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u={x:o},c={filterSize:t,strides:n,pad:r,dimRoundingMode:a,dataFormat:s},h=M.runKernel(Gl,u,c);return h=Ae(h,o.dtype),l?H(h,[h.shape[1],h.shape[2],h.shape[3],h.shape[4]]):h}var zf=O({avgPool3d_:LI});function PI(e,t=0){F(e.length>=1,()=>"Pass at least one tensor to concat");let n=Bu(e,"tensors","concat","string_or_numeric");if(n[0].dtype==="complex64"&&n.forEach(s=>{if(s.dtype!=="complex64")throw new Error(`Cannot concatenate complex64 tensors with a tensor with dtype ${s.dtype}. `)}),n.length===1)return Ir(n[0]);let r=n,a={axis:t};return M.runKernel(ji,r,a)}var ot=O({concat_:PI});function WI(e){let t={x:R(e,"x","sigmoid")};return M.runKernel(Rs,t)}var Qn=O({sigmoid_:WI});function BI(e,t,n){let r=R(e,"x","slice","string_or_numeric");if(r.rank===0)throw new Error("Slicing scalar is not possible");let a={x:r},s={begin:t,size:n};return M.runKernel(Io,a,s)}var Fe=O({slice_:BI});function VI(e){let t={x:R(e,"x","tanh")};return M.runKernel(zs,t)}var Po=O({tanh_:VI});function UI(e,t,n,r,a,s){let i=R(e,"forgetBias","basicLSTMCell"),o=R(t,"lstmKernel","basicLSTMCell"),l=R(n,"lstmBias","basicLSTMCell"),u=R(r,"data","basicLSTMCell"),c=R(a,"c","basicLSTMCell"),h=R(s,"h","basicLSTMCell"),d=ot([u,h],1),p=Ge(d,o),f=oe(p,l),m=f.shape[0],A=f.shape[1]/4,y=[m,A],g=Fe(f,[0,0],y),w=Fe(f,[0,A],y),_=Fe(f,[0,A*2],y),b=Fe(f,[0,A*3],y),x=oe(W(Qn(g),Po(w)),W(c,Qn(oe(i,_)))),N=W(Po(x),Qn(b));return[x,N]}var z4=O({basicLSTMCell_:UI});function jI(e,t,n){let r=R(e,"x","batchToSpaceND"),a=t.reduce((o,l)=>o*l);F(r.rank>=1+t.length,()=>`input rank is ${r.rank} but should be > than blockShape.length ${t.length}`),F(n.length===t.length,()=>`crops.length is ${n.length} but should be equal to blockShape.length ${t.length}`),F(r.shape[0]%a==0,()=>`input tensor batch is ${r.shape[0]} but is not divisible by the product of the elements of blockShape ${t.join(" * ")} === ${a}`);let s={x:r},i={blockShape:t,crops:n};return M.runKernel(ql,s,i)}var mu=O({batchToSpaceND_:jI});function HI(e){let t;return 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Wf=O({depthToSpace_:mN});function AN(e,t,n,r,a="NHWC",s=[1,1],i){let o=R(e,"x","depthwiseConv2d"),l=R(t,"filter","depthwiseConv2d"),u=o,c=!1;o.rank===3&&(c=!0,u=H(o,[1,o.shape[0],o.shape[1],o.shape[2]])),F(u.rank===4,()=>`Error in depthwiseConv2d: input must be rank 4, but got rank ${u.rank}.`),F(l.rank===4,()=>`Error in depthwiseConv2d: filter must be rank 4, but got rank ${l.rank}.`),F(u.shape[3]===l.shape[2],()=>`Error in depthwiseConv2d: number of input channels (${u.shape[3]}) must match the inChannels dimension in filter ${l.shape[2]}.`),i!=null&&F(jt(r),()=>`Error in depthwiseConv2d: pad must be an integer when using, dimRoundingMode ${i} but got pad ${r}.`);let h={x:u,filter:l},d={strides:n,pad:r,dataFormat:a,dilations:s,dimRoundingMode:i},p=M.runKernel(rs,h,d);return c?H(p,[p.shape[1],p.shape[2],p.shape[3]]):p}var Wo=O({depthwiseConv2d_:AN});function yN(e){let t={x:R(e,"x","diag")};return M.runKernel(yh,t)}var P4=O({diag_:yN});function gN(e,t,n,r,a=[1,1],s="NHWC"){let 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a=R(e,"labels","absoluteDifference"),s=R(t,"predictions","absoluteDifference"),i=null;n!=null&&(i=R(n,"weights","absoluteDifference")),nn(a.shape,s.shape,"Error in absoluteDifference: ");let o=Dt(xe(a,s));return na(o,i,r)}var RE=O({absoluteDifference_:CE});function FE(e,t,n,r,a=ln.SUM_BY_NONZERO_WEIGHTS){let s=R(e,"labels","cosineDistance"),i=R(t,"predictions","cosineDistance"),o=null;r!=null&&(o=R(r,"weights","cosineDistance")),nn(s.shape,i.shape,"Error in cosineDistance: ");let l=ke(1),u=xe(l,Ee(W(s,i),n,!0));return na(u,o,a)}var $E=O({cosineDistance_:FE});function ME(e,t,n,r=ln.SUM_BY_NONZERO_WEIGHTS){let a=R(e,"labels","hingeLoss"),s=R(t,"predictions","hingeLoss"),i=null;n!=null&&(i=R(n,"weights","hingeLoss")),nn(a.shape,s.shape,"Error in hingeLoss: ");let o=ke(1);a=xe(W(ke(2),a),o);let l=Cr(xe(o,W(a,s)));return na(l,i,r)}var DE=O({hingeLoss_:ME});function OE(e,t,n,r=1,a=ln.SUM_BY_NONZERO_WEIGHTS){let s=R(e,"labels","huberLoss"),i=R(t,"predictions","huberLoss"),o=null;n!=null&&(o=R(n,"weights","huberLoss")),nn(s.shape,i.shape,"Error in huberLoss: ");let l=ke(r),u=Dt(xe(i,s)),c=Ho(u,l),h=xe(u,c),d=oe(W(ke(.5),it(c)),W(l,h));return na(d,o,a)}var zE=O({huberLoss_:OE});function LE(e,t,n,r=1e-7,a=ln.SUM_BY_NONZERO_WEIGHTS){let s=R(e,"labels","logLoss"),i=R(t,"predictions","logLoss"),o=null;n!=null&&(o=R(n,"weights","logLoss")),nn(s.shape,i.shape,"Error in logLoss: ");let l=ke(1),u=ke(r),c=_t(W(s,Sn(oe(i,u)))),h=W(xe(l,s),Sn(oe(xe(l,i),u))),d=xe(c,h);return na(d,o,a)}var PE=O({logLoss_:LE});function WE(e,t,n,r=ln.SUM_BY_NONZERO_WEIGHTS){let a=R(e,"labels","meanSquaredError"),s=R(t,"predictions","meanSquaredError"),i=null;n!=null&&(i=R(n,"weights","meanSquaredError")),nn(a.shape,s.shape,"Error in meanSquaredError: ");let o=cd(a,s);return na(o,i,r)}var BE=O({meanSquaredError_:WE});function VE(e,t){let n=R(e,"labels","sigmoidCrossEntropyWithLogits"),r=R(t,"logits","sigmoidCrossEntropyWithLogits");nn(n.shape,r.shape,"Error in sigmoidCrossEntropyWithLogits: ");let a=Cr(r),s=W(r,n),i=Zh(Vn(_t(Dt(r))));return oe(xe(a,s),i)}function UE(e,t,n,r=0,a=ln.SUM_BY_NONZERO_WEIGHTS){let s=R(e,"multiClassLabels","sigmoidCrossEntropy"),i=R(t,"logits","sigmoidCrossEntropy"),o=null;if(n!=null&&(o=R(n,"weights","sigmoidCrossEntropy")),nn(s.shape,i.shape,"Error in sigmoidCrossEntropy: "),r>0){let u=ke(r),c=ke(1),h=ke(.5);s=oe(W(s,xe(c,u)),W(h,u))}let l=VE(s,i);return na(l,o,a)}var jE=O({sigmoidCrossEntropy_:UE});function HE(e,t,n=-1){if(n===-1&&(n=t.rank-1),n!==t.rank-1)throw Error(`Softmax cross entropy along a non-last dimension is not yet supported. Labels / logits was rank ${t.rank} and dim was ${n}`);return Sr((r,a,s)=>{let i=qf(a,[n],!0),o=xe(Ae(a,"float32"),i);s([r,o]);let l=_t(W(o,r));return{value:Ee(l,[n]),gradFunc:(u,c)=>{let[h,d]=c,p=ei(u.shape,[n]);return[W(H(u,p),xe(Ae(h,"float32"),Vn(d))),W(H(u,p),xe(Vn(d),Ae(h,"float32")))]}}})(e,t)}function GE(e,t,n,r=0,a=ln.SUM_BY_NONZERO_WEIGHTS){let s=R(e,"onehotLabels","softmaxCrossEntropy"),i=R(t,"logits","softmaxCrossEntropy"),o=null;if(n!=null&&(o=R(n,"weights","softmaxCrossEntropy")),nn(s.shape,i.shape,"Error in softmaxCrossEntropy: "),r>0){let u=ke(r),c=ke(1),h=ke(s.shape[1]);s=oe(W(s,xe(c,u)),ve(u,h))}let l=HE(s,i);return na(l,o,a)}var qE=O({softmaxCrossEntropy_:GE}),l8={fft:Su,ifft:qo,rfft:Tu,irfft:ud},u8={hammingWindow:GT,hannWindow:K5,frame:Z5,stft:ZT},St={flipLeftRight:eE,resizeNearestNeighbor:nx,resizeBilinear:tx,rotateWithOffset:nE,cropAndResize:JT,nonMaxSuppression:aE,nonMaxSuppressionAsync:dE,nonMaxSuppressionWithScore:fE,nonMaxSuppressionWithScoreAsync:AE,nonMaxSuppressionPadded:gE,nonMaxSuppressionPaddedAsync:wE},y0={bandPart:kE,gramSchmidt:NE,qr:TE},c8={absoluteDifference:RE,computeWeightedLoss:na,cosineDistance:$E,hingeLoss:DE,huberLoss:zE,logLoss:PE,meanSquaredError:BE,sigmoidCrossEntropy:jE,softmaxCrossEntropy:qE},Jr=class extends D5{minimize(e,t=!1,n){let{value:r,grads:a}=this.computeGradients(e,n);if(n!=null){let s=n.map(i=>({name:i.name,tensor:a[i.name]}));this.applyGradients(s)}else this.applyGradients(a);return Re(a),t?r:(r.dispose(),null)}get iterations(){return this.iterations_==null&&(this.iterations_=0),this.iterations_}incrementIterations(){this.iterations_=this.iterations+1}computeGradients(e,t){return a0(e,t)}dispose(){this.iterations_!=null&&Re(this.iterations_)}async saveIterations(){return this.iterations_==null&&(this.iterations_=0),{name:"iter",tensor:ke(this.iterations_,"int32")}}async getWeights(){throw new Error("getWeights() is not implemented for this optimizer yet.")}async setWeights(e){throw new Error(`setWeights() is not implemented for this optimizer class ${this.getClassName()}`)}async extractIterations(e){return this.iterations_=(await e[0].tensor.data())[0],e.slice(1)}};Object.defineProperty(Jr,Symbol.hasInstance,{value:e=>e.minimize!=null&&e.computeGradients!=null&&e.applyGradients!=null});var fd=class extends Jr{constructor(e,t,n=null){super();this.learningRate=e,this.rho=t,this.epsilon=n,this.accumulatedGrads=[],this.accumulatedUpdates=[],n==null&&(this.epsilon=M.backend.epsilon())}applyGradients(e){(Array.isArray(e)?e.map(t=>t.name):Object.keys(e)).forEach((t,n)=>{let r=M.registeredVariables[t],a=!1;this.accumulatedGrads[n]==null&&(this.accumulatedGrads[n]={originalName:`${t}/accum_grad`,variable:V(()=>je(r).variable(a))}),this.accumulatedUpdates[n]==null&&(this.accumulatedUpdates[n]={originalName:`${t}/accum_var`,variable:V(()=>je(r).variable(a))});let s=Array.isArray(e)?e[n].tensor:e[t];if(s==null)return;let i=this.accumulatedGrads[n].variable,o=this.accumulatedUpdates[n].variable;V(()=>{let l=oe(W(i,this.rho),W(it(s),1-this.rho)),u=W(ve(Yt(oe(o,this.epsilon)),Yt(oe(i,this.epsilon))),s),c=oe(W(o,this.rho),W(it(u),1-this.rho));i.assign(l),o.assign(c);let h=oe(W(u,-this.learningRate),r);r.assign(h)})}),this.incrementIterations()}dispose(){this.accumulatedUpdates!=null&&(Re(this.accumulatedGrads.map(e=>e.variable)),Re(this.accumulatedUpdates.map(e=>e.variable)))}async getWeights(){let e=[...this.accumulatedGrads,...this.accumulatedUpdates];return[await this.saveIterations()].concat(e.map(t=>({name:t.originalName,tensor:t.variable})))}async setWeights(e){e=await this.extractIterations(e);let t=e.length/2,n=!1;this.accumulatedGrads=e.slice(0,t).map(r=>({originalName:r.name,variable:r.tensor.variable(n)})),this.accumulatedUpdates=e.slice(t,t*2).map(r=>({originalName:r.name,variable:r.tensor.variable(n)}))}getConfig(){return{learningRate:this.learningRate,rho:this.rho,epsilon:this.epsilon}}static fromConfig(e,t){return new e(t.learningRate,t.rho,t.epsilon)}};fd.className="Adadelta";Ca(fd);var md=class extends Jr{constructor(e,t=.1){super();this.learningRate=e,this.initialAccumulatorValue=t,this.accumulatedGrads=[]}applyGradients(e){(Array.isArray(e)?e.map(t=>t.name):Object.keys(e)).forEach((t,n)=>{let r=M.registeredVariables[t];if(this.accumulatedGrads[n]==null){let i=!1;this.accumulatedGrads[n]={originalName:`${t}/accumulator`,variable:V(()=>gu(r.shape,this.initialAccumulatorValue).variable(i))}}let a=Array.isArray(e)?e[n].tensor:e[t];if(a==null)return;let s=this.accumulatedGrads[n].variable;V(()=>{let i=oe(s,it(a));s.assign(i);let o=oe(W(ve(a,Yt(oe(i,M.backend.epsilon()))),-this.learningRate),r);r.assign(o)})}),this.incrementIterations()}dispose(){this.accumulatedGrads!=null&&Re(this.accumulatedGrads.map(e=>e.variable))}async getWeights(){return[await this.saveIterations()].concat(this.accumulatedGrads.map(e=>({name:e.originalName,tensor:e.variable})))}async setWeights(e){e=await this.extractIterations(e);let t=!1;this.accumulatedGrads=e.map(n=>({originalName:n.name,variable:n.tensor.variable(t)}))}getConfig(){return{learningRate:this.learningRate,initialAccumulatorValue:this.initialAccumulatorValue}}static fromConfig(e,t){return new e(t.learningRate,t.initialAccumulatorValue)}};md.className="Adagrad";Ca(md);var Ad=class extends Jr{constructor(e,t,n,r=null){super();this.learningRate=e,this.beta1=t,this.beta2=n,this.epsilon=r,this.accumulatedFirstMoment=[],this.accumulatedSecondMoment=[],V(()=>{this.accBeta1=ke(t).variable(),this.accBeta2=ke(n).variable()}),r==null&&(this.epsilon=M.backend.epsilon())}applyGradients(e){let t=Array.isArray(e)?e.map(n=>n.name):Object.keys(e);V(()=>{let n=xe(1,this.accBeta1),r=xe(1,this.accBeta2);t.forEach((a,s)=>{let i=M.registeredVariables[a],o=!1;this.accumulatedFirstMoment[s]==null&&(this.accumulatedFirstMoment[s]={originalName:`${a}/m`,variable:V(()=>je(i).variable(o))}),this.accumulatedSecondMoment[s]==null&&(this.accumulatedSecondMoment[s]={originalName:`${a}/v`,variable:V(()=>je(i).variable(o))});let l=Array.isArray(e)?e[s].tensor:e[a];if(l==null)return;let u=this.accumulatedFirstMoment[s].variable,c=this.accumulatedSecondMoment[s].variable,h=oe(W(u,this.beta1),W(l,1-this.beta1)),d=oe(W(c,this.beta2),W(it(l),1-this.beta2)),p=ve(h,n),f=ve(d,r);u.assign(h),c.assign(d);let m=oe(W(ve(p,oe(Yt(f),this.epsilon)),-this.learningRate),i);i.assign(m)}),this.accBeta1.assign(W(this.accBeta1,this.beta1)),this.accBeta2.assign(W(this.accBeta2,this.beta2))}),this.incrementIterations()}dispose(){this.accBeta1.dispose(),this.accBeta2.dispose(),this.accumulatedFirstMoment!=null&&Re(this.accumulatedFirstMoment.map(e=>e.variable)),this.accumulatedSecondMoment!=null&&Re(this.accumulatedSecondMoment.map(e=>e.variable))}async getWeights(){let e=[...this.accumulatedFirstMoment,...this.accumulatedSecondMoment];return[await this.saveIterations()].concat(e.map(t=>({name:t.originalName,tensor:t.variable})))}async setWeights(e){e=await this.extractIterations(e),V(()=>{this.accBeta1.assign(Yr(this.beta1,this.iterations_+1)),this.accBeta2.assign(Yr(this.beta2,this.iterations_+1))});let t=e.length/2,n=!1;this.accumulatedFirstMoment=e.slice(0,t).map(r=>({originalName:r.name,variable:r.tensor.variable(n)})),this.accumulatedSecondMoment=e.slice(t,t*2).map(r=>({originalName:r.name,variable:r.tensor.variable(n)}))}getConfig(){return{learningRate:this.learningRate,beta1:this.beta1,beta2:this.beta2,epsilon:this.epsilon}}static fromConfig(e,t){return new e(t.learningRate,t.beta1,t.beta2,t.epsilon)}};Ad.className="Adam";Ca(Ad);var yd=class extends Jr{constructor(e,t,n,r=null,a=0){super();this.learningRate=e,this.beta1=t,this.beta2=n,this.epsilon=r,this.decay=a,this.accumulatedFirstMoment=[],this.accumulatedWeightedInfNorm=[],V(()=>{this.iteration=ke(0).variable(),this.accBeta1=ke(t).variable()}),r==null&&(this.epsilon=M.backend.epsilon())}applyGradients(e){let t=Array.isArray(e)?e.map(n=>n.name):Object.keys(e);V(()=>{let n=xe(1,this.accBeta1),r=ve(-this.learningRate,oe(W(this.iteration,this.decay),1));t.forEach((a,s)=>{let i=M.registeredVariables[a],o=!1;this.accumulatedFirstMoment[s]==null&&(this.accumulatedFirstMoment[s]={originalName:`${a}/m`,variable:je(i).variable(o)}),this.accumulatedWeightedInfNorm[s]==null&&(this.accumulatedWeightedInfNorm[s]={originalName:`${a}/v`,variable:je(i).variable(o)});let l=Array.isArray(e)?e[s].tensor:e[a];if(l==null)return;let u=this.accumulatedFirstMoment[s].variable,c=this.accumulatedWeightedInfNorm[s].variable,h=oe(W(u,this.beta1),W(l,1-this.beta1)),d=W(c,this.beta2),p=Dt(l),f=Tr(d,p);u.assign(h),c.assign(f);let m=oe(W(ve(r,n),ve(h,oe(f,this.epsilon))),i);i.assign(m)}),this.iteration.assign(oe(this.iteration,1)),this.accBeta1.assign(W(this.accBeta1,this.beta1))}),this.incrementIterations()}dispose(){this.accBeta1.dispose(),this.iteration.dispose(),this.accumulatedFirstMoment!=null&&Re(this.accumulatedFirstMoment.map(e=>e.variable)),this.accumulatedWeightedInfNorm!=null&&Re(this.accumulatedWeightedInfNorm.map(e=>e.variable))}async getWeights(){throw new Error("getWeights() is not implemented for Adamax yet.")}async setWeights(e){throw new Error("setWeights() is not implemented for Adamax yet.")}getConfig(){return{learningRate:this.learningRate,beta1:this.beta1,beta2:this.beta2,epsilon:this.epsilon,decay:this.decay}}static fromConfig(e,t){return new e(t.learningRate,t.beta1,t.beta2,t.epsilon,t.decay)}};yd.className="Adamax";Ca(yd);var Eu=class extends Jr{constructor(e){super();this.learningRate=e,this.setLearningRate(e)}applyGradients(e){(Array.isArray(e)?e.map(t=>t.name):Object.keys(e)).forEach((t,n)=>{let r=Array.isArray(e)?e[n].tensor:e[t];if(r==null)return;let a=M.registeredVariables[t];V(()=>{let s=oe(W(this.c,r),a);a.assign(s)})}),this.incrementIterations()}setLearningRate(e){this.learningRate=e,this.c!=null&&this.c.dispose(),this.c=Vt(ke(-e))}dispose(){this.c.dispose()}async getWeights(){return[await this.saveIterations()]}async setWeights(e){if(e=await this.extractIterations(e),e.length!==0)throw new Error("SGD optimizer does 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RF(e){let{inputs:t,backend:n,attrs:r}=e,{image:a,boxes:s,boxInd:i}=t,{cropSize:o,method:l,extrapolationValue:u}=r,[c,h,d,p]=a.shape,f=s.shape[0],[m,A]=o,y=We([f,m,A,p],"float32"),g=n.data.get(s.dataId).values,w=n.data.get(i.dataId).values,_=n.data.get(a.dataId).values,b=v.computeStrides(a.shape),x=v.computeStrides(y.shape);for(let N=0;N=c)continue;let U=m>1?(D-E)*(h-1)/(m-1):0,j=A>1?(L-$)*(d-1)/(A-1):0;for(let X=0;X1?E*(h-1)+X*U:.5*(E+D)*(h-1);if(G<0||G>h-1){for(let ee=0;ee1?$*(d-1)+te*j:.5*($+L)*(d-1);if(le<0||le>d-1){for(let me=0;me1?$*(d-1)+ee*j:.5*($+L)*(d-1);if(J<0||J>d-1){for(let le=0;ley+f-g-1:(y,g)=>y+g;for(let y=0;y`Only NHWC dataFormat supported on CPU for depthToSpace. 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te=v.locToIndex([U,j,G,J],L,v.computeStrides($));P[te]=se}}}return{dataId:l.write(v.toTypedArray(P,r.dtype),$,r.dtype),shape:$,dtype:r.dtype}}},qF={kernelName:xh,backendName:"cpu",kernelFunc:({inputs:e,backend:t,attrs:n})=>{let{x:r,filter:a,dy:s}=e,{strides:i,pad:o,dilations:l}=n,u=t,c=v.toNestedArray(r.shape,u.data.get(r.dataId).values),h=v.toNestedArray(a.shape,u.data.get(a.dataId).values),{batchSize:d,inHeight:p,inWidth:f,inChannels:m,outHeight:A,outWidth:y,padInfo:g,strideHeight:w,strideWidth:_,filterHeight:b,filterWidth:x,dilationHeight:N,dilationWidth:T,outShape:E}=C.computeDilation2DInfo(r.shape,a.shape,i,o,"NHWC",l);v.assert(s.rank===E.length,()=>`Error in ${xh}, dy must have the same rank as output ${E.length}, but got ${s.rank}`);let $=v.toNestedArray(E,u.data.get(s.dataId).values),D=v.makeZerosNestedTypedArray(a.shape,a.dtype);for(let 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w$(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:u,dataFormat:c,dilations:h,dimRoundingMode:d,activation:p,leakyreluAlpha:f}=r,m=Bx({inputs:{x:a,filter:s},backend:n,attrs:{strides:l,pad:u,dataFormat:c,dilations:h,dimRoundingMode:d}});if(i){let A=m;m=ju({inputs:{a:m,b:i},backend:n}),n.disposeIntermediateTensorInfo(A)}if(p){let A=m;m=lA(n,m,p,o,f),n.disposeIntermediateTensorInfo(A)}return m}var _$={kernelName:Ws,backendName:"cpu",kernelFunc:w$};function b$(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:u,dataFormat:c,dilations:h,dimRoundingMode:d,activation:p,leakyreluAlpha:f}=r,m=Vx({inputs:{x:a,filter:s},backend:n,attrs:{strides:l,pad:u,dataFormat:c,dilations:h,dimRoundingMode:d}});if(i){let A=m;m=ju({inputs:{a:m,b:i},backend:n}),n.disposeIntermediateTensorInfo(A)}if(p){let A=m;m=lA(n,m,p,o,f),n.disposeIntermediateTensorInfo(A)}return m}var v$={kernelName:Bs,backendName:"cpu",kernelFunc:b$};function k$(e){let{inputs:t,backend:n}=e,{params:r,indices:a}=t,s=v.sizeFromShape(r.shape),i=a.shape,o=i[i.length-1],[l,u,c,h]=C.prepareAndValidate(r,a);if(u===0)return n.makeTensorInfo(l,r.dtype,[]);let d=We([u,c],r.dtype),p=n.data.get(a.dataId).values,f=n.data.get(r.dataId).values;for(let m=0;m=s/c)throw new Error(`Invalid indices: ${A} does not index into ${r.shape}`);for(let g=0;ge>=t?1:0),E$=Ht(us,T$,null,"bool"),C$={kernelName:us,backendName:"cpu",kernelFunc:E$};function R$(e){let{inputs:t,backend:n}=e,{input:r}=t,a=v.sizeFromShape(r.shape),s=r.shape[r.shape.length-1],i=a/s,o=At({inputs:{x:r},backend:n,attrs:{shape:[i,s]}}),l=jx(o,!0,n),u=At({inputs:{x:l},backend:n,attrs:{shape:r.shape}});return n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(l),u}var F$={kernelName:bh,backendName:"cpu",kernelFunc:R$},$$=at(ro,e=>Number.isFinite(e)?1:0,"bool"),M$={kernelName:ro,backendName:"cpu",kernelFunc:$$},D$=at(ao,e=>Math.abs(e)===Infinity?1:0,"bool"),O$={kernelName:ao,backendName:"cpu",kernelFunc:D$},z$=at(so,e=>Number.isNaN(e)?1:0,"bool"),L$={kernelName:so,backendName:"cpu",kernelFunc:z$},P$=Rt((e,t)=>e<=t?1:0),W$=Ht(oo,P$,null,"bool"),B$={kernelName:oo,backendName:"cpu",kernelFunc:W$};function V$(e){let{backend:t,attrs:n}=e,{start:r,stop:a,num:s}=n,i=yx(r,a,s);return t.makeTensorInfo([i.length],"float32",i)}var U$={kernelName:kh,backendName:"cpu",kernelFunc:V$},j$=at(lo,e=>Math.log1p(e)),H$={kernelName:lo,backendName:"cpu",kernelFunc:j$},G$=Rt((e,t)=>e&&t),q$=Ht(uo,G$,null,"bool"),X$={kernelName:uo,backendName:"cpu",kernelFunc:q$},K$=at(Jl,e=>e?0:1,"bool"),Z$={kernelName:Jl,backendName:"cpu",kernelFunc:K$},Y$=Rt((e,t)=>e||t),J$=Ht(Ql,Y$,null,"bool"),Q$={kernelName:Ql,backendName:"cpu",kernelFunc:J$};function eM(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{depthRadius:s,bias:i,alpha:o,beta:l}=r;be(a,"LRN");let u=a.shape[3],c=u-1,h=n.data.get(a.dataId).values,d=v.sizeFromShape(a.shape),p=new Float32Array(d);function f(m){let A=m%u,y=m-A+Math.max(0,A-s),g=m-A+Math.min(A+s,c),w=0;for(;y<=g;y++){let _=h[y];w+=_*_}return w}for(let m=0;m`Error in maxPool: Either strides or dilations must be 1. 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c=C.computePool3DInfo(s.shape,i,o,1,l,u),h=n.bufferSync(s),d=KR(h,c),p=c.strideDepth,f=c.strideHeight,m=c.strideWidth,A=c.dilationDepth,y=c.dilationHeight,g=c.dilationWidth,w=c.effectiveFilterDepth,_=c.effectiveFilterHeight,b=c.effectiveFilterWidth,x=w-1-c.padInfo.front,N=b-1-c.padInfo.left,T=_-1-c.padInfo.top,E=We(s.shape,"float32"),$=n.bufferSync(a);for(let D=0;D=c.outDepth||Math.floor(te)!==te))for(let le=0;le<_;le+=y){let Q=(G+le)/f;if(!(Q<0||Q>=c.outHeight||Math.floor(Q)!==Q))for(let de=0;de=c.outWidth||Math.floor(ue)!==ue)continue;let me=w*_*b-1-d.get(D,te,Q,ue,L),fe=se*_*b+le*b+de,Ie=me===fe?1:0;Ie!==0&&(J+=$.get(D,te,Q,ue,L)*Ie)}}}E.set(J,D,P,U,j,L)}return n.makeTensorInfo(E.shape,E.dtype,E.values)}var cM={kernelName:Sh,backendName:"cpu",kernelFunc:uM};function hM(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,input:s,output:i}=t,o=s;be([s,i],"maxPoolGrad");let{filterSize:l,strides:u,pad:c,dimRoundingMode:h}=r,d=C.computePool2DInfo(o.shape,l,u,1,c,h),p=n.data.get(o.dataId).values,f=We(d.outShape,o.dtype,Px(p,o.shape,o.dtype,d).values),m=d.strideHeight,A=d.strideWidth,y=d.dilationHeight,g=d.dilationWidth,w=d.effectiveFilterHeight,_=d.effectiveFilterWidth,b=_-1-d.padInfo.left,x=w-1-d.padInfo.top,N=We(o.shape,"float32"),T=n.data.get(a.dataId).values,E=We(a.shape,"float32",T);for(let $=0;$=d.outHeight||Math.floor(ee)!==ee))for(let J=0;J<_;J+=g){let se=(j+J)/A;if(se<0||se>=d.outWidth||Math.floor(se)!==se)continue;let te=w*_-1-f.get($,ee,se,D),le=G*_+J,Q=te===le?1:0;Q!==0&&(X+=E.get($,ee,se,D)*Q)}}N.set(X,$,L,P,D)}return n.makeTensorInfo(N.shape,N.dtype,N.values)}var dM={kernelName:Nh,backendName:"cpu",kernelFunc:hM};function pM(e,t,n,r,a){let s=v.computeStrides(t),i=uA(e,t,n,s,a,"max"),o=Px(e,t,n,a,!0,r);return[i.values,o.values]}var fM={kernelName:Th,backendName:"cpu",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{x:r}=e,{filterSize:a,strides:s,pad:i,includeBatchInIndex:o}=t,l=n;be(r,"MaxPoolWithArgmax");let u=l.data.get(r.dataId).values,c=C.computePool2DInfo(r.shape,a,s,[1,1],i),[h,d]=pM(u,r.shape,r.dtype,o,c),p=l.write(h,c.outShape,r.dtype),f=l.write(d,c.outShape,r.dtype);return[{dataId:p,shape:c.outShape,dtype:r.dtype},{dataId:f,shape:c.outShape,dtype:"int32"}]}};function Bd(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r;be(a,"sum");let o;a.dtype==="bool"?o=Fa({inputs:{x:a},backend:n,attrs:{dtype:"int32"}}):o=zr({inputs:{x:a},backend:n});let l=o.shape.length,u=v.parseAxisParam(s,o.shape),c=C.getAxesPermutation(u,l),h=u,d=o;c!=null&&(d=sr({inputs:{x:o},backend:n,attrs:{perm:c}}),h=C.getInnerMostAxes(h.length,l)),C.assertAxesAreInnerMostDims("sum",h,d.shape.length);let[p,f]=C.computeOutAndReduceShapes(d.shape,h),m=C.upcastType(d.dtype,"int32"),A=Pd(n,p,m),y=v.sizeFromShape(f),g=n.data.get(A.dataId).values,w=n.data.get(d.dataId).values;for(let _=0;_n.disposeIntermediateTensorInfo(m)),f}var yM={kernelName:As,backendName:"cpu",kernelFunc:AM};function gM(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r;be(a,"min");let o=v.parseAxisParam(s,a.shape),l=o,u=C.getAxesPermutation(l,a.shape.length),c=a;u!=null&&(c=sr({inputs:{x:a},backend:n,attrs:{perm:u}}),l=C.getInnerMostAxes(l.length,a.shape.length)),C.assertAxesAreInnerMostDims("min",l,c.shape.length);let[h,d]=C.computeOutAndReduceShapes(c.shape,l),p=v.sizeFromShape(d),f=v.makeZerosTypedArray(v.sizeFromShape(h),c.dtype),m=n.data.get(c.dataId).values;for(let 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this.uploadToGPU(e),this.texData.get(e).texture}getDataInfo(e){return this.texData.get(e)}getCPUBackend(){return Y().getBool("WEBGL_CPU_FORWARD")?(this.cpuBackend==null&&(this.cpuBackend=Nr().findBackend("cpu")),this.cpuBackend):null}shouldExecuteOnCPU(e,t=iL){let n=this.getCPUBackend();return!Y().getBool("IS_TEST")&&!this.warnedAboutCPUBackend&&n==null&&(console.warn("Your application contains ops that are small enough to be executed on the CPU backend, however the CPU backend cannot be found. 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NAN : result.a; `;function Xe({opSnippet:e,packedOpSnippet:t,cpuKernelImpl:n,dtype:r}){return({inputs:a,backend:s})=>{let{x:i}=a,o=s,l=r||i.dtype;if(o.shouldExecuteOnCPU([i])&&n!=null){let h=o.texData.get(i.dataId),d=n(h.values,l);return o.makeTensorInfo(i.shape,l,d)}let u=Y().getBool("WEBGL_PACK_UNARY_OPERATIONS")&&t!=null,c;return u?c=new yl(i.shape,t):c=new $a(i.shape,e),o.runWebGLProgram(c,[i],l)}}function Qt({opSnippet:e,packedOpSnippet:t,checkOutOfBounds:n=!1,supportsComplex:r=!1,cpuKernelImpl:a,dtype:s}){return({inputs:i,backend:o})=>{let{a:l,b:u}=i,c=o;if(r&&l.dtype==="complex64"){let f=c.texData.get(l.dataId),m=c.texData.get(u.dataId),[A,y]=[[f.complexTensorInfos.real,m.complexTensorInfos.real],[f.complexTensorInfos.imag,m.complexTensorInfos.imag]].map(w=>{let[_,b]=w,x={dataId:_.dataId,dtype:_.dtype,shape:l.shape},N={dataId:b.dataId,dtype:b.dtype,shape:u.shape},T=new gl(e,l.shape,u.shape);return c.runWebGLProgram(T,[x,N],Jn(_.dtype,b.dtype))}),g=Ma({inputs:{real:A,imag:y},backend:c});return c.disposeIntermediateTensorInfo(A),c.disposeIntermediateTensorInfo(y),g}let h=s||Jn(l.dtype,u.dtype);if(c.shouldExecuteOnCPU([l,u])&&a!=null){let f=c.texData.get(l.dataId),m=c.texData.get(u.dataId),[A,y]=a(l.shape,u.shape,f.values,m.values,h),g=c.makeTensorInfo(y,h),w=c.texData.get(g.dataId);return w.values=A,g}let d=Y().getBool("WEBGL_PACK_BINARY_OPERATIONS")&&t!=null,p;return d?p=new Ju(t,l.shape,u.shape,n):p=new gl(e,l.shape,u.shape),c.runWebGLProgram(p,[l,u],h)}}function Yd(e,t=!1){if(e==="linear")return t?Yz:qz;if(e==="relu")return t?Qz:Kz;if(e==="elu")return t?Jz:Xz;if(e==="relu6")return t?eL:Zz;if(e==="prelu")return t?t_:e_;if(e==="leakyrelu")return t?Qw:Jw;throw new Error(`Activation ${e} has not been implemented for the WebGL backend.`)}var r_=class{constructor(e,t,n,r=!1,a=!1,s=!1,i=null,o=!1,l=!1){this.variableNames=["matrixA","matrixB"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=n;let u=r?e[1]:e[2],c=Math.ceil(u/2),h=r?"i * 2, rc.y":"rc.y, i * 2",d=a?"rc.z, i * 2":"i * 2, rc.z",p=r?["a.xxyy","a.zzww"]:["a.xxzz","a.yyww"],f=a?["b.xzxz","b.ywyw"]:["b.xyxy","b.zwzw"],m="",A="";i&&(o?m=`vec4 activation(vec4 a) { vec4 b = getPreluActivationWeightsAtOutCoords(); ${i} }`:l?m=`vec4 activation(vec4 a) { vec4 b = getLeakyreluAlphaAtOutCoords(); ${i} }`:m=`vec4 activation(vec4 x) { ${i} }`,A="result = activation(result);");let y=s?"result += getBiasAtOutCoords();":"";s&&this.variableNames.push("bias"),o&&this.variableNames.push("preluActivationWeights"),l&&this.variableNames.push("leakyreluAlpha");let g="rc.x",w="rc.x";e[0]`The new shape (${l}) has ${u} elements and the old shape (${a.shape}) has ${o} elements. 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} return acos(x); `,ML=Xe({opSnippet:$L}),DL={kernelName:zi,backendName:"webgl",kernelFunc:ML},OL=mr+` if (x < 1.0) return NAN; return log(x + sqrt(x * x - 1.0));`,zL=Xe({opSnippet:OL}),LL={kernelName:Li,backendName:"webgl",kernelFunc:zL},h_="return a + b;",PL=Qt({opSnippet:h_,packedOpSnippet:h_,supportsComplex:!0,cpuKernelImpl:cz}),WL={kernelName:Aa,backendName:"webgl",kernelFunc:PL},BL=class{constructor(e,t){this.outputShape=[],this.outputShape=e,this.variableNames=t.map((a,s)=>`T${s}`);let n=[];this.variableNames.forEach(a=>{n.push(`float v${a} = get${a}AtOutCoords();`)});let r=this.variableNames.map(a=>`v${a}`).join(" + ");this.userCode=` void main() { ${n.join(` `)} float result = ${r}; setOutput(result); } `}},VL=class{constructor(e,t){this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.variableNames=t.map((a,s)=>`T${s}`);let n=[];this.variableNames.forEach(a=>{n.push(`vec4 v${a} = get${a}AtOutCoords();`)});let r=this.variableNames.map(a=>`v${a}`).join(" + ");this.userCode=` void main() { ${n.join(` `)} vec4 result = ${r}; 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int batch = coords[0]; int outIdx = coords[1]; int inOffset = outIdx * ${r}; int bestIndex = inOffset; float bestValue = getA(batch, bestIndex); for (int i = 0; i < ${r}; i++) { int inIdx = ${o}; float candidate = getA(batch, inIdx); if (candidate ${i} bestValue) { bestValue = candidate; bestIndex = inIdx; } } setOutput(float(bestIndex)); } `}},KL=class{constructor(e,t,n,r){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,v.assert(e.length>2,()=>`Packed arg${n.charAt(0).toUpperCase()+n.slice(1)} supports only inputs with rank above 2.`);let a=e[e.length-1],s=Math.ceil(a/t);this.outputShape=e.slice(0,-1),s>1&&this.outputShape.push(s),r||this.variableNames.push("bestIndicesA");let i=this.outputShape,o=i.length,l=lt(o),u=cn("coords",o),c,h;if(s===1){h=o+1;let N=lt(h);c=` ${N} sourceLocR = ${N}(${u.join()}, 0); ++${u[o-1]}; ${N} sourceLocG = ${N}(${u.join()}, 0); ++${u[o-2]}; ${N} sourceLocA = ${N}(${u.join()}, 0); --${u[o-1]}; ${N} sourceLocB = ${N}(${u.join()}, 0); --${u[o-2]};`}else h=o,c=` ${l} sourceLocR = coords; ++${u[o-1]}; ${l} sourceLocG = coords; ++${u[o-2]}; ${l} sourceLocA = coords; --${u[o-1]}; ${l} sourceLocB = coords; --${u[o-2]};`;let d=["x","y","z","w","u","v"].slice(0,h),p="."+d[h-1],f=d.map(N=>"int "+N),m=cn("sourceLocR",h-1).concat("inIdx.r"),A=cn("sourceLocG",h-1).concat("inIdx.g"),y=cn("sourceLocB",h-1).concat("inIdx.b"),g=cn("sourceLocA",h-1).concat("inIdx.a"),w=n==="max"?"greaterThan":"lessThan",_=r?"":` inIdx = round(vec4(getBestIndicesAChannel(${m.join()}), getBestIndicesAChannel(${A.join()}), getBestIndicesAChannel(${y.join()}), getBestIndicesAChannel(${g.join()})));`,b=`vec4( getAChannel(${m.join()}), hasNextCol ? getAChannel(${A.join()}) : 0., hasNextRow ? getAChannel(${y.join()}) : 0., hasNextRow && hasNextCol ? getAChannel(${g.join()}) : 0.)`,x=r?"":` float getBestIndicesAChannel(${f.join()}) { return getChannel(getBestIndicesA(${d.join()}), vec2(${d.slice(-2).join()})); }`;this.userCode=` float getAChannel(${f.join()}) { return getChannel(getA(${d.join()}), vec2(${d.slice(-2).join()})); } ${x} void main() { ${l} coords = getOutputCoords(); bool hasNextCol = ${u[o-1]} < ${i[o-1]-1}; bool hasNextRow = ${u[o-2]} < ${i[o-2]-1}; ${c} ivec4 srcIdx = ivec4(sourceLocR${p}, sourceLocG${p}, sourceLocB${p}, sourceLocA${p}) * ${t}; ivec4 inIdx = srcIdx; vec4 bestIndex = vec4(inIdx); vec4 bestValue = ${b}; for (int i = 0; i < ${t}; i++) { inIdx = srcIdx; ${_} vec4 candidate = ${b}; bvec4 nan = isnan(candidate); bvec4 replace = bvec4( vec4(${w}(candidate, bestValue)) * (vec4(1.0) - vec4(nan))); bestValue = vec4(replace.x ? candidate.x : bestValue.x, replace.y ? candidate.y : bestValue.y, replace.z ? candidate.z : bestValue.z, replace.w ? candidate.w : bestValue.w); bestIndex = mix(bestIndex, vec4(inIdx), vec4(replace)); srcIdx++; } setOutput(bestIndex); } `}};function d_(e,t,n,r=null){let a=t.shape[0],s=t.shape[1];r!=null&&(a=r.shape[0],s=r.shape[1]);let i=C.computeOptimalWindowSize(s),o={windowSize:i,inSize:s,batchSize:a,outSize:Math.ceil(s/i)},l=new XL(o,n,r==null),u=[t];r!=null&&u.push(r);let c=e.runWebGLProgram(l,u,"int32");if(c.shape[1]===1)return c;let h=d_(e,t,n,c);return e.disposeIntermediateTensorInfo(c),h}function p_(e,t,n,r=null){let a=r!=null?r.shape:t.shape,s=a[a.length-1],i=C.computeOptimalWindowSize(s),o=new KL(a,i,n,r==null),l=r==null?[t]:[t,r],u=e.runWebGLProgram(o,l,"int32");if(u.shape.length===t.shape.length){let c=p_(e,t,n,u);return e.disposeIntermediateTensorInfo(u),c}return u}function f_(e,t,n,r){let a=[n];if(C.assertAxesAreInnerMostDims("arg"+r.charAt(0).toUpperCase()+r.slice(1),a,t.shape.length),!Y().getBool("WEBGL_PACK_REDUCE")||t.shape.length<=2){let s=[],[i,o]=C.computeOutAndReduceShapes(t.shape,a),l=v.sizeFromShape(o),u=ye({inputs:{x:t},backend:e,attrs:{shape:[-1,l]}});s.push(u);let c=d_(e,u,r);s.push(c);let h=ye({inputs:{x:c},backend:e,attrs:{shape:i}});return s.forEach(d=>e.disposeIntermediateTensorInfo(d)),h}return p_(e,t,r)}function ZL(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s}=r,i=v.parseAxisParam(s,a.shape),o=C.getAxesPermutation(i,a.shape.length),l=a,u=[];o!=null&&(l=wn({inputs:{x:a},backend:n,attrs:{perm:o}}),u.push(l),i=C.getInnerMostAxes(i.length,l.shape.length)),C.assertAxesAreInnerMostDims("argMax",[i[0]],l.shape.length);let c=f_(n,l,i[0],"max");return u.forEach(h=>n.disposeIntermediateTensorInfo(h)),c}var YL={kernelName:Xa,backendName:"webgl",kernelFunc:ZL};function JL(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s}=r,i=v.parseAxisParam(s,a.shape),o=C.getAxesPermutation(i,a.shape.length),l=a,u=[];o!=null&&(l=wn({inputs:{x:a},backend:n,attrs:{perm:o}}),u.push(l),i=C.getInnerMostAxes(i.length,l.shape.length)),C.assertAxesAreInnerMostDims("argMin",[i[0]],l.shape.length);let c=f_(n,l,i[0],"min");return u.forEach(h=>n.disposeIntermediateTensorInfo(h)),c}var QL={kernelName:Hl,backendName:"webgl",kernelFunc:JL},eP=mr+` if (abs(x) > 1.) { return NAN; } return asin(x); `,tP=Xe({opSnippet:eP}),nP={kernelName:Pi,backendName:"webgl",kernelFunc:tP},rP=mr+"return log(x + sqrt(x * x + 1.0));",aP=Xe({opSnippet:rP}),sP={kernelName:Wi,backendName:"webgl",kernelFunc:aP},iP=mr+` return atan(x); `,oP=Xe({opSnippet:iP}),lP={kernelName:Bi,backendName:"webgl",kernelFunc:oP},uP=AL+` return atan(a, b); `,cP=` vec4 result = atan(a, b); vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0)); `+yL+` return result; `,hP=Qt({opSnippet:uP,packedOpSnippet:cP}),dP={kernelName:Ui,backendName:"webgl",kernelFunc:hP},pP=mr+` if ((x < -1.0) || (x > 1.0)) return NAN; return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,fP=Xe({opSnippet:pP}),mP={kernelName:Vi,backendName:"webgl",kernelFunc:fP},Qu=class{constructor(e,t,n,r=!1,a=!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,c=e.effectiveFilterHeight,h=e.effectiveFilterWidth,d=e.padInfo.top,p=e.padInfo.left;this.outputShape=e.outShape;let f=t==="avg",m=`((batch * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + d`,A=`(xR * ${e.inWidth} + xC) * ${e.inChannels} + d`,y="0.0";if(f||(y="-1.0 / 1e-20"),n){let N=">=";this.userCode=` const ivec2 strides = ivec2(${i}, ${o}); const ivec2 pads = ivec2(${d}, ${p}); 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 < ${c}; wR += ${l}) { int xR = xRCorner + wR; if (xR < 0 || xR >= ${e.inHeight}) { continue; } for (int wC = 0; wC < ${h}; wC += ${u}) { int xC = xCCorner + wC; if (xC < 0 || xC >= ${e.inWidth}) { continue; } float value = getX(batch, xR, xC, d); // If a min / max value has already been found, use it. If not, // use the current value. float currMinMaxValue = mix( value, minMaxValue, minMaxValueFound); if (value ${N} currMinMaxValue) { minMaxValue = value; minMaxValueFound = 1.0; minMaxPosition = ${r?a?m:A:`wR * ${h} + wC`}; } } } setOutput(float(minMaxPosition)); } `;return}let g="max",w=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="avg"&&(w="avgValue / count");let _=Math.floor(s/4)*4,b=s%4,x=` if (${f}) { avgValue += dot(values, ones); } else { minMaxValue = ${g}(values, minMaxValue); } `;this.userCode=` const ivec2 strides = ivec2(${i}, ${o}); const ivec2 pads = ivec2(${d}, ${p}); const float initializationValue = ${y}; const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0); float count = 0.0; float getValue(int batch, int xR, int xC, int d) { if (xC < 0 || xC >= ${e.inWidth}) { return initializationValue; } count += 1.0; return getX(batch, xR, xC, d); } void main() { ivec4 coords = getOutputCoords(); int batch = coords[0]; int d = coords[3]; ivec2 xRCCorner = coords.yz * strides - pads; int xRCorner = xRCCorner.x; int xCCorner = xRCCorner.y; // max/min x(?, ?, d) to get y(yR, yC, d). // ? = to be determined vec4 minMaxValue = vec4(${y}); float avgValue = 0.0; count = 0.0; for (int wR = 0; wR < ${c}; wR += ${l}) { int xR = xRCorner + wR; if (xR < 0 || xR >= ${e.inHeight}) { continue; } for (int wC = 0; wC < ${_}; 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) ); ${x} } int xC = xCCorner + ${_}; if (${b===1}) { vec4 values = vec4( getValue(batch, xR, xC, d), initializationValue, initializationValue, initializationValue ); ${x} } else if (${b===2}) { vec4 values = vec4( getValue(batch, xR, xC, d), getValue(batch, xR, xC + ${u}, d), initializationValue, initializationValue ); ${x} } else if (${b===3}) { vec4 values = vec4( getValue(batch, xR, xC, d), getValue(batch, xR, xC + ${u}, d), getValue(batch, xR, xC + 2 * ${u}, d), initializationValue ); ${x} } } setOutput(${w}); } `}},EA=class{constructor(e,t,n,r=!1,a=!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,c=e.dilationHeight,h=e.dilationWidth,d=e.effectiveFilterDepth,p=e.effectiveFilterHeight,f=e.effectiveFilterWidth,m=e.padInfo.front,A=e.padInfo.top,y=e.padInfo.left;this.outputShape=e.outShape;let g=t==="avg",w="0.0";if(g||(w="-1.0 / 1e-20"),n){let E=">=";this.userCode=` const ivec3 strides = ivec3(${i}, ${o}, ${l}); const ivec3 pads = ivec3(${m}, ${A}, ${y}); void main() { ivec5 coords = getOutputCoords(); int batch = coords.x; int ch = coords.u; ivec3 xCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads; int xDCorner = xCorner.x; int xRCorner = xCorner.y; int xCCorner = xCorner.z; // max/min x(?, ?, ?, ch) to get y(yD, yR, yC, ch). // ? = to be determined float minMaxValue = 0.0; float minMaxValueFound = 0.0; int minMaxPosition = 0; for (int wD = 0; wD < ${d}; wD += ${u}) { int xD = xDCorner + wD; if (xD < 0 || xD >= ${e.inDepth}) { continue; } for (int wR = 0; wR < ${p}; wR += ${c}) { int xR = xRCorner + wR; if (xR < 0 || xR >= ${e.inHeight}) { continue; } for (int wC = 0; wC < ${f}; wC += ${h}) { int xC = xCCorner + wC; if (xC < 0 || xC >= ${e.inWidth}) { continue; } float value = getX(batch, xD, xR, xC, ch); // If a min / max value has already been found, use it. If not, // use the current value. float currMinMaxValue = mix( value, minMaxValue, minMaxValueFound); if (value ${E} currMinMaxValue) { minMaxValue = value; minMaxValueFound = 1.0; minMaxPosition = ${r?a?`(((batch * ${e.inDepth} + xD) * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + ch`:`((xD * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + ch`:`wD * ${p} * ${f} + wR * ${f} + wC`}; } } } } setOutput(float(minMaxPosition)); } `;return}let _="max",b=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="avg"&&(b="avgValue / count");let x=Math.floor(s/4)*4,N=s%4,T=` if (${g}) { avgValue += dot(values, ones); } else { minMaxValue = ${_}(values, minMaxValue); } `;this.userCode=` const ivec3 strides = ivec3(${i}, ${o}, ${l}); const ivec3 pads = ivec3(${m}, ${A}, ${y}); const float initializationValue = ${w}; const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0); float count = 0.0; float getValue(int batch, int xD, int xR, int xC, int ch) { if (xC < 0 || xC >= ${e.inWidth}) { return initializationValue; } count += 1.0; return getX(batch, xD, xR, xC, ch); } void main() { ivec5 coords = getOutputCoords(); int batch = coords.x; int ch = coords.u; ivec3 xCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads; int xDCorner = xCorner.x; int xRCorner = xCorner.y; int xCCorner = xCorner.z; // max/min x(?, ?, ?, d) to get y(yD, yR, yC, ch). // ? = to be determined vec4 minMaxValue = vec4(${w}); float avgValue = 0.0; count = 0.0; for (int wD = 0; wD < ${d}; wD += ${u}) { int xD = xDCorner + wD; if (xD < 0 || xD >= ${e.inDepth}) { continue; } for (int wR = 0; wR < ${p}; wR += ${c}) { int xR = xRCorner + wR; if (xR < 0 || xR >= ${e.inHeight}) { continue; } for (int wC = 0; wC < ${x}; wC += 4) { int xC = xCCorner + wC * ${h}; vec4 values = vec4( getValue(batch, xD, xR, xC, ch), getValue(batch, xD, xR, xC + ${h}, ch), getValue(batch, xD, xR, xC + 2 * ${h}, ch), getValue(batch, xD, xR, xC + 3 * ${h}, ch) ); ${T} } int xC = xCCorner + ${x}; if (${N===1}) { vec4 values = vec4( getValue(batch, xD, xR, xC, ch), initializationValue, initializationValue, initializationValue ); ${T} } else if (${N===2}) { vec4 values = vec4( getValue(batch, xD, xR, xC, ch), getValue(batch, xD, xR, xC + ${h}, ch), initializationValue, initializationValue ); ${T} } else if (${N===3}) { vec4 values = vec4( getValue(batch, xD, xR, xC, ch), getValue(batch, xD, xR, xC + ${h}, ch), getValue(batch, xD, xR, xC + 2 * ${h}, ch), initializationValue ); ${T} } } setOutput(${b}); } } `}};function AP(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t;hl(a,"avgPool");let{filterSize:s,strides:i,pad:o,dimRoundingMode:l}=r,u=1;v.assert(C.eitherStridesOrDilationsAreOne(i,u),()=>`Error in avgPool: Either strides or dilations must be 1. Got strides ${i} and dilations '${u}'`);let c=C.computePool2DInfo(a.shape,s,i,u,o,l);if(c.filterWidth===1&&c.filterHeight===1&&v.arraysEqual(c.inShape,c.outShape))return Fn({inputs:{x:a},backend:n});let h=new Qu(c,"avg",!1);return n.runWebGLProgram(h,[a],"float32")}var yP={kernelName:Ka,backendName:"webgl",kernelFunc:AP};function gP(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{filterSize:s,strides:i,pad:o,dimRoundingMode:l,dataFormat:u}=r,c=[1,1,1],h=C.computePool3DInfo(a.shape,s,i,c,o,l,u),d=new EA(h,"avg",!1);return n.runWebGLProgram(d,[a],"float32")}var xP={kernelName:Gl,backendName:"webgl",kernelFunc:gP},wP=class{constructor(e){this.variableNames=["dy"],this.outputShape=e.inShape;let t=e.filterHeight,n=e.filterWidth,r=e.strideHeight,a=e.strideWidth,s=e.dilationHeight,i=e.dilationWidth,o=e.effectiveFilterHeight,l=e.effectiveFilterWidth,u=o-1-e.padInfo.top,c=l-1-e.padInfo.left,h=1/(t*n);this.userCode=` const ivec2 pads = ivec2(${u}, ${c}); const float avgMultiplier = float(${h}); void main() { ivec4 coords = getOutputCoords(); int b = coords[0]; int d = coords[3]; ivec2 dyRCCorner = coords.yz - pads; int dyRCorner = dyRCCorner.x; int dyCCorner = dyRCCorner.y; // Convolve dy(?, ?, d) with pos mask(:, :, d) to get dx(xR, xC, d). // ? = to be determined. : = across all values in that axis. float dotProd = 0.0; for (int wR = 0; wR < ${o}; wR += ${s}) { float dyR = float(dyRCorner + wR) / ${r}.0; if (dyR < 0.0 || dyR >= ${e.outHeight}.0 || fract(dyR) > 0.0) { continue; } int idyR = int(dyR); for (int wC = 0; wC < ${l}; wC+= ${i}) { float dyC = float(dyCCorner + wC) / ${a}.0; if (dyC < 0.0 || dyC >= ${e.outWidth}.0 || fract(dyC) > 0.0) { continue; } int idyC = int(dyC); float dyValue = getDy(b, idyR, idyC, d); dotProd += dyValue * avgMultiplier; } } setOutput(dotProd); } `}},_P=class{constructor(e){this.variableNames=["dy"],this.outputShape=e.inShape;let t=e.filterDepth,n=e.filterHeight,r=e.filterWidth,a=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=e.dilationDepth,l=e.dilationHeight,u=e.dilationWidth,c=e.effectiveFilterDepth,h=e.effectiveFilterHeight,d=e.effectiveFilterWidth,p=c-1-e.padInfo.front,f=h-1-e.padInfo.top,m=d-1-e.padInfo.left,A=1/(t*n*r);this.userCode=` const ivec3 pads = ivec3(${p}, ${f}, ${m}); const float avgMultiplier = float(${A}); 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 < ${c}; wD += ${o}) { float dyD = float(dyDCorner + wD) / ${a}.0; if (dyD < 0.0 || dyD >= ${e.outDepth}.0 || fract(dyD) > 0.0) { continue; } int idyD = int(dyD); for (int wR = 0; wR < ${h}; wR += ${l}) { float dyR = float(dyRCorner + wR) / ${s}.0; if (dyR < 0.0 || dyR >= ${e.outHeight}.0 || fract(dyR) > 0.0) { continue; } int idyR = int(dyR); for (int wC = 0; wC < ${d}; wC += ${u}) { float dyC = float(dyCCorner + wC) / ${i}.0; if (dyC < 0.0 || dyC >= ${e.outWidth}.0 || fract(dyC) > 0.0) { continue; } int idyC = int(dyC); float dyValue = getDy(batch, idyD, idyR, idyC, ch); dotProd += dyValue * avgMultiplier; } } } setOutput(dotProd); } `}};function bP(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,input:s}=t,i=s,{filterSize:o,strides:l,pad:u,dimRoundingMode:c}=r,h=[1,1,1],d=C.computePool3DInfo(i.shape,o,l,h,u,c),p=new _P(d);return n.runWebGLProgram(p,[a],i.dtype)}var vP={kernelName:lh,backendName:"webgl",kernelFunc:bP};function kP(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,input:s}=t,i=s;hl([a,s],"avgPoolGrad");let{filterSize:o,strides:l,pad:u}=r,c=C.computePool2DInfo(i.shape,o,l,1,u),h=new wP(c);return n.runWebGLProgram(h,[a],i.dtype)}var IP={kernelName:oh,backendName:"webgl",kernelFunc:kP};function NP(e){let{inputs:t,backend:n,attrs:r}=e,{a,b:s}=t,{transposeA:i,transposeB:o}=r;return Qd({a,b:s,transposeA:i,transposeB:o,backend:n})}var SP={kernelName:Za,backendName:"webgl",kernelFunc:NP},TP=class{constructor(e,t,n,r,a,s){this.outputShape=[],this.variableNames=["x","mean","variance"],C.assertAndGetBroadcastShape(e,t),C.assertAndGetBroadcastShape(e,n);let i="0.0";r!=null&&(C.assertAndGetBroadcastShape(e,r),this.variableNames.push("offset"),i="getOffsetAtOutCoords()");let o="1.0";a!=null&&(C.assertAndGetBroadcastShape(e,a),this.variableNames.push("scale"),o="getScaleAtOutCoords()"),this.outputShape=e,this.userCode=` void main() { float x = getXAtOutCoords(); float mean = getMeanAtOutCoords(); float variance = getVarianceAtOutCoords(); float offset = ${i}; float scale = ${o}; float inv = scale * inversesqrt(variance + float(${s})); setOutput(dot(vec3(x, -mean, offset), vec3(inv, inv, 1))); } `}},EP=class{constructor(e,t,n,r,a,s){this.packedInputs=!0,this.packedOutput=!0,this.variableNames=["x","mean","variance"],C.assertAndGetBroadcastShape(e,t),C.assertAndGetBroadcastShape(e,n);let i="vec4(0.0)";r!=null&&(C.assertAndGetBroadcastShape(e,r),this.variableNames.push("offset"),i="getOffsetAtOutCoords()");let o="vec4(1.0)";a!=null&&(C.assertAndGetBroadcastShape(e,a),this.variableNames.push("scale"),o="getScaleAtOutCoords()"),this.outputShape=e,this.userCode=` void main() { vec4 offset = ${i}; vec4 scale = ${o}; vec4 x = getXAtOutCoords(); vec4 mean = getMeanAtOutCoords(); vec4 variance = getVarianceAtOutCoords(); vec4 inv = scale * inversesqrt(variance + vec4(${s})); setOutput((x - mean) * inv + offset); } `}},CP=({inputs:e,backend:t,attrs:n})=>{let{x:r,mean:a,variance:s,offset:i,scale:o}=e;v.assert(a.shape.length===s.shape.length,()=>"Batch normalization gradient requires mean and variance to have equal ranks."),v.assert(i==null||a.shape.length===i.shape.length,()=>"Batch normalization gradient requires mean and offset to have equal ranks."),v.assert(o==null||a.shape.length===o.shape.length,()=>"Batch normalization gradient requires mean and scale to have equal ranks.");let{varianceEpsilon:l}=n;l==null&&(l=.001);let u=[r,a,s],c=null;i!=null&&(c=i.shape,u.push(i));let h=null;o!=null&&(h=o.shape,u.push(o));let d=Y().getBool("WEBGL_PACK_NORMALIZATION")?new EP(r.shape,a.shape,s.shape,c,h,l):new TP(r.shape,a.shape,s.shape,c,h,l);return t.runWebGLProgram(d,u,u[0].dtype)},RP={kernelName:ls,backendName:"webgl",kernelFunc:CP},$P=class{constructor(e){this.variableNames=["source"],this.outputShape=e,this.rank=e.length;let t=lt(this.rank),n=`uniform int start[${this.rank}];`,r=FP(this.rank),a,s=e.map((i,o)=>`sourceLoc.${CA[o]} = start[${o}] + coords.${CA[o]};`);a=` ${t} sourceLoc; 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result.y = ${s}; --${r[this.rank-1]}; } `,o=this.rank===1?"":` --${n[this.rank-1]}; if (++${n[this.rank-2]} < ${e[this.rank-2]}) { ++${r[this.rank-2]}; result.z = ${s}; if (++${n[this.rank-1]} < ${e[this.rank-1]}) { ++${r[this.rank-1]}; result.w = ${s}; } } `,l=this.rank<=4?`sourceLoc = coords + ${t}(${e.map((u,c)=>`start[${c}]`).join()});`:e.map((u,c)=>`${r[c]} = ${n[c]} + start[${c}];`).join(` `);this.userCode=` uniform int start[${this.rank}]; void main() { ${t} coords = getOutputCoords(); ${t} sourceLoc; ${l} vec4 result = vec4(0.); ${i} ${o} setOutput(result); } `}getCustomSetupFunc(e){if(e.length!==this.rank)throw Error(`The rank (${this.rank}) of the program must match the length of start (${e.length})`);return(t,n)=>{this.startLoc==null&&(this.startLoc=t.getUniformLocationNoThrow(n,"start"),this.startLoc==null)||t.gl.uniform1iv(this.startLoc,e)}}};function DP(e,t,n,r){let a=r.texData.get(e.dataId),s=r.makeTensorInfo(n,e.dtype),i=r.texData.get(s.dataId);Object.assign(i,a),i.refCount=1,i.shape=n,i.dtype=e.dtype;let o=sn.computeFlatOffset(t,v.computeStrides(e.shape));a.slice&&(o+=a.slice.flatOffset),i.slice={flatOffset:o,origDataId:a.slice&&a.slice.origDataId||e.dataId};let l=r.dataRefCount.get(i.slice.origDataId)||1;return r.dataRefCount.set(i.slice.origDataId,l+1),s}function ec(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{begin:s,size:i}=r,[o,l]=sn.parseSliceParams(a,s,i);if(sn.assertParamsValid(a,o,l),v.sizeFromShape(l)===0)return n.makeTensorInfo(l,a.dtype,[]);if(n.shouldExecuteOnCPU([a])||a.dtype==="string"){let h=n.texData.get(a.dataId),d=Cz(h.values,o,l,a.shape,a.dtype);return n.makeTensorInfo(l,a.dtype,d)}let{isPacked:u}=n.texData.get(a.dataId),c=sn.isSliceContinous(a.shape,o,l);if(u||!c){let h=Y().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new MP(l):new $P(l),d=h.getCustomSetupFunc(o);return n.runWebGLProgram(h,[a],a.dtype,d)}return n.uploadToGPU(a.dataId),DP(a,o,l,n)}var OP={kernelName:Io,backendName:"webgl",kernelFunc:ec},zP=e=>{let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{blockShape:s,crops:i}=r;v.assert(a.shape.length<=4,()=>"batchToSpaceND for rank > 4 with a WebGL backend not implemented yet");let o=s.reduce((g,w)=>g*w),l=C.getReshaped(a.shape,s,o),u=C.getPermuted(l.length,s.length),c=C.getReshapedPermuted(a.shape,s,o),h=C.getSliceBeginCoords(i,s.length),d=C.getSliceSize(c,i,s.length),p=[],f=ye({inputs:{x:a},backend:n,attrs:{shape:l}}),m=wn({inputs:{x:f},backend:n,attrs:{perm:u}}),A=ye({inputs:{x:m},backend:n,attrs:{shape:c}}),y=ec({inputs:{x:A},backend:n,attrs:{begin:h,size:d}});return p.push(f),p.push(m),p.push(A),p.forEach(g=>n.disposeIntermediateTensorInfo(g)),y},LP={kernelName:ql,backendName:"webgl",kernelFunc:zP};function PP(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,weights:s}=t,{size:i}=r,o=n.readSync(a.dataId),l=n.readSync(s.dataId),u=Uw(o,l,s.dtype,s.shape,i);return n.makeTensorInfo([i],s.dtype,u)}var WP={kernelName:uh,backendName:"webgl",kernelFunc:PP},BP="return float(a != b);",m_=Qt({opSnippet:BP,dtype:"bool"}),VP={kernelName:po,backendName:"webgl",kernelFunc:m_};function tc(e){let{inputs:t,backend:n}=e,{input:r}=t,a=n.texData.get(r.dataId);return Fn({inputs:{x:a.complexTensorInfos.real},backend:n})}var UP={kernelName:Ch,backendName:"webgl",kernelFunc:tc},jP="return float(int(x));";function HP(e,t){let n=new $a(e.shape,jP),r=t.runWebGLProgram(n,[e],"int32");return{dataId:r.dataId,shape:r.shape,dtype:r.dtype}}function RA(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{dtype:s}=r;if(s==="complex64"){if(a.dtype==="complex64")return Fn({inputs:{x:a},backend:n});let i=Ct(a.shape),o=RA({inputs:{x:a},backend:n,attrs:{dtype:"float32"}}),l=Ma({inputs:{real:o,imag:i},backend:n});return i.dispose(),n.disposeIntermediateTensorInfo(o),l}if(a.dtype==="complex64"){let i=tc({inputs:{input:a},backend:n}),o=RA({inputs:{x:i},backend:n,attrs:{dtype:s}});return n.disposeIntermediateTensorInfo(i),o}if(!v.hasEncodingLoss(a.dtype,s)){let i=Fn({inputs:{x:a},backend:n});return{dataId:i.dataId,shape:i.shape,dtype:s}}if(s==="int32")return HP(a,n);if(s==="bool"){let i=n.makeTensorInfo([],"bool",v.getTypedArrayFromDType("bool",1)),o=m_({inputs:{a,b:i},backend:n});return n.disposeIntermediateTensorInfo(i),o}throw new Error(`Error in Cast: failed to cast ${a.dtype} to ${s}`)}var GP={kernelName:Ya,backendName:"webgl",kernelFunc:RA},A_="return ceil(x);",qP=Xe({opSnippet:A_,packedOpSnippet:A_,cpuKernelImpl:dz}),XP={kernelName:Ja,backendName:"webgl",kernelFunc:qP},KP=class{constructor(e){this.variableNames=["A"],this.outputShape=e,this.userCode=` uniform float minVal; 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${n} }`:a?w=`float activation(float a) { float b = getLeakyreluAlphaAtOutCoords(); ${n} }`:w=` float activation(float x) { ${n} } `,_="result = activation(result);");let b=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),r&&this.variableNames.push("preluActivationWeights"),a&&this.variableNames.push("leakyreluAlpha"),this.userCode=` ${w} const ivec2 strides = ivec2(${o}, ${l}); const ivec2 pads = ivec2(${s}, ${i}); void main() { ivec4 coords = getOutputCoords(); int batch = coords[0]; int d2 = coords[${g}]; ivec2 xRCCorner = ivec2(coords[${A}], coords[${y}]) * strides - pads; int xRCorner = xRCCorner.x; int xCCorner = xRCCorner.y; // Convolve x(?, ?, d1) with w(:, :, d1, d2) to get y(yR, yC, d2). // ? = to be determined. : = across all values in that axis. float dotProd = 0.0; for (int wR = 0; wR < ${h}; wR++) { int xR = xRCorner + wR * ${u}; if (xR < 0 || xR >= ${e.inHeight}) { continue; } for (int wC = 0; wC < ${d}; wC++) { int xC = xCCorner + wC * ${c}; if (xC < 0 || xC >= ${e.inWidth}) { continue; } for (int d1 = 0; d1 < ${p}; d1 += 4) { vec4 wValues = vec4( getW(wR, wC, d1, d2), getW(wR, wC, d1 + 1, d2), getW(wR, wC, d1 + 2, d2), getW(wR, wC, d1 + 3, d2) ); if (${m}) { vec4 xValues = vec4( getX(batch, xR, xC, d1), getX(batch, xR, xC, d1 + 1), getX(batch, xR, xC, d1 + 2), getX(batch, xR, xC, d1 + 3) ); dotProd += dot(xValues, wValues); } else { vec4 xValues = vec4( getX(batch, d1, xR, xC), getX(batch, d1 + 1, xR, xC), getX(batch, d1 + 2, xR, xC), getX(batch, d1 + 3, xR, xC) ); dotProd += dot(xValues, wValues); } } if (${f===1}) { if (${m}) { dotProd += getX(batch, xR, xC, ${p}) * getW(wR, wC, ${p}, d2); } else { dotProd += getX(batch, ${p}, xR, xC) * getW(wR, wC, ${p}, d2); } } else if (${f===2}) { vec2 wValues = vec2( getW(wR, wC, ${p}, d2), getW(wR, wC, ${p} + 1, d2) ); if (${m}) { vec2 xValues = vec2( getX(batch, xR, xC, ${p}), getX(batch, xR, xC, ${p} + 1) ); dotProd += dot(xValues, wValues); } else { vec2 xValues = vec2( getX(batch, ${p}, xR, xC), getX(batch, ${p} + 1, xR, xC) ); dotProd += dot(xValues, wValues); } } else if (${f===3}) { vec3 wValues = vec3( getW(wR, wC, ${p}, d2), getW(wR, wC, ${p} + 1, d2), getW(wR, wC, ${p} + 2, d2) ); if (${m}) { vec3 xValues = vec3( getX(batch, xR, xC, ${p}), getX(batch, xR, xC, ${p} + 1), getX(batch, xR, xC, ${p} + 2) ); dotProd += dot(xValues, wValues); } else { vec3 xValues = vec3( getX(batch, ${p}, xR, xC), getX(batch, ${p} + 1, xR, xC), getX(batch, ${p} + 2, xR, xC) ); dotProd += dot(xValues, wValues); } } } } float result = dotProd; ${b} ${_} setOutput(result); } `}},iW=class{constructor(e){this.variableNames=["x","W"],this.outputShape=e.outShape;let t=e.padInfo.front,n=e.padInfo.top,r=e.padInfo.left,a=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=e.dilationDepth,l=e.dilationHeight,u=e.dilationWidth,c=e.filterDepth,h=e.filterHeight,d=e.filterWidth,p=Math.floor(e.inChannels/4)*4,f=e.inChannels%4;this.userCode=` const ivec3 strides = ivec3(${a}, ${s}, ${i}); const ivec3 pads = ivec3(${t}, ${n}, ${r}); 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 < ${c}; wF++) { int xF = xFCorner + wF * ${o}; if (xF < 0 || xF >= ${e.inDepth}) { continue; } for (int wR = 0; wR < ${h}; wR++) { int xR = xRCorner + wR * ${l}; if (xR < 0 || xR >= ${e.inHeight}) { continue; } for (int wC = 0; wC < ${d}; wC++) { int xC = xCCorner + wC * ${u}; if (xC < 0 || xC >= ${e.inWidth}) { continue; } for (int d1 = 0; d1 < ${p}; d1 += 4) { vec4 xValues = vec4( getX(batch, xF, xR, xC, d1), getX(batch, xF, xR, xC, d1 + 1), getX(batch, xF, xR, xC, d1 + 2), getX(batch, xF, xR, xC, d1 + 3) ); vec4 wValues = vec4( getW(wF, wR, wC, d1, d2), getW(wF, wR, wC, d1 + 1, d2), getW(wF, wR, wC, d1 + 2, d2), getW(wF, wR, wC, d1 + 3, d2) ); dotProd += dot(xValues, wValues); } if (${f===1}) { dotProd += getX(batch, xF, xR, xC, ${p}) * getW(wF, wR, wC, ${p}, d2); } else if (${f===2}) { vec2 xValues = vec2( getX(batch, xF, xR, xC, ${p}), getX(batch, xF, xR, xC, ${p} + 1) ); vec2 wValues = vec2( getW(wF, wR, wC, ${p}, d2), getW(wF, wR, wC, ${p} + 1, d2) ); dotProd += dot(xValues, wValues); } else if (${f===3}) { vec3 xValues = vec3( getX(batch, xF, xR, xC, ${p}), getX(batch, xF, xR, xC, ${p} + 1), getX(batch, xF, xR, xC, ${p} + 2) ); vec3 wValues = vec3( getW(wF, wR, wC, ${p}, d2), getW(wF, wR, wC, ${p} + 1, d2), getW(wF, wR, wC, ${p} + 2, d2) ); dotProd += dot(xValues, wValues); } } } } setOutput(dotProd); } `}},oW=class{constructor(e,t,n){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e;let{filterWidth:r,inChannels:a,strideWidth:s,strideHeight:i,padInfo:o,outWidth:l,dilationWidth:u,dilationHeight:c,dataFormat:h}=n,{left:d,top:p}=o,f=a*r,m=un(),A=h==="channelsLast",y=A?0:1,g=A?1:2,w="";for(let _=0;_<=1;_++)for(let b=0;b<=1;b++)w+=` blockIndex = rc.y + ${b}; pos = rc.x + ${_}; if(blockIndex < ${e[1]} && pos < ${e[0]}) { offsetY = int(blockIndex / (${l})) * ${i} - ${p}; d0 = offsetY + ${c} * (pos / ${f}); if(d0 < ${t[y]} && d0 >= 0) { offsetX = int(mod(float(blockIndex), ${l}.) * ${s}. - ${d}.); d1 = offsetX + ${u} * (int(mod(float(pos), ${f}.) / ${a}.)); if(d1 < ${t[g]} && d1 >= 0) { ch = int(mod(float(pos), ${a}.)); if (${A}) { innerDims = vec2(d1, ch); result[${_*2+b}] = getChannel( getA(d0, int(innerDims.x), int(innerDims.y)), innerDims); } else { innerDims = vec2(d0, d1); result[${_*2+b}] = getChannel( getA(ch, int(innerDims.x), int(innerDims.y)), innerDims); } } } } `;this.userCode=` void main() { ivec2 rc = getOutputCoords(); vec4 result = vec4(0); int blockIndex, pos, offsetY, d0, offsetX, d1, ch; vec2 innerDims; ${w} ${m.output} = result; } `}};function __({x:e,filter:t,convInfo:n,backend:r,bias:a=null,preluActivationWeights:s=null,leakyreluAlpha:i=0,activation:o=null}){let l=e.shape,u=r.texData.get(e.dataId),c=n.inChannels,h=l[0]*l[1]*l[2],d=n.outChannels,p=n.dataFormat==="channelsLast",f=!1,m=!1,A,y=[],g=(h===1||d===1)&&c>u_,w=l[2]%2!=0&&!!u.isPacked;if(g||!Y().getBool("WEBGL_LAZILY_UNPACK")||!Y().getBool("WEBGL_PACK_BINARY_OPERATIONS")||!w){let _=p?l[0]*l[1]*l[2]:l[0]*l[2]*l[3],b=ye({inputs:{x:e},backend:r,attrs:{shape:[1,_,n.inChannels]}}),x=ye({inputs:{x:t},backend:r,attrs:{shape:[1,n.inChannels,n.outChannels]}}),N=Qd({a:b,b:x,transposeA:f,transposeB:m,backend:r,bias:a,activation:o,preluActivationWeights:s,leakyreluAlpha:i});A=ye({inputs:{x:N},backend:r,attrs:{shape:n.outShape}}),y.push(b),y.push(x),y.push(N)}else{let _=p?l[0]*l[1]*(l[2]+1):l[0]*l[2]*(l[3]+1),b={dataId:e.dataId,shape:[1,_,n.inChannels],dtype:e.dtype},x=u.shape;u.shape=u.shape.slice(),u.shape[u.shape.length-2]++,v.assert(qu(u.shape,b.shape),()=>`packed reshape ${u.shape} to ${b.shape} isn't free`);let N=ye({inputs:{x:t},backend:r,attrs:{shape:[1,n.inChannels,n.outChannels]}});y.push(N);let T=Qd({a:b,b:N,backend:r,transposeA:f,transposeB:m,bias:a,activation:o,preluActivationWeights:s,leakyreluAlpha:i}),E=r.texData.get(T.dataId);v.assert(E.isPacked,()=>"batchMatMul result is expected to be packed"),u.shape=x,E.shape=n.outShape,A=Fn({inputs:{x:T},backend:r}),A.shape=n.outShape,y.push(T)}for(let _ of y)r.disposeIntermediateTensorInfo(_);return A}function b_({x:e,filter:t,convInfo:n,backend:r,bias:a=null,preluActivationWeights:s=null,leakyreluAlpha:i=0,activation:o=null}){let{filterWidth:l,filterHeight:u,inChannels:c,outWidth:h,outHeight:d,dataFormat:p}=n,f=p==="channelsLast",m=l*u*c,A=d*h,y=[m,A],g=!0,w=!1,_=[],b=ye({inputs:{x:e},backend:r,attrs:{shape:e.shape.slice(1)}}),x=ye({inputs:{x:t},backend:r,attrs:{shape:[1,m,v.sizeFromShape(t.shape)/m]}});_.push(b),_.push(x);let N=new oW(y,b.shape,n),T=r.runWebGLProgram(N,[b],"float32"),E=ye({inputs:{x:T},backend:r,attrs:{shape:[1,y[0],y[1]]}});_.push(T),_.push(E);let $=a!=null,D=s!=null,L=o==="leakyrelu",P=o?Yd(o,!0):null,U=new r_(E.shape,x.shape,[1,A,n.outChannels],g,w,$,P,D,L),j=[E,x];if(a&&j.push(a),D&&j.push(s),L){let J=r.makeTensorInfo([],"float32",v.createScalarValue(i,"float32"));j.push(J),_.push(J)}let X=r.runWebGLProgram(U,j,"float32"),G=f?[1,d,h,n.outChannels]:[1,n.outChannels,d,h],ee=ye({inputs:{x:X},backend:r,attrs:{shape:G}});_.push(X);for(let J of _)r.disposeIntermediateTensorInfo(J);return ee}function lW(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s}=t,{strides:i,pad:o,dataFormat:l,dilations:u,dimRoundingMode:c}=r,h=C.convertConv2DDataFormat(l),d=C.computeConv2DInfo(a.shape,s.shape,i,u,o,c,!1,h),p;if(d.filterHeight===1&&d.filterWidth===1&&d.dilationHeight===1&&d.dilationWidth===1&&d.strideHeight===1&&d.strideWidth===1&&(d.padInfo.type==="SAME"||d.padInfo.type==="VALID"))p=__({x:a,filter:s,convInfo:d,backend:n});else if(Y().getBool("WEBGL_CONV_IM2COL")&&a.shape[0]===1)p=b_({x:a,filter:s,convInfo:d,backend:n});else{let m=new w_(d);p=n.runWebGLProgram(m,[a,s],"float32")}let f=ye({inputs:{x:p},backend:n,attrs:{shape:d.outShape}});return n.disposeIntermediateTensorInfo(p),f}var uW={kernelName:Qa,backendName:"webgl",kernelFunc:lW},cW=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideHeight,n=e.strideWidth,r=e.padInfo.top,a=e.padInfo.left,s=e.dataFormat==="channelsLast";this.userCode=` void main() { ivec4 coords = getOutputCoords(); int wR = coords.x; int wC = coords.y; int d1 = coords.z; int d2 = coords.w; // Convolve x(?, ?, d1) with dy(:, :, d2) to get dw(wR, wC, d1, d2). // ? = to be determined. : = across all values in that axis. float dotProd = 0.0; for (int b = 0; b < ${e.batchSize}; b++) { for (int yR = 0; yR < ${e.outHeight}; yR++) { int xR = wR + yR * ${t} - ${r}; if (xR < 0 || xR >= ${e.inHeight}) { continue; } for (int yC = 0; yC < ${e.outWidth}; yC++) { int xC = wC + yC * ${n} - ${a}; if (xC < 0 || xC >= ${e.inWidth}) { continue; } if (${s}) { float dyValue = getDy(b, yR, yC, d2); float xValue = getX(b, xR, xC, d1); dotProd += (xValue * dyValue); } else { float dyValue = getDy(b, d2, yR, yC); float xValue = getX(b, d1, xR, xC); dotProd += (xValue * dyValue); } } } } setOutput(dotProd); } `}},hW=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterHeight,n=e.filterWidth,r=e.strideHeight,a=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,c=s?3:1;this.userCode=` const ivec2 pads = ivec2(${i}, ${o}); void main() { ivec4 coords = getOutputCoords(); int batch = coords[0]; int d1 = coords[${c}]; 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) / ${r}.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) / ${a}.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); } `}},dW=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideDepth,n=e.strideHeight,r=e.strideWidth,a=e.padInfo.front,s=e.padInfo.top,i=e.padInfo.left;this.userCode=` void main() { ivec5 coords = getOutputCoords(); int wF = coords.x; int wR = coords.y; int wC = coords.z; int d1 = coords.w; int d2 = coords.u; float dotProd = 0.0; for (int b = 0; b < ${e.batchSize}; b++) { for (int yF = 0; yF < ${e.outDepth}; yF++) { int xF = wF + yF * ${t} - ${a}; if (xF < 0 || xF >= ${e.inDepth}) { continue; } for (int yR = 0; yR < ${e.outHeight}; yR++) { int xR = wR + yR * ${n} - ${s}; if (xR < 0 || xR >= ${e.inHeight}) { continue; } for (int yC = 0; yC < ${e.outWidth}; yC++) { int xC = wC + yC * ${r} - ${i}; if (xC < 0 || xC >= ${e.inWidth}) { continue; } float dyValue = getDy(b, yF, yR, yC, d2); float xValue = getX(b, xF, xR, xC, d1); dotProd += (xValue * dyValue); } } } } setOutput(dotProd); } `}},pW=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterDepth,n=e.filterHeight,r=e.filterWidth,a=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=t-1-e.padInfo.front,l=n-1-e.padInfo.top,u=r-1-e.padInfo.left;this.userCode=` const ivec3 pads = ivec3(${o}, ${l}, ${u}); void main() { ivec5 coords = getOutputCoords(); int batch = coords.x; int d1 = coords.u; ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads; int dyFCorner = dyCorner.x; int dyRCorner = dyCorner.y; int dyCCorner = dyCorner.z; float dotProd = 0.0; for (int wF = 0; wF < ${t}; wF++) { float dyF = float(dyFCorner + wF) / ${a}.0; if (dyF < 0.0 || dyF >= ${e.outDepth}.0 || fract(dyF) > 0.0) { continue; } int idyF = int(dyF); int wFPerm = ${t} - 1 - wF; for (int wR = 0; wR < ${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 < ${r}; 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 = ${r} - 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 fW(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,dy:s}=t,{strides:i,pad:o,dataFormat:l,dimRoundingMode:u,filterShape:c}=r,h=C.convertConv2DDataFormat(l),d=C.computeConv2DInfo(a.shape,c,i,1,o,u,!1,h),p=new cW(d);return n.runWebGLProgram(p,[a,s],"float32")}var mW={kernelName:hh,backendName:"webgl",kernelFunc:fW};function AW(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,filter:s}=t,{inputShape:i,strides:o,pad:l,dataFormat:u,dimRoundingMode:c}=r,h=C.convertConv2DDataFormat(u),d=C.computeConv2DInfo(i,s.shape,o,1,l,c,!1,h),p=new hW(d);return n.runWebGLProgram(p,[a,s],"float32")}var yW={kernelName:es,backendName:"webgl",kernelFunc:AW};function gW(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s}=t,{strides:i,pad:o,dilations:l}=r,u=C.computeConv3DInfo(a.shape,s.shape,i,l,o),c=new iW(u);return n.runWebGLProgram(c,[a,s],"float32")}var xW={kernelName:Kl,backendName:"webgl",kernelFunc:gW};function wW(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,dy:s}=t,{strides:i,pad:o,filterShape:l}=r,u=C.computeConv3DInfo(a.shape,l,i,1,o),c=new dW(u);return n.runWebGLProgram(c,[a,s],"float32")}var _W={kernelName:dh,backendName:"webgl",kernelFunc:wW};function bW(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,filter:s}=t,{pad:i,strides:o,inputShape:l}=r,u=C.computeConv3DInfo(l,s.shape,o,1,i),c=new pW(u);return n.runWebGLProgram(c,[a,s],"float32")}var vW={kernelName:ph,backendName:"webgl",kernelFunc:bW},kW=n_+` return cos(x); `,IW=Xe({opSnippet:kW}),NW={kernelName:ts,backendName:"webgl",kernelFunc:IW},SW=` float e2x = exp(-x); return (e2x + 1.0 / e2x) / 2.0; `,TW=Xe({opSnippet:SW}),EW={kernelName:Hi,backendName:"webgl",kernelFunc:TW},CW=class{constructor(e,t,n,r,a){this.variableNames=["Image","Boxes","BoxInd"],this.outputShape=[];let[s,i,o,l]=e,[u]=t,[c,h]=n;this.outputShape=[u,c,h,l];let d=r==="bilinear"?1:0,[p,f]=[`${i-1}.0`,`${o-1}.0`],[m,A,y]=c>1?[`${(i-1)/(c-1)}`,"(y2-y1) * height_ratio",`y1*${p} + float(y)*(height_scale)`]:["0.0","0.0",`0.5 * (y1+y2) * ${p}`],[g,w,_]=h>1?[`${(o-1)/(h-1)}`,"(x2-x1) * width_ratio",`x1*${f} + float(x)*(width_scale)`]:["0.0","0.0",`0.5 * (x1+x2) * ${f}`];this.userCode=` const float height_ratio = float(${m}); const float width_ratio = float(${g}); 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 = ${A}; float width_scale = ${w}; float in_y = ${y}; if( in_y < 0.0 || in_y > ${p} ) { setOutput(float(${a})); return; } float in_x = ${_}; if( in_x < 0.0 || in_x > ${f} ) { setOutput(float(${a})); return; } vec2 sourceFracIndexCR = vec2(in_x,in_y); if(${d} == 1) { // Compute the four integer indices. ivec2 sourceFloorCR = ivec2(sourceFracIndexCR); ivec2 sourceCeilCR = ivec2(ceil(sourceFracIndexCR)); float topLeft = getImage(b, sourceFloorCR.y, sourceFloorCR.x, d); float bottomLeft = getImage(b, sourceCeilCR.y, sourceFloorCR.x, d); float topRight = getImage(b, sourceFloorCR.y, sourceCeilCR.x, d); float bottomRight = getImage(b, sourceCeilCR.y, sourceCeilCR.x, d); vec2 fracCR = sourceFracIndexCR - vec2(sourceFloorCR); float top = topLeft + (topRight - topLeft) * fracCR.x; float bottom = bottomLeft + (bottomRight - bottomLeft) * fracCR.x; float newValue = top + (bottom - top) * fracCR.y; setOutput(newValue); } else { // Compute the coordinators of nearest neighbor point. ivec2 sourceNearestCR = ivec2(floor( sourceFracIndexCR + vec2(0.5,0.5))); float newValue = getImage(b, sourceNearestCR.y, sourceNearestCR.x, d); setOutput(newValue); } } `}},RW=e=>{let{inputs:t,backend:n,attrs:r}=e,{image:a,boxes:s,boxInd:i}=t,{cropSize:o,method:l,extrapolationValue:u}=r,c=new CW(a.shape,s.shape,o,l,u);return n.runWebGLProgram(c,[a,s,i],"float32")},FW={kernelName:Gi,backendName:"webgl",kernelFunc:RW},I_=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=e;let r=e.length,a=t?"0.0":`getX(${v_(r,"coords")})`,s=e[e.length-1],i="",o="";t?(i=n?`end != ${s-1}`:"end != 0",o=n?"end + 1":"end - 1"):(i=n?`end + pow2 < ${s}`:"end >= pow2",o=n?"end + pow2":"end - pow2"),this.userCode=` uniform float index; void main() { ${lt(r)} coords = getOutputCoords(); int end = ${k_(r,"coords")}; float val = ${a}; int pow2 = int(pow(2.0, index)); if (${i}) { int idx = ${o}; ${k_(r,"coords")} = idx; val += getX(${v_(r,"coords")}); } setOutput(val); } `}getCustomSetupFunc(e){return(t,n)=>{this.index==null&&(this.index=t.getUniformLocation(n,"index")),t.gl.uniform1f(this.index,e)}}};function v_(e,t){if(e===1)return`${t}`;if(e===2)return`${t}.x, ${t}.y`;if(e===3)return`${t}.x, ${t}.y, ${t}.z`;if(e===4)return`${t}.x, ${t}.y, ${t}.z, ${t}.w`;throw Error(`Cumulative sum for rank ${e} is not yet supported`)}function k_(e,t){if(e===1)return`${t}`;if(e===2)return`${t}.y`;if(e===3)return`${t}.z`;if(e===4)return`${t}.w`;throw Error(`Cumulative sum for rank ${e} is not yet supported`)}function $W(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,exclusive:i,reverse:o}=r,l=a.shape.length,u=C.getAxesPermutation([s],l),c=a;u!=null&&(c=wn({inputs:{x:a},backend:n,attrs:{perm:u}}));let h=C.getInnerMostAxes(1,l)[0];if(h!==l-1)throw new Error(`WebGL cumsum shader expects an inner-most axis=${a.shape.length-1} but got axis=${s}`);let d=c.shape[h],p=Fn({inputs:{x:c},backend:n});for(let f=0;f<=Math.ceil(Math.log2(d))-1;f++){let m=new I_(c.shape,!1,o),A=m.getCustomSetupFunc(f),y=p;p=n.runWebGLProgram(m,[p],p.dtype,A),n.disposeIntermediateTensorInfo(y)}if(i){let f=new I_(c.shape,i,o),m=p;p=n.runWebGLProgram(f,[p],p.dtype),n.disposeIntermediateTensorInfo(m)}if(u!=null){let f=C.getUndoAxesPermutation(u),m=wn({inputs:{x:p},backend:n,attrs:{perm:f}});return n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(c),m}return p}var MW={kernelName:ns,backendName:"webgl",kernelFunc:$W};function DW(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,weights:s}=t,{size:i,binaryOutput:o}=r;if(a.shape.length===1){let l=n.readSync(a.dataId),u=n.readSync(s.dataId),c=Uw(l,u,s.dtype,s.shape,i);return n.makeTensorInfo([i],s.dtype,c)}else if(a.shape.length===2){let l=n.bufferSync(a),u=n.bufferSync(s),c=hz(l,u,i,o);return n.makeTensorInfo(c.shape,s.dtype,c.values)}throw new Error(`Error in denseBincount: input must be at most rank 2, but got rank${a.shape.length}.`)}var OW={kernelName:fh,backendName:"webgl",kernelFunc:DW},zW=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 LW(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{blockSize:s,dataFormat:i}=r;v.assert(s>1,()=>`blockSize should be > 1 for depthToSpace, but was: ${s}`);let o=a.shape[0],l=i==="NHWC"?a.shape[1]:a.shape[2],u=i==="NHWC"?a.shape[2]:a.shape[3],c=i==="NHWC"?a.shape[3]:a.shape[1],h=l*s,d=u*s,p=c/(s*s),f=i==="NHWC"?[o,h,d,p]:[o,p,h,d],m=new zW(f,s,i);return n.runWebGLProgram(m,[a],a.dtype)}var PW={kernelName:qi,backendName:"webgl",kernelFunc:LW},N_=class{constructor(e,t=!1,n=null,r=!1,a=!1){this.variableNames=["x","W"],this.outputShape=e.outShape;let s=e.inHeight,i=e.inWidth,o=e.padInfo.top,l=e.padInfo.left,u=e.strideHeight,c=e.strideWidth,h=e.dilationHeight,d=e.dilationWidth,p=e.filterHeight,f=e.filterWidth,m=e.outChannels/e.inChannels,A="",y="";n&&(r?A=`float activation(float a) { float b = getPreluActivationWeightsAtOutCoords(); ${n} }`:a?A=`float activation(float a) { float b = getLeakyreluAlphaAtOutCoords(); ${n} }`:A=` float activation(float x) { ${n} } `,y="result = activation(result);");let g=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),r&&this.variableNames.push("preluActivationWeights"),a&&this.variableNames.push("leakyreluAlpha"),this.userCode=` ${A} const ivec2 strides = ivec2(${u}, ${c}); const ivec2 pads = ivec2(${o}, ${l}); void main() { ivec4 coords = getOutputCoords(); int batch = coords.x; ivec2 xRCCorner = coords.yz * strides - pads; int d2 = coords.w; int d1 = d2 / ${m}; int q = d2 - d1 * ${m}; 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 < ${p}; wR++) { int xR = xRCorner + wR * ${h}; if (xR < 0 || xR >= ${s}) { continue; } for (int wC = 0; wC < ${f}; wC++) { int xC = xCCorner + wC * ${d}; if (xC < 0 || xC >= ${i}) { continue; } float xVal = getX(batch, xR, xC, d1); float wVal = getW(wR, wC, d1, q); dotProd += xVal * wVal; } } float result = dotProd; ${g} ${y} setOutput(result); } `}},S_=class{constructor(e,t=!1,n=null,r=!1,a=!1){this.variableNames=["x","W"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e.outShape;let s=e.inHeight,i=e.inWidth,o=e.padInfo.top,l=e.padInfo.left,u=e.strideHeight,c=e.strideWidth,h=e.dilationHeight,d=e.dilationWidth,p=e.filterHeight,f=e.filterWidth,m=f,A="int xR; int xC; int xCOffset;";for(let _=0;_= 0 && xR < ${s} && xCOffset >= 0 && xCOffset < ${i}) { xTexelR${_}C${x} = getX(batch, xR, xCOffset, d1); // Need to manually clear unused channels in case // we're reading from recycled texture. if(xCOffset + 1 >= ${i}) { xTexelR${_}C${x}.zw = vec2(0.); } } else { xTexelR${_}C${x} = vec4(0.); } xCOffset = xC + 1 - 2; if(xR >= 0 && xR < ${s} && xCOffset >= 0 && xCOffset < ${i}) { vec4 previous = getX(batch, xR, xCOffset, d1); // Need to manually clear unused channels in case // we're reading from recycled texture. if(xCOffset + 1 >= ${i}) { previous.zw = vec2(0.); } xR${_}C${x} = vec4(previous.zw, xTexelR${_}C${x}.xy); } else { xR${_}C${x} = vec4(0, 0, xTexelR${_}C${x}.xy); } `:A+=` if(xR >= 0 && xR < ${s} && xC >= 0 && xC < ${i}) { xTexelR${_}C${x} = getX(batch, xR, xC, d1); } else { xTexelR${_}C${x} = vec4(0.); } xR${_}C${x} = xTexelR${_}C${x}; `,x+1= 0 && xR < ${s} && xCOffset >= 0 && xCOffset < ${i}) { xTexelR${_}C${x+2} = getX(batch, xR, xCOffset, d1); } `,d>1&&(A+=` xCOffset -= 2; if(xR >= 0 && xR < ${s} && xCOffset >= 0 && xCOffset < ${i}) { xTexelR${_}C${x} = getX(batch, xR, xCOffset, d1); } else { xTexelR${_}C${x} = vec4(0.); } `),A+=` xR${_}C${x+1} = vec4( xTexelR${_}C${x}.zw, xTexelR${_}C${x+2}.xy); `):A+=` xCOffset = xC + ${N}; if(xR >= 0 && xR < ${s} && xCOffset >= 0 && xCOffset < ${i}) { xTexelR${_}C${x+2} = getX(batch, xR, xCOffset, d1); } xR${_}C${x+1} = xTexelR${_}C${x+2}; `}}else x= 0 && xR < ${s}) { `,l%2==1?(A+=` xCOffset = xC + 1 - ${c}; if(xCOffset >= 0 && xCOffset < ${i}) { xTexelR${_}C${x} = getX(batch, xR, xCOffset, d1); } else { xTexelR${_}C${x} = vec4(0.); } if(xC + 1 >= 0 && xC + 1 < ${i}) { xTexelR${_}C${x+2} = getX(batch, xR, xC + 1, d1); } else { xTexelR${_}C${x+2} = vec4(0.); } xR${_}C${x} = vec4( xTexelR${_}C${x}.zw, xTexelR${_}C${x+2}.zw); `,x+1= 0 && xCOffset < ${i}) { final = getX(batch, xR, xCOffset, d1); } xR${_}C${x+1} = vec4(xTexelR${_}C${x+2}.xy, final.xy); `)):(A+=` if(xC >= 0 && xC < ${i}) { xTexelR${_}C${x} = getX(batch, xR, xC, d1); } else { xTexelR${_}C${x} = vec4(0.); } xCOffset = xC + ${c}; if(xCOffset >= 0 && xCOffset < ${i}) { xTexelR${_}C${x+2} = getX(batch, xR, xCOffset, d1); } else { xTexelR${_}C${x+2} = vec4(0.); } xR${_}C${x} = vec4( xTexelR${_}C${x}.xy, xTexelR${_}C${x+2}.xy); `,x+1`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${i} and dilations '${c}'`);let h=C.computeConv2DInfo(a.shape,s.shape,i,c,o,u,!0),d;return Y().getBool("WEBGL_PACK_DEPTHWISECONV")&&h.strideWidth<=2&&h.outChannels/h.inChannels==1?d=new S_(h):d=new N_(h),n.runWebGLProgram(d,[a,s],"float32")}var BW={kernelName:rs,backendName:"webgl",kernelFunc:WW},VW=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideHeight,n=e.strideWidth,r=e.padInfo.top,a=e.padInfo.left,s=e.outChannels/e.inChannels;this.userCode=` void main() { ivec4 coords = getOutputCoords(); int wR = coords.x; int wC = coords.y; int d1 = coords.z; int dm = coords.w; int d2 = d1 * ${s} + dm; float dotProd = 0.0; // TO DO: Vec4 over the batch size for (int b = 0; b < ${e.batchSize}; b++) { for (int yR = 0; yR < ${e.outHeight}; yR++) { int xR = wR + yR * ${t} - ${r}; if (xR < 0 || xR >= ${e.inHeight}) { continue; } for (int yC = 0; yC < ${e.outWidth}; yC++) { int xC = wC + yC * ${n} - ${a}; if (xC < 0 || xC >= ${e.inWidth}) { continue; } float dyValue = getDy(b, yR, yC, d2); float xValue = getX(b, xR, xC, d1); dotProd += (xValue * dyValue); } } } setOutput(dotProd); } `}},UW=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterHeight,n=e.filterWidth,r=e.strideHeight,a=e.strideWidth,s=t-1-e.padInfo.top,i=n-1-e.padInfo.left,o=e.outChannels/e.inChannels;this.userCode=` const ivec2 pads = ivec2(${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) / ${r}.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) / ${a}.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 * ${o} + dm; float xValue = getDy(batch, idyR, idyC, d2); float wValue = getW(wRPerm, wCPerm, d1, dm); dotProd += xValue * wValue; } } } setOutput(dotProd); } `}};function jW(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,dy:s}=t,{strides:i,dilations:o,pad:l,dimRoundingMode:u,filterShape:c}=r,h=C.computeConv2DInfo(a.shape,c,i,o,l,u,!0),d=new VW(h);return n.runWebGLProgram(d,[a,s],"float32")}var HW={kernelName:mh,backendName:"webgl",kernelFunc:jW};function GW(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,filter:s}=t,{strides:i,dilations:o,pad:l,dimRoundingMode:u,inputShape:c}=r,h=C.computeConv2DInfo(c,s.shape,i,o,l,u,!0),d=new UW(h);return n.runWebGLProgram(d,[a,s],"float32")}var qW={kernelName:Ah,backendName:"webgl",kernelFunc:GW},XW=class{constructor(e){this.variableNames=["X"],this.outputShape=[e,e],this.userCode=` void main() { ivec2 coords = getOutputCoords(); float val = coords[0] == coords[1] ? getX(coords[0]) : 0.0; setOutput(val); } `}};function KW(e){let{inputs:t,backend:n}=e,{x:r}=t,a=[...r.shape,...r.shape],s=v.sizeFromShape(r.shape),i=ye({inputs:{x:r},backend:n,attrs:{shape:[s]}}),o=new XW(s),l=n.runWebGLProgram(o,[i],i.dtype),u=ye({inputs:{x:l},backend:n,attrs:{shape:a}});return n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(l),u}var ZW={kernelName:yh,backendName:"webgl",kernelFunc:KW},YW=class{constructor(e){this.variableNames=["x","W"],this.outputShape=e.outShape;let{inHeight:t,inWidth:n,padInfo:r,strideHeight:a,strideWidth:s,filterHeight:i,filterWidth:o,dilationHeight:l,dilationWidth:u}=e,{top:c,left:h}=r;this.userCode=` const ivec2 strides = ivec2(${a}, ${s}); const ivec2 pads = ivec2(${c}, ${h}); const float neg_infinity = -3.4e38; void main() { ivec4 coords = getOutputCoords(); int batch = coords.x; int d1 = coords.w; ivec2 outTopLeftCorner = coords.yz * strides - pads; int hBeg = outTopLeftCorner.x; int wBeg = outTopLeftCorner.y; float curVal = neg_infinity; for (int h = 0; h < ${i}; h++) { int hIn = hBeg + h * ${l}; if (hIn >= 0 && hIn < ${t}) { for (int w = 0; w < ${o}; w++) { int wIn = wBeg + w * ${u}; if (wIn >= 0 && wIn < ${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 JW(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,filter:s}=t,{strides:i,pad:o,dilations:l}=r,u=C.computeDilation2DInfo(a.shape,s.shape,i,o,"NHWC",l),c,h=new YW(u);c=n.runWebGLProgram(h,[a,s],"float32");let d=ye({inputs:{x:c},backend:n,attrs:{shape:u.outShape}});return n.disposeIntermediateTensorInfo(c),d}var QW={kernelName:Zl,backendName:"webgl",kernelFunc:JW},eB="return (x >= 0.0) ? x : (exp(x) - 1.0);",tB=` 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; `,nB=Xe({opSnippet:eB,packedOpSnippet:tB}),rB={kernelName:Xi,backendName:"webgl",kernelFunc:nB},aB="return (b >= 1.0) ? a : a * (b + 1.0);",sB=` vec4 bGTEZero = vec4(greaterThanEqual(b, vec4(0.))); return (bGTEZero * a) + ((vec4(1.0) - bGTEZero) * (a * (b + vec4(1.0)))); `,iB=e=>{let{inputs:t,backend:n}=e,{dy:r,y:a}=t,s=Y().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new Ju(sB,r.shape,a.shape):new gl(aB,r.shape,a.shape);return n.runWebGLProgram(s,[r,a],r.dtype)},oB={kernelName:wh,backendName:"webgl",kernelFunc:iB},lB=` return vec4(equal(a, b)); `,uB="return float(a == b);",cB=Qt({opSnippet:uB,packedOpSnippet:lB,dtype:"bool"}),hB={kernelName:Zi,backendName:"webgl",kernelFunc:cB},dB=` // Error function is calculated approximately with elementary function. // See "Handbook of Mathematical Functions with Formulas, // Graphs, and Mathematical Tables", Abramowitz and Stegun. float p = ${C.ERF_P}; float a1 = ${C.ERF_A1}; float a2 = ${C.ERF_A2}; float a3 = ${C.ERF_A3}; float a4 = ${C.ERF_A4}; float a5 = ${C.ERF_A5}; float sign = sign(x); x = abs(x); float t = 1.0 / (1.0 + p * x); return sign * (1.0 - (((((a5*t + a4)*t) + a3)*t + a2)*t + a1)*t*exp(-x*x)); `,pB=Xe({opSnippet:dB}),fB={kernelName:Ki,backendName:"webgl",kernelFunc:pB},T_="return exp(x);",E_=Xe({opSnippet:T_,packedOpSnippet:T_,cpuKernelImpl:fz}),mB={kernelName:ss,backendName:"webgl",kernelFunc:E_};function FA(e){let{inputs:t,attrs:n,backend:r}=e,{dim:a}=n,{input:s}=t,i=s.shape.length,o=s.shape.slice(),l=a;return a<0&&(v.assert(-(i+1)<=a,()=>`Axis must be in the interval [${-(i+1)}, ${i}]`),l=i+a+1),o.splice(l,0,1),ye({inputs:{x:s},backend:r,attrs:{shape:o}})}var AB={kernelName:Yi,backendName:"webgl",kernelFunc:FA},C_="return exp(x) - 1.0;",yB=Xe({opSnippet:C_,packedOpSnippet:C_,cpuKernelImpl:mz}),gB={kernelName:Ji,backendName:"webgl",kernelFunc:yB},R_=class{constructor(e,t,n){this.variableNames=["real","imag"];let r=t[1];this.outputShape=t;let a=n?`2.0 * ${Math.PI}`:`-2.0 * ${Math.PI}`,s=n?`${r}.0`:"1.0",i;if(e==="real")i="return real * expR - imag * expI;";else if(e==="imag")i="return real * expI + imag * expR;";else throw new Error(`FFT component must be either "real" or "imag", got ${e}.`);this.userCode=` const float exponentMultiplier = ${a}; 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NAN : result.a; return result; `,vV=Xe({opSnippet:_V,packedOpSnippet:bV,cpuKernelImpl:_z}),kV={kernelName:ds,backendName:"webgl",kernelFunc:vV},IV="return log(1.0 + x);",NV=Xe({opSnippet:IV}),SV={kernelName:lo,backendName:"webgl",kernelFunc:NV},TV="return float(a >= 1.0 && b >= 1.0);",EV=` return vec4( vec4(greaterThanEqual(a, vec4(1.0))) * vec4(greaterThanEqual(b, vec4(1.0)))); `,CV=Qt({opSnippet:TV,packedOpSnippet:EV,dtype:"bool"}),RV={kernelName:uo,backendName:"webgl",kernelFunc:CV},FV="return float(!(x >= 1.0));",$V=Xe({opSnippet:FV}),MV={kernelName:Jl,backendName:"webgl",kernelFunc:$V},DV="return float(a >= 1.0 || b >= 1.0);",OV=` return min( vec4(greaterThanEqual(a, vec4(1.0))) + vec4(greaterThanEqual(b, vec4(1.0))), vec4(1.0)); `,zV=Qt({opSnippet:DV,packedOpSnippet:OV,dtype:"bool"}),LV={kernelName:Ql,backendName:"webgl",kernelFunc:zV},PV=class{constructor(e,t,n,r,a){this.variableNames=["x"],this.outputShape=[];let s=t,i=e[3]-1;this.outputShape=e;let o,l=`float(${n}) + float(${r}) * sum`;a===.5?o=`inversesqrt(${l})`:a===1?o=`1.0/(${l})`:o=`exp(log(${l}) * float(-${a}));`,this.userCode=` void main() { ivec4 coords = getOutputCoords(); int b = coords[0]; int r = coords[1]; int c = coords[2]; int d = coords[3]; float x = getX(b, r, c, d); float sum = 0.0; for (int j = -${s}; j <= ${s}; j++) { int idx = d + j; if (idx >= 0 && idx <= ${i}) { float z = getX(b, r, c, idx); sum += z * z; } } float val = x * ${o}; setOutput(val); } `}},WV=class{constructor(e,t,n,r,a){this.variableNames=["x"],this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0;let s=t,i=e[3]-1;this.outputShape=e;let o,l=`float(${n}) + float(${r}) * sum`;a===.5?o=`inversesqrt(${l})`:a===1?o=`1.0/(${l})`:o=`exp(log(${l}) * float(-${a}));`,this.userCode=` void main() { ivec4 coords = getOutputCoords(); int b = coords.x; int r = coords.y; int c = coords.z; int d = coords.w; bool hasNextCol = d < ${this.outputShape[3]}; bool hasNextRow = c < ${this.outputShape[2]}; vec4 sum = vec4(0.); vec4 xFragAtOutputCoords = getX(b, r, c, d); vec4 xAtOutputCoords = vec4( getChannel(xFragAtOutputCoords, vec2(c, d)), hasNextCol ? getChannel(xFragAtOutputCoords, vec2(c, d + 1)) : 0.0, hasNextRow ? getChannel(xFragAtOutputCoords , vec2(c + 1, d)) : 0.0, (hasNextRow && hasNextCol) ? getChannel(xFragAtOutputCoords, vec2(c + 1, d + 1)) : 0.0 ); int firstChannel = d - ${s}; vec2 cache = vec2(0.); if(firstChannel >= 0){ vec4 firstChannelFrag = getX(b, r, c, firstChannel); cache.x = getChannel(firstChannelFrag, vec2(c, firstChannel)); if(hasNextRow){ cache.y = getChannel(firstChannelFrag, vec2(c + 1, firstChannel)); } } ivec2 depth = ivec2(d, d + 1); for (int j = - ${s}; j <= ${s}; j++) { ivec2 idx = depth + j; bvec2 aboveLowerBound = greaterThanEqual(idx, ivec2(0)); bvec2 belowUpperBound = lessThanEqual(idx, ivec2(${i})); bool depthInRange = aboveLowerBound.x && belowUpperBound.x; bool depthPlusOneInRange = aboveLowerBound.y && belowUpperBound.y; if(depthInRange || depthPlusOneInRange){ vec4 z = vec4(0.); vec4 xFragAtCurrentDepth; z.xz = cache.xy; if(depthPlusOneInRange && hasNextCol){ xFragAtCurrentDepth = idx.y != d ? getX(b, r, c, idx.y) : xFragAtOutputCoords; z.y = getChannel(xFragAtCurrentDepth, vec2(c, idx.y)); if(hasNextRow){ z.w = getChannel(xFragAtCurrentDepth, vec2(c + 1, idx.y)); } } cache.xy = z.yw; sum += z * z; } } vec4 result = xAtOutputCoords * ${o}; setOutput(result); } `}},BV=e=>{let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{depthRadius:s,bias:i,alpha:o,beta:l}=r,u=Y().getBool("WEBGL_PACK_NORMALIZATION")?new WV(a.shape,s,i,o,l):new PV(a.shape,s,i,o,l);return n.runWebGLProgram(u,[a],a.dtype)},VV={kernelName:eu,backendName:"webgl",kernelFunc:BV},UV=class{constructor(e,t,n,r,a){this.variableNames=["inputImage","outputImage","dy"],this.outputShape=[],this.outputShape=e,this.depth=e[3],this.depthRadius=t,this.bias=n,this.alpha=r,this.beta=a,this.userCode=` void main() { ivec4 coords = getOutputCoords(); int b = coords[0]; int r = coords[1]; int c = coords[2]; float result = 0.0; for (int d = 0; d < ${this.depth}; ++d) { int depthBegin = int(max(0.0, float(d - ${t}))); int depthEnd = int(min(float(${this.depth}), float(d + ${t} + 1))); const int MIN_DEPTH_BEGIN = 0; const int MAX_DEPTH_END = ${this.depth}; float norm = 0.0; for (int k = MIN_DEPTH_BEGIN; k < MAX_DEPTH_END; ++k) { if (k < depthBegin){ continue; } else if (k >= depthBegin && k < depthEnd) { norm += getInputImage(b, r, c, k) * getInputImage(b, r, c, k); } else { break; } } norm = float(${r}) * norm + float(${n}); for(int k = MIN_DEPTH_BEGIN; k < MAX_DEPTH_END; ++k){ if (k < depthBegin){ continue; } else if (k >= depthBegin && k < depthEnd){ float dyi = -2.0 * float(${r}) * float(${a}) * getInputImage(b ,r ,c, k) * getOutputImage(b, r, c, d) / norm; if (k == d) { dyi += pow(norm, -1.0 * ${a}); } if (k == coords[3]) { dyi *= getDy(b, r, c, d); result += dyi; } } else { break; } } } setOutput(result); } `}},jV=e=>{let{inputs:t,backend:n,attrs:r}=e,{x:a,y:s,dy:i}=t,{depthRadius:o,bias:l,alpha:u,beta:c}=r,h=new UV(a.shape,o,l,u,c);return n.runWebGLProgram(h,[a,s,i],a.dtype)},HV={kernelName:Ih,backendName:"webgl",kernelFunc:jV};function GV(e,t,n,r){let a=v.sizeFromShape(t),s=v.sizeFromShape(e.shape)/a,i=ye({inputs:{x:e},attrs:{shape:[s,a]},backend:r}),o=ui(i,e.dtype,"max",r),l=ye({inputs:{x:o},attrs:{shape:n},backend:r});return r.disposeIntermediateTensorInfo(i),r.disposeIntermediateTensorInfo(o),l}function M_(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{reductionIndices:s,keepDims:i}=r,o=a.shape.length,l=v.parseAxisParam(s,a.shape),u=l,c=C.getAxesPermutation(u,o),h=c!=null,d=n.shouldExecuteOnCPU([a]),p=a;if(h){if(d){let g=n.texData.get(p.dataId).values,w=new Array(o);for(let x=0;x`Error in maxPool: Either strides or dilations must be 1. Got strides ${i} and dilations '${u}'`);let c=C.computePool2DInfo(a.shape,s,i,u,o,l);if(c.filterWidth===1&&c.filterHeight===1&&v.arraysEqual(c.inShape,c.outShape))return Fn({inputs:{x:a},backend:n});let h=new Qu(c,"max",!1);return n.runWebGLProgram(h,[a],a.dtype)}var QV={kernelName:ms,backendName:"webgl",kernelFunc:JV};function eU(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{filterSize:s,strides:i,pad:o,dataFormat:l,dimRoundingMode:u}=r,c=[1,1,1],h=C.computePool3DInfo(a.shape,s,i,c,o,u,l),d=new EA(h,"max",!1);return n.runWebGLProgram(d,[a],a.dtype)}var tU={kernelName:tu,backendName:"webgl",kernelFunc:eU},nU=class{constructor(e){this.variableNames=["dy","maxPos"],this.outputShape=e.inShape;let t=e.strideHeight,n=e.strideWidth,r=e.dilationHeight,a=e.effectiveFilterHeight,s=e.effectiveFilterWidth,i=a-1-e.padInfo.top,o=s-1-e.padInfo.left,l=a*s-1;this.userCode=` const ivec2 pads = ivec2(${i}, ${o}); void main() { ivec4 coords = getOutputCoords(); int b = coords[0]; int d = coords[3]; ivec2 dyRCCorner = coords.yz - pads; int dyRCorner = dyRCCorner.x; int dyCCorner = dyRCCorner.y; // Convolve dy(?, ?, d) with pos mask(:, :, d) to get dx(xR, xC, d). // ? = to be determined. : = across all values in that axis. float dotProd = 0.0; for (int wR = 0; wR < ${a}; wR += ${r}) { 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 * ${s} + wC; float mask = float(maxPosValue == curPosValue ? 1.0 : 0.0); dotProd += dyValue * mask; } } setOutput(dotProd); } `}},rU=class{constructor(e){this.variableNames=["dy","maxPos"],this.outputShape=e.inShape;let t=e.strideDepth,n=e.strideHeight,r=e.strideWidth,a=e.dilationDepth,s=e.dilationHeight,i=e.dilationWidth,o=e.effectiveFilterDepth,l=e.effectiveFilterHeight,u=e.effectiveFilterWidth,c=o-1-e.padInfo.front,h=l-1-e.padInfo.top,d=u-1-e.padInfo.left,p=o*l*u-1;this.userCode=` const ivec3 pads = ivec3(${c}, ${h}, ${d}); void main() { ivec5 coords = getOutputCoords(); int batch = coords.x; int ch = coords.u; ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads; int dyDCorner = dyCorner.x; int dyRCorner = dyCorner.y; int dyCCorner = dyCorner.z; // Convolve dy(?, ?, ?, ch) with pos mask(:, :, :, d) to get // dx(xD, xR, xC, ch). // ? = to be determined. : = across all values in that axis. float dotProd = 0.0; for (int wD = 0; wD < ${o}; wD += ${a}) { float dyD = float(dyDCorner + wD) / ${t}.0; if (dyD < 0.0 || dyD >= ${e.outDepth}.0 || fract(dyD) > 0.0) { continue; } int idyD = int(dyD); for (int wR = 0; wR < ${l}; wR += ${s}) { float dyR = float(dyRCorner + wR) / ${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) / ${r}.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 = ${p} - 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 aU(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,input:s}=t,i=s,{filterSize:o,strides:l,pad:u,dimRoundingMode:c}=r,h=[1,1,1],d=C.computePool3DInfo(i.shape,o,l,h,u,c),p=new EA(d,"max",!0),f=n.runWebGLProgram(p,[i],i.dtype),m=new rU(d),A=n.runWebGLProgram(m,[a,f],i.dtype);return n.disposeIntermediateTensorInfo(f),A}var sU={kernelName:Sh,backendName:"webgl",kernelFunc:aU};function iU(e){let{inputs:t,backend:n,attrs:r}=e,{dy:a,input:s,output:i}=t,o=s;hl([s,i],"maxPoolGrad");let{filterSize:l,strides:u,pad:c,dimRoundingMode:h}=r,d=C.computePool2DInfo(o.shape,l,u,1,c,h),p=!0,f=new Qu(d,"max",p),m=n.runWebGLProgram(f,[o],o.dtype),A=new nU(d),y=n.runWebGLProgram(A,[a,m],o.dtype);return n.disposeIntermediateTensorInfo(m),y}var oU={kernelName:Nh,backendName:"webgl",kernelFunc:iU};function lU(e,t,n,r){let a=new Qu(n,"max",!1),s=r.runWebGLProgram(a,[e],"float32");a=new Qu(n,"max",!0,!0,t);let i=r.runWebGLProgram(a,[e],"float32");return[s,i]}var uU={kernelName:Th,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{x:r}=e,{filterSize:a,strides:s,pad:i,includeBatchInIndex:o}=t,l=n;v.assert(r.shape.length===4,()=>`Error in maxPool: input must be rank 4 but got rank ${r.shape.length}.`);let u=[1,1];v.assert(C.eitherStridesOrDilationsAreOne(s,u),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${s} and dilations '${u}'`);let c=C.computePool2DInfo(r.shape,a,s,u,i),[h,d]=lU(r,o,c,l);return[h,d]}};function cU(e,t,n,r){let a=v.sizeFromShape(t),s=v.sizeFromShape(e.shape)/a,i=ye({inputs:{x:e},attrs:{shape:[s,a]},backend:r}),o=ui(i,"float32","mean",r),l=ye({inputs:{x:o},attrs:{shape:n},backend:r});return r.disposeIntermediateTensorInfo(i),r.disposeIntermediateTensorInfo(o),l}var hU={kernelName:As,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{x:r}=e,{keepDims:a,axis:s}=t,i=n,o=r.shape.length,l=v.parseAxisParam(s,r.shape),u=l,c=C.getAxesPermutation(u,o),h=c!=null,d=i.shouldExecuteOnCPU([r]),p=[],f=r;if(h){if(d){let w=i.texData.get(f.dataId).values,_=new Array(o);for(let N=0;N<_.length;N++)_[N]=r.shape[c[N]];let b=NA(w,r.shape,r.dtype,c,_);f=i.makeTensorInfo(_,r.dtype);let x=i.texData.get(f.dataId);x.values=b}else f=Jd(r,c,i);p.push(f),u=C.getInnerMostAxes(u.length,o)}C.assertAxesAreInnerMostDims("sum",u,o);let[m,A]=C.computeOutAndReduceShapes(f.shape,u),y=m;a&&(y=C.expandShapeToKeepDim(m,l));let g=cU(f,A,y,i);for(let w of p)i.disposeIntermediateTensorInfo(w);return g}};function dU(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r,o=a.shape.length,l=v.parseAxisParam(s,a.shape),u=l,c=C.getAxesPermutation(u,o),h=a;c!=null&&(h=wn({inputs:{x:a},backend:n,attrs:{perm:c}}),u=C.getInnerMostAxes(u.length,a.shape.length)),C.assertAxesAreInnerMostDims("min",u,o);let[d,p]=C.computeOutAndReduceShapes(h.shape,u),f=v.sizeFromShape(p),m=ye({inputs:{x:h},backend:n,attrs:{shape:[-1,f]}}),A=ui(m,m.dtype,"min",n),y;if(i){let g=C.expandShapeToKeepDim(d,l);y=ye({inputs:{x:A},backend:n,attrs:{shape:g}})}else y=ye({inputs:{x:A},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(A),c!=null&&n.disposeIntermediateTensorInfo(h),y}var pU={kernelName:ys,backendName:"webgl",kernelFunc:dU},fU=Yw+` return min(a, b); `,mU=` vec4 result = vec4(min(a, b)); vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0)); `+Zd+` return result; `,AU=Qt({opSnippet:fU,packedOpSnippet:mU,cpuKernelImpl:kz}),yU={kernelName:gs,backendName:"webgl",kernelFunc:AU},gU=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=t.map((u,c)=>u[0]+e[c]+u[1]);let r=e.length,a=lt(r),s=t.map(u=>u[0]).join(","),i=t.map((u,c)=>u[0]+e[c]).join(","),o=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,r),l=n==="reflect"?0:1;if(r===1){this.userCode=` int start = ${s}; int end = ${i}; void main() { int outC = getOutputCoords(); if (outC < start) { outC = start * 2 - outC - ${l}; } else if(outC >= end) { outC = (end - 1) * 2 - outC + ${l}; } setOutput(getX(outC - start)); } `;return}this.userCode=` ${a} start = ${a}(${s}); ${a} end = ${a}(${i}); void main() { ${a} outC = getOutputCoords(); for (int i = 0; i < ${r}; i++) { if (outC[i] < start[i]) { outC[i] = start[i] * 2 - outC[i] - ${l}; } else if(outC[i] >= end[i]) { outC[i] = (end[i] - 1) * 2 - outC[i] + ${l}; } } ${a} coords = outC - start; setOutput(getX(${o})); } `}},xU=class{constructor(e,t,n){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t.map((p,f)=>p[0]+e[f]+p[1]);let r=e.length,a=lt(r),s=t.map(p=>p[0]).join(","),i=t.map((p,f)=>p[0]+e[f]).join(","),o=cn("rc",r),l=cn("source",r),u=`${o[r-1]} < ${this.outputShape[r-1]}`,c=r===1?"source":`vec2(${l.slice(-2).join()})`,h=n==="reflect"?0:1,d="";if(r===1){let p=` ${a} source = rc; if (source < start) { source = start * 2 - source - ${h}; } else if (source >= end) { source = (end - 1) * 2 - source + ${h}; } source -= start; `;d=` ${a} rc = outputLoc; ${p} result[0] = getChannel(getX(${l.join()}), ${c}); ${o[r-1]} += 1; if(${u}) { ${p} result[1] = getChannel(getX(${l.join()}), ${c}); } `}else{let p=` ${a} source = rc; ${a} lt = ${a}(lessThan(source, start)); ${a} gte = ${a}(greaterThanEqual(source, end)); ${a} orig = 1 - (lt + gte); source = orig * source + lt * (start * 2 - source - ${h}) + gte * ((end - 1) * 2 - source + ${h}); source -= start; `;d=` ${a} rc = outputLoc; ${p} result[0] = getChannel(getX(${l.join()}), ${c}); ${o[r-1]} += 1; if(${u}) { ${p} result[1] = getChannel(getX(${l.join()}), ${c}); } rc = outputLoc; ${o[r-2]} += 1; if(${o[r-2]} < ${this.outputShape[r-2]}) { ${p} result[2] = getChannel(getX(${l.join()}), ${c}); ${o[r-1]} += 1; if(${u}) { ${p} result[3] = getChannel(getX(${l.join()}), ${c}); } } `}this.userCode=` const ${a} start = ${a}(${s}); const ${a} end = ${a}(${i}); void main() { ${a} outputLoc = getOutputCoords(); vec4 result = vec4(0.); ${d} setOutput(result); } `}},wU=({inputs:e,backend:t,attrs:n})=>{let{x:r}=e,{paddings:a,mode:s}=n,i=Y().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new xU(r.shape,a,s):new gU(r.shape,a,s);return t.runWebGLProgram(i,[r],r.dtype)},_U={kernelName:nu,backendName:"webgl",kernelFunc:wU},bU=`if (b == 0.0) return NAN; return mod(a, b);`,vU=` vec4 result = mod(a, b); vec4 isNaN = vec4(equal(b, vec4(0.0))); `+Zd+` return result; `,kU=Qt({opSnippet:bU,packedOpSnippet:vU}),IU={kernelName:co,backendName:"webgl",kernelFunc:kU},NU=class{constructor(e,t,n){this.variableNames=["probs"],this.outputShape=[e,n],this.userCode=` uniform float seed; 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})); } `}getCustomSetupFunc(e){return(t,n)=>{this.seedLoc==null&&(this.seedLoc=t.getUniformLocation(n,"seed")),t.gl.uniform1f(this.seedLoc,e)}}},SU=` if (a == b) { return 1.0; }; return a / b;`,TU=` // 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; `,D_=Qt({opSnippet:SU,packedOpSnippet:TU,checkOutOfBounds:!0}),EU={kernelName:as,backendName:"webgl",kernelFunc:D_},O_="return a - b;",z_=Qt({opSnippet:O_,packedOpSnippet:O_,supportsComplex:!0,cpuKernelImpl:Fz}),CU={kernelName:Os,backendName:"webgl",kernelFunc:z_};function L_(e){let{inputs:t,backend:n,attrs:r}=e,{logits:a}=t,{dim:s}=r,i=v.parseAxisParam([s],a.shape),o=M_({inputs:{x:a},backend:n,attrs:{reductionIndices:i,keepDims:!1}}),l=C.expandShapeToKeepDim(o.shape,i),u=ye({inputs:{x:o},backend:n,attrs:{shape:l}}),c=z_({inputs:{a,b:u},backend:n}),h=E_({inputs:{x:c},backend:n}),d=TA({inputs:{x:h},backend:n,attrs:{axis:i,keepDims:!1}}),p=ye({inputs:{x:d},backend:n,attrs:{shape:l}}),f=D_({inputs:{a:h,b:p},backend:n});return n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(u),n.disposeIntermediateTensorInfo(c),n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(p),f}var RU={kernelName:Ms,backendName:"webgl",kernelFunc:L_};function FU(e){let{inputs:t,backend:n,attrs:r}=e,{logits:a}=t,{numSamples:s,seed:i,normalized:o}=r,l=o?a:L_({inputs:{logits:a},backend:n,attrs:{dim:a.shape.length-1}}),u=l.shape[0],c=l.shape[1],h=new NU(u,c,s),d=h.getCustomSetupFunc(i),p=n.runWebGLProgram(h,[l],"int32",d);return o||n.disposeIntermediateTensorInfo(l),p}var $U={kernelName:Eh,backendName:"webgl",kernelFunc:FU},P_="return -x;";function MU(e){let{inputs:t,backend:n}=e,{x:r}=t;if(n.shouldExecuteOnCPU([r])){let s=n.texData.get(r.dataId),[i,o]=Nz(s.values,r.shape,r.dtype);return n.makeTensorInfo(o,r.dtype,i)}let a;return Y().getBool("WEBGL_PACK_UNARY_OPERATIONS")?a=new yl(r.shape,P_):a=new $a(r.shape,P_),n.runWebGLProgram(a,[r],r.dtype)}var DU={kernelName:ho,backendName:"webgl",kernelFunc:MU},OU=Rr.nonMaxSuppressionV3Impl;function zU(e){C.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:r}=e,{boxes:a,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l}=r,u=n.readSync(a.dataId),c=n.readSync(s.dataId),{selectedIndices:h}=OU(u,c,i,o,l);return n.makeTensorInfo([h.length],"int32",new Int32Array(h))}var LU={kernelName:fo,backendName:"webgl",kernelFunc:zU},PU=Rr.nonMaxSuppressionV4Impl;function WU(e){C.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:r}=e,{boxes:a,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l,padToMaxOutputSize:u}=r,c=n.readSync(a.dataId),h=n.readSync(s.dataId),{selectedIndices:d,validOutputs:p}=PU(c,h,i,o,l,u);return[n.makeTensorInfo([d.length],"int32",new Int32Array(d)),n.makeTensorInfo([],"int32",new Int32Array([p]))]}var BU={kernelName:mo,backendName:"webgl",kernelFunc:WU},VU=Rr.nonMaxSuppressionV5Impl;function UU(e){C.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:r}=e,{boxes:a,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l,softNmsSigma:u}=r,c=n.readSync(a.dataId),h=n.readSync(s.dataId),d=i,p=o,f=l,m=u,{selectedIndices:A,selectedScores:y}=VU(c,h,d,p,f,m);return[n.makeTensorInfo([A.length],"int32",new Int32Array(A)),n.makeTensorInfo([y.length],"float32",new Float32Array(y))]}var jU={kernelName:Ao,backendName:"webgl",kernelFunc:UU},HU=class{constructor(e,t,n,r){this.variableNames=["indices"],this.outputShape=[e,t],this.userCode=` void main() { ivec2 coords = getOutputCoords(); int index = round(getIndices(coords.x)); setOutput(mix(float(${r}), float(${n}), float(index == coords.y))); } `}},GU=e=>{let{inputs:t,backend:n,attrs:r}=e,{indices:a}=t,{depth:s,onValue:i,offValue:o}=r,l=v.sizeFromShape(a.shape),u=new HU(l,s,i,o),c=ye({inputs:{x:a},backend:n,attrs:{shape:[l]}}),h=n.runWebGLProgram(u,[c],a.dtype);n.disposeIntermediateTensorInfo(c);let d=[...a.shape,s],p=ye({inputs:{x:h},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(h),p},qU={kernelName:ws,backendName:"webgl",kernelFunc:GU};function rp(e){let{inputs:t,backend:n}=e,{x:r}=t;if(r.dtype==="complex64"){let a=tc({inputs:{input:r},backend:n}),s=rp({inputs:{x:a},backend:n}),i=np({inputs:{input:r},backend:n}),o=rp({inputs:{x:i},backend:n}),l=Ma({inputs:{real:s,imag:o},backend:n});return n.disposeIntermediateTensorInfo(a),n.disposeIntermediateTensorInfo(s),n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(o),l}else return $A({attrs:{shape:r.shape,dtype:r.dtype,value:r.dtype==="string"?"":0},backend:n})}var XU={kernelName:Mo,backendName:"webgl",kernelFunc:rp};function W_(e){let{inputs:t,backend:n}=e,{x:r}=t;if(r.dtype==="string")throw new Error("onesLike is not supported under string dtype");if(r.dtype==="complex64"){let a=tc({inputs:{input:r},backend:n}),s=W_({inputs:{x:a},backend:n}),i=np({inputs:{input:r},backend:n}),o=rp({inputs:{x:i},backend:n}),l=Ma({inputs:{real:s,imag:o},backend:n});return n.disposeIntermediateTensorInfo(a),n.disposeIntermediateTensorInfo(s),n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(o),l}else return $A({attrs:{shape:r.shape,dtype:r.dtype,value:1},backend:n})}var KU={kernelName:yo,backendName:"webgl",kernelFunc:W_};function ZU(e){let{inputs:t,backend:n,attrs:r}=e,{axis:a}=r;if(t.length===1)return FA({inputs:{input:t[0]},backend:n,attrs:{dim:a}});let s=t[0].shape,i=t[0].dtype;t.forEach(c=>{v.assertShapesMatch(s,c.shape,"All tensors passed to stack must have matching shapes"),v.assert(i===c.dtype,()=>"All tensors passed to stack must have matching dtypes")});let o=[],l=t.map(c=>{let h=FA({inputs:{input:c},backend:n,attrs:{dim:a}});return o.push(h),h}),u=x_({inputs:l,backend:n,attrs:{axis:a}});return o.forEach(c=>n.disposeIntermediateTensorInfo(c)),u}var YU={kernelName:go,backendName:"webgl",kernelFunc:ZU},JU=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=t.map((l,u)=>l[0]+e[u]+l[1]);let r=e.length,a=lt(r),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,r);if(r===1){this.userCode=` int start = ${s}; int end = ${i}; void main() { int outC = getOutputCoords(); if (outC < start || outC >= end) { setOutput(float(${n})); } else { setOutput(getX(outC - start)); } } `;return}this.userCode=` ${a} start = ${a}(${s}); ${a} end = ${a}(${i}); void main() { ${a} outC = getOutputCoords(); if (any(lessThan(outC, start)) || any(greaterThanEqual(outC, end))) { setOutput(float(${n})); } else { ${a} coords = outC - start; setOutput(getX(${o})); } } `}},QU=class{constructor(e,t,n){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t.map((f,m)=>f[0]+e[m]+f[1]);let r=e.length,a=lt(r),s=t.map(f=>f[0]).join(","),i=t.map((f,m)=>f[0]+e[m]).join(","),o=cn("rc",r),l=cn("source",r),u=`${o[r-1]} < ${this.outputShape[r-1]}`,c=r===1?"source":`vec2(${l.slice(-2).join()})`,h=[`${a} rc = outputLoc;`,`${o[r-1]} += 1; if(${u}) { `,r===1?"":`} rc = outputLoc; ${o[r-2]} += 1; if(${o[r-2]} < ${this.outputShape[r-2]}) {`,r===1?"":` ${o[r-1]} += 1; if(${u}) {`],d=r===1?"rc < start || rc >= end":"any(lessThan(rc, start)) || any(greaterThanEqual(rc, end))",p="";for(let f=0,m=r===1?2:4;f{let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{paddings:s,constantValue:i}=r,o=Y().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new QU(a.shape,s,i):new JU(a.shape,s,i);return n.runWebGLProgram(o,[a],a.dtype)},ej={kernelName:_s,backendName:"webgl",kernelFunc:B_},tj=` 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); `,nj=` // isModRound1 has 1 for components with round(mod(b, 2.0)) == 1, 0 otherwise. vec4 isModRound1 = vec4(equal(round(mod(b, 2.0)), ivec4(1))); vec4 multiplier = sign(a) * isModRound1 + (vec4(1.0) - isModRound1); vec4 result = multiplier * pow(abs(a), b); // Ensure that a^0 = 1, including 0^0 = 1 as this correspond to TF and JS bvec4 isExpZero = equal(b, vec4(0.0)); result.r = isExpZero.r ? 1.0 : result.r; result.g = isExpZero.g ? 1.0 : result.g; result.b = isExpZero.b ? 1.0 : result.b; result.a = isExpZero.a ? 1.0 : result.a; vec4 isNaN = vec4(lessThan(a, vec4(0.0))) * vec4(lessThan(floor(b), b)); `+Zd+` return result; `,rj=Qt({opSnippet:tj,packedOpSnippet:nj}),aj={kernelName:bs,backendName:"webgl",kernelFunc:rj};function sj(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{axis:s,keepDims:i}=r,o=a.shape.length,l=[],u=v.parseAxisParam(s,a.shape),c=u,h=C.getAxesPermutation(c,o),d=a;h!=null&&(d=wn({inputs:{x:a},backend:n,attrs:{perm:h}}),c=C.getInnerMostAxes(c.length,o),l.push(d)),C.assertAxesAreInnerMostDims("prod",c,o);let p;if(n.shouldExecuteOnCPU([d])){let f=n.texData.get(d.dataId).values,{outVals:m,outShape:A,outDtype:y}=Sz(d.shape,d.dtype,f,c);p=n.makeTensorInfo(A,y,m)}else{let[f,m]=C.computeOutAndReduceShapes(d.shape,c),A=v.sizeFromShape(m),y=ye({inputs:{x:d},backend:n,attrs:{shape:[-1,A]}}),g=zh(a.dtype),w=ui(y,g,"prod",n);p=ye({inputs:{x:w},backend:n,attrs:{shape:f}}),l.push(y),l.push(w)}if(i){l.push(p);let f=C.expandShapeToKeepDim(p.shape,u);p=ye({inputs:{x:p},backend:n,attrs:{shape:f}})}return l.forEach(f=>n.disposeIntermediateTensorInfo(f)),p}var ij={kernelName:xo,backendName:"webgl",kernelFunc:sj},V_=e=>{let{backend:t,attrs:n}=e,{start:r,stop:a,step:s,dtype:i}=n,o=Tz(r,a,s,i);return t.makeTensorInfo([o.length],i,o)},oj={kernelName:ru,backendName:"webgl",kernelFunc:V_},lj="return 1.0 / x;",uj=Xe({opSnippet:lj}),cj={kernelName:wo,backendName:"webgl",kernelFunc:uj},hj=mr+` return (x < 0.0) ? 0.0 : x; `,dj=` 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; `,pj=Xe({opSnippet:hj,packedOpSnippet:dj}),fj={kernelName:ks,backendName:"webgl",kernelFunc:pj},mj=mr+` return (x < 0.0) ? 0.0 : min(6.0, x); `,Aj=` 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; `,yj=Xe({opSnippet:mj,packedOpSnippet:Aj}),gj={kernelName:Ns,backendName:"webgl",kernelFunc:yj},xj=class{constructor(e,t,n,r,a){this.variableNames=["A"],this.outputShape=[];let[s,i,o,l]=e;this.outputShape=[s,t,n,l];let u=[r&&t>1?i-1:i,r&&n>1?o-1:o],c=[r&&t>1?t-1:t,r&&n>1?n-1:n],h;a?h="(vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC - vec2(0.5)":h="vec2(yRC) * effectiveInputOverOutputRatioRC",this.userCode=` const vec2 effectiveInputOverOutputRatioRC = vec2( ${u[0]/c[0]}, ${u[1]/c[1]}); const vec2 inputShapeRC = vec2(${i}.0, ${o}.0); void main() { ivec4 coords = getOutputCoords(); int b = coords[0]; int d = coords[3]; ivec2 yRC = coords.yz; // Fractional source index. vec2 sourceFracIndexRC = ${h}; // Compute the four integer indices. ivec2 sourceFloorRC = ivec2(max(sourceFracIndexRC, vec2(0.0))); ivec2 sourceCeilRC = ivec2( min(inputShapeRC - 1.0, ceil(sourceFracIndexRC))); float topLeft = getA(b, sourceFloorRC.x, sourceFloorRC.y, d); float bottomLeft = getA(b, sourceCeilRC.x, sourceFloorRC.y, d); float topRight = getA(b, sourceFloorRC.x, sourceCeilRC.y, d); float bottomRight = getA(b, sourceCeilRC.x, sourceCeilRC.y, d); vec2 fracRC = sourceFracIndexRC - vec2(sourceFloorRC); float top = topLeft + (topRight - topLeft) * fracRC.y; float bottom = bottomLeft + (bottomRight - bottomLeft) * fracRC.y; float newValue = top + (bottom - top) * fracRC.x; setOutput(newValue); } `}},wj=class{constructor(e,t,n,r,a){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=[r&&t>1?i-1:i,r&&n>1?o-1:o],c=[r&&t>1?t-1:t,r&&n>1?n-1:n],h;a?h="(vec3(yRC) + vec3(0.5)) * effectiveInputOverOutputRatioRC - vec3(0.5)":h="vec3(yRC) * effectiveInputOverOutputRatioRC",this.userCode=` const vec3 effectiveInputOverOutputRatioRC = vec3( ${u[0]/c[0]}, ${u[1]/c[1]}, ${u[1]/c[1]}); const vec3 inputShapeRC = vec3(${i}.0, ${o}.0, ${o}.0); float getAValue(int b, int r, int c, int d) { return getChannel(getA(b, r, c, d), vec2(c, d)); } void main() { ivec4 coords = getOutputCoords(); int b = coords[0]; int d = coords[3]; // Calculate values for next column in yRC.z. ivec3 yRC = coords.yzz + ivec3(0, 0, 1); // Fractional source index. vec3 sourceFracIndexRC = ${h}; // Compute the four integer indices. ivec3 sourceFloorRC = ivec3(max(sourceFracIndexRC, vec3(0.0))); ivec3 sourceCeilRC = ivec3( min(inputShapeRC - 1.0, ceil(sourceFracIndexRC))); // Should we calculate next column and row elements in 2x2 packed cell. bool hasNextCol = d < ${l-1}; bool hasNextRow = coords.z < ${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 _j(e){let{inputs:t,backend:n,attrs:r}=e,{images:a}=t,{alignCorners:s,halfPixelCenters:i,size:o}=r,[l,u]=o,c=Y().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new wj(a.shape,l,u,s,i):new xj(a.shape,l,u,s,i);return n.runWebGLProgram(c,[a],"float32")}var bj={kernelName:Is,backendName:"webgl",kernelFunc:_j},vj=class{constructor(e,t,n){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t;let[,r,a]=t,[,s,i]=e,o=[n&&s>1?r-1:r,n&&i>1?a-1:a],l=[n&&s>1?s-1:s,n&&i>1?i-1:i],u=o[0]/l[0],c=o[1]/l[1],h=1/u,d=1/c,p=Math.ceil(h)*2+2,f=Math.ceil(d)*2+2;this.userCode=` void main() { ivec4 coords = getOutputCoords(); int b = coords[0]; int d = coords[3]; int r = coords[1]; int c = coords[2]; float accumulator = 0.0; const float heightScale = float(${u}); const float widthScale = float(${c}); const float invHeightScale = float(${h}); const float invWidthScale = float(${d}); const int winHeight = int(${p}); const int winWidth = int(${f}); // Compute bounds for where in dy we will look float startRLerp = floor(float(r) * invHeightScale); int startDyR = int(startRLerp - float(winHeight / 2)); float startCLerp = floor(float(c) * invWidthScale); int startDyC = int(startCLerp - float(winWidth / 2)); // Loop over dy for (int dyROffset = 0; dyROffset < winHeight; dyROffset++) { int dyR = dyROffset + startDyR; // Guard against the window exceeding the bounds of dy if (dyR < 0 || dyR >= ${s}) { continue; } for (int dyCOffset = 0; dyCOffset < winWidth; dyCOffset++) { int dyC = dyCOffset + startDyC; // Guard against the window exceeding the bounds of dy if (dyC < 0 || dyC >= ${i}) { continue; } float dxR = float(dyR) * heightScale; int topDxRIndex = int(floor(dxR)); int bottomDxRIndex = int(min(ceil(dxR), ${r-1}.0)); float dxRLerp = dxR - float(topDxRIndex); float inverseDxRLerp = 1.0 - dxRLerp; float dxC = float(dyC) * widthScale; int leftDxCIndex = int(floor(dxC)); int rightDxCIndex = int(min(ceil(dxC), ${a-1}.0)); float dxCLerp = dxC - float(leftDxCIndex); float inverseDxCLerp = 1.0 - dxCLerp; if (r == topDxRIndex && c == leftDxCIndex) { // topLeft accumulator += getDy(b, dyR, dyC, d) * inverseDxRLerp * inverseDxCLerp; } if (r == topDxRIndex && c == rightDxCIndex) { // topRight accumulator += getDy(b, dyR, dyC, d) * inverseDxRLerp * dxCLerp; } if (r == bottomDxRIndex && c == leftDxCIndex) { // bottomLeft accumulator += getDy(b, dyR, dyC, d) * dxRLerp * inverseDxCLerp; } if (r == bottomDxRIndex && c == rightDxCIndex) { // bottomRight accumulator += getDy(b, dyR, dyC, d) * dxRLerp * dxCLerp; } } } // End loop over dy setOutput(accumulator); } `}};function kj(e){let{inputs:t,backend:n,attrs:r}=e,{images:a,dy:s}=t,{alignCorners:i}=r,o=new vj(s.shape,a.shape,i);return n.runWebGLProgram(o,[s],s.dtype)}var Ij={kernelName:Fh,backendName:"webgl",kernelFunc:kj},Nj=class{constructor(e,t,n,r,a){this.variableNames=["A"],this.outputShape=[];let[s,i,o,l]=e;this.outputShape=[s,t,n,l];let u=[r&&t>1?i-1:i,r&&n>1?o-1:o],c=[r&&t>1?t-1:t,r&&n>1?n-1:n],h=r?"0.5":"0.0",d;a?d="max((vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC, vec2(0.0))":d="vec2(yRC) * effectiveInputOverOutputRatioRC",this.userCode=` const vec2 effectiveInputOverOutputRatioRC = vec2( ${u[0]/c[0]}, ${u[1]/c[1]}); const vec2 inputShapeRC = vec2(${i}.0, ${o}.0); void main() { ivec4 coords = getOutputCoords(); int b = coords[0]; int d = coords[3]; ivec2 yRC = coords.yz; // Fractional source index. vec2 sourceFracIndexRC = ${d}; // Compute the coordinators of nearest neighbor point. ivec2 sourceNearestRC = ivec2( min(inputShapeRC - 1.0, floor(sourceFracIndexRC + ${h}))); float newValue = getA(b, sourceNearestRC.x, sourceNearestRC.y, d); setOutput(newValue); } `}};function Sj(e){let{inputs:t,backend:n,attrs:r}=e,{images:a}=t,{alignCorners:s,halfPixelCenters:i,size:o}=r,[l,u]=o,c=new Nj(a.shape,l,u,s,i);return n.runWebGLProgram(c,[a],a.dtype)}var Tj={kernelName:au,backendName:"webgl",kernelFunc:Sj},Ej=class{constructor(e,t,n){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t;let[,r,a]=t,[,s,i]=e,o=[n&&s>1?r-1:r,n&&i>1?a-1:a],l=[n&&s>1?s-1:s,n&&i>1?i-1:i],u=o[0]/l[0],c=o[1]/l[1],h=1/u,d=1/c,p=Math.ceil(h)*2+2,f=Math.ceil(d)*2+2;this.userCode=` void main() { ivec4 coords = getOutputCoords(); int b = coords[0]; int d = coords[3]; int r = coords[1]; int c = coords[2]; float accumulator = 0.0; const float heightScale = float(${u}); const float widthScale = float(${c}); const float invHeightScale = float(${h}); const float invWidthScale = float(${d}); const int winHeight = int(${p}); const int winWidth = int(${f}); // Compute bounds for where in dy we will look float startRLerp = floor(float(r) * invHeightScale); int startDyR = int(floor(startRLerp - float(winHeight / 2))); float startCLerp = floor(float(c) * invWidthScale); int startDyC = int(floor(startCLerp - float(winWidth / 2))); // Loop over dy for (int dyROffset = 0; dyROffset < winHeight; dyROffset++) { int dyR = dyROffset + startDyR; // Guard against the window exceeding the bounds of dy if (dyR < 0 || dyR >= ${s}) { continue; } for (int dyCOffset = 0; dyCOffset < winWidth; dyCOffset++) { int dyC = dyCOffset + startDyC; // Guard against the window exceeding the bounds of dy if (dyC < 0 || dyC >= ${i}) { continue; } float sourceFracRow = float(${o[0]}) * (float(dyR) / float(${l[0]})); float sourceFracCol = float(${o[1]}) * (float(dyC) / float(${l[1]})); int sourceNearestRow = int(min( float(int(${r}) - 1), ${n} ? float(round(sourceFracRow)) : float(floor(sourceFracRow)))); int sourceNearestCol = int(min( float(int(${a}) - 1), ${n} ? float(round(sourceFracCol)) : float(floor(sourceFracCol)))); if (r == sourceNearestRow && c == sourceNearestCol) { accumulator += getDy(b, dyR, dyC, d); } } } // End loop over dy setOutput(accumulator); } `}};function Cj(e){let{inputs:t,backend:n,attrs:r}=e,{images:a,dy:s}=t,{alignCorners:i}=r,o=new Ej(s.shape,a.shape,i);return n.runWebGLProgram(o,[s],s.dtype)}var Rj={kernelName:Rh,backendName:"webgl",kernelFunc:Cj},Fj=class{constructor(e,t){this.variableNames=["x"];let n=e.length;if(n>4)throw new Error(`WebGL backend: Reverse of rank-${n} tensor is not yet supported`);if(this.outputShape=e,n===1){this.userCode=` void main() { int coord = getOutputCoords(); setOutput(getX(${e[0]} - coord - 1)); } `;return}let r=i=>t.indexOf(i)!==-1&&e[i]!==1?`${e[i]} - coords[${i}] - 1`:`coords[${i}]`,a=e.map((i,o)=>r(o)).join(","),s=lt(n);this.userCode=` void main() { ${s} coords = getOutputCoords(); setOutput(getX(${a})); } `}},$j=class{constructor(e,t){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0;let n=e.length;if(n>4)throw new Error(`WebGL backend: Reverse of rank-${n} tensor is not yet supported`);this.outputShape=e;let r=cn("rc",n),a=`${r[n-1]} + 1 < ${this.outputShape[n-1]}`,s=`${r[n-2]} + 1 < ${this.outputShape[n-2]}`,i=lt(n);n===1?this.userCode=` void main(){ int rc = getOutputCoords(); vec4 result = vec4(0.); result.r = getChannel(getX(${e[0]} - rc - 1), ${e[0]} - rc - 1); if(${a}){ result.g = getChannel(getX(${e[0]} - (rc + 1) - 1), ${e[0]} - (rc + 1) - 1); } setOutput(result); } `:this.userCode=` void main() { ${i} rc = getOutputCoords(); vec4 result = vec4(0.); result.r = ${o(r.slice())}; if(${a}){ result.g = ${l(r.slice())}; } if(${s}) { result.b = ${u(r.slice())}; if(${a}) { result.a = ${c(r.slice())}; } } setOutput(result); } `;function o(p){return h(p)}function l(p){return p[n-1]="("+p[n-1]+" + 1)",h(p)}function u(p){return p[n-2]="("+p[n-2]+" + 1)",h(p)}function c(p){return p[n-1]="("+p[n-1]+" + 1)",p[n-2]="("+p[n-2]+" + 1)",h(p)}function h(p){let f=e.map((y,g)=>d(g,p)),m=f.join(","),A=f.slice(-2).join(",");return`getChannel(getX(${m}), vec2(${A}))`}function d(p,f){return t.indexOf(p)!==-1&&e[p]!==1?`${e[p]} - ${f[p]} - 1`:`${f[p]}`}}};function Mj(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{dims:s}=r,i=a.shape.length,o=v.parseAxisParam(s,a.shape);if(i===0)return Fn({inputs:{x:a},backend:n});let l=Y().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new $j(a.shape,o):new Fj(a.shape,o);return n.runWebGLProgram(l,[a],a.dtype)}var Dj={kernelName:Ss,backendName:"webgl",kernelFunc:Mj},Oj=class{constructor(e,t,n,r){this.variableNames=["Image"],this.outputShape=[];let a=e[1],s=e[2],i=Math.sin(t).toFixed(3),o=Math.cos(t).toFixed(3);this.outputShape=e;let[l,u]=C.getImageCenter(r,a,s),c=l.toFixed(3),h=u.toFixed(3),d="";typeof n=="number"?d=`float outputValue = ${n.toFixed(2)};`:d=` vec3 fill = vec3(${n.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) - ${c}) * ${o} - (float(y) - ${h}) * ${i}; float coordYFloat = (float(x) - ${c}) * ${i} + (float(y) - ${h}) * ${o}; int coordX = int(round(coordXFloat + ${c})); int coordY = int(round(coordYFloat + ${h})); ${d} if(coordX >= 0 && coordX < ${s} && coordY >= 0 && coordY < ${a}) { outputValue = getImage(coords[0], coordY, coordX, coords[3]); } setOutput(outputValue); } `}},zj={kernelName:Do,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{image:r}=e,{radians:a,fillValue:s,center:i}=t,o=n,l=new Oj(r.shape,a,s,i);return o.runWebGLProgram(l,[r],r.dtype)}},Lj=` // OpenGL ES does not support round function. // The algorithm is based on banker's rounding. float base = floor(x); if ((x - base) < 0.5) { return floor(x); } else if ((x - base) > 0.5) { return ceil(x); } else { if (mod(base, 2.0) == 0.0) { return base; } else { return base + 1.0; } } `,Pj=Xe({opSnippet:Lj}),Wj={kernelName:Ts,backendName:"webgl",kernelFunc:Pj},Bj="return inversesqrt(x);",Vj=Xe({opSnippet:Bj,cpuKernelImpl:Ez}),Uj={kernelName:Es,backendName:"webgl",kernelFunc:Vj},U_=class{constructor(e,t,n,r,a,s,i=!0){this.variableNames=["updates","indices","defaultValue"],this.outputShape=s;let o=lt(a.length),l=lt(s.length),u="";n===1?u="i":n===2&&(u="i, j");let c=`getIndices(${u})`,h="";r===1?h="i":r===2&&(h="i, coords[1]");let d=`getUpdates(${h})`,p=t>1?"strides[j]":"strides";this.userCode=` ${o} strides = ${o}(${a}); void main() { ${l} coords = getOutputCoords(); float sum = 0.0; bool found = false; for (int i = 0; i < ${e}; i++) { int flattenedIndex = 0; for (int j = 0; j < ${t}; j++) { int index = round(${c}); flattenedIndex += index * ${p}; } if (flattenedIndex == coords[0]) { sum += ${d}; found = true; } } setOutput(mix(getDefaultValue(), sum, float(found))); } `}};function jj(e){let{inputs:t,backend:n,attrs:r}=e,{indices:a,updates:s}=t,{shape:i}=r,{sliceRank:o,numUpdates:l,sliceSize:u,strides:c,outputSize:h}=C.calculateShapes(s,a,i),d=[h/u,u];if(h===0)return n.makeTensorInfo(i,a.dtype);let p=ye({inputs:{x:a},backend:n,attrs:{shape:[l,o]}}),f=ye({inputs:{x:s},backend:n,attrs:{shape:[l,u]}}),m=n.makeTensorInfo([],"float32",new Float32Array([0])),A=new U_(l,o,p.shape.length,f.shape.length,c,d),y=n.runWebGLProgram(A,[f,p,m],f.dtype),g=ye({inputs:{x:y},backend:n,attrs:{shape:i}});return n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(f),n.disposeIntermediateTensorInfo(y),n.disposeIntermediateTensorInfo(m),g}var Hj={kernelName:bo,backendName:"webgl",kernelFunc:jj},Gj=class{constructor(e,t,n){this.variableNames=["c","a","b"],this.outputShape=t;let r,a;if(n>4)throw Error(`Where for rank ${n} is not yet supported`);if(n===1)a="resRC",r="resRC";else{let i=["resRC.x","resRC.y","resRC.z","resRC.w"],o=[],l=[];for(let u=0;u= 1.0) { setOutput(getA(${a})); } else { setOutput(getB(${a})); } } `}};function qj(e){let{inputs:t,backend:n}=e,{condition:r,t:a,e:s}=t,i=new Gj(r.shape.length,a.shape,a.shape.length);return n.runWebGLProgram(i,[r,a,s],Jn(a.dtype,s.dtype))}var Xj={kernelName:vo,backendName:"webgl",kernelFunc:qj},Kj=` // Stable and Attracting Fixed Point (0, 1) for Normalized Weights. // see: https://arxiv.org/abs/1706.02515 float scaleAlpha = ${C.SELU_SCALEALPHA}; float scale = ${C.SELU_SCALE}; return (x >= 0.0) ? scale * x : scaleAlpha * (exp(x) - 1.0); `,Zj=Xe({opSnippet:Kj}),Yj={kernelName:ko,backendName:"webgl",kernelFunc:Zj},Jj="return 1.0 / (1.0 + exp(-1.0 * x));",Qj=Xe({opSnippet:Jj}),eH={kernelName:Rs,backendName:"webgl",kernelFunc:Qj},tH=` if (isnan(x)) { return 0.0; } return sign(x); `,nH=Xe({opSnippet:tH}),rH={kernelName:So,backendName:"webgl",kernelFunc:nH},aH=n_+` return sin(x); `,sH=Xe({opSnippet:aH}),iH={kernelName:Cs,backendName:"webgl",kernelFunc:sH},oH=` float e2x = exp(x); return (e2x - 1.0 / e2x) / 2.0; `,lH=Xe({opSnippet:oH}),uH={kernelName:No,backendName:"webgl",kernelFunc:lH},cH=` float epsilon = 1.1920928955078125e-7; float threshold = log(epsilon) + 2.0; bool too_large = x > -threshold; bool too_small = x < threshold; float result; float exp_x = exp(x); if (too_large){ result = x; } else if (too_small){ result = exp_x; } else{ result = log(exp_x + 1.0); } return result; `,hH=Xe({opSnippet:cH}),dH={kernelName:To,backendName:"webgl",kernelFunc:hH},pH=e=>{let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{blockShape:s,paddings:i}=r;v.assert(a.shape.length<=4,()=>"spaceToBatchND for rank > 4 with a WebGL backend not implemented yet");let o=s.reduce((y,g)=>y*g),l=[[0,0]];l.push(...i);for(let y=1+s.length;yn.disposeIntermediateTensorInfo(y)),A},fH={kernelName:su,backendName:"webgl",kernelFunc:pH};function mH(e){let{inputs:t,backend:n,attrs:r}=e,{sparseIndices:a,sparseValues:s,defaultValue:i}=t,{outputShape:o}=r,{sliceRank:l,numUpdates:u,strides:c,outputSize:h}=C.calculateShapes(s,a,o),d=!1,p=new U_(u,l,a.shape.length,s.shape.length,c,[h,1],d),f=n.runWebGLProgram(p,[s,a,i],s.dtype),m=ye({inputs:{x:f},backend:n,attrs:{shape:o}});return n.disposeIntermediateTensorInfo(f),m}var AH={kernelName:$h,backendName:"webgl",kernelFunc:mH};function yH(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{numOrSizeSplits:s,axis:i}=r,o=v.parseAxisParam(i,a.shape)[0],l=C.prepareSplitSize(a,s,o),u=a.shape.length,c=new Array(u).fill(0),h=a.shape.slice();return l.map(d=>{let p=[...h];p[o]=d;let f=ec({inputs:{x:a},backend:n,attrs:{begin:c,size:p}});return c[o]+=d,f})}var gH={kernelName:Eo,backendName:"webgl",kernelFunc:yH},xH="return sqrt(x);",wH=Xe({opSnippet:xH}),_H={kernelName:Fs,backendName:"webgl",kernelFunc:wH},bH="return x * x;",vH=Xe({opSnippet:bH}),kH={kernelName:iu,backendName:"webgl",kernelFunc:vH},j_="return (a - b) * (a - b);",IH=Qt({opSnippet:j_,packedOpSnippet:j_}),NH={kernelName:Ds,backendName:"webgl",kernelFunc:IH};function SH({inputs:e,attrs:t,backend:n}){let{x:r}=e,a=mr+` return x > 0.0 ? 1.0 : float(${t.alpha}); `,s=new $a(r.shape,a);return n.runWebGLProgram(s,[r],r.dtype)}var TH={kernelName:xa,backendName:"webgl",kernelFunc:SH},EH=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=n;let r=n.length,a=lt(n.length),s=lt(n.length),i="";if(r===1)i="coords * strides + begin";else{let o=0;i=n.map((l,u)=>(o++,n.length===1?`coords * strides[${u}] + begin[${u}]`:`coords[${o-1}] * strides[${u}] + begin[${u}]`)).join(",")}this.userCode=` ${a} begin = ${a}(${e}); ${a} strides = ${a}(${t}); void main() { ${s} coords = getOutputCoords(); setOutput(getX(${i})); } `}};function CH(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{begin:s,end:i,strides:o,beginMask:l,endMask:u,ellipsisMask:c,newAxisMask:h,shrinkAxisMask:d}=r,{nonStrided:p,$begin:f,$strides:m,size:A,newShape:y,outShape:g}=sn.sliceInfo(a.shape,s,i,o,l,u,c,h,d),w=ye({inputs:{x:a},backend:n,attrs:{shape:y}}),_;if(p){let x=ec({inputs:{x:w},backend:n,attrs:{begin:f,size:A}});_=ye({inputs:{x},backend:n,attrs:{shape:g}}),n.disposeIntermediateTensorInfo(x)}else if(g.some(x=>x===0))_=n.makeTensorInfo(g,a.dtype,[]);else if(n.shouldExecuteOnCPU([w])){let x=n.texData.get(w.dataId).values,N=We(w.shape,w.dtype,x),T=Rz(g,N,m,f);_=n.makeTensorInfo(g,w.dtype,T.values)}else{let x=new EH(f,m,g);_=n.runWebGLProgram(x,[w],w.dtype)}let b=ye({inputs:{x:_},backend:n,attrs:{shape:g}});return n.disposeIntermediateTensorInfo(w),n.disposeIntermediateTensorInfo(_),b}var RH={kernelName:Co,backendName:"webgl",kernelFunc:CH},FH="return tan(x);",$H=Xe({opSnippet:FH}),MH={kernelName:Ro,backendName:"webgl",kernelFunc:$H},DH=` float e2x = exp(-2.0 * abs(x)); return sign(x) * (1.0 - e2x) / (1.0 + e2x); `,OH=Xe({opSnippet:DH}),zH={kernelName:zs,backendName:"webgl",kernelFunc:OH},PH=class{constructor(e,t){this.variableNames=["A"];let n=new Array(e.length);for(let s=0;s5)throw Error(`Tile for rank ${t} is not yet supported`);if(t===1)return`imod(resRC, ${e[0]})`;let n=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u"],r=[];for(let a=0;av.decodeString(c)),l=We(a.shape,a.dtype,o),u=$z(l,s);return n.makeTensorInfo(u.shape,u.dtype,u.values)}let i=new PH(a.shape,s);return n.runWebGLProgram(i,[a],a.dtype)}var WH={kernelName:ga,backendName:"webgl",kernelFunc:H_};function BH(e){let{inputs:t,backend:n,attrs:r}=e,{x:a}=t,{k:s,sorted:i}=r,o=n.readSync(a.dataId),[l,u]=Mz(o,a.shape,a.dtype,s,i);return[n.makeTensorInfo(l.shape,l.dtype,l.values),n.makeTensorInfo(u.shape,u.dtype,u.values)]}var VH={kernelName:Fo,backendName:"webgl",kernelFunc:BH};function UH(e){let{inputs:t,attrs:n,backend:r}=e,{axis:a}=n,{x:s}=t;hl(s,"unique"),console.warn("WARNING: ","UI might be locked temporarily as data is being downloaded");let i=r.readSync(s.dataId),{outputValues:o,outputShape:l,indices:u}=Dz(i,a,s.shape,s.dtype);return[r.makeTensorInfo(l,s.dtype,o),r.makeTensorInfo([u.length],"int32",u)]}var jH={kernelName:Mh,backendName:"webgl",kernelFunc:UH};function HH(e){let{inputs:t,backend:n,attrs:r}=e,{value:a}=t,{axis:s}=r;s<0&&(s+=a.shape.length);let i=a,o=i.shape.length,l=a.shape[s],u=new Array(o-1),c=0;for(let m=0;mn.disposeIntermediateTensorInfo(m)),f}var GH={kernelName:$o,backendName:"webgl",kernelFunc:HH},qH=class{constructor(e,t){this.variableNames=["x","segmentIds"];let n=e.windowSize,r=e.batchSize,a=e.inSize,s=e.numSegments,i=s*Math.ceil(a/n);this.outputShape=[r,i];let o="0.0",l="sumValue",u=Math.floor(n/4)*4,c=n%4,h=` sumValue += dot(values, segFilter); `,d="";a%n>0&&(d=` if (inIdx < 0 || inIdx >= ${a}) { return initializationValue; } `);let p="";a%n>0&&(p=` if (inIdx < 0 || inIdx >= ${a}) { return -1.0; } `),this.userCode=` const float initializationValue = ${o}; float getValue(int batch, int inIdx) { ${d} return getX(batch, inIdx); } float getSegmentIdAtIndex(int inIdx) { ${p} 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 ); ${h} } int inIdx = inOffset + ${u}; if (${c===1}) { vec4 values = vec4( getValue(batch, inIdx), initializationValue, initializationValue, initializationValue ); int inIdxSeg = int(getSegmentIdAtIndex(inIdx)); vec4 segFilter = vec4( int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0, 0, 0, 0 ); ${h} } else if (${c===2}) { vec4 values = vec4( getValue(batch, inIdx), getValue(batch, inIdx + 1), initializationValue, initializationValue ); vec4 segFilter = vec4( int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0, int(getSegmentIdAtIndex(inIdx + 1)) == currentSeg ? 1 : 0, 0, 0 ); ${h} } else if (${c===3}) { vec4 values = vec4( getValue(batch, inIdx), getValue(batch, inIdx + 1), getValue(batch, inIdx + 2), initializationValue ); vec4 segFilter = vec4( int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0, int(getSegmentIdAtIndex(inIdx + 1)) == currentSeg ? 1 : 0, int(getSegmentIdAtIndex(inIdx + 2)) == currentSeg ? 1 : 0, 0 ); ${h} } setOutput(${l}); } `}};function XH(e){let{inputs:t,backend:n,attrs:r}=e,{x:a,segmentIds:s}=t,{numSegments:i}=r,o=a.shape.length,l=[],u=0,c=C.getAxesPermutation([u],o),h=a;c!=null&&(h=wn({inputs:{x:a},backend:n,attrs:{perm:c}}),l.push(h),u=C.getInnerMostAxes(1,o)[0]);let d=C.segment_util.computeOutShape(h.shape,u,i),p=v.sizeFromShape([h.shape[u]]),f=ye({inputs:{x:h},backend:n,attrs:{shape:[-1,p]}});l.push(f);let m=zh(a.dtype),A=(_,b,x,N,T)=>{let E=_.shape[0],$=_.shape[1],D=C.segment_util.segOpComputeOptimalWindowSize($,T),L={windowSize:D,inSize:$,batchSize:E,numSegments:T},P=new qH(L,b),U=n.compileAndRun(P,[_,x],N);if(l.push(U),U.shape[1]===T)return U;let j=V_({backend:n,attrs:{start:0,stop:T,step:1,dtype:"float32"}}),X=H_({inputs:{x:j},backend:n,attrs:{reps:[$/D]}});return l.push(j),l.push(X),A(U,b,X,N,T)},y=A(f,"unsortedSegmentSum",s,m,i),g=ye({inputs:{x:y},backend:n,attrs:{shape:d}}),w=g;if(c!=null){l.push(g);let _=C.getUndoAxesPermutation(c);w=wn({inputs:{x:w},backend:n,attrs:{perm:_}})}return 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Please use 'channelsLast'.`);let D=r.makeOutput(p.outShape,"float32"),L=r.dataIdMap.get(D.dataId).id;return sb(i,a.shape[0],a.shape[1],a.shape[2],o,f,m,A,y,g,w,$,_,b,x,N,T,E,L),D}var HG={kernelName:rs,backendName:"wasm",setupFunc:UG,kernelFunc:jG},GG=!1,qG=hn(Zi,GG,"bool"),XG=_n(ss);function DA(e){let{inputs:t,attrs:n,backend:r}=e,{input:a}=t,{dim:s}=n,i=a.shape.length,o=a.shape.slice(),l=s;return s<0&&(v.assert(-(i+1)<=s,()=>`Axis must be in the interval [${-(i+1)}, ${i}]`),l=i+s+1),o.splice(l,0,1),Ar({inputs:{x:a},backend:r,attrs:{shape:o}})}var KG={kernelName:Yi,backendName:"wasm",kernelFunc:DA};function ZG(e){let{attrs:{shape:t,value:n,dtype:r},backend:a}=e,s=a.makeOutput(t,r);return a.typedArrayFromHeap(s).fill(n),s}var YG={kernelName:Yl,backendName:"wasm",kernelFunc:ZG},ib;function JG(e){ib=e.wasm.cwrap(Qi,null,["number","number","number","number","number","number"])}function QG(e){let{inputs:t,backend:n}=e,{image:r}=t,a=n.makeOutput(r.shape,r.dtype),s=n.dataIdMap.get(r.dataId).id,i=n.dataIdMap.get(a.dataId).id,[o,l,u,c]=r.shape;return ib(s,o,l,u,c,i),a}var eq={kernelName:Qi,backendName:"wasm",kernelFunc:QG,setupFunc:JG},tq=_n(is),nq=!1,rq=hn(os,nq),ob;function aq(e){ob=e.wasm.cwrap(ls,null,["number","number","number","number","number","number","number"])}function sq(e){let{backend:t,inputs:n,attrs:r}=e,{varianceEpsilon:a}=r,{x:s,mean:i,variance:o,offset:l,scale:u}=n,c=t.dataIdMap.get(s.dataId).id,h=t.dataIdMap.get(i.dataId).id,d=t.dataIdMap.get(o.dataId).id,p=l!=null?t.dataIdMap.get(l.dataId).id:0,f=u!=null?t.dataIdMap.get(u.dataId).id:0,m=t.makeOutput(s.shape,s.dtype);if(v.sizeFromShape(s.shape)===0)return m;let A=t.dataIdMap.get(m.dataId).id;return ob(c,h,d,p,f,a,A),m}var iq={kernelName:ls,backendName:"wasm",setupFunc:aq,kernelFunc:sq},lb;function oq(e){lb=e.wasm.cwrap(Ws,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function lq(e){let{inputs:t,attrs:n,backend:r}=e,{x:a,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:u,dilations:c,dataFormat:h,dimRoundingMode:d,activation:p,leakyreluAlpha:f}=n,m=C.computeConv2DInfo(a.shape,s.shape,l,c,u,d),A=nc[p];if(A==null)throw new Error(`${p} activation not yet supported for FusedConv2D in the wasm backend.`);let y=r.dataIdMap.get(a.dataId).id,g=r.dataIdMap.get(s.dataId).id,w=m.outChannels,_=0;if(i!=null){let Q=r.dataIdMap.get(i.dataId);if(Q.shape.length!==1)throw new Error(`FusedConv2D only supports rank-1 bias but got rank ${Q.shape.length}.`);if(Q.shape[0]!==w)throw new Error(`FusedConv2D bias shape (${Q.shape}) does not match the number of output channels (${w})`);_=Q.id}let b=m.filterHeight,x=m.filterWidth,N=m.padInfo.top,T=m.padInfo.right,E=m.padInfo.bottom,$=m.padInfo.left,D=m.dilationHeight,L=m.dilationWidth,P=m.strideHeight,U=m.strideWidth,j=m.inChannels,X=m.padInfo.type==="SAME"?1:0,G=m.batchSize,ee=m.inHeight,J=m.inWidth;if(h!=="NHWC")throw new Error(`wasm backend FusedConv2D does not support dataFormat:'${h}'. 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Please use 'NHWC'.`);let se=r.makeOutput(m.outShape,"float32"),te=r.dataIdMap.get(se.dataId).id,le=o==null?0:r.dataIdMap.get(o.dataId).id;return ub(y,G,ee,J,g,b,x,_,N,T,E,$,X,D,L,P,U,j,w,A,le,f||0,te),se}var dq={kernelName:Bs,backendName:"wasm",setupFunc:cq,kernelFunc:hq},cb;function pq(e){cb=e.wasm.cwrap(to,null,["number","number","number","number","number","number","array","number"])}function fq(e){let{backend:t,inputs:n}=e,{params:r,indices:a}=n,[s,i,o,l]=Nf.prepareAndValidate(r,a),u=t.makeOutput(s,r.dtype);if(i===0)return u;let c=a.shape,h=c[c.length-1],d=t.dataIdMap.get(r.dataId).id,p=t.dataIdMap.get(a.dataId).id,f=new Uint8Array(new Int32Array(l).buffer),m=t.dataIdMap.get(u.dataId).id;return cb(d,$n[r.dtype],p,i,h,o,f,m),u}var mq={kernelName:to,backendName:"wasm",setupFunc:pq,kernelFunc:fq},hb;function Aq(e){hb=e.wasm.cwrap("Gather",null,["number","number","array","number","number","number","array","number"])}function yq(e){let{backend:t,inputs:n,attrs:r}=e,{x:a,indices:s}=n,{axis:i,batchDims:o}=r,l=v.parseAxisParam(i,a.shape)[0],u=C.segment_util.collectGatherOpShapeInfo(a,s,l,o),c=Ar({inputs:{x:a},attrs:{shape:[u.batchSize,u.outerSize,u.dimSize,u.sliceSize]},backend:t}),h=v.sizeFromShape(s.shape),d=Ar({inputs:{x:s},attrs:{shape:[u.batchSize,h/u.batchSize]},backend:t}),p=[u.batchSize,u.outerSize,h/u.batchSize,u.sliceSize],f=t.makeOutput(p,a.dtype);if(v.sizeFromShape(a.shape)===0)return f;let m=c.shape.length-1,A=t.dataIdMap.get(c.dataId).id,y=t.dataIdMap.get(d.dataId).id,g=t.dataIdMap.get(f.dataId).id,w=new Uint8Array(new Int32Array(v.computeStrides(c.shape)).buffer),_=new Uint8Array(new Int32Array(v.computeStrides(p)).buffer);return hb(A,$n[a.dtype],w,m,y,u.batchSize,_,g),t.disposeData(c.dataId),t.disposeData(d.dataId),f.shape=u.outputShape,f}var gq={kernelName:eo,backendName:"wasm",setupFunc:Aq,kernelFunc:yq},xq=!1,wq=hn(no,xq,"bool"),_q=!1,bq=hn(us,_q,"bool"),db;function vq(e){db=e.wasm.cwrap(hs,null,["number","number","number"])}function kq(e){let{inputs:{x:t},attrs:{alpha:n},backend:r}=e,a=r.dataIdMap.get(t.dataId).id,s=r.makeOutput(t.shape,t.dtype);if(v.sizeFromShape(t.shape)!==0){let i=r.dataIdMap.get(s.dataId).id;db(a,n,i)}return s}var Iq={kernelName:hs,backendName:"wasm",setupFunc:vq,kernelFunc:kq},Nq=!1,Sq=hn(io,Nq,"bool"),Tq=!1,Eq=hn(oo,Tq,"bool"),Cq=_n(ds),Rq=!1,Fq=hn(uo,Rq,"bool"),pb;function $q(e){pb=e.wasm.cwrap(ps,null,["number, number, number"])}function Mq(e){let{backend:t,inputs:n,attrs:r}=e,{reductionIndices:a,keepDims:s}=r,{x:i}=n,o=t.dataIdMap.get(i.dataId).id,l=i,{transposed:u,axes:c,originalAxes:h,inputWasTransposed:d}=_l(i,a,t);if(d){let g=t.dataIdMap.get(u.dataId).id;l=u,o=g}let p=l.shape.length;C.assertAxesAreInnerMostDims("max",c,p);let[f,m]=C.computeOutAndReduceShapes(l.shape,c),A=v.sizeFromShape(m),y=t.makeOutput(f,i.dtype);if(v.sizeFromShape(l.shape)!==0){let g=t.dataIdMap.get(y.dataId).id;pb(o,A,g)}if(d&&t.disposeData(u.dataId),s){let g=C.expandShapeToKeepDim(y.shape,h);y.shape=g}return y}var Dq={kernelName:ps,backendName:"wasm",setupFunc:$q,kernelFunc:Mq},Oq=!1,zq=hn(fs,Oq),fb;function Lq(e){fb=e.wasm.cwrap(ms,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function Pq(e){let{inputs:t,attrs:n,backend:r}=e,a=t.x,s=r.dataIdMap.get(a.dataId).id,{filterSize:i,strides:o,pad:l,dimRoundingMode:u}=n,c=C.computePool2DInfo(a.shape,i,o,1,l,u),h=c.filterHeight,d=c.filterWidth,p=c.padInfo.top,f=c.padInfo.right,m=c.padInfo.bottom,A=c.padInfo.left,y=c.dilationHeight,g=c.dilationWidth,w=c.strideHeight,_=c.strideWidth,b=c.inChannels,x=c.outChannels;if(c.dataFormat!=="channelsLast")throw new Error(`wasm backend does not support dataFormat:'${c.dataFormat}'. 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_=C.expandShapeToKeepDim(w.shape,d);w.shape=_}return u.dtype!=="float32"&&t.disposeData(g.dataId),w}var Uq={kernelName:As,backendName:"wasm",setupFunc:Bq,kernelFunc:Vq},Ab;function jq(e){Ab=e.wasm.cwrap(ys,null,["number, number, number"])}function Hq(e){let{backend:t,inputs:n,attrs:r}=e,{axis:a,keepDims:s}=r,{x:i}=n,o=t.dataIdMap.get(i.dataId).id,l=o,u=i,{transposed:c,axes:h,originalAxes:d,inputWasTransposed:p}=_l(i,a,t);if(p){let w=t.dataIdMap.get(c.dataId).id;w!==o&&(u=c,l=w)}let f=u.shape.length;C.assertAxesAreInnerMostDims("min",h,f);let[m,A]=C.computeOutAndReduceShapes(u.shape,h),y=v.sizeFromShape(A),g=t.makeOutput(m,u.dtype);if(v.sizeFromShape(u.shape)!==0){let w=t.dataIdMap.get(g.dataId).id;Ab(l,y,w)}if(p&&t.disposeData(c.dataId),s){let w=C.expandShapeToKeepDim(g.shape,d);g.shape=w}return g}var Gq={kernelName:ys,backendName:"wasm",setupFunc:jq,kernelFunc:Hq},qq=!1,Xq=hn(gs,qq),Kq=!0,Zq=hn(xs,Kq),Yq=_n(ho);function OA(e,t){let n=new Int32Array(e.wasm.HEAPU8.buffer,t,4),r=n[0],a=n[1],s=n[2],i=n[3];return e.wasm._free(t),{pSelectedIndices:r,selectedSize:a,pSelectedScores:s,pValidOutputs:i}}var yb;function Jq(e){yb=e.wasm.cwrap(fo,"number",["number","number","number","number","number"])}function Qq(e){let{backend:t,inputs:n,attrs:r}=e,{iouThreshold:a,maxOutputSize:s,scoreThreshold:i}=r,{boxes:o,scores:l}=n,u=t.dataIdMap.get(o.dataId).id,c=t.dataIdMap.get(l.dataId).id,h=yb(u,c,s,a,i),{pSelectedIndices:d,selectedSize:p,pSelectedScores:f,pValidOutputs:m}=OA(t,h);return t.wasm._free(f),t.wasm._free(m),t.makeOutput([p],"int32",d)}var eX={kernelName:fo,backendName:"wasm",setupFunc:Jq,kernelFunc:Qq},gb;function tX(e){gb=e.wasm.cwrap(mo,"number",["number","number","number","number","number","bool"])}function nX(e){let{backend:t,inputs:n,attrs:r}=e,{iouThreshold:a,maxOutputSize:s,scoreThreshold:i,padToMaxOutputSize:o}=r,{boxes:l,scores:u}=n,c=t.dataIdMap.get(l.dataId).id,h=t.dataIdMap.get(u.dataId).id,d=gb(c,h,s,a,i,o),{pSelectedIndices:p,selectedSize:f,pSelectedScores:m,pValidOutputs:A}=OA(t,d);t.wasm._free(m);let y=t.makeOutput([f],"int32",p),g=t.makeOutput([],"int32",A);return[y,g]}var rX={kernelName:mo,backendName:"wasm",setupFunc:tX,kernelFunc:nX},xb;function aX(e){xb=e.wasm.cwrap(Ao,"number",["number","number","number","number","number","number"])}function sX(e){let{backend:t,inputs:n,attrs:r}=e,{iouThreshold:a,maxOutputSize:s,scoreThreshold:i,softNmsSigma:o}=r,{boxes:l,scores:u}=n,c=t.dataIdMap.get(l.dataId).id,h=t.dataIdMap.get(u.dataId).id,d=xb(c,h,s,a,i,o),{pSelectedIndices:p,selectedSize:f,pSelectedScores:m,pValidOutputs:A}=OA(t,d);t.wasm._free(A);let y=t.makeOutput([f],"int32",p),g=t.makeOutput([f],"float32",m);return[y,g]}var iX={kernelName:Ao,backendName:"wasm",setupFunc:aX,kernelFunc:sX},oX=!1,lX=hn(po,oX,"bool"),wb;function uX(e){wb=e.wasm.cwrap(ws,null,["number","number","number","number","number"])}function cX(e){let{inputs:t,backend:n,attrs:r}=e,{indices:a}=t,{depth:s,onValue:i,offValue:o}=r,l=n.makeOutput([...a.shape,s],"int32"),u=n.dataIdMap.get(l.dataId).id,c=n.dataIdMap.get(a.dataId).id;return wb(c,s,i,o,u),l}var hX={kernelName:ws,backendName:"wasm",setupFunc:uX,kernelFunc:cX};function dX(e){let{inputs:{x:t},backend:n}=e,r=n.makeOutput(t.shape,t.dtype);return n.typedArrayFromHeap(r).fill(1),r}var pX={kernelName:yo,backendName:"wasm",kernelFunc:dX};function fX(e){let{inputs:t,backend:n,attrs:r}=e,{axis:a}=r;if(t.length===1)return DA({inputs:{input:t[0]},backend:n,attrs:{dim:a}});let s=t[0].shape,i=t[0].dtype;t.forEach(c=>{v.assertShapesMatch(s,c.shape,"All tensors passed to stack must have matching shapes"),v.assert(i===c.dtype,()=>"All tensors passed to stack must have matching dtypes")});let o=[],l=t.map(c=>{let h=DA({inputs:{input:c},backend:n,attrs:{dim:a}});return o.push(h),h}),u=Q_({inputs:l,backend:n,attrs:{axis:a}});return o.forEach(c=>n.disposeData(c.dataId)),u}var mX={kernelName:go,backendName:"wasm",kernelFunc:fX},_b;function AX(e){_b=e.wasm.cwrap(_s,null,["number","array","number","number","array","array","number","number"])}function yX(e){let{inputs:{x:t},backend:n,attrs:{paddings:r,constantValue:a}}=e,s=r.map((f,m)=>f[0]+t.shape[m]+f[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),c=r.map(f=>f[0]),h=r.map(f=>f[1]),d=new Uint8Array(new Int32Array(c).buffer),p=new Uint8Array(new Int32Array(h).buffer);return _b(i,u,t.shape.length,$n[t.dtype],d,p,a,l),o}var gX={kernelName:_s,backendName:"wasm",kernelFunc:yX,setupFunc:AX},xX=!1,wX=hn(bs,xX),bb;function _X(e){bb=e.wasm.cwrap(vs,null,["number","number","number"])}function bX(e){let{inputs:t,backend:n}=e,{x:r,alpha:a}=t,s=n.dataIdMap.get(r.dataId).id,i=n.dataIdMap.get(a.dataId).id,o=n.makeOutput(r.shape,"float32"),l=n.dataIdMap.get(o.dataId).id;return bb(s,i,l),o}var vX={kernelName:vs,backendName:"wasm",setupFunc:_X,kernelFunc:bX},vb;function kX(e){vb=e.wasm.cwrap(xo,null,["number","number","number","number"])}function IX(e){let{backend:t,inputs:n,attrs:r}=e,{axis:a,keepDims:s}=r,{x:i}=n,o=t.dataIdMap.get(i.dataId).id,l=o,u=i,{transposed:c,axes:h,originalAxes:d,inputWasTransposed:p}=_l(i,a,t),f=h;if(p){let w=t.dataIdMap.get(c.dataId).id;w!==o&&(u=c,l=w,f=C.getInnerMostAxes(f.length,u.shape.length))}C.assertAxesAreInnerMostDims("prod",f,u.shape.length);let[m,A]=C.computeOutAndReduceShapes(u.shape,f),y=v.sizeFromShape(A),g=t.makeOutput(m,u.dtype);if(v.sizeFromShape(u.shape)!==0){let w=t.dataIdMap.get(g.dataId).id;vb(l,y,$n[g.dtype],w)}if(p&&t.disposeData(c.dataId),s){let w=C.expandShapeToKeepDim(g.shape,d);g.shape=w}return g}var NX={kernelName:xo,backendName:"wasm",setupFunc:kX,kernelFunc:IX},SX=e=>{let{backend:t,attrs:n}=e,{start:r,stop:a,step:s,dtype:i}=n,o=aA(r,a,s,i),l=t.makeOutput([o.length],i);return t.typedArrayFromHeap(l).set(o),l},TX={kernelName:ru,backendName:"wasm",kernelFunc:SX},EX=!0,CX=hn(as,EX),RX=_n(ks),FX=_n(Ns),kb;function $X(e){kb=e.wasm.cwrap(Is,null,["number","number","number","number","number","number","number","number","number","number"])}function MX(e){let{backend:t,inputs:n,attrs:r}=e,{images:a}=n,{alignCorners:s,halfPixelCenters:i,size:o}=r,[l,u]=o,[c,h,d,p]=a.shape,f=[c,l,u,p],m=t.dataIdMap.get(a.dataId),A;m.dtype!=="float32"&&(A=ip({backend:t,inputs:{x:a},attrs:{dtype:"float32"}}),m=t.dataIdMap.get(A.dataId));let y=m.id,g=t.makeOutput(f,"float32");if(v.sizeFromShape(a.shape)===0)return g;let w=t.dataIdMap.get(g.dataId).id;return kb(y,c,h,d,p,l,u,s?1:0,i?1:0,w),A!=null&&t.disposeData(A.dataId),g}var DX={kernelName:Is,backendName:"wasm",setupFunc:$X,kernelFunc:MX},Ib;function 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For multi-output layers, use the functional API.");this.checkShape(e),this.outputs=[r],this.inboundNodes[0].outputTensors=this.outputs,this.inboundNodes[0].outputShapes=[this.outputs[0].shape]}this.layers.push(e),this.built=!1}pop(){if(this.layers.length===0)throw new TypeError("There are no layers in the model.");if(this.layers.pop(),this.layers.length===0)this.outputs=[],this.inboundNodes=[],this.outboundNodes=[];else{let e=this.layers.length-1;this.layers[e].outboundNodes=[],this.outputs=[this.layers[e].output],this.inboundNodes[0].outputTensors=this.outputs,this.inboundNodes[0].outputShapes=[this.outputs[0].shape]}}call(e,t){return this.model==null&&this.build(),this.model.call(e,t)}build(e){if(ut(e),this.inputs.length===0||this.outputs.length===0)throw new TypeError("Sequential model cannot be built: model is empty. Add some layers first.");this.model=new Qr({inputs:this.inputs,outputs:this.outputs[0],name:this.name+"_model"}),this.model.trainable=this.trainable,this.supportsMasking=this.model.supportsMasking,this.inputLayers=this.model.inputLayers,this.inputLayersNodeIndices=this.model.inputLayersNodeIndices,this.inputLayersTensorIndices=this.model.inputLayersTensorIndices,this.outputLayers=this.model.outputLayers,this.outputLayersNodeIndices=this.model.outputLayersNodeIndices,this.outputLayersTensorIndices=this.model.outputLayersTensorIndices,this.nodesByDepth=this.model.nodesByDepth,this.containerNodes=this.model.containerNodes,this.outputNames=this.model.outputNames,this.inputNames=this.model.inputNames,this.built=!0}countParams(){return this.built||this.build(),super.countParams()}summary(e,t,n=console.log){this.built||this.build(),super.summary(e,t,n)}setWeights(e){this.model==null&&this.build(),this.model.setWeights(e)}evaluate(e,t,n={}){if(!this.built)throw new gr("The model needs to be compiled before being used.");return this.model.evaluate(e,t,n)}async evaluateDataset(e,t){if(!this.built)throw new gr("The model needs to be compiled before being used.");return this.model.evaluateDataset(e,t)}predict(e,t={}){return this.model==null&&this.build(),this.model.predict(e,t)}predictOnBatch(e){return this.model==null&&this.build(),this.model.predictOnBatch(e)}compile(e){this.build(),this.model.compile(e),this.optimizer_=this.model.optimizer,this.isOptimizerOwned=this.model.isOptimizerOwned,this.loss=this.model.loss,this.metrics=this.model.metrics,this.metricsTensors=this.model.metricsTensors,this.metricsNames=this.model.metricsNames}get optimizer(){return this.model==null?void 0:this.model.optimizer}set optimizer(e){this.model.optimizer=e}async fit(e,t,n={}){if(!this.built)throw new gr("The model needs to be compiled before being used.");return this.model.fit(e,t,n)}async fitDataset(e,t){if(!this.built)throw new gr("The model needs to be compiled before being used.");return this.model.fitDataset(e,t)}async trainOnBatch(e,t){return this.model.trainOnBatch(e,t)}static fromConfig(e,t,n={},r=!1){let a,s={};if(t instanceof Array){if(t[0].className==null||t[0].className==="Merge")throw new B("Legacy serialization format not supported yet.");a=t}else v.assert(t.layers!=null,()=>"When the config data for a Sequential model is not an Array, it must be an Object that contains the 'layers' field."),a=t.layers,delete t.layers,s=t;let i=new e(s);if(!(i instanceof Ko))throw new De(`Sequential.fromConfig called on non-Sequential input: ${i}`);for(let o of a){let l=wr(o,void 0,r);r&&l.setFastWeightInitDuringBuild(!0),i.add(l)}return i}set stopTraining(e){if(this.model==null)throw new B("Cannot set the stopTraining property of a sequential model before it is compiled.");this.model.stopTraining=e}get stopTraining(){if(this.model==null)throw new B("Cannot get the stopTraining property of a sequential model before it is compiled.");return this.model.stopTraining}getConfig(){let e=[];for(let t of this.layers){let n={};n.className=t.getClassName(),n.config=t.getConfig(),e.push(n)}return{name:this.name,layers:e}}};Ko.className="Sequential";re.registerClass(Ko);function f8(e){return new Qr(e)}function m8(e){return new Ko(e)}function A8(e,t){return t==null&&(t={}),Bee(e,t)}function F0(e){return A3(e)}function y8(e,t){lr.registerCallbackConstructor(e,t)}var Mn=class extends re.Serializable{getConfig(){return{}}},B3=class extends Mn{apply(e,t=1){return kJ(e,t)}};B3.className="elu";re.registerClass(B3);var V3=class extends Mn{apply(e){return ad(e)}};V3.className="selu";re.registerClass(V3);var U3=class extends Mn{apply(e){return Cr(e)}};U3.className="relu";re.registerClass(U3);var j3=class extends Mn{apply(e){return V(()=>Ho(6,Cr(e)))}};j3.className="relu6";re.registerClass(j3);var H3=class extends Mn{apply(e){return e}};H3.className="linear";re.registerClass(H3);var G3=class extends Mn{apply(e){return Qn(e)}};G3.className="sigmoid";re.registerClass(G3);var q3=class extends Mn{apply(e){return NJ(e)}};q3.className="hardSigmoid";re.registerClass(q3);var X3=class extends Mn{apply(e){return Uo(e)}};X3.className="softplus";re.registerClass(X3);var K3=class extends Mn{apply(e){return IJ(e)}};K3.className="softsign";re.registerClass(K3);var Z3=class extends Mn{apply(e){return Po(e)}};Z3.className="tanh";re.registerClass(Z3);var vy=class extends Mn{apply(e,t=-1){return Nu(e,t)}};vy.className="softmax";re.registerClass(vy);var Y3=class extends Mn{apply(e,t=-1){return Yh(e,t)}};Y3.className="logSoftmax";re.registerClass(Y3);var J3=class extends Mn{apply(e,t=1){return V(()=>Qn(e.mul(t)).mul(e))}};J3.className="swish";re.registerClass(J3);function Pa(e){return e.getClassName()}function ky(e,t={}){return ic(e,re.SerializationMap.getMap().classNameMap,t,"activation")}function Wa(e){if(e==null){let t={};return t.className="linear",t.config={},ky(t)}if(typeof e=="string"){let t={};return t.className=e,t.config={},ky(t)}else return e instanceof Mn?e:ky(e)}function Iy(e){if(e!=null&&typeof e!="object")throw new Error(`Argument to L1L2 regularizer's constructor is expected to be an object, but received: ${e}`)}var Q3=class extends re.Serializable{},gc=class extends Q3{constructor(e){super();Iy(e),this.l1=e==null||e.l1==null?.01:e.l1,this.l2=e==null||e.l2==null?.01:e.l2,this.hasL1=this.l1!==0,this.hasL2=this.l2!==0}apply(e){return V(()=>{let t=Ct([1]);return this.hasL1&&(t=oe(t,Ee(W(this.l1,Dt(e))))),this.hasL2&&(t=oe(t,Ee(W(this.l2,hc(e))))),t.asScalar()})}getConfig(){return{l1:this.l1,l2:this.l2}}static fromConfig(e,t){return new e({l1:t.l1,l2:t.l2})}};gc.className="L1L2";re.registerClass(gc);function Uee(e){return Iy(e),new gc({l1:e!=null?e.l1:null,l2:0})}function jee(e){return Iy(e),new gc({l2:e!=null?e.l2:null,l1:0})}var e7={l1l2:"L1L2"};function ct(e){return WA(e)}function t7(e,t={}){return ic(e,re.SerializationMap.getMap().classNameMap,t,"regularizer")}function gt(e){if(e==null)return null;if(typeof e=="string"){let t={className:e in e7?e7[e]:e,config:{}};return t7(t)}else return e instanceof Q3?e:t7(e)}var Ny=class extends qe{constructor(e){super(e==null?{}:e);this.supportsMasking=!0,e!=null&&(this.maxValue=e.maxValue)}call(e,t){e=Le(e);let n=Cr(e);return this.maxValue!=null&&(n=gn(n,0,this.maxValue)),n}computeOutputShape(e){return e}getConfig(){let e={maxValue:this.maxValue},t=super.getConfig();return Object.assign(e,t),e}};Ny.className="ReLU";re.registerClass(Ny);var Sy=class extends qe{constructor(e){super(e==null?{}:e);this.DEFAULT_ALPHA=.3,e==null&&(e={}),this.alpha=e.alpha==null?this.DEFAULT_ALPHA:e.alpha}call(e,t){let n=Le(e);return xu(n,this.alpha)}computeOutputShape(e){return e}getConfig(){let e={alpha:this.alpha},t=super.getConfig();return Object.assign(e,t),e}};Sy.className="LeakyReLU";re.registerClass(Sy);var Ty=class extends qe{constructor(e){super(e==null?{}:e);if(this.DEFAULT_ALPHA_INITIALIZER="zeros",e==null&&(e={}),this.supportsMasking=!0,this.alphaInitializer=yt(e.alphaInitializer||this.DEFAULT_ALPHA_INITIALIZER),this.alphaRegularizer=gt(e.alphaRegularizer),this.alphaConstraint=Wt(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 B(`Expected sharedAxes to be a number or an array of numbers, but got ${e.sharedAxes}`)}build(e){e=ut(e);let t=e.slice(1);if(this.sharedAxes!=null)for(let r of this.sharedAxes)t[r-1]=1;this.alpha=this.addWeight("alpha",t,"float32",this.alphaInitializer,this.alphaRegularizer,!0,this.alphaConstraint);let n={};if(this.sharedAxes!=null)for(let r=1;r(Tt(t),t==="channelsFirst"?rt(e,[0,2,3,1]):e))}function n7(e,t){return V(()=>(Tt(t),t==="channelsFirst"?rt(e,[0,2,3,4,1]):e))}function Hee(e,t,n,r=1,a="valid",s,i=1){return V(()=>{if(s==null&&(s=yr()),Tt(s),e.shape.length!==3)throw new B(`The input of a conv1dWithBias operation should be 3, but is ${e.shape.length} instead.`);if(t.shape.length!==3)throw new B(`The kernel for a conv1dWithBias operation should be 3, but is ${t.shape.length} instead`);if(n!=null&&n.shape.length!==1)throw new B(`The bias for a conv1dWithBias operation should be 1, but is ${t.shape.length} instead`);if(s==="channelsFirst"&&(e=rt(e,[0,2,1])),a==="causal")throw new De("The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.");let o=jh(e,t,r,a==="same"?"same":"valid","NWC",i);return n!=null&&(o=Br(o,n)),o})}function r7(e,t,n,r=[1,1],a="valid",s,i,o=null){return V(()=>{if(s==null&&(s=yr()),Tt(s),e.rank!==3&&e.rank!==4)throw new B(`conv2dWithBiasActivation expects input to be of rank 3 or 4, but received ${e.rank}.`);if(t.rank!==3&&t.rank!==4)throw new B(`conv2dWithBiasActivation expects kernel to be of rank 3 or 4, but received ${e.rank}.`);let l=Fy(e,s);if(a==="causal")throw new De("The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.");return l=Ia.conv2d({x:l,filter:t,strides:r,pad:a==="same"?"same":"valid",dilations:i,dataFormat:"NHWC",bias:n,activation:o}),s==="channelsFirst"&&(l=rt(l,[0,3,1,2])),l})}function Gee(e,t,n,r=[1,1,1],a="valid",s,i){return V(()=>{if(s==null&&(s=yr()),Tt(s),e.rank!==4&&e.rank!==5)throw new B(`conv3dWithBias expects input to be of rank 4 or 5, but received ${e.rank}.`);if(t.rank!==4&&t.rank!==5)throw new B(`conv3dWithBias expects kernel to be of rank 4 or 5, but received ${e.rank}.`);let o=n7(e,s);if(a==="causal")throw new De("The support for CAUSAL padding mode in conv3dWithBias is not implemented yet.");return o=Pf(o,t,r,a==="same"?"same":"valid","NDHWC",i),n!=null&&(o=Br(o,n)),s==="channelsFirst"&&(o=rt(o,[0,4,1,2,3])),o})}var $y=class extends qe{constructor(e,t){super(t);if(this.bias=null,this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_BIAS_INITIALIZER="zeros",$y.verifyArgs(t),this.rank=e,Gt(this.rank,"rank"),this.rank!==1&&this.rank!==2&&this.rank!==3)throw new De(`Convolution layer for rank other than 1, 2, or 3 (${this.rank}) is not implemented yet.`);if(this.kernelSize=Sl(t.kernelSize,e,"kernelSize"),this.strides=Sl(t.strides==null?1:t.strides,e,"strides"),this.padding=t.padding==null?"valid":t.padding,qn(this.padding),this.dataFormat=t.dataFormat==null?"channelsLast":t.dataFormat,Tt(this.dataFormat),this.activation=Wa(t.activation),this.useBias=t.useBias==null?!0:t.useBias,this.biasInitializer=yt(t.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.biasConstraint=Wt(t.biasConstraint),this.biasRegularizer=gt(t.biasRegularizer),this.activityRegularizer=gt(t.activityRegularizer),this.dilationRate=Sl(t.dilationRate==null?1:t.dilationRate,e,"dilationRate"),this.rank===1&&Array.isArray(this.dilationRate)&&this.dilationRate.length!==1)throw new B(`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 B(`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 B(`dilationRate must be a number or array of three numbers for 3D convolution, but received ${JSON.stringify(this.dilationRate)}`)}}static verifyArgs(e){if(Pr("kernelSize"in e,"required key 'kernelSize' not in config"),typeof e.kernelSize!="number"&&!VA(e.kernelSize,"number",1,3))throw new B(`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:Pa(this.activation),useBias:this.useBias,biasInitializer:kt(this.biasInitializer),biasRegularizer:ct(this.biasRegularizer),activityRegularizer:ct(this.activityRegularizer),biasConstraint:Pt(this.biasConstraint)},t=super.getConfig();return Object.assign(e,t),e}},xc=class extends $y{constructor(e,t){super(e,t);this.kernel=null,xc.verifyArgs(t),this.filters=t.filters,Gt(this.filters,"filters"),this.kernelInitializer=yt(t.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.kernelConstraint=Wt(t.kernelConstraint),this.kernelRegularizer=gt(t.kernelRegularizer)}build(e){e=ut(e);let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null)throw new B(`The channel dimension of the input should be defined. Found ${e[t]}`);let n=e[t],r=this.kernelSize.concat([n,this.filters]);this.kernel=this.addWeight("kernel",r,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 V(()=>{e=Le(e);let n,r=this.bias==null?null:this.bias.read(),a=Kb(this.activation.getClassName());if(a!=null&&this.rank===2)n=r7(e,this.kernel.read(),r,this.strides,this.padding,this.dataFormat,this.dilationRate,a);else{if(this.rank===1)n=Hee(e,this.kernel.read(),r,this.strides[0],this.padding,this.dataFormat,this.dilationRate[0]);else if(this.rank===2)n=r7(e,this.kernel.read(),r,this.strides,this.padding,this.dataFormat,this.dilationRate);else if(this.rank===3)n=Gee(e,this.kernel.read(),r,this.strides,this.padding,this.dataFormat,this.dilationRate);else throw new De("convolutions greater than 3D are not implemented yet.");this.activation!=null&&(n=this.activation.apply(n))}return n})}computeOutputShape(e){e=ut(e);let t=[],n=this.dataFormat==="channelsLast"?e.slice(1,e.length-1):e.slice(2);for(let a=0;a 0 but got ${JSON.stringify(e.filters)}`)}},wc=class extends xc{constructor(e){super(2,e);wc.verifyArgs(e)}getConfig(){let e=super.getConfig();return delete e.rank,e}static verifyArgs(e){if(typeof e.kernelSize!="number"&&!VA(e.kernelSize,"number",1,2))throw new B(`Conv2D expects config.kernelSize to be number or number[] with length 1 or 2, but received ${JSON.stringify(e.kernelSize)}.`)}};wc.className="Conv2D";re.registerClass(wc);var $p=class extends xc{constructor(e){super(3,e);$p.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 B(`Conv3D expects config.kernelSize to be number or [number, number, number], but received ${JSON.stringify(e.kernelSize)}.`)}};$p.className="Conv3D";re.registerClass($p);var My=class extends wc{constructor(e){super(e);if(this.inputSpec=[new Ut({ndim:4})],this.padding!=="same"&&this.padding!=="valid")throw new B(`Conv2DTranspose currently supports only padding modes 'same' and 'valid', but received padding mode ${this.padding}`)}build(e){if(e=ut(e),e.length!==4)throw new B("Input should have rank 4; Received input shape: "+JSON.stringify(e));let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null)throw new B("The channel dimension of the inputs should be defined. Found `None`.");let n=e[t],r=this.kernelSize.concat([this.filters,n]);this.kernel=this.addWeight("kernel",r,"float32",this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[new Ut({ndim:4,axes:{[t]:n}})],this.built=!0}call(e,t){return V(()=>{let n=Le(e);if(n.shape.length!==4)throw new B(`Conv2DTranspose.call() expects input tensor to be rank-4, but received a tensor of rank-${n.shape.length}`);let r=n.shape,a=r[0],s,i;this.dataFormat==="channelsFirst"?(s=2,i=3):(s=1,i=2);let o=r[s],l=r[i],u=this.kernelSize[0],c=this.kernelSize[1],h=this.strides[0],d=this.strides[1],p=Fp(o,h,u,this.padding),f=Fp(l,d,c,this.padding),m=[a,p,f,this.filters];this.dataFormat!=="channelsLast"&&(n=rt(n,[0,2,3,1]));let A=Hh(n,this.kernel.read(),m,this.strides,this.padding);return this.dataFormat!=="channelsLast"&&(A=rt(A,[0,3,1,2])),this.bias!=null&&(A=Br(A,this.bias.read(),this.dataFormat)),this.activation!=null&&(A=this.activation.apply(A)),A})}computeOutputShape(e){e=ut(e);let t=e.slice(),n,r,a;this.dataFormat==="channelsFirst"?(n=1,r=2,a=3):(n=3,r=1,a=2);let s=this.kernelSize[0],i=this.kernelSize[1],o=this.strides[0],l=this.strides[1];return t[n]=this.filters,t[r]=Fp(t[r],o,s,this.padding),t[a]=Fp(t[a],l,i,this.padding),t}getConfig(){let e=super.getConfig();return delete e.dilationRate,e}};My.className="Conv2DTranspose";re.registerClass(My);var a7=class extends xc{constructor(e,t){super(e,t);if(this.DEFAULT_DEPTHWISE_INITIALIZER="glorotUniform",this.DEFAULT_POINTWISE_INITIALIZER="glorotUniform",this.depthwiseKernel=null,this.pointwiseKernel=null,t.filters==null)throw new B("The `filters` configuration field is required by SeparableConv, but is unspecified.");if(t.kernelInitializer!=null||t.kernelRegularizer!=null||t.kernelConstraint!=null)throw new B("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 B(`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=yt(t.depthwiseInitializer||this.DEFAULT_DEPTHWISE_INITIALIZER),this.depthwiseRegularizer=gt(t.depthwiseRegularizer),this.depthwiseConstraint=Wt(t.depthwiseConstraint),this.pointwiseInitializer=yt(t.depthwiseInitializer||this.DEFAULT_POINTWISE_INITIALIZER),this.pointwiseRegularizer=gt(t.pointwiseRegularizer),this.pointwiseConstraint=Wt(t.pointwiseConstraint)}build(e){if(e=ut(e),e.length{e=Le(e);let n;if(this.rank===1)throw new De("1D separable convolution is not implemented yet.");return this.rank===2&&(this.dataFormat==="channelsFirst"&&(e=rt(e,[0,2,3,1])),n=Qf(e,this.depthwiseKernel.read(),this.pointwiseKernel.read(),this.strides,this.padding,this.dilationRate,"NHWC")),this.useBias&&(n=Br(n,this.bias.read(),this.dataFormat)),this.activation!=null&&(n=this.activation.apply(n)),this.dataFormat==="channelsFirst"&&(n=rt(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=kt(this.depthwiseInitializer),e.pointwiseInitializer=kt(this.pointwiseInitializer),e.depthwiseRegularizer=ct(this.depthwiseRegularizer),e.pointwiseRegularizer=ct(this.pointwiseRegularizer),e.depthwiseConstraint=Pt(this.depthwiseConstraint),e.pointwiseConstraint=Pt(this.pointwiseConstraint),e}};a7.className="SeparableConv";var Dy=class extends a7{constructor(e){super(2,e)}};Dy.className="SeparableConv2D";re.registerClass(Dy);var Mp=class extends xc{constructor(e){super(1,e);Mp.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"&&!VA(e.kernelSize,"number",1,1))throw new B(`Conv1D expects config.kernelSize to be number or number[] with length 1, but received ${JSON.stringify(e.kernelSize)}.`)}};Mp.className="Conv1D";re.registerClass(Mp);var Oy=class extends qe{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 V(()=>{if(e=Le(e),this.dataFormat==="channelsLast"){let n=cp(e,this.cropping[0][0],e.shape[1]-this.cropping[0][0]-this.cropping[0][1],2);return cp(n,this.cropping[1][0],e.shape[2]-this.cropping[1][1]-this.cropping[1][0],3)}else{let n=cp(e,this.cropping[0][0],e.shape[2]-this.cropping[0][0]-this.cropping[0][1],3);return cp(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}};Oy.className="Cropping2D";re.registerClass(Oy);var zy=class extends qe{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,Tt(this.dataFormat),this.interpolation=e.interpolation==null?"nearest":e.interpolation,yJ(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 V(()=>{let n=Le(e),r=n.shape;if(this.dataFormat==="channelsFirst"){n=rt(n,[0,2,3,1]);let a=this.size[0]*r[2],s=this.size[1]*r[3],i=this.interpolation==="nearest"?n.resizeNearestNeighbor([a,s]):n.resizeBilinear([a,s]);return rt(i,[0,3,1,2])}else{let a=this.size[0]*r[1],s=this.size[1]*r[2];return this.interpolation==="nearest"?n.resizeNearestNeighbor([a,s]):n.resizeBilinear([a,s])}})}getConfig(){let e={size:this.size,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}};zy.className="UpSampling2D";re.registerClass(zy);function qee(e,t,n=[1,1],r="valid",a,s){return V(()=>{a==null&&(a=yr()),Tt(a);let i=Fy(e,a);if(e.rank!==4)throw new B(`Input for depthwiseConv2d is required to be 4-D, but is instead ${e.rank}-D`);if(t.rank!==4)throw new B(`depthwiseKernel is required to be 4-D, but is instead ${t.rank}-D`);return i=Wo(i,t,n,r==="same"?"same":"valid","NHWC",s),a==="channelsFirst"&&(i=rt(i,[0,3,1,2])),i})}var Ly=class extends $y{constructor(e){super(2,e);this.depthwiseKernel=null,this.depthMultiplier=e.depthMultiplier==null?1:e.depthMultiplier,this.depthwiseInitializer=yt(e.depthwiseInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.depthwiseConstraint=Wt(e.depthwiseConstraint),this.depthwiseRegularizer=gt(e.depthwiseRegularizer)}build(e){if(e=ut(e),e.length<4)throw new B(`Inputs to DepthwiseConv2D should have rank 4. Received input shape: ${JSON.stringify(e)}.`);let t=this.dataFormat==="channelsFirst"?1:3;if(e[t]==null||e[t]<0)throw new B(`The channel dimension of the inputs to DepthwiseConv2D should be defined, but is not (${e[t]}).`);let n=e[t],r=[this.kernelSize[0],this.kernelSize[1],n,this.depthMultiplier];this.depthwiseKernel=this.addWeight("depthwise_kernel",r,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 V(()=>{e=Le(e);let n=qee(e,this.depthwiseKernel.read(),this.strides,this.padding,this.dataFormat,null);return this.useBias&&(n=Br(n,this.bias.read(),this.dataFormat)),this.activation!=null&&(n=this.activation.apply(n)),n})}computeOutputShape(e){e=ut(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],n=this.dataFormat==="channelsFirst"?e[3]:e[2],r=this.dataFormat==="channelsFirst"?e[1]*this.depthMultiplier:e[3]*this.depthMultiplier,a=_r(t,this.kernelSize[0],this.padding,this.strides[0]),s=_r(n,this.kernelSize[1],this.padding,this.strides[1]);return this.dataFormat==="channelsFirst"?[e[0],r,a,s]:[e[0],a,s,r]}getConfig(){let e=super.getConfig();return e.depthMultiplier=this.depthMultiplier,e.depthwiseInitializer=kt(this.depthwiseInitializer),e.depthwiseRegularizer=ct(this.depthwiseRegularizer),e.depthwiseConstraint=Pt(this.depthwiseRegularizer),e}};Ly.className="DepthwiseConv2D";re.registerClass(Ly);function s7(e,t,n,r){if(Array.isArray(e)){if(t!=null||n!=null)throw new B("When inputs is an array, neither initialState or constants should be provided");r!=null&&(n=e.slice(e.length-r,e.length),e=e.slice(0,e.length-r)),e.length>1&&(t=e.slice(1,e.length)),e=e[0]}function a(s){return s==null||Array.isArray(s)?s:[s]}return t=a(t),n=a(n),{inputs:e,initialState:t,constants:n}}function i7(e,t,n,r=!1,a,s,i=!1,o=!1){return V(()=>{let l=t.shape.length;if(l<3)throw new B(`Input should be at least 3D, but is ${l}D.`);let u=[1,0].concat(xr(2,l));if(t=rt(t,u),s!=null)throw new De("The rnn() functoin of the deeplearn.js backend does not support constants yet.");i&&console.warn("Backend rnn(): the unroll = true option is not applicable to the imperative deeplearn.js backend."),a!=null&&(a=a.asType("bool").asType("float32"),a.rank===l-1&&(a=Nn(a,-1)),a=rt(a,u)),r&&(t=En(t,0),a!=null&&(a=En(a,0)));let c=[],h,d=n,p=t.shape[0],f=nr(t),m;a!=null&&(m=nr(a));for(let y=0;ye(g,d));if(a==null)h=w[0],d=w[1];else{let _=V(()=>{let b=m[y],x=Tn(b).sub(b),N=w[0].mul(b).add(d[0].mul(x)),T=d.map((E,$)=>w[1][$].mul(b).add(E.mul(x)));return{output:N,newStates:T}});h=_.output,d=_.newStates}o&&c.push(h)}let A;return o&&(A=Cn(c,1)),[h,A,d]})}var Fr=class extends qe{constructor(e){super(e);let t;if(e.cell==null)throw new B("cell property is missing for the constructor of RNN.");if(Array.isArray(e.cell)?t=new Dp({cells:e.cell}):t=e.cell,t.stateSize==null)throw new B("The RNN cell should have an attribute `stateSize` (tuple of integers, one integer per RNN state).");this.cell=t,this.returnSequences=e.returnSequences==null?!1:e.returnSequences,this.returnState=e.returnState==null?!1:e.returnState,this.goBackwards=e.goBackwards==null?!1:e.goBackwards,this._stateful=e.stateful==null?!1:e.stateful,this.unroll=e.unroll==null?!1:e.unroll,this.supportsMasking=!0,this.inputSpec=[new Ut({ndim:3})],this.stateSpec=null,this.states_=null,this.numConstants=null,this.keptStates=[]}getStates(){if(this.states_==null){let e=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1;return xr(0,e).map(t=>null)}else return this.states_}setStates(e){this.states_=e}computeOutputShape(e){ly(e)&&(e=e[0]),e=e;let t=this.cell.stateSize;Array.isArray(t)||(t=[t]);let n=t[0],r;if(this.returnSequences?r=[e[0],e[1],n]:r=[e[0],n],this.returnState){let a=[];for(let s of t)a.push([e[0],s]);return[r].concat(a)}else return r}computeMask(e,t){return V(()=>{Array.isArray(t)&&(t=t[0]);let n=this.returnSequences?t:null;if(this.returnState){let r=this.states.map(a=>null);return[n].concat(r)}else return n})}get states(){if(this.states_==null){let e=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1,t=[];for(let n=0;ni.shape[i.shape.length-1]),s))throw new B(`An initialState was passed that is not compatible with cell.stateSize. Received stateSpec=${this.stateSpec}; However cell.stateSize is ${this.cell.stateSize}`)}else this.stateSpec=s.map(i=>new Ut({shape:[null,i]}));this.stateful&&this.resetStates()}resetStates(e,t=!1){V(()=>{if(!this.stateful)throw new aa("Cannot call resetStates() on an RNN Layer that is not stateful.");let n=this.inputSpec[0].shape[0];if(n==null)throw new B("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(r=>Ct([n,r])):this.states_=[Ct([n,this.cell.stateSize])];else if(e==null)Re(this.states_),this.keptStates!=null&&(Re(this.keptStates),this.keptStates=[]),Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(r=>Ct([n,r])):this.states_[0]=Ct([n,this.cell.stateSize]);else{if(Array.isArray(e)||(e=[e]),e.length!==this.states_.length)throw new B(`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()):Re(this.states_);for(let r=0;rVt(r.clone()))})}apply(e,t){let n=t==null?null:t.initialState,r=t==null?null:t.constants;t==null&&(t={});let a=s7(e,n,r,this.numConstants);e=a.inputs,n=a.initialState,r=a.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 Ut({shape:o.shape}));i=i.concat(this.stateSpec)}if(r!=null&&(t.constants=r,s=s.concat(r),this.numConstants=r.length),s[0]instanceof fr){let o=[e].concat(s),l=this.inputSpec.concat(i),u=this.inputSpec;this.inputSpec=l;let c=super.apply(o,t);return this.inputSpec=u,c}else return super.apply(e,t)}call(e,t){return V(()=>{let n=t==null?null:t.mask,r=t==null?null:t.training,a=t==null?null:t.initialState;e=Le(e),a==null&&(this.stateful?a=this.states_:a=this.getInitialState(e));let s=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1;if(a.length!==s)throw new B(`RNN Layer has ${s} state(s) but was passed ${a.length} initial state(s).`);this.unroll&&console.warn("Ignoring unroll = true for RNN layer, due to imperative backend.");let i={training:r},o=i7((d,p)=>{let f=this.cell.call([d].concat(p),i);return[f[0],f.slice(1)]},e,a,this.goBackwards,n,null,this.unroll,this.returnSequences),l=o[0],u=o[1],c=o[2];this.stateful&&this.resetStates(c,r);let h=this.returnSequences?u:l;return this.returnState?[h].concat(c):h})}getInitialState(e){return V(()=>{let t=Ct(e.shape);return t=Ee(t,[1,2]),t=cc(t),Array.isArray(this.cell.stateSize)?this.cell.stateSize.map(n=>n>1?XA(t,[1,n]):t):this.cell.stateSize>1?[XA(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()===Fr.className&&(t.cell={className:this.cell.getClassName(),config:n}),Object.assign({},n,e,t)}static fromConfig(e,t,n={}){let r=t.cell,a=wr(r,n);return new e(Object.assign(t,{cell:a}))}};Fr.className="RNN";re.registerClass(Fr);var pc=class extends qe{},Op=class extends pc{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,Gt(this.units,"units"),this.activation=Wa(e.activation==null?this.DEFAULT_ACTIVATION:e.activation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=yt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=yt(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=yt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelRegularizer=gt(e.kernelRegularizer),this.recurrentRegularizer=gt(e.recurrentRegularizer),this.biasRegularizer=gt(e.biasRegularizer),this.kernelConstraint=Wt(e.kernelConstraint),this.recurrentConstraint=Wt(e.recurrentConstraint),this.biasConstraint=Wt(e.biasConstraint),this.dropout=vl([1,za([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=vl([1,za([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.stateSize=this.units,this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){e=ut(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 V(()=>{if(e=e,e.length!==2)throw new B(`SimpleRNNCell expects 2 input Tensors, got ${e.length}.`);let n=e[1];e=e[0];let r=t.training==null?!1:t.training;0Tn(e),rate:this.dropout,training:r})),0Tn(n),rate:this.recurrentDropout,training:r}));let a,s=this.dropoutMask,i=this.recurrentDropoutMask;s!=null?a=Wr(W(e,s),this.kernel.read()):a=Wr(e,this.kernel.read()),this.bias!=null&&(a=Br(a,this.bias.read())),i!=null&&(n=W(n,i));let o=oe(a,Wr(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:Pa(this.activation),useBias:this.useBias,kernelInitializer:kt(this.kernelInitializer),recurrentInitializer:kt(this.recurrentInitializer),biasInitializer:kt(this.biasInitializer),kernelRegularizer:ct(this.kernelRegularizer),recurrentRegularizer:ct(this.recurrentRegularizer),biasRegularizer:ct(this.biasRegularizer),activityRegularizer:ct(this.activityRegularizer),kernelConstraint:Pt(this.kernelConstraint),recurrentConstraint:Pt(this.recurrentConstraint),biasConstraint:Pt(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout};return Object.assign({},e,t)}};Op.className="SimpleRNNCell";re.registerClass(Op);var Py=class extends Fr{constructor(e){e.cell=new Op(e),super(e)}call(e,t){return V(()=>{this.cell.dropoutMask!=null&&(Re(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(Re(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=t==null?null:t.mask,r=t==null?null:t.training,a=t==null?null:t.initialState;return super.call(e,{mask:n,training:r,initialState:a})})}static fromConfig(e,t){return new e(t)}};Py.className="SimpleRNN";re.registerClass(Py);var zp=class extends pc{constructor(e){super(e);if(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 B("GRUCell does not support reset_after parameter set to true.");this.units=e.units,Gt(this.units,"units"),this.activation=Wa(e.activation===void 0?this.DEFAULT_ACTIVATION:e.activation),this.recurrentActivation=Wa(e.recurrentActivation===void 0?this.DEFAULT_RECURRENT_ACTIVATION:e.recurrentActivation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=yt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=yt(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=yt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelRegularizer=gt(e.kernelRegularizer),this.recurrentRegularizer=gt(e.recurrentRegularizer),this.biasRegularizer=gt(e.biasRegularizer),this.kernelConstraint=Wt(e.kernelConstraint),this.recurrentConstraint=Wt(e.recurrentConstraint),this.biasConstraint=Wt(e.biasConstraint),this.dropout=vl([1,za([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=vl([1,za([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.implementation=e.implementation,this.stateSize=this.units,this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){e=ut(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 V(()=>{if(e=e,e.length!==2)throw new B(`GRUCell expects 2 input Tensors (inputs, h, c), got ${e.length}.`);let n=t.training==null?!1:t.training,r=e[1];e=e[0],0Tn(e),rate:this.dropout,training:n,count:3})),0Tn(r),rate:this.recurrentDropout,training:n,count:3}));let a=this.dropoutMask,s=this.recurrentDropoutMask,i,o,l;0{this.cell.dropoutMask!=null&&(Re(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(Re(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=t==null?null:t.mask,r=t==null?null:t.training,a=t==null?null:t.initialState;return super.call(e,{mask:n,training:r,initialState:a})})}static fromConfig(e,t){return t.implmentation===0&&(t.implementation=1),new e(t)}};Wy.className="GRU";re.registerClass(Wy);var _c=class extends pc{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,Gt(this.units,"units"),this.activation=Wa(e.activation===void 0?this.DEFAULT_ACTIVATION:e.activation),this.recurrentActivation=Wa(e.recurrentActivation===void 0?this.DEFAULT_RECURRENT_ACTIVATION:e.recurrentActivation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=yt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=yt(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=yt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.unitForgetBias=e.unitForgetBias,this.kernelRegularizer=gt(e.kernelRegularizer),this.recurrentRegularizer=gt(e.recurrentRegularizer),this.biasRegularizer=gt(e.biasRegularizer),this.kernelConstraint=Wt(e.kernelConstraint),this.recurrentConstraint=Wt(e.recurrentConstraint),this.biasConstraint=Wt(e.biasConstraint),this.dropout=vl([1,za([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=vl([1,za([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.implementation=e.implementation,this.stateSize=[this.units,this.units],this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){var t;e=ut(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 r;if(this.useBias){if(this.unitForgetBias){let a=this.biasInitializer,s=this.units;r=new(t=class extends or{apply(i,o){let l=a.apply([s]),u=new dp().apply([s]),c=a.apply([s*2]);return a3(a3(l,u),c)}},t.className="CustomInit",t)}else r=this.biasInitializer;this.bias=this.addWeight("bias",[this.units*4],null,r,this.biasRegularizer,!0,this.biasConstraint)}else this.bias=null;this.built=!0}call(e,t){return V(()=>{let n=t.training==null?!1:t.training;if(e=e,e.length!==3)throw new B(`LSTMCell expects 3 input Tensors (inputs, h, c), got ${e.length}.`);let r=e[1],a=e[2];e=e[0],0Tn(e),rate:this.dropout,training:n,count:4})),0Tn(r),rate:this.recurrentDropout,training:n,count:4}));let s=this.dropoutMask,i=this.recurrentDropoutMask,o,l,u,c;0{this.cell.dropoutMask!=null&&(Re(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(Re(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=t==null?null:t.mask,r=t==null?null:t.training,a=t==null?null:t.initialState;return super.call(e,{mask:n,training:r,initialState:a})})}static fromConfig(e,t){return t.implmentation===0&&(t.implementation=1),new e(t)}};By.className="LSTM";re.registerClass(By);var Dp=class extends pc{constructor(e){super(e);this.cells=e.cells}get stateSize(){let e=[];for(let t of this.cells.slice().reverse())Array.isArray(t.stateSize)?e.push(...t.stateSize):e.push(t.stateSize);return e}call(e,t){return V(()=>{e=e;let n=e.slice(1),r=[];for(let i of this.cells.slice().reverse())Array.isArray(i.stateSize)?r.push(n.splice(0,i.stateSize.length)):r.push(n.splice(0,1));r.reverse();let a=[],s;for(let i=0;i{pi(`RNNCell_${r}`,()=>{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=r=>({className:r.getClassName(),config:r.getConfig()}),n={cells:this.cells.map(t)};return Object.assign({},e,n)}static fromConfig(e,t,n={}){let r=[];for(let a of t.cells)r.push(wr(a,n));return new e({cells:r})}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 uy(e)}setWeights(e){let t=[];for(let n of this.cells){let r=n.weights.length,a=e.splice(r);for(let s=0;si3(t(),n),i=()=>dc(s,t,r);return!a||a<=1?Vt(i().clone()):Array(a).fill(void 0).map(i).map(o=>Vt(o.clone()))}var Xee=function(e,t){var n={};for(var r in e)Object.prototype.hasOwnProperty.call(e,r)&&t.indexOf(r)<0&&(n[r]=e[r]);if(e!=null&&typeof Object.getOwnPropertySymbols=="function")for(var a=0,r=Object.getOwnPropertySymbols(e);a{if(this.cell.dropoutMask!=null&&(Re(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(Re(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null),t&&t.constants)throw new B("ConvRNN2D cell does not support constants");let n=t==null?null:t.mask,r=t==null?null:t.training,a=t==null?null:t.initialState;return super.call(e,{mask:n,training:r,initialState:a})})}computeOutputShape(e){let t=this.computeSingleOutputShape(e);return this.returnSequences||(t=[t[0],...t.slice(2)]),this.returnState&&(t=[t,...Array(2).fill([e[0],...t.slice(-3)])]),t}getInitialState(e){return V(()=>{let{stateSize:t}=this.cell,n=e.shape,r=this.computeSingleOutputShape(n),a=[r[0],...r.slice(2)],s=Ct(a);return Array.isArray(t)?Array(t.length).fill(s):[s]})}resetStates(e,t=!1){V(()=>{if(!this.stateful)throw new aa("Cannot call resetStates() on an RNN Layer that is not stateful.");let n=this.inputSpec[0].shape,r=this.computeSingleOutputShape(n),a=[r[0],...r.slice(2)];if(n[0]==null)throw new B("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(()=>Ct(a)):this.states_=[Ct(a)];else if(e==null)Re(this.states_),this.keptStates!=null&&(Re(this.keptStates),this.keptStates=[]),Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(()=>Ct(a)):this.states_[0]=Ct(a);else{if(Array.isArray(e)||(e=[e]),e.length!==this.states_.length)throw new B(`Layer ${this.name} expects ${this.states_.length} state(s), but it received ${e.length} state value(s). 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Found ${e[n]}`);let r=e[n],a=4,s=this.kernelSize.concat([r,this.filters*a]);this.kernel=this.addWeight("kernel",s,null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint);let i=this.kernelSize.concat([this.filters,this.filters*a]);if(this.recurrentKernel=this.addWeight("recurrent_kernel",i,null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint),this.useBias){let o;if(this.unitForgetBias){let l=this.biasInitializer,u=this.filters;o=new(t=class extends or{apply(c,h){let d=l.apply([u]),p=Er([u]),f=l.apply([u*2]);return ZA([d,p,f])}},t.className="CustomInit",t)}else o=this.biasInitializer;this.bias=this.addWeight("bias",[this.filters*a],null,o,this.biasRegularizer,!0,this.biasConstraint)}this.built=!0}call(e,t){return V(()=>{if(e.length!==3)throw new B(`ConvLSTM2DCell expects 3 input Tensors (inputs, h, c), got ${e.length}.`);let n=t.training||!1,r=e[0],a=e[1],s=e[2],i=4;0Tn(r),rate:this.dropout,training:n,count:i}));let o=this.dropoutMask,l=(J,se,te)=>!se||!se[te]?J:W(se[te],J),u=l(r,o,0),c=l(r,o,1),h=l(r,o,2),d=l(r,o,3);0Tn(a),rate:this.recurrentDropout,training:n,count:i}));let p=this.recurrentDropoutMask,f=l(a,p,0),m=l(a,p,1),A=l(a,p,2),y=l(a,p,3),g=3,[w,_,b,x]=on(this.kernel.read(),i,g),[N,T,E,$]=this.useBias?on(this.bias.read(),i):[null,null,null,null];u=this.inputConv(u,w,N,this.padding),c=this.inputConv(c,_,T,this.padding),h=this.inputConv(h,b,E,this.padding),d=this.inputConv(d,x,$,this.padding);let[D,L,P,U]=on(this.recurrentKernel.read(),i,g);f=this.recurrentConv(f,D),m=this.recurrentConv(m,L),A=this.recurrentConv(A,P),y=this.recurrentConv(y,U);let j=this.recurrentActivation.apply(oe(u,f)),X=this.recurrentActivation.apply(oe(c,m)),G=oe(W(X,s),W(j,this.activation.apply(oe(h,A)))),ee=W(this.recurrentActivation.apply(oe(d,y)),this.activation.apply(G));return[ee,ee,G]})}getConfig(){let e=super.getConfig(),{units:t}=e,n=Xee(e,["units"]),r={filters:this.filters,kernelSize:this.kernelSize,padding:this.padding,dataFormat:this.dataFormat,dilationRate:this.dilationRate,strides:this.strides};return Object.assign({},n,r)}inputConv(e,t,n,r){let a=Kr(e,t,this.strides,r||"valid",this.dataFormat==="channelsFirst"?"NCHW":"NHWC",this.dilationRate);return n?Br(a,n,this.dataFormat):a}recurrentConv(e,t){return Kr(e,t,1,"same",this.dataFormat==="channelsFirst"?"NCHW":"NHWC")}};Lp.className="ConvLSTM2DCell";re.registerClass(Lp);var Vy=class extends o7{constructor(e){let t=new Lp(e);super(Object.assign({},e,{cell:t}))}static fromConfig(e,t){return new e(t)}};Vy.className="ConvLSTM2D";re.registerClass(Vy);var Pp=class extends qe{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 r=0;r{this.invokeCallHook(e,t);let n=Le(e);if(0i3(n,this.rate,a,this.seed),()=>n,r)}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()}};Pp.className="Dropout";re.registerClass(Pp);var Uy=class extends Pp{constructor(e){super(e);this.inputSpec=[{ndim:3}]}getNoiseShape(e){let t=e.shape;return[t[0],1,t[2]]}};Uy.className="SpatialDropout1D";re.registerClass(Uy);var jy=class extends qe{constructor(e){super(e);if(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,Gt(this.units,"units"),this.activation=Wa(e.activation),e.useBias!=null&&(this.useBias=e.useBias),this.kernelInitializer=yt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.biasInitializer=yt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelConstraint=Wt(e.kernelConstraint),this.biasConstraint=Wt(e.biasConstraint),this.kernelRegularizer=gt(e.kernelRegularizer),this.biasRegularizer=gt(e.biasRegularizer),this.activityRegularizer=gt(e.activityRegularizer),this.supportsMasking=!0,this.inputSpec=[{minNDim:2}]}build(e){e=ut(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=ut(e);let t=e.slice();return t[t.length-1]=this.units,t}call(e,t){return V(()=>{this.invokeCallHook(e,t);let n=Le(e),r=Kb(this.activation.getClassName()),a;return r!=null?a=Wr(n,this.kernel.read(),r,this.bias?this.bias.read():null):(a=Wr(n,this.kernel.read()),this.bias!=null&&(a=Br(a,this.bias.read())),this.activation!=null&&(a=this.activation.apply(a))),a})}getConfig(){let e={units:this.units,activation:Pa(this.activation),useBias:this.useBias,kernelInitializer:kt(this.kernelInitializer),biasInitializer:kt(this.biasInitializer),kernelRegularizer:ct(this.kernelRegularizer),biasRegularizer:ct(this.biasRegularizer),activityRegularizer:ct(this.activityRegularizer),kernelConstraint:Pt(this.kernelConstraint),biasConstraint:Pt(this.biasConstraint)},t=super.getConfig();return Object.assign(e,t),e}};jy.className="Dense";re.registerClass(jy);var Hy=class extends qe{constructor(e){e=e||{},super(e),this.inputSpec=[{minNDim:3}],this.dataFormat=e.dataFormat}computeOutputShape(e){e=ut(e);for(let t of e.slice(1))if(t==null)throw new B(`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],Oa(e,1)]}call(e,t){return V(()=>{this.invokeCallHook(e,t);let n=Le(e);if(this.dataFormat==="channelsFirst"&&n.rank>1){let r=[0];for(let a=2;a{this.invokeCallHook(e,t);let n=Le(e);return this.activation.apply(n)})}getConfig(){let e={activation:Pa(this.activation)},t=super.getConfig();return Object.assign(e,t),e}};Gy.className="Activation";re.registerClass(Gy);var qy=class extends qe{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 V(()=>(e=Le(e),_J(e,this.n)))}getConfig(){let e={n:this.n},t=super.getConfig();return Object.assign(e,t),e}};qy.className="RepeatVector";re.registerClass(qy);var Xy=class extends qe{constructor(e){super(e);this.targetShape=e.targetShape;for(let t=0;t{this.invokeCallHook(e,t);let n=Le(e),r=n.shape,a=r.slice(0,1).concat(this.fixUnknownDimension(r.slice(1),this.targetShape));return n.reshape(a)})}getConfig(){let e={targetShape:this.targetShape},t=super.getConfig();return Object.assign(e,t),e}};Xy.className="Reshape";re.registerClass(Xy);var Ky=class extends qe{constructor(e){super(e);if(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=xr(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 Ut({ndim:this.dims.length+1})]}computeOutputShape(e){e=ut(e);let t=e.slice();return this.dims.forEach((n,r)=>{t[r+1]=e[n]}),t}call(e,t){return rt(Le(e),this.dimsIncludingBatch)}getConfig(){let e={dims:this.dims},t=super.getConfig();return Object.assign(e,t),e}};Ky.className="Permute";re.registerClass(Ky);var Zy=class extends qe{constructor(e){super(e==null?{}:e);this.supportsMasking=!0,e!=null?this.maskValue=e.maskValue==null?0:e.maskValue:this.maskValue=0}computeOutputShape(e){return e}getConfig(){let e=super.getConfig(),t={maskValue:this.maskValue};return Object.assign(t,e),t}computeMask(e,t){let n=Le(e),r=-1;return du(Hs(n,this.maskValue),r)}call(e,t){return V(()=>{this.invokeCallHook(e,t);let n=Le(e),r=-1,a=!0,s=du(Hs(n,this.maskValue),r,a);return n.mul(s.asType(n.dtype))})}};Zy.className="Masking";re.registerClass(Zy);var Yy=class extends qe{constructor(e){super(e);if(this.embeddings=null,this.DEFAULT_EMBEDDINGS_INITIALIZER="randomUniform",e.batchInputShape==null&&e.inputShape==null){let t=null;e.batchSize!=null&&(t=e.batchSize),e.inputLength==null?this.batchInputShape=[t,null]:this.batchInputShape=[t].concat(pt(e.inputLength))}this.inputDim=e.inputDim,Gt(this.inputDim,"inputDim"),this.outputDim=e.outputDim,Gt(this.outputDim,"outputDim"),this.embeddingsInitializer=yt(e.embeddingsInitializer||this.DEFAULT_EMBEDDINGS_INITIALIZER),this.embeddingsRegularizer=gt(e.embeddingsRegularizer),this.activityRegularizer=gt(e.activityRegularizer),this.embeddingsConstraint=Wt(e.embeddingsConstraint),this.maskZero=e.maskZero,this.supportsMasking=e.maskZero,this.inputLength=e.inputLength}build(e){this.embeddings=this.addWeight("embeddings",[this.inputDim,this.outputDim],this.dtype,this.embeddingsInitializer,this.embeddingsRegularizer,!0,this.embeddingsConstraint),this.built=!0}warnOnIncompatibleInputShape(e){}computeMask(e,t){return V(()=>this.maskZero?(e=Le(e),Hs(e,je(e))):null)}computeOutputShape(e){if(e=ut(e),this.inputLength==null)return[...e,this.outputDim];let t=pt(this.inputLength);if(t.length!==e.length-1)throw new B(`"inputLength" is ${this.inputLength}, but received input shape has shape ${e}`);{let n=0;for(let r=0;r{this.invokeCallHook(e,t);let n=Le(e);return n.dtype!=="int32"&&(n=uc(n,"int32")),s3(this.embeddings.read(),n.as1D()).reshape(ut(this.computeOutputShape(n.shape)))})}getConfig(){let e={inputDim:this.inputDim,outputDim:this.outputDim,embeddingsInitializer:kt(this.embeddingsInitializer),embeddingsRegularizer:ct(this.embeddingsRegularizer),activityRegularizer:ct(this.activityRegularizer),embeddingsConstraint:Pt(this.embeddingsConstraint),maskZero:this.maskZero,inputLength:this.inputLength},t=super.getConfig();return Object.assign(e,t),e}};Yy.className="Embedding";re.registerClass(Yy);var gi=class extends qe{constructor(e){super(e||{});this.supportsMasking=!0}mergeFunction(e){throw new De}computeElementwiseOpOutputShape(e,t){if(e==null||t==null)return null;if(e.length1)throw new B(`Can not merge tensors with different batch sizes. Got tensors with shapes: ${JSON.stringify(e)}.`);let n=e[0]==null?null:e[0].slice(1);for(let a=1;aa.length);e.indexOf(null)===-1&&Da(r).length===1?this.reshapeRequired=!1:this.reshapeRequired=!0}call(e,t){return V(()=>{if(e=e,this.reshapeRequired){let n=[],r=e.map(a=>a.rank);if(r.indexOf(null)===-1){let a=za(r);for(let s of e){let i=s.rank;for(let o=0;o1){let u=xr(1,l).concat([0]);n.push(rt(o,u)),a=!0}else n.push(o)}let s=this.mergeFunction(n),i=s.rank;if(a){if(i==null){let o=s.shape,l=o.length,u=o[l-1],c=[u].concat(o.slice(0,o.length-1));s=rt(s.reshape([-1,u]),[1,0]).reshape(c)}else if(i>1){let o=[i-1].concat(xr(0,i-1));s=rt(s,o)}}return s}}else return this.mergeFunction(e)})}computeOutputShape(e){e=e;let t;e[0]==null?t=null:t=e[0].slice(1);for(let r=1;r{if(t==null)return null;if(!Array.isArray(t))throw new B("`mask` should be an Array");if(!Array.isArray(e))throw new B("`inputs` should be an Array");if(t.length!==e.length)throw new B(`The Array 'inputs' and 'mask' are expected to have the same length, but have different lengths (${e.length} vs ${t.length})`);if(t.every(r=>r==null))return null;t=t.map(r=>r==null?r:Nn(r,0));let n=t[0];for(let r=1;r{let t=e[0].clone();for(let n=1;n{let t=e[0].clone();for(let n=1;n{let t=e[0].clone();for(let n=1;n{let t=e[0];for(let n=1;n{let t=e[0];for(let n=1;n1)throw new B("A `Concatenate` layer requires inputs with matching shapes except for the concat axis. Got input shapes: "+JSON.stringify(e))}mergeFunction(e){return V(()=>ZA(e,this.axis))}computeOutputShape(e){if(!(Array.isArray(e)&&Array.isArray(e[0])))throw new B("A `Concatenate` layer should be called on a list of inputs.");let t=e,n=t[0].slice(),r=this.axis<0?n.length+this.axis:this.axis;for(let a of t.slice(1)){if(n[r]==null||a[r]==null){n[r]=null;break}n[r]+=a[r]}return n}computeMask(e,t){if(t==null)return null;if(!Array.isArray(t))throw new B("`mask` should be an array for Concatenate");if(!Array.isArray(e))throw new B("`inputs` should be an array for Concatenate");if(t.length!==e.length)throw new B(`Mismatch in the length of mask (${t.length}) and the legnth of inputs (${e.length})`);return V(()=>{let n=!0;if(t.forEach(s=>{if(s!=null){n=!1;return}}),n)return null;let r=[];for(let s=0;s3||t.shape.length>3)throw new De("batchDot is not implemented for tensors of 4D or higher rank yet");if(v.assert(e.shape.length>=2,()=>`batchDot requires the rank of x to be >= 2, but got ${e.shape.length}`),v.assert(e.shape.length>=2,()=>`batchDot requires the rank of y to be >= 2, but got ${t.shape.length}`),typeof n=="number"&&(n=[n,n]),e.dtype==="complex64"||t.dtype==="complex64")throw new De("batchDot is not implemented for complex64-type Tensors yet.");let r=e.shape.length,a=t.shape.length;n==null&&(n=[r-1,a-2]);let s=n;return V(()=>{let i;if(r>a){i=r-a;let l=[];for(let u=0;ur){i=a-r;let l=[];for(let u=0;u0){let l;r>a?l=r+a-3:l=r-1;let u=[];for(let c=l;c"A `Dot` layer should be called on a list of exactly 2 inputs.");let t=e[0],n=e[1];if(t.length>3||n.length>3)throw new De("Dot layer does not support tensors of 4D or higher rank yet.");let r=this.interpretAxes(t,n);if(t[r[0]]!==n[r[1]])throw new B(`Dimension incompatibility: ${t[r[0]]} !== ${n[r[1]]}`)}mergeFunction(e){if(e.length!==2)throw new B(`A \`Dot\` layer must be called on exactly 2 inputs, but received ${e.length} input(s).`);let t=e[0],n=e[1],r;return Array.isArray(this.axes)?r=this.axes.map((a,s)=>bc(a,e[s].shape.length)):r=[bc(this.axes,t.shape.length),bc(this.axes,n.shape.length)],this.normalize&&(t=kp(t,r[0]),n=kp(n,r[1])),Kee(t,n,r)}interpretAxes(e,t){let n;return Array.isArray(this.axes)?n=this.axes:n=[bc(this.axes,e.length),bc(this.axes,t.length)],n}computeOutputShape(e){v.assert(Array.isArray(e)&&e.length===2&&Array.isArray(e[0])&&Array.isArray(e[1]),()=>"A `Dot` layer should be called on a list of exactly 2 inputs.");let t=e[0].slice(),n=e[1].slice();if(t.length>3||n.length>3)throw new De("Dot layer does not support tensors of 4D or higher rank yet.");let r=this.interpretAxes(t,n);t.splice(r[0],1),n.splice(r[1],1),n.splice(0,1);let a=t.concat(n);return a.length===1&&a.push(1),a}computeMask(e,t){return null}getConfig(){let e={axes:this.axes,normalize:this.normalize},t=super.getConfig();return Object.assign(e,t),e}};ag.className="Dot";re.registerClass(ag);var sg=class extends qe{constructor(e){super(e);this.supportsMasking=!0,this.stddev=e.stddev}computeOutputShape(e){return e}getConfig(){let e=super.getConfig(),t={stddev:this.stddev};return Object.assign(t,e),t}call(e,t){return V(()=>{this.invokeCallHook(e,t);let n=Le(e);return dc(()=>hp(n.shape,0,this.stddev).add(n),()=>n,t.training||!1)})}};sg.className="GaussianNoise";re.registerClass(sg);var ig=class extends qe{constructor(e){super(e);this.supportsMasking=!0,this.rate=e.rate}computeOutputShape(e){return e}getConfig(){let e=super.getConfig(),t={rate:this.rate};return Object.assign(t,e),t}call(e,t){return V(()=>{this.invokeCallHook(e,t);let n=Le(e);return this.rate>0&&this.rate<1?dc(()=>{let r=Math.sqrt(this.rate/(1-this.rate));return n.mul(hp(n.shape,1,r))},()=>n,t.training||!1):n})}};ig.className="GaussianDropout";re.registerClass(ig);var og=class extends qe{constructor(e){super(e);this.supportsMasking=!0,this.rate=e.rate,this.noiseShape=e.noiseShape}_getNoiseShape(e){return this.noiseShape||Le(e).shape}computeOutputShape(e){return e}getConfig(){let e=super.getConfig(),t={rate:this.rate};return Object.assign(t,e),t}call(e,t){return V(()=>{if(this.rate<1&&this.rate>0){let n=this._getNoiseShape(e);return dc(()=>{let r=Le(e),a=1.6732632423543772,s=1.0507009873554805,i=-a*s,o=va(Go(n),this.rate);o=uc(o,"float32");let l=((1-this.rate)*(1+this.rate*i**2))**-.5,u=-l*i*this.rate;return r.mul(o).add(o.add(-1).mul(i)).mul(l).add(u)},()=>Le(e),t.training||!1)}return e})}};og.className="AlphaDropout";re.registerClass(og);function vc(e,t,n,r,a,s=.001){let i;if(e.rank===2)i=H2(e,t,n,r,a,s);else if(e.rank===3)i=G2(e,t,n,r,a,s);else if(e.rank===4)i=q2(e,t,n,r,a,s);else throw new De(`batchNormalization is not implemented for array of rank ${e.rank} yet`);return i}function Zee(e,t,n,r,a=.001){return V(()=>{let s=Qh(e,r),i=s.mean,o=s.variance;return[vc(e,i,o,n,t,a),i,o]})}function Yee(e,t,n,r,a=.001){return V(()=>{let s=Qh(e,r),i=s.mean,o=s.variance,l=[];for(let p of xr(0,e.rank))r.indexOf(p)!==-1?l.push(1):l.push(e.shape[p]);let u=i.reshape(l),c=o.reshape(l),h=t==null?null:t.reshape(l),d=n==null?null:n.reshape(l);return[vc(e,u,c,d,h,a),i,o]})}function Jee(e,t,n,r,a=.001){return v.arraysEqual(r.slice().sort(),xr(0,e.rank-1))?Zee(e,t,n,r,a):Yee(e,t,n,r,a)}var lg=class extends qe{constructor(e){e==null&&(e={}),super(e),this.supportsMasking=!0,this.axis=e.axis==null?-1:e.axis,this.momentum=e.momentum==null?.99:e.momentum,this.epsilon=e.epsilon==null?.001:e.epsilon,this.center=e.center==null?!0:e.center,this.scale=e.scale==null?!0:e.scale,this.betaInitializer=yt(e.betaInitializer||"zeros"),this.gammaInitializer=yt(e.gammaInitializer||"ones"),this.movingMeanInitializer=yt(e.movingMeanInitializer||"zeros"),this.movingVarianceInitializer=yt(e.movingVarianceInitializer||"ones"),this.betaConstraint=Wt(e.betaConstraint),this.gammaConstraint=Wt(e.gammaConstraint),this.betaRegularizer=gt(e.betaRegularizer),this.gammaRegularizer=gt(e.gammaRegularizer)}build(e){e=ut(e);let t=this.axis>=0?this.axis:this.axis+e.length,n=e[t];if(n==null)throw new B(`Axis ${t} of input tensor should have a defined dimension but the layer received an input with shape ${JSON.stringify(e)}.`);this.inputSpec=[new Ut({ndim:e.length,axes:{[t]:n}})];let r=[n];this.scale&&(this.gamma=this.addWeight("gamma",r,null,this.gammaInitializer,this.gammaRegularizer,!0,this.gammaConstraint)),this.center&&(this.beta=this.addWeight("beta",r,null,this.betaInitializer,this.betaRegularizer,!0,this.betaConstraint)),this.movingMean=this.addWeight("moving_mean",r,null,this.movingMeanInitializer,null,!1),this.movingVariance=this.addWeight("moving_variance",r,null,this.movingVarianceInitializer,null,!1),this.built=!0}call(e,t){return V(()=>{let n=t.training==null?!1:t.training,r=Le(e),a=r.shape,s=a.length,i=xr(0,s),o=this.axis>=0?this.axis:this.axis+s;i.splice(o,1);let l=ci(1,s);l[o]=a[o];let u=i.slice();u.sort();let c=!v.arraysEqual(u,xr(0,s).slice(0,s-1)),h=()=>{if(c){let A=this.movingMean.read().reshape(l),y=this.movingVariance.read().reshape(l),g=this.center?this.beta.read().reshape(l):null,w=this.scale?this.gamma.read().reshape(l):null;return vc(r,A,y,g,w,this.epsilon)}else return vc(r,this.movingMean.read(),this.movingVariance.read(),this.beta==null?null:this.beta.read(),this.gamma==null?null:this.gamma.read(),this.epsilon)};if(!n)return h();let[d,p,f]=Jee(r,this.gamma.read(),this.beta.read(),i,this.epsilon),m=(A,y,g)=>{V(()=>{let w=1-g,_=A.read(),b=_.sub(y).mul(w);A.write(_.sub(b))})};return(()=>{m(this.movingMean,p,this.momentum),m(this.movingVariance,f,this.momentum)})(),d})}getConfig(){let e={axis:this.axis,momentum:this.momentum,epsilon:this.epsilon,center:this.center,scale:this.scale,betaInitializer:kt(this.betaInitializer),gammaInitializer:kt(this.gammaInitializer),movingMeanInitializer:kt(this.movingMeanInitializer),movingVarianceInitializer:kt(this.movingVarianceInitializer),betaRegularizer:ct(this.betaRegularizer),gammaRegularizer:ct(this.gammaRegularizer),betaConstraint:Pt(this.betaConstraint),gammaConstraint:Pt(this.gammaConstraint)},t=super.getConfig();return Object.assign(e,t),e}};lg.className="BatchNormalization";re.registerClass(lg);var ug=class extends qe{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=yt(e.betaInitializer||"zeros"),this.gammaInitializer=yt(e.gammaInitializer||"ones"),this.betaRegularizer=gt(e.betaRegularizer),this.gammaRegularizer=gt(e.gammaRegularizer),this.supportsMasking=!0}build(e){e=ut(e);let t=e.length;typeof this.axis=="number"&&(this.axis=[this.axis]);for(let a=0;a=t)throw new Error(`Invalid axis: ${a}`);if(this.axis.length!==Da(this.axis).length)throw new Error(`Found duplicate axes in: ${this.axis}`);let n=this.axis.map(a=>e[a]),r=!0;this.scale?this.gamma=this.addWeight("gamma",n,"float32",this.gammaInitializer,this.gammaRegularizer,r):this.gamma=null,this.center?this.beta=this.addWeight("beta",n,"float32",this.betaInitializer,this.betaRegularizer,r):this.beta=null,this.built=!0}call(e,t){let n=Le(e),r=n.shape,a=r.length;return V(()=>{let s=!0,{mean:i,variance:o}=Qh(n,this.axis,s),l=ci(1,a);for(let f of this.axis)l[f]=r[f];let u=f=>f!=null&&f.shape.length!==a&&this.axis!==[a-1]?f.reshape(l):f,c=u(this.gamma.read()),h=u(this.beta.read()),d=[],p=[];for(let f=0;f{if(e.rank!==4)throw new B(`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 B("spatial2dPadding expects `padding` to be an Array of two Arrays, each of which is an Array of two integers.");if(n==null&&(n=yr()),n!=="channelsLast"&&n!=="channelsFirst")throw new B(`Unknown data format: ${n}. Supported data formats are 'channelsLast' and 'channelsFirst.`);let r;return n==="channelsFirst"?r=[[0,0],[0,0],t[0],t[1]]:r=[[0,0],t[0],t[1],[0,0]],Zr(e,r)})}var cg=class extends qe{constructor(e){if(e==null&&(e={}),super(e),this.dataFormat=e.dataFormat==null?yr():e.dataFormat,e.padding==null)this.padding=[[1,1],[1,1]];else if(typeof e.padding=="number")this.padding=[[e.padding,e.padding],[e.padding,e.padding]];else{if(e.padding=e.padding,e.padding.length!==2)throw new B(`ZeroPadding2D expects padding to be a length-2 array, but received a length-${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 B(`ZeroPadding2D expects height padding to be a length-2 array, but received a length-${e.padding[0].length} array.`);if(t=e.padding[0],e.padding[1].length!==2)throw new B(`ZeroPadding2D expects width padding to be a length-2 array, but received a length-${e.padding[1].length} array.`);n=e.padding[1]}this.padding=[t,n]}this.inputSpec=[new Ut({ndim:4})]}computeOutputShape(e){e=ut(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 V(()=>Qee(Le(e),this.padding,this.dataFormat))}getConfig(){let e={padding:this.padding,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}};cg.className="ZeroPadding2D";re.registerClass(cg);function Wp(e,t,n,r,a,s){return V(()=>{Tt(a),Jb(s),qn(r),n==null&&(n=[1,1]),r==null&&(r="valid"),a==null&&(a=yr()),s==null&&(s="max"),e=Fy(e,a);let i,o=r==="same"?"same":"valid";return s==="max"?i=_u(e,t,n,o):i=fu(e,t,n,o),a==="channelsFirst"&&(i=rt(i,[0,3,1,2])),i})}function l7(e,t,n,r,a,s){return V(()=>{Tt(a),Jb(s),qn(r),n==null&&(n=[1,1,1]),r==null&&(r="valid"),a==null&&(a=yr()),s==null&&(s="max"),e=n7(e,a);let i,o=r==="same"?"same":"valid";return s==="max"?i=Xf(e,t,n,o):i=zf(e,t,n,o),a==="channelsFirst"&&(i=rt(i,[0,4,1,2,3])),i})}var u7=class extends qe{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 B(`poolSize for 1D convolutional layer must be a number or an Array of a single number, but received ${JSON.stringify(e.poolSize)}`);if(Gt(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 B(`strides for 1D convolutional layer must be a number or an Array of a single number, but received ${JSON.stringify(e.strides)}`);Gt(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,qn(this.padding),this.inputSpec=[new Ut({ndim:3})]}computeOutputShape(e){e=ut(e);let t=_r(e[1],this.poolSize[0],this.padding,this.strides[0]);return[e[0],t,e[2]]}call(e,t){return V(()=>{this.invokeCallHook(e,t),e=cc(Le(e),2);let n=this.poolingFunction(Le(e),[this.poolSize[0],1],[this.strides[0],1],this.padding,"channelsLast");return ka(n,[2])})}getConfig(){let e={poolSize:this.poolSize,padding:this.padding,strides:this.strides},t=super.getConfig();return Object.assign(e,t),e}},hg=class extends u7{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return Tt(a),qn(r),Wp(e,t,n,r,a,"max")}};hg.className="MaxPooling1D";re.registerClass(hg);var dg=class extends u7{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return Tt(a),qn(r),Wp(e,t,n,r,a,"avg")}};dg.className="AveragePooling1D";re.registerClass(dg);var c7=class extends qe{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 B(`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];Gt(this.poolSize,"poolSize"),Gt(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,Tt(this.dataFormat),qn(this.padding),this.inputSpec=[new Ut({ndim:4})]}computeOutputShape(e){e=ut(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],n=this.dataFormat==="channelsFirst"?e[3]:e[2];return t=_r(t,this.poolSize[0],this.padding,this.strides[0]),n=_r(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 V(()=>(this.invokeCallHook(e,t),this.poolingFunction(Le(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}},pg=class extends c7{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return Tt(a),qn(r),Wp(e,t,n,r,a,"max")}};pg.className="MaxPooling2D";re.registerClass(pg);var fg=class extends c7{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return Tt(a),qn(r),Wp(e,t,n,r,a,"avg")}};fg.className="AveragePooling2D";re.registerClass(fg);var h7=class extends qe{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 B(`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];Gt(this.poolSize,"poolSize"),Gt(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,Tt(this.dataFormat),qn(this.padding),this.inputSpec=[new Ut({ndim:5})]}computeOutputShape(e){e=ut(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],n=this.dataFormat==="channelsFirst"?e[3]:e[2],r=this.dataFormat==="channelsFirst"?e[4]:e[3];return t=_r(t,this.poolSize[0],this.padding,this.strides[0]),n=_r(n,this.poolSize[1],this.padding,this.strides[1]),r=_r(r,this.poolSize[2],this.padding,this.strides[2]),this.dataFormat==="channelsFirst"?[e[0],e[1],t,n,r]:[e[0],t,n,r,e[4]]}call(e,t){return V(()=>(this.invokeCallHook(e,t),this.poolingFunction(Le(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}},mg=class extends h7{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return Tt(a),qn(r),l7(e,t,n,r,a,"max")}};mg.className="MaxPooling3D";re.registerClass(mg);var Ag=class extends h7{constructor(e){super(e)}poolingFunction(e,t,n,r,a){return Tt(a),qn(r),l7(e,t,n,r,a,"avg")}};Ag.className="AveragePooling3D";re.registerClass(Ag);var d7=class extends qe{constructor(e){super(e);this.inputSpec=[new Ut({ndim:3})]}computeOutputShape(e){return[e[0],e[2]]}call(e,t){throw new De}},yg=class extends d7{constructor(e){super(e||{})}call(e,t){return V(()=>{let n=Le(e);return bt(n,1)})}};yg.className="GlobalAveragePooling1D";re.registerClass(yg);var gg=class extends d7{constructor(e){super(e||{})}call(e,t){return V(()=>{let n=Le(e);return Un(n,1)})}};gg.className="GlobalMaxPooling1D";re.registerClass(gg);var p7=class extends qe{constructor(e){super(e);this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,Tt(this.dataFormat),this.inputSpec=[new Ut({ndim:4})]}computeOutputShape(e){return e=e,this.dataFormat==="channelsLast"?[e[0],e[3]]:[e[0],e[1]]}call(e,t){throw new De}getConfig(){let e={dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}},xg=class extends p7{call(e,t){return V(()=>{let n=Le(e);return this.dataFormat==="channelsLast"?bt(n,[1,2]):bt(n,[2,3])})}};xg.className="GlobalAveragePooling2D";re.registerClass(xg);var wg=class extends p7{call(e,t){return V(()=>{let n=Le(e);return 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t}},Bte=(e,t,n)=>{switch(e.op){case"BiasAdd":case"AddV2":case"Add":return[oe(k("a",e,t,n),k("b",e,t,n))];case"AddN":return[Bh(k("tensors",e,t,n))];case"FloorMod":case"Mod":return[Zf(k("a",e,t,n),k("b",e,t,n))];case"Mul":return[W(k("a",e,t,n),k("b",e,t,n))];case"RealDiv":case"Div":return[ve(k("a",e,t,n),k("b",e,t,n))];case"DivNoNan":return[Vf(k("a",e,t,n),k("b",e,t,n))];case"FloorDiv":return[Wh(k("a",e,t,n),k("b",e,t,n))];case"Sub":return[xe(k("a",e,t,n),k("b",e,t,n))];case"Minimum":return[Ho(k("a",e,t,n),k("b",e,t,n))];case"Maximum":return[Tr(k("a",e,t,n),k("b",e,t,n))];case"Pow":return[Yr(k("a",e,t,n),k("b",e,t,n))];case"SquaredDifference":return[cd(k("a",e,t,n),k("b",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}},Vte=(e,t,n)=>{switch(e.op){case"Abs":case"ComplexAbs":return[Dt(k("x",e,t,n))];case"Acos":return[Ef(k("x",e,t,n))];case"Acosh":return[Cf(k("x",e,t,n))];case"Asin":return[Ff(k("x",e,t,n))];case"Asinh":return[$f(k("x",e,t,n))];case"Atan":return[Mf(k("x",e,t,n))];case"Atan2":return[Df(k("x",e,t,n),k("y",e,t,n))];case"Atanh":return[Of(k("x",e,t,n))];case"Ceil":return[Lf(k("x",e,t,n))];case"Complex":return[wa(k("real",e,t,n),k("imag",e,t,n))];case"Cos":return[yu(k("x",e,t,n))];case"Cosh":return[Gh(k("x",e,t,n))];case"Elu":return[Bo(k("x",e,t,n))];case"Erf":return[Uf(k("x",e,t,n))];case"Exp":return[Vn(k("x",e,t,n))];case"Expm1":return[jf(k("x",e,t,n))];case"Floor":return[Vo(k("x",e,t,n))];case"Log":return[Sn(k("x",e,t,n))];case"Log1p":return[Zh(k("x",e,t,n))];case"Imag":return[Xh(k("x",e,t,n))];case"Neg":return[_t(k("x",e,t,n))];case"Reciprocal":return[Yf(k("x",e,t,n))];case"Real":return[ku(k("x",e,t,n))];case"Relu":return[Cr(k("x",e,t,n))];case"Round":return[Jf(k("x",e,t,n))];case"Selu":return[ad(k("x",e,t,n))];case"Sigmoid":return[Qn(k("x",e,t,n))];case"Sin":return[sd(k("x",e,t,n))];case"Sign":return[em(k("x",e,t,n))];case"Sinh":return[id(k("x",e,t,n))];case"Softplus":return[Uo(k("x",e,t,n))];case"Sqrt":return[Yt(k("x",e,t,n))];case"Square":return[it(k("x",e,t,n))];case"Tanh":return[Po(k("x",e,t,n))];case"Tan":return[rm(k("x",e,t,n))];case"ClipByValue":return[gn(k("x",e,t,n),k("clipValueMin",e,t,n),k("clipValueMax",e,t,n))];case"Relu6":return[nd(k("x",e,t,n))];case"Rsqrt":return[rd(kn(e.inputNames[0],t,n))];case"Prod":return[ed(k("x",e,t,n),k("axes",e,t,n))];case"LeakyRelu":return[xu(k("x",e,t,n),k("alpha",e,t,n))];case"Prelu":return[vu(k("x",e,t,n),k("alpha",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}};function ur(e,t,n=""){if(!(typeof e=="number"||typeof t=="number")){v.assert(e.length===t.length,()=>n+` Shapes ${e} and ${t} must match`);for(let r=0;rn+` Shapes ${e} and ${t} must match`)}}}function P7(e){return!(typeof e=="number"||e.some(t=>t<0))}function kc(e,t,n){let r=Dg(e,n),a=!P7(r);if(a&&t.length===0)throw new Error(`Tried to calculate elements of an empty list with non-fully-defined elementShape: ${r}`);if(a&&t.forEach(s=>{r=Dg(s.shape,r)}),!P7(r))throw new Error(`Non-fully-defined elementShape: ${r}`);return r}function Dg(e,t){if(typeof e=="number")return t;if(typeof t=="number")return e;if(e.length!==t.length)throw new Error(`Incompatible ranks during merge: ${e} vs. ${t}`);let n=[];for(let r=0;r=0&&s>=0&&a!==s)throw new Error(`Incompatible shape during merge: ${e} vs. ${t}`);n[r]=a>=0?a:s}return n}var Ute=class{constructor(e,t,n,r,a,s,i){this.name=e,this.dtype=t,this.maxSize=n,this.elementShape=r,this.identicalElementShapes=a,this.dynamicSize=s,this.clearAfterRead=i,this.tensors=[],this.closed_=!1,this.idTensor=ke(0),Vt(this.idTensor)}get id(){return this.idTensor.id}get closed(){return this.closed_}clearAndClose(e){this.tensors.forEach(t=>{(e==null||!e.has(t.tensor.id))&&t.tensor.dispose()}),this.tensors=[],this.closed_=!0,this.idTensor.dispose()}size(){return this.tensors.length}read(e){if(this.closed_)throw new Error(`TensorArray ${this.name} has already been closed.`);if(e<0||e>=this.size())throw new Error(`Tried to read from index ${e}, but array size is: ${this.size()}`);let t=this.tensors[e];if(t.cleared)throw new Error(`TensorArray ${this.name}: Could not read index ${e} twice because it was cleared after a previous read (perhaps try setting clear_after_read = false?).`);return this.clearAfterRead&&(t.cleared=!0),t.read=!0,t.tensor}readMany(e){return 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written.`);n.tensor=t,Vt(t),n.written=!0,this.tensors[e]=n}writeMany(e,t){if(e.length!==t.length)throw new Error(`TensorArray ${this.name}: could not write multiple tensors,because the index size: ${e.length} is not the same as tensors size: ${t.length}.`);e.forEach((n,r)=>this.write(n,t[r]))}gather(e,t){if(!!t&&t!==this.dtype)throw new Error(`TensorArray dtype is ${this.dtype} but gather requested dtype ${t}`);if(e)e=e.slice(0,this.size());else{e=[];for(let r=0;r=this.maxSize)throw new Error(`Max index must be < array size (${n} vs. ${this.maxSize})`);this.writeMany(e,nr(t,0))}split(e,t){if(t.dtype!==this.dtype)throw new Error(`TensorArray dtype is ${this.dtype} but tensor has dtype ${t.dtype}`);let n=0,r=e.map(o=>(n+=o,n));if(n!==t.shape[0])throw new Error(`Expected sum of lengths to be equal to tensor.shape[0], but sum of lengths is ${n}, and tensor's shape is: ${t.shape}`);if(!this.dynamicSize&&e.length!==this.maxSize)throw new Error(`TensorArray's size is not equal to the size of 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r=kc(this.elementShape,this.tensors,e);return V(()=>{let a=this.tensors.map(s=>H(s,r));return Cn(a,0)})}popBack(e,t){if(t!==this.elementDtype)throw new Error(`Invalid data types; op elements ${t}, but list elements ${this.elementDtype}`);if(this.size()===0)throw new Error("Trying to pop from an empty list.");let n=kc(this.elementShape,this.tensors,e),r=this.tensors.pop();return ur(r.shape,e,"TensorList shape mismatch: "),H(r,n)}pushBack(e){if(e.dtype!==this.elementDtype)throw new Error(`Invalid data types; op elements ${e.dtype}, but list elements ${this.elementDtype}`);if(ur(e.shape,this.elementShape,"TensorList shape mismatch: "),this.maxNumElements===this.size())throw new Error("Trying to push element into a full list.");Vt(e),this.tensors.push(e)}resize(e){if(e<0)throw new Error(`TensorListResize expects size to be non-negative. 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a=e.shape.slice(1);ur(a,t,"TensorList shape mismatch: ");let s=nr(e);return new Ic(s,t,r)}function Hte(e,t,n){return new Ic([],e,t,n)}function Gte(e,t,n,r){if(t.length!==e.shape[0])throw new Error(`Expected len(indices) == tensor.shape[0], but saw: ${t.length} vs. ${e.shape[0]}`);let a=Math.max(...t);if(r!=null&&r!==-1&&a>=r)throw new Error(`Max index must be < array size (${a} vs. ${r})`);let s=new Ic([],n,e.dtype,r),i=nr(e,0);return t.forEach((o,l)=>{s.setItem(o,i[l])}),s}function qte(e,t,n){let r=0,a=t.map(c=>(r+=c,r));if(r!==e.shape[0])throw new Error(`Expected sum of lengths to be equal to tensor.shape[0], but sum of lengths is ${r}, and tensor's shape is: ${e.shape}`);let s=e.shape.slice(1),i=Dg(s,n),o=r===0?0:e.size/r,l=V(()=>{let c=[];e=H(e,[1,r,o]);for(let h=0;h{switch(e.op){case"If":case"StatelessIf":{let r=k("thenBranch",e,t,n),a=k("elseBranch",e,t,n),s=k("cond",e,t,n),i=k("args",e,t,n);return(await 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0,a]:[a,void 0]}case"Merge":{let r=e.inputNames.find(a=>kn(a,t,n)!==void 0);if(r){let a=kn(r,t,n);return[oa(a)]}return}case"Enter":{let r=k("frameName",e,t,n),a=k("tensor",e,t,n);return n.enterFrame(r),[oa(a)]}case"Exit":{let r=k("tensor",e,t,n);return n.exitFrame(),[oa(r)]}case"NextIteration":{let r=k("tensor",e,t,n);return n.nextIteration(),[oa(r)]}case"TensorArrayV3":{let r=k("size",e,t,n),a=k("dtype",e,t,n),s=k("elementShape",e,t,n),i=k("dynamicSize",e,t,n),o=k("clearAfterRead",e,t,n),l=k("identicalElementShapes",e,t,n),u=k("name",e,t,n),c=new Ute(u,a,r,s,l,i,o);return n.addTensorArray(c),[c.idTensor,ke(1)]}case"TensorArrayWriteV3":{let r=k("tensorArrayId",e,t,n),a=k("index",e,t,n),s=k("tensor",e,t,n),i=n.getTensorArray(r.id);return i.write(a,s),[i.idTensor]}case"TensorArrayReadV3":{let r=k("tensorArrayId",e,t,n),a=k("index",e,t,n);return[n.getTensorArray(r.id).read(a)]}case"TensorArrayGatherV3":{let r=k("tensorArrayId",e,t,n),a=k("indices",e,t,n),s=k("dtype",e,t,n);return[n.getTensorArray(r.id).gather(a,s)]}case"TensorArrayScatterV3":{let r=k("tensorArrayId",e,t,n),a=k("indices",e,t,n),s=k("tensor",e,t,n),i=n.getTensorArray(r.id);return i.scatter(a,s),[i.idTensor]}case"TensorArrayConcatV3":{let r=k("tensorArrayId",e,t,n),a=n.getTensorArray(r.id),s=k("dtype",e,t,n);return[a.concat(s)]}case"TensorArraySplitV3":{let r=k("tensorArrayId",e,t,n),a=k("tensor",e,t,n),s=k("lengths",e,t,n),i=n.getTensorArray(r.id);return i.split(s,a),[i.idTensor]}case"TensorArraySizeV3":{let r=k("tensorArrayId",e,t,n),a=n.getTensorArray(r.id);return[ke(a.size(),"int32")]}case"TensorArrayCloseV3":{let r=k("tensorArrayId",e,t,n),a=n.getTensorArray(r.id);return a.clearAndClose(),[a.idTensor]}case"TensorListSetItem":{let r=k("tensorListId",e,t,n),a=k("index",e,t,n),s=k("tensor",e,t,n),i=n.getTensorList(r.id);return i.setItem(a,s),[i.idTensor]}case"TensorListGetItem":{let r=k("tensorListId",e,t,n),a=k("index",e,t,n),s=k("elementShape",e,t,n),i=k("elementDType",e,t,n);return[n.getTensorList(r.id).getItem(a,s,i)]}case"TensorListScatterV2":case"TensorListScatter":{let r=k("indices",e,t,n),a=k("tensor",e,t,n),s=k("elementShape",e,t,n),i=k("numElements",e,t,n),o=Gte(a,r,s,i);return n.addTensorList(o),[o.idTensor]}case"TensorListReserve":case"EmptyTensorList":{let r=k("elementShape",e,t,n),a=k("elementDType",e,t,n),s;e.op==="TensorListReserve"?s="numElements":s="maxNumElements";let i=k(s,e,t,n),o=Hte(r,a,i);return n.addTensorList(o),[o.idTensor]}case"TensorListGather":{let r=k("tensorListId",e,t,n),a=k("indices",e,t,n),s=k("elementShape",e,t,n),i=k("elementDType",e,t,n);return[n.getTensorList(r.id).gather(a,i,s)]}case"TensorListStack":{let r=k("tensorListId",e,t,n),a=k("elementShape",e,t,n),s=k("elementDType",e,t,n),i=k("numElements",e,t,n);return[n.getTensorList(r.id).stack(a,s,i)]}case"TensorListFromTensor":{let 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k("x",e,t,n).map(u=>tn(u.shape));case"Size":return[ke(k("x",e,t,n).size,"int32")];case"Rank":return[ke(k("x",e,t,n).rank,"int32")];case"NoOp":return[ke(1)];case"Print":let s=k("x",e,t,n),i=k("data",e,t,n),o=k("message",e,t,n),l=k("summarize",e,t,n);console.warn("The graph has a tf.print() operation,usually used for debugging, which slows down performance."),console.log(o);for(let u=0;ue.dispose()),this.tensorMap.clear(),this.handle.dispose()}size(){return this.tensorMap.size}async import(e,t){this.checkKeyAndValueTensor(e,t);let n=await e.data();return this.tensorMap.forEach(r=>r.dispose()),this.tensorMap.clear(),V(()=>{let r=nr(t),a=n.length,s=r.length;v.assert(a===s,()=>`The number of elements doesn't match, keys has ${a} elements, the values has ${s} elements.`);for(let i=0;i{let r=[];for(let a=0;a{switch(e.op){case"HashTable":case"HashTableV2":{let a=k("keyDType",e,t,n),s=k("valueDType",e,t,n),i=new ene(a,s);return 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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 j7(e,t,n,r){let a=new Set,s=[],i=null,o=null,l=new Set,u=Object.keys(e).map(d=>Dn(d)[0]),c=[];r!=null&&(c=r.map(d=>Dn(d.name)[0]));let h=[...t];for(;h.length>0;){let d=h.pop();if((U7(d)||cne(d)||hne(d))&&i==null&&(i=d,o=i.children.map(p=>p.name).filter(p=>a.has(p))),a.add(d.name),n[d.name]==null&&u.indexOf(d.name)===-1&&c.indexOf(d.name)===-1){if(d.inputs.length===0){s.push(d.name);continue}d.inputs.forEach(p=>{l.has(p.name)||(l.add(p.name),h.push(p))})}}return{inputs:e,outputs:t,usedNodes:a,missingInputs:s,dynamicNode:i,syncInputs:o}}function dne(e,t,n){let{usedNodes:r,inputs:a}=n,s=[],i=Object.keys(a).map(c=>Dn(c)[0]).map(c=>e.nodes[c]),o=e.initNodes;i.forEach(c=>{r.has(c.name)&&s.push(c)}),e.weights.forEach(c=>{r.has(c.name)&&s.push(c)}),o!=null&&o.forEach(c=>{r.has(c.name)&&s.push(c)});let l=new Set,u=[];for(;s.length>0;){let c=s.pop();l.add(c.name),t[c.name]||u.push(c),c.children.forEach(h=>{!l.has(h.name)&&r.has(h.name)&&h.inputs.every(d=>l.has(d.name))&&s.push(h)})}return u}var pne=["Switch","Merge","Enter","Exit","NextIteration","StatelessIf","StatelessWhile","if","While"],fne=["NonMaxSuppressionV2","NonMaxSuppressionV3","NonMaxSuppressionV5","Where"],mne=["HashTable","HashTableV2","LookupTableImport","LookupTableImportV2","LookupTableFind","LookupTableFindV2"];function U7(e){return pne.indexOf(e.op)>=0}function cne(e){return fne.indexOf(e.op)>=0}function hne(e){return mne.indexOf(e.op)>=0}var zg=class{constructor(e,t){this.graph=e,this.parent=t,this.compiledMap=new Map,this._weightMap={},this.SEPERATOR=",",this._functions={},this._functionExecutorMap={},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 zg(e.functions[n],this)})}get weightIds(){return this.parent?this.parent.weightIds:this._weightIds}get functionExecutorMap(){return this.parent?this.parent.functionExecutorMap:this._functionExecutorMap}get weightMap(){return this.parent?this.parent.weightMap:this._weightMap}set weightMap(e){let t=Object.keys(e).map(n=>e[n].map(r=>r.id));this._weightIds=[].concat(...t),this._weightMap=e}set resourceManager(e){this._resourceManager=e}get inputs(){return this._inputs.map(e=>({name:e.name,shape:e.attrParams.shape?e.attrParams.shape.value:void 0,dtype:e.attrParams.dtype?e.attrParams.dtype.value:void 0}))}get outputs(){return 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u}processChildNodes(e,t,n,r,a,s){e.children.forEach(i=>{let[o]=ia(i.name,n);a[o]||!s.has(i.name)||(i.op==="Merge"?i.inputNames.some(l=>!!kn(l,r,n))&&(a[o]=!0,t.push({contexts:n.currentContext,node:i})):i.inputNames.every(l=>!!kn(l,r,n))&&(a[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],[r]=Dn(t),a=this.graph.nodes[r];if(a.attrParams.shape&&a.attrParams.shape.value){let s=a.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['${a.name}'] provided in model.execute(dict) must be [${s}], but was [${n.shape}]`)}a.attrParams.dtype&&a.attrParams.dtype.value&&v.assert(n.dtype===a.attrParams.dtype.value,()=>`The dtype of dict['${a.name}'] provided in model.execute(dict) must be ${a.attrParams.dtype.value}, but was ${n.dtype}`)})}mapInputs(e){let t={};for(let n in e)if(this._signature!=null&&this._signature.inputs!=null&&this._signature.inputs[n]!=null){let r=this._signature.inputs[n];t[r.name]=e[n]}else t[n]=e[n];return t}checkInputs(e){let t=Object.keys(e).filter(n=>{let[r]=Dn(n);return this.graph.nodes[r]==null});if(t.length>0)throw new Error(`The dict provided in model.execute(dict) has keys: [${t}] that are not part of graph`)}mapOutputs(e){return e.map(t=>this._signature!=null&&this._signature.outputs!=null&&this._signature.outputs[t]!=null?this._signature.outputs[t].name:t,{})}checkOutputs(e){e.forEach(t=>{let[n]=Dn(t);if(!this.graph.nodes[n])throw new Error(`The output '${t}' is not found in the graph`)})}},Ane=class{constructor(e={},t={}){this.hashTableNameToHandle=e,this.hashTableMap=t}addHashTable(e,t){this.hashTableNameToHandle[e]=t.handle,this.hashTableMap[t.id]=t}getHashTableHandleByName(e){return this.hashTableNameToHandle[e]}getHashTableById(e){return this.hashTableMap[e]}dispose(){for(let e in this.hashTableMap)this.hashTableMap[e].clearAndClose(),delete this.hashTableMap[e];for(let e in this.hashTableNameToHandle)this.hashTableNameToHandle[e].dispose(),delete this.hashTableNameToHandle[e]}},yne="?tfjs-format=file",gne="model.json",L0=class{constructor(e,t={}){this.modelUrl=e,this.loadOptions=t,this.version="n/a",t==null&&(this.loadOptions={}),this.resourceManager=new Ane}get modelVersion(){return this.version}get inputNodes(){return this.executor.inputNodes}get outputNodes(){return this.executor.outputNodes}get inputs(){return this.executor.inputs}get outputs(){return this.executor.outputs}get weights(){return this.executor.weightMap}get metadata(){return this.artifacts.userDefinedMetadata}get modelSignature(){return this.signature}findIOHandler(){let e=this.modelUrl;if(e.load!=null)this.handler=e;else if(this.loadOptions.requestInit!=null)this.handler=yn.browserHTTPRequest(e,this.loadOptions);else{let t=yn.getLoadHandlers(e,this.loadOptions);if(t.length===0)t.push(yn.browserHTTPRequest(e,this.loadOptions));else if(t.length>1)throw new Error(`Found more than one (${t.length}) load handlers for URL '${[e]}'`);this.handler=t[0]}}async load(){if(this.findIOHandler(),this.handler.load==null)throw new Error("Cannot proceed with model loading because the IOHandler provided does not have the `load` method implemented.");let e=await this.handler.load();return this.loadSync(e)}loadSync(e){this.artifacts=e;let t=this.artifacts.modelTopology,n;this.artifacts.userDefinedMetadata!=null&&this.artifacts.userDefinedMetadata.signature!=null?n=this.artifacts.userDefinedMetadata.signature:n=this.artifacts.signature,this.signature=n,this.version=`${t.versions.producer}.${t.versions.minConsumer}`;let r=yn.decodeWeights(this.artifacts.weightData,this.artifacts.weightSpecs);if(this.executor=new zg(O7.Instance.transformGraph(t,this.signature)),this.executor.weightMap=this.convertTensorMapToTensorsMap(r),this.executor.resourceManager=this.resourceManager,e.modelInitializer!=null&&e.modelInitializer.node!=null){let a=O7.Instance.transformGraph(e.modelInitializer);this.initializer=new zg(a),this.initializer.weightMap=this.executor.weightMap,this.initializer.resourceManager=this.resourceManager,this.initializer.executeAsync({},[])}return!0}async save(e,t){if(typeof e=="string"){let n=yn.getSaveHandlers(e);if(n.length===0)throw new Error(`Cannot find any save handlers for URL '${e}'`);if(n.length>1)throw new Error(`Found more than one (${n.length}) save handlers for URL '${e}'`);e=n[0]}if(e.save==null)throw new Error("GraphModel.save() cannot proceed because the IOHandler provided does not have the `save` attribute defined.");return e.save(this.artifacts)}predict(e,t){return this.execute(e,this.outputNodes)}normalizeInputs(e){if(!(e instanceof Ye)&&!Array.isArray(e))return e;if(e=Array.isArray(e)?e:[e],e.length!==this.inputNodes.length)throw new Error(`Input tensor count mismatch,the graph model has ${this.inputNodes.length} placeholders, while there are ${e.length} input tensors.`);return this.inputNodes.reduce((t,n,r)=>(t[n]=e[r],t),{})}normalizeOutputs(e){return e=e||this.outputNodes,Array.isArray(e)?e:[e]}execute(e,t){e=this.normalizeInputs(e),t=this.normalizeOutputs(t);let n=this.executor.execute(e,t);return n.length>1?n:n[0]}async executeAsync(e,t){e=this.normalizeInputs(e),t=this.normalizeOutputs(t);let n=await this.executor.executeAsync(e,t);return n.length>1?n:n[0]}convertTensorMapToTensorsMap(e){return Object.keys(e).reduce((t,n)=>(t[n]=[e[n]],t),{})}dispose(){this.executor.dispose(),this.initializer&&this.initializer.dispose(),this.resourceManager.dispose()}};async function Yn(e,t={}){if(e==null)throw new Error("modelUrl in loadGraphModel() cannot be null. Please provide a url or an IOHandler that loads the model");t==null&&(t={}),t.fromTFHub&&e.load==null&&(e.endsWith("/")||(e=e+"/"),e=`${e}${gne}${yne}`);let n=new L0(e,t);return await n.load(),n}var _8="3.2.0",P0={};ze(P0,{CSVDataset:()=>G7,Dataset:()=>Tl,FileDataSource:()=>q7,TextLineDataset:()=>H7,URLDataSource:()=>X7,array:()=>xne,csv:()=>_ne,func:()=>bne,generator:()=>vne,microphone:()=>Ine,version_data:()=>Nne,webcam:()=>kne,zip:()=>wne});var Sne=Zo(W0()),Tne=Zo(W0());function Ene(e,t){return jp(e,t)}function jp(e,t,n=new Map,r=new Set){if(e==null)return null;if(r.has(e))throw new Error("Circular references are not supported.");if(n.has(e))return n.get(e);let a=t(e);if(a.recurse&&a.value!==null)throw new Error("A deep map function may not return both a value and recurse=true.");if(a.recurse)if(El(e)){let s=Array.isArray(e)?[]:{};r.add(e);for(let i in e){let o=e[i],l=jp(o,t,n,r);s[i]=l}return r.delete(e),s}else throw new Error(`Can't recurse into non-iterable type: ${e}`);else return n.set(e,a.value),a.value}function Cne(e,t=Z7){return K7(e,t)}function K7(e,t,n=new Set){let r=e[0];if(n.has(r))throw new Error("Circular references are not supported.");let a=t(e);if(a.recurse&&a.value!==null)throw new Error("A deep zip function may not return both a value and recurse=true.");if(a.recurse)if(El(r)){let s=Array.isArray(r)?[]:{};n.add(r);for(let i in r){let o=e.map(u=>u[i]),l=K7(o,t,n);s[i]=l}return n.delete(r),s}else throw new Error(`Can't recurse into non-iterable type: ${r}`);else return a.value}function Z7(e){return e===null?null:El(e[0])?{value:null,recurse:!0}:{value:e,recurse:!1}}async function Y7(e,t){let n=new Map;jp(e,t,n);for(let r of Array.from(n.keys())){let a=n.get(r);if(v.isPromise(a)){let s=await a;n.set(r,s)}}return jp(e,t,n)}function El(e){return e!=null&&!ArrayBuffer.isView(e)&&(Array.isArray(e)||typeof e=="object"&&!(e instanceof Ye))}function Fne(e){return e==null||Rne(e)||Array.isArray(e)||typeof e=="object"&&e instanceof Ye||v.isTypedArray(e)}function Rne(e){return e===null||typeof e!="object"&&typeof e!="function"}function Mne(e){return Ene(e,$ne)}function $ne(e){return e instanceof Ye?{value:e.clone(),recurse:!1}:El(e)?{value:null,recurse:!0}:{value:e,recurse:!1}}var J7=class{constructor(e){if(this.capacity=e,this.begin=0,this.end=0,e==null)throw new RangeError("Can't create a ring buffer of unknown capacity.");if(e<1)throw new RangeError("Can't create ring buffer of capacity < 1.");this.data=new Array(e),this.doubledCapacity=2*e}wrap(e){for(;e<0;)e+=this.doubledCapacity;return e%this.doubledCapacity}get(e){if(e<0)throw new RangeError("Can't get item at a negative index.");return this.data[e%this.capacity]}set(e,t){if(e<0)throw new RangeError("Can't set item at a negative index.");this.data[e%this.capacity]=t}length(){let e=this.end-this.begin;return e<0&&(e=this.doubledCapacity+e),e}isFull(){return this.length()===this.capacity}isEmpty(){return this.length()===0}push(e){if(this.isFull())throw new RangeError("Ring buffer is full.");this.set(this.end,e),this.end=this.wrap(this.end+1)}pushAll(e){for(let t of e)this.push(t)}pop(){if(this.isEmpty())throw new RangeError("Ring buffer is empty.");this.end=this.wrap(this.end-1);let e=this.get(this.end);return this.set(this.end,void 0),e}unshift(e){if(this.isFull())throw new RangeError("Ring buffer is full.");this.begin=this.wrap(this.begin-1),this.set(this.begin,e)}shift(){if(this.isEmpty())throw new RangeError("Ring buffer is empty.");let e=this.get(this.begin);return this.set(this.begin,void 0),this.begin=this.wrap(this.begin+1),e}shuffleExcise(e){if(this.isEmpty())throw new RangeError("Ring buffer is empty.");let t=this.wrap(this.begin+e),n=this.get(t);return this.set(t,this.pop()),n}},Lg=class extends J7{constructor(){super(Lg.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 r=0;rt===!0)}rowMajorBatch(e,t=!0){return new Une(this,e,t)}columnMajorBatch(e,t=!0,n=Z7){return this.rowMajorBatch(e,t).map(r=>Cne(r,n))}concatenate(e,t){return new ev(Q7([this,e]),t)}take(e){return e<0||e==null?this:new Vne(this,e)}skip(e){return e<0||e==null?this:new Bne(this,e)}prefetch(e){return new nv(this,e)}shuffle(e,t){return new Xne(this,e,t)}serial(){return new Wne(this)}},Dne=class extends qt{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:Mne(e),done:!1}}},One=class extends qt{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: ${e.message}`,e}}},Wne=class extends qt{constructor(e){super();this.upstream=e,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> Serial`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){return this.upstream.next()}},Bne=class extends qt{constructor(e,t){super();this.upstream=e,this.maxCount=t,this.count=0,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> Skip`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){for(;this.count++ Take`}async next(){return this.count++>=this.maxCount?{value:null,done:!0}:this.upstream.next()}},Une=class extends qt{constructor(e,t,n=!0){super();this.upstream=e,this.batchSize=t,this.enableSmallLastBatch=n,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> RowMajorBatch`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){let e=[];for(;e.length0?{value:e,done:!1}:{value:null,done:!0};e.push(t.value)}return{value:e,done:!1}}},jne=class extends qt{constructor(e,t){super();this.upstream=e,this.predicate=t,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> Filter`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){for(;;){let e=await this.upstream.next();if(e.done||this.predicate(e.value))return e;Re(e.value)}}},Hne=class extends qt{constructor(e,t){super();this.upstream=e,this.transform=t}summary(){return`${this.upstream.summary()} -> Map`}async next(){let e=await this.upstream.next();if(e.done)return{value:null,done:!0};let t=hr.getTensorsInContainer(e.value),n=this.transform(e.value),r=hr.getTensorsInContainer(n);for(let a of t)hr.isTensorInList(a,r)||a.dispose();return{value:n,done:!1}}},Gne=class extends qt{constructor(e,t){super();this.upstream=e,this.handler=t,this.count=0,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> handleErrors`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){for(;;)try{return await this.upstream.next()}catch(e){if(!this.handler(e))return{value:null,done:!0}}}},tv=class extends qt{constructor(e,t){super();this.upstream=e,this.transform=t}summary(){return`${this.upstream.summary()} -> AsyncMap`}async next(){let e=await this.upstream.next();if(e.done)return{value:null,done:!0};let t=hr.getTensorsInContainer(e.value),n=await this.transform(e.value),r=hr.getTensorsInContainer(n);for(let a of t)hr.isTensorInList(a,r)||a.dispose();return{value:n,done:!1}}},Wg=class extends qt{constructor(){super();this.outputQueue=new Lg,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}}},qne=class extends Wg{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=hr.getTensorsInContainer(e.value),n=this.transform(e.value),r=hr.getTensorsInContainer(n);this.outputQueue.pushAll(n);for(let a of t)hr.isTensorInList(a,r)||a.dispose();return!0}},ev=class extends qt{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}},Va;(function(e){e[e.FAIL=0]="FAIL",e[e.SHORTEST=1]="SHORTEST",e[e.LONGEST=2]="LONGEST"})(Va||(Va={}));var Lne=class extends qt{constructor(e,t=Va.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 r(s){return s instanceof qt?{value:s.next().then(i=>(t++,i.done&&n++,i.value)),recurse:!1}:{value:null,recurse:!0}}let a=await Y7(this.iterators,r);if(t===n)return{value:null,done:!0};if(n>0)switch(this.mismatchMode){case Va.FAIL:throw new Error(`Zipped streams should have the same length. Mismatched at element ${this.count}.`);case Va.SHORTEST:return{value:null,done:!0};case Va.LONGEST:default:}return this.count++,{value:a,done:!1}}async next(){return this.currentPromise=this.nextState(this.currentPromise),this.currentPromise}},nv=class extends qt{constructor(e,t){super();this.upstream=e,this.bufferSize=t,this.buffer=new J7(t)}summary(){return`${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()}},Xne=class extends nv{constructor(e,t,n){super(e,t);this.upstream=e,this.windowSize=t,this.upstreamExhausted=!1,this.random=Tne.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}}},Tl=class{constructor(){this.size=null}batch(e,t=!0){let n=this;v.assert(e>0,()=>`batchSize needs to be positive, but it is ${e}`);let r;return this.size===Infinity||this.size==null?r=this.size:t?r=Math.ceil(this.size/e):r=Math.floor(this.size/e),On(async()=>(await n.iterator()).columnMajorBatch(e,t,Kne),r)}concatenate(e){let t=this,n;return this.size===Infinity||e.size===Infinity?n=Infinity:this.size!=null&&e.size!=null?n=this.size+e.size:n=null,On(async()=>(await t.iterator()).concatenate(await e.iterator()),n)}filter(e){let t=this,n;return this.size===Infinity?n=Infinity:n=null,On(async()=>(await t.iterator()).filter(r=>V(()=>e(r))),n)}async forEachAsync(e){return(await this.iterator()).forEachAsync(e)}map(e){let t=this;return On(async()=>(await t.iterator()).map(n=>V(()=>e(n))),this.size)}mapAsync(e){let t=this;return On(async()=>(await t.iterator()).mapAsync(e),this.size)}prefetch(e){if(e==null)throw new RangeError("`Dataset.prefetch()` requires bufferSize to be specified.");let t=this;return On(async()=>(await t.iterator()).prefetch(e),this.size)}repeat(e){let t=this,n;return this.size!=null&&e>0?n=this.size*e:e===0?n=0:this.size!=null&&(e===void 0||e<0)?n=Infinity:n=null,On(async()=>{let r=Pg(async()=>({value:await t.iterator(),done:!1}));return zne(r.take(e))},n)}skip(e){let t=this,n;return this.size!=null&&e>=0&&this.size>=e?n=this.size-e:this.size!=null&&(this.size(await t.iterator()).skip(e),n)}shuffle(e,t,n=!0){if(e==null||e<0)throw this.size==null?new RangeError("`Dataset.shuffle()` requires bufferSize to be specified."):new RangeError(`\`Dataset.shuffle()\` requires bufferSize to be specified. If your data fits in main memory (for regular JS objects), and/or GPU memory (for \`tf.Tensor\`s), consider setting bufferSize to the dataset size (${this.size} elements)`);let r=this,a=Sne.alea(t||v.now().toString());return On(async()=>{let s=a.int32();return n&&(s+=a.int32()),(await r.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,On(async()=>(await t.iterator()).take(e),n)}async toArray(){if(this.size===Infinity)throw new Error("Can not convert infinite data stream to array.");return(await this.iterator()).toArray()}async toArrayForTest(){if(this.size===Infinity)throw new Error("Can not convert infinite data stream to array.");return(await this.iterator()).toArrayForTest()}};Tl.MAX_BUFFER_SIZE=1e4;function On(e,t=null){return new class extends Tl{constructor(){super(...arguments);this.size=t}async iterator(){return e()}}}function xne(e){return On(async()=>Q7(e),e.length)}function wne(e){if(!El(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{let n=await Y7(e,r=>{if(r instanceof Tl)return{value:r.iterator(),recurse:!1};if(El(r))return{value:null,recurse:!0};throw new Error("Leaves of the structure passed to zip() must be Datasets, not primitives.")});return Pne(n,Va.SHORTEST)},t)}function Kne(e){if(e===null)return null;let t=e[0];return Fne(t)?{value:Zne(e),recurse:!1}:{value:null,recurse:!0}}function Zne(e){if(e.length===0)throw new Error("Can't make a batch of zero elements.");return e[0]instanceof Ye?Cn(e):dr(e)}var H7=class extends Tl{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))}},Hp='"',Nc=Symbol("out"),rv=Symbol("field"),Gp=Symbol("quote"),Bg=Symbol("quoteafterquote"),av=Symbol("quoteinquote"),G7=class extends Tl{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 H7(e),t||(t={}),this.hasHeader=t.hasHeader!==!1,this.fullColumnNames=t.columnNames,this.columnConfigs=t.columnConfigs,this.configuredColumnsOnly=t.configuredColumnsOnly,t.delimWhitespace?(v.assert(t.delimiter==null,()=>"Delimiter should not be provided when delimWhitespace is true."),this.delimWhitespace=!0,this.delimiter=" "):this.delimiter=t.delimiter?t.delimiter:","}async columnNames(){return this.columnNamesValidated||await this.setColumnNames(),this.configuredColumnsOnly?Object.keys(this.columnConfigs):this.fullColumnNames}async setColumnNames(){let e=await this.maybeReadHeaderLine();if(!this.fullColumnNames&&!e)throw new Error("Column names must be provided if there is no header line.");this.fullColumnNames&&e&&v.assert(e.length===this.fullColumnNames.length,()=>"The length of provided columnNames ("+this.fullColumnNames.length.toString()+") does not match the length of the header line read from file ("+e.length.toString()+")."),this.fullColumnNames||(this.fullColumnNames=e);let t=this.fullColumnNames.reduce((r,a)=>(r[a]=r[a]+1||1,r),{}),n=Object.keys(t).filter(r=>t[r]>1);if(v.assert(n.length===0,()=>"Duplicate column names found: "+n.toString()),this.columnConfigs){for(let r of Object.keys(this.columnConfigs))if(this.fullColumnNames.indexOf(r)===-1)throw new Error('The key "'+r+'" provided in columnConfigs does not match any of the column names ('+this.fullColumnNames.toString()+").")}this.columnNamesValidated=!0}async maybeReadHeaderLine(){if(this.hasHeader){let e=await(await this.base.iterator()).next();if(e.done)throw new Error("No data was found for CSV parsing.");let t=e.value;return this.parseRow(t,!1)}else return null}async iterator(){this.columnNamesValidated||await this.setColumnNames();let e=await this.base.iterator();return this.hasHeader&&(e=e.skip(1)),e.map(t=>this.makeDataElement(t))}makeDataElement(e){let t=this.parseRow(e),n={},r={};for(let a=0;a14||!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(Y().get("IS_NODE"))throw new Error("microphone API is only supported in browser environment.");let t=new sv(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 r=this.flattenQueue(n.freqDataQueue);e=this.getTensorFromAudioDataArray(r,[this.numFrames,this.columnTruncateLength,1])}if(this.includeWaveform){let r=this.flattenQueue(n.timeDataQueue);t=this.getTensorFromAudioDataArray(r,[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(r=>{let a=setInterval(()=>{this.includeSpectrogram&&(this.analyser.getFloatFrequencyData(this.freqData),this.freqData[0]===-Infinity&&r({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(a),r({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((r,a)=>n.set(r,a*t)),n}getTensorFromAudioDataArray(e,t){let n=new Float32Array(v.sizeFromShape(t));return n.set(e,n.length-e.length),dr(n,t)}},iv=class extends qt{constructor(e,t){super();if(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=tn([0],"int32"),this.webcamConfig.centerCrop){let n=this.webcamConfig.resizeWidth*1/this.webcamVideoElement.width,r=this.webcamConfig.resizeHeight*1/this.webcamVideoElement.height,a=(1-n)/2,s=(1-r)/2,i=a+n,o=r+s;this.cropBox=pr([s,a,o,i],[1,4])}else this.cropBox=pr([0,0,1,1],[1,4])}summary(){return"webcam"}static async create(e,t={}){if(Y().get("IS_NODE"))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 iv(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=cu.fromPixels(this.webcamVideoElement)}catch(t){throw new Error(`Error thrown converting video to pixels: ${JSON.stringify(t)}`)}if(this.resize)try{return{value:this.cropAndResizeFrame(e),done:!1}}catch(t){throw new Error(`Error thrown cropping the video: ${t.message}`)}finally{e.dispose()}else return{value:e,done:!1}}needToResize(){return!!(this.webcamConfig.resizeWidth&&this.webcamConfig.resizeHeight&&(this.webcamVideoElement.width!==this.webcamConfig.resizeWidth||this.webcamVideoElement.height!==this.webcamConfig.resizeHeight))}cropAndResizeFrame(e){return V(()=>{let t=Nn(Ae(e,"float32"),0),n;n=St.cropAndResize(t,this.cropBox,this.cropBoxInd,this.cropSize,"bilinear");let r=n.shape;return H(n,r.slice(1))})}async capture(){return(await this.next()).value}stop(){this.stream.getTracks().forEach(e=>e.stop());try{this.webcamVideoElement.srcObject=null}catch(e){console.log(e),this.webcamVideoElement.src=null}this.isClosed=!0}toArray(){throw new Error("Can not convert infinite video stream to array.")}},ov=class{},lv=class extends qt{split(e){return new Yne(this,e)}},Yne=class extends lv{constructor(e,t){super();this.upstream=e,this.impl=new Jne(e,t)}summary(){return this.impl.summary()}async next(){return this.impl.next()}},Jne=class extends Wg{constructor(e,t){super();this.upstream=e,this.separator=t,this.carryover=""}summary(){return`${this.upstream.summary()} -> Split('${this.separator}')`}async pump(){let e=await this.upstream.next();if(e.done)return this.carryover===""?!1:(this.outputQueue.push(this.carryover),this.carryover="",!0);let t=e.value.split(this.separator);t[0]=this.carryover+t[0];for(let n of t.slice(0,-1))this.outputQueue.push(n);return this.carryover=t[t.length-1],!0}},ere=class extends qt{decodeUTF8(){return new Qne(this)}},Qne=class extends lv{constructor(e){super();this.upstream=e,this.impl=new tre(e)}summary(){return this.impl.summary()}async next(){return this.impl.next()}},tre=class extends Wg{constructor(e){super();if(this.upstream=e,Y().get("IS_BROWSER"))this.decoder=new TextDecoder("utf-8");else{let{StringDecoder:t}=ak();this.decoder=new t("utf8")}}summary(){return`${this.upstream.summary()} -> Utf8`}async pump(){let e=await this.upstream.next(),t;if(e.done)return!1;t=e.value;let n;return Y().get("IS_BROWSER")?n=this.decoder.decode(t,{stream:!0}):n=this.decoder.write(Buffer.from(t.buffer)),this.outputQueue.push(n),!0}},uv=class extends ere{constructor(e,t={}){super();this.file=e,this.options=t,v.assert(e instanceof Uint8Array||(Y().get("IS_BROWSER")?e instanceof File||e instanceof Blob:!1),()=>"FileChunkIterator only supports File, Blob and Uint8Array right now."),this.offset=t.offset||0,this.chunkSize=t.chunkSize||1024*1024}summary(){return`FileChunks ${this.file}`}async next(){return this.offset>=(this.file instanceof Uint8Array?this.file.byteLength:this.file.size)?{value:null,done:!0}:{value:await new Promise((e,t)=>{let n=this.offset+this.chunkSize;if(this.file instanceof Uint8Array)e(new Uint8Array(this.file.slice(this.offset,n)));else{let r=new FileReader;r.onload=s=>{let i=r.result;if(i instanceof 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o=m2(A2(i),jv),l={confidence:i.confidence,box:{topLeft:o.startPoint,bottomRight:o.endPoint}};a.push(l)}}return this.storedBoxes=this.storedBoxes.filter(s=>s!==null),this.detectedHands=a.length,a}calculateLandmarksBoundingBox(e){let t=e.map(s=>s[0]),n=e.map(s=>s[1]),r=[Math.min(...t),Math.min(...n)],a=[Math.max(...t),Math.max(...n)];return{startPoint:r,endPoint:a}}},pae=[{w:1,h:1,x_center:.015625,y_center:.015625},{w:1,h:1,x_center:.015625,y_center:.015625},{w:1,h:1,x_center:.046875,y_center:.015625},{w:1,h:1,x_center:.046875,y_center:.015625},{w:1,h:1,x_center:.078125,y_center:.015625},{w:1,h:1,x_center:.078125,y_center:.015625},{w:1,h:1,x_center:.109375,y_center:.015625},{w:1,h:1,x_center:.109375,y_center:.015625},{w:1,h:1,x_center:.140625,y_center:.015625},{w:1,h:1,x_center:.140625,y_center:.015625},{w:1,h:1,x_center:.171875,y_center:.015625},{w:1,h:1,x_center:.171875,y_center:.015625},{w:1,h:1,x_center:.203125,y_center:.015625},{w:1,h:1,x_center:.203125,y_center:.015625},{w:1,h:1,x_center:.234375,y_center:.015625},{w:1,h:1,x_center:.234375,y_center:.015625},{w:1,h:1,x_center:.265625,y_center:.015625},{w:1,h:1,x_center:.265625,y_center:.015625},{w:1,h:1,x_center:.296875,y_center:.015625},{w:1,h:1,x_center:.296875,y_center:.015625},{w:1,h:1,x_center:.328125,y_center:.015625},{w:1,h:1,x_center:.328125,y_center:.015625},{w:1,h:1,x_center:.359375,y_center:.015625},{w:1,h:1,x_center:.359375,y_center:.015625},{w:1,h:1,x_center:.390625,y_center:.015625},{w:1,h:1,x_center:.390625,y_center:.015625},{w:1,h:1,x_center:.421875,y_center:.015625},{w:1,h:1,x_center:.421875,y_center:.015625},{w:1,h:1,x_center:.453125,y_center:.015625},{w:1,h:1,x_center:.453125,y_center:.015625},{w:1,h:1,x_center:.484375,y_center:.015625},{w:1,h:1,x_center:.484375,y_center:.015625},{w:1,h:1,x_center:.515625,y_center:.015625},{w:1,h:1,x_center:.515625,y_center:.015625},{w:1,h:1,x_center:.546875,y_center:.015625},{w:1,h:1,x_center:.546875,y_center:.015625},{w:1,h:1,x_center:.578125,y_center:.015625},{w:1,h:1,x_center:.578125,y_center:.015625},{w:1,h:1,x_center:.609375,y_center:.015625},{w:1,h:1,x_center:.609375,y_center:.015625},{w:1,h:1,x_center:.640625,y_center:.015625},{w:1,h:1,x_center:.640625,y_center:.015625},{w:1,h:1,x_center:.671875,y_center:.015625},{w:1,h:1,x_center:.671875,y_center:.015625},{w:1,h:1,x_center:.703125,y_center:.015625},{w:1,h:1,x_center:.703125,y_center:.015625},{w:1,h:1,x_center:.734375,y_center:.015625},{w:1,h:1,x_center:.734375,y_center:.015625},{w:1,h:1,x_center:.765625,y_center:.015625},{w:1,h:1,x_center:.765625,y_center:.015625},{w:1,h:1,x_center:.796875,y_center:.015625},{w:1,h:1,x_center:.796875,y_center:.015625},{w:1,h:1,x_center:.828125,y_center:.015625},{w:1,h:1,x_center:.828125,y_center:.015625},{w:1,h:1,x_center:.859375,y_center:.015625},{w:1,h:1,x_center:.859375,y_center:.015625},{w:1,h:1,x_center:.890625,y_center:.015625},{w:1,h:1,x_center:.890625,y_center:.015625},{w:1,h:1,x_center:.921875,y_center:.015625},{w:1,h:1,x_center:.921875,y_center:.015625},{w:1,h:1,x_center:.953125,y_center:.015625},{w:1,h:1,x_center:.953125,y_center:.015625},{w:1,h:1,x_center:.984375,y_center:.015625},{w:1,h:1,x_center:.984375,y_center:.015625},{w:1,h:1,x_center:.015625,y_center:.046875},{w:1,h:1,x_center:.015625,y_center:.046875},{w:1,h:1,x_center:.046875,y_center:.046875},{w:1,h:1,x_center:.046875,y_center:.046875},{w:1,h:1,x_center:.078125,y_center:.046875},{w:1,h:1,x_center:.078125,y_center:.046875},{w:1,h:1,x_center:.109375,y_center:.046875},{w:1,h:1,x_center:.109375,y_center:.046875},{w:1,h:1,x_center:.140625,y_center:.046875},{w:1,h:1,x_center:.140625,y_center:.046875},{w:1,h:1,x_center:.171875,y_center:.046875},{w:1,h:1,x_center:.171875,y_center:.046875},{w:1,h:1,x_center:.203125,y_center:.046875},{w:1,h:1,x_center:.203125,y_center:.046875},{w:1,h:1,x_center:.234375,y_center:.046875},{w:1,h:1,x_center:.234375,y_center:.046875},{w:1,h:1,x_center:.265625,y_center:.046875},{w:1,h:1,x_center:.265625,y_center:.046875},{w:1,h:1,x_center:.296875,y_center:.046875},{w:1,h:1,x_center:.296875,y_center:.046875},{w:1,h:1,x_center:.328125,y_center:.046875},{w:1,h:1,x_center:.328125,y_center:.046875},{w:1,h:1,x_center:.359375,y_center:.046875},{w:1,h:1,x_center:.359375,y_center:.046875},{w:1,h:1,x_center:.390625,y_center:.046875},{w:1,h:1,x_center:.390625,y_center:.046875},{w:1,h:1,x_center:.421875,y_center:.046875},{w:1,h:1,x_center:.421875,y_center:.046875},{w:1,h:1,x_center:.453125,y_center:.046875},{w:1,h:1,x_center:.453125,y_center:.046875},{w:1,h:1,x_center:.484375,y_center:.046875},{w:1,h:1,x_center:.484375,y_center:.046875},{w:1,h:1,x_center:.515625,y_center:.046875},{w:1,h:1,x_center:.515625,y_center:.046875},{w:1,h:1,x_center:.546875,y_center:.046875},{w:1,h:1,x_center:.546875,y_center:.046875},{w:1,h:1,x_center:.578125,y_center:.046875},{w:1,h:1,x_center:.578125,y_center:.046875},{w:1,h:1,x_center:.609375,y_center:.046875},{w:1,h:1,x_center:.609375,y_center:.046875},{w:1,h:1,x_center:.640625,y_center:.046875},{w:1,h:1,x_center:.640625,y_center:.046875},{w:1,h:1,x_center:.671875,y_center:.046875},{w:1,h:1,x_center:.671875,y_center:.046875},{w:1,h:1,x_center:.703125,y_center:.046875},{w:1,h:1,x_center:.703125,y_center:.046875},{w:1,h:1,x_center:.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${e.hand.skeleton.modelPath.match(/\/(.*)\./)[1]}`),s}var fae=e=>{if(!e)return[];let t=[];for(let n=0;nl.part==="leftWrist"),a=e[n].keypoints.find(l=>l.part==="rightWrist"),s=e[n].keypoints.find(l=>l.part==="nose");s&&r&&a&&r.position.yl.part==="leftShoulder"),o=e[n].keypoints.find(l=>l.part==="rightShoulder");i&&o&&t.push({body:n,gesture:`leaning ${i.position.y>o.position.y?"left":"right"}`})}return t},mae=e=>{if(!e)return[];let t=[];for(let n=0;n0){let r=e[n].mesh[35][2]-e[n].mesh[263][2];Math.abs(r)<10?t.push({face:n,gesture:"facing camera"}):t.push({face:n,gesture:`facing ${r<0?"right":"left"}`}),Math.abs(e[n].mesh[374][1]-e[n].mesh[386][1])/Math.abs(e[n].mesh[443][1]-e[n].mesh[450][1])<.2&&t.push({face:n,gesture:"blink left eye"}),Math.abs(e[n].mesh[145][1]-e[n].mesh[159][1])/Math.abs(e[n].mesh[223][1]-e[n].mesh[230][1])<.2&&t.push({face:n,gesture:"blink right eye"});let a=Math.min(100,500*Math.abs(e[n].mesh[13][1]-e[n].mesh[14][1])/Math.abs(e[n].mesh[10][1]-e[n].mesh[152][1]));a>10&&t.push({face:n,gesture:`mouth ${Math.trunc(a)}% open`});let s=e[n].mesh[152][2];Math.abs(s)>10&&t.push({face:n,gesture:`head ${s<0?"up":"down"}`})}return t},Aae=e=>{if(!e)return[];let t=[];for(let n=0;n{if(!e)return[];let t=[];for(let n=0;n0){let a=r.reduce((i,o)=>i.position[2]i.position[1](u[d]=0,h))},a=function(o,l){let u=e.createShader(l);if(e.shaderSource(u,o),e.compileShader(u),!e.getShaderParameter(u,e.COMPILE_STATUS))throw new Error("Filter: GL compile failed",e.getShaderInfoLog(u));return u};this.uniform={},this.attribute={};let s=a(t,e.VERTEX_SHADER),i=a(n,e.FRAGMENT_SHADER);if(this.id=e.createProgram(),e.attachShader(this.id,s),e.attachShader(this.id,i),e.linkProgram(this.id),!e.getProgramParameter(this.id,e.LINK_STATUS))throw new Error("Filter: GL link failed",e.getProgramInfoLog(this.id));e.useProgram(this.id),r(t,"attribute",this.attribute);for(let o in 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Promise.all([this.models.face||(this.config.face.enabled?n.load(this.config):null),this.models.age||(this.config.face.enabled&&this.config.face.age.enabled?Yg(this.config):null),this.models.gender||(this.config.face.enabled&&this.config.face.gender.enabled?Qg(this.config):null),this.models.emotion||(this.config.face.enabled&&this.config.face.emotion.enabled?a2(this.config):null),this.models.embedding||(this.config.face.enabled&&this.config.face.embedding.enabled?Iv(this.config):null),this.models.posenet||(this.config.body.enabled?l2(this.config):null),this.models.handpose||(this.config.hand.enabled?p2(this.config):null)]):(this.config.face.enabled&&!this.models.face&&(this.models.face=await n.load(this.config)),this.config.face.enabled&&this.config.face.age.enabled&&!this.models.age&&(this.models.age=await Yg(this.config)),this.config.face.enabled&&this.config.face.gender.enabled&&!this.models.gender&&(this.models.gender=await Qg(this.config)),this.config.face.enabled&&this.config.face.emotion.enabled&&!this.models.emotion&&(this.models.emotion=await a2(this.config)),this.config.face.enabled&&this.config.face.embedding.enabled&&!this.models.embedding&&(this.models.embedding=await Iv(this.config)),this.config.body.enabled&&!this.models.posenet&&(this.models.posenet=await l2(this.config)),this.config.hand.enabled&&!this.models.handpose&&(this.models.handpose=await p2(this.config))),this.firstRun&&(Ve("tf engine state:",this.tf.engine().state.numBytes,"bytes",this.tf.engine().state.numTensors,"tensors"),this.firstRun=!1);let r=Math.trunc(ht()-t);r>(this.perf.load||0)&&(this.perf.load=r)}async checkBackend(e=!1){if(this.config.backend&&this.config.backend!==""&&e||this.tf.getBackend()!==this.config.backend){let t=ht();this.state="backend",Ve("setting backend:",this.config.backend),this.config.backend==="wasm"&&(Ve("settings wasm path:",this.config.wasmPath),this.tf.setWasmPaths(this.config.wasmPath),await this.tf.env().getAsync("WASM_HAS_SIMD_SUPPORT")||Ve("warning: wasm simd support is not enabled")),this.config.backend==="humangl"&&are();try{await this.tf.setBackend(this.config.backend)}catch(n){Ve("error: cannot set backend:",this.config.backend,n)}if(this.tf.enableProdMode(),this.tf.getBackend()==="webgl"){this.config.deallocate&&(Ve("changing webgl: WEBGL_DELETE_TEXTURE_THRESHOLD:",this.config.deallocate),this.tf.ENV.set("WEBGL_DELETE_TEXTURE_THRESHOLD",this.config.deallocate?0:-1));let n=await this.tf.backend().getGPGPUContext().gl;Ve(`gl version:${n.getParameter(n.VERSION)} renderer:${n.getParameter(n.RENDERER)}`)}await this.tf.ready(),this.perf.backend=Math.trunc(ht()-t)}}async detectFace(e){var t,n,r,a,s,i;let o,l,u,c,h,d=[];this.state="run:face",o=ht();let p=await((t=this.models.face)==null?void 0:t.estimateFaces(e,this.config));this.perf.face=Math.trunc(ht()-o);for(let f of p){if(this.analyze("Get Face"),!f.image||f.image.isDisposedInternal){Ve("Face object is disposed:",f.image);continue}this.analyze("Start Age:"),this.config.async?l=this.config.face.age.enabled?Jg(f.image,this.config):{}:(this.state="run:age",o=ht(),l=this.config.face.age.enabled?await Jg(f.image,this.config):{},this.perf.age=Math.trunc(ht()-o)),this.analyze("Start Gender:"),this.config.async?u=this.config.face.gender.enabled?e2(f.image,this.config):{}:(this.state="run:gender",o=ht(),u=this.config.face.gender.enabled?await e2(f.image,this.config):{},this.perf.gender=Math.trunc(ht()-o)),this.analyze("Start Emotion:"),this.config.async?c=this.config.face.emotion.enabled?s2(f.image,this.config):{}:(this.state="run:emotion",o=ht(),c=this.config.face.emotion.enabled?await s2(f.image,this.config):{},this.perf.emotion=Math.trunc(ht()-o)),this.analyze("End Emotion:"),this.analyze("Start Embedding:"),this.config.async?h=this.config.face.embedding.enabled?Nv(f.image,this.config):[]:(this.state="run:embedding",o=ht(),h=this.config.face.embedding.enabled?await Nv(f.image,this.config):[],this.perf.embedding=Math.trunc(ht()-o)),this.analyze("End Emotion:"),this.config.async&&([l,u,c,h]=await Promise.all([l,u,c,h])),this.analyze("Finish Face:"),!this.config.face.iris.enabled&&((n=f==null?void 0:f.annotations)==null?void 0:n.leftEyeIris)&&((r=f==null?void 0:f.annotations)==null?void 0:r.rightEyeIris)&&(delete f.annotations.leftEyeIris,delete f.annotations.rightEyeIris);let m=((a=f.annotations)==null?void 0:a.leftEyeIris)&&((s=f.annotations)==null?void 0:s.rightEyeIris)?11.7*Math.max(Math.abs(f.annotations.leftEyeIris[3][0]-f.annotations.leftEyeIris[1][0]),Math.abs(f.annotations.rightEyeIris[4][1]-f.annotations.rightEyeIris[2][1])):0;d.push({confidence:f.confidence,box:f.box,mesh:f.mesh,boxRaw:f.boxRaw,meshRaw:f.meshRaw,annotations:f.annotations,age:l.age,gender:u.gender,genderConfidence:u.confidence,emotion:c,embedding:h,iris:m!==0?Math.trunc(m)/100:0}),(i=f.image)==null||i.dispose(),this.analyze("End Face")}return this.analyze("End FaceMesh:"),this.config.async&&(this.perf.face&&delete this.perf.face,this.perf.age&&delete this.perf.age,this.perf.gender&&delete this.perf.gender,this.perf.emotion&&delete this.perf.emotion),d}async detect(e,t={}){return new Promise(async n=>{var r,a,s,i;this.state="config";let o;this.config=Tc(this.config,t),this.state="check";let l=this.sanity(e);l&&(Ve(l,e),n({error:l}));let u,c,h,d=ht();await this.checkBackend(),await this.load(),this.config.scoped&&this.tf.engine().startScope(),this.analyze("Start Scope:"),o=ht();let p=wae(e,this.config);if(!p||!p.tensor){Ve("could not convert input to tensor"),n({error:"could not convert input to tensor"});return}this.perf.image=Math.trunc(ht()-o),this.analyze("Get Image:"),this.config.async?(h=this.config.face.enabled?this.detectFace(p.tensor):[],this.perf.face&&delete this.perf.face):(this.state="run:face",o=ht(),h=this.config.face.enabled?await this.detectFace(p.tensor):[],this.perf.face=Math.trunc(ht()-o)),this.analyze("Start Body:"),this.config.async?(u=this.config.body.enabled?(r=this.models.posenet)==null?void 0:r.estimatePoses(p.tensor,this.config):[],this.perf.body&&delete this.perf.body):(this.state="run:body",o=ht(),u=this.config.body.enabled?await((a=this.models.posenet)==null?void 0:a.estimatePoses(p.tensor,this.config)):[],this.perf.body=Math.trunc(ht()-o)),this.analyze("End Body:"),this.analyze("Start Hand:"),this.config.async?(c=this.config.hand.enabled?(s=this.models.handpose)==null?void 0:s.estimateHands(p.tensor,this.config):[],this.perf.hand&&delete this.perf.hand):(this.state="run:hand",o=ht(),c=this.config.hand.enabled?await((i=this.models.handpose)==null?void 0:i.estimateHands(p.tensor,this.config)):[],this.perf.hand=Math.trunc(ht()-o)),this.analyze("End Hand:"),this.config.async&&([h,u,c]=await Promise.all([h,u,c])),p.tensor.dispose(),this.config.scoped&&this.tf.engine().endScope(),this.analyze("End Scope:");let f=[];this.config.gesture.enabled&&(o=ht(),f=[...mae(h),...fae(u),...yae(c),...Aae(h)],this.config.async?this.perf.gesture&&delete this.perf.gesture:this.perf.gesture=Math.trunc(ht()-o)),this.perf.total=Math.trunc(ht()-d),this.state="idle",n({face:h,body:u,hand:c,gesture:f,performance:this.perf,canvas:p.canvas})})}async warmupBitmap(){let e=(r,a="application/octet-stream")=>fetch(`data:${a};base64,${r}`).then(s=>s.blob()),t,n;switch(this.config.warmup){case"face":t=await e(g2);break;case"full":t=await e(x2);break;default:t=null}if(t){let r=await createImageBitmap(t);n=await this.detect(r,this.config),r.close()}return n}async warmupCanvas(){return new Promise(e=>{let t,n=0;switch(this.config.warmup){case"face":n=256,t="data:image/jpeg;base64,"+g2;break;case"full":n=1200,t="data:image/jpeg;base64,"+x2;break;default:t=null}let r=new Image(n,n);r.onload=()=>{let a=typeof OffscreenCanvas!="undefined"?new OffscreenCanvas(n,n):document.createElement("canvas");a.width=n,a.height=n;let s=a.getContext("2d");s==null||s.drawImage(r,0,0);let i=s==null?void 0:s.getImageData(0,0,n,n);this.detect(i,this.config).then(o=>e(o))},t?r.src=t:e(null)})}async warmupNode(){let e=s=>Buffer.from(s,"base64"),t=this.config.warmup==="face"?e(g2):e(x2),n=(void 0).decodeJpeg(t),r=n.expandDims(0);this.tf.dispose(n);let a=await this.detect(r,this.config);return this.tf.dispose(r),a}async warmup(e){let t=ht();e&&(this.config=Tc(this.config,e));let n=this.config.videoOptimized;this.config.videoOptimized=!1;let r;typeof createImageBitmap=="function"?r=await this.warmupBitmap():typeof Image!="undefined"?r=await this.warmupCanvas():r=await this.warmupNode(),this.config.videoOptimized=n;let a=ht();return Ve("Warmup",this.config.warmup,Math.round(a-t),"ms",r),r}};async function vae(e,t,n){if(!e)return;let r=t.getContext("2d");r.font=n.baseFont,r.fillStyle=n.baseLabel;let a=1;for(let s=0;s1&&o[1].length>0){let l=i[1]>0?`#${i[1]}`:"",u=`${i[0]} ${l}: ${o[1]}`;r.fillStyle="black",r.fillText(u,8,2+a*n.baseLineHeight),r.fillStyle=n.baseLabel,r.fillText(u,6,0+a*n.baseLineHeight),a+=1}}}async function kae(e,t,n,r){if(!e)return;let a=t.getContext("2d");for(let s of e){a.font=n.baseFont,a.strokeStyle=n.baseColor,a.fillStyle=n.baseColor,a.lineWidth=n.baseLineWidth,a.beginPath(),n.drawBoxes&&a.rect(s.box[0],s.box[1],s.box[2],s.box[3]);let i=[];if(i.push(`detect confidence: ${Math.trunc(100*s.confidence)}%`),s.genderConfidence&&i.push(`${s.gender||""} ${Math.trunc(100*s.genderConfidence)}% confident`),s.age&&i.push(`age: ${s.age||""}`),s.iris&&i.push(`iris distance: ${s.iris}`),s.emotion&&s.emotion.length>0){let o=s.emotion.map(l=>`${Math.trunc(100*l.score)}% ${l.emotion}`);i.push(o.join(" "))}i.length===0&&i.push("face"),a.fillStyle=n.baseLabel;for(let o=i.length-1;o>=0;o--){a.fillStyle="black";let l=Math.max(s.box[0],0),u=o*n.baseLineHeight+s.box[1];a.fillText(i[o],l+5,u+16),a.fillStyle=n.baseLabel,a.fillText(i[o],l+4,u+15)}if(a.fillStyle=n.baseColor,a.stroke(),a.lineWidth=1,s.mesh){if(n.drawPoints)for(let o of s.mesh)a.fillStyle=n.useDepth?`rgba(${127.5+2*o[2]}, ${127.5-2*o[2]}, 255, 0.5)`:n.baseColor,a.beginPath(),a.arc(o[0],o[1],2,0,2*Math.PI),a.fill();if(n.drawPolygons){for(let o=0;os.mesh[c]),u=new Path2D;u.moveTo(l[0][0],l[0][1]);for(let c of l)u.lineTo(c[0],c[1]);u.closePath(),a.strokeStyle=n.useDepth?`rgba(${127.5+2*l[0][2]}, ${127.5-2*l[0][2]}, 255, 0.3)`:n.baseColor,a.stroke(u),n.fillPolygons&&(a.fillStyle=n.useDepth?`rgba(${127.5+2*l[0][2]}, ${127.5-2*l[0][2]}, 255, 0.3)`:n.baseColor,a.fill(u))}if(s.annotations&&s.annotations.leftEyeIris){a.strokeStyle=n.useDepth?"rgba(255, 200, 255, 0.3)":n.baseColor,a.beginPath();let o=Math.abs(s.annotations.leftEyeIris[3][0]-s.annotations.leftEyeIris[1][0])/2,l=Math.abs(s.annotations.leftEyeIris[4][1]-s.annotations.leftEyeIris[2][1])/2;a.ellipse(s.annotations.leftEyeIris[0][0],s.annotations.leftEyeIris[0][1],o,l,0,0,2*Math.PI),a.stroke(),n.fillPolygons&&(a.fillStyle=n.useDepth?"rgba(255, 255, 200, 0.3)":n.baseColor,a.fill())}if(s.annotations&&s.annotations.rightEyeIris){a.strokeStyle=n.useDepth?"rgba(255, 200, 255, 0.3)":n.baseColor,a.beginPath();let o=Math.abs(s.annotations.rightEyeIris[3][0]-s.annotations.rightEyeIris[1][0])/2,l=Math.abs(s.annotations.rightEyeIris[4][1]-s.annotations.rightEyeIris[2][1])/2;a.ellipse(s.annotations.rightEyeIris[0][0],s.annotations.rightEyeIris[0][1],o,l,0,0,2*Math.PI),a.stroke(),n.fillPolygons&&(a.fillStyle=n.useDepth?"rgba(255, 255, 200, 0.3)":n.baseColor,a.fill())}}}}}var Ua=[];async function Iae(e,t,n){if(!e)return;let r=t.getContext("2d");r.lineJoin="round";for(let a=0;al.part==="leftShoulder"),i&&(s.moveTo(i.position.x,i.position.y),o=e[a].keypoints.find(l=>l.part==="rightShoulder"),o&&s.lineTo(o.position.x,o.position.y),o=e[a].keypoints.find(l=>l.part==="rightHip"),o&&s.lineTo(o.position.x,o.position.y),o=e[a].keypoints.find(l=>l.part==="leftHip"),o&&s.lineTo(o.position.x,o.position.y),o=e[a].keypoints.find(l=>l.part==="leftShoulder"),o&&s.lineTo(o.position.x,o.position.y)),i=e[a].keypoints.find(l=>l.part==="leftHip"),i&&(s.moveTo(i.position.x,i.position.y),o=e[a].keypoints.find(l=>l.part==="leftKnee"),o&&s.lineTo(o.position.x,o.position.y),o=e[a].keypoints.find(l=>l.part==="leftAnkle"),o&&s.lineTo(o.position.x,o.position.y)),i=e[a].keypoints.find(l=>l.part==="rightHip"),i&&(s.moveTo(i.position.x,i.position.y),o=e[a].keypoints.find(l=>l.part==="rightKnee"),o&&s.lineTo(o.position.x,o.position.y),o=e[a].keypoints.find(l=>l.part==="rightAnkle"),o&&s.lineTo(o.position.x,o.position.y)),i=e[a].keypoints.find(l=>l.part==="leftShoulder"),i&&(s.moveTo(i.position.x,i.position.y),o=e[a].keypoints.find(l=>l.part==="leftElbow"),o&&s.lineTo(o.position.x,o.position.y),o=e[a].keypoints.find(l=>l.part==="leftWrist"),o&&s.lineTo(o.position.x,o.position.y)),i=e[a].keypoints.find(l=>l.part==="rightShoulder"),i&&(s.moveTo(i.position.x,i.position.y),o=e[a].keypoints.find(l=>l.part==="rightElbow"),o&&s.lineTo(o.position.x,o.position.y),o=e[a].keypoints.find(l=>l.part==="rightWrist"),o&&s.lineTo(o.position.x,o.position.y)),r.stroke(s)}}}async function Nae(e,t,n){if(!e)return;let r=t.getContext("2d");r.lineJoin="round";for(let a of e){if(r.font=n.baseFont,r.lineWidth=n.baseLineWidth,n.drawBoxes&&(r.lineWidth=n.baseLineWidth,r.beginPath(),r.strokeStyle=n.baseColor,r.fillStyle=n.baseColor,r.rect(a.box[0],a.box[1],a.box[2],a.box[3]),r.fillStyle="black",r.fillText("hand",a.box[0]+3,1+a.box[1]+n.baseLineHeight,a.box[2]),r.fillStyle=n.baseLabel,r.fillText("hand",a.box[0]+2,0+a.box[1]+n.baseLineHeight,a.box[2]),r.stroke()),n.drawPoints&&a.landmarks&&a.landmarks.length>0)for(let s of a.landmarks)r.fillStyle=n.useDepth?`rgba(${127.5+2*s[2]}, ${127.5-2*s[2]}, 255, 0.5)`:n.baseColor,r.beginPath(),r.arc(s[0],s[1],2,0,2*Math.PI),r.fill();if(n.drawPolygons){let s=i=>{if(!!i)for(let o=0;o0?o-1:0][0],i[o>0?o-1:0][1]),r.lineTo(i[o][0],i[o][1]),r.stroke()};s(a.annotations.indexFinger),s(a.annotations.middleFinger),s(a.annotations.ringFinger),s(a.annotations.pinky),s(a.annotations.thumb)}}}var Ec={face:kae,body:Iae,hand:Nae,gesture:vae};var Cc=0,d6=!1,xt={background:"darkslategray",hover:"lightgray",itemBackground:"black",itemColor:"white",buttonBackground:"lightblue",buttonHover:"lightgreen",checkboxOn:"lightgreen",checkboxOff:"lightcoral",rangeBackground:"lightblue",rangeLabel:"white",chartColor:"lightblue"};function Sae(){if(d6)return;let e=` :root { --rounded: 0.2rem; } .menu { position: absolute; top: 0rem; right: 0; width: max-content; padding: 0 0.2rem 0 0.2rem; line-height: 1.8rem; z-index: 10; box-shadow: 0 0 8px dimgrey; background: ${xt.background}; border-radius: var(--rounded); border-color: black; border-style: solid; border-width: thin; } .menu:hover { box-shadow: 0 0 8px ${xt.hover}; } .menu-container { display: block; max-height: 100vh; } .menu-container-fadeout { max-height: 0; overflow: hidden; transition: max-height, 0.5s ease; } .menu-container-fadein { max-height: 100vh; overflow: hidden; transition: max-height, 0.5s ease; } .menu-item { display: flex; white-space: nowrap; padding: 0.2rem; cursor: default; width: 100%; } .menu-title { cursor: pointer; } .menu-hr { margin: 0.2rem; border: 1px solid rgba(0, 0, 0, 0.5) } .menu-label { padding: 0; font-weight: 800; } .menu-list { margin-right: 0.8rem; } select:focus { outline: none; } .menu-list-item { background: ${xt.itemBackground}; color: ${xt.itemColor}; border: none; padding: 0.2rem; font-family: inherit; font-variant: inherit; border-radius: var(--rounded); font-weight: 800; } .menu-chart-title { padding: 0; font-size: 0.8rem; font-weight: 800; align-items: center} .menu-chart-canvas { background: transparent; margin: 0.2rem 0 0.2rem 0.6rem; } .menu-button { border: 0; background: ${xt.buttonBackground}; width: -webkit-fill-available; padding: 8px; margin: 8px; cursor: pointer; box-shadow: 4px 4px 4px 0 dimgrey; border-radius: var(--rounded); justify-content: center; font-family: inherit; font-variant: inherit; font-size: 1rem; font-weight: 800; } .menu-button:hover { background: ${xt.buttonHover}; box-shadow: 4px 4px 4px 0 black; } .menu-button:focus { outline: none; } .menu-checkbox { width: 2.8rem; height: 1rem; background: ${xt.itemBackground}; margin: 0.5rem 0.5rem 0 0; position: relative; border-radius: var(--rounded); } .menu-checkbox:after { content: 'OFF'; color: ${xt.checkboxOff}; position: absolute; right: 0.2rem; top: -0.4rem; font-weight: 800; font-size: 0.5rem; } .menu-checkbox:before { content: 'ON'; color: ${xt.checkboxOn}; position: absolute; left: 0.3rem; top: -0.4rem; font-weight: 800; font-size: 0.5rem; } .menu-checkbox-label { width: 1.3rem; height: 0.8rem; cursor: pointer; position: absolute; top: 0.1rem; left: 0.1rem; z-index: 1; background: ${xt.checkboxOff}; border-radius: var(--rounded); transition: left 0.6s ease; } input[type=checkbox] { visibility: hidden; } input[type=checkbox]:checked + label { left: 1.4rem; background: ${xt.checkboxOn}; } .menu-range { margin: 0.2rem 0.5rem 0 0; width: 3.5rem; background: transparent; color: ${xt.rangeBackground}; } .menu-range:before { color: ${xt.rangeLabel}; margin: 0 0.4rem 0 0; font-weight: 800; font-size: 0.6rem; position: relative; top: 0.3rem; content: attr(value); } input[type=range] { -webkit-appearance: none; } input[type=range]::-webkit-slider-runnable-track { width: 100%; height: 1rem; cursor: pointer; background: ${xt.itemBackground}; border-radius: var(--rounded); border: 1px; } input[type=range]::-moz-range-track { width: 100%; height: 1rem; cursor: pointer; background: ${xt.itemBackground}; border-radius: var(--rounded); border: 1px; } input[type=range]::-webkit-slider-thumb { border: 1px solid #000000; margin-top: 0.05rem; height: 0.9rem; width: 1rem; border-radius: var(--rounded); background: ${xt.rangeBackground}; cursor: pointer; -webkit-appearance: none; } input[type=range]::-moz-range-thumb { border: 1px solid #000000; margin-top: 0.05rem; height: 0.9rem; width: 1rem; border-radius: var(--rounded); background: ${xt.rangeBackground}; cursor: pointer; -webkit-appearance: none; } .svg-background { fill:darkslategrey; cursor:pointer; opacity: 0.6; } .svg-foreground { fill:white; cursor:pointer; opacity: 0.8; } `,t=document.createElement("style");t.innerHTML=e,document.getElementsByTagName("head")[0].appendChild(t),d6=!0}var p6=class{constructor(t,n,r,a){a&&(xt={...xt,...a}),Sae(),this.createMenu(t,n,r),this.id=0,this.instance=Cc,Cc++,this._maxFPS=0,this.hidden=0}createMenu(t,n="",r={top:null,left:null,bottom:null,right:null}){this.menu=document.createElement("div"),this.menu.id=`menu-${Cc}`,this.menu.className="menu",r&&(r.top&&(this.menu.style.top=r.top),r.bottom&&(this.menu.style.bottom=r.bottom),r.left&&(this.menu.style.left=r.left),r.right&&(this.menu.style.right=r.right)),this.container=document.createElement("div"),this.container.id=`menu-container-${Cc}`,this.container.className="menu-container menu-container-fadein";let a=document.createElement("div");a.className="menu-title",a.id=`menu-title-${Cc}`;let s=` `;n&&(a.innerHTML=`${n}${s}`),this.menu.appendChild(a),a.addEventListener("click",()=>{this.container.classList.toggle("menu-container-fadeout"),this.container.classList.toggle("menu-container-fadein"),this.menu.style.borderStyle=this.container.classList.contains("menu-container-fadeout")?"none":"solid"}),this.menu.appendChild(this.container),typeof t=="object"?t.appendChild(this.menu):document.getElementById(t).appendChild(this.menu)}get newID(){return this.id++,`menu-${this.instance}-${this.id}`}get ID(){return`menu-${this.instance}-${this.id}`}get width(){return this.menu.offsetWidth}get height(){return this.menu.offsetHeight}hide(){this.container.classList.contains("menu-container-fadein")&&(this.container.classList.toggle("menu-container-fadeout"),this.container.classList.toggle("menu-container-fadein"))}visible(){return this.container.classList.contains("menu-container-fadein")}toggle(t){if(this.container.classList.toggle("menu-container-fadeout"),this.container.classList.toggle("menu-container-fadein"),this.container.classList.contains("menu-container-fadein")&&t){let n=t.x||(t.touches&&t.touches[0]?t.touches[0].pageX:null);n&&(this.menu.style.left=`${n-this.menu.offsetWidth/2}px`),this.menu.offsetLeft<0&&(this.menu.style.left=0),this.menu.offsetLeft+this.menu.offsetWidth>window.innerWidth&&(this.menu.style.left=null,this.menu.style.right=0),this.menu.style.borderStyle="solid"}else this.menu.style.borderStyle="none"}addTitle(t){let n=document.createElement("div");return n.className="menu-title",n.id=this.newID,n.innerHTML=t,this.menu.appendChild(n),n.addEventListener("click",()=>{this.hidden=!this.hidden;let r=document.getElementsByClassName("menu");for(let a of r)a.style.display=this.hidden?"none":"block"}),n}addLabel(t){let n=document.createElement("div");return n.className="menu-item 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t=n1,n=document.getElementById("canvas");ie.drawFPS.push(1e3/(performance.now()-A6)),ie.drawFPS.length>ie.maxFPSframes&&ie.drawFPS.shift(),A6=performance.now(),await ge.process.updateChart("FPS",ie.detectFPS),(ie.buffered||!t.canvas)&&(t.canvas=await ae.image(e,Ur));let r=n.getContext("2d");r.fillStyle=ie.baseBackground,r.fillRect(0,0,n.width,n.height),t.canvas?(t.canvas.width!==n.width&&(n.width=t.canvas.width),t.canvas.height!==n.height&&(n.height=t.canvas.height),r.drawImage(t.canvas,0,0,t.canvas.width,t.canvas.height,0,0,t.canvas.width,t.canvas.height)):r.drawImage(e,0,0,e.width,e.height,0,0,n.width,n.height),await Ec.face(t.face,n,ie,ae.facemesh.triangulation),await Ec.body(t.body,n,ie),await Ec.hand(t.hand,n,ie),await Ec.gesture(t.gesture,n,ie),await Rae(t);let a=ae.tf.engine(),s=a.backendInstance?`gpu: ${(a.backendInstance.numBytesInGPU?a.backendInstance.numBytesInGPU:0).toLocaleString()} bytes`:"",i=`system: ${a.state.numBytes.toLocaleString()} bytes ${s} | tensors: 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performance: ${Cae(t.performance)}ms FPS process:${l} refresh:${u}
${c}
`,ie.framesDraw++,ie.lastFrame=performance.now(),ie.buffered?ie.drawThread=requestAnimationFrame(()=>r1(e,n)):!ie.buffered&&ie.drawThread&&(Ln("stopping buffered refresh"),cancelAnimationFrame(ie.drawThread),ie.drawThread=null)}async function a1(){var u;if(ie.busy)return null;ie.busy=!0;let e=document.getElementById("video"),t=document.getElementById("canvas"),n=document.getElementById("log"),r=e.srcObject?e.srcObject.getVideoTracks()[0].readyState==="live"&&e.readyState>2&&!e.paused:!1,a="";if(Xn("setting up camera"),!navigator.mediaDevices)return a="camera access not supported",n.innerText+=` ${a}`,Ln(a),Xn(a),ie.busy=!1,a;let s,i={audio:!1,video:{facingMode:ie.facing?"user":"environment",resizeMode:ie.crop?"crop-and-scale":"none"}};window.innerWidth>window.innerHeight?i.video.width={ideal:window.innerWidth}:i.video.height={ideal:window.innerHeight-document.getElementById("menubar").offsetHeight};try{s=await navigator.mediaDevices.getUserMedia(i)}catch(c){return c.name==="PermissionDeniedError"||c.name==="NotAllowedError"?a="camera permission denied":c.name==="SourceUnavailableError"?a="camera not available":a=`camera error: ${c.message||c}`,n.innerText+=` ${a}`,Xn(a),Ln("camera error:",c),ie.busy=!1,a}if(s)e.srcObject=s;else return ie.busy=!1,"camera stream empty";let o=s.getVideoTracks()[0],l=o.getSettings();return ie.camera={name:(u=o.label)==null?void 0:u.toLowerCase(),width:l.width,height:l.height,facing:l.facingMode==="user"?"front":"back"},new Promise(c=>{e.onloadeddata=async()=>{e.width=e.videoWidth,e.height=e.videoHeight,t.width=e.width,t.height=e.height,t.style.width=t.width>t.height?"100vw":"",t.style.height=t.width>t.height?"":"100vh",ie.menuWidth.input.setAttribute("value",e.width),ie.menuHeight.input.setAttribute("value",e.height);let h=Math.trunc(window.devicePixelRatio*(8+4*t.width/window.innerWidth));ie.baseFont=ie.baseFontProto.replace(/{size}/,`${h}px`),ie.baseLineHeight=h+2,r&&e.play(),r&&!ie.detectThread&&Fc(e,t),ie.busy=!1,Xn(""),c()}})}function y6(){if(!bi){let e=null;bi=new m6(e,{trackGPU:!1,chartHz:20,chartLen:20}),bi.begin()}}function Fae(e,t,n,r){t1||(Ln("creating worker thread"),t1=new Worker(ie.worker,{type:"module"}),t1.addEventListener("message",a=>{a.data.result.performance&&a.data.result.performance.total&&ie.detectFPS.push(1e3/a.data.result.performance.total),ie.detectFPS.length>ie.maxFPSframes&&ie.detectFPS.shift(),ie.bench&&(bi||y6(),bi.nextFrame(r)),document.getElementById("gl-bench")&&(document.getElementById("gl-bench").style.display=ie.bench?"block":"none"),n1=a.data.result,ie.framesDetect++,ie.drawThread||r1(e),ie.detectThread=requestAnimationFrame(s=>Fc(e,n,s))})),t1.postMessage({image:t.data.buffer,width:n.width,height:n.height,userConfig:Ur},[t.data.buffer])}function Fc(e,t,n){var a;if(!(e.srcObject&&e.srcObject.getVideoTracks()[0].readyState==="live"&&e.readyState>2&&!e.paused)&&e.srcObject){ie.drawThread&&cancelAnimationFrame(ie.drawThread),ie.detectThread&&cancelAnimationFrame(ie.detectThread),ie.drawThread=null,ie.detectThread=null,e.paused?Ln("camera paused"):e.srcObject.getVideoTracks()[0].readyState==="live"&&e.readyState<=2?setTimeout(()=>Fc(e,t),500):Ln(`camera not ready: track state: ${(a=e.srcObject)==null?void 0:a.getVideoTracks()[0].readyState} stream state: ${e.readyState}`),clearTimeout(ie.drawThread),ie.drawThread=null,Ln("frame statistics: process:",ie.framesDetect,"refresh:",ie.framesDraw),Ln("memory",ae.tf.engine().memory());return}if(Xn(""),ie.useWorker){let s=typeof OffscreenCanvas!="undefined"?new OffscreenCanvas(t.width,t.height):document.createElement("canvas");s.width=t.width,s.height=t.height;let i=s.getContext("2d");i.drawImage(e,0,0,e.width,e.height,0,0,t.width,t.height);let o=i.getImageData(0,0,t.width,t.height);Fae(e,o,t,Ur,n)}else ae.detect(e,Ur).then(s=>{s.performance&&s.performance.total&&ie.detectFPS.push(1e3/s.performance.total),ie.detectFPS.length>ie.maxFPSframes&&ie.detectFPS.shift(),ie.bench&&(bi||y6(),bi.nextFrame(n)),document.getElementById("gl-bench")&&(document.getElementById("gl-bench").style.display=ie.bench?"block":"none"),s.error?(Ln(s.error),document.getElementById("log").innerText+=` Human error: ${s.error}`):(n1=s,ie.drawThread||r1(e),ie.framesDetect++,ie.detectThread=requestAnimationFrame(i=>Fc(e,t,i)))})}async function $ae(e){return new Promise(t=>{let n=new Image;n.onload=async()=>{Ln("Processing image:",n.src);let r=document.getElementById("canvas");n.width=n.naturalWidth,n.height=n.naturalHeight,r.width=ae.config.filter.width&&ae.config.filter.width>0?ae.config.filter.width:n.naturalWidth,r.height=ae.config.filter.height&&ae.config.filter.height>0?ae.config.filter.height:n.naturalHeight,n1=await ae.detect(n,Ur),await r1(n);let s=document.createElement("canvas");s.className="thumbnail",s.width=window.innerWidth/(ie.columns+.1),s.height=r.height/(window.innerWidth/s.width),s.getContext("2d").drawImage(r,0,0,r.width,r.height,0,0,s.width,s.height),document.getElementById("samples-container").appendChild(s),n.src="",t(!0)},n.src=e})}async function g6(){Ur.videoOptimized=!0,document.getElementById("samples-container").style.display="none",document.getElementById("canvas").style.display="block";let e=document.getElementById("video"),t=document.getElementById("canvas");if(e.srcObject!==null&&!e.paused)document.getElementById("play").style.display="block",document.getElementById("btnStart").className="button button-start",document.getElementById("btnStart").innerHTML="start
video",Xn("paused"),e.pause();else{let n=await a1();if(n)Xn(n);else{document.getElementById("play").style.display="none";for(let r of Object.values(ge))r.hide();Xn(""),document.getElementById("btnStart").className="button button-stop",document.getElementById("btnStart").innerHTML="pause
video",await e.play(),ie.detectThread||Fc(e,t)}}}async function Mae(){document.getElementById("play").style.display="none",Ur.videoOptimized=!1;let e=Math.trunc(window.devicePixelRatio*(12+4*ie.columns));ie.baseFont=ie.baseFontProto.replace(/{size}/,`${e}px`),ie.baseLineHeight=e+2,document.getElementById("canvas").style.display="none",document.getElementById("samples-container").style.display="block",Ln("Running detection of sample images"),Xn("processing images"),document.getElementById("samples-container").innerHTML="";for(let t of ie.samples)await $ae(t);Xn("")}function Dae(){let e=[];window.innerWidth>800?e=[`${document.getElementById("btnDisplay").offsetLeft-50}px`,`${document.getElementById("btnImage").offsetLeft-50}px`,`${document.getElementById("btnProcess").offsetLeft-50}px`,`${document.getElementById("btnModel").offsetLeft-50}px`]:e=["0rem","11rem","21.1rem","33rem"],ge.display=new Rc(document.body,"",{top:`${document.getElementById("menubar").offsetHeight}px`,left:e[0]}),ge.display.addBool("perf monitor",ie,"bench",t=>ie.bench=t),ge.display.addBool("buffered output",ie,"buffered",t=>ie.buffered=t),ge.display.addBool("crop & scale",ie,"crop",t=>{ie.crop=t,a1()}),ge.display.addBool("camera facing",ie,"facing",t=>{ie.facing=t,a1()}),ge.display.addHTML('
'),ge.display.addBool("use 3D depth",ie,"useDepth"),ge.display.addBool("draw boxes",ie,"drawBoxes"),ge.display.addBool("draw polygons",ie,"drawPolygons"),ge.display.addBool("Fill Polygons",ie,"fillPolygons"),ge.display.addBool("draw points",ie,"drawPoints"),ge.image=new Rc(document.body,"",{top:`${document.getElementById("menubar").offsetHeight}px`,left:e[1]}),ge.image.addBool("enabled",ae.config.filter,"enabled",t=>ae.config.filter.enabled=t),ie.menuWidth=ge.image.addRange("image width",ae.config.filter,"width",0,3840,10,t=>ae.config.filter.width=parseInt(t)),ie.menuHeight=ge.image.addRange("image height",ae.config.filter,"height",0,2160,10,t=>ae.config.filter.height=parseInt(t)),ge.image.addHTML('
'),ge.image.addRange("brightness",ae.config.filter,"brightness",-1,1,.05,t=>ae.config.filter.brightness=parseFloat(t)),ge.image.addRange("contrast",ae.config.filter,"contrast",-1,1,.05,t=>ae.config.filter.contrast=parseFloat(t)),ge.image.addRange("sharpness",ae.config.filter,"sharpness",0,1,.05,t=>ae.config.filter.sharpness=parseFloat(t)),ge.image.addRange("blur",ae.config.filter,"blur",0,20,1,t=>ae.config.filter.blur=parseInt(t)),ge.image.addRange("saturation",ae.config.filter,"saturation",-1,1,.05,t=>ae.config.filter.saturation=parseFloat(t)),ge.image.addRange("hue",ae.config.filter,"hue",0,360,5,t=>ae.config.filter.hue=parseInt(t)),ge.image.addRange("pixelate",ae.config.filter,"pixelate",0,32,1,t=>ae.config.filter.pixelate=parseInt(t)),ge.image.addHTML('
'),ge.image.addBool("negative",ae.config.filter,"negative",t=>ae.config.filter.negative=t),ge.image.addBool("sepia",ae.config.filter,"sepia",t=>ae.config.filter.sepia=t),ge.image.addBool("vintage",ae.config.filter,"vintage",t=>ae.config.filter.vintage=t),ge.image.addBool("kodachrome",ae.config.filter,"kodachrome",t=>ae.config.filter.kodachrome=t),ge.image.addBool("technicolor",ae.config.filter,"technicolor",t=>ae.config.filter.technicolor=t),ge.image.addBool("polaroid",ae.config.filter,"polaroid",t=>ae.config.filter.polaroid=t),ge.process=new Rc(document.body,"",{top:`${document.getElementById("menubar").offsetHeight}px`,left:e[2]}),ge.process.addList("backend",["cpu","webgl","wasm","humangl"],ae.config.backend,t=>ae.config.backend=t),ge.process.addBool("async operations",ae.config,"async",t=>ae.config.async=t),ge.process.addBool("enable profiler",ae.config,"profile",t=>ae.config.profile=t),ge.process.addBool("memory shield",ae.config,"deallocate",t=>ae.config.deallocate=t),ge.process.addBool("use web worker",ie,"useWorker"),ge.process.addHTML('
'),ge.process.addLabel("model parameters"),ge.process.addRange("max objects",ae.config.face.detector,"maxFaces",1,50,1,t=>{ae.config.face.detector.maxFaces=parseInt(t),ae.config.body.maxDetections=parseInt(t),ae.config.hand.maxHands=parseInt(t)}),ge.process.addRange("skip frames",ae.config.face.detector,"skipFrames",0,50,1,t=>{ae.config.face.detector.skipFrames=parseInt(t),ae.config.face.emotion.skipFrames=parseInt(t),ae.config.face.age.skipFrames=parseInt(t),ae.config.hand.skipFrames=parseInt(t)}),ge.process.addRange("min confidence",ae.config.face.detector,"minConfidence",0,1,.05,t=>{ae.config.face.detector.minConfidence=parseFloat(t),ae.config.face.gender.minConfidence=parseFloat(t),ae.config.face.emotion.minConfidence=parseFloat(t),ae.config.hand.minConfidence=parseFloat(t)}),ge.process.addRange("score threshold",ae.config.face.detector,"scoreThreshold",.1,1,.05,t=>{ae.config.face.detector.scoreThreshold=parseFloat(t),ae.config.hand.scoreThreshold=parseFloat(t),ae.config.body.scoreThreshold=parseFloat(t)}),ge.process.addRange("overlap",ae.config.face.detector,"iouThreshold",.1,1,.05,t=>{ae.config.face.detector.iouThreshold=parseFloat(t),ae.config.hand.iouThreshold=parseFloat(t)}),ge.process.addBool("detection rotation",ae.config.face.detector,"rotation",t=>{ae.config.face.detector.rotation=t,ae.config.hand.rotation=t}),ge.process.addHTML('
'),ge.process.addButton("process sample images","process images",()=>Mae()),ge.process.addHTML('
'),ge.process.addChart("FPS","FPS"),ge.models=new Rc(document.body,"",{top:`${document.getElementById("menubar").offsetHeight}px`,left:e[3]}),ge.models.addBool("face detect",ae.config.face,"enabled",t=>ae.config.face.enabled=t),ge.models.addBool("face mesh",ae.config.face.mesh,"enabled",t=>ae.config.face.mesh.enabled=t),ge.models.addBool("face iris",ae.config.face.iris,"enabled",t=>ae.config.face.iris.enabled=t),ge.models.addBool("face age",ae.config.face.age,"enabled",t=>ae.config.face.age.enabled=t),ge.models.addBool("face gender",ae.config.face.gender,"enabled",t=>ae.config.face.gender.enabled=t),ge.models.addBool("face emotion",ae.config.face.emotion,"enabled",t=>ae.config.face.emotion.enabled=t),ge.models.addHTML('
'),ge.models.addBool("body pose",ae.config.body,"enabled",t=>ae.config.body.enabled=t),ge.models.addBool("hand pose",ae.config.hand,"enabled",t=>ae.config.hand.enabled=t),ge.models.addHTML('
'),ge.models.addBool("gestures",ae.config.gesture,"enabled",t=>ae.config.gesture.enabled=t),ge.models.addHTML('
'),ge.models.addBool("face compare",ae.config.face.embedding,"enabled",t=>{ae.config.face.embedding.enabled=t,vi=null}),document.getElementById("btnDisplay").addEventListener("click",t=>ge.display.toggle(t)),document.getElementById("btnImage").addEventListener("click",t=>ge.image.toggle(t)),document.getElementById("btnProcess").addEventListener("click",t=>ge.process.toggle(t)),document.getElementById("btnModel").addEventListener("click",t=>ge.models.toggle(t)),document.getElementById("btnStart").addEventListener("click",()=>g6()),document.getElementById("play").addEventListener("click",()=>g6())}async function Oae(){Ln("Demo starting ..."),Ln("Browser:",navigator==null?void 0:navigator.userAgent),Dae(),document.getElementById("log").innerText=`Human: version ${ae.version}`,ie.modelsPreload&&!ie.useWorker&&(Xn("loading"),await ae.load(Ur)),ie.useWorker||(Xn("initializing"),await ae.warmup(Ur)),Xn("human: ready"),document.getElementById("loader").style.display="none",document.getElementById("play").style.display="block",Ln("Demo ready...")}window.onload=Oae;window.onresize=a1; /** * @license * Copyright 2017 Google LLC. All Rights Reserved. * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. * ============================================================================= */ /** * @license * Copyright 2018 Google LLC * * Use of this source code is governed by an MIT-style * license that can be found in the LICENSE file or at * https://opensource.org/licenses/MIT. * ============================================================================= */ /** * @license * Copyright 2018 Google LLC. All Rights Reserved. * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. * * ============================================================================= */ /** * @license * Copyright 2018 Google LLC. All Rights Reserved. * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. * ============================================================================= */ /** * @license * Copyright 2019 Google LLC * * Use of this source code is governed by an MIT-style * license that can be found in the LICENSE file or at * https://opensource.org/licenses/MIT. * ============================================================================= */ /** * @license * Copyright 2019 Google LLC. All Rights Reserved. * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. * * ============================================================================= */ /** * @license * Copyright 2019 Google LLC. All Rights Reserved. * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. * ============================================================================= */ /** * @license * Copyright 2020 Google Inc. All Rights Reserved. * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. * ============================================================================= */ /** * @license * Copyright 2020 Google LLC * * Use of this source code is governed by an MIT-style * license that can be found in the LICENSE file or at * https://opensource.org/licenses/MIT. * ============================================================================= */ /** * @license * Copyright 2020 Google LLC. All Rights Reserved. * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. * ============================================================================= */ /** * @license * Copyright 2020 Google LLC. All Rights Reserved. * Licensed under the Apache License, Version 2.0 (the License); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an AS IS BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. * ============================================================================= */ /** * @license * Copyright 2021 Google LLC. All Rights Reserved. * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. * ============================================================================= */ /** @license See the LICENSE file. */ //# sourceMappingURL=demo-browser-index.js.map