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face-api/dist/face-api.esm.js

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/*
Face-API
homepage: <https://github.com/vladmandic/face-api>
author: <https://github.com/vladmandic>'
*/
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this.state.registeredVariables[r.name]=r,this.incRef(r,this.backend),r}trackTensor(e,t){this.state.numTensors++,e.dtype==="string"&&this.state.numStringTensors++;let n=0;e.dtype!=="complex64"&&e.dtype!=="string"&&(n=e.size*Lh(e.dtype)),this.state.numBytes+=n,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:n})),e instanceof os||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 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a=O.registeredVariables[t],r=!1;this.accumulatedGrads[n]==null&&(this.accumulatedGrads[n]={originalName:`${t}/accum_grad`,variable:P(()=>qe(a).variable(r))}),this.accumulatedUpdates[n]==null&&(this.accumulatedUpdates[n]={originalName:`${t}/accum_var`,variable:P(()=>qe(a).variable(r))});let s=Array.isArray(e)?e[n].tensor:e[t];if(s==null)return;let i=this.accumulatedGrads[n].variable,o=this.accumulatedUpdates[n].variable;P(()=>{let l=X(z(i,this.rho),z(lt(s),1-this.rho)),u=z(he(hn(X(o,this.epsilon)),hn(X(i,this.epsilon))),s),p=X(z(o,this.rho),z(lt(u),1-this.rho));i.assign(l),o.assign(p);let d=X(z(u,-this.learningRate),a);a.assign(d)})}),this.incrementIterations()}dispose(){this.accumulatedUpdates!=null&&(_e(this.accumulatedGrads.map(e=>e.variable)),_e(this.accumulatedUpdates.map(e=>e.variable)))}async getWeights(){let e=[...this.accumulatedGrads,...this.accumulatedUpdates];return[await this.saveIterations()].concat(e.map(t=>({name:t.originalName,tensor:t.variable})))}async setWeights(e){e=await this.extractIterations(e);let t=e.length/2,n=!1;this.accumulatedGrads=e.slice(0,t).map(a=>({originalName:a.name,variable:a.tensor.variable(n)})),this.accumulatedUpdates=e.slice(t,t*2).map(a=>({originalName:a.name,variable:a.tensor.variable(n)}))}getConfig(){return{learningRate:this.learningRate,rho:this.rho,epsilon:this.epsilon}}static fromConfig(e,t){return new e(t.learningRate,t.rho,t.epsilon)}},Ew=class extends Mr{static get className(){return"Adagrad"}constructor(e,t=.1){super(),this.learningRate=e,this.initialAccumulatorValue=t,this.accumulatedGrads=[]}applyGradients(e){(Array.isArray(e)?e.map(t=>t.name):Object.keys(e)).forEach((t,n)=>{let a=O.registeredVariables[t];this.accumulatedGrads[n]==null&&(this.accumulatedGrads[n]={originalName:`${t}/accumulator`,variable:P(()=>xn(a.shape,this.initialAccumulatorValue).variable(!1))});let r=Array.isArray(e)?e[n].tensor:e[t];if(r==null)return;let s=this.accumulatedGrads[n].variable;P(()=>{let 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Hence the notion of "output shape" is ill-defined for the layer.`)}countParams(){if(!this.built)throw new Ba(`You tried to call countParams() on ${this.name}, but the layer is not built yet. Build it first by calling build(batchInputShape).`);return Kh(this.weights)}build(e){this.built=!0}getWeights(e=!1){return Ax(e?this.trainableWeights:this.weights)}setWeights(e){P(()=>{let t=this.weights;if(t.length!==e.length)throw new V(`You called setWeights(weights) on layer "${this.name}" with a weight list of length ${e.length}, but the layer was expecting ${t.length} weights. 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Provided ${n} not understood: ${JSON.stringify(e)}`)}function f2(e,t){return UG(e,t,"classWeight")}async function g2(e,t,n,a){if(t!=null||a!=null)throw new Error("Support sampleWeight is not implemented yet");if(n!=null){let r=P(()=>{if(e.shape.length===1)return sr(e);if(e.shape.length===2){if(e.shape[1]>1)return pi(e,1);if(e.shape[1]===1)return W(e,[e.shape[0]]);throw new Error(`Encountered unexpected last-dimension size (${e.shape[1]}) during handling of class weights. The size is expected to be >= 1.`)}else throw new Error(`Unexpected rank of target (y) tensor (${e.rank}) during handling of class weights. The rank is expected to be 1 or 2.`)}),s=Array.from(await r.data());_e(r);let i=[];return s.forEach(o=>{if(n[o]==null)throw new Error(`classWeight must contain all classes in the training data. 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t=[],n,a=e.slice(0,this.inputs.length),r=e.slice(this.inputs.length,this.inputs.length+this.outputs.length),s=[];for(let l=0;l<this.inputs.length;++l)s.push({key:this.inputs[l],value:a[l]});let i=new ei(s),o=Yp(this.outputs,i);for(let l=0;l<this.lossFunctions.length;++l){let u=this.lossFunctions[l],p=Et(u(r[l],o[l]));l===0?n=p:n=X(n,p),t.push(n)}for(let l=0;l<this.metricsTensors.length;++l){let u=this.metricsTensors[l][0],p=this.metricsTensors[l][1],d=Et(u(r[p],o[p]));t.push(d)}return t})}async fit(e,t,n={}){if(this.isTraining)throw new Error("Cannot start training because another fit() call is ongoing.");this.isTraining=!0;let a,r,s,i,o,l,u,p,d;try{let c=n.batchSize==null?32:n.batchSize;ax(c);let h=!1,m=await this.standardizeUserData(e,t,n.sampleWeight,n.classWeight,h,c);a=m[0],r=m[1],d=m[2];let f=!1,g;if(n.validationData!=null&&n.validationData.length>0){if(f=!0,n.validationData.length===2)o=n.validationData[0],l=n.validationData[1];else throw n.validationData.length===3?new Oe("validationData including sample weights is not supported yet."):new V(`When passing validation data, it must contain 2 (valX, valY) or 3 (valX, valY, valSampleWeight) items; ${n.validationData} is invalid.`);let C=!0,E=await this.standardizeUserData(o,l,null,null,C,c);u=E[0],p=E[1],g=u.concat(p)}else if(n.validationSplit!=null&&n.validationSplit>0&&n.validationSplit<1){f=!0;let C=Math.floor(a[0].shape[0]*(1-n.validationSplit)),E=a[0].shape[0];u=Gp(a,C,E),s=a,a=Gp(a,0,C),p=Gp(r,C,E),i=r,r=Gp(r,0,C),g=u.concat(p)}else n.validationSteps!=null&&(f=!0);let b=a.concat(r).concat(d);this.checkTrainableWeightsConsistency();let y=this.makeTrainFunction(),x=this.getDedupedMetricsNames(),w,I;f?(this.makeTestFunction(),w=this.testFunction,I=x.slice().concat(x.map(C=>"val_"+C))):(w=null,g=[],I=x.slice());let T=o2(n.callbacks,n.yieldEvery);return await this.fitLoop(y,b,x,c,n.epochs,n.verbose,T,w,g,n.shuffle,I,n.initialEpoch,null,null)}finally{this.isTraining=!1,za(a,e),za(r,t),za(s,e),za(i,t),za(u,o),za(p,l),d!=null&&_e(d)}}async fitLoop(e,t,n,a,r,s,i,o,l,u,p,d,c,h){a==null&&(a=32),r==null&&(r=1),u==null&&(u=!0),d==null&&(d=0);let m=!1;if(o!=null&&l!=null&&(m=!0),h!=null&&(m=!0,c==null))throw new V("Can only use `validationSteps` when doing step-wise training, i.e., `stepsPerEpoch` must be set.");let f=this.checkNumSamples(t,a,c,"steps_per_epoch"),g;f!=null&&(g=qa(0,f)),s==null&&(s=1);let{callbackList:b,history:y}=l2(i,s,r,d,f,c,a,m,p);b.setModel(this),this.history=y,await b.onTrainBegin(),this.stopTraining_=!1;for(let x=d;x<r;++x){await b.onEpochBegin(x);let w={};if(c!=null)throw new Oe("stepsPerEpoch mode is not implemented yet.");{if(u==="batch")throw new Oe("batch shuffling is not implemneted yet");u&&v.shuffle(g);let I=je(g),T=rx(f,a);for(let C=0;C<T.length;++C){let E={};if(await b.onBatchBegin(C,E),P(()=>{let 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i=qt.getSaveHandlers(e);if(i.length===0)throw new V(`Cannot find any save handlers for URL '${e}'`);if(i.length>1)throw new V(`Found more than one (${i.length}) save handlers for URL '${e}'`);e=i[0]}if(e.save==null)throw new V("LayersModel.save() cannot proceed because the IOHandler provided does not have the `save` attribute defined.");let n=await qt.encodeWeights(this.getNamedWeights(t)),a=!1,r=null,s={modelTopology:this.toJSON(r,a),format:tH,generatedBy:`TensorFlow.js tfjs-layers v${s0}`,convertedBy:null};if(t!=null&&t.includeOptimizer&&this.optimizer!=null){s.trainingConfig=this.getTrainingConfig();let i="optimizer",{data:o,specs:l}=await qt.encodeWeights(await this.optimizer.getWeights(),i);n.specs.push(...l),n.data=qt.concatenateArrayBuffers([n.data,o])}return 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Be{constructor(e){if(super(e==null?{}:e),this.DEFAULT_ALPHA_INITIALIZER="zeros",e==null&&(e={}),this.supportsMasking=!0,this.alphaInitializer=Tt(e.alphaInitializer||this.DEFAULT_ALPHA_INITIALIZER),this.alphaRegularizer=Ct(e.alphaRegularizer),this.alphaConstraint=Yt(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 V(`Expected sharedAxes to be a number or an array of numbers, but got ${e.sharedAxes}`)}build(e){e=Ze(e);let t=e.slice(1);if(this.sharedAxes!=null)for(let a of this.sharedAxes)t[a-1]=1;this.alpha=this.addWeight("alpha",t,"float32",this.alphaInitializer,this.alphaRegularizer,!0,this.alphaConstraint);let n={};if(this.sharedAxes!=null)for(let a=1;a<e.length;++a)n[a]=e[a];this.inputSpec=[new Bt({ndim:e.length,axes:n})],this.built=!0}call(e,t){return e=Te(e),id(e,this.alpha.read())}getConfig(){let e={alphaInitializer:At(this.alphaInitializer),alphaRegularizer:mt(this.alphaRegularizer),alphaConstraint:Xt(this.alphaConstraint),sharedAxes:this.sharedAxes},t=super.getConfig();return Object.assign(e,t),e}};p0.className="PReLU";ne.registerClass(p0);var c0=class extends Be{constructor(e){if(super(e==null?{}:e),this.DEFAULT_ALPHA=1,e==null&&(e={}),e.alpha!=null&&e.alpha!==this.DEFAULT_ALPHA)throw new Oe(`Non-default alpha value (${e.alpha}) is not supported by the ELU layer yet.`);this.alpha=e.alpha==null?this.DEFAULT_ALPHA:e.alpha}call(e,t){let n=Te(e);return Zu(n)}computeOutputShape(e){return e}getConfig(){let e={alpha:this.alpha},t=super.getConfig();return Object.assign(e,t),e}};c0.className="ELU";ne.registerClass(c0);var d0=class extends Be{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 n=Te(e);return z(n,ie(Cn(n,this.theta),"float32"))}computeOutputShape(e){return e}getConfig(){let e={theta:this.theta},t=super.getConfig();return Object.assign(e,t),e}};d0.className="ThresholdedReLU";ne.registerClass(d0);var h0=class extends Be{constructor(e){super(e==null?{}:e),this.DEFAULT_AXIS=1,e==null&&(e={}),this.softmax=new i0().apply,this.axis=e.axis==null?this.DEFAULT_AXIS:e.axis}call(e,t){let n=Te(e);return this.softmax(n,this.axis)}computeOutputShape(e){return e}getConfig(){let e={axis:this.axis},t=super.getConfig();return Object.assign(e,t),e}};h0.className="Softmax";ne.registerClass(h0);function Il(e,t,n){if(typeof e=="number")return gi(e,t);if(e.length!==t)throw new V(`The ${n} argument must be an integer or tuple of ${t} integers. 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instead`);if(s==="channelsFirst"&&(e=De(e,[0,2,1])),r==="causal")throw new Oe("The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.");let o=Lm(e,t,a,r==="same"?"same":"valid","NWC",i);return n!=null&&(o=Ya(o,n)),o})}function gI(e,t,n,a=[1,1],r="valid",s,i,o=null){return P(()=>{if(s==null&&(s=ja()),Pt(s),e.rank!==3&&e.rank!==4)throw new V(`conv2dWithBiasActivation expects input to be of rank 3 or 4, but received ${e.rank}.`);if(t.rank!==3&&t.rank!==4)throw new V(`conv2dWithBiasActivation expects kernel to be of rank 3 or 4, but received ${e.rank}.`);let l=m0(e,s);if(r==="causal")throw new Oe("The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.");return l=Rl.conv2d({x:l,filter:t,strides:a,pad:r==="same"?"same":"valid",dilations:i,dataFormat:"NHWC",bias:n,activation:o}),s==="channelsFirst"&&(l=De(l,[0,3,1,2])),l})}function dH(e,t,n,a=[1,1,1],r="valid",s,i){return P(()=>{if(s==null&&(s=ja()),Pt(s),e.rank!==4&&e.rank!==5)throw new V(`conv3dWithBias expects input to be of rank 4 or 5, but received ${e.rank}.`);if(t.rank!==4&&t.rank!==5)throw new V(`conv3dWithBias expects kernel to be of rank 4 or 5, but received ${e.rank}.`);let o=M2(e,s);if(r==="causal")throw new Oe("The support for CAUSAL padding mode in conv3dWithBias is not implemented yet.");return o=Vv(o,t,a,r==="same"?"same":"valid","NDHWC",i),n!=null&&(o=Ya(o,n)),s==="channelsFirst"&&(o=De(o,[0,4,1,2,3])),o})}var f0=class extends Be{constructor(e,t){if(super(t),this.bias=null,this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_BIAS_INITIALIZER="zeros",f0.verifyArgs(t),this.rank=e,nn(this.rank,"rank"),this.rank!==1&&this.rank!==2&&this.rank!==3)throw new Oe(`Convolution layer for rank other than 1, 2, or 3 (${this.rank}) is not implemented yet.`);if(this.kernelSize=Il(t.kernelSize,e,"kernelSize"),this.strides=Il(t.strides==null?1:t.strides,e,"strides"),this.padding=t.padding==null?"valid":t.padding,va(this.padding),this.dataFormat=t.dataFormat==null?"channelsLast":t.dataFormat,Pt(this.dataFormat),this.activation=ds(t.activation),this.useBias=t.useBias==null?!0:t.useBias,this.biasInitializer=Tt(t.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.biasConstraint=Yt(t.biasConstraint),this.biasRegularizer=Ct(t.biasRegularizer),this.activityRegularizer=Ct(t.activityRegularizer),this.dilationRate=Il(t.dilationRate==null?1:t.dilationRate,e,"dilationRate"),this.rank===1&&Array.isArray(this.dilationRate)&&this.dilationRate.length!==1)throw new V(`dilationRate must be a number or an array of a single number for 1D convolution, but received ${JSON.stringify(this.dilationRate)}`);if(this.rank===2){if(typeof this.dilationRate=="number")this.dilationRate=[this.dilationRate,this.dilationRate];else if(this.dilationRate.length!==2)throw new V(`dilationRate must be a number or array of two numbers for 2D convolution, but received ${JSON.stringify(this.dilationRate)}`)}else if(this.rank===3){if(typeof this.dilationRate=="number")this.dilationRate=[this.dilationRate,this.dilationRate,this.dilationRate];else if(this.dilationRate.length!==3)throw new V(`dilationRate must be a number or array of three numbers for 3D convolution, but received ${JSON.stringify(this.dilationRate)}`)}}static verifyArgs(e){if(nr("kernelSize"in e,"required key 'kernelSize' not in config"),typeof e.kernelSize!="number"&&!Ww(e.kernelSize,"number",1,3))throw new V(`BaseConv expects config.kernelSize to be number or number[] with length 1, 2, or 3, but received ${JSON.stringify(e.kernelSize)}.`)}getConfig(){let e={kernelSize:this.kernelSize,strides:this.strides,padding:this.padding,dataFormat:this.dataFormat,dilationRate:this.dilationRate,activation:cs(this.activation),useBias:this.useBias,biasInitializer:At(this.biasInitializer),biasRegularizer:mt(this.biasRegularizer),activityRegularizer:mt(this.activityRegularizer),biasConstraint:Xt(this.biasConstraint)},t=super.getConfig();return Object.assign(e,t),e}},bd=class extends f0{constructor(e,t){super(e,t),this.kernel=null,bd.verifyArgs(t),this.filters=t.filters,nn(this.filters,"filters"),this.kernelInitializer=Tt(t.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.kernelConstraint=Yt(t.kernelConstraint),this.kernelRegularizer=Ct(t.kernelRegularizer)}build(e){e=Ze(e);let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null)throw new V(`The channel dimension of the input should be defined. Found ${e[t]}`);let n=e[t],a=this.kernelSize.concat([n,this.filters]);this.kernel=this.addWeight("kernel",a,null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[{ndim:this.rank+2,axes:{[t]:n}}],this.built=!0}call(e,t){return P(()=>{e=Te(e);let n,a=this.bias==null?null:this.bias.read(),r=UT(this.activation.getClassName());if(r!=null&&this.rank===2)n=gI(e,this.kernel.read(),a,this.strides,this.padding,this.dataFormat,this.dilationRate,r);else{if(this.rank===1)n=cH(e,this.kernel.read(),a,this.strides[0],this.padding,this.dataFormat,this.dilationRate[0]);else if(this.rank===2)n=gI(e,this.kernel.read(),a,this.strides,this.padding,this.dataFormat,this.dilationRate);else if(this.rank===3)n=dH(e,this.kernel.read(),a,this.strides,this.padding,this.dataFormat,this.dilationRate);else throw new Oe("convolutions greater than 3D are not implemented yet.");this.activation!=null&&(n=this.activation.apply(n))}return n})}computeOutputShape(e){e=Ze(e);let t=[],n=this.dataFormat==="channelsLast"?e.slice(1,e.length-1):e.slice(2);for(let r=0;r<n.length;++r){let s=Ha(n[r],this.kernelSize[r],this.padding,this.strides[r],typeof this.dilationRate=="number"?this.dilationRate:this.dilationRate[r]);t.push(s)}let a=[e[0]];return this.dataFormat==="channelsLast"?(a=a.concat(t),a.push(this.filters)):(a.push(this.filters),a=a.concat(t)),a}getConfig(){let e={filters:this.filters,kernelInitializer:At(this.kernelInitializer),kernelRegularizer:mt(this.kernelRegularizer),kernelConstraint:Xt(this.kernelConstraint)},t=super.getConfig();return Object.assign(e,t),e}static verifyArgs(e){if(!("filters"in e)||typeof e.filters!="number"||e.filters<1)throw new V(`Convolution layer expected config.filters to be a 'number' > 0 but got ${JSON.stringify(e.filters)}`)}},yd=class extends bd{constructor(e){super(2,e),yd.verifyArgs(e)}getConfig(){let e=super.getConfig();return delete e.rank,e}static verifyArgs(e){if(typeof e.kernelSize!="number"&&!Ww(e.kernelSize,"number",1,2))throw new V(`Conv2D expects config.kernelSize to be number or number[] with length 1 or 2, but received ${JSON.stringify(e.kernelSize)}.`)}};yd.className="Conv2D";ne.registerClass(yd);var xd=class extends bd{constructor(e){super(3,e),xd.verifyArgs(e)}getConfig(){let e=super.getConfig();return delete e.rank,e}static verifyArgs(e){if(typeof e.kernelSize!="number"&&!(Array.isArray(e.kernelSize)&&(e.kernelSize.length===1||e.kernelSize.length===3)))throw new V(`Conv3D expects config.kernelSize to be number or [number, number, number], but received ${JSON.stringify(e.kernelSize)}.`)}};xd.className="Conv3D";ne.registerClass(xd);var g0=class extends yd{constructor(e){if(super(e),this.inputSpec=[new Bt({ndim:4})],this.padding!=="same"&&this.padding!=="valid")throw new V(`Conv2DTranspose currently supports only padding modes 'same' and 'valid', but received padding mode ${this.padding}`)}build(e){if(e=Ze(e),e.length!==4)throw new V("Input should have rank 4; Received input shape: "+JSON.stringify(e));let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null)throw new V("The channel dimension of the inputs should be defined. Found `None`.");let n=e[t],a=this.kernelSize.concat([this.filters,n]);this.kernel=this.addWeight("kernel",a,"float32",this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[new Bt({ndim:4,axes:{[t]:n}})],this.built=!0}call(e,t){return P(()=>{let n=Te(e);if(n.shape.length!==4)throw new V(`Conv2DTranspose.call() expects input tensor to be rank-4, but received a tensor of rank-${n.shape.length}`);let a=n.shape,r=a[0],s,i;this.dataFormat==="channelsFirst"?(s=2,i=3):(s=1,i=2);let o=a[s],l=a[i],u=this.kernelSize[0],p=this.kernelSize[1],d=this.strides[0],c=this.strides[1],h=ar(o,d,u,this.padding),m=ar(l,c,p,this.padding),f=[r,h,m,this.filters];this.dataFormat!=="channelsLast"&&(n=De(n,[0,2,3,1]));let g=zm(n,this.kernel.read(),f,this.strides,this.padding);return this.dataFormat!=="channelsLast"&&(g=De(g,[0,3,1,2])),this.bias!=null&&(g=Ya(g,this.bias.read(),this.dataFormat)),this.activation!=null&&(g=this.activation.apply(g)),g})}computeOutputShape(e){e=Ze(e);let t=e.slice(),n,a,r;this.dataFormat==="channelsFirst"?(n=1,a=2,r=3):(n=3,a=1,r=2);let s=this.kernelSize[0],i=this.kernelSize[1],o=this.strides[0],l=this.strides[1];return t[n]=this.filters,t[a]=ar(t[a],o,s,this.padding),t[r]=ar(t[r],l,i,this.padding),t}getConfig(){let e=super.getConfig();return delete e.dilationRate,e}};g0.className="Conv2DTranspose";ne.registerClass(g0);var b0=class extends xd{constructor(e){if(super(e),this.inputSpec=[new Bt({ndim:5})],this.padding!=="same"&&this.padding!=="valid")throw new V(`Conv3DTranspose currently supports only padding modes 'same' and 'valid', but received padding mode ${this.padding}`)}build(e){if(e=Ze(e),e.length!==5)throw new V("Input should have rank 5; Received input shape: "+JSON.stringify(e));let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null)throw new V("The channel dimension of the inputs should be defined. Found `None`.");let n=e[t],a=this.kernelSize.concat([this.filters,n]);this.kernel=this.addWeight("kernel",a,"float32",this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[new Bt({ndim:5,axes:{[t]:n}})],this.built=!0}call(e,t){return P(()=>{let n=Te(e);if(n.shape.length!==5)throw new V(`Conv3DTranspose.call() expects input tensor to be rank-4, but received a tensor of rank-${n.shape.length}`);let a=n.shape,r=a[0],s,i,o;this.dataFormat==="channelsFirst"?(o=2,s=3,i=4):(o=1,s=2,i=3);let l=a[o],u=a[s],p=a[i],d=this.kernelSize[0],c=this.kernelSize[1],h=this.kernelSize[2],m=this.strides[0],f=this.strides[1],g=this.strides[2],b=ar(l,m,d,this.padding),y=ar(u,f,c,this.padding),x=ar(p,g,h,this.padding),w=[r,b,y,x,this.filters];this.dataFormat!=="channelsLast"&&(n=De(n,[0,2,3,4,1]));let I=Uv(n,this.kernel.read(),w,this.strides,this.padding);return this.dataFormat!=="channelsLast"&&(I=De(I,[0,4,1,2,3])),this.bias!==null&&(I=Ya(I,this.bias.read(),this.dataFormat)),this.activation!==null&&(I=this.activation.apply(I)),I})}computeOutputShape(e){e=Ze(e);let t=e.slice(),n,a,r,s;this.dataFormat==="channelsFirst"?(n=1,a=2,r=3,s=4):(n=4,a=1,r=2,s=3);let i=this.kernelSize[0],o=this.kernelSize[1],l=this.kernelSize[2],u=this.strides[0],p=this.strides[1],d=this.strides[2];return t[n]=this.filters,t[a]=ar(t[a],u,i,this.padding),t[r]=ar(t[r],p,o,this.padding),t[s]=ar(t[s],d,l,this.padding),t}getConfig(){let e=super.getConfig();return delete e.dilationRate,e}};b0.className="Conv3DTranspose";ne.registerClass(b0);var P2=class extends bd{constructor(e,t){if(super(e,t),this.DEFAULT_DEPTHWISE_INITIALIZER="glorotUniform",this.DEFAULT_POINTWISE_INITIALIZER="glorotUniform",this.depthwiseKernel=null,this.pointwiseKernel=null,t.filters==null)throw new V("The `filters` configuration field is required by SeparableConv, but is unspecified.");if(t.kernelInitializer!=null||t.kernelRegularizer!=null||t.kernelConstraint!=null)throw new V("Fields kernelInitializer, kernelRegularizer and kernelConstraint are invalid for SeparableConv2D. Use depthwiseInitializer, depthwiseRegularizer, depthwiseConstraint, pointwiseInitializer, pointwiseRegularizer and pointwiseConstraint instead.");if(t.padding!=null&&t.padding!=="same"&&t.padding!=="valid")throw new V(`SeparableConv${this.rank}D supports only padding modes: 'same' and 'valid', but received ${JSON.stringify(t.padding)}`);this.depthMultiplier=t.depthMultiplier==null?1:t.depthMultiplier,this.depthwiseInitializer=Tt(t.depthwiseInitializer||this.DEFAULT_DEPTHWISE_INITIALIZER),this.depthwiseRegularizer=Ct(t.depthwiseRegularizer),this.depthwiseConstraint=Yt(t.depthwiseConstraint),this.pointwiseInitializer=Tt(t.depthwiseInitializer||this.DEFAULT_POINTWISE_INITIALIZER),this.pointwiseRegularizer=Ct(t.pointwiseRegularizer),this.pointwiseConstraint=Yt(t.pointwiseConstraint)}build(e){if(e=Ze(e),e.length<this.rank+2)throw new V(`Inputs to SeparableConv${this.rank}D should have rank ${this.rank+2}, but received input shape: ${JSON.stringify(e)}`);let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null||e[t]<0)throw new V(`The channel dimension of the inputs should be defined, but found ${JSON.stringify(e[t])}`);let n=e[t],a=this.kernelSize.concat([n,this.depthMultiplier]),r=[];for(let i=0;i<this.rank;++i)r.push(1);r.push(n*this.depthMultiplier,this.filters);let s=!0;this.depthwiseKernel=this.addWeight("depthwise_kernel",a,"float32",this.depthwiseInitializer,this.depthwiseRegularizer,s,this.depthwiseConstraint),this.pointwiseKernel=this.addWeight("pointwise_kernel",r,"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 Bt({ndim:this.rank+2,axes:{[t]:n}})],this.built=!0}call(e,t){return P(()=>{e=Te(e);let n;if(this.rank===1)throw new Oe("1D separable convolution is not implemented yet.");return this.rank===2&&(this.dataFormat==="channelsFirst"&&(e=De(e,[0,2,3,1])),n=Ts(e,this.depthwiseKernel.read(),this.pointwiseKernel.read(),this.strides,this.padding,this.dilationRate,"NHWC")),this.useBias&&(n=Ya(n,this.bias.read(),this.dataFormat)),this.activation!=null&&(n=this.activation.apply(n)),this.dataFormat==="channelsFirst"&&(n=De(n,[0,3,1,2])),n})}getConfig(){let e=super.getConfig();return delete e.rank,delete e.kernelInitializer,delete e.kernelRegularizer,delete e.kernelConstraint,e.depthwiseInitializer=At(this.depthwiseInitializer),e.pointwiseInitializer=At(this.pointwiseInitializer),e.depthwiseRegularizer=mt(this.depthwiseRegularizer),e.pointwiseRegularizer=mt(this.pointwiseRegularizer),e.depthwiseConstraint=Xt(this.depthwiseConstraint),e.pointwiseConstraint=Xt(this.pointwiseConstraint),e}};P2.className="SeparableConv";var y0=class extends P2{constructor(e){super(2,e)}};y0.className="SeparableConv2D";ne.registerClass(y0);var Cf=class extends bd{constructor(e){super(1,e),Cf.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"&&!Ww(e.kernelSize,"number",1,1))throw new V(`Conv1D expects config.kernelSize to be number or number[] with length 1, but received ${JSON.stringify(e.kernelSize)}.`)}};Cf.className="Conv1D";ne.registerClass(Cf);var x0=class extends Be{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 P(()=>{if(e=Te(e),this.dataFormat==="channelsLast"){let n=yh(e,this.cropping[0][0],e.shape[1]-this.cropping[0][0]-this.cropping[0][1],2);return yh(n,this.cropping[1][0],e.shape[2]-this.cropping[1][1]-this.cropping[1][0],3)}else{let n=yh(e,this.cropping[0][0],e.shape[2]-this.cropping[0][0]-this.cropping[0][1],3);return yh(n,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}};x0.className="Cropping2D";ne.registerClass(x0);var v0=class extends Be{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,Pt(this.dataFormat),this.interpolation=e.interpolation==null?"nearest":e.interpolation,NU(this.interpolation)}computeOutputShape(e){if(this.dataFormat==="channelsFirst"){let t=e[2]==null?null:this.size[0]*e[2],n=e[3]==null?null:this.size[1]*e[3];return[e[0],e[1],t,n]}else{let t=e[1]==null?null:this.size[0]*e[1],n=e[2]==null?null:this.size[1]*e[2];return[e[0],t,n,e[3]]}}call(e,t){return P(()=>{let n=Te(e),a=n.shape;if(this.dataFormat==="channelsFirst"){n=De(n,[0,2,3,1]);let r=this.size[0]*a[2],s=this.size[1]*a[3],i=this.interpolation==="nearest"?Qn.resizeNearestNeighbor(n,[r,s]):Qn.resizeBilinear(n,[r,s]);return De(i,[0,3,1,2])}else{let r=this.size[0]*a[1],s=this.size[1]*a[2];return this.interpolation==="nearest"?Qn.resizeNearestNeighbor(n,[r,s]):Qn.resizeBilinear(n,[r,s])}})}getConfig(){let e={size:this.size,dataFormat:this.dataFormat,interpolation:this.interpolation},t=super.getConfig();return Object.assign(e,t),e}};v0.className="UpSampling2D";ne.registerClass(v0);function hH(e,t,n=[1,1],a="valid",r,s){return P(()=>{r==null&&(r=ja()),Pt(r);let i=m0(e,r);if(e.rank!==4)throw new V(`Input for depthwiseConv2d is required to be 4-D, but is instead ${e.rank}-D`);if(t.rank!==4)throw new V(`depthwiseKernel is required to be 4-D, but is instead ${t.rank}-D`);return i=Is(i,t,n,a==="same"?"same":"valid","NHWC",s),r==="channelsFirst"&&(i=De(i,[0,3,1,2])),i})}var w0=class extends f0{constructor(e){super(2,e),this.depthwiseKernel=null,this.depthMultiplier=e.depthMultiplier==null?1:e.depthMultiplier,this.depthwiseInitializer=Tt(e.depthwiseInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.depthwiseConstraint=Yt(e.depthwiseConstraint),this.depthwiseRegularizer=Ct(e.depthwiseRegularizer)}build(e){if(e=Ze(e),e.length<4)throw new V(`Inputs to DepthwiseConv2D should have rank 4. Received input shape: ${JSON.stringify(e)}.`);let t=this.dataFormat==="channelsFirst"?1:3;if(e[t]==null||e[t]<0)throw new V(`The channel dimension of the inputs to DepthwiseConv2D should be defined, but is not (${e[t]}).`);let n=e[t],a=[this.kernelSize[0],this.kernelSize[1],n,this.depthMultiplier];this.depthwiseKernel=this.addWeight("depthwise_kernel",a,null,this.depthwiseInitializer,this.depthwiseRegularizer,!0,this.depthwiseConstraint),this.useBias?this.bias=this.addWeight("bias",[n*this.depthMultiplier],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint):this.bias=null,this.built=!0}call(e,t){return P(()=>{e=Te(e);let n=hH(e,this.depthwiseKernel.read(),this.strides,this.padding,this.dataFormat,null);return this.useBias&&(n=Ya(n,this.bias.read(),this.dataFormat)),this.activation!=null&&(n=this.activation.apply(n)),n})}computeOutputShape(e){e=Ze(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],n=this.dataFormat==="channelsFirst"?e[3]:e[2],a=this.dataFormat==="channelsFirst"?e[1]*this.depthMultiplier:e[3]*this.depthMultiplier,r=Ha(t,this.kernelSize[0],this.padding,this.strides[0]),s=Ha(n,this.kernelSize[1],this.padding,this.strides[1]);return this.dataFormat==="channelsFirst"?[e[0],a,r,s]:[e[0],r,s,a]}getConfig(){let e=super.getConfig();return e.depthMultiplier=this.depthMultiplier,e.depthwiseInitializer=At(this.depthwiseInitializer),e.depthwiseRegularizer=mt(this.depthwiseRegularizer),e.depthwiseConstraint=Xt(this.depthwiseRegularizer),e}};w0.className="DepthwiseConv2D";ne.registerClass(w0);function O2(e,t,n,a){if(Array.isArray(e)){if(t!=null||n!=null)throw new V("When inputs is an array, neither initialState or constants should be provided");a!=null&&(n=e.slice(e.length-a,e.length),e=e.slice(0,e.length-a)),e.length>1&&(t=e.slice(1,e.length)),e=e[0]}function r(s){return s==null||Array.isArray(s)?s:[s]}return t=r(t),n=r(n),{inputs:e,initialState:t,constants:n}}function L2(e,t,n,a=!1,r,s,i=!1,o=!1){return P(()=>{let l=t.shape.length;if(l<3)throw new V(`Input should be at least 3D, but is ${l}D.`);let u=[1,0].concat(qa(2,l));if(t=De(t,u),s!=null)throw new Oe("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."),r!=null&&(r=ie(ie(r,"bool"),"float32"),r.rank===l-1&&(r=tn(r,-1)),r=De(r,u)),a&&(t=ba(t,0),r!=null&&(r=ba(r,0)));let p=[],d,c=n,h=t.shape[0],m=pt(t),f;r!=null&&(f=pt(r));for(let b=0;b<h;++b){let y=m[b],x=P(()=>e(y,c));if(r==null)d=x[0],c=x[1];else{let w=P(()=>{let I=f[b],T=pe(na(I),I),C=X(z(x[0],I),z(c[0],T)),E=c.map((F,D)=>X(z(x[1][D],I),z(F,T)));return{output:C,newStates:E}});d=w.output,c=w.newStates}o&&p.push(d)}let g;return o&&(g=Dt(p,1)),[d,g,c]})}var mr=class extends Be{constructor(e){super(e);let t;if(e.cell==null)throw new V("cell property is missing for the constructor of RNN.");if(Array.isArray(e.cell)?t=new Af({cells:e.cell}):t=e.cell,t.stateSize==null)throw new V("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 Bt({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 qa(0,e).map(t=>null)}else return this.states_}setStates(e){this.states_=e}computeOutputShape(e){Ex(e)&&(e=e[0]),e=e;let t=this.cell.stateSize;Array.isArray(t)||(t=[t]);let n=t[0],a;if(this.returnSequences?a=[e[0],e[1],n]:a=[e[0],n],this.returnState){let r=[];for(let s of t)r.push([e[0],s]);return[a].concat(r)}else return a}computeMask(e,t){return P(()=>{Array.isArray(t)&&(t=t[0]);let n=this.returnSequences?t:null;if(this.returnState){let a=this.states.map(r=>null);return[n].concat(a)}else return n})}get states(){if(this.states_==null){let e=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1,t=[];for(let n=0;n<e;++n)t.push(null);return t}else return this.states_}set states(e){this.states_=e}build(e){if(this.numConstants!=null)throw new Oe("Constants support is not implemented in RNN yet.");Ex(e)&&(e=e[0]),e=e;let t=this.stateful?e[0]:null,n=e.slice(2);this.inputSpec[0]=new Bt({shape:[t,null,...n]});let a=[e[0]].concat(e.slice(2));this.cell.build(a);let r;if(Array.isArray(this.cell.stateSize)?r=this.cell.stateSize:r=[this.cell.stateSize],this.stateSpec!=null){if(!v.arraysEqual(this.stateSpec.map(s=>s.shape[s.shape.length-1]),r))throw new V(`An initialState was passed that is not compatible with cell.stateSize. Received stateSpec=${this.stateSpec}; However cell.stateSize is ${this.cell.stateSize}`)}else this.stateSpec=r.map(s=>new Bt({shape:[null,s]}));this.stateful&&this.resetStates()}resetStates(e,t=!1){P(()=>{if(!this.stateful)throw new Ir("Cannot call resetStates() on an RNN Layer that is not stateful.");let n=this.inputSpec[0].shape[0];if(n==null)throw new V("If an RNN is stateful, it needs to know its batch size. Specify the batch size of your input tensors: \n- If using a Sequential model, specify the batch size by passing a `batchInputShape` option to your first layer.\n- If using the functional API, specify the batch size by passing a `batchShape` option to your Input layer.");if(this.states_==null)Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(a=>Nt([n,a])):this.states_=[Nt([n,this.cell.stateSize])];else if(e==null)_e(this.states_),this.keptStates!=null&&(_e(this.keptStates),this.keptStates=[]),Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(a=>Nt([n,a])):this.states_[0]=Nt([n,this.cell.stateSize]);else{if(Array.isArray(e)||(e=[e]),e.length!==this.states_.length)throw new V(`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()):_e(this.states_);for(let a=0;a<this.states_.length;++a){let r=e[a],s=Array.isArray(this.cell.stateSize)?this.cell.stateSize[a]:this.cell.stateSize,i=[n,s];if(!v.arraysEqual(r.shape,i))throw new V(`State ${a} is incompatible with layer ${this.name}: expected shape=${i}, received shape=${r.shape}`);this.states_[a]=r}}this.states_=this.states_.map(a=>Ht(a.clone()))})}apply(e,t){let n=t==null?null:t.initialState,a=t==null?null:t.constants;t==null&&(t={});let r=O2(e,n,a,this.numConstants);e=r.inputs,n=r.initialState,a=r.constants;let s=[],i=[];if(n!=null){t.initialState=n,s=s.concat(n),this.stateSpec=[];for(let o of n)this.stateSpec.push(new Bt({shape:o.shape}));i=i.concat(this.stateSpec)}if(a!=null&&(t.constants=a,s=s.concat(a),this.numConstants=a.length),s[0]instanceof Va){let o=[e].concat(s),l=this.inputSpec.concat(i),u=this.inputSpec;this.inputSpec=l;let p=super.apply(o,t);return this.inputSpec=u,p}else return super.apply(e,t)}call(e,t){return P(()=>{let n=t==null?null:t.mask,a=t==null?null:t.training,r=t==null?null:t.initialState;e=Te(e),r==null&&(this.stateful?r=this.states_:r=this.getInitialState(e));let s=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1;if(r.length!==s)throw new V(`RNN Layer has ${s} state(s) but was passed ${r.length} initial state(s).`);this.unroll&&console.warn("Ignoring unroll = true for RNN layer, due to imperative backend.");let i={training:a},o=L2((c,h)=>{let m=this.cell.call([c].concat(h),i);return[m[0],m.slice(1)]},e,r,this.goBackwards,n,null,this.unroll,this.returnSequences),l=o[0],u=o[1],p=o[2];this.stateful&&this.resetStates(p,a);let d=this.returnSequences?u:l;return this.returnState?[d].concat(p):d})}getInitialState(e){return P(()=>{let t=Nt(e.shape);return t=fe(t,[1,2]),t=dd(t),Array.isArray(this.cell.stateSize)?this.cell.stateSize.map(n=>n>1?Cx(t,[1,n]):t):this.cell.stateSize>1?[Cx(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 n=this.cell.getConfig();return this.getClassName()===mr.className&&(t.cell={className:this.cell.getClassName(),config:n}),Object.assign(Object.assign(Object.assign({},n),e),t)}static fromConfig(e,t,n={}){let a=t.cell,r=Ga(a,n);return new e(Object.assign(t,{cell:r}))}};mr.className="RNN";ne.registerClass(mr);var vd=class extends Be{},_f=class extends vd{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,nn(this.units,"units"),this.activation=ds(e.activation==null?this.DEFAULT_ACTIVATION:e.activation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=Tt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=Tt(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=Tt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelRegularizer=Ct(e.kernelRegularizer),this.recurrentRegularizer=Ct(e.recurrentRegularizer),this.biasRegularizer=Ct(e.biasRegularizer),this.kernelConstraint=Yt(e.kernelConstraint),this.recurrentConstraint=Yt(e.recurrentConstraint),this.biasConstraint=Yt(e.biasConstraint),this.dropout=Pl([1,ps([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=Pl([1,ps([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.dropoutFunc=e.dropoutFunc,this.stateSize=this.units,this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){e=Ze(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 P(()=>{if(e=e,e.length!==2)throw new V(`SimpleRNNCell expects 2 input Tensors, got ${e.length}.`);let n=e[1];e=e[0];let a=t.training==null?!1:t.training;0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=hs({ones:()=>na(e),rate:this.dropout,training:a,dropoutFunc:this.dropoutFunc})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=hs({ones:()=>na(n),rate:this.recurrentDropout,training:a,dropoutFunc:this.dropoutFunc}));let r,s=this.dropoutMask,i=this.recurrentDropoutMask;s!=null?r=or(z(e,s),this.kernel.read()):r=or(e,this.kernel.read()),this.bias!=null&&(r=Ya(r,this.bias.read())),i!=null&&(n=z(n,i));let o=X(r,or(n,this.recurrentKernel.read()));return this.activation!=null&&(o=this.activation.apply(o)),[o,o]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:cs(this.activation),useBias:this.useBias,kernelInitializer:At(this.kernelInitializer),recurrentInitializer:At(this.recurrentInitializer),biasInitializer:At(this.biasInitializer),kernelRegularizer:mt(this.kernelRegularizer),recurrentRegularizer:mt(this.recurrentRegularizer),biasRegularizer:mt(this.biasRegularizer),activityRegularizer:mt(this.activityRegularizer),kernelConstraint:Xt(this.kernelConstraint),recurrentConstraint:Xt(this.recurrentConstraint),biasConstraint:Xt(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout};return Object.assign(Object.assign({},e),t)}};_f.className="SimpleRNNCell";ne.registerClass(_f);var k0=class extends mr{constructor(e){e.cell=new _f(e),super(e)}call(e,t){return P(()=>{this.cell.dropoutMask!=null&&(_e(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(_e(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=t==null?null:t.mask,a=t==null?null:t.training,r=t==null?null:t.initialState;return super.call(e,{mask:n,training:a,initialState:r})})}static fromConfig(e,t){return new e(t)}};k0.className="SimpleRNN";ne.registerClass(k0);var Ef=class extends vd{constructor(e){if(super(e),this.DEFAULT_ACTIVATION="tanh",this.DEFAULT_RECURRENT_ACTIVATION="hardSigmoid",this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_RECURRENT_INITIALIZER="orthogonal",this.DEFAULT_BIAS_INITIALIZER="zeros",e.resetAfter)throw new V("GRUCell does not support reset_after parameter set to true.");this.units=e.units,nn(this.units,"units"),this.activation=ds(e.activation===void 0?this.DEFAULT_ACTIVATION:e.activation),this.recurrentActivation=ds(e.recurrentActivation===void 0?this.DEFAULT_RECURRENT_ACTIVATION:e.recurrentActivation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=Tt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=Tt(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=Tt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelRegularizer=Ct(e.kernelRegularizer),this.recurrentRegularizer=Ct(e.recurrentRegularizer),this.biasRegularizer=Ct(e.biasRegularizer),this.kernelConstraint=Yt(e.kernelConstraint),this.recurrentConstraint=Yt(e.recurrentConstraint),this.biasConstraint=Yt(e.biasConstraint),this.dropout=Pl([1,ps([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=Pl([1,ps([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=Ze(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 P(()=>{if(e=e,e.length!==2)throw new V(`GRUCell expects 2 input Tensors (inputs, h, c), got ${e.length}.`);let n=t.training==null?!1:t.training,a=e[1];e=e[0],0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=hs({ones:()=>na(e),rate:this.dropout,training:n,count:3,dropoutFunc:this.dropoutFunc})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=hs({ones:()=>na(a),rate:this.recurrentDropout,training:n,count:3,dropoutFunc:this.dropoutFunc}));let r=this.dropoutMask,s=this.recurrentDropoutMask,i,o,l;0<this.dropout&&this.dropout<1&&(e=z(e,r[0]));let u=or(e,this.kernel.read());this.useBias&&(u=Ya(u,this.bias.read())),0<this.recurrentDropout&&this.recurrentDropout<1&&(a=z(a,s[0]));let p=this.recurrentKernel.read(),[d,c]=zn(p,[2*this.units,this.units],p.rank-1),h=or(a,d),[m,f,g]=zn(u,3,u.rank-1),[b,y]=zn(h,2,h.rank-1);i=this.recurrentActivation.apply(X(m,b)),o=this.recurrentActivation.apply(X(f,y));let x=or(z(o,a),c);l=this.activation.apply(X(g,x));let w=X(z(i,a),z(X(1,yt(i)),l));return[w,w]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:cs(this.activation),recurrentActivation:cs(this.recurrentActivation),useBias:this.useBias,kernelInitializer:At(this.kernelInitializer),recurrentInitializer:At(this.recurrentInitializer),biasInitializer:At(this.biasInitializer),kernelRegularizer:mt(this.kernelRegularizer),recurrentRegularizer:mt(this.recurrentRegularizer),biasRegularizer:mt(this.biasRegularizer),activityRegularizer:mt(this.activityRegularizer),kernelConstraint:Xt(this.kernelConstraint),recurrentConstraint:Xt(this.recurrentConstraint),biasConstraint:Xt(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation,resetAfter:!1};return Object.assign(Object.assign({},e),t)}};Ef.className="GRUCell";ne.registerClass(Ef);var I0=class extends mr{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 Ef(e),super(e)}call(e,t){return P(()=>{this.cell.dropoutMask!=null&&(_e(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(_e(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=t==null?null:t.mask,a=t==null?null:t.training,r=t==null?null:t.initialState;return super.call(e,{mask:n,training:a,initialState:r})})}static fromConfig(e,t){return t.implmentation===0&&(t.implementation=1),new e(t)}};I0.className="GRU";ne.registerClass(I0);var wd=class extends vd{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,nn(this.units,"units"),this.activation=ds(e.activation===void 0?this.DEFAULT_ACTIVATION:e.activation),this.recurrentActivation=ds(e.recurrentActivation===void 0?this.DEFAULT_RECURRENT_ACTIVATION:e.recurrentActivation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=Tt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=Tt(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=Tt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.unitForgetBias=e.unitForgetBias,this.kernelRegularizer=Ct(e.kernelRegularizer),this.recurrentRegularizer=Ct(e.recurrentRegularizer),this.biasRegularizer=Ct(e.biasRegularizer),this.kernelConstraint=Yt(e.kernelConstraint),this.recurrentConstraint=Yt(e.recurrentConstraint),this.biasConstraint=Yt(e.biasConstraint),this.dropout=Pl([1,ps([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=Pl([1,ps([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=Ze(e);let n=e[e.length-1];this.kernel=this.addWeight("kernel",[n,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 a;if(this.useBias){if(this.unitForgetBias){let r=this.biasInitializer,s=this.units;a=new(t=class extends Ra{apply(i,o){let l=r.apply([s]),u=new bf().apply([s]),p=r.apply([s*2]);return eI(eI(l,u),p)}},t.className="CustomInit",t)}else a=this.biasInitializer;this.bias=this.addWeight("bias",[this.units*4],null,a,this.biasRegularizer,!0,this.biasConstraint)}else this.bias=null;this.built=!0}call(e,t){return P(()=>{let n=t.training==null?!1:t.training;if(e=e,e.length!==3)throw new V(`LSTMCell expects 3 input Tensors (inputs, h, c), got ${e.length}.`);let a=e[1],r=e[2];e=e[0],0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=hs({ones:()=>na(e),rate:this.dropout,training:n,count:4,dropoutFunc:this.dropoutFunc})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=hs({ones:()=>na(a),rate:this.recurrentDropout,training:n,count:4,dropoutFunc:this.dropoutFunc}));let s=this.dropoutMask,i=this.recurrentDropoutMask,o,l,u,p;0<this.dropout&&this.dropout<1&&(e=z(e,s[0]));let d=or(e,this.kernel.read());0<this.recurrentDropout&&this.recurrentDropout<1&&(a=z(a,i[0])),d=X(d,or(a,this.recurrentKernel.read())),this.useBias&&(d=Ya(d,this.bias.read()));let[c,h,m,f]=zn(d,4,d.rank-1);o=this.recurrentActivation.apply(c),l=this.recurrentActivation.apply(h),u=X(z(l,r),z(o,this.activation.apply(m))),p=this.recurrentActivation.apply(f);let g=z(p,this.activation.apply(u));return[g,g,u]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:cs(this.activation),recurrentActivation:cs(this.recurrentActivation),useBias:this.useBias,kernelInitializer:At(this.kernelInitializer),recurrentInitializer:At(this.recurrentInitializer),biasInitializer:At(this.biasInitializer),unitForgetBias:this.unitForgetBias,kernelRegularizer:mt(this.kernelRegularizer),recurrentRegularizer:mt(this.recurrentRegularizer),biasRegularizer:mt(this.biasRegularizer),activityRegularizer:mt(this.activityRegularizer),kernelConstraint:Xt(this.kernelConstraint),recurrentConstraint:Xt(this.recurrentConstraint),biasConstraint:Xt(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation};return Object.assign(Object.assign({},e),t)}};wd.className="LSTMCell";ne.registerClass(wd);var S0=class extends mr{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 wd(e),super(e)}call(e,t){return P(()=>{this.cell.dropoutMask!=null&&(_e(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(_e(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=t==null?null:t.mask,a=t==null?null:t.training,r=t==null?null:t.initialState;return super.call(e,{mask:n,training:a,initialState:r})})}static fromConfig(e,t){return t.implmentation===0&&(t.implementation=1),new e(t)}};S0.className="LSTM";ne.registerClass(S0);var Af=class extends vd{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 P(()=>{e=e;let n=e.slice(1),a=[];for(let i of this.cells.slice().reverse())Array.isArray(i.stateSize)?a.push(n.splice(0,i.stateSize.length)):a.push(n.splice(0,1));a.reverse();let r=[],s;for(let i=0;i<this.cells.length;++i){let o=this.cells[i];n=a[i],i===0?s=[e[0]].concat(n):s=[s[0]].concat(n),s=o.call(s,t),r.push(s.slice(1))}n=[];for(let i of r.slice().reverse())n.push(...i);return[s[0]].concat(n)})}build(e){Ex(e)&&(e=e[0]),e=e;let t;this.cells.forEach((n,a)=>{ai(`RNNCell_${a}`,()=>{n.build(e),Array.isArray(n.stateSize)?t=n.stateSize[0]:t=n.stateSize,e=[e[0],t]})}),this.built=!0}getConfig(){let e=super.getConfig(),t=a=>({className:a.getClassName(),config:a.getConfig()}),n={cells:this.cells.map(t)};return Object.assign(Object.assign({},e),n)}static fromConfig(e,t,n={}){let a=[];for(let r of t.cells)a.push(Ga(r,n));return new e({cells:a})}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 n of this.cells)t.push(...n.trainableWeights);return t.concat(e)}return e}getWeights(){let e=[];for(let t of this.cells)e.push(...t.weights);return Ax(e)}setWeights(e){let t=[];for(let n of this.cells){let a=n.weights.length,r=e.splice(a);for(let s=0;s<n.weights.length;++s)t.push([n.weights[s],r[s]])}Xw(t)}};Af.className="StackedRNNCells";ne.registerClass(Af);function hs(e){let{ones:t,rate:n,training:a=!1,count:r=1,dropoutFunc:s}=e,i=()=>s!=null?s(t(),n):YT(t(),n),o=()=>md(i,t,a);return!r||r<=1?Ht(o().clone()):Array(r).fill(void 0).map(o).map(l=>Ht(l.clone()))}var mH=function(e,t){var n={};for(var a in e)Object.prototype.hasOwnProperty.call(e,a)&&t.indexOf(a)<0&&(n[a]=e[a]);if(e!=null&&typeof Object.getOwnPropertySymbols=="function")for(var r=0,a=Object.getOwnPropertySymbols(e);r<a.length;r++)t.indexOf(a[r])<0&&Object.prototype.propertyIsEnumerable.call(e,a[r])&&(n[a[r]]=e[a[r]]);return n},z2=class extends mr{constructor(e){if(e.unroll)throw new Oe("Unrolling is not possible with convolutional RNNs.");if(Array.isArray(e.cell))throw new Oe("It is not possible at the moment to stack convolutional cells.");super(e),this.inputSpec=[new Bt({ndim:5})]}call(e,t){return P(()=>{if(this.cell.dropoutMask!=null&&(_e(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(_e(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null),t&&t.constants)throw new V("ConvRNN2D cell does not support constants");let n=t==null?null:t.mask,a=t==null?null:t.training,r=t==null?null:t.initialState;return super.call(e,{mask:n,training:a,initialState:r})})}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 P(()=>{let{stateSize:t}=this.cell,n=e.shape,a=this.computeSingleOutputShape(n),r=[a[0],...a.slice(2)],s=Nt(r);return Array.isArray(t)?Array(t.length).fill(s):[s]})}resetStates(e,t=!1){P(()=>{if(!this.stateful)throw new Ir("Cannot call resetStates() on an RNN Layer that is not stateful.");let n=this.inputSpec[0].shape,a=this.computeSingleOutputShape(n),r=[a[0],...a.slice(2)];if(n[0]==null)throw new V("If an RNN is stateful, it needs to know its batch size. Specify the batch size of your input tensors: \n- If using a Sequential model, specify the batch size by passing a `batchInputShape` option to your first layer.\n- If using the functional API, specify the batch size by passing a `batchShape` option to your Input layer.");if(this.getStates()==null)Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(()=>Nt(r)):this.states_=[Nt(r)];else if(e==null)_e(this.states_),this.keptStates!=null&&(_e(this.keptStates),this.keptStates=[]),Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(()=>Nt(r)):this.states_[0]=Nt(r);else{if(Array.isArray(e)||(e=[e]),e.length!==this.states_.length)throw new V(`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()):_e(this.states_);for(let s=0;s<this.states_.length;++s){let i=e[s],o=r;if(!v.arraysEqual(i.shape,o))throw new V(`State ${s} is incompatible with layer ${this.name}: expected shape=${o}, received shape=${i.shape}`);this.states_[s]=i}}this.states_=this.states_.map(s=>Ht(s.clone()))})}computeSingleOutputShape(e){let{dataFormat:t,filters:n,kernelSize:a,padding:r,strides:s,dilationRate:i}=this.cell,o=t==="channelsFirst",l=e[o?3:2],u=e[o?4:3],p=Ha(l,a[0],r,s[0],i[0]),d=Ha(u,a[1],r,s[1],i[1]);return[...e.slice(0,2),...o?[n,p,d]:[p,d,n]]}};z2.className="ConvRNN2D";var Ff=class extends wd{constructor(e){let{filters:t,kernelSize:n,strides:a,padding:r,dataFormat:s,dilationRate:i}=e;super(Object.assign(Object.assign({},e),{units:t})),this.filters=t,nn(this.filters,"filters"),this.kernelSize=Il(n,2,"kernelSize"),this.kernelSize.forEach(o=>nn(o,"kernelSize")),this.strides=Il(a||1,2,"strides"),this.strides.forEach(o=>nn(o,"strides")),this.padding=r||"valid",va(this.padding),this.dataFormat=s||"channelsLast",Pt(this.dataFormat),this.dilationRate=Il(i||1,2,"dilationRate"),this.dilationRate.forEach(o=>nn(o,"dilationRate"))}build(e){var t;e=Ze(e);let n=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[n]==null)throw new V(`The channel dimension of the input should be defined. Found ${e[n]}`);let a=e[n],r=4,s=this.kernelSize.concat([a,this.filters*r]);this.kernel=this.addWeight("kernel",s,null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint);let i=this.kernelSize.concat([this.filters,this.filters*r]);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 Ra{apply(p,d){let c=l.apply([u]),h=Jn([u]),m=l.apply([u*2]);return Bw([c,h,m])}},t.className="CustomInit",t)}else o=this.biasInitializer;this.bias=this.addWeight("bias",[this.filters*r],null,o,this.biasRegularizer,!0,this.biasConstraint)}this.built=!0}call(e,t){return P(()=>{if(e.length!==3)throw new V(`ConvLSTM2DCell expects 3 input Tensors (inputs, h, c), got ${e.length}.`);let n=t.training||!1,a=e[0],r=e[1],s=e[2],i=4;0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=hs({ones:()=>na(a),rate:this.dropout,training:n,count:i,dropoutFunc:this.dropoutFunc}));let o=this.dropoutMask,l=(Z,J,ee)=>!J||!J[ee]?Z:z(J[ee],Z),u=l(a,o,0),p=l(a,o,1),d=l(a,o,2),c=l(a,o,3);0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=hs({ones:()=>na(r),rate:this.recurrentDropout,training:n,count:i,dropoutFunc:this.dropoutFunc}));let h=this.recurrentDropoutMask,m=l(r,h,0),f=l(r,h,1),g=l(r,h,2),b=l(r,h,3),y=3,[x,w,I,T]=zn(this.kernel.read(),i,y),[C,E,F,D]=this.useBias?zn(this.bias.read(),i):[null,null,null,null];u=this.inputConv(u,x,C,this.padding),p=this.inputConv(p,w,E,this.padding),d=this.inputConv(d,I,F,this.padding),c=this.inputConv(c,T,D,this.padding);let[$,S,M,B]=zn(this.recurrentKernel.read(),i,y);m=this.recurrentConv(m,$),f=this.recurrentConv(f,S),g=this.recurrentConv(g,M),b=this.recurrentConv(b,B);let U=this.recurrentActivation.apply(X(u,m)),H=this.recurrentActivation.apply(X(p,f)),j=X(z(H,s),z(U,this.activation.apply(X(d,g)))),K=z(this.recurrentActivation.apply(X(c,b)),this.activation.apply(j));return[K,K,j]})}getConfig(){let e=super.getConfig(),{units:t}=e,n=mH(e,["units"]),a={filters:this.filters,kernelSize:this.kernelSize,padding:this.padding,dataFormat:this.dataFormat,dilationRate:this.dilationRate,strides:this.strides};return Object.assign(Object.assign({},n),a)}inputConv(e,t,n,a){let r=Rt(e,t,this.strides,a||"valid",this.dataFormat==="channelsFirst"?"NCHW":"NHWC",this.dilationRate);return n?Ya(r,n,this.dataFormat):r}recurrentConv(e,t){return Rt(e,t,1,"same",this.dataFormat==="channelsFirst"?"NCHW":"NHWC")}};Ff.className="ConvLSTM2DCell";ne.registerClass(Ff);var N0=class extends z2{constructor(e){let t=new Ff(e);super(Object.assign(Object.assign({},e),{cell:t}))}static fromConfig(e,t){return new e(t)}};N0.className="ConvLSTM2D";ne.registerClass(N0);var $f=class extends Be{constructor(e){super(e),this.rate=Math.max(Math.min(e.rate,1),0),this.noiseShape=e.noiseShape,this.seed=e.seed,this.supportsMasking=!0}getNoiseShape(e){if(this.noiseShape==null)return this.noiseShape;let t=e.shape,n=[];for(let a=0;a<this.noiseShape.length;++a)n.push(this.noiseShape[a]==null?t[a]:this.noiseShape[a]);return n}call(e,t){return P(()=>{this.invokeCallHook(e,t);let n=Te(e);if(0<this.rate&&this.rate<1){let a=t.training==null?!1:t.training,r=this.getNoiseShape(n);return md(()=>YT(n,this.rate,r,this.seed),()=>n,a)}return e})}getConfig(){let e={rate:this.rate,noiseShape:this.noiseShape,seed:this.seed},t=super.getConfig();return Object.assign(e,t),e}dispose(){return super.dispose()}};$f.className="Dropout";ne.registerClass($f);var T0=class extends $f{constructor(e){super(e),this.inputSpec=[{ndim:3}]}getNoiseShape(e){let t=e.shape;return[t[0],1,t[2]]}};T0.className="SpatialDropout1D";ne.registerClass(T0);var C0=class extends Be{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,nn(this.units,"units"),this.activation=ds(e.activation),e.useBias!=null&&(this.useBias=e.useBias),this.kernelInitializer=Tt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.biasInitializer=Tt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelConstraint=Yt(e.kernelConstraint),this.biasConstraint=Yt(e.biasConstraint),this.kernelRegularizer=Ct(e.kernelRegularizer),this.biasRegularizer=Ct(e.biasRegularizer),this.activityRegularizer=Ct(e.activityRegularizer),this.supportsMasking=!0,this.inputSpec=[{minNDim:2}]}build(e){e=Ze(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=Ze(e);let t=e.slice();return t[t.length-1]=this.units,t}call(e,t){return P(()=>{this.invokeCallHook(e,t);let n=Te(e),a=UT(this.activation.getClassName()),r;return a!=null?r=or(n,this.kernel.read(),a,this.bias?this.bias.read():null):(r=or(n,this.kernel.read()),this.bias!=null&&(r=Ya(r,this.bias.read())),this.activation!=null&&(r=this.activation.apply(r))),r})}getConfig(){let e={units:this.units,activation:cs(this.activation),useBias:this.useBias,kernelInitializer:At(this.kernelInitializer),biasInitializer:At(this.biasInitializer),kernelRegularizer:mt(this.kernelRegularizer),biasRegularizer:mt(this.biasRegularizer),activityRegularizer:mt(this.activityRegularizer),kernelConstraint:Xt(this.kernelConstraint),biasConstraint:Xt(this.biasConstraint)},t=super.getConfig();return Object.assign(e,t),e}};C0.className="Dense";ne.registerClass(C0);var _0=class extends Be{constructor(e){e=e||{},super(e),this.inputSpec=[{minNDim:3}],this.dataFormat=e.dataFormat}computeOutputShape(e){e=Ze(e);for(let t of e.slice(1))if(t==null)throw new V(`The shape of the input to "Flatten" is not fully defined (got ${e.slice(1)}). Make sure to pass a complete "input_shape" or "batch_input_shape" argument to the first layer in your model.`);return[e[0],rs(e,1)]}call(e,t){return P(()=>{this.invokeCallHook(e,t);let n=Te(e);if(this.dataFormat==="channelsFirst"&&n.rank>1){let a=[0];for(let r=2;r<n.rank;++r)a.push(r);a.push(1),n=De(n,a)}return FU(n)})}getConfig(){let e={};this.dataFormat!=null&&(e.dataFormat=this.dataFormat);let t=super.getConfig();return Object.assign(e,t),e}};_0.className="Flatten";ne.registerClass(_0);var E0=class extends Be{constructor(e){super(e),this.supportsMasking=!0,this.activation=ds(e.activation)}call(e,t){return P(()=>{this.invokeCallHook(e,t);let n=Te(e);return this.activation.apply(n)})}getConfig(){let e={activation:cs(this.activation)},t=super.getConfig();return Object.assign(e,t),e}};E0.className="Activation";ne.registerClass(E0);var A0=class extends Be{constructor(e){super(e),this.n=e.n,this.inputSpec=[{ndim:2}]}computeOutputShape(e){return[e[0],this.n,e[1]]}call(e,t){return 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n=Te(e),a=n.shape,r=a.slice(0,1).concat(this.fixUnknownDimension(a.slice(1),this.targetShape));return W(n,r)})}getConfig(){let e={targetShape:this.targetShape},t=super.getConfig();return Object.assign(e,t),e}};F0.className="Reshape";ne.registerClass(F0);var $0=class extends Be{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=qa(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 Bt({ndim:this.dims.length+1})]}computeOutputShape(e){e=Ze(e);let t=e.slice();return this.dims.forEach((n,a)=>{t[a+1]=e[n]}),t}call(e,t){return 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Ho=class extends Be{constructor(e){super(e||{}),this.supportsMasking=!0}mergeFunction(e){throw new Oe}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 n=e.slice(0,e.length-t.length);for(let a=0;a<t.length;++a){let r=e[e.length-t.length+a],s=t[a];if(r==null||s==null||r<0||s<0)n.push(null);else if(r===1)n.push(s);else if(s===1)n.push(r);else{if(r!==s)throw new V("Operands could not be broadcast together with shapes "+JSON.stringify(e)+" "+JSON.stringify(t));n.push(r)}}return n}build(e){if(Array.isArray(e)&&!Array.isArray(e[0])&&(e=[Ze(e)]),e=e,e.length<2)throw new V(`A merge layer should be called on an Array of at least 2 inputs. 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t=this.axis>=0?this.axis:this.axis+e.length,n=e[t];if(n==null)throw new V(`Axis ${t} of input tensor should have a defined dimension but the layer received an input with shape ${JSON.stringify(e)}.`);this.inputSpec=[new Bt({ndim:e.length,axes:{[t]:n}})];let a=[n];this.scale&&(this.gamma=this.addWeight("gamma",a,null,this.gammaInitializer,this.gammaRegularizer,!0,this.gammaConstraint)),this.center&&(this.beta=this.addWeight("beta",a,null,this.betaInitializer,this.betaRegularizer,!0,this.betaConstraint)),this.movingMean=this.addWeight("moving_mean",a,null,this.movingMeanInitializer,null,!1),this.movingVariance=this.addWeight("moving_variance",a,null,this.movingVarianceInitializer,null,!1),this.built=!0}call(e,t){return P(()=>{let n=t.training==null?!1:t.training,a=Te(e),r=a.shape,s=r.length,i=qa(0,s),o=this.axis>=0?this.axis:this.axis+s;i.splice(o,1);let l=gi(1,s);l[o]=r[o];let u=i.slice();u.sort();let p=!v.arraysEqual(u,qa(0,s).slice(0,s-1)),d=()=>{if(p){let 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e={axis:this.axis,momentum:this.momentum,epsilon:this.epsilon,center:this.center,scale:this.scale,betaInitializer:At(this.betaInitializer),gammaInitializer:At(this.gammaInitializer),movingMeanInitializer:At(this.movingMeanInitializer),movingVarianceInitializer:At(this.movingVarianceInitializer),betaRegularizer:mt(this.betaRegularizer),gammaRegularizer:mt(this.gammaRegularizer),betaConstraint:Xt(this.betaConstraint),gammaConstraint:Xt(this.gammaConstraint)},t=super.getConfig();return Object.assign(e,t),e}};H0.className="BatchNormalization";ne.registerClass(H0);var q0=class extends Be{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=Tt(e.betaInitializer||"zeros"),this.gammaInitializer=Tt(e.gammaInitializer||"ones"),this.betaRegularizer=Ct(e.betaRegularizer),this.gammaRegularizer=Ct(e.gammaRegularizer),this.supportsMasking=!0}build(e){e=Ze(e);let t=e.length;typeof this.axis=="number"&&(this.axis=[this.axis]);for(let r=0;r<this.axis.length;++r)this.axis[r]<0&&(this.axis[r]+=t);for(let r of this.axis)if(r<0||r>=t)throw new Error(`Invalid axis: ${r}`);if(this.axis.length!==as(this.axis).length)throw new Error(`Found duplicate axes in: ${this.axis}`);let n=this.axis.map(r=>e[r]),a=!0;this.scale?this.gamma=this.addWeight("gamma",n,"float32",this.gammaInitializer,this.gammaRegularizer,a):this.gamma=null,this.center?this.beta=this.addWeight("beta",n,"float32",this.betaInitializer,this.betaRegularizer,a):this.beta=null,this.built=!0}call(e,t){let n=Te(e),a=n.shape,r=a.length;return P(()=>{let{mean:s,variance:i}=rd(n,this.axis,!0),o=gi(1,r);for(let h of this.axis)o[h]=a[h];let l=h=>h!=null&&h.shape.length!==r?W(h,o):h,u=this.scale?l(this.gamma.read()):null,p=this.center?l(this.beta.read()):null,d=[],c=[];for(let h=0;h<r;++h)this.axis.indexOf(h)!==-1?(d.push(a[h]),c.push(1)):(d.push(1),c.push(a[h]));return s=Ln(s,d),i=Ln(i,d),u!=null&&(u=Ln(u,c)),p!=null&&(p=Ln(p,c)),xc(n,s,i,p,u,this.epsilon)})}getConfig(){let e={axis:this.axis,epsilon:this.epsilon,center:this.center,scale:this.scale,betaInitializer:At(this.betaInitializer),gammaInitializer:At(this.gammaInitializer),betaRegularizer:mt(this.betaRegularizer),gammaRegularizer:mt(this.gammaRegularizer)},t=super.getConfig();return Object.assign(e,t),e}};q0.className="LayerNormalization";ne.registerClass(q0);function xH(e,t,n){return P(()=>{if(e.rank!==4)throw new V(`temporalPadding expects input tensor to be 4-D, but received a ${e.rank}-D tensor.`);if(t==null&&(t=[[1,1],[1,1]]),t.length!==2||t[0].length!==2||t[1].length!==2)throw new V("spatial2dPadding expects `padding` to be an Array of two Arrays, each of which is an Array of two integers.");if(n==null&&(n=ja()),n!=="channelsLast"&&n!=="channelsFirst")throw new V(`Unknown data format: ${n}. Supported data formats are 'channelsLast' and 'channelsFirst.`);let a;return n==="channelsFirst"?a=[[0,0],[0,0],t[0],t[1]]:a=[[0,0],t[0],t[1],[0,0]],xa(e,a)})}var j0=class extends Be{constructor(e){if(e==null&&(e={}),super(e),this.dataFormat=e.dataFormat==null?ja():e.dataFormat,e.padding==null)this.padding=[[1,1],[1,1]];else if(typeof e.padding=="number")this.padding=[[e.padding,e.padding],[e.padding,e.padding]];else{if(e.padding=e.padding,e.padding.length!==2)throw new V(`ZeroPadding2D expects padding to be a length-2 array, but received a length-${e.padding.length} array.`);let t,n;if(typeof e.padding[0]=="number")t=[e.padding[0],e.padding[0]],n=[e.padding[1],e.padding[1]];else{if(e.padding=e.padding,e.padding[0].length!==2)throw new V(`ZeroPadding2D expects height padding to be a length-2 array, but received a length-${e.padding[0].length} array.`);if(t=e.padding[0],e.padding[1].length!==2)throw new V(`ZeroPadding2D expects width padding to be a length-2 array, but received a length-${e.padding[1].length} array.`);n=e.padding[1]}this.padding=[t,n]}this.inputSpec=[new Bt({ndim:4})]}computeOutputShape(e){e=Ze(e);let t,n;return this.dataFormat==="channelsFirst"?(e[2]!=null&&e[2]>=0?t=e[2]+this.padding[0][0]+this.padding[0][1]:t=null,e[3]!=null&&e[3]>=0?n=e[3]+this.padding[1][0]+this.padding[1][1]:n=null,[e[0],e[1],t,n]):(e[1]!=null&&e[1]>=0?t=e[1]+this.padding[0][0]+this.padding[0][1]:t=null,e[2]!=null&&e[2]>=0?n=e[2]+this.padding[1][0]+this.padding[1][1]:n=null,[e[0],t,n,e[3]])}call(e,t){return P(()=>xH(Te(e),this.padding,this.dataFormat))}getConfig(){let e={padding:this.padding,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}};j0.className="ZeroPadding2D";ne.registerClass(j0);function Df(e,t,n,a,r,s){return P(()=>{Pt(r),HT(s),va(a),n==null&&(n=[1,1]),a==null&&(a="valid"),r==null&&(r=ja()),s==null&&(s="max"),e=m0(e,r);let i,o=a==="same"?"same":"valid";return s==="max"?i=Mt(e,t,n,o):i=ya(e,t,n,o),r==="channelsFirst"&&(i=De(i,[0,3,1,2])),i})}function W2(e,t,n,a,r,s){return P(()=>{Pt(r),HT(s),va(a),n==null&&(n=[1,1,1]),a==null&&(a="valid"),r==null&&(r=ja()),s==null&&(s="max"),e=M2(e,r);let i,o=a==="same"?"same":"valid";return s==="max"?i=sw(e,t,n,o):i=Fv(e,t,n,o),r==="channelsFirst"&&(i=De(i,[0,4,1,2,3])),i})}var B2=class extends Be{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 V(`poolSize for 1D convolutional layer must be a number or an Array of a single number, but received ${JSON.stringify(e.poolSize)}`);if(nn(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 V(`strides for 1D convolutional layer must be a number or an Array of a single number, but received ${JSON.stringify(e.strides)}`);nn(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,va(this.padding),this.inputSpec=[new Bt({ndim:3})]}computeOutputShape(e){e=Ze(e);let t=Ha(e[1],this.poolSize[0],this.padding,this.strides[0]);return[e[0],t,e[2]]}call(e,t){return P(()=>{this.invokeCallHook(e,t),e=dd(Te(e),2);let n=this.poolingFunction(Te(e),[this.poolSize[0],1],[this.strides[0],1],this.padding,"channelsLast");return Cs(n,[2])})}getConfig(){let e={poolSize:this.poolSize,padding:this.padding,strides:this.strides},t=super.getConfig();return Object.assign(e,t),e}},K0=class extends B2{constructor(e){super(e)}poolingFunction(e,t,n,a,r){return Pt(r),va(a),Df(e,t,n,a,r,"max")}};K0.className="MaxPooling1D";ne.registerClass(K0);var X0=class extends B2{constructor(e){super(e)}poolingFunction(e,t,n,a,r){return Pt(r),va(a),Df(e,t,n,a,r,"avg")}};X0.className="AveragePooling1D";ne.registerClass(X0);var V2=class extends Be{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 V(`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];nn(this.poolSize,"poolSize"),nn(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,Pt(this.dataFormat),va(this.padding),this.inputSpec=[new Bt({ndim:4})]}computeOutputShape(e){e=Ze(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],n=this.dataFormat==="channelsFirst"?e[3]:e[2];return t=Ha(t,this.poolSize[0],this.padding,this.strides[0]),n=Ha(n,this.poolSize[1],this.padding,this.strides[1]),this.dataFormat==="channelsFirst"?[e[0],e[1],t,n]:[e[0],t,n,e[3]]}call(e,t){return P(()=>(this.invokeCallHook(e,t),this.poolingFunction(Te(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}},Y0=class extends V2{constructor(e){super(e)}poolingFunction(e,t,n,a,r){return Pt(r),va(a),Df(e,t,n,a,r,"max")}};Y0.className="MaxPooling2D";ne.registerClass(Y0);var Z0=class extends V2{constructor(e){super(e)}poolingFunction(e,t,n,a,r){return Pt(r),va(a),Df(e,t,n,a,r,"avg")}};Z0.className="AveragePooling2D";ne.registerClass(Z0);var U2=class extends Be{constructor(e){if(e.poolSize==null&&(e.poolSize=[2,2,2]),super(e),this.poolSize=Array.isArray(e.poolSize)?e.poolSize:[e.poolSize,e.poolSize,e.poolSize],e.strides==null)this.strides=this.poolSize;else if(Array.isArray(e.strides)){if(e.strides.length!==3)throw new V(`If the strides property of a 3D pooling layer is an Array, it is expected to have a length of 3, but received length ${e.strides.length}.`);this.strides=e.strides}else this.strides=[e.strides,e.strides,e.strides];nn(this.poolSize,"poolSize"),nn(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,Pt(this.dataFormat),va(this.padding),this.inputSpec=[new Bt({ndim:5})]}computeOutputShape(e){e=Ze(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],n=this.dataFormat==="channelsFirst"?e[3]:e[2],a=this.dataFormat==="channelsFirst"?e[4]:e[3];return t=Ha(t,this.poolSize[0],this.padding,this.strides[0]),n=Ha(n,this.poolSize[1],this.padding,this.strides[1]),a=Ha(a,this.poolSize[2],this.padding,this.strides[2]),this.dataFormat==="channelsFirst"?[e[0],e[1],t,n,a]:[e[0],t,n,a,e[4]]}call(e,t){return P(()=>(this.invokeCallHook(e,t),this.poolingFunction(Te(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}},J0=class extends U2{constructor(e){super(e)}poolingFunction(e,t,n,a,r){return Pt(r),va(a),W2(e,t,n,a,r,"max")}};J0.className="MaxPooling3D";ne.registerClass(J0);var Q0=class extends U2{constructor(e){super(e)}poolingFunction(e,t,n,a,r){return Pt(r),va(a),W2(e,t,n,a,r,"avg")}};Q0.className="AveragePooling3D";ne.registerClass(Q0);var G2=class extends Be{constructor(e){super(e),this.inputSpec=[new Bt({ndim:3})]}computeOutputShape(e){return[e[0],e[2]]}call(e,t){throw new 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e(s)}},r1=class extends q2{constructor(e){super(e),this.supportsMasking=!0}build(e){if(e=Ze(e),e.length<3)throw new V(`TimeDistributed layer expects an input shape >= 3D, but received input shape ${JSON.stringify(e)}`);this.inputSpec=[{shape:e}];let t=[e[0]].concat(e.slice(2));this.layer.built||(this.layer.build(t),this.layer.built=!0),super.build(e)}computeOutputShape(e){e=Ze(e);let t=[e[0]].concat(e.slice(2)),n=this.layer.computeOutputShape(t),a=e[1];return[n[0],a].concat(n.slice(1))}call(e,t){return P(()=>(e=Te(e),L2((n,a)=>[Te(this.layer.call(n,t)),[]],e,[],!1,null,null,!1,!0)[1]))}};r1.className="TimeDistributed";ne.registerClass(r1);function vH(e){Uo(SU,"BidirectionalMergeMode",e)}var wH="concat",s1=class extends q2{constructor(e){super(e);let t=e.layer.getConfig(),n={};n.className=e.layer.getClassName(),n.config=t,this.forwardLayer=Ga(n),t.goBackwards=t.goBackwards!==!0;let a={};if(a.className=e.layer.getClassName(),a.config=t,this.backwardLayer=Ga(a),this.forwardLayer.name="forward_"+this.forwardLayer.name,this.backwardLayer.name="backward_"+this.backwardLayer.name,this.mergeMode=e.mergeMode===void 0?wH:e.mergeMode,vH(this.mergeMode),e.weights)throw new Oe("weights support is not implemented for Bidirectional layer yet.");this._stateful=e.layer.stateful,this.returnSequences=e.layer.returnSequences,this.returnState=e.layer.returnState,this.supportsMasking=!0,this._trainable=!0,this.inputSpec=e.layer.inputSpec,this.numConstants=null}get trainable(){return this._trainable}set trainable(e){this._trainable=e,this.forwardLayer!=null&&(this.forwardLayer.trainable=e),this.backwardLayer!=null&&(this.backwardLayer.trainable=e)}getWeights(){return this.forwardLayer.getWeights().concat(this.backwardLayer.getWeights())}setWeights(e){let t=e.length,n=Math.floor(t/2);this.forwardLayer.setWeights(e.slice(0,n)),this.backwardLayer.setWeights(e.slice(n))}computeOutputShape(e){let t=this.forwardLayer.computeOutputShape(e);Array.isArray(t)&&Array.isArray(t[0])||(t=[t]),t=t;let n,a,r;return this.returnState&&(r=t.slice(1)),n=t[0],n=n,this.mergeMode==="concat"?(n[n.length-1]*=2,a=[n]):this.mergeMode==null?a=[n,n.slice()]:a=[n],this.returnState?this.mergeMode==null?a.concat(r).concat(r.slice()):[n].concat(r).concat(r.slice()):On(a)}apply(e,t){let n=t==null?null:t.initialState,a=t==null?null:t.constants;t==null&&(t={});let r=O2(e,n,a,this.numConstants);if(e=r.inputs,n=r.initialState,a=r.constants,Array.isArray(e)&&(n=e.slice(1),e=e[0]),(n==null||n.length===0)&&a==null)return super.apply(e,t);let s=[],i=[];if(n!=null){let l=n.length;if(l%2>0)throw new V("When passing `initialState` to a Bidrectional RNN, the state should be an Array containing the states of the underlying RNNs.");t.initialState=n,s.push(...n);let u=n.map(p=>new 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r=k("outputShape",e,t,n),s=k("strides",e,t,n),i=Ah(e,t,n);return[a.conv2dTranspose(k("x",e,t,n),k("filter",e,t,n),r,[s[1],s[2]],i)]}case"DepthwiseConv2dNative":case"DepthwiseConv2d":{let r=k("strides",e,t,n),s=Ah(e,t,n),i=k("dilations",e,t,n),o=k("dataFormat",e,t,n).toUpperCase();return[a.depthwiseConv2d(k("input",e,t,n),k("filter",e,t,n),[r[1],r[2]],s,o,[i[1],i[2]])]}case"Conv3D":{let r=k("strides",e,t,n),s=k("pad",e,t,n),i=k("dataFormat",e,t,n).toUpperCase(),o=k("dilations",e,t,n);return[a.conv3d(k("x",e,t,n),k("filter",e,t,n),[r[1],r[2],r[3]],s,i,[o[1],o[2],o[3]])]}case"AvgPool":{let r=k("strides",e,t,n),s=k("pad",e,t,n),i=k("kernelSize",e,t,n);return[a.avgPool(k("x",e,t,n),[i[1],i[2]],[r[1],r[2]],s)]}case"MaxPool":{let r=k("strides",e,t,n),s=k("pad",e,t,n),i=k("kernelSize",e,t,n);return[a.maxPool(k("x",e,t,n),[i[1],i[2]],[r[1],r[2]],s)]}case"MaxPoolWithArgmax":{let r=k("strides",e,t,n),s=k("pad",e,t,n),i=k("kernelSize",e,t,n),o=k("includeBatchInIndex",e,t,n),{result:l,indexes:u}=a.maxPoolWithArgmax(k("x",e,t,n),[i[1],i[2]],[r[1],r[2]],s,o);return[l,u]}case"AvgPool3D":{let r=k("strides",e,t,n),s=k("pad",e,t,n),i=k("kernelSize",e,t,n);return[a.avgPool3d(k("x",e,t,n),[i[1],i[2],i[3]],[r[1],r[2],r[3]],s)]}case"MaxPool3D":{let r=k("strides",e,t,n),s=k("pad",e,t,n),i=k("kernelSize",e,t,n);return[a.maxPool3d(k("x",e,t,n),[i[1],i[2],i[3]],[r[1],r[2],r[3]],s)]}case"Dilation2D":{let r=k("strides",e,t,n),s=k("pad",e,t,n),i=k("dilations",e,t,n),o=r[1],l=r[2],u=i[1],p=i[2];return[a.dilation2d(k("x",e,t,n),k("filter",e,t,n),[o,l],s,[u,p],"NHWC")]}default:throw TypeError(`Node type ${e.op} is not implemented`)}},Bq=(e,t,n,a=on)=>{switch(e.op){case"Fill":{let r=k("shape",e,t,n),s=k("dtype",e,t,n),i=k("value",e,t,n);return[a.fill(r,i,s)]}case"LinSpace":{let r=k("start",e,t,n),s=k("stop",e,t,n),i=k("num",e,t,n);return[a.linspace(r,s,i)]}case"Multinomial":{let r=k("logits",e,t,n),s=k("numSamples",e,t,n),i=k("seed",e,t,n);return[a.multinomial(r,s,i)]}case"OneHot":{let r=k("indices",e,t,n),s=k("depth",e,t,n),i=k("onValue",e,t,n),o=k("offValue",e,t,n),l=k("dtype",e,t,n);return[a.oneHot(r,s,i,o,l)]}case"Ones":return[a.ones(k("shape",e,t,n),k("dtype",e,t,n))];case"OnesLike":return[a.onesLike(k("x",e,t,n))];case"RandomStandardNormal":return[a.randomStandardNormal(k("shape",e,t,n),k("dtype",e,t,n),k("seed",e,t,n))];case"RandomUniform":return[a.randomUniform(k("shape",e,t,n),k("minval",e,t,n),k("maxval",e,t,n),k("dtype",e,t,n))];case"RandomUniformInt":return[a.randomUniformInt(k("shape",e,t,n),k("minval",e,t,n),k("maxval",e,t,n),k("seed",e,t,n))];case"Range":{let r=k("start",e,t,n),s=k("stop",e,t,n),i=k("step",e,t,n);return[a.range(r,s,i,k("dtype",e,t,n))]}case"TruncatedNormal":{let 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a=[];for(let r=0;r<n.length;r++){let s=n[r],i=this.findWithDefault(s,t);a.push(i)}return Dt(a)})}findWithDefault(e,t){let n=this.tensorMap.get(e);return n!=null?n:t}checkKeyAndValueTensor(e,t){if(e.dtype!==this.keyDType)throw new Error(`Expect key dtype ${this.keyDType}, but got ${e.dtype}`);if(t.dtype!==this.valueDType)throw new Error(`Expect value dtype ${this.valueDType}, but got ${t.dtype}`)}},qq=async(e,t,n,a)=>{switch(e.op){case"HashTable":case"HashTableV2":{let r=a.getHashTableHandleByName(e.name);if(r!=null)return[r];{let s=k("keyDType",e,t,n),i=k("valueDType",e,t,n),o=new Hq(s,i);return a.addHashTable(e.name,o),[o.handle]}}case"InitializeTable":case"InitializeTableV2":case"LookupTableImport":case"LookupTableImportV2":{let r=k("tableHandle",e,t,n,a),s=k("keys",e,t,n),i=k("values",e,t,n);return[await a.getHashTableById(r.id).import(s,i)]}case"LookupTableFind":case"LookupTableFindV2":{let r=k("tableHandle",e,t,n,a),s=k("keys",e,t,n),i=k("defaultValue",e,t,n);return[await 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r=k("images",e,t,n),s=k("transforms",e,t,n),i=k("outputShape",e,t,n),o=k("fillValue",e,t,n),l=k("interpolation",e,t,n),u=k("fillMode",e,t,n);return[a.image.transform(r,s,l.toLowerCase(),u.toLowerCase(),o,i)]}default:throw TypeError(`Node type ${e.op} is not implemented`)}},Kq=(e,t,n,a=on)=>{switch(e.op){case"Equal":return[a.equal(k("a",e,t,n),k("b",e,t,n))];case"NotEqual":return[a.notEqual(k("a",e,t,n),k("b",e,t,n))];case"Greater":return[a.greater(k("a",e,t,n),k("b",e,t,n))];case"GreaterEqual":return[a.greaterEqual(k("a",e,t,n),k("b",e,t,n))];case"Less":return[a.less(k("a",e,t,n),k("b",e,t,n))];case"LessEqual":return[a.lessEqual(k("a",e,t,n),k("b",e,t,n))];case"LogicalAnd":return[a.logicalAnd(k("a",e,t,n),k("b",e,t,n))];case"LogicalNot":return[a.logicalNot(k("a",e,t,n))];case"LogicalOr":return[a.logicalOr(k("a",e,t,n),k("b",e,t,n))];case"Select":case"SelectV2":return[a.where(k("condition",e,t,n),k("a",e,t,n),k("b",e,t,n))];case"BitwiseAnd":return[a.bitwiseAnd(k("a",e,t,n),k("b",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}},Xq=(e,t,n,a=on)=>{switch(e.op){case"BatchMatMul":case"BatchMatMulV2":case"MatMul":return[a.matMul(k("a",e,t,n),k("b",e,t,n),k("transposeA",e,t,n),k("transposeB",e,t,n))];case"Einsum":return[a.einsum(k("equation",e,t,n),...k("tensors",e,t,n))];case"Transpose":return[a.transpose(k("x",e,t,n),k("perm",e,t,n))];case"_FusedMatMul":let[r,s]=k("fusedOps",e,t,n),i=r==="biasadd",o=s==="prelu",l=k("numArgs",e,t,n),u=k("leakyreluAlpha",e,t,n);if(i){if(o&&l!==2)throw new Error("Fused MatMul with BiasAdd and Prelu must have two extra arguments: bias and alpha.");if(!o&&l!==1)throw new Error("Fused MatMul with BiasAdd must have one extra argument: bias.")}let[p,d]=k("args",e,t,n);return[a.fused.matMul({a:k("a",e,t,n),b:k("b",e,t,n),transposeA:k("transposeA",e,t,n),transposeB:k("transposeB",e,t,n),bias:p,activation:s,preluActivationWeights:d,leakyreluAlpha:u})];case"MatrixBandPart":return[a.linalg.bandPart(k("a",e,t,n),k("numLower",e,t,n),k("numUpper",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}},Yq=(e,t,n,a=on)=>{switch(e.op){case"EuclideanNorm":return[a.euclideanNorm(k("x",e,t,n),k("axis",e,t,n),k("keepDims",e,t,n))];case"FusedBatchNorm":case"FusedBatchNormV2":return[a.batchNorm(k("x",e,t,n),k("mean",e,t,n),k("variance",e,t,n),k("offset",e,t,n),k("scale",e,t,n),k("epsilon",e,t,n))];case"FusedBatchNormV3":return[a.batchNorm(k("x",e,t,n),k("mean",e,t,n),k("variance",e,t,n),k("offset",e,t,n),k("scale",e,t,n),k("epsilon",e,t,n))];case"LRN":return[a.localResponseNormalization(k("x",e,t,n),k("radius",e,t,n),k("bias",e,t,n),k("alpha",e,t,n),k("beta",e,t,n))];case"Softmax":return[a.softmax(k("x",e,t,n))];case"LogSoftmax":return[a.logSoftmax(k("x",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}},Zq=(e,t,n,a=on)=>{switch(e.op){case"RaggedGather":{let{outputNestedSplits:r,outputDenseValues:s}=a.raggedGather(k("paramsNestedSplits",e,t,n),k("paramsDenseValues",e,t,n),k("indices",e,t,n),k("outputRaggedRank",e,t,n));return r.concat(s)}case"RaggedRange":{let{rtNestedSplits:r,rtDenseValues:s}=a.raggedRange(k("starts",e,t,n),k("limits",e,t,n),k("splits",e,t,n));return[r,s]}case"RaggedTensorToTensor":return[a.raggedTensorToTensor(k("shape",e,t,n),k("values",e,t,n),k("defaultValue",e,t,n),k("rowPartitionTensors",e,t,n),k("rowPartitionTypes",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}},Jq=(e,t,n,a=on)=>{switch(e.op){case"Max":{let o=k("axis",e,t,n),l=k("keepDims",e,t,n);return[a.max(k("x",e,t,n),o,l)]}case"Mean":{let o=k("axis",e,t,n),l=k("keepDims",e,t,n);return[a.mean(k("x",e,t,n),o,l)]}case"Min":{let o=k("axis",e,t,n),l=k("keepDims",e,t,n);return[a.min(k("x",e,t,n),o,l)]}case"Sum":{let o=k("axis",e,t,n),l=k("keepDims",e,t,n);return[a.sum(k("x",e,t,n),o,l)]}case"All":{let o=k("axis",e,t,n),l=k("keepDims",e,t,n);return[a.all(k("x",e,t,n),o,l)]}case"Any":{let o=k("axis",e,t,n),l=k("keepDims",e,t,n);return[a.any(k("x",e,t,n),o,l)]}case"ArgMax":{let o=k("axis",e,t,n);return[a.argMax(k("x",e,t,n),o)]}case"ArgMin":{let o=k("axis",e,t,n);return[a.argMin(k("x",e,t,n),o)]}case"Prod":{let o=k("axis",e,t,n),l=k("keepDims",e,t,n);return[a.prod(k("x",e,t,n),o,l)]}case"Cumprod":{let o=k("axis",e,t,n),l=k("exclusive",e,t,n),u=k("reverse",e,t,n);return[a.cumprod(k("x",e,t,n),o,l,u)]}case"Cumsum":{let o=k("axis",e,t,n),l=k("exclusive",e,t,n),u=k("reverse",e,t,n);return[a.cumsum(k("x",e,t,n),o,l,u)]}case"Bincount":let r=k("x",e,t,n),s=k("weights",e,t,n),i=k("size",e,t,n);return[a.bincount(r,s,i)];case"DenseBincount":{let o=k("x",e,t,n),l=k("weights",e,t,n),u=k("size",e,t,n),p=k("binaryOutput",e,t,n);return[a.denseBincount(o,l,u,p)]}default:throw TypeError(`Node type ${e.op} is not implemented`)}},Qq=(e,t,n,a=on)=>{switch(e.op){case"ConcatV2":case"Concat":{let r=k("n",e,t,n),s=k("axis",e,t,n),i=k("tensors",e,t,n);return i=i.slice(0,r),[a.concat(i,s)]}case"Gather":{let r=k("x",e,t,n),s=k("indices",e,t,n);return[a.gather(r,a.cast(s,"int32"),0)]}case"GatherV2":{let r=k("axis",e,t,n),s=k("batchDims",e,t,n),i=k("x",e,t,n),o=k("indices",e,t,n);return[a.gather(i,a.cast(o,"int32"),r,s)]}case"Reverse":{let r=k("dims",e,t,n),s=[];for(let o=0;o<r.length;o++)r[o]&&s.push(o);let i=k("x",e,t,n);return[a.reverse(i,s)]}case"ReverseV2":{let r=k("axis",e,t,n),s=k("x",e,t,n);return[a.reverse(s,r)]}case"Slice":{let r=k("begin",e,t,n),s=k("size",e,t,n);return[a.slice(k("x",e,t,n),r,s)]}case"StridedSlice":{let r=k("begin",e,t,n),s=k("end",e,t,n),i=k("strides",e,t,n),o=k("beginMask",e,t,n),l=k("endMask",e,t,n),u=k("ellipsisMask",e,t,n),p=k("newAxisMask",e,t,n),d=k("shrinkAxisMask",e,t,n),c=k("x",e,t,n);return[a.stridedSlice(c,r,s,i,o,l,u,p,d)]}case"Pack":return P(()=>{let r=k("axis",e,t,n),s=k("tensors",e,t,n),i=s[0].shape,o=a.squeeze(s[0]).shape,l=s.map(u=>{let p=v.arraysEqual(u.shape,i);if(!p&&!v.arraysEqual(a.squeeze(u).shape,o))throw new Error("the input tensors shape does not match");return p?u:a.reshape(u,i)});return[a.stack(l,r)]});case"Unpack":{let r=k("axis",e,t,n),s=k("tensor",e,t,n);return a.unstack(s,r)}case"Tile":{let r=k("reps",e,t,n);return[a.tile(k("x",e,t,n),r)]}case"Split":case"SplitV":{let r=k("axis",e,t,n),s=k("numOrSizeSplits",e,t,n),i=k("x",e,t,n);return a.split(i,s,r)}case"ScatterNd":{let r=k("indices",e,t,n),s=k("values",e,t,n),i=k("shape",e,t,n);return[a.scatterND(r,s,i)]}case"GatherNd":{let r=k("x",e,t,n),s=k("indices",e,t,n);return[a.gatherND(r,s)]}case"SparseToDense":{let r=k("sparseIndices",e,t,n),s=k("outputShape",e,t,n),i=k("sparseValues",e,t,n),o=k("defaultValue",e,t,n);return[a.sparseToDense(r,i,s,i.dtype===o.dtype?o:a.cast(o,i.dtype))]}case"TensorScatterUpdate":{let r=k("indices",e,t,n),s=k("values",e,t,n),i=k("tensor",e,t,n);return[a.tensorScatterUpdate(i,r,s)]}default:throw TypeError(`Node type ${e.op} is not implemented`)}},ej=(e,t,n,a=on)=>{switch(e.op){case"SparseFillEmptyRows":{let{outputIndices:r,outputValues:s,emptyRowIndicator:i,reverseIndexMap:o}=a.sparse.sparseFillEmptyRows(k("indices",e,t,n),k("values",e,t,n),k("denseShape",e,t,n),k("defaultValue",e,t,n));return[r,s,i,o]}case"SparseReshape":{let{outputIndices:r,outputShape:s}=a.sparse.sparseReshape(k("inputIndices",e,t,n),k("inputShape",e,t,n),k("newShape",e,t,n));return[r,s]}case"SparseSegmentMean":return[a.sparse.sparseSegmentMean(k("data",e,t,n),k("indices",e,t,n),k("segmentIds",e,t,n))];case"SparseSegmentSum":return[a.sparse.sparseSegmentSum(k("data",e,t,n),k("indices",e,t,n),k("segmentIds",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}},tj=(e,t,n,a=on)=>{switch(e.op){case"FFT":return[a.fft(k("x",e,t,n))];case"IFFT":return[a.ifft(k("x",e,t,n))];case"RFFT":return[a.rfft(k("x",e,t,n))];case"IRFFT":return[a.irfft(k("x",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}},nj=(e,t,n,a=on)=>{switch(e.op){case"StaticRegexReplace":return[a.string.staticRegexReplace(k("input",e,t,n),k("pattern",e,t,n),k("rewrite",e,t,n),k("replaceGlobal",e,t,n))];case"StringNGrams":{let{nGrams:r,nGramsSplits:s}=a.string.stringNGrams(k("data",e,t,n),k("dataSplits",e,t,n),k("separator",e,t,n),k("nGramWidths",e,t,n),k("leftPad",e,t,n),k("rightPad",e,t,n),k("padWidth",e,t,n),k("preserveShortSequences",e,t,n));return[r,s]}case"StringSplit":{let{indices:r,values:s,shape:i}=a.string.stringSplit(k("input",e,t,n),k("delimiter",e,t,n),k("skipEmpty",e,t,n));return[r,s,i]}case"StringToHashBucketFast":return[a.string.stringToHashBucketFast(k("input",e,t,n),k("numBuckets",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}},aj=(e,t,n,a=on)=>{switch(e.op){case"Cast":return[a.cast(k("x",e,t,n),k("dtype",e,t,n))];case"ExpandDims":{let r=k("axis",e,t,n);return[a.expandDims(k("x",e,t,n),r)]}case"Squeeze":{let r=k("axis",e,t,n);return[a.squeeze(k("x",e,t,n),r)]}case"Reshape":return[a.reshape(k("x",e,t,n),k("shape",e,t,n))];case"EnsureShape":return[a.ensureShape(k("x",e,t,n),k("shape",e,t,n))];case"MirrorPad":return[a.mirrorPad(k("x",e,t,n),k("padding",e,t,n),k("mode",e,t,n))];case"PadV2":case"Pad":return[a.pad(k("x",e,t,n),k("padding",e,t,n),k("constantValue",e,t,n))];case"SpaceToBatchND":{let r=k("blockShape",e,t,n),s=k("paddings",e,t,n);return[a.spaceToBatchND(k("x",e,t,n),r,s)]}case"BatchToSpaceND":{let r=k("blockShape",e,t,n),s=k("crops",e,t,n);return[a.batchToSpaceND(k("x",e,t,n),r,s)]}case"DepthToSpace":{let r=k("blockSize",e,t,n),s=k("dataFormat",e,t,n).toUpperCase();return[a.depthToSpace(k("x",e,t,n),r,s)]}case"BroadcastTo":return[a.broadcastTo(k("x",e,t,n),k("shape",e,t,n))];case"BroadcastArgs":return[a.broadcastArgs(k("s0",e,t,n),k("s1",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}};function TI(e,t,n,a,r=P){let s=((i,o,l)=>{switch(i.category){case"arithmetic":return r(()=>$q(i,o,l));case"basic_math":return r(()=>Dq(i,o,l));case"control":return zq(i,o,l);case"convolution":return r(()=>Wq(i,o,l));case"creation":return r(()=>Bq(i,o,l));case"dynamic":return Vq(i,o,l);case"evaluation":return r(()=>Uq(i,o,l));case"image":return r(()=>jq(i,o,l));case"graph":return r(()=>Gq(i,o,l));case"logical":return r(()=>Kq(i,o,l));case"matrices":return r(()=>Xq(i,o,l));case"normalization":return r(()=>Yq(i,o,l));case"ragged":return r(()=>Zq(i,o,l));case"reduction":return r(()=>Jq(i,o,l));case"slice_join":return r(()=>Qq(i,o,l));case"sparse":return r(()=>ej(i,o,l));case"spectral":return r(()=>tj(i,o,l));case"string":return r(()=>nj(i,o,l));case"transformation":return r(()=>aj(i,o,l));case"hash_table":return qq(i,o,l,a);case"custom":let u=rC(i.op);if(u&&u.customExecutor)return u.customExecutor(new Fq(i,o,l));throw TypeError(`Custom op ${i.op} is not registered.`);default:throw TypeError(`Unknown op '${i.op}'. File an issue at https://github.com/tensorflow/tfjs/issues so we can add it, or register a custom execution with tf.registerOp()`)}})(e,t,n);return v.isPromise(s)?s.then(i=>[].concat(i)):[].concat(s)}var CI=class{constructor(e={},t={},n={},a={},r){this.weightMap=e,this.tensorArrayMap=t,this.tensorListMap=n,this.functionMap=a,this.parseNodeNameCache=r,this.rootContext={id:0,frameName:"",iterationId:0},this.contexts=[this.rootContext],this.lastId=0,this.generateCurrentContextIds()}newFrame(e,t){return{id:e,frameName:t,iterationId:0}}set currentContext(e){this.contexts!==e&&(this.contexts=e,this.generateCurrentContextIds())}get currentContext(){return this.contexts}get currentContextId(){return this._currentContextIds[0]}get currentContextIds(){return this._currentContextIds}generateCurrentContextIds(){let e=[];for(let t=0;t<this.contexts.length-1;t++){let n=this.contexts.slice(0,this.contexts.length-t);e.push(this.contextIdforContexts(n))}e.push(""),this._currentContextIds=e}contextIdforContexts(e){return e?e.map(t=>t.id===0&&t.iterationId===0?"":`${t.frameName}-${t.iterationId}`).join("/"):""}enterFrame(e){this.contexts&&(this.lastId++,this.contexts=this.contexts.slice(),this.contexts.push(this.newFrame(this.lastId,e)),this._currentContextIds.unshift(this.contextIdforContexts(this.contexts)))}exitFrame(){if(this.contexts&&this.contexts.length>1)this.contexts=this.contexts.slice(),this.contexts.splice(-1),this.currentContextIds.shift();else throw new Error("Cannot exit frame, the context is empty")}nextIteration(){if(this.contexts&&this.contexts.length>0){this.contexts=this.contexts.slice(),this.lastId++;let e=Object.assign({},this.contexts[this.contexts.length-1]);e.iterationId+=1,e.id=this.lastId,this.contexts.splice(-1,1,e),this._currentContextIds.splice(0,1,this.contextIdforContexts(this.contexts))}else throw new Error("Cannot increase frame iteration, the context is empty")}getWeight(e){return this.weightMap[e]}addTensorArray(e){this.tensorArrayMap[e.id]=e}getTensorArray(e){return this.tensorArrayMap[e]}addTensorList(e){this.tensorListMap[e.id]=e}getTensorList(e){return this.tensorListMap[e]}dispose(e){for(let t in this.tensorArrayMap)this.tensorArrayMap[t].clearAndClose(e);for(let t in this.tensorListMap)this.tensorListMap[t].clearAndClose(e)}};function _I(e,t,n,a){let r=new Set,s=[],i=null,o=null,l=new Set,u=new Set(Object.keys(e).map(c=>Yn(c)[0]));a=a||[];let p=new Set(a.map(c=>Yn(c.name)[0])),d=[...t];for(;d.length>0;){let c=d.pop();if((Zs(c)||cj(c)||dj(c))&&i==null&&(i=c,o=i.children.map(h=>h.name).filter(h=>r.has(h))),r.add(c.name),n[c.name]==null&&!u.has(c.name)&&!p.has(c.name)){if(c.inputs.length===0){s.push(c.name);continue}c.inputs.forEach(h=>{l.has(h.name)||(l.add(h.name),d.push(h))})}}return{inputs:e,outputs:t,usedNodes:r,missingInputs:s,dynamicNode:i,syncInputs:o}}function rj(e,t){let{usedNodes:n,inputs:a}=t,r=Object.keys(a).map(g=>Yn(g)[0]).map(g=>e.nodes[g]),s=e.initNodes||[],i=g=>n.has(typeof g=="string"?g:g.name);function o(g){return[...new Map(g.map(b=>[b.name,b])).values()]}let l=o([...r,...e.weights,...s]).filter(i),u=o([...l,...Object.values(e.nodes)]).filter(i),p=new Map(u.map(g=>[g.name,g])),d={};for(let g of u){d[g.name]=d[g.name]||0;for(let b of g.children)i(b)||(d[b.name]=Number.POSITIVE_INFINITY),d[b.name]=(d[b.name]||0)+1}let c=Object.entries(d).filter(([,g])=>g===0).map(([g])=>g),h=[...c];for(;c.length>0;){let g=c.pop(),b=p.get(g);for(let y of b.children.filter(i))--d[y.name]===0&&(h.push(y.name),c.push(y.name))}let m=h.map(g=>p.get(g)),f=sj(m,l);return ij(f,l),f}function sj(e,t){let n=new Map(e.map(s=>[s.name,s])),a=t.map(s=>s.name),r=new Set(a);for(;a.length>0;){let s=a.pop(),i=n.get(s);for(let o of i.children)!n.has(o.name)||r.has(o.name)||(r.add(o.name),a.push(o.name))}return e.filter(s=>r.has(s.name))}var wh=class extends Error{constructor(e){super(`NodesExecutionOrderError: ${e}`)}};function ij(e,t){let n=new Map(e.map((o,l)=>[o.name,l])),a=new Set(t.map(o=>o.name)),r=o=>a.has(typeof o=="string"?o:o.name),s=new Set(e.map(o=>o.name)),i=o=>s.has(typeof o=="string"?o:o.name);for(let o of e){for(let l of o.children.filter(i)){if(!n.has(l.name))throw new wh(`Child ${l.name} of node ${o.name} is unreachable.`);if(n.get(o.name)>n.get(l.name))throw new wh(`Node ${o.name} is scheduled to run after its child ${l.name}.`)}if(!r(o))for(let l of o.inputs){if(!n.has(l.name))throw new wh(`Input ${l.name} of node ${o.name} is unreachable.`);if(n.get(l.name)>n.get(o.name))throw new wh(`Node ${o.name} is scheduled to run before its input ${l.name}.`)}}}function oj(e){let t=new Map(e.map((o,l)=>[o.name,l])),n=Number.MAX_SAFE_INTEGER,a=e.map((o,l)=>Zs(o)?n:l),r=o=>{let l=a[t.get(o.name)];return l==null?-1:l},s=e.map((o,l)=>o.children.map(r).reduce((u,p)=>Math.max(u,p),a[l])),i=new Map;for(let o=0;o<e.length;++o){let l=s[o];if(l===n)continue;let u=e[o],p=e[l];i.has(p.name)||i.set(p.name,[]),i.get(p.name).push(u)}return i}var lj=new Set(["Switch","Merge","Enter","Exit","NextIteration","StatelessIf","StatelessWhile","if","While"]),uj=new Set(["NonMaxSuppressionV2","NonMaxSuppressionV3","NonMaxSuppressionV5","Where"]),pj=new Set(["HashTable","HashTableV2","LookupTableImport","LookupTableImportV2","LookupTableFind","LookupTableFindV2","LookupTableSize","LookupTableSizeV2"]);function Zs(e){return lj.has(e.op)}function cj(e){return uj.has(e.op)}function dj(e){return pj.has(e.op)}var qx=class{get weightIds(){return this.parent?this.parent.weightIds:this._weightIds}get functionExecutorMap(){return this.parent?this.parent.functionExecutorMap:this._functionExecutorMap}get weightMap(){return this.parent?this.parent.weightMap:this._weightMap}set weightMap(e){let t=Object.keys(e).map(n=>e[n].map(a=>a.id));this._weightIds=[].concat(...t),this._weightMap=e}set resourceManager(e){this._resourceManager=e}get inputs(){return this._inputs.map(e=>({name:e.name,shape:e.attrParams.shape?e.attrParams.shape.value:void 0,dtype:e.attrParams.dtype?e.attrParams.dtype.value:void 0}))}get outputs(){return this._outputs.map(e=>({name:e.name,shape:e.attrParams.shape?e.attrParams.shape.value:void 0,dtype:e.attrParams.dtype?e.attrParams.dtype.value:void 0}))}get inputNodes(){return this._inputs.map(e=>e.signatureKey||e.name)}get outputNodes(){return this._outputs.map(e=>{let t=e.signatureKey||e.name;return e.defaultOutput?`${t}:${e.defaultOutput}`:t})}get functions(){return Object.keys(this._functions).reduce((e,t)=>(e[t]=this._functions[t].signature,e),{})}constructor(e,t){this.graph=e,this.parent=t,this.compiledMap=new Map,this.parseNodeNameCache=new Map,this._weightMap={},this.SEPARATOR=",",this._functions={},this._functionExecutorMap={},this.keepIntermediateTensors=!1,this._outputs=e.outputs,this._inputs=e.inputs,this._initNodes=e.initNodes,this._signature=e.signature,this._functions=e.functions,e.functions!=null&&Object.keys(e.functions).forEach(n=>{this._functionExecutorMap[n]=new qx(e.functions[n],this)})}getCompilationKey(e,t){let n=e.map(r=>r.name).sort(),a=t.map(r=>r.name).sort();return n.join(this.SEPARATOR)+"--"+a.join(this.SEPARATOR)}compile(e,t){let n=_I(e,t,this.weightMap,this._initNodes),{missingInputs:a,dynamicNode:r,syncInputs:s}=n;if(r!=null)throw new Error(`This execution contains the node '${r.name}', which has the dynamic op '${r.op}'. Please use model.executeAsync() instead. Alternatively, to avoid the dynamic ops, specify the inputs [${s}]`);if(a.length>0){let l=t.map(p=>p.name),u=Object.keys(e);throw new Error(`Cannot compute the outputs [${l}] from the provided inputs [${u}]. Missing the following inputs: [${a}]`)}let i=rj(this.graph,n),o=oj(i);return{orderedNodes:i,nodeLiveUntilMap:o}}cloneAndKeepTensor(e){if(e==null)return null;let t=e.clone();return Ht(t),t}cloneTensorList(e){return e?e.map(t=>this.cloneAndKeepTensor(t)):null}cloneTensorMap(e){return Object.fromEntries(Object.entries(e).map(([t,n])=>[t,this.cloneTensorList(n)]))}execute(e,t){this.disposeIntermediateTensors(),e=this.mapInputs(e);let n=Object.keys(e).sort();this.checkInputs(e),this.checkInputShapeAndType(e),t=this.mapOutputs(t),this.checkOutputs(t);let a=n.map(d=>this.graph.nodes[Yn(d)[0]]),r=t.map(d=>Yn(d)[0]),s=new Set(r),i=r.map(d=>this.graph.nodes[d]);i.length===0&&(i=this._outputs);let o=this.getCompilationKey(a,i),l=this.compiledMap.get(o);l==null&&(l=this.compile(e,i),this.compiledMap.set(o,l));try{this.keepIntermediateTensors=G().getBool("KEEP_INTERMEDIATE_TENSORS")}catch(d){this.keepIntermediateTensors=!1,console.warn(d.message)}let u={},p={};return P(()=>{let d=new CI(this.weightMap,u,p,this.functionExecutorMap,this.parseNodeNameCache),c=Object.assign({},this.weightMap);this.keepIntermediateTensors&&(this.clonedTensorsMap=this.cloneTensorMap(this.weightMap)),Object.keys(e).forEach(g=>{let[b,y]=Yn(g,d),x=[];x[y]=e[g],c[b]=x,this.keepIntermediateTensors&&(this.clonedTensorsMap[b]=this.cloneTensorList(x))});let h=this.getFrozenTensorIds(c),{orderedNodes:m,nodeLiveUntilMap:f}=l;for(let g of m){if(c[g.name])continue;let b=TI(g,c,d,this._resourceManager);if(v.isPromise(b))throw new Error(`The execution of the op '${g.op}' returned a promise. Please use model.executeAsync() instead.`);c[g.name]=b,this.keepIntermediateTensors&&(this.clonedTensorsMap[g.name]=this.cloneTensorList(b)),this.checkTensorForDisposalWithNodeLiveUntilInfo(g,c,d,h,s,f.get(g.name))}return this.parent==null&&d.dispose(h),t.map(g=>cn(g,c,d))})}getFrozenTensorIds(e){let t=[].concat.apply([],Object.keys(e).map(n=>e[n]).map(n=>n.map(a=>a.id)));return new Set(t)}checkTensorForDisposal(e,t,n,a,r,s,i){if(!(Zs(t)||s.has(e))){for(let o of n[e])o!=null&&(i[o.id]=(i[o.id]||0)+t.children.length);for(let o of t.inputs){if(Zs(o))continue;let l=wI(o.name,n,a);if(l!=null)for(let u of l){if(!u||u.kept||r.has(u.id))continue;let p=i[u.id];p===1?(u.dispose(),delete i[u.id]):p!=null&&i[u.id]--}}}}checkTensorForDisposalWithNodeLiveUntilInfo(e,t,n,a,r,s){function i(o){return Zs(o)||r.has(o.name)}if(!(Zs(e)||s==null))for(let o of s){if(i(o))continue;let l=wI(o.name,t,n);for(let u of l)!u||u.kept||a.has(u.id)||u.dispose()}}async executeAsync(e,t){return this._executeAsync(e,t)}disposeIntermediateTensors(){this.clonedTensorsMap&&(Object.values(this.clonedTensorsMap).forEach(e=>{for(let t of e)t&&!t.isDisposed&&t.dispose()}),this.clonedTensorsMap=null)}getIntermediateTensors(){return this.clonedTensorsMap}async _executeAsync(e,t,n=!1,a={},r={}){this.disposeIntermediateTensors(),n||(e=this.mapInputs(e),this.checkInputs(e),this.checkInputShapeAndType(e),t=this.mapOutputs(t),this.checkOutputs(t));try{this.keepIntermediateTensors=G().getBool("KEEP_INTERMEDIATE_TENSORS")}catch(d){this.keepIntermediateTensors=!1,console.warn(d.message)}let s=new CI(this.weightMap,a,r,this.functionExecutorMap,this.parseNodeNameCache);this.keepIntermediateTensors&&(this.clonedTensorsMap=this.cloneTensorMap(this.weightMap));let i=await this.executeWithControlFlow(e,s,t,n),o=t.map(d=>cn(d,i,s)),l=o.map(d=>d.id),u=Object.keys(e).map(d=>e[d].id),p=new Set([...l,...u,...this.weightIds]);return Object.values(i).forEach(d=>{d.forEach(c=>{c&&!c.isDisposed&&!p.has(c.id)&&c.dispose()})}),this.parent==null&&s.dispose(p),o}async executeFunctionAsync(e,t,n){let a=e.reduce((r,s,i)=>(r[this.inputs[i].name]=s,r),{});return this._executeAsync(a,this.outputNodes,!0,t,n)}async executeWithControlFlow(e,t,n,a){let r=Object.keys(e),s=r.map(x=>this.graph.nodes[Yn(x)[0]]),i=n.map(x=>Yn(x)[0]),o=new Set(i),l=i.map(x=>this.graph.nodes[x]);l.length===0&&(l=this._outputs);let{usedNodes:u,missingInputs:p,dynamicNode:d,syncInputs:c}=_I(e,l,this.weightMap,this._initNodes),h=[...s,...this.graph.weights,...this._initNodes||[]].map(x=>({node:x,contexts:t.currentContext})),m=Object.assign({},this.weightMap);Object.keys(e).forEach(x=>{let[w,I]=Yn(x),T=[];T[I]=e[x],m[w]=T});let f={},g=this.getFrozenTensorIds(m),b={};for(;h.length>0;){let x=this.processStack(s,h,t,m,b,g,o,f,u);await Promise.all(x)}d==null&&!a&&console.warn("This model execution did not contain any nodes with control flow or dynamic output shapes. You can use model.execute() instead.");let y=l.filter(x=>!Zs(x)&&!cn(x.name,m,t)).map(x=>x.name);if(y.length>0){let x="";throw d!=null&&(x=`Alternatively, to avoid the dynamic ops, use model.execute() and specify the inputs [${c}]`),new Error(`Cannot compute the outputs [${y}] from the provided inputs [${r}]. Consider providing the following inputs: [${p}]. ${x}`)}return m}processStack(e,t,n,a,r,s,i,o,l){let u=[];for(;t.length>0;){let p=t.pop();n.currentContext=p.contexts;let d="";if(p.node.op==="Enter"&&k("isConstant",p.node,a,n)&&([d]=Nr(p.node.name,n)),a[p.node.name]==null){let c=TI(p.node,a,n,this._resourceManager);d||([d]=Nr(p.node.name,n));let h=n.currentContext;v.isPromise(c)?u.push(c.then(m=>(a[d]=m,this.keepIntermediateTensors&&(this.clonedTensorsMap[d]=this.cloneTensorList(m)),n.currentContext=h,this.checkTensorForDisposal(d,p.node,a,n,s,i,o),this.processChildNodes(p.node,t,n,a,r,l),m))):(a[d]=c,this.keepIntermediateTensors&&(this.clonedTensorsMap[d]=this.cloneTensorList(c)),this.checkTensorForDisposal(d,p.node,a,n,s,i,o),this.processChildNodes(p.node,t,n,a,r,l))}else this.processChildNodes(p.node,t,n,a,r,l)}return u}processChildNodes(e,t,n,a,r,s){e.children.forEach(i=>{let[o]=Nr(i.name,n);r[o]||!s.has(i.name)||(i.op==="Merge"?i.inputNames.some(l=>!!cn(l,a,n))&&(r[o]=!0,t.push({contexts:n.currentContext,node:i})):i.inputNames.every(l=>!!cn(l,a,n))&&(r[o]=!0,t.push({contexts:n.currentContext,node:i})))})}dispose(){Object.keys(this.weightMap).forEach(e=>this.weightMap[e].forEach(t=>t.dispose()))}checkInputShapeAndType(e){Object.keys(e).forEach(t=>{let n=e[t],[a]=Yn(t),r=this.graph.nodes[a];if(r.attrParams.shape&&r.attrParams.shape.value){let s=r.attrParams.shape.value,i=s.length===n.shape.length&&n.shape.every((o,l)=>s[l]===-1||s[l]===o);v.assert(i,()=>`The shape of dict['${r.name}'] provided in model.execute(dict) must be [${s}], but was [${n.shape}]`)}r.attrParams.dtype&&r.attrParams.dtype.value&&v.assert(n.dtype===r.attrParams.dtype.value,()=>`The dtype of dict['${r.name}'] provided in model.execute(dict) must be ${r.attrParams.dtype.value}, but was ${n.dtype}`)})}mapInputs(e){var t,n;let 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AC{constructor(){super(b1.INITIAL_CAPACITY)}isFull(){return!1}push(e){super.isFull()&&this.expand(),super.push(e)}unshift(e){super.isFull()&&this.expand(),super.unshift(e)}expand(){let e=this.capacity*2,t=new Array(e),n=this.length();for(let a=0;a<n;a++)t[a]=this.get(this.wrap(this.begin+a));this.data=t,this.capacity=e,this.doubledCapacity=2*this.capacity,this.begin=0,this.end=n}};b1.INITIAL_CAPACITY=32;function FC(e){return new Aj(e)}function y1(e){return new Fj(e)}function _j(e,t){return new $C(e,t)}function Ej(e,t=es.FAIL){return new Wj(e,t)}var sn=class{async toArray(){let e=[],t=await this.next();for(;!t.done;)e.push(t.value),t=await this.next();return e}async toArrayForTest(){let e=this.prefetch(100),t=[],n=await e.next();for(;!n.done;)t.push(n.value),n=await e.next();return t}async resolveFully(){let e=await this.next();for(;!e.done;)e=await this.next()}async resolveWhile(e){let t=await this.next(),n=e(t.value);for(;!t.done&&n;)t=await this.next(),n=e(t.value)}handleErrors(e){return new Lj(this,e)}filter(e){return new Pj(this,e)}map(e){return new Oj(this,e)}mapAsync(e){return new EI(this,e)}serialMapAsync(e){return new EI(this,e).serial()}flatmap(e){return new zj(this,e)}async forEachAsync(e){return this.map(e).resolveFully()}async serialForEach(e){return this.serialMapAsync(e).resolveWhile(t=>t===!0)}rowMajorBatch(e,t=!0){return new Mj(this,e,t)}columnMajorBatch(e,t=!0,n=_C){return this.rowMajorBatch(e,t).map(a=>Ij(a,n))}concatenate(e,t){return new $C(FC([this,e]),t)}take(e){return e<0||e==null?this:new Rj(this,e)}skip(e){return e<0||e==null?this:new Dj(this,e)}prefetch(e){return new DC(this,e)}shuffle(e,t){return new Bj(this,e,t)}serial(){return new $j(this)}},Aj=class extends sn{constructor(e){super(),this.items=e,this.trav=0}summary(){return`Array of ${this.items.length} items`}async next(){if(this.trav>=this.items.length)return{value:null,done:!0};let e=this.items[this.trav];return this.trav++,{value:Tj(e),done:!1}}},Fj=class extends sn{constructor(e){super(),this.nextFn=e}summary(){return"Function call"}async next(){try{return this.nextFn()}catch(e){throw e.message=`Error thrown while iterating through a dataset: ${e.message}`,e}}},$j=class extends sn{constructor(e){super(),this.upstream=e,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> Serial`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){return this.upstream.next()}},Dj=class extends sn{constructor(e,t){super(),this.upstream=e,this.maxCount=t,this.count=0,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> Skip`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){for(;this.count++<this.maxCount;){let e=await this.upstream.next();if(e.done)return e;_e(e.value)}return this.upstream.next()}},Rj=class extends sn{constructor(e,t){super(),this.upstream=e,this.maxCount=t,this.count=0}summary(){return`${this.upstream.summary()} -> Take`}async next(){return this.count++>=this.maxCount?{value:null,done:!0}:this.upstream.next()}},Mj=class extends sn{constructor(e,t,n=!0){super(),this.upstream=e,this.batchSize=t,this.enableSmallLastBatch=n,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${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}}},Pj=class extends sn{constructor(e,t){super(),this.upstream=e,this.predicate=t,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> Filter`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){for(;;){let e=await this.upstream.next();if(e.done||this.predicate(e.value))return e;_e(e.value)}}},Oj=class extends sn{constructor(e,t){super(),this.upstream=e,this.transform=t}summary(){return`${this.upstream.summary()} -> Map`}async next(){let e=await this.upstream.next();if(e.done)return{value:null,done:!0};let t=Ua.getTensorsInContainer(e.value),n=this.transform(e.value),a=Ua.getTensorsInContainer(n);for(let r of t)Ua.isTensorInList(r,a)||r.dispose();return{value:n,done:!1}}},Lj=class extends sn{constructor(e,t){super(),this.upstream=e,this.handler=t,this.count=0,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> handleErrors`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){for(;;)try{return await this.upstream.next()}catch(e){if(!this.handler(e))return{value:null,done:!0}}}},EI=class extends sn{constructor(e,t){super(),this.upstream=e,this.transform=t}summary(){return`${this.upstream.summary()} -> AsyncMap`}async next(){let e=await this.upstream.next();if(e.done)return{value:null,done:!0};let t=Ua.getTensorsInContainer(e.value),n=await this.transform(e.value),a=Ua.getTensorsInContainer(n);for(let r of t)Ua.isTensorInList(r,a)||r.dispose();return{value:n,done:!1}}},x1=class extends sn{constructor(){super(),this.outputQueue=new b1,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}}},zj=class extends x1{constructor(e,t){super(),this.upstream=e,this.transform=t}summary(){return`${this.upstream.summary()} -> Flatmap`}async pump(){let e=await this.upstream.next();if(e.done)return!1;let t=Ua.getTensorsInContainer(e.value),n=this.transform(e.value),a=Ua.getTensorsInContainer(n);this.outputQueue.pushAll(n);for(let r of t)Ua.isTensorInList(r,a)||r.dispose();return!0}},$C=class extends sn{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 n=await this.moreIterators.next();if(n.done)return{value:null,done:!0};this.iterator=n.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}},es;(function(e){e[e.FAIL=0]="FAIL",e[e.SHORTEST=1]="SHORTEST",e[e.LONGEST=2]="LONGEST"})(es||(es={}));var Wj=class extends sn{constructor(e,t=es.FAIL){super(),this.iterators=e,this.mismatchMode=t,this.count=0,this.currentPromise=null}summary(){return"{TODO: fill in upstream of zip summaries} -> Zip"}async nextState(e){await e;let t=0,n=0;function a(s){return s instanceof sn?{value:s.next().then(i=>(t++,i.done&&n++,i.value)),recurse:!1}:{value:null,recurse:!0}}let r=await EC(this.iterators,a);if(t===n)return{value:null,done:!0};if(n>0)switch(this.mismatchMode){case es.FAIL:throw new Error(`Zipped streams should have the same length. Mismatched at element ${this.count}.`);case es.SHORTEST:return{value:null,done:!0};case es.LONGEST:default:}return this.count++,{value:r,done:!1}}async next(){return this.currentPromise=this.nextState(this.currentPromise),this.currentPromise}},DC=class extends sn{constructor(e,t){super(),this.upstream=e,this.bufferSize=t,this.buffer=new AC(t)}summary(){return`${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()}},Bj=class extends DC{constructor(e,t,n){super(e,t),this.upstream=e,this.windowSize=t,this.upstreamExhausted=!1,this.random=wj.alea(n||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}}},rp=class{constructor(){this.size=null}batch(e,t=!0){let n=this;v.assert(e>0,()=>`batchSize needs to be positive, but it is
${e}`);let a;return this.size===1/0||this.size==null?a=this.size:t?a=Math.ceil(this.size/e):a=Math.floor(this.size/e),Xn(async()=>(await n.iterator()).columnMajorBatch(e,t,Gj),a)}concatenate(e){let t=this,n;return this.size===1/0||e.size===1/0?n=1/0:this.size!=null&&e.size!=null?n=this.size+e.size:n=null,Xn(async()=>(await t.iterator()).concatenate(await e.iterator()),n)}filter(e){let t=this,n;return this.size===1/0?n=1/0:n=null,Xn(async()=>(await t.iterator()).filter(a=>P(()=>e(a))),n)}async forEachAsync(e){return(await this.iterator()).forEachAsync(e)}map(e){let t=this;return Xn(async()=>(await t.iterator()).map(n=>P(()=>e(n))),this.size)}mapAsync(e){let t=this;return Xn(async()=>(await t.iterator()).mapAsync(e),this.size)}prefetch(e){if(e==null)throw new RangeError("`Dataset.prefetch()` requires bufferSize to be specified.");let t=this;return Xn(async()=>(await t.iterator()).prefetch(e),this.size)}repeat(e){let t=this,n;return this.size!=null&&e>0?n=this.size*e:e===0?n=0:this.size!=null&&(e===void 0||e<0)?n=1/0:n=null,Xn(async()=>{let a=y1(async()=>({value:await t.iterator(),done:!1}));return _j(a.take(e))},n)}skip(e){let t=this,n;return this.size!=null&&e>=0&&this.size>=e?n=this.size-e:this.size!=null&&(this.size<e||e===void 0||e<0)?n=0:n=null,Xn(async()=>(await t.iterator()).skip(e),n)}shuffle(e,t,n=!0){if(e==null||e<0)throw this.size==null?new RangeError("`Dataset.shuffle()` requires bufferSize to be specified."):new RangeError(`\`Dataset.shuffle()\` requires bufferSize to be specified. If your data fits in main memory (for regular JS objects), and/or GPU memory (for \`tf.Tensor\`s), consider setting bufferSize to the dataset size (${this.size} elements)`);let a=this,r=vj.alea(t||v.now().toString());return Xn(async()=>{let s=r.int32();return n&&(s+=r.int32()),(await a.iterator()).shuffle(e,s.toString())},this.size)}take(e){let t=this,n;return this.size!=null&&this.size>e?n=e:this.size!=null&&this.size<=e?n=this.size:n=null,Xn(async()=>(await t.iterator()).take(e),n)}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()}};rp.MAX_BUFFER_SIZE=1e4;function Xn(e,t=null){return new class extends rp{constructor(){super(...arguments),this.size=t}async iterator(){return e()}}}function Vj(e){return Xn(async()=>FC(e),e.length)}function Uj(e){if(!Wl(e))throw new Error("The argument to zip() must be an object or array.");let t;if(Array.isArray(e))for(let n=0;n<e.length;n++)t=t==null?e[n].size:Math.min(t,e[n].size);else if(e instanceof Object)for(let n in e)t=t==null?e[n].size:Math.min(t,e[n].size);return Xn(async()=>{let n=await EC(e,a=>{if(a instanceof rp)return{value:a.iterator(),recurse:!1};if(Wl(a))return{value:null,recurse:!0};throw new Error("Leaves of the structure passed to zip() must be Datasets, not primitives.")});return Ej(n,es.SHORTEST)},t)}function Gj(e){if(e===null)return null;let t=e[0];return Sj(t)?{value:Hj(e),recurse:!1}:{value:null,recurse:!0}}function Hj(e){if(e.length===0)throw new Error("Can't make a batch of zero elements.");return e[0]instanceof Ce?Dt(e):bn(e)}var RC=class extends rp{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))}},kh='"',jp=Symbol("out"),AI=Symbol("field"),Ih=Symbol("quote"),ox=Symbol("quoteafterquote"),FI=Symbol("quoteinquote"),MC=class extends rp{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((a,r)=>(a[r]=a[r]+1||1,a),{}),n=Object.keys(t).filter(a=>t[a]>1);if(v.assert(n.length===0,()=>"Duplicate column names found: "+n.toString()),this.columnConfigs){for(let a of Object.keys(this.columnConfigs))if(this.fullColumnNames.indexOf(a)===-1)throw new Error('The key "'+a+'" provided in columnConfigs does not match any of the column names ('+this.fullColumnNames.toString()+").")}this.columnNamesValidated=!0}async maybeReadHeaderLine(){if(this.hasHeader){let e=await(await this.base.iterator()).next();if(e.done)throw new Error("No data was found for CSV parsing.");let t=e.value;return this.parseRow(t,!1)}else return null}constructor(e,t){super(),this.input=e,this.hasHeader=!0,this.fullColumnNames=null,this.columnNamesValidated=!1,this.columnConfigs=null,this.configuredColumnsOnly=!1,this.delimiter=",",this.delimWhitespace=!1,this.base=new RC(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 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),n={},a={};for(let r=0;r<this.fullColumnNames.length;r++){let s=this.fullColumnNames[r],i=this.columnConfigs?this.columnConfigs[s]:null;if(!(this.configuredColumnsOnly&&!i)){let o=t[r],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?a[s]=l:n[s]=l}}return Object.keys(a).length===0?n:{xs:n,ys:a}}getBoolean(e){return e==="1"||e.toLowerCase()==="true"?1:0}parseRow(e,t=!0){let n=[],a=0,r=e.length,s=jp;for(let i=0;i<r;i++)switch(s){case jp:switch(e.charAt(i)){case kh:a=i+1,s=Ih;break;case this.delimiter:if(a=i+1,this.delimiter===" "&&this.delimWhitespace)break;n.push(""),s=jp;break;default:s=AI,a=i;break}break;case AI:switch(e.charAt(i)){case this.delimiter:n.push(e.substring(a,i)),s=jp,a=i+1;break;default:}break;case Ih:switch(e.charAt(i)){case kh:s=ox;break;default:}break;case ox:switch(e.charAt(i)){case this.delimiter:n.push(e.substring(a,i-1)),s=jp,a=i+1;break;case kh:s=Ih;break;default:s=FI;break}break;case FI:switch(e.charAt(i)){case kh:s=Ih;break;default:}break;default:}if(s===ox?n.push(e.substring(a,r-1)):n.push(e.substring(a)),t&&n.length!==this.fullColumnNames.length)throw new Error(`Invalid row in csv file. Should have ${this.fullColumnNames.length} elements in a row, but got ${n}`);return n}},PC=class extends sn{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(!G().get("IS_BROWSER"))throw new Error("microphone API is only supported in browser environment.");let t=new PC(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(n){throw new Error(`Error thrown while initializing video stream: ${n.message}`)}if(!this.stream)throw new Error("Could not obtain audio from microphone.");let 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,n=await this.getAudioData();if(this.includeSpectrogram){let a=this.flattenQueue(n.freqDataQueue);e=this.getTensorFromAudioDataArray(a,[this.numFrames,this.columnTruncateLength,1])}if(this.includeWaveform){let a=this.flattenQueue(n.timeDataQueue);t=this.getTensorFromAudioDataArray(a,[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=[],n=0;return new Promise(a=>{let r=setInterval(()=>{this.includeSpectrogram&&(this.analyser.getFloatFrequencyData(this.freqData),this.freqData[0]===-1/0&&a({freqDataQueue:e,timeDataQueue:t}),e.push(this.freqData.slice(0,this.columnTruncateLength))),this.includeWaveform&&(this.analyser.getFloatTimeDomainData(this.timeData),t.push(this.timeData.slice())),++n===this.numFrames&&(clearInterval(r),a({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,n=new Float32Array(e.length*t);return e.forEach((a,r)=>n.set(a,r*t)),n}getTensorFromAudioDataArray(e,t){let n=new Float32Array(v.sizeFromShape(t));return n.set(e,n.length-e.length),bn(n,t)}},OC=class extends sn{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=je([0],"int32"),this.webcamConfig.centerCrop){let n=this.webcamConfig.resizeWidth*1/this.webcamVideoElement.width,a=this.webcamConfig.resizeHeight*1/this.webcamVideoElement.height,r=(1-n)/2,s=(1-a)/2,i=r+n,o=a+s;this.cropBox=Aa([s,r,o,i],[1,4])}else this.cropBox=Aa([0,0,1,1],[1,4])}summary(){return"webcam"}static async create(e,t={}){if(!G().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 n=new OC(e,t);return await n.start(),n}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=Vo.fromPixels(this.webcamVideoElement)}catch(t){throw new Error(`Error thrown converting video to pixels: 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XC=fr(e=>Math.ceil(e)),g5=_s(Ri,XC),b5={kernelName:Ri,backendName:"cpu",kernelFunc:g5};function I1(e,t,n,a){let r=v.getArrayFromDType(n,v.sizeFromShape(t));if(a&&n!=="string"){let s=0;e.forEach(i=>{let o=v.sizeFromShape(i.shape);r.set(i.vals,s),s+=o})}else{let s=0;e.forEach(i=>{let o=n==="string"?N.fromUint8ToStringArray(i.vals):i.vals,l=0;for(let u=0;u<i.shape[0];++u){let p=u*t[1]+s;for(let d=0;d<i.shape[1];++d)r[p+d]=o[l++]}s+=i.shape[1]})}return r}var YC=Ot((e,t)=>e===t?1:0),ZC=Zt(lu,YC,null,"bool"),y5={kernelName:lu,backendName:"cpu",kernelFunc:ZC},JC=fr(e=>Math.exp(e)),QC=_s(Hi,JC,"float32"),x5={kernelName:Hi,backendName:"cpu",kernelFunc:QC},e_=fr(e=>Math.expm1(e)),v5=_s(qi,e_),w5={kernelName:qi,backendName:"cpu",kernelFunc:v5},t_=fr(e=>Math.floor(e)),k5=_s(ji,t_),I5={kernelName:ji,backendName:"cpu",kernelFunc:k5},n_=Ot((e,t)=>Math.floor(e/t)),S5=Zt(Ki,n_,null,"int32"),N5={kernelName:Ki,backendName:"cpu",kernelFunc:S5};function a_(e,t,n,a,r,s,i,o,l){let u=Le([a,s],n);for(let p=0;p<a;p++){let d=[],c=0;for(let h=0;h<r;h++){let m=e[p*r+h];c+=m*i[h],d.push(m)}if(c<0||c>=l/s)throw new Error(`Invalid indices: ${d} does not index into ${o}`);for(let h=0;h<s;h++)u.values[p*s+h]=t.get(...t.indexToLoc(c*s+h))}return u}function r_(e,t,n){let a=Le(n,e.dtype);for(let r=0;r<a.size;++r){let s=a.indexToLoc(r).slice(),i=s[0],o=s[2],l=t.locToIndex([i,o]);s[2]=t.values[l];let u=e.locToIndex(s);0<=u&&u<e.values.length&&(a.values[r]=e.values[u])}return a}var s_=Ot((e,t)=>e>t?1:0),T5=Zt(hu,s_,null,"bool"),C5={kernelName:hu,backendName:"cpu",kernelFunc:T5},i_=Ot((e,t)=>e>=t?1:0),_5=Zt(Yi,i_,null,"bool"),E5={kernelName:Yi,backendName:"cpu",kernelFunc:_5},o_=Ot((e,t)=>e<t?1:0),A5=Zt(mu,o_,null,"bool"),F5={kernelName:mu,backendName:"cpu",kernelFunc:A5},l_=Ot((e,t)=>e<=t?1:0),$5=Zt(fu,l_,null,"bool"),D5={kernelName:fu,backendName:"cpu",kernelFunc:$5};function u_(e,t,n){let a=(t-e)/(n-1),r=v.makeZerosTypedArray(n,"float32");r[0]=e;for(let s=1;s<r.length;s++)r[s]=r[s-1]+a;return r}var p_=fr(e=>Math.log(e)),R5=_s(no,p_),M5={kernelName:no,backendName:"cpu",kernelFunc:R5};function c_(e,t,n,a){let r=v.getTypedArrayFromDType(a,v.sizeFromShape(n));for(let s=0;s<r.length;++s){let i=s*t,o=e[i];for(let l=0;l<t;++l){let u=e[i+l];(Number.isNaN(u)||u>o)&&(o=u)}r[s]=o}return r}var d_=Ot((e,t)=>Math.max(e,t)),P5=Zt(io,d_),O5={kernelName:io,backendName:"cpu",kernelFunc:P5},h_=Ot((e,t)=>Math.min(e,t)),L5=Zt(po,h_),z5={kernelName:po,backendName:"cpu",kernelFunc:L5},S1=Ot((e,t)=>e*t),W5=w1((e,t,n,a)=>({real:e*n-t*a,imag:e*a+t*n})),Mf=Zt(ho,S1,W5),B5={kernelName:ho,backendName:"cpu",kernelFunc:Mf};function m_(e,t,n){let a=v.createScalarValue(-1,n);return S1([],t,a,e,n)}function V5(e){let{inputs:t,backend:n}=e,{x:a}=t;ge(a,"neg");let r=n.data.get(a.dataId).values,[s,i]=m_(r,a.shape,a.dtype);return n.makeTensorInfo(i,a.dtype,s)}var U5={kernelName:Su,backendName:"cpu",kernelFunc:V5},f_=Ot((e,t)=>e!==t?1:0),G5=Zt(Nu,f_,null,"bool"),H5={kernelName:Nu,backendName:"cpu",kernelFunc:G5};function N1(e,t,n,a,r){let s=t.length,i=v.sizeFromShape(t),o=v.computeStrides(t),l=v.computeStrides(r),u=v.getTypedArrayFromDType(n,v.sizeFromShape(r));for(let p=0;p<i;++p){let d=v.indexToLoc(p,s,o),c=new Array(d.length);for(let m=0;m<c.length;m++)c[m]=d[a[m]];let h=v.locToIndex(c,s,l);u[h]=e[p]}return u}function Un(e){let{inputs:t,attrs:n,backend:a}=e,{x:r}=t,{perm:s}=n;ge(r,"transpose");let i=r.shape.length,o=new Array(i);for(let p=0;p<o.length;p++)o[p]=r.shape[s[p]];let l=a.data.get(r.dataId).values,u=N1(l,r.shape,r.dtype,s,o);return{dataId:a.write(u,o,r.dtype),shape:o,dtype:r.dtype}}var q5={kernelName:_r,backendName:"cpu",kernelFunc:Un};function g_(e,t,n,a){let[r,s]=N.computeOutAndReduceShapes(e,a),i=ga(t,"int32"),o=v.makeZerosTypedArray(v.sizeFromShape(r),i),l=v.sizeFromShape(s);for(let u=0;u<o.length;++u){let p=u*l,d=1;for(let c=0;c<l;++c)d*=n[p+c];o[u]=d}return{outVals:o,outShape:r,outDtype:i}}function j5(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{axis:s,keepDims:i}=a;ge(r,"prod");let o=r.shape.length,l=v.parseAxisParam(s,r.shape),u=N.getAxesPermutation(l,o),p=l,d=r,c=[];u!=null&&(d=Un({inputs:{x:r},backend:n,attrs:{perm:u}}),c.push(d),p=N.getInnerMostAxes(p.length,o));let h=n.data.get(d.dataId).values,{outVals:m,outShape:f,outDtype:g}=g_(d.shape,d.dtype,h,p),b=f;return i&&(b=N.expandShapeToKeepDim(f,l)),c.forEach(y=>n.disposeIntermediateTensorInfo(y)),n.makeTensorInfo(b,g,m)}var K5={kernelName:yo,backendName:"cpu",kernelFunc:j5};function X5(e,t,n){e.forEach((a,r)=>{if(a<0||a>=n){let s=v.indexToLoc(r,t.length,v.computeStrides(t)).join(",");throw new Error(`indices[${s}] = ${a} is not in [0, ${n})`)}})}function Y5(e,t){for(let n=0;n<e.length;++n){let a=e[n],r=n===e.length-1?t:e[n+1].length;if(a.length===0)throw new Error("Ragged splits may not be empty");if(a[0]<0)throw new Error("Ragged splits must be non-negative");if(a[a.length-1]>r)throw new Error("Ragged splits must not point past values");for(let s=1;s<a.length;++s)if(a[s-1]>a[s])throw new Error("Ragged splits must be sorted in ascending order")}}function Z5(e,t,n,a){let r=[],s=0,i=t.length-1+n.length,o=new Array(i).fill(null).map(()=>[0]);Y5(n,a);let l=1;for(let u=0;u<t.length-1;++u){l*=t[u];let p=t[u+1];for(let d=1;d<l+1;++d)o[u].push(d*p)}for(let u=0;u<e.length;++u){let p=e[u],d=e[u]+1;for(let c=0;c<n.length;++c){let h=n[c],m=c+t.length-1;if(m>=0){let f=o[m],g=f[f.length-1]-h[p];for(let b=p;b<d;++b)o[m].push(h[b+1]+g)}p=h[p],d=h[d]}d!==p&&(r.push([p,d]),s+=d-p)}return{outSplits:o,valueSlices:r,numValues:s}}function J5(e){let t=[];for(let n=0;n<e.length;++n){let a=e[n].length,r=v.getArrayFromDType("int32",a);t.push(r),e[n].forEach((s,i)=>r[i]=s)}return t}function $I(e,t){let n=e.slice(0,t);for(;n.length<t;)n.push(1);for(let a=t;a<e.length;a++)n[t-1]*=e[a];return n}function Q5(e,t,n,a,r,s){let i=$I(t,2)[1],o=$I(s,2)[1],l=0;for(let u of n)for(let p=u[0];p<u[1];++p){for(let d=0;d<a;++d)r[l*o+d]=e[p*i+d];++l}}function eK(e,t,n,a,r){let s=t.slice();s[0]=r;let i=v.getArrayFromDType(n,v.sizeFromShape(s)),o=e.length,l=o===0?0:o/t[0];return Q5(e,t,a,l,i,s),[i,s]}function b_(e,t,n,a,r,s,i,o){if(e.length===0)throw new Error("paramsNestedSplits must be non empty");if(t[0].length===0)throw new Error("Split tensors must not be scalars");let l=t[0][0]-1;if(X5(s,i,l),a.length===0)throw new Error("params.rank must be nonzero");let u=a[0],{outSplits:p,valueSlices:d,numValues:c}=Z5(s,i,e,u),h=J5(p),m=eK(n,a,r,d,c);return[h,m[0],m[1]]}var DI=2147483647;function y_(e,t,n,a,r,s,i){if(t.length>1)throw new Error("starts must be a scalar or vector");if(r.length>1)throw new Error("limits must be a scalar or vector");if(i.length>1)throw new Error("deltas must be a scalar or vector");let o=t.length===0,l=r.length===0,u=i.length===0,p=[];o||p.push(t[0]),l||p.push(r[0]),u||p.push(i[0]);for(let g=1;g<p.length;++g)if(p[g]!==p[g-1])throw new Error("starts, limits, and deltas must have the same shape");let d=p.length===0?1:p[0],c=v.getArrayFromDType("int32",d+1);c[0]=0;for(let g=0;g<d;++g){let b=o?e[0]:e[g],y=l?a[0]:a[g],x=u?s[0]:s[g];if(x===0)throw new Error("Requires delta != 0");let w;if(x>0&&y<b||x<0&&y>b)w=0;else if(w=Math.ceil(Math.abs((y-b)/x)),w>DI)throw new Error(`Requires ((limit - start) / delta) <= ${DI}`);c[g+1]=c[g]+w}let h=c[d],m=v.getArrayFromDType(n,h),f=0;for(let g=0;g<d;++g){let b=c[g+1]-c[g],y=o?e[0]:e[g],x=u?s[0]:s[g];for(let w=0;w<b;++w)m[f++]=y,y+=x}return[c,m]}var Na=N.RowPartitionType,jx=class{constructor(e,t,n,a,r,s,i,o,l,u){this.shape=e,this.shapeShape=t,this.values=n,this.valuesShape=a,this.valuesDType=r,this.defaultValue=s,this.defaultValueShape=i,this.rowPartitionValues=o,this.rowPartitionValuesShapes=l,this.rowPartitionTypes=N.getRowPartitionTypesHelper(u),this.raggedRank=N.getRaggedRank(this.rowPartitionTypes)}getRowPartitionTypeByDimension(e){return this.rowPartitionTypes[0]===Na.FIRST_DIM_SIZE?this.rowPartitionTypes[e+1]:this.rowPartitionTypes[e]}getRowPartitionTensor(e){return this.rowPartitionTypes[0]===Na.FIRST_DIM_SIZE?this.rowPartitionValues[e+1]:this.rowPartitionValues[e]}getMaxWidth(e){let t=this.getRowPartitionTensor(e-1);switch(this.getRowPartitionTypeByDimension(e-1)){case Na.VALUE_ROWIDS:return jx.getMaxWidthValueRowID(t);case Na.ROW_SPLITS:return jx.getMaxWidthRowSplit(t);default:throw new Error(`Cannot handle partition type ${Na[this.getRowPartitionTypeByDimension(e-1)]}`)}}static getMaxWidthRowSplit(e){let t=e.length;if(t===0||t===1)return 0;let n=0;for(let a=0;a<t-1;++a){let r=e[a+1]-e[a];r>n&&(n=r)}return n}static getMaxWidthValueRowID(e){let t=e.length;if(t===0)return 0;let n=0,a=e[0],r=0;for(let s=1;s<t;++s){let i=e[s];i!==a&&(a=i,r=Math.max(s-n,r),n=s)}return Math.max(t-n,r)}tensorShapeFromTensor(e,t,n=!0){if(t.length===0){if(e[0]===-1)return[];throw new Error("The only valid scalar shape tensor is the fully unknown shape specified as -1.")}return MI(e,n)}calculateOutputSize(e){let t=this.valuesShape,n=this.defaultValueShape;N.validateDefaultValueShape(n,t);let a=this.tensorShapeFromTensor(this.shape,this.shapeShape),r=N.combineRaggedTensorToTensorShapes(this.raggedRank,a,t);r[0]<0&&(r[0]=e);for(let s=1;s<=this.raggedRank;++s)r[s]<0&&(r[s]=this.getMaxWidth(s));return r}calculateFirstParentOutputIndex(e,t,n){let a=Math.min(e,n),r=[],s=0;for(let i=0;i<a;++i,s+=t)r.push(s);for(let i=a;i<e;++i)r.push(-1);return v.assert(r.length===e,()=>"Final length of result must be equal to firstDimension."),r}calculateOutputIndexRowSplit(e,t,n,a){let r=e.length,s=[];for(let i=0;i<r-1;++i){let o=e[i+1]-e[i],l=Math.min(a,o),u=t[i];u===-1&&(l=0);for(let p=0;p<l;++p)s.push(u),u+=n;for(let p=0;p<o-l;++p)s.push(-1)}if(r>0&&s.length!==e[r-1])throw new Error("Invalid row split size.");return s}calculateOutputIndexValueRowID(e,t,n,a){let r=e.length,s=[];if(r===0)return[];let i=0,o=e[0];if(o>=t.length)throw new Error(`Got currentValueRowId=${o}, which is not less than ${t.length}`);let l=t[o];s.push(l);for(let u=1;u<r;++u){let p=e[u];if(p===o)l>=0&&(++i,i<a?l+=n:l=-1);else{if(i=0,o=p,p>=t.length)throw new Error(`Got nextValueRowId=${p} which is not less than ${t.length}`);l=t[p]}s.push(l)}if(s.length!==e.length)throw new Error("Invalid row ids.");return s}calculateOutputIndex(e,t,n,a){let r=this.getRowPartitionTensor(e),s=this.getRowPartitionTypeByDimension(e);switch(s){case Na.VALUE_ROWIDS:return this.calculateOutputIndexValueRowID(r,t,n,a);case Na.ROW_SPLITS:if(r.length-1>t.length)throw new Error(`Row partition size is greater than output size: ${r.length-1} > ${t.length}`);return this.calculateOutputIndexRowSplit(r,t,n,a);default:throw new Error(`Unsupported partition type: ${Na[s]}`)}}getFirstDimensionSize(){let e=this.rowPartitionValues[0];if(this.rowPartitionTypes.length===0)throw new Error("No row_partition_types given.");let t=this.rowPartitionTypes[0];switch(t){case Na.FIRST_DIM_SIZE:return e[0];case Na.VALUE_ROWIDS:throw new Error("Cannot handle VALUE_ROWIDS in first dimension.");case Na.ROW_SPLITS:return this.rowPartitionValuesShapes[0][0]-1;default:throw new Error(`Cannot handle type ${Na[t]}`)}}compute(){if(this.rowPartitionValues[0].length<=0)throw new Error("Invalid first partition input. Tensor requires at least one element.");let e=this.getFirstDimensionSize(),t=this.calculateOutputSize(e),n=new Array(this.raggedRank+1);n[n.length-1]=1;for(let s=n.length-2;s>=0;--s)n[s]=n[s+1]*t[s+1];let a=MI(t,!1),r=v.getArrayFromDType(this.valuesDType,v.sizeFromShape(a));if(n[0]*t[0]>0){let s=this.calculateFirstParentOutputIndex(e,n[0],t[0]);for(let i=1;i<=this.raggedRank;++i)s=this.calculateOutputIndex(i-1,s,n[i],t[i]);this.setOutput(this.raggedRank,s,r,a)}return[a,r]}setOutput(e,t,n,a){if(n.length===0)return;let r=this.values,s=n,i=a.slice();i=i.slice(e+1);let o=v.sizeFromShape(i),l=t.length,u=this.defaultValue;if(u.length!==o&&u.length!==1){let h=this.defaultValueShape;P(()=>{let m=W(u,h);u=ni(m,i).dataSync()})}let p=0,d=0,c=0;for(let h=0;h<=l;++h){let m=h<l?t[h]:-1;if(m===c){++c;continue}if(d<c){let f=r.subarray(p*o),g=s.subarray(d*o),b=(c-d)*o;RI(g,f,b)}if(h>=l){let 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RK(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{axis:s,keepDims:i}=a;ge(r,"all");let o=v.parseAxisParam(s,r.shape),l=o,u=N.getAxesPermutation(l,r.shape.length),p=r;u!=null&&(p=Un({inputs:{x:r},backend:n,attrs:{perm:u}}),l=N.getInnerMostAxes(l.length,r.shape.length)),N.assertAxesAreInnerMostDims("all",l,p.shape.length);let[d,c]=N.computeOutAndReduceShapes(p.shape,l),h=v.sizeFromShape(c),m=v.makeZerosTypedArray(v.sizeFromShape(d),p.dtype),f=n.data.get(p.dataId).values;for(let b=0;b<m.length;++b){let y=b*h,x=f[y];for(let w=0;w<h;++w){let I=f[y+w];x=x&&I}m[b]=x}u!=null&&n.disposeIntermediateTensorInfo(p);let g=n.makeTensorInfo(d,p.dtype,m);if(i){let b=N.expandShapeToKeepDim(d,o),y=xt({inputs:{x:g},backend:n,attrs:{shape:b}});return n.disposeIntermediateTensorInfo(g),y}return g}var MK={kernelName:jl,backendName:"cpu",kernelFunc:RK};function PK(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{axis:s,keepDims:i}=a;ge(r,"any");let 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i=v.parseAxisParam(s,r.shape),o=N.getAxesPermutation(i,r.shape.length),l=r,u=[];o!=null&&(l=Un({inputs:{x:r},backend:n,attrs:{perm:o}}),u.push(l),i=N.getInnerMostAxes(i.length,l.shape.length)),i=[i[0]],N.assertAxesAreInnerMostDims("argMax",i,l.shape.length);let[p,d]=N.computeOutAndReduceShapes(l.shape,i),c=v.sizeFromShape(p),h=v.makeZerosTypedArray(c,"int32"),m=v.sizeFromShape(d),f=n.data.get(l.dataId).values;for(let g=0;g<h.length;++g){let b=g*m,y=f[b],x=0;for(let w=0;w<m;++w){let I=f[b+w];I>y&&(y=I,x=w)}h[g]=x}return u.forEach(g=>n.disposeIntermediateTensorInfo(g)),n.makeTensorInfo(p,"int32",h)}var zK={kernelName:Xl,backendName:"cpu",kernelFunc:LK};function WK(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{axis:s}=a;ge(r,"argMin");let i=v.parseAxisParam(s,r.shape),o=N.getAxesPermutation(i,r.shape.length),l=r,u=[];o!=null&&(l=Un({inputs:{x:r},backend:n,attrs:{perm:o}}),u.push(l),i=N.getInnerMostAxes(i.length,l.shape.length)),i=[i[0]],N.assertAxesAreInnerMostDims("argMin",i,l.shape.length);let[p,d]=N.computeOutAndReduceShapes(l.shape,i),c=v.sizeFromShape(p),h=v.makeZerosTypedArray(c,"int32"),m=v.sizeFromShape(d),f=n.data.get(l.dataId).values;for(let g=0;g<h.length;++g){let b=g*m,y=f[b],x=0;for(let w=0;w<m;++w){let I=f[b+w];I<y&&(y=I,x=w)}h[g]=x}return u.forEach(g=>n.disposeIntermediateTensorInfo(g)),n.makeTensorInfo(p,"int32",h)}var BK={kernelName:Yl,backendName:"cpu",kernelFunc:WK},VK=it(Ti,e=>Math.asin(e)),UK={kernelName:Ti,backendName:"cpu",kernelFunc:VK},GK=it(Ci,e=>Math.asinh(e)),HK={kernelName:Ci,backendName:"cpu",kernelFunc:GK},qK=it(_i,e=>Math.atan(e)),jK={kernelName:_i,backendName:"cpu",kernelFunc:qK},KK=Ot((e,t)=>Math.atan2(e,t)),XK=Zt(Ai,KK),YK={kernelName:Ai,backendName:"cpu",kernelFunc:XK},ZK=it(Ei,e=>Math.atanh(e)),JK={kernelName:Ei,backendName:"cpu",kernelFunc:ZK};function D1(e,t,n,a,r,s){let i=r.strideHeight,o=r.strideWidth,l=r.dilationHeight,u=r.dilationWidth,p=r.effectiveFilterHeight,d=r.effectiveFilterWidth,c=r.padInfo.top,h=r.padInfo.left,m=s==="max"?Number.NEGATIVE_INFINITY:Number.POSITIVE_INFINITY,f=Le(r.outShape,n),g=f.values,b=r.outShape[1]*r.outShape[2]*r.outShape[3],y=r.outShape[2]*r.outShape[3],x=r.outShape[3];for(let w=0;w<r.batchSize;++w){let I=w*b,T=w*a[0];for(let C=0;C<r.inChannels;++C)for(let E=0;E<r.outHeight;++E){let 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U=B-C,H=f.get(g,S,B,b);H>D&&(D=H,r?$=s?((g*a.inHeight+S)*a.inWidth+B)*a.inChannels+b:(S*a.inWidth+B)*a.inChannels+b:$=M*c+U)}}i.set($,g,y,T,b)}}return i}function L_(e,t,n,a,r,s){let i=r.strideDepth,o=r.strideHeight,l=r.strideWidth,u=r.dilationDepth,p=r.dilationHeight,d=r.dilationWidth,c=r.effectiveFilterDepth,h=r.effectiveFilterHeight,m=r.effectiveFilterWidth,f=r.padInfo.front,g=r.padInfo.top,b=r.padInfo.left,y=s==="max"?Number.NEGATIVE_INFINITY:Number.POSITIVE_INFINITY,x=Le(r.outShape,n),w=x.values,I=r.outShape[1]*r.outShape[2]*r.outShape[3]*r.outShape[4],T=r.outShape[2]*r.outShape[3]*r.outShape[4],C=r.outShape[3]*r.outShape[4],E=r.outShape[4];for(let F=0;F<r.batchSize;++F){let D=F*I,$=F*a[0];for(let S=0;S<r.inChannels;++S)for(let M=0;M<r.outDepth;++M){let B=M*i-f,U=B;for(;U<0;)U+=u;let H=Math.min(r.inDepth,c+B),j=D+M*T;for(let K=0;K<r.outHeight;++K){let Z=K*o-g,J=Z;for(;J<0;)J+=p;let ee=Math.min(r.inHeight,h+Z),ae=j+K*C;for(let te=0;te<r.outWidth;++te){let re=te*l-b,se=re;for(;se<0;)se+=d;let ye=Math.min(r.inWidth,m+re),ue=ae+te*E,be=y,ke=0,Se=0;for(let Ge=U;Ge<H;Ge+=u){let ht=$+Ge*a[1];for(let st=J;st<ee;st+=p){let tt=ht+st*a[2];for(let nt=se;nt<ye;nt+=d){let Re=tt+nt*a[3],ft=e[Re+S];if(s==="max"&&ft>be?be=ft:s==="avg"&&(ke+=ft,Se++),isNaN(be))break}if(isNaN(be))break}if(isNaN(be))break}let We=ue+S;w[We]=s==="avg"?ke/Math.max(Se,1):be}}}}return x}function QK(e,t){let n=Le(t.outShape,"int32"),a=t.strideDepth,r=t.strideHeight,s=t.strideWidth,i=t.dilationDepth,o=t.dilationHeight,l=t.dilationWidth,u=t.effectiveFilterDepth,p=t.effectiveFilterHeight,d=t.effectiveFilterWidth,c=t.padInfo.front,h=t.padInfo.top,m=t.padInfo.left;for(let f=0;f<t.batchSize;++f)for(let g=0;g<t.inChannels;++g)for(let b=0;b<t.outDepth;++b){let y=b*a-c,x=y;for(;x<0;)x+=i;let w=Math.min(t.inDepth,u+y);for(let I=0;I<t.outHeight;++I){let T=I*r-h,C=T;for(;C<0;)C+=o;let E=Math.min(t.inHeight,p+T);for(let F=0;F<t.outWidth;++F){let D=F*s-m,$=D;for(;$<0;)$+=l;let S=Math.min(t.inWidth,d+D),M=Number.NEGATIVE_INFINITY,B=-1;for(let U=x;U<w;U+=i){let H=U-y;for(let j=C;j<E;j+=o){let K=j-T;for(let Z=$;Z<S;Z+=l){let J=Z-D,ee=e.get(f,U,j,Z,g);ee>=M&&(M=ee,B=H*p*d+K*p+J)}}}n.set(B,f,b,I,F,g)}}}return n}function e8(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t;ge(r,"avgPool");let{filterSize:s,strides:i,pad:o,dimRoundingMode:l}=a,u=1;v.assert(N.eitherStridesOrDilationsAreOne(i,u),()=>`Error in avgPool: Either strides or dilations must be 1. 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p=N.computePool3DInfo(s.shape,i,o,1,l,u),d=p.strideDepth,c=p.strideHeight,h=p.strideWidth,m=p.filterDepth,f=p.filterHeight,g=p.filterWidth,b=p.dilationDepth,y=p.dilationHeight,x=p.dilationWidth,w=p.effectiveFilterDepth,I=p.effectiveFilterHeight,T=p.effectiveFilterWidth,C=w-1-p.padInfo.front,E=T-1-p.padInfo.left,F=I-1-p.padInfo.top,D=Le(s.shape,"float32"),$=1/(m*f*g),S=n.bufferSync(r);for(let M=0;M<p.batchSize;++M)for(let B=0;B<p.inChannels;++B)for(let U=0;U<p.inDepth;++U)for(let H=0;H<p.inHeight;++H)for(let j=0;j<p.inWidth;++j){let K=U-C,Z=H-F,J=j-E,ee=0;for(let ae=0;ae<w;ae+=b){let te=(K+ae)/d;if(!(te<0||te>=p.outDepth||Math.floor(te)!==te))for(let re=0;re<I;re+=y){let se=(Z+re)/c;if(!(se<0||se>=p.outHeight||Math.floor(se)!==se))for(let ye=0;ye<T;ye+=x){let ue=(J+ye)/h;if(ue<0||ue>=p.outWidth||Math.floor(ue)!==ue)continue;let be=S.get(M,te,se,ue,B);ee+=be}}}D.set(ee*$,M,U,H,j,B)}return n.makeTensorInfo(D.shape,D.dtype,D.values)}var s8={kernelName:_c,backendName:"cpu",kernelFunc:r8};function i8(e){let{inputs:t,backend:n,attrs:a}=e,{dy:r,input:s}=t,i=s;ge([r,s],"avgPoolGrad");let{filterSize:o,strides:l,pad:u}=a,p=N.computePool2DInfo(i.shape,o,l,1,u),d=p.strideHeight,c=p.strideWidth,h=p.filterHeight,m=p.filterWidth,f=p.dilationHeight,g=p.dilationWidth,b=p.effectiveFilterHeight,y=p.effectiveFilterWidth,x=y-1-p.padInfo.left,w=b-1-p.padInfo.top,I=Le(i.shape,"float32"),T=1/(h*m),C=n.data.get(r.dataId).values,E=Le(r.shape,"float32",C);for(let F=0;F<p.batchSize;++F)for(let D=0;D<p.inChannels;++D)for(let $=0;$<p.inHeight;++$)for(let S=0;S<p.inWidth;++S){let M=$-w,B=S-x,U=0;for(let H=0;H<b;H+=f){let j=(M+H)/d;if(!(j<0||j>=p.outHeight||Math.floor(j)!==j))for(let K=0;K<y;K+=g){let Z=(B+K)/c;if(Z<0||Z>=p.outWidth||Math.floor(Z)!==Z)continue;let J=E.get(F,j,Z,D);U+=J}}I.set(U*T,F,$,S,D)}return n.makeTensorInfo(I.shape,I.dtype,I.values)}var o8={kernelName:bm,backendName:"cpu",kernelFunc:i8};function 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n.makeTensorInfo(r.shape,r.dtype,f)}var u8={kernelName:Xi,backendName:"cpu",kernelFunc:l8};function p8(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{blockShape:s,crops:i}=a;ge([r],"batchToSpaceND");let o=s.reduce((b,y)=>b*y),l=N.getReshaped(r.shape,s,o),u=N.getPermuted(l.length,s.length),p=N.getReshapedPermuted(r.shape,s,o),d=N.getSliceBeginCoords(i,s.length),c=N.getSliceSize(p,i,s.length),h=xt({inputs:{x:r},backend:n,attrs:{shape:l}}),m=Un({inputs:{x:h},backend:n,attrs:{perm:u}}),f=xt({inputs:{x:m},backend:n,attrs:{shape:p}}),g=yi({inputs:{x:f},backend:n,attrs:{begin:d,size:c}});return n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(f),g}var c8={kernelName:Jl,backendName:"cpu",kernelFunc:p8};function d8(e){let{inputs:t,backend:n,attrs:a}=e,{x:r,weights:s}=t,{size:i}=a,o=n.data.get(r.dataId).values,l=n.data.get(s.dataId).values,u=k1(o,l,s.dtype,s.shape,i);return n.makeTensorInfo([i],s.dtype,u)}var h8={kernelName:Ql,backendName:"cpu",kernelFunc:d8};function m8(e){let{inputs:t,backend:n}=e,{s0:a,s1:r}=t,s=n.data.get(a.dataId).values,i=n.data.get(r.dataId).values,o=N.assertAndGetBroadcastShape(Array.from(s),Array.from(i));return n.makeTensorInfo([o.length],"int32",Int32Array.from(o))}var f8={kernelName:Ec,backendName:"cpu",kernelFunc:m8},g8=it(ys,(e,t)=>{let n=t;return e>n.clipValueMax?n.clipValueMax:e<n.clipValueMin?n.clipValueMin:e}),b8={kernelName:ys,backendName:"cpu",kernelFunc:g8},y8=e=>{let{x:t}=e.inputs,n=e.backend,a=new Float32Array(v.sizeFromShape(t.shape)),r=n.data.get(t.dataId),s=r.complexTensorInfos.real,i=r.complexTensorInfos.imag,o=n.data.get(s.dataId).values,l=n.data.get(i.dataId).values;for(let u=0;u<o.length;u++){let p=o[u],d=l[u];a[u]=Math.hypot(p,d)}return n.makeOutput(a,t.shape,"float32")},x8={kernelName:Ac,backendName:"cpu",kernelFunc:y8};function Vl(e){let{inputs:t,backend:n}=e,{input:a}=t,r=n.data.get(a.dataId).complexTensorInfos.imag,s=n.data.get(r.dataId).values;return n.makeTensorInfo(r.shape,r.dtype,s)}var v8={kernelName:Tm,backendName:"cpu",kernelFunc:Vl};function Ul(e){let{inputs:t,backend:n,attrs:a}=e,{axis:r}=a,s=v.parseAxisParam(r,t[0].shape)[0],i=t.map(f=>f.shape);N.assertParamsConsistent(i,s);let o=N.computeOutShape(t.map(f=>f.shape),s);if(v.sizeFromShape(o)===0)return n.makeTensorInfo(o,t[0].dtype,[]);let l=t.filter(f=>v.sizeFromShape(f.shape)>0);if(l.length===1)return pr({inputs:{x:l[0]},backend:n});if(l[0].dtype==="complex64"){let f=l.map(w=>bi({inputs:{input:w},backend:n})),g=l.map(w=>Vl({inputs:{input:w},backend:n})),b=Ul({inputs:f,backend:n,attrs:{axis:s}}),y=Ul({inputs:g,backend:n,attrs:{axis:s}}),x=Zn({inputs:{real:b,imag:y},backend:n});return 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Vt(c.outShape,r.dtype),I=v.computeStrides(r.shape),T=v.computeStrides(s.shape),C=I[0],E=x?I[1]:I[2],F=x?I[2]:1,D=x?1:I[1],$=w.strides[0],S=x?w.strides[1]:w.strides[2],M=x?w.strides[2]:1,B=x?1:w.strides[1],U=n.data.get(r.dataId).values,H=n.data.get(s.dataId).values,j=w.values;for(let K=0;K<c.batchSize;++K){let Z=K*C,J=K*$;for(let ee=0;ee<c.outHeight;++ee){let ae=J+ee*S,te=ee*c.strideHeight-y;for(let re=0;re<h;++re){let se=te+re*f;if(se<0||se>=c.inHeight)continue;let ye=re*T[0],ue=Z+se*E;for(let be=0;be<c.outWidth;++be){let ke=ae+be*M,Se=be*c.strideWidth-b;for(let We=0;We<m;++We){let Ge=Se+We*g;if(Ge<0||Ge>=c.inWidth)continue;let ht=ye+We*T[1],st=ue+Ge*F,tt=ht;for(let nt=0;nt<c.inChannels;++nt){let Re=U[st+nt*D];for(let ft=0;ft<c.outChannels;++ft)j[ke+ft*B]+=Re*H[tt+ft];tt+=c.outChannels}}}}}}return n.makeTensorInfo(w.shape,w.dtype,j)}var k8={kernelName:Mi,backendName:"cpu",kernelFunc:z_};function I8(e){let{inputs:t,backend:n,attrs:a}=e,{x:r,dy:s}=t,{strides:i,pad:o,dataFormat:l,dimRoundingMode:u,filterShape:p}=a;ge([r,s],"conv2dBackpropFilter");let d=N.convertConv2DDataFormat(l),c=N.computeConv2DInfo(r.shape,p,i,1,o,u,!1,d),{strideHeight:h,strideWidth:m,filterHeight:f,filterWidth:g}=c,b=c.dataFormat==="channelsLast",y=new Vt(c.filterShape,"float32"),x=c.padInfo.left,w=c.padInfo.top,I=n.data.get(r.dataId).values,T=n.data.get(s.dataId).values,C=new Vt(r.shape,r.dtype,I),E=new Vt(s.shape,s.dtype,T);for(let F=0;F<f;++F){let D=Math.max(0,Math.ceil((w-F)/h)),$=Math.min(c.outHeight,(c.inHeight+w-F)/h);for(let S=0;S<g;++S){let M=Math.max(0,Math.ceil((x-S)/m)),B=Math.min(c.outWidth,(c.inWidth+x-S)/m);for(let U=0;U<c.inChannels;++U)for(let H=0;H<c.outChannels;++H){let j=0;for(let K=0;K<c.batchSize;++K)for(let Z=D;Z<$;++Z){let J=F+Z*h-w;for(let ee=M;ee<B;++ee){let ae=S+ee*m-x;b?j+=C.get(K,J,ae,U)*E.get(K,Z,ee,H):j+=C.get(K,U,J,ae)*E.get(K,H,Z,ee)}}y.set(j,F,S,U,H)}}}return n.makeTensorInfo(y.shape,y.dtype,y.values)}var S8={kernelName:vm,backendName:"cpu",kernelFunc:I8};function N8(e){let{inputs:t,backend:n,attrs:a}=e,{dy:r,filter:s}=t,{inputShape:i,strides:o,pad:l,dataFormat:u,dimRoundingMode:p}=a;ge([r,s],"conv2dBackpropInput");let d=v.computeStrides(s.shape),c=v.computeStrides(r.shape),h=N.convertConv2DDataFormat(u),m=N.computeConv2DInfo(i,s.shape,o,1,l,p,!1,h),f=new Vt(m.inShape,"float32"),g=f.values,b=n.data.get(r.dataId).values,y=n.data.get(s.dataId).values,[x,w,I]=d,{batchSize:T,filterHeight:C,filterWidth:E,inChannels:F,inHeight:D,inWidth:$,outChannels:S,outHeight:M,outWidth:B,strideHeight:U,strideWidth:H}=m;h=m.dataFormat;let j=C-1-m.padInfo.top,K=E-1-m.padInfo.left,Z=h==="channelsLast",J=f.strides[0],ee=Z?f.strides[1]:f.strides[2],ae=Z?f.strides[2]:1,te=Z?1:f.strides[1],re=c[0],se=Z?c[1]:c[2],ye=Z?c[2]:1,ue=Z?1:c[1];for(let be=0;be<T;++be)for(let ke=0;ke<F;++ke)for(let Se=0;Se<D;++Se){let 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u=v.computeStrides(r.shape),p=v.computeStrides(s.shape),d=N.computeConv3DInfo(r.shape,l,i,1,o),c=d.strideDepth,h=d.strideHeight,m=d.strideWidth,f=d.filterDepth,g=d.filterHeight,b=d.filterWidth,y=new Vt(d.filterShape,"float32"),x=y.values,[w,I,T,C]=y.strides,E=n.data.get(s.dataId).values,[F,D,$,S]=p,M=n.data.get(r.dataId).values,[B,U,H,j]=u,K=d.padInfo.front,Z=d.padInfo.left,J=d.padInfo.top;for(let ee=0;ee<f;++ee){let ae=Math.max(0,Math.ceil((K-ee)/c)),te=Math.min(d.outDepth,(d.inDepth+K-ee)/c),re=ee*w;for(let se=0;se<g;++se){let ye=Math.max(0,Math.ceil((J-se)/h)),ue=Math.min(d.outHeight,(d.inHeight+J-se)/h),be=se*I+re;for(let ke=0;ke<b;++ke){let Se=Math.max(0,Math.ceil((Z-ke)/m)),We=Math.min(d.outWidth,(d.inWidth+Z-ke)/m),Ge=ke*T+be;for(let ht=0;ht<d.inChannels;++ht){let st=ht*C+Ge;for(let tt=0;tt<d.outChannels;++tt){let nt=0;for(let Re=0;Re<d.batchSize;++Re){let ft=Re*B,qn=Re*F;for(let Lt=ae;Lt<te;++Lt){let oa=(ee+Lt*c-K)*U+ft,pn=Lt*D+qn;for(let $n=ye;$n<ue;++$n){let la=(se+$n*h-J)*H+oa,Dn=$n*$+pn;for(let ot=Se;ot<We;++ot){let Rn=(ke+ot*m-Z)*j+la,jn=ot*S+Dn;nt+=M[Rn+ht]*E[jn+tt]}}}}x[st+tt]=nt}}}}}return n.makeTensorInfo(y.shape,y.dtype,y.values)}var A8={kernelName:tu,backendName:"cpu",kernelFunc:E8};function F8(e){let{inputs:t,backend:n,attrs:a}=e,{dy:r,filter:s}=t,{pad:i,strides:o,inputShape:l}=a;ge([r],"conv3dBackpropInputV2");let u=v.computeStrides(r.shape),p=v.computeStrides(s.shape),d=N.computeConv3DInfo(l,s.shape,o,1,i),c=new Vt(d.inShape,"float32"),h=c.values,[m,f,g,b]=c.strides,y=n.data.get(r.dataId).values,[x,w,I,T]=u,C=n.data.get(s.dataId).values,[E,F,D,$]=p,{batchSize:S,filterDepth:M,filterHeight:B,filterWidth:U,inChannels:H,inDepth:j,inHeight:K,inWidth:Z,outChannels:J,outDepth:ee,outHeight:ae,outWidth:te,strideDepth:re,strideHeight:se,strideWidth:ye}=d,ue=M-1-d.padInfo.front,be=B-1-d.padInfo.top,ke=U-1-d.padInfo.left;for(let Se=0;Se<S;++Se)for(let We=0;We<H;++We)for(let Ge=0;Ge<j;++Ge){let ht=Ge-ue,st=Math.max(0,Math.ceil(ht/re)),tt=Math.min(ee,(M+ht)/re);for(let nt=0;nt<K;++nt){let Re=nt-be,ft=Math.max(0,Math.ceil(Re/se)),qn=Math.min(ae,(B+Re)/se);for(let Lt=0;Lt<Z;++Lt){let oa=Lt-ke,pn=Math.max(0,Math.ceil(oa/ye)),$n=Math.min(te,(U+oa)/ye),la=0;for(let Dn=st;Dn<tt;++Dn){let ot=Dn*re-ht;for(let Rn=ft;Rn<qn;++Rn){let jn=Rn*se-Re;for(let xr=pn;xr<$n;++xr){let ll=xr*ye-oa,Qa=x*Se+w*Dn+I*Rn+T*xr,Mp=E*(M-1-ot)+F*(B-1-jn)+D*(U-1-ll)+$*We;for(let Ia=0;Ia<J;++Ia){let Hr=y[Qa+Ia],Jt=C[Mp+Ia];la+=Hr*Jt}}}}h[m*Se+f*Ge+g*nt+b*Lt+We]=la}}}return n.makeTensorInfo(c.shape,c.dtype,c.values)}var $8={kernelName:nu,backendName:"cpu",kernelFunc:F8},D8=it(Li,e=>Math.cos(e)),R8={kernelName:Li,backendName:"cpu",kernelFunc:D8},M8=it(zi,e=>Math.cosh(e)),P8={kernelName:zi,backendName:"cpu",kernelFunc:M8};function O8(e){let{inputs:t,backend:n,attrs:a}=e,{image:r,boxes:s,boxInd:i}=t,{cropSize:o,method:l,extrapolationValue:u}=a,[p,d,c,h]=r.shape,m=s.shape[0],[f,g]=o,b=Le([m,f,g,h],"float32"),y=n.data.get(s.dataId).values,x=n.data.get(i.dataId).values,w=n.data.get(r.dataId).values,I=v.computeStrides(r.shape),T=v.computeStrides(b.shape);for(let C=0;C<m;C++){let E=C*4,F=y[E],D=y[E+1],$=y[E+2],S=y[E+3],M=x[C];if(M>=p)continue;let B=f>1?($-F)*(d-1)/(f-1):0,U=g>1?(S-D)*(c-1)/(g-1):0;for(let H=0;H<f;H++){let j=f>1?F*(d-1)+H*B:.5*(F+$)*(d-1);if(j<0||j>d-1){for(let K=0;K<g;K++)for(let Z=0;Z<h;Z++){let J=Z+K*T[2]+H*T[1]+C*T[0];b.values[J]=u}continue}if(l==="bilinear"){let K=Math.floor(j),Z=Math.ceil(j),J=j-K;for(let ee=0;ee<g;ee++){let ae=g>1?D*(c-1)+ee*U:.5*(D+S)*(c-1);if(ae<0||ae>c-1){for(let ye=0;ye<h;ye++){let ue=ye+ee*T[2]+H*T[1]+C*T[0];b.values[ue]=u}continue}let te=Math.floor(ae),re=Math.ceil(ae),se=ae-te;for(let ye=0;ye<h;ye++){let ue=ye+te*I[2]+K*I[1]+M*I[0],be=w[ue];ue=ye+re*I[2]+K*I[1]+M*I[0];let ke=w[ue];ue=ye+te*I[2]+Z*I[1]+M*I[0];let Se=w[ue];ue=ye+re*I[2]+Z*I[1]+M*I[0];let We=w[ue],Ge=be+(ke-be)*se,ht=Se+(We-Se)*se;ue=ye+ee*T[2]+H*T[1]+C*T[0],b.values[ue]=Ge+(ht-Ge)*J}}}else for(let K=0;K<g;++K){let Z=g>1?D*(c-1)+K*U:.5*(D+S)*(c-1);if(Z<0||Z>c-1){for(let ae=0;ae<h;ae++){let te=ae+K*T[2]+H*T[1]+C*T[0];b.values[te]=u}continue}let J=Math.round(Z),ee=Math.round(j);for(let ae=0;ae<h;ae++){let te=ae+J*I[2]+ee*I[1]+M*I[0],re=ae+K*T[2]+H*T[1]+C*T[0];b.values[re]=w[te]}}}}return n.makeTensorInfo(b.shape,b.dtype,b.values)}var L8={kernelName:ru,backendName:"cpu",kernelFunc:O8};function z8(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{axis:s,exclusive:i,reverse:o}=a;ge(r,"cumprod");let l=N.getAxesPermutation([s],r.shape.length),u=r;l!=null&&(u=Un({inputs:{x:r},backend:n,attrs:{perm:l}}));let p=N.getInnerMostAxes(1,r.shape.length)[0];if(p!==u.shape.length-1)throw new Error(`backend.cumprod in CPU expects an inner-most axis=${u.shape.length-1} but got axis=${p}`);let d=ga(u.dtype,"int32"),c=v.makeOnesTypedArray(v.sizeFromShape(u.shape),d),h=n.data.get(u.dataId).values,m=u.shape[u.shape.length-1],f=o?(b,y)=>b+m-y-1:(b,y)=>b+y;for(let b=0;b<h.length;b+=m)for(let y=0;y<m;y++){let x=f(b,y);if(y===0)c[x]=i?1:h[x];else{let w=f(b,y-1);c[x]=i?h[w]*c[w]:h[x]*c[w]}}let g=n.makeTensorInfo(u.shape,d,c);if(l!=null){let b=N.getUndoAxesPermutation(l),y=Un({inputs:{x:g},backend:n,attrs:{perm:b}});return n.disposeIntermediateTensorInfo(g),n.disposeIntermediateTensorInfo(u),y}return g}var W8={kernelName:au,backendName:"cpu",kernelFunc:z8};function B8(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{axis:s,exclusive:i,reverse:o}=a;ge(r,"cumsum");let l=N.getAxesPermutation([s],r.shape.length),u=r;l!=null&&(u=Un({inputs:{x:r},backend:n,attrs:{perm:l}}));let p=N.getInnerMostAxes(1,r.shape.length)[0];if(p!==u.shape.length-1)throw new Error(`backend.cumsum in CPU expects an inner-most axis=${u.shape.length-1} but got axis=${p}`);let d=ga(u.dtype,"int32"),c=v.makeZerosTypedArray(v.sizeFromShape(u.shape),d),h=n.data.get(u.dataId).values,m=u.shape[u.shape.length-1],f=o?(b,y)=>b+m-y-1:(b,y)=>b+y;for(let b=0;b<h.length;b+=m)for(let y=0;y<m;y++){let x=f(b,y);if(y===0)c[x]=i?0:h[x];else{let w=f(b,y-1);c[x]=i?h[w]+c[w]:h[x]+c[w]}}let g=n.makeTensorInfo(u.shape,d,c);if(l!=null){let b=N.getUndoAxesPermutation(l),y=Un({inputs:{x:g},backend:n,attrs:{perm:b}});return n.disposeIntermediateTensorInfo(g),n.disposeIntermediateTensorInfo(u),y}return g}var V8={kernelName:Wi,backendName:"cpu",kernelFunc:B8};function U8(e){let{inputs:t,backend:n,attrs:a}=e,{x:r,weights:s}=t,{size:i,binaryOutput:o}=a;if(r.shape.length===1){let l=n.data.get(r.dataId).values,u=n.data.get(s.dataId).values,p=k1(l,u,s.dtype,s.shape,i);return n.makeTensorInfo([i],s.dtype,p)}else if(r.shape.length===2){let l=n.bufferSync(r),u=n.bufferSync(s),p=jC(l,u,i,o);return n.makeTensorInfo(p.shape,s.dtype,p.values)}throw new Error(`Error in denseBincount: input must be at most rank 2, but got rank${r.shape.length}.`)}var G8={kernelName:Fc,backendName:"cpu",kernelFunc:U8};function H8(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{blockSize:s,dataFormat:i}=a;v.assert(i==="NHWC",()=>`Only NHWC dataFormat supported on CPU for depthToSpace. 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program.')}function lE(e,t,n){return e.getUniformLocation(t,n)}function uE(e,t,n,a){de(e,()=>iE(e,t,a)),de(e,()=>e.uniform1i(n,a))}function UZ(e){de(e,()=>e.bindFramebuffer(e.FRAMEBUFFER,null)),de(e,()=>e.viewport(0,0,e.canvas.width,e.canvas.height)),de(e,()=>e.scissor(0,0,e.canvas.width,e.canvas.height))}function $h(e,t,n){de(e,()=>e.bindFramebuffer(e.FRAMEBUFFER,n)),de(e,()=>e.framebufferTexture2D(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0,e.TEXTURE_2D,t,0))}function Zx(e,t){de(e,()=>e.bindFramebuffer(e.FRAMEBUFFER,t)),de(e,()=>e.framebufferTexture2D(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0,e.TEXTURE_2D,null,0))}function ec(e){let t=e.checkFramebufferStatus(e.FRAMEBUFFER);if(t!==e.FRAMEBUFFER_COMPLETE)throw new Error("Error binding framebuffer: "+pE(e,t))}function pE(e,t){switch(t){case e.FRAMEBUFFER_INCOMPLETE_ATTACHMENT:return"FRAMEBUFFER_INCOMPLETE_ATTACHMENT";case e.FRAMEBUFFER_INCOMPLETE_MISSING_ATTACHMENT:return"FRAMEBUFFER_INCOMPLETE_MISSING_ATTACHMENT";case e.FRAMEBUFFER_INCOMPLETE_DIMENSIONS:return"FRAMEBUFFER_INCOMPLETE_DIMENSIONS";case e.FRAMEBUFFER_UNSUPPORTED:return"FRAMEBUFFER_UNSUPPORTED";default:return`unknown error ${t}`}}function Pr(e,t,n){let a=de(e,()=>t());if(a==null)throw new Error(n);return a}function cE(e,t){let n=e.MAX_COMBINED_TEXTURE_IMAGE_UNITS-1,a=t+e.TEXTURE0;if(a<e.TEXTURE0||a>n){let r=`[gl.TEXTURE0, gl.TEXTURE${n}]`;throw new Error(`textureUnit must be in ${r}.`)}}function xi(e,t=2){return v.sizeFromShape(e.slice(0,e.length-t))}function vi(e){if(e.length===0)throw Error("Cannot get rows and columns of an empty shape array.");return[e.length>1?e[e.length-2]:1,e[e.length-1]]}function tc(e){let t=[1,1,1];return e.length===0||e.length===1&&e[0]===1||(t=[xi(e),...vi(e)]),t}function dE(e,t=!1){let n=G().getNumber("WEBGL_MAX_TEXTURE_SIZE"),a=G().getNumber("WEBGL_MAX_SIZE_FOR_NARROW_TEXTURE");a===1/0&&G().getBool("WEBGL_AUTO_SQUARIFY_NARROW_TEXTURE_SHAPE")&&(a=n/2),t&&(n=n*2,a=a*2,e=e.map((o,l)=>l>=e.length-2?v.nearestLargerEven(e[l]):e[l]),e.length===1&&(e=[2,e[0]])),e.length!==2&&(e=v.squeezeShape(e).newShape);let r=v.sizeFromShape(e),s=null;e.length<=1&&r<=n?s=[1,r]:e.length===2&&e[0]<=n&&e[1]<=n?s=e:e.length===3&&e[0]*e[1]<=n&&e[2]<=n?s=[e[0]*e[1],e[2]]:e.length===3&&e[0]<=n&&e[1]*e[2]<=n?s=[e[0],e[1]*e[2]]:e.length===4&&e[0]*e[1]*e[2]<=n&&e[3]<=n?s=[e[0]*e[1]*e[2],e[3]]:e.length===4&&e[0]<=n&&e[1]*e[2]*e[3]<=n&&(s=[e[0],e[1]*e[2]*e[3]]);let i=s!=null&&Math.max(...s)>a&&Math.min(...s)<=(t?2:1)&&Math.min(...s)>0;if(s==null||i)if(t){let o=xi(e),l=2,u=2;e.length&&([l,u]=vi(e)),r=o*(l/2)*(u/2),s=v.sizeToSquarishShape(r).map(p=>p*2)}else s=v.sizeToSquarishShape(r);return s}function Th(e){return e%2===0}function wc(e,t){if(e=e.slice(-2),t=t.slice(-2),v.arraysEqual(e,t)||!e.length||!t.length||e[0]===0||e[1]===0||t[0]===0||t[1]===0)return!0;if(e.length!==t.length){let n=e[e.length-1],a=t[t.length-1];if(n===a||Th(n)&&Th(a)&&(e[0]===1||t[0]===1))return!0}return e[1]===t[1]&&Th(e[0])&&Th(t[0])}var Dh,Rh;function hE(e){if(Dh==null){let t=Ka(e);Dh=t.getParameter(t.MAX_TEXTURE_SIZE)}return Dh}function GZ(){Dh=null}function HZ(){Rh=null}function mE(e){if(Rh==null){let t=Ka(e);Rh=t.getParameter(t.MAX_TEXTURE_IMAGE_UNITS)}return Math.min(16,Rh)}function fE(e){if(e===0)return 0;let t,n=Ka(e);return ha(n,"EXT_disjoint_timer_query_webgl2")&&e===2?t=2:ha(n,"EXT_disjoint_timer_query")?t=1:t=0,t}function ha(e,t){return e.getExtension(t)!=null}function Jx(e){try{if(Ka(e)!=null)return!0}catch(t){return console.log("Error when getting WebGL context: ",t),!1}return!1}function gE(e){if(e===0)return!1;let t=Ka(e);if(e===1){if(!ha(t,"OES_texture_float"))return!1}else if(!ha(t,"EXT_color_buffer_float"))return!1;return Qx(t)}function bE(e){if(e===0)return!1;let t=Ka(e);if(e===1){if(!ha(t,"OES_texture_float")||!ha(t,"WEBGL_color_buffer_float"))return!1}else{if(ha(t,"EXT_color_buffer_float"))return Qx(t);let n="EXT_color_buffer_half_float";if(ha(t,n)){let a=t.getExtension(n);return qZ(t,a)}return!1}return Qx(t)}function Qx(e){let t=P1(e),n=e.createTexture();e.bindTexture(e.TEXTURE_2D,n);let a=1,r=1;e.texImage2D(e.TEXTURE_2D,0,t.internalFormatFloat,a,r,0,t.textureFormatFloat,t.textureTypeFloat,null);let s=e.createFramebuffer();e.bindFramebuffer(e.FRAMEBUFFER,s),e.framebufferTexture2D(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0,e.TEXTURE_2D,n,0);let i=e.checkFramebufferStatus(e.FRAMEBUFFER)===e.FRAMEBUFFER_COMPLETE;return e.bindTexture(e.TEXTURE_2D,null),e.bindFramebuffer(e.FRAMEBUFFER,null),e.deleteTexture(n),e.deleteFramebuffer(s),i}function qZ(e,t){let n=P1(e,t),a=e.createTexture();e.bindTexture(e.TEXTURE_2D,a);let r=1,s=1;e.texImage2D(e.TEXTURE_2D,0,n.internalFormatHalfFloat,r,s,0,n.textureFormatFloat,n.textureTypeHalfFloat,null);let i=e.createFramebuffer();e.bindFramebuffer(e.FRAMEBUFFER,i),e.framebufferTexture2D(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0,e.TEXTURE_2D,a,0);let o=e.checkFramebufferStatus(e.FRAMEBUFFER)===e.FRAMEBUFFER_COMPLETE;return e.bindTexture(e.TEXTURE_2D,null),e.bindFramebuffer(e.FRAMEBUFFER,null),e.deleteTexture(a),e.deleteFramebuffer(i),o}function yE(e){return e!==2?!1:Ka(e).fenceSync!=null}function ip(e,t){Array.isArray(e)||(e=[e]),e.forEach(n=>{n!=null&&v.assert(n.dtype!=="complex64",()=>`${t} does not support complex64 tensors in the WebGL backend.`)})}var xe=G();xe.registerFlag("HAS_WEBGL",()=>xe.getNumber("WEBGL_VERSION")>0);xe.registerFlag("WEBGL_VERSION",()=>Jx(2)?2:Jx(1)?1:0);xe.registerFlag("WEBGL_CHECK_NUMERICAL_PROBLEMS",()=>!1);xe.registerFlag("WEBGL_BUFFER_SUPPORTED",()=>xe.get("WEBGL_VERSION")===2);xe.registerFlag("WEBGL_CPU_FORWARD",()=>!0);xe.registerFlag("WEBGL_FORCE_F16_TEXTURES",()=>!1);xe.registerFlag("WEBGL_PACK",()=>xe.getBool("HAS_WEBGL"));xe.registerFlag("WEBGL_PACK_NORMALIZATION",()=>xe.getBool("WEBGL_PACK"));xe.registerFlag("WEBGL_PACK_CLIP",()=>xe.getBool("WEBGL_PACK"));xe.registerFlag("WEBGL_PACK_DEPTHWISECONV",()=>xe.getBool("WEBGL_PACK"));xe.registerFlag("WEBGL_PACK_BINARY_OPERATIONS",()=>xe.getBool("WEBGL_PACK"));xe.registerFlag("WEBGL_PACK_UNARY_OPERATIONS",()=>xe.getBool("WEBGL_PACK"));xe.registerFlag("WEBGL_PACK_ARRAY_OPERATIONS",()=>xe.getBool("WEBGL_PACK"));xe.registerFlag("WEBGL_PACK_IMAGE_OPERATIONS",()=>xe.getBool("WEBGL_PACK"));xe.registerFlag("WEBGL_PACK_REDUCE",()=>xe.getBool("WEBGL_PACK"));xe.registerFlag("WEBGL_LAZILY_UNPACK",()=>xe.getBool("WEBGL_PACK"));xe.registerFlag("WEBGL_CONV_IM2COL",()=>xe.getBool("WEBGL_PACK"));xe.registerFlag("WEBGL_MAX_TEXTURE_SIZE",()=>hE(xe.getNumber("WEBGL_VERSION")));xe.registerFlag("WEBGL_MAX_TEXTURES_IN_SHADER",()=>mE(xe.getNumber("WEBGL_VERSION")));xe.registerFlag("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION",()=>{let 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Error(`WEBGL_FLUSH_THRESHOLD must be -1 (indicating never manual flush) or at least 0, but got ${e}.`)});xe.registerFlag("CPU_HANDOFF_SIZE_THRESHOLD",()=>128);xe.registerFlag("WEBGL_USE_SHAPES_UNIFORMS",()=>!1);xe.registerFlag("TOPK_LAST_DIM_CPU_HANDOFF_SIZE_THRESHOLD",()=>1e5);xe.registerFlag("TOPK_K_CPU_HANDOFF_THRESHOLD",()=>128);xe.registerFlag("WEBGL_EXP_CONV",()=>!1);xe.registerFlag("SOFTWARE_WEBGL_ENABLED",()=>xe.getBool("IS_TEST"));xe.registerFlag("WEBGL_MAX_SIZE_FOR_NARROW_TEXTURE",()=>1/0);xe.registerFlag("WEBGL_AUTO_SQUARIFY_NARROW_TEXTURE_SHAPE",()=>!1);xe.registerFlag("WEBGL2_ISNAN_CUSTOM",()=>!1);xe.registerFlag("ENGINE_COMPILE_ONLY",()=>!1);function _n(){let e,t,n,a,r,s,i,o,l,u;return G().getNumber("WEBGL_VERSION")===2?(e="#version 300 es",t="in",n="out",a="in",r="texture",s="outputColor",i="out vec4 outputColor;",o=G().getBool("WEBGL2_ISNAN_CUSTOM")?`
bool isnan_custom(float val) {
uint floatToUint = floatBitsToUint(val);
return (floatToUint & 0x7fffffffu) > 0x7f800000u;
}
bvec4 isnan_custom(vec4 val) {
return bvec4(isnan_custom(val.x),
isnan_custom(val.y), isnan_custom(val.z), isnan_custom(val.w));
}
#define isnan(value) isnan_custom(value)
`:"",l="",u=`
#define round(value) newRound(value)
int newRound(float value) {
return int(floor(value + 0.5));
}
ivec4 newRound(vec4 value) {
return ivec4(floor(value + vec4(0.5)));
}
`):(e="",t="attribute",n="varying",a="varying",r="texture2D",s="gl_FragColor",i="",o=`
#define isnan(value) isnan_custom(value)
bool isnan_custom(float val) {
return (val > 0. || val < 1. || val == 0.) ? false : true;
}
bvec4 isnan_custom(vec4 val) {
return bvec4(isnan(val.x), isnan(val.y), isnan(val.z), isnan(val.w));
}
`,l=`
uniform float INFINITY;
bool isinf(float val) {
return abs(val) == INFINITY;
}
bvec4 isinf(vec4 val) {
return equal(abs(val), vec4(INFINITY));
}
`,u=`
int round(float value) {
return int(floor(value + 0.5));
}
ivec4 round(vec4 value) {
return ivec4(floor(value + vec4(0.5)));
}
`),{version:e,attribute:t,varyingVs:n,varyingFs:a,texture2D:r,output:s,defineOutput:i,defineSpecialNaN:o,defineSpecialInf:l,defineRound:u}}function qo(e,t,n="index"){let a=v.computeStrides(t);return a.map((r,s)=>{let i=`int ${e[s]} = ${n} / ${r}`,o=s===a.length-1?`int ${e[s+1]} = ${n} - ${e[s]} * ${r}`:`index -= ${e[s]} * ${r}`;return`${i}; ${o};`}).join("")}function Pf(e,t,n="index"){let a=v.computeStrides(t);return a.map((r,s)=>{let i=`int ${e[s]} = ${n} / outShapeStrides[${s}]`,o=s===a.length-1?`int ${e[s+1]} = ${n} - ${e[s]} * outShapeStrides[${s}]`:`index -= ${e[s]} * outShapeStrides[${s}]`;return`${i}; ${o};`}).join("")}function jZ(e,t){let n=e.length,a=e.map(s=>`${t}[${s}]`),r=new Array(n-1);r[n-2]=a[n-1];for(let s=n-3;s>=0;--s)r[s]=`(${r[s+1]} * ${a[s+1]})`;return r}function KZ(e,t,n="index"){let a=e.map((s,i)=>i),r=jZ(a,t);return r.map((s,i)=>{let o=`int ${e[i]} = ${n} / ${r[i]}`,l=i===r.length-1?`int ${e[i+1]} = ${n} - ${e[i]} * ${r[i]}`:`index -= ${e[i]} * ${r[i]}`;return`${o}; ${l};`}).join("")}function L1(e){let t=v.computeStrides(e).map(n=>n.toString());return`
int getFlatIndex(ivec3 coords) {
return coords.x * ${t[0]} + coords.y * ${t[1]} + coords.z;
}
`}function z1(){return`
int getFlatIndex(ivec3 coords) {
return coords.x * outShapeStrides[0] + coords.y * outShapeStrides[1] + coords.z;
}
`}var xE=`
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:vE}=N;function XZ(e,t,n){let a=[];if(e.forEach(c=>{let h=v.sizeFromShape(c.shapeInfo.logicalShape);if(c.shapeInfo.isUniform?a.push(`uniform float ${c.name}${h>1?`[${h}]`:""};`):(a.push(`uniform sampler2D ${c.name};`),a.push(`uniform int offset${c.name};`)),n.enableShapeUniforms){let{uniformShape:m}=W1(n.packedInputs,c.shapeInfo.logicalShape,c.shapeInfo.texShape);switch(m.length){case 1:a.push(`uniform int ${c.name}Shape;`);break;case 2:a.push(`uniform ivec2 ${c.name}Shape;`);break;case 3:a.push(`uniform ivec3 ${c.name}Shape;`);break;case 4:a.push(`uniform ivec4 ${c.name}Shape;`);break;default:break}a.push(`uniform ivec2 ${c.name}TexShape;`)}}),n.enableShapeUniforms){switch(t.logicalShape.length){case 1:a.push("uniform int outShape;");break;case 2:a.push("uniform ivec2 outShape;"),a.push("uniform int outShapeStrides;");break;case 3:a.push("uniform ivec3 outShape;"),a.push("uniform ivec2 outShapeStrides;");break;case 4:a.push("uniform ivec4 outShape;"),a.push("uniform ivec3 outShapeStrides;");break;default:break}a.push("uniform ivec2 outTexShape;")}n.customUniforms&&n.customUniforms.forEach(c=>{a.push(`uniform ${c.type} ${c.name}${c.arrayIndex?`[${c.arrayIndex}]`:""};`)});let r=a.join(`
`),s=e.map(c=>YZ(c,t,n.packedInputs,n.enableShapeUniforms)).join(`
`),i=t.texShape,o=_n(),l=QZ(o),u,p,d=nJ(o);return t.isPacked?(u=ZZ(t.logicalShape,i,n.enableShapeUniforms),p=tJ(o)):(u=JZ(t.logicalShape,i,n.enableShapeUniforms),p=eJ(o)),n.packedInputs&&(d+=iJ),[d,l,p,r,u,s,n.userCode].join(`
`)}function op(e,t=!1){let n=e.shapeInfo.logicalShape;switch(n.length){case 0:return yJ(e,t);case 1:return vJ(e,t);case 2:return kJ(e,t);case 3:return SJ(e,t);case 4:return TJ(e,t);case 5:return CJ(e);case 6:return _J(e);default:throw new Error(`${n.length}-D input sampling is not yet supported`)}}function wE(e,t){switch(e.shapeInfo.logicalShape.length){case 0:return bJ(e);case 1:return xJ(e,t);case 2:return wJ(e,t);case 3:return IJ(e,t);default:return NJ(e,t)}}function YZ(e,t,n=!1,a){let r="";n?r+=wE(e,a):r+=op(e,a);let s=e.shapeInfo.logicalShape,i=t.logicalShape;return s.length<=i.length&&(n?r+=EJ(e,t):r+=AJ(e,t)),r}function ZZ(e,t,n){switch(e.length){case 0:return kE();case 1:return oJ(e,t,n);case 2:return fJ(e,t,n);case 3:return uJ(e,t,n);default:return cJ(e,t,n)}}function JZ(e,t,n){switch(e.length){case 0:return kE();case 1:return lJ(e,t,n);case 2:return gJ(e,t,n);case 3:return pJ(e,t,n);case 4:return dJ(e,t,n);case 5:return hJ(e,t);case 6:return mJ(e,t);default:throw new Error(`${e.length}-D output sampling is not yet supported`)}}function QZ(e){return`
float sampleTexture(sampler2D textureSampler, vec2 uv) {
return ${e.texture2D}(textureSampler, uv).r;
}
`}function eJ(e){return`
void setOutput(float val) {
${e.output} = vec4(val, 0, 0, 0);
}
`}function tJ(e){return`
void setOutput(vec4 val) {
${e.output} = val;
}
`}function nJ(e){return`${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);
}
${aJ}
${rJ}
${sJ}
`}var aJ=`
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);
}
`,rJ=`
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);
}
`,sJ=`
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);
}
`,iJ=`
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 kE(){return`
int getOutputCoords() {
return 0;
}
`}function oJ(e,t,n){let a=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)];return a[0]===1?n?`
int getOutputCoords() {
return 2 * int(resultUV.x * ceil(float(outTexShape[1]) / 2.0));
}
`:`
int getOutputCoords() {
return 2 * int(resultUV.x * ${a[1]}.0);
}
`:a[1]===1?n?`
int getOutputCoords() {
return 2 * int(resultUV.y * ceil(float(outTexShape[0]) / 2.0));
}
`:`
int getOutputCoords() {
return 2 * int(resultUV.y * ${a[0]}.0);
}
`:n?`
int getOutputCoords() {
ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(packedTexShape[0], packedTexShape[1]));
return 2 * (resTexRC.x * packedTexShape[1] + resTexRC.y);
}
`:`
int getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${a[0]}, ${a[1]}));
return 2 * (resTexRC.x * ${a[1]} + resTexRC.y);
}
`}function lJ(e,t,n){return t[0]===1?n?`
int getOutputCoords() {
return int(resultUV.x * float(outTexShape[1]));
}
`:`
int getOutputCoords() {
return int(resultUV.x * ${t[1]}.0);
}
`:t[1]===1?n?`
int getOutputCoords() {
return int(resultUV.y * float(outTexShape[0]));
}
`:`
int getOutputCoords() {
return int(resultUV.y * ${t[0]}.0);
}
`:n?`
int getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(outTexShape[0], outTexShape[1]));
return resTexRC.x * outTexShape[1] + resTexRC.y;
}
`:`
int getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${t[0]}, ${t[1]}));
return resTexRC.x * ${t[1]} + resTexRC.y;
}
`}function uJ(e,t,n){if(n)return`
ivec3 getOutputCoords() {
ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));
int texelsInLogicalRow = int(ceil(float(outShape[2]) / 2.0));
int texelsInBatch = texelsInLogicalRow * int(ceil(float(outShape[1]) / 2.0));
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(packedTexShape[0], packedTexShape[1]));
int index = resTexRC.x * packedTexShape[1] + resTexRC.y;
int b = index / texelsInBatch;
index -= b * texelsInBatch;
int r = 2 * (index / texelsInLogicalRow);
int c = imod(index, texelsInLogicalRow) * 2;
return ivec3(b, r, c);
}
`;let a=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)],r=Math.ceil(e[2]/2),s=r*Math.ceil(e[1]/2);return`
ivec3 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${a[0]}, ${a[1]}));
int index = resTexRC.x * ${a[1]} + resTexRC.y;
int b = index / ${s};
index -= b * ${s};
int r = 2 * (index / ${r});
int c = imod(index, ${r}) * 2;
return ivec3(b, r, c);
}
`}function pJ(e,t,n){if(n)return`
ivec3 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(outTexShape[0], outTexShape[1]));
int index = resTexRC.x * outTexShape[1] + resTexRC.y;
${Pf(["r","c","d"],e)}
return ivec3(r, c, d);
}
`;let a=qo(["r","c","d"],e);return`
ivec3 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${t[0]}, ${t[1]}));
int index = resTexRC.x * ${t[1]} + resTexRC.y;
${a}
return ivec3(r, c, d);
}
`}function cJ(e,t,n){if(n)return`
ivec4 getOutputCoords() {
ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(packedTexShape[0], packedTexShape[1]));
int index = resTexRC.x * packedTexShape[1] + resTexRC.y;
int texelsInLogicalRow = int(ceil(float(outShape[3]) / 2.0));
int texelsInBatch = texelsInLogicalRow * int(ceil(float(outShape[2]) / 2.0));
int texelsInBatchN = texelsInBatch * outShape[1];
int b2 = index / texelsInBatchN;
index -= b2 * texelsInBatchN;
int b = index / texelsInBatch;
index -= b * texelsInBatch;
int r = 2 * (index / texelsInLogicalRow);
int c = imod(index, texelsInLogicalRow) * 2;
return ivec4(b2, b, r, c);
}
`;let a=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)],r=Math.ceil(e[e.length-1]/2),s=r*Math.ceil(e[e.length-2]/2),i=s,o="",l="b, r, c";for(let u=2;u<e.length-1;u++)i*=e[e.length-u-1],o=`
int b${u} = index / ${i};
index -= b${u} * ${i};
`+o,l=`b${u}, `+l;return`
ivec${e.length} getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${a[0]}, ${a[1]}));
int index = resTexRC.x * ${a[1]} + resTexRC.y;
${o}
int b = index / ${s};
index -= b * ${s};
int r = 2 * (index / ${r});
int c = imod(index, ${r}) * 2;
return ivec${e.length}(${l});
}
`}function dJ(e,t,n){if(n)return`
ivec4 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(outTexShape[0], outTexShape[1]));
int index = resTexRC.x * outTexShape[1] + resTexRC.y;
${Pf(["r","c","d","d2"],e)}
return ivec4(r, c, d, d2);
}
`;let a=qo(["r","c","d","d2"],e);return`
ivec4 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${t[0]}, ${t[1]}));
int index = resTexRC.x * ${t[1]} + resTexRC.y;
${a}
return ivec4(r, c, d, d2);
}
`}function hJ(e,t){let n=qo(["r","c","d","d2","d3"],e);return`
ivec5 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx * vec2(${t[0]},
${t[1]}));
int index = resTexRC.x * ${t[1]} + resTexRC.y;
${n}
ivec5 outShape = ivec5(r, c, d, d2, d3);
return outShape;
}
`}function mJ(e,t){let n=qo(["r","c","d","d2","d3","d4"],e);return`
ivec6 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${t[0]}, ${t[1]}));
int index = resTexRC.x * ${t[1]} + resTexRC.y;
${n}
ivec6 result = ivec6(r, c, d, d2, d3, d4);
return result;
}
`}function fJ(e,t,n){let a=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)];if(v.arraysEqual(e,t))return n?`
ivec2 getOutputCoords() {
ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));
return 2 * ivec2(resultUV.yx * vec2(packedTexShape[0], packedTexShape[1]));
}
`:`
ivec2 getOutputCoords() {
return 2 * ivec2(resultUV.yx * vec2(${a[0]}, ${a[1]}));
}
`;let r=Math.ceil(e[1]/2);return n?`
ivec2 getOutputCoords() {
ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));
int texelsInLogicalRow = int(ceil(float(outShape[1]) / 2.0));
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(packedTexShape[0], packedTexShape[1]));
int index = resTexRC.x * packedTexShape[1] + resTexRC.y;
int r = 2 * (index / texelsInLogicalRow);
int c = imod(index, texelsInLogicalRow) * 2;
return ivec2(r, c);
}
`:`
ivec2 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${a[0]}, ${a[1]}));
int index = resTexRC.x * ${a[1]} + resTexRC.y;
int r = 2 * (index / ${r});
int c = imod(index, ${r}) * 2;
return ivec2(r, c);
}
`}function gJ(e,t,n){return v.arraysEqual(e,t)?n?`
ivec2 getOutputCoords() {
return ivec2(resultUV.yx * vec2(outTexShape[0], outTexShape[1]));
}
`:`
ivec2 getOutputCoords() {
return ivec2(resultUV.yx * vec2(${t[0]}, ${t[1]}));
}
`:e[1]===1?n?`
ivec2 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(outTexShape[0], outTexShape[1]));
int index = resTexRC.x * outTexShape[1] + resTexRC.y;
return ivec2(index, 0);
}
`:`
ivec2 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${t[0]}, ${t[1]}));
int index = resTexRC.x * ${t[1]} + resTexRC.y;
return ivec2(index, 0);
}
`:e[0]===1?n?`
ivec2 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(outTexShape[0], outTexShape[1]));
int index = resTexRC.x * outTexShape[1] + resTexRC.y;
return ivec2(0, index);
}
`:`
ivec2 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${t[0]}, ${t[1]}));
int index = resTexRC.x * ${t[1]} + resTexRC.y;
return ivec2(0, index);
}
`:n?`
ivec2 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(outTexShape[0], outTexShape[1]));
int index = resTexRC.x * outTexShape[1] + resTexRC.y;
int r = index / outShape[1];
int c = index - r * outShape[1];
return ivec2(r, c);
}
`:`
ivec2 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${t[0]}, ${t[1]}));
int index = resTexRC.x * ${t[1]} + resTexRC.y;
int r = index / ${e[1]};
int c = index - r * ${e[1]};
return ivec2(r, c);
}
`}function jo(e){return`offset${e}`}function bJ(e){let t=e.name,n="get"+t.charAt(0).toUpperCase()+t.slice(1),a=_n();return`
vec4 ${n}() {
return ${a.texture2D}(${t}, halfCR);
}
`}function yJ(e,t){let n=e.name,a="get"+n.charAt(0).toUpperCase()+n.slice(1);if(e.shapeInfo.isUniform)return`float ${a}() {return ${n};}`;let[r,s]=e.shapeInfo.texShape;if(r===1&&s===1)return`
float ${a}() {
return sampleTexture(${n}, halfCR);
}
`;let i=jo(n);if(t)return`
float ${a}() {
vec2 uv = uvFromFlat(${n}TexShape[0], ${n}TexShape[1], ${i});
return sampleTexture(${n}, uv);
}
`;let[o,l]=e.shapeInfo.texShape;return`
float ${a}() {
vec2 uv = uvFromFlat(${o}, ${l}, ${i});
return sampleTexture(${n}, uv);
}
`}function xJ(e,t){let n=e.name,a="get"+n.charAt(0).toUpperCase()+n.slice(1),r=e.shapeInfo.texShape,s=_n();if(t)return`
vec4 ${a}(int index) {
ivec2 packedTexShape = ivec2(ceil(float(${n}TexShape[0]) / 2.0), ceil(float(${n}TexShape[1]) / 2.0));
vec2 uv = packedUVfrom1D(
packedTexShape[0], packedTexShape[1], index);
return ${s.texture2D}(${n}, uv);
}
`;let i=[Math.ceil(r[0]/2),Math.ceil(r[1]/2)];return`
vec4 ${a}(int index) {
vec2 uv = packedUVfrom1D(
${i[0]}, ${i[1]}, index);
return ${s.texture2D}(${n}, uv);
}
`}function vJ(e,t){let n=e.name,a="get"+n.charAt(0).toUpperCase()+n.slice(1);if(e.shapeInfo.isUniform)return`
float ${a}(int index) {
${lp(e)}
}
`;let r=e.shapeInfo.texShape,s=r[0],i=r[1];if(i===1&&s===1)return`
float ${a}(int index) {
return sampleTexture(${n}, halfCR);
}
`;let o=jo(n);return i===1?t?`
float ${a}(int index) {
vec2 uv = vec2(0.5, (float(index + ${o}) + 0.5) / float(${n}TexShape[0]));
return sampleTexture(${n}, uv);
}
`:`
float ${a}(int index) {
vec2 uv = vec2(0.5, (float(index + ${o}) + 0.5) / ${s}.0);
return sampleTexture(${n}, uv);
}
`:s===1?t?`
float ${a}(int index) {
vec2 uv = vec2((float(index + ${o}) + 0.5) / float(${n}TexShape[1]), 0.5);
return sampleTexture(${n}, uv);
}
`:`
float ${a}(int index) {
vec2 uv = vec2((float(index + ${o}) + 0.5) / ${i}.0, 0.5);
return sampleTexture(${n}, uv);
}
`:t?`
float ${a}(int index) {
vec2 uv = uvFromFlat(${n}TexShape[0], ${n}TexShape[1], index + ${o});
return sampleTexture(${n}, uv);
}
`:`
float ${a}(int index) {
vec2 uv = uvFromFlat(${s}, ${i}, index + ${o});
return sampleTexture(${n}, uv);
}
`}function wJ(e,t){let n=e.shapeInfo.logicalShape,a=e.name,r="get"+a.charAt(0).toUpperCase()+a.slice(1),s=e.shapeInfo.texShape,i=s[0],o=s[1],l=_n();if(s!=null&&v.arraysEqual(n,s))return t?`
vec4 ${r}(int row, int col) {
vec2 uv = (vec2(col, row) + halfCR) / vec2(${a}TexShape[1], ${a}TexShape[0]);
return ${l.texture2D}(${a}, uv);
}
`:`
vec4 ${r}(int row, int col) {
vec2 uv = (vec2(col, row) + halfCR) / vec2(${o}.0, ${i}.0);
return ${l.texture2D}(${a}, uv);
}
`;if(t)return`
vec4 ${r}(int row, int col) {
ivec2 packedTexShape = ivec2(ceil(float(${a}TexShape[0]) / 2.0), ceil(float(${a}TexShape[1]) / 2.0));
int valuesPerRow = int(ceil(float(${a}Shape[1]) / 2.0));
vec2 uv = packedUVfrom2D(valuesPerRow, packedTexShape[0], packedTexShape[1], row, col);
return ${l.texture2D}(${a}, uv);
}
`;let u=[Math.ceil(s[0]/2),Math.ceil(s[1]/2)],p=Math.ceil(n[1]/2);return`
vec4 ${r}(int row, int col) {
vec2 uv = packedUVfrom2D(${p}, ${u[0]}, ${u[1]}, row, col);
return ${l.texture2D}(${a}, uv);
}
`}function kJ(e,t){let n=e.shapeInfo.logicalShape,a=e.name,r="get"+a.charAt(0).toUpperCase()+a.slice(1),s=e.shapeInfo.texShape;if(s!=null&&v.arraysEqual(n,s)){if(t)return`
float ${r}(int row, int col) {
vec2 uv = (vec2(col, row) + halfCR) / vec2(${a}TexShape[1], ${a}TexShape[0]);
return sampleTexture(${a}, uv);
}
`;let c=s[0],h=s[1];return`
float ${r}(int row, int col) {
vec2 uv = (vec2(col, row) + halfCR) / vec2(${h}.0, ${c}.0);
return sampleTexture(${a}, uv);
}
`}let{newShape:i,keptDims:o}=v.squeezeShape(n),l=i;if(l.length<n.length){let c=up(e,l),h=["row","col"];return`
${op(c,t)}
float ${r}(int row, int col) {
return ${r}(${pp(h,o)});
}
`}if(e.shapeInfo.isUniform)return`
float ${r}(int row, int col) {
int index = round(dot(vec2(row, col), vec2(${n[1]}, 1)));
${lp(e)}
}
`;let u=s[0],p=s[1],d=jo(a);return p===1?t?`
float ${r}(int row, int col) {
float index = dot(vec3(row, col, ${d}), vec3(${a}Shape[1], 1, 1));
vec2 uv = vec2(0.5, (index + 0.5) / float(${a}TexShape[0]));
return sampleTexture(${a}, uv);
}
`:`
float ${r}(int row, int col) {
float index = dot(vec3(row, col, ${d}), vec3(${n[1]}, 1, 1));
vec2 uv = vec2(0.5, (index + 0.5) / ${u}.0);
return sampleTexture(${a}, uv);
}
`:u===1?t?`
float ${r}(int row, int col) {
float index = dot(vec3(row, col, ${d}), vec3(${a}Shape[1], 1, 1));
vec2 uv = vec2((index + 0.5) / float(${a}TexShape[1]), 0.5);
return sampleTexture(${a}, uv);
}
`:`
float ${r}(int row, int col) {
float index = dot(vec3(row, col, ${d}), vec3(${n[1]}, 1, 1));
vec2 uv = vec2((index + 0.5) / ${p}.0, 0.5);
return sampleTexture(${a}, uv);
}
`:t?`
float ${r}(int row, int col) {
// Explicitly use integer operations as dot() only works on floats.
int index = row * ${a}Shape[1] + col + ${d};
vec2 uv = uvFromFlat(${a}TexShape[0], ${a}TexShape[1], index);
return sampleTexture(${a}, uv);
}
`:`
float ${r}(int row, int col) {
// Explicitly use integer operations as dot() only works on floats.
int index = row * ${n[1]} + col + ${d};
vec2 uv = uvFromFlat(${u}, ${p}, index);
return sampleTexture(${a}, uv);
}
`}function IJ(e,t){let n=e.shapeInfo.logicalShape,a=e.name,r="get"+a.charAt(0).toUpperCase()+a.slice(1),s=e.shapeInfo.texShape,i=[Math.ceil(s[0]/2),Math.ceil(s[1]/2)];if(n[0]===1){let c=n.slice(1),h=[1,2],m=up(e,c),f=["b","row","col"];return`
${wE(m,t)}
vec4 ${r}(int b, int row, int col) {
return ${r}(${pp(f,h)});
}
`}let o=_n();if(t)return`
vec4 ${r}(int b, int row, int col) {
ivec2 packedTexShape = ivec2(ceil(float(${a}TexShape[0]) / 2.0), ceil(float(${a}TexShape[1]) / 2.0));
int valuesPerRow = int(ceil(float(${a}Shape[2]) / 2.0));
int texelsInBatch = valuesPerRow * int(ceil(float(${a}Shape[1]) / 2.0));
vec2 uv = packedUVfrom3D(
packedTexShape[0], packedTexShape[1], texelsInBatch, valuesPerRow, b, row, col);
return ${o.texture2D}(${a}, uv);
}
`;let l=i[0],u=i[1],p=Math.ceil(n[2]/2),d=p*Math.ceil(n[1]/2);return`
vec4 ${r}(int b, int row, int col) {
vec2 uv = packedUVfrom3D(
${l}, ${u}, ${d}, ${p}, b, row, col);
return ${o.texture2D}(${a}, uv);
}
`}function SJ(e,t){let n=e.shapeInfo.logicalShape,a=e.name,r="get"+a.charAt(0).toUpperCase()+a.slice(1),s=n[1]*n[2],i=n[2],{newShape:o,keptDims:l}=v.squeezeShape(n),u=o;if(u.length<n.length){let f=up(e,u),g=["row","col","depth"];return`
${op(f,t)}
float ${r}(int row, int col, int depth) {
return ${r}(${pp(g,l)});
}
`}if(e.shapeInfo.isUniform)return`
float ${r}(int row, int col, int depth) {
int index = round(dot(vec3(row, col, depth),
vec3(${s}, ${i}, 1)));
${lp(e)}
}
`;let p=e.shapeInfo.texShape,d=p[0],c=p[1],h=e.shapeInfo.flatOffset;if(c===s&&h==null)return t?`
float ${r}(int row, int col, int depth) {
int stride1 = ${a}Shape[2];
float texR = float(row);
float texC = dot(vec2(col, depth), vec2(stride1, 1));
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${a}TexShape[1], ${a}TexShape[0]);
return sampleTexture(${a}, uv);
}
`:`
float ${r}(int row, int col, int depth) {
float texR = float(row);
float texC = dot(vec2(col, depth), vec2(${i}, 1));
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${c}.0, ${d}.0);
return sampleTexture(${a}, uv);
}
`;if(c===i&&h==null)return t?`
float ${r}(int row, int col, int depth) {
float texR = dot(vec2(row, col), vec2(${a}Shape[1], 1));
float texC = float(depth);
vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${a}TexShape[1], ${a}TexShape[0]);
return sampleTexture(${a}, uv);
}
`:`
float ${r}(int row, int col, int depth) {
float texR = dot(vec2(row, col), vec2(${n[1]}, 1));
float texC = float(depth);
vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${c}.0, ${d}.0);
return sampleTexture(${a}, uv);
}
`;let m=jo(a);return t?`
float ${r}(int row, int col, int depth) {
// Explicitly use integer operations as dot() only works on floats.
int stride0 = ${a}Shape[1] * ${a}Shape[2];
int stride1 = ${a}Shape[2];
int index = row * stride0 + col * stride1 + depth + ${m};
vec2 uv = uvFromFlat(${a}TexShape[0], ${a}TexShape[1], index);
return sampleTexture(${a}, uv);
}
`:`
float ${r}(int row, int col, int depth) {
// Explicitly use integer operations as dot() only works on floats.
int index = row * ${s} + col * ${i} + depth + ${m};
vec2 uv = uvFromFlat(${d}, ${c}, index);
return sampleTexture(${a}, uv);
}
`}function NJ(e,t){let n=e.name,a="get"+n.charAt(0).toUpperCase()+n.slice(1),r=_n();if(t)return`
vec4 ${a}(int b2, int b, int row, int col) {
int valuesPerRow = int(ceil(float(${n}Shape[3]) / 2.0));
int texelsInBatch = valuesPerRow * int(ceil(float(${n}Shape[2]) / 2.0));
int index = b * texelsInBatch + (row / 2) * valuesPerRow + (col / 2);
texelsInBatch *= ${n}Shape[1];
index = b2 * texelsInBatch + index;
ivec2 packedTexShape = ivec2(ceil(float(${n}TexShape[0]) / 2.0), ceil(float(${n}TexShape[1]) / 2.0));
int texR = index / packedTexShape[1];
int texC = index - texR * packedTexShape[1];
vec2 uv = (vec2(texC, texR) + halfCR) / vec2(packedTexShape[1], packedTexShape[0]); return ${r.texture2D}(${n}, uv);
}
`;let s=e.shapeInfo.logicalShape,i=s.length,o=e.shapeInfo.texShape,l=[Math.ceil(o[0]/2),Math.ceil(o[1]/2)],u=l[0],p=l[1],d=Math.ceil(s[i-1]/2),c=d*Math.ceil(s[i-2]/2),h="int b, int row, int col",m=`b * ${c} + (row / 2) * ${d} + (col / 2)`;for(let f=2;f<i-1;f++)h=`int b${f}, `+h,c*=s[i-f-1],m=`b${f} * ${c} + `+m;return`
vec4 ${a}(${h}) {
int index = ${m};
int texR = index / ${p};
int texC = index - texR * ${p};
vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${p}, ${u});
return ${r.texture2D}(${n}, uv);
}
`}function TJ(e,t){let n=e.shapeInfo.logicalShape,a=e.name,r="get"+a.charAt(0).toUpperCase()+a.slice(1),s=n[3],i=n[2]*s,o=n[1]*i,{newShape:l,keptDims:u}=v.squeezeShape(n);if(l.length<n.length){let y=up(e,l),x=["row","col","depth","depth2"];return`
${op(y,t)}
float ${r}(int row, int col, int depth, int depth2) {
return ${r}(${pp(x,u)});
}
`}if(e.shapeInfo.isUniform)return`
float ${r}(int row, int col, int depth, int depth2) {
int index = round(dot(vec4(row, col, depth, depth2),
vec4(${o}, ${i}, ${s}, 1)));
${lp(e)}
}
`;let p=e.shapeInfo.flatOffset,d=e.shapeInfo.texShape,c=d[0],h=d[1],m=`int stride2 = ${a}Shape[3];`,f=`int stride1 = ${a}Shape[2] * stride2;`,g=`int stride0 = ${a}Shape[1] * stride1;`;if(h===o&&p==null)return t?`
float ${r}(int row, int col, int depth, int depth2) {
${m}
${f}
float texR = float(row);
float texC =
dot(vec3(col, depth, depth2),
vec3(stride1, stride2, 1));
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${a}TexShape[1], ${a}TexShape[0]);
return sampleTexture(${a}, uv);
}
`:`
float ${r}(int row, int col, int depth, int depth2) {
float texR = float(row);
float texC =
dot(vec3(col, depth, depth2),
vec3(${i}, ${s}, 1));
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${h}.0, ${c}.0);
return sampleTexture(${a}, uv);
}
`;if(h===s&&p==null)return t?`
float ${r}(int row, int col, int depth, int depth2) {
float texR = dot(vec3(row, col, depth),
vec3(${a}Shape[1] * ${a}Shape[2], ${a}Shape[2], 1));
float texC = float(depth2);
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${a}TexShape[1], ${a}TexShape[0]);
return sampleTexture(${a}, uv);
}
`:`
float ${r}(int row, int col, int depth, int depth2) {
float texR = dot(vec3(row, col, depth),
vec3(${n[1]*n[2]}, ${n[2]}, 1));
float texC = float(depth2);
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${h}.0, ${c}.0);
return sampleTexture(${a}, uv);
}
`;let b=jo(a);return t?`
float ${r}(int row, int col, int depth, int depth2) {
// Explicitly use integer operations as dot() only works on floats.
${m}
${f}
${g}
int index = row * stride0 + col * stride1 +
depth * stride2 + depth2;
vec2 uv = uvFromFlat(${a}TexShape[0], ${a}TexShape[1], index + ${b});
return sampleTexture(${a}, uv);
}
`:`
float ${r}(int row, int col, int depth, int depth2) {
// Explicitly use integer operations as dot() only works on floats.
int index = row * ${o} + col * ${i} +
depth * ${s} + depth2;
vec2 uv = uvFromFlat(${c}, ${h}, index + ${b});
return sampleTexture(${a}, uv);
}
`}function CJ(e){let t=e.shapeInfo.logicalShape,n=e.name,a="get"+n.charAt(0).toUpperCase()+n.slice(1),r=t[4],s=t[3]*r,i=t[2]*s,o=t[1]*i,{newShape:l,keptDims:u}=v.squeezeShape(t);if(l.length<t.length){let f=up(e,l),g=["row","col","depth","depth2","depth3"];return`
${op(f)}
float ${a}(int row, int col, int depth, int depth2, int depth3) {
return ${a}(${pp(g,u)});
}
`}if(e.shapeInfo.isUniform)return`
float ${a}(int row, int col, int depth, int depth2, int depth3) {
float index = dot(
vec4(row, col, depth, depth2),
vec4(${o}, ${i}, ${s}, ${r})) +
depth3;
${lp(e)}
}
`;let p=e.shapeInfo.flatOffset,d=e.shapeInfo.texShape,c=d[0],h=d[1];if(h===o&&p==null)return`
float ${a}(int row, int col, int depth, int depth2, int depth3) {
int texR = row;
float texC = dot(vec4(col, depth, depth2, depth3),
vec4(${i}, ${s}, ${r}, 1));
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${h}.0, ${c}.0);
return sampleTexture(${n}, uv);
}
`;if(h===r&&p==null)return`
float ${a}(int row, int col, int depth, int depth2, int depth3) {
float texR = dot(
vec4(row, col, depth, depth2),
vec4(${t[1]*t[2]*t[3]},
${t[2]*t[3]}, ${t[3]}, 1));
int texC = depth3;
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${h}.0, ${c}.0);
return sampleTexture(${n}, uv);
}
`;let m=jo(n);return`
float ${a}(int row, int col, int depth, int depth2, int depth3) {
// Explicitly use integer operations as dot() only works on floats.
int index = row * ${o} + col * ${i} + depth * ${s} +
depth2 * ${r} + depth3 + ${m};
vec2 uv = uvFromFlat(${c}, ${h}, index);
return sampleTexture(${n}, uv);
}
`}function _J(e){let t=e.shapeInfo.logicalShape,n=e.name,a="get"+n.charAt(0).toUpperCase()+n.slice(1),{newShape:r,keptDims:s}=v.squeezeShape(t);if(r.length<t.length){let g=up(e,r),b=["row","col","depth","depth2","depth3","depth4"];return`
${op(g)}
float ${a}(int row, int col, int depth,
int depth2, int depth3, int depth4) {
return ${a}(${pp(b,s)});
}
`}let i=t[5],o=t[4]*i,l=t[3]*o,u=t[2]*l,p=t[1]*u;if(e.shapeInfo.isUniform)return`
float ${a}(int row, int col, int depth,
int depth2, int depth3, int depth4) {
int index = round(dot(
vec4(row, col, depth, depth2),
vec4(${p}, ${u}, ${l}, ${o})) +
dot(
vec2(depth3, depth4),
vec2(${i}, 1)));
${lp(e)}
}
`;let d=e.shapeInfo.flatOffset,c=e.shapeInfo.texShape,h=c[0],m=c[1];if(m===p&&d==null)return`
float ${a}(int row, int col, int depth,
int depth2, int depth3, int depth4) {
int texR = row;
float texC = dot(vec4(col, depth, depth2, depth3),
vec4(${u}, ${l}, ${o}, ${i})) +
float(depth4);
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${m}.0, ${h}.0);
return sampleTexture(${n}, uv);
}
`;if(m===i&&d==null)return`
float ${a}(int row, int col, int depth,
int depth2, int depth3, int depth4) {
float texR = dot(vec4(row, col, depth, depth2),
vec4(${t[1]*t[2]*t[3]*t[4]},
${t[2]*t[3]*t[4]},
${t[3]*t[4]},
${t[4]})) + float(depth3);
int texC = depth4;
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${m}.0, ${h}.0);
return sampleTexture(${n}, uv);
}
`;let f=jo(n);return`
float ${a}(int row, int col, int depth,
int depth2, int depth3, int depth4) {
// Explicitly use integer operations as dot() only works on floats.
int index = row * ${p} + col * ${u} + depth * ${l} +
depth2 * ${o} + depth3 * ${i} + depth4 + ${f};
vec2 uv = uvFromFlat(${h}, ${m}, index);
return sampleTexture(${n}, uv);
}
`}function lp(e){let t=e.name,n=v.sizeFromShape(e.shapeInfo.logicalShape);return n<2?`return ${t};`:`
for (int i = 0; i < ${n}; i++) {
if (i == index) {
return ${t}[i];
}
}
`}function EJ(e,t){let n=e.name,a=n.charAt(0).toUpperCase()+n.slice(1),r="get"+a+"AtOutCoords",s=e.shapeInfo.logicalShape.length,i=t.logicalShape.length,o=vE(e.shapeInfo.logicalShape,t.logicalShape),l=ct(i),u=i-s,p,d=["x","y","z","w","u","v"];s===0?p="":i<2&&o.length>=1?p="coords = 0;":p=o.map(g=>`coords.${d[g+u]} = 0;`).join(`
`);let c="";i<2&&s>0?c="coords":c=e.shapeInfo.logicalShape.map((g,b)=>`coords.${d[b+u]}`).join(", ");let h="return outputValue;",m=v.sizeFromShape(e.shapeInfo.logicalShape)===1,f=v.sizeFromShape(t.logicalShape)===1;if(s===1&&!m&&!f)h=`
return vec4(outputValue.xy, outputValue.xy);
`;else if(m&&!f)i===1?h=`
return vec4(outputValue.x, outputValue.x, 0., 0.);
`:h=`
return vec4(outputValue.x);
`;else if(o.length){let g=s-2,b=s-1;o.indexOf(g)>-1&&o.indexOf(b)>-1?h="return vec4(outputValue.x);":o.indexOf(g)>-1?h="return vec4(outputValue.x, outputValue.y, outputValue.x, outputValue.y);":o.indexOf(b)>-1&&(h="return vec4(outputValue.xx, outputValue.zz);")}return`
vec4 ${r}() {
${l} coords = getOutputCoords();
${p}
vec4 outputValue = get${a}(${c});
${h}
}
`}function AJ(e,t){let n=e.name,a=n.charAt(0).toUpperCase()+n.slice(1),r="get"+a+"AtOutCoords",s=t.texShape,i=e.shapeInfo.texShape,o=e.shapeInfo.logicalShape.length,l=t.logicalShape.length;if(!e.shapeInfo.isUniform&&o===l&&e.shapeInfo.flatOffset==null&&v.arraysEqual(i,s))return`
float ${r}() {
return sampleTexture(${n}, resultUV);
}
`;let u=ct(l),p=vE(e.shapeInfo.logicalShape,t.logicalShape),d=l-o,c,h=["x","y","z","w","u","v"];o===0?c="":l<2&&p.length>=1?c="coords = 0;":c=p.map(f=>`coords.${h[f+d]} = 0;`).join(`
`);let m="";return l<2&&o>0?m="coords":m=e.shapeInfo.logicalShape.map((f,g)=>`coords.${h[g+d]}`).join(", "),`
float ${r}() {
${u} coords = getOutputCoords();
${c}
return get${a}(${m});
}
`}function ct(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 ${e} is not yet supported`)}function W1(e,t,n){let{newShape:a,keptDims:r}=v.squeezeShape(t),s=t.length,i=e&&s===3&&t[0]===1,o=i?t.slice(1):a,l=!e&&s>1&&!v.arraysEqual(t,n)&&a.length<s||i;return{useSqueezeShape:l,uniformShape:l?o:t,keptDims:r}}function up(e,t){let n=JSON.parse(JSON.stringify(e));return n.shapeInfo.logicalShape=t,n}function pp(e,t){return t.map(n=>e[n]).join(", ")}function FJ(e,t,n,a){let r=n.map((p,d)=>{let c={logicalShape:p.shape,texShape:p.isUniform?null:p.texData.texShape,isUniform:p.isUniform,isPacked:p.isUniform?!1:p.texData.isPacked,flatOffset:null};return p.texData!=null&&p.texData.slice!=null&&p.texData.slice.flatOffset>0&&(c.flatOffset=p.texData.slice.flatOffset),{name:t.variableNames[d],shapeInfo:c}}),s=r.map(p=>p.shapeInfo),i={logicalShape:a.shape,texShape:a.texData.texShape,isUniform:!1,isPacked:a.texData.isPacked,flatOffset:null},o=XZ(r,i,t),l=J_(e.gl,o),u=e.createProgram(l);return G().get("ENGINE_COMPILE_ONLY")?{program:t,fragmentShader:l,source:o,webGLProgram:u,inShapeInfos:s,outShapeInfo:i,variablesLocations:null,customUniformLocations:null,infLoc:null,nanLoc:null,outShapeLocation:null,outShapeStridesLocation:null,outTexShapeLocation:null}:(e.buildVao(u),Object.assign({program:t,fragmentShader:l,source:o,webGLProgram:u,inShapeInfos:s,outShapeInfo:i},IE(e,t,u)))}function IE(e,t,n){let a=[],r=[],s,i,o,l=null,u=null;u=e.getUniformLocation(n,"NAN",!1),G().getNumber("WEBGL_VERSION")===1&&(l=e.getUniformLocation(n,"INFINITY",!1));let p=!1;for(let d of t.variableNames){let c={name:d,uniform:e.getUniformLocation(n,d,p),offset:e.getUniformLocation(n,`offset${d}`,p)};t.enableShapeUniforms&&(c.shape=e.getUniformLocation(n,`${d}Shape`,p),c.texShape=e.getUniformLocation(n,`${d}TexShape`,p)),a.push(c)}if(t.enableShapeUniforms&&(s=e.getUniformLocation(n,"outShape",p),o=e.getUniformLocation(n,"outShapeStrides",p),i=e.getUniformLocation(n,"outTexShape",p)),t.customUniforms)for(let d of t.customUniforms)r.push(e.getUniformLocation(n,d.name,p));return{variablesLocations:a,customUniformLocations:r,infLoc:l,nanLoc:u,outShapeLocation:s,outShapeStridesLocation:o,outTexShapeLocation:i}}function LI(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((n,a)=>{let r=n.logicalShape,s=t[a],i=s.shape;if(!v.arraysEqual(r,i))throw Error(`Binary was compiled with different shapes than the current args. Shapes ${r} and ${i} must match`);if(n.isUniform&&s.isUniform)return;let o=n.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 $J(e,t,n,a,r){t.program.enableShapeUniforms||(LI(t.inShapeInfos,n),LI([t.outShapeInfo],[a]));let s=a.texData.texture,i=a.texData.texShape;a.texData.isPacked?e.setOutputPackedMatrixTexture(s.texture,i[0],i[1]):e.setOutputMatrixTexture(s.texture,i[0],i[1]),e.setProgram(t.webGLProgram),e.bindVertexArray(t.webGLProgram.vao),G().getNumber("WEBGL_VERSION")===1&&t.infLoc!==null&&e.gl.uniform1f(t.infLoc,1/0),t.nanLoc!==null&&e.gl.uniform1f(t.nanLoc,NaN);for(let l=0;l<n.length;++l){let u=n[l],{uniform:p,offset:d,shape:c,texShape:h}=t.variablesLocations[l];if(c){let{uniformShape:m}=W1(t.program.packedInputs,u.shape,u.texData.texShape);switch(m.length){case 1:e.gl.uniform1iv(c,new Int32Array(m));break;case 2:e.gl.uniform2iv(c,new Int32Array(m));break;case 3:e.gl.uniform3iv(c,new Int32Array(m));break;case 4:e.gl.uniform4iv(c,new Int32Array(m));break;default:break}}if(h&&e.gl.uniform2i(h,u.texData.texShape[0],u.texData.texShape[1]),p!=null){if(u.isUniform){if(v.sizeFromShape(u.shape)<2)e.gl.uniform1f(p,u.uniformValues[0]);else{let m=u.uniformValues;m instanceof Float32Array||(m=new Float32Array(m)),e.gl.uniform1fv(p,m)}continue}u.texData.slice!=null&&d!=null&&e.gl.uniform1i(d,u.texData.slice.flatOffset),e.setInputMatrixTexture(u.texData.texture.texture,p,l)}}let o=t.outShapeLocation;if(o)switch(a.shape.length){case 1:e.gl.uniform1iv(o,new Int32Array(a.shape));break;case 2:e.gl.uniform2iv(o,new Int32Array(a.shape));break;case 3:e.gl.uniform3iv(o,new Int32Array(a.shape));break;case 4:e.gl.uniform4iv(o,new Int32Array(a.shape));break;default:break}if(t.outShapeStridesLocation){let l=v.computeStrides(a.shape);switch(a.shape.length){case 2:e.gl.uniform1iv(t.outShapeStridesLocation,new Int32Array(l));break;case 3:e.gl.uniform2iv(t.outShapeStridesLocation,new Int32Array(l));break;case 4:e.gl.uniform3iv(t.outShapeStridesLocation,new Int32Array(l));break;default:break}}if(t.outTexShapeLocation&&e.gl.uniform2i(t.outTexShapeLocation,a.texData.texShape[0],a.texData.texShape[1]),t.program.customUniforms&&r)for(let l=0;l<t.program.customUniforms.length;++l){let u=t.program.customUniforms[l],p=t.customUniformLocations[l],d=r[l];if(u.type==="float")e.gl.uniform1fv(p,d);else if(u.type==="vec2")e.gl.uniform2fv(p,d);else if(u.type==="vec3")e.gl.uniform3fv(p,d);else if(u.type==="vec4")e.gl.uniform4fv(p,d);else if(u.type==="int")e.gl.uniform1iv(p,d);else if(u.type==="ivec2")e.gl.uniform2iv(p,d);else if(u.type==="ivec3")e.gl.uniform3iv(p,d);else if(u.type==="ivec4")e.gl.uniform4iv(p,d);else throw Error(`uniform type ${u.type} is not supported yet.`)}e.executeProgram()}function DJ(e,t,n){let a="";t.concat(n).forEach(i=>{let o=i.texData!=null&&i.texData.slice!=null&&i.texData.slice.flatOffset>0;if(e.enableShapeUniforms&&!i.isUniform){let l=i.texData.texShape,{useSqueezeShape:u,uniformShape:p,keptDims:d}=W1(e.packedInputs,i.shape,l),c="",h="",m="";if(p.length===1&&e.packedInputs){let I=[Math.ceil(l[0]/2),Math.ceil(l[1]/2)];c=`${I[0]>1}_${I[1]>1}`}else if(p.length===2&&!e.packedInputs)h=`${p[0]>1}_${p[1]>1}`;else if(p.length>2&&!e.packedInputs){let I=v.computeStrides(p);m=`${I[0]===l[1]}_${I[I.length-1]===l[1]}`}let f=i.shape.length,g=p.length===2&&v.arraysEqual(i.shape,l),b=v.sizeFromShape(i.shape)===1,y=N.getBroadcastDims(i.shape,n.shape),x=!e.packedInputs&&f===n.shape.length&&v.arraysEqual(l,n.texData.texShape),w=e.packedInputs||p.length>2?"":`${l[0]>1}_${l[1]>1}`;a+=`${f}_${x}_${u?d:""}_${p.length}_${b}_${y}_${g}_${c}_${h}_${m}_${w}_${o}`}else{let l=i.isUniform?"uniform":i.texData.texShape;a+=`${i.shape}_${l}_${o}`}});let r=e.userCode,s=e.constructor.name;return s+="_"+a+"_"+r+`${G().getNumber("WEBGL_VERSION")}`,s}function vn(e){return G().getBool("WEBGL_USE_SHAPES_UNIFORMS")&&e<=4}var RJ=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outPackingScheme=vc.DENSE,this.customUniforms=[{name:"texShape",type:"ivec2"}];let t=_n();this.outputShape=e,this.enableShapeUniforms=vn(this.outputShape.length),this.userCode=`
ivec3 outCoordsFromFlatIndex(int index) {
${this.enableShapeUniforms?Pf(["r","c","d"],e):qo(["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;
}
`}},MJ=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outPackingScheme=vc.DENSE,this.customUniforms=[{name:"texShape",type:"ivec2"}];let t=_n();this.outputShape=e,this.enableShapeUniforms=vn(this.outputShape.length),this.userCode=`
ivec3 outCoordsFromFlatIndex(int index) {
${this.enableShapeUniforms?Pf(["r","c","d"],e):qo(["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;
}
`}},PJ=class{constructor(e){this.variableNames=["A"],this.outTexUsage=da.DOWNLOAD;let t=_n();this.outputShape=e,this.userCode=`
${xE}
void main() {
float x = getAAtOutCoords();
${t.output} = encode_float(x);
}
`}},OJ=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outTexUsage=da.DOWNLOAD;let t=_n();this.outputShape=e,this.userCode=`
${xE}
void main() {
ivec3 coords = getOutputCoords();
float x = getChannel(getAAtOutCoords(), vec2(coords.y, coords.z));
${t.output} = encode_float(x);
}
`}},LJ={R:0,G:1,B:2,A:3},zI=class{constructor(e,t=!1,n="RGBA"){this.variableNames=["A"],this.customUniforms=[{name:"texShape",type:"ivec2"}];let a=_n();this.outputShape=e,this.enableShapeUniforms=vn(this.outputShape.length);let r="result";t&&(r="floor(result * 255. + 0.5)");let s="";for(let i=0;i<n.length;i++){let o=n[i];s+=`
if(offset == ${i}) {
result = values[${LJ[o]}];
}`}this.userCode=`
${this.enableShapeUniforms?z1():L1(e)}
void main() {
ivec3 coords = getOutputCoords();
int flatIndex = getFlatIndex(coords);
float result = 0.;
int offset = imod(flatIndex, ${n.length});
flatIndex = idiv(flatIndex, ${n.length}, 1.);
int r = flatIndex / texShape[1];
if (r < texShape[0]) {
int c = imod(flatIndex, texShape[1]);
vec2 uv = (vec2(c, r) + halfCR) / vec2(texShape[1], texShape[0]);
vec4 values = ${a.texture2D}(A, uv);
${s}
}
${a.output} = vec4(${r}, 0., 0., 0.);
}
`}},zJ=class{constructor(e,t=!1){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.customUniforms=[{name:"texShape",type:"ivec2"}];let n=_n();this.outputShape=e,this.enableShapeUniforms=vn(this.outputShape.length);let a="",r="result";t&&(r="floor(result * 255. + 0.5)");for(let s=0;s<=1;s++)for(let i=0;i<=1;i++){let o=s*2+i;a+=`
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 = ${n.texture2D}(A, uv);
if (offset == 0) {
result[${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?z1():L1(e)}
void main() {
ivec3 coords = getOutputCoords();
vec4 result = vec4(0.);
int flatIndex, r, c, offset;
ivec3 localCoords;
vec2 uv;
vec4 values;
${a}
${n.output} = ${r};
}
`}},SE={};Ee(SE,{bindVertexProgramAttributeStreams:()=>DE,createBufferFromOutputTexture:()=>PE,createFloat16MatrixTexture:()=>EE,createFloat16PackedMatrixTexture:()=>$E,createFloat32MatrixTexture:()=>_E,createIndexBuffer:()=>CE,createPackedMatrixTexture:()=>FE,createUnsignedBytesMatrixTexture:()=>AE,createVertexBuffer:()=>TE,createVertexShader:()=>NE,downloadByteEncodedFloatMatrixFromOutputTexture:()=>LE,downloadFloat32MatrixFromBuffer:()=>OE,downloadMatrixFromPackedOutputTexture:()=>WE,downloadPackedMatrixFromBuffer:()=>zE,getInternalFormatForFloat16MatrixTexture:()=>V1,getInternalFormatForFloat16PackedMatrixTexture:()=>H1,getInternalFormatForFloat32MatrixTexture:()=>B1,getInternalFormatForPackedMatrixTexture:()=>G1,getInternalFormatForUnsignedBytesMatrixTexture:()=>U1,uploadDenseMatrixToTexture:()=>RE,uploadPixelDataToTexture:()=>ME});function NE(e){let t=_n(),n=`${t.version}
precision highp float;
${t.attribute} vec3 clipSpacePos;
${t.attribute} vec2 uv;
${t.varyingVs} vec2 resultUV;
void main() {
gl_Position = vec4(clipSpacePos, 1);
resultUV = uv;
}`;return Z_(e,n)}function TE(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 tE(e,t)}function CE(e){let t=new Uint16Array([0,1,2,2,1,3]);return nE(e,t)}function Sd(e,t,n,a,r,s){rE(t,n);let i=aE(e),o=e.TEXTURE_2D;return de(e,()=>e.bindTexture(o,i)),de(e,()=>e.texParameteri(o,e.TEXTURE_WRAP_S,e.CLAMP_TO_EDGE)),de(e,()=>e.texParameteri(o,e.TEXTURE_WRAP_T,e.CLAMP_TO_EDGE)),de(e,()=>e.texParameteri(o,e.TEXTURE_MIN_FILTER,e.NEAREST)),de(e,()=>e.texParameteri(o,e.TEXTURE_MAG_FILTER,e.NEAREST)),G().getNumber("WEBGL_VERSION")===1?de(e,()=>e.texImage2D(o,0,a,t,n,0,r,s,null)):de(e,()=>e.texStorage2D(o,1,a,t,n)),de(e,()=>e.bindTexture(e.TEXTURE_2D,null)),{texture:i,texShape:[n,t]}}function B1(e){return e.internalFormatFloat}function _E(e,t,n,a){let[r,s]=Id(t,n);return Sd(e,r,s,B1(a),a.textureFormatFloat,e.FLOAT)}function V1(e){return e.internalFormatHalfFloat}function EE(e,t,n,a){let[r,s]=Id(t,n);return 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de(e,()=>e.bufferData(e.PIXEL_PACK_BUFFER,s,e.STREAM_READ)),de(e,()=>e.readPixels(0,0,n,t,e.RGBA,e.FLOAT,0)),de(e,()=>e.bindBuffer(e.PIXEL_PACK_BUFFER,null)),r}function OE(e,t,n){let a=e,r=new Float32Array(n);return a.bindBuffer(a.PIXEL_PACK_BUFFER,t),a.getBufferSubData(a.PIXEL_PACK_BUFFER,0,r),a.bindBuffer(a.PIXEL_PACK_BUFFER,null),r}function LE(e,t,n,a){let[r,s]=Id(t,n),i=4,o=new Uint8Array(MZ(t*n,i));return de(e,()=>e.readPixels(0,0,r,s,a.downloadTextureFormat,e.UNSIGNED_BYTE,o)),new Float32Array(o.buffer)}function zE(e,t,n,a,r,s,i,o){let l=e,u=new Float32Array(PZ(s,i));return l.bindBuffer(l.PIXEL_PACK_BUFFER,t),l.getBufferSubData(l.PIXEL_PACK_BUFFER,0,u),l.bindBuffer(l.PIXEL_PACK_BUFFER,null),u}function WE(e,t,n){let a=new Float32Array(t*n*4);return de(e,()=>e.readPixels(0,0,n,t,e.RGBA,e.FLOAT,a)),a}var Mh=class{constructor(e){this.outputTexture=null,this.program=null,this.disposed=!1,this.itemsToPoll=[];let 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r="OES_texture_float",s="OES_texture_half_float";if(this.textureFloatExtension=Qp(this.gl,r),ha(this.gl,s))this.textureHalfFloatExtension=Qp(this.gl,s);else if(G().get("WEBGL_FORCE_F16_TEXTURES"))throw new Error("GL context does not support half float textures, yet the environment flag WEBGL_FORCE_F16_TEXTURES is set to true.");if(this.colorBufferFloatExtension=this.gl.getExtension(n),ha(this.gl,a))this.colorBufferHalfFloatExtension=Qp(this.gl,a);else if(G().get("WEBGL_FORCE_F16_TEXTURES"))throw new Error("GL context does not support color renderable half floats, yet the environment flag WEBGL_FORCE_F16_TEXTURES is set to true.")}else if(n="EXT_color_buffer_float",ha(this.gl,n))this.colorBufferFloatExtension=this.gl.getExtension(n);else if(ha(this.gl,a))this.colorBufferHalfFloatExtension=this.gl.getExtension(a);else throw new Error("GL context does not support color renderable floats");this.vertexBuffer=TE(this.gl),this.indexBuffer=CE(this.gl),this.framebuffer=sE(this.gl),this.textureConfig=P1(this.gl,this.textureHalfFloatExtension)}get debug(){return G().getBool("DEBUG")}dispose(){if(this.disposed)return;this.program!=null&&console.warn("Disposing a GPGPUContext that still has a bound WebGLProgram. This is probably a resource leak, delete the program with GPGPUContext.deleteProgram before disposing."),this.outputTexture!=null&&console.warn("Disposing a GPGPUContext that still has a bound output matrix texture. This is probably a resource leak, delete the output matrix texture with GPGPUContext.deleteMatrixTexture before disposing.");let e=this.gl;de(e,()=>e.finish()),de(e,()=>e.bindFramebuffer(e.FRAMEBUFFER,null)),de(e,()=>e.deleteFramebuffer(this.framebuffer)),de(e,()=>e.bindBuffer(e.ARRAY_BUFFER,null)),de(e,()=>e.bindBuffer(e.ELEMENT_ARRAY_BUFFER,null)),de(e,()=>e.deleteBuffer(this.indexBuffer)),this.disposed=!0}createFloat32MatrixTexture(e,t){return this.throwIfDisposed(),_E(this.gl,e,t,this.textureConfig)}createFloat16MatrixTexture(e,t){return this.throwIfDisposed(),EE(this.gl,e,t,this.textureConfig)}createUnsignedBytesMatrixTexture(e,t){return this.throwIfDisposed(),AE(this.gl,e,t,this.textureConfig)}uploadPixelDataToTexture(e,t){this.throwIfDisposed(),ME(this.gl,e,t)}uploadDenseMatrixToTexture(e,t,n,a){this.throwIfDisposed(),RE(this.gl,e,t,n,a,this.textureConfig)}createFloat16PackedMatrixTexture(e,t){return this.throwIfDisposed(),$E(this.gl,e,t,this.textureConfig)}createPackedMatrixTexture(e,t){return this.throwIfDisposed(),FE(this.gl,e,t,this.textureConfig)}deleteMatrixTexture(e){this.throwIfDisposed(),this.outputTexture===e&&(Zx(this.gl,this.framebuffer),this.outputTexture=null),de(this.gl,()=>this.gl.deleteTexture(e))}downloadByteEncodedFloatMatrixFromOutputTexture(e,t,n){return this.downloadMatrixDriver(e,()=>LE(this.gl,t,n,this.textureConfig))}downloadPackedMatrixFromBuffer(e,t,n,a,r,s){return zE(this.gl,e,t,n,a,r,s,this.textureConfig)}downloadFloat32MatrixFromBuffer(e,t){return OE(this.gl,e,t)}createBufferFromTexture(e,t,n){this.bindTextureToFrameBuffer(e);let a=PE(this.gl,t,n,this.textureConfig);return this.unbindTextureToFrameBuffer(),a}createAndWaitForFence(){let e=this.createFence(this.gl);return this.pollFence(e)}createFence(e){let t,n;if(G().getBool("WEBGL_FENCE_API_ENABLED")){let a=e,r=a.fenceSync(a.SYNC_GPU_COMMANDS_COMPLETE,0);e.flush(),n=()=>{let s=a.clientWaitSync(r,0,0);return s===a.ALREADY_SIGNALED||s===a.CONDITION_SATISFIED},t=r}else G().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")>0?(t=this.beginQuery(),this.endQuery(),n=()=>this.isQueryAvailable(t,G().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))):n=()=>!0;return{query:t,isFencePassed:n}}downloadMatrixFromPackedTexture(e,t,n){return this.downloadMatrixDriver(e,()=>WE(this.gl,t,n))}createProgram(e){this.throwIfDisposed();let t=this.gl;this.vertexShader==null&&(this.vertexShader=NE(t));let n=Q_(t);de(t,()=>t.attachShader(n,this.vertexShader)),de(t,()=>t.attachShader(n,e)),eE(t,n);let a=Object.assign(n,{vao:this.createVertexArray()});return this.debug&&Fh(t,a),a}buildVao(e){this.setProgram(e),this.bindVertexArray(e.vao);let t=this.gl;de(t,()=>t.bindBuffer(t.ELEMENT_ARRAY_BUFFER,this.indexBuffer)),DE(t,e,this.vertexBuffer)}deleteProgram(e){this.throwIfDisposed(),e===this.program&&(this.program=null),e!=null&&(de(this.gl,()=>this.gl.deleteProgram(e)),this.deleteVertexArray(e.vao))}setProgram(e){this.throwIfDisposed(),this.program=e,this.program!=null&&this.debug&&Fh(this.gl,this.program),de(this.gl,()=>this.gl.useProgram(e))}getUniformLocation(e,t,n=!0){return this.throwIfDisposed(),n?oE(this.gl,e,t):lE(this.gl,e,t)}getAttributeLocation(e,t){return this.throwIfDisposed(),de(this.gl,()=>this.gl.getAttribLocation(e,t))}getUniformLocationNoThrow(e,t){return this.throwIfDisposed(),this.gl.getUniformLocation(e,t)}setInputMatrixTexture(e,t,n){this.throwIfDisposed(),this.throwIfNoProgram(),uE(this.gl,e,t,n)}setOutputMatrixTexture(e,t,n){this.setOutputMatrixTextureDriver(e,n,t)}setOutputPackedMatrixTexture(e,t,n){this.throwIfDisposed();let[a,r]=sp(t,n);this.setOutputMatrixTextureDriver(e,a,r)}setOutputMatrixWriteRegion(e,t,n,a){this.setOutputMatrixWriteRegionDriver(n,e,a,t)}setOutputPackedMatrixWriteRegion(e,t,n,a){throw new Error("setOutputPackedMatrixWriteRegion not implemented.")}debugValidate(){this.program!=null&&Fh(this.gl,this.program),ec(this.gl)}executeProgram(){this.throwIfDisposed(),this.throwIfNoProgram();let e=this.gl;if(this.debug){let t=this.getVertexArray();console.assert(t===this.program.vao,"VAO changed between setProgram and 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this.unbindTextureToFrameBuffer(),n}setOutputMatrixTextureDriver(e,t,n){this.throwIfDisposed();let a=this.gl;$h(a,e,this.framebuffer),this.debug&&ec(a),this.outputTexture=e,de(a,()=>a.viewport(0,0,t,n)),de(a,()=>a.scissor(0,0,t,n))}setOutputMatrixWriteRegionDriver(e,t,n,a){this.throwIfDisposed(),de(this.gl,()=>this.gl.scissor(e,t,n,a))}throwIfDisposed(){if(this.disposed)throw new Error("Attempted to use disposed GPGPUContext.")}throwIfNoProgram(){if(this.program==null)throw new Error("No GPU program is currently set.")}};function WJ(e){let t=0;for(;t<e.length&&e[t]();++t);return t-1}var{addImpl:BJ,bincountImpl:BE,bincountReduceImpl:VJ,castImpl:UJ,ceilImpl:GJ,concatImpl:HJ,equalImpl:qJ,expImpl:jJ,expm1Impl:KJ,floorImpl:XJ,gatherNdImpl:YJ,gatherV2Impl:ZJ,greaterImpl:JJ,greaterEqualImpl:QJ,lessImpl:e9,lessEqualImpl:t9,linSpaceImpl:n9,logImpl:a9,maxImpl:r9,maximumImpl:s9,minimumImpl:i9,multiplyImpl:o9,negImpl:l9,notEqualImpl:u9,prodImpl:p9,raggedGatherImpl:c9,raggedRangeImpl:d9,raggedTensorToTensorImpl:h9,rangeImpl:m9,rsqrtImpl:f9,scatterImpl:g9,sigmoidImpl:b9,simpleAbsImpl:VE,sliceImpl:y9,sparseFillEmptyRowsImpl:x9,sparseReshapeImpl:v9,sparseSegmentReductionImpl:UE,sqrtImpl:w9,staticRegexReplaceImpl:k9,stridedSliceImpl:I9,stringNGramsImpl:S9,stringSplitImpl:N9,stringToHashBucketFastImpl:T9,subImpl:C9,tileImpl:_9,topKImpl:E9,transposeImpl:q1,uniqueImpl:A9}=v1;function GE(e,t){return["x","y","z","w","u","v"].slice(0,t).map(n=>`${e}.${n}`)}function In(e,t){return t===1?[e]:GE(e,t)}function F9(e,t){if(e===1)return"rc";let n="";for(let a=0;a<e;a++)n+=t[a],a<e-1&&(n+=",");return n}var $9=class{constructor(e){if(this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outputShape=e,this.rank=e.length,this.enableShapeUniforms=vn(this.outputShape.length),this.rank===0)this.userCode=`
void main() {
setOutput(vec4(getA(), 0., 0., 0.));
}
`;else{let t=In("rc",this.rank),n=ct(this.rank),a=this.getOutOfBoundsCondition(t),r=this.getSetup(t),s=this.getOutput(t);this.userCode=`
void main() {
${n} rc = getOutputCoords();
if(${a}) {
setOutput(vec4(0));
} else {
${r}
setOutput(vec4(${s}));
}
}
`}}getSourceCoordsArr(e){let t=[];for(let n=0;n<=1;n++)for(let a=0;a<=1;a++){let r=`${n===0?"r":"rp1"}, ${a===0?"c":"cp1"}`;for(let s=2;s<this.rank;s++)r=`${e[e.length-1-s]},`+r;t.push(r)}return t}getOutOfBoundsCondition(e){if(this.rank===1)return`rc > ${this.enableShapeUniforms?"outShape":this.outputShape[0]}`;let t="";for(let n=this.rank-2;n<this.rank;n++)t+=`${e[n]} >= ${this.enableShapeUniforms?`outShape[${n}]`:this.outputShape[n]}`,n<this.rank-1&&(t+="||");return t}getSetup(e){if(this.rank===1)return"";let t=e.slice(-2),n=this.enableShapeUniforms?`outShape[${this.rank} - 1]`:this.outputShape[this.rank-1],a=this.enableShapeUniforms?`outShape[${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 >= ${n};
bool rEdge = rp1 >= ${a};
`}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]})`}},HE=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"inputShape",type:"ivec3"}],this.outputShape=e,this.enableShapeUniforms=vn(this.outputShape.length);let n="";for(let a=0;a<4;a++){let r="thisRC = rc;";a%2===1&&(r+="thisRC.z += 1;"),a>1&&(r+="thisRC.y += 1;"),n+=`
${r}
${a>0?"if(thisRC.y < rows && thisRC.z < cols){":""}
int flatIndex = getFlatIndex(thisRC);
ivec3 inputRC = inputCoordsFromReshapedOutCoords(flatIndex);
vec2 inputRCInnerDims = vec2(float(inputRC.y),float(inputRC.z));
result[${a}] =
getChannel(getA(inputRC.x, inputRC.y, inputRC.z), inputRCInnerDims);
${a>0?"}":""}
`}this.userCode=`
${D9(t,this.enableShapeUniforms)}
${this.enableShapeUniforms?z1():L1(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]};
${n}
setOutput(result);
}
`}};function D9(e,t){return`
ivec3 inputCoordsFromReshapedOutCoords(int index) {
${t?KZ(["r","c","d"],"inputShape"):qo(["r","c","d"],e)}
return ivec3(r, c, d);
}
`}var R9=class{constructor(e){this.gpgpu=e,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0,this.freeTextures={},this.usedTextures={},this.logEnabled=!1}acquireTexture(e,t,n){let a=BI(t,n),r=VI(e,a,n);r in this.freeTextures||(this.freeTextures[r]=[]),r in this.usedTextures||(this.usedTextures[r]=[]);let s=WI(e,a,this.gpgpu.gl,this.gpgpu.textureConfig,n);if(this.freeTextures[r].length>0){this.numFreeTextures--,this.numUsedTextures++,this._numBytesFree-=s,this.log();let o=this.freeTextures[r].pop();return this.usedTextures[r].push(o),o}let i;return a===dn.PACKED_2X2_FLOAT32?i=this.gpgpu.createPackedMatrixTexture(e[0],e[1]):a===dn.PACKED_2X2_FLOAT16?i=this.gpgpu.createFloat16PackedMatrixTexture(e[0],e[1]):a===dn.UNPACKED_FLOAT32?i=this.gpgpu.createFloat32MatrixTexture(e[0],e[1]):a===dn.UNPACKED_FLOAT16?i=this.gpgpu.createFloat16MatrixTexture(e[0],e[1]):a===dn.PACKED_4X1_UNSIGNED_BYTE&&(i=this.gpgpu.createUnsignedBytesMatrixTexture(e[0],e[1])),this.usedTextures[r].push(i),this.numUsedTextures++,this._numBytesAllocated+=s,this.log(),i}releaseTexture(e,t,n,a){if(this.freeTextures==null)return;let r=BI(n,a),s=VI(t,r,a);s in this.freeTextures||(this.freeTextures[s]=[]);let i=WI(t,r,this.gpgpu.gl,this.gpgpu.textureConfig,a),o=G().get("WEBGL_DELETE_TEXTURE_THRESHOLD");o!==-1&&this._numBytesAllocated>o?(this.gpgpu.deleteMatrixTexture(e.texture),this._numBytesAllocated-=i):(this.freeTextures[s].push(e),this.numFreeTextures++,this._numBytesFree+=i),this.numUsedTextures--;let l=this.usedTextures[s],u=l&&l.indexOf(e);if(u==null||u<0)throw new Error("Cannot release a texture that was never provided by this texture manager");l[u]=l[l.length-1],l.pop(),this.log()}log(){if(!this.logEnabled)return;let e=this.numFreeTextures+this.numUsedTextures;console.log("Free/Used",`${this.numFreeTextures} / ${this.numUsedTextures}`,`(${e})`);let t=this._numBytesFree/this._numBytesAllocated;console.log(`Bytes allocated: ${this._numBytesAllocated}`),console.log(`Bytes unused: ${this._numBytesFree} (${Math.round(100*t)}%)`)}get numBytesAllocated(){return this._numBytesAllocated}get numBytesFree(){return this._numBytesFree}getNumUsedTextures(){return this.numUsedTextures}getNumFreeTextures(){return this.numFreeTextures}dispose(){if(this.freeTextures!=null){for(let e in this.freeTextures)this.freeTextures[e].forEach(t=>{this.gpgpu.deleteMatrixTexture(t.texture)});for(let e in this.usedTextures)this.usedTextures[e].forEach(t=>{this.gpgpu.deleteMatrixTexture(t.texture)});this.freeTextures=null,this.usedTextures=null,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0}}};function M9(e,t){let n=e;if(t===n.R32F)return 4;if(t===n.R16F)return 2;if(t===n.RGBA32F||t===e.RGBA)return 16;if(t===n.RGBA16F)return 8;if(t===n.RGBA8)return 4;throw new Error(`Unknown internal format ${t}`)}function WI(e,t,n,a,r){let s=P9(t,a),i;if(r){let[l,u]=sp(e[0],e[1]);i=l*u}else{let[l,u]=Id(e[0],e[1]);i=l*u}let o=M9(n,s);return i*o}function P9(e,t){switch(e){case dn.PACKED_2X2_FLOAT32:return G1(t);case dn.PACKED_2X2_FLOAT16:return H1(t);case dn.UNPACKED_FLOAT32:return B1(t);case dn.UNPACKED_FLOAT16:return V1(t);case dn.PACKED_4X1_UNSIGNED_BYTE:return U1(t);default:throw new Error(`Unknown physical texture type ${e}`)}}function O9(e){return G().getBool("WEBGL_RENDER_FLOAT32_ENABLED")?e?dn.PACKED_2X2_FLOAT32:dn.UNPACKED_FLOAT32:e?dn.PACKED_2X2_FLOAT16:dn.UNPACKED_FLOAT16}function BI(e,t){if(e===da.UPLOAD)return dn.PACKED_2X2_FLOAT32;if(e===da.RENDER||e==null)return O9(t);if(e===da.DOWNLOAD||e===da.PIXELS)return dn.PACKED_4X1_UNSIGNED_BYTE;throw new Error(`Unknown logical texture type ${e}`)}function VI(e,t,n){return`${e[0]}_${e[1]}_${t}_${n}`}var rr=class{constructor(e,t){this.variableNames=["A"],this.outputShape=e,this.enableShapeUniforms=vn(this.outputShape.length),this.userCode=`
float unaryOperation(float x) {
${t}
}
void main() {
float x = getAAtOutCoords();
float y = unaryOperation(x);
setOutput(y);
}
`}},Ma="if (isnan(x)) return x;",L9="return x;",UI="return abs(x);",z9="return (x >= 0.0) ? x : (exp(x) - 1.0);",W9=Ma+`
return (x < 0.0) ? 0.0 : x;
`,B9=Ma+`
return (x < 0.0) ? 0.0 : min(6.0, x);
`,Yr="return x;",V9="return 1.0 / (1.0 + exp(-1.0 * x));",U9="return x;",G9=`
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;
`,H9=`
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;
`,q9=`
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;
`,j9="return 1.0 / (1.0 + exp(-1.0 * x));",ts=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.enableShapeUniforms=vn(this.outputShape.length),this.userCode=`
vec4 unaryOperation(vec4 x) {
${t}
}
void main() {
vec4 x = getAAtOutCoords();
vec4 y = unaryOperation(x);
setOutput(y);
}
`}},K9=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outputShape=e,this.enableShapeUniforms=vn(this.outputShape.length);let t=e.length,n=In("rc",t),a=ct(t),r=F9(t,n),s=n.slice(-2),i=t<=1?"rc":`vec2(${s.join(",")})`;this.userCode=`
void main() {
${a} rc = getOutputCoords();
vec4 packedInput = getA(${r});
setOutput(getChannel(packedInput, ${i}));
}
`}},X9=hr.whereImpl,Y9=1e-7,Z9=1e-4,lx={};function J9(e){return e in lx||(lx[e]={}),lx[e]}var Q9=G().getNumber("CPU_HANDOFF_SIZE_THRESHOLD"),eQ=600;function tQ(){return G().global.screen==null?1024:G().global.screen.height*G().global.screen.width*window.devicePixelRatio*eQ/1024/1024}var Of=class extends Tc{nextDataId(){return Of.nextDataId++}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,!G().getBool("HAS_WEBGL"))throw new Error("WebGL is not supported on this device");let t;if(e!=null){if(e instanceof Mh)t=e;else{let n=Ka(G().getNumber("WEBGL_VERSION"),e);t=new Mh(n)}this.binaryCache={},this.gpgpuCreatedLocally=!1}else{let n=Ka(G().getNumber("WEBGL_VERSION"));t=new Mh(n),this.binaryCache=J9(G().getNumber("WEBGL_VERSION")),this.gpgpuCreatedLocally=!0}this.gpgpu=t,this.canvas=this.gpgpu.gl.canvas,this.textureManager=new R9(this.gpgpu),this.numMBBeforeWarning=tQ(),this.texData=new mm(this,_a())}numDataIds(){return this.texData.numDataIds()-this.pendingDeletes}writeTexture(e,t,n,a,r,s){let i=this.makeTensorInfo(t,n),o=this.texData.get(i.dataId);o.isPacked=!1,o.texture={texture:e,texShape:[a,r]},o.texShape=[a,r];let l=tc(t),u=new zI(l,!1,s),p=this.runWebGLProgram(u,[i],n,[[a,r]]);return p.shape=t,o.texture=null,this.disposeIntermediateTensorInfo(i),p.dataId}write(e,t,n){if((G().getBool("WEBGL_CHECK_NUMERICAL_PROBLEMS")||G().getBool("DEBUG"))&&this.checkNumericalProblems(e),n==="complex64"&&e!=null)throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");let a={id:this.nextDataId()};return this.texData.set(a,{shape:t,dtype:n,values:e,usage:da.UPLOAD,refCount:1}),a}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,n,a,r){if(G().getBool("DEBUG")&&this.checkNumericalProblems(t),a==="complex64")throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");this.texData.set(e,{shape:n,dtype:a,values:t,usage:da.UPLOAD,refCount:r})}disposeIntermediateTensorInfo(e){this.disposeData(e.dataId)}readSync(e){let t=this.texData.get(e),{values:n,dtype:a,complexTensorInfos:r,slice:s,shape:i,isPacked:o}=t;if(s!=null){let d;o?d=new ts(i,Yr):d=new rr(i,Yr);let c=this.runWebGLProgram(d,[{dataId:e,shape:i,dtype:a}],a),h=this.readSync(c.dataId);return this.disposeIntermediateTensorInfo(c),h}if(n!=null)return this.convertAndCacheOnCPU(e);if(a==="string")return n;let l=this.activeTimers!=null,u;l&&(u=v.now());let p;if(a==="complex64"){let d=this.readSync(r.real.dataId),c=this.readSync(r.imag.dataId);p=N.mergeRealAndImagArrays(d,c)}else p=this.getValuesFromTexture(e);return l&&(this.downloadWaitMs+=v.now()-u),this.convertAndCacheOnCPU(e,p)}async read(e){if(this.pendingRead.has(e)){let h=this.pendingRead.get(e);return new Promise(m=>h.push(m))}let t=this.texData.get(e),{values:n,shape:a,slice:r,dtype:s,complexTensorInfos:i,isPacked:o}=t;if(r!=null){let h;o?h=new ts(a,Yr):h=new rr(a,Yr);let m=this.runWebGLProgram(h,[{dataId:e,shape:a,dtype:s}],s),f=this.read(m.dataId);return this.disposeIntermediateTensorInfo(m),f}if(n!=null)return this.convertAndCacheOnCPU(e);if(G().getBool("DEBUG")&&!G().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")&&G().getNumber("WEBGL_VERSION")===2)throw new Error("tensor.data() with WEBGL_DOWNLOAD_FLOAT_ENABLED=false and WEBGL_VERSION=2 not yet supported.");let l=null,u;if(s!=="complex64"&&G().get("WEBGL_BUFFER_SUPPORTED")){u=this.decode(e);let h=this.texData.get(u.dataId);l=this.gpgpu.createBufferFromTexture(h.texture.texture,...Nh(a))}this.pendingRead.set(e,[]),s!=="complex64"&&await this.gpgpu.createAndWaitForFence();let p;if(s==="complex64"){let h=await Promise.all([this.read(i.real.dataId),this.read(i.imag.dataId)]),m=h[0],f=h[1];p=N.mergeRealAndImagArrays(m,f)}else if(l==null)p=this.getValuesFromTexture(e);else{let h=v.sizeFromShape(a);p=this.gpgpu.downloadFloat32MatrixFromBuffer(l,h)}if(u!=null&&this.disposeIntermediateTensorInfo(u),l!=null){let h=this.gpgpu.gl;de(h,()=>h.deleteBuffer(l))}let d=this.convertAndCacheOnCPU(e,p),c=this.pendingRead.get(e);return this.pendingRead.delete(e),c.forEach(h=>h(d)),this.pendingDisposal.has(e)&&(this.pendingDisposal.delete(e),this.disposeData(e)&&_a().removeDataId(e,this),this.pendingDeletes--),d}readToGPU(e,t={}){let n=this.texData.get(e),{values:a,shape:r,slice:s,dtype:i,isPacked:o,texture:l}=n;if(i==="complex64")throw new Error("Does not support reading texture for complex64 dtype.");if(s!=null){let c;o?c=new ts(r,Yr):c=new rr(r,Yr);let h=this.runWebGLProgram(c,[{dataId:e,shape:r,dtype:i}],i),m=this.readToGPU(h,t);return this.disposeIntermediateTensorInfo(h),m}if(l==null)throw a!=null?new Error("Data is not on GPU but on CPU."):new Error("There is no data on GPU or CPU.");let u=this.decode(e,t.customTexShape),p=_a().makeTensorFromTensorInfo(u),d=this.texData.get(u.dataId);return Object.assign({tensorRef:p},d.texture)}bufferSync(e){let t=this.readSync(e.dataId);if(e.dtype==="string")try{let n=t.map(a=>v.decodeString(a));return Le(e.shape,e.dtype,n)}catch(n){throw new Error("Failed to decode encoded string bytes into utf-8")}return Le(e.shape,e.dtype,t)}checkNumericalProblems(e){if(e!=null)for(let t=0;t<e.length;t++){let n=e[t];if(!X_(n))throw G().getBool("WEBGL_RENDER_FLOAT32_CAPABLE")?Error(`The value ${n} cannot be represented with your current settings. Consider enabling float32 rendering: 'tf.env().set('WEBGL_RENDER_FLOAT32_ENABLED', true);'`):Error(`The value ${n} cannot be represented on this device.`)}}getValuesFromTexture(e){let{shape:t,dtype:n,isPacked:a}=this.texData.get(e),r=v.sizeFromShape(t);if(G().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")){let d=this.decode(e),c=this.texData.get(d.dataId),h=this.gpgpu.downloadMatrixFromPackedTexture(c.texture.texture,...Nh(t)).subarray(0,r);return this.disposeIntermediateTensorInfo(d),h}let s=G().getBool("WEBGL_PACK")&&a===!0,i=s?tc(t):t,o=s?new OJ(i):new PJ(i),l=this.runWebGLProgram(o,[{shape:i,dtype:n,dataId:e}],"float32"),u=this.texData.get(l.dataId),p=this.gpgpu.downloadByteEncodedFloatMatrixFromOutputTexture(u.texture.texture,u.texShape[0],u.texShape[1]).subarray(0,r);return this.disposeIntermediateTensorInfo(l),p}timerAvailable(){return G().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0}time(e){let t=this.activeTimers,n=[],a=!1;this.programTimersStack==null?(this.programTimersStack=n,a=!0):this.activeTimers.push(n),this.activeTimers=n,e();let r=v.flatten(this.activeTimers.map(o=>o.query)).filter(o=>o!=null),s=v.flatten(this.activeTimers.map(o=>o.name)).filter(o=>o!=null);this.activeTimers=t,a&&(this.programTimersStack=null);let i={uploadWaitMs:this.uploadWaitMs,downloadWaitMs:this.downloadWaitMs,kernelMs:null,wallMs:null};return(async()=>{if(G().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0){let o=await Promise.all(r);i.kernelMs=v.sum(o),i.getExtraProfileInfo=()=>o.map((l,u)=>({name:s[u],ms:l})).map(l=>`${l.name}: ${l.ms}`).join(", ")}else i.kernelMs={error:"WebGL query timers are not supported in this environment."};return this.uploadWaitMs=0,this.downloadWaitMs=0,i})()}memory(){return{unreliable:!1,numBytesInGPU:this.numBytesInGPU,numBytesInGPUAllocated:this.textureManager.numBytesAllocated,numBytesInGPUFree:this.textureManager.numBytesFree}}startTimer(){return G().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?this.gpgpu.beginQuery():{startMs:v.now(),endMs:null}}endTimer(e){return G().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?(this.gpgpu.endQuery(),e):(e.endMs=v.now(),e)}async getQueryTime(e){if(G().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:n}=this.texData.get(e);return n!=null&&(this.disposeData(n.real.dataId,t),this.disposeData(n.imag.dataId,t)),this.texData.delete(e),!0}releaseGPUData(e){let{texture:t,dtype:n,texShape:a,usage:r,isPacked:s,slice:i}=this.texData.get(e),o=i&&i.origDataId||e,l=this.dataRefCount.get(o);l>1?this.dataRefCount.set(o,l-1):(this.dataRefCount.delete(o),t!=null&&(this.numBytesInGPU-=this.computeBytes(a,n),this.textureManager.releaseTexture(t,a,r,s)));let u=this.texData.get(e);u.texture=null,u.texShape=null,u.isPacked=!1,u.slice=null}getTexture(e){return this.uploadToGPU(e),this.texData.get(e).texture.texture}getDataInfo(e){return this.texData.get(e)}shouldExecuteOnCPU(e,t=Q9){return G().getBool("WEBGL_CPU_FORWARD")&&e.every(n=>this.texData.get(n.dataId).texture==null&&v.sizeFromShape(n.shape)<t)}getGPGPUContext(){return this.gpgpu}where(e){N.warn("tf.where() in webgl locks the UI thread. Call tf.whereAsync() instead");let t=e.dataSync();return X9(e.shape,t)}packedUnaryOp(e,t,n){let a=new ts(e.shape,t),r=this.compileAndRun(a,[e],n);return _a().makeTensorFromTensorInfo(r)}abs(e){if(this.shouldExecuteOnCPU([e])&&e.dtype!=="complex64"){let a=VE(this.texData.get(e.dataId).values);return this.makeOutput(e.shape,e.dtype,a)}if(G().getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(e,UI,e.dtype);let t=new rr(e.shape,UI),n=this.compileAndRun(t,[e]);return _a().makeTensorFromTensorInfo(n)}makeTensorInfo(e,t,n){let a;if(t==="string"&&n!=null&&n.length>0&&v.isString(n[0])){let r=n.map(s=>v.encodeString(s));a=this.write(r,e,t)}else a=this.write(n,e,t);return this.texData.get(a).usage=null,{dataId:a,shape:e,dtype:t}}makeOutput(e,t,n){return _a().makeTensorFromTensorInfo(this.makeTensorInfo(e,t,n),this)}unpackTensor(e){let t=new K9(e.shape);return this.runWebGLProgram(t,[e],e.dtype)}packTensor(e){let t=new $9(e.shape),n=!0;return this.runWebGLProgram(t,[e],e.dtype,null,n)}packedReshape(e,t){let n=[xi(e.shape),...vi(e.shape)],a={dtype:e.dtype,shape:n,dataId:e.dataId},r=[xi(t),...vi(t)],s=new HE(r,n),i=!0,o=[n],l=this.runWebGLProgram(s,[a],e.dtype,o,i);return{dataId:l.dataId,shape:t,dtype:l.dtype}}decode(e,t){let n=this.texData.get(e),{isPacked:a,shape:r,dtype:s}=n;if(t!=null){let d=v.sizeFromShape(r),c=t[0]*t[1]*4;v.assert(d<=c,()=>"customTexShape is too small. Row * Column * 4 should be equal or larger than the size of the tensor data.")}let i=tc(r),o;a?o=new MJ(i):o=new RJ(i);let l=!0,u=[t!=null?t:Nh(i)],p=this.runWebGLProgram(o,[{shape:i,dtype:s,dataId:e}],s,u,l,t);return{dtype:s,shape:r,dataId:p.dataId}}runWebGLProgram(e,t,n,a,r=!1,s){let i=this.makeTensorInfo(e.outputShape,n),o=this.texData.get(i.dataId);if(e.packedOutput&&(o.isPacked=!0),e.outPackingScheme===vc.DENSE){let g=s!=null?s:Nh(e.outputShape);o.texShape=g.map(b=>b*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 b=this.texData.get(g.dataId);if(b.texture==null){if(!e.packedInputs&&v.sizeFromShape(g.shape)<=G().getNumber("WEBGL_SIZE_UPLOAD_UNIFORM"))return{shape:g.shape,texData:null,isUniform:!0,uniformValues:b.values};e.packedInputs&&(b.isPacked=!0,b.shape=g.shape)}if(this.uploadToGPU(g.dataId),!!b.isPacked!=!!e.packedInputs)g=b.isPacked?this.unpackTensor(g):this.packTensor(g),l.push(g),b=this.texData.get(g.dataId);else if(b.isPacked&&!wc(b.shape,g.shape)){let y=g,x=g.shape;g.shape=b.shape,g=this.packedReshape(g,x),l.push(g),b=this.texData.get(g.dataId),y.shape=x}return{shape:g.shape,texData:b,isUniform:!1}});this.uploadToGPU(i.dataId);let p={shape:i.shape,texData:o,isUniform:!1},d=DJ(e,u,p),c=this.getAndSaveBinary(d,()=>FJ(this.gpgpu,e,u,p)),h=this.activeTimers!=null,m;h&&(m=this.startTimer()),G().get("ENGINE_COMPILE_ONLY")||$J(this.gpgpu,c,u,p,a),l.forEach(g=>this.disposeIntermediateTensorInfo(g)),h&&(m=this.endTimer(m),this.activeTimers.push({name:e.constructor.name,query:this.getQueryTime(m)}));let f=G().get("WEBGL_FLUSH_THRESHOLD");if(f>0){let g=v.now();g-this.lastGlFlushTime>f&&(this.gpgpu.gl.flush(),this.lastGlFlushTime=g)}if(!G().getBool("WEBGL_LAZILY_UNPACK")&&o.isPacked&&r===!1){let g=this.unpackTensor(i);return this.disposeIntermediateTensorInfo(i),g}return i}compileAndRun(e,t,n,a,r=!1){return n=n||t[0].dtype,this.runWebGLProgram(e,t,n,a,r)}getAndSaveBinary(e,t){return e in this.binaryCache||(this.binaryCache[e]=t()),this.binaryCache[e]}getTextureManager(){return this.textureManager}dispose(){this.disposed||(G().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=P(()=>{if(!G().get("WEBGL_RENDER_FLOAT32_ENABLED")){let e=G().getBool("DEBUG");G().set("DEBUG",!1);let t=this.abs(ve(1e-8)).dataSync()[0];if(G().set("DEBUG",e),t>0)return 32}return 16})),this.floatPrecisionValue}epsilon(){return this.floatPrecision()===32?Y9:Z9}uploadToGPU(e){let t=this.texData.get(e),{shape:n,dtype:a,values:r,texture:s,usage:i,isPacked:o}=t;if(s!=null)return;let l=this.activeTimers!=null,u;l&&(u=v.now());let p=t.texShape;if(p==null&&(p=dE(n,o),t.texShape=p),r!=null){let d=tc(n),c,h=p[1],m=p[0],f=r instanceof Uint8Array||r instanceof Uint8ClampedArray;(o||!f)&&([h,m]=sp(p[0],p[1])),o?c=new zJ(d,f):c=new zI(d,f);let g=f?[m,h]:p,b=this.makeTensorInfo(g,a),y=this.texData.get(b.dataId);f?y.usage=da.PIXELS:y.usage=da.UPLOAD,y.texShape=g,this.gpgpu.uploadDenseMatrixToTexture(this.getTexture(b.dataId),h,m,r);let x=[[m,h]],w=!0,I=this.runWebGLProgram(c,[b],a,x,w),T=this.texData.get(I.dataId);t.texShape=T.texShape,t.isPacked=T.isPacked,t.usage=T.usage,G().get("ENGINE_COMPILE_ONLY")?this.disposeData(I.dataId):(t.texture=T.texture,t.values=null,this.texData.delete(I.dataId)),this.disposeIntermediateTensorInfo(b),l&&(this.uploadWaitMs+=v.now()-u)}else{let d=this.acquireTexture(p,i,a,o);t.texture=d}}convertAndCacheOnCPU(e,t){let n=this.texData.get(e),{dtype:a}=n;return t!=null&&(n.values=nQ(t,a)),n.values}acquireTexture(e,t,n,a){if(this.numBytesInGPU+=this.computeBytes(e,n),!this.warnedAboutMemory&&this.numBytesInGPU>this.numMBBeforeWarning*1024*1024){let r=(this.numBytesInGPU/1024/1024).toFixed(2);this.warnedAboutMemory=!0,console.warn(`High memory usage in GPU: ${r} MB, most likely due to a memory leak`)}return this.textureManager.acquireTexture(e,t,a)}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 n=new Promise(a=>{try{this.checkCompletion_(t),a(!0)}catch(r){throw r}});e.push(n)}return Promise.all(e)}}async checkCompletionAsync_(e){return this.gpgpu.gl.getProgramParameter(e.webGLProgram,this.gpgpu.parallelCompilationExtension.COMPLETION_STATUS_KHR)?this.checkCompletion_(e):(await Ow(),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?(O1(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.values(this.binaryCache)){this.gpgpu.buildVao(e.webGLProgram);let{variablesLocations:t,customUniformLocations:n,infLoc:a,nanLoc:r,outShapeLocation:s,outShapeStridesLocation:i,outTexShapeLocation:o}=IE(this.gpgpu,e.program,e.webGLProgram);e.variablesLocations=t,e.customUniformLocations=n,e.infLoc=a,e.nanLoc=r,e.outShapeLocation=s,e.outShapeStridesLocation=i,e.outTexShapeLocation=o}}createTensorFromGPUData(e,t,n){e.channels=e.channels||"RGBA";let{texture:a,height:r,width:s,channels:i}=e,o=_a().backend;if(!o.gpgpu.gl.isTexture(a))throw new Error("The texture is invalid. Also, please make sure the texture and the TFJS WebGL backend are using the same canvas. If you want to use your own custom canvas, you have to create and use the custom TFJS WebGL backend created from the canvas through 'new tf.MathBackendWebGL(customCanvas)'.");let l=o.writeTexture(a,t,n,r,s,i);return _a().makeTensorFromDataId(l,t,n,o)}};Of.nextDataId=0;function nQ(e,t){if(t==="float32"||t==="complex64")return e;if(t==="int32"||t==="bool"){let n=t==="int32"?new Int32Array(e.length):new Uint8Array(e.length);for(let a=0;a<n.length;++a)n[a]=Math.round(e[a]);return n}else throw new Error(`Unknown dtype ${t}`)}var aQ="4.5.0";function qE(){G().set("WEBGL_FORCE_F16_TEXTURES",!0)}Xc.isBrowser()&&Mm("webgl",()=>new Of,2);var rQ={forceHalfFloat:qE},j1=`
if (isnan(a)) return a;
if (isnan(b)) return b;
`,Gl=class{constructor(e,t,n){this.variableNames=["A","B"],this.outputShape=N.assertAndGetBroadcastShape(t,n),this.enableShapeUniforms=vn(this.outputShape.length),this.userCode=`
float binaryOperation(float a, float b) {
${e}
}
void main() {
float a = getAAtOutCoords();
float b = getBAtOutCoords();
setOutput(binaryOperation(a, b));
}
`}},Ko=`
result.r = isNaN.r ? NAN : result.r;
result.g = isNaN.g ? NAN : result.g;
result.b = isNaN.b ? NAN : result.b;
result.a = isNaN.a ? NAN : result.a;
`,Nd=class{constructor(e,t,n,a=!1){this.variableNames=["A","B"],this.supportsBroadcasting=!0,this.packedInputs=!0,this.packedOutput=!0,this.outputShape=N.assertAndGetBroadcastShape(t,n);let r=this.outputShape.length;this.enableShapeUniforms=vn(r);let s="";if(a)if(r===0||v.sizeFromShape(this.outputShape)===1)s=`
result.y = 0.;
result.z = 0.;
result.w = 0.;
`;else if(s=`
${ct(r)} coords = getOutputCoords();
`,r===1)this.enableShapeUniforms?s+=`
result.y = (coords + 1) >= outShape ? 0. : result.y;
result.z = 0.;
result.w = 0.;
`:s+=`
result.y = (coords + 1) >= ${this.outputShape[0]} ? 0. : result.y;
result.z = 0.;
result.w = 0.;
`;else{let i=In("coords",r);this.enableShapeUniforms?s+=`
bool nextRowOutOfBounds =
(${i[r-2]} + 1) >= outShape[${r} - 2];
bool nextColOutOfBounds =
(${i[r-1]} + 1) >= outShape[${r} - 1];
result.y = nextColOutOfBounds ? 0. : result.y;
result.z = nextRowOutOfBounds ? 0. : result.z;
result.w = nextColOutOfBounds || nextRowOutOfBounds ? 0. : result.w;
`:s+=`
bool nextRowOutOfBounds =
(${i[r-2]} + 1) >= ${this.outputShape[r-2]};
bool nextColOutOfBounds =
(${i[r-1]} + 1) >= ${this.outputShape[r-1]};
result.y = nextColOutOfBounds ? 0. : result.y;
result.z = nextRowOutOfBounds ? 0. : result.z;
result.w = nextColOutOfBounds || nextRowOutOfBounds ? 0. : result.w;
`}this.userCode=`
vec4 binaryOperation(vec4 a, vec4 b) {
${e}
}
void main() {
vec4 a = getAAtOutCoords();
vec4 b = getBAtOutCoords();
vec4 result = binaryOperation(a, b);
${s}
setOutput(result);
}
`}};function aa(e){let{inputs:t,backend:n}=e,{x:a}=t;return n.incRef(a.dataId),{dataId:a.dataId,shape:a.shape,dtype:a.dtype}}var sQ={kernelName:Zi,backendName:"webgl",kernelFunc:aa};function Es(e){let{inputs:t,backend:n}=e,{real:a,imag:r}=t,s=n.makeTensorInfo(a.shape,"complex64"),i=n.texData.get(s.dataId),o=aa({inputs:{x:a},backend:n}),l=aa({inputs:{x:r},backend:n});return i.complexTensorInfos={real:o,imag:l},s}var iQ={kernelName:xm,backendName:"webgl",kernelFunc:Es},jE="return (a < 0.) ? b * a : a;",KE=`
vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));
return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);
`;function oQ(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{alpha:s}=a,i=n.makeTensorInfo([],"float32",v.createScalarValue(s,"float32")),o=G().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new Nd(KE,r.shape,i.shape):new Gl(jE,r.shape,i.shape),l=n.runWebGLProgram(o,[r,i],"float32");return n.disposeIntermediateTensorInfo(i),l}var lQ={kernelName:to,backendName:"webgl",kernelFunc:oQ},XE="return (a < 0.) ? b * a : a;",YE=`
vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));
return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);
`;function uQ(e){let{inputs:t,backend:n}=e,{x:a,alpha:r}=t,s=G().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new Nd(YE,a.shape,r.shape):new Gl(XE,a.shape,r.shape);return n.runWebGLProgram(s,[a,r],"float32")}var pQ={kernelName:bo,backendName:"webgl",kernelFunc:uQ},cp="if (isnan(x)) return x;";function Ye({opSnippet:e,packedOpSnippet:t,cpuKernelImpl:n,dtype:a}){return({inputs:r,backend:s})=>{let{x:i}=r,o=s,l=a||i.dtype;if(o.shouldExecuteOnCPU([i])&&n!=null){let d=o.texData.get(i.dataId),c=n(d.values,l);return o.makeTensorInfo(i.shape,l,c)}let u=G().getBool("WEBGL_PACK_UNARY_OPERATIONS")&&t!=null,p;return u?p=new ts(i.shape,t):p=new rr(i.shape,e),o.runWebGLProgram(p,[i],l)}}function mn({opSnippet:e,packedOpSnippet:t,checkOutOfBounds:n=!1,supportsComplex:a=!1,cpuKernelImpl:r,dtype:s}){return({inputs:i,backend:o})=>{let{a:l,b:u}=i,p=o;if(a&&l.dtype==="complex64"){let m=p.texData.get(l.dataId),f=p.texData.get(u.dataId),[g,b]=[[m.complexTensorInfos.real,f.complexTensorInfos.real],[m.complexTensorInfos.imag,f.complexTensorInfos.imag]].map(x=>{let[w,I]=x,T={dataId:w.dataId,dtype:w.dtype,shape:l.shape},C={dataId:I.dataId,dtype:I.dtype,shape:u.shape},E=new Gl(e,l.shape,u.shape);return p.runWebGLProgram(E,[T,C],ga(w.dtype,I.dtype))}),y=Es({inputs:{real:g,imag:b},backend:p});return p.disposeIntermediateTensorInfo(g),p.disposeIntermediateTensorInfo(b),y}let d=s||ga(l.dtype,u.dtype);if((l.dtype==="string"||u.dtype==="string"||p.shouldExecuteOnCPU([l,u]))&&r!=null){let m=p.texData.get(l.dataId).values,f=p.texData.get(u.dataId).values,g=l.dtype==="string"?N.fromUint8ToStringArray(m):m,b=l.dtype==="string"?N.fromUint8ToStringArray(f):f,[y,x]=r(l.shape,u.shape,g,b,d),w=p.makeTensorInfo(x,d),I=p.texData.get(w.dataId);return I.values=y,w}let c=G().getBool("WEBGL_PACK_BINARY_OPERATIONS")&&t!=null,h;return c?h=new Nd(t,l.shape,u.shape,n):h=new Gl(e,l.shape,u.shape),p.runWebGLProgram(h,[l,u],d)}}function kc(e,t=!1){if(e==="linear")return t?U9:L9;if(e==="relu")return t?H9:W9;if(e==="elu")return t?G9:z9;if(e==="relu6")return t?q9:B9;if(e==="prelu")return t?YE:XE;if(e==="leakyrelu")return t?KE:jE;if(e==="sigmoid")return t?j9:V9;throw new Error(`Activation ${e} has not been implemented for the WebGL backend.`)}var ZE=class{constructor(e,t,n,a=!1,r=!1,s=!1,i=null,o=!1,l=!1){this.variableNames=["matrixA","matrixB"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=n,this.enableShapeUniforms=vn(this.outputShape.length);let u=a?e[1]:e[2],p=Math.ceil(u/2),d=a?"i * 2, rc.y":"rc.y, i * 2",c=r?"rc.z, i * 2":"i * 2, rc.z",h=a?["a.xxyy","a.zzww"]:["a.xxzz","a.yyww"],m=r?["b.xzxz","b.ywyw"]:["b.xyxy","b.zwzw"],f="",g="";i&&(o?f=`vec4 activation(vec4 a) {
vec4 b = getPreluActivationWeightsAtOutCoords();
${i}
}`:l?f=`vec4 activation(vec4 a) {
vec4 b = getLeakyreluAlphaAtOutCoords();
${i}
}`:f=`vec4 activation(vec4 x) {
${i}
}`,g="result = activation(result);");let b=s?"result += getBiasAtOutCoords();":"";s&&this.variableNames.push("bias"),o&&this.variableNames.push("preluActivationWeights"),l&&this.variableNames.push("leakyreluAlpha");let y="rc.x",x="rc.x";e[0]<t[0]?y=`imod(rc.x, ${e[0]})`:t[0]<e[0]&&(x=`imod(rc.x, ${t[0]})`),this.userCode=`
${f}
// Don't use uniform for sharedDimensionPacked for performance.
const float sharedDimension = ${p}.0;
vec4 dot2x2ARowBCol(ivec3 rc) {
vec4 result = vec4(0);
int batchA = ${y};
int batchB = ${x};
for (int i = 0; i < ${p}; i++) {
vec4 a = getMatrixA(batchA, ${d});
vec4 b = getMatrixB(batchB, ${c});
// These swizzled products need to be separately added.
// See: https://github.com/tensorflow/tfjs/issues/1735
result += (${h[0]} * ${m[0]});
result += (${h[1]} * ${m[1]});
}
return result;
}
void main() {
ivec3 rc = getOutputCoords();
vec4 result = dot2x2ARowBCol(rc);
${b}
${g}
setOutput(result);
}
`}},GI={REAL:"return areal * breal - aimag * bimag;",IMAG:"return areal * bimag + aimag * breal;"},HI=class{constructor(e,t,n){this.variableNames=["AReal","AImag","BReal","BImag"],this.outputShape=N.assertAndGetBroadcastShape(t,n),this.userCode=`
float binaryOpComplex(
float areal, float aimag, float breal, float bimag) {
${e}
}
void main() {
float areal = getARealAtOutCoords();
float aimag = getAImagAtOutCoords();
float breal = getBRealAtOutCoords();
float bimag = getBImagAtOutCoords();
setOutput(binaryOpComplex(areal, aimag, breal, bimag));
}
`}},qI="return a * b;";function K1(e){let{inputs:t,backend:n}=e,{a,b:r}=t,s=N.upcastType(a.dtype,r.dtype);if(a.dtype==="complex64"){let o=n.texData.get(a.dataId),l=n.texData.get(r.dataId),u=new HI(GI.REAL,a.shape,r.shape),p=new HI(GI.IMAG,a.shape,r.shape),d=[{dataId:o.complexTensorInfos.real.dataId,dtype:o.complexTensorInfos.real.dtype,shape:a.shape},{dataId:o.complexTensorInfos.imag.dataId,dtype:o.complexTensorInfos.imag.dtype,shape:a.shape},{dataId:l.complexTensorInfos.real.dataId,dtype:l.complexTensorInfos.real.dtype,shape:r.shape},{dataId:l.complexTensorInfos.imag.dataId,dtype:l.complexTensorInfos.imag.dtype,shape:r.shape}],c=n.runWebGLProgram(u,d,"float32"),h=n.runWebGLProgram(p,d,"float32"),m=Es({inputs:{real:c,imag:h},backend:n});return n.disposeIntermediateTensorInfo(c),n.disposeIntermediateTensorInfo(h),m}if(n.shouldExecuteOnCPU([a,r])){let o=n.texData.get(a.dataId),l=n.texData.get(r.dataId),[u,p]=o9(a.shape,r.shape,o.values,l.values,s),d=n.makeTensorInfo(p,s),c=n.texData.get(d.dataId);return c.values=u,d}let i;return G().getBool("WEBGL_PACK_BINARY_OPERATIONS")?i=new Nd(qI,a.shape,r.shape):i=new Gl(qI,a.shape,r.shape),n.runWebGLProgram(i,[a,r],s)}var cQ={kernelName:ho,backendName:"webgl",kernelFunc:K1};function dQ(e,t,n){let a=[xi(e.shape),...vi(e.shape)],r={dtype:e.dtype,shape:a,dataId:e.dataId},s=[xi(t),...vi(t)],i=new HE(s,a),o=!0,l=[a],u=n.runWebGLProgram(i,[r],e.dtype,l,o);return{dataId:u.dataId,shape:t,dtype:u.dtype}}function ce(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{shape:s}=a,i=n,o=v.sizeFromShape(r.shape),l=v.inferFromImplicitShape(s,o),u=v.sizeFromShape(l);v.assert(o===u,()=>`The new shape (${l}) has ${u} elements and the old shape (${r.shape}) has ${o} elements. The new shape and old shape must have the same number of elements.`);let p=i.texData.get(r.dataId);return p.isPacked&&!wc(r.shape,l)&&!(p.texture!==null&&wc(p.shape,l))?dQ(r,l,i):(i.incRef(r.dataId),{dataId:r.dataId,shape:l,dtype:r.dtype})}var hQ={kernelName:Fu,backendName:"webgl",kernelFunc:ce},jI=class{constructor(e,t){this.variableNames=["x"];let{windowSize:n,batchSize:a,inSize:r,outSize:s}=e;this.outputShape=[a,s];let i=Math.floor(n/4)*4,o=n%4,l="sumValue += dot(values, ones);";if(t!=null){let p=1/t;l=`sumValue += dot(values * ${v.isInt(p)?p.toPrecision(2):p}, ones);`}let u="";r%n>0&&(u=`
if (inIdx < 0 || inIdx >= ${r}) {
return 0.0;
}
`),this.userCode=`
const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);
float getValue(int batch, int inIdx) {
${u}
return getX(batch, inIdx);
}
void main() {
ivec2 coords = getOutputCoords();
int batch = coords[0];
int outIdx = coords[1];
int inOffset = outIdx * ${n};
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);
${l}
}
setOutput(sumValue);
}
`}},mQ=class{constructor(e,t){this.variableNames=["x"];let{windowSize:n,batchSize:a,inSize:r,outSize:s}=e;this.outputShape=[a,s];let i="0.0",o="";t==="prod"?i="1.0":t==="min"?(i="1.0 / 1e-20",o="min"):t==="max"&&(i="-1.0 / 1e-20",o="max");let l=`${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(n/4)*4,p=n%4,d=`
if (${t==="sum"}) {
sumValue += dot(values, ones);
} else if (${t==="prod"}) {
vec2 tmp = vec2(values[0], values[1]) * vec2(values[2], values[3]);
prodValue *= tmp[0] * tmp[1];
} else {
minMaxValue = ${o}(values, minMaxValue);
if (${t==="min"} || ${t==="max"}) {
minMaxValue = ${o}(values, minMaxValue);
bvec4 isNaN = isnan(values);
if (isNaN.r || isNaN.g || isNaN.b || isNaN.a) {
minMaxValue = vec4(NAN);
}
}
}
`,c="vec4";t==="all"?(i="1.0",d=`
bool reducedAllValue = all(values);
float floatedReducedAllValue = float(reducedAllValue);
allValue = float(allValue >= 1.0 && floatedReducedAllValue >= 1.0);
`,c="bvec4"):t==="any"&&(i="0.0",d=`
bool reducedAnyValue = any(values);
float floatedReducedAnyValue = float(reducedAnyValue);
anyValue = float(anyValue >= 1.0 || floatedReducedAnyValue >= 1.0);
`,c="bvec4");let h="";r%n>0&&(h=`
if (inIdx < 0 || inIdx >= ${r}) {
return initializationValue;
}
`),this.userCode=`
const float initializationValue = ${i};
const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);
float getValue(int batch, int inIdx) {
${h}
return getX(batch, inIdx);
}
void main() {
ivec2 coords = getOutputCoords();
int batch = coords[0];
int outIdx = coords[1];
int inOffset = outIdx * ${n};
vec4 minMaxValue = vec4(${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;
${c} values = ${c}(
getValue(batch, inIdx),
getValue(batch, inIdx + 1),
getValue(batch, inIdx + 2),
getValue(batch, inIdx + 3)
);
${d}
}
int inIdx = inOffset + ${u};
if (${p===1}) {
${c} values = ${c}(
getValue(batch, inIdx),
initializationValue,
initializationValue,
initializationValue
);
${d}
} else if (${p===2}) {
${c} values = ${c}(
getValue(batch, inIdx),
getValue(batch, inIdx + 1),
initializationValue,
initializationValue
);
${d}
} else if (${p===3}) {
${c} values = ${c}(
getValue(batch, inIdx),
getValue(batch, inIdx + 1),
getValue(batch, inIdx + 2),
initializationValue
);
${d}
}
setOutput(${l});
}
`}};function fQ(e){let t=[];for(;t.length===0||t[t.length-1].outSize!==1;){let n=t.length?t[t.length-1].outSize:e[1],a=N.computeOptimalWindowSize(n);t.push({inSize:n,windowSize:a,outSize:Math.ceil(n/a)})}return t}function Xo(e,t,n,a){let r=fQ(e.shape),s=e;for(let i=0;i<r.length;i++){let{inSize:o,windowSize:l,outSize:u}=r[i],p,d;n==="mean"?p=i===0?new jI({windowSize:l,inSize:o,batchSize:e.shape[0],outSize:u},o):new jI({windowSize:l,inSize:o,batchSize:e.shape[0],outSize:u}):p=new mQ({windowSize:l,inSize:o,batchSize:e.shape[0],outSize:u},n),d=s,s=a.runWebGLProgram(p,[s],t),d.dataId!==e.dataId&&a.disposeIntermediateTensorInfo(d)}return s}var gQ=class{constructor(e,t){this.variableNames=["A"];let n=new Array(e.length);for(let s=0;s<n.length;s++)n[s]=e[t[s]];this.outputShape=n,this.rank=n.length;let a=ct(this.rank),r=bQ(t);this.userCode=`
void main() {
${a} resRC = getOutputCoords();
setOutput(getA(${r}));
}
`}};function bQ(e){let t=e.length;if(t>6)throw Error(`Transpose for rank ${t} is not yet supported`);let n=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u","resRC.v"],a=new Array(t);for(let r=0;r<e.length;r++)a[e[r]]=n[r];return a.join()}var yQ=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0;let n=new Array(e.length);for(let u=0;u<n.length;u++)n[u]=e[t[u]];if(this.outputShape=n,this.rank=n.length,this.rank>6)throw Error(`Packed transpose for rank ${this.rank} is not yet supported.`);let a=ct(this.rank),r=GE("rc",this.rank),s=new Array(this.rank);for(let u=0;u<t.length;u++)s[t[u]]=r[u];let i=`vec2(${s.slice(-2).join()})`,o=`++${r[this.rank-1]} < ${n[this.rank-1]}`,l=`getChannel(getA(${s.join()}), ${i})`;this.userCode=`
void main() {
${a} rc = getOutputCoords();
vec4 result = vec4(0.);
result[0] = ${l};
if(${o}) {
result[1] = ${l};
}
--${r[this.rank-1]};
if(++${r[this.rank-2]} < ${n[this.rank-2]}) {
result[2] = ${l};
if(${o}) {
result[3] = ${l};
}
}
setOutput(result);
}
`}};function Lf(e,t,n){let a=G().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new yQ(e.shape,t):new gQ(e.shape,t);return n.runWebGLProgram(a,[e],e.dtype)}function xQ(e,t,n,a){let r=t,s=e.shape.length,i=v.parseAxisParam(r,e.shape),o=i,l=N.getAxesPermutation(o,s),u=l!=null,p=e;u&&(p=Lf(e,l,a),o=N.getInnerMostAxes(o.length,s)),N.assertAxesAreInnerMostDims("sum",o,s);let[d,c]=N.computeOutAndReduceShapes(p.shape,o),h=d;n&&(h=N.expandShapeToKeepDim(d,i));let m=v.sizeFromShape(c),f=v.sizeFromShape(e.shape)/m,g=ce({inputs:{x:p},attrs:{shape:[f,m]},backend:a}),b=Rm(e.dtype),y=Xo(g,b,"sum",a),x=ce({inputs:{x:y},attrs:{shape:h},backend:a});return a.disposeIntermediateTensorInfo(g),a.disposeIntermediateTensorInfo(y),u&&a.disposeIntermediateTensorInfo(p),x}function zf(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{axis:s,keepDims:i}=a;return xQ(r,s,i,n)}var vQ={kernelName:Do,backendName:"webgl",kernelFunc:zf};function Sn(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{perm:s}=a,i=n,o=r.shape.length,l=new Array(o);for(let p=0;p<l.length;p++)l[p]=r.shape[s[p]];let u;if(i.shouldExecuteOnCPU([r])){let p=i.texData.get(r.dataId).values,d=q1(p,r.shape,r.dtype,s,l);u=i.makeTensorInfo(l,r.dtype);let c=i.texData.get(u.dataId);c.values=d}else u=Lf(r,s,i);return u}var wQ={kernelName:_r,backendName:"webgl",kernelFunc:Sn},JE=1e3;function um({a:e,b:t,transposeA:n,transposeB:a,backend:r,bias:s=null,preluActivationWeights:i=null,leakyreluAlpha:o=0,activation:l=null}){let u=e.shape.length,p=t.shape.length,d=n?e.shape[u-2]:e.shape[u-1],c=a?t.shape[p-1]:t.shape[p-2],h=n?e.shape[u-1]:e.shape[u-2],m=a?t.shape[p-2]:t.shape[p-1],f=e.shape.slice(0,-2),g=t.shape.slice(0,-2),b=v.sizeFromShape(f),y=v.sizeFromShape(g),x=Yu.assertAndGetBroadcastShape(e.shape.slice(0,-2),t.shape.slice(0,-2)).concat([h,m]);v.assert(d===c,()=>`Error in matMul: inner shapes (${d}) and (${c}) of Tensors with shapes ${e.shape} and ${t.shape} and transposeA=${n} and transposeB=${a} must match.`);let w=n?[b,d,h]:[b,h,d],I=a?[y,m,c]:[y,c,m],T=ce({inputs:{x:e},backend:r,attrs:{shape:w}}),C=ce({inputs:{x:t},backend:r,attrs:{shape:I}}),E=[T,C],F=Math.max(b,y),D=n?T.shape[1]:T.shape[2],$=s!=null,S=i!=null,M=l==="leakyrelu",B=l!=null?kc(l,!0):null,U=$||S||M||B!=null,H;if((h===1||m===1)&&D>JE&&U===!1){let K=T,Z=C;n&&(K=Sn({inputs:{x:T},backend:r,attrs:{perm:[0,2,1]}}),E.push(K)),a&&(Z=Sn({inputs:{x:C},backend:r,attrs:{perm:[0,2,1]}}),E.push(Z));let J=m!==1,ee=m===1,ae=K;J&&(ae=ce({inputs:{x:K},backend:r,attrs:{shape:[F,D,1]}}),E.push(ae));let te=m===1?2:1,re=Z;ee&&(re=ce({inputs:{x:Z},backend:r,attrs:{shape:[F,1,D]}}),E.push(re));let se=K1({inputs:{a:ae,b:re},backend:r});H=zf({inputs:{x:se},backend:r,attrs:{axis:te,keepDims:!0}}),E.push(se)}else{let K=ga(e.dtype,t.dtype),Z=new ZE(w,I,[F,h,m],n,a,$,B,S,M),J=[T,C];if(s!=null&&J.push(s),S&&J.push(i),M){let ee=r.makeTensorInfo([],"float32",v.createScalarValue(o,"float32"));J.push(ee),E.push(ee)}H=r.runWebGLProgram(Z,J,K)}let j=ce({inputs:{x:H},backend:r,attrs:{shape:x}});E.push(H);for(let K of E)r.disposeIntermediateTensorInfo(K);return j}function kQ(e){let{inputs:t,backend:n,attrs:a}=e,{a:r,b:s,bias:i,preluActivationWeights:o}=t,{transposeA:l,transposeB:u,activation:p,leakyreluAlpha:d}=a;return um({a:r,b:s,transposeA:l,transposeB:u,backend:n,bias:i,preluActivationWeights:o,leakyreluAlpha:d,activation:p})}var IQ={kernelName:si,backendName:"webgl",kernelFunc:kQ},KI="return abs(x);";function SQ(e){let{inputs:t,backend:n}=e,{x:a}=t;if(n.shouldExecuteOnCPU([a])&&a.dtype!=="complex64"){let s=n.texData.get(a.dataId),i=VE(s.values);return n.makeTensorInfo(a.shape,a.dtype,i)}let r;return G().getBool("WEBGL_PACK_UNARY_OPERATIONS")?r=new ts(a.shape,KI):r=new rr(a.shape,KI),n.runWebGLProgram(r,[a],a.dtype)}var NQ={kernelName:ql,backendName:"webgl",kernelFunc:SQ},TQ=Ma+`
if (abs(x) > 1.) {
return NAN;
}
return acos(x);
`,CQ=Ye({opSnippet:TQ}),_Q={kernelName:Ii,backendName:"webgl",kernelFunc:CQ},EQ=Ma+`
if (x < 1.0) return NAN;
return log(x + sqrt(x * x - 1.0));`,AQ=Ye({opSnippet:EQ}),FQ={kernelName:Si,backendName:"webgl",kernelFunc:AQ},XI="return a + b;",$Q=mn({opSnippet:XI,packedOpSnippet:XI,supportsComplex:!0,cpuKernelImpl:BJ}),DQ={kernelName:bs,backendName:"webgl",kernelFunc:$Q},RQ=class{constructor(e,t){this.outputShape=[],this.outputShape=e,this.variableNames=t.map((r,s)=>`T${s}`);let n=[];this.variableNames.forEach(r=>{n.push(`float v${r} = get${r}AtOutCoords();`)});let a=this.variableNames.map(r=>`v${r}`).join(" + ");this.userCode=`
void main() {
${n.join(`
`)}
float result = ${a};
setOutput(result);
}
`}},MQ=class{constructor(e,t){this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.variableNames=t.map((r,s)=>`T${s}`);let n=[];this.variableNames.forEach(r=>{n.push(`vec4 v${r} = get${r}AtOutCoords();`)});let a=this.variableNames.map(r=>`v${r}`).join(" + ");this.userCode=`
void main() {
${n.join(`
`)}
vec4 result = ${a};
setOutput(result);
}
`}};function Ph(e){let{inputs:t,backend:n}=e,a=t;if(a.length===1)return aa({inputs:{x:a[0]},backend:n});if(a.length>G().get("WEBGL_MAX_TEXTURES_IN_SHADER")){let o=Math.floor(a.length/2),l=Ph({inputs:a.slice(0,o),backend:n}),u=Ph({inputs:a.slice(o),backend:n});return Ph({inputs:[l,u],backend:n})}let r=a.map(o=>o.dtype).reduce((o,l)=>ga(o,l)),s=a.map(o=>o.shape),i=G().getBool("WEBGL_PACK")?new MQ(a[0].shape,s):new RQ(a[0].shape,s);return n.runWebGLProgram(i,a,r)}var PQ={kernelName:Ni,backendName:"webgl",kernelFunc:Ph};function OQ(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{axis:s,keepDims:i}=a,o=r.shape.length,l=v.parseAxisParam(s,r.shape),u=l,p=N.getAxesPermutation(u,o),d=r;p!=null&&(d=Sn({inputs:{x:r},backend:n,attrs:{perm:p}}),u=N.getInnerMostAxes(u.length,o)),N.assertAxesAreInnerMostDims("all",u,o);let[c,h]=N.computeOutAndReduceShapes(d.shape,u),m=v.sizeFromShape(h),f=ce({inputs:{x:d},backend:n,attrs:{shape:[-1,m]}}),g=Xo(f,f.dtype,"all",n),b;if(i){let y=N.expandShapeToKeepDim(c,l);b=ce({inputs:{x:g},backend:n,attrs:{shape:y}})}else b=ce({inputs:{x:g},backend:n,attrs:{shape:c}});return n.disposeIntermediateTensorInfo(f),n.disposeIntermediateTensorInfo(g),p!=null&&n.disposeIntermediateTensorInfo(d),b}var LQ={kernelName:jl,backendName:"webgl",kernelFunc:OQ};function zQ(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{axis:s,keepDims:i}=a,o=r.shape.length,l=v.parseAxisParam(s,r.shape),u=l,p=N.getAxesPermutation(u,o),d=r;p!=null&&(d=Sn({inputs:{x:r},backend:n,attrs:{perm:p}}),u=N.getInnerMostAxes(u.length,o)),N.assertAxesAreInnerMostDims("any",u,o);let[c,h]=N.computeOutAndReduceShapes(d.shape,u),m=v.sizeFromShape(h),f=ce({inputs:{x:d},backend:n,attrs:{shape:[-1,m]}}),g=Xo(f,f.dtype,"any",n),b;if(i){let y=N.expandShapeToKeepDim(c,l);b=ce({inputs:{x:g},backend:n,attrs:{shape:y}})}else b=ce({inputs:{x:g},backend:n,attrs:{shape:c}});return n.disposeIntermediateTensorInfo(f),n.disposeIntermediateTensorInfo(g),p!=null&&n.disposeIntermediateTensorInfo(d),b}var WQ={kernelName:Kl,backendName:"webgl",kernelFunc:zQ},BQ=class{constructor(e,t,n){this.variableNames=["A"];let{windowSize:a,batchSize:r,outSize:s}=e;n||this.variableNames.push("bestIndicesA"),this.outputShape=[r,s];let i=t==="max"?">":"<",o=n?"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 * ${a};
int bestIndex = inOffset;
float bestValue = getA(batch, bestIndex);
for (int i = 0; i < ${a}; i++) {
int inIdx = ${o};
float candidate = getA(batch, inIdx);
if (candidate ${i} bestValue) {
bestValue = candidate;
bestIndex = inIdx;
}
}
setOutput(float(bestIndex));
}
`}},VQ=class{constructor(e,t,n,a){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,v.assert(e.length>2,()=>`Packed arg${n.charAt(0).toUpperCase()+n.slice(1)} supports only inputs with rank above 2.`);let r=e[e.length-1],s=Math.ceil(r/t);this.outputShape=e.slice(0,-1),s>1&&this.outputShape.push(s),a||this.variableNames.push("bestIndicesA");let i=this.outputShape,o=i.length,l=ct(o),u=In("coords",o),p,d;if(s===1){d=o+1;let C=ct(d);p=`
${C} sourceLocR = ${C}(${u.join()}, 0);
++${u[o-1]};
${C} sourceLocG = ${C}(${u.join()}, 0);
++${u[o-2]};
${C} sourceLocA = ${C}(${u.join()}, 0);
--${u[o-1]};
${C} sourceLocB = ${C}(${u.join()}, 0);
--${u[o-2]};`}else d=o,p=`
${l} sourceLocR = coords;
++${u[o-1]};
${l} sourceLocG = coords;
++${u[o-2]};
${l} sourceLocA = coords;
--${u[o-1]};
${l} sourceLocB = coords;
--${u[o-2]};`;let c=["x","y","z","w","u","v"].slice(0,d),h="."+c[d-1],m=c.map(C=>"int "+C),f=In("sourceLocR",d-1).concat("inIdx.r"),g=In("sourceLocG",d-1).concat("inIdx.g"),b=In("sourceLocB",d-1).concat("inIdx.b"),y=In("sourceLocA",d-1).concat("inIdx.a"),x=n==="max"?"greaterThan":"lessThan",w=a?"":`
inIdx = round(vec4(getBestIndicesAChannel(${f.join()}),
getBestIndicesAChannel(${g.join()}),
getBestIndicesAChannel(${b.join()}),
getBestIndicesAChannel(${y.join()})));`,I=`vec4(
getAChannel(${f.join()}),
hasNextCol ? getAChannel(${g.join()}) : 0.,
hasNextRow ? getAChannel(${b.join()}) : 0.,
hasNextRow && hasNextCol ? getAChannel(${y.join()}) : 0.)`,T=a?"":`
float getBestIndicesAChannel(${m.join()}) {
return getChannel(getBestIndicesA(${c.join()}),
vec2(${c.slice(-2).join()}));
}`;this.userCode=`
float getAChannel(${m.join()}) {
return getChannel(getA(${c.join()}),
vec2(${c.slice(-2).join()}));
}
${T}
void main() {
${l} coords = getOutputCoords();
bool hasNextCol = ${u[o-1]} < ${i[o-1]-1};
bool hasNextRow = ${u[o-2]} < ${i[o-2]-1};
${p}
ivec4 srcIdx = ivec4(sourceLocR${h}, sourceLocG${h},
sourceLocB${h}, sourceLocA${h}) * ${t};
ivec4 inIdx = srcIdx;
vec4 bestIndex = vec4(inIdx);
vec4 bestValue = ${I};
for (int i = 0; i < ${t}; i++) {
inIdx = srcIdx;
${w}
vec4 candidate = ${I};
bvec4 nan = isnan(candidate);
bvec4 replace = bvec4(
vec4(${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 QE(e,t,n,a=null){let r=t.shape[0],s=t.shape[1];a!=null&&(r=a.shape[0],s=a.shape[1]);let i=N.computeOptimalWindowSize(s),o={windowSize:i,inSize:s,batchSize:r,outSize:Math.ceil(s/i)},l=new BQ(o,n,a==null),u=[t];a!=null&&u.push(a);let p=e.runWebGLProgram(l,u,"int32");if(p.shape[1]===1)return p;let d=QE(e,t,n,p);return e.disposeIntermediateTensorInfo(p),d}function eA(e,t,n,a=null){let r=a!=null?a.shape:t.shape,s=r[r.length-1],i=N.computeOptimalWindowSize(s),o=new VQ(r,i,n,a==null),l=a==null?[t]:[t,a],u=e.runWebGLProgram(o,l,"int32");if(u.shape.length===t.shape.length){let p=eA(e,t,n,u);return e.disposeIntermediateTensorInfo(u),p}return u}function tA(e,t,n,a){let r=[n];if(N.assertAxesAreInnerMostDims("arg"+a.charAt(0).toUpperCase()+a.slice(1),r,t.shape.length),!G().getBool("WEBGL_PACK_REDUCE")||t.shape.length<=2){let s=[],i=e.texData.get(t.dataId),o=i!==null&&i.isPacked,l=t;o&&(l=e.unpackTensor(t),s.push(l));let[u,p]=N.computeOutAndReduceShapes(l.shape,r),d=v.sizeFromShape(p),c=ce({inputs:{x:l},backend:e,attrs:{shape:[-1,d]}});s.push(c);let h=QE(e,c,a);s.push(h);let m=ce({inputs:{x:h},backend:e,attrs:{shape:u}});return s.forEach(f=>e.disposeIntermediateTensorInfo(f)),m}return eA(e,t,a)}function UQ(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{axis:s}=a,i=v.parseAxisParam(s,r.shape),o=N.getAxesPermutation(i,r.shape.length),l=r,u=[];o!=null&&(l=Sn({inputs:{x:r},backend:n,attrs:{perm:o}}),u.push(l),i=N.getInnerMostAxes(i.length,l.shape.length)),N.assertAxesAreInnerMostDims("argMax",[i[0]],l.shape.length);let p=tA(n,l,i[0],"max");return u.forEach(d=>n.disposeIntermediateTensorInfo(d)),p}var GQ={kernelName:Xl,backendName:"webgl",kernelFunc:UQ};function HQ(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{axis:s}=a,i=v.parseAxisParam(s,r.shape),o=N.getAxesPermutation(i,r.shape.length),l=r,u=[];o!=null&&(l=Sn({inputs:{x:r},backend:n,attrs:{perm:o}}),u.push(l),i=N.getInnerMostAxes(i.length,l.shape.length)),N.assertAxesAreInnerMostDims("argMin",[i[0]],l.shape.length);let p=tA(n,l,i[0],"min");return u.forEach(d=>n.disposeIntermediateTensorInfo(d)),p}var qQ={kernelName:Yl,backendName:"webgl",kernelFunc:HQ},jQ=Ma+`
if (abs(x) > 1.) {
return NAN;
}
return asin(x);
`,KQ=Ye({opSnippet:jQ}),XQ={kernelName:Ti,backendName:"webgl",kernelFunc:KQ},YQ=Ma+"return log(x + sqrt(x * x + 1.0));",ZQ=Ye({opSnippet:YQ}),JQ={kernelName:Ci,backendName:"webgl",kernelFunc:ZQ},QQ=Ma+`
return atan(x);
`,eee=Ye({opSnippet:QQ}),tee={kernelName:_i,backendName:"webgl",kernelFunc:eee},nee=j1+`
return atan(a, b);
`,aee=`
vec4 result = atan(a, b);
bvec4 isNaNA = isnan(a);
bvec4 isNaNB = isnan(b);
bvec4 isNaN = bvec4(isNaNA.x || isNaNB.x, isNaNA.y || isNaNB.y, isNaNA.z || isNaNB.z, isNaNA.w || isNaNB.w);
`+Ko+`
return result;
`,ree=mn({opSnippet:nee,packedOpSnippet:aee}),see={kernelName:Ai,backendName:"webgl",kernelFunc:ree},iee=Ma+`
if ((x < -1.0) || (x > 1.0)) return NAN;
return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,oee=Ye({opSnippet:iee}),lee={kernelName:Ei,backendName:"webgl",kernelFunc:oee},Ic=class{constructor(e,t,n,a=!1,r=!1){if(this.variableNames=["x"],t==="avg"&&n)throw new Error("Cannot compute positions for average pool.");let s=e.filterWidth,i=e.strideHeight,o=e.strideWidth,l=e.dilationHeight,u=e.dilationWidth,p=e.effectiveFilterHeight,d=e.effectiveFilterWidth,c=e.padInfo.top,h=e.padInfo.left;this.outputShape=e.outShape;let m=t==="avg",f=`((batch * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + d`,g=`(xR * ${e.inWidth} + xC) * ${e.inChannels} + d`,b="0.0";if(m||(b="-1.0 / 1e-20"),n){let C=">=";this.userCode=`
const ivec2 strides = ivec2(${i}, ${o});
const ivec2 pads = ivec2(${c}, ${h});
void main() {
ivec4 coords = getOutputCoords();
int batch = coords[0];
int d = coords[3];
ivec2 xRCCorner = coords.yz * strides - pads;
int xRCorner = xRCCorner.x;
int xCCorner = xRCCorner.y;
// max/min x(?, ?, d) to get y(yR, yC, d).
// ? = to be determined
float minMaxValue = 0.0;
float minMaxValueFound = 0.0;
int minMaxPosition = 0;
float avgValue = 0.0;
for (int wR = 0; wR < ${p};
wR += ${l}) {
int xR = xRCorner + wR;
if (xR < 0 || xR >= ${e.inHeight}) {
continue;
}
for (int wC = 0; wC < ${d};
wC += ${u}) {
int xC = xCCorner + wC;
if (xC < 0 || xC >= ${e.inWidth}) {
continue;
}
float value = getX(batch, xR, xC, d);
// If a min / max value has already been found, use it. If not,
// use the current value.
float currMinMaxValue = mix(
value, minMaxValue, minMaxValueFound);
if (value ${C} currMinMaxValue) {
minMaxValue = value;
minMaxValueFound = 1.0;
minMaxPosition = ${a?r?f:g:`wR * ${d} + wC`};
}
}
}
setOutput(float(minMaxPosition));
}
`;return}let y="max",x=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="avg"&&(x="avgValue / max(count, 1.0)");let w=Math.floor(s/4)*4,I=s%4,T=`
if (${m}) {
avgValue += dot(values, ones);
} else {
minMaxValue = ${y}(values, minMaxValue);
}
`;this.userCode=`
const ivec2 strides = ivec2(${i}, ${o});
const ivec2 pads = ivec2(${c}, ${h});
const float initializationValue = ${b};
const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);
float count = 0.0;
float getValue(int batch, int xR, int xC, int d) {
if (xC < 0 || xC >= ${e.inWidth}) {
return initializationValue;
}
count += 1.0;
return getX(batch, xR, xC, d);
}
void main() {
ivec4 coords = getOutputCoords();
int batch = coords[0];
int d = coords[3];
ivec2 xRCCorner = coords.yz * strides - pads;
int xRCorner = xRCCorner.x;
int xCCorner = xRCCorner.y;
// max/min x(?, ?, d) to get y(yR, yC, d).
// ? = to be determined
vec4 minMaxValue = vec4(${b});
float avgValue = 0.0;
count = 0.0;
for (int wR = 0; wR < ${p};
wR += ${l}) {
int xR = xRCorner + wR;
if (xR < 0 || xR >= ${e.inHeight}) {
continue;
}
for (int wC = 0; wC < ${w}; 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)
);
${T}
}
int xC = xCCorner + ${w};
if (${I===1}) {
vec4 values = vec4(
getValue(batch, xR, xC, d),
initializationValue,
initializationValue,
initializationValue
);
${T}
} else if (${I===2}) {
vec4 values = vec4(
getValue(batch, xR, xC, d),
getValue(batch, xR, xC + ${u}, d),
initializationValue,
initializationValue
);
${T}
} else if (${I===3}) {
vec4 values = vec4(
getValue(batch, xR, xC, d),
getValue(batch, xR, xC + ${u}, d),
getValue(batch, xR, xC + 2 * ${u}, d),
initializationValue
);
${T}
}
}
setOutput(${x});
}
`}},X1=class{constructor(e,t,n,a=!1,r=!1){if(this.variableNames=["x"],t==="avg"&&n)throw new Error("Cannot compute positions for average pool.");let s=e.filterWidth,i=e.strideDepth,o=e.strideHeight,l=e.strideWidth,u=e.dilationDepth,p=e.dilationHeight,d=e.dilationWidth,c=e.effectiveFilterDepth,h=e.effectiveFilterHeight,m=e.effectiveFilterWidth,f=e.padInfo.front,g=e.padInfo.top,b=e.padInfo.left;this.outputShape=e.outShape;let y=t==="avg",x="0.0";if(y||(x="-1.0 / 1e-20"),n){let F=">=";this.userCode=`
const ivec3 strides =
ivec3(${i}, ${o}, ${l});
const ivec3 pads = ivec3(${f}, ${g}, ${b});
void main() {
ivec5 coords = getOutputCoords();
int batch = coords.x;
int ch = coords.u;
ivec3 xCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;
int xDCorner = xCorner.x;
int xRCorner = xCorner.y;
int xCCorner = xCorner.z;
// max/min x(?, ?, ?, ch) to get y(yD, yR, yC, ch).
// ? = to be determined
float minMaxValue = 0.0;
float minMaxValueFound = 0.0;
int minMaxPosition = 0;
for (int wD = 0; wD < ${c};
wD += ${u}) {
int xD = xDCorner + wD;
if (xD < 0 || xD >= ${e.inDepth}) {
continue;
}
for (int wR = 0; wR < ${h};
wR += ${p}) {
int xR = xRCorner + wR;
if (xR < 0 || xR >= ${e.inHeight}) {
continue;
}
for (int wC = 0; wC < ${m};
wC += ${d}) {
int xC = xCCorner + wC;
if (xC < 0 || xC >= ${e.inWidth}) {
continue;
}
float value = getX(batch, xD, xR, xC, ch);
// If a min / max value has already been found, use it. If not,
// use the current value.
float currMinMaxValue = mix(
value, minMaxValue, minMaxValueFound);
if (value ${F} currMinMaxValue) {
minMaxValue = value;
minMaxValueFound = 1.0;
minMaxPosition = ${a?r?`(((batch * ${e.inDepth} + xD) * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + ch`:`((xD * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + ch`:`wD * ${h} * ${m} +
wR * ${m} + wC`};
}
}
}
}
setOutput(float(minMaxPosition));
}
`;return}let w="max",I=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="avg"&&(I="avgValue / max(count, 1.0)");let T=Math.floor(s/4)*4,C=s%4,E=`
if (${y}) {
avgValue += dot(values, ones);
} else {
minMaxValue = ${w}(values, minMaxValue);
}
`;this.userCode=`
const ivec3 strides =
ivec3(${i}, ${o}, ${l});
const ivec3 pads = ivec3(${f}, ${g}, ${b});
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 < ${c};
wD += ${u}) {
int xD = xDCorner + wD;
if (xD < 0 || xD >= ${e.inDepth}) {
continue;
}
for (int wR = 0; wR < ${h};
wR += ${p}) {
int xR = xRCorner + wR;
if (xR < 0 || xR >= ${e.inHeight}) {
continue;
}
for (int wC = 0; wC < ${T}; wC += 4) {
int xC = xCCorner + wC * ${d};
vec4 values = vec4(
getValue(batch, xD, xR, xC, ch),
getValue(batch, xD, xR, xC + ${d}, ch),
getValue(batch, xD, xR, xC + 2 * ${d}, ch),
getValue(batch, xD, xR, xC + 3 * ${d}, ch)
);
${E}
}
int xC = xCCorner + ${T};
if (${C===1}) {
vec4 values = vec4(
getValue(batch, xD, xR, xC, ch),
initializationValue,
initializationValue,
initializationValue
);
${E}
} else if (${C===2}) {
vec4 values = vec4(
getValue(batch, xD, xR, xC, ch),
getValue(batch, xD, xR, xC + ${d}, ch),
initializationValue,
initializationValue
);
${E}
} else if (${C===3}) {
vec4 values = vec4(
getValue(batch, xD, xR, xC, ch),
getValue(batch, xD, xR, xC + ${d}, ch),
getValue(batch, xD, xR, xC + 2 * ${d}, ch),
initializationValue
);
${E}
}
}
}
setOutput(${I});
}
`}};function uee(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t;ip(r,"avgPool");let{filterSize:s,strides:i,pad:o,dimRoundingMode:l}=a,u=1;v.assert(N.eitherStridesOrDilationsAreOne(i,u),()=>`Error in avgPool: Either strides or dilations must be 1. Got strides ${i} and dilations '${u}'`);let p=N.computePool2DInfo(r.shape,s,i,u,o,l);if(p.filterWidth===1&&p.filterHeight===1&&v.arraysEqual(p.inShape,p.outShape))return aa({inputs:{x:r},backend:n});let d=new Ic(p,"avg",!1);return n.runWebGLProgram(d,[r],"float32")}var pee={kernelName:Fi,backendName:"webgl",kernelFunc:uee};function cee(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{filterSize:s,strides:i,pad:o,dimRoundingMode:l,dataFormat:u}=a,p=[1,1,1],d=N.computePool3DInfo(r.shape,s,i,p,o,l,u),c=new X1(d,"avg",!1);return n.runWebGLProgram(c,[r],"float32")}var dee={kernelName:Zl,backendName:"webgl",kernelFunc:cee},hee=class{constructor(e){this.variableNames=["dy"],this.outputShape=e.inShape;let t=e.filterHeight,n=e.filterWidth,a=e.strideHeight,r=e.strideWidth,s=e.dilationHeight,i=e.dilationWidth,o=e.effectiveFilterHeight,l=e.effectiveFilterWidth,u=o-1-e.padInfo.top,p=l-1-e.padInfo.left,d=1/(t*n);this.userCode=`
const ivec2 pads = ivec2(${u}, ${p});
const float avgMultiplier = float(${d});
void main() {
ivec4 coords = getOutputCoords();
int b = coords[0];
int d = coords[3];
ivec2 dyRCCorner = coords.yz - pads;
int dyRCorner = dyRCCorner.x;
int dyCCorner = dyRCCorner.y;
// Convolve dy(?, ?, d) with pos mask(:, :, d) to get dx(xR, xC, d).
// ? = to be determined. : = across all values in that axis.
float dotProd = 0.0;
for (int wR = 0; wR < ${o};
wR += ${s}) {
float dyR = float(dyRCorner + wR) / ${a}.0;
if (dyR < 0.0 || dyR >= ${e.outHeight}.0 || fract(dyR) > 0.0) {
continue;
}
int idyR = int(dyR);
for (int wC = 0; wC < ${l};
wC+= ${i}) {
float dyC = float(dyCCorner + wC) / ${r}.0;
if (dyC < 0.0 || dyC >= ${e.outWidth}.0 ||
fract(dyC) > 0.0) {
continue;
}
int idyC = int(dyC);
float dyValue = getDy(b, idyR, idyC, d);
dotProd += dyValue * avgMultiplier;
}
}
setOutput(dotProd);
}
`}},mee=class{constructor(e){this.variableNames=["dy"],this.outputShape=e.inShape;let t=e.filterDepth,n=e.filterHeight,a=e.filterWidth,r=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=e.dilationDepth,l=e.dilationHeight,u=e.dilationWidth,p=e.effectiveFilterDepth,d=e.effectiveFilterHeight,c=e.effectiveFilterWidth,h=p-1-e.padInfo.front,m=d-1-e.padInfo.top,f=c-1-e.padInfo.left,g=1/(t*n*a);this.userCode=`
const ivec3 pads = ivec3(${h}, ${m}, ${f});
const float avgMultiplier = float(${g});
void main() {
ivec5 coords = getOutputCoords();
int batch = coords.x;
int ch = coords.u;
ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads;
int dyDCorner = dyCorner.x;
int dyRCorner = dyCorner.y;
int dyCCorner = dyCorner.z;
// Convolve dy(?, ?, ?, d) with pos mask(:, :, :, ch) to get
// dx(xD, xR, xC, ch).
// ? = to be determined. : = across all values in that axis.
float dotProd = 0.0;
for (int wD = 0; wD < ${p};
wD += ${o}) {
float dyD = float(dyDCorner + wD) / ${r}.0;
if (dyD < 0.0 || dyD >= ${e.outDepth}.0 || fract(dyD) > 0.0) {
continue;
}
int idyD = int(dyD);
for (int wR = 0; wR < ${d};
wR += ${l}) {
float dyR = float(dyRCorner + wR) / ${s}.0;
if (dyR < 0.0 || dyR >= ${e.outHeight}.0 ||
fract(dyR) > 0.0) {
continue;
}
int idyR = int(dyR);
for (int wC = 0; wC < ${c};
wC += ${u}) {
float dyC = float(dyCCorner + wC) / ${i}.0;
if (dyC < 0.0 || dyC >= ${e.outWidth}.0 ||
fract(dyC) > 0.0) {
continue;
}
int idyC = int(dyC);
float dyValue = getDy(batch, idyD, idyR, idyC, ch);
dotProd += dyValue * avgMultiplier;
}
}
}
setOutput(dotProd);
}
`}};function fee(e){let{inputs:t,backend:n,attrs:a}=e,{dy:r,input:s}=t,i=s,{filterSize:o,strides:l,pad:u,dimRoundingMode:p}=a,d=[1,1,1],c=N.computePool3DInfo(i.shape,o,l,d,u,p),h=new mee(c);return n.runWebGLProgram(h,[r],i.dtype)}var gee={kernelName:_c,backendName:"webgl",kernelFunc:fee};function bee(e){let{inputs:t,backend:n,attrs:a}=e,{dy:r,input:s}=t,i=s;ip([r,s],"avgPoolGrad");let{filterSize:o,strides:l,pad:u}=a,p=N.computePool2DInfo(i.shape,o,l,1,u),d=new hee(p);return n.runWebGLProgram(d,[r],i.dtype)}var yee={kernelName:bm,backendName:"webgl",kernelFunc:bee};function xee(e){let{inputs:t,backend:n,attrs:a}=e,{a:r,b:s}=t,{transposeA:i,transposeB:o}=a;return um({a:r,b:s,transposeA:i,transposeB:o,backend:n})}var vee={kernelName:$i,backendName:"webgl",kernelFunc:xee},wee=class{constructor(e,t,n,a,r,s){this.outputShape=[],this.variableNames=["x","mean","variance"],N.assertAndGetBroadcastShape(e,t),N.assertAndGetBroadcastShape(e,n);let i="0.0";a!=null&&(N.assertAndGetBroadcastShape(e,a),this.variableNames.push("offset"),i="getOffsetAtOutCoords()");let o="1.0";r!=null&&(N.assertAndGetBroadcastShape(e,r),this.variableNames.push("scale"),o="getScaleAtOutCoords()"),this.outputShape=e,this.userCode=`
void main() {
float x = getXAtOutCoords();
float mean = getMeanAtOutCoords();
float variance = getVarianceAtOutCoords();
float offset = ${i};
float scale = ${o};
float inv = scale * inversesqrt(variance + float(${s}));
setOutput(dot(vec3(x, -mean, offset), vec3(inv, inv, 1)));
}
`}},kee=class{constructor(e,t,n,a,r,s){this.packedInputs=!0,this.packedOutput=!0,this.variableNames=["x","mean","variance"],N.assertAndGetBroadcastShape(e,t),N.assertAndGetBroadcastShape(e,n);let i="vec4(0.0)";a!=null&&(N.assertAndGetBroadcastShape(e,a),this.variableNames.push("offset"),i="getOffsetAtOutCoords()");let o="vec4(1.0)";r!=null&&(N.assertAndGetBroadcastShape(e,r),this.variableNames.push("scale"),o="getScaleAtOutCoords()"),this.outputShape=e,this.userCode=`
void main() {
vec4 offset = ${i};
vec4 scale = ${o};
vec4 x = getXAtOutCoords();
vec4 mean = getMeanAtOutCoords();
vec4 variance = getVarianceAtOutCoords();
vec4 inv = scale * inversesqrt(variance + vec4(${s}));
setOutput((x - mean) * inv + offset);
}
`}},Iee=({inputs:e,backend:t,attrs:n})=>{let{x:a,mean:r,variance:s,offset:i,scale:o}=e;v.assert(r.shape.length===s.shape.length,()=>"Batch normalization gradient requires mean and variance to have equal ranks."),v.assert(i==null||r.shape.length===i.shape.length,()=>"Batch normalization gradient requires mean and offset to have equal ranks."),v.assert(o==null||r.shape.length===o.shape.length,()=>"Batch normalization gradient requires mean and scale to have equal ranks.");let{varianceEpsilon:l}=n;l==null&&(l=.001);let u=[a,r,s],p=null;i!=null&&(p=i.shape,u.push(i));let d=null;o!=null&&(d=o.shape,u.push(o));let c=G().getBool("WEBGL_PACK_NORMALIZATION")?new kee(a.shape,r.shape,s.shape,p,d,l):new wee(a.shape,r.shape,s.shape,p,d,l);return t.runWebGLProgram(c,u,u[0].dtype)},See={kernelName:Xi,backendName:"webgl",kernelFunc:Iee},Nee=class{constructor(e){this.variableNames=["source"],this.outputShape=e,this.rank=e.length;let t=ct(this.rank);this.customUniforms=[{name:"start",arrayIndex:this.rank,type:"int"}];let n=Tee(this.rank),a,r=e.map((s,i)=>`sourceLoc.${ev[i]} = start[${i}] + coords.${ev[i]};`);a=`
${t} sourceLoc;
${t} coords = getOutputCoords();
${r.join(`
`)}
`,this.userCode=`
void main() {
${a}
setOutput(getSource(${n}));
}
`}},ev=["x","y","z","w","u","v"];function Tee(e){if(e===1)return"sourceLoc";if(e<=6)return ev.slice(0,e).map(t=>"sourceLoc."+t).join(",");throw Error(`Slicing for rank ${e} is not yet supported`)}var Cee=class{constructor(e){this.variableNames=["source"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.rank=e.length,this.customUniforms=[{name:"start",arrayIndex:this.rank,type:"int"}];let t=ct(this.rank),n=In("coords",this.rank),a=In("sourceLoc",this.rank),r=this.rank===1?"sourceLoc":`vec2(${a.slice(-2).join()})`,s=`getChannel(getSource(${a.join()}), ${r})`,i=`
result.x = ${s};
if (++${n[this.rank-1]} < ${e[this.rank-1]}) {
++${a[this.rank-1]};
result.y = ${s};
--${a[this.rank-1]};
}
`,o=this.rank===1?"":`
--${n[this.rank-1]};
if (++${n[this.rank-2]} < ${e[this.rank-2]}) {
++${a[this.rank-2]};
result.z = ${s};
if (++${n[this.rank-1]} < ${e[this.rank-1]}) {
++${a[this.rank-1]};
result.w = ${s};
}
}
`,l=this.rank<=4?`sourceLoc = coords +
${t}(${e.map((u,p)=>`start[${p}]`).join()});`:e.map((u,p)=>`${a[p]} = ${n[p]} + start[${p}];`).join(`
`);this.userCode=`
void main() {
${t} coords = getOutputCoords();
${t} sourceLoc;
${l}
vec4 result = vec4(0.);
${i}
${o}
setOutput(result);
}
`}};function _ee(e,t,n,a){let r=a.texData.get(e.dataId),s=a.makeTensorInfo(n,e.dtype),i=a.texData.get(s.dataId);Object.assign(i,r),i.refCount=1,i.shape=n,i.dtype=e.dtype;let o=Kt.computeFlatOffset(t,v.computeStrides(e.shape));r.slice&&(o+=r.slice.flatOffset),i.slice={flatOffset:o,origDataId:r.slice&&r.slice.origDataId||e.dataId};let l=a.dataRefCount.get(i.slice.origDataId)||1;return a.dataRefCount.set(i.slice.origDataId,l+1),s}function dp(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{begin:s,size:i}=a,[o,l]=Kt.parseSliceParams(r,s,i);if(Kt.assertParamsValid(r,o,l),v.sizeFromShape(l)===0)return n.makeTensorInfo(l,r.dtype,[]);if(n.shouldExecuteOnCPU([r])||r.dtype==="string"){let d=n.texData.get(r.dataId),c=y9(d.values,o,l,r.shape,r.dtype);return n.makeTensorInfo(l,r.dtype,c)}let{isPacked:u}=n.texData.get(r.dataId),p=Kt.isSliceContinous(r.shape,o,l);if(u||!p){let d=G().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new Cee(l):new Nee(l),c=[o];return n.runWebGLProgram(d,[r],r.dtype,c)}return n.uploadToGPU(r.dataId),_ee(r,o,l,n)}var Eee={kernelName:Lu,backendName:"webgl",kernelFunc:dp},Aee=e=>{let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{blockShape:s,crops:i}=a;v.assert(r.shape.length<=4,()=>"batchToSpaceND for rank > 4 with a WebGL backend not implemented yet");let o=s.reduce((y,x)=>y*x),l=N.getReshaped(r.shape,s,o),u=N.getPermuted(l.length,s.length),p=N.getReshapedPermuted(r.shape,s,o),d=N.getSliceBeginCoords(i,s.length),c=N.getSliceSize(p,i,s.length),h=[],m=ce({inputs:{x:r},backend:n,attrs:{shape:l}}),f=Sn({inputs:{x:m},backend:n,attrs:{perm:u}}),g=ce({inputs:{x:f},backend:n,attrs:{shape:p}}),b=dp({inputs:{x:g},backend:n,attrs:{begin:d,size:c}});return h.push(m),h.push(f),h.push(g),h.forEach(y=>n.disposeIntermediateTensorInfo(y)),b},Fee={kernelName:Jl,backendName:"webgl",kernelFunc:Aee};function $ee(e){let{inputs:t,backend:n,attrs:a}=e,{x:r,weights:s}=t,{size:i}=a,o=n.readSync(r.dataId),l=n.readSync(s.dataId),u=BE(o,l,s.dtype,s.shape,i);return n.makeTensorInfo([i],s.dtype,u)}var Dee={kernelName:Ql,backendName:"webgl",kernelFunc:$ee};function Ree(e){let{inputs:t,backend:n}=e,{s0:a,s1:r}=t,s=n.readSync(a.dataId),i=n.readSync(r.dataId),o=N.assertAndGetBroadcastShape(Array.from(s),Array.from(i));return n.makeTensorInfo([o.length],"int32",Int32Array.from(o))}var Mee={kernelName:Ec,backendName:"webgl",kernelFunc:Ree},Pee="return float(a != b);",nA=mn({opSnippet:Pee,cpuKernelImpl:u9,dtype:"bool"}),Oee={kernelName:Nu,backendName:"webgl",kernelFunc:nA};function Td(e){let{inputs:t,backend:n}=e,{input:a}=t,r=n.texData.get(a.dataId);return aa({inputs:{x:r.complexTensorInfos.real},backend:n})}var Lee={kernelName:$m,backendName:"webgl",kernelFunc:Td},zee="return float(int(x));";function Wee(e,t){let n=new rr(e.shape,zee),a=t.runWebGLProgram(n,[e],"int32");return{dataId:a.dataId,shape:a.shape,dtype:a.dtype}}function tv(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{dtype:s}=a;if(s==="complex64"){if(r.dtype==="complex64")return aa({inputs:{x:r},backend:n});let i=Nt(r.shape),o=tv({inputs:{x:r},backend:n,attrs:{dtype:"float32"}}),l=Es({inputs:{real:o,imag:i},backend:n});return i.dispose(),n.disposeIntermediateTensorInfo(o),l}if(r.dtype==="complex64"){let i=Td({inputs:{input:r},backend:n}),o=tv({inputs:{x:i},backend:n,attrs:{dtype:s}});return n.disposeIntermediateTensorInfo(i),o}if(!v.hasEncodingLoss(r.dtype,s)){let i=aa({inputs:{x:r},backend:n});return{dataId:i.dataId,shape:i.shape,dtype:s}}if(n.shouldExecuteOnCPU([r])){let i=n.texData.get(r.dataId).values,[o,l,u]=UJ(i,r.shape,r.dtype,s);return n.makeTensorInfo(o,l,u)}if(s==="int32")return Wee(r,n);if(s==="bool"){let i=n.makeTensorInfo([],"bool",v.getTypedArrayFromDType("bool",1)),o=nA({inputs:{a:r,b:i},backend:n});return n.disposeIntermediateTensorInfo(i),o}throw new Error(`Error in Cast: failed to cast ${r.dtype} to ${s}`)}var Bee={kernelName:Di,backendName:"webgl",kernelFunc:tv},YI="return ceil(x);",Vee=Ye({opSnippet:YI,packedOpSnippet:YI,cpuKernelImpl:GJ}),Uee={kernelName:Ri,backendName:"webgl",kernelFunc:Vee},Gee=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));
}
`}},Hee=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 qee(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{clipValueMin:s,clipValueMax:i}=a,o;G().getBool("WEBGL_PACK_CLIP")?o=new Hee(r.shape):o=new Gee(r.shape);let l=[[s],[i]];return n.runWebGLProgram(o,[r],r.dtype,l)}var jee={kernelName:ys,backendName:"webgl",kernelFunc:qee},Kee=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 ZI(e,t){return{dataId:t.dataId,dtype:t.dtype,shape:e.shape}}function Xee(e){let{inputs:t,backend:n}=e,{x:a}=t,r=n.texData.get(a.dataId),s=new Kee(a.shape),i=[ZI(a,r.complexTensorInfos.real),ZI(a,r.complexTensorInfos.imag)];return n.runWebGLProgram(s,i,i[0].dtype)}var Yee={kernelName:Ac,backendName:"webgl",kernelFunc:Xee},Zee=class{constructor(e){this.outputShape=[],this.outputShape=N.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 n=[`if (yC < ${t[0]}) setOutput(getT0(yR, yC));`];for(let s=1;s<t.length;s++){let i=t[s-1];n.push(`else if (yC < ${t[s]}) setOutput(getT${s}(yR, yC-${i}));`)}let a=t.length,r=t[t.length-1];n.push(`else setOutput(getT${a}(yR, yC-${r}));`),this.userCode=`
void main() {
ivec2 coords = getOutputCoords();
int yR = coords.x;
int yC = coords.y;
${n.join(`
`)}
}
`}},Jee=class{constructor(e,t){this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[],this.outputShape=N.computeOutShape(e,t);let n=this.outputShape,a=n.length,r=ct(a),s=In("coords",a),i=["x","y","z","w","u","v"].slice(0,a);this.variableNames=e.map((m,f)=>`T${f}`);let o=new Array(e.length-1);o[0]=e[0][t];for(let m=1;m<o.length;m++)o[m]=o[m-1]+e[m][t];let l=i[t],u=i.slice(-2),p=i.join(),d=`if (${l} < ${o[0]}) {
return getChannel(
getT0(${p}), vec2(${u.join()}));
}`;for(let m=1;m<o.length;m++){let f=o[m-1];d+=`
if (${l} < ${o[m]} && ${l} >= ${o[m-1]}) {
return getChannel(
getT${m}(${Ch(i,l,f)}),
vec2(${Ch(u,l,f)}));
}`}let c=o.length,h=o[o.length-1];d+=`
return getChannel(
getT${c}(${Ch(i,l,h)}),
vec2(${Ch(u,l,h)}));`,this.userCode=`
float getValue(${i.map(m=>"int "+m)}) {
${d}
}
void main() {
${r} coords = getOutputCoords();
vec4 result = vec4(getValue(${s}), 0., 0., 0.);
${s[a-1]} = ${s[a-1]} + 1;
if (${s[a-1]} < ${n[a-1]}) {
result.g = getValue(${s});
}
${s[a-2]} = ${s[a-2]} + 1;
if (${s[a-2]} < ${n[a-2]}) {
result.a = getValue(${s});
}
${s[a-1]} = ${s[a-1]} - 1;
if (${s[a-2]} < ${n[a-2]} &&
${s[a-1]} < ${n[a-1]}) {
result.b = getValue(${s});
}
setOutput(result);
}
`}};function Ch(e,t,n){let a=e.indexOf(t);return e.map((r,s)=>s===a?`${r} - ${n}`:r).join()}function Wf(e){let{inputs:t,backend:n}=e,{input:a}=t,r=n.texData.get(a.dataId);return aa({inputs:{x:r.complexTensorInfos.imag},backend:n})}var Qee={kernelName:Tm,backendName:"webgl",kernelFunc:Wf};function nc(e,t,n){let a=e[0].dtype;if(a==="complex64"){let h=e.map(y=>Td({inputs:{input:y},backend:n})),m=e.map(y=>Wf({inputs:{input:y},backend:n})),f=nc(h,t,n),g=nc(m,t,n),b=Es({inputs:{real:f,imag:g},backend:n});return h.forEach(y=>n.disposeIntermediateTensorInfo(y)),m.forEach(y=>n.disposeIntermediateTensorInfo(y)),n.disposeIntermediateTensorInfo(f),n.disposeIntermediateTensorInfo(g),b}let r=n.shouldExecuteOnCPU(e);if(a==="string"&&(r=!0),r){let h=e.map(w=>{let I=[-1,v.sizeFromShape(w.shape.slice(t))];return ce({inputs:{x:w},backend:n,attrs:{shape:I}})}),m=h.map(w=>({vals:n.readSync(w.dataId),shape:w.shape})),f=N.computeOutShape(h.map(w=>w.shape),1),g=h[0].shape[0]===1,b=HJ(m,f,a,g),y=N.computeOutShape(e.map(w=>w.shape),t),x=n.makeTensorInfo(y,a,b);return h.forEach(w=>n.disposeIntermediateTensorInfo(w)),x}let s=e.filter(h=>v.sizeFromShape(h.shape)>0),i=G().getBool("WEBGL_PACK_ARRAY_OPERATIONS")&&s[0].shape.length>1;if(s.length===1){let h=i?new rr(e[0].shape,Yr):new ts(e[0].shape,Yr);return n.runWebGLProgram(h,e,a)}let o=G().getNumber("WEBGL_MAX_TEXTURES_IN_SHADER");if(s.length>o){let h=[];for(let f=0;f<s.length;f+=o){let g=s.slice(f,f+o);h.push(nc(g,t,n))}let m=nc(h,t,n);for(let f of h)n.disposeIntermediateTensorInfo(f);return m}if(i){let h=new Jee(s.map(m=>m.shape),t);return n.runWebGLProgram(h,s,a)}let{tensors2D:l,outShape:u}=ete(s,t,n),p=new Zee(l.map(h=>h.shape)),d=n.runWebGLProgram(p,l,a);l.forEach(h=>n.disposeIntermediateTensorInfo(h));let c=ce({inputs:{x:d},attrs:{shape:u},backend:n});return n.disposeIntermediateTensorInfo(d),c}function ete(e,t,n){let a=N.computeOutShape(e.map(r=>r.shape),t);return{tensors2D:e.map(r=>ce({inputs:{x:r},attrs:{shape:[-1,v.sizeFromShape(r.shape.slice(t))]},backend:n})),outShape:a}}function aA(e){let{inputs:t,backend:n,attrs:a}=e,{axis:r}=a,s=v.parseAxisParam(r,t[0].shape)[0],i=t.map(u=>u.shape);N.assertParamsConsistent(i,s);let o=N.computeOutShape(t.map(u=>u.shape),s);if(v.sizeFromShape(o)===0)return n.makeTensorInfo(o,t[0].dtype,[]);let l=t.filter(u=>v.sizeFromShape(u.shape)>0);return l.length===1?aa({inputs:{x:l[0]},backend:n}):nc(l,s,n)}var tte={kernelName:eu,backendName:"webgl",kernelFunc:aA},rA=class{constructor(e,t=!1,n=null,a=!1,r=!1){this.variableNames=["x","W"],this.outputShape=e.outShape;let s=e.padInfo.top,i=e.padInfo.left,o=e.strideHeight,l=e.strideWidth,u=e.dilationHeight,p=e.dilationWidth,d=e.filterHeight,c=e.filterWidth,h=Math.floor(e.inChannels/4)*4,m=e.inChannels%4,f=e.dataFormat==="channelsLast",g=f?1:2,b=f?2:3,y=f?3:1,x="",w="";n&&(a?x=`float activation(float a) {
float b = getPreluActivationWeightsAtOutCoords();
${n}
}`:r?x=`float activation(float a) {
float b = getLeakyreluAlphaAtOutCoords();
${n}
}`:x=`
float activation(float x) {
${n}
}
`,w="result = activation(result);");let I=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),a&&this.variableNames.push("preluActivationWeights"),r&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
${x}
const ivec2 strides = ivec2(${o}, ${l});
const ivec2 pads = ivec2(${s}, ${i});
void main() {
ivec4 coords = getOutputCoords();
int batch = coords[0];
int d2 = coords[${y}];
ivec2 xRCCorner =
ivec2(coords[${g}], coords[${b}]) * strides - pads;
int xRCorner = xRCCorner.x;
int xCCorner = xRCCorner.y;
// Convolve x(?, ?, d1) with w(:, :, d1, d2) to get y(yR, yC, d2).
// ? = to be determined. : = across all values in that axis.
float dotProd = 0.0;
for (int wR = 0; wR < ${d}; wR++) {
int xR = xRCorner + wR * ${u};
if (xR < 0 || xR >= ${e.inHeight}) {
continue;
}
for (int wC = 0; wC < ${c}; wC++) {
int xC = xCCorner + wC * ${p};
if (xC < 0 || xC >= ${e.inWidth}) {
continue;
}
for (int d1 = 0; d1 < ${h}; d1 += 4) {
vec4 wValues = vec4(
getW(wR, wC, d1, d2),
getW(wR, wC, d1 + 1, d2),
getW(wR, wC, d1 + 2, d2),
getW(wR, wC, d1 + 3, d2)
);
if (${f}) {
vec4 xValues = vec4(
getX(batch, xR, xC, d1),
getX(batch, xR, xC, d1 + 1),
getX(batch, xR, xC, d1 + 2),
getX(batch, xR, xC, d1 + 3)
);
dotProd += dot(xValues, wValues);
} else {
vec4 xValues = vec4(
getX(batch, d1, xR, xC),
getX(batch, d1 + 1, xR, xC),
getX(batch, d1 + 2, xR, xC),
getX(batch, d1 + 3, xR, xC)
);
dotProd += dot(xValues, wValues);
}
}
if (${m===1}) {
if (${f}) {
dotProd +=
getX(batch, xR, xC, ${h}) *
getW(wR, wC, ${h}, d2);
} else {
dotProd +=
getX(batch, ${h}, xR, xC) *
getW(wR, wC, ${h}, d2);
}
} else if (${m===2}) {
vec2 wValues = vec2(
getW(wR, wC, ${h}, d2),
getW(wR, wC, ${h} + 1, d2)
);
if (${f}) {
vec2 xValues = vec2(
getX(batch, xR, xC, ${h}),
getX(batch, xR, xC, ${h} + 1)
);
dotProd += dot(xValues, wValues);
} else {
vec2 xValues = vec2(
getX(batch, ${h}, xR, xC),
getX(batch, ${h} + 1, xR, xC)
);
dotProd += dot(xValues, wValues);
}
} else if (${m===3}) {
vec3 wValues = vec3(
getW(wR, wC, ${h}, d2),
getW(wR, wC, ${h} + 1, d2),
getW(wR, wC, ${h} + 2, d2)
);
if (${f}) {
vec3 xValues = vec3(
getX(batch, xR, xC, ${h}),
getX(batch, xR, xC, ${h} + 1),
getX(batch, xR, xC, ${h} + 2)
);
dotProd += dot(xValues, wValues);
} else {
vec3 xValues = vec3(
getX(batch, ${h}, xR, xC),
getX(batch, ${h} + 1, xR, xC),
getX(batch, ${h} + 2, xR, xC)
);
dotProd += dot(xValues, wValues);
}
}
}
}
float result = dotProd;
${I}
${w}
setOutput(result);
}
`}},nte=class{constructor(e){this.variableNames=["x","W"],this.outputShape=e.outShape;let t=e.padInfo.front,n=e.padInfo.top,a=e.padInfo.left,r=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=e.dilationDepth,l=e.dilationHeight,u=e.dilationWidth,p=e.filterDepth,d=e.filterHeight,c=e.filterWidth,h=Math.floor(e.inChannels/4)*4,m=e.inChannels%4;this.userCode=`
const ivec3 strides = ivec3(${r}, ${s}, ${i});
const ivec3 pads = ivec3(${t}, ${n}, ${a});
void main() {
ivec5 coords = getOutputCoords();
int batch = coords.x;
int d2 = coords.u;
ivec3 xFRCCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;
int xFCorner = xFRCCorner.x;
int xRCorner = xFRCCorner.y;
int xCCorner = xFRCCorner.z;
// Convolve x(?, ?, ?, d1) with w(:, :, :, d1, d2) to get
// y(yF, yR, yC, d2). ? = to be determined. : = across all
// values in that axis.
float dotProd = 0.0;
for (int wF = 0; wF < ${p}; wF++) {
int xF = xFCorner + wF * ${o};
if (xF < 0 || xF >= ${e.inDepth}) {
continue;
}
for (int wR = 0; wR < ${d}; wR++) {
int xR = xRCorner + wR * ${l};
if (xR < 0 || xR >= ${e.inHeight}) {
continue;
}
for (int wC = 0; wC < ${c}; wC++) {
int xC = xCCorner + wC * ${u};
if (xC < 0 || xC >= ${e.inWidth}) {
continue;
}
for (int d1 = 0; d1 < ${h}; d1 += 4) {
vec4 xValues = vec4(
getX(batch, xF, xR, xC, d1),
getX(batch, xF, xR, xC, d1 + 1),
getX(batch, xF, xR, xC, d1 + 2),
getX(batch, xF, xR, xC, d1 + 3)
);
vec4 wValues = vec4(
getW(wF, wR, wC, d1, d2),
getW(wF, wR, wC, d1 + 1, d2),
getW(wF, wR, wC, d1 + 2, d2),
getW(wF, wR, wC, d1 + 3, d2)
);
dotProd += dot(xValues, wValues);
}
if (${m===1}) {
dotProd +=
getX(batch, xF, xR, xC, ${h}) *
getW(wF, wR, wC, ${h}, d2);
} else if (${m===2}) {
vec2 xValues = vec2(
getX(batch, xF, xR, xC, ${h}),
getX(batch, xF, xR, xC, ${h} + 1)
);
vec2 wValues = vec2(
getW(wF, wR, wC, ${h}, d2),
getW(wF, wR, wC, ${h} + 1, d2)
);
dotProd += dot(xValues, wValues);
} else if (${m===3}) {
vec3 xValues = vec3(
getX(batch, xF, xR, xC, ${h}),
getX(batch, xF, xR, xC, ${h} + 1),
getX(batch, xF, xR, xC, ${h} + 2)
);
vec3 wValues = vec3(
getW(wF, wR, wC, ${h}, d2),
getW(wF, wR, wC, ${h} + 1, d2),
getW(wF, wR, wC, ${h} + 2, d2)
);
dotProd += dot(xValues, wValues);
}
}
}
}
setOutput(dotProd);
}
`}},sA=class{constructor(e,t=!1,n=null,a=!1,r=!1){this.variableNames=["x","W"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"pads",type:"ivec2"},{name:"strides",type:"ivec2"},{name:"dilations",type:"ivec2"},{name:"inDims",type:"ivec2"}],this.outputShape=e.outShape,this.enableShapeUniforms=vn(this.outputShape.length);let s=e.padInfo.left,i=e.strideWidth,o=e.dilationWidth,l=e.filterHeight,u=e.filterWidth,p=u,d=`
int xR; int xC; int xCOffset;
vec4 wTexel; vec4 previous; vec4 final;`;for(let f=0;f<u;f++)d+=`
vec4 xTexelC${f*2};
int xTexelC${f*2}Ready;
vec4 xTexelC${f*2+1};
int xTexelC${f*2+1}Ready;
vec4 xC${f};`;d+=`
for (int r = 0; r < ${l}; r++) {
for (int d1 = 0; d1 < ${e.inChannels}; d1 += 2) {
`;for(let f=0;f<u;f++)d+=`
xTexelC${f*2} = vec4(0.0);
xTexelC${f*2}Ready = 0;
xTexelC${f*2+1} = vec4(0.0);
xTexelC${f*2+1}Ready = 0;
xC${f} = vec4(0.0);`;d+=`
xR = xRCorner + r * dilations[0];
if (xR >=0 && xR < inDims[0]) {
`;for(let f=0;f<(p+1)/2;f++){let g=f*2;if(d+=`
xC = xCCorner + ${g*o};
`,i===1){if(g<u&&(s%2===1?(d+=`
xCOffset = xC + 1;
if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${g}Ready == 0) {
xTexelC${g} = getX(batch, xR, xCOffset, d1);
// Need to manually clear unused channels in case
// we're reading from recycled texture.
if (xCOffset + 1 >= inDims[1]) {
xTexelC${g}.zw = vec2(0.0);
}
xTexelC${g}Ready = 1;
}
`,o===1&&g>0?d+=`
xC${g} = vec4(xTexelC${g-2}.zw, xTexelC${g}.xy);
`:d+=`
xCOffset = xC + 1 - 2;
if (xCOffset >= 0 && xCOffset < inDims[1]) {
previous = getX(batch, xR, xCOffset, d1);
// Need to manually clear unused channels in case
// we're reading from recycled texture.
if (xCOffset + 1 >= inDims[1]) {
previous.zw = vec2(0.0);
}
xC${g} = vec4(previous.zw, xTexelC${g}.xy);
} else {
xC${g} = vec4(0.0, 0.0, xTexelC${g}.xy);
}
`):d+=`
if (xC >= 0 && xC < inDims[1] && xTexelC${g}Ready == 0) {
xTexelC${g} = getX(batch, xR, xC, d1);
if (xC + 1 >= inDims[1]) {
xTexelC${g}.zw = vec2(0.0);
}
xTexelC${g}Ready = 1;
}
xC${g} = xTexelC${g};
`,g+1<u)){let b=s%2===0?v.nearestLargerEven(o):o;o%2===0&&s%2===1||o%2!==0&&s%2!==1?(d+=`
xCOffset = xC + imod(pads[1], 2) + ${b};
if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${g+1}Ready == 0) {
xTexelC${g+1} = getX(batch, xR, xCOffset, d1);
// Need to manually clear unused channels in case
// we're reading from recycled texture.
if (xCOffset + 1 >= inDims[1]) {
xTexelC${g+1}.zw = vec2(0.0);
}
xTexelC${g+1}Ready = 1;
}
`,o>1?d+=`
xCOffset -= 2;
if (xCOffset >= 0 && xCOffset < inDims[1]) {
previous = getX(batch, xR, xCOffset, d1);
xC${g+1} = vec4(previous.zw, xTexelC${g+1}.xy);
} else {
xC${g+1} = vec4(0.0, 0.0, xTexelC${g+1}.xy);
}
`:d+=`
xC${g+1} = vec4(xTexelC${g}.zw, xTexelC${g+1}.xy);
`):b===1?d+=`
xC${g+1} = xTexelC${g};
`:d+=`
xCOffset = xC + ${b};
if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${g+1}Ready == 0) {
xTexelC${g+1} = getX(batch, xR, xCOffset, d1);
if (xCOffset + 1 >= inDims[1]) {
xTexelC${g+1}.zw = vec2(0.0);
}
xTexelC${g+1}Ready = 1;
}
xC${g+1} = xTexelC${g+1};
`}}else g<u&&(s%2===1?(d+=`
xCOffset = xC + 1 - strides[1];
if(xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${g}Ready == 0) {
xTexelC${g} = getX(batch, xR, xCOffset, d1);
// Need to manually clear unused channels in case
// we're reading from recycled texture.
if (xCOffset + 1 >= inDims[1]) {
xTexelC${g}.zw = vec2(0.0);
}
xTexelC${g}Ready = 1;
}
if(xC + 1 >= 0 && xC + 1 < inDims[1] && xTexelC${g+1}Ready == 0) {
xTexelC${g+1} = getX(batch, xR, xC + 1, d1);
// Need to manually clear unused channels in case
// we're reading from recycled texture.
if (xC + 2 >= inDims[1]) {
xTexelC${g+1}.zw = vec2(0.0);
}
xTexelC${g+1}Ready = 1;
}
xC${g} = vec4(xTexelC${g}.zw, xTexelC${g+1}.zw);
`,g+1<u&&(d+=`
final = vec4(0.0);
xCOffset = xC + 1 + strides[1];
if(xCOffset >= 0 && xCOffset < inDims[1]) {
final = getX(batch, xR, xCOffset, d1);
}
xC${g+1} = vec4(xTexelC${g+1}.xy, final.xy);
`)):(d+=`
if(xC >= 0 && xC < inDims[1] && xTexelC${g}Ready == 0) {
xTexelC${g} = getX(batch, xR, xC, d1);
if (xC + 1 >= inDims[1]) {
xTexelC${g}.zw = vec2(0.0);
}
xTexelC${g}Ready = 1;
}
xCOffset = xC + strides[1];
if(xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${g+1}Ready == 0) {
xTexelC${g+1} = getX(batch, xR, xCOffset, d1);
if (xCOffset + 1 >= inDims[1]) {
xTexelC${g+1}.zw = vec2(0.);
}
xTexelC${g+1}Ready = 1;
}
xC${g} = vec4(
xTexelC${g}.xy, xTexelC${g+1}.xy);
`,g+1<u&&(d+=`
xC${g+1} = vec4(xTexelC${g}.zw, xTexelC${g+1}.zw);
`)));g<u&&(d+=`
wTexel = getW(r, ${g}, d1, d2);
dotProd += xC${g}.xxzz * vec4(wTexel.xy, wTexel.xy);
if(d1 + 1 < ${e.inChannels}) {
dotProd += xC${g}.yyww * vec4(wTexel.zw, wTexel.zw);
}
`,g+1<u&&(d+=`
wTexel = getW(r, ${g+1}, d1, d2);
dotProd += xC${g+1}.xxzz * vec4(wTexel.xy, wTexel.xy);
if(d1 + 1 < ${e.inChannels}) {
dotProd += xC${g+1}.yyww * vec4(wTexel.zw, wTexel.zw);
}
`))}d+=`
}
`,d+=`
}
`,d+=`
}
`;let c="",h="";n&&(a?c=`vec4 activation(vec4 a) {
vec4 b = getPreluActivationWeightsAtOutCoords();
${n}
}`:r?c=`vec4 activation(vec4 a) {
vec4 b = getLeakyreluAlphaAtOutCoords();
${n}
}`:c=`vec4 activation(vec4 x) {
${n}
}`,h="result = activation(result);");let m=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),a&&this.variableNames.push("preluActivationWeights"),r&&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 xRCorner = xRCCorner.x;
int xCCorner = xRCCorner.y;
//intialize dotProd with a small epsilon seems to reduce GPU accuracy loss.
vec4 dotProd = vec4(0.000000000000001);
${d}
vec4 result = dotProd - vec4(0.000000000000001);
${m}
${h}
setOutput(result);
}
`}},ate=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=vn(this.outputShape.length);let{dataFormat:n}=t,a=_n(),r=n==="channelsLast",s=r?1:2,i=r?2:3,o=this.enableShapeUniforms?"if(blockIndex < outShape[2] && pos < outShape[1]) {":`if(blockIndex < ${e[2]} && pos < ${e[1]}) {`,l="";for(let u=0;u<=1;u++)for(let p=0;p<=1;p++)l+=`
blockIndex = rc.z + ${p};
pos = rc.y + ${u};
${o}
offsetY = int(blockIndex / outWidth) * stride[0] - pad[0];
d0 = offsetY + dilation[0] * (pos / itemsPerBlockRow);
if(d0 < inputShape[${s}] && d0 >= 0) {
// Use custom imod instead mod. On Intel GPU, mod may generate
// unexpected value.
// https://github.com/tensorflow/tfjs/issues/5447
offsetX = imod(blockIndex, outWidth) * stride[1] - pad[1];
d1 = offsetX + dilation[1] * (imod(pos, itemsPerBlockRow) /
inChannels);
if(d1 < inputShape[${i}] && d1 >= 0) {
ch = imod(pos, inChannels);
if (${r}) {
innerDims = vec2(d1, ch);
result[${u*2+p}] = getChannel(
getA(rc.x, d0, int(innerDims.x),
int(innerDims.y)), innerDims);
} else {
innerDims = vec2(d0, d1);
result[${u*2+p}] = getChannel(
getA(rc.x, ch, int(innerDims.x),
int(innerDims.y)), innerDims);
}
}
}
}
`;this.userCode=`
void main() {
ivec3 rc = getOutputCoords();
vec4 result = vec4(0);
int blockIndex, pos, offsetY, d0, offsetX, d1, ch;
vec2 innerDims;
${l}
${a.output} = result;
}
`}};function pm(e,t){let n=e.length;return n>=3?t?[...e.slice(0,-3),e[n-3]*e[n-2],e[n-1]]:[...e.slice(0,-3),e[n-3],e[n-2]*e[n-1]]:!t&&n===1&&e[0]>1?[e[0],1]:null}function iA({x:e,filter:t,convInfo:n,backend:a,bias:r=null,preluActivationWeights:s=null,leakyreluAlpha:i=0,activation:o=null}){let l=e.shape,u=a.texData.get(e.dataId),p=n.inChannels,d=l[0]*l[1]*l[2],c=n.outChannels,h=n.dataFormat==="channelsLast",m=!1,f=!1,g,b=[];if(s!=null){let y=pm(s.shape,h);y!=null&&(s=ce({inputs:{x:s},backend:a,attrs:{shape:y}}),b.push(s))}if(r!=null){let y=pm(r.shape,h);y!=null&&(r=ce({inputs:{x:r},backend:a,attrs:{shape:y}}),b.push(r))}if(!((d===1||c===1)&&p>JE)&&u.isPacked&&h&&u.texture!=null&&l[2]%2!==0&&v.arraysEqual(u.shape.slice(-3),l.slice(-3))){let y=l[0]*l[1]*(l[2]+1),x={dataId:e.dataId,shape:[1,y,n.inChannels],dtype:e.dtype},w=u.shape;u.shape=u.shape.slice(),u.shape[u.shape.length-2]++,v.assert(wc(u.shape,x.shape),()=>`packed reshape ${u.shape} to ${x.shape} isn't free`);let I=ce({inputs:{x:t},backend:a,attrs:{shape:[1,n.inChannels,n.outChannels]}});b.push(I);let T=um({a:x,b:I,backend:a,transposeA:m,transposeB:f,bias:r,activation:o,preluActivationWeights:s,leakyreluAlpha:i}),C=a.texData.get(T.dataId);v.assert(C.isPacked,()=>"batchMatMul result is expected to be packed"),u.shape=w,C.shape=n.outShape,g=aa({inputs:{x:T},backend:a}),g.shape=n.outShape,b.push(T)}else{let y=n.outHeight*n.outWidth,x=ce({inputs:{x:e},backend:a,attrs:{shape:h?[n.batchSize,y,n.inChannels]:[n.batchSize,n.inChannels,y]}}),w=ce({inputs:{x:t},backend:a,attrs:{shape:[1,n.inChannels,n.outChannels]}}),I=um({a:h?x:w,b:h?w:x,transposeA:!h,transposeB:f,backend:a,bias:r,activation:o,preluActivationWeights:s,leakyreluAlpha:i});g=ce({inputs:{x:I},backend:a,attrs:{shape:n.outShape}}),b.push(x),b.push(w),b.push(I)}for(let y of b)a.disposeIntermediateTensorInfo(y);return g}function oA({x:e,filter:t,convInfo:n,backend:a,bias:r=null,preluActivationWeights:s=null,leakyreluAlpha:i=0,activation:o=null}){let{filterWidth:l,filterHeight:u,inChannels:p,outWidth:d,outHeight:c,dataFormat:h}=n,m=h==="channelsLast",f=l*u*p,g=c*d,b=[n.batchSize,f,g],y=!0,x=!1,w=[];if(s!=null){let K=pm(s.shape,m);K!=null&&(s=ce({inputs:{x:s},backend:a,attrs:{shape:K}}),w.push(s))}if(r!=null){let K=pm(r.shape,m);K!=null&&(r=ce({inputs:{x:r},backend:a,attrs:{shape:K}}),w.push(r))}let I=ce({inputs:{x:t},backend:a,attrs:{shape:[1,f,v.sizeFromShape(t.shape)/f]}});w.push(I);let T=new ate(b,n),C=[e.shape,[n.padInfo.top,n.padInfo.left],[n.strideHeight,n.strideWidth],[n.dilationHeight,n.dilationWidth],[n.inChannels],[n.filterWidth*n.inChannels],[n.outWidth]],E=a.runWebGLProgram(T,[e],"float32",C),F=ce({inputs:{x:E},backend:a,attrs:{shape:b}});w.push(E),w.push(F);let D=r!=null,$=s!=null,S=o==="leakyrelu",M=o?kc(o,!0):null,B=new ZE(m?F.shape:I.shape,m?I.shape:F.shape,m?[n.batchSize,g,n.outChannels]:[n.batchSize,n.outChannels,g],y,x,D,M,$,S),U=m?[F,I]:[I,F];if(r&&U.push(r),$&&U.push(s),S){let K=a.makeTensorInfo([],"float32",v.createScalarValue(i,"float32"));U.push(K),w.push(K)}let H=a.runWebGLProgram(B,U,"float32"),j=ce({inputs:{x:H},backend:a,attrs:{shape:n.outShape}});w.push(H);for(let K of w)a.disposeIntermediateTensorInfo(K);return j}function rte(e){let{inputs:t,backend:n,attrs:a}=e,{x:r,filter:s}=t,{strides:i,pad:o,dataFormat:l,dilations:u,dimRoundingMode:p}=a,d=N.convertConv2DDataFormat(l),c=N.computeConv2DInfo(r.shape,s.shape,i,u,o,p,!1,d),h;if(c.filterHeight===1&&c.filterWidth===1&&c.dilationHeight===1&&c.dilationWidth===1&&c.strideHeight===1&&c.strideWidth===1&&(c.padInfo.type==="SAME"||c.padInfo.type==="VALID"))h=iA({x:r,filter:s,convInfo:c,backend:n});else if(c.strideWidth<=2&&d==="channelsLast"&&G().getBool("WEBGL_EXP_CONV")){let f=new sA(c),g=[[c.padInfo.top,c.padInfo.left],[c.strideHeight,c.strideWidth],[c.dilationHeight,c.dilationWidth],[c.inHeight,c.inWidth]];h=n.runWebGLProgram(f,[r,s],"float32",g)}else if(G().getBool("WEBGL_CONV_IM2COL"))h=oA({x:r,filter:s,convInfo:c,backend:n});else{let f=new rA(c);h=n.runWebGLProgram(f,[r,s],"float32")}let m=ce({inputs:{x:h},backend:n,attrs:{shape:c.outShape}});return n.disposeIntermediateTensorInfo(h),m}var ste={kernelName:Mi,backendName:"webgl",kernelFunc:rte},ite=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideHeight,n=e.strideWidth,a=e.padInfo.top,r=e.padInfo.left,s=e.dataFormat==="channelsLast";this.userCode=`
void main() {
ivec4 coords = getOutputCoords();
int wR = coords.x;
int wC = coords.y;
int d1 = coords.z;
int d2 = coords.w;
// Convolve x(?, ?, d1) with dy(:, :, d2) to get dw(wR, wC, d1, d2).
// ? = to be determined. : = across all values in that axis.
float dotProd = 0.0;
for (int b = 0; b < ${e.batchSize}; b++) {
for (int yR = 0; yR < ${e.outHeight}; yR++) {
int xR = wR + yR * ${t} - ${a};
if (xR < 0 || xR >= ${e.inHeight}) {
continue;
}
for (int yC = 0; yC < ${e.outWidth}; yC++) {
int xC = wC + yC * ${n} - ${r};
if (xC < 0 || xC >= ${e.inWidth}) {
continue;
}
${s?`float dyValue = getDy(b, yR, yC, d2);
float xValue = getX(b, xR, xC, d1);
dotProd += (xValue * dyValue);`:`float dyValue = getDy(b, d2, yR, yC);
float xValue = getX(b, d1, xR, xC);
dotProd += (xValue * dyValue);`}
}
}
}
setOutput(dotProd);
}
`}},ote=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterHeight,n=e.filterWidth,a=e.strideHeight,r=e.strideWidth,s=e.dataFormat==="channelsLast",i=t-1-e.padInfo.top,o=n-1-e.padInfo.left,l=s?1:2,u=s?2:3,p=s?3:1;this.userCode=`
const ivec2 pads = ivec2(${i}, ${o});
void main() {
ivec4 coords = getOutputCoords();
int batch = coords[0];
int d1 = coords[${p}];
ivec2 dyCorner = ivec2(coords[${l}], coords[${u}]) - pads;
int dyRCorner = dyCorner.x;
int dyCCorner = dyCorner.y;
// Convolve dy(?, ?, d2) with w(:, :, d1, d2) to compute dx(xR, xC, d1).
// ? = to be determined. : = across all values in that axis.
float dotProd = 0.0;
for (int wR = 0; wR < ${t}; wR++) {
float dyR = float(dyRCorner + wR) / ${a}.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 < ${n}; wC++) {
float dyC = float(dyCCorner + wC) / ${r}.0;
if (dyC < 0.0 || dyC >= ${e.outWidth}.0 ||
fract(dyC) > 0.0) {
continue;
}
int idyC = int(dyC);
int wCPerm = ${n} - 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);
}
`}},lte=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideDepth,n=e.strideHeight,a=e.strideWidth,r=e.padInfo.front,s=e.padInfo.top,i=e.padInfo.left;this.userCode=`
void main() {
ivec5 coords = getOutputCoords();
int wF = coords.x;
int wR = coords.y;
int wC = coords.z;
int d1 = coords.w;
int d2 = coords.u;
float dotProd = 0.0;
for (int b = 0; b < ${e.batchSize}; b++) {
for (int yF = 0; yF < ${e.outDepth}; yF++) {
int xF = wF + yF * ${t} - ${r};
if (xF < 0 || xF >= ${e.inDepth}) {
continue;
}
for (int yR = 0; yR < ${e.outHeight}; yR++) {
int xR = wR + yR * ${n} - ${s};
if (xR < 0 || xR >= ${e.inHeight}) {
continue;
}
for (int yC = 0; yC < ${e.outWidth}; yC++) {
int xC = wC + yC * ${a} - ${i};
if (xC < 0 || xC >= ${e.inWidth}) {
continue;
}
float dyValue = getDy(b, yF, yR, yC, d2);
float xValue = getX(b, xF, xR, xC, d1);
dotProd += (xValue * dyValue);
}
}
}
}
setOutput(dotProd);
}
`}},ute=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterDepth,n=e.filterHeight,a=e.filterWidth,r=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=t-1-e.padInfo.front,l=n-1-e.padInfo.top,u=a-1-e.padInfo.left;this.userCode=`
const ivec3 pads = ivec3(${o}, ${l}, ${u});
void main() {
ivec5 coords = getOutputCoords();
int batch = coords.x;
int d1 = coords.u;
ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads;
int dyFCorner = dyCorner.x;
int dyRCorner = dyCorner.y;
int dyCCorner = dyCorner.z;
float dotProd = 0.0;
for (int wF = 0; wF < ${t}; wF++) {
float dyF = float(dyFCorner + wF) / ${r}.0;
if (dyF < 0.0 || dyF >= ${e.outDepth}.0 || fract(dyF) > 0.0) {
continue;
}
int idyF = int(dyF);
int wFPerm = ${t} - 1 - wF;
for (int wR = 0; wR < ${n}; 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 = ${n} - 1 - wR;
for (int wC = 0; wC < ${a}; 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 = ${a} - 1 - wC;
for (int d2 = 0; d2 < ${e.outChannels}; d2++) {
float xValue = getDy(batch, idyF, idyR, idyC, d2);
float wValue = getW(wFPerm, wRPerm, wCPerm, d1, d2);
dotProd += xValue * wValue;
}
}
}
}
setOutput(dotProd);
}
`}};function pte(e){let{inputs:t,backend:n,attrs:a}=e,{x:r,dy:s}=t,{strides:i,pad:o,dataFormat:l,dimRoundingMode:u,filterShape:p}=a,d=N.convertConv2DDataFormat(l),c=N.computeConv2DInfo(r.shape,p,i,1,o,u,!1,d),h=new ite(c);return n.runWebGLProgram(h,[r,s],"float32")}var cte={kernelName:vm,backendName:"webgl",kernelFunc:pte},dte=class{constructor(e){this.variableNames=["dy","W"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"strides",type:"vec2"}],this.outputShape=e.inShape,this.enableShapeUniforms=vn(this.outputShape.length);let t=e.filterHeight,n=e.filterWidth,a=t-1-e.padInfo.top,r=n-1-e.padInfo.left;this.userCode=`
const ivec2 pads = ivec2(${a}, ${r});
void main() {
ivec4 coords = getOutputCoords();
int batch = coords[0];
int d1 = coords[3];
ivec2 dyCorner = ivec2(coords[1], coords[2]) - pads;
int dyRCorner = dyCorner.x;
int dyCCorner = dyCorner.y;
vec4 result = vec4(0.);
for (int wR = 0; wR < ${t}; wR++) {
float dyR = float(dyRCorner + wR) / strides[0];
if (dyR < 0.0 || dyR >= ${e.outHeight}.0 || fract(dyR) > 0.0) {
continue;
}
int idyR = int(dyR);
int wRPerm = ${t} - 1 - wR;
for (int wC = 0; wC < ${n}; wC++) {
int wCPerm = ${n} - 1 - wC;
float dyC = float(dyCCorner + wC) / strides[1];
bool idyCVal = (dyC >= 0.0) && (dyC < ${e.outWidth}.0)
&& (fract(dyC) == 0.0);
int idyC = int(dyC);
float dyC2 = float(dyCCorner + wC + 1) / strides[1];
bool idyCVal2 = (dyC2 >= 0.0) && (dyC2 < ${e.outWidth}.0)
&& (fract(dyC2) == 0.0);
int idyC2 = int(dyC2);
if (idyCVal && idyCVal2) {
for (int d2 = 0; d2 < ${e.outChannels}; d2 += 2) {
vec4 wValue = getW(wRPerm, wCPerm, d1, d2);
vec4 dySample = getDy(batch, idyR, idyC, d2);
vec4 dySample2 = (idyC / 2 == idyC2 / 2) ?
dySample : getDy(batch, idyR, idyC2, d2);
vec2 dyValue = mod(float(idyC), 2.) == 0. ?
dySample.xy : dySample.zw;
result.xy += vec2(dot(dyValue, wValue.xy),
dot(dyValue, wValue.zw));
dyValue = mod(float(idyC2), 2.) == 0. ?
dySample2.xy : dySample2.zw;
result.zw += vec2(dot(dyValue, wValue.xy),
dot(dyValue, wValue.zw));
}
} else if (idyCVal) {
for (int d2 = 0; d2 < ${e.outChannels}; d2 += 2) {
vec4 wValue = getW(wRPerm, wCPerm, d1, d2);
vec4 dySample = getDy(batch, idyR, idyC, d2);
vec2 dyValue = mod(float(idyC), 2.) == 0. ?
dySample.xy : dySample.zw;
result.xy += vec2(dot(dyValue, wValue.xy),
dot(dyValue, wValue.zw));
}
} else if (idyCVal2) {
for (int d2 = 0; d2 < ${e.outChannels}; d2 += 2) {
vec4 wValue = getW(wRPerm, wCPerm, d1, d2);
vec4 dySample = getDy(batch, idyR, idyC2, d2);
vec2 dyValue = mod(float(idyC2), 2.) == 0. ?
dySample.xy : dySample.zw;
result.zw += vec2(dot(dyValue, wValue.xy),
dot(dyValue, wValue.zw));
}
}
}
}
setOutput(result);
}
`}};function hte(e){let{inputs:t,backend:n,attrs:a}=e,{dy:r,filter:s}=t,{inputShape:i,strides:o,pad:l,dataFormat:u,dimRoundingMode:p}=a,d=N.convertConv2DDataFormat(u),c=N.computeConv2DInfo(i,s.shape,o,1,l,p,!1,d);if(G().getBool("WEBGL_PACK")&&d==="channelsLast"){let h=[[c.strideHeight,c.strideWidth]],m=new dte(c);return n.runWebGLProgram(m,[r,s],"float32",h)}else{let h=new ote(c);return n.runWebGLProgram(h,[r,s],"float32")}}var mte={kernelName:Pi,backendName:"webgl",kernelFunc:hte};function fte(e){let{inputs:t,backend:n,attrs:a}=e,{x:r,filter:s}=t,{strides:i,pad:o,dilations:l}=a,u=N.computeConv3DInfo(r.shape,s.shape,i,l,o),p=new nte(u);return n.runWebGLProgram(p,[r,s],"float32")}var gte={kernelName:Oi,backendName:"webgl",kernelFunc:fte};function bte(e){let{inputs:t,backend:n,attrs:a}=e,{x:r,dy:s}=t,{strides:i,pad:o,filterShape:l}=a,u=N.computeConv3DInfo(r.shape,l,i,1,o),p=new lte(u);return n.runWebGLProgram(p,[r,s],"float32")}var yte={kernelName:tu,backendName:"webgl",kernelFunc:bte};function xte(e){let{inputs:t,backend:n,attrs:a}=e,{dy:r,filter:s}=t,{pad:i,strides:o,inputShape:l}=a,u=N.computeConv3DInfo(l,s.shape,o,1,i),p=new ute(u);return n.runWebGLProgram(p,[r,s],"float32")}var vte={kernelName:nu,backendName:"webgl",kernelFunc:xte},wte=cp+`
return cos(x);
`,kte=`
vec4 result = cos(x);
bvec4 isNaN = isnan(x);
${Ko}
return result;
`,Ite=Ye({opSnippet:wte,packedOpSnippet:kte}),Ste={kernelName:Li,backendName:"webgl",kernelFunc:Ite},Nte=`
float e2x = exp(-x);
return (e2x + 1.0 / e2x) / 2.0;
`,Tte=Ye({opSnippet:Nte}),Cte={kernelName:zi,backendName:"webgl",kernelFunc:Tte},_te=class{constructor(e,t,n,a,r){this.variableNames=["Image","Boxes","BoxInd"],this.outputShape=[];let[s,i,o,l]=e,[u]=t,[p,d]=n;this.outputShape=[u,p,d,l];let c=a==="bilinear"?1:0,[h,m]=[`${i-1}.0`,`${o-1}.0`],[f,g,b]=p>1?[`${(i-1)/(p-1)}`,"(y2-y1) * height_ratio",`y1*${h} + float(y)*(height_scale)`]:["0.0","0.0",`0.5 * (y1+y2) * ${h}`],[y,x,w]=d>1?[`${(o-1)/(d-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(${y});
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 = ${b};
if( in_y < 0.0 || in_y > ${h} ) {
setOutput(float(${r}));
return;
}
float in_x = ${w};
if( in_x < 0.0 || in_x > ${m} ) {
setOutput(float(${r}));
return;
}
vec2 sourceFracIndexCR = vec2(in_x,in_y);
if(${c} == 1) {
// Compute the four integer indices.
ivec2 sourceFloorCR = ivec2(sourceFracIndexCR);
ivec2 sourceCeilCR = ivec2(ceil(sourceFracIndexCR));
float topLeft = getImage(b, sourceFloorCR.y, sourceFloorCR.x, d);
float bottomLeft = getImage(b, sourceCeilCR.y, sourceFloorCR.x, d);
float topRight = getImage(b, sourceFloorCR.y, sourceCeilCR.x, d);
float bottomRight = getImage(b, sourceCeilCR.y, sourceCeilCR.x, d);
vec2 fracCR = sourceFracIndexCR - vec2(sourceFloorCR);
float top = topLeft + (topRight - topLeft) * fracCR.x;
float bottom = bottomLeft + (bottomRight - bottomLeft) * fracCR.x;
float newValue = top + (bottom - top) * fracCR.y;
setOutput(newValue);
} else {
// Compute the coordinators of nearest neighbor point.
ivec2 sourceNearestCR = ivec2(floor(
sourceFracIndexCR + vec2(0.5,0.5)));
float newValue = getImage(b, sourceNearestCR.y, sourceNearestCR.x, d);
setOutput(newValue);
}
}
`}},Ete=e=>{let{inputs:t,backend:n,attrs:a}=e,{image:r,boxes:s,boxInd:i}=t,{cropSize:o,method:l,extrapolationValue:u}=a,p=new _te(r.shape,s.shape,o,l,u);return n.runWebGLProgram(p,[r,s,i],"float32")},Ate={kernelName:ru,backendName:"webgl",kernelFunc:Ete},Sc;(function(e){e.Prod="*",e.Sum="+"})(Sc||(Sc={}));var JI=class{constructor(e,t,n,a){this.op=e,this.outputShape=t,this.variableNames=["x"],this.customUniforms=[{name:"index",type:"float"}];let r=this.outputShape.length,s=this.op===Sc.Prod?"1.0":"0.0",i=n?s:`getX(${QI(r,"coords",this.op)})`,o=this.outputShape[this.outputShape.length-1],l="",u="";n?(l=a?`end != ${o-1}`:"end != 0",u=a?"end + 1":"end - 1"):(l=a?`end + pow2 < ${o}`:"end >= pow2",u=a?"end + pow2":"end - pow2"),this.userCode=`
void main() {
${ct(r)} coords = getOutputCoords();
int end = ${eS(r,"coords",this.op)};
float val = ${i};
int pow2 = int(pow(2.0, index));
if (${l}) {
int idx = ${u};
${eS(r,"coords",this.op)} = idx;
val ${this.op}= getX(${QI(r,"coords",this.op)});
}
setOutput(val);
}
`}};function QI(e,t,n){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 ${n} for rank ${e} is not yet supported`)}function eS(e,t,n){if(e===1)return`${t}`;if(e===2)return`${t}.y`;if(e===3)return`${t}.z`;if(e===4)return`${t}.w`;throw new Error(`Cumulative ${n} for rank ${e} is not yet supported`)}function lA(e,t,n,a,r,s){let i=t.shape.length,o=N.getAxesPermutation([a],i),l=t;o!=null&&(l=Sn({inputs:{x:t},backend:n,attrs:{perm:o}}));let u=N.getInnerMostAxes(1,i)[0];if(u!==i-1)throw new Error(`WebGL cumprod shader expects an inner-most axis=${t.shape.length-1} but got axis=${a}`);let p=l.shape[u],d=aa({inputs:{x:l},backend:n});for(let c=0;c<=Math.ceil(Math.log2(p))-1;c++){let h=new JI(e,l.shape,!1,s),m=[[c]],f=d;d=n.runWebGLProgram(h,[d],d.dtype,m),n.disposeIntermediateTensorInfo(f)}if(r){let c=new JI(e,l.shape,r,s),h=d;d=n.runWebGLProgram(c,[d],d.dtype),n.disposeIntermediateTensorInfo(h)}if(o!=null){let c=N.getUndoAxesPermutation(o),h=Sn({inputs:{x:d},backend:n,attrs:{perm:c}});return n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(l),h}return d}function Fte(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{axis:s,exclusive:i,reverse:o}=a;return lA(Sc.Prod,r,n,s,i,o)}var $te={kernelName:au,backendName:"webgl",kernelFunc:Fte};function Dte(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{axis:s,exclusive:i,reverse:o}=a;return lA(Sc.Sum,r,n,s,i,o)}var Rte={kernelName:Wi,backendName:"webgl",kernelFunc:Dte};function Mte(e){let{inputs:t,backend:n,attrs:a}=e,{x:r,weights:s}=t,{size:i,binaryOutput:o}=a;if(r.shape.length===1){let l=n.readSync(r.dataId),u=n.readSync(s.dataId),p=BE(l,u,s.dtype,s.shape,i);return n.makeTensorInfo([i],s.dtype,p)}else if(r.shape.length===2){let l=n.bufferSync(r),u=n.bufferSync(s),p=VJ(l,u,i,o);return n.makeTensorInfo(p.shape,s.dtype,p.values)}throw new Error(`Error in denseBincount: input must be at most rank 2, but got rank${r.shape.length}.`)}var Pte={kernelName:Fc,backendName:"webgl",kernelFunc:Mte},Ote=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=[],this.outputShape=e,this.blockSize=t,this.dataFormat=n,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 Lte(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{blockSize:s,dataFormat:i}=a,o=r.shape[0],l=i==="NHWC"?r.shape[1]:r.shape[2],u=i==="NHWC"?r.shape[2]:r.shape[3],p=i==="NHWC"?r.shape[3]:r.shape[1],d=l*s,c=u*s,h=p/(s*s),m=i==="NHWC"?[o,d,c,h]:[o,h,d,c],f=new Ote(m,s,i);return n.runWebGLProgram(f,[r],r.dtype)}var zte={kernelName:su,backendName:"webgl",kernelFunc:Lte},uA=class{constructor(e,t=!1,n=null,a=!1,r=!1){this.variableNames=["x","W"],this.customUniforms=[{name:"pads",type:"ivec2"},{name:"strides",type:"ivec2"},{name:"dilations",type:"ivec2"},{name:"inDims",type:"ivec2"}],this.outputShape=e.outShape,this.enableShapeUniforms=vn(this.outputShape.length);let s=e.filterHeight,i=e.filterWidth,o=e.outChannels/e.inChannels,l="",u="";n&&(a?l=`float activation(float a) {
float b = getPreluActivationWeightsAtOutCoords();
${n}
}`:r?l=`float activation(float a) {
float b = getLeakyreluAlphaAtOutCoords();
${n}
}`:l=`
float activation(float x) {
${n}
}
`,u="result = activation(result);");let p=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),a&&this.variableNames.push("preluActivationWeights"),r&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
${l}
void main() {
ivec4 coords = getOutputCoords();
int batch = coords.x;
ivec2 xRCCorner = coords.yz * strides - pads;
int d2 = coords.w;
int d1 = d2 / ${o};
int q = d2 - d1 * ${o};
int xRCorner = xRCCorner.x;
int xCCorner = xRCCorner.y;
// Convolve x(?, ?, d1) with w(:, :, d1, q) to get y(yR, yC, d2).
// ? = to be determined. : = across all values in that axis.
float dotProd = 0.0;
// TO DO(dsmilkov): Flatten the two for loops and vec4 the operations.
for (int wR = 0; wR < ${s}; wR++) {
int xR = xRCorner + wR * dilations[0];
if (xR < 0 || xR >= inDims[0]) {
continue;
}
for (int wC = 0; wC < ${i}; wC++) {
int xC = xCCorner + wC * dilations[1];
if (xC < 0 || xC >= inDims[1]) {
continue;
}
float xVal = getX(batch, xR, xC, d1);
float wVal = getW(wR, wC, d1, q);
dotProd += xVal * wVal;
}
}
float result = dotProd;
${p}
${u}
setOutput(result);
}
`}},pA=class{constructor(e,t=!1,n=null,a=!1,r=!1){this.variableNames=["x","W"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"pads",type:"ivec2"},{name:"strides",type:"ivec2"},{name:"dilations",type:"ivec2"},{name:"inDims",type:"ivec2"}],this.outputShape=e.outShape,this.enableShapeUniforms=vn(this.outputShape.length);let s=e.outChannels/e.inChannels,i=e.padInfo.left,o=e.strideWidth,l=e.dilationWidth,u=e.filterHeight,p=e.filterWidth,d=p,c=`
int xR; int xC; int xCOffset;
vec4 wTexel; vec4 previous; vec4 final;`;for(let g=0;g<p;g++)c+=`
vec4 xTexelC${g*2};
int xTexelC${g*2}Ready;
vec4 xTexelC${g*2+1};
int xTexelC${g*2+1}Ready;
vec4 xC${g};`;c+=`
for (int r = 0; r < ${u}; r++) {
`;for(let g=0;g<p;g++)c+=`
xTexelC${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);`;c+=`
xR = xRCorner + r * dilations[0];
if (xR >=0 && xR < inDims[0]) {
`;for(let g=0;g<(d+1)/2;g++){let b=g*2;if(c+=`
xC = xCCorner + ${b*l};
`,o===1){if(b<p&&(i%2===1?(c+=`
xCOffset = xC + 1;
if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${b}Ready == 0) {
xTexelC${b} = getX(batch, xR, xCOffset, d1);
// Need to manually clear unused channels in case
// we're reading from recycled texture.
if (xCOffset + 1 >= inDims[1]) {
xTexelC${b}.zw = vec2(0.0);
}
xTexelC${b}Ready = 1;
}
`,l===1&&b>0?c+=`
xC${b} = vec4(xTexelC${b-2}.zw, xTexelC${b}.xy);
`:c+=`
xCOffset = xC + 1 - 2;
if (xCOffset >= 0 && xCOffset < inDims[1]) {
previous = getX(batch, xR, xCOffset, d1);
// Need to manually clear unused channels in case
// we're reading from recycled texture.
if (xCOffset + 1 >= inDims[1]) {
previous.zw = vec2(0.0);
}
xC${b} = vec4(previous.zw, xTexelC${b}.xy);
} else {
xC${b} = vec4(0.0, 0.0, xTexelC${b}.xy);
}
`):c+=`
if (xC >= 0 && xC < inDims[1] && xTexelC${b}Ready == 0) {
xTexelC${b} = getX(batch, xR, xC, d1);
if (xC + 1 >= inDims[1]) {
xTexelC${b}.zw = vec2(0.0);
}
xTexelC${b}Ready = 1;
}
xC${b} = xTexelC${b};
`,b+1<p)){let y=i%2===0?v.nearestLargerEven(l):l;l%2===0&&i%2===1||l%2!==0&&i%2!==1?(c+=`
xCOffset = xC + imod(pads[1], 2) + ${y};
if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${b+1}Ready == 0) {
xTexelC${b+1} = getX(batch, xR, xCOffset, d1);
// Need to manually clear unused channels in case
// we're reading from recycled texture.
if (xCOffset + 1 >= inDims[1]) {
xTexelC${b+1}.zw = vec2(0.0);
}
xTexelC${b+1}Ready = 1;
}
`,l>1?c+=`
xCOffset -= 2;
if (xCOffset >= 0 && xCOffset < inDims[1]) {
previous = getX(batch, xR, xCOffset, d1);
xC${b+1} = vec4(previous.zw, xTexelC${b+1}.xy);
} else {
xC${b+1} = vec4(0.0, 0.0, xTexelC${b+1}.xy);
}
`:c+=`
xC${b+1} = vec4(xTexelC${b}.zw, xTexelC${b+1}.xy);
`):y===1?c+=`
xC${b+1} = xTexelC${b};
`:c+=`
xCOffset = xC + ${y};
if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${b+1}Ready == 0) {
xTexelC${b+1} = getX(batch, xR, xCOffset, d1);
if (xCOffset + 1 >= inDims[1]) {
xTexelC${b+1}.zw = vec2(0.0);
}
xTexelC${b+1}Ready = 1;
}
xC${b+1} = xTexelC${b+1};
`}}else b<p&&(i%2===1?(c+=`
xCOffset = xC + 1 - strides[1];
if(xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${b}Ready == 0) {
xTexelC${b} = getX(batch, xR, xCOffset, d1);
// Need to manually clear unused channels in case
// we're reading from recycled texture.
if (xCOffset + 1 >= inDims[1]) {
xTexelC${b}.zw = vec2(0.0);
}
xTexelC${b}Ready = 1;
}
if(xC + 1 >= 0 && xC + 1 < inDims[1] && xTexelC${b+1}Ready == 0) {
xTexelC${b+1} = getX(batch, xR, xC + 1, d1);
// Need to manually clear unused channels in case
// we're reading from recycled texture.
if (xC + 2 >= inDims[1]) {
xTexelC${b+1}.zw = vec2(0.0);
}
xTexelC${b+1}Ready = 1;
}
xC${b} = vec4(xTexelC${b}.zw, xTexelC${b+1}.zw);
`,b+1<p&&(c+=`
final = vec4(0.0);
xCOffset = xC + 1 + strides[1];
if(xCOffset >= 0 && xCOffset < inDims[1]) {
final = getX(batch, xR, xCOffset, d1);
}
xC${b+1} = vec4(xTexelC${b+1}.xy, final.xy);
`)):(c+=`
if(xC >= 0 && xC < inDims[1] && xTexelC${b}Ready == 0) {
xTexelC${b} = getX(batch, xR, xC, d1);
if (xC + 1 >= inDims[1]) {
xTexelC${b}.zw = vec2(0.0);
}
xTexelC${b}Ready = 1;
}
xCOffset = xC + strides[1];
if(xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${b+1}Ready == 0) {
xTexelC${b+1} = getX(batch, xR, xCOffset, d1);
if (xCOffset + 1 >= inDims[1]) {
xTexelC${b+1}.zw = vec2(0.);
}
xTexelC${b+1}Ready = 1;
}
xC${b} = vec4(
xTexelC${b}.xy, xTexelC${b+1}.xy);
`,b+1<p&&(c+=`
xC${b+1} = vec4(xTexelC${b}.zw, xTexelC${b+1}.zw);
`)));b<p&&(c+=`
wTexel = getW(r, ${b}, d1, q);
dotProd += xC${b} * vec4(wTexel.xz, wTexel.xz);
`,b+1<p&&(c+=`
wTexel = getW(r, ${b+1}, d1, q);
dotProd += xC${b+1} * vec4(wTexel.xz, wTexel.xz);
`))}c+=`
}
`,c+=`
}
`;let h="",m="";n&&(a?h=`vec4 activation(vec4 a) {
vec4 b = getPreluActivationWeightsAtOutCoords();
${n}
}`:r?h=`vec4 activation(vec4 a) {
vec4 b = getLeakyreluAlphaAtOutCoords();
${n}
}`:h=`vec4 activation(vec4 x) {
${n}
}`,m="result = activation(result);");let f=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),a&&this.variableNames.push("preluActivationWeights"),r&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
${h}
void main() {
ivec4 coords = getOutputCoords();
int batch = coords.x;
ivec2 xRCCorner = coords.yz * strides - pads;
int d2 = coords.w;
int d1 = d2 / ${s};
int q = d2 - d1 * ${s};
int xRCorner = xRCCorner.x;
int xCCorner = xRCCorner.y;
//intialize dotProd with a small epsilon seems to reduce GPU accuracy loss.
vec4 dotProd = vec4(0.000000000000001);
${c}
vec4 result = dotProd - vec4(0.000000000000001);
${f}
${m}
setOutput(result);
}
`}};function Wte(e){let{inputs:t,backend:n,attrs:a}=e,{x:r,filter:s}=t,{strides:i,pad:o,dilations:l,dimRoundingMode:u}=a,p=l;p==null&&(p=[1,1]),v.assert(N.eitherStridesOrDilationsAreOne(i,p),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${i} and dilations '${p}'`);let d=N.computeConv2DInfo(r.shape,s.shape,i,p,o,u,!0),c;G().getBool("WEBGL_PACK_DEPTHWISECONV")&&d.strideWidth<=2&&d.outChannels/d.inChannels===1?c=new pA(d):c=new uA(d);let h=[[d.padInfo.top,d.padInfo.left],[d.strideHeight,d.strideWidth],[d.dilationHeight,d.dilationWidth],[d.inHeight,d.inWidth]];return n.runWebGLProgram(c,[r,s],"float32",h)}var Bte={kernelName:Bi,backendName:"webgl",kernelFunc:Wte},Vte=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideHeight,n=e.strideWidth,a=e.padInfo.top,r=e.padInfo.left,s=e.outChannels/e.inChannels;this.userCode=`
void main() {
ivec4 coords = getOutputCoords();
int wR = coords.x;
int wC = coords.y;
int d1 = coords.z;
int dm = coords.w;
int d2 = d1 * ${s} + dm;
float dotProd = 0.0;
// TO DO: Vec4 over the batch size
for (int b = 0; b < ${e.batchSize}; b++) {
for (int yR = 0; yR < ${e.outHeight}; yR++) {
int xR = wR + yR * ${t} - ${a};
if (xR < 0 || xR >= ${e.inHeight}) {
continue;
}
for (int yC = 0; yC < ${e.outWidth}; yC++) {
int xC = wC + yC * ${n} - ${r};
if (xC < 0 || xC >= ${e.inWidth}) {
continue;
}
float dyValue = getDy(b, yR, yC, d2);
float xValue = getX(b, xR, xC, d1);
dotProd += (xValue * dyValue);
}
}
}
setOutput(dotProd);
}
`}},Ute=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterHeight,n=e.filterWidth,a=e.strideHeight,r=e.strideWidth,s=t-1-e.padInfo.top,i=n-1-e.padInfo.left,o=e.outChannels/e.inChannels;this.userCode=`
const ivec2 pads = ivec2(${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) / ${a}.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 < ${n}; wC++) {
float dyC = float(dyCCorner + wC) / ${r}.0;
if (dyC < 0.0 || dyC >= ${e.outWidth}.0 ||
fract(dyC) > 0.0) {
continue;
}
int idyC = int(dyC);
int wCPerm = ${n} - 1 - wC;
// TO DO: Vec4 over the channelMul
for (int dm = 0; dm < ${o}; dm++) {
int d2 = d1 * ${o} + dm;
float xValue = getDy(batch, idyR, idyC, d2);
float wValue = getW(wRPerm, wCPerm, d1, dm);
dotProd += xValue * wValue;
}
}
}
setOutput(dotProd);
}
`}};function Gte(e){let{inputs:t,backend:n,attrs:a}=e,{x:r,dy:s}=t,{strides:i,dilations:o,pad:l,dimRoundingMode:u,filterShape:p}=a,d=N.computeConv2DInfo(r.shape,p,i,o,l,u,!0),c=new Vte(d);return n.runWebGLProgram(c,[r,s],"float32")}var Hte={kernelName:wm,backendName:"webgl",kernelFunc:Gte};function qte(e){let{inputs:t,backend:n,attrs:a}=e,{dy:r,filter:s}=t,{strides:i,dilations:o,pad:l,dimRoundingMode:u,inputShape:p}=a,d=N.computeConv2DInfo(p,s.shape,i,o,l,u,!0),c=new Ute(d);return n.runWebGLProgram(c,[r,s],"float32")}var jte={kernelName:km,backendName:"webgl",kernelFunc:qte},Kte=class{constructor(e){this.variableNames=["X"],this.outputShape=[e,e],this.userCode=`
void main() {
ivec2 coords = getOutputCoords();
float val = coords[0] == coords[1] ? getX(coords[0]) : 0.0;
setOutput(val);
}
`}};function Xte(e){let{inputs:t,backend:n}=e,{x:a}=t,r=[...a.shape,...a.shape],s=v.sizeFromShape(a.shape),i=ce({inputs:{x:a},backend:n,attrs:{shape:[s]}}),o=new Kte(s),l=n.runWebGLProgram(o,[i],i.dtype),u=ce({inputs:{x:l},backend:n,attrs:{shape:r}});return n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(l),u}var Yte={kernelName:$c,backendName:"webgl",kernelFunc:Xte},Zte=class{constructor(e){this.variableNames=["x","W"],this.outputShape=e.outShape;let{inHeight:t,inWidth:n,padInfo:a,strideHeight:r,strideWidth:s,filterHeight:i,filterWidth:o,dilationHeight:l,dilationWidth:u}=e,{top:p,left:d}=a;this.userCode=`
const ivec2 strides = ivec2(${r}, ${s});
const ivec2 pads = ivec2(${p}, ${d});
const float neg_infinity = -3.4e38;
void main() {
ivec4 coords = getOutputCoords();
int batch = coords.x;
int d1 = coords.w;
ivec2 outTopLeftCorner =
coords.yz * strides - pads;
int hBeg = outTopLeftCorner.x;
int wBeg = outTopLeftCorner.y;
float curVal = neg_infinity;
for (int h = 0; h < ${i}; h++) {
int hIn = hBeg + h * ${l};
if (hIn >= 0 && hIn < ${t}) {
for (int w = 0; w < ${o}; w++) {
int wIn = wBeg + w * ${u};
if (wIn >= 0 && wIn < ${n}) {
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 Jte(e){let{inputs:t,backend:n,attrs:a}=e,{x:r,filter:s}=t,{strides:i,pad:o,dilations:l}=a,u=N.computeDilation2DInfo(r.shape,s.shape,i,o,"NHWC",l),p,d=new Zte(u);p=n.runWebGLProgram(d,[r,s],"float32");let c=ce({inputs:{x:p},backend:n,attrs:{shape:u.outShape}});return n.disposeIntermediateTensorInfo(p),c}var Qte={kernelName:Vi,backendName:"webgl",kernelFunc:Jte};function ene(e){let{inputs:t,backend:n,attrs:a}=e,{equation:r}=a,s=t,{allDims:i,summedDims:o,idDims:l}=N.decodeEinsumEquation(r,s.length);N.checkEinsumDimSizes(i.length,l,s);let{path:u,steps:p}=N.getEinsumComputePath(o,l),d=p.length,c=null,h=i.length,m=[];for(let f=0;f<d;++f){for(let g of p[f]){let{permutationIndices:b,expandDims:y}=N.getEinsumPermutation(h,l[g]),x;N.isIdentityPermutation(b)?x=s[g]:(x=Sn({inputs:{x:s[g]},backend:n,attrs:{perm:b}}),m.push(x));let w=x.shape.slice();for(let I=0;I<y.length;++I)w.splice(y[I],0,1);v.arraysEqual(x.shape,w)||(x=ce({inputs:{x},backend:n,attrs:{shape:w}}),m.push(x)),c===null?c=x:(c=K1({inputs:{a:x,b:c},backend:n}),m.push(c))}f<d-1&&(u[f]>=0&&(c=zf({inputs:{x:c},backend:n,attrs:{axis:u[f]-(i.length-h),keepDims:!1}}),m.push(c)),h--)}for(let f of m)f!==c&&n.disposeIntermediateTensorInfo(f);return c}var tne={kernelName:Im,backendName:"webgl",kernelFunc:ene},nne="return (x >= 0.0) ? x : (exp(x) - 1.0);",ane=`
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;
`,rne=Ye({opSnippet:nne,packedOpSnippet:ane}),sne={kernelName:Gi,backendName:"webgl",kernelFunc:rne},ine="return (b >= 0.0) ? a : a * (b + 1.0);",one=`
vec4 bGTEZero = vec4(greaterThanEqual(b, vec4(0.)));
return (bGTEZero * a) + ((vec4(1.0) - bGTEZero) * (a * (b + vec4(1.0))));
`,lne=e=>{let{inputs:t,backend:n}=e,{dy:a,y:r}=t,s=G().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new Nd(one,a.shape,r.shape):new Gl(ine,a.shape,r.shape);return n.runWebGLProgram(s,[a,r],a.dtype)},une={kernelName:iu,backendName:"webgl",kernelFunc:lne},pne=`
return vec4(equal(a, b));
`,cne="return float(a == b);",dne=mn({opSnippet:cne,packedOpSnippet:pne,dtype:"bool",cpuKernelImpl:qJ}),hne={kernelName:lu,backendName:"webgl",kernelFunc:dne},mne=`
// Error function is calculated approximately with elementary function.
// See "Handbook of Mathematical Functions with Formulas,
// Graphs, and Mathematical Tables", Abramowitz and Stegun.
float p = ${N.ERF_P};
float a1 = ${N.ERF_A1};
float a2 = ${N.ERF_A2};
float a3 = ${N.ERF_A3};
float a4 = ${N.ERF_A4};
float a5 = ${N.ERF_A5};
float sign = sign(x);
x = abs(x);
float t = 1.0 / (1.0 + p * x);
return sign * (1.0 - (((((a5*t + a4)*t) + a3)*t + a2)*t + a1)*t*exp(-x*x));
`,fne=Ye({opSnippet:mne}),gne={kernelName:ou,backendName:"webgl",kernelFunc:fne},bne=cp+`
return exp(x);
`,yne=`
vec4 result = exp(x);
bvec4 isNaN = isnan(x);
result.r = isNaN.r ? x.r : result.r;
result.g = isNaN.g ? x.g : result.g;
result.b = isNaN.b ? x.b : result.b;
result.a = isNaN.a ? x.a : result.a;
return result;
`,cA=Ye({opSnippet:bne,packedOpSnippet:yne,cpuKernelImpl:jJ,dtype:"float32"}),xne={kernelName:Hi,backendName:"webgl",kernelFunc:cA};function nv(e){let{inputs:t,attrs:n,backend:a}=e,{dim:r}=n,{input:s}=t,i=s.shape.length,o=s.shape.slice(),l=r;return r<0&&(v.assert(-(i+1)<=r,()=>`Axis must be in the interval [${-(i+1)}, ${i}]`),l=i+r+1),o.splice(l,0,1),ce({inputs:{x:s},backend:a,attrs:{shape:o}})}var vne={kernelName:uu,backendName:"webgl",kernelFunc:nv},tS="return exp(x) - 1.0;",wne=Ye({opSnippet:tS,packedOpSnippet:tS,cpuKernelImpl:KJ}),kne={kernelName:qi,backendName:"webgl",kernelFunc:wne},nS=class{constructor(e,t,n){this.variableNames=["real","imag"];let a=t[1];this.outputShape=t;let r=n?`2.0 * ${Math.PI}`:`-2.0 * ${Math.PI}`,s=n?`${a}.0`:"1.0",i;if(e==="real")i="return real * expR - imag * expI;";else if(e==="imag")i="return real * expI + imag * expR;";else throw new Error(`FFT component must be either "real" or "imag", got ${e}.`);this.userCode=`
const float exponentMultiplier = ${r};
float unaryOpComplex(float real, float expR, float imag, float expI) {
${i}
}
float mulMatDFT(int batch, int index) {
float indexRatio = float(index) / float(${a});
float exponentMultiplierTimesIndexRatio =
exponentMultiplier * indexRatio;
float result = 0.0;
for (int i = 0; i < ${a}; 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 dA(e,t,n){let a=n.texData.get(e.dataId),r=v.sizeFromShape(e.shape),s=e.shape[e.shape.length-1],i=r/s,o=ce({inputs:{x:e},backend:n,attrs:{shape:[i,s]}}),l=o.shape,u=new nS("real",l,t),p=new nS("imag",l,t),d=[{dataId:a.complexTensorInfos.real.dataId,dtype:a.complexTensorInfos.real.dtype,shape:l},{dataId:a.complexTensorInfos.imag.dataId,dtype:a.complexTensorInfos.imag.dtype,shape:l}],c=n.runWebGLProgram(u,d,"float32"),h=n.runWebGLProgram(p,d,"float32"),m=Es({inputs:{real:c,imag:h},backend:n});n.disposeIntermediateTensorInfo(c),n.disposeIntermediateTensorInfo(h);let f=ce({inputs:{x:m},backend:n,attrs:{shape:e.shape}});return n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(m),f}function Ine(e){let{inputs:t,backend:n}=e,{input:a}=t;return dA(a,!1,n)}var Sne={kernelName:Sm,backendName:"webgl",kernelFunc:Ine},Nne=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 Cd(e){let{backend:t,attrs:n}=e,{shape:a,value:r}=n,{dtype:s}=n;if(s=s||v.inferDtype(r),s==="string"){let i=v.getArrayFromDType(s,v.sizeFromShape(a));return i.fill(r),t.makeTensorInfo(a,s,i)}else{let i=new Nne(a,r),o=[[r]];return t.runWebGLProgram(i,[],s,o)}}var Tne={kernelName:Dc,backendName:"webgl",kernelFunc:Cd},Cne=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 < ${t}) {
outputValue = getImage(coords[0], coords[1], coordX, coords[3]);
} else {
outputValue = getImage(coords[0], coords[1], coords[2], coords[3]);
}
setOutput(outputValue);
}
`}},_ne={kernelName:pu,backendName:"webgl",kernelFunc:({inputs:e,backend:t})=>{let{image:n}=e,a=t,r=new Cne(n.shape);return a.runWebGLProgram(r,[n],n.dtype)}},aS="return floor(x);",Ene=Ye({opSnippet:aS,packedOpSnippet:aS,cpuKernelImpl:XJ}),Ane={kernelName:ji,backendName:"webgl",kernelFunc:Ene},Fne=`
float s = sign(a) * sign(b);
int ia = round(a);
int ib = round(b);
if (ib != 0) {
// Windows (D3D) wants guaranteed non-zero int division at compile-time.
return float(idiv(ia, ib, s));
} else {
return NAN;
}
`,$ne=`
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);
`,Dne=mn({opSnippet:Fne,packedOpSnippet:$ne,dtype:"int32"}),Rne={kernelName:Ki,backendName:"webgl",kernelFunc:Dne},Mne=class{constructor(e){this.variableNames=["A"];let t=_n(),[n,a]=e;this.outputShape=e,this.userCode=`
void main() {
ivec3 coords = getOutputCoords();
int texR = coords[0];
int texC = coords[1];
int depth = coords[2];
vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${a}.0, ${n}.0);
vec4 values = ${t.texture2D}(A, uv);
float value;
if (depth == 0) {
value = values.r;
} else if (depth == 1) {
value = values.g;
} else if (depth == 2) {
value = values.b;
} else if (depth == 3) {
value = values.a;
}
setOutput(floor(value * 255.0 + 0.5));
}
`}},Pne=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0;let t=_n(),[n,a]=e;this.outputShape=e,this.userCode=`
void main() {
ivec3 coords = getOutputCoords();
int texR = coords[0];
int texC = coords[1];
int depth = coords[2];
vec4 result = vec4(0.);
for(int row=0; row<=1; row++) {
for(int col=0; col<=1; col++) {
texC = coords[1] + row;
depth = coords[2] + col;
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${a}.0, ${n}.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);
}
}
${t.output} = result;
}
`}},One={kernelName:Wh,backendName:"webgl",kernelFunc:Lne},bl,ux=G().getBool("CANVAS2D_WILL_READ_FREQUENTLY_FOR_GPU");function Lne(e){let{inputs:t,backend:n,attrs:a}=e,{pixels:r}=t,{numChannels:s}=a,i=typeof HTMLVideoElement!="undefined"&&r instanceof HTMLVideoElement,o=typeof HTMLImageElement!="undefined"&&r instanceof HTMLImageElement,[l,u]=i?[r.videoWidth,r.videoHeight]:[r.width,r.height],p=[u,l],d=[u,l,s];if(o||i){let f=G().getBool("CANVAS2D_WILL_READ_FREQUENTLY_FOR_GPU");(bl==null||f!==ux)&&(ux=f,bl=document.createElement("canvas").getContext("2d",{willReadFrequently:ux})),bl.canvas.width=l,bl.canvas.height=u,bl.drawImage(r,0,0,l,u),r=bl.canvas}let c=n.makeTensorInfo(p,"int32");n.texData.get(c.dataId).usage=da.PIXELS,n.gpgpu.uploadPixelDataToTexture(n.getTexture(c.dataId),r);let h=G().getBool("WEBGL_PACK")?new Pne(d):new Mne(d),m=n.runWebGLProgram(h,[c],"int32");return n.disposeData(c.dataId),m}function zne(e){let{inputs:t,backend:n,attrs:a}=e,{x:r,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:u,dataFormat:p,dilations:d,dimRoundingMode:c,activation:h,leakyreluAlpha:m}=a,f=N.convertConv2DDataFormat(p),g=N.computeConv2DInfo(r.shape,s.shape,l,d,u,c,!1,f),b,y=[],x=i!=null,w=o!=null,I=h==="leakyrelu",T=()=>{let E=[r,s],F=(D,$)=>{if($==="NCHW"&&D.shape.length===1&&D.shape[0]!==1){let S=ce({inputs:{x:D},backend:n,attrs:{shape:[D.shape[0],1,1]}});return y.push(S),S}return D};if(x&&E.push(F(i,p)),w&&E.push(F(o,p)),I){let D=n.makeTensorInfo([],"float32",v.createScalarValue(m,"float32"));E.push(D),y.push(D)}return E};if(g.filterHeight===1&&g.filterWidth===1&&g.dilationHeight===1&&g.dilationWidth===1&&g.strideHeight===1&&g.strideWidth===1&&(g.padInfo.type==="SAME"||g.padInfo.type==="VALID"))b=iA({x:r,filter:s,convInfo:g,backend:n,bias:i,activation:h,preluActivationWeights:o,leakyreluAlpha:m});else if(g.strideWidth<=2&&f==="channelsLast"&&G().getBool("WEBGL_EXP_CONV")){let E=h?kc(h,!0):null,F=new sA(g,x,E,w,I),D=[[g.padInfo.top,g.padInfo.left],[g.strideHeight,g.strideWidth],[g.dilationHeight,g.dilationWidth],[g.inHeight,g.inWidth]],$=T();b=n.runWebGLProgram(F,$,"float32",D)}else if(G().getBool("WEBGL_CONV_IM2COL"))b=oA({x:r,filter:s,convInfo:g,backend:n,bias:i,activation:h,preluActivationWeights:o,leakyreluAlpha:m});else{let E=h?kc(h,!1):null,F=new rA(g,x,E,w,I),D=T();b=n.runWebGLProgram(F,D,"float32")}let C=ce({inputs:{x:b},backend:n,attrs:{shape:g.outShape}});return y.push(b),y.forEach(E=>n.disposeIntermediateTensorInfo(E)),C}var Wne={kernelName:ii,backendName:"webgl",kernelFunc:zne};function Bne(e){let{inputs:t,backend:n,attrs:a}=e,{x:r,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:u,dilations:p,dimRoundingMode:d,activation:c,leakyreluAlpha:h}=a,m=[],f=p;f==null&&(f=[1,1]),v.assert(N.eitherStridesOrDilationsAreOne(l,f),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${l} and dilations '${f}'`);let g=N.computeConv2DInfo(r.shape,s.shape,l,f,u,d,!0),b=G().getBool("WEBGL_PACK_DEPTHWISECONV")&&g.strideWidth<=2&&g.outChannels/g.inChannels===1,y=c?kc(c,b):null,x=[r,s],w=i!=null,I=o!=null,T=c==="leakyrelu";if(w&&x.push(i),I&&x.push(o),T){let D=n.makeTensorInfo([],"float32",v.createScalarValue(h,"float32"));x.push(D),m.push(D)}let C;b?C=new pA(g,w,y,I,T):C=new uA(g,w,y,I,T);let E=[[g.padInfo.top,g.padInfo.left],[g.strideHeight,g.strideWidth],[g.dilationHeight,g.dilationWidth],[g.inHeight,g.inWidth]],F=n.runWebGLProgram(C,x,"float32",E);return m.forEach(D=>n.disposeIntermediateTensorInfo(D)),F}var Vne={kernelName:oi,backendName:"webgl",kernelFunc:Bne},Une=class{constructor(e,t,n,a){this.sliceDim=e,this.strides=t,this.paramsShape=a,this.variableNames=["x","indices"],this.outputShape=n;let r=ct(n.length),s=`
int index;`;for(let i=0;i<this.sliceDim;i++)s+=`
index = round(getIndices(coords[0], ${i}));
out_of_bounds = out_of_bounds || index < 0;
out_of_bounds = out_of_bounds || index >= ${this.paramsShape[i]};
flattenIndex += index * ${this.strides[i]};`;this.userCode=`
void main() {
${r} coords = getOutputCoords();
int flattenIndex = 0;
bool out_of_bounds = false;
${s}
setOutput(out_of_bounds ? 0.0 : getX(flattenIndex, coords[1]));
}
`}};function Gne(e){let{inputs:t,backend:n}=e,{params:a,indices:r}=t,s=r.shape,i=s[s.length-1],o=v.sizeFromShape(a.shape),[l,u,p,d]=N.prepareAndValidate(a,r),c=ce({inputs:{x:r},backend:n,attrs:{shape:[u,i]}}),h=ce({inputs:{x:a},backend:n,attrs:{shape:[v.sizeFromShape(a.shape)/p,p]}});if(n.shouldExecuteOnCPU([a,r])||a.dtype==="string"){let b=n.readSync(r.dataId),y=n.bufferSync(a),x=YJ(b,y,a.dtype,u,i,p,d,a.shape,o);return n.makeTensorInfo(l,a.dtype,x.values)}let m=new Une(i,d,[u,p],a.shape),f=n.runWebGLProgram(m,[h,c],h.dtype),g=ce({inputs:{x:f},backend:n,attrs:{shape:l}});return n.disposeIntermediateTensorInfo(c),n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(f),g}var Hne={kernelName:du,backendName:"webgl",kernelFunc:Gne},qne=class{constructor(e,t){this.variableNames=["A","indices"],this.outputShape=t,this.rank=t.length;let n=ct(this.rank),a=jne(e,2);this.userCode=`
void main() {
${n} resRC = getOutputCoords();
int index = int(getIndices(resRC.x, resRC.z));
float inBounds = (index >= 0) && (index < ${e[2]}) ? 1.0 : 0.0;
setOutput(inBounds * getA(${a}));
}
`}};function jne(e,t){let n=["resRC.x","resRC.y","resRC.z","resRC.w"],a=[];for(let r=0;r<e.length;r++)r===2?a.push("index"):a.push(`${n[r]}`);return a.join()}function hA(e){let{inputs:t,backend:n,attrs:a}=e,{x:r,indices:s}=t,{axis:i,batchDims:o}=a,l=v.parseAxisParam(i,r.shape)[0];if(G().get("DEBUG")){let y=n.readSync(s.dataId),x=r.shape[l];for(let w=0;w<y.length;++w){let I=y[w];v.assert(I<=x-1&&I>=0,()=>`GatherV2: the index value ${I} is not in [0, ${x-1}]`)}}let u=N.segment_util.collectGatherOpShapeInfo(r,s,l,o),p=v.sizeFromShape(s.shape),d=[],c=ce({inputs:{x:r},backend:n,attrs:{shape:[u.batchSize,u.outerSize,u.dimSize,u.sliceSize]}}),h=ce({inputs:{x:s},backend:n,attrs:{shape:[u.batchSize,p/u.batchSize]}});d.push(c),d.push(h);let m=[u.batchSize,u.outerSize,p/u.batchSize,u.sliceSize];if(n.shouldExecuteOnCPU([r,s])||r.dtype==="string"){let y=n.bufferSync(h),x=n.bufferSync(c),w=ZJ(x,y,m);return d.forEach(I=>n.disposeIntermediateTensorInfo(I)),n.makeTensorInfo(u.outputShape,w.dtype,w.values)}let f=new qne(c.shape,m),g=n.runWebGLProgram(f,[c,h],c.dtype);d.push(g);let b=ce({inputs:{x:g},backend:n,attrs:{shape:u.outputShape}});return d.forEach(y=>n.disposeIntermediateTensorInfo(y)),b}var Kne={kernelName:cu,backendName:"webgl",kernelFunc:hA},Xne="return float(a > b);",Yne=`
return vec4(greaterThan(a, b));
`,Zne=mn({opSnippet:Xne,packedOpSnippet:Yne,cpuKernelImpl:JJ,dtype:"bool"}),Jne={kernelName:hu,backendName:"webgl",kernelFunc:Zne},Qne="return float(a >= b);",eae=`
return vec4(greaterThanEqual(a, b));
`,tae=mn({opSnippet:Qne,packedOpSnippet:eae,dtype:"bool",cpuKernelImpl:QJ}),nae={kernelName:Yi,backendName:"webgl",kernelFunc:tae};function aae(e){let{inputs:t,backend:n}=e,{input:a}=t;return dA(a,!0,n)}var rae={kernelName:Nm,backendName:"webgl",kernelFunc:aae},sae="return float(!isnan(x) && !isinf(x));",iae=Ye({opSnippet:sae,dtype:"bool"}),oae={kernelName:Ji,backendName:"webgl",kernelFunc:iae},lae="return float(isinf(x));",uae=Ye({opSnippet:lae,dtype:"bool"}),pae={kernelName:Qi,backendName:"webgl",kernelFunc:uae},cae="return float(isnan(x));",dae=Ye({opSnippet:cae,dtype:"bool"}),hae={kernelName:eo,backendName:"webgl",kernelFunc:dae},mae="return float(a < b);",fae=`
return vec4(lessThan(a, b));
`,gae=mn({opSnippet:mae,packedOpSnippet:fae,cpuKernelImpl:e9,dtype:"bool"}),bae={kernelName:mu,backendName:"webgl",kernelFunc:gae},yae="return float(a <= b);",xae=`
return vec4(lessThanEqual(a, b));
`,vae=mn({opSnippet:yae,packedOpSnippet:xae,cpuKernelImpl:t9,dtype:"bool"}),wae={kernelName:fu,backendName:"webgl",kernelFunc:vae};function kae(e){let{backend:t,attrs:n}=e,{start:a,stop:r,num:s}=n,i=n9(a,r,s);return t.makeTensorInfo([i.length],"float32",i)}var Iae={kernelName:gu,backendName:"webgl",kernelFunc:kae},Sae=cp+`
return x < 0.0 ? 0./0. : log(x);
`,Nae=`
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;
`,Tae=Ye({opSnippet:Sae,packedOpSnippet:Nae,cpuKernelImpl:a9}),Cae={kernelName:no,backendName:"webgl",kernelFunc:Tae},_ae=cp+`
return log(1.0 + x);
`,Eae=Ye({opSnippet:_ae}),Aae={kernelName:ao,backendName:"webgl",kernelFunc:Eae},Fae="return float(a >= 1.0 && b >= 1.0);",$ae=`
return vec4(
vec4(greaterThanEqual(a, vec4(1.0))) *
vec4(greaterThanEqual(b, vec4(1.0))));
`,Dae=mn({opSnippet:Fae,packedOpSnippet:$ae,dtype:"bool"}),Rae={kernelName:bu,backendName:"webgl",kernelFunc:Dae},Mae="return float(!(x >= 1.0));",Pae=Ye({opSnippet:Mae}),Oae={kernelName:yu,backendName:"webgl",kernelFunc:Pae},Lae="return float(a >= 1.0 || b >= 1.0);",zae=`
return min(
vec4(greaterThanEqual(a, vec4(1.0))) +
vec4(greaterThanEqual(b, vec4(1.0))),
vec4(1.0));
`,Wae=mn({opSnippet:Lae,packedOpSnippet:zae,dtype:"bool"}),Bae={kernelName:xu,backendName:"webgl",kernelFunc:Wae},Vae=class{constructor(e,t,n,a,r){this.variableNames=["x"],this.outputShape=[];let s=t,i=e[3]-1;this.outputShape=e;let o,l=`float(${n}) + float(${a}) * sum`;r===.5?o=`inversesqrt(${l})`:r===1?o=`1.0/(${l})`:o=`exp(log(${l}) * float(-${r}));`,this.userCode=`
void main() {
ivec4 coords = getOutputCoords();
int b = coords[0];
int r = coords[1];
int c = coords[2];
int d = coords[3];
float x = getX(b, r, c, d);
float sum = 0.0;
for (int j = -${s}; j <= ${s}; j++) {
int idx = d + j;
if (idx >= 0 && idx <= ${i}) {
float z = getX(b, r, c, idx);
sum += z * z;
}
}
float val = x * ${o};
setOutput(val);
}
`}},Uae=class{constructor(e,t,n,a,r){this.variableNames=["x"],this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0;let s=t,i=e[3]-1;this.outputShape=e;let o,l=`float(${n}) + float(${a}) * sum`;r===.5?o=`inversesqrt(${l})`:r===1?o=`1.0/(${l})`:o=`exp(log(${l}) * float(-${r}));`,this.userCode=`
void main() {
ivec4 coords = getOutputCoords();
int b = coords.x;
int r = coords.y;
int c = coords.z;
int d = coords.w;
bool hasNextCol = d < ${this.outputShape[3]};
bool hasNextRow = c < ${this.outputShape[2]};
vec4 sum = vec4(0.);
vec4 xFragAtOutputCoords = getX(b, r, c, d);
vec4 xAtOutputCoords = vec4(
getChannel(xFragAtOutputCoords, vec2(c, d)),
hasNextCol ?
getChannel(xFragAtOutputCoords, vec2(c, d + 1)) : 0.0,
hasNextRow ?
getChannel(xFragAtOutputCoords , vec2(c + 1, d)) : 0.0,
(hasNextRow && hasNextCol) ?
getChannel(xFragAtOutputCoords, vec2(c + 1, d + 1)) : 0.0
);
int firstChannel = d - ${s};
vec2 cache = vec2(0.);
if(firstChannel >= 0){
vec4 firstChannelFrag = getX(b, r, c, firstChannel);
cache.x = getChannel(firstChannelFrag, vec2(c, firstChannel));
if(hasNextRow){
cache.y = getChannel(firstChannelFrag, vec2(c + 1, firstChannel));
}
}
ivec2 depth = ivec2(d, d + 1);
for (int j = - ${s}; j <= ${s}; j++) {
ivec2 idx = depth + j;
bvec2 aboveLowerBound = greaterThanEqual(idx, ivec2(0));
bvec2 belowUpperBound = lessThanEqual(idx, ivec2(${i}));
bool depthInRange = aboveLowerBound.x && belowUpperBound.x;
bool depthPlusOneInRange = aboveLowerBound.y && belowUpperBound.y;
if(depthInRange || depthPlusOneInRange){
vec4 z = vec4(0.);
vec4 xFragAtCurrentDepth;
z.xz = cache.xy;
if(depthPlusOneInRange && hasNextCol){
xFragAtCurrentDepth = idx.y != d ?
getX(b, r, c, idx.y) : xFragAtOutputCoords;
z.y = getChannel(xFragAtCurrentDepth, vec2(c, idx.y));
if(hasNextRow){
z.w = getChannel(xFragAtCurrentDepth, vec2(c + 1, idx.y));
}
}
cache.xy = z.yw;
sum += z * z;
}
}
vec4 result = xAtOutputCoords * ${o};
setOutput(result);
}
`}},Gae=e=>{let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{depthRadius:s,bias:i,alpha:o,beta:l}=a,u=G().getBool("WEBGL_PACK_NORMALIZATION")?new Uae(r.shape,s,i,o,l):new Vae(r.shape,s,i,o,l);return n.runWebGLProgram(u,[r],r.dtype)},Hae={kernelName:ro,backendName:"webgl",kernelFunc:Gae},qae=class{constructor(e,t,n,a,r){this.variableNames=["inputImage","outputImage","dy"],this.outputShape=[],this.outputShape=e,this.depth=e[3],this.depthRadius=t,this.bias=n,this.alpha=a,this.beta=r,this.userCode=`
void main() {
ivec4 coords = getOutputCoords();
int b = coords[0];
int r = coords[1];
int c = coords[2];
float result = 0.0;
for (int d = 0; d < ${this.depth}; ++d) {
int depthBegin = int(max(0.0, float(d - ${t})));
int depthEnd = int(min(float(${this.depth}),
float(d + ${t} + 1)));
const int MIN_DEPTH_BEGIN = 0;
const int MAX_DEPTH_END = ${this.depth};
float norm = 0.0;
for (int k = MIN_DEPTH_BEGIN; k < MAX_DEPTH_END; ++k) {
if (k < depthBegin){
continue;
}
else if (k >= depthBegin && k < depthEnd) {
norm += getInputImage(b, r, c, k) * getInputImage(b, r, c, k);
}
else {
break;
}
}
norm = float(${a}) * norm + float(${n});
for(int k = MIN_DEPTH_BEGIN; k < MAX_DEPTH_END; ++k){
if (k < depthBegin){
continue;
}
else if (k >= depthBegin && k < depthEnd){
float dyi = -2.0 * float(${a})
* float(${r})
* getInputImage(b, r, c, k) * getOutputImage(b, r, c, d)
/ norm;
if (k == d) {
dyi += pow(norm, -1.0 * ${r});
}
if (k == coords[3]) {
dyi *= getDy(b, r, c, d);
result += dyi;
}
}
else {
break;
}
}
}
setOutput(result);
}
`}},jae=e=>{let{inputs:t,backend:n,attrs:a}=e,{x:r,y:s,dy:i}=t,{depthRadius:o,bias:l,alpha:u,beta:p}=a,d=new qae(r.shape,o,l,u,p);return n.runWebGLProgram(d,[r,s,i],r.dtype)},Kae={kernelName:vu,backendName:"webgl",kernelFunc:jae};function Xae(e,t,n,a){let r=v.sizeFromShape(t),s=v.sizeFromShape(e.shape)/r,i=ce({inputs:{x:e},attrs:{shape:[s,r]},backend:a}),o=Xo(i,e.dtype,"max",a),l=ce({inputs:{x:o},attrs:{shape:n},backend:a});return a.disposeIntermediateTensorInfo(i),a.disposeIntermediateTensorInfo(o),l}function mA(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{reductionIndices:s,keepDims:i}=a,o=r.shape.length,l=v.parseAxisParam(s,r.shape),u=l,p=N.getAxesPermutation(u,o),d=p!=null,c=n.shouldExecuteOnCPU([r]),h=r;if(d){if(c){let y=n.texData.get(h.dataId).values,x=new Array(o);for(let T=0;T<x.length;T++)x[T]=r.shape[p[T]];let w=q1(y,r.shape,r.dtype,p,x);h=n.makeTensorInfo(x,r.dtype);let I=n.texData.get(h.dataId);I.values=w}else h=Lf(r,p,n);u=N.getInnerMostAxes(u.length,o)}N.assertAxesAreInnerMostDims("max",u,o);let[m,f]=N.computeOutAndReduceShapes(h.shape,u),g=m;i&&(g=N.expandShapeToKeepDim(m,l));let b;if(c){let y=n.texData.get(h.dataId).values,x=r9(y,v.sizeFromShape(f),g,r.dtype);b=n.makeTensorInfo(g,r.dtype);let w=n.texData.get(b.dataId);w.values=x}else b=Xae(h,f,g,n);return d&&n.disposeIntermediateTensorInfo(h),b}var Yae={kernelName:so,backendName:"webgl",kernelFunc:mA},Zae=j1+`
return max(a, b);
`,Jae=`
vec4 result = vec4(max(a, b));
bvec4 isNaNA = isnan(a);
bvec4 isNaNB = isnan(b);
bvec4 isNaN = bvec4(isNaNA.x || isNaNB.x, isNaNA.y || isNaNB.y, isNaNA.z || isNaNB.z, isNaNA.w || isNaNB.w);
`+Ko+`
return result;
`,Qae=mn({opSnippet:Zae,packedOpSnippet:Jae,cpuKernelImpl:s9}),ere={kernelName:io,backendName:"webgl",kernelFunc:Qae};function tre(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t;ip(r,"maxPool");let{filterSize:s,strides:i,pad:o,dimRoundingMode:l}=a,u=1;v.assert(N.eitherStridesOrDilationsAreOne(i,u),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${i} and dilations '${u}'`);let p=N.computePool2DInfo(r.shape,s,i,u,o,l);if(p.filterWidth===1&&p.filterHeight===1&&v.arraysEqual(p.inShape,p.outShape))return aa({inputs:{x:r},backend:n});let d=new Ic(p,"max",!1);return n.runWebGLProgram(d,[r],r.dtype)}var nre={kernelName:oo,backendName:"webgl",kernelFunc:tre};function are(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{filterSize:s,strides:i,pad:o,dataFormat:l,dimRoundingMode:u}=a,p=[1,1,1],d=N.computePool3DInfo(r.shape,s,i,p,o,u,l),c=new X1(d,"max",!1);return n.runWebGLProgram(c,[r],r.dtype)}var rre={kernelName:wu,backendName:"webgl",kernelFunc:are},sre=class{constructor(e){this.variableNames=["dy","maxPos"],this.outputShape=e.inShape;let t=e.strideHeight,n=e.strideWidth,a=e.dilationHeight,r=e.effectiveFilterHeight,s=e.effectiveFilterWidth,i=r-1-e.padInfo.top,o=s-1-e.padInfo.left,l=r*s-1;this.userCode=`
const ivec2 pads = ivec2(${i}, ${o});
void main() {
ivec4 coords = getOutputCoords();
int b = coords[0];
int d = coords[3];
ivec2 dyRCCorner = coords.yz - pads;
int dyRCorner = dyRCCorner.x;
int dyCCorner = dyRCCorner.y;
// Convolve dy(?, ?, d) with pos mask(:, :, d) to get dx(xR, xC, d).
// ? = to be determined. : = across all values in that axis.
float dotProd = 0.0;
for (int wR = 0; wR < ${r};
wR += ${a}) {
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) / ${n}.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 * ${s} + wC;
float mask = float(maxPosValue == curPosValue ? 1.0 : 0.0);
dotProd += dyValue * mask;
}
}
setOutput(dotProd);
}
`}},ire=class{constructor(e){this.variableNames=["dy","maxPos"],this.outputShape=e.inShape;let t=e.strideDepth,n=e.strideHeight,a=e.strideWidth,r=e.dilationDepth,s=e.dilationHeight,i=e.dilationWidth,o=e.effectiveFilterDepth,l=e.effectiveFilterHeight,u=e.effectiveFilterWidth,p=o-1-e.padInfo.front,d=l-1-e.padInfo.top,c=u-1-e.padInfo.left,h=o*l*u-1;this.userCode=`
const ivec3 pads = ivec3(${p}, ${d}, ${c});
void main() {
ivec5 coords = getOutputCoords();
int batch = coords.x;
int ch = coords.u;
ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads;
int dyDCorner = dyCorner.x;
int dyRCorner = dyCorner.y;
int dyCCorner = dyCorner.z;
// Convolve dy(?, ?, ?, ch) with pos mask(:, :, :, d) to get
// dx(xD, xR, xC, ch).
// ? = to be determined. : = across all values in that axis.
float dotProd = 0.0;
for (int wD = 0; wD < ${o};
wD += ${r}) {
float dyD = float(dyDCorner + wD) / ${t}.0;
if (dyD < 0.0 || dyD >= ${e.outDepth}.0 || fract(dyD) > 0.0) {
continue;
}
int idyD = int(dyD);
for (int wR = 0; wR < ${l};
wR += ${s}) {
float dyR = float(dyRCorner + wR) / ${n}.0;
if (dyR < 0.0 || dyR >= ${e.outHeight}.0 ||
fract(dyR) > 0.0) {
continue;
}
int idyR = int(dyR);
for (int wC = 0; wC < ${u};
wC += ${i}) {
float dyC = float(dyCCorner + wC) / ${a}.0;
if (dyC < 0.0 || dyC >= ${e.outWidth}.0 ||
fract(dyC) > 0.0) {
continue;
}
int idyC = int(dyC);
float dyValue = getDy(batch, idyD, idyR, idyC, ch);
int maxPosValue = ${h} -
int(getMaxPos(batch, idyD, idyR, idyC, ch));
// Get the current value, check it against the value from the
// position matrix.
int curPosValue =
wD * ${l} * ${u} +
wR * ${u} + wC;
float mask = float(maxPosValue == curPosValue ? 1.0 : 0.0);
dotProd += dyValue * mask;
}
}
}
setOutput(dotProd);
}
`}};function ore(e){let{inputs:t,backend:n,attrs:a}=e,{dy:r,input:s}=t,i=s,{filterSize:o,strides:l,pad:u,dimRoundingMode:p}=a,d=[1,1,1],c=N.computePool3DInfo(i.shape,o,l,d,u,p),h=new X1(c,"max",!0),m=n.runWebGLProgram(h,[i],i.dtype),f=new ire(c),g=n.runWebGLProgram(f,[r,m],i.dtype);return n.disposeIntermediateTensorInfo(m),g}var lre={kernelName:Rc,backendName:"webgl",kernelFunc:ore};function ure(e){let{inputs:t,backend:n,attrs:a}=e,{dy:r,input:s,output:i}=t,o=s;ip([s,i],"maxPoolGrad");let{filterSize:l,strides:u,pad:p,dimRoundingMode:d}=a,c=N.computePool2DInfo(o.shape,l,u,1,p,d),h=!0,m=new Ic(c,"max",h),f=n.runWebGLProgram(m,[o],o.dtype),g=new sre(c),b=n.runWebGLProgram(g,[r,f],o.dtype);return n.disposeIntermediateTensorInfo(f),b}var pre={kernelName:Cm,backendName:"webgl",kernelFunc:ure};function cre(e,t,n,a){let r=new Ic(n,"max",!1),s=a.runWebGLProgram(r,[e],"float32");r=new Ic(n,"max",!0,!0,t);let i=a.runWebGLProgram(r,[e],"float32");return[s,i]}var dre={kernelName:_m,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{x:a}=e,{filterSize:r,strides:s,pad:i,includeBatchInIndex:o}=t,l=n;v.assert(a.shape.length===4,()=>`Error in maxPool: input must be rank 4 but got rank ${a.shape.length}.`);let u=[1,1];v.assert(N.eitherStridesOrDilationsAreOne(s,u),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${s} and dilations '${u}'`);let p=N.computePool2DInfo(a.shape,r,s,u,i),[d,c]=cre(a,o,p,l);return[d,c]}};function hre(e,t,n,a){let r=v.sizeFromShape(t),s=v.sizeFromShape(e.shape)/r,i=ce({inputs:{x:e},attrs:{shape:[s,r]},backend:a}),o=Xo(i,"float32","mean",a),l=ce({inputs:{x:o},attrs:{shape:n},backend:a});return a.disposeIntermediateTensorInfo(i),a.disposeIntermediateTensorInfo(o),l}var mre={kernelName:lo,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{x:a}=e,{keepDims:r,axis:s}=t,i=n,o=a.shape.length,l=v.parseAxisParam(s,a.shape),u=l,p=N.getAxesPermutation(u,o),d=p!=null,c=i.shouldExecuteOnCPU([a]),h=[],m=a;if(d){if(c){let x=i.texData.get(m.dataId).values,w=new Array(o);for(let C=0;C<w.length;C++)w[C]=a.shape[p[C]];let I=q1(x,a.shape,a.dtype,p,w);m=i.makeTensorInfo(w,a.dtype);let T=i.texData.get(m.dataId);T.values=I}else m=Lf(a,p,i);h.push(m),u=N.getInnerMostAxes(u.length,o)}N.assertAxesAreInnerMostDims("sum",u,o);let[f,g]=N.computeOutAndReduceShapes(m.shape,u),b=f;r&&(b=N.expandShapeToKeepDim(f,l));let y=hre(m,g,b,i);for(let x of h)i.disposeIntermediateTensorInfo(x);return y}};function fre(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{axis:s,keepDims:i}=a,o=r.shape.length,l=v.parseAxisParam(s,r.shape),u=l,p=N.getAxesPermutation(u,o),d=r;p!=null&&(d=Sn({inputs:{x:r},backend:n,attrs:{perm:p}}),u=N.getInnerMostAxes(u.length,r.shape.length)),N.assertAxesAreInnerMostDims("min",u,o);let[c,h]=N.computeOutAndReduceShapes(d.shape,u),m=v.sizeFromShape(h),f=ce({inputs:{x:d},backend:n,attrs:{shape:[-1,m]}}),g=Xo(f,f.dtype,"min",n),b;if(i){let y=N.expandShapeToKeepDim(c,l);b=ce({inputs:{x:g},backend:n,attrs:{shape:y}})}else b=ce({inputs:{x:g},backend:n,attrs:{shape:c}});return n.disposeIntermediateTensorInfo(f),n.disposeIntermediateTensorInfo(g),p!=null&&n.disposeIntermediateTensorInfo(d),b}var gre={kernelName:uo,backendName:"webgl",kernelFunc:fre},bre=j1+`
return min(a, b);
`,yre=`
vec4 result = vec4(min(a, b));
bvec4 isNaNA = isnan(a);
bvec4 isNaNB = isnan(b);
bvec4 isNaN = bvec4(isNaNA.x || isNaNB.x, isNaNA.y || isNaNB.y, isNaNA.z || isNaNB.z, isNaNA.w || isNaNB.w);
`+Ko+`
return result;
`,xre=mn({opSnippet:bre,packedOpSnippet:yre,cpuKernelImpl:i9}),vre={kernelName:po,backendName:"webgl",kernelFunc:xre},wre=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=t.map((u,p)=>u[0]+e[p]+u[1]);let a=e.length,r=ct(a),s=t.map(u=>u[0]).join(","),i=t.map((u,p)=>u[0]+e[p]).join(","),o=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,a),l=n==="reflect"?0:1;if(a===1){this.userCode=`
int start = ${s};
int end = ${i};
void main() {
int outC = getOutputCoords();
if (outC < start) {
outC = start * 2 - outC - ${l};
} else if(outC >= end) {
outC = (end - 1) * 2 - outC + ${l};
}
setOutput(getX(outC - start));
}
`;return}this.userCode=`
${r} start = ${r}(${s});
${r} end = ${r}(${i});
void main() {
${r} outC = getOutputCoords();
for (int i = 0; i < ${a}; i++) {
if (outC[i] < start[i]) {
outC[i] = start[i] * 2 - outC[i] - ${l};
} else if(outC[i] >= end[i]) {
outC[i] = (end[i] - 1) * 2 - outC[i] + ${l};
}
}
${r} coords = outC - start;
setOutput(getX(${o}));
}
`}},kre=class{constructor(e,t,n){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t.map((h,m)=>h[0]+e[m]+h[1]);let a=e.length,r=ct(a),s=t.map(h=>h[0]).join(","),i=t.map((h,m)=>h[0]+e[m]).join(","),o=In("rc",a),l=In("source",a),u=`${o[a-1]} < ${this.outputShape[a-1]}`,p=a===1?"source":`vec2(${l.slice(-2).join()})`,d=n==="reflect"?0:1,c="";if(a===1){let h=`
${r} source = rc;
if (source < start) {
source = start * 2 - source - ${d};
} else if (source >= end) {
source = (end - 1) * 2 - source + ${d};
}
source -= start;
`;c=`
${r} rc = outputLoc;
${h}
result[0] = getChannel(getX(${l.join()}), ${p});
${o[a-1]} += 1;
if(${u}) {
${h}
result[1] = getChannel(getX(${l.join()}), ${p});
}
`}else{let h=`
${r} source = rc;
${r} lt = ${r}(lessThan(source, start));
${r} gte = ${r}(greaterThanEqual(source, end));
${r} orig = 1 - (lt + gte);
source = orig * source +
lt * (start * 2 - source - ${d}) +
gte * ((end - 1) * 2 - source + ${d});
source -= start;
`;c=`
${r} rc = outputLoc;
${h}
result[0] = getChannel(getX(${l.join()}), ${p});
${o[a-1]} += 1;
if(${u}) {
${h}
result[1] = getChannel(getX(${l.join()}), ${p});
}
rc = outputLoc;
${o[a-2]} += 1;
if(${o[a-2]} < ${this.outputShape[a-2]}) {
${h}
result[2] = getChannel(getX(${l.join()}), ${p});
${o[a-1]} += 1;
if(${u}) {
${h}
result[3] = getChannel(getX(${l.join()}), ${p});
}
}
`}this.userCode=`
const ${r} start = ${r}(${s});
const ${r} end = ${r}(${i});
void main() {
${r} outputLoc = getOutputCoords();
vec4 result = vec4(0.);
${c}
setOutput(result);
}
`}},Ire=({inputs:e,backend:t,attrs:n})=>{let{x:a}=e,{paddings:r,mode:s}=n,i=G().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new kre(a.shape,r,s):new wre(a.shape,r,s);return t.runWebGLProgram(i,[a],a.dtype)},Sre={kernelName:co,backendName:"webgl",kernelFunc:Ire},Nre=`if (b == 0.0) return NAN;
return mod(a, b);`,Tre=`
vec4 result = mod(a, b);
bvec4 isNaN = equal(b, vec4(0.0));
`+Ko+`
return result;
`,Cre=mn({opSnippet:Nre,packedOpSnippet:Tre}),_re={kernelName:ku,backendName:"webgl",kernelFunc:Cre},Ere=class{constructor(e,t,n){this.variableNames=["probs"],this.customUniforms=[{name:"seed",type:"float"}],this.outputShape=[e,n],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}));
}
`}},Are=`
if (a == b) {
return 1.0;
};
return a / b;`,Fre=`
// 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;
`,fA=mn({opSnippet:Are,packedOpSnippet:Fre,checkOutOfBounds:!0}),$re={kernelName:Ui,backendName:"webgl",kernelFunc:fA},rS="return a - b;",gA=mn({opSnippet:rS,packedOpSnippet:rS,supportsComplex:!0,cpuKernelImpl:C9}),Dre={kernelName:Po,backendName:"webgl",kernelFunc:gA};function bA(e){let{inputs:t,backend:n,attrs:a}=e,{logits:r}=t,{dim:s}=a,i=v.parseAxisParam([s],r.shape),o=mA({inputs:{x:r},backend:n,attrs:{reductionIndices:i,keepDims:!1}}),l=N.expandShapeToKeepDim(o.shape,i),u=ce({inputs:{x:o},backend:n,attrs:{shape:l}}),p=gA({inputs:{a:r,b:u},backend:n}),d=cA({inputs:{x:p},backend:n}),c=zf({inputs:{x:d},backend:n,attrs:{axis:i,keepDims:!1}}),h=ce({inputs:{x:c},backend:n,attrs:{shape:l}}),m=fA({inputs:{a:d,b:h},backend:n});return n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(u),n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(c),n.disposeIntermediateTensorInfo(h),m}var Rre={kernelName:Ro,backendName:"webgl",kernelFunc:bA};function Mre(e){let{inputs:t,backend:n,attrs:a}=e,{logits:r}=t,{numSamples:s,seed:i,normalized:o}=a,l=o?r:bA({inputs:{logits:r},backend:n,attrs:{dim:r.shape.length-1}}),u=l.shape[0],p=l.shape[1],d=new Ere(u,p,s),c=[[i]],h=n.runWebGLProgram(d,[l],"int32",c);return o||n.disposeIntermediateTensorInfo(l),h}var Pre={kernelName:Iu,backendName:"webgl",kernelFunc:Mre},Ore=Ma+`
return -x;
`,Lre=`
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 zre(e){let{inputs:t,backend:n}=e,{x:a}=t;if(n.shouldExecuteOnCPU([a])){let s=n.texData.get(a.dataId),[i,o]=l9(s.values,a.shape,a.dtype);return n.makeTensorInfo(o,a.dtype,i)}let r;return G().getBool("WEBGL_PACK_UNARY_OPERATIONS")?r=new ts(a.shape,Lre):r=new rr(a.shape,Ore),n.runWebGLProgram(r,[a],a.dtype)}var Wre={kernelName:Su,backendName:"webgl",kernelFunc:zre},Bre=hr.nonMaxSuppressionV3Impl;function Vre(e){N.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:a}=e,{boxes:r,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l}=a,u=n.readSync(r.dataId),p=n.readSync(s.dataId),{selectedIndices:d}=Bre(u,p,i,o,l);return n.makeTensorInfo([d.length],"int32",new Int32Array(d))}var Ure={kernelName:Tu,backendName:"webgl",kernelFunc:Vre},Gre=hr.nonMaxSuppressionV4Impl;function Hre(e){N.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:a}=e,{boxes:r,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l,padToMaxOutputSize:u}=a,p=n.readSync(r.dataId),d=n.readSync(s.dataId),{selectedIndices:c,validOutputs:h}=Gre(p,d,i,o,l,u);return[n.makeTensorInfo([c.length],"int32",new Int32Array(c)),n.makeTensorInfo([],"int32",new Int32Array([h]))]}var qre={kernelName:Cu,backendName:"webgl",kernelFunc:Hre},jre=hr.nonMaxSuppressionV5Impl;function Kre(e){N.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:a}=e,{boxes:r,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l,softNmsSigma:u}=a,p=n.readSync(r.dataId),d=n.readSync(s.dataId),c=i,h=o,m=l,f=u,{selectedIndices:g,selectedScores:b}=jre(p,d,c,h,m,f);return[n.makeTensorInfo([g.length],"int32",new Int32Array(g)),n.makeTensorInfo([b.length],"float32",new Float32Array(b))]}var Xre={kernelName:_u,backendName:"webgl",kernelFunc:Kre},Yre=class{constructor(e,t,n,a){this.variableNames=["indices"],this.outputShape=[e,t],this.userCode=`
void main() {
ivec2 coords = getOutputCoords();
int index = round(getIndices(coords.x));
setOutput(mix(float(${a}), float(${n}),
float(index == coords.y)));
}
`}},Zre=e=>{let{inputs:t,backend:n,attrs:a}=e,{indices:r}=t,{dtype:s,depth:i,onValue:o,offValue:l}=a,u=v.sizeFromShape(r.shape),p=new Yre(u,i,o,l),d=ce({inputs:{x:r},backend:n,attrs:{shape:[u]}}),c=n.runWebGLProgram(p,[d],s);n.disposeIntermediateTensorInfo(d);let h=[...r.shape,i],m=ce({inputs:{x:c},backend:n,attrs:{shape:h}});return n.disposeIntermediateTensorInfo(c),m},Jre={kernelName:mo,backendName:"webgl",kernelFunc:Zre};function cm(e){let{inputs:t,backend:n}=e,{x:a}=t;if(a.dtype==="complex64"){let r=Td({inputs:{input:a},backend:n}),s=cm({inputs:{x:r},backend:n}),i=Wf({inputs:{input:a},backend:n}),o=cm({inputs:{x:i},backend:n}),l=Es({inputs:{real:s,imag:o},backend:n});return n.disposeIntermediateTensorInfo(r),n.disposeIntermediateTensorInfo(s),n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(o),l}else return Cd({attrs:{shape:a.shape,dtype:a.dtype,value:a.dtype==="string"?"":0},backend:n})}var Qre={kernelName:Ku,backendName:"webgl",kernelFunc:cm};function yA(e){let{inputs:t,backend:n}=e,{x:a}=t;if(a.dtype==="string")throw new Error("onesLike is not supported under string dtype");if(a.dtype==="complex64"){let r=Td({inputs:{input:a},backend:n}),s=yA({inputs:{x:r},backend:n}),i=Wf({inputs:{input:a},backend:n}),o=cm({inputs:{x:i},backend:n}),l=Es({inputs:{real:s,imag:o},backend:n});return n.disposeIntermediateTensorInfo(r),n.disposeIntermediateTensorInfo(s),n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(o),l}else return Cd({attrs:{shape:a.shape,dtype:a.dtype,value:1},backend:n})}var ese={kernelName:Eu,backendName:"webgl",kernelFunc:yA};function tse(e){let{inputs:t,backend:n,attrs:a}=e,{axis:r}=a;if(t.length===1)return nv({inputs:{input:t[0]},backend:n,attrs:{dim:r}});let s=t[0].shape,i=t[0].dtype;t.forEach(p=>{v.assertShapesMatch(s,p.shape,"All tensors passed to stack must have matching shapes"),v.assert(i===p.dtype,()=>"All tensors passed to stack must have matching dtypes")});let o=[],l=t.map(p=>{let d=nv({inputs:{input:p},backend:n,attrs:{dim:r}});return o.push(d),d}),u=aA({inputs:l,backend:n,attrs:{axis:r}});return o.forEach(p=>n.disposeIntermediateTensorInfo(p)),u}var nse={kernelName:Au,backendName:"webgl",kernelFunc:tse},ase=class{constructor(e,t,n){this.variableNames=["x"],this.customUniforms=[{name:"value",type:"float"}],this.outputShape=t.map((l,u)=>l[0]+e[u]+l[1]);let a=e.length,r=ct(a),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,a);if(a===1){this.userCode=`
int start = ${s};
int end = ${i};
void main() {
int outC = getOutputCoords();
if (outC < start || outC >= end) {
setOutput(value);
} else {
setOutput(getX(outC - start));
}
}
`;return}this.userCode=`
${r} start = ${r}(${s});
${r} end = ${r}(${i});
void main() {
${r} outC = getOutputCoords();
if (any(lessThan(outC, start)) || any(greaterThanEqual(outC, end))) {
setOutput(value);
} else {
${r} coords = outC - start;
setOutput(getX(${o}));
}
}
`}},rse=class{constructor(e,t,n){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 a=e.length,r=ct(a),s=t.map(m=>m[0]).join(","),i=t.map((m,f)=>m[0]+e[f]).join(","),o=In("rc",a),l=In("source",a),u=`${o[a-1]} < ${this.outputShape[a-1]}`,p=a===1?"source":`vec2(${l.slice(-2).join()})`,d=[`${r} rc = outputLoc;`,`${o[a-1]} += 1;
if(${u}) {
`,a===1?"":`}
rc = outputLoc;
${o[a-2]} += 1;
if(${o[a-2]} < ${this.outputShape[a-2]}) {`,a===1?"":` ${o[a-1]} += 1;
if(${u}) {`],c=a===1?"rc < start || rc >= end":"any(lessThan(rc, start)) || any(greaterThanEqual(rc, end))",h="";for(let m=0,f=a===1?2:4;m<f;m++)h+=`
${d[m]}
if (${c}) {
result[${m}] = float(value);
} else {
${r} source = rc - start;
result[${m}] = getChannel(getX(${l.join()}), ${p});
}
`;h+=a===1?"} ":"}}",this.userCode=`
const ${r} start = ${r}(${s});
const ${r} end = ${r}(${i});
void main() {
${r} outputLoc = getOutputCoords();
vec4 result = vec4(0.);
${h}
setOutput(result);
}
`}},xA=e=>{let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{paddings:s,constantValue:i}=a;if(v.sizeFromShape(r.shape)===0){let u=s.map((p,d)=>p[0]+r.shape[d]+p[1]);return Cd({backend:n,attrs:{shape:u,value:i,dtype:r.dtype}})}let o=G().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new rse(r.shape,s,i):new ase(r.shape,s,i),l=[[i]];return n.runWebGLProgram(o,[r],r.dtype,l)},sse={kernelName:fo,backendName:"webgl",kernelFunc:xA},ise=`
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);
`,ose=`
// isModRound1 has 1 for components with round(mod(b, 2.0)) == 1, 0 otherwise.
vec4 isModRound1 = vec4(equal(round(mod(b, 2.0)), ivec4(1)));
vec4 multiplier = sign(a) * isModRound1 + (vec4(1.0) - isModRound1);
vec4 result = multiplier * pow(abs(a), b);
// Ensure that a^0 = 1, including 0^0 = 1 as this correspond to TF and JS
bvec4 isExpZero = equal(b, vec4(0.0));
result.r = isExpZero.r ? 1.0 : result.r;
result.g = isExpZero.g ? 1.0 : result.g;
result.b = isExpZero.b ? 1.0 : result.b;
result.a = isExpZero.a ? 1.0 : result.a;
bvec4 isNaN1 = lessThan(a, vec4(0.0));
bvec4 isNaN2 = lessThan(floor(b), b);
bvec4 isNaN = bvec4(isNaN1.x && isNaN2.x, isNaN1.y && isNaN2.y, isNaN1.z && isNaN2.z, isNaN1.w && isNaN2.w);
`+Ko+`
return result;
`,lse=mn({opSnippet:ise,packedOpSnippet:ose}),use={kernelName:go,backendName:"webgl",kernelFunc:lse};function pse(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{axis:s,keepDims:i}=a,o=r.shape.length,l=[],u=v.parseAxisParam(s,r.shape),p=u,d=N.getAxesPermutation(p,o),c=r;d!=null&&(c=Sn({inputs:{x:r},backend:n,attrs:{perm:d}}),p=N.getInnerMostAxes(p.length,o),l.push(c)),N.assertAxesAreInnerMostDims("prod",p,o);let h;if(n.shouldExecuteOnCPU([c])){let m=n.texData.get(c.dataId).values,{outVals:f,outShape:g,outDtype:b}=p9(c.shape,c.dtype,m,p);h=n.makeTensorInfo(g,b,f)}else{let[m,f]=N.computeOutAndReduceShapes(c.shape,p),g=v.sizeFromShape(f),b=ce({inputs:{x:c},backend:n,attrs:{shape:[-1,g]}}),y=Rm(r.dtype),x=Xo(b,y,"prod",n);h=ce({inputs:{x},backend:n,attrs:{shape:m}}),l.push(b),l.push(x)}if(i){l.push(h);let m=N.expandShapeToKeepDim(h.shape,u);h=ce({inputs:{x:h},backend:n,attrs:{shape:m}})}return l.forEach(m=>n.disposeIntermediateTensorInfo(m)),h}var cse={kernelName:yo,backendName:"webgl",kernelFunc:pse};function dse(e){let{inputs:t,backend:n,attrs:a}=e,{paramsNestedSplits:r,paramsDenseValues:s,indices:i}=t,{outputRaggedRank:o}=a,l=r.map(b=>n.readSync(b.dataId)),u=r.map(b=>b.shape),p=n.readSync(s.dataId),d=n.readSync(i.dataId),[c,h,m]=c9(l,u,p,s.shape,s.dtype,d,i.shape,o),f=c.map(b=>n.makeTensorInfo([b.length],"int32",b)),g=n.makeTensorInfo(m,s.dtype,h);return f.concat([g])}var hse={kernelName:Em,backendName:"webgl",kernelFunc:dse};function mse(e){let{inputs:t,backend:n}=e,{starts:a,limits:r,deltas:s}=t,i=n.readSync(a.dataId),o=n.readSync(r.dataId),l=n.readSync(s.dataId),[u,p]=d9(i,a.shape,a.dtype,o,r.shape,l,s.shape),d=n.makeTensorInfo([u.length],"int32",u),c=n.makeTensorInfo([p.length],a.dtype,p);return[d,c]}var fse={kernelName:Am,backendName:"webgl",kernelFunc:mse};function gse(e){let{inputs:t,backend:n,attrs:a}=e,{shape:r,values:s,defaultValue:i,rowPartitionTensors:o}=t,{rowPartitionTypes:l}=a,u=n.readSync(r.dataId),p=n.readSync(s.dataId),d=n.readSync(i.dataId),c=o.map(g=>n.readSync(g.dataId)),h=o.map(g=>g.shape),[m,f]=h9(u,r.shape,p,s.shape,s.dtype,d,i.shape,c,h,l);return n.makeTensorInfo(m,s.dtype,f)}var bse={kernelName:Fm,backendName:"webgl",kernelFunc:gse},vA=e=>{let{backend:t,attrs:n}=e,{start:a,stop:r,step:s,dtype:i}=n,o=m9(a,r,s,i);return t.makeTensorInfo([o.length],i,o)},yse={kernelName:Mc,backendName:"webgl",kernelFunc:vA},xse="return 1.0 / x;",vse=Ye({opSnippet:xse}),wse={kernelName:xo,backendName:"webgl",kernelFunc:vse},kse=Ma+`
return (x < 0.0) ? 0.0 : x;
`,Ise=`
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;
`,Sse=Ye({opSnippet:kse,packedOpSnippet:Ise}),Nse={kernelName:vo,backendName:"webgl",kernelFunc:Sse},Tse=Ma+`
return (x < 0.0) ? 0.0 : min(6.0, x);
`,Cse=`
vec4 result = min(x, vec4(6.)) * vec4(greaterThanEqual(x, vec4(0.0)));
bvec4 isNaN = isnan(x);
result.r = isNaN.r ? x.r : result.r;
result.g = isNaN.g ? x.g : result.g;
result.b = isNaN.b ? x.b : result.b;
result.a = isNaN.a ? x.a : result.a;
return result;
`,_se=Ye({opSnippet:Tse,packedOpSnippet:Cse}),Ese={kernelName:Io,backendName:"webgl",kernelFunc:_se},Ase=class{constructor(e,t,n,a,r){this.variableNames=["A"],this.outputShape=[];let[s,i,o,l]=e;this.outputShape=[s,t,n,l];let u=[a&&t>1?i-1:i,a&&n>1?o-1:o],p=[a&&t>1?t-1:t,a&&n>1?n-1:n],d;r?d="(vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC - vec2(0.5)":d="vec2(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
const vec2 effectiveInputOverOutputRatioRC = vec2(
${u[0]/p[0]},
${u[1]/p[1]});
const vec2 inputShapeRC = vec2(${i}.0, ${o}.0);
void main() {
ivec4 coords = getOutputCoords();
int b = coords[0];
int d = coords[3];
ivec2 yRC = coords.yz;
// Fractional source index.
vec2 sourceFracIndexRC = ${d};
// Compute the 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);
}
`}},Fse=class{constructor(e,t,n,a,r){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[];let[s,i,o,l]=e;this.outputShape=[s,t,n,l];let u=[a&&t>1?i-1:i,a&&n>1?o-1:o],p=[a&&t>1?t-1:t,a&&n>1?n-1:n],d;r?d="(vec3(yRC) + vec3(0.5)) * effectiveInputOverOutputRatioRC - vec3(0.5)":d="vec3(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
const vec3 effectiveInputOverOutputRatioRC = vec3(
${u[0]/p[0]},
${u[1]/p[1]},
${u[1]/p[1]});
const vec3 inputShapeRC = vec3(${i}.0, ${o}.0,
${o}.0);
float getAValue(int b, int r, int c, int d) {
return getChannel(getA(b, r, c, d), vec2(c, d));
}
void main() {
ivec4 coords = getOutputCoords();
int b = coords[0];
int d = coords[3];
// Calculate values for next column in yRC.z.
ivec3 yRC = coords.yzz + ivec3(0, 0, 1);
// Fractional source index.
vec3 sourceFracIndexRC = ${d};
// Compute the 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 < ${n-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 $se(e){let{inputs:t,backend:n,attrs:a}=e,{images:r}=t,{alignCorners:s,halfPixelCenters:i,size:o}=a,[l,u]=o,p=G().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new Fse(r.shape,l,u,s,i):new Ase(r.shape,l,u,s,i);return n.runWebGLProgram(p,[r],"float32")}var Dse={kernelName:ko,backendName:"webgl",kernelFunc:$se},Rse=class{constructor(e,t,n){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t;let[,a,r]=t,[,s,i]=e,o=[n&&s>1?a-1:a,n&&i>1?r-1:r],l=[n&&s>1?s-1:s,n&&i>1?i-1:i],u=o[0]/l[0],p=o[1]/l[1],d=1/u,c=1/p,h=Math.ceil(d)*2+2,m=Math.ceil(c)*2+2;this.userCode=`
void main() {
ivec4 coords = getOutputCoords();
int b = coords[0];
int d = coords[3];
int r = coords[1];
int c = coords[2];
float accumulator = 0.0;
const float heightScale = float(${u});
const float widthScale = float(${p});
const float invHeightScale = float(${d});
const float invWidthScale = float(${c});
const int winHeight = int(${h});
const int winWidth = int(${m});
// Compute bounds for where in dy we will look
float startRLerp = floor(float(r) * invHeightScale);
int startDyR = int(startRLerp - float(winHeight / 2));
float startCLerp = floor(float(c) * invWidthScale);
int startDyC = int(startCLerp - float(winWidth / 2));
// Loop over dy
for (int dyROffset = 0; dyROffset < winHeight; dyROffset++) {
int dyR = dyROffset + startDyR;
// Guard against the window exceeding the bounds of dy
if (dyR < 0 || dyR >= ${s}) {
continue;
}
for (int dyCOffset = 0; dyCOffset < winWidth; dyCOffset++) {
int dyC = dyCOffset + startDyC;
// Guard against the window exceeding the bounds of dy
if (dyC < 0 || dyC >= ${i}) {
continue;
}
float dxR = float(dyR) * heightScale;
int topDxRIndex = int(floor(dxR));
int bottomDxRIndex = int(min(ceil(dxR), ${a-1}.0));
float dxRLerp = dxR - float(topDxRIndex);
float inverseDxRLerp = 1.0 - dxRLerp;
float dxC = float(dyC) * widthScale;
int leftDxCIndex = int(floor(dxC));
int rightDxCIndex = int(min(ceil(dxC), ${r-1}.0));
float dxCLerp = dxC - float(leftDxCIndex);
float inverseDxCLerp = 1.0 - dxCLerp;
if (r == topDxRIndex && c == leftDxCIndex) {
// topLeft
accumulator +=
getDy(b, dyR, dyC, d) * inverseDxRLerp * inverseDxCLerp;
}
if (r == topDxRIndex && c == rightDxCIndex) {
// topRight
accumulator += getDy(b, dyR, dyC, d) * inverseDxRLerp * dxCLerp;
}
if (r == bottomDxRIndex && c == leftDxCIndex) {
// bottomLeft
accumulator += getDy(b, dyR, dyC, d) * dxRLerp * inverseDxCLerp;
}
if (r == bottomDxRIndex && c == rightDxCIndex) {
// bottomRight
accumulator += getDy(b, dyR, dyC, d) * dxRLerp * dxCLerp;
}
}
}
// End loop over dy
setOutput(accumulator);
}
`}};function Mse(e){let{inputs:t,backend:n,attrs:a}=e,{images:r,dy:s}=t,{alignCorners:i}=a,o=new Rse(s.shape,r.shape,i);return n.runWebGLProgram(o,[s],s.dtype)}var Pse={kernelName:Du,backendName:"webgl",kernelFunc:Mse},Ose=class{constructor(e,t,n,a,r){this.variableNames=["A"],this.outputShape=[];let[s,i,o,l]=e;this.outputShape=[s,t,n,l];let u=[a&&t>1?i-1:i,a&&n>1?o-1:o],p=[a&&t>1?t-1:t,a&&n>1?n-1:n],d=a?"0.5":"0.0",c;r?c="max((vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC, vec2(0.0))":c="vec2(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
const vec2 effectiveInputOverOutputRatioRC = vec2(
${u[0]/p[0]},
${u[1]/p[1]});
const vec2 inputShapeRC = vec2(${i}.0, ${o}.0);
void main() {
ivec4 coords = getOutputCoords();
int b = coords[0];
int d = coords[3];
ivec2 yRC = coords.yz;
// Fractional source index.
vec2 sourceFracIndexRC = ${c};
// Compute the coordinators of nearest neighbor point.
ivec2 sourceNearestRC = ivec2(
min(inputShapeRC - 1.0, floor(sourceFracIndexRC + ${d})));
float newValue = getA(b, sourceNearestRC.x, sourceNearestRC.y, d);
setOutput(newValue);
}
`}},Lse=class{constructor(e,t,n,a,r){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[];let[s,i,o,l]=e;this.outputShape=[s,t,n,l];let u=[a&&t>1?i-1:i,a&&n>1?o-1:o],p=[a&&t>1?t-1:t,a&&n>1?n-1:n],d=a?"0.5":"0.0",c;r?c="max((vec3(yRC) + vec3(0.5)) * effectiveInputOverOutputRatioRC, vec3(0.0))":c="vec3(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
const vec3 effectiveInputOverOutputRatioRC = vec3(
${u[0]/p[0]},
${u[1]/p[1]},
${u[1]/p[1]});
const vec3 inputShapeRC = vec3(${i}.0, ${o}.0,
${o}.0);
float getAValue(int b, int r, int c, int d) {
return getChannel(getA(b, r, c, d), vec2(c, d));
}
void main() {
ivec4 coords = getOutputCoords();
int b = coords[0];
int d = coords[3];
// Calculate values for next column in yRC.z.
ivec3 yRC = coords.yzz + ivec3(0, 0, 1);
// Fractional source index.
vec3 sourceFracIndexRC = ${c};
// Compute the coordinators of nearest neighbor point.
ivec3 sourceNearestRC = ivec3(
min(inputShapeRC - 1.0, floor(sourceFracIndexRC + ${d})));
// Should we calculate next column and row elements in 2x2 packed cell.
bool hasNextCol = d < ${l-1};
bool hasNextRow = coords.z < ${n-1};
vec4 newValue = vec4(
getAValue(b, sourceNearestRC.x, sourceNearestRC.y, d),
hasNextCol ? getAValue(b, sourceNearestRC.x, sourceNearestRC.y, d + 1)
: 0.0,
hasNextRow ? getAValue(b, sourceNearestRC.x, sourceNearestRC.z, d)
: 0.0,
(hasNextRow && hasNextCol) ?
getAValue(b, sourceNearestRC.x, sourceNearestRC.z, d + 1) : 0.0);
setOutput(newValue);
}
`}};function zse(e){let{inputs:t,backend:n,attrs:a}=e,{images:r}=t,{alignCorners:s,halfPixelCenters:i,size:o}=a,[l,u]=o,p=G().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new Lse(r.shape,l,u,s,i):new Ose(r.shape,l,u,s,i);return n.runWebGLProgram(p,[r],r.dtype)}var Wse={kernelName:wo,backendName:"webgl",kernelFunc:zse},Bse=class{constructor(e,t,n){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t;let[,a,r]=t,[,s,i]=e,o=[n&&s>1?a-1:a,n&&i>1?r-1:r],l=[n&&s>1?s-1:s,n&&i>1?i-1:i],u=o[0]/l[0],p=o[1]/l[1],d=1/u,c=1/p,h=Math.ceil(d)*2+2,m=Math.ceil(c)*2+2;this.userCode=`
void main() {
ivec4 coords = getOutputCoords();
int b = coords[0];
int d = coords[3];
int r = coords[1];
int c = coords[2];
float accumulator = 0.0;
const float heightScale = float(${u});
const float widthScale = float(${p});
const float invHeightScale = float(${d});
const float invWidthScale = float(${c});
const int winHeight = int(${h});
const int winWidth = int(${m});
// Compute bounds for where in dy we will look
float startRLerp = floor(float(r) * invHeightScale);
int startDyR = int(floor(startRLerp - float(winHeight / 2)));
float startCLerp = floor(float(c) * invWidthScale);
int startDyC = int(floor(startCLerp - float(winWidth / 2)));
// Loop over dy
for (int dyROffset = 0; dyROffset < winHeight; dyROffset++) {
int dyR = dyROffset + startDyR;
// Guard against the window exceeding the bounds of dy
if (dyR < 0 || dyR >= ${s}) {
continue;
}
for (int dyCOffset = 0; dyCOffset < winWidth; dyCOffset++) {
int dyC = dyCOffset + startDyC;
// Guard against the window exceeding the bounds of dy
if (dyC < 0 || dyC >= ${i}) {
continue;
}
float sourceFracRow =
float(${o[0]}) *
(float(dyR) / float(${l[0]}));
float sourceFracCol =
float(${o[1]}) *
(float(dyC) / float(${l[1]}));
int sourceNearestRow = int(min(
float(int(${a}) - 1),
${n} ? float(round(sourceFracRow)) :
float(floor(sourceFracRow))));
int sourceNearestCol = int(min(
float(int(${r}) - 1),
${n} ? float(round(sourceFracCol)) :
float(floor(sourceFracCol))));
if (r == sourceNearestRow && c == sourceNearestCol) {
accumulator += getDy(b, dyR, dyC, d);
}
}
}
// End loop over dy
setOutput(accumulator);
}
`}};function Vse(e){let{inputs:t,backend:n,attrs:a}=e,{images:r,dy:s}=t,{alignCorners:i}=a,o=new Bse(s.shape,r.shape,i);return n.runWebGLProgram(o,[s],s.dtype)}var Use={kernelName:$u,backendName:"webgl",kernelFunc:Vse},Gse=class{constructor(e,t){this.variableNames=["x"];let n=e.length;if(n>4)throw new Error(`WebGL backend: Reverse of rank-${n} tensor is not yet supported`);if(this.outputShape=e,n===1){this.userCode=`
void main() {
int coord = getOutputCoords();
setOutput(getX(${e[0]} - coord - 1));
}
`;return}let a=i=>t.indexOf(i)!==-1&&e[i]!==1?`${e[i]} - coords[${i}] - 1`:`coords[${i}]`,r=e.map((i,o)=>a(o)).join(","),s=ct(n);this.userCode=`
void main() {
${s} coords = getOutputCoords();
setOutput(getX(${r}));
}
`}},Hse=class{constructor(e,t){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0;let n=e.length;if(n>4)throw new Error(`WebGL backend: Reverse of rank-${n} tensor is not yet supported`);this.outputShape=e;let a=In("rc",n),r=`${a[n-1]} + 1 < ${this.outputShape[n-1]}`,s=`${a[n-2]} + 1 < ${this.outputShape[n-2]}`,i=ct(n);n===1?this.userCode=`
void main(){
int rc = getOutputCoords();
vec4 result = vec4(0.);
result.r = getChannel(getX(${e[0]} - rc - 1),
${e[0]} - rc - 1);
if(${r}){
result.g = getChannel(getX(${e[0]} - (rc + 1) - 1),
${e[0]} - (rc + 1) - 1);
}
setOutput(result);
}
`:this.userCode=`
void main() {
${i} rc = getOutputCoords();
vec4 result = vec4(0.);
result.r = ${o(a.slice())};
if(${r}){
result.g = ${l(a.slice())};
}
if(${s}) {
result.b = ${u(a.slice())};
if(${r}) {
result.a = ${p(a.slice())};
}
}
setOutput(result);
}
`;function o(h){return d(h)}function l(h){return h[n-1]="("+h[n-1]+" + 1)",d(h)}function u(h){return h[n-2]="("+h[n-2]+" + 1)",d(h)}function p(h){return h[n-1]="("+h[n-1]+" + 1)",h[n-2]="("+h[n-2]+" + 1)",d(h)}function d(h){let m=e.map((b,y)=>c(y,h)),f=m.join(","),g=m.slice(-2).join(",");return`getChannel(getX(${f}), vec2(${g}))`}function c(h,m){return t.indexOf(h)!==-1&&e[h]!==1?`${e[h]} - ${m[h]} - 1`:`${m[h]}`}}};function qse(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{dims:s}=a,i=r.shape.length,o=v.parseAxisParam(s,r.shape);if(i===0)return aa({inputs:{x:r},backend:n});let l=G().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new Hse(r.shape,o):new Gse(r.shape,o);return n.runWebGLProgram(l,[r],r.dtype)}var jse={kernelName:So,backendName:"webgl",kernelFunc:qse},Kse=class{constructor(e,t){this.variableNames=["Image"],this.outputShape=[],this.customUniforms=[{name:"params",type:"vec4"}];let n=e[1],a=e[2];this.outputShape=e;let r="";typeof t=="number"?r=`float outputValue = ${t.toFixed(2)};`:r=`
vec3 fill = vec3(${t.join(",")});
float outputValue = fill[coords[3]];`,this.userCode=`
void main() {
ivec4 coords = getOutputCoords();
int x = coords[2];
int y = coords[1];
float coordXFloat = (float(x) - params[0]) * params[3] -
(float(y) - params[1]) * params[2];
float coordYFloat = (float(x) - params[0]) * params[2] +
(float(y) - params[1]) * params[3];
int coordX = int(round(coordXFloat + params[0]));
int coordY = int(round(coordYFloat + params[1]));
${r}
if(coordX >= 0 && coordX < ${a} && coordY >= 0 && coordY < ${n}) {
outputValue = getImage(coords[0], coordY, coordX, coords[3]);
}
setOutput(outputValue);
}
`}},Xse={kernelName:Xu,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{image:a}=e,{radians:r,fillValue:s,center:i}=t,o=n,l=new Kse(a.shape,s),[u,p]=N.getImageCenter(i,a.shape[1],a.shape[2]),d=[[u,p,Math.sin(r),Math.cos(r)]];return o.runWebGLProgram(l,[a],a.dtype,d)}},Yse=`
// OpenGL ES does not support round function.
// The algorithm is based on banker's rounding.
float base = floor(x);
if ((x - base) < 0.5) {
return floor(x);
} else if ((x - base) > 0.5) {
return ceil(x);
} else {
if (mod(base, 2.0) == 0.0) {
return base;
} else {
return base + 1.0;
}
}
`,Zse=Ye({opSnippet:Yse}),Jse={kernelName:No,backendName:"webgl",kernelFunc:Zse},Qse="return inversesqrt(x);",eie=Ye({opSnippet:Qse,cpuKernelImpl:f9}),tie={kernelName:To,backendName:"webgl",kernelFunc:eie},Y1=class{constructor(e,t,n,a,r,s,i=!0,o=!1){this.variableNames=["updates","indices","defaultValue"],this.outputShape=s;let l=ct(r.length),u=ct(s.length),p="";n===1?p="i":n===2&&(p="i, j");let d=`getIndices(${p})`,c="";a===1?c="i":a===2&&(c="i, coords[1]");let h=`getUpdates(${c})`,m="";o&&(m="coords[0], coords[1]");let f=`getDefaultValue(${m})`,g=t>1?"strides[j]":"strides";this.userCode=`
${l} strides = ${l}(${r});
void main() {
${u} coords = getOutputCoords();
float sum = 0.0;
bool found = false;
for (int i = 0; i < ${e}; i++) {
int flattenedIndex = 0;
for (int j = 0; j < ${t}; j++) {
int index = round(${d});
flattenedIndex += index * ${g};
}
if (flattenedIndex == coords[0]) {
sum += ${h};
found = true;
}
}
setOutput(mix(${f}, sum, float(found)));
}
`}},nie=class{constructor(e,t,n,a,r,s,i=!0,o=!1){this.variableNames=["updates","indices","defaultValue"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=s;let l=ct(r.length),u=ct(s.length),p="";n===1?p="i":n===2&&(p="i, j");let d=`getIndices(${p})`,c="";a===1?c="i":a===2&&(c="i, coords[1]");let h=`getUpdates(${c})`,m="";o&&(m="coords[0], coords[1]");let f=`getDefaultValue(${m})`,g=t>1?"strides[j]":"strides",b=t>1?"strides[j + 1]":"strides";this.userCode=`
${l} strides = ${l}(${r});
void main() {
${u} coords = getOutputCoords();
vec4 sum = vec4(0.);
vec4 found = vec4(0.);
for (int i = 0; i < ${e}; i+=2) {
ivec2 flattenedIndex = ivec2(0);
for (int j = 0; j < ${t}; j+=2) {
ivec4 index = round(${d});
flattenedIndex += index.xz * ${g};
if (j + 1 < ${t}) {
flattenedIndex += index.yw * ${b};
}
}
if (flattenedIndex[0] == coords[0] || flattenedIndex[1] == coords[0] ||
flattenedIndex[0] == coords[0] + 1 || flattenedIndex[1] == coords[0] + 1) {
vec4 updVals = ${h};
if (flattenedIndex[0] == coords[0]) {
sum.xy += updVals.xy;
found.xy = vec2(1.);
} else if (flattenedIndex[0] == coords[0] + 1) {
sum.zw += updVals.xy;
found.zw = vec2(1.);
}
if (flattenedIndex[1] == coords[0]) {
sum.xy += updVals.zw;
found.xy = vec2(1.);
} else if (flattenedIndex[1] == coords[0] + 1) {
sum.zw += updVals.zw;
found.zw = vec2(1.);
}
}
}
setOutput(mix(${f}, sum, found));
}
`}};function aie(e){let{inputs:t,backend:n,attrs:a}=e,{indices:r,updates:s}=t,{shape:i}=a,{sliceRank:o,numUpdates:l,sliceSize:u,strides:p,outputSize:d}=N.calculateShapes(s,r,i),c=[d/u,u];if(d===0)return n.makeTensorInfo(i,r.dtype);let h=ce({inputs:{x:r},backend:n,attrs:{shape:[l,o]}}),m=ce({inputs:{x:s},backend:n,attrs:{shape:[l,u]}}),f=n.makeTensorInfo([],"float32",new Float32Array([0])),g;G().getBool("WEBGL_PACK")?g=new nie(l,o,h.shape.length,m.shape.length,p,c):g=new Y1(l,o,h.shape.length,m.shape.length,p,c);let b=n.runWebGLProgram(g,[m,h,f],m.dtype),y=ce({inputs:{x:b},backend:n,attrs:{shape:i}});return n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(b),n.disposeIntermediateTensorInfo(f),y}var rie={kernelName:Ru,backendName:"webgl",kernelFunc:aie},sie=class{constructor(e,t,n,a){this.variableNames=["sortedSequence","values"],this.customUniforms=[{name:"numInputs",type:"int"}],this.outputShape=[e,n];let r="while (left < right) {",s=`for (int i = 0; i < ${Math.ceil(Math.log2(t+1))}; ++i) { if (left >= right) break;`,i=G().getNumber("WEBGL_VERSION")===2?r:s,o=a==="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 iie(e){let{inputs:t,backend:n,attrs:a}=e,{sortedSequence:r,values:s}=t,{side:i}=a,o=new sie(r.shape[0],r.shape[1],s.shape[1],i),l=[[r.shape[1]]];return n.runWebGLProgram(o,[r,s],"int32",l)}var oie={kernelName:Pu,backendName:"webgl",kernelFunc:iie},lie=class{constructor(e,t,n){this.variableNames=["c","a","b"],this.outputShape=t;let a,r;if(n>4)throw Error(`Where for rank ${n} is not yet supported`);if(n===1)r="resRC",a="resRC";else{let i=["resRC.x","resRC.y","resRC.z","resRC.w"],o=[],l=[];for(let u=0;u<t.length;u++)l.push(`${i[u]}`),u<e&&o.push(`${i[u]}`);a=o.join(),r=l.join()}let s=ct(n);this.userCode=`
void main() {
${s} resRC = getOutputCoords();
float cVal = getC(${a});
if (cVal >= 1.0) {
setOutput(getA(${r}));
} else {
setOutput(getB(${r}));
}
}
`}};function uie(e){let{inputs:t,backend:n}=e,{condition:a,t:r,e:s}=t,i=new lie(a.shape.length,r.shape,r.shape.length);return n.runWebGLProgram(i,[a,r,s],ga(r.dtype,s.dtype))}var pie={kernelName:Ou,backendName:"webgl",kernelFunc:uie},cie=`
// Stable and Attracting Fixed Point (0, 1) for Normalized Weights.
// see: https://arxiv.org/abs/1706.02515
float scaleAlpha = ${N.SELU_SCALEALPHA};
float scale = ${N.SELU_SCALE};
return (x >= 0.0) ? scale * x : scaleAlpha * (exp(x) - 1.0);
`,die=Ye({opSnippet:cie}),hie={kernelName:Co,backendName:"webgl",kernelFunc:die},mie=cp+`
return 1.0 / (1.0 + exp(-1.0 * x));
`,fie=`
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;
`,gie=Ye({opSnippet:mie,packedOpSnippet:fie,cpuKernelImpl:b9}),bie={kernelName:Ao,backendName:"webgl",kernelFunc:gie},yie=`
if (isnan(x)) { return 0.0; }
return sign(x);
`,xie=Ye({opSnippet:yie}),vie={kernelName:Eo,backendName:"webgl",kernelFunc:xie},wie=cp+`
return sin(x);
`,kie=`
vec4 result = sin(x);
bvec4 isNaN = isnan(x);
${Ko}
return result;
`,Iie=Ye({opSnippet:wie,packedOpSnippet:kie}),Sie={kernelName:_o,backendName:"webgl",kernelFunc:Iie},Nie=`
float e2x = exp(x);
return (e2x - 1.0 / e2x) / 2.0;
`,Tie=Ye({opSnippet:Nie}),Cie={kernelName:zu,backendName:"webgl",kernelFunc:Tie},_ie=`
float epsilon = 1.1920928955078125e-7;
float threshold = log(epsilon) + 2.0;
bool too_large = x > -threshold;
bool too_small = x < threshold;
float result;
float exp_x = exp(x);
if (too_large){
result = x;
}
else if (too_small){
result = exp_x;
}
else{
result = log(exp_x + 1.0);
}
return result;
`,Eie=Ye({opSnippet:_ie}),Aie={kernelName:Fo,backendName:"webgl",kernelFunc:Eie},Fie=e=>{let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{blockShape:s,paddings:i}=a;v.assert(r.shape.length<=4,()=>"spaceToBatchND for rank > 4 with a WebGL backend not implemented yet");let o=s.reduce((b,y)=>b*y),l=[[0,0]];l.push(...i);for(let b=1+s.length;b<r.shape.length;++b)l.push([0,0]);let u=[],p=xA({inputs:{x:r},backend:n,attrs:{paddings:l,constantValue:0}}),d=N.getReshaped(p.shape,s,o,!1),c=N.getPermuted(d.length,s.length,!1),h=N.getReshapedPermuted(p.shape,s,o,!1),m=ce({inputs:{x:p},backend:n,attrs:{shape:d}}),f=Sn({inputs:{x:m},backend:n,attrs:{perm:c}}),g=ce({inputs:{x:f},backend:n,attrs:{shape:h}});return u.push(p),u.push(m),u.push(f),u.forEach(b=>n.disposeIntermediateTensorInfo(b)),g},$ie={kernelName:Wu,backendName:"webgl",kernelFunc:Fie};function Die(e){let{inputs:t,backend:n}=e,{indices:a,values:r,denseShape:s,defaultValue:i}=t;if(s.shape.length!==1)throw new Error(`Dense shape must be a vector, saw:
${s.shape}`);if(a.shape.length!==2)throw new Error(`Indices must be a matrix, saw:
${a.shape}`);if(r.shape.length!==1)throw new Error(`Values must be a vector, saw:
${r.shape}`);if(i.shape.length!==0)throw new Error(`Default value must be a scalar, saw:
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${r.shape}`);if(s.shape.length!==1)throw new Error(`Segment ids should be a vector but received shape
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${r.shape}`);if(s.shape.length!==1)throw new Error(`Segment ids should be a vector but received shape
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${r} begin = ${r}(${e});
${r} strides = ${r}(${t});
void main() {
${s} coords = getOutputCoords();
setOutput(getX(${i}));
}
`}};function aoe(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{begin:s,end:i,strides:o,beginMask:l,endMask:u,ellipsisMask:p,newAxisMask:d,shrinkAxisMask:c}=a,{finalShapeSparse:h,finalShape:m,isIdentity:f,sliceDim0:g,isSimpleSlice:b,begin:y,end:x,strides:w}=Kt.sliceInfo(r.shape,s,i,o,l,u,p,d,c),I;if(f)I=ce({inputs:{x:r},backend:n,attrs:{shape:m}});else if(g||b){v.assert(r.shape.length>=1,()=>`Input must have rank at least 1, got: ${r.shape.length}`);let C=Kt.computeOutShape(y,x,w),E=dp({inputs:{x:r},backend:n,attrs:{begin:y,size:C}});I=ce({inputs:{x:E},backend:n,attrs:{shape:m}}),n.disposeIntermediateTensorInfo(E)}else if(n.shouldExecuteOnCPU([r])){let C=n.readSync(r.dataId),E=Le(r.shape,r.dtype,C),F=I9(h,E,w,y);I=n.makeTensorInfo(m,r.dtype,F.values)}else{let C=new noe(y,w,h);I=n.runWebGLProgram(C,[r],r.dtype)}let T=ce({inputs:{x:I},backend:n,attrs:{shape:m}});return n.disposeIntermediateTensorInfo(I),T}var roe={kernelName:Gu,backendName:"webgl",kernelFunc:aoe};function soe(e){let{inputs:t,backend:n,attrs:a}=e,{separator:r,nGramWidths:s,leftPad:i,rightPad:o,padWidth:l,preserveShortSequences:u}=a,{data:p,dataSplits:d}=t,c=n.readSync(p.dataId),h=n.readSync(d.dataId),[m,f]=S9(c,h,r,s,i,o,l,u);return[n.makeTensorInfo([m.length],"string",m),n.makeTensorInfo(d.shape,"int32",f)]}var ioe={kernelName:Bc,backendName:"webgl",kernelFunc:soe};function ooe(e){let{inputs:t,backend:n,attrs:a}=e,{skipEmpty:r}=a,{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=n.readSync(s.dataId),l=n.readSync(i.dataId)[0],[u,p,d]=N9(o,l,r),c=p.length;return[n.makeTensorInfo([c,2],"int32",u),n.makeTensorInfo([c],"string",p),n.makeTensorInfo([2],"int32",new Int32Array(d))]}var loe={kernelName:Vc,backendName:"webgl",kernelFunc:ooe};function uoe(e){let{inputs:t,backend:n,attrs:a}=e,{numBuckets:r}=a,{input:s}=t;if(s.dtype!=="string")throw new Error("Input must be of datatype string");if(r<=0)throw new Error("Number of buckets must be at least 1");let i=n.readSync(s.dataId),o=T9(i,r);return n.makeTensorInfo(s.shape,"int32",o)}var poe={kernelName:Uc,backendName:"webgl",kernelFunc:uoe},coe="return tan(x);",doe=Ye({opSnippet:coe}),hoe={kernelName:Oo,backendName:"webgl",kernelFunc:doe},moe=`
float e2x = exp(-2.0 * abs(x));
return sign(x) * (1.0 - e2x) / (1.0 + e2x);
`,foe=Ye({opSnippet:moe}),goe={kernelName:Lo,backendName:"webgl",kernelFunc:foe};function boe(e){let{inputs:t,backend:n,attrs:a}=e,{tensor:r,indices:s,updates:i}=t,{}=a,{sliceRank:o,numUpdates:l,sliceSize:u,strides:p,outputSize:d}=N.calculateShapes(i,s,r.shape),c=[d/u,u];if(d===0)return n.makeTensorInfo(r.shape,s.dtype);let h=ce({inputs:{x:s},backend:n,attrs:{shape:[l,o]}}),m=ce({inputs:{x:i},backend:n,attrs:{shape:[l,u]}}),f=ce({inputs:{x:r},backend:n,attrs:{shape:c}}),g=new Y1(l,o,h.shape.length,m.shape.length,p,c,!1,!0),b=n.runWebGLProgram(g,[m,h,f],f.dtype),y=ce({inputs:{x:b},backend:n,attrs:{shape:r.shape}});return n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(f),n.disposeIntermediateTensorInfo(b),y}var yoe={kernelName:Mu,backendName:"webgl",kernelFunc:boe},xoe=class{constructor(e,t){this.variableNames=["A"];let n=new Array(e.length);for(let s=0;s<n.length;s++)n[s]=e[s]*t[s];this.outputShape=n,this.rank=n.length;let a=ct(this.rank),r=voe(e);this.userCode=`
void main() {
${a} resRC = getOutputCoords();
setOutput(getA(${r}));
}
`}};function voe(e){let t=e.length;if(t>5)throw Error(`Tile for rank ${t} is not yet supported`);if(t===1)return`imod(resRC, ${e[0]})`;let n=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u"],a=[];for(let r=0;r<e.length;r++)a.push(`imod(${n[r]}, ${e[r]})`);return a.join()}function wA(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{reps:s}=a;if(r.dtype==="string"||r.shape.length>5){let o=n.readSync(r.dataId),l=r.dtype==="string"?o.map(d=>v.decodeString(d)):o,u=Le(r.shape,r.dtype,l),p=_9(u,s);return n.makeTensorInfo(p.shape,p.dtype,p.values)}let i=new xoe(r.shape,s);return n.runWebGLProgram(i,[r],r.dtype)}var woe={kernelName:xs,backendName:"webgl",kernelFunc:wA},koe=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));
}
}
`}},Ioe=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 Hs(e,t){t!==null&&e.disposeIntermediateTensorInfo(t)}function oS(e){let t=1;for(;t<e;)t*=2;return t}function Soe(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{k:s,sorted:i}=a,o=G().getNumber("TOPK_LAST_DIM_CPU_HANDOFF_SIZE_THRESHOLD"),l=G().getNumber("TOPK_K_CPU_HANDOFF_THRESHOLD"),u=r.shape,p=u[u.length-1];if(n.shouldExecuteOnCPU([r])||p<o||s>l){let F=n.readSync(r.dataId),[D,$]=E9(F,u,r.dtype,s,i);return[n.makeTensorInfo(D.shape,D.dtype,D.values),n.makeTensorInfo($.shape,$.dtype,$.values)]}if(s===0)return u[u.length-1]=0,[n.makeTensorInfo(u,r.dtype,[]),n.makeTensorInfo(u,"int32",[])];if(p===1)return[r,Cd({attrs:{shape:u,dtype:"int32",value:0},backend:n})];let d=n.texData.get(r.dataId),c=d!==null&&d.isPacked,h=c?n.unpackTensor(r):r,m=v.sizeFromShape(u)/p,f=ce({inputs:{x:h},attrs:{shape:[m,p]},backend:n});c&&Hs(n,h);let g=oS(s),b=oS(p),y=null,x=()=>y===null?[f,f]:[f,y],w=(F,D,$)=>{let S=x(),M=new koe($),B=[[p],[y===null?1:0],[Number.NEGATIVE_INFINITY],[F],[D]],U=y;y=n.runWebGLProgram(M,S,"int32",B),Hs(n,U)};for(let F=1;F<g;F*=2){let D=F*2;for(let $=F;$>=1;$/=2)w(D,$,[m,b])}for(let F=b;F>g;F/=2){let D=x(),$=new Ioe([m,F/2]),S=[[p],[y===null?1:0],[g]],M=y;y=n.runWebGLProgram($,D,"int32",S),Hs(n,M);let B=g/2,U=B*2;for(let H=B;H>=1;H/=2)w(U,H,y.shape)}let I=y;y=dp({inputs:{x:y},backend:n,attrs:{begin:0,size:[m,s]}}),Hs(n,I);let T=hA({inputs:{x:f,indices:y},backend:n,attrs:{axis:1,batchDims:1}});Hs(n,f);let C=u.slice(0,-1);C.push(s),I=y,y=ce({inputs:{x:y},attrs:{shape:C},backend:n}),Hs(n,I);let E=T;return T=ce({inputs:{x:T},attrs:{shape:C},backend:n}),Hs(n,E),[T,y]}var Noe={kernelName:Hu,backendName:"webgl",kernelFunc:Soe},Toe=class{constructor(e,t,n,a,r,s){this.variableNames=["Image","Transforms"],this.outputShape=s;let i=n==="nearest"?1:2,o;switch(a){case"constant":o=1;break;case"reflect":o=2;break;case"wrap":o=3;break;case"nearest":o=4;break;default:o=1;break}this.userCode=`
float mapCoord(float outCoord, float len) {
float inCoord = outCoord;
if(${o} == 2) {
if (inCoord < 0.0) {
if (len <= 1.0) {
inCoord = 0.0;
} else {
float sz2 = 2.0 * len;
if (inCoord < sz2) {
inCoord = sz2 * float(int(float(-inCoord / sz2))) +
inCoord;
}
inCoord = inCoord < -len ? inCoord + sz2 : -inCoord - 1.0;
}
} else if (inCoord > len - 1.0) {
if (len <= 1.0) {
inCoord = 0.0;
} else {
float sz2 = 2.0 * len;
inCoord -= sz2 * float(int(float(inCoord / sz2)));
if (inCoord >= len) {
inCoord = sz2 - inCoord - 1.0;
}
}
}
return clamp(inCoord, 0.0, len - 1.0);
} else if (${o} == 3) {
if (inCoord < 0.0) {
if (len <= 1.0) {
inCoord = 0.0;
} else {
float sz = len - 1.0;
inCoord += len * (float(int(float(-inCoord / sz))) + 1.0);
}
} else if (inCoord > len - 1.0) {
if (len <= 1.0) {
inCoord = 0.0;
} else {
float sz = len - 1.0;
inCoord -= len * float(int(float(inCoord / sz)));
}
}
return clamp(inCoord, 0.0, len - 1.0);
} else if (${o} == 4) {
return clamp(outCoord, 0.0, len - 1.0);
} else {
return outCoord;
}
}
float readWithFillValue(int batch, int coordY, int coordX,
int channel) {
float outputValue;
if (0 <= coordY && coordY < ${e} && 0 <= coordX && coordX < ${t}) {
outputValue = getImage(batch, coordY, coordX, channel);
} else {
outputValue = float(${r});
}
return outputValue;
}
void main() {
ivec4 coords = getOutputCoords();
float outputValue;
int batch = coords[0];
int x = coords[2];
int y = coords[1];
int channel = coords[3];
float xf = float(x);
float yf = float(y);
float a1 = getTransforms(batch, 0);
float a2 = getTransforms(batch, 1);
float a3 = getTransforms(batch, 2);
float b1 = getTransforms(batch, 3);
float b2 = getTransforms(batch, 4);
float b3 = getTransforms(batch, 5);
float c1 = getTransforms(batch, 6);
float c2 = getTransforms(batch, 7);
float projection = c1 * xf + c2 * yf + 1.0;
if (projection == 0.0) {
outputValue = float(${r});
} else {
float inX = (a1 * xf + a2 * yf + a3) / projection;
float inY = (b1 * xf + b2 * yf + b3) / projection;
float mapX = mapCoord(inX, float(${t}));
float mapY = mapCoord(inY, float(${e}));
if (${i} == 1) {
int coordY = int(round(mapY));
int coordX = int(round(mapX));
outputValue = readWithFillValue(batch, coordY, coordX,
channel);
} else {
float yFloor = floor(mapY);
float xFloor = floor(mapX);
float yCeil = yFloor + 1.0;
float xCeil = xFloor + 1.0;
float valueYFloor = (xCeil - mapX) *
readWithFillValue(batch, int(yFloor), int(xFloor), channel) +
(mapX - xFloor) *
readWithFillValue(batch, int(yFloor), int(xCeil), channel);
float valueYCeil = (xCeil - mapX) *
readWithFillValue(batch, int(yCeil), int(xFloor), channel) +
(mapX - xFloor) *
readWithFillValue(batch, int(yCeil), int(xCeil), channel);
outputValue = (yCeil - mapY) * valueYFloor +
(mapY - yFloor) * valueYCeil;
}
}
setOutput(outputValue);
}
`}};function Coe(e){let{inputs:t,backend:n,attrs:a}=e,{image:r,transforms:s}=t,{interpolation:i,fillMode:o,fillValue:l,outputShape:u}=a,[p,d,c,h]=r.shape,[m,f]=u!=null?u:[d,c],g=[p,m,f,h],b=new Toe(d,c,i,o,l,g);return n.runWebGLProgram(b,[r,s],"float32")}var _oe={kernelName:qu,backendName:"webgl",kernelFunc:Coe};function Eoe(e){let{inputs:t,attrs:n,backend:a}=e,{axis:r}=n,{x:s}=t;ip(s,"unique"),console.warn("WARNING: ","UI might be locked temporarily as data is being downloaded");let i=a.readSync(s.dataId),{outputValues:o,outputShape:l,indices:u}=A9(i,r,s.shape,s.dtype);return[a.makeTensorInfo(l,s.dtype,o),a.makeTensorInfo([u.length],"int32",u)]}var Aoe={kernelName:Gc,backendName:"webgl",kernelFunc:Eoe};function Foe(e){let{inputs:t,backend:n,attrs:a}=e,{value:r}=t,{axis:s}=a;s<0&&(s+=r.shape.length);let i=r,o=i.shape.length,l=r.shape[s],u=new Array(o-1),p=0;for(let f=0;f<o;f++)f!==s&&(u[p++]=i.shape[f]);let d=[],c=new Array(o).fill(0),h=i.shape.slice();h[s]=1;let m=new Array(l);for(let f=0;f<m.length;f++){c[s]=f;let g=dp({inputs:{x:i},backend:n,attrs:{begin:c,size:h}}),b=ce({inputs:{x:g},backend:n,attrs:{shape:u}});m[f]=b,d.push(g)}return d.forEach(f=>n.disposeIntermediateTensorInfo(f)),m}var $oe={kernelName:ju,backendName:"webgl",kernelFunc:Foe},Doe=class{constructor(e,t){this.variableNames=["x","segmentIds"];let n=e.windowSize,a=e.batchSize,r=e.inSize,s=e.numSegments,i=s*Math.ceil(r/n);this.outputShape=[a,i];let o="0.0",l="sumValue",u=Math.floor(n/4)*4,p=n%4,d=`
sumValue += dot(values, segFilter);
`,c="";r%n>0&&(c=`
if (inIdx < 0 || inIdx >= ${r}) {
return initializationValue;
}
`);let h="";r%n>0&&(h=`
if (inIdx < 0 || inIdx >= ${r}) {
return -1.0;
}
`),this.userCode=`
const float initializationValue = ${o};
float getValue(int batch, int inIdx) {
${c}
return getX(batch, inIdx);
}
float getSegmentIdAtIndex(int inIdx) {
${h}
return getSegmentIds(inIdx);
}
void main() {
ivec2 coords = getOutputCoords();
int batch = coords[0];
int outIdx = coords[1];
int inOffset = int(floor(float(outIdx) / float(
${s})) * float(${n}));
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
);
${d}
}
int inIdx = inOffset + ${u};
if (${p===1}) {
vec4 values = vec4(
getValue(batch, inIdx),
initializationValue,
initializationValue,
initializationValue
);
int inIdxSeg = int(getSegmentIdAtIndex(inIdx));
vec4 segFilter = vec4(
int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,
0,
0,
0
);
${d}
} else if (${p===2}) {
vec4 values = vec4(
getValue(batch, inIdx),
getValue(batch, inIdx + 1),
initializationValue,
initializationValue
);
vec4 segFilter = vec4(
int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,
int(getSegmentIdAtIndex(inIdx + 1)) == currentSeg ? 1 : 0,
0,
0
);
${d}
} else if (${p===3}) {
vec4 values = vec4(
getValue(batch, inIdx),
getValue(batch, inIdx + 1),
getValue(batch, inIdx + 2),
initializationValue
);
vec4 segFilter = vec4(
int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,
int(getSegmentIdAtIndex(inIdx + 1)) == currentSeg ? 1 : 0,
int(getSegmentIdAtIndex(inIdx + 2)) == currentSeg ? 1 : 0,
0
);
${d}
}
setOutput(${l});
}
`}};function Roe(e){let{inputs:t,backend:n,attrs:a}=e,{x:r,segmentIds:s}=t,{numSegments:i}=a,o=r.shape.length,l=[],u=0,p=N.getAxesPermutation([u],o),d=r;p!=null&&(d=Sn({inputs:{x:r},backend:n,attrs:{perm:p}}),l.push(d),u=N.getInnerMostAxes(1,o)[0]);let c=N.segment_util.computeOutShape(d.shape,u,i),h=v.sizeFromShape([d.shape[u]]),m=ce({inputs:{x:d},backend:n,attrs:{shape:[-1,h]}});l.push(m);let f=Rm(r.dtype),g=(w,I,T,C,E)=>{let F=w.shape[0],D=w.shape[1],$=N.segment_util.segOpComputeOptimalWindowSize(D,E),S={windowSize:$,inSize:D,batchSize:F,numSegments:E},M=new Doe(S,I),B=n.compileAndRun(M,[w,T],C);if(l.push(B),B.shape[1]===E)return B;let U=vA({backend:n,attrs:{start:0,stop:E,step:1,dtype:"float32"}}),H=wA({inputs:{x:U},backend:n,attrs:{reps:[D/$]}});return l.push(U),l.push(H),g(B,I,H,C,E)},b=g(m,"unsortedSegmentSum",s,f,i),y=ce({inputs:{x:b},backend:n,attrs:{shape:c}}),x=y;if(p!=null){l.push(y);let w=N.getUndoAxesPermutation(p);x=Sn({inputs:{x},backend:n,attrs:{perm:w}})}return l.forEach(w=>n.disposeIntermediateTensorInfo(w)),x}var Moe={kernelName:Hc,backendName:"webgl",kernelFunc:Roe},Poe=[IQ,NQ,_Q,FQ,DQ,PQ,LQ,WQ,GQ,qQ,XQ,JQ,tee,see,lee,pee,dee,gee,yee,vee,See,Fee,Dee,Mee,Bee,Uee,jee,iQ,Yee,tte,ste,cte,mte,gte,yte,vte,Ste,Cte,Ate,$te,Rte,Pte,zte,Bte,Hte,jte,Yte,Qte,tne,sne,une,hne,gne,xne,vne,kne,Sne,Tne,_ne,Ane,Rne,One,Wne,Vne,Hne,Kne,Jne,nae,sQ,rae,Qee,oae,pae,hae,lQ,bae,wae,Iae,Cae,Aae,Rae,Oae,Bae,Hae,Kae,Yae,ere,nre,rre,lre,pre,dre,mre,gre,vre,Sre,_re,Pre,cQ,Wre,Ure,qre,Xre,Oee,Jre,ese,nse,sse,use,pQ,cse,hse,fse,bse,yse,Lee,$re,wse,Nse,Ese,hQ,Dse,Pse,Wse,Use,jse,Xse,Jse,tie,rie,oie,pie,hie,bie,vie,Sie,Cie,Eee,Rre,Aie,$ie,Rie,Pie,Lie,Wie,Vie,Gie,qie,Xie,Zie,Qie,toe,roe,ioe,loe,poe,Dre,vQ,hoe,goe,yoe,woe,Noe,_oe,wQ,Aoe,$oe,Moe,Qre];for(let e of Poe)qc(e);var et;(function(e){e[e.float32=0]="float32",e[e.int32=1]="int32",e[e.bool=2]="bool",e[e.string=3]="string",e[e.complex64=4]="complex64"})(et||(et={}));var Nc;(function(e){e[e.linear=0]="linear",e[e.relu=1]="relu",e[e.relu6=2]="relu6",e[e.prelu=3]="prelu",e[e.leakyrelu=4]="leakyrelu",e[e.sigmoid=5]="sigmoid",e[e.elu=6]="elu"})(Nc||(Nc={}));var kA;function Ooe(e){kA=e.wasm.cwrap(si,null,["number","array","number","number","array","number","number","number","number","number","number","number","number"])}function Loe(e){let{inputs:t,backend:n,attrs:a}=e,{a:r,b:s,bias:i,preluActivationWeights:o}=t;if(r.dtype!=="float32"||s.dtype!=="float32")throw new Error("_FusedMatMul for non non-float32 tensors not yet supported.");let{transposeA:l,transposeB:u,activation:p,leakyreluAlpha:d}=a,c=n.dataIdMap.get(r.dataId).id,h=n.dataIdMap.get(s.dataId).id,m=0;if(i!=null){let E=n.dataIdMap.get(i.dataId);if(E.shape.length!==1)throw new Error(`_FusedMatMul only supports rank-1 bias but got rank ${E.shape.length}.`);m=E.id}let f=o==null?0:n.dataIdMap.get(o.dataId).id,g=Nc[p];if(g==null)throw new Error(`${p} activation not yet supported for FusedConv2D in the wasm backend.`);let b=l?r.shape[2]:r.shape[1],y=u?s.shape[1]:s.shape[2],x=Yu.assertAndGetBroadcastShape(r.shape.slice(0,-2),s.shape.slice(0,-2)),w=n.makeOutput([...x,b,y],r.dtype),I=n.dataIdMap.get(w.dataId).id,T=new Uint8Array(new Int32Array(r.shape).buffer),C=new Uint8Array(new Int32Array(s.shape).buffer);return kA(c,T,r.shape.length,h,C,s.shape.length,l,u,g,m,f,d||0,I),w}var zoe={kernelName:si,backendName:"wasm",setupFunc:Ooe,kernelFunc:Loe};function Je(e,t){let n;function a(s){n=s.wasm.cwrap(e,null,["number","number","number"])}function r(s){let{backend:i,inputs:{x:o}}=s,l=i.dataIdMap.get(o.dataId).id,u=i.makeOutput(o.shape,t||o.dtype),p=i.dataIdMap.get(u.dataId).id;return v.sizeFromShape(u.shape)===0||n(l,et[o.dtype],p),u}return{kernelName:e,backendName:"wasm",setupFunc:a,kernelFunc:r}}var Woe=Je(ql),Boe=Je(Ii),Voe=Je(Si);function ln(e,t,n){let a;function r(i){a=i.wasm.cwrap(e,null,["number","array","number","number","array","number","number","number"])}function s(i){let{backend:o,inputs:l}=i,{a:u,b:p}=l,d=o.dataIdMap.get(u.dataId).id,c=o.dataIdMap.get(p.dataId).id,h=n!=null?n:u.dtype,m=N.assertAndGetBroadcastShape(u.shape,p.shape),f=o.makeOutput(m,h);if(v.sizeFromShape(m)===0)return f;let g=new Uint8Array(new Int32Array(u.shape).buffer),b=new Uint8Array(new Int32Array(p.shape).buffer),y=o.dataIdMap.get(f.dataId).id;return a(d,g,u.shape.length,c,b,p.shape.length,et[u.dtype],y),f}return{kernelName:e,backendName:"wasm",setupFunc:r,kernelFunc:s}}var Uoe=!0,Goe=ln(bs,Uoe),IA;function Hoe(e){IA=e.wasm.cwrap(Ni,null,["array","number","number","number"])}function qoe(e){let{inputs:t,backend:n}=e,a=n.makeOutput(t[0].shape,t[0].dtype);if(v.sizeFromShape(a.shape)===0)return a;let r=t.map(o=>n.dataIdMap.get(o.dataId).id),s=new Uint8Array(new Int32Array(r).buffer),i=n.dataIdMap.get(a.dataId).id;return IA(s,r.length,et[a.dtype],i),a}var joe={kernelName:Ni,backendName:"wasm",setupFunc:Hoe,kernelFunc:qoe};function Bf(e){let{inputs:{x:t},backend:n}=e;if(t.dtype==="string")return bn(n.readSync(t.dataId),t.shape,t.dtype);let a=n.makeOutput(t.shape,t.dtype),r=n.typedArrayFromHeap(t);return n.typedArrayFromHeap(a).set(r),a}var Koe={kernelName:Zi,backendName:"wasm",kernelFunc:Bf},SA;function Xoe(e){SA=e.wasm.cwrap(_r,null,["number","array","number","number","number","array","number"])}function fs(e){let{inputs:t,backend:n,attrs:a}=e,[r,s]=Zoe(t.x.shape,a.perm),i=!0;for(let m=0;m<s.length;m++)s[m]!==m&&(i=!1);let o=Yoe(t.x.shape,a.perm),l={dataId:t.x.dataId,shape:r,dtype:t.x.dtype};if(i){let m=Bf({inputs:t,backend:n});return m.shape=o,m}let u=n.makeOutput(o,l.dtype),p=n.dataIdMap.get(l.dataId).id,d=n.dataIdMap.get(u.dataId).id,c=new Uint8Array(new Int32Array(s).buffer),h=new Uint8Array(new Int32Array(l.shape).buffer);return SA(p,h,l.shape.length,et[l.dtype],d,c,s.length),u}function Yoe(e,t){let n=new Array(e.length);for(let a=0;a<n.length;a++)n[a]=e[t[a]];return n}function Zoe(e,t){let n=[],a=[];for(let r=0;r<e.length;++r)e[r]!==1&&n.push(e[r]),e[t[r]]!==1&&a.push(t[r]);for(let r=0;r<a.length;++r){let s=-1;for(let i=0;i<a.length;++i)a[i]>=r&&(s===-1||a[s]>a[i])&&(s=i);a[s]=r}return[n,a]}var Joe={kernelName:_r,backendName:"wasm",kernelFunc:fs,setupFunc:Xoe};function As(e,t,n){let a=e.shape,r=e.shape.length,s=v.parseAxisParam(t,a),i=s,o=N.getAxesPermutation(i,r),l=null,u=!1;if(o!=null){let p=new Array(r);for(let c=0;c<p.length;c++)p[c]=a[o[c]];i=N.getInnerMostAxes(i.length,r),l=fs({inputs:{x:e},attrs:{perm:o},backend:n});let d=n.dataIdMap.get(e.dataId).id;n.dataIdMap.get(l.dataId).id!==d&&(u=!0)}return{transposed:l,originalAxes:s,axes:i,inputWasTransposed:u}}var NA;function Qoe(e){NA=e.wasm.cwrap(jl,null,["number, number, number"])}function ele(e){let{backend:t,inputs:n,attrs:a}=e,{axis:r,keepDims:s}=a,{x:i}=n,o=t.dataIdMap.get(i.dataId).id,l=i,{transposed:u,axes:p,originalAxes:d,inputWasTransposed:c}=As(i,r,t);if(c){let y=t.dataIdMap.get(u.dataId).id;l=u,o=y}let h=l.shape.length;N.assertAxesAreInnerMostDims("all",p,h);let[m,f]=N.computeOutAndReduceShapes(l.shape,p),g=v.sizeFromShape(f),b=t.makeOutput(m,i.dtype);if(v.sizeFromShape(l.shape)!==0){let y=t.dataIdMap.get(b.dataId).id;NA(o,g,y)}if(c&&t.disposeData(u.dataId),s){let y=N.expandShapeToKeepDim(b.shape,d);b.shape=y}return b}var tle={kernelName:jl,backendName:"wasm",setupFunc:Qoe,kernelFunc:ele},TA;function nle(e){TA=e.wasm.cwrap(Kl,null,["number, number, number"])}function ale(e){let{backend:t,inputs:n,attrs:a}=e,{axis:r,keepDims:s}=a,{x:i}=n,o=t.dataIdMap.get(i.dataId).id,l=i,{transposed:u,axes:p,originalAxes:d,inputWasTransposed:c}=As(i,r,t);if(c){let y=t.dataIdMap.get(u.dataId).id;l=u,o=y}let h=l.shape.length;N.assertAxesAreInnerMostDims("any",p,h);let[m,f]=N.computeOutAndReduceShapes(l.shape,p),g=v.sizeFromShape(f),b=t.makeOutput(m,i.dtype);if(v.sizeFromShape(l.shape)!==0){let y=t.dataIdMap.get(b.dataId).id;TA(o,g,y)}if(c&&t.disposeData(u.dataId),s){let y=N.expandShapeToKeepDim(b.shape,d);b.shape=y}return b}var rle={kernelName:Kl,backendName:"wasm",setupFunc:nle,kernelFunc:ale};function CA(e){let t;function n(r){t=r.wasm.cwrap(e,null,["number","number","number","number","number"])}function a(r){let{backend:s,inputs:i,attrs:o}=r,{axis:l}=o,{x:u}=i,p=s.dataIdMap.get(u.dataId).id,d=p,c=u,{transposed:h,axes:m,inputWasTransposed:f}=As(u,l,s);if(f){let I=s.dataIdMap.get(h.dataId).id;I!==p&&(c=h,d=I)}let g=c.shape.slice(0,-1),b=s.makeOutput(g,"int32"),y=s.dataIdMap.get(b.dataId).id,x=v.sizeFromShape(b.shape),w=c.shape[m[0]];return t(d,et[c.dtype],x,w,y),f&&s.disposeData(h.dataId),b}return{kernelName:e,backendName:"wasm",setupFunc:n,kernelFunc:a}}var sle=CA(Xl),ile=CA(Yl),ole=Je(Ti),lle=Je(Ci),ule=Je(_i),ple=ln(Ai,!1),cle=Je(Ei),_A;function dle(e){_A=e.wasm.cwrap(Fi,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function hle(e){let{inputs:t,attrs:n,backend:a}=e,r=t.x,s=a.dataIdMap.get(r.dataId).id,{filterSize:i,strides:o,pad:l,dimRoundingMode:u}=n,p=N.computePool2DInfo(r.shape,i,o,1,l,u),d=p.filterHeight,c=p.filterWidth,h=p.padInfo.top,m=p.padInfo.right,f=p.padInfo.bottom,g=p.padInfo.left,b=p.strideHeight,y=p.strideWidth,x=p.inChannels;if(p.dataFormat!=="channelsLast")throw new Error(`wasm backend does not support dataFormat:'${p.dataFormat}'. Please use 'channelsLast'.`);if(p.dilationWidth!==1||p.dilationHeight!==1)throw new Error(`was backend only supports average pooling with dilation = [1, 1], got [${p.dilationHeight}, ${p.dilationWidth}].`);let w=a.makeOutput(p.outShape,"float32"),I=a.dataIdMap.get(w.dataId).id;return _A(s,r.shape[0],r.shape[1],r.shape[2],d,c,h,m,f,g,b,y,x,I),w}var mle={kernelName:Fi,backendName:"wasm",setupFunc:dle,kernelFunc:hle},EA;function fle(e){EA=e.wasm.cwrap("AvgPool3D",null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function gle(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{filterSize:s,strides:i,pad:o,dimRoundingMode:l,dataFormat:u}=a,p=N.computePool3DInfo(r.shape,s,i,1,o,l,u),d=n.makeOutput(p.outShape,r.dtype);return EA(n.dataIdMap.get(r.dataId).id,n.dataIdMap.get(d.dataId).id,p.batchSize,p.inChannels,p.inDepth,p.inHeight,p.inWidth,p.outDepth,p.outHeight,p.outWidth,p.strideDepth,p.strideHeight,p.strideWidth,p.dilationDepth,p.dilationHeight,p.dilationWidth,p.effectiveFilterDepth,p.effectiveFilterHeight,p.effectiveFilterWidth,p.padInfo.front,p.padInfo.top,p.padInfo.left),d}var ble={kernelName:Zl,backendName:"wasm",setupFunc:fle,kernelFunc:gle},AA;function yle(e){AA=e.wasm.cwrap("AvgPool3DGrad",null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function xle(e){let{inputs:t,backend:n,attrs:a}=e,{dy:r,input:s}=t,{filterSize:i,strides:o,pad:l,dimRoundingMode:u}=a,p=N.computePool3DInfo(s.shape,i,o,1,l,u),d=n.makeOutput(s.shape,s.dtype);return AA(n.dataIdMap.get(r.dataId).id,n.dataIdMap.get(d.dataId).id,p.batchSize,p.inChannels,p.inDepth,p.inHeight,p.inWidth,p.outDepth,p.outHeight,p.outWidth,p.strideDepth,p.strideHeight,p.strideWidth,p.dilationDepth,p.dilationHeight,p.dilationWidth,p.effectiveFilterDepth,p.effectiveFilterHeight,p.effectiveFilterWidth,p.padInfo.front,p.padInfo.top,p.padInfo.left,p.filterDepth,p.filterHeight,p.filterWidth),d}var vle={kernelName:_c,backendName:"wasm",setupFunc:yle,kernelFunc:xle};function Wn(e){let{inputs:t,attrs:n}=e,{x:a}=t,{shape:r}=n,s=v.sizeFromShape(a.shape),i=v.inferFromImplicitShape(r,s);return v.assert(s===v.sizeFromShape(i),()=>`new shape: ${i}, old shape: ${a.shape}. New shape and old shape must have the same number of elements.`),e.backend.incRef(a.dataId),{dataId:a.dataId,shape:i,dtype:a.dtype}}var wle={kernelName:Fu,backendName:"wasm",kernelFunc:Wn},FA;function kle(e){FA=e.wasm.cwrap($i,null,["number","array","number","number","array","number","number","number","number"])}function Ile(e){let{inputs:t,backend:n,attrs:a}=e,{a:r,b:s}=t,{transposeA:i,transposeB:o}=a;if(r.dtype!=="float32"||s.dtype!=="float32")throw new Error("BatchMatMul for non non-float32 tensors not yet supported.");let l=r.shape.length,u=s.shape.length,p=i?r.shape[l-2]:r.shape[l-1],d=o?s.shape[u-1]:s.shape[u-2],c=i?r.shape[l-1]:r.shape[l-2],h=o?s.shape[u-2]:s.shape[u-1],m=r.shape.slice(0,-2),f=s.shape.slice(0,-2),g=v.sizeFromShape(m),b=v.sizeFromShape(f),y=Yu.assertAndGetBroadcastShape(r.shape.slice(0,-2),s.shape.slice(0,-2)).concat([c,h]);v.assert(p===d,()=>`Error in matMul: inner shapes (${p}) and (${d}) of Tensors with shapes ${r.shape} and ${s.shape} and transposeA=${i} and transposeB=${o} must match.`);let x=i?[g,p,c]:[g,c,p],w=o?[b,h,d]:[b,d,h],I=Wn({inputs:{x:r},backend:n,attrs:{shape:x}}),T=Wn({inputs:{x:s},backend:n,attrs:{shape:w}}),C=n.dataIdMap.get(I.dataId).id,E=n.dataIdMap.get(T.dataId).id,F=i?I.shape[2]:I.shape[1],D=o?T.shape[1]:T.shape[2],$=Math.max(g,b),S=n.makeOutput([$,F,D],I.dtype),M=n.dataIdMap.get(S.dataId).id,B=new Uint8Array(new Int32Array(I.shape).buffer),U=new Uint8Array(new Int32Array(T.shape).buffer);return FA(C,B,I.shape.length,E,U,T.shape.length,i,o,M),n.disposeData(I.dataId),n.disposeData(T.dataId),S.shape=y,S}var Sle={kernelName:$i,backendName:"wasm",setupFunc:kle,kernelFunc:Ile};function wi(e){let{inputs:{x:t},attrs:{begin:n,size:a},backend:r}=e,[s,i]=Kt.parseSliceParams(t,n,a),o=Kt.isSliceContinous(t.shape,s,i),l=r.readSync(t.dataId),u=r.makeOutput(i,t.dtype),p=v.computeStrides(t.shape),d=r.dataIdMap.get(u.dataId);if(o){let m=Kt.computeFlatOffset(s,p);return t.dtype==="string"?d.stringBytes=l.slice(m,m+v.sizeFromShape(i)):r.typedArrayFromHeap(u).set(l.subarray(m,m+v.sizeFromShape(i))),u}if(t.dtype==="string"){let m=sm(l,s,i,t.shape,t.dtype);return d.stringBytes=m,u}let c=r.typedArrayFromHeap(u),h=t.shape.length;if(h===2)Nle(l,p[0],c,s,i);else if(h===3)Tle(l,p[0],p[1],c,s,i);else if(h===4)Cle(l,p[0],p[1],p[2],c,s,i);else{let m=sm(l,s,i,t.shape,t.dtype);c.set(m)}return u}function Nle(e,t,n,a,r){let s=0,i=a[0],o=a[1],l=i+r[0];for(let u=i;u<l;u++){let p=u*t+o;n.set(e.subarray(p,p+r[1]),s),s+=r[1]}}function Tle(e,t,n,a,r,s){let i=0,o=r[0],l=r[1],u=r[2],p=o+s[0],d=l+s[1];for(let c=o;c<p;c++)for(let h=l;h<d;h++){let m=c*t+h*n+u;a.set(e.subarray(m,m+s[2]),i),i+=s[2]}}function Cle(e,t,n,a,r,s,i){let o=0,l=s[0],u=s[1],p=s[2],d=l+i[0],c=u+i[1],h=p+i[2],m=s[3];for(let f=l;f<d;f++)for(let g=u;g<c;g++)for(let b=p;b<h;b++){let y=f*t+g*n+b*a+m;r.set(e.subarray(y,y+i[3]),o),o+=i[3]}}var _le={kernelName:Lu,backendName:"wasm",kernelFunc:wi};function Ele(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{blockShape:s,crops:i}=a,o=s.reduce((b,y)=>b*y),l=N.getReshaped(r.shape,s,o),u=N.getPermuted(l.length,s.length),p=N.getReshapedPermuted(r.shape,s,o),d=N.getSliceBeginCoords(i,s.length),c=N.getSliceSize(p,i,s.length),h=Wn({inputs:{x:r},backend:n,attrs:{shape:l}}),m=fs({inputs:{x:h},backend:n,attrs:{perm:u}}),f=Wn({inputs:{x:m},backend:n,attrs:{shape:p}}),g=wi({inputs:{x:f},backend:n,attrs:{begin:d,size:c}});return n.disposeData(h.dataId),n.disposeData(m.dataId),n.disposeData(h.dataId),g}var Ale={kernelName:Jl,backendName:"wasm",kernelFunc:Ele},$A;function Fle(e){$A=e.wasm.cwrap(Ql,null,["number","number","boolean","number","number","number"])}function $le(e){let{backend:t,inputs:n,attrs:a}=e,{x:r,weights:s}=n,{size:i}=a,o=s.shape.reduce((d,c)=>d*c,1)!==0,l=r.shape.length===1?[i]:[r.shape[0],i],u=t.makeOutput(l,s.dtype);function p(d){return t.dataIdMap.get(d.dataId).id}return $A(p(r),i,o,p(s),et[s.dtype],p(u)),u}var Dle={kernelName:Ql,backendName:"wasm",setupFunc:Fle,kernelFunc:$le};function Rle(e){let{inputs:t,backend:n}=e,{s0:a,s1:r}=t,s=n.typedArrayFromHeap(a),i=n.typedArrayFromHeap(r),o=N.assertAndGetBroadcastShape(Array.from(s),Array.from(i));return n.makeOutput([o.length],"int32",void 0,new Int32Array(o))}var Mle={kernelName:Ec,backendName:"wasm",kernelFunc:Rle};function Fs(e){let{inputs:{x:t},attrs:{dtype:n},backend:a}=e,r=a.makeOutput(t.shape,n),s=a.typedArrayFromHeap(t);return a.typedArrayFromHeap(r).set(s),r}var Ple={kernelName:Di,backendName:"wasm",kernelFunc:Fs},Ole=Je(Ri),DA;function Lle(e){DA=e.wasm.cwrap(ys,null,["number","number","number","number"])}function zle(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{clipValueMin:s,clipValueMax:i}=a,o=n.dataIdMap.get(r.dataId).id,l=n.makeOutput(r.shape,r.dtype),u=n.dataIdMap.get(l.dataId).id;return DA(o,s,i,u),l}var Wle={kernelName:ys,backendName:"wasm",setupFunc:Lle,kernelFunc:zle};function RA(e){let{inputs:t,backend:n}=e,a=v.parseAxisParam(e.attrs.axis,t[0].shape)[0],r=t.map(h=>h.shape);N.assertParamsConsistent(r,a);let s=N.computeOutShape(t.map(h=>h.shape),a),i=t.filter(h=>v.sizeFromShape(h.shape)>0);if(i.length===1)return Bf({inputs:{x:i[0]},backend:n});let o=n.makeOutput(s,t[0].dtype);if(v.sizeFromShape(s)===0)return o;if(i[0].dtype==="string"){let h=i.map(x=>{let w=[-1,v.sizeFromShape(x.shape.slice(a))];return Wn({inputs:{x},backend:n,attrs:{shape:w}})}),m=h.map(x=>({vals:n.readSync(x.dataId),shape:x.shape}));s=N.computeOutShape(h.map(x=>x.shape),1);let f=h[0].shape[0]===1,g=I1(m,s,t[0].dtype,f),b=N.computeOutShape(i.map(x=>x.shape),a);o.shape=b;let y=n.dataIdMap.get(o.dataId);return y.stringBytes=N.fromStringArrayToUint8(g),h.forEach(x=>n.disposeData(x.dataId)),o}let l=v.sizeFromShape(i[0].shape.slice(0,a)),u=0,p=i.map(h=>{let m=v.sizeFromShape(h.shape.slice(a));return u+=m,m}),d=i.map(h=>n.typedArrayFromHeap(h)),c=n.typedArrayFromHeap(o);for(let h=0;h<l;h++){let m=h*u;for(let f=0;f<d.length;f++){let g=p[f],b=h*g,y=d[f].subarray(b,b+g);c.set(y,m),m+=g}}return o}var Ble={kernelName:eu,backendName:"wasm",kernelFunc:RA},MA;function Vle(e){MA=e.wasm.cwrap(Mi,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function Ule(e){let{inputs:t,attrs:n,backend:a}=e,{x:r,filter:s}=t,i=a.dataIdMap.get(r.dataId).id,o=a.dataIdMap.get(s.dataId).id,{strides:l,dilations:u,pad:p,dimRoundingMode:d,dataFormat:c}=n,h=N.convertConv2DDataFormat(c),m=N.computeConv2DInfo(r.shape,s.shape,l,u,p,d,!1,h),f=m.filterHeight,g=m.filterWidth,b=m.padInfo.top,y=m.padInfo.right,x=m.padInfo.bottom,w=m.padInfo.left,I=m.dilationHeight,T=m.dilationWidth,C=m.strideHeight,E=m.strideWidth,F=m.inChannels,D=m.outChannels,$=m.padInfo.type==="SAME"?1:0;if(m.dataFormat!=="channelsLast")throw new Error(`wasm backend Conv2D does not support dataFormat:'${m.dataFormat}'. Please use 'channelsLast'.`);let S=a.makeOutput(m.outShape,"float32"),M=a.dataIdMap.get(S.dataId).id;return MA(i,r.shape[0],r.shape[1],r.shape[2],o,f,g,b,y,x,w,$,I,T,C,E,F,D,M),S}var Gle={kernelName:Mi,backendName:"wasm",setupFunc:Vle,kernelFunc:Ule},PA;function Hle(e){PA=e.wasm.cwrap(Pi,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function qle(e){let{backend:t,inputs:n,attrs:a}=e,{dy:r,filter:s}=n,{strides:i,pad:o,dataFormat:l,dimRoundingMode:u,inputShape:p}=a,d=1,c=N.convertConv2DDataFormat(l),h=N.computeConv2DInfo(p,s.shape,i,d,o,u,!1,c),{batchSize:m,filterHeight:f,filterWidth:g,inChannels:b,inHeight:y,inWidth:x,outChannels:w,outHeight:I,outWidth:T,strideHeight:C,strideWidth:E}=h,F=f-1-h.padInfo.top,D=g-1-h.padInfo.left,$=h.dataFormat==="channelsLast",S=v.computeStrides(h.inShape),M=v.computeStrides(r.shape),[B,U,H]=v.computeStrides(s.shape),j=S[0],K=$?S[1]:S[2],Z=$?S[2]:1,J=$?1:S[1],ee=M[0],ae=$?M[1]:M[2],te=$?M[2]:1,re=$?1:M[1],se=t.makeOutput(h.inShape,"float32"),ye=t.dataIdMap.get(se.dataId).id,ue=t.dataIdMap.get(r.dataId).id,be=t.dataIdMap.get(s.dataId).id;return PA(ue,be,m,f,g,y,x,b,I,T,w,C,E,F,D,B,U,H,j,K,Z,J,ee,ae,te,re,ye),se}var jle={kernelName:Pi,backendName:"wasm",setupFunc:Hle,kernelFunc:qle},OA;function Kle(e){OA=e.wasm.cwrap(Oi,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function Xle(e){let{inputs:t,backend:n,attrs:a}=e,{x:r,filter:s}=t,{strides:i,pad:o,dilations:l}=a;if(r.dtype!=="float32")throw new Error(`Tensor x must have dtype float32, got ${r.dtype}`);if(s.dtype!=="float32")throw new Error(`Tensor filter must have dtype float32, got ${s.dtype}`);let u=N.computeConv3DInfo(r.shape,s.shape,i,l,o),p=n.makeOutput(u.outShape,r.dtype);return OA(n.dataIdMap.get(r.dataId).id,n.dataIdMap.get(s.dataId).id,n.dataIdMap.get(p.dataId).id,u.batchSize,u.inDepth,u.inHeight,u.inWidth,u.inChannels,u.outDepth,u.outHeight,u.outWidth,u.outChannels,u.strideDepth,u.strideHeight,u.strideWidth,u.dilationDepth,u.dilationHeight,u.dilationWidth,u.filterDepth,u.filterHeight,u.filterWidth,u.padInfo.front,u.padInfo.top,u.padInfo.left),p}var Yle={kernelName:Oi,backendName:"wasm",setupFunc:Kle,kernelFunc:Xle},LA;function Zle(e){LA=e.wasm.cwrap(tu,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function Jle(e){let{inputs:t,backend:n,attrs:a}=e,{x:r,dy:s}=t,{strides:i,pad:o,filterShape:l}=a;if(r.dtype!=="float32")throw new Error(`Tensor dy must have dtype float32, got ${r.dtype}`);if(s.dtype!=="float32")throw new Error(`Tensor filter must have dtype float32, got ${s.dtype}`);let u=N.computeConv3DInfo(r.shape,l,i,1,o),p=n.makeOutput(u.filterShape,s.dtype);return LA(n.dataIdMap.get(r.dataId).id,n.dataIdMap.get(s.dataId).id,n.dataIdMap.get(p.dataId).id,u.batchSize,u.inDepth,u.inHeight,u.inWidth,u.inChannels,u.outDepth,u.outHeight,u.outWidth,u.outChannels,u.strideDepth,u.strideHeight,u.strideWidth,u.dilationDepth,u.dilationHeight,u.dilationWidth,u.filterDepth,u.filterHeight,u.filterWidth,u.padInfo.front,u.padInfo.top,u.padInfo.left),p}var Qle={kernelName:tu,backendName:"wasm",setupFunc:Zle,kernelFunc:Jle},zA;function eue(e){zA=e.wasm.cwrap(nu,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function tue(e){let{inputs:t,backend:n,attrs:a}=e,{dy:r,filter:s}=t,{pad:i,strides:o,inputShape:l}=a;if(r.dtype!=="float32")throw new Error(`Tensor dy must have dtype float32, got ${r.dtype}`);if(s.dtype!=="float32")throw new Error(`Tensor filter must have dtype float32, got ${s.dtype}`);let u=N.computeConv3DInfo(l,s.shape,o,1,i),p=n.makeOutput(u.inShape,r.dtype);return zA(n.dataIdMap.get(s.dataId).id,n.dataIdMap.get(r.dataId).id,n.dataIdMap.get(p.dataId).id,u.batchSize,u.inDepth,u.inHeight,u.inWidth,u.inChannels,u.outDepth,u.outHeight,u.outWidth,u.outChannels,u.strideDepth,u.strideHeight,u.strideWidth,u.dilationDepth,u.dilationHeight,u.dilationWidth,u.filterDepth,u.filterHeight,u.filterWidth,u.padInfo.front,u.padInfo.top,u.padInfo.left),p}var nue={kernelName:nu,backendName:"wasm",setupFunc:eue,kernelFunc:tue},aue=Je(Li),rue=Je(zi),av;(function(e){e[e.bilinear=0]="bilinear",e[e.nearest=1]="nearest"})(av||(av={}));var WA;function sue(e){WA=e.wasm.cwrap(ru,null,["number","number","number","number","array","number","number","number","number","number"])}function iue(e){let{backend:t,inputs:n,attrs:a}=e,{method:r,extrapolationValue:s,cropSize:i}=a,{image:o,boxes:l,boxInd:u}=n,p=l.shape[0],[d,c]=i,h=[p,d,c,o.shape[3]],m=t.dataIdMap.get(o.dataId),f;o.dtype!=="float32"&&(f=Fs({backend:t,inputs:{x:o},attrs:{dtype:"float32"}}),m=t.dataIdMap.get(f.dataId));let g=m.id,b=t.dataIdMap.get(l.dataId).id,y=t.dataIdMap.get(u.dataId).id,x=t.makeOutput(h,"float32"),w=t.dataIdMap.get(x.dataId).id,I=new Uint8Array(new Int32Array(o.shape).buffer);return WA(g,b,y,p,I,d,c,av[r],s,w),f!=null&&t.disposeData(f.dataId),x}var oue={kernelName:ru,backendName:"wasm",setupFunc:sue,kernelFunc:iue},BA;function lue(e){BA=e.wasm.cwrap(au,null,["number","number","number","number","number","number"])}function uue(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{axis:s,exclusive:i,reverse:o}=a,l=r.shape.length;v.assert(r.dtype==="float32"||r.dtype==="int32",()=>`cumprod does not support ${r.dtype} tensors in the WASM backend`);let u=N.getAxesPermutation([s],l),p=r;u!==null&&(p=fs({inputs:{x:r},attrs:{perm:u},backend:n}));let d=N.getInnerMostAxes(1,l)[0];N.assertAxesAreInnerMostDims("cumprod",[d],l);let c=n.makeOutput(p.shape,p.dtype),h=p.shape[d],m=n.dataIdMap.get(p.dataId).id,f=n.dataIdMap.get(c.dataId).id;BA(m,i?1:0,o?1:0,h,f,et[r.dtype]);let g=c;if(u!==null){let b=N.getUndoAxesPermutation(u);g=fs({inputs:{x:c},attrs:{perm:b},backend:n}),n.disposeData(p.dataId),n.disposeData(c.dataId)}return g}var pue={kernelName:au,backendName:"wasm",setupFunc:lue,kernelFunc:uue},VA;function cue(e){VA=e.wasm.cwrap(Wi,null,["number","number","number","number","number","number"])}function due(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{axis:s,exclusive:i,reverse:o}=a,l=r.shape.length;v.assert(r.dtype==="float32"||r.dtype==="int32",()=>`cumsum does not support ${r.dtype} tensors in the WASM backend`);let u=N.getAxesPermutation([s],l),p=r;u!==null&&(p=fs({inputs:{x:r},attrs:{perm:u},backend:n}));let d=N.getInnerMostAxes(1,l)[0];N.assertAxesAreInnerMostDims("cumsum",[d],l);let c=n.makeOutput(p.shape,p.dtype),h=p.shape[d],m=n.dataIdMap.get(p.dataId).id,f=n.dataIdMap.get(c.dataId).id;VA(m,i?1:0,o?1:0,h,f,et[r.dtype]);let g=c;if(u!==null){let b=N.getUndoAxesPermutation(u);g=fs({inputs:{x:c},attrs:{perm:b},backend:n}),n.disposeData(p.dataId),n.disposeData(c.dataId)}return g}var hue={kernelName:Wi,backendName:"wasm",setupFunc:cue,kernelFunc:due},UA;function mue(e){UA=e.wasm.cwrap("DenseBincount",null,["number","array","number","number","boolean","number","number","boolean","number"])}function fue(e){let{backend:t,inputs:n,attrs:a}=e,{x:r,weights:s}=n,{size:i,binaryOutput:o}=a,l=s.shape.reduce((c,h)=>c*h,1)!==0,u=r.shape.length===1?[i]:[r.shape[0],i],p=t.makeOutput(u,s.dtype);function d(c){return t.dataIdMap.get(c.dataId).id}return UA(d(r),new Uint8Array(new Int32Array(r.shape).buffer),r.shape.length,i,l,d(s),et[s.dtype],o,d(p)),p}var gue={kernelName:Fc,backendName:"wasm",setupFunc:mue,kernelFunc:fue},GA;function bue(e){GA=e.wasm.cwrap(su,null,["number","number","number","array","number","array","array","number","number"])}function yue(e){let{backend:t,inputs:n,attrs:a}=e,{x:r}=n,{blockSize:s,dataFormat:i}=a,o=r.shape[0],l=i==="NHWC"?r.shape[1]:r.shape[2],u=i==="NHWC"?r.shape[2]:r.shape[3],p=i==="NHWC"?r.shape[3]:r.shape[1],d=l*s,c=u*s,h=p/(s*s),m=i==="NHWC"?[o,d,c,h]:[o,h,d,c],f=t.makeOutput(m,"float32"),g=t.dataIdMap.get(r.dataId).id,b=new Uint8Array(new Int32Array(v.computeStrides(r.shape)).buffer),y=new Uint8Array(new Int32Array(m).buffer),x=new Uint8Array(new Int32Array(v.computeStrides(m)).buffer),w=t.dataIdMap.get(f.dataId).id;return GA(g,s,i==="NHWC"?1:0,b,r.shape.length-1,y,x,m.length,w),f}var xue={kernelName:su,backendName:"wasm",setupFunc:bue,kernelFunc:yue},HA;function vue(e){HA=e.wasm.cwrap(Bi,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function wue(e){let{inputs:t,attrs:n,backend:a}=e,{x:r,filter:s}=t,i=a.dataIdMap.get(r.dataId).id,o=a.dataIdMap.get(s.dataId).id,{strides:l,dilations:u,pad:p,dimRoundingMode:d}=n,c=u==null?[1,1]:u,h=N.computeConv2DInfo(r.shape,s.shape,l,c,p,d,!0),m=h.filterHeight,f=h.filterWidth,g=h.padInfo.top,b=h.padInfo.right,y=h.padInfo.bottom,x=h.padInfo.left,w=h.dilationHeight,I=h.dilationWidth,T=h.strideHeight,C=h.strideWidth,E=h.inChannels,F=h.outChannels,D=h.padInfo.type==="SAME"?1:0;if(h.dataFormat!=="channelsLast")throw new Error(`wasm backend DepthwiseConv2dNative does not support dataFormat:'${h.dataFormat}'. Please use 'channelsLast'.`);let $=a.makeOutput(h.outShape,"float32"),S=a.dataIdMap.get($.dataId).id;return HA(i,r.shape[0],r.shape[1],r.shape[2],o,m,f,g,b,y,x,D,w,I,T,C,E,F,S),$}var kue={kernelName:Bi,backendName:"wasm",setupFunc:vue,kernelFunc:wue},qA;function Iue(e){qA=e.wasm.cwrap("Diag",null,["number","number","number","number"])}function Sue(e){let{inputs:t,backend:n}=e,{x:a}=t,r=v.sizeFromShape(a.shape),s=n.makeOutput([...a.shape,...a.shape],a.dtype);return qA(n.dataIdMap.get(a.dataId).id,et[a.dtype],r,n.dataIdMap.get(s.dataId).id),s}var Nue={kernelName:$c,backendName:"wasm",setupFunc:Iue,kernelFunc:Sue},jA;function Tue(e){jA=e.wasm.cwrap(Vi,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function Cue(e){let{inputs:t,backend:n,attrs:a}=e,{x:r,filter:s}=t,{strides:i,pad:o,dilations:l}=a;if(r.dtype!==s.dtype)throw new Error(`Dilation2D error: x must have the same dtype as filter. 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Got ${r.dtype}, ${s.dtype}, and ${i.dtype}`);let p=N.computeDilation2DInfo(r.shape,s.shape,o,l,"NHWC",u),d=n.makeOutput(s.shape,s.dtype);return KA(n.dataIdMap.get(r.dataId).id,n.dataIdMap.get(s.dataId).id,n.dataIdMap.get(i.dataId).id,n.dataIdMap.get(d.dataId).id,et[r.dtype],p.batchSize,p.inChannels,p.inHeight,p.inWidth,p.outHeight,p.outWidth,p.strideHeight,p.strideWidth,p.dilationHeight,p.dilationWidth,p.filterHeight,p.filterWidth,p.padInfo.top,p.padInfo.left),d}var Fue={kernelName:Tl,backendName:"wasm",setupFunc:Eue,kernelFunc:Aue},XA;function $ue(e){XA=e.wasm.cwrap(Nl,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function Due(e){let{inputs:t,backend:n,attrs:a}=e,{x:r,filter:s,dy:i}=t,{strides:o,pad:l,dilations:u}=a;if(r.dtype!==s.dtype||r.dtype!==i.dtype)throw new Error(`Dilation2DBackpropInput error: x must have the same dtype as filter and dy. Got ${r.dtype}, ${s.dtype}, and ${i.dtype}`);let p=N.computeDilation2DInfo(r.shape,s.shape,o,l,"NHWC",u),d=n.makeOutput(r.shape,r.dtype);return XA(n.dataIdMap.get(r.dataId).id,n.dataIdMap.get(s.dataId).id,n.dataIdMap.get(i.dataId).id,n.dataIdMap.get(d.dataId).id,et[r.dtype],p.batchSize,p.inChannels,p.inHeight,p.inWidth,p.outHeight,p.outWidth,p.strideHeight,p.strideWidth,p.dilationHeight,p.dilationWidth,p.filterHeight,p.filterWidth,p.padInfo.top,p.padInfo.left),d}var Rue={kernelName:Nl,backendName:"wasm",setupFunc:$ue,kernelFunc:Due},Mue=Je(Gi),YA;function Pue(e){YA=e.wasm.cwrap(iu,null,["number","number","number"])}function Oue(e){let{inputs:t,backend:n}=e,{dy:a,y:r}=t,s=n.makeOutput(r.shape,"float32"),i=o=>n.dataIdMap.get(o.dataId).id;return YA(i(r),i(a),i(s)),s}var Lue={kernelName:iu,backendName:"wasm",setupFunc:Pue,kernelFunc:Oue},zue=!1,Wue=ln(lu,zue,"bool"),Bue=Je(Hi,"float32");function rv(e){let{inputs:t,attrs:n,backend:a}=e,{input:r}=t,{dim:s}=n,i=r.shape.length,o=r.shape.slice(),l=s;return s<0&&(v.assert(-(i+1)<=s,()=>`Axis must be in the interval [${-(i+1)}, ${i}]`),l=i+s+1),o.splice(l,0,1),Wn({inputs:{x:r},backend:a,attrs:{shape:o}})}var Vue={kernelName:uu,backendName:"wasm",kernelFunc:rv},Uue=Je(qi,"float32");function ZA(e){let{attrs:{shape:t,value:n,dtype:a},backend:r}=e,s=r.makeOutput(t,a);return r.typedArrayFromHeap(s).fill(n),s}var Gue={kernelName:Dc,backendName:"wasm",kernelFunc:ZA},JA;function Hue(e){JA=e.wasm.cwrap(pu,null,["number","number","number","number","number","number"])}function que(e){let{inputs:t,backend:n}=e,{image:a}=t,r=n.makeOutput(a.shape,a.dtype),s=n.dataIdMap.get(a.dataId).id,i=n.dataIdMap.get(r.dataId).id,[o,l,u,p]=a.shape;return JA(s,o,l,u,p,i),r}var jue={kernelName:pu,backendName:"wasm",kernelFunc:que,setupFunc:Hue},Kue=Je(ji),Xue=!1,Yue=ln(Ki,Xue),QA;function Zue(e){QA=e.wasm.cwrap(Xi,null,["number","number","number","number","number","number","number"])}function Jue(e){let{backend:t,inputs:n,attrs:a}=e,{varianceEpsilon:r}=a,{x:s,mean:i,variance:o,offset:l,scale:u}=n,p=t.dataIdMap.get(s.dataId).id,d=t.dataIdMap.get(i.dataId).id,c=t.dataIdMap.get(o.dataId).id,h=l!=null?t.dataIdMap.get(l.dataId).id:0,m=u!=null?t.dataIdMap.get(u.dataId).id:0,f=t.makeOutput(s.shape,s.dtype);if(v.sizeFromShape(s.shape)===0)return f;let g=t.dataIdMap.get(f.dataId).id;return QA(p,d,c,h,m,r,g),f}var Que={kernelName:Xi,backendName:"wasm",setupFunc:Zue,kernelFunc:Jue},eF;function epe(e){eF=e.wasm.cwrap(ii,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function tpe(e){let{inputs:t,attrs:n,backend:a}=e,{x:r,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:u,dilations:p,dataFormat:d,dimRoundingMode:c,activation:h,leakyreluAlpha:m}=n,f=N.computeConv2DInfo(r.shape,s.shape,l,p,u,c),g=Nc[h];if(g==null)throw new Error(`${h} activation not yet supported for FusedConv2D in the wasm backend.`);let b=a.dataIdMap.get(r.dataId).id,y=a.dataIdMap.get(s.dataId).id,x=f.outChannels,w=0;if(i!=null){let te=a.dataIdMap.get(i.dataId);if(te.shape.length!==1)throw new Error(`FusedConv2D only supports rank-1 bias but got rank ${te.shape.length}.`);if(te.shape[0]!==x)throw new Error(`FusedConv2D bias shape (${te.shape}) does not match the number of output channels (${x})`);w=te.id}let I=f.filterHeight,T=f.filterWidth,C=f.padInfo.top,E=f.padInfo.right,F=f.padInfo.bottom,D=f.padInfo.left,$=f.dilationHeight,S=f.dilationWidth,M=f.strideHeight,B=f.strideWidth,U=f.inChannels,H=f.padInfo.type==="SAME"?1:0,j=f.batchSize,K=f.inHeight,Z=f.inWidth;if(d!=="NHWC")throw new Error(`wasm backend FusedConv2D does not support dataFormat:'${d}'. Please use 'NHWC'.`);let J=a.makeOutput(f.outShape,"float32"),ee=a.dataIdMap.get(J.dataId).id,ae=o==null?0:a.dataIdMap.get(o.dataId).id;return eF(b,j,K,Z,y,I,T,w,C,E,F,D,H,$,S,M,B,U,x,g,ae,m||0,ee),J}var npe={kernelName:ii,backendName:"wasm",setupFunc:epe,kernelFunc:tpe},tF;function ape(e){tF=e.wasm.cwrap(oi,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 rpe(e){let{inputs:t,attrs:n,backend:a}=e,{x:r,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:u,dilations:p,dataFormat:d,dimRoundingMode:c,activation:h,leakyreluAlpha:m}=n,f=N.computeConv2DInfo(r.shape,s.shape,l,p,u,c,!0),g=Nc[h];if(g==null)throw new Error(`${h} activation not yet supported for FusedDepthwiseConv2D in the wasm backend.`);let b=a.dataIdMap.get(r.dataId).id,y=a.dataIdMap.get(s.dataId).id,x=f.outChannels,w=0;if(i!=null){let te=a.dataIdMap.get(i.dataId);if(te.shape.length!==1)throw new Error(`FusedDepthwiseConv2D only supports rank-1 bias but got rank ${te.shape.length}.`);if(te.shape[0]!==x)throw new Error(`FusedDepthwiseConv2D bias shape (${te.shape}) does not match the number of output channels (${x})`);w=te.id}let I=f.filterHeight,T=f.filterWidth,C=f.padInfo.top,E=f.padInfo.right,F=f.padInfo.bottom,D=f.padInfo.left,$=f.dilationHeight,S=f.dilationWidth,M=f.strideHeight,B=f.strideWidth,U=f.inChannels,H=f.padInfo.type==="SAME"?1:0,j=f.batchSize,K=f.inHeight,Z=f.inWidth;if(d!=="NHWC")throw new Error(`wasm backend FusedDepthwiseConv2D does not support dataFormat:'${d}'. Please use 'NHWC'.`);let J=a.makeOutput(f.outShape,"float32"),ee=a.dataIdMap.get(J.dataId).id,ae=o==null?0:a.dataIdMap.get(o.dataId).id;return tF(b,j,K,Z,y,I,T,w,C,E,F,D,H,$,S,M,B,U,x,g,ae,m||0,ee),J}var spe={kernelName:oi,backendName:"wasm",setupFunc:ape,kernelFunc:rpe},nF;function ipe(e){nF=e.wasm.cwrap(du,null,["number","number","number","number","number","number","array","number"])}function ope(e){let{backend:t,inputs:n}=e,{params:a,indices:r}=n,[s,i,o,l]=Pw.prepareAndValidate(a,r),u=t.makeOutput(s,a.dtype);if(i===0)return u;let p=r.shape,d=p[p.length-1],c=t.dataIdMap.get(a.dataId).id,h=t.dataIdMap.get(r.dataId).id,m=new Uint8Array(new Int32Array(l).buffer),f=t.dataIdMap.get(u.dataId).id;return nF(c,et[a.dtype],h,i,d,o,m,f),u}var lpe={kernelName:du,backendName:"wasm",setupFunc:ipe,kernelFunc:ope},aF;function upe(e){aF=e.wasm.cwrap("Gather",null,["number","number","array","number","number","number","array","number"])}function ppe(e){let{backend:t,inputs:n,attrs:a}=e,{x:r,indices:s}=n,{axis:i,batchDims:o}=a,l=v.parseAxisParam(i,r.shape)[0],u=t.readSync(s.dataId),p=r.shape[l];for(let C=0;C<u.length;++C){let E=u[C];v.assert(E<=p-1&&E>=0,()=>`GatherV2: the index value ${E} is not in [0, ${p-1}]`)}let d=N.segment_util.collectGatherOpShapeInfo(r,s,l,o),c=Wn({inputs:{x:r},attrs:{shape:[d.batchSize,d.outerSize,d.dimSize,d.sliceSize]},backend:t}),h=v.sizeFromShape(s.shape),m=Wn({inputs:{x:s},attrs:{shape:[d.batchSize,h/d.batchSize]},backend:t}),f=[d.batchSize,d.outerSize,h/d.batchSize,d.sliceSize],g=t.makeOutput(f,r.dtype);if(v.sizeFromShape(r.shape)===0)return g;let b=c.shape.length-1,y=t.dataIdMap.get(c.dataId).id,x=t.dataIdMap.get(m.dataId).id,w=t.dataIdMap.get(g.dataId).id,I=new Uint8Array(new Int32Array(v.computeStrides(c.shape)).buffer),T=new Uint8Array(new Int32Array(v.computeStrides(f)).buffer);return aF(y,et[r.dtype],I,b,x,d.batchSize,T,w),t.disposeData(c.dataId),t.disposeData(m.dataId),g.shape=d.outputShape,g}var cpe={kernelName:cu,backendName:"wasm",setupFunc:upe,kernelFunc:ppe},dpe=!1,hpe=ln(hu,dpe,"bool"),mpe=!1,fpe=ln(Yi,mpe,"bool"),gpe=Je(Ji,"bool"),bpe=Je(Qi,"bool"),ype=Je(eo,"bool"),rF;function xpe(e){rF=e.wasm.cwrap(to,null,["number","number","number","number"])}function vpe(e){let{inputs:{x:t},attrs:{alpha:n},backend:a}=e,r=a.dataIdMap.get(t.dataId).id,s=a.makeOutput(t.shape,"float32");if(v.sizeFromShape(t.shape)!==0){let i=a.dataIdMap.get(s.dataId).id;rF(r,et[t.dtype],n,i)}return s}var wpe={kernelName:to,backendName:"wasm",setupFunc:xpe,kernelFunc:vpe},kpe=!1,Ipe=ln(mu,kpe,"bool"),Spe=!1,Npe=ln(fu,Spe,"bool"),sF;function Tpe(e){sF=e.wasm.cwrap(gu,null,["number","number","number","number"])}function Cpe(e){let{attrs:t,backend:n}=e,{start:a,stop:r,num:s}=t,i=Math.floor(s),o=n.makeOutput([i],"float32");return sF(n.dataIdMap.get(o.dataId).id,a,r,i),o}var _pe={kernelName:gu,backendName:"wasm",setupFunc:Tpe,kernelFunc:Cpe},Epe=Je(no),Ape=Je(ao),Fpe=!1,$pe=ln(bu,Fpe,"bool"),Dpe=Je(yu),Rpe=!1,Mpe=ln(xu,Rpe,"bool"),Ppe=!1,Ope=ln(_S,Ppe,"bool"),iF;function Lpe(e){iF=e.wasm.cwrap(ro,null,["number","number","number","number","number","number","number"])}function zpe(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{depthRadius:s,bias:i,alpha:o,beta:l}=a;if(r.dtype!=="float32")throw new Error("LRN error: x must have dtype float32");let u=n.makeOutput(r.shape,r.dtype);return iF(n.dataIdMap.get(r.dataId).id,n.dataIdMap.get(u.dataId).id,r.shape[3],s,i,o,l),u}var Wpe={kernelName:ro,backendName:"wasm",setupFunc:Lpe,kernelFunc:zpe},oF;function Bpe(e){oF=e.wasm.cwrap(vu,null,["number","number","number","number","number","number","number","number","number"])}function Vpe(e){let{inputs:t,backend:n,attrs:a}=e,{x:r,y:s,dy:i}=t,{depthRadius:o,bias:l,alpha:u,beta:p}=a;if(r.dtype!=="float32"||s.dtype!=="float32"||i.dtype!=="float32")throw new Error("LRNGrad 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qpe={kernelName:so,backendName:"wasm",setupFunc:Gpe,kernelFunc:Hpe},jpe=!1,Kpe=ln(io,jpe),uF;function Xpe(e){uF=e.wasm.cwrap(oo,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function Ype(e){let{inputs:t,attrs:n,backend:a}=e,r=t.x,s=a.dataIdMap.get(r.dataId).id;v.assert(r.dtype==="float32",()=>`Error in MaxPool: only float32 input is supported. Got ${r.dtype}.`);let{filterSize:i,strides:o,pad:l,dimRoundingMode:u}=n,p=N.computePool2DInfo(r.shape,i,o,1,l,u),d=p.filterHeight,c=p.filterWidth,h=p.padInfo.top,m=p.padInfo.right,f=p.padInfo.bottom,g=p.padInfo.left,b=p.dilationHeight,y=p.dilationWidth,x=p.strideHeight,w=p.strideWidth,I=p.inChannels,T=p.outChannels;if(p.dataFormat!=="channelsLast")throw new Error(`wasm backend does not support dataFormat:'${p.dataFormat}'. Please use 'channelsLast'.`);let C=a.makeOutput(p.outShape,"float32"),E=a.dataIdMap.get(C.dataId).id;return uF(s,r.shape[0],r.shape[1],r.shape[2],d,c,h,m,f,g,b,y,x,w,I,T,E),C}var Zpe={kernelName:oo,backendName:"wasm",setupFunc:Xpe,kernelFunc:Ype},pF;function Jpe(e){pF=e.wasm.cwrap("MaxPool3D",null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function Qpe(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{filterSize:s,strides:i,pad:o,dimRoundingMode:l,dataFormat:u}=a,p=N.computePool3DInfo(r.shape,s,i,1,o,l,u),d=n.makeOutput(p.outShape,r.dtype);return pF(n.dataIdMap.get(r.dataId).id,n.dataIdMap.get(d.dataId).id,p.batchSize,p.inChannels,p.inDepth,p.inHeight,p.inWidth,p.outDepth,p.outHeight,p.outWidth,p.strideDepth,p.strideHeight,p.strideWidth,p.dilationDepth,p.dilationHeight,p.dilationWidth,p.effectiveFilterDepth,p.effectiveFilterHeight,p.effectiveFilterWidth,p.padInfo.front,p.padInfo.top,p.padInfo.left),d}var ece={kernelName:wu,backendName:"wasm",setupFunc:Jpe,kernelFunc:Qpe},cF;function tce(e){cF=e.wasm.cwrap("MaxPool3DGrad",null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function nce(e){let{inputs:t,backend:n,attrs:a}=e,{dy:r,input:s}=t,{filterSize:i,strides:o,pad:l,dimRoundingMode:u}=a,p=N.computePool3DInfo(s.shape,i,o,1,l,u),d=n.makeOutput(s.shape,s.dtype);return cF(n.dataIdMap.get(s.dataId).id,n.dataIdMap.get(r.dataId).id,n.dataIdMap.get(d.dataId).id,p.batchSize,p.inChannels,p.inDepth,p.inHeight,p.inWidth,p.outDepth,p.outHeight,p.outWidth,p.strideDepth,p.strideHeight,p.strideWidth,p.dilationDepth,p.dilationHeight,p.dilationWidth,p.effectiveFilterDepth,p.effectiveFilterHeight,p.effectiveFilterWidth,p.padInfo.front,p.padInfo.top,p.padInfo.left),d}var ace={kernelName:Rc,backendName:"wasm",setupFunc:tce,kernelFunc:nce},dF;function rce(e){dF=e.wasm.cwrap(lo,null,["number, number, number"])}function sce(e){let{backend:t,inputs:n,attrs:a}=e,{axis:r,keepDims:s}=a,{x:i}=n,o=t.dataIdMap.get(i.dataId).id,l=o,u=i,{transposed:p,axes:d,originalAxes:c,inputWasTransposed:h}=As(i,r,t),m=d;if(h){let w=t.dataIdMap.get(p.dataId).id;w!==o&&(u=p,l=w,m=N.getInnerMostAxes(m.length,u.shape.length))}N.assertAxesAreInnerMostDims("mean",m,u.shape.length);let[f,g]=N.computeOutAndReduceShapes(u.shape,m),b=v.sizeFromShape(g),y=u;u.dtype!=="float32"&&(y=Fs({backend:t,inputs:{x:u},attrs:{dtype:"float32"}}),l=t.dataIdMap.get(y.dataId).id);let x=t.makeOutput(f,"float32");if(v.sizeFromShape(u.shape)!==0){let w=t.dataIdMap.get(x.dataId).id;dF(l,b,w)}if(h&&t.disposeData(p.dataId),s){let w=N.expandShapeToKeepDim(x.shape,c);x.shape=w}return u.dtype!=="float32"&&t.disposeData(y.dataId),x}var ice={kernelName:lo,backendName:"wasm",setupFunc:rce,kernelFunc:sce},hF;function oce(e){hF=e.wasm.cwrap(uo,null,["number","number","number","number"])}function lce(e){let{backend:t,inputs:n,attrs:a}=e,{axis:r,keepDims:s}=a,{x:i}=n,o=t.dataIdMap.get(i.dataId).id,l=o,u=i,{transposed:p,axes:d,originalAxes:c,inputWasTransposed:h}=As(i,r,t);if(h){let x=t.dataIdMap.get(p.dataId).id;x!==o&&(u=p,l=x)}let m=u.shape.length;N.assertAxesAreInnerMostDims("min",d,m);let[f,g]=N.computeOutAndReduceShapes(u.shape,d),b=v.sizeFromShape(g),y=t.makeOutput(f,u.dtype);if(v.sizeFromShape(u.shape)!==0){let x=t.dataIdMap.get(y.dataId).id;hF(l,et[i.dtype],b,x)}if(h&&t.disposeData(p.dataId),s){let x=N.expandShapeToKeepDim(y.shape,c);y.shape=x}return y}var uce={kernelName:uo,backendName:"wasm",setupFunc:oce,kernelFunc:lce},pce=!1,cce=ln(po,pce),sv;(function(e){e[e.reflect=0]="reflect",e[e.symmetric=1]="symmetric"})(sv||(sv={}));var mF;function dce(e){mF=e.wasm.cwrap(co,null,["number","array","number","number","array","array","number","number"])}function hce(e){let{inputs:{x:t},backend:n,attrs:{paddings:a,mode:r}}=e,s=a.map((m,f)=>m[0]+t.shape[f]+m[1]),i=n.dataIdMap.get(t.dataId).id,o=n.makeOutput(s,t.dtype),l=n.dataIdMap.get(o.dataId).id,u=new Uint8Array(new Int32Array(t.shape).buffer),p=a.map(m=>m[0]),d=a.map(m=>m[1]),c=new Uint8Array(new Int32Array(p).buffer),h=new Uint8Array(new Int32Array(d).buffer);return mF(i,u,t.shape.length,et[t.dtype],c,h,sv[r],l),o}var mce={kernelName:co,backendName:"wasm",kernelFunc:hce,setupFunc:dce},fF;function fce(e){fF=e.wasm.cwrap(Ro,null,["number","number","number","number"])}function gF(e){let{backend:t,inputs:{logits:n},attrs:{dim:a}}=e,r=t.dataIdMap.get(n.dataId).id,s=t.makeOutput(n.shape,n.dtype),i=t.dataIdMap.get(s.dataId).id,o=n.shape[a],l=v.sizeFromShape(n.shape)/o;return v.sizeFromShape(s.shape)===0||fF(r,i,o,l),s}var gce={kernelName:Ro,backendName:"wasm",setupFunc:fce,kernelFunc:gF},bF;function bce(e){bF=e.wasm.cwrap(Iu,null,["number","number","number","number","number","number"])}function yce(e){let{inputs:t,backend:n,attrs:a}=e,{logits:r}=t,{numSamples:s,seed:i,normalized:o}=a;if(r.dtype!=="float32")throw new Error(`Tensor logits must have dtype float32, got ${r.dtype}`);let l=o?r:gF({inputs:{logits:r},backend:n,attrs:{dim:r.shape.length-1}}),[u,p]=l.shape,d=n.makeOutput([u,s],"int32");return bF(n.dataIdMap.get(l.dataId).id,u,p,s,i,n.dataIdMap.get(d.dataId).id),o||n.disposeData(l.dataId),d}var xce={kernelName:Iu,backendName:"wasm",setupFunc:bce,kernelFunc:yce},vce=!0,wce=ln(ho,vce),kce=Je(Su);function Z1(e,t){let n=new Int32Array(e.wasm.HEAPU8.buffer,t,4),a=n[0],r=n[1],s=n[2],i=n[3];return e.wasm._free(t),{pSelectedIndices:a,selectedSize:r,pSelectedScores:s,pValidOutputs:i}}var yF;function Ice(e){yF=e.wasm.cwrap(Tu,"number",["number","number","number","number","number"])}function Sce(e){let{backend:t,inputs:n,attrs:a}=e,{iouThreshold:r,maxOutputSize:s,scoreThreshold:i}=a,{boxes:o,scores:l}=n,u=t.dataIdMap.get(o.dataId).id,p=t.dataIdMap.get(l.dataId).id,d=yF(u,p,s,r,i),{pSelectedIndices:c,selectedSize:h,pSelectedScores:m,pValidOutputs:f}=Z1(t,d);return t.wasm._free(m),t.wasm._free(f),t.makeOutput([h],"int32",c)}var Nce={kernelName:Tu,backendName:"wasm",setupFunc:Ice,kernelFunc:Sce},xF;function Tce(e){xF=e.wasm.cwrap(Cu,"number",["number","number","number","number","number","bool"])}function Cce(e){let{backend:t,inputs:n,attrs:a}=e,{iouThreshold:r,maxOutputSize:s,scoreThreshold:i,padToMaxOutputSize:o}=a,{boxes:l,scores:u}=n,p=t.dataIdMap.get(l.dataId).id,d=t.dataIdMap.get(u.dataId).id,c=xF(p,d,s,r,i,o),{pSelectedIndices:h,selectedSize:m,pSelectedScores:f,pValidOutputs:g}=Z1(t,c);t.wasm._free(f);let b=t.makeOutput([m],"int32",h),y=t.makeOutput([],"int32",g);return[b,y]}var _ce={kernelName:Cu,backendName:"wasm",setupFunc:Tce,kernelFunc:Cce},vF;function Ece(e){vF=e.wasm.cwrap(_u,"number",["number","number","number","number","number","number"])}function Ace(e){let{backend:t,inputs:n,attrs:a}=e,{iouThreshold:r,maxOutputSize:s,scoreThreshold:i,softNmsSigma:o}=a,{boxes:l,scores:u}=n,p=t.dataIdMap.get(l.dataId).id,d=t.dataIdMap.get(u.dataId).id,c=vF(p,d,s,r,i,o),{pSelectedIndices:h,selectedSize:m,pSelectedScores:f,pValidOutputs:g}=Z1(t,c);t.wasm._free(g);let b=t.makeOutput([m],"int32",h),y=t.makeOutput([m],"float32",f);return[b,y]}var Fce={kernelName:_u,backendName:"wasm",setupFunc:Ece,kernelFunc:Ace},$ce=!1,Dce=ln(Nu,$ce,"bool"),wF;function Rce(e){wF=e.wasm.cwrap(mo,null,["number","number","number","number","number"])}function Mce(e){let{inputs:t,backend:n,attrs:a}=e,{indices:r}=t,{dtype:s,depth:i,onValue:o,offValue:l}=a,u=n.makeOutput([...r.shape,i],s),p=n.dataIdMap.get(u.dataId).id,d=n.dataIdMap.get(r.dataId).id;return wF(d,i,o,l,p),u}var Pce={kernelName:mo,backendName:"wasm",setupFunc:Rce,kernelFunc:Mce};function Oce(e){let{inputs:{x:t},backend:n}=e,a=n.makeOutput(t.shape,t.dtype);return n.typedArrayFromHeap(a).fill(1),a}var Lce={kernelName:Eu,backendName:"wasm",kernelFunc:Oce};function zce(e){let{inputs:t,backend:n,attrs:a}=e,{axis:r}=a;if(t.length===1)return rv({inputs:{input:t[0]},backend:n,attrs:{dim:r}});let s=t[0].shape,i=t[0].dtype;t.forEach(p=>{v.assertShapesMatch(s,p.shape,"All tensors passed to stack must have matching 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IF={kernelName:fo,backendName:"wasm",kernelFunc:Vce,setupFunc:Bce},Uce=!1,Gce=ln(go,Uce),SF;function Hce(e){SF=e.wasm.cwrap(bo,null,["number","number","number"])}function qce(e){let{inputs:t,backend:n}=e,{x:a,alpha:r}=t,s=n.dataIdMap.get(a.dataId).id,i=n.dataIdMap.get(r.dataId).id,o=s,l=a,u=l;l.dtype!=="float32"&&(u=Fs({backend:n,inputs:{x:a},attrs:{dtype:"float32"}}),o=n.dataIdMap.get(u.dataId).id);let p=n.makeOutput(a.shape,"float32"),d=n.dataIdMap.get(p.dataId).id;return SF(o,i,d),l.dtype!=="float32"&&n.disposeData(u.dataId),p}var jce={kernelName:bo,backendName:"wasm",setupFunc:Hce,kernelFunc:qce},NF;function Kce(e){NF=e.wasm.cwrap(yo,null,["number","number","number","number"])}function Xce(e){let{backend:t,inputs:n,attrs:a}=e,{axis:r,keepDims:s}=a,{x:i}=n,o=t.dataIdMap.get(i.dataId).id,l=o,u=i,{transposed:p,axes:d,originalAxes:c,inputWasTransposed:h}=As(i,r,t),m=d;if(h){let x=t.dataIdMap.get(p.dataId).id;x!==o&&(u=p,l=x,m=N.getInnerMostAxes(m.length,u.shape.length))}N.assertAxesAreInnerMostDims("prod",m,u.shape.length);let[f,g]=N.computeOutAndReduceShapes(u.shape,m),b=v.sizeFromShape(g),y=t.makeOutput(f,u.dtype);if(v.sizeFromShape(u.shape)!==0){let x=t.dataIdMap.get(y.dataId).id;NF(l,b,et[y.dtype],x)}if(h&&t.disposeData(p.dataId),s){let x=N.expandShapeToKeepDim(y.shape,c);y.shape=x}return y}var Yce={kernelName:yo,backendName:"wasm",setupFunc:Kce,kernelFunc:Xce},Zce=e=>{let{backend:t,attrs:n}=e,{start:a,stop:r,step:s,dtype:i}=n,o=T1(a,r,s,i),l=t.makeOutput([o.length],i);return t.typedArrayFromHeap(l).set(o),l},Jce={kernelName:Mc,backendName:"wasm",kernelFunc:Zce},Qce=!0,ede=ln(Ui,Qce),tde=Je(xo),nde=Je(vo),ade=Je(Io),TF;function rde(e){TF=e.wasm.cwrap(ko,null,["number","number","number","number","number","number","number","number","number","number"])}function sde(e){let{backend:t,inputs:n,attrs:a}=e,{images:r}=n,{alignCorners:s,halfPixelCenters:i,size:o}=a,[l,u]=o,[p,d,c,h]=r.shape,m=[p,l,u,h],f=t.dataIdMap.get(r.dataId),g;f.dtype!=="float32"&&(g=Fs({backend:t,inputs:{x:r},attrs:{dtype:"float32"}}),f=t.dataIdMap.get(g.dataId));let b=f.id,y=t.makeOutput(m,"float32");if(v.sizeFromShape(r.shape)===0)return y;let x=t.dataIdMap.get(y.dataId).id;return TF(b,p,d,c,h,l,u,s?1:0,i?1:0,x),g!=null&&t.disposeData(g.dataId),y}var ide={kernelName:ko,backendName:"wasm",setupFunc:rde,kernelFunc:sde},CF;function ode(e){CF=e.wasm.cwrap(Du,null,["number","number","number","array","array","boolean"])}function lde(e){let{inputs:t,backend:n,attrs:a}=e,{images:r,dy:s}=t,{alignCorners:i}=a,o=n.makeOutput(r.shape,"float32"),l=n.dataIdMap.get(r.dataId),u;return l.dtype!=="float32"&&(u=Fs({backend:n,inputs:{x:r},attrs:{dtype:"float32"}}),l=n.dataIdMap.get(u.dataId)),CF(n.dataIdMap.get(r.dataId).id,n.dataIdMap.get(s.dataId).id,n.dataIdMap.get(o.dataId).id,new Uint8Array(new Int32Array(r.shape).buffer),new Uint8Array(new Int32Array(s.shape).buffer),i),u!=null&&n.disposeData(u.dataId),o}var ude={kernelName:Du,backendName:"wasm",setupFunc:ode,kernelFunc:lde},_F;function pde(e){_F=e.wasm.cwrap(wo,null,["number","number","number","number","number","number","number","number","number","number"])}function cde(e){let{backend:t,inputs:n,attrs:a}=e,{images:r}=n,{alignCorners:s,halfPixelCenters:i,size:o}=a,[l,u]=o,[p,d,c,h]=r.shape,m=[p,l,u,h],f=t.makeOutput(m,"float32");if(v.sizeFromShape(r.shape)===0)return f;let g=t.dataIdMap.get(r.dataId),b;g.dtype!=="float32"&&(b=Fs({backend:t,inputs:{x:r},attrs:{dtype:"float32"}}),g=t.dataIdMap.get(b.dataId));let y=g.id,x=t.dataIdMap.get(f.dataId).id;return _F(y,p,d,c,h,l,u,s?1:0,i?1:0,x),b!=null&&t.disposeData(b.dataId),f}var dde={kernelName:wo,backendName:"wasm",setupFunc:pde,kernelFunc:cde},EF;function hde(e){EF=e.wasm.cwrap($u,null,["number","number","number","array","array","boolean"])}function 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Nde(e){let{backend:t,inputs:n,attrs:a}=e,{indices:r,updates:s}=n,{shape:i}=a,o=t.makeOutput(i,s.dtype);if(v.sizeFromShape(i)===0)return o;let{sliceRank:l,numUpdates:u,sliceSize:p,strides:d,outputSize:c}=rf.calculateShapes(s,r,i),h=t.dataIdMap.get(r.dataId).id,m=t.dataIdMap.get(s.dataId).id,f=new Uint8Array(new Int32Array(d).buffer),g=t.dataIdMap.get(o.dataId).id;return $F(h,m,et[s.dtype],l,u,p,f,c,g),o}var Tde={kernelName:Ru,backendName:"wasm",setupFunc:Sde,kernelFunc:Nde},DF;function Cde(e){DF=e.wasm.cwrap(Pu,null,["number","number","number","number","number","number","bool","number"])}function _de(e){let{inputs:t,backend:n,attrs:a}=e,{sortedSequence:r,values:s}=t,{side:i}=a;if(r.dtype!==s.dtype)throw new Error(`SearchSorted error: sorted_sequence must have the same dtype as values. 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dt{constructor(t,n,a,r,s=!1){super({x:t,y:n,width:a,height:r},s)}};var ume=.5,pme=.43,cme=.45,ka=class{constructor(t,n,a=new Pe(0,0)){let{width:r,height:s}=n;this._imgDims=new En(r,s),this._shift=a,this._positions=t.map(i=>i.mul(new Pe(r,s)).add(a))}get shift(){return new Pe(this._shift.x,this._shift.y)}get imageWidth(){return this._imgDims.width}get imageHeight(){return this._imgDims.height}get positions(){return this._positions}get relativePositions(){return this._positions.map(t=>t.sub(this._shift).div(new Pe(this.imageWidth,this.imageHeight)))}forSize(t,n){return new this.constructor(this.relativePositions,{width:t,height:n})}shiftBy(t,n){return new this.constructor(this.relativePositions,this._imgDims,new Pe(t,n))}shiftByPoint(t){return this.shiftBy(t.x,t.y)}align(t,n={}){if(t){let s=t instanceof wt?t.box.floor():new dt(t);return this.shiftBy(s.x,s.y).align(null,n)}let{useDlibAlignment:a,minBoxPadding:r}={useDlibAlignment:!1,minBoxPadding:.2,...n};return a?this.alignDlib():this.alignMinBbox(r)}alignDlib(){let t=this.getRefPointsForAlignment(),[n,a,r]=t,s=d=>r.sub(d).magnitude(),i=(s(n)+s(a))/2,o=Math.floor(i/cme),l=Jo(t),u=Math.floor(Math.max(0,l.x-ume*o)),p=Math.floor(Math.max(0,l.y-pme*o));return new fp(u,p,Math.min(o,this.imageWidth+u),Math.min(o,this.imageHeight+p))}alignMinBbox(t){let n=QF(this.positions);return n.pad(n.width*t,n.height*t)}getRefPointsForAlignment(){throw new Error("getRefPointsForAlignment not implemented by base class")}};var n$=class extends ka{getRefPointsForAlignment(){let t=this.positions;return[t[0],t[1],Jo([t[3],t[4]])]}};var gp=class extends ka{getJawOutline(){return this.positions.slice(0,17)}getLeftEyeBrow(){return this.positions.slice(17,22)}getRightEyeBrow(){return this.positions.slice(22,27)}getNose(){return this.positions.slice(27,36)}getLeftEye(){return this.positions.slice(36,42)}getRightEye(){return this.positions.slice(42,48)}getMouth(){return this.positions.slice(48,68)}getRefPointsForAlignment(){return[this.getLeftEye(),this.getRightEye(),this.getMouth()].map(Jo)}};var _d=class{constructor(t,n){this._label=t,this._distance=n}get label(){return this._label}get distance(){return this._distance}toString(t=!0){return`${this.label}${t?` (${Zo(this.distance)})`:""}`}};var Ed=class extends dt{constructor(n,a){super(n);this._label=a}static assertIsValidLabeledBox(n,a){if(dt.assertIsValidBox(n,a),!Za(n.label))throw new Error(`${a} - expected property label (${n.label}) to be a number`)}get label(){return this._label}};var zr=class{constructor(t,n){if(typeof t!="string")throw new Error("LabeledFaceDescriptors - constructor expected label to be a string");if(!Array.isArray(n)||n.some(a=>!(a instanceof Float32Array)))throw new Error("LabeledFaceDescriptors - constructor expected descriptors to be an array of Float32Array");this._label=t,this._descriptors=n}get label(){return this._label}get descriptors(){return this._descriptors}toJSON(){return{label:this.label,descriptors:this.descriptors.map(t=>Array.from(t))}}static fromJSON(t){let n=t.descriptors.map(a=>new Float32Array(a));return new zr(t.label,n)}};var a$=class extends Ed{constructor(n,a,r,s){super(n,a);this._score=r,this._classScore=s}static assertIsValidPredictedBox(n,a){if(Ed.assertIsValidLabeledBox(n,a),!hp(n.score)||!hp(n.classScore))throw new Error(`${a} - expected properties score (${n.score}) and (${n.classScore}) to be a number between [0, 1]`)}get score(){return this._score}get classScore(){return this._classScore}};function Wr(e){return e.detection instanceof wt}function bp(e,t){return{...e,...{detection:t}}}function nk(){let e=window.fetch;if(!e)throw new Error("fetch - missing fetch implementation for browser environment");return{Canvas:HTMLCanvasElement,CanvasRenderingContext2D,Image:HTMLImageElement,ImageData,Video:HTMLVideoElement,createCanvasElement:()=>document.createElement("canvas"),createImageElement:()=>document.createElement("img"),createVideoElement:()=>document.createElement("video"),fetch:e,readFile:()=>{throw new Error("readFile - filesystem not available for browser environment")}}}function Ad(){return typeof global=="object"&&typeof process!="undefined"&&process.versions!=null&&process.versions.node!=null}function Hf(e){let t="";if(!e&&Ad())try{e=FD("fs")}catch(a){t=a.toString()}return{readFile:e?a=>new Promise((r,s)=>{e.readFile(a,(i,o)=>i?s(i):r(o))}):()=>{throw new Error(`readFile - failed to require fs in nodejs environment with error: ${t}`)}}}function ak(){let e=global.Canvas||global.HTMLCanvasElement,t=global.Image||global.HTMLImageElement,n=global.Video||global.HTMLVideoElement,a=()=>{if(e)return new e;throw new Error("createCanvasElement - missing Canvas implementation for nodejs environment")},r=()=>{if(t)return new t;throw new Error("createImageElement - missing Image implementation for nodejs environment")},s=()=>{if(n)return new n;throw new Error("createVideoElement - missing Video implementation for nodejs environment")},i=global.fetch,o=Hf();return{Canvas:e||class{},CanvasRenderingContext2D:global.CanvasRenderingContext2D||class{},Image:t||class{},ImageData:global.ImageData||class{},Video:global.HTMLVideoElement||class{},createCanvasElement:a,createImageElement:r,createVideoElement:s,fetch:i,...o}}function rk(){return typeof window=="object"&&typeof document!="undefined"&&typeof HTMLImageElement!="undefined"&&typeof HTMLCanvasElement!="undefined"&&typeof HTMLVideoElement!="undefined"&&typeof ImageData!="undefined"&&typeof CanvasRenderingContext2D!="undefined"}var un;function dme(){if(!un)throw new Error("getEnv - environment is not defined, check isNodejs() and isBrowser()");return un}function sk(e){un=e}function ik(){return rk()?sk(nk()):Ad()?sk(ak()):null}function hme(e){if(un||ik(),!un)throw new Error("monkeyPatch - environment is not defined, check isNodejs() and isBrowser()");let{Canvas:t=un.Canvas,Image:n=un.Image}=e;un.Canvas=t,un.Image=n,un.createCanvasElement=e.createCanvasElement||(()=>new t),un.createImageElement=e.createImageElement||(()=>new n),un.ImageData=e.ImageData||un.ImageData,un.Video=e.Video||un.Video,un.fetch=e.fetch||un.fetch,un.readFile=e.readFile||un.readFile}var at={getEnv:dme,setEnv:sk,initialize:ik,createBrowserEnv:nk,createFileSystem:Hf,createNodejsEnv:ak,monkeyPatch:hme,isBrowser:rk,isNodejs:Ad};ik();function yp(e){return!at.isNodejs()&&typeof e=="string"?document.getElementById(e):e}function sa(e){let{Canvas:t,CanvasRenderingContext2D:n}=at.getEnv();if(e instanceof n)return e;let a=yp(e);if(!(a instanceof t))throw new Error("resolveContext2d - expected canvas to be of instance of Canvas");let r=a.getContext("2d");if(!r)throw new Error("resolveContext2d - canvas 2d context is null");return r}var ok=(r=>(r.TOP_LEFT="TOP_LEFT",r.TOP_RIGHT="TOP_RIGHT",r.BOTTOM_LEFT="BOTTOM_LEFT",r.BOTTOM_RIGHT="BOTTOM_RIGHT",r))(ok||{}),xp=class{constructor(t={}){let{anchorPosition:n,backgroundColor:a,fontColor:r,fontSize:s,fontStyle:i,padding:o}=t;this.anchorPosition=n||"TOP_LEFT",this.backgroundColor=a||"rgba(0, 0, 0, 0.5)",this.fontColor=r||"rgba(255, 255, 255, 1)",this.fontSize=s||14,this.fontStyle=i||"Georgia",this.padding=o||4}},Br=class{constructor(t,n,a={}){this.text=typeof t=="string"?[t]:t instanceof Br?t.text:t,this.anchor=n,this.options=new xp(a)}measureWidth(t){let{padding:n}=this.options;return this.text.map(a=>t.measureText(a).width).reduce((a,r)=>a<r?r:a,0)+2*n}measureHeight(){let{fontSize:t,padding:n}=this.options;return this.text.length*t+2*n}getUpperLeft(t,n){let{anchorPosition:a}=this.options,r=a==="BOTTOM_RIGHT"||a==="TOP_RIGHT",s=a==="BOTTOM_LEFT"||a==="BOTTOM_RIGHT",i=this.measureWidth(t),o=this.measureHeight(),l=r?this.anchor.x-i:this.anchor.x,u=s?this.anchor.y-o:this.anchor.y;if(n){let{width:p,height:d}=n,c=Math.max(Math.min(l,p-i),0),h=Math.max(Math.min(u,d-o),0);return{x:c,y:h}}return{x:l,y:u}}draw(t){let n=yp(t),a=sa(n),{backgroundColor:r,fontColor:s,fontSize:i,fontStyle:o,padding:l}=this.options;a.font=`${i}px ${o}`;let u=this.measureWidth(a),p=this.measureHeight();a.fillStyle=r;let d=this.getUpperLeft(a,n);a.fillRect(d.x,d.y,u,p),a.fillStyle=s,this.text.forEach((c,h)=>{let m=l+d.x,f=l+d.y+(h+1)*i;a.fillText(c,m,f)})}};var qf=class{constructor(t={}){let{boxColor:n,lineWidth:a,label:r,drawLabelOptions:s}=t;this.boxColor=n||"rgba(0, 0, 255, 1)",this.lineWidth=a||2,this.label=r;let i={anchorPosition:"BOTTOM_LEFT",backgroundColor:this.boxColor};this.drawLabelOptions=new xp({...i,...s})}},Fd=class{constructor(t,n={}){this.box=new dt(t),this.options=new qf(n)}draw(t){let n=sa(t),{boxColor:a,lineWidth:r}=this.options,{x:s,y:i,width:o,height:l}=this.box;n.strokeStyle=a,n.lineWidth=r,n.strokeRect(s,i,o,l);let{label:u}=this.options;u&&new Br([u],{x:s-r/2,y:i},this.options.drawLabelOptions).draw(t)}};function mme(e,t){(Array.isArray(t)?t:[t]).forEach(a=>{let r=a instanceof wt?a.score:Wr(a)?a.detection.score:void 0,s=a instanceof wt?a.box:Wr(a)?a.detection.box:new dt(a),i=r?`${Zo(r)}`:void 0;new Fd(s,{label:i}).draw(e)})}function jf(e){let{Image:t,Video:n}=at.getEnv();return e instanceof t&&e.complete||e instanceof n&&e.readyState>=3}function r$(e){return new Promise((t,n)=>{(e instanceof at.getEnv().Canvas||jf(e))&&t(null);function a(s){s.currentTarget&&(s.currentTarget.removeEventListener("load",r),s.currentTarget.removeEventListener("error",a),n(s))}function r(s){s.currentTarget&&(s.currentTarget.removeEventListener("load",r),s.currentTarget.removeEventListener("error",a),t(s))}e.addEventListener("load",r),e.addEventListener("error",a)})}function s$(e){return new Promise((t,n)=>{e instanceof Blob||n(new Error("bufferToImage - expected buf to be of type: Blob"));let a=new FileReader;a.onload=()=>{typeof a.result!="string"&&n(new Error("bufferToImage - expected reader.result to be a string, in onload"));let r=at.getEnv().createImageElement();r.onload=()=>t(r),r.onerror=n,r.src=a.result},a.onerror=n,a.readAsDataURL(e)})}function vp(e){let{Image:t,Video:n}=at.getEnv();return e instanceof t?new En(e.naturalWidth,e.naturalHeight):e instanceof n?new En(e.videoWidth,e.videoHeight):new En(e.width,e.height)}function wp({width:e,height:t}){let{createCanvasElement:n}=at.getEnv(),a=n();return a.width=e,a.height=t,a}function Kf(e,t){let{ImageData:n}=at.getEnv();if(!(e instanceof n)&&!jf(e))throw new Error("createCanvasFromMedia - media has not finished loading yet");let{width:a,height:r}=t||vp(e),s=wp({width:a,height:r});return e instanceof n?sa(s).putImageData(e,0,0):sa(s).drawImage(e,0,0,a,r),s}async function i$(e,t){let n=t||at.getEnv().createCanvasElement(),[a,r,s]=e.shape.slice(wa(e)?1:0),i=P(()=>e.as3D(a,r,s).toInt());return await Vo.toPixels(i,n),i.dispose(),n}function lk(e){let{Image:t,Canvas:n,Video:a}=at.getEnv();return e instanceof t||e instanceof n||e instanceof a}function o$(e,t,n=!1){let{Image:a,Canvas:r}=at.getEnv();if(!(e instanceof a||e instanceof r))throw new Error("imageToSquare - expected arg0 to be HTMLImageElement | HTMLCanvasElement");if(t<=0)return wp({width:1,height:1});let s=vp(e),i=t/Math.max(s.height,s.width),o=i*s.width,l=i*s.height,u=wp({width:t,height:t}),p=e instanceof r?e:Kf(e),d=Math.abs(o-l)/2,c=n&&o<l?d:0,h=n&&l<o?d:0;return p.width>0&&p.height>0&&sa(u).drawImage(p,c,h,o,l),u}var Vr=class{constructor(t,n=!1){this._imageTensors=[];this._canvases=[];this._treatAsBatchInput=!1;this._inputDimensions=[];this._inputSize=0;if(!Array.isArray(t))throw new Error(`NetInput.constructor - expected inputs to be an Array of TResolvedNetInput or to be instanceof tf.Tensor4D, instead have ${t}`);this._treatAsBatchInput=n,this._batchSize=t.length,t.forEach((a,r)=>{if(Lr(a)){this._imageTensors[r]=a,this._inputDimensions[r]=a.shape;return}if(wa(a)){let i=a.shape[0];if(i!==1)throw new Error(`NetInput - tf.Tensor4D with batchSize ${i} passed, but not supported in input array`);this._imageTensors[r]=a,this._inputDimensions[r]=a.shape.slice(1);return}let s=a instanceof at.getEnv().Canvas?a:Kf(a);this._canvases[r]=s,this._inputDimensions[r]=[s.height,s.width,3]})}get imageTensors(){return this._imageTensors}get canvases(){return this._canvases}get isBatchInput(){return this.batchSize>1||this._treatAsBatchInput}get batchSize(){return this._batchSize}get inputDimensions(){return this._inputDimensions}get inputSize(){return this._inputSize}get reshapedInputDimensions(){return gr(this.batchSize,0,1).map((t,n)=>this.getReshapedInputDimensions(n))}getInput(t){return this.canvases[t]||this.imageTensors[t]}getInputDimensions(t){return this._inputDimensions[t]}getInputHeight(t){return this._inputDimensions[t][0]}getInputWidth(t){return this._inputDimensions[t][1]}getReshapedInputDimensions(t){if(typeof this.inputSize!="number")throw new Error("getReshapedInputDimensions - inputSize not set, toBatchTensor has not been called yet");let n=this.getInputWidth(t),a=this.getInputHeight(t);return tk({width:n,height:a},this.inputSize)}toBatchTensor(t,n=!0){return this._inputSize=t,P(()=>{let a=gr(this.batchSize,0,1).map(s=>{let i=this.getInput(s);if(i instanceof Ce){let o=wa(i)?i:tn(i);return o=t$(o,n),(o.shape[1]!==t||o.shape[2]!==t)&&(o=Qn.resizeBilinear(o,[t,t],!1,!1)),o.as3D(t,t,3)}if(i instanceof at.getEnv().Canvas)return Vo.fromPixels(o$(i,t,n));throw new Error(`toBatchTensor - at batchIdx ${s}, expected input to be instanceof tf.Tensor or instanceof HTMLCanvasElement, instead have ${i}`)});return Dt(a.map(s=>ie(s,"float32"))).as4D(this.batchSize,t,t,3)})}};async function kt(e){if(e instanceof Vr)return e;let t=Array.isArray(e)?e:[e];if(!t.length)throw new Error("toNetInput - empty array passed as input");let n=r=>Array.isArray(e)?` at input index ${r}:`:"",a=t.map(yp);return a.forEach((r,s)=>{if(!lk(r)&&!Lr(r)&&!wa(r))throw typeof t[s]=="string"?new Error(`toNetInput -${n(s)} string passed, but could not resolve HTMLElement for element id ${t[s]}`):new Error(`toNetInput -${n(s)} expected media to be of type HTMLImageElement | HTMLVideoElement | HTMLCanvasElement | tf.Tensor3D, or to be an element id`);if(wa(r)){let i=r.shape[0];if(i!==1)throw new Error(`toNetInput -${n(s)} tf.Tensor4D with batchSize ${i} passed, but not supported in input array`)}}),await Promise.all(a.map(r=>lk(r)&&r$(r))),new Vr(a,Array.isArray(e))}async function $d(e,t){let{Canvas:n}=at.getEnv(),a=e;if(!(e instanceof n)){let i=await kt(e);if(i.batchSize>1)throw new Error("extractFaces - batchSize > 1 not supported");let o=i.getInput(0);a=o instanceof n?o:await i$(o)}let r=sa(a);return t.map(i=>i instanceof wt?i.forSize(a.width,a.height).box.floor():i).map(i=>i.clipAtImageBorders(a.width,a.height)).map(({x:i,y:o,width:l,height:u})=>{let p=wp({width:l,height:u});return l>0&&u>0&&sa(p).putImageData(r.getImageData(i,o,l,u),0,0),p})}async function Dd(e,t){if(!Lr(e)&&!wa(e))throw new Error("extractFaceTensors - expected image tensor to be 3D or 4D");if(wa(e)&&e.shape[0]>1)throw new Error("extractFaceTensors - batchSize > 1 not supported");return P(()=>{let[n,a,r]=e.shape.slice(wa(e)?1:0);return t.map(o=>o instanceof wt?o.forSize(a,n).box:o).map(o=>o.clipAtImageBorders(a,n)).filter(o=>o.width>0&&o.height>0).map(({x:o,y:l,width:u,height:p})=>Wo(e.as3D(n,a,r),[l,o,0],[p,u,r]))})}async function Ds(e,t){let{fetch:n}=at.getEnv(),a=await n(e,t);if(!(a.status<400))throw new Error(`failed to fetch: (${a.status}) ${a.statusText}, from url: ${a.url}`);return a}async function ake(e){let t=await Ds(e),n=await t.blob();if(!n.type.startsWith("image/"))throw new Error(`fetchImage - expected blob type to be of type image/*, instead have: ${n.type}, for url: ${t.url}`);return s$(n)}async function l$(e){return(await Ds(e)).json()}async function lke(e){return new Float32Array(await(await Ds(e)).arrayBuffer())}function u$(e){return new Promise((t,n)=>{e instanceof Blob||n(new Error("bufferToVideo - expected buf to be of type: Blob"));let a=at.getEnv().createVideoElement();a.oncanplay=()=>t(a),a.onerror=n,a.playsInline=!0,a.muted=!0,a.src=URL.createObjectURL(e),a.play()})}async function mke(e){let t=await Ds(e),n=await t.blob();if(!n.type.startsWith("video/"))throw new Error(`fetchVideo - expected blob type to be of type video/*, instead have: ${n.type}, for url: ${t.url}`);return u$(n)}function Xf(e,t){let n=`${t}-weights_manifest.json`;if(!e)return{modelBaseUri:"",manifestUri:n};if(e==="/")return{modelBaseUri:"/",manifestUri:`/${n}`};let a=e.startsWith("http://")?"http://":e.startsWith("https://")?"https://":"";e=e.replace(a,"");let r=e.split("/").filter(o=>o),s=e.endsWith(".json")?r[r.length-1]:n,i=a+(e.endsWith(".json")?r.slice(0,r.length-1):r).join("/");return i=e.startsWith("/")?`/${i}`:i,{modelBaseUri:i,manifestUri:i==="/"?`/${s}`:`${i}/${s}`}}async function p$(e,t){let{manifestUri:n,modelBaseUri:a}=Xf(e,t),r=await l$(n);return qt.loadWeights(r,a)}function wke(e,t,n=!1){let{width:a,height:r}=n?vp(t):t;return e.width=a,e.height=r,{width:a,height:r}}var fn=class{constructor(t){this._params=void 0;this._paramMappings=[];this._name=t}get params(){return this._params}get paramMappings(){return this._paramMappings}get isLoaded(){return!!this.params}getParamFromPath(t){let{obj:n,objProp:a}=this.traversePropertyPath(t);return 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Float32Array){this.extractWeights(t);return}await this.loadFromUri(t)}async loadFromUri(t){if(t&&typeof t!="string")throw new Error(`${this._name}.loadFromUri - expected model uri`);let n=await p$(t,this.getDefaultModelName());this.loadFromWeightMap(n)}async loadFromDisk(t){if(t&&typeof t!="string")throw new Error(`${this._name}.loadFromDisk - expected model file path`);let{readFile:n}=at.getEnv(),{manifestUri:a,modelBaseUri:r}=Xf(t,this.getDefaultModelName()),s=u=>Promise.all(u.map(p=>n(p).then(d=>d.buffer))),i=qt.weightsLoaderFactory(s),o=JSON.parse((await n(a)).toString()),l=await i(o,r);this.loadFromWeightMap(l)}loadFromWeightMap(t){let{paramMappings:n,params:a}=this.extractParamsFromWeightMap(t);this._paramMappings=n,this._params=a}extractWeights(t){let{paramMappings:n,params:a}=this.extractParams(t);this._paramMappings=n,this._params=a}traversePropertyPath(t){if(!this.params)throw new Error("traversePropertyPath - model has no loaded params");let 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Qo(e,t,n="same",a=!1){return P(()=>{let r=X(Rt(e,t.filters,[1,1],n),t.bias);return a?Ke(r):r})}function An(e,t){Object.keys(e).forEach(n=>{t.some(a=>a.originalPath===n)||e[n].dispose()})}function kp(e,t){return(n,a,r,s)=>{let i=Da(e(n*a*r*r),[r,r,n,a]),o=je(e(a));return t.push({paramPath:`${s}/filters`},{paramPath:`${s}/bias`}),{filters:i,bias:o}}}function Zf(e,t){return(n,a,r)=>{let s=Aa(e(n*a),[n,a]),i=je(e(a));return t.push({paramPath:`${r}/weights`},{paramPath:`${r}/bias`}),{weights:s,bias:i}}}var Md=class{constructor(t,n,a){this.depthwise_filter=t;this.pointwise_filter=n;this.bias=a}};function Ip(e,t){return(n,a,r)=>{let s=Da(e(9*n),[3,3,n,1]),i=Da(e(n*a),[1,1,n,a]),o=je(e(a));return t.push({paramPath:`${r}/depthwise_filter`},{paramPath:`${r}/pointwise_filter`},{paramPath:`${r}/bias`}),new Md(s,i,o)}}function Sp(e){return t=>{let n=e(`${t}/depthwise_filter`,4),a=e(`${t}/pointwise_filter`,4),r=e(`${t}/bias`,1);return new Md(n,a,r)}}function ia(e,t){return(n,a,r)=>{let 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a=ie(t.toBatchTensor(112,!0),"float32"),s=br(a,[122.782,117.001,104.298]).div(255),i=Rd(s,n.dense0,!0);return i=Rd(i,n.dense1),i=Rd(i,n.dense2),i=Rd(i,n.dense3),i=ya(i,[7,7],[2,2],"valid"),i})}async forward(t){return this.forwardInput(await kt(t))}getDefaultModelName(){return"face_feature_extractor_model"}extractParamsFromWeightMap(t){return d$(t)}extractParams(t){return c$(t)}};function Pd(e,t){return P(()=>X($e(e,t.weights),t.bias))}function h$(e,t,n){let a=[],{extractWeights:r,getRemainingWeights:s}=Fn(e),o=Zf(r,a)(t,n,"fc");if(s().length!==0)throw new Error(`weights remaing after extract: ${s().length}`);return{paramMappings:a,params:{fc:o}}}function m$(e){let t=[],n=ia(e,t);function a(s){let i=n(`${s}/weights`,2),o=n(`${s}/bias`,1);return{weights:i,bias:o}}let r={fc:a("fc")};return An(e,t),{params:r,paramMappings:t}}function tg(e){let t={},n={};return Object.keys(e).forEach(a=>{let r=a.startsWith("fc")?n:t;r[a]=e[a]}),{featureExtractorMap:t,classifierMap:n}}var Tp=class extends fn{constructor(n,a){super(n);this._faceFeatureExtractor=a}get faceFeatureExtractor(){return this._faceFeatureExtractor}runNet(n){let{params:a}=this;if(!a)throw new Error(`${this._name} - load model before inference`);return P(()=>{let r=n instanceof Vr?this.faceFeatureExtractor.forwardInput(n):n;return Pd(r.as2D(r.shape[0],-1),a.fc)})}dispose(n=!0){this.faceFeatureExtractor.dispose(n),super.dispose(n)}loadClassifierParams(n){let{params:a,paramMappings:r}=this.extractClassifierParams(n);this._params=a,this._paramMappings=r}extractClassifierParams(n){return h$(n,this.getClassifierChannelsIn(),this.getClassifierChannelsOut())}extractParamsFromWeightMap(n){let{featureExtractorMap:a,classifierMap:r}=tg(n);return this.faceFeatureExtractor.loadFromWeightMap(a),m$(r)}extractParams(n){let a=this.getClassifierChannelsIn(),r=this.getClassifierChannelsOut(),s=r*a+r,i=n.slice(0,n.length-s),o=n.slice(n.length-s);return this.faceFeatureExtractor.extractWeights(i),this.extractClassifierParams(o)}};var f$=["neutral","happy","sad","angry","fearful","disgusted","surprised"],Rs=class{constructor(t){this.neutral=0;this.happy=0;this.sad=0;this.angry=0;this.fearful=0;this.disgusted=0;this.surprised=0;if(t.length!==7)throw new Error(`FaceExpressions.constructor - expected probabilities.length to be 7, have: ${t.length}`);f$.forEach((n,a)=>{this[n]=t[a]})}asSortedArray(){return f$.map(t=>({expression:t,probability:this[t]})).sort((t,n)=>n.probability-t.probability)}};var ng=class extends Tp{constructor(t=new Np){super("FaceExpressionNet",t)}forwardInput(t){return P(()=>Xa(this.runNet(t)))}async forward(t){return this.forwardInput(await kt(t))}async predictExpressions(t){let n=await kt(t),a=await this.forwardInput(n),r=await Promise.all(pt(a).map(async i=>{let o=i.dataSync();return i.dispose(),o}));a.dispose();let s=r.map(i=>new Rs(i));return n.isBatchInput?s:s[0]}getDefaultModelName(){return"face_expression_model"}getClassifierChannelsIn(){return 256}getClassifierChannelsOut(){return 7}};function g$(e){return e.expressions instanceof Rs}function uk(e,t){return{...e,...{expressions:t}}}function fme(e,t,n=.1,a){(Array.isArray(t)?t:[t]).forEach(s=>{let i=s instanceof Rs?s:g$(s)?s.expressions:void 0;if(!i)throw new Error("drawFaceExpressions - expected faceExpressions to be FaceExpressions | WithFaceExpressions<{}> or array thereof");let l=i.asSortedArray().filter(d=>d.probability>n),u=Wr(s)?s.detection.box.bottomLeft:a||new Pe(0,0);new Br(l.map(d=>`${d.expression} (${Zo(d.probability)})`),u).draw(e)})}function Cp(e){return Wr(e)&&e.landmarks instanceof ka&&e.unshiftedLandmarks instanceof ka&&e.alignedRect instanceof wt}function gme(e){let t=l=>l*180/Math.PI,n=(l,u)=>Math.sqrt((l._x-u._x)**2+(l._y-u._y)**2),a={roll:void 0,pitch:void 0,yaw:void 0},r=(l,u,p)=>{let d=Math.floor(l._x-u._x),c=Math.floor(u._x-p._x);return d-c},s=(l,u)=>{let p=Math.hypot(u._x-l._x,u._y-l._y),d=u._y-l._y,c=Math.asin(d/p),h=t(c),m=Math.floor(90-h),f=u._x-l._x<0?-1:1;return m*f},i=(l,u,p)=>{let 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n=sa(t),{drawLines:a,drawPoints:r,lineWidth:s,lineColor:i,pointSize:o,pointColor:l}=this.options;if(a&&this.faceLandmarks instanceof gp&&(n.strokeStyle=i,n.lineWidth=s,Or(n,this.faceLandmarks.getJawOutline()),Or(n,this.faceLandmarks.getLeftEyeBrow()),Or(n,this.faceLandmarks.getRightEyeBrow()),Or(n,this.faceLandmarks.getNose()),Or(n,this.faceLandmarks.getLeftEye(),!0),Or(n,this.faceLandmarks.getRightEye(),!0),Or(n,this.faceLandmarks.getMouth(),!0)),r){n.strokeStyle=l,n.fillStyle=l;let u=p=>{n.beginPath(),n.arc(p.x,p.y,o,0,2*Math.PI),n.fill()};this.faceLandmarks.positions.forEach(u)}}};function bme(e,t){(Array.isArray(t)?t:[t]).forEach(a=>{let r=a instanceof ka?a:Cp(a)?a.landmarks:void 0;if(!r)throw new Error("drawFaceLandmarks - expected faceExpressions to be FaceLandmarks | WithFaceLandmarks<WithFaceDetection<{}>> or array thereof");new rg(r).draw(e)})}var y$="1.7.11";function vme(e,t){let n=kp(e,t),a=Ip(e,t);function r(i,o,l){let u=a(i,o,`${l}/separable_conv0`),p=a(o,o,`${l}/separable_conv1`),d=n(i,o,1,`${l}/expansion_conv`);return{separable_conv0:u,separable_conv1:p,expansion_conv:d}}function s(i,o){let l=a(i,i,`${o}/separable_conv0`),u=a(i,i,`${o}/separable_conv1`),p=a(i,i,`${o}/separable_conv2`);return{separable_conv0:l,separable_conv1:u,separable_conv2:p}}return{extractConvParams:n,extractSeparableConvParams:a,extractReductionBlockParams:r,extractMainBlockParams:s}}function x$(e,t){let n=[],{extractWeights:a,getRemainingWeights:r}=Fn(e),{extractConvParams:s,extractSeparableConvParams:i,extractReductionBlockParams:o,extractMainBlockParams:l}=vme(a,n),u=s(3,32,3,"entry_flow/conv_in"),p=o(32,64,"entry_flow/reduction_block_0"),d=o(64,128,"entry_flow/reduction_block_1"),c={conv_in:u,reduction_block_0:p,reduction_block_1:d},h={};gr(t,0,1).forEach(b=>{h[`main_block_${b}`]=l(128,`middle_flow/main_block_${b}`)});let m=o(128,256,"exit_flow/reduction_block"),f=i(256,512,"exit_flow/separable_conv"),g={reduction_block:m,separable_conv:f};if(r().length!==0)throw new Error(`weights remaing after extract: ${r().length}`);return{paramMappings:n,params:{entry_flow:c,middle_flow:h,exit_flow:g}}}function wme(e,t){let n=ia(e,t),a=Qf(n),r=Sp(n);function s(o){let l=r(`${o}/separable_conv0`),u=r(`${o}/separable_conv1`),p=a(`${o}/expansion_conv`);return{separable_conv0:l,separable_conv1:u,expansion_conv:p}}function i(o){let l=r(`${o}/separable_conv0`),u=r(`${o}/separable_conv1`),p=r(`${o}/separable_conv2`);return{separable_conv0:l,separable_conv1:u,separable_conv2:p}}return{extractConvParams:a,extractSeparableConvParams:r,extractReductionBlockParams:s,extractMainBlockParams:i}}function v$(e,t){let n=[],{extractConvParams:a,extractSeparableConvParams:r,extractReductionBlockParams:s,extractMainBlockParams:i}=wme(e,n),o=a("entry_flow/conv_in"),l=s("entry_flow/reduction_block_0"),u=s("entry_flow/reduction_block_1"),p={conv_in:o,reduction_block_0:l,reduction_block_1:u},d={};gr(t,0,1).forEach(f=>{d[`main_block_${f}`]=i(`middle_flow/main_block_${f}`)});let c=s("exit_flow/reduction_block"),h=r("exit_flow/separable_conv"),m={reduction_block:c,separable_conv:h};return An(e,n),{params:{entry_flow:p,middle_flow:d,exit_flow:m},paramMappings:n}}function w$(e,t,n){return X(Rt(e,t.filters,n,"same"),t.bias)}function pk(e,t,n=!0){let a=n?Ke(e):e;return a=Hn(a,t.separable_conv0,[1,1]),a=Hn(Ke(a),t.separable_conv1,[1,1]),a=Mt(a,[3,3],[2,2],"same"),a=X(a,w$(e,t.expansion_conv,[2,2])),a}function kme(e,t){let n=Hn(Ke(e),t.separable_conv0,[1,1]);return n=Hn(Ke(n),t.separable_conv1,[1,1]),n=Hn(Ke(n),t.separable_conv2,[1,1]),n=X(n,e),n}var sg=class extends fn{constructor(n){super("TinyXception");this._numMainBlocks=n}forwardInput(n){let{params:a}=this;if(!a)throw new Error("TinyXception - load model before inference");return P(()=>{let r=ie(n.toBatchTensor(112,!0),"float32"),i=br(r,[122.782,117.001,104.298]).div(255),o=Ke(w$(i,a.entry_flow.conv_in,[2,2]));return o=pk(o,a.entry_flow.reduction_block_0,!1),o=pk(o,a.entry_flow.reduction_block_1),gr(this._numMainBlocks,0,1).forEach(l=>{o=kme(o,a.middle_flow[`main_block_${l}`])}),o=pk(o,a.exit_flow.reduction_block),o=Ke(Hn(o,a.exit_flow.separable_conv,[1,1])),o})}async forward(n){return this.forwardInput(await kt(n))}getDefaultModelName(){return"tiny_xception_model"}extractParamsFromWeightMap(n){return v$(n,this._numMainBlocks)}extractParams(n){return x$(n,this._numMainBlocks)}};function k$(e){let t=[],{extractWeights:n,getRemainingWeights:a}=Fn(e),r=Zf(n,t),s=r(512,1,"fc/age"),i=r(512,2,"fc/gender");if(a().length!==0)throw new Error(`weights remaing after extract: ${a().length}`);return{paramMappings:t,params:{fc:{age:s,gender:i}}}}function I$(e){let t=[],n=ia(e,t);function a(s){let i=n(`${s}/weights`,2),o=n(`${s}/bias`,1);return{weights:i,bias:o}}let r={fc:{age:a("fc/age"),gender:a("fc/gender")}};return An(e,t),{params:r,paramMappings:t}}var ck=(n=>(n.FEMALE="female",n.MALE="male",n))(ck||{});var ig=class extends fn{constructor(n=new sg(2)){super("AgeGenderNet");this._faceFeatureExtractor=n}get faceFeatureExtractor(){return this._faceFeatureExtractor}runNet(n){let{params:a}=this;if(!a)throw new Error(`${this._name} - load model before inference`);return P(()=>{let r=n instanceof Vr?this.faceFeatureExtractor.forwardInput(n):n,s=ya(r,[7,7],[2,2],"valid").as2D(r.shape[0],-1),i=Pd(s,a.fc.age).as1D(),o=Pd(s,a.fc.gender);return{age:i,gender:o}})}forwardInput(n){return P(()=>{let{age:a,gender:r}=this.runNet(n);return{age:a,gender:Xa(r)}})}async forward(n){return this.forwardInput(await kt(n))}async predictAgeAndGender(n){let a=await kt(n),r=await this.forwardInput(a),s=pt(r.age),i=pt(r.gender),o=s.map((u,p)=>({ageTensor:u,genderTensor:i[p]})),l=await Promise.all(o.map(async({ageTensor:u,genderTensor:p})=>{let d=u.dataSync()[0],c=p.dataSync()[0],h=c>.5,m=h?"male":"female",f=h?c:1-c;return u.dispose(),p.dispose(),{age:d,gender:m,genderProbability:f}}));return r.age.dispose(),r.gender.dispose(),a.isBatchInput?l:l[0]}getDefaultModelName(){return"age_gender_model"}dispose(n=!0){this.faceFeatureExtractor.dispose(n),super.dispose(n)}loadClassifierParams(n){let{params:a,paramMappings:r}=this.extractClassifierParams(n);this._params=a,this._paramMappings=r}extractClassifierParams(n){return k$(n)}extractParamsFromWeightMap(n){let{featureExtractorMap:a,classifierMap:r}=tg(n);return this.faceFeatureExtractor.loadFromWeightMap(a),I$(r)}extractParams(n){let r=n.slice(0,n.length-1539),s=n.slice(n.length-1539);return this.faceFeatureExtractor.extractWeights(r),this.extractClassifierParams(s)}};var _p=class extends Tp{postProcess(t,n,a){let 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p=Array.from(u.dataSync()),c=R$(l,p,a,.5,r),h=s.getReshapedInputDimensions(0),m=s.inputSize,f=m/h.width,g=m/h.height,b=l.arraySync(),y=c.map(x=>{let[w,I]=[Math.max(0,b[x][0]),Math.min(1,b[x][2])].map(E=>E*g),[T,C]=[Math.max(0,b[x][1]),Math.min(1,b[x][3])].map(E=>E*f);return new wt(p[x],new fp(T,w,C-T,I-w),{height:s.getInputHeight(0),width:s.getInputWidth(0)})});return l.dispose(),u.dispose(),y}getDefaultModelName(){return"ssd_mobilenetv1_model"}extractParamsFromWeightMap(t){return $$(t)}extractParams(t){return F$(t)}};function Dme(e){let t=new tl;return t.extractWeights(e),t}function j2e(e){return Dme(e)}var O$=class extends tl{};var L$=.4,z$=[new Pe(.738768,.874946),new Pe(2.42204,2.65704),new Pe(4.30971,7.04493),new Pe(10.246,4.59428),new Pe(12.6868,11.8741)],W$=[new Pe(1.603231,2.094468),new Pe(6.041143,7.080126),new Pe(2.882459,3.518061),new Pe(4.266906,5.178857),new Pe(9.041765,10.66308)],B$=[117.001,114.697,97.404],V$="tiny_yolov2_model",U$="tiny_yolov2_separable_conv_model";var pg=e=>typeof e=="number";function G$(e){if(!e)throw new Error(`invalid config: ${e}`);if(typeof e.withSeparableConvs!="boolean")throw new Error(`config.withSeparableConvs has to be a boolean, have: ${e.withSeparableConvs}`);if(!pg(e.iouThreshold)||e.iouThreshold<0||e.iouThreshold>1)throw new Error(`config.iouThreshold has to be a number between [0, 1], have: ${e.iouThreshold}`);if(!Array.isArray(e.classes)||!e.classes.length||!e.classes.every(t=>typeof t=="string"))throw new Error(`config.classes has to be an array class names: string[], have: ${JSON.stringify(e.classes)}`);if(!Array.isArray(e.anchors)||!e.anchors.length||!e.anchors.map(t=>t||{}).every(t=>pg(t.x)&&pg(t.y)))throw new Error(`config.anchors has to be an array of { x: number, y: number }, have: ${JSON.stringify(e.anchors)}`);if(e.meanRgb&&(!Array.isArray(e.meanRgb)||e.meanRgb.length!==3||!e.meanRgb.every(pg)))throw new Error(`config.meanRgb has to be an array of shape [number, number, number], have: ${JSON.stringify(e.meanRgb)}`)}function Fp(e){return P(()=>{let t=z(e,ve(.10000000149011612));return X(Ke(pe(e,t)),t)})}function Ur(e,t){return P(()=>{let n=xa(e,[[0,0],[1,1],[1,1],[0,0]]);return n=Rt(n,t.conv.filters,[1,1],"valid"),n=pe(n,t.bn.sub),n=z(n,t.bn.truediv),n=X(n,t.conv.bias),Fp(n)})}function Gr(e,t){return P(()=>{let n=xa(e,[[0,0],[1,1],[1,1],[0,0]]);return n=Ts(n,t.depthwise_filter,t.pointwise_filter,[1,1],"valid"),n=X(n,t.bias),Fp(n)})}function Rme(e,t){let n=kp(e,t);function a(i,o){let l=je(e(i)),u=je(e(i));return t.push({paramPath:`${o}/sub`},{paramPath:`${o}/truediv`}),{sub:l,truediv:u}}function r(i,o,l){let u=n(i,o,3,`${l}/conv`),p=a(o,`${l}/bn`);return{conv:u,bn:p}}let s=Ip(e,t);return{extractConvParams:n,extractConvWithBatchNormParams:r,extractSeparableConvParams:s}}function H$(e,t,n,a){let{extractWeights:r,getRemainingWeights:s}=Fn(e),i=[],{extractConvParams:o,extractConvWithBatchNormParams:l,extractSeparableConvParams:u}=Rme(r,i),p;if(t.withSeparableConvs){let[d,c,h,m,f,g,b,y,x]=a,w=t.isFirstLayerConv2d?o(d,c,3,"conv0"):u(d,c,"conv0"),I=u(c,h,"conv1"),T=u(h,m,"conv2"),C=u(m,f,"conv3"),E=u(f,g,"conv4"),F=u(g,b,"conv5"),D=y?u(b,y,"conv6"):void 0,$=x?u(y,x,"conv7"):void 0,S=o(x||y||b,5*n,1,"conv8");p={conv0:w,conv1:I,conv2:T,conv3:C,conv4:E,conv5:F,conv6:D,conv7:$,conv8:S}}else{let[d,c,h,m,f,g,b,y,x]=a,w=l(d,c,"conv0"),I=l(c,h,"conv1"),T=l(h,m,"conv2"),C=l(m,f,"conv3"),E=l(f,g,"conv4"),F=l(g,b,"conv5"),D=l(b,y,"conv6"),$=l(y,x,"conv7"),S=o(x,5*n,1,"conv8");p={conv0:w,conv1:I,conv2:T,conv3:C,conv4:E,conv5:F,conv6:D,conv7:$,conv8:S}}if(s().length!==0)throw new Error(`weights remaing after extract: ${s().length}`);return{params:p,paramMappings:i}}function Mme(e,t){let n=ia(e,t);function a(o){let l=n(`${o}/sub`,1),u=n(`${o}/truediv`,1);return{sub:l,truediv:u}}function r(o){let l=n(`${o}/filters`,4),u=n(`${o}/bias`,1);return{filters:l,bias:u}}function s(o){let l=r(`${o}/conv`),u=a(`${o}/bn`);return{conv:l,bn:u}}let i=Sp(n);return{extractConvParams:r,extractConvWithBatchNormParams:s,extractSeparableConvParams:i}}function q$(e,t){let n=[],{extractConvParams:a,extractConvWithBatchNormParams:r,extractSeparableConvParams:s}=Mme(e,n),i;if(t.withSeparableConvs){let o=t.filterSizes&&t.filterSizes.length||9;i={conv0:t.isFirstLayerConv2d?a("conv0"):s("conv0"),conv1:s("conv1"),conv2:s("conv2"),conv3:s("conv3"),conv4:s("conv4"),conv5:s("conv5"),conv6:o>7?s("conv6"):void 0,conv7:o>8?s("conv7"):void 0,conv8:a("conv8")}}else i={conv0:r("conv0"),conv1:r("conv1"),conv2:r("conv2"),conv3:r("conv3"),conv4:r("conv4"),conv5:r("conv5"),conv6:r("conv6"),conv7:r("conv7"),conv8:a("conv8")};return An(e,n),{params:i,paramMappings:n}}var yr=class{constructor({inputSize:t,scoreThreshold:n}={}){this._name="TinyYolov2Options";if(this._inputSize=t||416,this._scoreThreshold=n||.5,typeof this._inputSize!="number"||this._inputSize%32!==0)throw new Error(`${this._name} - expected inputSize to be a number divisible by 32`);if(typeof this._scoreThreshold!="number"||this._scoreThreshold<=0||this._scoreThreshold>=1)throw new Error(`${this._name} - expected scoreThreshold to be a number between 0 and 1`)}get inputSize(){return this._inputSize}get scoreThreshold(){return this._scoreThreshold}};var bk=class extends fn{constructor(n){super("TinyYolov2");G$(n),this._config=n}get config(){return this._config}get withClassScores(){return this.config.withClassScores||this.config.classes.length>1}get boxEncodingSize(){return 5+(this.withClassScores?this.config.classes.length:0)}runTinyYolov2(n,a){let r=Ur(n,a.conv0);return r=Mt(r,[2,2],[2,2],"same"),r=Ur(r,a.conv1),r=Mt(r,[2,2],[2,2],"same"),r=Ur(r,a.conv2),r=Mt(r,[2,2],[2,2],"same"),r=Ur(r,a.conv3),r=Mt(r,[2,2],[2,2],"same"),r=Ur(r,a.conv4),r=Mt(r,[2,2],[2,2],"same"),r=Ur(r,a.conv5),r=Mt(r,[2,2],[1,1],"same"),r=Ur(r,a.conv6),r=Ur(r,a.conv7),Qo(r,a.conv8,"valid",!1)}runMobilenet(n,a){let r=this.config.isFirstLayerConv2d?Fp(Qo(n,a.conv0,"valid",!1)):Gr(n,a.conv0);return r=Mt(r,[2,2],[2,2],"same"),r=Gr(r,a.conv1),r=Mt(r,[2,2],[2,2],"same"),r=Gr(r,a.conv2),r=Mt(r,[2,2],[2,2],"same"),r=Gr(r,a.conv3),r=Mt(r,[2,2],[2,2],"same"),r=Gr(r,a.conv4),r=Mt(r,[2,2],[2,2],"same"),r=Gr(r,a.conv5),r=Mt(r,[2,2],[1,1],"same"),r=a.conv6?Gr(r,a.conv6):r,r=a.conv7?Gr(r,a.conv7):r,Qo(r,a.conv8,"valid",!1)}forwardInput(n,a){let{params:r}=this;if(!r)throw new Error("TinyYolov2 - load model before inference");return P(()=>{let s=ie(n.toBatchTensor(a,!1),"float32");return s=this.config.meanRgb?br(s,this.config.meanRgb):s,s=s.div(255),this.config.withSeparableConvs?this.runMobilenet(s,r):this.runTinyYolov2(s,r)})}async forward(n,a){return this.forwardInput(await kt(n),a)}async detect(n,a={}){let{inputSize:r,scoreThreshold:s}=new yr(a),i=await kt(n),o=await this.forwardInput(i,r),l=P(()=>pt(o)[0].expandDims()),u={width:i.getInputWidth(0),height:i.getInputHeight(0)},p=await this.extractBoxes(l,i.getReshapedInputDimensions(0),s);o.dispose(),l.dispose();let d=p.map(b=>b.box),c=p.map(b=>b.score),h=p.map(b=>b.classScore),m=p.map(b=>this.config.classes[b.label]);return e$(d.map(b=>b.rescale(r)),c,this.config.iouThreshold,!0).map(b=>new $s(c[b],h[b],m[b],d[b],u))}getDefaultModelName(){return""}extractParamsFromWeightMap(n){return q$(n,this.config)}extractParams(n){let a=this.config.filterSizes||bk.DEFAULT_FILTER_SIZES,r=a?a.length:void 0;if(r!==7&&r!==8&&r!==9)throw new Error(`TinyYolov2 - expected 7 | 8 | 9 convolutional filters, but found ${r} filterSizes in config`);return H$(n,this.config,this.boxEncodingSize,a)}async extractBoxes(n,a,r){let{width:s,height:i}=a,o=Math.max(s,i),l=o/s,u=o/i,p=n.shape[1],d=this.config.anchors.length,[c,h,m]=P(()=>{let y=n.reshape([p,p,d,this.boxEncodingSize]),x=y.slice([0,0,0,0],[p,p,d,4]),w=y.slice([0,0,0,4],[p,p,d,1]),I=this.withClassScores?Xa(y.slice([0,0,0,5],[p,p,d,this.config.classes.length]),3):ve(0);return[x,w,I]}),f=[],g=await h.array(),b=await c.array();for(let y=0;y<p;y++)for(let x=0;x<p;x++)for(let w=0;w<d;w++){let I=Gf(g[y][x][w][0]);if(!r||I>r){let T=(x+Gf(b[y][x][w][0]))/p*l,C=(y+Gf(b[y][x][w][1]))/p*u,E=Math.exp(b[y][x][w][2])*this.config.anchors[w].x/p*l,F=Math.exp(b[y][x][w][3])*this.config.anchors[w].y/p*u,D=T-E/2,$=C-F/2,S={row:y,col:x,anchor:w},{classScore:M,label:B}=this.withClassScores?await this.extractPredictedClass(m,S):{classScore:1,label:0};f.push({box:new mp(D,$,D+E,$+F),score:I,classScore:I*M,label:B,...S})}}return c.dispose(),h.dispose(),m.dispose(),f}async extractPredictedClass(n,a){let{row:r,col:s,anchor:i}=a,o=await n.array();return Array(this.config.classes.length).fill(0).map((l,u)=>o[r][s][i][u]).map((l,u)=>({classScore:l,label:u})).reduce((l,u)=>l.classScore>u.classScore?l:u)}},nl=bk;nl.DEFAULT_FILTER_SIZES=[3,16,32,64,128,256,512,1024,1024];var $p=class extends nl{constructor(t=!0){let n={withSeparableConvs:t,iouThreshold:L$,classes:["face"],...t?{anchors:W$,meanRgb:B$}:{anchors:z$,withClassScores:!0}};super(n)}get withSeparableConvs(){return this.config.withSeparableConvs}get anchors(){return this.config.anchors}async locateFaces(t,n){return(await this.detect(t,n)).map(r=>new wt(r.score,r.relativeBox,{width:r.imageWidth,height:r.imageHeight}))}getDefaultModelName(){return this.withSeparableConvs?U$:V$}extractParamsFromWeightMap(t){return super.extractParamsFromWeightMap(t)}};function LCe(e,t=!0){let n=new $p(t);return n.extractWeights(e),n}var cg=class extends yr{constructor(){super(...arguments);this._name="TinyFaceDetectorOptions"}};var La=class{async then(t){return t(await this.run())}async run(){throw new Error("ComposableTask - run is not implemented")}};async function al(e,t,n,a,r=({alignedRect:s})=>s){let s=e.map(l=>Cp(l)?r(l):l.detection),i=a||(t instanceof Ce?await Dd(t,s):await $d(t,s)),o=await n(i);return i.forEach(l=>l instanceof Ce&&l.dispose()),o}async function Dp(e,t,n,a,r){return al([e],t,async s=>n(s[0]),a,r)}var j$=.4,K$=[new Pe(1.603231,2.094468),new Pe(6.041143,7.080126),new Pe(2.882459,3.518061),new Pe(4.266906,5.178857),new Pe(9.041765,10.66308)],X$=[117.001,114.697,97.404];var Rp=class extends nl{constructor(){let t={withSeparableConvs:!0,iouThreshold:j$,classes:["face"],anchors:K$,meanRgb:X$,isFirstLayerConv2d:!0,filterSizes:[3,16,32,64,128,256,512]};super(t)}get anchors(){return this.config.anchors}async locateFaces(t,n){return(await this.detect(t,n)).map(r=>new wt(r.score,r.relativeBox,{width:r.imageWidth,height:r.imageHeight}))}getDefaultModelName(){return"tiny_face_detector_model"}extractParamsFromWeightMap(t){return super.extractParamsFromWeightMap(t)}};var rt={ssdMobilenetv1:new tl,tinyFaceDetector:new Rp,tinyYolov2:new $p,faceLandmark68Net:new Ep,faceLandmark68TinyNet:new lg,faceRecognitionNet:new Ap,faceExpressionNet:new ng,ageGenderNet:new ig},Pme=(e,t)=>rt.ssdMobilenetv1.locateFaces(e,t),m_e=(e,t)=>rt.tinyFaceDetector.locateFaces(e,t),f_e=(e,t)=>rt.tinyYolov2.locateFaces(e,t),Ome=e=>rt.faceLandmark68Net.detectLandmarks(e),g_e=e=>rt.faceLandmark68TinyNet.detectLandmarks(e),b_e=e=>rt.faceRecognitionNet.computeFaceDescriptor(e),y_e=e=>rt.faceExpressionNet.predictExpressions(e),x_e=e=>rt.ageGenderNet.predictAgeAndGender(e),Lme=e=>rt.ssdMobilenetv1.load(e),v_e=e=>rt.tinyFaceDetector.load(e),w_e=e=>rt.tinyYolov2.load(e),k_e=e=>rt.faceLandmark68Net.load(e),I_e=e=>rt.faceLandmark68TinyNet.load(e),S_e=e=>rt.faceRecognitionNet.load(e),N_e=e=>rt.faceExpressionNet.load(e),T_e=e=>rt.ageGenderNet.load(e),C_e=Lme,__e=Pme,E_e=Ome;var dg=class extends La{constructor(n,a,r){super();this.parentTask=n;this.input=a;this.extractedFaces=r}},rl=class extends dg{async run(){let t=await this.parentTask,n=await al(t,this.input,async a=>Promise.all(a.map(r=>rt.faceExpressionNet.predictExpressions(r))),this.extractedFaces);return t.map((a,r)=>uk(a,n[r]))}withAgeAndGender(){return new il(this,this.input)}},sl=class extends dg{async run(){let t=await this.parentTask;if(!t)return;let n=await Dp(t,this.input,a=>rt.faceExpressionNet.predictExpressions(a),this.extractedFaces);return uk(t,n)}withAgeAndGender(){return new ol(this,this.input)}},Ms=class extends rl{withAgeAndGender(){return new Os(this,this.input)}withFaceDescriptors(){return new zs(this,this.input)}},Ps=class extends sl{withAgeAndGender(){return new Ls(this,this.input)}withFaceDescriptor(){return new Ws(this,this.input)}};var hg=class extends La{constructor(n,a,r){super();this.parentTask=n;this.input=a;this.extractedFaces=r}},il=class extends hg{async run(){let t=await this.parentTask,n=await al(t,this.input,async a=>Promise.all(a.map(r=>rt.ageGenderNet.predictAgeAndGender(r))),this.extractedFaces);return t.map((a,r)=>{let{age:s,gender:i,genderProbability:o}=n[r];return fk(gk(a,i,o),s)})}withFaceExpressions(){return new rl(this,this.input)}},ol=class extends hg{async run(){let t=await this.parentTask;if(!t)return;let{age:n,gender:a,genderProbability:r}=await Dp(t,this.input,s=>rt.ageGenderNet.predictAgeAndGender(s),this.extractedFaces);return fk(gk(t,a,r),n)}withFaceExpressions(){return new sl(this,this.input)}},Os=class extends il{withFaceExpressions(){return new Ms(this,this.input)}withFaceDescriptors(){return new zs(this,this.input)}},Ls=class extends ol{withFaceExpressions(){return new Ps(this,this.input)}withFaceDescriptor(){return new Ws(this,this.input)}};var mg=class extends La{constructor(n,a){super();this.parentTask=n;this.input=a}},zs=class extends mg{async run(){let t=await this.parentTask;return(await al(t,this.input,a=>Promise.all(a.map(r=>rt.faceRecognitionNet.computeFaceDescriptor(r))),null,a=>a.landmarks.align(null,{useDlibAlignment:!0}))).map((a,r)=>mk(t[r],a))}withFaceExpressions(){return new Ms(this,this.input)}withAgeAndGender(){return new Os(this,this.input)}},Ws=class extends mg{async run(){let t=await this.parentTask;if(!t)return;let n=await Dp(t,this.input,a=>rt.faceRecognitionNet.computeFaceDescriptor(a),null,a=>a.landmarks.align(null,{useDlibAlignment:!0}));return mk(t,n)}withFaceExpressions(){return new Ps(this,this.input)}withAgeAndGender(){return new Ls(this,this.input)}};var fg=class extends La{constructor(n,a,r){super();this.parentTask=n;this.input=a;this.useTinyLandmarkNet=r}get landmarkNet(){return this.useTinyLandmarkNet?rt.faceLandmark68TinyNet:rt.faceLandmark68Net}},gg=class extends fg{async run(){let t=await this.parentTask,n=t.map(i=>i.detection),a=this.input instanceof Ce?await Dd(this.input,n):await $d(this.input,n),r=await Promise.all(a.map(i=>this.landmarkNet.detectLandmarks(i)));return a.forEach(i=>i instanceof Ce&&i.dispose()),t.filter((i,o)=>r[o]).map((i,o)=>Od(i,r[o]))}withFaceExpressions(){return new Ms(this,this.input)}withAgeAndGender(){return new Os(this,this.input)}withFaceDescriptors(){return new zs(this,this.input)}},bg=class extends fg{async run(){let t=await this.parentTask;if(!t)return;let{detection:n}=t,a=this.input instanceof Ce?await Dd(this.input,[n]):await $d(this.input,[n]),r=await this.landmarkNet.detectLandmarks(a[0]);return a.forEach(s=>s instanceof Ce&&s.dispose()),Od(t,r)}withFaceExpressions(){return new Ps(this,this.input)}withAgeAndGender(){return new Ls(this,this.input)}withFaceDescriptor(){return new Ws(this,this.input)}};var yg=class extends La{constructor(n,a=new Oa){super();this.input=n;this.options=a}},zd=class extends yg{async run(){let{input:t,options:n}=this,a;if(n instanceof cg)a=rt.tinyFaceDetector.locateFaces(t,n);else if(n instanceof Oa)a=rt.ssdMobilenetv1.locateFaces(t,n);else if(n instanceof yr)a=rt.tinyYolov2.locateFaces(t,n);else throw new Error("detectFaces - expected options to be instance of TinyFaceDetectorOptions | SsdMobilenetv1Options | TinyYolov2Options");return a}runAndExtendWithFaceDetections(){return new Promise((t,n)=>{this.run().then(a=>t(a.map(r=>bp({},r)))).catch(a=>n(a))})}withFaceLandmarks(t=!1){return new gg(this.runAndExtendWithFaceDetections(),this.input,t)}withFaceExpressions(){return new rl(this.runAndExtendWithFaceDetections(),this.input)}withAgeAndGender(){return new il(this.runAndExtendWithFaceDetections(),this.input)}},xg=class extends yg{async run(){let t=await new zd(this.input,this.options),n=t[0];return t.forEach(a=>{a.score>n.score&&(n=a)}),n}runAndExtendWithFaceDetection(){return new Promise(async t=>{let n=await this.run();t(n?bp({},n):void 0)})}withFaceLandmarks(t=!1){return new bg(this.runAndExtendWithFaceDetection(),this.input,t)}withFaceExpressions(){return new sl(this.runAndExtendWithFaceDetection(),this.input)}withAgeAndGender(){return new ol(this.runAndExtendWithFaceDetection(),this.input)}};function TEe(e,t=new Oa){return new xg(e,t)}function yk(e,t=new Oa){return new zd(e,t)}async function zme(e,t){return yk(e,new Oa(t?{minConfidence:t}:{})).withFaceLandmarks().withFaceDescriptors()}async function $Ee(e,t={}){return yk(e,new yr(t)).withFaceLandmarks().withFaceDescriptors()}var DEe=zme;function Y$(e,t){if(e.length!==t.length)throw new Error("euclideanDistance: arr1.length !== arr2.length");let n=Array.from(e),a=Array.from(t);return Math.sqrt(n.map((r,s)=>r-a[s]).reduce((r,s)=>r+s*s,0))}var vg=class{constructor(t,n=.6){this._distanceThreshold=n;let a=Array.isArray(t)?t:[t];if(!a.length)throw new Error("FaceRecognizer.constructor - expected atleast one input");let r=1,s=()=>`person ${r++}`;this._labeledDescriptors=a.map(i=>{if(i instanceof zr)return i;if(i instanceof Float32Array)return new zr(s(),[i]);if(i.descriptor&&i.descriptor instanceof Float32Array)return new zr(s(),[i.descriptor]);throw new Error("FaceRecognizer.constructor - expected inputs to be of type LabeledFaceDescriptors | WithFaceDescriptor<any> | Float32Array | Array<LabeledFaceDescriptors | WithFaceDescriptor<any> | Float32Array>")})}get labeledDescriptors(){return this._labeledDescriptors}get distanceThreshold(){return this._distanceThreshold}computeMeanDistance(t,n){return n.map(a=>Y$(a,t)).reduce((a,r)=>a+r,0)/(n.length||1)}matchDescriptor(t){return this.labeledDescriptors.map(({descriptors:n,label:a})=>new _d(a,this.computeMeanDistance(t,n))).reduce((n,a)=>n.distance<a.distance?n:a)}findBestMatch(t){let n=this.matchDescriptor(t);return n.distance<this._distanceThreshold?n:new _d("unknown",n.distance)}toJSON(){return{distanceThreshold:this._distanceThreshold,labeledDescriptors:this._labeledDescriptors.map(t=>t.toJSON())}}static fromJSON(t){let n=t.labeledDescriptors.map(a=>zr.fromJSON(a));return new vg(n,t.distanceThreshold)}};function ZEe(e){let t=new Rp;return t.extractWeights(e),t}function Wme(e,t){let{width:n,height:a}=new En(t.width,t.height);if(n<=0||a<=0)throw new Error(`resizeResults - invalid dimensions: ${JSON.stringify({width:n,height:a})}`);if(Array.isArray(e))return e.map(r=>Wme(r,{width:n,height:a}));if(Cp(e)){let r=e.detection.forSize(n,a),s=e.unshiftedLandmarks.forSize(r.box.width,r.box.height);return Od(bp(e,r),s)}return Wr(e)?bp(e,e.detection.forSize(n,a)):e instanceof ka||e instanceof wt?e.forSize(n,a):e}var lAe=y$;export{ig as AgeGenderNet,mp as BoundingBox,dt as Box,La as ComposableTask,zs as ComputeAllFaceDescriptorsTask,mg as ComputeFaceDescriptorsTaskBase,Ws as ComputeSingleFaceDescriptorTask,gg as DetectAllFaceLandmarksTask,zd as DetectAllFacesTask,fg as DetectFaceLandmarksTaskBase,yg as DetectFacesTaskBase,bg as DetectSingleFaceLandmarksTask,xg as DetectSingleFaceTask,En as Dimensions,f$ as FACE_EXPRESSION_LABELS,wt as FaceDetection,O$ as FaceDetectionNet,ng as FaceExpressionNet,Rs as FaceExpressions,Ep as FaceLandmark68Net,lg as FaceLandmark68TinyNet,T$ as FaceLandmarkNet,ka as FaceLandmarks,n$ as FaceLandmarks5,gp as FaceLandmarks68,_d as FaceMatch,vg as FaceMatcher,Ap as FaceRecognitionNet,ck as Gender,Ed as LabeledBox,zr as LabeledFaceDescriptors,Vr as NetInput,fn as NeuralNetwork,$s as ObjectDetection,Pe as Point,a$ as PredictedBox,fp as Rect,tl as SsdMobilenetv1,Oa as SsdMobilenetv1Options,Rp as TinyFaceDetector,cg as TinyFaceDetectorOptions,$p as TinyYolov2,yr as TinyYolov2Options,DEe as allFaces,zme as allFacesSsdMobilenetv1,$Ee as allFacesTinyYolov2,r$ as awaitMediaLoaded,s$ as bufferToImage,b_e as computeFaceDescriptor,wp as createCanvas,Kf as createCanvasFromMedia,j2e as createFaceDetectionNet,jTe as createFaceRecognitionNet,Dme as createSsdMobilenetv1,ZEe as createTinyFaceDetector,LCe as createTinyYolov2,yk as detectAllFaces,Ome as detectFaceLandmarks,g_e as detectFaceLandmarksTiny,E_e as detectLandmarks,TEe as detectSingleFace,b$ as draw,at as env,Y$ as euclideanDistance,fk as extendWithAge,mk as extendWithFaceDescriptor,bp as extendWithFaceDetection,uk as extendWithFaceExpressions,Od as extendWithFaceLandmarks,gk as extendWithGender,Dd as extractFaceTensors,$d as extractFaces,ake as fetchImage,l$ as fetchJson,lke as fetchNetWeights,Ds as fetchOrThrow,mke as fetchVideo,sa as getContext2dOrThrow,vp as getMediaDimensions,i$ as imageTensorToCanvas,o$ as imageToSquare,ywe as inverseSigmoid,JF as iou,lk as isMediaElement,jf as isMediaLoaded,ZTe as isWithAge,Wr as isWithFaceDetection,g$ as isWithFaceExpressions,Cp as isWithFaceLandmarks,t2e as isWithGender,T_e as loadAgeGenderModel,C_e as loadFaceDetectionModel,N_e as loadFaceExpressionModel,k_e as loadFaceLandmarkModel,I_e as loadFaceLandmarkTinyModel,S_e as loadFaceRecognitionModel,Lme as loadSsdMobilenetv1Model,v_e as loadTinyFaceDetectorModel,w_e as loadTinyYolov2Model,p$ as loadWeightMap,__e as locateFaces,wke as matchDimensions,QF as minBbox,rt as nets,e$ as nonMaxSuppression,br as normalize,t$ as padToSquare,x_e as predictAgeAndGender,y_e as recognizeFaceExpressions,Wme as resizeResults,yp as resolveInput,gwe as shuffleArray,Gf as sigmoid,Pme as ssdMobilenetv1,ze as tf,m_e as tinyFaceDetector,f_e as tinyYolov2,kt as toNetInput,ZF as utils,G$ as validateConfig,lAe as version};
//# sourceMappingURL=face-api.esm.js.map
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