN=e=>{if(!e)return[];let t=[];for(let r=0;r<e.length;r++){let n=e[r].keypoints.find(l=>l.part==="leftWrist"),a=e[r].keypoints.find(l=>l.part==="rightWrist"),s=e[r].keypoints.find(l=>l.part==="nose");s&&n&&a&&n.position[1]<s.position[1]&&a.position[1]<s.position[1]?t.push({body:r,gesture:"i give up"}):s&&n&&n.position[1]<s.position[1]?t.push({body:r,gesture:"raise left hand"}):s&&a&&a.position[1]<s.position[1]&&t.push({body:r,gesture:"raise right hand"});let i=e[r].keypoints.find(l=>l.part==="leftShoulder"),o=e[r].keypoints.find(l=>l.part==="rightShoulder");i&&o&&Math.abs(i.positionRaw[1]-o.positionRaw[1])>.1&&t.push({body:r,gesture:`leaning ${i.position[1]>o.position[1]?"left":"right"}`})}return t},QN=e=>{if(!e)return[];let t=[];for(let r=0;r<e.length;r++)if(e[r].mesh&&e[r].mesh.length>450){let n=(e[r].mesh[33][2]||0)-(e[r].mesh[263][2]||0),a=e[r].mesh[33][0]-e[r].mesh[263][0];Math.abs(n/a)<=.15?t.push({face:r,gesture:"facing center"}):t.push({face:r,gesture:`facing ${n<0?"left":"right"}`}),Math.abs(e[r].mesh[374][1]-e[r].mesh[386][1])/Math.abs(e[r].mesh[443][1]-e[r].mesh[450][1])<.2&&t.push({face:r,gesture:"blink left eye"}),Math.abs(e[r].mesh[145][1]-e[r].mesh[159][1])/Math.abs(e[r].mesh[223][1]-e[r].mesh[230][1])<.2&&t.push({face:r,gesture:"blink right eye"});let o=Math.min(100,500*Math.abs(e[r].mesh[13][1]-e[r].mesh[14][1])/Math.abs(e[r].mesh[10][1]-e[r].mesh[152][1]));o>10&&t.push({face:r,gesture:`mouth ${Math.trunc(o)}% open`});let l=e[r].mesh[152][2]||0;Math.abs(l)>10&&t.push({face:r,gesture:`head ${l<0?"up":"down"}`})}return t},eE=e=>{if(!e)return[];let t=[];for(let r=0;r<e.length;r++){if(!e[r].annotations||!e[r].annotations.leftEyeIris||!e[r].annotations.leftEyeIris[0]||!e[r].annotations.rightEyeIris||!e[r].annotations.rightEyeIris[0])continue;let n=e[r].annotations.leftEyeIris[3][0]-e[r].annotations.leftEyeIris[1][0],a=e[r].annotations.leftEyeIris[4][1]-e[r].annotations.leftEyeIris[2][1],s=Math.abs(n*a),i=e[r].annotations.rightEyeIris[3][0]-e[r].annotations.rightEyeIris[1][0],o=e[r].annotations.rightEyeIris[4][1]-e[r].annotations.rightEyeIris[2][1],l=Math.abs(i*o),u=!1;Math.abs(s-l)/Math.max(s,l)<.25&&(u=!0,t.push({iris:r,gesture:"facing center"}));let h=Math.abs(e[r].mesh[263][0]-e[r].annotations.leftEyeIris[0][0])/e[r].box[2],p=Math.abs(e[r].mesh[33][0]-e[r].annotations.rightEyeIris[0][0])/e[r].box[2];(h>.06||p>.06)&&(u=!1),h>p?h>.05&&t.push({iris:r,gesture:"looking right"}):p>.05&&t.push({iris:r,gesture:"looking left"});let c=Math.abs(e[r].mesh[145][1]-e[r].annotations.rightEyeIris[0][1])/e[r].box[3],m=Math.abs(e[r].mesh[374][1]-e[r].annotations.leftEyeIris[0][1])/e[r].box[3];(m<.01||c<.01||m>.022||c>.022)&&(u=!1),(m<.01||c<.01)&&t.push({iris:r,gesture:"looking down"}),(m>.022||c>.022)&&t.push({iris:r,gesture:"looking up"}),u&&t.push({iris:r,gesture:"looking center"})}return t},tE=e=>{if(!e)return[];let t=[];for(let r=0;r<e.length;r++){let n=[];if(e[r].annotations)for(let[a,s]of Object.entries(e[r].annotations))a!=="palmBase"&&Array.isArray(s)&&s[0]&&n.push({name:a.toLowerCase(),position:s[0]});if(n&&n.length>0){let a=n.reduce((i,o)=>(i.position[2]||0)<(o.position[2]||0)?i:o);t.push({hand:r,gesture:`${a.name} forward`});let s=n.reduce((i,o)=>i.position[1]<o.position[1]?i:o);t.push({hand:r,gesture:`${s.name} up`})}if(e[r].keypoints){let a=fN(e[r].keypoints);for(let s of a)t.push({hand:r,gesture:s.name})}}return t};var Ne={face:[],body:[],hand:[],gesture:[],object:[],persons:[],performance:{},timestamp:0,error:null},fb=0;function rE(e,t){var i,o,l,u,d,h,p,c,m,f,g,y,A,x,b,w,I,T,E,R,O,M,S,P,z,j,K;let r=oe();if(!e)return{face:[],body:[],hand:[],gesture:[],object:[],persons:[],performance:{},timestamp:0,error:null};let n=Date.now()-e.timestamp,a=n<1e3?8-Math.log(n+1):1;if(e.canvas&&(Ne.canvas=e.canvas),e.error&&(Ne.error=e.error),!Ne.body||e.body.length!==Ne.body.length)Ne.body=JSON.parse(JSON.stringify(e.body));else for(let D=0;D<e.body.length;D++){let Y=e.body[D].box.map((J,ae)=>((a-1)*Ne.body[D].box[ae]+J)/a),V=e.body[D].boxRaw.map((J,ae)=>((a-1)*Ne.body[D].boxRaw[ae]+J)/a),re=e.body[D].keypoints.map((J,ae)=>{var de,be,ve,Ee,Me,De,We,Ke,ot;return{score:J.score,part:J.part,position:[Ne.body[D].keypoints[ae]?((a-1)*(Ne.body[D].keypoints[ae].position[0]||0)+(J.position[0]||0))/a:J.position[0],Ne.body[D].keypoints[ae]?((a-1)*(Ne.body[D].keypoints[ae].position[1]||0)+(J.position[1]||0))/a:J.position[1],Ne.body[D].keypoints[ae]?((a-1)*(Ne.body[D].keypoints[ae].position[2]||0)+(J.position[2]||0))/a:J.position[2]],positionRaw:[Ne.body[D].keypoints[ae]?((a-1)*(Ne.body[D].keypoints[ae].positionRaw[0]||0)+(J.positionRaw[0]||0))/a:J.positionRaw[0],Ne.body[D].keypoints[ae]?((a-1)*(Ne.body[D].keypoints[ae].positionRaw[1]||0)+(J.positionRaw[1]||0))/a:J.positionRaw[1],Ne.body[D].keypoints[ae]?((a-1)*(Ne.body[D].keypoints[ae].positionRaw[2]||0)+(J.positionRaw[2]||0))/a:J.positionRaw[2]],distance:[Ne.body[D].keypoints[ae]?((a-1)*(((de=Ne.body[D].keypoints[ae].distance)==null?void 0:de[0])||0)+(((be=J.distance)==null?void 0:be[0])||0))/a:(ve=J.distance)==null?void 0:ve[0],Ne.body[D].keypoints[ae]?((a-1)*(((Ee=Ne.body[D].keypoints[ae].distance)==null?void 0:Ee[1])||0)+(((Me=J.distance)==null?void 0:Me[1])||0))/a:(De=J.distance)==null?void 0:De[1],Ne.body[D].keypoints[ae]?((a-1)*(((We=Ne.body[D].keypoints[ae].distance)==null?void 0:We[2])||0)+(((Ke=J.distance)==null?void 0:Ke[2])||0))/a:(ot=J.distance)==null?void 0:ot[2]]}}),Q={},ie={connected:{}};(o=(i=t.body)==null?void 0:i.modelPath)!=null&&o.includes("efficientpose")?ie=a1:(u=(l=t.body)==null?void 0:l.modelPath)!=null&&u.includes("blazepose")?ie=Qm:(h=(d=t.body)==null?void 0:d.modelPath)!=null&&h.includes("movenet")&&(ie=uc);for(let[J,ae]of Object.entries(ie.connected)){let de=[];for(let be=0;be<ae.length-1;be++){let ve=re.find(Me=>Me.part===ae[be]),Ee=re.find(Me=>Me.part===ae[be+1]);ve&&Ee&&de.push([ve.position,Ee.position])}Q[J]=de}Ne.body[D]={...e.body[D],box:Y,boxRaw:V,keypoints:re,annotations:Q}}if(!Ne.hand||e.hand.length!==Ne.hand.length)Ne.hand=JSON.parse(JSON.stringify(e.hand));else for(let D=0;D<e.hand.length;D++){let Y=e.hand[D].box.map((ie,J)=>((a-1)*Ne.hand[D].box[J]+ie)/a),V=e.hand[D].boxRaw.map((ie,J)=>((a-1)*Ne.hand[D].boxRaw[J]+ie)/a);Ne.hand[D].keypoints.length!==e.hand[D].keypoints.length&&(Ne.hand[D].keypoints=e.hand[D].keypoints);let re=e.hand[D].keypoints&&e.hand[D].keypoints.length>0?e.hand[D].keypoints.map((ie,J)=>ie.map((ae,de)=>((a-1)*(Ne.hand[D].keypoints[J][de]||1)+(ae||0))/a)):[],Q={};if(Object.keys(Ne.hand[D].annotations).length!==Object.keys(e.hand[D].annotations).length)Ne.hand[D].annotations=e.hand[D].annotations,Q=Ne.hand[D].annotations;else if(e.hand[D].annotations)for(let ie of Object.keys(e.hand[D].annotations))Q[ie]=e.hand[D].annotations[ie]&&e.hand[D].annotations[ie][0]?e.hand[D].annotations[ie].map((J,ae)=>J.map((de,be)=>((a-1)*Ne.hand[D].annotations[ie][ae][be]+de)/a)):null;Ne.hand[D]={...e.hand[D],box:Y,boxRaw:V,keypoints:re,annotations:Q}}if(!Ne.face||e.face.length!==Ne.face.length)Ne.face=JSON.parse(JSON.stringify(e.face));else for(let D=0;D<e.face.length;D++){let Y=e.face[D].box.map((re,Q)=>((a-1)*Ne.face[D].box[Q]+re)/a),V=e.face[D].boxRaw.map((re,Q)=>((a-1)*Ne.face[D].boxRaw[Q]+re)/a);if(e.face[D].rotation){let re={matrix:[0,0,0,0,0,0,0,0,0],angle:{roll:0,yaw:0,pitch:0},gaze:{bearing:0,strength:0}};re.matrix=(p=e.face[D].rotation)==null?void 0:p.matrix,re.angle={roll:((a-1)*(((m=(c=Ne.face[D].rotation)==null?void 0:c.angle)==null?void 0:m.roll)||0)+(((g=(f=e.face[D].rotation)==null?void 0:f.angle)==null?void 0:g.roll)||0))/a,yaw:((a-1)*(((A=(y=Ne.face[D].rotation)==null?void 0:y.angle)==null?void 0:A.yaw)||0)+(((b=(x=e.face[D].rotation)==null?void 0:x.angle)==null?void 0:b.yaw)||0))/a,pitch:((a-1)*(((I=(w=Ne.face[D].rotation)==null?void 0:w.angle)==null?void 0:I.pitch)||0)+(((E=(T=e.face[D].rotation)==null?void 0:T.angle)==null?void 0:E.pitch)||0))/a},re.gaze={bearing:((a-1)*(((O=(R=Ne.face[D].rotation)==null?void 0:R.gaze)==null?void 0:O.bearing)||0)+(((S=(M=e.face[D].rotation)==null?void 0:M.gaze)==null?void 0:S.bearing)||0))/a,strength:((a-1)*(((z=(P=Ne.face[D].rotation)==null?void 0:P.gaze)==null?void 0:z.strength)||0)+(((K=(j=e.face[D].rotation)==null?void 0:j.gaze)==null?void 0:K.strength)||0))/a},Ne.face[D]={...e.face[D],rotation:re,box:Y,boxRaw:V}}Ne.face[D]={...e.face[D],box:Y,boxRaw:V}}if(!Ne.object||e.object.length!==Ne.object.length)Ne.object=JSON.parse(JSON.stringify(e.object));else for(let D=0;D<e.object.length;D++){let Y=e.object[D].box.map((re,Q)=>((a-1)*Ne.object[D].box[Q]+re)/a),V=e.object[D].boxRaw.map((re,Q)=>((a-1)*Ne.object[D].boxRaw[Q]+re)/a);Ne.object[D]={...e.object[D],box:Y,boxRaw:V}}if(e.persons){let D=e.persons;if(!Ne.persons||D.length!==Ne.persons.length)Ne.persons=JSON.parse(JSON.stringify(D));else for(let Y=0;Y<D.length;Y++)Ne.persons[Y].box=D[Y].box.map((V,re)=>((a-1)*Ne.persons[Y].box[re]+V)/a)}e.gesture&&(Ne.gesture=e.gesture);let s=oe();return fb=he.perfadd?fb+Math.round(s-r):Math.round(s-r),e.performance&&(Ne.performance={...e.performance,interpolate:fb}),Ne}var yb={};vs(yb,{distance:()=>cc,match:()=>gb,similarity:()=>mb});function cc(e,t,r={order:2,multiplier:25}){let n=0;for(let a=0;a<e.length;a++){let s=!r.order||r.order===2?e[a]-t[a]:Math.abs(e[a]-t[a]);n+=!r.order||r.order===2?s*s:s**r.order}return(r.multiplier||20)*n}var nE=(e,t,r,n)=>{if(e===0)return 1;let a=t===2?Math.sqrt(e):e**(1/t),s=(1-a/100-r)/(n-r);return Math.max(Math.min(s,1),0)};function mb(e,t,r={order:2,multiplier:25,min:.2,max:.8}){let n=cc(e,t,r);return nE(n,r.order||2,r.min||0,r.max||1)}function gb(e,t,r={order:2,multiplier:25,threshold:0,min:.2,max:.8}){if(!Array.isArray(e)||!Array.isArray(t)||e.length<64||t.length===0||e.length!==t[0].length)return{index:-1,distance:Number.POSITIVE_INFINITY,similarity:0};let n=Number.MAX_SAFE_INTEGER,a=-1;for(let i=0;i<t.length;i++){let o=cc(e,t[i],r);if(o<n&&(n=o,a=i),n<(r.threshold||0))break}let 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xx(o.tensor,p):[]:(T=this.config.body.modelPath)!=null&&T.includes("movenet")&&(u=this.config.body.enabled?await qx(o.tensor,p):[]),this.performance.body=this.env.perfadd?(this.performance.body||0)+Math.trunc(oe()-a):Math.trunc(oe()-a)),this.analyze("End Body:"),this.analyze("Start Hand:"),this.state="detect:hand";let c=this.config.hand.maxDetected===-1?Gt(this.config,{hand:{maxDetected:this.config.face.enabled?2*l.length:1}}):this.config;this.config.async?((R=(E=this.config.hand.detector)==null?void 0:E.modelPath)!=null&&R.includes("handdetect")?d=this.config.hand.enabled?Px(o.tensor,c):[]:(M=(O=this.config.hand.detector)==null?void 0:O.modelPath)!=null&&M.includes("handtrack")&&(d=this.config.hand.enabled?Lx(o.tensor,c):[]),this.performance.hand&&delete this.performance.hand):(a=oe(),(P=(S=this.config.hand.detector)==null?void 0:S.modelPath)!=null&&P.includes("handdetect")?d=this.config.hand.enabled?await Px(o.tensor,c):[]:(j=(z=this.config.hand.detector)==null?void 0:z.modelPath)!=null&&j.includes("handtrack")&&(d=this.config.hand.enabled?await Lx(o.tensor,c):[]),this.performance.hand=this.env.perfadd?(this.performance.hand||0)+Math.trunc(oe()-a):Math.trunc(oe()-a)),this.analyze("End Hand:"),this.analyze("Start Object:"),this.state="detect:object",this.config.async?((K=this.config.object.modelPath)!=null&&K.includes("nanodet")?h=this.config.object.enabled?Kx(o.tensor,this.config):[]:(D=this.config.object.modelPath)!=null&&D.includes("centernet")&&(h=this.config.object.enabled?mx(o.tensor,this.config):[]),this.performance.object&&delete this.performance.object):(a=oe(),(Y=this.config.object.modelPath)!=null&&Y.includes("nanodet")?h=this.config.object.enabled?await Kx(o.tensor,this.config):[]:(V=this.config.object.modelPath)!=null&&V.includes("centernet")&&(h=this.config.object.enabled?await mx(o.tensor,this.config):[]),this.performance.object=this.env.perfadd?(this.performance.object||0)+Math.trunc(oe()-a):Math.trunc(oe()-a)),this.analyze("End Object:"),this.state="detect:await",this.config.async&&([l,u,d,h]=await Promise.all([l,u,d,h])),this.state="detect:gesture";let m=[];this.config.gesture.enabled&&(a=oe(),m=[...QN(l),...JN(u),...tE(d),...eE(l)],this.config.async?this.performance.gesture&&delete this.performance.gesture:this.performance.gesture=this.env.perfadd?(this.performance.gesture||0)+Math.trunc(oe()-a):Math.trunc(oe()-a)),this.performance.total=this.env.perfadd?(this.performance.total||0)+Math.trunc(oe()-i):Math.trunc(oe()-i);let f=((Q=(re=this.process)==null?void 0:re.tensor)==null?void 0:Q.shape)||[];this.result={face:l,body:u,hand:d,gesture:m,object:h,performance:this.performance,canvas:this.process.canvas,timestamp:Date.now(),error:null,get persons(){return aE(l,u,d,m,f)}},te(o.tensor),this.emit("detect"),this.state="idle",n(this.result)})}};op=new WeakMap,fc=new WeakMap,mc=new WeakMap,R1=new WeakMap;return aR(rAe);})();
/**
* @license
* Copyright 2017 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
/**
* @license
* Copyright 2018 Google LLC
*
* Use of this source code is governed by an MIT-style
* license that can be found in the LICENSE file or at
* https://opensource.org/licenses/MIT.
* =============================================================================
*/
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*
* =============================================================================
*/
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
/**
* @license
* Copyright 2019 Google LLC
*
* Use of this source code is governed by an MIT-style
* license that can be found in the LICENSE file or at
* https://opensource.org/licenses/MIT.
* =============================================================================
*/
/**
* @license
* Copyright 2019 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*
* =============================================================================
*/
/**
* @license
* Copyright 2019 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
/**
* @license
* Copyright 2020 Google Inc. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
/**
* @license
* Copyright 2020 Google LLC
*
* Use of this source code is governed by an MIT-style
* license that can be found in the LICENSE file or at
* https://opensource.org/licenses/MIT.
* =============================================================================
*/
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use backend file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the License);
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an AS IS BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
/**
* @license
* Copyright 2021 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
/**
* @license
* Copyright 2021 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* https://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
/**
* @license
* Copyright 2021 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the License);
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an AS IS BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
/**
* @license
* Copyright 2022 Google Inc. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
/**
* @license
* Copyright 2022 Google LLC
*
* Use of this source code is governed by an MIT-style
* license that can be found in the LICENSE file or at
* https://opensource.org/licenses/MIT.
* =============================================================================
*/
/**
* @license
* Copyright 2022 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
/**
* @license
* Copyright 2022 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the 'License');
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an 'AS IS' BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
/**
* Human main module
* @default Human Library
* @summary <https://github.com/vladmandic/human>
* @author <https://github.com/vladmandic>
* @copyright <https://github.com/vladmandic>
* @license MIT
*/
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
/** @license See the LICENSE file. */
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