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| /*
| Face-API
| homepage: <https://github.com/vladmandic/face-api>
| author: <https://github.com/vladmandic>'
| */
|
| "use strict";var faceapi=(()=>{var ux=Object.defineProperty;var YD=Object.getOwnPropertyDescriptor;var ZD=Object.getOwnPropertyNames;var JD=Object.prototype.hasOwnProperty;var QD=(e=>typeof require!="undefined"?require:typeof Proxy!="undefined"?new Proxy(e,{get:(t,n)=>(typeof require!="undefined"?require:t)[n]}):e)(function(e){if(typeof require!="undefined")return require.apply(this,arguments);throw new Error('Dynamic require of "'+e+'" is not supported')});var Dh=(e,t)=>{for(var n in t)ux(e,n,{get:t[n],enumerable:!0})},eR=(e,t,n,a)=>{if(t&&typeof t=="object"||typeof t=="function")for(let r of ZD(t))!JD.call(e,r)&&r!==n&&ux(e,r,{get:()=>t[r],enumerable:!(a=YD(t,r))||a.enumerable});return e};var tR=e=>eR(ux({},"__esModule",{value:!0}),e);var 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${o.rank}.`),A(l.rank===3||l.rank===1,()=>`Error in batchNorm3D: variance must be rank 3 or rank 1 but got rank ${l.rank}.`),u!=null&&A(u.rank===3||u.rank===1,()=>`Error in batchNorm3D: scale must be rank 3 or rank 1 but got rank ${u.rank}.`),p!=null&&A(p.rank===3||p.rank===1,()=>`Error in batchNorm3D: offset must be rank 3 or rank 1 but got rank ${p.rank}.`),_s(i,o,l,p,u,s)}var Xv=L({batchNorm3d_:rO});function sO(e,t,n,a,r,s){let i=_(e,"x","batchNorm"),o=_(t,"mean","batchNorm"),l=_(n,"variance","batchNorm"),u;r!=null&&(u=_(r,"scale","batchNorm"));let p;return a!=null&&(p=_(a,"offset","batchNorm")),A(i.rank===4,()=>`Error in batchNorm4D: x must be rank 4 but got rank ${i.rank}.`),A(o.rank===4||o.rank===1,()=>`Error in batchNorm4D: mean must be rank 4 or rank 1 but got rank ${o.rank}.`),A(l.rank===4||l.rank===1,()=>`Error in batchNorm4D: variance must be rank 4 or rank 1 but got rank ${l.rank}.`),u!=null&&A(u.rank===4||u.rank===1,()=>`Error in batchNorm4D: scale must be rank 4 or rank 1 but got rank ${u.rank}.`),p!=null&&A(p.rank===4||p.rank===1,()=>`Error in batchNorm4D: offset must be rank 4 or rank 1 but got rank ${p.rank}.`),_s(i,o,l,p,u,s)}var Yv=L({batchNorm4d_:sO});function iO(e,t,n){let a=_(e,"x","bincount"),r=_(t,"weights","bincount");A(a.dtype==="int32",()=>`Error in bincount: input dtype must be int32, but got ${a.dtype}`),A(n>=0,()=>`size must be non-negative, but got ${n}.`),A(r.size===a.size||r.size===0,()=>`Error in bincount: weights must have the same size as input or0-length, but got input shape: ${a.shape}, weights shape: ${r.shape}.`);let s={x:a,weights:r},i={size:n};return O.runKernel(fu,s,i)}var Zv=L({bincount_:iO});function oO(e,t){let n=_(e,"x","bitwiseAnd"),a=_(t,"y","bitwiseAnd");if(!Pr(n.shape,a.shape))throw new Error(`BitwiseAnd: Tensors must have the same shape. x: ${n.shape}, y: ${a.shape}`);if(n.dtype!=="int32"||a.dtype!=="int32")throw new Error(`BitwiseAnd: Only supports 'int32' values in tensor, found type of x: ${n.dtype} and type of 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| ${s} and ${t} for depthToSpace with input shape
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t=[],n,a=e.slice(0,this.inputs.length),r=e.slice(this.inputs.length,this.inputs.length+this.outputs.length),s=[];for(let l=0;l<this.inputs.length;++l)s.push({key:this.inputs[l],value:a[l]});let i=new ni(s),o=sc(this.outputs,i);for(let l=0;l<this.lossFunctions.length;++l){let u=this.lossFunctions[l],p=Et(u(r[l],o[l]));l===0?n=p:n=X(n,p),t.push(n)}for(let l=0;l<this.metricsTensors.length;++l){let u=this.metricsTensors[l][0],p=this.metricsTensors[l][1],d=Et(u(r[p],o[p]));t.push(d)}return t})}async fit(e,t,n={}){if(this.isTraining)throw new Error("Cannot start training because another fit() call is ongoing.");this.isTraining=!0;let a,r,s,i,o,l,u,p,d;try{let c=n.batchSize==null?32:n.batchSize;xx(c);let h=!1,m=await this.standardizeUserData(e,t,n.sampleWeight,n.classWeight,h,c);a=m[0],r=m[1],d=m[2];let f=!1,g;if(n.validationData!=null&&n.validationData.length>0){if(f=!0,n.validationData.length===2)o=n.validationData[0],l=n.validationData[1];else throw n.validationData.length===3?new 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Be{constructor(e){if(super(e==null?{}:e),this.DEFAULT_ALPHA_INITIALIZER="zeros",e==null&&(e={}),this.supportsMasking=!0,this.alphaInitializer=Tt(e.alphaInitializer||this.DEFAULT_ALPHA_INITIALIZER),this.alphaRegularizer=Ct(e.alphaRegularizer),this.alphaConstraint=Zt(e.alphaConstraint),e.sharedAxes==null)this.sharedAxes=null;else if(Array.isArray(e.sharedAxes))this.sharedAxes=e.sharedAxes;else if(typeof e.sharedAxes=="number")this.sharedAxes=[e.sharedAxes];else throw new V(`Expected sharedAxes to be a number or an array of numbers, but got ${e.sharedAxes}`)}build(e){e=Je(e);let t=e.slice(1);if(this.sharedAxes!=null)for(let a of this.sharedAxes)t[a-1]=1;this.alpha=this.addWeight("alpha",t,"float32",this.alphaInitializer,this.alphaRegularizer,!0,this.alphaConstraint);let n={};if(this.sharedAxes!=null)for(let a=1;a<e.length;++a)n[a]=e[a];this.inputSpec=[new Bt({ndim:e.length,axes:n})],this.built=!0}call(e,t){return e=Ce(e),yd(e,this.alpha.read())}getConfig(){let e={alphaInitializer:At(this.alphaInitializer),alphaRegularizer:mt(this.alphaRegularizer),alphaConstraint:Yt(this.alphaConstraint),sharedAxes:this.sharedAxes},t=super.getConfig();return Object.assign(e,t),e}};T0.className="PReLU";ne.registerClass(T0);var C0=class extends Be{constructor(e){if(super(e==null?{}:e),this.DEFAULT_ALPHA=1,e==null&&(e={}),e.alpha!=null&&e.alpha!==this.DEFAULT_ALPHA)throw new Le(`Non-default alpha value (${e.alpha}) is not supported by the ELU layer yet.`);this.alpha=e.alpha==null?this.DEFAULT_ALPHA:e.alpha}call(e,t){let n=Ce(e);return cp(n)}computeOutputShape(e){return e}getConfig(){let e={alpha:this.alpha},t=super.getConfig();return Object.assign(e,t),e}};C0.className="ELU";ne.registerClass(C0);var _0=class extends Be{constructor(e){super(e==null?{}:e),this.DEFAULT_THETA=1,e==null&&(e={}),this.theta=e.theta==null?this.DEFAULT_THETA:e.theta}call(e,t){let n=Ce(e);return z(n,se(_n(n,this.theta),"float32"))}computeOutputShape(e){return e}getConfig(){let e={theta:this.theta},t=super.getConfig();return Object.assign(e,t),e}};_0.className="ThresholdedReLU";ne.registerClass(_0);var E0=class extends Be{constructor(e){super(e==null?{}:e),this.DEFAULT_AXIS=1,e==null&&(e={}),this.softmax=new k0().apply,this.axis=e.axis==null?this.DEFAULT_AXIS:e.axis}call(e,t){let n=Ce(e);return this.softmax(n,this.axis)}computeOutputShape(e){return e}getConfig(){let e={axis:this.axis},t=super.getConfig();return Object.assign(e,t),e}};E0.className="Softmax";ne.registerClass(E0);function Wl(e,t,n){if(typeof e=="number")return yi(e,t);if(e.length!==t)throw new V(`The ${n} argument must be an integer or tuple of ${t} integers. 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instead`);if(s==="channelsFirst"&&(e=De(e,[0,2,1])),r==="causal")throw new Le("The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.");let o=ef(e,t,a,r==="same"?"same":"valid","NWC",i);return n!=null&&(o=Ya(o,n)),o})}function qI(e,t,n,a=[1,1],r="valid",s,i,o=null){return P(()=>{if(s==null&&(s=ja()),Pt(s),e.rank!==3&&e.rank!==4)throw new V(`conv2dWithBiasActivation expects input to be of rank 3 or 4, but received ${e.rank}.`);if(t.rank!==3&&t.rank!==4)throw new V(`conv2dWithBiasActivation expects kernel to be of rank 3 or 4, but received ${e.rank}.`);let l=A0(e,s);if(r==="causal")throw new Le("The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.");return l=Zl.conv2d({x:l,filter:t,strides:a,pad:r==="same"?"same":"valid",dilations:i,dataFormat:"NHWC",bias:n,activation:o}),s==="channelsFirst"&&(l=De(l,[0,3,1,2])),l})}function LH(e,t,n,a=[1,1,1],r="valid",s,i){return P(()=>{if(s==null&&(s=ja()),Pt(s),e.rank!==4&&e.rank!==5)throw new V(`conv3dWithBias expects input to be of rank 4 or 5, but received ${e.rank}.`);if(t.rank!==4&&t.rank!==5)throw new V(`conv3dWithBias expects kernel to be of rank 4 or 5, but received ${e.rank}.`);let o=dC(e,s);if(r==="causal")throw new Le("The support for CAUSAL padding mode in conv3dWithBias is not implemented yet.");return o=rw(o,t,a,r==="same"?"same":"valid","NDHWC",i),n!=null&&(o=Ya(o,n)),s==="channelsFirst"&&(o=De(o,[0,4,1,2,3])),o})}var F0=class extends Be{constructor(e,t){if(super(t),this.bias=null,this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_BIAS_INITIALIZER="zeros",F0.verifyArgs(t),this.rank=e,an(this.rank,"rank"),this.rank!==1&&this.rank!==2&&this.rank!==3)throw new Le(`Convolution layer for rank other than 1, 2, or 3 (${this.rank}) is not implemented yet.`);if(this.kernelSize=Wl(t.kernelSize,e,"kernelSize"),this.strides=Wl(t.strides==null?1:t.strides,e,"strides"),this.padding=t.padding==null?"valid":t.padding,wa(this.padding),this.dataFormat=t.dataFormat==null?"channelsLast":t.dataFormat,Pt(this.dataFormat),this.activation=ys(t.activation),this.useBias=t.useBias==null?!0:t.useBias,this.biasInitializer=Tt(t.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.biasConstraint=Zt(t.biasConstraint),this.biasRegularizer=Ct(t.biasRegularizer),this.activityRegularizer=Ct(t.activityRegularizer),this.dilationRate=Wl(t.dilationRate==null?1:t.dilationRate,e,"dilationRate"),this.rank===1&&Array.isArray(this.dilationRate)&&this.dilationRate.length!==1)throw new V(`dilationRate must be a number or an array of a single number for 1D convolution, but received ${JSON.stringify(this.dilationRate)}`);if(this.rank===2){if(typeof this.dilationRate=="number")this.dilationRate=[this.dilationRate,this.dilationRate];else if(this.dilationRate.length!==2)throw new V(`dilationRate must be a number or array of two numbers for 2D convolution, but received ${JSON.stringify(this.dilationRate)}`)}else if(this.rank===3){if(typeof this.dilationRate=="number")this.dilationRate=[this.dilationRate,this.dilationRate,this.dilationRate];else if(this.dilationRate.length!==3)throw new V(`dilationRate must be a number or array of three numbers for 3D convolution, but received ${JSON.stringify(this.dilationRate)}`)}}static verifyArgs(e){if(rr("kernelSize"in e,"required key 'kernelSize' not in config"),typeof e.kernelSize!="number"&&!n0(e.kernelSize,"number",1,3))throw new V(`BaseConv expects config.kernelSize to be number or number[] with length 1, 2, or 3, but received ${JSON.stringify(e.kernelSize)}.`)}getConfig(){let e={kernelSize:this.kernelSize,strides:this.strides,padding:this.padding,dataFormat:this.dataFormat,dilationRate:this.dilationRate,activation:bs(this.activation),useBias:this.useBias,biasInitializer:At(this.biasInitializer),biasRegularizer:mt(this.biasRegularizer),activityRegularizer:mt(this.activityRegularizer),biasConstraint:Yt(this.biasConstraint)},t=super.getConfig();return Object.assign(e,t),e}},Ed=class extends F0{constructor(e,t){super(e,t),this.kernel=null,Ed.verifyArgs(t),this.filters=t.filters,an(this.filters,"filters"),this.kernelInitializer=Tt(t.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.kernelConstraint=Zt(t.kernelConstraint),this.kernelRegularizer=Ct(t.kernelRegularizer)}build(e){e=Je(e);let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null)throw new V(`The channel dimension of the input should be defined. Found ${e[t]}`);let n=e[t],a=this.kernelSize.concat([n,this.filters]);this.kernel=this.addWeight("kernel",a,null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[{ndim:this.rank+2,axes:{[t]:n}}],this.built=!0}call(e,t){return P(()=>{e=Ce(e);let n,a=this.bias==null?null:this.bias.read(),r=v2(this.activation.getClassName());if(r!=null&&this.rank===2)n=qI(e,this.kernel.read(),a,this.strides,this.padding,this.dataFormat,this.dilationRate,r);else{if(this.rank===1)n=OH(e,this.kernel.read(),a,this.strides[0],this.padding,this.dataFormat,this.dilationRate[0]);else if(this.rank===2)n=qI(e,this.kernel.read(),a,this.strides,this.padding,this.dataFormat,this.dilationRate);else if(this.rank===3)n=LH(e,this.kernel.read(),a,this.strides,this.padding,this.dataFormat,this.dilationRate);else throw new Le("convolutions greater than 3D are not implemented yet.");this.activation!=null&&(n=this.activation.apply(n))}return n})}computeOutputShape(e){e=Je(e);let t=[],n=this.dataFormat==="channelsLast"?e.slice(1,e.length-1):e.slice(2);for(let r=0;r<n.length;++r){let s=Ha(n[r],this.kernelSize[r],this.padding,this.strides[r],typeof this.dilationRate=="number"?this.dilationRate:this.dilationRate[r]);t.push(s)}let a=[e[0]];return this.dataFormat==="channelsLast"?(a=a.concat(t),a.push(this.filters)):(a.push(this.filters),a=a.concat(t)),a}getConfig(){let e={filters:this.filters,kernelInitializer:At(this.kernelInitializer),kernelRegularizer:mt(this.kernelRegularizer),kernelConstraint:Yt(this.kernelConstraint)},t=super.getConfig();return Object.assign(e,t),e}static verifyArgs(e){if(!("filters"in e)||typeof e.filters!="number"||e.filters<1)throw new V(`Convolution layer expected config.filters to be a 'number' > 0 but got ${JSON.stringify(e.filters)}`)}},Ad=class extends Ed{constructor(e){super(2,e),Ad.verifyArgs(e)}getConfig(){let e=super.getConfig();return delete e.rank,e}static verifyArgs(e){if(typeof e.kernelSize!="number"&&!n0(e.kernelSize,"number",1,2))throw new V(`Conv2D expects config.kernelSize to be number or number[] with length 1 or 2, but received ${JSON.stringify(e.kernelSize)}.`)}};Ad.className="Conv2D";ne.registerClass(Ad);var Fd=class extends Ed{constructor(e){super(3,e),Fd.verifyArgs(e)}getConfig(){let e=super.getConfig();return delete e.rank,e}static verifyArgs(e){if(typeof e.kernelSize!="number"&&!(Array.isArray(e.kernelSize)&&(e.kernelSize.length===1||e.kernelSize.length===3)))throw new V(`Conv3D expects config.kernelSize to be number or [number, number, number], but received ${JSON.stringify(e.kernelSize)}.`)}};Fd.className="Conv3D";ne.registerClass(Fd);var $0=class extends Ad{constructor(e){if(super(e),this.inputSpec=[new Bt({ndim:4})],this.padding!=="same"&&this.padding!=="valid")throw new V(`Conv2DTranspose currently supports only padding modes 'same' and 'valid', but received padding mode ${this.padding}`)}build(e){if(e=Je(e),e.length!==4)throw new V("Input should have rank 4; Received input shape: "+JSON.stringify(e));let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null)throw new V("The channel dimension of the inputs should be defined. Found `None`.");let n=e[t],a=this.kernelSize.concat([this.filters,n]);this.kernel=this.addWeight("kernel",a,"float32",this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[new Bt({ndim:4,axes:{[t]:n}})],this.built=!0}call(e,t){return P(()=>{let n=Ce(e);if(n.shape.length!==4)throw new V(`Conv2DTranspose.call() expects input tensor to be rank-4, but received a tensor of rank-${n.shape.length}`);let a=n.shape,r=a[0],s,i;this.dataFormat==="channelsFirst"?(s=2,i=3):(s=1,i=2);let o=a[s],l=a[i],u=this.kernelSize[0],p=this.kernelSize[1],d=this.strides[0],c=this.strides[1],h=sr(o,d,u,this.padding),m=sr(l,c,p,this.padding),f=[r,h,m,this.filters];this.dataFormat!=="channelsLast"&&(n=De(n,[0,2,3,1]));let g=tf(n,this.kernel.read(),f,this.strides,this.padding);return this.dataFormat!=="channelsLast"&&(g=De(g,[0,3,1,2])),this.bias!=null&&(g=Ya(g,this.bias.read(),this.dataFormat)),this.activation!=null&&(g=this.activation.apply(g)),g})}computeOutputShape(e){e=Je(e);let t=e.slice(),n,a,r;this.dataFormat==="channelsFirst"?(n=1,a=2,r=3):(n=3,a=1,r=2);let s=this.kernelSize[0],i=this.kernelSize[1],o=this.strides[0],l=this.strides[1];return t[n]=this.filters,t[a]=sr(t[a],o,s,this.padding),t[r]=sr(t[r],l,i,this.padding),t}getConfig(){let e=super.getConfig();return delete e.dilationRate,e}};$0.className="Conv2DTranspose";ne.registerClass($0);var D0=class extends Fd{constructor(e){if(super(e),this.inputSpec=[new Bt({ndim:5})],this.padding!=="same"&&this.padding!=="valid")throw new V(`Conv3DTranspose currently supports only padding modes 'same' and 'valid', but received padding mode ${this.padding}`)}build(e){if(e=Je(e),e.length!==5)throw new V("Input should have rank 5; Received input shape: "+JSON.stringify(e));let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null)throw new V("The channel dimension of the inputs should be defined. 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Use depthwiseInitializer, depthwiseRegularizer, depthwiseConstraint, pointwiseInitializer, pointwiseRegularizer and pointwiseConstraint instead.");if(t.padding!=null&&t.padding!=="same"&&t.padding!=="valid")throw new V(`SeparableConv${this.rank}D supports only padding modes: 'same' and 'valid', but received ${JSON.stringify(t.padding)}`);this.depthMultiplier=t.depthMultiplier==null?1:t.depthMultiplier,this.depthwiseInitializer=Tt(t.depthwiseInitializer||this.DEFAULT_DEPTHWISE_INITIALIZER),this.depthwiseRegularizer=Ct(t.depthwiseRegularizer),this.depthwiseConstraint=Zt(t.depthwiseConstraint),this.pointwiseInitializer=Tt(t.depthwiseInitializer||this.DEFAULT_POINTWISE_INITIALIZER),this.pointwiseRegularizer=Ct(t.pointwiseRegularizer),this.pointwiseConstraint=Zt(t.pointwiseConstraint)}build(e){if(e=Je(e),e.length<this.rank+2)throw new V(`Inputs to SeparableConv${this.rank}D should have rank ${this.rank+2}, but received input shape: ${JSON.stringify(e)}`);let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null||e[t]<0)throw new V(`The channel dimension of the inputs should be defined, but found ${JSON.stringify(e[t])}`);let n=e[t],a=this.kernelSize.concat([n,this.depthMultiplier]),r=[];for(let i=0;i<this.rank;++i)r.push(1);r.push(n*this.depthMultiplier,this.filters);let s=!0;this.depthwiseKernel=this.addWeight("depthwise_kernel",a,"float32",this.depthwiseInitializer,this.depthwiseRegularizer,s,this.depthwiseConstraint),this.pointwiseKernel=this.addWeight("pointwise_kernel",r,"float32",this.pointwiseInitializer,this.pointwiseRegularizer,s,this.pointwiseConstraint),this.useBias?this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,s,this.biasConstraint):this.bias=null,this.inputSpec=[new Bt({ndim:this.rank+2,axes:{[t]:n}})],this.built=!0}call(e,t){return P(()=>{e=Ce(e);let n;if(this.rank===1)throw new Le("1D separable convolution is not implemented yet.");return this.rank===2&&(this.dataFormat==="channelsFirst"&&(e=De(e,[0,2,3,1])),n=$s(e,this.depthwiseKernel.read(),this.pointwiseKernel.read(),this.strides,this.padding,this.dilationRate,"NHWC")),this.useBias&&(n=Ya(n,this.bias.read(),this.dataFormat)),this.activation!=null&&(n=this.activation.apply(n)),this.dataFormat==="channelsFirst"&&(n=De(n,[0,3,1,2])),n})}getConfig(){let e=super.getConfig();return delete e.rank,delete e.kernelInitializer,delete e.kernelRegularizer,delete e.kernelConstraint,e.depthwiseInitializer=At(this.depthwiseInitializer),e.pointwiseInitializer=At(this.pointwiseInitializer),e.depthwiseRegularizer=mt(this.depthwiseRegularizer),e.pointwiseRegularizer=mt(this.pointwiseRegularizer),e.depthwiseConstraint=Yt(this.depthwiseConstraint),e.pointwiseConstraint=Yt(this.pointwiseConstraint),e}};hC.className="SeparableConv";var R0=class extends hC{constructor(e){super(2,e)}};R0.className="SeparableConv2D";ne.registerClass(R0);var Uf=class extends Ed{constructor(e){super(1,e),Uf.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"&&!n0(e.kernelSize,"number",1,1))throw new V(`Conv1D expects config.kernelSize to be number or number[] with length 1, but received ${JSON.stringify(e.kernelSize)}.`)}};Uf.className="Conv1D";ne.registerClass(Uf);var M0=class extends Be{constructor(e){super(e),typeof e.cropping=="number"?this.cropping=[[e.cropping,e.cropping],[e.cropping,e.cropping]]:typeof e.cropping[0]=="number"?this.cropping=[[e.cropping[0],e.cropping[0]],[e.cropping[1],e.cropping[1]]]:this.cropping=e.cropping,this.dataFormat=e.dataFormat===void 0?"channelsLast":e.dataFormat,this.inputSpec=[{ndim:4}]}computeOutputShape(e){return this.dataFormat==="channelsFirst"?[e[0],e[1],e[2]-this.cropping[0][0]-this.cropping[0][1],e[3]-this.cropping[1][0]-this.cropping[1][1]]:[e[0],e[1]-this.cropping[0][0]-this.cropping[0][1],e[2]-this.cropping[1][0]-this.cropping[1][1],e[3]]}call(e,t){return P(()=>{if(e=Ce(e),this.dataFormat==="channelsLast"){let n=Lh(e,this.cropping[0][0],e.shape[1]-this.cropping[0][0]-this.cropping[0][1],2);return Lh(n,this.cropping[1][0],e.shape[2]-this.cropping[1][1]-this.cropping[1][0],3)}else{let n=Lh(e,this.cropping[0][0],e.shape[2]-this.cropping[0][0]-this.cropping[0][1],3);return Lh(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}};M0.className="Cropping2D";ne.registerClass(M0);var P0=class extends Be{constructor(e){super(e),this.DEFAULT_SIZE=[2,2],this.inputSpec=[{ndim:4}],this.size=e.size==null?this.DEFAULT_SIZE:e.size,this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,Pt(this.dataFormat),this.interpolation=e.interpolation==null?"nearest":e.interpolation,ZU(this.interpolation)}computeOutputShape(e){if(this.dataFormat==="channelsFirst"){let t=e[2]==null?null:this.size[0]*e[2],n=e[3]==null?null:this.size[1]*e[3];return[e[0],e[1],t,n]}else{let t=e[1]==null?null:this.size[0]*e[1],n=e[2]==null?null:this.size[1]*e[2];return[e[0],t,n,e[3]]}}call(e,t){return P(()=>{let n=Ce(e),a=n.shape;if(this.dataFormat==="channelsFirst"){n=De(n,[0,2,3,1]);let r=this.size[0]*a[2],s=this.size[1]*a[3],i=this.interpolation==="nearest"?ea.resizeNearestNeighbor(n,[r,s]):ea.resizeBilinear(n,[r,s]);return De(i,[0,3,1,2])}else{let r=this.size[0]*a[1],s=this.size[1]*a[2];return this.interpolation==="nearest"?ea.resizeNearestNeighbor(n,[r,s]):ea.resizeBilinear(n,[r,s])}})}getConfig(){let e={size:this.size,dataFormat:this.dataFormat,interpolation:this.interpolation},t=super.getConfig();return Object.assign(e,t),e}};P0.className="UpSampling2D";ne.registerClass(P0);function zH(e,t,n=[1,1],a="valid",r,s){return P(()=>{r==null&&(r=ja()),Pt(r);let i=A0(e,r);if(e.rank!==4)throw new V(`Input for depthwiseConv2d is required to be 4-D, but is instead ${e.rank}-D`);if(t.rank!==4)throw new V(`depthwiseKernel is required to be 4-D, but is instead ${t.rank}-D`);return i=Es(i,t,n,a==="same"?"same":"valid","NHWC",s),r==="channelsFirst"&&(i=De(i,[0,3,1,2])),i})}var O0=class extends F0{constructor(e){super(2,e),this.depthwiseKernel=null,this.depthMultiplier=e.depthMultiplier==null?1:e.depthMultiplier,this.depthwiseInitializer=Tt(e.depthwiseInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.depthwiseConstraint=Zt(e.depthwiseConstraint),this.depthwiseRegularizer=Ct(e.depthwiseRegularizer)}build(e){if(e=Je(e),e.length<4)throw new V(`Inputs to DepthwiseConv2D should have rank 4. Received input shape: ${JSON.stringify(e)}.`);let t=this.dataFormat==="channelsFirst"?1:3;if(e[t]==null||e[t]<0)throw new V(`The channel dimension of the inputs to DepthwiseConv2D should be defined, but is not (${e[t]}).`);let n=e[t],a=[this.kernelSize[0],this.kernelSize[1],n,this.depthMultiplier];this.depthwiseKernel=this.addWeight("depthwise_kernel",a,null,this.depthwiseInitializer,this.depthwiseRegularizer,!0,this.depthwiseConstraint),this.useBias?this.bias=this.addWeight("bias",[n*this.depthMultiplier],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint):this.bias=null,this.built=!0}call(e,t){return P(()=>{e=Ce(e);let n=zH(e,this.depthwiseKernel.read(),this.strides,this.padding,this.dataFormat,null);return this.useBias&&(n=Ya(n,this.bias.read(),this.dataFormat)),this.activation!=null&&(n=this.activation.apply(n)),n})}computeOutputShape(e){e=Je(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],n=this.dataFormat==="channelsFirst"?e[3]:e[2],a=this.dataFormat==="channelsFirst"?e[1]*this.depthMultiplier:e[3]*this.depthMultiplier,r=Ha(t,this.kernelSize[0],this.padding,this.strides[0]),s=Ha(n,this.kernelSize[1],this.padding,this.strides[1]);return this.dataFormat==="channelsFirst"?[e[0],a,r,s]:[e[0],r,s,a]}getConfig(){let e=super.getConfig();return e.depthMultiplier=this.depthMultiplier,e.depthwiseInitializer=At(this.depthwiseInitializer),e.depthwiseRegularizer=mt(this.depthwiseRegularizer),e.depthwiseConstraint=Yt(this.depthwiseRegularizer),e}};O0.className="DepthwiseConv2D";ne.registerClass(O0);function mC(e,t,n,a){if(Array.isArray(e)){if(t!=null||n!=null)throw new V("When inputs is an array, neither initialState or constants should be provided");a!=null&&(n=e.slice(e.length-a,e.length),e=e.slice(0,e.length-a)),e.length>1&&(t=e.slice(1,e.length)),e=e[0]}function r(s){return s==null||Array.isArray(s)?s:[s]}return t=r(t),n=r(n),{inputs:e,initialState:t,constants:n}}function fC(e,t,n,a=!1,r,s,i=!1,o=!1){return P(()=>{let l=t.shape.length;if(l<3)throw new V(`Input should be at least 3D, but is ${l}D.`);let u=[1,0].concat(qa(2,l));if(t=De(t,u),s!=null)throw new Le("The rnn() functoin of the deeplearn.js backend does not support constants yet.");i&&console.warn("Backend rnn(): the unroll = true option is not applicable to the imperative deeplearn.js backend."),r!=null&&(r=se(se(r,"bool"),"float32"),r.rank===l-1&&(r=nn(r,-1)),r=De(r,u)),a&&(t=ya(t,0),r!=null&&(r=ya(r,0)));let p=[],d,c=n,h=t.shape[0],m=ct(t),f;r!=null&&(f=ct(r));for(let b=0;b<h;++b){let y=m[b],x=P(()=>e(y,c));if(r==null)d=x[0],c=x[1];else{let v=P(()=>{let I=f[b],T=pe(aa(I),I),C=X(z(x[0],I),z(c[0],T)),E=c.map((F,D)=>X(z(x[1][D],I),z(F,T)));return{output:C,newStates:E}});d=v.output,c=v.newStates}o&&p.push(d)}let g;return o&&(g=Dt(p,1)),[d,g,c]})}var br=class extends Be{constructor(e){super(e);let t;if(e.cell==null)throw new V("cell property is missing for the constructor of RNN.");if(Array.isArray(e.cell)?t=new qf({cells:e.cell}):t=e.cell,t.stateSize==null)throw new V("The RNN cell should have an attribute `stateSize` (tuple of integers, one integer per RNN state).");this.cell=t,this.returnSequences=e.returnSequences==null?!1:e.returnSequences,this.returnState=e.returnState==null?!1:e.returnState,this.goBackwards=e.goBackwards==null?!1:e.goBackwards,this._stateful=e.stateful==null?!1:e.stateful,this.unroll=e.unroll==null?!1:e.unroll,this.supportsMasking=!0,this.inputSpec=[new Bt({ndim:3})],this.stateSpec=null,this.states_=null,this.numConstants=null,this.keptStates=[]}getStates(){if(this.states_==null){let e=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1;return qa(0,e).map(t=>null)}else return this.states_}setStates(e){this.states_=e}computeOutputShape(e){Hx(e)&&(e=e[0]),e=e;let t=this.cell.stateSize;Array.isArray(t)||(t=[t]);let n=t[0],a;if(this.returnSequences?a=[e[0],e[1],n]:a=[e[0],n],this.returnState){let r=[];for(let s of t)r.push([e[0],s]);return[a].concat(r)}else return a}computeMask(e,t){return P(()=>{Array.isArray(t)&&(t=t[0]);let n=this.returnSequences?t:null;if(this.returnState){let a=this.states.map(r=>null);return[n].concat(a)}else return n})}get states(){if(this.states_==null){let e=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1,t=[];for(let n=0;n<e;++n)t.push(null);return t}else return this.states_}set states(e){this.states_=e}build(e){if(this.numConstants!=null)throw new Le("Constants support is not implemented in RNN yet.");Hx(e)&&(e=e[0]),e=e;let t=this.stateful?e[0]:null,n=e.slice(2);this.inputSpec[0]=new Bt({shape:[t,null,...n]});let a=[e[0]].concat(e.slice(2));this.cell.build(a);let r;if(Array.isArray(this.cell.stateSize)?r=this.cell.stateSize:r=[this.cell.stateSize],this.stateSpec!=null){if(!w.arraysEqual(this.stateSpec.map(s=>s.shape[s.shape.length-1]),r))throw new V(`An initialState was passed that is not compatible with cell.stateSize. Received stateSpec=${this.stateSpec}; However cell.stateSize is ${this.cell.stateSize}`)}else this.stateSpec=r.map(s=>new Bt({shape:[null,s]}));this.stateful&&this.resetStates()}resetStates(e,t=!1){P(()=>{if(!this.stateful)throw new Cr("Cannot call resetStates() on an RNN Layer that is not stateful.");let n=this.inputSpec[0].shape[0];if(n==null)throw new V("If an RNN is stateful, it needs to know its batch size. Specify the batch size of your input tensors: \n- If using a Sequential model, specify the batch size by passing a `batchInputShape` option to your first layer.\n- If using the functional API, specify the batch size by passing a `batchShape` option to your Input layer.");if(this.states_==null)Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(a=>Nt([n,a])):this.states_=[Nt([n,this.cell.stateSize])];else if(e==null)_e(this.states_),this.keptStates!=null&&(_e(this.keptStates),this.keptStates=[]),Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(a=>Nt([n,a])):this.states_[0]=Nt([n,this.cell.stateSize]);else{if(Array.isArray(e)||(e=[e]),e.length!==this.states_.length)throw new V(`Layer ${this.name} expects ${this.states_.length} state(s), but it received ${e.length} state value(s). Input received: ${e}`);t===!0?this.keptStates.push(this.states_.slice()):_e(this.states_);for(let a=0;a<this.states_.length;++a){let r=e[a],s=Array.isArray(this.cell.stateSize)?this.cell.stateSize[a]:this.cell.stateSize,i=[n,s];if(!w.arraysEqual(r.shape,i))throw new V(`State ${a} is incompatible with layer ${this.name}: expected shape=${i}, received shape=${r.shape}`);this.states_[a]=r}}this.states_=this.states_.map(a=>qt(a.clone()))})}apply(e,t){let n=t==null?null:t.initialState,a=t==null?null:t.constants;t==null&&(t={});let r=mC(e,n,a,this.numConstants);e=r.inputs,n=r.initialState,a=r.constants;let s=[],i=[];if(n!=null){t.initialState=n,s=s.concat(n),this.stateSpec=[];for(let o of n)this.stateSpec.push(new Bt({shape:o.shape}));i=i.concat(this.stateSpec)}if(a!=null&&(t.constants=a,s=s.concat(a),this.numConstants=a.length),s[0]instanceof Va){let o=[e].concat(s),l=this.inputSpec.concat(i),u=this.inputSpec;this.inputSpec=l;let p=super.apply(o,t);return this.inputSpec=u,p}else return super.apply(e,t)}call(e,t){return P(()=>{let n=t==null?null:t.mask,a=t==null?null:t.training,r=t==null?null:t.initialState;e=Ce(e),r==null&&(this.stateful?r=this.states_:r=this.getInitialState(e));let s=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1;if(r.length!==s)throw new V(`RNN Layer has ${s} state(s) but was passed ${r.length} initial state(s).`);this.unroll&&console.warn("Ignoring unroll = true for RNN layer, due to imperative backend.");let i={training:a},o=fC((c,h)=>{let m=this.cell.call([c].concat(h),i);return[m[0],m.slice(1)]},e,r,this.goBackwards,n,null,this.unroll,this.returnSequences),l=o[0],u=o[1],p=o[2];this.stateful&&this.resetStates(p,a);let d=this.returnSequences?u:l;return this.returnState?[d].concat(p):d})}getInitialState(e){return P(()=>{let t=Nt(e.shape);return t=fe(t,[1,2]),t=Sd(t),Array.isArray(this.cell.stateSize)?this.cell.stateSize.map(n=>n>1?Ux(t,[1,n]):t):this.cell.stateSize>1?[Ux(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()===br.className&&(t.cell={className:this.cell.getClassName(),config:n}),Object.assign(Object.assign(Object.assign({},n),e),t)}static fromConfig(e,t,n={}){let a=t.cell,r=Ga(a,n);return new e(Object.assign(t,{cell:r}))}};br.className="RNN";ne.registerClass(br);var $d=class extends Be{},Gf=class extends $d{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,an(this.units,"units"),this.activation=ys(e.activation==null?this.DEFAULT_ACTIVATION:e.activation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=Tt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=Tt(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=Tt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelRegularizer=Ct(e.kernelRegularizer),this.recurrentRegularizer=Ct(e.recurrentRegularizer),this.biasRegularizer=Ct(e.biasRegularizer),this.kernelConstraint=Zt(e.kernelConstraint),this.recurrentConstraint=Zt(e.recurrentConstraint),this.biasConstraint=Zt(e.biasConstraint),this.dropout=Ql([1,gs([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=Ql([1,gs([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.dropoutFunc=e.dropoutFunc,this.stateSize=this.units,this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){e=Je(e),this.kernel=this.addWeight("kernel",[e[e.length-1],this.units],null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.recurrentKernel=this.addWeight("recurrent_kernel",[this.units,this.units],null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint),this.useBias?this.bias=this.addWeight("bias",[this.units],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint):this.bias=null,this.built=!0}call(e,t){return P(()=>{if(e=e,e.length!==2)throw new V(`SimpleRNNCell expects 2 input Tensors, got ${e.length}.`);let n=e[1];e=e[0];let a=t.training==null?!1:t.training;0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=xs({ones:()=>aa(e),rate:this.dropout,training:a,dropoutFunc:this.dropoutFunc})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=xs({ones:()=>aa(n),rate:this.recurrentDropout,training:a,dropoutFunc:this.dropoutFunc}));let r,s=this.dropoutMask,i=this.recurrentDropoutMask;s!=null?r=ur(z(e,s),this.kernel.read()):r=ur(e,this.kernel.read()),this.bias!=null&&(r=Ya(r,this.bias.read())),i!=null&&(n=z(n,i));let o=X(r,ur(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:bs(this.activation),useBias:this.useBias,kernelInitializer:At(this.kernelInitializer),recurrentInitializer:At(this.recurrentInitializer),biasInitializer:At(this.biasInitializer),kernelRegularizer:mt(this.kernelRegularizer),recurrentRegularizer:mt(this.recurrentRegularizer),biasRegularizer:mt(this.biasRegularizer),activityRegularizer:mt(this.activityRegularizer),kernelConstraint:Yt(this.kernelConstraint),recurrentConstraint:Yt(this.recurrentConstraint),biasConstraint:Yt(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout};return Object.assign(Object.assign({},e),t)}};Gf.className="SimpleRNNCell";ne.registerClass(Gf);var L0=class extends br{constructor(e){e.cell=new Gf(e),super(e)}call(e,t){return P(()=>{this.cell.dropoutMask!=null&&(_e(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(_e(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=t==null?null:t.mask,a=t==null?null:t.training,r=t==null?null:t.initialState;return super.call(e,{mask:n,training:a,initialState:r})})}static fromConfig(e,t){return new e(t)}};L0.className="SimpleRNN";ne.registerClass(L0);var Hf=class extends $d{constructor(e){if(super(e),this.DEFAULT_ACTIVATION="tanh",this.DEFAULT_RECURRENT_ACTIVATION="hardSigmoid",this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_RECURRENT_INITIALIZER="orthogonal",this.DEFAULT_BIAS_INITIALIZER="zeros",e.resetAfter)throw new V("GRUCell does not support reset_after parameter set to true.");this.units=e.units,an(this.units,"units"),this.activation=ys(e.activation===void 0?this.DEFAULT_ACTIVATION:e.activation),this.recurrentActivation=ys(e.recurrentActivation===void 0?this.DEFAULT_RECURRENT_ACTIVATION:e.recurrentActivation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=Tt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=Tt(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=Tt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelRegularizer=Ct(e.kernelRegularizer),this.recurrentRegularizer=Ct(e.recurrentRegularizer),this.biasRegularizer=Ct(e.biasRegularizer),this.kernelConstraint=Zt(e.kernelConstraint),this.recurrentConstraint=Zt(e.recurrentConstraint),this.biasConstraint=Zt(e.biasConstraint),this.dropout=Ql([1,gs([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=Ql([1,gs([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.dropoutFunc=e.dropoutFunc,this.implementation=e.implementation,this.stateSize=this.units,this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){e=Je(e);let t=e[e.length-1];this.kernel=this.addWeight("kernel",[t,this.units*3],null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.recurrentKernel=this.addWeight("recurrent_kernel",[this.units,this.units*3],null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint),this.useBias?this.bias=this.addWeight("bias",[this.units*3],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint):this.bias=null,this.built=!0}call(e,t){return P(()=>{if(e=e,e.length!==2)throw new V(`GRUCell expects 2 input Tensors (inputs, h, c), got ${e.length}.`);let n=t.training==null?!1:t.training,a=e[1];e=e[0],0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=xs({ones:()=>aa(e),rate:this.dropout,training:n,count:3,dropoutFunc:this.dropoutFunc})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=xs({ones:()=>aa(a),rate:this.recurrentDropout,training:n,count:3,dropoutFunc:this.dropoutFunc}));let r=this.dropoutMask,s=this.recurrentDropoutMask,i,o,l;0<this.dropout&&this.dropout<1&&(e=z(e,r[0]));let u=ur(e,this.kernel.read());this.useBias&&(u=Ya(u,this.bias.read())),0<this.recurrentDropout&&this.recurrentDropout<1&&(a=z(a,s[0]));let p=this.recurrentKernel.read(),[d,c]=zn(p,[2*this.units,this.units],p.rank-1),h=ur(a,d),[m,f,g]=zn(u,3,u.rank-1),[b,y]=zn(h,2,h.rank-1);i=this.recurrentActivation.apply(X(m,b)),o=this.recurrentActivation.apply(X(f,y));let x=ur(z(o,a),c);l=this.activation.apply(X(g,x));let v=X(z(i,a),z(X(1,yt(i)),l));return[v,v]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:bs(this.activation),recurrentActivation:bs(this.recurrentActivation),useBias:this.useBias,kernelInitializer:At(this.kernelInitializer),recurrentInitializer:At(this.recurrentInitializer),biasInitializer:At(this.biasInitializer),kernelRegularizer:mt(this.kernelRegularizer),recurrentRegularizer:mt(this.recurrentRegularizer),biasRegularizer:mt(this.biasRegularizer),activityRegularizer:mt(this.activityRegularizer),kernelConstraint:Yt(this.kernelConstraint),recurrentConstraint:Yt(this.recurrentConstraint),biasConstraint:Yt(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation,resetAfter:!1};return Object.assign(Object.assign({},e),t)}};Hf.className="GRUCell";ne.registerClass(Hf);var z0=class extends br{constructor(e){e.implementation===0&&console.warn("`implementation=0` has been deprecated, and now defaults to `implementation=1`. Please update your layer call."),e.cell=new Hf(e),super(e)}call(e,t){return P(()=>{this.cell.dropoutMask!=null&&(_e(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(_e(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=t==null?null:t.mask,a=t==null?null:t.training,r=t==null?null:t.initialState;return super.call(e,{mask:n,training:a,initialState:r})})}static fromConfig(e,t){return t.implmentation===0&&(t.implementation=1),new e(t)}};z0.className="GRU";ne.registerClass(z0);var Dd=class extends $d{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,an(this.units,"units"),this.activation=ys(e.activation===void 0?this.DEFAULT_ACTIVATION:e.activation),this.recurrentActivation=ys(e.recurrentActivation===void 0?this.DEFAULT_RECURRENT_ACTIVATION:e.recurrentActivation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=Tt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=Tt(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=Tt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.unitForgetBias=e.unitForgetBias,this.kernelRegularizer=Ct(e.kernelRegularizer),this.recurrentRegularizer=Ct(e.recurrentRegularizer),this.biasRegularizer=Ct(e.biasRegularizer),this.kernelConstraint=Zt(e.kernelConstraint),this.recurrentConstraint=Zt(e.recurrentConstraint),this.biasConstraint=Zt(e.biasConstraint),this.dropout=Ql([1,gs([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=Ql([1,gs([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.dropoutFunc=e.dropoutFunc,this.implementation=e.implementation,this.stateSize=[this.units,this.units],this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){var t;e=Je(e);let n=e[e.length-1];this.kernel=this.addWeight("kernel",[n,this.units*4],null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.recurrentKernel=this.addWeight("recurrent_kernel",[this.units,this.units*4],null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint);let a;if(this.useBias){if(this.unitForgetBias){let r=this.biasInitializer,s=this.units;a=new(t=class extends Pa{apply(i,o){let l=r.apply([s]),u=new Df().apply([s]),p=r.apply([s*2]);return AI(AI(l,u),p)}},t.className="CustomInit",t)}else a=this.biasInitializer;this.bias=this.addWeight("bias",[this.units*4],null,a,this.biasRegularizer,!0,this.biasConstraint)}else this.bias=null;this.built=!0}call(e,t){return P(()=>{let n=t.training==null?!1:t.training;if(e=e,e.length!==3)throw new V(`LSTMCell expects 3 input Tensors (inputs, h, c), got ${e.length}.`);let a=e[1],r=e[2];e=e[0],0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=xs({ones:()=>aa(e),rate:this.dropout,training:n,count:4,dropoutFunc:this.dropoutFunc})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=xs({ones:()=>aa(a),rate:this.recurrentDropout,training:n,count:4,dropoutFunc:this.dropoutFunc}));let s=this.dropoutMask,i=this.recurrentDropoutMask,o,l,u,p;0<this.dropout&&this.dropout<1&&(e=z(e,s[0]));let d=ur(e,this.kernel.read());0<this.recurrentDropout&&this.recurrentDropout<1&&(a=z(a,i[0])),d=X(d,ur(a,this.recurrentKernel.read())),this.useBias&&(d=Ya(d,this.bias.read()));let[c,h,m,f]=zn(d,4,d.rank-1);o=this.recurrentActivation.apply(c),l=this.recurrentActivation.apply(h),u=X(z(l,r),z(o,this.activation.apply(m))),p=this.recurrentActivation.apply(f);let g=z(p,this.activation.apply(u));return[g,g,u]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:bs(this.activation),recurrentActivation:bs(this.recurrentActivation),useBias:this.useBias,kernelInitializer:At(this.kernelInitializer),recurrentInitializer:At(this.recurrentInitializer),biasInitializer:At(this.biasInitializer),unitForgetBias:this.unitForgetBias,kernelRegularizer:mt(this.kernelRegularizer),recurrentRegularizer:mt(this.recurrentRegularizer),biasRegularizer:mt(this.biasRegularizer),activityRegularizer:mt(this.activityRegularizer),kernelConstraint:Yt(this.kernelConstraint),recurrentConstraint:Yt(this.recurrentConstraint),biasConstraint:Yt(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation};return Object.assign(Object.assign({},e),t)}};Dd.className="LSTMCell";ne.registerClass(Dd);var W0=class extends br{constructor(e){e.implementation===0&&console.warn("`implementation=0` has been deprecated, and now defaults to `implementation=1`. Please update your layer call."),e.cell=new Dd(e),super(e)}call(e,t){return P(()=>{this.cell.dropoutMask!=null&&(_e(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(_e(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=t==null?null:t.mask,a=t==null?null:t.training,r=t==null?null:t.initialState;return super.call(e,{mask:n,training:a,initialState:r})})}static fromConfig(e,t){return t.implmentation===0&&(t.implementation=1),new e(t)}};W0.className="LSTM";ne.registerClass(W0);var qf=class extends $d{constructor(e){super(e),this.cells=e.cells}get stateSize(){let e=[];for(let t of this.cells.slice().reverse())Array.isArray(t.stateSize)?e.push(...t.stateSize):e.push(t.stateSize);return e}call(e,t){return P(()=>{e=e;let n=e.slice(1),a=[];for(let i of this.cells.slice().reverse())Array.isArray(i.stateSize)?a.push(n.splice(0,i.stateSize.length)):a.push(n.splice(0,1));a.reverse();let r=[],s;for(let i=0;i<this.cells.length;++i){let o=this.cells[i];n=a[i],i===0?s=[e[0]].concat(n):s=[s[0]].concat(n),s=o.call(s,t),r.push(s.slice(1))}n=[];for(let i of r.slice().reverse())n.push(...i);return[s[0]].concat(n)})}build(e){Hx(e)&&(e=e[0]),e=e;let t;this.cells.forEach((n,a)=>{si(`RNNCell_${a}`,()=>{n.build(e),Array.isArray(n.stateSize)?t=n.stateSize[0]:t=n.stateSize,e=[e[0],t]})}),this.built=!0}getConfig(){let e=super.getConfig(),t=a=>({className:a.getClassName(),config:a.getConfig()}),n={cells:this.cells.map(t)};return Object.assign(Object.assign({},e),n)}static fromConfig(e,t,n={}){let a=[];for(let r of t.cells)a.push(Ga(r,n));return new e({cells:a})}get trainableWeights(){if(!this.trainable)return[];let e=[];for(let t of this.cells)e.push(...t.trainableWeights);return e}get nonTrainableWeights(){let e=[];for(let t of this.cells)e.push(...t.nonTrainableWeights);if(!this.trainable){let t=[];for(let n of this.cells)t.push(...n.trainableWeights);return t.concat(e)}return e}getWeights(){let e=[];for(let t of this.cells)e.push(...t.weights);return qx(e)}setWeights(e){let t=[];for(let n of this.cells){let a=n.weights.length,r=e.splice(a);for(let s=0;s<n.weights.length;++s)t.push([n.weights[s],r[s]])}c0(t)}};qf.className="StackedRNNCells";ne.registerClass(qf);function xs(e){let{ones:t,rate:n,training:a=!1,count:r=1,dropoutFunc:s}=e,i=()=>s!=null?s(t(),n):C2(t(),n),o=()=>Td(i,t,a);return!r||r<=1?qt(o().clone()):Array(r).fill(void 0).map(o).map(l=>qt(l.clone()))}var WH=function(e,t){var n={};for(var a in e)Object.prototype.hasOwnProperty.call(e,a)&&t.indexOf(a)<0&&(n[a]=e[a]);if(e!=null&&typeof Object.getOwnPropertySymbols=="function")for(var r=0,a=Object.getOwnPropertySymbols(e);r<a.length;r++)t.indexOf(a[r])<0&&Object.prototype.propertyIsEnumerable.call(e,a[r])&&(n[a[r]]=e[a[r]]);return n},gC=class extends br{constructor(e){if(e.unroll)throw new Le("Unrolling is not possible with convolutional RNNs.");if(Array.isArray(e.cell))throw new Le("It is not possible at the moment to stack convolutional cells.");super(e),this.inputSpec=[new Bt({ndim:5})]}call(e,t){return P(()=>{if(this.cell.dropoutMask!=null&&(_e(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(_e(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null),t&&t.constants)throw new V("ConvRNN2D cell does not support constants");let n=t==null?null:t.mask,a=t==null?null:t.training,r=t==null?null:t.initialState;return super.call(e,{mask:n,training:a,initialState:r})})}computeOutputShape(e){let t=this.computeSingleOutputShape(e);return this.returnSequences||(t=[t[0],...t.slice(2)]),this.returnState&&(t=[t,...Array(2).fill([e[0],...t.slice(-3)])]),t}getInitialState(e){return P(()=>{let{stateSize:t}=this.cell,n=e.shape,a=this.computeSingleOutputShape(n),r=[a[0],...a.slice(2)],s=Nt(r);return Array.isArray(t)?Array(t.length).fill(s):[s]})}resetStates(e,t=!1){P(()=>{if(!this.stateful)throw new Cr("Cannot call resetStates() on an RNN Layer that is not stateful.");let n=this.inputSpec[0].shape,a=this.computeSingleOutputShape(n),r=[a[0],...a.slice(2)];if(n[0]==null)throw new V("If an RNN is stateful, it needs to know its batch size. Specify the batch size of your input tensors: \n- If using a Sequential model, specify the batch size by passing a `batchInputShape` option to your first layer.\n- If using the functional API, specify the batch size by passing a `batchShape` option to your Input layer.");if(this.getStates()==null)Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(()=>Nt(r)):this.states_=[Nt(r)];else if(e==null)_e(this.states_),this.keptStates!=null&&(_e(this.keptStates),this.keptStates=[]),Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(()=>Nt(r)):this.states_[0]=Nt(r);else{if(Array.isArray(e)||(e=[e]),e.length!==this.states_.length)throw new V(`Layer ${this.name} expects ${this.states_.length} state(s), but it received ${e.length} state value(s). 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Found ${e[n]}`);let a=e[n],r=4,s=this.kernelSize.concat([a,this.filters*r]);this.kernel=this.addWeight("kernel",s,null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint);let i=this.kernelSize.concat([this.filters,this.filters*r]);if(this.recurrentKernel=this.addWeight("recurrent_kernel",i,null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint),this.useBias){let o;if(this.unitForgetBias){let l=this.biasInitializer,u=this.filters;o=new(t=class extends Pa{apply(p,d){let c=l.apply([u]),h=Qn([u]),m=l.apply([u*2]);return a0([c,h,m])}},t.className="CustomInit",t)}else o=this.biasInitializer;this.bias=this.addWeight("bias",[this.filters*r],null,o,this.biasRegularizer,!0,this.biasConstraint)}this.built=!0}call(e,t){return P(()=>{if(e.length!==3)throw new V(`ConvLSTM2DCell expects 3 input Tensors (inputs, h, c), got ${e.length}.`);let n=t.training||!1,a=e[0],r=e[1],s=e[2],i=4;0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=xs({ones:()=>aa(a),rate:this.dropout,training:n,count:i,dropoutFunc:this.dropoutFunc}));let o=this.dropoutMask,l=(Z,J,ee)=>!J||!J[ee]?Z:z(J[ee],Z),u=l(a,o,0),p=l(a,o,1),d=l(a,o,2),c=l(a,o,3);0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=xs({ones:()=>aa(r),rate:this.recurrentDropout,training:n,count:i,dropoutFunc:this.dropoutFunc}));let h=this.recurrentDropoutMask,m=l(r,h,0),f=l(r,h,1),g=l(r,h,2),b=l(r,h,3),y=3,[x,v,I,T]=zn(this.kernel.read(),i,y),[C,E,F,D]=this.useBias?zn(this.bias.read(),i):[null,null,null,null];u=this.inputConv(u,x,C,this.padding),p=this.inputConv(p,v,E,this.padding),d=this.inputConv(d,I,F,this.padding),c=this.inputConv(c,T,D,this.padding);let[$,S,M,B]=zn(this.recurrentKernel.read(),i,y);m=this.recurrentConv(m,$),f=this.recurrentConv(f,S),g=this.recurrentConv(g,M),b=this.recurrentConv(b,B);let U=this.recurrentActivation.apply(X(u,m)),H=this.recurrentActivation.apply(X(p,f)),j=X(z(H,s),z(U,this.activation.apply(X(d,g)))),K=z(this.recurrentActivation.apply(X(c,b)),this.activation.apply(j));return[K,K,j]})}getConfig(){let e=super.getConfig(),{units:t}=e,n=WH(e,["units"]),a={filters:this.filters,kernelSize:this.kernelSize,padding:this.padding,dataFormat:this.dataFormat,dilationRate:this.dilationRate,strides:this.strides};return Object.assign(Object.assign({},n),a)}inputConv(e,t,n,a){let r=Rt(e,t,this.strides,a||"valid",this.dataFormat==="channelsFirst"?"NCHW":"NHWC",this.dilationRate);return n?Ya(r,n,this.dataFormat):r}recurrentConv(e,t){return Rt(e,t,1,"same",this.dataFormat==="channelsFirst"?"NCHW":"NHWC")}};jf.className="ConvLSTM2DCell";ne.registerClass(jf);var B0=class extends gC{constructor(e){let t=new jf(e);super(Object.assign(Object.assign({},e),{cell:t}))}static fromConfig(e,t){return new e(t)}};B0.className="ConvLSTM2D";ne.registerClass(B0);var Kf=class extends Be{constructor(e){super(e),this.rate=Math.max(Math.min(e.rate,1),0),this.noiseShape=e.noiseShape,this.seed=e.seed,this.supportsMasking=!0}getNoiseShape(e){if(this.noiseShape==null)return this.noiseShape;let t=e.shape,n=[];for(let a=0;a<this.noiseShape.length;++a)n.push(this.noiseShape[a]==null?t[a]:this.noiseShape[a]);return n}call(e,t){return P(()=>{this.invokeCallHook(e,t);let n=Ce(e);if(0<this.rate&&this.rate<1){let a=t.training==null?!1:t.training,r=this.getNoiseShape(n);return Td(()=>C2(n,this.rate,r,this.seed),()=>n,a)}return e})}getConfig(){let e={rate:this.rate,noiseShape:this.noiseShape,seed:this.seed},t=super.getConfig();return Object.assign(e,t),e}dispose(){return super.dispose()}};Kf.className="Dropout";ne.registerClass(Kf);var V0=class extends Kf{constructor(e){super(e),this.inputSpec=[{ndim:3}]}getNoiseShape(e){let t=e.shape;return[t[0],1,t[2]]}};V0.className="SpatialDropout1D";ne.registerClass(V0);var U0=class extends Be{constructor(e){if(super(e),this.activation=null,this.useBias=!0,this.kernel=null,this.bias=null,this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_BIAS_INITIALIZER="zeros",e.batchInputShape==null&&e.inputShape==null&&e.inputDim!=null){let t=null;e.batchSize!=null&&(t=e.batchSize),this.batchInputShape=[t,e.inputDim]}this.units=e.units,an(this.units,"units"),this.activation=ys(e.activation),e.useBias!=null&&(this.useBias=e.useBias),this.kernelInitializer=Tt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.biasInitializer=Tt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelConstraint=Zt(e.kernelConstraint),this.biasConstraint=Zt(e.biasConstraint),this.kernelRegularizer=Ct(e.kernelRegularizer),this.biasRegularizer=Ct(e.biasRegularizer),this.activityRegularizer=Ct(e.activityRegularizer),this.supportsMasking=!0,this.inputSpec=[{minNDim:2}]}build(e){e=Je(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=Je(e);let t=e.slice();return t[t.length-1]=this.units,t}call(e,t){return P(()=>{this.invokeCallHook(e,t);let n=Ce(e),a=v2(this.activation.getClassName()),r;return a!=null?r=ur(n,this.kernel.read(),a,this.bias?this.bias.read():null):(r=ur(n,this.kernel.read()),this.bias!=null&&(r=Ya(r,this.bias.read())),this.activation!=null&&(r=this.activation.apply(r))),r})}getConfig(){let e={units:this.units,activation:bs(this.activation),useBias:this.useBias,kernelInitializer:At(this.kernelInitializer),biasInitializer:At(this.biasInitializer),kernelRegularizer:mt(this.kernelRegularizer),biasRegularizer:mt(this.biasRegularizer),activityRegularizer:mt(this.activityRegularizer),kernelConstraint:Yt(this.kernelConstraint),biasConstraint:Yt(this.biasConstraint)},t=super.getConfig();return Object.assign(e,t),e}};U0.className="Dense";ne.registerClass(U0);var G0=class extends Be{constructor(e){e=e||{},super(e),this.inputSpec=[{minNDim:3}],this.dataFormat=e.dataFormat}computeOutputShape(e){e=Je(e);for(let t of e.slice(1))if(t==null)throw new V(`The shape of the input to "Flatten" is not fully defined (got ${e.slice(1)}). 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t=this.axis>=0?this.axis:this.axis+e.length,n=e[t];if(n==null)throw new V(`Axis ${t} of input tensor should have a defined dimension but the layer received an input with shape ${JSON.stringify(e)}.`);this.inputSpec=[new Bt({ndim:e.length,axes:{[t]:n}})];let a=[n];this.scale&&(this.gamma=this.addWeight("gamma",a,null,this.gammaInitializer,this.gammaRegularizer,!0,this.gammaConstraint)),this.center&&(this.beta=this.addWeight("beta",a,null,this.betaInitializer,this.betaRegularizer,!0,this.betaConstraint)),this.movingMean=this.addWeight("moving_mean",a,null,this.movingMeanInitializer,null,!1),this.movingVariance=this.addWeight("moving_variance",a,null,this.movingVarianceInitializer,null,!1),this.built=!0}call(e,t){return P(()=>{let n=t.training==null?!1:t.training,a=Ce(e),r=a.shape,s=r.length,i=qa(0,s),o=this.axis>=0?this.axis:this.axis+s;i.splice(o,1);let l=yi(1,s);l[o]=r[o];let u=i.slice();u.sort();let p=!w.arraysEqual(u,qa(0,s).slice(0,s-1)),d=()=>{if(p){let 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e={axis:this.axis,momentum:this.momentum,epsilon:this.epsilon,center:this.center,scale:this.scale,betaInitializer:At(this.betaInitializer),gammaInitializer:At(this.gammaInitializer),movingMeanInitializer:At(this.movingMeanInitializer),movingVarianceInitializer:At(this.movingVarianceInitializer),betaRegularizer:mt(this.betaRegularizer),gammaRegularizer:mt(this.gammaRegularizer),betaConstraint:Yt(this.betaConstraint),gammaConstraint:Yt(this.gammaConstraint)},t=super.getConfig();return Object.assign(e,t),e}};o1.className="BatchNormalization";ne.registerClass(o1);var l1=class extends Be{constructor(e){if(e==null&&(e={}),super(e),this.axis=e.axis==null?-1:e.axis,typeof this.axis=="number"){if(!Number.isInteger(this.axis))throw new Error(`Expected axis to be an integer, but received ${this.axis}`)}else if(Array.isArray(this.axis)){for(let t of this.axis)if(!Number.isInteger(t))throw new Error(`Expected axis to be an array of integers, but received ${JSON.stringify(this.axis)}`)}else throw new Error(`Expected axis to be an integer or an array of integers, but received ${JSON.stringify(this.axis)}`);this.epsilon=e.epsilon==null?.001:e.epsilon,this.center=e.center==null?!0:e.center,this.scale=e.scale==null?!0:e.scale,this.betaInitializer=Tt(e.betaInitializer||"zeros"),this.gammaInitializer=Tt(e.gammaInitializer||"ones"),this.betaRegularizer=Ct(e.betaRegularizer),this.gammaRegularizer=Ct(e.gammaRegularizer),this.supportsMasking=!0}build(e){e=Je(e);let t=e.length;typeof this.axis=="number"&&(this.axis=[this.axis]);for(let r=0;r<this.axis.length;++r)this.axis[r]<0&&(this.axis[r]+=t);for(let r of this.axis)if(r<0||r>=t)throw new Error(`Invalid axis: ${r}`);if(this.axis.length!==us(this.axis).length)throw new Error(`Found duplicate axes in: ${this.axis}`);let n=this.axis.map(r=>e[r]),a=!0;this.scale?this.gamma=this.addWeight("gamma",n,"float32",this.gammaInitializer,this.gammaRegularizer,a):this.gamma=null,this.center?this.beta=this.addWeight("beta",n,"float32",this.betaInitializer,this.betaRegularizer,a):this.beta=null,this.built=!0}call(e,t){let n=Ce(e),a=n.shape,r=a.length;return P(()=>{let{mean:s,variance:i}=gd(n,this.axis,!0),o=yi(1,r);for(let h of this.axis)o[h]=a[h];let l=h=>h!=null&&h.shape.length!==r?W(h,o):h,u=this.scale?l(this.gamma.read()):null,p=this.center?l(this.beta.read()):null,d=[],c=[];for(let h=0;h<r;++h)this.axis.indexOf(h)!==-1?(d.push(a[h]),c.push(1)):(d.push(1),c.push(a[h]));return s=Ln(s,d),i=Ln(i,d),u!=null&&(u=Ln(u,c)),p!=null&&(p=Ln(p,c)),_c(n,s,i,p,u,this.epsilon)})}getConfig(){let e={axis:this.axis,epsilon:this.epsilon,center:this.center,scale:this.scale,betaInitializer:At(this.betaInitializer),gammaInitializer:At(this.gammaInitializer),betaRegularizer:mt(this.betaRegularizer),gammaRegularizer:mt(this.gammaRegularizer)},t=super.getConfig();return Object.assign(e,t),e}};l1.className="LayerNormalization";ne.registerClass(l1);function HH(e,t,n){return P(()=>{if(e.rank!==4)throw new V(`temporalPadding expects input tensor to be 4-D, but received a ${e.rank}-D tensor.`);if(t==null&&(t=[[1,1],[1,1]]),t.length!==2||t[0].length!==2||t[1].length!==2)throw new V("spatial2dPadding expects `padding` to be an Array of two Arrays, each of which is an Array of two integers.");if(n==null&&(n=ja()),n!=="channelsLast"&&n!=="channelsFirst")throw new V(`Unknown data format: ${n}. Supported data formats are 'channelsLast' and 'channelsFirst.`);let a;return n==="channelsFirst"?a=[[0,0],[0,0],t[0],t[1]]:a=[[0,0],t[0],t[1],[0,0]],va(e,a)})}var u1=class extends Be{constructor(e){if(e==null&&(e={}),super(e),this.dataFormat=e.dataFormat==null?ja():e.dataFormat,e.padding==null)this.padding=[[1,1],[1,1]];else if(typeof e.padding=="number")this.padding=[[e.padding,e.padding],[e.padding,e.padding]];else{if(e.padding=e.padding,e.padding.length!==2)throw new V(`ZeroPadding2D expects padding to be a length-2 array, but received a length-${e.padding.length} array.`);let t,n;if(typeof e.padding[0]=="number")t=[e.padding[0],e.padding[0]],n=[e.padding[1],e.padding[1]];else{if(e.padding=e.padding,e.padding[0].length!==2)throw new V(`ZeroPadding2D expects height padding to be a length-2 array, but received a length-${e.padding[0].length} array.`);if(t=e.padding[0],e.padding[1].length!==2)throw new V(`ZeroPadding2D expects width padding to be a length-2 array, but received a length-${e.padding[1].length} array.`);n=e.padding[1]}this.padding=[t,n]}this.inputSpec=[new Bt({ndim:4})]}computeOutputShape(e){e=Je(e);let t,n;return this.dataFormat==="channelsFirst"?(e[2]!=null&&e[2]>=0?t=e[2]+this.padding[0][0]+this.padding[0][1]:t=null,e[3]!=null&&e[3]>=0?n=e[3]+this.padding[1][0]+this.padding[1][1]:n=null,[e[0],e[1],t,n]):(e[1]!=null&&e[1]>=0?t=e[1]+this.padding[0][0]+this.padding[0][1]:t=null,e[2]!=null&&e[2]>=0?n=e[2]+this.padding[1][0]+this.padding[1][1]:n=null,[e[0],t,n,e[3]])}call(e,t){return P(()=>HH(Ce(e),this.padding,this.dataFormat))}getConfig(){let e={padding:this.padding,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}};u1.className="ZeroPadding2D";ne.registerClass(u1);function Xf(e,t,n,a,r,s){return P(()=>{Pt(r),k2(s),wa(a),n==null&&(n=[1,1]),a==null&&(a="valid"),r==null&&(r=ja()),s==null&&(s="max"),e=A0(e,r);let i,o=a==="same"?"same":"valid";return s==="max"?i=Mt(e,t,n,o):i=xa(e,t,n,o),r==="channelsFirst"&&(i=De(i,[0,3,1,2])),i})}function bC(e,t,n,a,r,s){return P(()=>{Pt(r),k2(s),wa(a),n==null&&(n=[1,1,1]),a==null&&(a="valid"),r==null&&(r=ja()),s==null&&(s="max"),e=dC(e,r);let i,o=a==="same"?"same":"valid";return s==="max"?i=ww(e,t,n,o):i=jv(e,t,n,o),r==="channelsFirst"&&(i=De(i,[0,4,1,2,3])),i})}var yC=class extends Be{constructor(e){if(e.poolSize==null&&(e.poolSize=2),super(e),typeof e.poolSize=="number")this.poolSize=[e.poolSize];else if(Array.isArray(e.poolSize)&&e.poolSize.length===1&&typeof e.poolSize[0]=="number")this.poolSize=e.poolSize;else throw new V(`poolSize for 1D convolutional layer must be a number or an Array of a single number, but received ${JSON.stringify(e.poolSize)}`);if(an(this.poolSize,"poolSize"),e.strides==null)this.strides=this.poolSize;else if(typeof e.strides=="number")this.strides=[e.strides];else if(Array.isArray(e.strides)&&e.strides.length===1&&typeof e.strides[0]=="number")this.strides=e.strides;else throw new V(`strides for 1D convolutional layer must be a number or an Array of a single number, but received ${JSON.stringify(e.strides)}`);an(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,wa(this.padding),this.inputSpec=[new Bt({ndim:3})]}computeOutputShape(e){e=Je(e);let t=Ha(e[1],this.poolSize[0],this.padding,this.strides[0]);return[e[0],t,e[2]]}call(e,t){return P(()=>{this.invokeCallHook(e,t),e=Sd(Ce(e),2);let n=this.poolingFunction(Ce(e),[this.poolSize[0],1],[this.strides[0],1],this.padding,"channelsLast");return Ds(n,[2])})}getConfig(){let e={poolSize:this.poolSize,padding:this.padding,strides:this.strides},t=super.getConfig();return Object.assign(e,t),e}},p1=class extends yC{constructor(e){super(e)}poolingFunction(e,t,n,a,r){return Pt(r),wa(a),Xf(e,t,n,a,r,"max")}};p1.className="MaxPooling1D";ne.registerClass(p1);var c1=class extends yC{constructor(e){super(e)}poolingFunction(e,t,n,a,r){return Pt(r),wa(a),Xf(e,t,n,a,r,"avg")}};c1.className="AveragePooling1D";ne.registerClass(c1);var xC=class extends Be{constructor(e){if(e.poolSize==null&&(e.poolSize=[2,2]),super(e),this.poolSize=Array.isArray(e.poolSize)?e.poolSize:[e.poolSize,e.poolSize],e.strides==null)this.strides=this.poolSize;else if(Array.isArray(e.strides)){if(e.strides.length!==2)throw new V(`If the strides property of a 2D pooling layer is an Array, it is expected to have a length of 2, but received length ${e.strides.length}.`);this.strides=e.strides}else this.strides=[e.strides,e.strides];an(this.poolSize,"poolSize"),an(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,Pt(this.dataFormat),wa(this.padding),this.inputSpec=[new Bt({ndim:4})]}computeOutputShape(e){e=Je(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],n=this.dataFormat==="channelsFirst"?e[3]:e[2];return t=Ha(t,this.poolSize[0],this.padding,this.strides[0]),n=Ha(n,this.poolSize[1],this.padding,this.strides[1]),this.dataFormat==="channelsFirst"?[e[0],e[1],t,n]:[e[0],t,n,e[3]]}call(e,t){return P(()=>(this.invokeCallHook(e,t),this.poolingFunction(Ce(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}},d1=class extends xC{constructor(e){super(e)}poolingFunction(e,t,n,a,r){return Pt(r),wa(a),Xf(e,t,n,a,r,"max")}};d1.className="MaxPooling2D";ne.registerClass(d1);var h1=class extends xC{constructor(e){super(e)}poolingFunction(e,t,n,a,r){return Pt(r),wa(a),Xf(e,t,n,a,r,"avg")}};h1.className="AveragePooling2D";ne.registerClass(h1);var vC=class extends Be{constructor(e){if(e.poolSize==null&&(e.poolSize=[2,2,2]),super(e),this.poolSize=Array.isArray(e.poolSize)?e.poolSize:[e.poolSize,e.poolSize,e.poolSize],e.strides==null)this.strides=this.poolSize;else if(Array.isArray(e.strides)){if(e.strides.length!==3)throw new V(`If the strides property of a 3D pooling layer is an Array, it is expected to have a length of 3, but received length ${e.strides.length}.`);this.strides=e.strides}else this.strides=[e.strides,e.strides,e.strides];an(this.poolSize,"poolSize"),an(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,Pt(this.dataFormat),wa(this.padding),this.inputSpec=[new Bt({ndim:5})]}computeOutputShape(e){e=Je(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],n=this.dataFormat==="channelsFirst"?e[3]:e[2],a=this.dataFormat==="channelsFirst"?e[4]:e[3];return t=Ha(t,this.poolSize[0],this.padding,this.strides[0]),n=Ha(n,this.poolSize[1],this.padding,this.strides[1]),a=Ha(a,this.poolSize[2],this.padding,this.strides[2]),this.dataFormat==="channelsFirst"?[e[0],e[1],t,n,a]:[e[0],t,n,a,e[4]]}call(e,t){return P(()=>(this.invokeCallHook(e,t),this.poolingFunction(Ce(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}},m1=class extends vC{constructor(e){super(e)}poolingFunction(e,t,n,a,r){return Pt(r),wa(a),bC(e,t,n,a,r,"max")}};m1.className="MaxPooling3D";ne.registerClass(m1);var f1=class extends vC{constructor(e){super(e)}poolingFunction(e,t,n,a,r){return Pt(r),wa(a),bC(e,t,n,a,r,"avg")}};f1.className="AveragePooling3D";ne.registerClass(f1);var wC=class extends Be{constructor(e){super(e),this.inputSpec=[new Bt({ndim:3})]}computeOutputShape(e){return[e[0],e[2]]}call(e,t){throw new Le}},g1=class extends wC{constructor(e){super(e||{})}call(e,t){return P(()=>{let n=Ce(e);return Et(n,1)})}};g1.className="GlobalAveragePooling1D";ne.registerClass(g1);var b1=class extends wC{constructor(e){super(e||{})}call(e,t){return P(()=>{let n=Ce(e);return ga(n,1)})}};b1.className="GlobalMaxPooling1D";ne.registerClass(b1);var kC=class extends Be{constructor(e){super(e),this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,Pt(this.dataFormat),this.inputSpec=[new Bt({ndim:4})]}computeOutputShape(e){return e=e,this.dataFormat==="channelsLast"?[e[0],e[3]]:[e[0],e[1]]}call(e,t){throw new Le}getConfig(){let e={dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}},y1=class extends kC{call(e,t){return P(()=>{let n=Ce(e);return this.dataFormat==="channelsLast"?Et(n,[1,2]):Et(n,[2,3])})}};y1.className="GlobalAveragePooling2D";ne.registerClass(y1);var x1=class extends kC{call(e,t){return P(()=>{let n=Ce(e);return this.dataFormat==="channelsLast"?ga(n,[1,2]):ga(n,[2,3])})}};x1.className="GlobalMaxPooling2D";ne.registerClass(x1);var IC=class extends Be{constructor(e){super(e),this.layer=e.layer}build(e){this.built=!0}get trainable(){return this.layer!=null?this.layer.trainable:!1}set trainable(e){this.layer!=null&&(this.layer.trainable=e)}get trainableWeights(){return this.layer.trainableWeights}get nonTrainableWeights(){return this.layer.nonTrainableWeights}get updates(){return this.layer._updates}get losses(){return this.layer.losses}getWeights(){return this.layer.getWeights()}setWeights(e){this.layer.setWeights(e)}getConfig(){let e={layer:{className:this.layer.getClassName(),config:this.layer.getConfig()}},t=super.getConfig();return Object.assign(e,t),e}setFastWeightInitDuringBuild(e){super.setFastWeightInitDuringBuild(e),this.layer!=null&&this.layer.setFastWeightInitDuringBuild(e)}static fromConfig(e,t,n={}){let a=t.layer,r=Ga(a,n);delete t.layer;let s={layer:r};return Object.assign(s,t),new e(s)}},v1=class extends IC{constructor(e){super(e),this.supportsMasking=!0}build(e){if(e=Je(e),e.length<3)throw new V(`TimeDistributed layer expects an input shape >= 3D, but received input shape ${JSON.stringify(e)}`);this.inputSpec=[{shape:e}];let t=[e[0]].concat(e.slice(2));this.layer.built||(this.layer.build(t),this.layer.built=!0),super.build(e)}computeOutputShape(e){e=Je(e);let t=[e[0]].concat(e.slice(2)),n=this.layer.computeOutputShape(t),a=e[1];return[n[0],a].concat(n.slice(1))}call(e,t){return P(()=>(e=Ce(e),fC((n,a)=>[Ce(this.layer.call(n,t)),[]],e,[],!1,null,null,!1,!0)[1]))}};v1.className="TimeDistributed";ne.registerClass(v1);function qH(e){Xo(YU,"BidirectionalMergeMode",e)}var jH="concat",w1=class extends IC{constructor(e){super(e);let t=e.layer.getConfig(),n={};n.className=e.layer.getClassName(),n.config=t,this.forwardLayer=Ga(n),t.goBackwards=t.goBackwards!==!0;let a={};if(a.className=e.layer.getClassName(),a.config=t,this.backwardLayer=Ga(a),this.forwardLayer.name="forward_"+this.forwardLayer.name,this.backwardLayer.name="backward_"+this.backwardLayer.name,this.mergeMode=e.mergeMode===void 0?jH:e.mergeMode,qH(this.mergeMode),e.weights)throw new Le("weights support is not implemented for Bidirectional layer yet.");this._stateful=e.layer.stateful,this.returnSequences=e.layer.returnSequences,this.returnState=e.layer.returnState,this.supportsMasking=!0,this._trainable=!0,this.inputSpec=e.layer.inputSpec,this.numConstants=null}get trainable(){return this._trainable}set trainable(e){this._trainable=e,this.forwardLayer!=null&&(this.forwardLayer.trainable=e),this.backwardLayer!=null&&(this.backwardLayer.trainable=e)}getWeights(){return this.forwardLayer.getWeights().concat(this.backwardLayer.getWeights())}setWeights(e){let t=e.length,n=Math.floor(t/2);this.forwardLayer.setWeights(e.slice(0,n)),this.backwardLayer.setWeights(e.slice(n))}computeOutputShape(e){let t=this.forwardLayer.computeOutputShape(e);Array.isArray(t)&&Array.isArray(t[0])||(t=[t]),t=t;let n,a,r;return this.returnState&&(r=t.slice(1)),n=t[0],n=n,this.mergeMode==="concat"?(n[n.length-1]*=2,a=[n]):this.mergeMode==null?a=[n,n.slice()]:a=[n],this.returnState?this.mergeMode==null?a.concat(r).concat(r.slice()):[n].concat(r).concat(r.slice()):On(a)}apply(e,t){let n=t==null?null:t.initialState,a=t==null?null:t.constants;t==null&&(t={});let r=mC(e,n,a,this.numConstants);if(e=r.inputs,n=r.initialState,a=r.constants,Array.isArray(e)&&(n=e.slice(1),e=e[0]),(n==null||n.length===0)&&a==null)return super.apply(e,t);let s=[],i=[];if(n!=null){let l=n.length;if(l%2>0)throw new V("When passing `initialState` to a Bidrectional RNN, the state should be an Array containing the states of the underlying RNNs.");t.initialState=n,s.push(...n);let u=n.map(p=>new 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a=[];for(let r=0;r<n.length;r++){let s=n[r],i=this.findWithDefault(s,t);a.push(i)}return Dt(a)})}findWithDefault(e,t){let n=this.tensorMap.get(e);return n!=null?n:t}checkKeyAndValueTensor(e,t){if(e.dtype!==this.keyDType)throw new Error(`Expect key dtype ${this.keyDType}, but got ${e.dtype}`);if(t.dtype!==this.valueDType)throw new Error(`Expect value dtype ${this.valueDType}, but got ${t.dtype}`)}},yj=async(e,t,n,a)=>{switch(e.op){case"HashTable":case"HashTableV2":{let r=a.getHashTableHandleByName(e.name);if(r!=null)return[r];{let s=k("keyDType",e,t,n),i=k("valueDType",e,t,n),o=new bj(s,i);return a.addHashTable(e.name,o),[o.handle]}}case"InitializeTable":case"InitializeTableV2":case"LookupTableImport":case"LookupTableImportV2":{let r=k("tableHandle",e,t,n,a),s=k("keys",e,t,n),i=k("values",e,t,n);return[await a.getHashTableById(r.id).import(s,i)]}case"LookupTableFind":case"LookupTableFindV2":{let r=k("tableHandle",e,t,n,a),s=k("keys",e,t,n),i=k("defaultValue",e,t,n);return[await 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r=k("images",e,t,n),s=k("transforms",e,t,n),i=k("outputShape",e,t,n),o=k("fillValue",e,t,n),l=k("interpolation",e,t,n),u=k("fillMode",e,t,n);return[a.image.transform(r,s,l.toLowerCase(),u.toLowerCase(),o,i)]}default:throw TypeError(`Node type ${e.op} is not implemented`)}},vj=(e,t,n,a=ln)=>{switch(e.op){case"Equal":return[a.equal(k("a",e,t,n),k("b",e,t,n))];case"NotEqual":return[a.notEqual(k("a",e,t,n),k("b",e,t,n))];case"Greater":return[a.greater(k("a",e,t,n),k("b",e,t,n))];case"GreaterEqual":return[a.greaterEqual(k("a",e,t,n),k("b",e,t,n))];case"Less":return[a.less(k("a",e,t,n),k("b",e,t,n))];case"LessEqual":return[a.lessEqual(k("a",e,t,n),k("b",e,t,n))];case"LogicalAnd":return[a.logicalAnd(k("a",e,t,n),k("b",e,t,n))];case"LogicalNot":return[a.logicalNot(k("a",e,t,n))];case"LogicalOr":return[a.logicalOr(k("a",e,t,n),k("b",e,t,n))];case"Select":case"SelectV2":return[a.where(k("condition",e,t,n),k("a",e,t,n),k("b",e,t,n))];case"BitwiseAnd":return[a.bitwiseAnd(k("a",e,t,n),k("b",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}},wj=(e,t,n,a=ln)=>{switch(e.op){case"BatchMatMul":case"BatchMatMulV2":case"MatMul":return[a.matMul(k("a",e,t,n),k("b",e,t,n),k("transposeA",e,t,n),k("transposeB",e,t,n))];case"Einsum":return[a.einsum(k("equation",e,t,n),...k("tensors",e,t,n))];case"Transpose":return[a.transpose(k("x",e,t,n),k("perm",e,t,n))];case"_FusedMatMul":let[r,s]=k("fusedOps",e,t,n),i=r==="biasadd",o=s==="prelu",l=k("numArgs",e,t,n),u=k("leakyreluAlpha",e,t,n);if(i){if(o&&l!==2)throw new Error("Fused MatMul with BiasAdd and Prelu must have two extra arguments: bias and alpha.");if(!o&&l!==1)throw new Error("Fused MatMul with BiasAdd must have one extra argument: bias.")}let[p,d]=k("args",e,t,n);return[a.fused.matMul({a:k("a",e,t,n),b:k("b",e,t,n),transposeA:k("transposeA",e,t,n),transposeB:k("transposeB",e,t,n),bias:p,activation:s,preluActivationWeights:d,leakyreluAlpha:u})];case"MatrixBandPart":return[a.linalg.bandPart(k("a",e,t,n),k("numLower",e,t,n),k("numUpper",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}},kj=(e,t,n,a=ln)=>{switch(e.op){case"EuclideanNorm":return[a.euclideanNorm(k("x",e,t,n),k("axis",e,t,n),k("keepDims",e,t,n))];case"FusedBatchNorm":case"FusedBatchNormV2":return[a.batchNorm(k("x",e,t,n),k("mean",e,t,n),k("variance",e,t,n),k("offset",e,t,n),k("scale",e,t,n),k("epsilon",e,t,n))];case"FusedBatchNormV3":return[a.batchNorm(k("x",e,t,n),k("mean",e,t,n),k("variance",e,t,n),k("offset",e,t,n),k("scale",e,t,n),k("epsilon",e,t,n))];case"LRN":return[a.localResponseNormalization(k("x",e,t,n),k("radius",e,t,n),k("bias",e,t,n),k("alpha",e,t,n),k("beta",e,t,n))];case"Softmax":return[a.softmax(k("x",e,t,n))];case"LogSoftmax":return[a.logSoftmax(k("x",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}},Ij=(e,t,n,a=ln)=>{switch(e.op){case"RaggedGather":{let{outputNestedSplits:r,outputDenseValues:s}=a.raggedGather(k("paramsNestedSplits",e,t,n),k("paramsDenseValues",e,t,n),k("indices",e,t,n),k("outputRaggedRank",e,t,n));return r.concat(s)}case"RaggedRange":{let{rtNestedSplits:r,rtDenseValues:s}=a.raggedRange(k("starts",e,t,n),k("limits",e,t,n),k("splits",e,t,n));return[r,s]}case"RaggedTensorToTensor":return[a.raggedTensorToTensor(k("shape",e,t,n),k("values",e,t,n),k("defaultValue",e,t,n),k("rowPartitionTensors",e,t,n),k("rowPartitionTypes",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}},Sj=(e,t,n,a=ln)=>{switch(e.op){case"Max":{let o=k("axis",e,t,n),l=k("keepDims",e,t,n);return[a.max(k("x",e,t,n),o,l)]}case"Mean":{let o=k("axis",e,t,n),l=k("keepDims",e,t,n);return[a.mean(k("x",e,t,n),o,l)]}case"Min":{let o=k("axis",e,t,n),l=k("keepDims",e,t,n);return[a.min(k("x",e,t,n),o,l)]}case"Sum":{let o=k("axis",e,t,n),l=k("keepDims",e,t,n);return[a.sum(k("x",e,t,n),o,l)]}case"All":{let o=k("axis",e,t,n),l=k("keepDims",e,t,n);return[a.all(k("x",e,t,n),o,l)]}case"Any":{let o=k("axis",e,t,n),l=k("keepDims",e,t,n);return[a.any(k("x",e,t,n),o,l)]}case"ArgMax":{let o=k("axis",e,t,n);return[a.argMax(k("x",e,t,n),o)]}case"ArgMin":{let o=k("axis",e,t,n);return[a.argMin(k("x",e,t,n),o)]}case"Prod":{let o=k("axis",e,t,n),l=k("keepDims",e,t,n);return[a.prod(k("x",e,t,n),o,l)]}case"Cumprod":{let o=k("axis",e,t,n),l=k("exclusive",e,t,n),u=k("reverse",e,t,n);return[a.cumprod(k("x",e,t,n),o,l,u)]}case"Cumsum":{let o=k("axis",e,t,n),l=k("exclusive",e,t,n),u=k("reverse",e,t,n);return[a.cumsum(k("x",e,t,n),o,l,u)]}case"Bincount":let r=k("x",e,t,n),s=k("weights",e,t,n),i=k("size",e,t,n);return[a.bincount(r,s,i)];case"DenseBincount":{let o=k("x",e,t,n),l=k("weights",e,t,n),u=k("size",e,t,n),p=k("binaryOutput",e,t,n);return[a.denseBincount(o,l,u,p)]}default:throw TypeError(`Node type ${e.op} is not implemented`)}},Nj=(e,t,n,a=ln)=>{switch(e.op){case"ConcatV2":case"Concat":{let r=k("n",e,t,n),s=k("axis",e,t,n),i=k("tensors",e,t,n);return i=i.slice(0,r),[a.concat(i,s)]}case"Gather":{let r=k("x",e,t,n),s=k("indices",e,t,n);return[a.gather(r,a.cast(s,"int32"),0)]}case"GatherV2":{let r=k("axis",e,t,n),s=k("batchDims",e,t,n),i=k("x",e,t,n),o=k("indices",e,t,n);return[a.gather(i,a.cast(o,"int32"),r,s)]}case"Reverse":{let r=k("dims",e,t,n),s=[];for(let o=0;o<r.length;o++)r[o]&&s.push(o);let i=k("x",e,t,n);return[a.reverse(i,s)]}case"ReverseV2":{let r=k("axis",e,t,n),s=k("x",e,t,n);return[a.reverse(s,r)]}case"Slice":{let r=k("begin",e,t,n),s=k("size",e,t,n);return[a.slice(k("x",e,t,n),r,s)]}case"StridedSlice":{let r=k("begin",e,t,n),s=k("end",e,t,n),i=k("strides",e,t,n),o=k("beginMask",e,t,n),l=k("endMask",e,t,n),u=k("ellipsisMask",e,t,n),p=k("newAxisMask",e,t,n),d=k("shrinkAxisMask",e,t,n),c=k("x",e,t,n);return[a.stridedSlice(c,r,s,i,o,l,u,p,d)]}case"Pack":return P(()=>{let r=k("axis",e,t,n),s=k("tensors",e,t,n),i=s[0].shape,o=a.squeeze(s[0]).shape,l=s.map(u=>{let p=w.arraysEqual(u.shape,i);if(!p&&!w.arraysEqual(a.squeeze(u).shape,o))throw new Error("the input tensors shape does not match");return p?u:a.reshape(u,i)});return[a.stack(l,r)]});case"Unpack":{let r=k("axis",e,t,n),s=k("tensor",e,t,n);return a.unstack(s,r)}case"Tile":{let r=k("reps",e,t,n);return[a.tile(k("x",e,t,n),r)]}case"Split":case"SplitV":{let r=k("axis",e,t,n),s=k("numOrSizeSplits",e,t,n),i=k("x",e,t,n);return a.split(i,s,r)}case"ScatterNd":{let r=k("indices",e,t,n),s=k("values",e,t,n),i=k("shape",e,t,n);return[a.scatterND(r,s,i)]}case"GatherNd":{let r=k("x",e,t,n),s=k("indices",e,t,n);return[a.gatherND(r,s)]}case"SparseToDense":{let r=k("sparseIndices",e,t,n),s=k("outputShape",e,t,n),i=k("sparseValues",e,t,n),o=k("defaultValue",e,t,n);return[a.sparseToDense(r,i,s,i.dtype===o.dtype?o:a.cast(o,i.dtype))]}case"TensorScatterUpdate":{let r=k("indices",e,t,n),s=k("values",e,t,n),i=k("tensor",e,t,n);return[a.tensorScatterUpdate(i,r,s)]}default:throw TypeError(`Node type ${e.op} is not implemented`)}},Tj=(e,t,n,a=ln)=>{switch(e.op){case"SparseFillEmptyRows":{let{outputIndices:r,outputValues:s,emptyRowIndicator:i,reverseIndexMap:o}=a.sparse.sparseFillEmptyRows(k("indices",e,t,n),k("values",e,t,n),k("denseShape",e,t,n),k("defaultValue",e,t,n));return[r,s,i,o]}case"SparseReshape":{let{outputIndices:r,outputShape:s}=a.sparse.sparseReshape(k("inputIndices",e,t,n),k("inputShape",e,t,n),k("newShape",e,t,n));return[r,s]}case"SparseSegmentMean":return[a.sparse.sparseSegmentMean(k("data",e,t,n),k("indices",e,t,n),k("segmentIds",e,t,n))];case"SparseSegmentSum":return[a.sparse.sparseSegmentSum(k("data",e,t,n),k("indices",e,t,n),k("segmentIds",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}},Cj=(e,t,n,a=ln)=>{switch(e.op){case"FFT":return[a.fft(k("x",e,t,n))];case"IFFT":return[a.ifft(k("x",e,t,n))];case"RFFT":return[a.rfft(k("x",e,t,n))];case"IRFFT":return[a.irfft(k("x",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}},_j=(e,t,n,a=ln)=>{switch(e.op){case"StaticRegexReplace":return[a.string.staticRegexReplace(k("input",e,t,n),k("pattern",e,t,n),k("rewrite",e,t,n),k("replaceGlobal",e,t,n))];case"StringNGrams":{let{nGrams:r,nGramsSplits:s}=a.string.stringNGrams(k("data",e,t,n),k("dataSplits",e,t,n),k("separator",e,t,n),k("nGramWidths",e,t,n),k("leftPad",e,t,n),k("rightPad",e,t,n),k("padWidth",e,t,n),k("preserveShortSequences",e,t,n));return[r,s]}case"StringSplit":{let{indices:r,values:s,shape:i}=a.string.stringSplit(k("input",e,t,n),k("delimiter",e,t,n),k("skipEmpty",e,t,n));return[r,s,i]}case"StringToHashBucketFast":return[a.string.stringToHashBucketFast(k("input",e,t,n),k("numBuckets",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}},Ej=(e,t,n,a=ln)=>{switch(e.op){case"Cast":return[a.cast(k("x",e,t,n),k("dtype",e,t,n))];case"ExpandDims":{let r=k("axis",e,t,n);return[a.expandDims(k("x",e,t,n),r)]}case"Squeeze":{let r=k("axis",e,t,n);return[a.squeeze(k("x",e,t,n),r)]}case"Reshape":return[a.reshape(k("x",e,t,n),k("shape",e,t,n))];case"EnsureShape":return[a.ensureShape(k("x",e,t,n),k("shape",e,t,n))];case"MirrorPad":return[a.mirrorPad(k("x",e,t,n),k("padding",e,t,n),k("mode",e,t,n))];case"PadV2":case"Pad":return[a.pad(k("x",e,t,n),k("padding",e,t,n),k("constantValue",e,t,n))];case"SpaceToBatchND":{let r=k("blockShape",e,t,n),s=k("paddings",e,t,n);return[a.spaceToBatchND(k("x",e,t,n),r,s)]}case"BatchToSpaceND":{let r=k("blockShape",e,t,n),s=k("crops",e,t,n);return[a.batchToSpaceND(k("x",e,t,n),r,s)]}case"DepthToSpace":{let r=k("blockSize",e,t,n),s=k("dataFormat",e,t,n).toUpperCase();return[a.depthToSpace(k("x",e,t,n),r,s)]}case"BroadcastTo":return[a.broadcastTo(k("x",e,t,n),k("shape",e,t,n))];case"BroadcastArgs":return[a.broadcastArgs(k("s0",e,t,n),k("s1",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}};function nS(e,t,n,a,r=P){let s=((i,o,l)=>{switch(i.category){case"arithmetic":return r(()=>rj(i,o,l));case"basic_math":return r(()=>sj(i,o,l));case"control":return cj(i,o,l);case"convolution":return r(()=>dj(i,o,l));case"creation":return r(()=>hj(i,o,l));case"dynamic":return mj(i,o,l);case"evaluation":return r(()=>fj(i,o,l));case"image":return r(()=>xj(i,o,l));case"graph":return r(()=>gj(i,o,l));case"logical":return r(()=>vj(i,o,l));case"matrices":return r(()=>wj(i,o,l));case"normalization":return r(()=>kj(i,o,l));case"ragged":return r(()=>Ij(i,o,l));case"reduction":return r(()=>Sj(i,o,l));case"slice_join":return r(()=>Nj(i,o,l));case"sparse":return r(()=>Tj(i,o,l));case"spectral":return r(()=>Cj(i,o,l));case"string":return r(()=>_j(i,o,l));case"transformation":return r(()=>Ej(i,o,l));case"hash_table":return yj(i,o,l,a);case"custom":let u=MC(i.op);if(u&&u.customExecutor)return u.customExecutor(new aj(i,o,l));throw TypeError(`Custom op ${i.op} is not registered.`);default:throw TypeError(`Unknown op '${i.op}'. File an issue at https://github.com/tensorflow/tfjs/issues so we can add it, or register a custom execution with tf.registerOp()`)}})(e,t,n);return w.isPromise(s)?s.then(i=>[].concat(i)):[].concat(s)}var aS=class{constructor(e={},t={},n={},a={},r){this.weightMap=e,this.tensorArrayMap=t,this.tensorListMap=n,this.functionMap=a,this.parseNodeNameCache=r,this.rootContext={id:0,frameName:"",iterationId:0},this.contexts=[this.rootContext],this.lastId=0,this.generateCurrentContextIds()}newFrame(e,t){return{id:e,frameName:t,iterationId:0}}set currentContext(e){this.contexts!==e&&(this.contexts=e,this.generateCurrentContextIds())}get currentContext(){return this.contexts}get currentContextId(){return this._currentContextIds[0]}get currentContextIds(){return this._currentContextIds}generateCurrentContextIds(){let e=[];for(let t=0;t<this.contexts.length-1;t++){let n=this.contexts.slice(0,this.contexts.length-t);e.push(this.contextIdforContexts(n))}e.push(""),this._currentContextIds=e}contextIdforContexts(e){return e?e.map(t=>t.id===0&&t.iterationId===0?"":`${t.frameName}-${t.iterationId}`).join("/"):""}enterFrame(e){this.contexts&&(this.lastId++,this.contexts=this.contexts.slice(),this.contexts.push(this.newFrame(this.lastId,e)),this._currentContextIds.unshift(this.contextIdforContexts(this.contexts)))}exitFrame(){if(this.contexts&&this.contexts.length>1)this.contexts=this.contexts.slice(),this.contexts.splice(-1),this.currentContextIds.shift();else throw new Error("Cannot exit frame, the context is empty")}nextIteration(){if(this.contexts&&this.contexts.length>0){this.contexts=this.contexts.slice(),this.lastId++;let e=Object.assign({},this.contexts[this.contexts.length-1]);e.iterationId+=1,e.id=this.lastId,this.contexts.splice(-1,1,e),this._currentContextIds.splice(0,1,this.contextIdforContexts(this.contexts))}else throw new Error("Cannot increase frame iteration, the context is empty")}getWeight(e){return this.weightMap[e]}addTensorArray(e){this.tensorArrayMap[e.id]=e}getTensorArray(e){return this.tensorArrayMap[e]}addTensorList(e){this.tensorListMap[e.id]=e}getTensorList(e){return this.tensorListMap[e]}dispose(e){for(let t in this.tensorArrayMap)this.tensorArrayMap[t].clearAndClose(e);for(let t in this.tensorListMap)this.tensorListMap[t].clearAndClose(e)}};function rS(e,t,n,a){let r=new Set,s=[],i=null,o=null,l=new Set,u=new Set(Object.keys(e).map(c=>Zn(c)[0]));a=a||[];let p=new Set(a.map(c=>Zn(c.name)[0])),d=[...t];for(;d.length>0;){let c=d.pop();if((Qs(c)||Oj(c)||Lj(c))&&i==null&&(i=c,o=i.children.map(h=>h.name).filter(h=>r.has(h))),r.add(c.name),n[c.name]==null&&!u.has(c.name)&&!p.has(c.name)){if(c.inputs.length===0){s.push(c.name);continue}c.inputs.forEach(h=>{l.has(h.name)||(l.add(h.name),d.push(h))})}}return{inputs:e,outputs:t,usedNodes:r,missingInputs:s,dynamicNode:i,syncInputs:o}}function Aj(e,t){let{usedNodes:n,inputs:a}=t,r=Object.keys(a).map(g=>Zn(g)[0]).map(g=>e.nodes[g]),s=e.initNodes||[],i=g=>n.has(typeof g=="string"?g:g.name);function o(g){return[...new Map(g.map(b=>[b.name,b])).values()]}let l=o([...r,...e.weights,...s]).filter(i),u=o([...l,...Object.values(e.nodes)]).filter(i),p=new Map(u.map(g=>[g.name,g])),d={};for(let g of u){d[g.name]=d[g.name]||0;for(let b of g.children)i(b)||(d[b.name]=Number.POSITIVE_INFINITY),d[b.name]=(d[b.name]||0)+1}let c=Object.entries(d).filter(([,g])=>g===0).map(([g])=>g),h=[...c];for(;c.length>0;){let g=c.pop(),b=p.get(g);for(let y of b.children.filter(i))--d[y.name]===0&&(h.push(y.name),c.push(y.name))}let m=h.map(g=>p.get(g)),f=Fj(m,l);return $j(f,l),f}function Fj(e,t){let n=new Map(e.map(s=>[s.name,s])),a=t.map(s=>s.name),r=new Set(a);for(;a.length>0;){let s=a.pop(),i=n.get(s);for(let o of i.children)!n.has(o.name)||r.has(o.name)||(r.add(o.name),a.push(o.name))}return e.filter(s=>r.has(s.name))}var Bh=class extends Error{constructor(e){super(`NodesExecutionOrderError: ${e}`)}};function $j(e,t){let n=new Map(e.map((o,l)=>[o.name,l])),a=new Set(t.map(o=>o.name)),r=o=>a.has(typeof o=="string"?o:o.name),s=new Set(e.map(o=>o.name)),i=o=>s.has(typeof o=="string"?o:o.name);for(let o of e){for(let l of o.children.filter(i)){if(!n.has(l.name))throw new Bh(`Child ${l.name} of node ${o.name} is unreachable.`);if(n.get(o.name)>n.get(l.name))throw new Bh(`Node ${o.name} is scheduled to run after its child ${l.name}.`)}if(!r(o))for(let l of o.inputs){if(!n.has(l.name))throw new Bh(`Input ${l.name} of node ${o.name} is unreachable.`);if(n.get(l.name)>n.get(o.name))throw new Bh(`Node ${o.name} is scheduled to run before its input ${l.name}.`)}}}function Dj(e){let t=new Map(e.map((o,l)=>[o.name,l])),n=Number.MAX_SAFE_INTEGER,a=e.map((o,l)=>Qs(o)?n:l),r=o=>{let l=a[t.get(o.name)];return l==null?-1:l},s=e.map((o,l)=>o.children.map(r).reduce((u,p)=>Math.max(u,p),a[l])),i=new Map;for(let o=0;o<e.length;++o){let l=s[o];if(l===n)continue;let u=e[o],p=e[l];i.has(p.name)||i.set(p.name,[]),i.get(p.name).push(u)}return i}var Rj=new Set(["Switch","Merge","Enter","Exit","NextIteration","StatelessIf","StatelessWhile","if","While"]),Mj=new Set(["NonMaxSuppressionV2","NonMaxSuppressionV3","NonMaxSuppressionV5","Where"]),Pj=new Set(["HashTable","HashTableV2","LookupTableImport","LookupTableImportV2","LookupTableFind","LookupTableFindV2","LookupTableSize","LookupTableSizeV2"]);function Qs(e){return Rj.has(e.op)}function Oj(e){return Mj.has(e.op)}function Lj(e){return Pj.has(e.op)}var lv=class{get weightIds(){return this.parent?this.parent.weightIds:this._weightIds}get functionExecutorMap(){return this.parent?this.parent.functionExecutorMap:this._functionExecutorMap}get weightMap(){return this.parent?this.parent.weightMap:this._weightMap}set weightMap(e){let t=Object.keys(e).map(n=>e[n].map(a=>a.id));this._weightIds=[].concat(...t),this._weightMap=e}set resourceManager(e){this._resourceManager=e}get inputs(){return this._inputs.map(e=>({name:e.name,shape:e.attrParams.shape?e.attrParams.shape.value:void 0,dtype:e.attrParams.dtype?e.attrParams.dtype.value:void 0}))}get outputs(){return this._outputs.map(e=>({name:e.name,shape:e.attrParams.shape?e.attrParams.shape.value:void 0,dtype:e.attrParams.dtype?e.attrParams.dtype.value:void 0}))}get inputNodes(){return this._inputs.map(e=>e.signatureKey||e.name)}get outputNodes(){return this._outputs.map(e=>{let t=e.signatureKey||e.name;return e.defaultOutput?`${t}:${e.defaultOutput}`:t})}get functions(){return Object.keys(this._functions).reduce((e,t)=>(e[t]=this._functions[t].signature,e),{})}constructor(e,t){this.graph=e,this.parent=t,this.compiledMap=new Map,this.parseNodeNameCache=new Map,this._weightMap={},this.SEPARATOR=",",this._functions={},this._functionExecutorMap={},this.keepIntermediateTensors=!1,this._outputs=e.outputs,this._inputs=e.inputs,this._initNodes=e.initNodes,this._signature=e.signature,this._functions=e.functions,e.functions!=null&&Object.keys(e.functions).forEach(n=>{this._functionExecutorMap[n]=new lv(e.functions[n],this)})}getCompilationKey(e,t){let n=e.map(r=>r.name).sort(),a=t.map(r=>r.name).sort();return n.join(this.SEPARATOR)+"--"+a.join(this.SEPARATOR)}compile(e,t){let n=rS(e,t,this.weightMap,this._initNodes),{missingInputs:a,dynamicNode:r,syncInputs:s}=n;if(r!=null)throw new Error(`This execution contains the node '${r.name}', which has the dynamic op '${r.op}'. 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this.upstream.next()}},i5=class extends on{constructor(e,t){super(),this.upstream=e,this.maxCount=t,this.count=0}summary(){return`${this.upstream.summary()} -> Take`}async next(){return this.count++>=this.maxCount?{value:null,done:!0}:this.upstream.next()}},o5=class extends on{constructor(e,t,n=!0){super(),this.upstream=e,this.batchSize=t,this.enableSmallLastBatch=n,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> RowMajorBatch`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){let e=[];for(;e.length<this.batchSize;){let t=await this.upstream.next();if(t.done)return this.enableSmallLastBatch&&e.length>0?{value:e,done:!1}:{value:null,done:!0};e.push(t.value)}return{value:e,done:!1}}},l5=class extends on{constructor(e,t){super(),this.upstream=e,this.predicate=t,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> Filter`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){for(;;){let e=await this.upstream.next();if(e.done||this.predicate(e.value))return e;_e(e.value)}}},u5=class extends on{constructor(e,t){super(),this.upstream=e,this.transform=t}summary(){return`${this.upstream.summary()} -> Map`}async next(){let e=await this.upstream.next();if(e.done)return{value:null,done:!0};let t=Ua.getTensorsInContainer(e.value),n=this.transform(e.value),a=Ua.getTensorsInContainer(n);for(let r of t)Ua.isTensorInList(r,a)||r.dispose();return{value:n,done:!1}}},p5=class extends on{constructor(e,t){super(),this.upstream=e,this.handler=t,this.count=0,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${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}}}},sS=class extends on{constructor(e,t){super(),this.upstream=e,this.transform=t}summary(){return`${this.upstream.summary()} -> AsyncMap`}async next(){let e=await this.upstream.next();if(e.done)return{value:null,done:!0};let t=Ua.getTensorsInContainer(e.value),n=await this.transform(e.value),a=Ua.getTensorsInContainer(n);for(let r of t)Ua.isTensorInList(r,a)||r.dispose();return{value:n,done:!1}}},M1=class extends on{constructor(){super(),this.outputQueue=new D1,this.lastRead=Promise.resolve({value:null,done:!1})}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){for(;this.outputQueue.length()===0;)if(!await this.pump())return{value:null,done:!0};return{value:this.outputQueue.shift(),done:!1}}},c5=class extends M1{constructor(e,t){super(),this.upstream=e,this.transform=t}summary(){return`${this.upstream.summary()} -> Flatmap`}async pump(){let e=await this.upstream.next();if(e.done)return!1;let t=Ua.getTensorsInContainer(e.value),n=this.transform(e.value),a=Ua.getTensorsInContainer(n);this.outputQueue.pushAll(n);for(let r of t)Ua.isTensorInList(r,a)||r.dispose();return!0}},u_=class extends on{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}},is;(function(e){e[e.FAIL=0]="FAIL",e[e.SHORTEST=1]="SHORTEST",e[e.LONGEST=2]="LONGEST"})(is||(is={}));var d5=class extends on{constructor(e,t=is.FAIL){super(),this.iterators=e,this.mismatchMode=t,this.count=0,this.currentPromise=null}summary(){return"{TODO: fill in upstream of zip summaries} -> Zip"}async nextState(e){await e;let t=0,n=0;function a(s){return s instanceof on?{value:s.next().then(i=>(t++,i.done&&n++,i.value)),recurse:!1}:{value:null,recurse:!0}}let r=await i_(this.iterators,a);if(t===n)return{value:null,done:!0};if(n>0)switch(this.mismatchMode){case is.FAIL:throw new Error(`Zipped streams should have the same length. Mismatched at element ${this.count}.`);case is.SHORTEST:return{value:null,done:!0};case is.LONGEST:default:}return this.count++,{value:r,done:!1}}async next(){return this.currentPromise=this.nextState(this.currentPromise),this.currentPromise}},p_=class extends on{constructor(e,t){super(),this.upstream=e,this.bufferSize=t,this.buffer=new o_(t)}summary(){return`${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()}},h5=class extends p_{constructor(e,t,n){super(e,t),this.upstream=e,this.windowSize=t,this.upstreamExhausted=!1,this.random=jj.alea(n||w.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}}},yp=class{constructor(){this.size=null}batch(e,t=!0){let n=this;w.assert(e>0,()=>`batchSize needs to be positive, but it is
| ${e}`);let a;return this.size===1/0||this.size==null?a=this.size:t?a=Math.ceil(this.size/e):a=Math.floor(this.size/e),Yn(async()=>(await n.iterator()).columnMajorBatch(e,t,g5),a)}concatenate(e){let t=this,n;return this.size===1/0||e.size===1/0?n=1/0:this.size!=null&&e.size!=null?n=this.size+e.size:n=null,Yn(async()=>(await t.iterator()).concatenate(await e.iterator()),n)}filter(e){let t=this,n;return this.size===1/0?n=1/0:n=null,Yn(async()=>(await t.iterator()).filter(a=>P(()=>e(a))),n)}async forEachAsync(e){return(await this.iterator()).forEachAsync(e)}map(e){let t=this;return Yn(async()=>(await t.iterator()).map(n=>P(()=>e(n))),this.size)}mapAsync(e){let t=this;return Yn(async()=>(await t.iterator()).mapAsync(e),this.size)}prefetch(e){if(e==null)throw new RangeError("`Dataset.prefetch()` requires bufferSize to be specified.");let t=this;return Yn(async()=>(await t.iterator()).prefetch(e),this.size)}repeat(e){let t=this,n;return this.size!=null&&e>0?n=this.size*e:e===0?n=0:this.size!=null&&(e===void 0||e<0)?n=1/0:n=null,Yn(async()=>{let a=R1(async()=>({value:await t.iterator(),done:!1}));return e5(a.take(e))},n)}skip(e){let t=this,n;return this.size!=null&&e>=0&&this.size>=e?n=this.size-e:this.size!=null&&(this.size<e||e===void 0||e<0)?n=0:n=null,Yn(async()=>(await t.iterator()).skip(e),n)}shuffle(e,t,n=!0){if(e==null||e<0)throw this.size==null?new RangeError("`Dataset.shuffle()` requires bufferSize to be specified."):new RangeError(`\`Dataset.shuffle()\` requires bufferSize to be specified. If your data fits in main memory (for regular JS objects), and/or GPU memory (for \`tf.Tensor\`s), consider setting bufferSize to the dataset size (${this.size} elements)`);let a=this,r=qj.alea(t||w.now().toString());return Yn(async()=>{let s=r.int32();return n&&(s+=r.int32()),(await a.iterator()).shuffle(e,s.toString())},this.size)}take(e){let t=this,n;return this.size!=null&&this.size>e?n=e:this.size!=null&&this.size<=e?n=this.size:n=null,Yn(async()=>(await t.iterator()).take(e),n)}async toArray(){if(this.size===1/0)throw new Error("Can not convert infinite data stream to array.");return(await this.iterator()).toArray()}async toArrayForTest(){if(this.size===1/0)throw new Error("Can not convert infinite data stream to array.");return(await this.iterator()).toArrayForTest()}};yp.MAX_BUFFER_SIZE=1e4;function Yn(e,t=null){return new class extends yp{constructor(){super(...arguments),this.size=t}async iterator(){return e()}}}function m5(e){return Yn(async()=>l_(e),e.length)}function f5(e){if(!au(e))throw new Error("The argument to zip() must be an object or array.");let t;if(Array.isArray(e))for(let n=0;n<e.length;n++)t=t==null?e[n].size:Math.min(t,e[n].size);else if(e instanceof Object)for(let n in e)t=t==null?e[n].size:Math.min(t,e[n].size);return Yn(async()=>{let n=await i_(e,a=>{if(a instanceof yp)return{value:a.iterator(),recurse:!1};if(au(a))return{value:null,recurse:!0};throw new Error("Leaves of the structure passed to zip() must be Datasets, not primitives.")});return t5(n,is.SHORTEST)},t)}function g5(e){if(e===null)return null;let t=e[0];return Yj(t)?{value:b5(e),recurse:!1}:{value:null,recurse:!0}}function b5(e){if(e.length===0)throw new Error("Can't make a batch of zero elements.");return e[0]instanceof Te?Dt(e):bn(e)}var c_=class extends yp{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))}},Vh='"',nc=Symbol("out"),iS=Symbol("field"),Uh=Symbol("quote"),Ix=Symbol("quoteafterquote"),oS=Symbol("quoteinquote"),d_=class extends yp{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&&w.assert(e.length===this.fullColumnNames.length,()=>"The length of provided columnNames ("+this.fullColumnNames.length.toString()+") does not match the length of the header line read from file ("+e.length.toString()+")."),this.fullColumnNames||(this.fullColumnNames=e);let t=this.fullColumnNames.reduce((a,r)=>(a[r]=a[r]+1||1,a),{}),n=Object.keys(t).filter(a=>t[a]>1);if(w.assert(n.length===0,()=>"Duplicate column names found: "+n.toString()),this.columnConfigs){for(let a of Object.keys(this.columnConfigs))if(this.fullColumnNames.indexOf(a)===-1)throw new Error('The key "'+a+'" provided in columnConfigs does not match any of the column names ('+this.fullColumnNames.toString()+").")}this.columnNamesValidated=!0}async maybeReadHeaderLine(){if(this.hasHeader){let e=await(await this.base.iterator()).next();if(e.done)throw new Error("No data was found for CSV parsing.");let t=e.value;return this.parseRow(t,!1)}else return null}constructor(e,t){super(),this.input=e,this.hasHeader=!0,this.fullColumnNames=null,this.columnNamesValidated=!1,this.columnConfigs=null,this.configuredColumnsOnly=!1,this.delimiter=",",this.delimWhitespace=!1,this.base=new c_(e),t||(t={}),this.hasHeader=t.hasHeader!==!1,this.fullColumnNames=t.columnNames,this.columnConfigs=t.columnConfigs,this.configuredColumnsOnly=t.configuredColumnsOnly,t.delimWhitespace?(w.assert(t.delimiter==null,()=>"Delimiter should not be provided when delimWhitespace is true."),this.delimWhitespace=!0,this.delimiter=" "):this.delimiter=t.delimiter?t.delimiter:","}async iterator(){this.columnNamesValidated||await this.setColumnNames();let e=await this.base.iterator();return this.hasHeader&&(e=e.skip(1)),e.map(t=>this.makeDataElement(t))}makeDataElement(e){let t=this.parseRow(e),n={},a={};for(let r=0;r<this.fullColumnNames.length;r++){let s=this.fullColumnNames[r],i=this.columnConfigs?this.columnConfigs[s]:null;if(!(this.configuredColumnsOnly&&!i)){let o=t[r],l=null;if(o==="")if(i&&i.default!==void 0)l=i.default;else{if(i&&(i.required||i.isLabel))throw new Error(`Required column ${s} is empty in this line: ${e}`);l=void 0}else{let u=Number(o);if(isNaN(u))i&&i.dtype==="bool"?l=this.getBoolean(o):l=o;else if(!i||!i.dtype)l=u;else switch(i.dtype){case"float32":l=u;break;case"int32":l=Math.floor(u);break;case"bool":l=this.getBoolean(o);break;default:l=u}}i&&i.isLabel?a[s]=l:n[s]=l}}return Object.keys(a).length===0?n:{xs:n,ys:a}}getBoolean(e){return e==="1"||e.toLowerCase()==="true"?1:0}parseRow(e,t=!0){let n=[],a=0,r=e.length,s=nc;for(let i=0;i<r;i++)switch(s){case nc:switch(e.charAt(i)){case Vh:a=i+1,s=Uh;break;case this.delimiter:if(a=i+1,this.delimiter===" "&&this.delimWhitespace)break;n.push(""),s=nc;break;default:s=iS,a=i;break}break;case iS:switch(e.charAt(i)){case this.delimiter:n.push(e.substring(a,i)),s=nc,a=i+1;break;default:}break;case Uh:switch(e.charAt(i)){case Vh:s=Ix;break;default:}break;case Ix:switch(e.charAt(i)){case this.delimiter:n.push(e.substring(a,i-1)),s=nc,a=i+1;break;case Vh:s=Uh;break;default:s=oS;break}break;case oS:switch(e.charAt(i)){case Vh:s=Uh;break;default:}break;default:}if(s===Ix?n.push(e.substring(a,r-1)):n.push(e.substring(a)),t&&n.length!==this.fullColumnNames.length)throw new Error(`Invalid row in csv file. Should have ${this.fullColumnNames.length} elements in a row, but got ${n}`);return n}},h_=class extends on{constructor(e){super(),this.microphoneConfig=e,this.isClosed=!1,this.fftSize=e.fftSize||1024;let t=Math.log2(this.fftSize);if(this.fftSize<0||t<4||t>14||!Number.isInteger(t))throw new Error(`Invalid fftSize: it must be a power of 2 between 2 to 4 and 2 to 14, but got ${this.fftSize}`);if(this.numFrames=e.numFramesPerSpectrogram||43,this.sampleRateHz=e.sampleRateHz,this.columnTruncateLength=e.columnTruncateLength||this.fftSize,this.audioTrackConstraints=e.audioTrackConstraints,this.smoothingTimeConstant=e.smoothingTimeConstant||0,this.includeSpectrogram=e.includeSpectrogram!==!1,this.includeWaveform=e.includeWaveform===!0,!this.includeSpectrogram&&!this.includeWaveform)throw new Error("Both includeSpectrogram and includeWaveform are false. At least one type of data should be returned.")}summary(){return"microphone"}static async create(e={}){if(!G().get("IS_BROWSER"))throw new Error("microphone API is only supported in browser environment.");let t=new h_(e);return await t.start(),t}async start(){try{this.stream=await navigator.mediaDevices.getUserMedia({audio:this.audioTrackConstraints==null?!0:this.audioTrackConstraints,video:!1})}catch(n){throw new Error(`Error thrown while initializing video stream: ${n.message}`)}if(!this.stream)throw new Error("Could not obtain audio from microphone.");let e=window.AudioContext||window.webkitAudioContext;if(this.audioContext=new e,!this.sampleRateHz)this.sampleRateHz=this.audioContext.sampleRate;else if(this.audioContext.sampleRate!==this.sampleRateHz)throw new Error(`Mismatch in sampling rate: Expected: ${this.sampleRateHz}; Actual: ${this.audioContext.sampleRate}`);let t=this.audioContext.createMediaStreamSource(this.stream);this.analyser=this.audioContext.createAnalyser(),this.analyser.fftSize=this.fftSize*2,this.analyser.smoothingTimeConstant=this.smoothingTimeConstant,t.connect(this.analyser),this.freqData=new Float32Array(this.fftSize),this.timeData=new Float32Array(this.fftSize)}async next(){if(this.isClosed)return{value:null,done:!0};let e,t,n=await this.getAudioData();if(this.includeSpectrogram){let a=this.flattenQueue(n.freqDataQueue);e=this.getTensorFromAudioDataArray(a,[this.numFrames,this.columnTruncateLength,1])}if(this.includeWaveform){let a=this.flattenQueue(n.timeDataQueue);t=this.getTensorFromAudioDataArray(a,[this.numFrames*this.fftSize,1])}return{value:{spectrogram:e,waveform:t},done:!1}}async capture(){return(await this.next()).value}async getAudioData(){let e=[],t=[],n=0;return new Promise(a=>{let r=setInterval(()=>{this.includeSpectrogram&&(this.analyser.getFloatFrequencyData(this.freqData),this.freqData[0]===-1/0&&a({freqDataQueue:e,timeDataQueue:t}),e.push(this.freqData.slice(0,this.columnTruncateLength))),this.includeWaveform&&(this.analyser.getFloatTimeDomainData(this.timeData),t.push(this.timeData.slice())),++n===this.numFrames&&(clearInterval(r),a({freqDataQueue:e,timeDataQueue:t}))},this.fftSize/this.sampleRateHz*1e3)})}stop(){this.isClosed||(this.isClosed=!0,this.analyser.disconnect(),this.audioContext.close(),this.stream!=null&&this.stream.getTracks().length>0&&this.stream.getTracks()[0].stop())}toArray(){throw new Error("Can not convert infinite audio stream to array.")}getSampleRate(){return this.sampleRateHz}flattenQueue(e){let t=e[0].length,n=new Float32Array(e.length*t);return e.forEach((a,r)=>n.set(a,r*t)),n}getTensorFromAudioDataArray(e,t){let n=new Float32Array(w.sizeFromShape(t));return n.set(e,n.length-e.length),bn(n,t)}},m_=class extends on{constructor(e,t){if(super(),this.webcamVideoElement=e,this.webcamConfig=t,this.isClosed=!0,this.resize=!1,this.needToResize())if(this.resize=!0,this.cropSize=[this.webcamConfig.resizeHeight,this.webcamConfig.resizeWidth],this.cropBoxInd=je([0],"int32"),this.webcamConfig.centerCrop){let n=this.webcamConfig.resizeWidth*1/this.webcamVideoElement.width,a=this.webcamConfig.resizeHeight*1/this.webcamVideoElement.height,r=(1-n)/2,s=(1-a)/2,i=r+n,o=a+s;this.cropBox=$a([s,r,o,i],[1,4])}else this.cropBox=$a([0,0,1,1],[1,4])}summary(){return"webcam"}static async create(e,t={}){if(!G().get("IS_BROWSER"))throw new Error("tf.data.webcam is only supported in browser environment.");if(!e){if(e=document.createElement("video"),!t.resizeWidth||!t.resizeHeight)throw new Error("Please provide webcam video element, or resizeWidth and resizeHeight to create a hidden video element.");e.width=t.resizeWidth,e.height=t.resizeHeight}let n=new m_(e,t);return await n.start(),n}async start(){this.webcamConfig.facingMode&&w.assert(this.webcamConfig.facingMode==="user"||this.webcamConfig.facingMode==="environment",()=>`Invalid webcam facing mode: ${this.webcamConfig.facingMode}. 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fK={kernelName:zu,backendName:"cpu",kernelFunc:mK},q_=Ot((e,t)=>e!==t?1:0),gK=Jt(Wu,q_,null,"bool"),bK={kernelName:Wu,backendName:"cpu",kernelFunc:gK};function B1(e,t,n,a,r){let s=t.length,i=w.sizeFromShape(t),o=w.computeStrides(t),l=w.computeStrides(r),u=w.getTypedArrayFromDType(n,w.sizeFromShape(r));for(let p=0;p<i;++p){let d=w.indexToLoc(p,s,o),c=new Array(d.length);for(let m=0;m<c.length;m++)c[m]=d[a[m]];let h=w.locToIndex(c,s,l);u[h]=e[p]}return u}function Un(e){let{inputs:t,attrs:n,backend:a}=e,{x:r}=t,{perm:s}=n;ge(r,"transpose");let i=r.shape.length,o=new Array(i);for(let p=0;p<o.length;p++)o[p]=r.shape[s[p]];let l=a.data.get(r.dataId).values,u=B1(l,r.shape,r.dtype,s,o);return{dataId:a.write(u,o,r.dtype),shape:o,dtype:r.dtype}}var yK={kernelName:$r,backendName:"cpu",kernelFunc:Un};function j_(e,t,n,a){let[r,s]=N.computeOutAndReduceShapes(e,a),i=ba(t,"int32"),o=w.makeZerosTypedArray(w.sizeFromShape(r),i),l=w.sizeFromShape(s);for(let u=0;u<o.length;++u){let p=u*l,d=1;for(let c=0;c<l;++c)d*=n[p+c];o[u]=d}return{outVals:o,outShape:r,outDtype:i}}function xK(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{axis:s,keepDims:i}=a;ge(r,"prod");let o=r.shape.length,l=w.parseAxisParam(s,r.shape),u=N.getAxesPermutation(l,o),p=l,d=r,c=[];u!=null&&(d=Un({inputs:{x:r},backend:n,attrs:{perm:u}}),c.push(d),p=N.getInnerMostAxes(p.length,o));let h=n.data.get(d.dataId).values,{outVals:m,outShape:f,outDtype:g}=j_(d.shape,d.dtype,h,p),b=f;return i&&(b=N.expandShapeToKeepDim(f,l)),c.forEach(y=>n.disposeIntermediateTensorInfo(y)),n.makeTensorInfo(b,g,m)}var vK={kernelName:Io,backendName:"cpu",kernelFunc:xK};function wK(e,t,n){e.forEach((a,r)=>{if(a<0||a>=n){let s=w.indexToLoc(r,t.length,w.computeStrides(t)).join(",");throw new Error(`indices[${s}] = ${a} is not in [0, ${n})`)}})}function kK(e,t){for(let n=0;n<e.length;++n){let a=e[n],r=n===e.length-1?t:e[n+1].length;if(a.length===0)throw new Error("Ragged splits may not be empty");if(a[0]<0)throw new Error("Ragged splits must be non-negative");if(a[a.length-1]>r)throw new Error("Ragged splits must not point past values");for(let s=1;s<a.length;++s)if(a[s-1]>a[s])throw new Error("Ragged splits must be sorted in ascending order")}}function IK(e,t,n,a){let r=[],s=0,i=t.length-1+n.length,o=new Array(i).fill(null).map(()=>[0]);kK(n,a);let l=1;for(let u=0;u<t.length-1;++u){l*=t[u];let p=t[u+1];for(let d=1;d<l+1;++d)o[u].push(d*p)}for(let u=0;u<e.length;++u){let p=e[u],d=e[u]+1;for(let c=0;c<n.length;++c){let h=n[c],m=c+t.length-1;if(m>=0){let f=o[m],g=f[f.length-1]-h[p];for(let b=p;b<d;++b)o[m].push(h[b+1]+g)}p=h[p],d=h[d]}d!==p&&(r.push([p,d]),s+=d-p)}return{outSplits:o,valueSlices:r,numValues:s}}function SK(e){let t=[];for(let n=0;n<e.length;++n){let a=e[n].length,r=w.getArrayFromDType("int32",a);t.push(r),e[n].forEach((s,i)=>r[i]=s)}return t}function lS(e,t){let n=e.slice(0,t);for(;n.length<t;)n.push(1);for(let a=t;a<e.length;a++)n[t-1]*=e[a];return n}function NK(e,t,n,a,r,s){let i=lS(t,2)[1],o=lS(s,2)[1],l=0;for(let u of n)for(let p=u[0];p<u[1];++p){for(let d=0;d<a;++d)r[l*o+d]=e[p*i+d];++l}}function TK(e,t,n,a,r){let s=t.slice();s[0]=r;let i=w.getArrayFromDType(n,w.sizeFromShape(s)),o=e.length,l=o===0?0:o/t[0];return NK(e,t,a,l,i,s),[i,s]}function K_(e,t,n,a,r,s,i,o){if(e.length===0)throw new Error("paramsNestedSplits must be non empty");if(t[0].length===0)throw new Error("Split tensors must not be scalars");let l=t[0][0]-1;if(wK(s,i,l),a.length===0)throw new Error("params.rank must be nonzero");let u=a[0],{outSplits:p,valueSlices:d,numValues:c}=IK(s,i,e,u),h=SK(p),m=TK(n,a,r,d,c);return[h,m[0],m[1]]}var uS=2147483647;function X_(e,t,n,a,r,s,i){if(t.length>1)throw new Error("starts must be a scalar or vector");if(r.length>1)throw new Error("limits must be a scalar or vector");if(i.length>1)throw new Error("deltas must be a scalar or vector");let o=t.length===0,l=r.length===0,u=i.length===0,p=[];o||p.push(t[0]),l||p.push(r[0]),u||p.push(i[0]);for(let g=1;g<p.length;++g)if(p[g]!==p[g-1])throw new Error("starts, limits, and deltas must have the same shape");let d=p.length===0?1:p[0],c=w.getArrayFromDType("int32",d+1);c[0]=0;for(let g=0;g<d;++g){let b=o?e[0]:e[g],y=l?a[0]:a[g],x=u?s[0]:s[g];if(x===0)throw new Error("Requires delta != 0");let v;if(x>0&&y<b||x<0&&y>b)v=0;else if(v=Math.ceil(Math.abs((y-b)/x)),v>uS)throw new Error(`Requires ((limit - start) / delta) <= ${uS}`);c[g+1]=c[g]+v}let h=c[d],m=w.getArrayFromDType(n,h),f=0;for(let g=0;g<d;++g){let b=c[g+1]-c[g],y=o?e[0]:e[g],x=u?s[0]:s[g];for(let v=0;v<b;++v)m[f++]=y,y+=x}return[c,m]}var Ca=N.RowPartitionType,uv=class{constructor(e,t,n,a,r,s,i,o,l,u){this.shape=e,this.shapeShape=t,this.values=n,this.valuesShape=a,this.valuesDType=r,this.defaultValue=s,this.defaultValueShape=i,this.rowPartitionValues=o,this.rowPartitionValuesShapes=l,this.rowPartitionTypes=N.getRowPartitionTypesHelper(u),this.raggedRank=N.getRaggedRank(this.rowPartitionTypes)}getRowPartitionTypeByDimension(e){return this.rowPartitionTypes[0]===Ca.FIRST_DIM_SIZE?this.rowPartitionTypes[e+1]:this.rowPartitionTypes[e]}getRowPartitionTensor(e){return this.rowPartitionTypes[0]===Ca.FIRST_DIM_SIZE?this.rowPartitionValues[e+1]:this.rowPartitionValues[e]}getMaxWidth(e){let t=this.getRowPartitionTensor(e-1);switch(this.getRowPartitionTypeByDimension(e-1)){case Ca.VALUE_ROWIDS:return uv.getMaxWidthValueRowID(t);case Ca.ROW_SPLITS:return uv.getMaxWidthRowSplit(t);default:throw new Error(`Cannot handle partition type ${Ca[this.getRowPartitionTypeByDimension(e-1)]}`)}}static getMaxWidthRowSplit(e){let t=e.length;if(t===0||t===1)return 0;let n=0;for(let a=0;a<t-1;++a){let r=e[a+1]-e[a];r>n&&(n=r)}return n}static getMaxWidthValueRowID(e){let t=e.length;if(t===0)return 0;let n=0,a=e[0],r=0;for(let s=1;s<t;++s){let i=e[s];i!==a&&(a=i,r=Math.max(s-n,r),n=s)}return Math.max(t-n,r)}tensorShapeFromTensor(e,t,n=!0){if(t.length===0){if(e[0]===-1)return[];throw new Error("The only valid scalar shape tensor is the fully unknown shape specified as -1.")}return cS(e,n)}calculateOutputSize(e){let t=this.valuesShape,n=this.defaultValueShape;N.validateDefaultValueShape(n,t);let a=this.tensorShapeFromTensor(this.shape,this.shapeShape),r=N.combineRaggedTensorToTensorShapes(this.raggedRank,a,t);r[0]<0&&(r[0]=e);for(let s=1;s<=this.raggedRank;++s)r[s]<0&&(r[s]=this.getMaxWidth(s));return r}calculateFirstParentOutputIndex(e,t,n){let a=Math.min(e,n),r=[],s=0;for(let i=0;i<a;++i,s+=t)r.push(s);for(let i=a;i<e;++i)r.push(-1);return w.assert(r.length===e,()=>"Final length of result must be equal to firstDimension."),r}calculateOutputIndexRowSplit(e,t,n,a){let r=e.length,s=[];for(let i=0;i<r-1;++i){let o=e[i+1]-e[i],l=Math.min(a,o),u=t[i];u===-1&&(l=0);for(let p=0;p<l;++p)s.push(u),u+=n;for(let p=0;p<o-l;++p)s.push(-1)}if(r>0&&s.length!==e[r-1])throw new Error("Invalid row split size.");return s}calculateOutputIndexValueRowID(e,t,n,a){let r=e.length,s=[];if(r===0)return[];let i=0,o=e[0];if(o>=t.length)throw new Error(`Got currentValueRowId=${o}, which is not less than ${t.length}`);let l=t[o];s.push(l);for(let u=1;u<r;++u){let p=e[u];if(p===o)l>=0&&(++i,i<a?l+=n:l=-1);else{if(i=0,o=p,p>=t.length)throw new Error(`Got nextValueRowId=${p} which is not less than ${t.length}`);l=t[p]}s.push(l)}if(s.length!==e.length)throw new Error("Invalid row ids.");return s}calculateOutputIndex(e,t,n,a){let r=this.getRowPartitionTensor(e),s=this.getRowPartitionTypeByDimension(e);switch(s){case Ca.VALUE_ROWIDS:return this.calculateOutputIndexValueRowID(r,t,n,a);case Ca.ROW_SPLITS:if(r.length-1>t.length)throw new Error(`Row partition size is greater than output size: ${r.length-1} > ${t.length}`);return this.calculateOutputIndexRowSplit(r,t,n,a);default:throw new Error(`Unsupported partition type: ${Ca[s]}`)}}getFirstDimensionSize(){let e=this.rowPartitionValues[0];if(this.rowPartitionTypes.length===0)throw new Error("No row_partition_types given.");let t=this.rowPartitionTypes[0];switch(t){case Ca.FIRST_DIM_SIZE:return e[0];case Ca.VALUE_ROWIDS:throw new Error("Cannot handle VALUE_ROWIDS in first dimension.");case Ca.ROW_SPLITS:return this.rowPartitionValuesShapes[0][0]-1;default:throw new Error(`Cannot handle type ${Ca[t]}`)}}compute(){if(this.rowPartitionValues[0].length<=0)throw new Error("Invalid first partition input. Tensor requires at least one element.");let e=this.getFirstDimensionSize(),t=this.calculateOutputSize(e),n=new Array(this.raggedRank+1);n[n.length-1]=1;for(let s=n.length-2;s>=0;--s)n[s]=n[s+1]*t[s+1];let a=cS(t,!1),r=w.getArrayFromDType(this.valuesDType,w.sizeFromShape(a));if(n[0]*t[0]>0){let s=this.calculateFirstParentOutputIndex(e,n[0],t[0]);for(let i=1;i<=this.raggedRank;++i)s=this.calculateOutputIndex(i-1,s,n[i],t[i]);this.setOutput(this.raggedRank,s,r,a)}return[a,r]}setOutput(e,t,n,a){if(n.length===0)return;let r=this.values,s=n,i=a.slice();i=i.slice(e+1);let o=w.sizeFromShape(i),l=t.length,u=this.defaultValue;if(u.length!==o&&u.length!==1){let h=this.defaultValueShape;P(()=>{let m=W(u,h);u=ri(m,i).dataSync()})}let p=0,d=0,c=0;for(let h=0;h<=l;++h){let m=h<l?t[h]:-1;if(m===c){++c;continue}if(d<c){let f=r.subarray(p*o),g=s.subarray(d*o),b=(c-d)*o;pS(g,f,b)}if(h>=l){let f=n.length;m=Math.floor(f/o)}if(m>c)if(this.defaultValue.length===1)s.subarray(c*o,m*o).fill(this.defaultValue[0]),c=m;else for(;m>c;){let f=s.slice(c*o);pS(f,u,o),++c}m<0?(p=h+1,d=c):(p=h,d=c,c=d+1)}}};function pS(e,t,n){for(let a=0;a<n;a++)e[a]=t[a]}function cS(e,t){let n=[];for(let a of e){if(a<0){if(!t)throw new Error(`Dimension ${a} must be >= 0`);if(a<-1)throw new Error(`Dimension ${a} must be >= -1`);a=-1}n.push(a)}return n}function Y_(e,t,n,a,r,s,i,o,l,u){return new uv(e,t,n,a,r,s,i,o,l,u).compute()}function V1(e,t,n,a){let r=e===t,s=e<t&&n<0,i=t<e&&n>1;if(r||s||i)return w.makeZerosTypedArray(0,a);let o=Math.abs(Math.ceil((t-e)/n)),l=w.makeZerosTypedArray(o,a);t<e&&n===1&&(n=-1),l[0]=e;for(let u=1;u<l.length;u++)l[u]=l[u-1]+n;return l}var Z_=yr(e=>1/Math.sqrt(e)),CK=Rs(Fo,Z_),_K={kernelName:Fo,backendName:"cpu",kernelFunc:CK};function ai(e,t,n,a,r,s,i,o,l,u){let p=[a/r,r],d=e.values,c=t.values;if(a===0)return ze(n,t.dtype);let h=l instanceof Vt?l:ze(p,t.dtype);typeof l=="string"||typeof l=="number"?h.values.fill(l):typeof l=="boolean"&&h.values.fill(+l);for(let m=0;m<s;m++){let f=[],g=0;for(let b=0;b<i;b++){let y=d[m*i+b];f.push(y),g+=y*o[b]}if(g<0||g>=a/r)throw new Error(`Invalid indices: ${f} does not index into ${n}`);for(let b=0;b<r;b++)u?h.values[g*r+b]+=c[m*r+b]:h.values[g*r+b]=t.rank===0?c[0]:c[m*r+b]}return h}var EK=yr(e=>1/(1+Math.exp(-e))),J_=it(Po,e=>1/(1+Math.exp(-e))),AK={kernelName:Po,backendName:"cpu",kernelFunc:J_};function Nm(e,t,n,a,r){let s=Xt.isSliceContinous(a,t,n),i=w.sizeFromShape(n),o=w.computeStrides(a);if(s){let d=Xt.computeFlatOffset(t,o);return r==="string"?e.slice(d,d+i):e.subarray(d,d+i)}let l=r==="string"?N.fromUint8ToStringArray(e):e,u=ze(a,r,l),p=ze(n,r);for(let d=0;d<p.size;++d){let c=p.indexToLoc(d),h=c.map((m,f)=>m+t[f]);p.set(u.get(...h),...c)}return r==="string"?N.fromStringArrayToUint8(p.values):p.values}function vi(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{begin:s,size:i}=a;ge(r,"slice");let[o,l]=Xt.parseSliceParams(r,s,i);Xt.assertParamsValid(r,o,l);let u=n.data.get(r.dataId).values,p=Nm(u,o,l,r.shape,r.dtype);return n.makeTensorInfo(l,r.dtype,p)}var FK={kernelName:Qu,backendName:"cpu",kernelFunc:vi};function Q_(e,t,n,a,r,s,i){let o=t[0],l=s[0],u=new Array(l),p=new Array(o),d=t[1];if(l===0){if(o!==0)throw new Error(N.getSparseFillEmptyRowsIndicesDenseShapeMismatch(o));let g=w.getArrayFromDType(n,0),b=w.getArrayFromDType(r,0);return[g,[0,d],b,u,p]}let c=!0,h=0,m=new Array(l).fill(0);for(let g=0;g<o;++g){let b=e[g*d];if(b<0)throw new Error(N.getSparseFillEmptyRowsNegativeIndexErrorMessage(g,b));if(b>=l)throw new Error(N.getSparseFillEmptyRowsOutOfRangeIndexErrorMessage(g,b,l));++m[b],c=c&&b>=h,h=b}let f=!0;for(let g=0;g<l;++g){let b=m[g]===0;u[g]=b,f=f&&!b,m[g]=Math.max(m[g],1),g>0&&(m[g]+=m[g-1])}if(f&&c){let g=e,b=a;for(let y=0;y<o;++y)p[y]=y;return[g,[o,d],b,u,p]}else{let 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p=t.slice();return p[p.length-1]=a,[ze(p,n,l),ze(p,"int32",u)]}function K1(e,t,n,a){let r=w.parseAxisParam(t,n)[0],s=[1,n[0],1];for(let m=0;m<r;m++)s[0]*=n[m];s[1]=n[r];for(let m=r+1;m<n.length;m++)s[2]*=n[m];let i=new Map,o=new Int32Array(n[r]),l=new Vt(s,a,e),u=[],p=s[0]===1&&s[2]===1;for(let m=0;m<n[r];m++){let f;if(p)f=e[m].toString();else{let b=[];for(let y=0;y<s[0];y++)for(let x=0;x<s[2];x++)b.push(l.get(y,m,x));f=b.join(",")}let g=i.get(f);if(g!=null)o[m]=g;else{let b=i.size;i.set(f,b),o[m]=b,u.push(m)}}let d=s.slice();d[1]=i.size;let c=new Vt(d,a);u.forEach((m,f)=>{for(let g=0;g<s[0];g++)for(let b=0;b<s[2];b++)c.set(l.get(g,m,b),g,f,b)});let h=n.slice();return h[r]=d[1],{outputValues:c.values,outputShape:h,indices:o}}var UK="4.7.0";Zm("cpu",()=>new Yf,1);var lE=it(ji,e=>e>=0?e:Math.exp(e)-1),GK={kernelName:ji,backendName:"cpu",kernelFunc:lE};function uE(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{alpha:s}=a;ge([r],"leakyRelu");let 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ZK={kernelName:Mi,backendName:"cpu",kernelFunc:hE};function JK(e){let{inputs:t,backend:n,attrs:a}=e,{a:r,b:s,bias:i,preluActivationWeights:o}=t,{transposeA:l,transposeB:u,activation:p,leakyreluAlpha:d}=a,c,h,m,f=[];c=hE({inputs:{a:r,b:s},attrs:{transposeA:l,transposeB:u},backend:n}),i&&(h=ru({inputs:{a:c,b:i},backend:n}),f.push(c),c=h),p&&(m=Tm(n,c,p,o,d),f.push(c),c=m);for(let g of f)n.disposeIntermediateTensorInfo(g);return c}var QK={kernelName:oi,backendName:"cpu",kernelFunc:JK},e8=it(Ti,e=>Math.acos(e)),t8={kernelName:Ti,backendName:"cpu",kernelFunc:e8},n8=it(Ci,e=>Math.acosh(e)),a8={kernelName:Ci,backendName:"cpu",kernelFunc:n8};function r8(e){let{inputs:t,backend:n}=e,a=t;ge(t,"addN");let r=a.map(o=>n.data.get(o.dataId).values),s=ze(a[0].shape,a[0].dtype),i=s.values;for(let o=0;o<a.length;o++){let l=r[o];for(let u=0;u<i.length;u++)i[u]+=l[u]}return n.makeTensorInfo(s.shape,s.dtype,s.values)}var s8={kernelName:_i,backendName:"cpu",kernelFunc:r8};function 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i=w.parseAxisParam(s,r.shape),o=N.getAxesPermutation(i,r.shape.length),l=r,u=[];o!=null&&(l=Un({inputs:{x:r},backend:n,attrs:{perm:o}}),u.push(l),i=N.getInnerMostAxes(i.length,l.shape.length)),i=[i[0]],N.assertAxesAreInnerMostDims("argMin",i,l.shape.length);let[p,d]=N.computeOutAndReduceShapes(l.shape,i),c=w.sizeFromShape(p),h=w.makeZerosTypedArray(c,"int32"),m=w.sizeFromShape(d),f=n.data.get(l.dataId).values;for(let g=0;g<h.length;++g){let b=g*m,y=f[b],x=0;for(let v=0;v<m;++v){let I=f[b+v];I<y&&(y=I,x=v)}h[g]=x}return u.forEach(g=>n.disposeIntermediateTensorInfo(g)),n.makeTensorInfo(p,"int32",h)}var h8={kernelName:du,backendName:"cpu",kernelFunc:d8},m8=it(Ei,e=>Math.asin(e)),f8={kernelName:Ei,backendName:"cpu",kernelFunc:m8},g8=it(Ai,e=>Math.asinh(e)),b8={kernelName:Ai,backendName:"cpu",kernelFunc:g8},y8=it(Fi,e=>Math.atan(e)),x8={kernelName:Fi,backendName:"cpu",kernelFunc:y8},v8=Ot((e,t)=>Math.atan2(e,t)),w8=Jt(Di,v8),k8={kernelName:Di,backendName:"cpu",kernelFunc:w8},I8=it($i,e=>Math.atanh(e)),S8={kernelName:$i,backendName:"cpu",kernelFunc:I8};function X1(e,t,n,a,r,s){let i=r.strideHeight,o=r.strideWidth,l=r.dilationHeight,u=r.dilationWidth,p=r.effectiveFilterHeight,d=r.effectiveFilterWidth,c=r.padInfo.top,h=r.padInfo.left,m=s==="max"?Number.NEGATIVE_INFINITY:Number.POSITIVE_INFINITY,f=ze(r.outShape,n),g=f.values,b=r.outShape[1]*r.outShape[2]*r.outShape[3],y=r.outShape[2]*r.outShape[3],x=r.outShape[3];for(let v=0;v<r.batchSize;++v){let I=v*b,T=v*a[0];for(let C=0;C<r.inChannels;++C)for(let E=0;E<r.outHeight;++E){let 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U=B-C,H=f.get(g,S,B,b);H>D&&(D=H,r?$=s?((g*a.inHeight+S)*a.inWidth+B)*a.inChannels+b:(S*a.inWidth+B)*a.inChannels+b:$=M*c+U)}}i.set($,g,y,T,b)}}return i}function fE(e,t,n,a,r,s){let i=r.strideDepth,o=r.strideHeight,l=r.strideWidth,u=r.dilationDepth,p=r.dilationHeight,d=r.dilationWidth,c=r.effectiveFilterDepth,h=r.effectiveFilterHeight,m=r.effectiveFilterWidth,f=r.padInfo.front,g=r.padInfo.top,b=r.padInfo.left,y=s==="max"?Number.NEGATIVE_INFINITY:Number.POSITIVE_INFINITY,x=ze(r.outShape,n),v=x.values,I=r.outShape[1]*r.outShape[2]*r.outShape[3]*r.outShape[4],T=r.outShape[2]*r.outShape[3]*r.outShape[4],C=r.outShape[3]*r.outShape[4],E=r.outShape[4];for(let F=0;F<r.batchSize;++F){let D=F*I,$=F*a[0];for(let S=0;S<r.inChannels;++S)for(let M=0;M<r.outDepth;++M){let B=M*i-f,U=B;for(;U<0;)U+=u;let H=Math.min(r.inDepth,c+B),j=D+M*T;for(let K=0;K<r.outHeight;++K){let Z=K*o-g,J=Z;for(;J<0;)J+=p;let ee=Math.min(r.inHeight,h+Z),ae=j+K*C;for(let te=0;te<r.outWidth;++te){let re=te*l-b,ie=re;for(;ie<0;)ie+=d;let ye=Math.min(r.inWidth,m+re),ue=ae+te*E,be=y,ke=0,Se=0;for(let Ge=U;Ge<H;Ge+=u){let ht=$+Ge*a[1];for(let st=J;st<ee;st+=p){let at=ht+st*a[2];for(let rt=ie;rt<ye;rt+=d){let Me=at+rt*a[3],ft=e[Me+S];if(s==="max"&&ft>be?be=ft:s==="avg"&&(ke+=ft,Se++),isNaN(be))break}if(isNaN(be))break}if(isNaN(be))break}let We=ue+S;v[We]=s==="avg"?ke/Math.max(Se,1):be}}}}return x}function N8(e,t){let n=ze(t.outShape,"int32"),a=t.strideDepth,r=t.strideHeight,s=t.strideWidth,i=t.dilationDepth,o=t.dilationHeight,l=t.dilationWidth,u=t.effectiveFilterDepth,p=t.effectiveFilterHeight,d=t.effectiveFilterWidth,c=t.padInfo.front,h=t.padInfo.top,m=t.padInfo.left;for(let f=0;f<t.batchSize;++f)for(let g=0;g<t.inChannels;++g)for(let b=0;b<t.outDepth;++b){let y=b*a-c,x=y;for(;x<0;)x+=i;let v=Math.min(t.inDepth,u+y);for(let I=0;I<t.outHeight;++I){let T=I*r-h,C=T;for(;C<0;)C+=o;let E=Math.min(t.inHeight,p+T);for(let F=0;F<t.outWidth;++F){let D=F*s-m,$=D;for(;$<0;)$+=l;let S=Math.min(t.inWidth,d+D),M=Number.NEGATIVE_INFINITY,B=-1;for(let U=x;U<v;U+=i){let H=U-y;for(let j=C;j<E;j+=o){let K=j-T;for(let Z=$;Z<S;Z+=l){let J=Z-D,ee=e.get(f,U,j,Z,g);ee>=M&&(M=ee,B=H*p*d+K*p+J)}}}n.set(B,f,b,I,F,g)}}}return n}function T8(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t;ge(r,"avgPool");let{filterSize:s,strides:i,pad:o,dimRoundingMode:l}=a,u=1;w.assert(N.eitherStridesOrDilationsAreOne(i,u),()=>`Error in avgPool: Either strides or dilations must be 1. 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p=N.computePool3DInfo(s.shape,i,o,1,l,u),d=p.strideDepth,c=p.strideHeight,h=p.strideWidth,m=p.filterDepth,f=p.filterHeight,g=p.filterWidth,b=p.dilationDepth,y=p.dilationHeight,x=p.dilationWidth,v=p.effectiveFilterDepth,I=p.effectiveFilterHeight,T=p.effectiveFilterWidth,C=v-1-p.padInfo.front,E=T-1-p.padInfo.left,F=I-1-p.padInfo.top,D=ze(s.shape,"float32"),$=1/(m*f*g),S=n.bufferSync(r);for(let M=0;M<p.batchSize;++M)for(let B=0;B<p.inChannels;++B)for(let U=0;U<p.inDepth;++U)for(let H=0;H<p.inHeight;++H)for(let j=0;j<p.inWidth;++j){let K=U-C,Z=H-F,J=j-E,ee=0;for(let ae=0;ae<v;ae+=b){let te=(K+ae)/d;if(!(te<0||te>=p.outDepth||Math.floor(te)!==te))for(let re=0;re<I;re+=y){let ie=(Z+re)/c;if(!(ie<0||ie>=p.outHeight||Math.floor(ie)!==ie))for(let ye=0;ye<T;ye+=x){let ue=(J+ye)/h;if(ue<0||ue>=p.outWidth||Math.floor(ue)!==ue)continue;let be=S.get(M,te,ie,ue,B);ee+=be}}}D.set(ee*$,M,U,H,j,B)}return n.makeTensorInfo(D.shape,D.dtype,D.values)}var F8={kernelName:Lc,backendName:"cpu",kernelFunc:A8};function $8(e){let{inputs:t,backend:n,attrs:a}=e,{dy:r,input:s}=t,i=s;ge([r,s],"avgPoolGrad");let{filterSize:o,strides:l,pad:u}=a,p=N.computePool2DInfo(i.shape,o,l,1,u),d=p.strideHeight,c=p.strideWidth,h=p.filterHeight,m=p.filterWidth,f=p.dilationHeight,g=p.dilationWidth,b=p.effectiveFilterHeight,y=p.effectiveFilterWidth,x=y-1-p.padInfo.left,v=b-1-p.padInfo.top,I=ze(i.shape,"float32"),T=1/(h*m),C=n.data.get(r.dataId).values,E=ze(r.shape,"float32",C);for(let F=0;F<p.batchSize;++F)for(let D=0;D<p.inChannels;++D)for(let $=0;$<p.inHeight;++$)for(let S=0;S<p.inWidth;++S){let M=$-v,B=S-x,U=0;for(let H=0;H<b;H+=f){let j=(M+H)/d;if(!(j<0||j>=p.outHeight||Math.floor(j)!==j))for(let K=0;K<y;K+=g){let Z=(B+K)/c;if(Z<0||Z>=p.outWidth||Math.floor(Z)!==Z)continue;let J=E.get(F,j,Z,D);U+=J}}I.set(U*T,F,$,S,D)}return n.makeTensorInfo(I.shape,I.dtype,I.values)}var D8={kernelName:Oc,backendName:"cpu",kernelFunc:$8};function 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n.makeTensorInfo(r.shape,r.dtype,f)}var M8={kernelName:Qi,backendName:"cpu",kernelFunc:R8};function P8(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{blockShape:s,crops:i}=a;ge([r],"batchToSpaceND");let o=s.reduce((b,y)=>b*y),l=N.getReshaped(r.shape,s,o),u=N.getPermuted(l.length,s.length),p=N.getReshapedPermuted(r.shape,s,o),d=N.getSliceBeginCoords(i,s.length),c=N.getSliceSize(p,i,s.length),h=xt({inputs:{x:r},backend:n,attrs:{shape:l}}),m=Un({inputs:{x:h},backend:n,attrs:{perm:u}}),f=xt({inputs:{x:m},backend:n,attrs:{shape:p}}),g=vi({inputs:{x:f},backend:n,attrs:{begin:d,size:c}});return n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(f),g}var O8={kernelName:mu,backendName:"cpu",kernelFunc:P8};function L8(e){let{inputs:t,backend:n,attrs:a}=e,{x:r,weights:s}=t,{size:i}=a,o=n.data.get(r.dataId).values,l=n.data.get(s.dataId).values,u=L1(o,l,s.dtype,s.shape,i);return n.makeTensorInfo([i],s.dtype,u)}var z8={kernelName:fu,backendName:"cpu",kernelFunc:L8};function W8(e){let{inputs:t,backend:n}=e,{s0:a,s1:r}=t,s=n.data.get(a.dataId).values,i=n.data.get(r.dataId).values,o=N.assertAndGetBroadcastShape(Array.from(s),Array.from(i));return n.makeTensorInfo([o.length],"int32",Int32Array.from(o))}var B8={kernelName:zc,backendName:"cpu",kernelFunc:W8},V8=it(Ss,(e,t)=>{let n=t;return e>n.clipValueMax?n.clipValueMax:e<n.clipValueMin?n.clipValueMin:e}),U8={kernelName:Ss,backendName:"cpu",kernelFunc:V8},G8=e=>{let{x:t}=e.inputs,n=e.backend,a=new Float32Array(w.sizeFromShape(t.shape)),r=n.data.get(t.dataId),s=r.complexTensorInfos.real,i=r.complexTensorInfos.imag,o=n.data.get(s.dataId).values,l=n.data.get(i.dataId).values;for(let u=0;u<o.length;u++){let p=o[u],d=l[u];a[u]=Math.hypot(p,d)}return n.makeOutput(a,t.shape,"float32")},H8={kernelName:Wc,backendName:"cpu",kernelFunc:G8};function su(e){let{inputs:t,backend:n}=e,{input:a}=t,r=n.data.get(a.dataId).complexTensorInfos.imag,s=n.data.get(r.dataId).values;return n.makeTensorInfo(r.shape,r.dtype,s)}var q8={kernelName:Gm,backendName:"cpu",kernelFunc:su};function iu(e){let{inputs:t,backend:n,attrs:a}=e,{axis:r}=a,s=w.parseAxisParam(r,t[0].shape)[0],i=t.map(f=>f.shape);N.assertParamsConsistent(i,s);let o=N.computeOutShape(t.map(f=>f.shape),s);if(w.sizeFromShape(o)===0)return n.makeTensorInfo(o,t[0].dtype,[]);let l=t.filter(f=>w.sizeFromShape(f.shape)>0);if(l.length===1)return dr({inputs:{x:l[0]},backend:n});if(l[0].dtype==="complex64"){let f=l.map(v=>xi({inputs:{input:v},backend:n})),g=l.map(v=>su({inputs:{input:v},backend:n})),b=iu({inputs:f,backend:n,attrs:{axis:s}}),y=iu({inputs:g,backend:n,attrs:{axis:s}}),x=Jn({inputs:{real:b,imag:y},backend:n});return f.forEach(v=>n.disposeIntermediateTensorInfo(v)),g.forEach(v=>n.disposeIntermediateTensorInfo(v)),n.disposeIntermediateTensorInfo(b),n.disposeIntermediateTensorInfo(y),x}let u=l.map(f=>{let g=[-1,w.sizeFromShape(f.shape.slice(s))];return xt({inputs:{x:f},backend:n,attrs:{shape:g}})}),p=u.map(f=>({vals:n.data.get(f.dataId).values,shape:f.shape}));o=N.computeOutShape(u.map(f=>f.shape),1);let d=u[0].shape[0]===1,c=z1(p,o,t[0].dtype,d),h=N.computeOutShape(l.map(f=>f.shape),s),m=n.makeTensorInfo(h,t[0].dtype,c);return u.forEach(f=>n.disposeIntermediateTensorInfo(f)),m}var j8={kernelName:bu,backendName:"cpu",kernelFunc:iu};function gE(e){let{inputs:t,backend:n,attrs:a}=e,{x:r,filter:s}=t,{strides:i,pad:o,dataFormat:l,dilations:u,dimRoundingMode:p}=a;ge([r,s],"conv2d");let d=N.convertConv2DDataFormat(l),c=N.computeConv2DInfo(r.shape,s.shape,i,u,o,p,!1,d),h=c.filterHeight,m=c.filterWidth,f=c.dilationHeight,g=c.dilationWidth,b=c.padInfo.left,y=c.padInfo.top,x=c.dataFormat==="channelsLast",v=new 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X8(e){let{inputs:t,backend:n,attrs:a}=e,{x:r,dy:s}=t,{strides:i,pad:o,dataFormat:l,dimRoundingMode:u,filterShape:p}=a;ge([r,s],"conv2dBackpropFilter");let d=N.convertConv2DDataFormat(l),c=N.computeConv2DInfo(r.shape,p,i,1,o,u,!1,d),{strideHeight:h,strideWidth:m,filterHeight:f,filterWidth:g}=c,b=c.dataFormat==="channelsLast",y=new Vt(c.filterShape,"float32"),x=c.padInfo.left,v=c.padInfo.top,I=n.data.get(r.dataId).values,T=n.data.get(s.dataId).values,C=new Vt(r.shape,r.dtype,I),E=new Vt(s.shape,s.dtype,T);for(let F=0;F<f;++F){let D=Math.max(0,Math.ceil((v-F)/h)),$=Math.min(c.outHeight,(c.inHeight+v-F)/h);for(let S=0;S<g;++S){let M=Math.max(0,Math.ceil((x-S)/m)),B=Math.min(c.outWidth,(c.inWidth+x-S)/m);for(let U=0;U<c.inChannels;++U)for(let H=0;H<c.outChannels;++H){let j=0;for(let K=0;K<c.batchSize;++K)for(let Z=D;Z<$;++Z){let J=F+Z*h-v;for(let ee=M;ee<B;++ee){let ae=S+ee*m-x;b?j+=C.get(K,J,ae,U)*E.get(K,Z,ee,H):j+=C.get(K,U,J,ae)*E.get(K,H,Z,ee)}}y.set(j,F,S,U,H)}}}return n.makeTensorInfo(y.shape,y.dtype,y.values)}var Y8={kernelName:Lm,backendName:"cpu",kernelFunc:X8};function Z8(e){let{inputs:t,backend:n,attrs:a}=e,{dy:r,filter:s}=t,{inputShape:i,strides:o,pad:l,dataFormat:u,dimRoundingMode:p}=a;ge([r,s],"conv2dBackpropInput");let d=w.computeStrides(s.shape),c=w.computeStrides(r.shape),h=N.convertConv2DDataFormat(u),m=N.computeConv2DInfo(i,s.shape,o,1,l,p,!1,h),f=new Vt(m.inShape,"float32"),g=f.values,b=n.data.get(r.dataId).values,y=n.data.get(s.dataId).values,[x,v,I]=d,{batchSize:T,filterHeight:C,filterWidth:E,inChannels:F,inHeight:D,inWidth:$,outChannels:S,outHeight:M,outWidth:B,strideHeight:U,strideWidth:H}=m;h=m.dataFormat;let j=C-1-m.padInfo.top,K=E-1-m.padInfo.left,Z=h==="channelsLast",J=f.strides[0],ee=Z?f.strides[1]:f.strides[2],ae=Z?f.strides[2]:1,te=Z?1:f.strides[1],re=c[0],ie=Z?c[1]:c[2],ye=Z?c[2]:1,ue=Z?1:c[1];for(let be=0;be<T;++be)for(let ke=0;ke<F;++ke)for(let Se=0;Se<D;++Se){let 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u=w.computeStrides(r.shape),p=w.computeStrides(s.shape),d=N.computeConv3DInfo(r.shape,l,i,1,o),c=d.strideDepth,h=d.strideHeight,m=d.strideWidth,f=d.filterDepth,g=d.filterHeight,b=d.filterWidth,y=new Vt(d.filterShape,"float32"),x=y.values,[v,I,T,C]=y.strides,E=n.data.get(s.dataId).values,[F,D,$,S]=p,M=n.data.get(r.dataId).values,[B,U,H,j]=u,K=d.padInfo.front,Z=d.padInfo.left,J=d.padInfo.top;for(let ee=0;ee<f;++ee){let ae=Math.max(0,Math.ceil((K-ee)/c)),te=Math.min(d.outDepth,(d.inDepth+K-ee)/c),re=ee*v;for(let ie=0;ie<g;++ie){let ye=Math.max(0,Math.ceil((J-ie)/h)),ue=Math.min(d.outHeight,(d.inHeight+J-ie)/h),be=ie*I+re;for(let ke=0;ke<b;++ke){let Se=Math.max(0,Math.ceil((Z-ke)/m)),We=Math.min(d.outWidth,(d.inWidth+Z-ke)/m),Ge=ke*T+be;for(let ht=0;ht<d.inChannels;++ht){let st=ht*C+Ge;for(let at=0;at<d.outChannels;++at){let rt=0;for(let Me=0;Me<d.batchSize;++Me){let ft=Me*B,jn=Me*F;for(let Lt=ae;Lt<te;++Lt){let la=(ee+Lt*c-K)*U+ft,cn=Lt*D+jn;for(let $n=ye;$n<ue;++$n){let 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uX(e){let{inputs:t,backend:n,attrs:a}=e,{image:r,boxes:s,boxInd:i}=t,{cropSize:o,method:l,extrapolationValue:u}=a,[p,d,c,h]=r.shape,m=s.shape[0],[f,g]=o,b=ze([m,f,g,h],"float32"),y=n.data.get(s.dataId).values,x=n.data.get(i.dataId).values,v=n.data.get(r.dataId).values,I=w.computeStrides(r.shape),T=w.computeStrides(b.shape);for(let C=0;C<m;C++){let E=C*4,F=y[E],D=y[E+1],$=y[E+2],S=y[E+3],M=x[C];if(M>=p)continue;let B=f>1?($-F)*(d-1)/(f-1):0,U=g>1?(S-D)*(c-1)/(g-1):0;for(let H=0;H<f;H++){let j=f>1?F*(d-1)+H*B:.5*(F+$)*(d-1);if(j<0||j>d-1){for(let K=0;K<g;K++)for(let Z=0;Z<h;Z++){let J=Z+K*T[2]+H*T[1]+C*T[0];b.values[J]=u}continue}if(l==="bilinear"){let K=Math.floor(j),Z=Math.ceil(j),J=j-K;for(let ee=0;ee<g;ee++){let ae=g>1?D*(c-1)+ee*U:.5*(D+S)*(c-1);if(ae<0||ae>c-1){for(let ye=0;ye<h;ye++){let ue=ye+ee*T[2]+H*T[1]+C*T[0];b.values[ue]=u}continue}let te=Math.floor(ae),re=Math.ceil(ae),ie=ae-te;for(let ye=0;ye<h;ye++){let ue=ye+te*I[2]+K*I[1]+M*I[0],be=v[ue];ue=ye+re*I[2]+K*I[1]+M*I[0];let 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d=ba(u.dtype,"int32"),c=w.makeOnesTypedArray(w.sizeFromShape(u.shape),d),h=n.data.get(u.dataId).values,m=u.shape[u.shape.length-1],f=o?(b,y)=>b+m-y-1:(b,y)=>b+y;for(let b=0;b<h.length;b+=m)for(let y=0;y<m;y++){let x=f(b,y);if(y===0)c[x]=i?1:h[x];else{let v=f(b,y-1);c[x]=i?h[v]*c[v]:h[x]*c[v]}}let g=n.makeTensorInfo(u.shape,d,c);if(l!=null){let b=N.getUndoAxesPermutation(l),y=Un({inputs:{x:g},backend:n,attrs:{perm:b}});return n.disposeIntermediateTensorInfo(g),n.disposeIntermediateTensorInfo(u),y}return g}var dX={kernelName:vu,backendName:"cpu",kernelFunc:cX};function hX(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{axis:s,exclusive:i,reverse:o}=a;ge(r,"cumsum");let l=N.getAxesPermutation([s],r.shape.length),u=r;l!=null&&(u=Un({inputs:{x:r},backend:n,attrs:{perm:l}}));let p=N.getInnerMostAxes(1,r.shape.length)[0];if(p!==u.shape.length-1)throw new Error(`backend.cumsum in CPU expects an inner-most axis=${u.shape.length-1} but got axis=${p}`);let d=ba(u.dtype,"int32"),c=w.makeZerosTypedArray(w.sizeFromShape(u.shape),d),h=n.data.get(u.dataId).values,m=u.shape[u.shape.length-1],f=o?(b,y)=>b+m-y-1:(b,y)=>b+y;for(let b=0;b<h.length;b+=m)for(let y=0;y<m;y++){let x=f(b,y);if(y===0)c[x]=i?0:h[x];else{let v=f(b,y-1);c[x]=i?h[v]+c[v]:h[x]+c[v]}}let g=n.makeTensorInfo(u.shape,d,c);if(l!=null){let b=N.getUndoAxesPermutation(l),y=Un({inputs:{x:g},backend:n,attrs:{perm:b}});return n.disposeIntermediateTensorInfo(g),n.disposeIntermediateTensorInfo(u),y}return g}var mX={kernelName:Ui,backendName:"cpu",kernelFunc:hX};function fX(e){let{inputs:t,backend:n,attrs:a}=e,{x:r,weights:s}=t,{size:i,binaryOutput:o}=a;if(r.shape.length===1){let l=n.data.get(r.dataId).values,u=n.data.get(s.dataId).values,p=L1(l,u,s.dtype,s.shape,i);return n.makeTensorInfo([i],s.dtype,p)}else if(r.shape.length===2){let l=n.bufferSync(r),u=n.bufferSync(s),p=S_(l,u,i,o);return n.makeTensorInfo(p.shape,s.dtype,p.values)}throw new Error(`Error in denseBincount: input must be 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vX(e){let{inputs:t,backend:n,attrs:a}=e,{x:r,dy:s}=t,{strides:i,dilations:o,pad:l,dimRoundingMode:u,filterShape:p}=a;ge([r,s],"depthwiseConv2dNativeBackpropFilter");let d=N.computeConv2DInfo(r.shape,p,i,o,l,u,!0),{strideHeight:c,strideWidth:h,filterHeight:m,filterWidth:f}=d,g=new Vt(d.filterShape,"float32"),b=d.padInfo.left,y=d.padInfo.top,x=d.outChannels/d.inChannels,v=n.data.get(r.dataId).values,I=new Vt(r.shape,r.dtype,v),T=n.data.get(s.dataId).values,C=new Vt(s.shape,s.dtype,T);for(let E=0;E<m;++E){let F=Math.max(0,Math.ceil((y-E)/c)),D=Math.min(d.outHeight,(d.inHeight+y-E)/c);for(let $=0;$<f;++$){let S=Math.max(0,Math.ceil((b-$)/h)),M=Math.min(d.outWidth,(d.inWidth+b-$)/h);for(let B=0;B<d.outChannels;++B){let U=Math.trunc(B/x),H=B%x,j=0;for(let K=0;K<d.batchSize;++K)for(let Z=F;Z<D;++Z){let J=E+Z*c-y;for(let ee=S;ee<M;++ee){let ae=$+ee*h-b;j+=I.get(K,J,ae,U)*C.get(K,Z,ee,B)}}g.set(j,E,$,U,H)}}}return n.makeTensorInfo(g.shape,g.dtype,g.values)}var 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e.FRAMEBUFFER_INCOMPLETE_DIMENSIONS:return"FRAMEBUFFER_INCOMPLETE_DIMENSIONS";case e.FRAMEBUFFER_UNSUPPORTED:return"FRAMEBUFFER_UNSUPPORTED";default:return`unknown error ${t}`}}function Wr(e,t,n){let a=de(e,()=>t());if(a==null)throw new Error(n);return a}function VE(e,t){let n=e.MAX_COMBINED_TEXTURE_IMAGE_UNITS-1,a=t+e.TEXTURE0;if(a<e.TEXTURE0||a>n){let r=`[gl.TEXTURE0, gl.TEXTURE${n}]`;throw new Error(`textureUnit must be in ${r}.`)}}function wi(e,t=2){return w.sizeFromShape(e.slice(0,e.length-t))}function ki(e){if(e.length===0)throw Error("Cannot get rows and columns of an empty shape array.");return[e.length>1?e[e.length-2]:1,e[e.length-1]]}function pc(e){let t=[1,1,1];return e.length===0||e.length===1&&e[0]===1||(t=[wi(e),...ki(e)]),t}function UE(e,t=!1){let n=G().getNumber("WEBGL_MAX_TEXTURE_SIZE"),a=G().getNumber("WEBGL_MAX_SIZE_FOR_NARROW_TEXTURE");a===1/0&&G().getBool("WEBGL_AUTO_SQUARIFY_NARROW_TEXTURE_SHAPE")&&(a=n/2),t&&(n=n*2,a=a*2,e=e.map((o,l)=>l>=e.length-2?w.nearestLargerEven(e[l]):e[l]),e.length===1&&(e=[2,e[0]])),e.length!==2&&(e=w.squeezeShape(e).newShape);let r=w.sizeFromShape(e),s=null;e.length<=1&&r<=n?s=[1,r]:e.length===2&&e[0]<=n&&e[1]<=n?s=e:e.length===3&&e[0]*e[1]<=n&&e[2]<=n?s=[e[0]*e[1],e[2]]:e.length===3&&e[0]<=n&&e[1]*e[2]<=n?s=[e[0],e[1]*e[2]]:e.length===4&&e[0]*e[1]*e[2]<=n&&e[3]<=n?s=[e[0]*e[1]*e[2],e[3]]:e.length===4&&e[0]<=n&&e[1]*e[2]*e[3]<=n&&(s=[e[0],e[1]*e[2]*e[3]]);let i=s!=null&&Math.max(...s)>a&&Math.min(...s)<=(t?2:1)&&Math.min(...s)>0;if(s==null||i)if(t){let o=wi(e),l=2,u=2;e.length&&([l,u]=ki(e)),r=o*(l/2)*(u/2),s=w.sizeToSquarishShape(r).map(p=>p*2)}else s=w.sizeToSquarishShape(r);return s}function qh(e){return e%2===0}function Ac(e,t){if(e=e.slice(-2),t=t.slice(-2),w.arraysEqual(e,t)||!e.length||!t.length||e[0]===0||e[1]===0||t[0]===0||t[1]===0)return!0;if(e.length!==t.length){let n=e[e.length-1],a=t[t.length-1];if(n===a||qh(n)&&qh(a)&&(e[0]===1||t[0]===1))return!0}return e[1]===t[1]&&qh(e[0])&&qh(t[0])}var Qh,em;function GE(e){if(Qh==null){let t=Ka(e);Qh=t.getParameter(t.MAX_TEXTURE_SIZE)}return Qh}function yJ(){Qh=null}function xJ(){em=null}function HE(e){if(em==null){let t=Ka(e);em=t.getParameter(t.MAX_TEXTURE_IMAGE_UNITS)}return Math.min(16,em)}function qE(e){if(e===0)return 0;let t,n=Ka(e);return ma(n,"EXT_disjoint_timer_query_webgl2")&&e===2?t=2:ma(n,"EXT_disjoint_timer_query")?t=1:t=0,t}function ma(e,t){return e.getExtension(t)!=null}function mv(e){try{if(Ka(e)!=null)return!0}catch(t){return console.log("Error when getting WebGL context: ",t),!1}return!1}function jE(e){if(e===0)return!1;let t=Ka(e);if(e===1){if(!ma(t,"OES_texture_float"))return!1}else if(!ma(t,"EXT_color_buffer_float"))return!1;return fv(t)}function KE(e){if(e===0)return!1;let t=Ka(e);if(e===1){if(!ma(t,"OES_texture_float")||!ma(t,"WEBGL_color_buffer_float"))return!1}else{if(ma(t,"EXT_color_buffer_float"))return fv(t);let n="EXT_color_buffer_half_float";if(ma(t,n)){let a=t.getExtension(n);return vJ(t,a)}return!1}return fv(t)}function fv(e){let t=J1(e),n=e.createTexture();e.bindTexture(e.TEXTURE_2D,n);let a=1,r=1;e.texImage2D(e.TEXTURE_2D,0,t.internalFormatFloat,a,r,0,t.textureFormatFloat,t.textureTypeFloat,null);let s=e.createFramebuffer();e.bindFramebuffer(e.FRAMEBUFFER,s),e.framebufferTexture2D(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0,e.TEXTURE_2D,n,0);let i=e.checkFramebufferStatus(e.FRAMEBUFFER)===e.FRAMEBUFFER_COMPLETE;return e.bindTexture(e.TEXTURE_2D,null),e.bindFramebuffer(e.FRAMEBUFFER,null),e.deleteTexture(n),e.deleteFramebuffer(s),i}function vJ(e,t){let n=J1(e,t),a=e.createTexture();e.bindTexture(e.TEXTURE_2D,a);let r=1,s=1;e.texImage2D(e.TEXTURE_2D,0,n.internalFormatHalfFloat,r,s,0,n.textureFormatFloat,n.textureTypeHalfFloat,null);let i=e.createFramebuffer();e.bindFramebuffer(e.FRAMEBUFFER,i),e.framebufferTexture2D(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0,e.TEXTURE_2D,a,0);let o=e.checkFramebufferStatus(e.FRAMEBUFFER)===e.FRAMEBUFFER_COMPLETE;return e.bindTexture(e.TEXTURE_2D,null),e.bindFramebuffer(e.FRAMEBUFFER,null),e.deleteTexture(a),e.deleteFramebuffer(i),o}function XE(e){return e!==2?!1:Ka(e).fenceSync!=null}function vp(e,t){Array.isArray(e)||(e=[e]),e.forEach(n=>{n!=null&&w.assert(n.dtype!=="complex64",()=>`${t} does not support complex64 tensors in the WebGL backend.`)})}var xe=G();xe.registerFlag("HAS_WEBGL",()=>xe.getNumber("WEBGL_VERSION")>0);xe.registerFlag("WEBGL_VERSION",()=>mv(2)?2:mv(1)?1:0);xe.registerFlag("WEBGL_CHECK_NUMERICAL_PROBLEMS",()=>!1);xe.registerFlag("WEBGL_BUFFER_SUPPORTED",()=>xe.get("WEBGL_VERSION")===2);xe.registerFlag("WEBGL_CPU_FORWARD",()=>!0);xe.registerFlag("WEBGL_FORCE_F16_TEXTURES",()=>!1);xe.registerFlag("WEBGL_PACK",()=>xe.getBool("HAS_WEBGL"));xe.registerFlag("WEBGL_PACK_NORMALIZATION",()=>xe.getBool("WEBGL_PACK"));xe.registerFlag("WEBGL_PACK_CLIP",()=>xe.getBool("WEBGL_PACK"));xe.registerFlag("WEBGL_PACK_DEPTHWISECONV",()=>xe.getBool("WEBGL_PACK"));xe.registerFlag("WEBGL_PACK_BINARY_OPERATIONS",()=>xe.getBool("WEBGL_PACK"));xe.registerFlag("WEBGL_PACK_UNARY_OPERATIONS",()=>xe.getBool("WEBGL_PACK"));xe.registerFlag("WEBGL_PACK_ARRAY_OPERATIONS",()=>xe.getBool("WEBGL_PACK"));xe.registerFlag("WEBGL_PACK_IMAGE_OPERATIONS",()=>xe.getBool("WEBGL_PACK"));xe.registerFlag("WEBGL_PACK_REDUCE",()=>xe.getBool("WEBGL_PACK"));xe.registerFlag("WEBGL_LAZILY_UNPACK",()=>xe.getBool("WEBGL_PACK"));xe.registerFlag("WEBGL_CONV_IM2COL",()=>xe.getBool("WEBGL_PACK"));xe.registerFlag("WEBGL_MAX_TEXTURE_SIZE",()=>GE(xe.getNumber("WEBGL_VERSION")));xe.registerFlag("WEBGL_MAX_TEXTURES_IN_SHADER",()=>HE(xe.getNumber("WEBGL_VERSION")));xe.registerFlag("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION",()=>{let e=xe.getNumber("WEBGL_VERSION");return e===0?0:qE(e)});xe.registerFlag("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE",()=>xe.getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")>0&&!od.isMobile());xe.registerFlag("WEBGL_RENDER_FLOAT32_CAPABLE",()=>jE(xe.getNumber("WEBGL_VERSION")));xe.registerFlag("WEBGL_RENDER_FLOAT32_ENABLED",()=>xe.getBool("WEBGL_FORCE_F16_TEXTURES")?!1:xe.getBool("WEBGL_RENDER_FLOAT32_CAPABLE"));xe.registerFlag("WEBGL_DOWNLOAD_FLOAT_ENABLED",()=>KE(xe.getNumber("WEBGL_VERSION")));xe.registerFlag("WEBGL_FENCE_API_ENABLED",()=>XE(xe.getNumber("WEBGL_VERSION")));xe.registerFlag("WEBGL_SIZE_UPLOAD_UNIFORM",()=>xe.getBool("WEBGL_RENDER_FLOAT32_ENABLED")?4:0);xe.registerFlag("WEBGL_DELETE_TEXTURE_THRESHOLD",()=>-1,e=>{if(e<0&&e!==-1)throw new Error(`WEBGL_DELETE_TEXTURE_THRESHOLD must be -1 (indicating never delete) or at least 0, but got ${e}.`)});xe.registerFlag("WEBGL_FLUSH_THRESHOLD",()=>od.isMobile()?1:-1,e=>{if(e<0&&e!==-1)throw new Error(`WEBGL_FLUSH_THRESHOLD must be -1 (indicating never manual flush) or at least 0, but got ${e}.`)});xe.registerFlag("CPU_HANDOFF_SIZE_THRESHOLD",()=>128);xe.registerFlag("WEBGL_USE_SHAPES_UNIFORMS",()=>!1);xe.registerFlag("TOPK_LAST_DIM_CPU_HANDOFF_SIZE_THRESHOLD",()=>1e5);xe.registerFlag("TOPK_K_CPU_HANDOFF_THRESHOLD",()=>128);xe.registerFlag("WEBGL_EXP_CONV",()=>!1);xe.registerFlag("SOFTWARE_WEBGL_ENABLED",()=>xe.getBool("IS_TEST"));xe.registerFlag("WEBGL_MAX_SIZE_FOR_NARROW_TEXTURE",()=>1/0);xe.registerFlag("WEBGL_AUTO_SQUARIFY_NARROW_TEXTURE_SHAPE",()=>!1);xe.registerFlag("WEBGL2_ISNAN_CUSTOM",()=>!1);xe.registerFlag("ENGINE_COMPILE_ONLY",()=>!1);function En(){let e,t,n,a,r,s,i,o,l,u;return G().getNumber("WEBGL_VERSION")===2?(e="#version 300 es",t="in",n="out",a="in",r="texture",s="outputColor",i="out vec4 outputColor;",o=G().getBool("WEBGL2_ISNAN_CUSTOM")?`
| bool isnan_custom(float val) {
| uint floatToUint = floatBitsToUint(val);
| return (floatToUint & 0x7fffffffu) > 0x7f800000u;
| }
|
| bvec4 isnan_custom(vec4 val) {
| return bvec4(isnan_custom(val.x),
| isnan_custom(val.y), isnan_custom(val.z), isnan_custom(val.w));
| }
|
| #define isnan(value) isnan_custom(value)
| `:"",l="",u=`
| #define round(value) newRound(value)
| int newRound(float value) {
| return int(floor(value + 0.5));
| }
|
| ivec4 newRound(vec4 value) {
| return ivec4(floor(value + vec4(0.5)));
| }
| `):(e="",t="attribute",n="varying",a="varying",r="texture2D",s="gl_FragColor",i="",o=`
| #define isnan(value) isnan_custom(value)
| bool isnan_custom(float val) {
| return (val > 0. || val < 1. || val == 0.) ? false : true;
| }
| bvec4 isnan_custom(vec4 val) {
| return bvec4(isnan(val.x), isnan(val.y), isnan(val.z), isnan(val.w));
| }
| `,l=`
| uniform float INFINITY;
|
| bool isinf(float val) {
| return abs(val) == INFINITY;
| }
| bvec4 isinf(vec4 val) {
| return equal(abs(val), vec4(INFINITY));
| }
| `,u=`
| int round(float value) {
| return int(floor(value + 0.5));
| }
|
| ivec4 round(vec4 value) {
| return ivec4(floor(value + vec4(0.5)));
| }
| `),{version:e,attribute:t,varyingVs:n,varyingFs:a,texture2D:r,output:s,defineOutput:i,defineSpecialNaN:o,defineSpecialInf:l,defineRound:u}}function Jo(e,t,n="index"){let a=w.computeStrides(t);return a.map((r,s)=>{let i=`int ${e[s]} = ${n} / ${r}`,o=s===a.length-1?`int ${e[s+1]} = ${n} - ${e[s]} * ${r}`:`index -= ${e[s]} * ${r}`;return`${i}; ${o};`}).join("")}function Jf(e,t,n="index"){let a=w.computeStrides(t);return a.map((r,s)=>{let i=`int ${e[s]} = ${n} / outShapeStrides[${s}]`,o=s===a.length-1?`int ${e[s+1]} = ${n} - ${e[s]} * outShapeStrides[${s}]`:`index -= ${e[s]} * outShapeStrides[${s}]`;return`${i}; ${o};`}).join("")}function wJ(e,t){let n=e.length,a=e.map(s=>`${t}[${s}]`),r=new Array(n-1);r[n-2]=a[n-1];for(let s=n-3;s>=0;--s)r[s]=`(${r[s+1]} * ${a[s+1]})`;return r}function kJ(e,t,n="index"){let a=e.map((s,i)=>i),r=wJ(a,t);return r.map((s,i)=>{let o=`int ${e[i]} = ${n} / ${r[i]}`,l=i===r.length-1?`int ${e[i+1]} = ${n} - ${e[i]} * ${r[i]}`:`index -= ${e[i]} * ${r[i]}`;return`${o}; ${l};`}).join("")}function ek(e){let t=w.computeStrides(e).map(n=>n.toString());return`
| int getFlatIndex(ivec3 coords) {
| return coords.x * ${t[0]} + coords.y * ${t[1]} + coords.z;
| }
| `}function tk(){return`
| int getFlatIndex(ivec3 coords) {
| return coords.x * outShapeStrides[0] + coords.y * outShapeStrides[1] + coords.z;
| }
| `}var YE=`
| const float FLOAT_MAX = 1.70141184e38;
| const float FLOAT_MIN = 1.17549435e-38;
|
| lowp vec4 encode_float(highp float v) {
| if (isnan(v)) {
| return vec4(255, 255, 255, 255);
| }
|
| highp float av = abs(v);
|
| if(av < FLOAT_MIN) {
| return vec4(0.0, 0.0, 0.0, 0.0);
| } else if(v > FLOAT_MAX) {
| return vec4(0.0, 0.0, 128.0, 127.0) / 255.0;
| } else if(v < -FLOAT_MAX) {
| return vec4(0.0, 0.0, 128.0, 255.0) / 255.0;
| }
|
| highp vec4 c = vec4(0,0,0,0);
|
| highp float e = floor(log2(av));
| highp float m = exp2(fract(log2(av))) - 1.0;
|
| c[2] = floor(128.0 * m);
| m -= c[2] / 128.0;
| c[1] = floor(32768.0 * m);
| m -= c[1] / 32768.0;
| c[0] = floor(8388608.0 * m);
|
| highp float ebias = e + 127.0;
| c[3] = floor(ebias / 2.0);
| ebias -= c[3] * 2.0;
| c[2] += floor(ebias) * 128.0;
|
| c[3] += 128.0 * step(0.0, -v);
|
| return c / 255.0;
| }
| `,{getBroadcastDims:ZE}=N;function IJ(e,t,n){let a=[];if(e.forEach(c=>{let h=w.sizeFromShape(c.shapeInfo.logicalShape);if(c.shapeInfo.isUniform?a.push(`uniform float ${c.name}${h>1?`[${h}]`:""};`):(a.push(`uniform sampler2D ${c.name};`),a.push(`uniform int offset${c.name};`)),n.enableShapeUniforms){let{uniformShape:m}=nk(n.packedInputs,c.shapeInfo.logicalShape,c.shapeInfo.texShape);switch(m.length){case 1:a.push(`uniform int ${c.name}Shape;`);break;case 2:a.push(`uniform ivec2 ${c.name}Shape;`);break;case 3:a.push(`uniform ivec3 ${c.name}Shape;`);break;case 4:a.push(`uniform ivec4 ${c.name}Shape;`);break;default:break}a.push(`uniform ivec2 ${c.name}TexShape;`)}}),n.enableShapeUniforms){switch(t.logicalShape.length){case 1:a.push("uniform int outShape;");break;case 2:a.push("uniform ivec2 outShape;"),a.push("uniform int outShapeStrides;");break;case 3:a.push("uniform ivec3 outShape;"),a.push("uniform ivec2 outShapeStrides;");break;case 4:a.push("uniform ivec4 outShape;"),a.push("uniform ivec3 outShapeStrides;");break;default:break}a.push("uniform ivec2 outTexShape;")}n.customUniforms&&n.customUniforms.forEach(c=>{a.push(`uniform ${c.type} ${c.name}${c.arrayIndex?`[${c.arrayIndex}]`:""};`)});let r=a.join(`
| `),s=e.map(c=>SJ(c,t,n.packedInputs,n.enableShapeUniforms)).join(`
| `),i=t.texShape,o=En(),l=CJ(o),u,p,d=AJ(o);return t.isPacked?(u=NJ(t.logicalShape,i,n.enableShapeUniforms),p=EJ(o)):(u=TJ(t.logicalShape,i,n.enableShapeUniforms),p=_J(o)),n.packedInputs&&(d+=RJ),[d,l,p,r,u,s,n.userCode].join(`
| `)}function wp(e,t=!1){let n=e.shapeInfo.logicalShape;switch(n.length){case 0:return qJ(e,t);case 1:return KJ(e,t);case 2:return YJ(e,t);case 3:return JJ(e,t);case 4:return e9(e,t);case 5:return t9(e);case 6:return n9(e);default:throw new Error(`${n.length}-D input sampling is not yet supported`)}}function JE(e,t){switch(e.shapeInfo.logicalShape.length){case 0:return HJ(e);case 1:return jJ(e,t);case 2:return XJ(e,t);case 3:return ZJ(e,t);default:return QJ(e,t)}}function SJ(e,t,n=!1,a){let r="";n?r+=JE(e,a):r+=wp(e,a);let s=e.shapeInfo.logicalShape,i=t.logicalShape;return s.length<=i.length&&(n?r+=a9(e,t):r+=r9(e,t)),r}function NJ(e,t,n){switch(e.length){case 0:return QE();case 1:return MJ(e,t,n);case 2:return UJ(e,t,n);case 3:return OJ(e,t,n);default:return zJ(e,t,n)}}function TJ(e,t,n){switch(e.length){case 0:return QE();case 1:return PJ(e,t,n);case 2:return GJ(e,t,n);case 3:return LJ(e,t,n);case 4:return WJ(e,t,n);case 5:return BJ(e,t);case 6:return VJ(e,t);default:throw new Error(`${e.length}-D output sampling is not yet supported`)}}function CJ(e){return`
| float sampleTexture(sampler2D textureSampler, vec2 uv) {
| return ${e.texture2D}(textureSampler, uv).r;
| }
| `}function _J(e){return`
| void setOutput(float val) {
| ${e.output} = vec4(val, 0, 0, 0);
| }
| `}function EJ(e){return`
| void setOutput(vec4 val) {
| ${e.output} = val;
| }
| `}function AJ(e){return`${e.version}
| precision highp float;
| precision highp int;
| precision highp sampler2D;
| ${e.varyingFs} vec2 resultUV;
| ${e.defineOutput}
| const vec2 halfCR = vec2(0.5, 0.5);
|
| struct ivec5
| {
| int x;
| int y;
| int z;
| int w;
| int u;
| };
|
| struct ivec6
| {
| int x;
| int y;
| int z;
| int w;
| int u;
| int v;
| };
|
| uniform float NAN;
| ${e.defineSpecialNaN}
| ${e.defineSpecialInf}
| ${e.defineRound}
|
| int imod(int x, int y) {
| return x - y * (x / y);
| }
|
| int idiv(int a, int b, float sign) {
| int res = a / b;
| int mod = imod(a, b);
| if (sign < 0. && mod != 0) {
| res -= 1;
| }
| return res;
| }
|
| //Based on the work of Dave Hoskins
| //https://www.shadertoy.com/view/4djSRW
| #define HASHSCALE1 443.8975
| float random(float seed){
| vec2 p = resultUV * seed;
| vec3 p3 = fract(vec3(p.xyx) * HASHSCALE1);
| p3 += dot(p3, p3.yzx + 19.19);
| return fract((p3.x + p3.y) * p3.z);
| }
|
| ${FJ}
| ${$J}
| ${DJ}
| `}var FJ=`
| vec2 uvFromFlat(int texNumR, int texNumC, int index) {
| int texR = index / texNumC;
| int texC = index - texR * texNumC;
| return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);
| }
| vec2 packedUVfrom1D(int texNumR, int texNumC, int index) {
| int texelIndex = index / 2;
| int texR = texelIndex / texNumC;
| int texC = texelIndex - texR * texNumC;
| return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);
| }
| `,$J=`
| vec2 packedUVfrom2D(int texelsInLogicalRow, int texNumR,
| int texNumC, int row, int col) {
| int texelIndex = (row / 2) * texelsInLogicalRow + (col / 2);
| int texR = texelIndex / texNumC;
| int texC = texelIndex - texR * texNumC;
| return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);
| }
| `,DJ=`
| vec2 packedUVfrom3D(int texNumR, int texNumC,
| int texelsInBatch, int texelsInLogicalRow, int b,
| int row, int col) {
| int index = b * texelsInBatch + (row / 2) * texelsInLogicalRow + (col / 2);
| int texR = index / texNumC;
| int texC = index - texR * texNumC;
| return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);
| }
| `,RJ=`
| float getChannel(vec4 frag, vec2 innerDims) {
| vec2 modCoord = mod(innerDims, 2.);
| return modCoord.x == 0. ?
| (modCoord.y == 0. ? frag.r : frag.g) :
| (modCoord.y == 0. ? frag.b : frag.a);
| }
| float getChannel(vec4 frag, int dim) {
| float modCoord = mod(float(dim), 2.);
| return modCoord == 0. ? frag.r : frag.g;
| }
| `;function QE(){return`
| int getOutputCoords() {
| return 0;
| }
| `}function MJ(e,t,n){let a=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)];return a[0]===1?n?`
| int getOutputCoords() {
| return 2 * int(resultUV.x * ceil(float(outTexShape[1]) / 2.0));
| }
| `:`
| int getOutputCoords() {
| return 2 * int(resultUV.x * ${a[1]}.0);
| }
| `:a[1]===1?n?`
| int getOutputCoords() {
| return 2 * int(resultUV.y * ceil(float(outTexShape[0]) / 2.0));
| }
| `:`
| int getOutputCoords() {
| return 2 * int(resultUV.y * ${a[0]}.0);
| }
| `:n?`
| int getOutputCoords() {
| ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));
| ivec2 resTexRC = ivec2(resultUV.yx *
| vec2(packedTexShape[0], packedTexShape[1]));
| return 2 * (resTexRC.x * packedTexShape[1] + resTexRC.y);
| }
| `:`
| int getOutputCoords() {
| ivec2 resTexRC = ivec2(resultUV.yx *
| vec2(${a[0]}, ${a[1]}));
| return 2 * (resTexRC.x * ${a[1]} + resTexRC.y);
| }
| `}function PJ(e,t,n){return t[0]===1?n?`
| int getOutputCoords() {
| return int(resultUV.x * float(outTexShape[1]));
| }
| `:`
| int getOutputCoords() {
| return int(resultUV.x * ${t[1]}.0);
| }
| `:t[1]===1?n?`
| int getOutputCoords() {
| return int(resultUV.y * float(outTexShape[0]));
| }
| `:`
| int getOutputCoords() {
| return int(resultUV.y * ${t[0]}.0);
| }
| `:n?`
| int getOutputCoords() {
| ivec2 resTexRC = ivec2(resultUV.yx *
| vec2(outTexShape[0], outTexShape[1]));
| return resTexRC.x * outTexShape[1] + resTexRC.y;
| }
| `:`
| int getOutputCoords() {
| ivec2 resTexRC = ivec2(resultUV.yx *
| vec2(${t[0]}, ${t[1]}));
| return resTexRC.x * ${t[1]} + resTexRC.y;
| }
| `}function OJ(e,t,n){if(n)return`
| ivec3 getOutputCoords() {
| ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));
| int texelsInLogicalRow = int(ceil(float(outShape[2]) / 2.0));
| int texelsInBatch = texelsInLogicalRow * int(ceil(float(outShape[1]) / 2.0));
| ivec2 resTexRC = ivec2(resultUV.yx *
| vec2(packedTexShape[0], packedTexShape[1]));
| int index = resTexRC.x * packedTexShape[1] + resTexRC.y;
|
| int b = index / texelsInBatch;
| index -= b * texelsInBatch;
|
| int r = 2 * (index / texelsInLogicalRow);
| int c = imod(index, texelsInLogicalRow) * 2;
|
| return ivec3(b, r, c);
| }
| `;let a=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)],r=Math.ceil(e[2]/2),s=r*Math.ceil(e[1]/2);return`
| ivec3 getOutputCoords() {
| ivec2 resTexRC = ivec2(resultUV.yx *
| vec2(${a[0]}, ${a[1]}));
| int index = resTexRC.x * ${a[1]} + resTexRC.y;
|
| int b = index / ${s};
| index -= b * ${s};
|
| int r = 2 * (index / ${r});
| int c = imod(index, ${r}) * 2;
|
| return ivec3(b, r, c);
| }
| `}function LJ(e,t,n){if(n)return`
| ivec3 getOutputCoords() {
| ivec2 resTexRC = ivec2(resultUV.yx *
| vec2(outTexShape[0], outTexShape[1]));
| int index = resTexRC.x * outTexShape[1] + resTexRC.y;
| ${Jf(["r","c","d"],e)}
| return ivec3(r, c, d);
| }
| `;let a=Jo(["r","c","d"],e);return`
| ivec3 getOutputCoords() {
| ivec2 resTexRC = ivec2(resultUV.yx *
| vec2(${t[0]}, ${t[1]}));
| int index = resTexRC.x * ${t[1]} + resTexRC.y;
| ${a}
| return ivec3(r, c, d);
| }
| `}function zJ(e,t,n){if(n)return`
| ivec4 getOutputCoords() {
| ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));
| ivec2 resTexRC = ivec2(resultUV.yx *
| vec2(packedTexShape[0], packedTexShape[1]));
| int index = resTexRC.x * packedTexShape[1] + resTexRC.y;
|
| int texelsInLogicalRow = int(ceil(float(outShape[3]) / 2.0));
| int texelsInBatch = texelsInLogicalRow * int(ceil(float(outShape[2]) / 2.0));
| int texelsInBatchN = texelsInBatch * outShape[1];
|
| int b2 = index / texelsInBatchN;
| index -= b2 * texelsInBatchN;
|
| int b = index / texelsInBatch;
| index -= b * texelsInBatch;
|
| int r = 2 * (index / texelsInLogicalRow);
| int c = imod(index, texelsInLogicalRow) * 2;
|
| return ivec4(b2, b, r, c);
| }
| `;let a=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)],r=Math.ceil(e[e.length-1]/2),s=r*Math.ceil(e[e.length-2]/2),i=s,o="",l="b, r, c";for(let u=2;u<e.length-1;u++)i*=e[e.length-u-1],o=`
| int b${u} = index / ${i};
| index -= b${u} * ${i};
| `+o,l=`b${u}, `+l;return`
| ivec${e.length} getOutputCoords() {
| ivec2 resTexRC = ivec2(resultUV.yx *
| vec2(${a[0]}, ${a[1]}));
| int index = resTexRC.x * ${a[1]} + resTexRC.y;
|
| ${o}
|
| int b = index / ${s};
| index -= b * ${s};
|
| int r = 2 * (index / ${r});
| int c = imod(index, ${r}) * 2;
|
| return ivec${e.length}(${l});
| }
| `}function WJ(e,t,n){if(n)return`
| ivec4 getOutputCoords() {
| ivec2 resTexRC = ivec2(resultUV.yx *
| vec2(outTexShape[0], outTexShape[1]));
| int index = resTexRC.x * outTexShape[1] + resTexRC.y;
| ${Jf(["r","c","d","d2"],e)}
| return ivec4(r, c, d, d2);
| }
| `;let a=Jo(["r","c","d","d2"],e);return`
| ivec4 getOutputCoords() {
| ivec2 resTexRC = ivec2(resultUV.yx *
| vec2(${t[0]}, ${t[1]}));
| int index = resTexRC.x * ${t[1]} + resTexRC.y;
| ${a}
| return ivec4(r, c, d, d2);
| }
| `}function BJ(e,t){let n=Jo(["r","c","d","d2","d3"],e);return`
| ivec5 getOutputCoords() {
| ivec2 resTexRC = ivec2(resultUV.yx * vec2(${t[0]},
| ${t[1]}));
|
| int index = resTexRC.x * ${t[1]} + resTexRC.y;
|
| ${n}
|
| ivec5 outShape = ivec5(r, c, d, d2, d3);
| return outShape;
| }
| `}function VJ(e,t){let n=Jo(["r","c","d","d2","d3","d4"],e);return`
| ivec6 getOutputCoords() {
| ivec2 resTexRC = ivec2(resultUV.yx *
| vec2(${t[0]}, ${t[1]}));
| int index = resTexRC.x * ${t[1]} + resTexRC.y;
|
| ${n}
|
| ivec6 result = ivec6(r, c, d, d2, d3, d4);
| return result;
| }
| `}function UJ(e,t,n){let a=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)];if(w.arraysEqual(e,t))return n?`
| ivec2 getOutputCoords() {
| ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));
| return 2 * ivec2(resultUV.yx * vec2(packedTexShape[0], packedTexShape[1]));
| }
| `:`
| ivec2 getOutputCoords() {
| return 2 * ivec2(resultUV.yx * vec2(${a[0]}, ${a[1]}));
| }
| `;let r=Math.ceil(e[1]/2);return n?`
| ivec2 getOutputCoords() {
| ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));
| int texelsInLogicalRow = int(ceil(float(outShape[1]) / 2.0));
| ivec2 resTexRC = ivec2(resultUV.yx *
| vec2(packedTexShape[0], packedTexShape[1]));
|
| int index = resTexRC.x * packedTexShape[1] + resTexRC.y;
| int r = 2 * (index / texelsInLogicalRow);
| int c = imod(index, texelsInLogicalRow) * 2;
|
| return ivec2(r, c);
| }
| `:`
| ivec2 getOutputCoords() {
| ivec2 resTexRC = ivec2(resultUV.yx *
| vec2(${a[0]}, ${a[1]}));
|
| int index = resTexRC.x * ${a[1]} + resTexRC.y;
| int r = 2 * (index / ${r});
| int c = imod(index, ${r}) * 2;
|
| return ivec2(r, c);
| }
| `}function GJ(e,t,n){return w.arraysEqual(e,t)?n?`
| ivec2 getOutputCoords() {
| return ivec2(resultUV.yx * vec2(outTexShape[0], outTexShape[1]));
| }
| `:`
| ivec2 getOutputCoords() {
| return ivec2(resultUV.yx * vec2(${t[0]}, ${t[1]}));
| }
| `:e[1]===1?n?`
| ivec2 getOutputCoords() {
| ivec2 resTexRC = ivec2(resultUV.yx *
| vec2(outTexShape[0], outTexShape[1]));
| int index = resTexRC.x * outTexShape[1] + resTexRC.y;
| return ivec2(index, 0);
| }
| `:`
| ivec2 getOutputCoords() {
| ivec2 resTexRC = ivec2(resultUV.yx *
| vec2(${t[0]}, ${t[1]}));
| int index = resTexRC.x * ${t[1]} + resTexRC.y;
| return ivec2(index, 0);
| }
| `:e[0]===1?n?`
| ivec2 getOutputCoords() {
| ivec2 resTexRC = ivec2(resultUV.yx *
| vec2(outTexShape[0], outTexShape[1]));
| int index = resTexRC.x * outTexShape[1] + resTexRC.y;
| return ivec2(0, index);
| }
| `:`
| ivec2 getOutputCoords() {
| ivec2 resTexRC = ivec2(resultUV.yx *
| vec2(${t[0]}, ${t[1]}));
| int index = resTexRC.x * ${t[1]} + resTexRC.y;
| return ivec2(0, index);
| }
| `:n?`
| ivec2 getOutputCoords() {
| ivec2 resTexRC = ivec2(resultUV.yx *
| vec2(outTexShape[0], outTexShape[1]));
| int index = resTexRC.x * outTexShape[1] + resTexRC.y;
| int r = index / outShape[1];
| int c = index - r * outShape[1];
| return ivec2(r, c);
| }
| `:`
| ivec2 getOutputCoords() {
| ivec2 resTexRC = ivec2(resultUV.yx *
| vec2(${t[0]}, ${t[1]}));
| int index = resTexRC.x * ${t[1]} + resTexRC.y;
| int r = index / ${e[1]};
| int c = index - r * ${e[1]};
| return ivec2(r, c);
| }
| `}function Qo(e){return`offset${e}`}function HJ(e){let t=e.name,n="get"+t.charAt(0).toUpperCase()+t.slice(1),a=En();return`
| vec4 ${n}() {
| return ${a.texture2D}(${t}, halfCR);
| }
| `}function qJ(e,t){let n=e.name,a="get"+n.charAt(0).toUpperCase()+n.slice(1);if(e.shapeInfo.isUniform)return`float ${a}() {return ${n};}`;let[r,s]=e.shapeInfo.texShape;if(r===1&&s===1)return`
| float ${a}() {
| return sampleTexture(${n}, halfCR);
| }
| `;let i=Qo(n);if(t)return`
| float ${a}() {
| vec2 uv = uvFromFlat(${n}TexShape[0], ${n}TexShape[1], ${i});
| return sampleTexture(${n}, uv);
| }
| `;let[o,l]=e.shapeInfo.texShape;return`
| float ${a}() {
| vec2 uv = uvFromFlat(${o}, ${l}, ${i});
| return sampleTexture(${n}, uv);
| }
| `}function jJ(e,t){let n=e.name,a="get"+n.charAt(0).toUpperCase()+n.slice(1),r=e.shapeInfo.texShape,s=En();if(t)return`
| vec4 ${a}(int index) {
| ivec2 packedTexShape = ivec2(ceil(float(${n}TexShape[0]) / 2.0), ceil(float(${n}TexShape[1]) / 2.0));
| vec2 uv = packedUVfrom1D(
| packedTexShape[0], packedTexShape[1], index);
| return ${s.texture2D}(${n}, uv);
| }
| `;let i=[Math.ceil(r[0]/2),Math.ceil(r[1]/2)];return`
| vec4 ${a}(int index) {
| vec2 uv = packedUVfrom1D(
| ${i[0]}, ${i[1]}, index);
| return ${s.texture2D}(${n}, uv);
| }
| `}function KJ(e,t){let n=e.name,a="get"+n.charAt(0).toUpperCase()+n.slice(1);if(e.shapeInfo.isUniform)return`
| float ${a}(int index) {
| ${kp(e)}
| }
| `;let r=e.shapeInfo.texShape,s=r[0],i=r[1];if(i===1&&s===1)return`
| float ${a}(int index) {
| return sampleTexture(${n}, halfCR);
| }
| `;let o=Qo(n);return i===1?t?`
| float ${a}(int index) {
| vec2 uv = vec2(0.5, (float(index + ${o}) + 0.5) / float(${n}TexShape[0]));
| return sampleTexture(${n}, uv);
| }
| `:`
| float ${a}(int index) {
| vec2 uv = vec2(0.5, (float(index + ${o}) + 0.5) / ${s}.0);
| return sampleTexture(${n}, uv);
| }
| `:s===1?t?`
| float ${a}(int index) {
| vec2 uv = vec2((float(index + ${o}) + 0.5) / float(${n}TexShape[1]), 0.5);
| return sampleTexture(${n}, uv);
| }
| `:`
| float ${a}(int index) {
| vec2 uv = vec2((float(index + ${o}) + 0.5) / ${i}.0, 0.5);
| return sampleTexture(${n}, uv);
| }
| `:t?`
| float ${a}(int index) {
| vec2 uv = uvFromFlat(${n}TexShape[0], ${n}TexShape[1], index + ${o});
| return sampleTexture(${n}, uv);
| }
| `:`
| float ${a}(int index) {
| vec2 uv = uvFromFlat(${s}, ${i}, index + ${o});
| return sampleTexture(${n}, uv);
| }
| `}function XJ(e,t){let n=e.shapeInfo.logicalShape,a=e.name,r="get"+a.charAt(0).toUpperCase()+a.slice(1),s=e.shapeInfo.texShape,i=s[0],o=s[1],l=En();if(s!=null&&w.arraysEqual(n,s))return t?`
| vec4 ${r}(int row, int col) {
| vec2 uv = (vec2(col, row) + halfCR) / vec2(${a}TexShape[1], ${a}TexShape[0]);
|
| return ${l.texture2D}(${a}, uv);
| }
| `:`
| vec4 ${r}(int row, int col) {
| vec2 uv = (vec2(col, row) + halfCR) / vec2(${o}.0, ${i}.0);
|
| return ${l.texture2D}(${a}, uv);
| }
| `;if(t)return`
| vec4 ${r}(int row, int col) {
| ivec2 packedTexShape = ivec2(ceil(float(${a}TexShape[0]) / 2.0), ceil(float(${a}TexShape[1]) / 2.0));
| int valuesPerRow = int(ceil(float(${a}Shape[1]) / 2.0));
| vec2 uv = packedUVfrom2D(valuesPerRow, packedTexShape[0], packedTexShape[1], row, col);
| return ${l.texture2D}(${a}, uv);
| }
| `;let u=[Math.ceil(s[0]/2),Math.ceil(s[1]/2)],p=Math.ceil(n[1]/2);return`
| vec4 ${r}(int row, int col) {
| vec2 uv = packedUVfrom2D(${p}, ${u[0]}, ${u[1]}, row, col);
| return ${l.texture2D}(${a}, uv);
| }
| `}function YJ(e,t){let n=e.shapeInfo.logicalShape,a=e.name,r="get"+a.charAt(0).toUpperCase()+a.slice(1),s=e.shapeInfo.texShape;if(s!=null&&w.arraysEqual(n,s)){if(t)return`
| float ${r}(int row, int col) {
| vec2 uv = (vec2(col, row) + halfCR) / vec2(${a}TexShape[1], ${a}TexShape[0]);
| return sampleTexture(${a}, uv);
| }
| `;let c=s[0],h=s[1];return`
| float ${r}(int row, int col) {
| vec2 uv = (vec2(col, row) + halfCR) / vec2(${h}.0, ${c}.0);
| return sampleTexture(${a}, uv);
| }
| `}let{newShape:i,keptDims:o}=w.squeezeShape(n),l=i;if(l.length<n.length){let c=Ip(e,l),h=["row","col"];return`
| ${wp(c,t)}
| float ${r}(int row, int col) {
| return ${r}(${Sp(h,o)});
| }
| `}if(e.shapeInfo.isUniform)return`
| float ${r}(int row, int col) {
| int index = round(dot(vec2(row, col), vec2(${n[1]}, 1)));
| ${kp(e)}
| }
| `;let u=s[0],p=s[1],d=Qo(a);return p===1?t?`
| float ${r}(int row, int col) {
| float index = dot(vec3(row, col, ${d}), vec3(${a}Shape[1], 1, 1));
| vec2 uv = vec2(0.5, (index + 0.5) / float(${a}TexShape[0]));
| return sampleTexture(${a}, uv);
| }
| `:`
| float ${r}(int row, int col) {
| float index = dot(vec3(row, col, ${d}), vec3(${n[1]}, 1, 1));
| vec2 uv = vec2(0.5, (index + 0.5) / ${u}.0);
| return sampleTexture(${a}, uv);
| }
| `:u===1?t?`
| float ${r}(int row, int col) {
| float index = dot(vec3(row, col, ${d}), vec3(${a}Shape[1], 1, 1));
| vec2 uv = vec2((index + 0.5) / float(${a}TexShape[1]), 0.5);
| return sampleTexture(${a}, uv);
| }
| `:`
| float ${r}(int row, int col) {
| float index = dot(vec3(row, col, ${d}), vec3(${n[1]}, 1, 1));
| vec2 uv = vec2((index + 0.5) / ${p}.0, 0.5);
| return sampleTexture(${a}, uv);
| }
| `:t?`
| float ${r}(int row, int col) {
| // Explicitly use integer operations as dot() only works on floats.
| int index = row * ${a}Shape[1] + col + ${d};
| vec2 uv = uvFromFlat(${a}TexShape[0], ${a}TexShape[1], index);
| return sampleTexture(${a}, uv);
| }
| `:`
| float ${r}(int row, int col) {
| // Explicitly use integer operations as dot() only works on floats.
| int index = row * ${n[1]} + col + ${d};
| vec2 uv = uvFromFlat(${u}, ${p}, index);
| return sampleTexture(${a}, uv);
| }
| `}function ZJ(e,t){let n=e.shapeInfo.logicalShape,a=e.name,r="get"+a.charAt(0).toUpperCase()+a.slice(1),s=e.shapeInfo.texShape,i=[Math.ceil(s[0]/2),Math.ceil(s[1]/2)];if(n[0]===1){let c=n.slice(1),h=[1,2],m=Ip(e,c),f=["b","row","col"];return`
| ${JE(m,t)}
| vec4 ${r}(int b, int row, int col) {
| return ${r}(${Sp(f,h)});
| }
| `}let o=En();if(t)return`
| vec4 ${r}(int b, int row, int col) {
| ivec2 packedTexShape = ivec2(ceil(float(${a}TexShape[0]) / 2.0), ceil(float(${a}TexShape[1]) / 2.0));
| int valuesPerRow = int(ceil(float(${a}Shape[2]) / 2.0));
| int texelsInBatch = valuesPerRow * int(ceil(float(${a}Shape[1]) / 2.0));
| vec2 uv = packedUVfrom3D(
| packedTexShape[0], packedTexShape[1], texelsInBatch, valuesPerRow, b, row, col);
| return ${o.texture2D}(${a}, uv);
| }
| `;let l=i[0],u=i[1],p=Math.ceil(n[2]/2),d=p*Math.ceil(n[1]/2);return`
| vec4 ${r}(int b, int row, int col) {
| vec2 uv = packedUVfrom3D(
| ${l}, ${u}, ${d}, ${p}, b, row, col);
| return ${o.texture2D}(${a}, uv);
| }
| `}function JJ(e,t){let n=e.shapeInfo.logicalShape,a=e.name,r="get"+a.charAt(0).toUpperCase()+a.slice(1),s=n[1]*n[2],i=n[2],{newShape:o,keptDims:l}=w.squeezeShape(n),u=o;if(u.length<n.length){let f=Ip(e,u),g=["row","col","depth"];return`
| ${wp(f,t)}
| float ${r}(int row, int col, int depth) {
| return ${r}(${Sp(g,l)});
| }
| `}if(e.shapeInfo.isUniform)return`
| float ${r}(int row, int col, int depth) {
| int index = round(dot(vec3(row, col, depth),
| vec3(${s}, ${i}, 1)));
| ${kp(e)}
| }
| `;let p=e.shapeInfo.texShape,d=p[0],c=p[1],h=e.shapeInfo.flatOffset;if(c===s&&h==null)return t?`
| float ${r}(int row, int col, int depth) {
| int stride1 = ${a}Shape[2];
| float texR = float(row);
| float texC = dot(vec2(col, depth), vec2(stride1, 1));
| vec2 uv = (vec2(texC, texR) + halfCR) /
| vec2(${a}TexShape[1], ${a}TexShape[0]);
| return sampleTexture(${a}, uv);
| }
| `:`
| float ${r}(int row, int col, int depth) {
| float texR = float(row);
| float texC = dot(vec2(col, depth), vec2(${i}, 1));
| vec2 uv = (vec2(texC, texR) + halfCR) /
| vec2(${c}.0, ${d}.0);
| return sampleTexture(${a}, uv);
| }
| `;if(c===i&&h==null)return t?`
| float ${r}(int row, int col, int depth) {
| float texR = dot(vec2(row, col), vec2(${a}Shape[1], 1));
| float texC = float(depth);
| vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${a}TexShape[1], ${a}TexShape[0]);
| return sampleTexture(${a}, uv);
| }
| `:`
| float ${r}(int row, int col, int depth) {
| float texR = dot(vec2(row, col), vec2(${n[1]}, 1));
| float texC = float(depth);
| vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${c}.0, ${d}.0);
| return sampleTexture(${a}, uv);
| }
| `;let m=Qo(a);return t?`
| float ${r}(int row, int col, int depth) {
| // Explicitly use integer operations as dot() only works on floats.
| int stride0 = ${a}Shape[1] * ${a}Shape[2];
| int stride1 = ${a}Shape[2];
| int index = row * stride0 + col * stride1 + depth + ${m};
| vec2 uv = uvFromFlat(${a}TexShape[0], ${a}TexShape[1], index);
| return sampleTexture(${a}, uv);
| }
| `:`
| float ${r}(int row, int col, int depth) {
| // Explicitly use integer operations as dot() only works on floats.
| int index = row * ${s} + col * ${i} + depth + ${m};
| vec2 uv = uvFromFlat(${d}, ${c}, index);
| return sampleTexture(${a}, uv);
| }
| `}function QJ(e,t){let n=e.name,a="get"+n.charAt(0).toUpperCase()+n.slice(1),r=En();if(t)return`
| vec4 ${a}(int b2, int b, int row, int col) {
| int valuesPerRow = int(ceil(float(${n}Shape[3]) / 2.0));
| int texelsInBatch = valuesPerRow * int(ceil(float(${n}Shape[2]) / 2.0));
| int index = b * texelsInBatch + (row / 2) * valuesPerRow + (col / 2);
| texelsInBatch *= ${n}Shape[1];
| index = b2 * texelsInBatch + index;
| ivec2 packedTexShape = ivec2(ceil(float(${n}TexShape[0]) / 2.0), ceil(float(${n}TexShape[1]) / 2.0));
| int texR = index / packedTexShape[1];
| int texC = index - texR * packedTexShape[1];
| vec2 uv = (vec2(texC, texR) + halfCR) / vec2(packedTexShape[1], packedTexShape[0]); return ${r.texture2D}(${n}, uv);
| }
| `;let s=e.shapeInfo.logicalShape,i=s.length,o=e.shapeInfo.texShape,l=[Math.ceil(o[0]/2),Math.ceil(o[1]/2)],u=l[0],p=l[1],d=Math.ceil(s[i-1]/2),c=d*Math.ceil(s[i-2]/2),h="int b, int row, int col",m=`b * ${c} + (row / 2) * ${d} + (col / 2)`;for(let f=2;f<i-1;f++)h=`int b${f}, `+h,c*=s[i-f-1],m=`b${f} * ${c} + `+m;return`
| vec4 ${a}(${h}) {
| int index = ${m};
| int texR = index / ${p};
| int texC = index - texR * ${p};
| vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${p}, ${u});
| return ${r.texture2D}(${n}, uv);
| }
| `}function e9(e,t){let n=e.shapeInfo.logicalShape,a=e.name,r="get"+a.charAt(0).toUpperCase()+a.slice(1),s=n[3],i=n[2]*s,o=n[1]*i,{newShape:l,keptDims:u}=w.squeezeShape(n);if(l.length<n.length){let y=Ip(e,l),x=["row","col","depth","depth2"];return`
| ${wp(y,t)}
| float ${r}(int row, int col, int depth, int depth2) {
| return ${r}(${Sp(x,u)});
| }
| `}if(e.shapeInfo.isUniform)return`
| float ${r}(int row, int col, int depth, int depth2) {
| int index = round(dot(vec4(row, col, depth, depth2),
| vec4(${o}, ${i}, ${s}, 1)));
| ${kp(e)}
| }
| `;let p=e.shapeInfo.flatOffset,d=e.shapeInfo.texShape,c=d[0],h=d[1],m=`int stride2 = ${a}Shape[3];`,f=`int stride1 = ${a}Shape[2] * stride2;`,g=`int stride0 = ${a}Shape[1] * stride1;`;if(h===o&&p==null)return t?`
| float ${r}(int row, int col, int depth, int depth2) {
| ${m}
| ${f}
| float texR = float(row);
| float texC =
| dot(vec3(col, depth, depth2),
| vec3(stride1, stride2, 1));
| vec2 uv = (vec2(texC, texR) + halfCR) /
| vec2(${a}TexShape[1], ${a}TexShape[0]);
| return sampleTexture(${a}, uv);
| }
| `:`
| float ${r}(int row, int col, int depth, int depth2) {
| float texR = float(row);
| float texC =
| dot(vec3(col, depth, depth2),
| vec3(${i}, ${s}, 1));
| vec2 uv = (vec2(texC, texR) + halfCR) /
| vec2(${h}.0, ${c}.0);
| return sampleTexture(${a}, uv);
| }
| `;if(h===s&&p==null)return t?`
| float ${r}(int row, int col, int depth, int depth2) {
| float texR = dot(vec3(row, col, depth),
| vec3(${a}Shape[1] * ${a}Shape[2], ${a}Shape[2], 1));
| float texC = float(depth2);
| vec2 uv = (vec2(texC, texR) + halfCR) /
| vec2(${a}TexShape[1], ${a}TexShape[0]);
| return sampleTexture(${a}, uv);
| }
| `:`
| float ${r}(int row, int col, int depth, int depth2) {
| float texR = dot(vec3(row, col, depth),
| vec3(${n[1]*n[2]}, ${n[2]}, 1));
| float texC = float(depth2);
| vec2 uv = (vec2(texC, texR) + halfCR) /
| vec2(${h}.0, ${c}.0);
| return sampleTexture(${a}, uv);
| }
| `;let b=Qo(a);return t?`
| float ${r}(int row, int col, int depth, int depth2) {
| // Explicitly use integer operations as dot() only works on floats.
| ${m}
| ${f}
| ${g}
| int index = row * stride0 + col * stride1 +
| depth * stride2 + depth2;
| vec2 uv = uvFromFlat(${a}TexShape[0], ${a}TexShape[1], index + ${b});
| return sampleTexture(${a}, uv);
| }
| `:`
| float ${r}(int row, int col, int depth, int depth2) {
| // Explicitly use integer operations as dot() only works on floats.
| int index = row * ${o} + col * ${i} +
| depth * ${s} + depth2;
| vec2 uv = uvFromFlat(${c}, ${h}, index + ${b});
| return sampleTexture(${a}, uv);
| }
| `}function t9(e){let t=e.shapeInfo.logicalShape,n=e.name,a="get"+n.charAt(0).toUpperCase()+n.slice(1),r=t[4],s=t[3]*r,i=t[2]*s,o=t[1]*i,{newShape:l,keptDims:u}=w.squeezeShape(t);if(l.length<t.length){let f=Ip(e,l),g=["row","col","depth","depth2","depth3"];return`
| ${wp(f)}
| float ${a}(int row, int col, int depth, int depth2, int depth3) {
| return ${a}(${Sp(g,u)});
| }
| `}if(e.shapeInfo.isUniform)return`
| float ${a}(int row, int col, int depth, int depth2, int depth3) {
| float index = dot(
| vec4(row, col, depth, depth2),
| vec4(${o}, ${i}, ${s}, ${r})) +
| depth3;
| ${kp(e)}
| }
| `;let p=e.shapeInfo.flatOffset,d=e.shapeInfo.texShape,c=d[0],h=d[1];if(h===o&&p==null)return`
| float ${a}(int row, int col, int depth, int depth2, int depth3) {
| int texR = row;
| float texC = dot(vec4(col, depth, depth2, depth3),
| vec4(${i}, ${s}, ${r}, 1));
| vec2 uv = (vec2(texC, texR) + halfCR) /
| vec2(${h}.0, ${c}.0);
| return sampleTexture(${n}, uv);
| }
| `;if(h===r&&p==null)return`
| float ${a}(int row, int col, int depth, int depth2, int depth3) {
| float texR = dot(
| vec4(row, col, depth, depth2),
| vec4(${t[1]*t[2]*t[3]},
| ${t[2]*t[3]}, ${t[3]}, 1));
| int texC = depth3;
| vec2 uv = (vec2(texC, texR) + halfCR) /
| vec2(${h}.0, ${c}.0);
| return sampleTexture(${n}, uv);
| }
| `;let m=Qo(n);return`
| float ${a}(int row, int col, int depth, int depth2, int depth3) {
| // Explicitly use integer operations as dot() only works on floats.
| int index = row * ${o} + col * ${i} + depth * ${s} +
| depth2 * ${r} + depth3 + ${m};
| vec2 uv = uvFromFlat(${c}, ${h}, index);
| return sampleTexture(${n}, uv);
| }
| `}function n9(e){let t=e.shapeInfo.logicalShape,n=e.name,a="get"+n.charAt(0).toUpperCase()+n.slice(1),{newShape:r,keptDims:s}=w.squeezeShape(t);if(r.length<t.length){let g=Ip(e,r),b=["row","col","depth","depth2","depth3","depth4"];return`
| ${wp(g)}
| float ${a}(int row, int col, int depth,
| int depth2, int depth3, int depth4) {
| return ${a}(${Sp(b,s)});
| }
| `}let i=t[5],o=t[4]*i,l=t[3]*o,u=t[2]*l,p=t[1]*u;if(e.shapeInfo.isUniform)return`
| float ${a}(int row, int col, int depth,
| int depth2, int depth3, int depth4) {
| int index = round(dot(
| vec4(row, col, depth, depth2),
| vec4(${p}, ${u}, ${l}, ${o})) +
| dot(
| vec2(depth3, depth4),
| vec2(${i}, 1)));
| ${kp(e)}
| }
| `;let d=e.shapeInfo.flatOffset,c=e.shapeInfo.texShape,h=c[0],m=c[1];if(m===p&&d==null)return`
| float ${a}(int row, int col, int depth,
| int depth2, int depth3, int depth4) {
| int texR = row;
| float texC = dot(vec4(col, depth, depth2, depth3),
| vec4(${u}, ${l}, ${o}, ${i})) +
| float(depth4);
| vec2 uv = (vec2(texC, texR) + halfCR) /
| vec2(${m}.0, ${h}.0);
| return sampleTexture(${n}, uv);
| }
| `;if(m===i&&d==null)return`
| float ${a}(int row, int col, int depth,
| int depth2, int depth3, int depth4) {
| float texR = dot(vec4(row, col, depth, depth2),
| vec4(${t[1]*t[2]*t[3]*t[4]},
| ${t[2]*t[3]*t[4]},
| ${t[3]*t[4]},
| ${t[4]})) + float(depth3);
| int texC = depth4;
| vec2 uv = (vec2(texC, texR) + halfCR) /
| vec2(${m}.0, ${h}.0);
| return sampleTexture(${n}, uv);
| }
| `;let f=Qo(n);return`
| float ${a}(int row, int col, int depth,
| int depth2, int depth3, int depth4) {
| // Explicitly use integer operations as dot() only works on floats.
| int index = row * ${p} + col * ${u} + depth * ${l} +
| depth2 * ${o} + depth3 * ${i} + depth4 + ${f};
| vec2 uv = uvFromFlat(${h}, ${m}, index);
| return sampleTexture(${n}, uv);
| }
| `}function kp(e){let t=e.name,n=w.sizeFromShape(e.shapeInfo.logicalShape);return n<2?`return ${t};`:`
| for (int i = 0; i < ${n}; i++) {
| if (i == index) {
| return ${t}[i];
| }
| }
| `}function a9(e,t){let n=e.name,a=n.charAt(0).toUpperCase()+n.slice(1),r="get"+a+"AtOutCoords",s=e.shapeInfo.logicalShape.length,i=t.logicalShape.length,o=ZE(e.shapeInfo.logicalShape,t.logicalShape),l=dt(i),u=i-s,p,d=["x","y","z","w","u","v"];s===0?p="":i<2&&o.length>=1?p="coords = 0;":p=o.map(g=>`coords.${d[g+u]} = 0;`).join(`
| `);let c="";i<2&&s>0?c="coords":c=e.shapeInfo.logicalShape.map((g,b)=>`coords.${d[b+u]}`).join(", ");let h="return outputValue;",m=w.sizeFromShape(e.shapeInfo.logicalShape)===1,f=w.sizeFromShape(t.logicalShape)===1;if(s===1&&!m&&!f)h=`
| return vec4(outputValue.xy, outputValue.xy);
| `;else if(m&&!f)i===1?h=`
| return vec4(outputValue.x, outputValue.x, 0., 0.);
| `:h=`
| return vec4(outputValue.x);
| `;else if(o.length){let g=s-2,b=s-1;o.indexOf(g)>-1&&o.indexOf(b)>-1?h="return vec4(outputValue.x);":o.indexOf(g)>-1?h="return vec4(outputValue.x, outputValue.y, outputValue.x, outputValue.y);":o.indexOf(b)>-1&&(h="return vec4(outputValue.xx, outputValue.zz);")}return`
| vec4 ${r}() {
| ${l} coords = getOutputCoords();
| ${p}
| vec4 outputValue = get${a}(${c});
| ${h}
| }
| `}function r9(e,t){let n=e.name,a=n.charAt(0).toUpperCase()+n.slice(1),r="get"+a+"AtOutCoords",s=t.texShape,i=e.shapeInfo.texShape,o=e.shapeInfo.logicalShape.length,l=t.logicalShape.length;if(!e.shapeInfo.isUniform&&o===l&&e.shapeInfo.flatOffset==null&&w.arraysEqual(i,s))return`
| float ${r}() {
| return sampleTexture(${n}, resultUV);
| }
| `;let u=dt(l),p=ZE(e.shapeInfo.logicalShape,t.logicalShape),d=l-o,c,h=["x","y","z","w","u","v"];o===0?c="":l<2&&p.length>=1?c="coords = 0;":c=p.map(f=>`coords.${h[f+d]} = 0;`).join(`
| `);let m="";return l<2&&o>0?m="coords":m=e.shapeInfo.logicalShape.map((f,g)=>`coords.${h[g+d]}`).join(", "),`
| float ${r}() {
| ${u} coords = getOutputCoords();
| ${c}
| return get${a}(${m});
| }
| `}function dt(e){if(e<=1)return"int";if(e===2)return"ivec2";if(e===3)return"ivec3";if(e===4)return"ivec4";if(e===5)return"ivec5";if(e===6)return"ivec6";throw Error(`GPU for rank ${e} is not yet supported`)}function nk(e,t,n){let{newShape:a,keptDims:r}=w.squeezeShape(t),s=t.length,i=e&&s===3&&t[0]===1,o=i?t.slice(1):a,l=!e&&s>1&&!w.arraysEqual(t,n)&&a.length<s||i;return{useSqueezeShape:l,uniformShape:l?o:t,keptDims:r}}function Ip(e,t){let n=JSON.parse(JSON.stringify(e));return n.shapeInfo.logicalShape=t,n}function Sp(e,t){return t.map(n=>e[n]).join(", ")}function s9(e,t,n,a){let r=n.map((p,d)=>{let c={logicalShape:p.shape,texShape:p.isUniform?null:p.texData.texShape,isUniform:p.isUniform,isPacked:p.isUniform?!1:p.texData.isPacked,flatOffset:null};return p.texData!=null&&p.texData.slice!=null&&p.texData.slice.flatOffset>0&&(c.flatOffset=p.texData.slice.flatOffset),{name:t.variableNames[d],shapeInfo:c}}),s=r.map(p=>p.shapeInfo),i={logicalShape:a.shape,texShape:a.texData.texShape,isUniform:!1,isPacked:a.texData.isPacked,flatOffset:null},o=IJ(r,i,t),l=EE(e.gl,o),u=e.createProgram(l);return G().get("ENGINE_COMPILE_ONLY")?{program:t,fragmentShader:l,source:o,webGLProgram:u,inShapeInfos:s,outShapeInfo:i,variablesLocations:null,customUniformLocations:null,infLoc:null,nanLoc:null,outShapeLocation:null,outShapeStridesLocation:null,outTexShapeLocation:null}:(e.buildVao(u),Object.assign({program:t,fragmentShader:l,source:o,webGLProgram:u,inShapeInfos:s,outShapeInfo:i},eA(e,t,u)))}function eA(e,t,n){let a=[],r=[],s,i,o,l=null,u=null;u=e.getUniformLocation(n,"NAN",!1),G().getNumber("WEBGL_VERSION")===1&&(l=e.getUniformLocation(n,"INFINITY",!1));let p=!1;for(let d of t.variableNames){let c={name:d,uniform:e.getUniformLocation(n,d,p),offset:e.getUniformLocation(n,`offset${d}`,p)};t.enableShapeUniforms&&(c.shape=e.getUniformLocation(n,`${d}Shape`,p),c.texShape=e.getUniformLocation(n,`${d}TexShape`,p)),a.push(c)}if(t.enableShapeUniforms&&(s=e.getUniformLocation(n,"outShape",p),o=e.getUniformLocation(n,"outShapeStrides",p),i=e.getUniformLocation(n,"outTexShape",p)),t.customUniforms)for(let d of t.customUniforms)r.push(e.getUniformLocation(n,d.name,p));return{variablesLocations:a,customUniformLocations:r,infLoc:l,nanLoc:u,outShapeLocation:s,outShapeStridesLocation:o,outTexShapeLocation:i}}function mS(e,t){if(e.length!==t.length)throw Error(`Binary was compiled with ${e.length} inputs, but was executed with ${t.length} inputs`);e.forEach((n,a)=>{let r=n.logicalShape,s=t[a],i=s.shape;if(!w.arraysEqual(r,i))throw Error(`Binary was compiled with different shapes than the current args. Shapes ${r} and ${i} must match`);if(n.isUniform&&s.isUniform)return;let o=n.texShape,l=s.isUniform?null:s.texData.texShape;if(!w.arraysEqual(o,l))throw Error(`Binary was compiled with different texture shapes than the current args. Shape ${o} and ${l} must match`)})}function i9(e,t,n,a,r){t.program.enableShapeUniforms||(mS(t.inShapeInfos,n),mS([t.outShapeInfo],[a]));let s=a.texData.texture,i=a.texData.texShape;a.texData.isPacked?e.setOutputPackedMatrixTexture(s.texture,i[0],i[1]):e.setOutputMatrixTexture(s.texture,i[0],i[1]),e.setProgram(t.webGLProgram),e.bindVertexArray(t.webGLProgram.vao),G().getNumber("WEBGL_VERSION")===1&&t.infLoc!==null&&e.gl.uniform1f(t.infLoc,1/0),t.nanLoc!==null&&e.gl.uniform1f(t.nanLoc,NaN);for(let l=0;l<n.length;++l){let u=n[l],{uniform:p,offset:d,shape:c,texShape:h}=t.variablesLocations[l];if(c){let{uniformShape:m}=nk(t.program.packedInputs,u.shape,u.texData.texShape);switch(m.length){case 1:e.gl.uniform1iv(c,new Int32Array(m));break;case 2:e.gl.uniform2iv(c,new Int32Array(m));break;case 3:e.gl.uniform3iv(c,new Int32Array(m));break;case 4:e.gl.uniform4iv(c,new Int32Array(m));break;default:break}}if(h&&e.gl.uniform2i(h,u.texData.texShape[0],u.texData.texShape[1]),p!=null){if(u.isUniform){if(w.sizeFromShape(u.shape)<2)e.gl.uniform1f(p,u.uniformValues[0]);else{let m=u.uniformValues;m instanceof Float32Array||(m=new Float32Array(m)),e.gl.uniform1fv(p,m)}continue}u.texData.slice!=null&&d!=null&&e.gl.uniform1i(d,u.texData.slice.flatOffset),e.setInputMatrixTexture(u.texData.texture.texture,p,l)}}let o=t.outShapeLocation;if(o)switch(a.shape.length){case 1:e.gl.uniform1iv(o,new Int32Array(a.shape));break;case 2:e.gl.uniform2iv(o,new Int32Array(a.shape));break;case 3:e.gl.uniform3iv(o,new Int32Array(a.shape));break;case 4:e.gl.uniform4iv(o,new Int32Array(a.shape));break;default:break}if(t.outShapeStridesLocation){let l=w.computeStrides(a.shape);switch(a.shape.length){case 2:e.gl.uniform1iv(t.outShapeStridesLocation,new Int32Array(l));break;case 3:e.gl.uniform2iv(t.outShapeStridesLocation,new Int32Array(l));break;case 4:e.gl.uniform3iv(t.outShapeStridesLocation,new Int32Array(l));break;default:break}}if(t.outTexShapeLocation&&e.gl.uniform2i(t.outTexShapeLocation,a.texData.texShape[0],a.texData.texShape[1]),t.program.customUniforms&&r)for(let l=0;l<t.program.customUniforms.length;++l){let u=t.program.customUniforms[l],p=t.customUniformLocations[l],d=r[l];if(u.type==="float")e.gl.uniform1fv(p,d);else if(u.type==="vec2")e.gl.uniform2fv(p,d);else if(u.type==="vec3")e.gl.uniform3fv(p,d);else if(u.type==="vec4")e.gl.uniform4fv(p,d);else if(u.type==="int")e.gl.uniform1iv(p,d);else if(u.type==="ivec2")e.gl.uniform2iv(p,d);else if(u.type==="ivec3")e.gl.uniform3iv(p,d);else if(u.type==="ivec4")e.gl.uniform4iv(p,d);else throw Error(`uniform type ${u.type} is not supported yet.`)}e.executeProgram()}function o9(e,t,n){let a="";t.concat(n).forEach(i=>{let o=i.texData!=null&&i.texData.slice!=null&&i.texData.slice.flatOffset>0;if(e.enableShapeUniforms&&!i.isUniform){let l=i.texData.texShape,{useSqueezeShape:u,uniformShape:p,keptDims:d}=nk(e.packedInputs,i.shape,l),c="",h="",m="";if(p.length===1&&e.packedInputs){let I=[Math.ceil(l[0]/2),Math.ceil(l[1]/2)];c=`${I[0]>1}_${I[1]>1}`}else if(p.length===2&&!e.packedInputs)h=`${p[0]>1}_${p[1]>1}`;else if(p.length>2&&!e.packedInputs){let I=w.computeStrides(p);m=`${I[0]===l[1]}_${I[I.length-1]===l[1]}`}let f=i.shape.length,g=p.length===2&&w.arraysEqual(i.shape,l),b=w.sizeFromShape(i.shape)===1,y=N.getBroadcastDims(i.shape,n.shape),x=!e.packedInputs&&f===n.shape.length&&w.arraysEqual(l,n.texData.texShape),v=e.packedInputs||p.length>2?"":`${l[0]>1}_${l[1]>1}`;a+=`${f}_${x}_${u?d:""}_${p.length}_${b}_${y}_${g}_${c}_${h}_${m}_${v}_${o}`}else{let l=i.isUniform?"uniform":i.texData.texShape;a+=`${i.shape}_${l}_${o}`}});let r=e.userCode,s=e.constructor.name;return s+="_"+a+"_"+r+`${G().getNumber("WEBGL_VERSION")}`,s}function vn(e){return G().getBool("WEBGL_USE_SHAPES_UNIFORMS")&&e<=4}var l9=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outPackingScheme=Ec.DENSE,this.customUniforms=[{name:"texShape",type:"ivec2"}];let t=En();this.outputShape=e,this.enableShapeUniforms=vn(this.outputShape.length),this.userCode=`
| ivec3 outCoordsFromFlatIndex(int index) {
| ${this.enableShapeUniforms?Jf(["r","c","d"],e):Jo(["r","c","d"],e)}
| return ivec3(r, c, d);
| }
|
| void main() {
| ivec2 resTexRC = ivec2(resultUV.yx * vec2(texShape[0], texShape[1]));
| int index = 4 * (resTexRC.x * texShape[1] + resTexRC.y);
|
| vec4 result = vec4(0.);
|
| for (int i=0; i<4; i++) {
| int flatIndex = index + i;
| ivec3 rc = outCoordsFromFlatIndex(flatIndex);
| result[i] = getA(rc.x, rc.y, rc.z);
| }
|
| ${t.output} = result;
| }
| `}},u9=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outPackingScheme=Ec.DENSE,this.customUniforms=[{name:"texShape",type:"ivec2"}];let t=En();this.outputShape=e,this.enableShapeUniforms=vn(this.outputShape.length),this.userCode=`
| ivec3 outCoordsFromFlatIndex(int index) {
| ${this.enableShapeUniforms?Jf(["r","c","d"],e):Jo(["r","c","d"],e)}
| return ivec3(r, c, d);
| }
|
| void main() {
| ivec2 resTexRC = ivec2(resultUV.yx * vec2(texShape[0], texShape[1]));
| int index = 4 * (resTexRC.x * texShape[1] + resTexRC.y);
|
| vec4 result = vec4(0.);
|
| for (int i=0; i<4; i++) {
| int flatIndex = index + i;
| ivec3 rc = outCoordsFromFlatIndex(flatIndex);
| result[i] = getChannel(getA(rc.x, rc.y, rc.z), vec2(rc.y, rc.z));
| }
|
| ${t.output} = result;
| }
| `}},p9=class{constructor(e){this.variableNames=["A"],this.outTexUsage=ha.DOWNLOAD;let t=En();this.outputShape=e,this.userCode=`
| ${YE}
|
| void main() {
| float x = getAAtOutCoords();
| ${t.output} = encode_float(x);
| }
| `}},c9=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outTexUsage=ha.DOWNLOAD;let t=En();this.outputShape=e,this.userCode=`
| ${YE}
|
| void main() {
| ivec3 coords = getOutputCoords();
| float x = getChannel(getAAtOutCoords(), vec2(coords.y, coords.z));
| ${t.output} = encode_float(x);
| }
| `}},d9={R:0,G:1,B:2,A:3},fS=class{constructor(e,t=!1,n="RGBA"){this.variableNames=["A"],this.customUniforms=[{name:"texShape",type:"ivec2"}];let a=En();this.outputShape=e,this.enableShapeUniforms=vn(this.outputShape.length);let r="result";t&&(r="floor(result * 255. + 0.5)");let s="";for(let i=0;i<n.length;i++){let o=n[i];s+=`
| if(offset == ${i}) {
| result = values[${d9[o]}];
| }`}this.userCode=`
| ${this.enableShapeUniforms?tk():ek(e)}
|
| void main() {
| ivec3 coords = getOutputCoords();
| int flatIndex = getFlatIndex(coords);
| float result = 0.;
| int offset = imod(flatIndex, ${n.length});
|
| flatIndex = idiv(flatIndex, ${n.length}, 1.);
|
| int r = flatIndex / texShape[1];
| if (r < texShape[0]) {
| int c = imod(flatIndex, texShape[1]);
| vec2 uv = (vec2(c, r) + halfCR) / vec2(texShape[1], texShape[0]);
| vec4 values = ${a.texture2D}(A, uv);
| ${s}
| }
| ${a.output} = vec4(${r}, 0., 0., 0.);
| }
| `}},h9=class{constructor(e,t=!1){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.customUniforms=[{name:"texShape",type:"ivec2"}];let n=En();this.outputShape=e,this.enableShapeUniforms=vn(this.outputShape.length);let a="",r="result";t&&(r="floor(result * 255. + 0.5)");for(let s=0;s<=1;s++)for(let i=0;i<=1;i++){let o=s*2+i;a+=`
| localCoords = coords;
| if(localCoords[2] + ${i} < ${this.enableShapeUniforms?"outShape[2]":`${e[2]}`}) {
| localCoords[2] += ${i};
| if (localCoords[1] + ${s} < ${this.enableShapeUniforms?"outShape[1]":`${e[1]}`}) {
| localCoords[1] += ${s};
|
| flatIndex = getFlatIndex(localCoords);
| offset = imod(flatIndex, 4);
|
| flatIndex = idiv(flatIndex, 4, 1.);
|
| int r = flatIndex / texShape[1];
| int c = imod(flatIndex, texShape[1]);
| vec2 uv = (vec2(c, r) + halfCR) / vec2(texShape[1], texShape[0]);
| values = ${n.texture2D}(A, uv);
|
| if (offset == 0) {
| result[${o}] = values[0];
| } else if (offset == 1) {
| result[${o}] = values[1];
| } else if (offset == 2) {
| result[${o}] = values[2];
| } else {
| result[${o}] = values[3];
| }
| }
| }
| `}this.userCode=`
| ${this.enableShapeUniforms?tk():ek(e)}
|
| void main() {
| ivec3 coords = getOutputCoords();
|
| vec4 result = vec4(0.);
| int flatIndex, r, c, offset;
| ivec3 localCoords;
| vec2 uv;
| vec4 values;
|
| ${a}
|
| ${n.output} = ${r};
| }
| `}},tA={};Ee(tA,{bindVertexProgramAttributeStreams:()=>pA,createBufferFromOutputTexture:()=>hA,createFloat16MatrixTexture:()=>iA,createFloat16PackedMatrixTexture:()=>uA,createFloat32MatrixTexture:()=>sA,createIndexBuffer:()=>rA,createPackedMatrixTexture:()=>lA,createUnsignedBytesMatrixTexture:()=>oA,createVertexBuffer:()=>aA,createVertexShader:()=>nA,downloadByteEncodedFloatMatrixFromOutputTexture:()=>fA,downloadFloat32MatrixFromBuffer:()=>mA,downloadMatrixFromPackedOutputTexture:()=>bA,downloadPackedMatrixFromBuffer:()=>gA,getInternalFormatForFloat16MatrixTexture:()=>rk,getInternalFormatForFloat16PackedMatrixTexture:()=>ok,getInternalFormatForFloat32MatrixTexture:()=>ak,getInternalFormatForPackedMatrixTexture:()=>ik,getInternalFormatForUnsignedBytesMatrixTexture:()=>sk,uploadDenseMatrixToTexture:()=>cA,uploadPixelDataToTexture:()=>dA});function nA(e){let t=En(),n=`${t.version}
| precision highp float;
| ${t.attribute} vec3 clipSpacePos;
| ${t.attribute} vec2 uv;
| ${t.varyingVs} vec2 resultUV;
|
| void main() {
| gl_Position = vec4(clipSpacePos, 1);
| resultUV = uv;
| }`;return _E(e,n)}function aA(e){let t=new Float32Array([-1,1,0,0,1,-1,-1,0,0,0,1,1,0,1,1,1,-1,0,1,0]);return $E(e,t)}function rA(e){let t=new Uint16Array([0,1,2,2,1,3]);return DE(e,t)}function Pd(e,t,n,a,r,s){ME(t,n);let i=RE(e),o=e.TEXTURE_2D;return de(e,()=>e.bindTexture(o,i)),de(e,()=>e.texParameteri(o,e.TEXTURE_WRAP_S,e.CLAMP_TO_EDGE)),de(e,()=>e.texParameteri(o,e.TEXTURE_WRAP_T,e.CLAMP_TO_EDGE)),de(e,()=>e.texParameteri(o,e.TEXTURE_MIN_FILTER,e.NEAREST)),de(e,()=>e.texParameteri(o,e.TEXTURE_MAG_FILTER,e.NEAREST)),G().getNumber("WEBGL_VERSION")===1?de(e,()=>e.texImage2D(o,0,a,t,n,0,r,s,null)):de(e,()=>e.texStorage2D(o,1,a,t,n)),de(e,()=>e.bindTexture(e.TEXTURE_2D,null)),{texture:i,texShape:[n,t]}}function ak(e){return e.internalFormatFloat}function sA(e,t,n,a){let[r,s]=Md(t,n);return Pd(e,r,s,ak(a),a.textureFormatFloat,e.FLOAT)}function rk(e){return e.internalFormatHalfFloat}function iA(e,t,n,a){let[r,s]=Md(t,n);return Pd(e,r,s,rk(a),a.textureFormatFloat,a.textureTypeHalfFloat)}function sk(e){return e.downloadTextureFormat}function oA(e,t,n,a){let[r,s]=Md(t,n);return Pd(e,r,s,sk(a),e.RGBA,e.UNSIGNED_BYTE)}function ik(e){return e.internalFormatPackedFloat}function lA(e,t,n,a){let[r,s]=xp(t,n);return Pd(e,r,s,ik(a),e.RGBA,e.FLOAT)}function ok(e){return e.internalFormatPackedHalfFloat}function uA(e,t,n,a){let[r,s]=xp(t,n);return Pd(e,r,s,ok(a),e.RGBA,a.textureTypeHalfFloat)}function pA(e,t,n){return de(e,()=>e.bindBuffer(e.ARRAY_BUFFER,n)),dv(e,t,"clipSpacePos",n,3,20,0)&&dv(e,t,"uv",n,2,20,12)}function cA(e,t,n,a,r,s){de(e,()=>e.bindTexture(e.TEXTURE_2D,t));let i,o,l;r instanceof Uint8Array?(i=new Uint8Array(n*a*4),o=e.UNSIGNED_BYTE,l=e.RGBA):(i=new Float32Array(n*a*4),o=e.FLOAT,l=s.internalFormatPackedFloat),i.set(r),G().getNumber("WEBGL_VERSION")===2?de(e,()=>e.texSubImage2D(e.TEXTURE_2D,0,0,0,n,a,e.RGBA,o,i)):de(e,()=>e.texImage2D(e.TEXTURE_2D,0,l,n,a,0,e.RGBA,o,i)),de(e,()=>e.bindTexture(e.TEXTURE_2D,null))}function dA(e,t,n){de(e,()=>e.bindTexture(e.TEXTURE_2D,t)),n.data instanceof Uint8Array?G().getNumber("WEBGL_VERSION")===2?de(e,()=>e.texSubImage2D(e.TEXTURE_2D,0,0,0,n.width,n.height,e.RGBA,e.UNSIGNED_BYTE,n.data)):de(e,()=>e.texImage2D(e.TEXTURE_2D,0,e.RGBA,n.width,n.height,0,e.RGBA,e.UNSIGNED_BYTE,n.data)):G().getNumber("WEBGL_VERSION")===2?de(e,()=>e.texSubImage2D(e.TEXTURE_2D,0,0,0,e.RGBA,e.UNSIGNED_BYTE,n)):de(e,()=>e.texImage2D(e.TEXTURE_2D,0,e.RGBA,e.RGBA,e.UNSIGNED_BYTE,n)),de(e,()=>e.bindTexture(e.TEXTURE_2D,null))}function hA(e,t,n,a){let r=e.createBuffer();de(e,()=>e.bindBuffer(e.PIXEL_PACK_BUFFER,r));let s=4*4*t*n;return de(e,()=>e.bufferData(e.PIXEL_PACK_BUFFER,s,e.STREAM_READ)),de(e,()=>e.readPixels(0,0,n,t,e.RGBA,e.FLOAT,0)),de(e,()=>e.bindBuffer(e.PIXEL_PACK_BUFFER,null)),r}function mA(e,t,n){let a=e,r=new Float32Array(n);return a.bindBuffer(a.PIXEL_PACK_BUFFER,t),a.getBufferSubData(a.PIXEL_PACK_BUFFER,0,r),a.bindBuffer(a.PIXEL_PACK_BUFFER,null),r}function fA(e,t,n,a){let[r,s]=Md(t,n),i=4,o=new Uint8Array(uJ(t*n,i));return de(e,()=>e.readPixels(0,0,r,s,a.downloadTextureFormat,e.UNSIGNED_BYTE,o)),new Float32Array(o.buffer)}function gA(e,t,n,a,r,s,i,o){let l=e,u=new Float32Array(pJ(s,i));return l.bindBuffer(l.PIXEL_PACK_BUFFER,t),l.getBufferSubData(l.PIXEL_PACK_BUFFER,0,u),l.bindBuffer(l.PIXEL_PACK_BUFFER,null),u}function bA(e,t,n){let a=new Float32Array(t*n*4);return de(e,()=>e.readPixels(0,0,n,t,e.RGBA,e.FLOAT,a)),a}var tm=class{constructor(e){this.outputTexture=null,this.program=null,this.disposed=!1,this.itemsToPoll=[];let t=G().getNumber("WEBGL_VERSION");if(e!=null?(this.gl=e,NE(t,e)):this.gl=Ka(t),e=this.gl,G().getNumber("WEBGL_VERSION")===2){let r=e;this.createVertexArray=()=>de(r,()=>r.createVertexArray()),this.bindVertexArray=s=>de(r,()=>r.bindVertexArray(s)),this.deleteVertexArray=s=>de(r,()=>r.deleteVertexArray(s)),this.getVertexArray=()=>de(r,()=>r.getParameter(r.VERTEX_ARRAY_BINDING))}else if(e!=null){let r=e.getExtension("OES_vertex_array_object");if(r==null)throw new Error("All WebGL1 implementations are expected to offer OES_vertex_array_object.");this.createVertexArray=()=>de(e,()=>r.createVertexArrayOES()),this.bindVertexArray=s=>de(e,()=>r.bindVertexArrayOES(s)),this.deleteVertexArray=s=>de(e,()=>r.deleteVertexArrayOES(s)),this.getVertexArray=()=>de(e,()=>e.getParameter(r.VERTEX_ARRAY_BINDING_OES))}let n="WEBGL_color_buffer_float",a="EXT_color_buffer_half_float";if(this.parallelCompilationExtension=this.gl.getExtension("KHR_parallel_shader_compile"),G().getNumber("WEBGL_VERSION")===1){let r="OES_texture_float",s="OES_texture_half_float";if(this.textureFloatExtension=lc(this.gl,r),ma(this.gl,s))this.textureHalfFloatExtension=lc(this.gl,s);else if(G().get("WEBGL_FORCE_F16_TEXTURES"))throw new Error("GL context does not support half float textures, yet the environment flag WEBGL_FORCE_F16_TEXTURES is set to true.");if(this.colorBufferFloatExtension=this.gl.getExtension(n),ma(this.gl,a))this.colorBufferHalfFloatExtension=lc(this.gl,a);else if(G().get("WEBGL_FORCE_F16_TEXTURES"))throw new Error("GL context does not support color renderable half floats, yet the environment flag WEBGL_FORCE_F16_TEXTURES is set to true.")}else if(n="EXT_color_buffer_float",ma(this.gl,n))this.colorBufferFloatExtension=this.gl.getExtension(n);else if(ma(this.gl,a))this.colorBufferHalfFloatExtension=this.gl.getExtension(a);else throw new Error("GL context does not support color renderable floats");this.vertexBuffer=aA(this.gl),this.indexBuffer=rA(this.gl),this.framebuffer=PE(this.gl),this.textureConfig=J1(this.gl,this.textureHalfFloatExtension)}get debug(){return G().getBool("DEBUG")}dispose(){if(this.disposed)return;this.program!=null&&console.warn("Disposing a GPGPUContext that still has a bound WebGLProgram. This is probably a resource leak, delete the program with GPGPUContext.deleteProgram before disposing."),this.outputTexture!=null&&console.warn("Disposing a GPGPUContext that still has a bound output matrix texture. This is probably a resource leak, delete the output matrix texture with GPGPUContext.deleteMatrixTexture before disposing.");let e=this.gl;de(e,()=>e.finish()),de(e,()=>e.bindFramebuffer(e.FRAMEBUFFER,null)),de(e,()=>e.deleteFramebuffer(this.framebuffer)),de(e,()=>e.bindBuffer(e.ARRAY_BUFFER,null)),de(e,()=>e.bindBuffer(e.ELEMENT_ARRAY_BUFFER,null)),de(e,()=>e.deleteBuffer(this.indexBuffer)),this.disposed=!0}createFloat32MatrixTexture(e,t){return this.throwIfDisposed(),sA(this.gl,e,t,this.textureConfig)}createFloat16MatrixTexture(e,t){return this.throwIfDisposed(),iA(this.gl,e,t,this.textureConfig)}createUnsignedBytesMatrixTexture(e,t){return this.throwIfDisposed(),oA(this.gl,e,t,this.textureConfig)}uploadPixelDataToTexture(e,t){this.throwIfDisposed(),dA(this.gl,e,t)}uploadDenseMatrixToTexture(e,t,n,a){this.throwIfDisposed(),cA(this.gl,e,t,n,a,this.textureConfig)}createFloat16PackedMatrixTexture(e,t){return this.throwIfDisposed(),uA(this.gl,e,t,this.textureConfig)}createPackedMatrixTexture(e,t){return this.throwIfDisposed(),lA(this.gl,e,t,this.textureConfig)}deleteMatrixTexture(e){this.throwIfDisposed(),this.outputTexture===e&&(hv(this.gl,this.framebuffer),this.outputTexture=null),de(this.gl,()=>this.gl.deleteTexture(e))}downloadByteEncodedFloatMatrixFromOutputTexture(e,t,n){return this.downloadMatrixDriver(e,()=>fA(this.gl,t,n,this.textureConfig))}downloadPackedMatrixFromBuffer(e,t,n,a,r,s){return gA(this.gl,e,t,n,a,r,s,this.textureConfig)}downloadFloat32MatrixFromBuffer(e,t){return mA(this.gl,e,t)}createBufferFromTexture(e,t,n){this.bindTextureToFrameBuffer(e);let a=hA(this.gl,t,n,this.textureConfig);return this.unbindTextureToFrameBuffer(),a}createAndWaitForFence(){let e=this.createFence(this.gl);return this.pollFence(e)}createFence(e){let t,n;if(G().getBool("WEBGL_FENCE_API_ENABLED")){let a=e,r=a.fenceSync(a.SYNC_GPU_COMMANDS_COMPLETE,0);e.flush(),n=()=>{let s=a.clientWaitSync(r,0,0);return s===a.ALREADY_SIGNALED||s===a.CONDITION_SATISFIED},t=r}else G().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")>0?(t=this.beginQuery(),this.endQuery(),n=()=>this.isQueryAvailable(t,G().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))):n=()=>!0;return{query:t,isFencePassed:n}}downloadMatrixFromPackedTexture(e,t,n){return this.downloadMatrixDriver(e,()=>bA(this.gl,t,n))}createProgram(e){this.throwIfDisposed();let t=this.gl;this.vertexShader==null&&(this.vertexShader=nA(t));let n=AE(t);de(t,()=>t.attachShader(n,this.vertexShader)),de(t,()=>t.attachShader(n,e)),FE(t,n);let a=Object.assign(n,{vao:this.createVertexArray()});return this.debug&&Zh(t,a),a}buildVao(e){this.setProgram(e),this.bindVertexArray(e.vao);let t=this.gl;de(t,()=>t.bindBuffer(t.ELEMENT_ARRAY_BUFFER,this.indexBuffer)),pA(t,e,this.vertexBuffer)}deleteProgram(e){this.throwIfDisposed(),e===this.program&&(this.program=null),e!=null&&(de(this.gl,()=>this.gl.deleteProgram(e)),this.deleteVertexArray(e.vao))}setProgram(e){this.throwIfDisposed(),this.program=e,this.program!=null&&this.debug&&Zh(this.gl,this.program),de(this.gl,()=>this.gl.useProgram(e))}getUniformLocation(e,t,n=!0){return this.throwIfDisposed(),n?LE(this.gl,e,t):zE(this.gl,e,t)}getAttributeLocation(e,t){return this.throwIfDisposed(),de(this.gl,()=>this.gl.getAttribLocation(e,t))}getUniformLocationNoThrow(e,t){return this.throwIfDisposed(),this.gl.getUniformLocation(e,t)}setInputMatrixTexture(e,t,n){this.throwIfDisposed(),this.throwIfNoProgram(),WE(this.gl,e,t,n)}setOutputMatrixTexture(e,t,n){this.setOutputMatrixTextureDriver(e,n,t)}setOutputPackedMatrixTexture(e,t,n){this.throwIfDisposed();let[a,r]=xp(t,n);this.setOutputMatrixTextureDriver(e,a,r)}setOutputMatrixWriteRegion(e,t,n,a){this.setOutputMatrixWriteRegionDriver(n,e,a,t)}setOutputPackedMatrixWriteRegion(e,t,n,a){throw new Error("setOutputPackedMatrixWriteRegion not implemented.")}debugValidate(){this.program!=null&&Zh(this.gl,this.program),uc(this.gl)}executeProgram(){this.throwIfDisposed(),this.throwIfNoProgram();let e=this.gl;if(this.debug){let t=this.getVertexArray();console.assert(t===this.program.vao,"VAO changed between setProgram and executeProgram!"),this.debugValidate()}de(e,()=>e.drawElements(e.TRIANGLES,6,e.UNSIGNED_SHORT,0))}blockUntilAllProgramsCompleted(){this.throwIfDisposed(),de(this.gl,()=>this.gl.finish())}getQueryTimerExtension(){return this.disjointQueryTimerExtension==null&&(this.disjointQueryTimerExtension=lc(this.gl,G().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")===2?"EXT_disjoint_timer_query_webgl2":"EXT_disjoint_timer_query")),this.disjointQueryTimerExtension}getQueryTimerExtensionWebGL2(){return this.getQueryTimerExtension()}getQueryTimerExtensionWebGL1(){return this.getQueryTimerExtension()}beginQuery(){if(G().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")===2){let n=this.gl,a=this.getQueryTimerExtensionWebGL2(),r=n.createQuery();return n.beginQuery(a.TIME_ELAPSED_EXT,r),r}let e=this.getQueryTimerExtensionWebGL1(),t=e.createQueryEXT();return e.beginQueryEXT(e.TIME_ELAPSED_EXT,t),t}endQuery(){if(G().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")===2){let t=this.gl,n=this.getQueryTimerExtensionWebGL2();t.endQuery(n.TIME_ELAPSED_EXT);return}let e=this.getQueryTimerExtensionWebGL1();e.endQueryEXT(e.TIME_ELAPSED_EXT)}async waitForQueryAndGetTime(e){return await w.repeatedTry(()=>this.disposed||this.isQueryAvailable(e,G().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))),this.getQueryTime(e,G().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))}getQueryTime(e,t){if(t===0)return null;if(t===2){let n=this.gl;return n.getQueryParameter(e,n.QUERY_RESULT)/1e6}else{let n=this.getQueryTimerExtensionWebGL1();return n.getQueryObjectEXT(e,n.QUERY_RESULT_EXT)/1e6}}isQueryAvailable(e,t){if(t===0)return!0;if(t===2){let n=this.gl,a=this.getQueryTimerExtensionWebGL2(),r=n.getQueryParameter(e,n.QUERY_RESULT_AVAILABLE);return this.disjoint==null&&(this.disjoint=this.gl.getParameter(a.GPU_DISJOINT_EXT)),r&&!this.disjoint}else{let n=this.getQueryTimerExtensionWebGL1(),a=n.getQueryObjectEXT(e,n.QUERY_RESULT_AVAILABLE_EXT);return this.disjoint==null&&(this.disjoint=this.gl.getParameter(n.GPU_DISJOINT_EXT)),a&&!this.disjoint}}pollFence(e){return new Promise(t=>{this.addItemToPoll(()=>e.isFencePassed(),()=>t())})}pollItems(){let e=m9(this.itemsToPoll.map(t=>t.isDoneFn));for(let t=0;t<=e;++t){let{resolveFn:n}=this.itemsToPoll[t];n()}this.itemsToPoll=this.itemsToPoll.slice(e+1)}addItemToPoll(e,t){if(this.itemsToPoll.push({isDoneFn:e,resolveFn:t}),this.itemsToPoll.length>1)return;let n;"setTimeoutCustom"in G().platform&&(n=G().platform.setTimeoutCustom.bind(G().platform)),w.repeatedTry(()=>(this.pollItems(),this.itemsToPoll.length===0),()=>0,null,n)}bindTextureToFrameBuffer(e){this.throwIfDisposed(),Jh(this.gl,e,this.framebuffer),this.debug&&uc(this.gl)}unbindTextureToFrameBuffer(){this.outputTexture!=null?(Jh(this.gl,this.outputTexture,this.framebuffer),this.debug&&uc(this.gl)):hv(this.gl,this.framebuffer)}downloadMatrixDriver(e,t){this.bindTextureToFrameBuffer(e);let n=t();return this.unbindTextureToFrameBuffer(),n}setOutputMatrixTextureDriver(e,t,n){this.throwIfDisposed();let a=this.gl;Jh(a,e,this.framebuffer),this.debug&&uc(a),this.outputTexture=e,de(a,()=>a.viewport(0,0,t,n)),de(a,()=>a.scissor(0,0,t,n))}setOutputMatrixWriteRegionDriver(e,t,n,a){this.throwIfDisposed(),de(this.gl,()=>this.gl.scissor(e,t,n,a))}throwIfDisposed(){if(this.disposed)throw new Error("Attempted to use disposed GPGPUContext.")}throwIfNoProgram(){if(this.program==null)throw new Error("No GPU program is currently set.")}};function m9(e){let t=0;for(;t<e.length&&e[t]();++t);return t-1}var{addImpl:f9,bincountImpl:yA,bincountReduceImpl:g9,bitwiseAndImpl:b9,castImpl:y9,ceilImpl:x9,concatImpl:v9,equalImpl:w9,expImpl:k9,expm1Impl:I9,floorImpl:S9,gatherNdImpl:N9,gatherV2Impl:T9,greaterImpl:C9,greaterEqualImpl:_9,lessImpl:E9,lessEqualImpl:A9,linSpaceImpl:F9,logImpl:$9,maxImpl:D9,maximumImpl:R9,minimumImpl:M9,multiplyImpl:P9,negImpl:O9,notEqualImpl:L9,prodImpl:z9,raggedGatherImpl:W9,raggedRangeImpl:B9,raggedTensorToTensorImpl:V9,rangeImpl:U9,rsqrtImpl:G9,scatterImpl:H9,sigmoidImpl:q9,simpleAbsImpl:xA,sliceImpl:j9,sparseFillEmptyRowsImpl:K9,sparseReshapeImpl:X9,sparseSegmentReductionImpl:vA,sqrtImpl:Y9,staticRegexReplaceImpl:Z9,stridedSliceImpl:J9,stringNGramsImpl:Q9,stringSplitImpl:eQ,stringToHashBucketFastImpl:tQ,subImpl:nQ,tileImpl:aQ,topKImpl:rQ,transposeImpl:lk,uniqueImpl:sQ}=P1;function wA(e,t){return["x","y","z","w","u","v"].slice(0,t).map(n=>`${e}.${n}`)}function Sn(e,t){return t===1?[e]:wA(e,t)}function iQ(e,t){if(e===1)return"rc";let n="";for(let a=0;a<e;a++)n+=t[a],a<e-1&&(n+=",");return n}var oQ=class{constructor(e){if(this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outputShape=e,this.rank=e.length,this.enableShapeUniforms=vn(this.outputShape.length),this.rank===0)this.userCode=`
| void main() {
| setOutput(vec4(getA(), 0., 0., 0.));
| }
| `;else{let t=Sn("rc",this.rank),n=dt(this.rank),a=this.getOutOfBoundsCondition(t),r=this.getSetup(t),s=this.getOutput(t);this.userCode=`
| void main() {
| ${n} rc = getOutputCoords();
|
| if(${a}) {
| setOutput(vec4(0));
| } else {
| ${r}
|
| setOutput(vec4(${s}));
| }
| }
| `}}getSourceCoordsArr(e){let t=[];for(let n=0;n<=1;n++)for(let a=0;a<=1;a++){let r=`${n===0?"r":"rp1"}, ${a===0?"c":"cp1"}`;for(let s=2;s<this.rank;s++)r=`${e[e.length-1-s]},`+r;t.push(r)}return t}getOutOfBoundsCondition(e){if(this.rank===1)return`rc > ${this.enableShapeUniforms?"outShape":this.outputShape[0]}`;let t="";for(let n=this.rank-2;n<this.rank;n++)t+=`${e[n]} >= ${this.enableShapeUniforms?`outShape[${n}]`:this.outputShape[n]}`,n<this.rank-1&&(t+="||");return t}getSetup(e){if(this.rank===1)return"";let t=e.slice(-2),n=this.enableShapeUniforms?`outShape[${this.rank} - 1]`:this.outputShape[this.rank-1],a=this.enableShapeUniforms?`outShape[${this.rank} - 2]`:this.outputShape[this.rank-2];return`
| int r = ${t[0]};
| int c = ${t[1]};
| int rp1 = r + 1;
| int cp1 = c + 1;
|
| bool cEdge = cp1 >= ${n};
| bool rEdge = rp1 >= ${a};
| `}getOutput(e){let t=this.getSourceCoordsArr(e);return this.rank===1?`getA(rc), (rc + 1 >= ${this.enableShapeUniforms?"outShape":this.outputShape[0]} ? 0. : getA(rc + 1)), 0, 0`:`getA(${t[0]}),
| cEdge ? 0. : getA(${t[1]}),
| rEdge ? 0. : getA(${t[2]}),
| rEdge || cEdge ? 0. : getA(${t[3]})`}},kA=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"inputShape",type:"ivec3"}],this.outputShape=e,this.enableShapeUniforms=vn(this.outputShape.length);let n="";for(let a=0;a<4;a++){let r="thisRC = rc;";a%2===1&&(r+="thisRC.z += 1;"),a>1&&(r+="thisRC.y += 1;"),n+=`
| ${r}
| ${a>0?"if(thisRC.y < rows && thisRC.z < cols){":""}
| int flatIndex = getFlatIndex(thisRC);
|
| ivec3 inputRC = inputCoordsFromReshapedOutCoords(flatIndex);
| vec2 inputRCInnerDims = vec2(float(inputRC.y),float(inputRC.z));
|
| result[${a}] =
| getChannel(getA(inputRC.x, inputRC.y, inputRC.z), inputRCInnerDims);
| ${a>0?"}":""}
| `}this.userCode=`
| ${lQ(t,this.enableShapeUniforms)}
| ${this.enableShapeUniforms?tk():ek(e)}
|
| void main() {
| ivec3 rc = getOutputCoords();
|
| vec4 result = vec4(0.);
|
| ivec3 thisRC;
| int rows = ${this.enableShapeUniforms?"outShape[1]":e[1]};
| int cols = ${this.enableShapeUniforms?"outShape[2]":e[2]};
|
| ${n}
|
| setOutput(result);
| }
| `}};function lQ(e,t){return`
| ivec3 inputCoordsFromReshapedOutCoords(int index) {
| ${t?kJ(["r","c","d"],"inputShape"):Jo(["r","c","d"],e)}
| return ivec3(r, c, d);
| }
| `}var uQ=class{constructor(e){this.gpgpu=e,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0,this.freeTextures={},this.usedTextures={},this.logEnabled=!1}acquireTexture(e,t,n){let a=bS(t,n),r=yS(e,a,n);r in this.freeTextures||(this.freeTextures[r]=[]),r in this.usedTextures||(this.usedTextures[r]=[]);let s=gS(e,a,this.gpgpu.gl,this.gpgpu.textureConfig,n);if(this.freeTextures[r].length>0){this.numFreeTextures--,this.numUsedTextures++,this._numBytesFree-=s,this.log();let o=this.freeTextures[r].pop();return this.usedTextures[r].push(o),o}let i;return a===hn.PACKED_2X2_FLOAT32?i=this.gpgpu.createPackedMatrixTexture(e[0],e[1]):a===hn.PACKED_2X2_FLOAT16?i=this.gpgpu.createFloat16PackedMatrixTexture(e[0],e[1]):a===hn.UNPACKED_FLOAT32?i=this.gpgpu.createFloat32MatrixTexture(e[0],e[1]):a===hn.UNPACKED_FLOAT16?i=this.gpgpu.createFloat16MatrixTexture(e[0],e[1]):a===hn.PACKED_4X1_UNSIGNED_BYTE&&(i=this.gpgpu.createUnsignedBytesMatrixTexture(e[0],e[1])),this.usedTextures[r].push(i),this.numUsedTextures++,this._numBytesAllocated+=s,this.log(),i}releaseTexture(e,t,n,a){if(this.freeTextures==null)return;let r=bS(n,a),s=yS(t,r,a);s in this.freeTextures||(this.freeTextures[s]=[]);let i=gS(t,r,this.gpgpu.gl,this.gpgpu.textureConfig,a),o=G().get("WEBGL_DELETE_TEXTURE_THRESHOLD");o!==-1&&this._numBytesAllocated>o?(this.gpgpu.deleteMatrixTexture(e.texture),this._numBytesAllocated-=i):(this.freeTextures[s].push(e),this.numFreeTextures++,this._numBytesFree+=i),this.numUsedTextures--;let l=this.usedTextures[s],u=l&&l.indexOf(e);if(u==null||u<0)throw new Error("Cannot release a texture that was never provided by this texture manager");l[u]=l[l.length-1],l.pop(),this.log()}log(){if(!this.logEnabled)return;let e=this.numFreeTextures+this.numUsedTextures;console.log("Free/Used",`${this.numFreeTextures} / ${this.numUsedTextures}`,`(${e})`);let t=this._numBytesFree/this._numBytesAllocated;console.log(`Bytes allocated: ${this._numBytesAllocated}`),console.log(`Bytes unused: ${this._numBytesFree} (${Math.round(100*t)}%)`)}get numBytesAllocated(){return this._numBytesAllocated}get numBytesFree(){return this._numBytesFree}getNumUsedTextures(){return this.numUsedTextures}getNumFreeTextures(){return this.numFreeTextures}dispose(){if(this.freeTextures!=null){for(let e in this.freeTextures)this.freeTextures[e].forEach(t=>{this.gpgpu.deleteMatrixTexture(t.texture)});for(let e in this.usedTextures)this.usedTextures[e].forEach(t=>{this.gpgpu.deleteMatrixTexture(t.texture)});this.freeTextures=null,this.usedTextures=null,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0}}};function pQ(e,t){let n=e;if(t===n.R32F)return 4;if(t===n.R16F)return 2;if(t===n.RGBA32F||t===e.RGBA)return 16;if(t===n.RGBA16F)return 8;if(t===n.RGBA8)return 4;throw new Error(`Unknown internal format ${t}`)}function gS(e,t,n,a,r){let s=cQ(t,a),i;if(r){let[l,u]=xp(e[0],e[1]);i=l*u}else{let[l,u]=Md(e[0],e[1]);i=l*u}let o=pQ(n,s);return i*o}function cQ(e,t){switch(e){case hn.PACKED_2X2_FLOAT32:return ik(t);case hn.PACKED_2X2_FLOAT16:return ok(t);case hn.UNPACKED_FLOAT32:return ak(t);case hn.UNPACKED_FLOAT16:return rk(t);case hn.PACKED_4X1_UNSIGNED_BYTE:return sk(t);default:throw new Error(`Unknown physical texture type ${e}`)}}function dQ(e){return G().getBool("WEBGL_RENDER_FLOAT32_ENABLED")?e?hn.PACKED_2X2_FLOAT32:hn.UNPACKED_FLOAT32:e?hn.PACKED_2X2_FLOAT16:hn.UNPACKED_FLOAT16}function bS(e,t){if(e===ha.UPLOAD)return hn.PACKED_2X2_FLOAT32;if(e===ha.RENDER||e==null)return dQ(t);if(e===ha.DOWNLOAD||e===ha.PIXELS)return hn.PACKED_4X1_UNSIGNED_BYTE;throw new Error(`Unknown logical texture type ${e}`)}function yS(e,t,n){return`${e[0]}_${e[1]}_${t}_${n}`}var ir=class{constructor(e,t){this.variableNames=["A"],this.outputShape=e,this.enableShapeUniforms=vn(this.outputShape.length),this.userCode=`
| float unaryOperation(float x) {
| ${t}
| }
|
| void main() {
| float x = getAAtOutCoords();
| float y = unaryOperation(x);
|
| setOutput(y);
| }
| `}},Oa="if (isnan(x)) return x;",hQ="return x;",xS="return abs(x);",mQ="return (x >= 0.0) ? x : (exp(x) - 1.0);",fQ=Oa+`
| return (x < 0.0) ? 0.0 : x;
| `,gQ=Oa+`
| return (x < 0.0) ? 0.0 : min(6.0, x);
| `,ns="return x;",bQ="return 1.0 / (1.0 + exp(-1.0 * x));",yQ="return x;",xQ=`
| 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;
| `,vQ=`
| 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;
| `,wQ=`
| 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;
| `,kQ="return 1.0 / (1.0 + exp(-1.0 * x));",os=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.enableShapeUniforms=vn(this.outputShape.length),this.userCode=`
| vec4 unaryOperation(vec4 x) {
| ${t}
| }
|
| void main() {
| vec4 x = getAAtOutCoords();
| vec4 y = unaryOperation(x);
|
| setOutput(y);
| }
| `}},IQ=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outputShape=e,this.enableShapeUniforms=vn(this.outputShape.length);let t=e.length,n=Sn("rc",t),a=dt(t),r=iQ(t,n),s=n.slice(-2),i=t<=1?"rc":`vec2(${s.join(",")})`;this.userCode=`
| void main() {
| ${a} rc = getOutputCoords();
| vec4 packedInput = getA(${r});
|
| setOutput(getChannel(packedInput, ${i}));
| }
| `}},SQ=gr.whereImpl,NQ=1e-7,TQ=1e-4,Sx={};function CQ(e){return e in Sx||(Sx[e]={}),Sx[e]}var _Q=G().getNumber("CPU_HANDOFF_SIZE_THRESHOLD"),EQ=600;function AQ(){return G().global.screen==null?1024:G().global.screen.height*G().global.screen.width*window.devicePixelRatio*EQ/1024/1024}var Qf=class extends Mc{nextDataId(){return Qf.nextDataId++}constructor(e){if(super(),this.pendingRead=new WeakMap,this.pendingDisposal=new WeakSet,this.dataRefCount=new WeakMap,this.numBytesInGPU=0,this.uploadWaitMs=0,this.downloadWaitMs=0,this.lastGlFlushTime=0,this.warnedAboutMemory=!1,this.pendingDeletes=0,this.disposed=!1,!G().getBool("HAS_WEBGL"))throw new Error("WebGL is not supported on this device");let t;if(e!=null){if(e instanceof tm)t=e;else{let n=Ka(G().getNumber("WEBGL_VERSION"),e);t=new tm(n)}this.binaryCache={},this.gpgpuCreatedLocally=!1}else{let n=Ka(G().getNumber("WEBGL_VERSION"));t=new tm(n),this.binaryCache=CQ(G().getNumber("WEBGL_VERSION")),this.gpgpuCreatedLocally=!0}this.gpgpu=t,this.canvas=this.gpgpu.gl.canvas,this.textureManager=new uQ(this.gpgpu),this.numMBBeforeWarning=AQ(),this.texData=new Rm(this,Aa())}numDataIds(){return this.texData.numDataIds()-this.pendingDeletes}writeTexture(e,t,n,a,r,s){let i=this.makeTensorInfo(t,n),o=this.texData.get(i.dataId);o.isPacked=!1,o.texture={texture:e,texShape:[a,r]},o.texShape=[a,r];let l=pc(t),u=new fS(l,!1,s),p=this.runWebGLProgram(u,[i],n,[[a,r]]);return p.shape=t,o.texture=null,this.disposeIntermediateTensorInfo(i),p.dataId}write(e,t,n){if((G().getBool("WEBGL_CHECK_NUMERICAL_PROBLEMS")||G().getBool("DEBUG"))&&this.checkNumericalProblems(e),n==="complex64"&&e!=null)throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");let a={id:this.nextDataId()};return this.texData.set(a,{shape:t,dtype:n,values:e,usage:ha.UPLOAD,refCount:1}),a}refCount(e){return this.texData.has(e)?this.texData.get(e).refCount:0}incRef(e){let t=this.texData.get(e);t.refCount++}decRef(e){if(this.texData.has(e)){let t=this.texData.get(e);t.refCount--}}move(e,t,n,a,r){if(G().getBool("DEBUG")&&this.checkNumericalProblems(t),a==="complex64")throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");this.texData.set(e,{shape:n,dtype:a,values:t,usage:ha.UPLOAD,refCount:r})}disposeIntermediateTensorInfo(e){this.disposeData(e.dataId)}readSync(e){let t=this.texData.get(e),{values:n,dtype:a,complexTensorInfos:r,slice:s,shape:i,isPacked:o}=t;if(s!=null){let d;o?d=new os(i,ns):d=new ir(i,ns);let c=this.runWebGLProgram(d,[{dataId:e,shape:i,dtype:a}],a),h=this.readSync(c.dataId);return this.disposeIntermediateTensorInfo(c),h}if(n!=null)return this.convertAndCacheOnCPU(e);if(a==="string")return n;let l=this.activeTimers!=null,u;l&&(u=w.now());let p;if(a==="complex64"){let d=this.readSync(r.real.dataId),c=this.readSync(r.imag.dataId);p=N.mergeRealAndImagArrays(d,c)}else p=this.getValuesFromTexture(e);return l&&(this.downloadWaitMs+=w.now()-u),this.convertAndCacheOnCPU(e,p)}async read(e){if(this.pendingRead.has(e)){let h=this.pendingRead.get(e);return new Promise(m=>h.push(m))}let t=this.texData.get(e),{values:n,shape:a,slice:r,dtype:s,complexTensorInfos:i,isPacked:o}=t;if(r!=null){let h;o?h=new os(a,ns):h=new ir(a,ns);let m=this.runWebGLProgram(h,[{dataId:e,shape:a,dtype:s}],s),f=this.read(m.dataId);return this.disposeIntermediateTensorInfo(m),f}if(n!=null)return this.convertAndCacheOnCPU(e);if(G().getBool("DEBUG")&&!G().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")&&G().getNumber("WEBGL_VERSION")===2)throw new Error("tensor.data() with WEBGL_DOWNLOAD_FLOAT_ENABLED=false and WEBGL_VERSION=2 not yet supported.");let l=null,u;if(s!=="complex64"&&G().get("WEBGL_BUFFER_SUPPORTED")){u=this.decode(e);let h=this.texData.get(u.dataId);l=this.gpgpu.createBufferFromTexture(h.texture.texture,...Hh(a))}this.pendingRead.set(e,[]),s!=="complex64"&&await this.gpgpu.createAndWaitForFence();let p;if(s==="complex64"){let h=await Promise.all([this.read(i.real.dataId),this.read(i.imag.dataId)]),m=h[0],f=h[1];p=N.mergeRealAndImagArrays(m,f)}else if(l==null)p=this.getValuesFromTexture(e);else{let h=w.sizeFromShape(a);p=this.gpgpu.downloadFloat32MatrixFromBuffer(l,h)}if(u!=null&&this.disposeIntermediateTensorInfo(u),l!=null){let h=this.gpgpu.gl;de(h,()=>h.deleteBuffer(l))}let d=this.convertAndCacheOnCPU(e,p),c=this.pendingRead.get(e);return this.pendingRead.delete(e),c.forEach(h=>h(d)),this.pendingDisposal.has(e)&&(this.pendingDisposal.delete(e),this.disposeData(e)&&Aa().removeDataId(e,this),this.pendingDeletes--),d}readToGPU(e,t={}){let n=this.texData.get(e),{values:a,shape:r,slice:s,dtype:i,isPacked:o,texture:l}=n;if(i==="complex64")throw new Error("Does not support reading texture for complex64 dtype.");if(s!=null){let c;o?c=new os(r,ns):c=new ir(r,ns);let h=this.runWebGLProgram(c,[{dataId:e,shape:r,dtype:i}],i),m=this.readToGPU(h,t);return this.disposeIntermediateTensorInfo(h),m}if(l==null)throw a!=null?new Error("Data is not on GPU but on CPU."):new Error("There is no data on GPU or CPU.");let u=this.decode(e,t.customTexShape),p=Aa().makeTensorFromTensorInfo(u),d=this.texData.get(u.dataId);return Object.assign({tensorRef:p},d.texture)}bufferSync(e){let t=this.readSync(e.dataId);if(e.dtype==="string")try{let n=t.map(a=>w.decodeString(a));return ze(e.shape,e.dtype,n)}catch(n){throw new Error("Failed to decode encoded string bytes into utf-8")}return ze(e.shape,e.dtype,t)}checkNumericalProblems(e){if(e!=null)for(let t=0;t<e.length;t++){let n=e[t];if(!TE(n))throw G().getBool("WEBGL_RENDER_FLOAT32_CAPABLE")?Error(`The value ${n} cannot be represented with your current settings. Consider enabling float32 rendering: 'tf.env().set('WEBGL_RENDER_FLOAT32_ENABLED', true);'`):Error(`The value ${n} cannot be represented on this device.`)}}getValuesFromTexture(e){let{shape:t,dtype:n,isPacked:a}=this.texData.get(e),r=w.sizeFromShape(t);if(G().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")){let d=this.decode(e),c=this.texData.get(d.dataId),h=this.gpgpu.downloadMatrixFromPackedTexture(c.texture.texture,...Hh(t)).subarray(0,r);return this.disposeIntermediateTensorInfo(d),h}let s=G().getBool("WEBGL_PACK")&&a===!0,i=s?pc(t):t,o=s?new c9(i):new p9(i),l=this.runWebGLProgram(o,[{shape:i,dtype:n,dataId:e}],"float32"),u=this.texData.get(l.dataId),p=this.gpgpu.downloadByteEncodedFloatMatrixFromOutputTexture(u.texture.texture,u.texShape[0],u.texShape[1]).subarray(0,r);return this.disposeIntermediateTensorInfo(l),p}timerAvailable(){return G().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0}time(e){let t=this.activeTimers,n=[],a=!1;this.programTimersStack==null?(this.programTimersStack=n,a=!0):this.activeTimers.push(n),this.activeTimers=n,e();let r=w.flatten(this.activeTimers.map(o=>o.query)).filter(o=>o!=null),s=w.flatten(this.activeTimers.map(o=>o.name)).filter(o=>o!=null);this.activeTimers=t,a&&(this.programTimersStack=null);let i={uploadWaitMs:this.uploadWaitMs,downloadWaitMs:this.downloadWaitMs,kernelMs:null,wallMs:null};return(async()=>{if(G().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0){let o=await Promise.all(r);i.kernelMs=w.sum(o),i.getExtraProfileInfo=()=>o.map((l,u)=>({name:s[u],ms:l})).map(l=>`${l.name}: ${l.ms}`).join(", ")}else i.kernelMs={error:"WebGL query timers are not supported in this environment."};return this.uploadWaitMs=0,this.downloadWaitMs=0,i})()}memory(){return{unreliable:!1,numBytesInGPU:this.numBytesInGPU,numBytesInGPUAllocated:this.textureManager.numBytesAllocated,numBytesInGPUFree:this.textureManager.numBytesFree}}startTimer(){return G().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?this.gpgpu.beginQuery():{startMs:w.now(),endMs:null}}endTimer(e){return G().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?(this.gpgpu.endQuery(),e):(e.endMs=w.now(),e)}async getQueryTime(e){if(G().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0)return this.gpgpu.waitForQueryAndGetTime(e);let t=e;return t.endMs-t.startMs}disposeData(e,t=!1){if(this.pendingDisposal.has(e))return!1;if(!this.texData.has(e))return!0;if(t?this.texData.get(e).refCount=0:this.texData.get(e).refCount--,!t&&this.texData.get(e).refCount>0)return!1;if(this.pendingRead.has(e))return this.pendingDisposal.add(e),this.pendingDeletes++,!1;this.releaseGPUData(e);let{complexTensorInfos:n}=this.texData.get(e);return n!=null&&(this.disposeData(n.real.dataId,t),this.disposeData(n.imag.dataId,t)),this.texData.delete(e),!0}releaseGPUData(e){let{texture:t,dtype:n,texShape:a,usage:r,isPacked:s,slice:i}=this.texData.get(e),o=i&&i.origDataId||e,l=this.dataRefCount.get(o);l>1?this.dataRefCount.set(o,l-1):(this.dataRefCount.delete(o),t!=null&&(this.numBytesInGPU-=this.computeBytes(a,n),this.textureManager.releaseTexture(t,a,r,s)));let u=this.texData.get(e);u.texture=null,u.texShape=null,u.isPacked=!1,u.slice=null}getTexture(e){return this.uploadToGPU(e),this.texData.get(e).texture.texture}getDataInfo(e){return this.texData.get(e)}shouldExecuteOnCPU(e,t=_Q){return G().getBool("WEBGL_CPU_FORWARD")&&e.every(n=>this.texData.get(n.dataId).texture==null&&w.sizeFromShape(n.shape)<t)}getGPGPUContext(){return this.gpgpu}where(e){N.warn("tf.where() in webgl locks the UI thread. Call tf.whereAsync() instead");let t=e.dataSync();return SQ(e.shape,t)}packedUnaryOp(e,t,n){let a=new os(e.shape,t),r=this.compileAndRun(a,[e],n);return Aa().makeTensorFromTensorInfo(r)}abs(e){if(this.shouldExecuteOnCPU([e])&&e.dtype!=="complex64"){let a=xA(this.texData.get(e.dataId).values);return this.makeOutput(e.shape,e.dtype,a)}if(G().getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(e,xS,e.dtype);let t=new ir(e.shape,xS),n=this.compileAndRun(t,[e]);return Aa().makeTensorFromTensorInfo(n)}makeTensorInfo(e,t,n){let a;if(t==="string"&&n!=null&&n.length>0&&w.isString(n[0])){let r=n.map(s=>w.encodeString(s));a=this.write(r,e,t)}else a=this.write(n,e,t);return this.texData.get(a).usage=null,{dataId:a,shape:e,dtype:t}}makeOutput(e,t,n){return Aa().makeTensorFromTensorInfo(this.makeTensorInfo(e,t,n),this)}unpackTensor(e){let t=new IQ(e.shape);return this.runWebGLProgram(t,[e],e.dtype)}packTensor(e){let t=new oQ(e.shape),n=!0;return this.runWebGLProgram(t,[e],e.dtype,null,n)}packedReshape(e,t){let n=[wi(e.shape),...ki(e.shape)],a={dtype:e.dtype,shape:n,dataId:e.dataId},r=[wi(t),...ki(t)],s=new kA(r,n),i=!0,o=[n],l=this.runWebGLProgram(s,[a],e.dtype,o,i);return{dataId:l.dataId,shape:t,dtype:l.dtype}}decode(e,t){let n=this.texData.get(e),{isPacked:a,shape:r,dtype:s}=n;if(t!=null){let d=w.sizeFromShape(r),c=t[0]*t[1]*4;w.assert(d<=c,()=>"customTexShape is too small. Row * Column * 4 should be equal or larger than the size of the tensor data.")}let i=pc(r),o;a?o=new u9(i):o=new l9(i);let l=!0,u=[t!=null?t:Hh(i)],p=this.runWebGLProgram(o,[{shape:i,dtype:s,dataId:e}],s,u,l,t);return{dtype:s,shape:r,dataId:p.dataId}}runWebGLProgram(e,t,n,a,r=!1,s){let i=this.makeTensorInfo(e.outputShape,n),o=this.texData.get(i.dataId);if(e.packedOutput&&(o.isPacked=!0),e.outPackingScheme===Ec.DENSE){let g=s!=null?s:Hh(e.outputShape);o.texShape=g.map(b=>b*2)}if(e.outTexUsage!=null&&(o.usage=e.outTexUsage),w.sizeFromShape(i.shape)===0)return o.values=w.getTypedArrayFromDType(i.dtype,0),i;let l=[],u=t.map(g=>{if(g.dtype==="complex64")throw new Error("GPGPUProgram does not support complex64 input. For complex64 dtypes, please separate the program into real and imaginary parts.");let b=this.texData.get(g.dataId);if(b.texture==null){if(!e.packedInputs&&w.sizeFromShape(g.shape)<=G().getNumber("WEBGL_SIZE_UPLOAD_UNIFORM"))return{shape:g.shape,texData:null,isUniform:!0,uniformValues:b.values};e.packedInputs&&(b.isPacked=!0,b.shape=g.shape)}if(this.uploadToGPU(g.dataId),!!b.isPacked!=!!e.packedInputs)g=b.isPacked?this.unpackTensor(g):this.packTensor(g),l.push(g),b=this.texData.get(g.dataId);else if(b.isPacked&&!Ac(b.shape,g.shape)){let y=g,x=g.shape;g.shape=b.shape,g=this.packedReshape(g,x),l.push(g),b=this.texData.get(g.dataId),y.shape=x}return{shape:g.shape,texData:b,isUniform:!1}});this.uploadToGPU(i.dataId);let p={shape:i.shape,texData:o,isUniform:!1},d=o9(e,u,p),c=this.getAndSaveBinary(d,()=>s9(this.gpgpu,e,u,p)),h=this.activeTimers!=null,m;h&&(m=this.startTimer()),G().get("ENGINE_COMPILE_ONLY")||i9(this.gpgpu,c,u,p,a),l.forEach(g=>this.disposeIntermediateTensorInfo(g)),h&&(m=this.endTimer(m),this.activeTimers.push({name:e.constructor.name,query:this.getQueryTime(m)}));let f=G().get("WEBGL_FLUSH_THRESHOLD");if(f>0){let g=w.now();g-this.lastGlFlushTime>f&&(this.gpgpu.gl.flush(),this.lastGlFlushTime=g)}if(!G().getBool("WEBGL_LAZILY_UNPACK")&&o.isPacked&&r===!1){let g=this.unpackTensor(i);return this.disposeIntermediateTensorInfo(i),g}return i}compileAndRun(e,t,n,a,r=!1){return n=n||t[0].dtype,this.runWebGLProgram(e,t,n,a,r)}getAndSaveBinary(e,t){return e in this.binaryCache||(this.binaryCache[e]=t()),this.binaryCache[e]}getTextureManager(){return this.textureManager}dispose(){this.disposed||(G().getBool("IS_TEST")||Object.keys(this.binaryCache).forEach(e=>{this.gpgpu.deleteProgram(this.binaryCache[e].webGLProgram),delete this.binaryCache[e]}),this.textureManager.dispose(),this.canvas!=null&&typeof HTMLCanvasElement!="undefined"&&this.canvas instanceof HTMLCanvasElement?this.canvas.remove():this.canvas=null,this.gpgpuCreatedLocally&&(this.gpgpu.program=null,this.gpgpu.dispose()),this.disposed=!0)}floatPrecision(){return this.floatPrecisionValue==null&&(this.floatPrecisionValue=P(()=>{if(!G().get("WEBGL_RENDER_FLOAT32_ENABLED")){let e=G().getBool("DEBUG");G().set("DEBUG",!1);let t=this.abs(ve(1e-8)).dataSync()[0];if(G().set("DEBUG",e),t>0)return 32}return 16})),this.floatPrecisionValue}epsilon(){return this.floatPrecision()===32?NQ:TQ}uploadToGPU(e){let t=this.texData.get(e),{shape:n,dtype:a,values:r,texture:s,usage:i,isPacked:o}=t;if(s!=null)return;let l=this.activeTimers!=null,u;l&&(u=w.now());let p=t.texShape;if(p==null&&(p=UE(n,o),t.texShape=p),r!=null){let d=pc(n),c,h=p[1],m=p[0],f=r instanceof Uint8Array||r instanceof Uint8ClampedArray;(o||!f)&&([h,m]=xp(p[0],p[1])),o?c=new h9(d,f):c=new fS(d,f);let g=f?[m,h]:p,b=this.makeTensorInfo(g,a),y=this.texData.get(b.dataId);f?y.usage=ha.PIXELS:y.usage=ha.UPLOAD,y.texShape=g,this.gpgpu.uploadDenseMatrixToTexture(this.getTexture(b.dataId),h,m,r);let x=[[m,h]],v=!0,I=this.runWebGLProgram(c,[b],a,x,v),T=this.texData.get(I.dataId);t.texShape=T.texShape,t.isPacked=T.isPacked,t.usage=T.usage,G().get("ENGINE_COMPILE_ONLY")?this.disposeData(I.dataId):(t.texture=T.texture,t.values=null,this.texData.delete(I.dataId)),this.disposeIntermediateTensorInfo(b),l&&(this.uploadWaitMs+=w.now()-u)}else{let d=this.acquireTexture(p,i,a,o);t.texture=d}}convertAndCacheOnCPU(e,t){let n=this.texData.get(e),{dtype:a}=n;return t!=null&&(n.values=FQ(t,a)),n.values}acquireTexture(e,t,n,a){if(this.numBytesInGPU+=this.computeBytes(e,n),!this.warnedAboutMemory&&this.numBytesInGPU>this.numMBBeforeWarning*1024*1024){let r=(this.numBytesInGPU/1024/1024).toFixed(2);this.warnedAboutMemory=!0,console.warn(`High memory usage in GPU: ${r} MB, most likely due to a memory leak`)}return this.textureManager.acquireTexture(e,t,a)}computeBytes(e,t){return e[0]*e[1]*w.bytesPerElement(t)}checkCompileCompletion(){for(let[,e]of Object.entries(this.binaryCache))this.checkCompletion_(e)}async checkCompileCompletionAsync(){let e=[];if(this.gpgpu.parallelCompilationExtension){for(let[,t]of Object.entries(this.binaryCache))e.push(this.checkCompletionAsync_(t));return Promise.all(e)}else{for(let[,t]of Object.entries(this.binaryCache)){let n=new Promise(a=>{try{this.checkCompletion_(t),a(!0)}catch(r){throw r}});e.push(n)}return Promise.all(e)}}async checkCompletionAsync_(e){return this.gpgpu.gl.getProgramParameter(e.webGLProgram,this.gpgpu.parallelCompilationExtension.COMPLETION_STATUS_KHR)?this.checkCompletion_(e):(await Qw(),this.checkCompletionAsync_(e))}checkCompletion_(e){if(this.gpgpu.gl.getProgramParameter(e.webGLProgram,this.gpgpu.gl.LINK_STATUS)===!1)throw console.log(this.gpgpu.gl.getProgramInfoLog(e.webGLProgram)),this.gpgpu.gl.getShaderParameter(e.fragmentShader,this.gpgpu.gl.COMPILE_STATUS)===!1?(Q1(e.source,this.gpgpu.gl.getShaderInfoLog(e.fragmentShader)),new Error("Failed to compile fragment shader.")):new Error("Failed to link vertex and fragment shaders.");return!0}getUniformLocations(){for(let e of Object.values(this.binaryCache)){this.gpgpu.buildVao(e.webGLProgram);let{variablesLocations:t,customUniformLocations:n,infLoc:a,nanLoc:r,outShapeLocation:s,outShapeStridesLocation:i,outTexShapeLocation:o}=eA(this.gpgpu,e.program,e.webGLProgram);e.variablesLocations=t,e.customUniformLocations=n,e.infLoc=a,e.nanLoc=r,e.outShapeLocation=s,e.outShapeStridesLocation=i,e.outTexShapeLocation=o}}createTensorFromGPUData(e,t,n){e.channels=e.channels||"RGBA";let{texture:a,height:r,width:s,channels:i}=e,o=Aa().backend;if(!o.gpgpu.gl.isTexture(a))throw new Error("The texture is invalid. Also, please make sure the texture and the TFJS WebGL backend are using the same canvas. If you want to use your own custom canvas, you have to create and use the custom TFJS WebGL backend created from the canvas through 'new tf.MathBackendWebGL(customCanvas)'.");let l=o.writeTexture(a,t,n,r,s,i);return Aa().makeTensorFromDataId(l,t,n,o)}};Qf.nextDataId=0;function FQ(e,t){if(t==="float32"||t==="complex64")return e;if(t==="int32"||t==="bool"){let n=t==="int32"?new Int32Array(e.length):new Uint8Array(e.length);for(let a=0;a<n.length;++a)n[a]=Math.round(e[a]);return n}else throw new Error(`Unknown dtype ${t}`)}var $Q="4.7.0";function IA(){G().set("WEBGL_FORCE_F16_TEXTURES",!0)}od.isBrowser()&&Zm("webgl",()=>new Qf,2);var DQ={forceHalfFloat:IA},uk=`
| if (isnan(a)) return a;
| if (isnan(b)) return b;
| `,Ii=class{constructor(e,t,n){this.variableNames=["A","B"],this.outputShape=N.assertAndGetBroadcastShape(t,n),this.enableShapeUniforms=vn(this.outputShape.length),this.userCode=`
| float binaryOperation(float a, float b) {
| ${e}
| }
|
| void main() {
| float a = getAAtOutCoords();
| float b = getBAtOutCoords();
| setOutput(binaryOperation(a, b));
| }
| `}},el=`
| result.r = isNaN.r ? NAN : result.r;
| result.g = isNaN.g ? NAN : result.g;
| result.b = isNaN.b ? NAN : result.b;
| result.a = isNaN.a ? NAN : result.a;
| `,Np=class{constructor(e,t,n,a=!1){this.variableNames=["A","B"],this.supportsBroadcasting=!0,this.packedInputs=!0,this.packedOutput=!0,this.outputShape=N.assertAndGetBroadcastShape(t,n);let r=this.outputShape.length;this.enableShapeUniforms=vn(r);let s="";if(a)if(r===0||w.sizeFromShape(this.outputShape)===1)s=`
| result.y = 0.;
| result.z = 0.;
| result.w = 0.;
| `;else if(s=`
| ${dt(r)} coords = getOutputCoords();
| `,r===1)this.enableShapeUniforms?s+=`
| result.y = (coords + 1) >= outShape ? 0. : result.y;
| result.z = 0.;
| result.w = 0.;
| `:s+=`
| result.y = (coords + 1) >= ${this.outputShape[0]} ? 0. : result.y;
| result.z = 0.;
| result.w = 0.;
| `;else{let i=Sn("coords",r);this.enableShapeUniforms?s+=`
| bool nextRowOutOfBounds =
| (${i[r-2]} + 1) >= outShape[${r} - 2];
| bool nextColOutOfBounds =
| (${i[r-1]} + 1) >= outShape[${r} - 1];
| result.y = nextColOutOfBounds ? 0. : result.y;
| result.z = nextRowOutOfBounds ? 0. : result.z;
| result.w = nextColOutOfBounds || nextRowOutOfBounds ? 0. : result.w;
| `:s+=`
| bool nextRowOutOfBounds =
| (${i[r-2]} + 1) >= ${this.outputShape[r-2]};
| bool nextColOutOfBounds =
| (${i[r-1]} + 1) >= ${this.outputShape[r-1]};
| result.y = nextColOutOfBounds ? 0. : result.y;
| result.z = nextRowOutOfBounds ? 0. : result.z;
| result.w = nextColOutOfBounds || nextRowOutOfBounds ? 0. : result.w;
| `}this.userCode=`
| vec4 binaryOperation(vec4 a, vec4 b) {
| ${e}
| }
|
| void main() {
| vec4 a = getAAtOutCoords();
| vec4 b = getBAtOutCoords();
|
| vec4 result = binaryOperation(a, b);
| ${s}
|
| setOutput(result);
| }
| `}};function ra(e){let{inputs:t,backend:n}=e,{x:a}=t;return n.incRef(a.dataId),{dataId:a.dataId,shape:a.shape,dtype:a.dtype}}var RQ={kernelName:to,backendName:"webgl",kernelFunc:ra};function Ms(e){let{inputs:t,backend:n}=e,{real:a,imag:r}=t,s=n.makeTensorInfo(a.shape,"complex64"),i=n.texData.get(s.dataId),o=ra({inputs:{x:a},backend:n}),l=ra({inputs:{x:r},backend:n});return i.complexTensorInfos={real:o,imag:l},s}var MQ={kernelName:Om,backendName:"webgl",kernelFunc:Ms},SA="return (a < 0.) ? b * a : a;",NA=`
| vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));
| return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);
| `;function PQ(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{alpha:s}=a,i=n.makeTensorInfo([],"float32",w.createScalarValue(s,"float32")),o=G().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new Np(NA,r.shape,i.shape):new Ii(SA,r.shape,i.shape),l=n.runWebGLProgram(o,[r,i],"float32");return n.disposeIntermediateTensorInfo(i),l}var OQ={kernelName:so,backendName:"webgl",kernelFunc:PQ},TA="return (a < 0.) ? b * a : a;",CA=`
| vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));
| return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);
| `;function LQ(e){let{inputs:t,backend:n}=e,{x:a,alpha:r}=t,s=G().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new Np(CA,a.shape,r.shape):new Ii(TA,a.shape,r.shape);return n.runWebGLProgram(s,[a,r],"float32")}var zQ={kernelName:ko,backendName:"webgl",kernelFunc:LQ},Tp="if (isnan(x)) return x;";function Ze({opSnippet:e,packedOpSnippet:t,cpuKernelImpl:n,dtype:a}){return({inputs:r,backend:s})=>{let{x:i}=r,o=s,l=a||i.dtype;if(o.shouldExecuteOnCPU([i])&&n!=null){let d=o.texData.get(i.dataId),c=n(d.values,l);return o.makeTensorInfo(i.shape,l,c)}let u=G().getBool("WEBGL_PACK_UNARY_OPERATIONS")&&t!=null,p;return u?p=new os(i.shape,t):p=new ir(i.shape,e),o.runWebGLProgram(p,[i],l)}}function fn({opSnippet:e,packedOpSnippet:t,checkOutOfBounds:n=!1,supportsComplex:a=!1,cpuKernelImpl:r,dtype:s}){return({inputs:i,backend:o})=>{let{a:l,b:u}=i,p=o;if(a&&l.dtype==="complex64"){let m=p.texData.get(l.dataId),f=p.texData.get(u.dataId),[g,b]=[[m.complexTensorInfos.real,f.complexTensorInfos.real],[m.complexTensorInfos.imag,f.complexTensorInfos.imag]].map(x=>{let[v,I]=x,T={dataId:v.dataId,dtype:v.dtype,shape:l.shape},C={dataId:I.dataId,dtype:I.dtype,shape:u.shape},E=new Ii(e,l.shape,u.shape);return p.runWebGLProgram(E,[T,C],ba(v.dtype,I.dtype))}),y=Ms({inputs:{real:g,imag:b},backend:p});return p.disposeIntermediateTensorInfo(g),p.disposeIntermediateTensorInfo(b),y}let d=s||ba(l.dtype,u.dtype);if((l.dtype==="string"||u.dtype==="string"||p.shouldExecuteOnCPU([l,u]))&&r!=null){let m=p.texData.get(l.dataId).values,f=p.texData.get(u.dataId).values,g=l.dtype==="string"?N.fromUint8ToStringArray(m):m,b=l.dtype==="string"?N.fromUint8ToStringArray(f):f,[y,x]=r(l.shape,u.shape,g,b,d),v=p.makeTensorInfo(x,d),I=p.texData.get(v.dataId);return I.values=y,v}let c=G().getBool("WEBGL_PACK_BINARY_OPERATIONS")&&t!=null,h;return c?h=new Np(t,l.shape,u.shape,n):h=new Ii(e,l.shape,u.shape),p.runWebGLProgram(h,[l,u],d)}}function Fc(e,t=!1){if(e==="linear")return t?yQ:hQ;if(e==="relu")return t?vQ:fQ;if(e==="elu")return t?xQ:mQ;if(e==="relu6")return t?wQ:gQ;if(e==="prelu")return t?CA:TA;if(e==="leakyrelu")return t?NA:SA;if(e==="sigmoid")return t?kQ:bQ;throw new Error(`Activation ${e} has not been implemented for the WebGL backend.`)}var _A=class{constructor(e,t,n,a=!1,r=!1,s=!1,i=null,o=!1,l=!1){this.variableNames=["matrixA","matrixB"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=n,this.enableShapeUniforms=vn(this.outputShape.length);let u=a?e[1]:e[2],p=Math.ceil(u/2),d=a?"i * 2, rc.y":"rc.y, i * 2",c=r?"rc.z, i * 2":"i * 2, rc.z",h=a?["a.xxyy","a.zzww"]:["a.xxzz","a.yyww"],m=r?["b.xzxz","b.ywyw"]:["b.xyxy","b.zwzw"],f="",g="";i&&(o?f=`vec4 activation(vec4 a) {
| vec4 b = getPreluActivationWeightsAtOutCoords();
| ${i}
| }`:l?f=`vec4 activation(vec4 a) {
| vec4 b = getLeakyreluAlphaAtOutCoords();
| ${i}
| }`:f=`vec4 activation(vec4 x) {
| ${i}
| }`,g="result = activation(result);");let b=s?"result += getBiasAtOutCoords();":"";s&&this.variableNames.push("bias"),o&&this.variableNames.push("preluActivationWeights"),l&&this.variableNames.push("leakyreluAlpha");let y="rc.x",x="rc.x";e[0]<t[0]?y=`imod(rc.x, ${e[0]})`:t[0]<e[0]&&(x=`imod(rc.x, ${t[0]})`),this.userCode=`
| ${f}
| // Don't use uniform for sharedDimensionPacked for performance.
| const float sharedDimension = ${p}.0;
|
| vec4 dot2x2ARowBCol(ivec3 rc) {
| vec4 result = vec4(0);
| int batchA = ${y};
| int batchB = ${x};
| for (int i = 0; i < ${p}; i++) {
| vec4 a = getMatrixA(batchA, ${d});
| vec4 b = getMatrixB(batchB, ${c});
|
| // These swizzled products need to be separately added.
| // See: https://github.com/tensorflow/tfjs/issues/1735
| result += (${h[0]} * ${m[0]});
| result += (${h[1]} * ${m[1]});
| }
| return result;
| }
|
| void main() {
| ivec3 rc = getOutputCoords();
| vec4 result = dot2x2ARowBCol(rc);
|
| ${b}
|
| ${g}
|
| setOutput(result);
| }
| `}},vS={REAL:"return areal * breal - aimag * bimag;",IMAG:"return areal * bimag + aimag * breal;"},wS=class{constructor(e,t,n){this.variableNames=["AReal","AImag","BReal","BImag"],this.outputShape=N.assertAndGetBroadcastShape(t,n),this.userCode=`
| float binaryOpComplex(
| float areal, float aimag, float breal, float bimag) {
| ${e}
| }
|
| void main() {
| float areal = getARealAtOutCoords();
| float aimag = getAImagAtOutCoords();
| float breal = getBRealAtOutCoords();
| float bimag = getBImagAtOutCoords();
| setOutput(binaryOpComplex(areal, aimag, breal, bimag));
| }
| `}},kS="return a * b;";function pk(e){let{inputs:t,backend:n}=e,{a,b:r}=t,s=N.upcastType(a.dtype,r.dtype);if(a.dtype==="complex64"){let o=n.texData.get(a.dataId),l=n.texData.get(r.dataId),u=new wS(vS.REAL,a.shape,r.shape),p=new wS(vS.IMAG,a.shape,r.shape),d=[{dataId:o.complexTensorInfos.real.dataId,dtype:o.complexTensorInfos.real.dtype,shape:a.shape},{dataId:o.complexTensorInfos.imag.dataId,dtype:o.complexTensorInfos.imag.dtype,shape:a.shape},{dataId:l.complexTensorInfos.real.dataId,dtype:l.complexTensorInfos.real.dtype,shape:r.shape},{dataId:l.complexTensorInfos.imag.dataId,dtype:l.complexTensorInfos.imag.dtype,shape:r.shape}],c=n.runWebGLProgram(u,d,"float32"),h=n.runWebGLProgram(p,d,"float32"),m=Ms({inputs:{real:c,imag:h},backend:n});return n.disposeIntermediateTensorInfo(c),n.disposeIntermediateTensorInfo(h),m}if(n.shouldExecuteOnCPU([a,r])){let o=n.texData.get(a.dataId),l=n.texData.get(r.dataId),[u,p]=P9(a.shape,r.shape,o.values,l.values,s),d=n.makeTensorInfo(p,s),c=n.texData.get(d.dataId);return c.values=u,d}let i;return G().getBool("WEBGL_PACK_BINARY_OPERATIONS")?i=new Np(kS,a.shape,r.shape):i=new Ii(kS,a.shape,r.shape),n.runWebGLProgram(i,[a,r],s)}var WQ={kernelName:yo,backendName:"webgl",kernelFunc:pk};function BQ(e,t,n){let a=[wi(e.shape),...ki(e.shape)],r={dtype:e.dtype,shape:a,dataId:e.dataId},s=[wi(t),...ki(t)],i=new kA(s,a),o=!0,l=[a],u=n.runWebGLProgram(i,[r],e.dtype,l,o);return{dataId:u.dataId,shape:t,dtype:u.dtype}}function ce(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{shape:s}=a,i=n,o=w.sizeFromShape(r.shape),l=w.inferFromImplicitShape(s,o),u=w.sizeFromShape(l);w.assert(o===u,()=>`The new shape (${l}) has ${u} elements and the old shape (${r.shape}) has ${o} elements. The new shape and old shape must have the same number of elements.`);let p=i.texData.get(r.dataId);return p.isPacked&&!Ac(r.shape,l)&&!(p.texture!==null&&Ac(p.shape,l))?BQ(r,l,i):(i.incRef(r.dataId),{dataId:r.dataId,shape:l,dtype:r.dtype})}var VQ={kernelName:qu,backendName:"webgl",kernelFunc:ce},IS=class{constructor(e,t){this.variableNames=["x"];let{windowSize:n,batchSize:a,inSize:r,outSize:s}=e;this.outputShape=[a,s];let i=Math.floor(n/4)*4,o=n%4,l="sumValue += dot(values, ones);";if(t!=null){let p=1/t;l=`sumValue += dot(values * ${w.isInt(p)?p.toPrecision(2):p}, ones);`}let u="";r%n>0&&(u=`
| if (inIdx < 0 || inIdx >= ${r}) {
| return 0.0;
| }
| `),this.userCode=`
| const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);
|
| float getValue(int batch, int inIdx) {
| ${u}
| return getX(batch, inIdx);
| }
|
| void main() {
| ivec2 coords = getOutputCoords();
| int batch = coords[0];
| int outIdx = coords[1];
| int inOffset = outIdx * ${n};
|
| float sumValue = 0.0;
|
| for (int i = 0; i < ${i}; i += 4) {
| int inIdx = inOffset + i;
| vec4 values = vec4(
| getValue(batch, inIdx),
| getValue(batch, inIdx + 1),
| getValue(batch, inIdx + 2),
| getValue(batch, inIdx + 3)
| );
|
| ${l}
| }
|
| int inIdx = inOffset + ${i};
| if (${o===1}) {
| vec4 values = vec4(getValue(batch, inIdx), 0.0, 0.0, 0.0);
|
| ${l}
| } else if (${o===2}) {
| vec4 values = vec4(
| getValue(batch, inIdx),
| getValue(batch, inIdx + 1), 0.0, 0.0);
|
| ${l}
| } else if (${o===3}) {
| vec4 values = vec4(
| getValue(batch, inIdx),
| getValue(batch, inIdx + 1),
| getValue(batch, inIdx + 2), 0.0);
|
| ${l}
| }
| setOutput(sumValue);
| }
| `}},UQ=class{constructor(e,t){this.variableNames=["x"];let{windowSize:n,batchSize:a,inSize:r,outSize:s}=e;this.outputShape=[a,s];let i="0.0",o="";t==="prod"?i="1.0":t==="min"?(i="1.0 / 1e-20",o="min"):t==="max"&&(i="-1.0 / 1e-20",o="max");let l=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="sum"?l="sumValue":t==="prod"?l="prodValue":t==="all"?l="allValue":t==="any"&&(l="anyValue");let u=Math.floor(n/4)*4,p=n%4,d=`
| if (${t==="sum"}) {
| sumValue += dot(values, ones);
| } else if (${t==="prod"}) {
| vec2 tmp = vec2(values[0], values[1]) * vec2(values[2], values[3]);
| prodValue *= tmp[0] * tmp[1];
| } else {
| minMaxValue = ${o}(values, minMaxValue);
| if (${t==="min"} || ${t==="max"}) {
| minMaxValue = ${o}(values, minMaxValue);
| bvec4 isNaN = isnan(values);
| if (isNaN.r || isNaN.g || isNaN.b || isNaN.a) {
| minMaxValue = vec4(NAN);
| }
| }
| }
| `,c="vec4";t==="all"?(i="1.0",d=`
| bool reducedAllValue = all(values);
| float floatedReducedAllValue = float(reducedAllValue);
| allValue = float(allValue >= 1.0 && floatedReducedAllValue >= 1.0);
| `,c="bvec4"):t==="any"&&(i="0.0",d=`
| bool reducedAnyValue = any(values);
| float floatedReducedAnyValue = float(reducedAnyValue);
| anyValue = float(anyValue >= 1.0 || floatedReducedAnyValue >= 1.0);
| `,c="bvec4");let h="";r%n>0&&(h=`
| if (inIdx < 0 || inIdx >= ${r}) {
| return initializationValue;
| }
| `),this.userCode=`
| const float initializationValue = ${i};
| const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);
|
| float getValue(int batch, int inIdx) {
| ${h}
| return getX(batch, inIdx);
| }
|
| void main() {
| ivec2 coords = getOutputCoords();
| int batch = coords[0];
| int outIdx = coords[1];
| int inOffset = outIdx * ${n};
|
| vec4 minMaxValue = vec4(${i});
| float prodValue = 1.0;
| float sumValue = 0.0;
| float allValue = 1.0;
| float anyValue = 0.0;
|
| for (int i = 0; i < ${u}; i += 4) {
| int inIdx = inOffset + i;
| ${c} values = ${c}(
| getValue(batch, inIdx),
| getValue(batch, inIdx + 1),
| getValue(batch, inIdx + 2),
| getValue(batch, inIdx + 3)
| );
|
| ${d}
| }
|
| int inIdx = inOffset + ${u};
| if (${p===1}) {
| ${c} values = ${c}(
| getValue(batch, inIdx),
| initializationValue,
| initializationValue,
| initializationValue
| );
|
| ${d}
| } else if (${p===2}) {
| ${c} values = ${c}(
| getValue(batch, inIdx),
| getValue(batch, inIdx + 1),
| initializationValue,
| initializationValue
| );
|
| ${d}
| } else if (${p===3}) {
| ${c} values = ${c}(
| getValue(batch, inIdx),
| getValue(batch, inIdx + 1),
| getValue(batch, inIdx + 2),
| initializationValue
| );
|
| ${d}
| }
| setOutput(${l});
| }
| `}};function GQ(e){let t=[];for(;t.length===0||t[t.length-1].outSize!==1;){let n=t.length?t[t.length-1].outSize:e[1],a=N.computeOptimalWindowSize(n);t.push({inSize:n,windowSize:a,outSize:Math.ceil(n/a)})}return t}function tl(e,t,n,a){let r=GQ(e.shape),s=e;for(let i=0;i<r.length;i++){let{inSize:o,windowSize:l,outSize:u}=r[i],p,d;n==="mean"?p=i===0?new IS({windowSize:l,inSize:o,batchSize:e.shape[0],outSize:u},o):new IS({windowSize:l,inSize:o,batchSize:e.shape[0],outSize:u}):p=new UQ({windowSize:l,inSize:o,batchSize:e.shape[0],outSize:u},n),d=s,s=a.runWebGLProgram(p,[s],t),d.dataId!==e.dataId&&a.disposeIntermediateTensorInfo(d)}return s}var HQ=class{constructor(e,t){this.variableNames=["A"];let n=new Array(e.length);for(let s=0;s<n.length;s++)n[s]=e[t[s]];this.outputShape=n,this.rank=n.length;let a=dt(this.rank),r=qQ(t);this.userCode=`
| void main() {
| ${a} resRC = getOutputCoords();
| setOutput(getA(${r}));
| }
| `}};function qQ(e){let t=e.length;if(t>6)throw Error(`Transpose for rank ${t} is not yet supported`);let n=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u","resRC.v"],a=new Array(t);for(let r=0;r<e.length;r++)a[e[r]]=n[r];return a.join()}var jQ=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0;let n=new Array(e.length);for(let u=0;u<n.length;u++)n[u]=e[t[u]];if(this.outputShape=n,this.rank=n.length,this.rank>6)throw Error(`Packed transpose for rank ${this.rank} is not yet supported.`);let a=dt(this.rank),r=wA("rc",this.rank),s=new Array(this.rank);for(let u=0;u<t.length;u++)s[t[u]]=r[u];let i=`vec2(${s.slice(-2).join()})`,o=`++${r[this.rank-1]} < ${n[this.rank-1]}`,l=`getChannel(getA(${s.join()}), ${i})`;this.userCode=`
| void main() {
| ${a} rc = getOutputCoords();
| vec4 result = vec4(0.);
| result[0] = ${l};
| if(${o}) {
| result[1] = ${l};
| }
| --${r[this.rank-1]};
| if(++${r[this.rank-2]} < ${n[this.rank-2]}) {
| result[2] = ${l};
| if(${o}) {
| result[3] = ${l};
| }
| }
| setOutput(result);
| }
| `}};function eg(e,t,n){let a=G().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new jQ(e.shape,t):new HQ(e.shape,t);return n.runWebGLProgram(a,[e],e.dtype)}function KQ(e,t,n,a){let r=t,s=e.shape.length,i=w.parseAxisParam(r,e.shape),o=i,l=N.getAxesPermutation(o,s),u=l!=null,p=e;u&&(p=eg(e,l,a),o=N.getInnerMostAxes(o.length,s)),N.assertAxesAreInnerMostDims("sum",o,s);let[d,c]=N.computeOutAndReduceShapes(p.shape,o),h=d;n&&(h=N.expandShapeToKeepDim(d,i));let m=w.sizeFromShape(c),f=w.sizeFromShape(e.shape)/m,g=ce({inputs:{x:p},attrs:{shape:[f,m]},backend:a}),b=Ym(e.dtype),y=tl(g,b,"sum",a),x=ce({inputs:{x:y},attrs:{shape:h},backend:a});return a.disposeIntermediateTensorInfo(g),a.disposeIntermediateTensorInfo(y),u&&a.disposeIntermediateTensorInfo(p),x}function tg(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{axis:s,keepDims:i}=a;return KQ(r,s,i,n)}var XQ={kernelName:zo,backendName:"webgl",kernelFunc:tg};function Nn(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{perm:s}=a,i=n,o=r.shape.length,l=new Array(o);for(let p=0;p<l.length;p++)l[p]=r.shape[s[p]];let u;if(i.shouldExecuteOnCPU([r])){let p=i.texData.get(r.dataId).values,d=lk(p,r.shape,r.dtype,s,l);u=i.makeTensorInfo(l,r.dtype);let c=i.texData.get(u.dataId);c.values=d}else u=eg(r,s,i);return u}var YQ={kernelName:$r,backendName:"webgl",kernelFunc:Nn},EA=1e3;function Em({a:e,b:t,transposeA:n,transposeB:a,backend:r,bias:s=null,preluActivationWeights:i=null,leakyreluAlpha:o=0,activation:l=null}){let u=e.shape.length,p=t.shape.length,d=n?e.shape[u-2]:e.shape[u-1],c=a?t.shape[p-1]:t.shape[p-2],h=n?e.shape[u-1]:e.shape[u-2],m=a?t.shape[p-2]:t.shape[p-1],f=e.shape.slice(0,-2),g=t.shape.slice(0,-2),b=w.sizeFromShape(f),y=w.sizeFromShape(g),x=pp.assertAndGetBroadcastShape(e.shape.slice(0,-2),t.shape.slice(0,-2)).concat([h,m]);w.assert(d===c,()=>`Error in matMul: inner shapes (${d}) and (${c}) of Tensors with shapes ${e.shape} and ${t.shape} and transposeA=${n} and transposeB=${a} must match.`);let v=n?[b,d,h]:[b,h,d],I=a?[y,m,c]:[y,c,m],T=ce({inputs:{x:e},backend:r,attrs:{shape:v}}),C=ce({inputs:{x:t},backend:r,attrs:{shape:I}}),E=[T,C],F=Math.max(b,y),D=n?T.shape[1]:T.shape[2],$=s!=null,S=i!=null,M=l==="leakyrelu",B=l!=null?Fc(l,!0):null,U=$||S||M||B!=null,H;if((h===1||m===1)&&D>EA&&U===!1){let K=T,Z=C;n&&(K=Nn({inputs:{x:T},backend:r,attrs:{perm:[0,2,1]}}),E.push(K)),a&&(Z=Nn({inputs:{x:C},backend:r,attrs:{perm:[0,2,1]}}),E.push(Z));let J=m!==1,ee=m===1,ae=K;J&&(ae=ce({inputs:{x:K},backend:r,attrs:{shape:[F,D,1]}}),E.push(ae));let te=m===1?2:1,re=Z;ee&&(re=ce({inputs:{x:Z},backend:r,attrs:{shape:[F,1,D]}}),E.push(re));let ie=pk({inputs:{a:ae,b:re},backend:r});H=tg({inputs:{x:ie},backend:r,attrs:{axis:te,keepDims:!0}}),E.push(ie)}else{let K=ba(e.dtype,t.dtype),Z=new _A(v,I,[F,h,m],n,a,$,B,S,M),J=[T,C];if(s!=null&&J.push(s),S&&J.push(i),M){let ee=r.makeTensorInfo([],"float32",w.createScalarValue(o,"float32"));J.push(ee),E.push(ee)}H=r.runWebGLProgram(Z,J,K)}let j=ce({inputs:{x:H},backend:r,attrs:{shape:x}});E.push(H);for(let K of E)r.disposeIntermediateTensorInfo(K);return j}function ZQ(e){let{inputs:t,backend:n,attrs:a}=e,{a:r,b:s,bias:i,preluActivationWeights:o}=t,{transposeA:l,transposeB:u,activation:p,leakyreluAlpha:d}=a;return Em({a:r,b:s,transposeA:l,transposeB:u,backend:n,bias:i,preluActivationWeights:o,leakyreluAlpha:d,activation:p})}var JQ={kernelName:oi,backendName:"webgl",kernelFunc:ZQ},SS="return abs(x);";function QQ(e){let{inputs:t,backend:n}=e,{x:a}=t;if(n.shouldExecuteOnCPU([a])&&a.dtype!=="complex64"){let s=n.texData.get(a.dataId),i=xA(s.values);return n.makeTensorInfo(a.shape,a.dtype,i)}let r;return G().getBool("WEBGL_PACK_UNARY_OPERATIONS")?r=new os(a.shape,SS):r=new ir(a.shape,SS),n.runWebGLProgram(r,[a],a.dtype)}var eee={kernelName:lu,backendName:"webgl",kernelFunc:QQ},tee=Oa+`
| if (abs(x) > 1.) {
| return NAN;
| }
| return acos(x);
| `,nee=Ze({opSnippet:tee}),aee={kernelName:Ti,backendName:"webgl",kernelFunc:nee},ree=Oa+`
| if (x < 1.0) return NAN;
| return log(x + sqrt(x * x - 1.0));`,see=Ze({opSnippet:ree}),iee={kernelName:Ci,backendName:"webgl",kernelFunc:see},NS="return a + b;",oee=fn({opSnippet:NS,packedOpSnippet:NS,supportsComplex:!0,cpuKernelImpl:f9}),lee={kernelName:Is,backendName:"webgl",kernelFunc:oee},uee=class{constructor(e,t){this.outputShape=[],this.outputShape=e,this.variableNames=t.map((r,s)=>`T${s}`);let n=[];this.variableNames.forEach(r=>{n.push(`float v${r} = get${r}AtOutCoords();`)});let a=this.variableNames.map(r=>`v${r}`).join(" + ");this.userCode=`
| void main() {
| ${n.join(`
| `)}
|
| float result = ${a};
| setOutput(result);
| }
| `}},pee=class{constructor(e,t){this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.variableNames=t.map((r,s)=>`T${s}`);let n=[];this.variableNames.forEach(r=>{n.push(`vec4 v${r} = get${r}AtOutCoords();`)});let a=this.variableNames.map(r=>`v${r}`).join(" + ");this.userCode=`
| void main() {
| ${n.join(`
| `)}
|
| vec4 result = ${a};
| setOutput(result);
| }
| `}};function nm(e){let{inputs:t,backend:n}=e,a=t;if(a.length===1)return ra({inputs:{x:a[0]},backend:n});if(a.length>G().get("WEBGL_MAX_TEXTURES_IN_SHADER")){let o=Math.floor(a.length/2),l=nm({inputs:a.slice(0,o),backend:n}),u=nm({inputs:a.slice(o),backend:n});return nm({inputs:[l,u],backend:n})}let r=a.map(o=>o.dtype).reduce((o,l)=>ba(o,l)),s=a.map(o=>o.shape),i=G().getBool("WEBGL_PACK")?new pee(a[0].shape,s):new uee(a[0].shape,s);return n.runWebGLProgram(i,a,r)}var cee={kernelName:_i,backendName:"webgl",kernelFunc:nm};function dee(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{axis:s,keepDims:i}=a,o=r.shape.length,l=w.parseAxisParam(s,r.shape),u=l,p=N.getAxesPermutation(u,o),d=r;p!=null&&(d=Nn({inputs:{x:r},backend:n,attrs:{perm:p}}),u=N.getInnerMostAxes(u.length,o)),N.assertAxesAreInnerMostDims("all",u,o);let[c,h]=N.computeOutAndReduceShapes(d.shape,u),m=w.sizeFromShape(h),f=ce({inputs:{x:d},backend:n,attrs:{shape:[-1,m]}}),g=tl(f,f.dtype,"all",n),b;if(i){let y=N.expandShapeToKeepDim(c,l);b=ce({inputs:{x:g},backend:n,attrs:{shape:y}})}else b=ce({inputs:{x:g},backend:n,attrs:{shape:c}});return n.disposeIntermediateTensorInfo(f),n.disposeIntermediateTensorInfo(g),p!=null&&n.disposeIntermediateTensorInfo(d),b}var hee={kernelName:uu,backendName:"webgl",kernelFunc:dee};function mee(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{axis:s,keepDims:i}=a,o=r.shape.length,l=w.parseAxisParam(s,r.shape),u=l,p=N.getAxesPermutation(u,o),d=r;p!=null&&(d=Nn({inputs:{x:r},backend:n,attrs:{perm:p}}),u=N.getInnerMostAxes(u.length,o)),N.assertAxesAreInnerMostDims("any",u,o);let[c,h]=N.computeOutAndReduceShapes(d.shape,u),m=w.sizeFromShape(h),f=ce({inputs:{x:d},backend:n,attrs:{shape:[-1,m]}}),g=tl(f,f.dtype,"any",n),b;if(i){let y=N.expandShapeToKeepDim(c,l);b=ce({inputs:{x:g},backend:n,attrs:{shape:y}})}else b=ce({inputs:{x:g},backend:n,attrs:{shape:c}});return n.disposeIntermediateTensorInfo(f),n.disposeIntermediateTensorInfo(g),p!=null&&n.disposeIntermediateTensorInfo(d),b}var fee={kernelName:pu,backendName:"webgl",kernelFunc:mee},gee=class{constructor(e,t,n){this.variableNames=["A"];let{windowSize:a,batchSize:r,outSize:s}=e;n||this.variableNames.push("bestIndicesA"),this.outputShape=[r,s];let i=t==="max"?">":"<",o=n?"inOffset + i;":"round(getBestIndicesA(batch, inOffset + i));";this.userCode=`
| void main() {
| ivec2 coords = getOutputCoords();
| int batch = coords[0];
| int outIdx = coords[1];
| int inOffset = outIdx * ${a};
|
| int bestIndex = inOffset;
| float bestValue = getA(batch, bestIndex);
|
| for (int i = 0; i < ${a}; i++) {
| int inIdx = ${o};
| float candidate = getA(batch, inIdx);
| if (candidate ${i} bestValue) {
| bestValue = candidate;
| bestIndex = inIdx;
| }
| }
| setOutput(float(bestIndex));
| }
| `}},bee=class{constructor(e,t,n,a){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,w.assert(e.length>2,()=>`Packed arg${n.charAt(0).toUpperCase()+n.slice(1)} supports only inputs with rank above 2.`);let r=e[e.length-1],s=Math.ceil(r/t);this.outputShape=e.slice(0,-1),s>1&&this.outputShape.push(s),a||this.variableNames.push("bestIndicesA");let i=this.outputShape,o=i.length,l=dt(o),u=Sn("coords",o),p,d;if(s===1){d=o+1;let C=dt(d);p=`
| ${C} sourceLocR = ${C}(${u.join()}, 0);
| ++${u[o-1]};
| ${C} sourceLocG = ${C}(${u.join()}, 0);
| ++${u[o-2]};
| ${C} sourceLocA = ${C}(${u.join()}, 0);
| --${u[o-1]};
| ${C} sourceLocB = ${C}(${u.join()}, 0);
| --${u[o-2]};`}else d=o,p=`
| ${l} sourceLocR = coords;
| ++${u[o-1]};
| ${l} sourceLocG = coords;
| ++${u[o-2]};
| ${l} sourceLocA = coords;
| --${u[o-1]};
| ${l} sourceLocB = coords;
| --${u[o-2]};`;let c=["x","y","z","w","u","v"].slice(0,d),h="."+c[d-1],m=c.map(C=>"int "+C),f=Sn("sourceLocR",d-1).concat("inIdx.r"),g=Sn("sourceLocG",d-1).concat("inIdx.g"),b=Sn("sourceLocB",d-1).concat("inIdx.b"),y=Sn("sourceLocA",d-1).concat("inIdx.a"),x=n==="max"?"greaterThan":"lessThan",v=a?"":`
| inIdx = round(vec4(getBestIndicesAChannel(${f.join()}),
| getBestIndicesAChannel(${g.join()}),
| getBestIndicesAChannel(${b.join()}),
| getBestIndicesAChannel(${y.join()})));`,I=`vec4(
| getAChannel(${f.join()}),
| hasNextCol ? getAChannel(${g.join()}) : 0.,
| hasNextRow ? getAChannel(${b.join()}) : 0.,
| hasNextRow && hasNextCol ? getAChannel(${y.join()}) : 0.)`,T=a?"":`
| float getBestIndicesAChannel(${m.join()}) {
| return getChannel(getBestIndicesA(${c.join()}),
| vec2(${c.slice(-2).join()}));
| }`;this.userCode=`
| float getAChannel(${m.join()}) {
| return getChannel(getA(${c.join()}),
| vec2(${c.slice(-2).join()}));
| }
| ${T}
| void main() {
| ${l} coords = getOutputCoords();
| bool hasNextCol = ${u[o-1]} < ${i[o-1]-1};
| bool hasNextRow = ${u[o-2]} < ${i[o-2]-1};
| ${p}
| ivec4 srcIdx = ivec4(sourceLocR${h}, sourceLocG${h},
| sourceLocB${h}, sourceLocA${h}) * ${t};
| ivec4 inIdx = srcIdx;
| vec4 bestIndex = vec4(inIdx);
| vec4 bestValue = ${I};
|
| for (int i = 0; i < ${t}; i++) {
| inIdx = srcIdx;
| ${v}
| vec4 candidate = ${I};
| bvec4 nan = isnan(candidate);
| bvec4 replace = bvec4(
| vec4(${x}(candidate, bestValue)) * (vec4(1.0) - vec4(nan)));
|
| bestValue = vec4(replace.x ? candidate.x : bestValue.x,
| replace.y ? candidate.y : bestValue.y,
| replace.z ? candidate.z : bestValue.z,
| replace.w ? candidate.w : bestValue.w);
| bestIndex = mix(bestIndex, vec4(inIdx), vec4(replace));
| srcIdx++;
| }
| setOutput(bestIndex);
| }
| `}};function AA(e,t,n,a=null){let r=t.shape[0],s=t.shape[1];a!=null&&(r=a.shape[0],s=a.shape[1]);let i=N.computeOptimalWindowSize(s),o={windowSize:i,inSize:s,batchSize:r,outSize:Math.ceil(s/i)},l=new gee(o,n,a==null),u=[t];a!=null&&u.push(a);let p=e.runWebGLProgram(l,u,"int32");if(p.shape[1]===1)return p;let d=AA(e,t,n,p);return e.disposeIntermediateTensorInfo(p),d}function FA(e,t,n,a=null){let r=a!=null?a.shape:t.shape,s=r[r.length-1],i=N.computeOptimalWindowSize(s),o=new bee(r,i,n,a==null),l=a==null?[t]:[t,a],u=e.runWebGLProgram(o,l,"int32");if(u.shape.length===t.shape.length){let p=FA(e,t,n,u);return e.disposeIntermediateTensorInfo(u),p}return u}function $A(e,t,n,a){let r=[n];if(N.assertAxesAreInnerMostDims("arg"+a.charAt(0).toUpperCase()+a.slice(1),r,t.shape.length),!G().getBool("WEBGL_PACK_REDUCE")||t.shape.length<=2){let s=[],i=e.texData.get(t.dataId),o=i!==null&&i.isPacked,l=t;o&&(l=e.unpackTensor(t),s.push(l));let[u,p]=N.computeOutAndReduceShapes(l.shape,r),d=w.sizeFromShape(p),c=ce({inputs:{x:l},backend:e,attrs:{shape:[-1,d]}});s.push(c);let h=AA(e,c,a);s.push(h);let m=ce({inputs:{x:h},backend:e,attrs:{shape:u}});return s.forEach(f=>e.disposeIntermediateTensorInfo(f)),m}return FA(e,t,a)}function yee(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{axis:s}=a,i=w.parseAxisParam(s,r.shape),o=N.getAxesPermutation(i,r.shape.length),l=r,u=[];o!=null&&(l=Nn({inputs:{x:r},backend:n,attrs:{perm:o}}),u.push(l),i=N.getInnerMostAxes(i.length,l.shape.length)),N.assertAxesAreInnerMostDims("argMax",[i[0]],l.shape.length);let p=$A(n,l,i[0],"max");return u.forEach(d=>n.disposeIntermediateTensorInfo(d)),p}var xee={kernelName:cu,backendName:"webgl",kernelFunc:yee};function vee(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{axis:s}=a,i=w.parseAxisParam(s,r.shape),o=N.getAxesPermutation(i,r.shape.length),l=r,u=[];o!=null&&(l=Nn({inputs:{x:r},backend:n,attrs:{perm:o}}),u.push(l),i=N.getInnerMostAxes(i.length,l.shape.length)),N.assertAxesAreInnerMostDims("argMin",[i[0]],l.shape.length);let p=$A(n,l,i[0],"min");return u.forEach(d=>n.disposeIntermediateTensorInfo(d)),p}var wee={kernelName:du,backendName:"webgl",kernelFunc:vee},kee=Oa+`
| if (abs(x) > 1.) {
| return NAN;
| }
| return asin(x);
| `,Iee=Ze({opSnippet:kee}),See={kernelName:Ei,backendName:"webgl",kernelFunc:Iee},Nee=Oa+"return log(x + sqrt(x * x + 1.0));",Tee=Ze({opSnippet:Nee}),Cee={kernelName:Ai,backendName:"webgl",kernelFunc:Tee},_ee=Oa+`
| return atan(x);
| `,Eee=Ze({opSnippet:_ee}),Aee={kernelName:Fi,backendName:"webgl",kernelFunc:Eee},Fee=uk+`
| return atan(a, b);
| `,$ee=`
| vec4 result = atan(a, b);
| bvec4 isNaNA = isnan(a);
| bvec4 isNaNB = isnan(b);
| bvec4 isNaN = bvec4(isNaNA.x || isNaNB.x, isNaNA.y || isNaNB.y, isNaNA.z || isNaNB.z, isNaNA.w || isNaNB.w);
| `+el+`
| return result;
| `,Dee=fn({opSnippet:Fee,packedOpSnippet:$ee}),Ree={kernelName:Di,backendName:"webgl",kernelFunc:Dee},Mee=Oa+`
| if ((x < -1.0) || (x > 1.0)) return NAN;
| return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,Pee=Ze({opSnippet:Mee}),Oee={kernelName:$i,backendName:"webgl",kernelFunc:Pee},$c=class{constructor(e,t,n,a=!1,r=!1){if(this.variableNames=["x"],t==="avg"&&n)throw new Error("Cannot compute positions for average pool.");let s=e.filterWidth,i=e.strideHeight,o=e.strideWidth,l=e.dilationHeight,u=e.dilationWidth,p=e.effectiveFilterHeight,d=e.effectiveFilterWidth,c=e.padInfo.top,h=e.padInfo.left;this.outputShape=e.outShape;let m=t==="avg",f=`((batch * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + d`,g=`(xR * ${e.inWidth} + xC) * ${e.inChannels} + d`,b="0.0";if(m||(b="-1.0 / 1e-20"),n){let C=">=";this.userCode=`
| const ivec2 strides = ivec2(${i}, ${o});
| const ivec2 pads = ivec2(${c}, ${h});
|
| void main() {
| ivec4 coords = getOutputCoords();
| int batch = coords[0];
| int d = coords[3];
|
| ivec2 xRCCorner = coords.yz * strides - pads;
| int xRCorner = xRCCorner.x;
| int xCCorner = xRCCorner.y;
|
| // max/min x(?, ?, d) to get y(yR, yC, d).
| // ? = to be determined
| float minMaxValue = 0.0;
| float minMaxValueFound = 0.0;
| int minMaxPosition = 0;
| float avgValue = 0.0;
|
| for (int wR = 0; wR < ${p};
| wR += ${l}) {
| int xR = xRCorner + wR;
|
| if (xR < 0 || xR >= ${e.inHeight}) {
| continue;
| }
|
| for (int wC = 0; wC < ${d};
| wC += ${u}) {
| int xC = xCCorner + wC;
|
| if (xC < 0 || xC >= ${e.inWidth}) {
| continue;
| }
|
| float value = getX(batch, xR, xC, d);
|
| // If a min / max value has already been found, use it. If not,
| // use the current value.
| float currMinMaxValue = mix(
| value, minMaxValue, minMaxValueFound);
| if (value ${C} currMinMaxValue) {
| minMaxValue = value;
| minMaxValueFound = 1.0;
| minMaxPosition = ${a?r?f:g:`wR * ${d} + wC`};
| }
| }
| }
| setOutput(float(minMaxPosition));
| }
| `;return}let y="max",x=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="avg"&&(x="avgValue / max(count, 1.0)");let v=Math.floor(s/4)*4,I=s%4,T=`
| if (${m}) {
| avgValue += dot(values, ones);
| } else {
| minMaxValue = ${y}(values, minMaxValue);
| }
| `;this.userCode=`
| const ivec2 strides = ivec2(${i}, ${o});
| const ivec2 pads = ivec2(${c}, ${h});
| const float initializationValue = ${b};
| const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);
|
| float count = 0.0;
|
| float getValue(int batch, int xR, int xC, int d) {
| if (xC < 0 || xC >= ${e.inWidth}) {
| return initializationValue;
| }
| count += 1.0;
| return getX(batch, xR, xC, d);
| }
|
| void main() {
| ivec4 coords = getOutputCoords();
| int batch = coords[0];
| int d = coords[3];
|
| ivec2 xRCCorner = coords.yz * strides - pads;
| int xRCorner = xRCCorner.x;
| int xCCorner = xRCCorner.y;
|
| // max/min x(?, ?, d) to get y(yR, yC, d).
| // ? = to be determined
| vec4 minMaxValue = vec4(${b});
| float avgValue = 0.0;
| count = 0.0;
|
| for (int wR = 0; wR < ${p};
| wR += ${l}) {
| int xR = xRCorner + wR;
|
| if (xR < 0 || xR >= ${e.inHeight}) {
| continue;
| }
|
| for (int wC = 0; wC < ${v}; wC += 4) {
| int xC = xCCorner + wC * ${u};
|
| vec4 values = vec4(
| getValue(batch, xR, xC, d),
| getValue(batch, xR, xC + ${u}, d),
| getValue(batch, xR, xC + 2 * ${u}, d),
| getValue(batch, xR, xC + 3 * ${u}, d)
| );
|
| ${T}
| }
|
| int xC = xCCorner + ${v};
| if (${I===1}) {
| vec4 values = vec4(
| getValue(batch, xR, xC, d),
| initializationValue,
| initializationValue,
| initializationValue
| );
|
| ${T}
| } else if (${I===2}) {
| vec4 values = vec4(
| getValue(batch, xR, xC, d),
| getValue(batch, xR, xC + ${u}, d),
| initializationValue,
| initializationValue
| );
|
| ${T}
| } else if (${I===3}) {
| vec4 values = vec4(
| getValue(batch, xR, xC, d),
| getValue(batch, xR, xC + ${u}, d),
| getValue(batch, xR, xC + 2 * ${u}, d),
| initializationValue
| );
|
| ${T}
| }
| }
| setOutput(${x});
| }
| `}},ck=class{constructor(e,t,n,a=!1,r=!1){if(this.variableNames=["x"],t==="avg"&&n)throw new Error("Cannot compute positions for average pool.");let s=e.filterWidth,i=e.strideDepth,o=e.strideHeight,l=e.strideWidth,u=e.dilationDepth,p=e.dilationHeight,d=e.dilationWidth,c=e.effectiveFilterDepth,h=e.effectiveFilterHeight,m=e.effectiveFilterWidth,f=e.padInfo.front,g=e.padInfo.top,b=e.padInfo.left;this.outputShape=e.outShape;let y=t==="avg",x="0.0";if(y||(x="-1.0 / 1e-20"),n){let F=">=";this.userCode=`
| const ivec3 strides =
| ivec3(${i}, ${o}, ${l});
| const ivec3 pads = ivec3(${f}, ${g}, ${b});
|
| void main() {
| ivec5 coords = getOutputCoords();
| int batch = coords.x;
| int ch = coords.u;
|
| ivec3 xCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;
| int xDCorner = xCorner.x;
| int xRCorner = xCorner.y;
| int xCCorner = xCorner.z;
|
| // max/min x(?, ?, ?, ch) to get y(yD, yR, yC, ch).
| // ? = to be determined
| float minMaxValue = 0.0;
| float minMaxValueFound = 0.0;
| int minMaxPosition = 0;
|
| for (int wD = 0; wD < ${c};
| wD += ${u}) {
| int xD = xDCorner + wD;
|
| if (xD < 0 || xD >= ${e.inDepth}) {
| continue;
| }
|
| for (int wR = 0; wR < ${h};
| wR += ${p}) {
| int xR = xRCorner + wR;
|
| if (xR < 0 || xR >= ${e.inHeight}) {
| continue;
| }
|
| for (int wC = 0; wC < ${m};
| wC += ${d}) {
| int xC = xCCorner + wC;
|
| if (xC < 0 || xC >= ${e.inWidth}) {
| continue;
| }
|
| float value = getX(batch, xD, xR, xC, ch);
|
| // If a min / max value has already been found, use it. If not,
| // use the current value.
| float currMinMaxValue = mix(
| value, minMaxValue, minMaxValueFound);
| if (value ${F} currMinMaxValue) {
| minMaxValue = value;
| minMaxValueFound = 1.0;
| minMaxPosition = ${a?r?`(((batch * ${e.inDepth} + xD) * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + ch`:`((xD * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + ch`:`wD * ${h} * ${m} +
| wR * ${m} + wC`};
| }
| }
| }
| }
| setOutput(float(minMaxPosition));
| }
| `;return}let v="max",I=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="avg"&&(I="avgValue / max(count, 1.0)");let T=Math.floor(s/4)*4,C=s%4,E=`
| if (${y}) {
| avgValue += dot(values, ones);
| } else {
| minMaxValue = ${v}(values, minMaxValue);
| }
| `;this.userCode=`
| const ivec3 strides =
| ivec3(${i}, ${o}, ${l});
| const ivec3 pads = ivec3(${f}, ${g}, ${b});
| const float initializationValue = ${x};
| const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);
|
| float count = 0.0;
|
| float getValue(int batch, int xD, int xR, int xC, int ch) {
| if (xC < 0 || xC >= ${e.inWidth}) {
| return initializationValue;
| }
| count += 1.0;
| return getX(batch, xD, xR, xC, ch);
| }
|
| void main() {
| ivec5 coords = getOutputCoords();
| int batch = coords.x;
| int ch = coords.u;
|
| ivec3 xCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;
| int xDCorner = xCorner.x;
| int xRCorner = xCorner.y;
| int xCCorner = xCorner.z;
|
| // max/min x(?, ?, ?, d) to get y(yD, yR, yC, ch).
| // ? = to be determined
| vec4 minMaxValue = vec4(${x});
| float avgValue = 0.0;
| count = 0.0;
|
| for (int wD = 0; wD < ${c};
| wD += ${u}) {
| int xD = xDCorner + wD;
|
| if (xD < 0 || xD >= ${e.inDepth}) {
| continue;
| }
|
| for (int wR = 0; wR < ${h};
| wR += ${p}) {
| int xR = xRCorner + wR;
|
| if (xR < 0 || xR >= ${e.inHeight}) {
| continue;
| }
|
| for (int wC = 0; wC < ${T}; wC += 4) {
| int xC = xCCorner + wC * ${d};
|
| vec4 values = vec4(
| getValue(batch, xD, xR, xC, ch),
| getValue(batch, xD, xR, xC + ${d}, ch),
| getValue(batch, xD, xR, xC + 2 * ${d}, ch),
| getValue(batch, xD, xR, xC + 3 * ${d}, ch)
| );
|
| ${E}
| }
|
| int xC = xCCorner + ${T};
| if (${C===1}) {
| vec4 values = vec4(
| getValue(batch, xD, xR, xC, ch),
| initializationValue,
| initializationValue,
| initializationValue
| );
|
| ${E}
| } else if (${C===2}) {
| vec4 values = vec4(
| getValue(batch, xD, xR, xC, ch),
| getValue(batch, xD, xR, xC + ${d}, ch),
| initializationValue,
| initializationValue
| );
|
| ${E}
| } else if (${C===3}) {
| vec4 values = vec4(
| getValue(batch, xD, xR, xC, ch),
| getValue(batch, xD, xR, xC + ${d}, ch),
| getValue(batch, xD, xR, xC + 2 * ${d}, ch),
| initializationValue
| );
|
| ${E}
| }
| }
| }
| setOutput(${I});
| }
| `}};function Lee(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t;vp(r,"avgPool");let{filterSize:s,strides:i,pad:o,dimRoundingMode:l}=a,u=1;w.assert(N.eitherStridesOrDilationsAreOne(i,u),()=>`Error in avgPool: Either strides or dilations must be 1. Got strides ${i} and dilations '${u}'`);let p=N.computePool2DInfo(r.shape,s,i,u,o,l);if(p.filterWidth===1&&p.filterHeight===1&&w.arraysEqual(p.inShape,p.outShape))return ra({inputs:{x:r},backend:n});let d=new $c(p,"avg",!1);return n.runWebGLProgram(d,[r],"float32")}var zee={kernelName:Ri,backendName:"webgl",kernelFunc:Lee};function Wee(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{filterSize:s,strides:i,pad:o,dimRoundingMode:l,dataFormat:u}=a,p=[1,1,1],d=N.computePool3DInfo(r.shape,s,i,p,o,l,u),c=new ck(d,"avg",!1);return n.runWebGLProgram(c,[r],"float32")}var Bee={kernelName:hu,backendName:"webgl",kernelFunc:Wee},Vee=class{constructor(e){this.variableNames=["dy"],this.outputShape=e.inShape;let t=e.filterHeight,n=e.filterWidth,a=e.strideHeight,r=e.strideWidth,s=e.dilationHeight,i=e.dilationWidth,o=e.effectiveFilterHeight,l=e.effectiveFilterWidth,u=o-1-e.padInfo.top,p=l-1-e.padInfo.left,d=1/(t*n);this.userCode=`
| const ivec2 pads = ivec2(${u}, ${p});
| const float avgMultiplier = float(${d});
|
| void main() {
| ivec4 coords = getOutputCoords();
| int b = coords[0];
| int d = coords[3];
|
| ivec2 dyRCCorner = coords.yz - pads;
| int dyRCorner = dyRCCorner.x;
| int dyCCorner = dyRCCorner.y;
|
| // Convolve dy(?, ?, d) with pos mask(:, :, d) to get dx(xR, xC, d).
| // ? = to be determined. : = across all values in that axis.
| float dotProd = 0.0;
| for (int wR = 0; wR < ${o};
| wR += ${s}) {
| float dyR = float(dyRCorner + wR) / ${a}.0;
|
| if (dyR < 0.0 || dyR >= ${e.outHeight}.0 || fract(dyR) > 0.0) {
| continue;
| }
| int idyR = int(dyR);
|
| for (int wC = 0; wC < ${l};
| wC+= ${i}) {
| float dyC = float(dyCCorner + wC) / ${r}.0;
|
| if (dyC < 0.0 || dyC >= ${e.outWidth}.0 ||
| fract(dyC) > 0.0) {
| continue;
| }
| int idyC = int(dyC);
|
| float dyValue = getDy(b, idyR, idyC, d);
|
| dotProd += dyValue * avgMultiplier;
| }
| }
| setOutput(dotProd);
| }
| `}},Uee=class{constructor(e){this.variableNames=["dy"],this.outputShape=e.inShape;let t=e.filterDepth,n=e.filterHeight,a=e.filterWidth,r=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=e.dilationDepth,l=e.dilationHeight,u=e.dilationWidth,p=e.effectiveFilterDepth,d=e.effectiveFilterHeight,c=e.effectiveFilterWidth,h=p-1-e.padInfo.front,m=d-1-e.padInfo.top,f=c-1-e.padInfo.left,g=1/(t*n*a);this.userCode=`
| const ivec3 pads = ivec3(${h}, ${m}, ${f});
| const float avgMultiplier = float(${g});
|
| void main() {
| ivec5 coords = getOutputCoords();
| int batch = coords.x;
| int ch = coords.u;
|
| ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads;
| int dyDCorner = dyCorner.x;
| int dyRCorner = dyCorner.y;
| int dyCCorner = dyCorner.z;
|
| // Convolve dy(?, ?, ?, d) with pos mask(:, :, :, ch) to get
| // dx(xD, xR, xC, ch).
| // ? = to be determined. : = across all values in that axis.
| float dotProd = 0.0;
|
| for (int wD = 0; wD < ${p};
| wD += ${o}) {
| float dyD = float(dyDCorner + wD) / ${r}.0;
|
| if (dyD < 0.0 || dyD >= ${e.outDepth}.0 || fract(dyD) > 0.0) {
| continue;
| }
| int idyD = int(dyD);
|
| for (int wR = 0; wR < ${d};
| wR += ${l}) {
| float dyR = float(dyRCorner + wR) / ${s}.0;
|
| if (dyR < 0.0 || dyR >= ${e.outHeight}.0 ||
| fract(dyR) > 0.0) {
| continue;
| }
| int idyR = int(dyR);
|
| for (int wC = 0; wC < ${c};
| wC += ${u}) {
| float dyC = float(dyCCorner + wC) / ${i}.0;
|
| if (dyC < 0.0 || dyC >= ${e.outWidth}.0 ||
| fract(dyC) > 0.0) {
| continue;
| }
| int idyC = int(dyC);
|
| float dyValue = getDy(batch, idyD, idyR, idyC, ch);
|
| dotProd += dyValue * avgMultiplier;
| }
| }
| }
| setOutput(dotProd);
| }
| `}};function Gee(e){let{inputs:t,backend:n,attrs:a}=e,{dy:r,input:s}=t,i=s,{filterSize:o,strides:l,pad:u,dimRoundingMode:p}=a,d=[1,1,1],c=N.computePool3DInfo(i.shape,o,l,d,u,p),h=new Uee(c);return n.runWebGLProgram(h,[r],i.dtype)}var Hee={kernelName:Lc,backendName:"webgl",kernelFunc:Gee};function qee(e){let{inputs:t,backend:n,attrs:a}=e,{dy:r,input:s}=t,i=s;vp([r,s],"avgPoolGrad");let{filterSize:o,strides:l,pad:u}=a,p=N.computePool2DInfo(i.shape,o,l,1,u),d=new Vee(p);return n.runWebGLProgram(d,[r],i.dtype)}var jee={kernelName:Oc,backendName:"webgl",kernelFunc:qee};function Kee(e){let{inputs:t,backend:n,attrs:a}=e,{a:r,b:s}=t,{transposeA:i,transposeB:o}=a;return Em({a:r,b:s,transposeA:i,transposeB:o,backend:n})}var Xee={kernelName:Mi,backendName:"webgl",kernelFunc:Kee},Yee=class{constructor(e,t,n,a,r,s){this.outputShape=[],this.variableNames=["x","mean","variance"],N.assertAndGetBroadcastShape(e,t),N.assertAndGetBroadcastShape(e,n);let i="0.0";a!=null&&(N.assertAndGetBroadcastShape(e,a),this.variableNames.push("offset"),i="getOffsetAtOutCoords()");let o="1.0";r!=null&&(N.assertAndGetBroadcastShape(e,r),this.variableNames.push("scale"),o="getScaleAtOutCoords()"),this.outputShape=e,this.userCode=`
| void main() {
| float x = getXAtOutCoords();
| float mean = getMeanAtOutCoords();
| float variance = getVarianceAtOutCoords();
| float offset = ${i};
| float scale = ${o};
| float inv = scale * inversesqrt(variance + float(${s}));
| setOutput(dot(vec3(x, -mean, offset), vec3(inv, inv, 1)));
| }
| `}},Zee=class{constructor(e,t,n,a,r,s){this.packedInputs=!0,this.packedOutput=!0,this.variableNames=["x","mean","variance"],N.assertAndGetBroadcastShape(e,t),N.assertAndGetBroadcastShape(e,n);let i="vec4(0.0)";a!=null&&(N.assertAndGetBroadcastShape(e,a),this.variableNames.push("offset"),i="getOffsetAtOutCoords()");let o="vec4(1.0)";r!=null&&(N.assertAndGetBroadcastShape(e,r),this.variableNames.push("scale"),o="getScaleAtOutCoords()"),this.outputShape=e,this.userCode=`
| void main() {
| vec4 offset = ${i};
| vec4 scale = ${o};
|
| vec4 x = getXAtOutCoords();
| vec4 mean = getMeanAtOutCoords();
| vec4 variance = getVarianceAtOutCoords();
|
| vec4 inv = scale * inversesqrt(variance + vec4(${s}));
|
| setOutput((x - mean) * inv + offset);
| }
| `}},Jee=({inputs:e,backend:t,attrs:n})=>{let{x:a,mean:r,variance:s,offset:i,scale:o}=e;w.assert(r.shape.length===s.shape.length,()=>"Batch normalization gradient requires mean and variance to have equal ranks."),w.assert(i==null||r.shape.length===i.shape.length,()=>"Batch normalization gradient requires mean and offset to have equal ranks."),w.assert(o==null||r.shape.length===o.shape.length,()=>"Batch normalization gradient requires mean and scale to have equal ranks.");let{varianceEpsilon:l}=n;l==null&&(l=.001);let u=[a,r,s],p=null;i!=null&&(p=i.shape,u.push(i));let d=null;o!=null&&(d=o.shape,u.push(o));let c=G().getBool("WEBGL_PACK_NORMALIZATION")?new Zee(a.shape,r.shape,s.shape,p,d,l):new Yee(a.shape,r.shape,s.shape,p,d,l);return t.runWebGLProgram(c,u,u[0].dtype)},Qee={kernelName:Qi,backendName:"webgl",kernelFunc:Jee},ete=class{constructor(e){this.variableNames=["source"],this.outputShape=e,this.rank=e.length;let t=dt(this.rank);this.customUniforms=[{name:"start",arrayIndex:this.rank,type:"int"}];let n=tte(this.rank),a,r=e.map((s,i)=>`sourceLoc.${gv[i]} = start[${i}] + coords.${gv[i]};`);a=`
| ${t} sourceLoc;
| ${t} coords = getOutputCoords();
| ${r.join(`
| `)}
| `,this.userCode=`
| void main() {
| ${a}
| setOutput(getSource(${n}));
| }
| `}},gv=["x","y","z","w","u","v"];function tte(e){if(e===1)return"sourceLoc";if(e<=6)return gv.slice(0,e).map(t=>"sourceLoc."+t).join(",");throw Error(`Slicing for rank ${e} is not yet supported`)}var nte=class{constructor(e){this.variableNames=["source"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.rank=e.length,this.customUniforms=[{name:"start",arrayIndex:this.rank,type:"int"}];let t=dt(this.rank),n=Sn("coords",this.rank),a=Sn("sourceLoc",this.rank),r=this.rank===1?"sourceLoc":`vec2(${a.slice(-2).join()})`,s=`getChannel(getSource(${a.join()}), ${r})`,i=`
| result.x = ${s};
| if (++${n[this.rank-1]} < ${e[this.rank-1]}) {
| ++${a[this.rank-1]};
| result.y = ${s};
| --${a[this.rank-1]};
| }
| `,o=this.rank===1?"":`
| --${n[this.rank-1]};
| if (++${n[this.rank-2]} < ${e[this.rank-2]}) {
| ++${a[this.rank-2]};
| result.z = ${s};
| if (++${n[this.rank-1]} < ${e[this.rank-1]}) {
| ++${a[this.rank-1]};
| result.w = ${s};
| }
| }
| `,l=this.rank<=4?`sourceLoc = coords +
| ${t}(${e.map((u,p)=>`start[${p}]`).join()});`:e.map((u,p)=>`${a[p]} = ${n[p]} + start[${p}];`).join(`
| `);this.userCode=`
| void main() {
| ${t} coords = getOutputCoords();
| ${t} sourceLoc;
| ${l}
| vec4 result = vec4(0.);
| ${i}
| ${o}
| setOutput(result);
| }
| `}};function ate(e,t,n,a){let r=a.texData.get(e.dataId),s=a.makeTensorInfo(n,e.dtype),i=a.texData.get(s.dataId);Object.assign(i,r),i.refCount=1,i.shape=n,i.dtype=e.dtype;let o=Xt.computeFlatOffset(t,w.computeStrides(e.shape));r.slice&&(o+=r.slice.flatOffset),i.slice={flatOffset:o,origDataId:r.slice&&r.slice.origDataId||e.dataId};let l=a.dataRefCount.get(i.slice.origDataId)||1;return a.dataRefCount.set(i.slice.origDataId,l+1),s}function Cp(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{begin:s,size:i}=a,[o,l]=Xt.parseSliceParams(r,s,i);if(Xt.assertParamsValid(r,o,l),w.sizeFromShape(l)===0)return n.makeTensorInfo(l,r.dtype,[]);if(n.shouldExecuteOnCPU([r])||r.dtype==="string"){let d=n.texData.get(r.dataId),c=j9(d.values,o,l,r.shape,r.dtype);return n.makeTensorInfo(l,r.dtype,c)}let{isPacked:u}=n.texData.get(r.dataId),p=Xt.isSliceContinous(r.shape,o,l);if(u||!p){let d=G().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new nte(l):new ete(l),c=[o];return n.runWebGLProgram(d,[r],r.dtype,c)}return n.uploadToGPU(r.dataId),ate(r,o,l,n)}var rte={kernelName:Qu,backendName:"webgl",kernelFunc:Cp},ste=e=>{let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{blockShape:s,crops:i}=a;w.assert(r.shape.length<=4,()=>"batchToSpaceND for rank > 4 with a WebGL backend not implemented yet");let o=s.reduce((y,x)=>y*x),l=N.getReshaped(r.shape,s,o),u=N.getPermuted(l.length,s.length),p=N.getReshapedPermuted(r.shape,s,o),d=N.getSliceBeginCoords(i,s.length),c=N.getSliceSize(p,i,s.length),h=[],m=ce({inputs:{x:r},backend:n,attrs:{shape:l}}),f=Nn({inputs:{x:m},backend:n,attrs:{perm:u}}),g=ce({inputs:{x:f},backend:n,attrs:{shape:p}}),b=Cp({inputs:{x:g},backend:n,attrs:{begin:d,size:c}});return h.push(m),h.push(f),h.push(g),h.forEach(y=>n.disposeIntermediateTensorInfo(y)),b},ite={kernelName:mu,backendName:"webgl",kernelFunc:ste};function ote(e){let{inputs:t,backend:n,attrs:a}=e,{x:r,weights:s}=t,{size:i}=a,o=n.readSync(r.dataId),l=n.readSync(s.dataId),u=yA(o,l,s.dtype,s.shape,i);return n.makeTensorInfo([i],s.dtype,u)}var lte={kernelName:fu,backendName:"webgl",kernelFunc:ote},ute=`
| int r = int(a.r) & int(b.r);
| int g = int(a.g) & int(b.g);
| int rb = int(a.b) & int(b.b);
| int ra = int(a.a) & int(b.a);
| return vec4(r, g, rb, ra);
| `,pte=`
| return float(int(a.r) & int(b.r));
| `;function cte(e){let{inputs:t,backend:n}=e,{a,b:r}=t,s=G().getBool("WEBGL_PACK_BINARY_OPERATIONS"),i=G().getNumber("WEBGL_VERSION");if(n.shouldExecuteOnCPU([a,r])||i===1){let l=n.texData.get(a.dataId).values,u=n.texData.get(r.dataId).values,[p,d]=b9(a.shape,r.shape,l,u,a.dtype),c=n.makeTensorInfo(d,a.dtype),h=n.texData.get(c.dataId);return h.values=p,c}let o;return s?o=new Np(ute,a.shape,r.shape,!1):o=new Ii(pte,a.shape,r.shape),n.runWebGLProgram(o,[a,r],a.dtype)}var dte={kernelName:gu,backendName:"webgl",kernelFunc:cte};function hte(e){let{inputs:t,backend:n}=e,{s0:a,s1:r}=t,s=n.readSync(a.dataId),i=n.readSync(r.dataId),o=N.assertAndGetBroadcastShape(Array.from(s),Array.from(i));return n.makeTensorInfo([o.length],"int32",Int32Array.from(o))}var mte={kernelName:zc,backendName:"webgl",kernelFunc:hte},fte="return float(a != b);",DA=fn({opSnippet:fte,cpuKernelImpl:L9,dtype:"bool"}),gte={kernelName:Wu,backendName:"webgl",kernelFunc:DA};function Od(e){let{inputs:t,backend:n}=e,{input:a}=t,r=n.texData.get(a.dataId);return ra({inputs:{x:r.complexTensorInfos.real},backend:n})}var bte={kernelName:Km,backendName:"webgl",kernelFunc:Od},yte="return float(int(x));";function xte(e,t){let n=new ir(e.shape,yte),a=t.runWebGLProgram(n,[e],"int32");return{dataId:a.dataId,shape:a.shape,dtype:a.dtype}}function bv(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{dtype:s}=a;if(s==="complex64"){if(r.dtype==="complex64")return ra({inputs:{x:r},backend:n});let i=Nt(r.shape),o=bv({inputs:{x:r},backend:n,attrs:{dtype:"float32"}}),l=Ms({inputs:{real:o,imag:i},backend:n});return i.dispose(),n.disposeIntermediateTensorInfo(o),l}if(r.dtype==="complex64"){let i=Od({inputs:{input:r},backend:n}),o=bv({inputs:{x:i},backend:n,attrs:{dtype:s}});return n.disposeIntermediateTensorInfo(i),o}if(!w.hasEncodingLoss(r.dtype,s)){let i=ra({inputs:{x:r},backend:n});return{dataId:i.dataId,shape:i.shape,dtype:s}}if(n.shouldExecuteOnCPU([r])){let i=n.texData.get(r.dataId).values,[o,l,u]=y9(i,r.shape,r.dtype,s);return n.makeTensorInfo(o,l,u)}if(s==="int32")return xte(r,n);if(s==="bool"){let i=n.makeTensorInfo([],"bool",w.getTypedArrayFromDType("bool",1)),o=DA({inputs:{a:r,b:i},backend:n});return n.disposeIntermediateTensorInfo(i),o}throw new Error(`Error in Cast: failed to cast ${r.dtype} to ${s}`)}var vte={kernelName:Pi,backendName:"webgl",kernelFunc:bv},TS="return ceil(x);",wte=Ze({opSnippet:TS,packedOpSnippet:TS,cpuKernelImpl:x9}),kte={kernelName:Oi,backendName:"webgl",kernelFunc:wte},Ite=class{constructor(e){this.variableNames=["A"],this.customUniforms=[{name:"minVal",type:"float"},{name:"maxVal",type:"float"}],this.outputShape=e,this.userCode=`
|
| void main() {
| float value = getAAtOutCoords();
| if (isnan(value)) {
| setOutput(value);
| return;
| }
|
| setOutput(clamp(value, minVal, maxVal));
| }
| `}},Ste=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"minVal",type:"float"},{name:"maxVal",type:"float"}],this.outputShape=e,this.userCode=`
| void main() {
| vec4 value = getAAtOutCoords();
|
| if (any(isnan(value))) {
| setOutput(value);
| return;
| }
|
| setOutput(clamp(value, vec4(minVal), vec4(maxVal)));
| }
| `}};function Nte(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{clipValueMin:s,clipValueMax:i}=a,o;G().getBool("WEBGL_PACK_CLIP")?o=new Ste(r.shape):o=new Ite(r.shape);let l=[[s],[i]];return n.runWebGLProgram(o,[r],r.dtype,l)}var Tte={kernelName:Ss,backendName:"webgl",kernelFunc:Nte},Cte=class{constructor(e){this.variableNames=["real","imag"],this.outputShape=e,this.userCode=`
| void main() {
| float re = abs(getRealAtOutCoords());
| float im = abs(getImagAtOutCoords());
| float mx = max(re, im);
|
| // sadly the length function in glsl is not underflow-safe
| // (at least not on Intel GPUs). So the safe solution is
| // to ensure underflow-safety in all cases.
| setOutput(
| mx == 0.0 ? 0.0 : mx * length(vec2(1, min(re, im)/mx))
| );
| }
| `}};function CS(e,t){return{dataId:t.dataId,dtype:t.dtype,shape:e.shape}}function _te(e){let{inputs:t,backend:n}=e,{x:a}=t,r=n.texData.get(a.dataId),s=new Cte(a.shape),i=[CS(a,r.complexTensorInfos.real),CS(a,r.complexTensorInfos.imag)];return n.runWebGLProgram(s,i,i[0].dtype)}var Ete={kernelName:Wc,backendName:"webgl",kernelFunc:_te},Ate=class{constructor(e){this.outputShape=[],this.outputShape=N.computeOutShape(e,1),this.variableNames=e.map((s,i)=>`T${i}`);let t=new Array(e.length-1);t[0]=e[0][1];for(let s=1;s<t.length;s++)t[s]=t[s-1]+e[s][1];let n=[`if (yC < ${t[0]}) setOutput(getT0(yR, yC));`];for(let s=1;s<t.length;s++){let i=t[s-1];n.push(`else if (yC < ${t[s]}) setOutput(getT${s}(yR, yC-${i}));`)}let a=t.length,r=t[t.length-1];n.push(`else setOutput(getT${a}(yR, yC-${r}));`),this.userCode=`
| void main() {
| ivec2 coords = getOutputCoords();
| int yR = coords.x;
| int yC = coords.y;
|
| ${n.join(`
| `)}
| }
| `}},Fte=class{constructor(e,t){this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[],this.outputShape=N.computeOutShape(e,t);let n=this.outputShape,a=n.length,r=dt(a),s=Sn("coords",a),i=["x","y","z","w","u","v"].slice(0,a);this.variableNames=e.map((m,f)=>`T${f}`);let o=new Array(e.length-1);o[0]=e[0][t];for(let m=1;m<o.length;m++)o[m]=o[m-1]+e[m][t];let l=i[t],u=i.slice(-2),p=i.join(),d=`if (${l} < ${o[0]}) {
| return getChannel(
| getT0(${p}), vec2(${u.join()}));
| }`;for(let m=1;m<o.length;m++){let f=o[m-1];d+=`
| if (${l} < ${o[m]} && ${l} >= ${o[m-1]}) {
| return getChannel(
| getT${m}(${jh(i,l,f)}),
| vec2(${jh(u,l,f)}));
| }`}let c=o.length,h=o[o.length-1];d+=`
| return getChannel(
| getT${c}(${jh(i,l,h)}),
| vec2(${jh(u,l,h)}));`,this.userCode=`
| float getValue(${i.map(m=>"int "+m)}) {
| ${d}
| }
|
| void main() {
| ${r} coords = getOutputCoords();
| vec4 result = vec4(getValue(${s}), 0., 0., 0.);
|
| ${s[a-1]} = ${s[a-1]} + 1;
| if (${s[a-1]} < ${n[a-1]}) {
| result.g = getValue(${s});
| }
|
| ${s[a-2]} = ${s[a-2]} + 1;
| if (${s[a-2]} < ${n[a-2]}) {
| result.a = getValue(${s});
| }
|
| ${s[a-1]} = ${s[a-1]} - 1;
| if (${s[a-2]} < ${n[a-2]} &&
| ${s[a-1]} < ${n[a-1]}) {
| result.b = getValue(${s});
| }
| setOutput(result);
| }
| `}};function jh(e,t,n){let a=e.indexOf(t);return e.map((r,s)=>s===a?`${r} - ${n}`:r).join()}function ng(e){let{inputs:t,backend:n}=e,{input:a}=t,r=n.texData.get(a.dataId);return ra({inputs:{x:r.complexTensorInfos.imag},backend:n})}var $te={kernelName:Gm,backendName:"webgl",kernelFunc:ng};function cc(e,t,n){let a=e[0].dtype;if(a==="complex64"){let h=e.map(y=>Od({inputs:{input:y},backend:n})),m=e.map(y=>ng({inputs:{input:y},backend:n})),f=cc(h,t,n),g=cc(m,t,n),b=Ms({inputs:{real:f,imag:g},backend:n});return h.forEach(y=>n.disposeIntermediateTensorInfo(y)),m.forEach(y=>n.disposeIntermediateTensorInfo(y)),n.disposeIntermediateTensorInfo(f),n.disposeIntermediateTensorInfo(g),b}let r=n.shouldExecuteOnCPU(e);if(a==="string"&&(r=!0),r){let h=e.map(v=>{let I=[-1,w.sizeFromShape(v.shape.slice(t))];return ce({inputs:{x:v},backend:n,attrs:{shape:I}})}),m=h.map(v=>({vals:n.readSync(v.dataId),shape:v.shape})),f=N.computeOutShape(h.map(v=>v.shape),1),g=h[0].shape[0]===1,b=v9(m,f,a,g),y=N.computeOutShape(e.map(v=>v.shape),t),x=n.makeTensorInfo(y,a,b);return h.forEach(v=>n.disposeIntermediateTensorInfo(v)),x}let s=e.filter(h=>w.sizeFromShape(h.shape)>0),i=G().getBool("WEBGL_PACK_ARRAY_OPERATIONS")&&s[0].shape.length>1;if(s.length===1){let h=i?new ir(e[0].shape,ns):new os(e[0].shape,ns);return n.runWebGLProgram(h,e,a)}let o=G().getNumber("WEBGL_MAX_TEXTURES_IN_SHADER");if(s.length>o){let h=[];for(let f=0;f<s.length;f+=o){let g=s.slice(f,f+o);h.push(cc(g,t,n))}let m=cc(h,t,n);for(let f of h)n.disposeIntermediateTensorInfo(f);return m}if(i){let h=new Fte(s.map(m=>m.shape),t);return n.runWebGLProgram(h,s,a)}let{tensors2D:l,outShape:u}=Dte(s,t,n),p=new Ate(l.map(h=>h.shape)),d=n.runWebGLProgram(p,l,a);l.forEach(h=>n.disposeIntermediateTensorInfo(h));let c=ce({inputs:{x:d},attrs:{shape:u},backend:n});return n.disposeIntermediateTensorInfo(d),c}function Dte(e,t,n){let a=N.computeOutShape(e.map(r=>r.shape),t);return{tensors2D:e.map(r=>ce({inputs:{x:r},attrs:{shape:[-1,w.sizeFromShape(r.shape.slice(t))]},backend:n})),outShape:a}}function RA(e){let{inputs:t,backend:n,attrs:a}=e,{axis:r}=a,s=w.parseAxisParam(r,t[0].shape)[0],i=t.map(u=>u.shape);N.assertParamsConsistent(i,s);let o=N.computeOutShape(t.map(u=>u.shape),s);if(w.sizeFromShape(o)===0)return n.makeTensorInfo(o,t[0].dtype,[]);let l=t.filter(u=>w.sizeFromShape(u.shape)>0);return l.length===1?ra({inputs:{x:l[0]},backend:n}):cc(l,s,n)}var Rte={kernelName:bu,backendName:"webgl",kernelFunc:RA},MA=class{constructor(e,t=!1,n=null,a=!1,r=!1){this.variableNames=["x","W"],this.outputShape=e.outShape;let s=e.padInfo.top,i=e.padInfo.left,o=e.strideHeight,l=e.strideWidth,u=e.dilationHeight,p=e.dilationWidth,d=e.filterHeight,c=e.filterWidth,h=Math.floor(e.inChannels/4)*4,m=e.inChannels%4,f=e.dataFormat==="channelsLast",g=f?1:2,b=f?2:3,y=f?3:1,x="",v="";n&&(a?x=`float activation(float a) {
| float b = getPreluActivationWeightsAtOutCoords();
| ${n}
| }`:r?x=`float activation(float a) {
| float b = getLeakyreluAlphaAtOutCoords();
| ${n}
| }`:x=`
| float activation(float x) {
| ${n}
| }
| `,v="result = activation(result);");let I=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),a&&this.variableNames.push("preluActivationWeights"),r&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
| ${x}
|
| const ivec2 strides = ivec2(${o}, ${l});
| const ivec2 pads = ivec2(${s}, ${i});
|
| void main() {
| ivec4 coords = getOutputCoords();
| int batch = coords[0];
| int d2 = coords[${y}];
|
| ivec2 xRCCorner =
| ivec2(coords[${g}], coords[${b}]) * strides - pads;
| int xRCorner = xRCCorner.x;
| int xCCorner = xRCCorner.y;
|
| // Convolve x(?, ?, d1) with w(:, :, d1, d2) to get y(yR, yC, d2).
| // ? = to be determined. : = across all values in that axis.
| float dotProd = 0.0;
| for (int wR = 0; wR < ${d}; wR++) {
| int xR = xRCorner + wR * ${u};
|
| if (xR < 0 || xR >= ${e.inHeight}) {
| continue;
| }
|
| for (int wC = 0; wC < ${c}; wC++) {
| int xC = xCCorner + wC * ${p};
|
| if (xC < 0 || xC >= ${e.inWidth}) {
| continue;
| }
|
| for (int d1 = 0; d1 < ${h}; d1 += 4) {
| vec4 wValues = vec4(
| getW(wR, wC, d1, d2),
| getW(wR, wC, d1 + 1, d2),
| getW(wR, wC, d1 + 2, d2),
| getW(wR, wC, d1 + 3, d2)
| );
|
| if (${f}) {
| vec4 xValues = vec4(
| getX(batch, xR, xC, d1),
| getX(batch, xR, xC, d1 + 1),
| getX(batch, xR, xC, d1 + 2),
| getX(batch, xR, xC, d1 + 3)
| );
| dotProd += dot(xValues, wValues);
| } else {
| vec4 xValues = vec4(
| getX(batch, d1, xR, xC),
| getX(batch, d1 + 1, xR, xC),
| getX(batch, d1 + 2, xR, xC),
| getX(batch, d1 + 3, xR, xC)
| );
| dotProd += dot(xValues, wValues);
| }
| }
|
| if (${m===1}) {
|
| if (${f}) {
| dotProd +=
| getX(batch, xR, xC, ${h}) *
| getW(wR, wC, ${h}, d2);
| } else {
| dotProd +=
| getX(batch, ${h}, xR, xC) *
| getW(wR, wC, ${h}, d2);
| }
|
| } else if (${m===2}) {
| vec2 wValues = vec2(
| getW(wR, wC, ${h}, d2),
| getW(wR, wC, ${h} + 1, d2)
| );
|
| if (${f}) {
| vec2 xValues = vec2(
| getX(batch, xR, xC, ${h}),
| getX(batch, xR, xC, ${h} + 1)
| );
| dotProd += dot(xValues, wValues);
| } else {
| vec2 xValues = vec2(
| getX(batch, ${h}, xR, xC),
| getX(batch, ${h} + 1, xR, xC)
| );
| dotProd += dot(xValues, wValues);
| }
|
| } else if (${m===3}) {
| vec3 wValues = vec3(
| getW(wR, wC, ${h}, d2),
| getW(wR, wC, ${h} + 1, d2),
| getW(wR, wC, ${h} + 2, d2)
| );
|
| if (${f}) {
| vec3 xValues = vec3(
| getX(batch, xR, xC, ${h}),
| getX(batch, xR, xC, ${h} + 1),
| getX(batch, xR, xC, ${h} + 2)
| );
| dotProd += dot(xValues, wValues);
| } else {
| vec3 xValues = vec3(
| getX(batch, ${h}, xR, xC),
| getX(batch, ${h} + 1, xR, xC),
| getX(batch, ${h} + 2, xR, xC)
| );
| dotProd += dot(xValues, wValues);
| }
|
| }
| }
| }
|
| float result = dotProd;
| ${I}
| ${v}
| setOutput(result);
| }
| `}},Mte=class{constructor(e){this.variableNames=["x","W"],this.outputShape=e.outShape;let t=e.padInfo.front,n=e.padInfo.top,a=e.padInfo.left,r=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=e.dilationDepth,l=e.dilationHeight,u=e.dilationWidth,p=e.filterDepth,d=e.filterHeight,c=e.filterWidth,h=Math.floor(e.inChannels/4)*4,m=e.inChannels%4;this.userCode=`
| const ivec3 strides = ivec3(${r}, ${s}, ${i});
| const ivec3 pads = ivec3(${t}, ${n}, ${a});
|
| void main() {
| ivec5 coords = getOutputCoords();
| int batch = coords.x;
| int d2 = coords.u;
|
| ivec3 xFRCCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;
| int xFCorner = xFRCCorner.x;
| int xRCorner = xFRCCorner.y;
| int xCCorner = xFRCCorner.z;
|
| // Convolve x(?, ?, ?, d1) with w(:, :, :, d1, d2) to get
| // y(yF, yR, yC, d2). ? = to be determined. : = across all
| // values in that axis.
| float dotProd = 0.0;
| for (int wF = 0; wF < ${p}; wF++) {
| int xF = xFCorner + wF * ${o};
|
| if (xF < 0 || xF >= ${e.inDepth}) {
| continue;
| }
|
| for (int wR = 0; wR < ${d}; wR++) {
| int xR = xRCorner + wR * ${l};
|
| if (xR < 0 || xR >= ${e.inHeight}) {
| continue;
| }
|
| for (int wC = 0; wC < ${c}; wC++) {
| int xC = xCCorner + wC * ${u};
|
| if (xC < 0 || xC >= ${e.inWidth}) {
| continue;
| }
|
| for (int d1 = 0; d1 < ${h}; d1 += 4) {
| vec4 xValues = vec4(
| getX(batch, xF, xR, xC, d1),
| getX(batch, xF, xR, xC, d1 + 1),
| getX(batch, xF, xR, xC, d1 + 2),
| getX(batch, xF, xR, xC, d1 + 3)
| );
| vec4 wValues = vec4(
| getW(wF, wR, wC, d1, d2),
| getW(wF, wR, wC, d1 + 1, d2),
| getW(wF, wR, wC, d1 + 2, d2),
| getW(wF, wR, wC, d1 + 3, d2)
| );
|
| dotProd += dot(xValues, wValues);
| }
|
| if (${m===1}) {
| dotProd +=
| getX(batch, xF, xR, xC, ${h}) *
| getW(wF, wR, wC, ${h}, d2);
| } else if (${m===2}) {
| vec2 xValues = vec2(
| getX(batch, xF, xR, xC, ${h}),
| getX(batch, xF, xR, xC, ${h} + 1)
| );
| vec2 wValues = vec2(
| getW(wF, wR, wC, ${h}, d2),
| getW(wF, wR, wC, ${h} + 1, d2)
| );
| dotProd += dot(xValues, wValues);
| } else if (${m===3}) {
| vec3 xValues = vec3(
| getX(batch, xF, xR, xC, ${h}),
| getX(batch, xF, xR, xC, ${h} + 1),
| getX(batch, xF, xR, xC, ${h} + 2)
| );
| vec3 wValues = vec3(
| getW(wF, wR, wC, ${h}, d2),
| getW(wF, wR, wC, ${h} + 1, d2),
| getW(wF, wR, wC, ${h} + 2, d2)
| );
| dotProd += dot(xValues, wValues);
| }
| }
| }
| }
| setOutput(dotProd);
| }
| `}},PA=class{constructor(e,t=!1,n=null,a=!1,r=!1){this.variableNames=["x","W"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"pads",type:"ivec2"},{name:"strides",type:"ivec2"},{name:"dilations",type:"ivec2"},{name:"inDims",type:"ivec2"}],this.outputShape=e.outShape,this.enableShapeUniforms=vn(this.outputShape.length);let s=e.padInfo.left,i=e.strideWidth,o=e.dilationWidth,l=e.filterHeight,u=e.filterWidth,p=u,d=`
| int xR; int xC; int xCOffset;
| vec4 wTexel; vec4 previous; vec4 final;`;for(let f=0;f<u;f++)d+=`
| vec4 xTexelC${f*2};
| int xTexelC${f*2}Ready;
| vec4 xTexelC${f*2+1};
| int xTexelC${f*2+1}Ready;
| vec4 xC${f};`;d+=`
| for (int r = 0; r < ${l}; r++) {
| for (int d1 = 0; d1 < ${e.inChannels}; d1 += 2) {
| `;for(let f=0;f<u;f++)d+=`
| xTexelC${f*2} = vec4(0.0);
| xTexelC${f*2}Ready = 0;
| xTexelC${f*2+1} = vec4(0.0);
| xTexelC${f*2+1}Ready = 0;
| xC${f} = vec4(0.0);`;d+=`
| xR = xRCorner + r * dilations[0];
| if (xR >=0 && xR < inDims[0]) {
| `;for(let f=0;f<(p+1)/2;f++){let g=f*2;if(d+=`
| xC = xCCorner + ${g*o};
| `,i===1){if(g<u&&(s%2===1?(d+=`
| xCOffset = xC + 1;
| if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${g}Ready == 0) {
| xTexelC${g} = getX(batch, xR, xCOffset, d1);
|
| // Need to manually clear unused channels in case
| // we're reading from recycled texture.
| if (xCOffset + 1 >= inDims[1]) {
| xTexelC${g}.zw = vec2(0.0);
| }
| xTexelC${g}Ready = 1;
| }
| `,o===1&&g>0?d+=`
| xC${g} = vec4(xTexelC${g-2}.zw, xTexelC${g}.xy);
| `:d+=`
| xCOffset = xC + 1 - 2;
|
| if (xCOffset >= 0 && xCOffset < inDims[1]) {
| previous = getX(batch, xR, xCOffset, d1);
|
| // Need to manually clear unused channels in case
| // we're reading from recycled texture.
| if (xCOffset + 1 >= inDims[1]) {
| previous.zw = vec2(0.0);
| }
|
| xC${g} = vec4(previous.zw, xTexelC${g}.xy);
| } else {
| xC${g} = vec4(0.0, 0.0, xTexelC${g}.xy);
| }
| `):d+=`
| if (xC >= 0 && xC < inDims[1] && xTexelC${g}Ready == 0) {
| xTexelC${g} = getX(batch, xR, xC, d1);
| if (xC + 1 >= inDims[1]) {
| xTexelC${g}.zw = vec2(0.0);
| }
| xTexelC${g}Ready = 1;
| }
|
| xC${g} = xTexelC${g};
| `,g+1<u)){let b=s%2===0?w.nearestLargerEven(o):o;o%2===0&&s%2===1||o%2!==0&&s%2!==1?(d+=`
| xCOffset = xC + imod(pads[1], 2) + ${b};
|
| if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${g+1}Ready == 0) {
| xTexelC${g+1} = getX(batch, xR, xCOffset, d1);
|
| // Need to manually clear unused channels in case
| // we're reading from recycled texture.
| if (xCOffset + 1 >= inDims[1]) {
| xTexelC${g+1}.zw = vec2(0.0);
| }
| xTexelC${g+1}Ready = 1;
| }
| `,o>1?d+=`
| xCOffset -= 2;
| if (xCOffset >= 0 && xCOffset < inDims[1]) {
| previous = getX(batch, xR, xCOffset, d1);
| xC${g+1} = vec4(previous.zw, xTexelC${g+1}.xy);
| } else {
| xC${g+1} = vec4(0.0, 0.0, xTexelC${g+1}.xy);
| }
| `:d+=`
| xC${g+1} = vec4(xTexelC${g}.zw, xTexelC${g+1}.xy);
| `):b===1?d+=`
| xC${g+1} = xTexelC${g};
| `:d+=`
| xCOffset = xC + ${b};
|
| if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${g+1}Ready == 0) {
| xTexelC${g+1} = getX(batch, xR, xCOffset, d1);
| if (xCOffset + 1 >= inDims[1]) {
| xTexelC${g+1}.zw = vec2(0.0);
| }
| xTexelC${g+1}Ready = 1;
| }
|
| xC${g+1} = xTexelC${g+1};
| `}}else g<u&&(s%2===1?(d+=`
| xCOffset = xC + 1 - strides[1];
| if(xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${g}Ready == 0) {
| xTexelC${g} = getX(batch, xR, xCOffset, d1);
| // Need to manually clear unused channels in case
| // we're reading from recycled texture.
| if (xCOffset + 1 >= inDims[1]) {
| xTexelC${g}.zw = vec2(0.0);
| }
| xTexelC${g}Ready = 1;
| }
|
| if(xC + 1 >= 0 && xC + 1 < inDims[1] && xTexelC${g+1}Ready == 0) {
| xTexelC${g+1} = getX(batch, xR, xC + 1, d1);
| // Need to manually clear unused channels in case
| // we're reading from recycled texture.
| if (xC + 2 >= inDims[1]) {
| xTexelC${g+1}.zw = vec2(0.0);
| }
| xTexelC${g+1}Ready = 1;
| }
|
| xC${g} = vec4(xTexelC${g}.zw, xTexelC${g+1}.zw);
| `,g+1<u&&(d+=`
| final = vec4(0.0);
| xCOffset = xC + 1 + strides[1];
| if(xCOffset >= 0 && xCOffset < inDims[1]) {
| final = getX(batch, xR, xCOffset, d1);
| }
| xC${g+1} = vec4(xTexelC${g+1}.xy, final.xy);
| `)):(d+=`
| if(xC >= 0 && xC < inDims[1] && xTexelC${g}Ready == 0) {
| xTexelC${g} = getX(batch, xR, xC, d1);
| if (xC + 1 >= inDims[1]) {
| xTexelC${g}.zw = vec2(0.0);
| }
| xTexelC${g}Ready = 1;
| }
|
| xCOffset = xC + strides[1];
| if(xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${g+1}Ready == 0) {
| xTexelC${g+1} = getX(batch, xR, xCOffset, d1);
| if (xCOffset + 1 >= inDims[1]) {
| xTexelC${g+1}.zw = vec2(0.);
| }
| xTexelC${g+1}Ready = 1;
| }
|
| xC${g} = vec4(
| xTexelC${g}.xy, xTexelC${g+1}.xy);
| `,g+1<u&&(d+=`
| xC${g+1} = vec4(xTexelC${g}.zw, xTexelC${g+1}.zw);
| `)));g<u&&(d+=`
| wTexel = getW(r, ${g}, d1, d2);
| dotProd += xC${g}.xxzz * vec4(wTexel.xy, wTexel.xy);
| if(d1 + 1 < ${e.inChannels}) {
| dotProd += xC${g}.yyww * vec4(wTexel.zw, wTexel.zw);
| }
| `,g+1<u&&(d+=`
| wTexel = getW(r, ${g+1}, d1, d2);
| dotProd += xC${g+1}.xxzz * vec4(wTexel.xy, wTexel.xy);
| if(d1 + 1 < ${e.inChannels}) {
| dotProd += xC${g+1}.yyww * vec4(wTexel.zw, wTexel.zw);
| }
| `))}d+=`
| }
| `,d+=`
| }
| `,d+=`
| }
| `;let c="",h="";n&&(a?c=`vec4 activation(vec4 a) {
| vec4 b = getPreluActivationWeightsAtOutCoords();
| ${n}
| }`:r?c=`vec4 activation(vec4 a) {
| vec4 b = getLeakyreluAlphaAtOutCoords();
| ${n}
| }`:c=`vec4 activation(vec4 x) {
| ${n}
| }`,h="result = activation(result);");let m=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),a&&this.variableNames.push("preluActivationWeights"),r&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
| ${c}
|
| void main() {
| ivec4 coords = getOutputCoords();
| int batch = coords.x;
| ivec2 xRCCorner = coords.yz * strides - pads;
| int d2 = coords.w;
| int xRCorner = xRCCorner.x;
| int xCCorner = xRCCorner.y;
|
| //intialize dotProd with a small epsilon seems to reduce GPU accuracy loss.
| vec4 dotProd = vec4(0.000000000000001);
|
| ${d}
|
| vec4 result = dotProd - vec4(0.000000000000001);
| ${m}
| ${h}
| setOutput(result);
| }
| `}},Pte=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"inputShape",type:"ivec4"},{name:"pad",type:"ivec2"},{name:"stride",type:"ivec2"},{name:"dilation",type:"ivec2"},{name:"inChannels",type:"int"},{name:"itemsPerBlockRow",type:"int"},{name:"outWidth",type:"int"}],this.outputShape=e,this.enableShapeUniforms=vn(this.outputShape.length);let{dataFormat:n}=t,a=En(),r=n==="channelsLast",s=r?1:2,i=r?2:3,o=this.enableShapeUniforms?"if(blockIndex < outShape[2] && pos < outShape[1]) {":`if(blockIndex < ${e[2]} && pos < ${e[1]}) {`,l="";for(let u=0;u<=1;u++)for(let p=0;p<=1;p++)l+=`
| blockIndex = rc.z + ${p};
| pos = rc.y + ${u};
|
| ${o}
| offsetY = int(blockIndex / outWidth) * stride[0] - pad[0];
| d0 = offsetY + dilation[0] * (pos / itemsPerBlockRow);
|
| if(d0 < inputShape[${s}] && d0 >= 0) {
| // Use custom imod instead mod. On Intel GPU, mod may generate
| // unexpected value.
| // https://github.com/tensorflow/tfjs/issues/5447
| offsetX = imod(blockIndex, outWidth) * stride[1] - pad[1];
| d1 = offsetX + dilation[1] * (imod(pos, itemsPerBlockRow) /
| inChannels);
|
| if(d1 < inputShape[${i}] && d1 >= 0) {
|
| ch = imod(pos, inChannels);
|
| if (${r}) {
| innerDims = vec2(d1, ch);
| result[${u*2+p}] = getChannel(
| getA(rc.x, d0, int(innerDims.x),
| int(innerDims.y)), innerDims);
| } else {
| innerDims = vec2(d0, d1);
| result[${u*2+p}] = getChannel(
| getA(rc.x, ch, int(innerDims.x),
| int(innerDims.y)), innerDims);
| }
| }
| }
| }
| `;this.userCode=`
| void main() {
| ivec3 rc = getOutputCoords();
|
| vec4 result = vec4(0);
|
| int blockIndex, pos, offsetY, d0, offsetX, d1, ch;
| vec2 innerDims;
|
| ${l}
|
| ${a.output} = result;
| }
| `}};function Am(e,t){let n=e.length;return n>=3?t?[...e.slice(0,-3),e[n-3]*e[n-2],e[n-1]]:[...e.slice(0,-3),e[n-3],e[n-2]*e[n-1]]:!t&&n===1&&e[0]>1?[e[0],1]:null}function OA({x:e,filter:t,convInfo:n,backend:a,bias:r=null,preluActivationWeights:s=null,leakyreluAlpha:i=0,activation:o=null}){let l=e.shape,u=a.texData.get(e.dataId),p=n.inChannels,d=l[0]*l[1]*l[2],c=n.outChannels,h=n.dataFormat==="channelsLast",m=!1,f=!1,g,b=[];if(s!=null){let y=Am(s.shape,h);y!=null&&(s=ce({inputs:{x:s},backend:a,attrs:{shape:y}}),b.push(s))}if(r!=null){let y=Am(r.shape,h);y!=null&&(r=ce({inputs:{x:r},backend:a,attrs:{shape:y}}),b.push(r))}if(!((d===1||c===1)&&p>EA)&&u.isPacked&&h&&u.texture!=null&&l[2]%2!==0&&w.arraysEqual(u.shape.slice(-3),l.slice(-3))){let y=l[0]*l[1]*(l[2]+1),x={dataId:e.dataId,shape:[1,y,n.inChannels],dtype:e.dtype},v=u.shape;u.shape=u.shape.slice(),u.shape[u.shape.length-2]++,w.assert(Ac(u.shape,x.shape),()=>`packed reshape ${u.shape} to ${x.shape} isn't free`);let I=ce({inputs:{x:t},backend:a,attrs:{shape:[1,n.inChannels,n.outChannels]}});b.push(I);let T=Em({a:x,b:I,backend:a,transposeA:m,transposeB:f,bias:r,activation:o,preluActivationWeights:s,leakyreluAlpha:i}),C=a.texData.get(T.dataId);w.assert(C.isPacked,()=>"batchMatMul result is expected to be packed"),u.shape=v,C.shape=n.outShape,g=ra({inputs:{x:T},backend:a}),g.shape=n.outShape,b.push(T)}else{let y=n.outHeight*n.outWidth,x=ce({inputs:{x:e},backend:a,attrs:{shape:h?[n.batchSize,y,n.inChannels]:[n.batchSize,n.inChannels,y]}}),v=ce({inputs:{x:t},backend:a,attrs:{shape:[1,n.inChannels,n.outChannels]}}),I=Em({a:h?x:v,b:h?v:x,transposeA:!h,transposeB:f,backend:a,bias:r,activation:o,preluActivationWeights:s,leakyreluAlpha:i});g=ce({inputs:{x:I},backend:a,attrs:{shape:n.outShape}}),b.push(x),b.push(v),b.push(I)}for(let y of b)a.disposeIntermediateTensorInfo(y);return g}function LA({x:e,filter:t,convInfo:n,backend:a,bias:r=null,preluActivationWeights:s=null,leakyreluAlpha:i=0,activation:o=null}){let{filterWidth:l,filterHeight:u,inChannels:p,outWidth:d,outHeight:c,dataFormat:h}=n,m=h==="channelsLast",f=l*u*p,g=c*d,b=[n.batchSize,f,g],y=!0,x=!1,v=[];if(s!=null){let K=Am(s.shape,m);K!=null&&(s=ce({inputs:{x:s},backend:a,attrs:{shape:K}}),v.push(s))}if(r!=null){let K=Am(r.shape,m);K!=null&&(r=ce({inputs:{x:r},backend:a,attrs:{shape:K}}),v.push(r))}let I=ce({inputs:{x:t},backend:a,attrs:{shape:[1,f,w.sizeFromShape(t.shape)/f]}});v.push(I);let T=new Pte(b,n),C=[e.shape,[n.padInfo.top,n.padInfo.left],[n.strideHeight,n.strideWidth],[n.dilationHeight,n.dilationWidth],[n.inChannels],[n.filterWidth*n.inChannels],[n.outWidth]],E=a.runWebGLProgram(T,[e],"float32",C),F=ce({inputs:{x:E},backend:a,attrs:{shape:b}});v.push(E),v.push(F);let D=r!=null,$=s!=null,S=o==="leakyrelu",M=o?Fc(o,!0):null,B=new _A(m?F.shape:I.shape,m?I.shape:F.shape,m?[n.batchSize,g,n.outChannels]:[n.batchSize,n.outChannels,g],y,x,D,M,$,S),U=m?[F,I]:[I,F];if(r&&U.push(r),$&&U.push(s),S){let K=a.makeTensorInfo([],"float32",w.createScalarValue(i,"float32"));U.push(K),v.push(K)}let H=a.runWebGLProgram(B,U,"float32"),j=ce({inputs:{x:H},backend:a,attrs:{shape:n.outShape}});v.push(H);for(let K of v)a.disposeIntermediateTensorInfo(K);return j}function Ote(e){let{inputs:t,backend:n,attrs:a}=e,{x:r,filter:s}=t,{strides:i,pad:o,dataFormat:l,dilations:u,dimRoundingMode:p}=a,d=N.convertConv2DDataFormat(l),c=N.computeConv2DInfo(r.shape,s.shape,i,u,o,p,!1,d),h;if(c.filterHeight===1&&c.filterWidth===1&&c.dilationHeight===1&&c.dilationWidth===1&&c.strideHeight===1&&c.strideWidth===1&&(c.padInfo.type==="SAME"||c.padInfo.type==="VALID"))h=OA({x:r,filter:s,convInfo:c,backend:n});else if(c.strideWidth<=2&&d==="channelsLast"&&G().getBool("WEBGL_EXP_CONV")){let f=new PA(c),g=[[c.padInfo.top,c.padInfo.left],[c.strideHeight,c.strideWidth],[c.dilationHeight,c.dilationWidth],[c.inHeight,c.inWidth]];h=n.runWebGLProgram(f,[r,s],"float32",g)}else if(G().getBool("WEBGL_CONV_IM2COL"))h=LA({x:r,filter:s,convInfo:c,backend:n});else{let f=new MA(c);h=n.runWebGLProgram(f,[r,s],"float32")}let m=ce({inputs:{x:h},backend:n,attrs:{shape:c.outShape}});return n.disposeIntermediateTensorInfo(h),m}var Lte={kernelName:Li,backendName:"webgl",kernelFunc:Ote},zte=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideHeight,n=e.strideWidth,a=e.padInfo.top,r=e.padInfo.left,s=e.dataFormat==="channelsLast";this.userCode=`
| void main() {
| ivec4 coords = getOutputCoords();
| int wR = coords.x;
| int wC = coords.y;
| int d1 = coords.z;
| int d2 = coords.w;
|
| // Convolve x(?, ?, d1) with dy(:, :, d2) to get dw(wR, wC, d1, d2).
| // ? = to be determined. : = across all values in that axis.
| float dotProd = 0.0;
|
| for (int b = 0; b < ${e.batchSize}; b++) {
| for (int yR = 0; yR < ${e.outHeight}; yR++) {
| int xR = wR + yR * ${t} - ${a};
|
| if (xR < 0 || xR >= ${e.inHeight}) {
| continue;
| }
|
| for (int yC = 0; yC < ${e.outWidth}; yC++) {
| int xC = wC + yC * ${n} - ${r};
|
| if (xC < 0 || xC >= ${e.inWidth}) {
| continue;
| }
|
| ${s?`float dyValue = getDy(b, yR, yC, d2);
| float xValue = getX(b, xR, xC, d1);
| dotProd += (xValue * dyValue);`:`float dyValue = getDy(b, d2, yR, yC);
| float xValue = getX(b, d1, xR, xC);
| dotProd += (xValue * dyValue);`}
| }
| }
| }
| setOutput(dotProd);
| }
| `}},Wte=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterHeight,n=e.filterWidth,a=e.strideHeight,r=e.strideWidth,s=e.dataFormat==="channelsLast",i=t-1-e.padInfo.top,o=n-1-e.padInfo.left,l=s?1:2,u=s?2:3,p=s?3:1;this.userCode=`
| const ivec2 pads = ivec2(${i}, ${o});
|
| void main() {
| ivec4 coords = getOutputCoords();
| int batch = coords[0];
| int d1 = coords[${p}];
|
| ivec2 dyCorner = ivec2(coords[${l}], coords[${u}]) - pads;
| int dyRCorner = dyCorner.x;
| int dyCCorner = dyCorner.y;
|
| // Convolve dy(?, ?, d2) with w(:, :, d1, d2) to compute dx(xR, xC, d1).
| // ? = to be determined. : = across all values in that axis.
| float dotProd = 0.0;
| for (int wR = 0; wR < ${t}; wR++) {
| float dyR = float(dyRCorner + wR) / ${a}.0;
|
| if (dyR < 0.0 || dyR >= ${e.outHeight}.0 || fract(dyR) > 0.0) {
| continue;
| }
| int idyR = int(dyR);
|
| int wRPerm = ${t} - 1 - wR;
|
| for (int wC = 0; wC < ${n}; wC++) {
| float dyC = float(dyCCorner + wC) / ${r}.0;
|
| if (dyC < 0.0 || dyC >= ${e.outWidth}.0 ||
| fract(dyC) > 0.0) {
| continue;
| }
| int idyC = int(dyC);
|
| int wCPerm = ${n} - 1 - wC;
|
| for (int d2 = 0; d2 < ${e.outChannels}; d2++) {
|
| if (${s}) {
| float xValue = getDy(batch, idyR, idyC, d2);
| float wValue = getW(wRPerm, wCPerm, d1, d2);
| dotProd += xValue * wValue;
| } else {
| float xValue = getDy(batch, d2, idyR, idyC);
| float wValue = getW(wRPerm, wCPerm, d1, d2);
| dotProd += xValue * wValue;
| }
|
| }
| }
| }
| setOutput(dotProd);
| }
| `}},Bte=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideDepth,n=e.strideHeight,a=e.strideWidth,r=e.padInfo.front,s=e.padInfo.top,i=e.padInfo.left;this.userCode=`
| void main() {
| ivec5 coords = getOutputCoords();
| int wF = coords.x;
| int wR = coords.y;
| int wC = coords.z;
| int d1 = coords.w;
| int d2 = coords.u;
|
| float dotProd = 0.0;
|
| for (int b = 0; b < ${e.batchSize}; b++) {
| for (int yF = 0; yF < ${e.outDepth}; yF++) {
| int xF = wF + yF * ${t} - ${r};
|
| if (xF < 0 || xF >= ${e.inDepth}) {
| continue;
| }
|
| for (int yR = 0; yR < ${e.outHeight}; yR++) {
| int xR = wR + yR * ${n} - ${s};
|
| if (xR < 0 || xR >= ${e.inHeight}) {
| continue;
| }
|
| for (int yC = 0; yC < ${e.outWidth}; yC++) {
| int xC = wC + yC * ${a} - ${i};
|
| if (xC < 0 || xC >= ${e.inWidth}) {
| continue;
| }
|
| float dyValue = getDy(b, yF, yR, yC, d2);
| float xValue = getX(b, xF, xR, xC, d1);
| dotProd += (xValue * dyValue);
| }
| }
| }
| }
| setOutput(dotProd);
| }
| `}},Vte=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterDepth,n=e.filterHeight,a=e.filterWidth,r=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=t-1-e.padInfo.front,l=n-1-e.padInfo.top,u=a-1-e.padInfo.left;this.userCode=`
| const ivec3 pads = ivec3(${o}, ${l}, ${u});
|
| void main() {
| ivec5 coords = getOutputCoords();
| int batch = coords.x;
| int d1 = coords.u;
|
|
| ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads;
| int dyFCorner = dyCorner.x;
| int dyRCorner = dyCorner.y;
| int dyCCorner = dyCorner.z;
|
| float dotProd = 0.0;
| for (int wF = 0; wF < ${t}; wF++) {
| float dyF = float(dyFCorner + wF) / ${r}.0;
|
| if (dyF < 0.0 || dyF >= ${e.outDepth}.0 || fract(dyF) > 0.0) {
| continue;
| }
| int idyF = int(dyF);
|
| int wFPerm = ${t} - 1 - wF;
|
| for (int wR = 0; wR < ${n}; wR++) {
| float dyR = float(dyRCorner + wR) / ${s}.0;
|
| if (dyR < 0.0 || dyR >= ${e.outHeight}.0 ||
| fract(dyR) > 0.0) {
| continue;
| }
| int idyR = int(dyR);
|
| int wRPerm = ${n} - 1 - wR;
|
| for (int wC = 0; wC < ${a}; wC++) {
| float dyC = float(dyCCorner + wC) / ${i}.0;
|
| if (dyC < 0.0 || dyC >= ${e.outWidth}.0 ||
| fract(dyC) > 0.0) {
| continue;
| }
| int idyC = int(dyC);
|
| int wCPerm = ${a} - 1 - wC;
|
| for (int d2 = 0; d2 < ${e.outChannels}; d2++) {
| float xValue = getDy(batch, idyF, idyR, idyC, d2);
| float wValue = getW(wFPerm, wRPerm, wCPerm, d1, d2);
| dotProd += xValue * wValue;
| }
| }
| }
| }
| setOutput(dotProd);
| }
| `}};function Ute(e){let{inputs:t,backend:n,attrs:a}=e,{x:r,dy:s}=t,{strides:i,pad:o,dataFormat:l,dimRoundingMode:u,filterShape:p}=a,d=N.convertConv2DDataFormat(l),c=N.computeConv2DInfo(r.shape,p,i,1,o,u,!1,d),h=new zte(c);return n.runWebGLProgram(h,[r,s],"float32")}var Gte={kernelName:Lm,backendName:"webgl",kernelFunc:Ute},Hte=class{constructor(e){this.variableNames=["dy","W"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"strides",type:"vec2"}],this.outputShape=e.inShape,this.enableShapeUniforms=vn(this.outputShape.length);let t=e.filterHeight,n=e.filterWidth,a=t-1-e.padInfo.top,r=n-1-e.padInfo.left;this.userCode=`
| const ivec2 pads = ivec2(${a}, ${r});
|
| void main() {
| ivec4 coords = getOutputCoords();
| int batch = coords[0];
| int d1 = coords[3];
|
| ivec2 dyCorner = ivec2(coords[1], coords[2]) - pads;
| int dyRCorner = dyCorner.x;
| int dyCCorner = dyCorner.y;
|
| vec4 result = vec4(0.);
| for (int wR = 0; wR < ${t}; wR++) {
| float dyR = float(dyRCorner + wR) / strides[0];
| if (dyR < 0.0 || dyR >= ${e.outHeight}.0 || fract(dyR) > 0.0) {
| continue;
| }
| int idyR = int(dyR);
| int wRPerm = ${t} - 1 - wR;
|
| for (int wC = 0; wC < ${n}; wC++) {
| int wCPerm = ${n} - 1 - wC;
|
| float dyC = float(dyCCorner + wC) / strides[1];
| bool idyCVal = (dyC >= 0.0) && (dyC < ${e.outWidth}.0)
| && (fract(dyC) == 0.0);
| int idyC = int(dyC);
|
| float dyC2 = float(dyCCorner + wC + 1) / strides[1];
| bool idyCVal2 = (dyC2 >= 0.0) && (dyC2 < ${e.outWidth}.0)
| && (fract(dyC2) == 0.0);
| int idyC2 = int(dyC2);
|
| if (idyCVal && idyCVal2) {
| for (int d2 = 0; d2 < ${e.outChannels}; d2 += 2) {
| vec4 wValue = getW(wRPerm, wCPerm, d1, d2);
| vec4 dySample = getDy(batch, idyR, idyC, d2);
| vec4 dySample2 = (idyC / 2 == idyC2 / 2) ?
| dySample : getDy(batch, idyR, idyC2, d2);
|
| vec2 dyValue = mod(float(idyC), 2.) == 0. ?
| dySample.xy : dySample.zw;
| result.xy += vec2(dot(dyValue, wValue.xy),
| dot(dyValue, wValue.zw));
|
| dyValue = mod(float(idyC2), 2.) == 0. ?
| dySample2.xy : dySample2.zw;
| result.zw += vec2(dot(dyValue, wValue.xy),
| dot(dyValue, wValue.zw));
| }
| } else if (idyCVal) {
| for (int d2 = 0; d2 < ${e.outChannels}; d2 += 2) {
| vec4 wValue = getW(wRPerm, wCPerm, d1, d2);
| vec4 dySample = getDy(batch, idyR, idyC, d2);
| vec2 dyValue = mod(float(idyC), 2.) == 0. ?
| dySample.xy : dySample.zw;
| result.xy += vec2(dot(dyValue, wValue.xy),
| dot(dyValue, wValue.zw));
| }
| } else if (idyCVal2) {
| for (int d2 = 0; d2 < ${e.outChannels}; d2 += 2) {
| vec4 wValue = getW(wRPerm, wCPerm, d1, d2);
| vec4 dySample = getDy(batch, idyR, idyC2, d2);
| vec2 dyValue = mod(float(idyC2), 2.) == 0. ?
| dySample.xy : dySample.zw;
| result.zw += vec2(dot(dyValue, wValue.xy),
| dot(dyValue, wValue.zw));
| }
| }
| }
| }
| setOutput(result);
| }
| `}};function qte(e){let{inputs:t,backend:n,attrs:a}=e,{dy:r,filter:s}=t,{inputShape:i,strides:o,pad:l,dataFormat:u,dimRoundingMode:p}=a,d=N.convertConv2DDataFormat(u),c=N.computeConv2DInfo(i,s.shape,o,1,l,p,!1,d);if(G().getBool("WEBGL_PACK")&&d==="channelsLast"){let h=[[c.strideHeight,c.strideWidth]],m=new Hte(c);return n.runWebGLProgram(m,[r,s],"float32",h)}else{let h=new Wte(c);return n.runWebGLProgram(h,[r,s],"float32")}}var jte={kernelName:zi,backendName:"webgl",kernelFunc:qte};function Kte(e){let{inputs:t,backend:n,attrs:a}=e,{x:r,filter:s}=t,{strides:i,pad:o,dilations:l}=a,u=N.computeConv3DInfo(r.shape,s.shape,i,l,o),p=new Mte(u);return n.runWebGLProgram(p,[r,s],"float32")}var Xte={kernelName:Wi,backendName:"webgl",kernelFunc:Kte};function Yte(e){let{inputs:t,backend:n,attrs:a}=e,{x:r,dy:s}=t,{strides:i,pad:o,filterShape:l}=a,u=N.computeConv3DInfo(r.shape,l,i,1,o),p=new Bte(u);return n.runWebGLProgram(p,[r,s],"float32")}var Zte={kernelName:yu,backendName:"webgl",kernelFunc:Yte};function Jte(e){let{inputs:t,backend:n,attrs:a}=e,{dy:r,filter:s}=t,{pad:i,strides:o,inputShape:l}=a,u=N.computeConv3DInfo(l,s.shape,o,1,i),p=new Vte(u);return n.runWebGLProgram(p,[r,s],"float32")}var Qte={kernelName:xu,backendName:"webgl",kernelFunc:Jte},ene=Tp+`
| return cos(x);
| `,tne=`
| vec4 result = cos(x);
| bvec4 isNaN = isnan(x);
| ${el}
| return result;
| `,nne=Ze({opSnippet:ene,packedOpSnippet:tne}),ane={kernelName:Bi,backendName:"webgl",kernelFunc:nne},rne=`
| float e2x = exp(-x);
| return (e2x + 1.0 / e2x) / 2.0;
| `,sne=Ze({opSnippet:rne}),ine={kernelName:Vi,backendName:"webgl",kernelFunc:sne},one=class{constructor(e,t,n,a,r){this.variableNames=["Image","Boxes","BoxInd"],this.outputShape=[];let[s,i,o,l]=e,[u]=t,[p,d]=n;this.outputShape=[u,p,d,l];let c=a==="bilinear"?1:0,[h,m]=[`${i-1}.0`,`${o-1}.0`],[f,g,b]=p>1?[`${(i-1)/(p-1)}`,"(y2-y1) * height_ratio",`y1*${h} + float(y)*(height_scale)`]:["0.0","0.0",`0.5 * (y1+y2) * ${h}`],[y,x,v]=d>1?[`${(o-1)/(d-1)}`,"(x2-x1) * width_ratio",`x1*${m} + float(x)*(width_scale)`]:["0.0","0.0",`0.5 * (x1+x2) * ${m}`];this.userCode=`
| const float height_ratio = float(${f});
| const float width_ratio = float(${y});
| void main() {
| ivec4 coords = getOutputCoords();
| int b = coords[0];
| int y = coords[1];
| int x = coords[2];
| int d = coords[3];
|
| // get box vals
| float y1 = getBoxes(b,0);
| float x1 = getBoxes(b,1);
| float y2 = getBoxes(b,2);
| float x2 = getBoxes(b,3);
|
| // get image in batch index
| int bInd = round(getBoxInd(b));
| if(bInd < 0 || bInd >= ${s}) {
| return;
| }
|
| float height_scale = ${g};
| float width_scale = ${x};
|
| float in_y = ${b};
| if( in_y < 0.0 || in_y > ${h} ) {
| setOutput(float(${r}));
| return;
| }
| float in_x = ${v};
| if( in_x < 0.0 || in_x > ${m} ) {
| setOutput(float(${r}));
| return;
| }
|
| vec2 sourceFracIndexCR = vec2(in_x,in_y);
| if(${c} == 1) {
| // Compute the four integer indices.
| ivec2 sourceFloorCR = ivec2(sourceFracIndexCR);
| ivec2 sourceCeilCR = ivec2(ceil(sourceFracIndexCR));
|
| float topLeft = getImage(b, sourceFloorCR.y, sourceFloorCR.x, d);
| float bottomLeft = getImage(b, sourceCeilCR.y, sourceFloorCR.x, d);
| float topRight = getImage(b, sourceFloorCR.y, sourceCeilCR.x, d);
| float bottomRight = getImage(b, sourceCeilCR.y, sourceCeilCR.x, d);
|
| vec2 fracCR = sourceFracIndexCR - vec2(sourceFloorCR);
|
| float top = topLeft + (topRight - topLeft) * fracCR.x;
| float bottom = bottomLeft + (bottomRight - bottomLeft) * fracCR.x;
| float newValue = top + (bottom - top) * fracCR.y;
| setOutput(newValue);
| } else {
| // Compute the coordinators of nearest neighbor point.
| ivec2 sourceNearestCR = ivec2(floor(
| sourceFracIndexCR + vec2(0.5,0.5)));
| float newValue = getImage(b, sourceNearestCR.y, sourceNearestCR.x, d);
| setOutput(newValue);
| }
| }
| `}},lne=e=>{let{inputs:t,backend:n,attrs:a}=e,{image:r,boxes:s,boxInd:i}=t,{cropSize:o,method:l,extrapolationValue:u}=a,p=new one(r.shape,s.shape,o,l,u);return n.runWebGLProgram(p,[r,s,i],"float32")},une={kernelName:wu,backendName:"webgl",kernelFunc:lne},Dc;(function(e){e.Prod="*",e.Sum="+"})(Dc||(Dc={}));var _S=class{constructor(e,t,n,a){this.op=e,this.outputShape=t,this.variableNames=["x"],this.customUniforms=[{name:"index",type:"float"}];let r=this.outputShape.length,s=this.op===Dc.Prod?"1.0":"0.0",i=n?s:`getX(${ES(r,"coords",this.op)})`,o=this.outputShape[this.outputShape.length-1],l="",u="";n?(l=a?`end != ${o-1}`:"end != 0",u=a?"end + 1":"end - 1"):(l=a?`end + pow2 < ${o}`:"end >= pow2",u=a?"end + pow2":"end - pow2"),this.userCode=`
| void main() {
| ${dt(r)} coords = getOutputCoords();
| int end = ${AS(r,"coords",this.op)};
| float val = ${i};
| int pow2 = int(pow(2.0, index));
| if (${l}) {
| int idx = ${u};
| ${AS(r,"coords",this.op)} = idx;
| val ${this.op}= getX(${ES(r,"coords",this.op)});
| }
| setOutput(val);
| }
| `}};function ES(e,t,n){if(e===1)return`${t}`;if(e===2)return`${t}.x, ${t}.y`;if(e===3)return`${t}.x, ${t}.y, ${t}.z`;if(e===4)return`${t}.x, ${t}.y, ${t}.z, ${t}.w`;throw new Error(`Cumulative ${n} for rank ${e} is not yet supported`)}function AS(e,t,n){if(e===1)return`${t}`;if(e===2)return`${t}.y`;if(e===3)return`${t}.z`;if(e===4)return`${t}.w`;throw new Error(`Cumulative ${n} for rank ${e} is not yet supported`)}function zA(e,t,n,a,r,s){let i=t.shape.length,o=N.getAxesPermutation([a],i),l=t;o!=null&&(l=Nn({inputs:{x:t},backend:n,attrs:{perm:o}}));let u=N.getInnerMostAxes(1,i)[0];if(u!==i-1)throw new Error(`WebGL cumprod shader expects an inner-most axis=${t.shape.length-1} but got axis=${a}`);let p=l.shape[u],d=ra({inputs:{x:l},backend:n});for(let c=0;c<=Math.ceil(Math.log2(p))-1;c++){let h=new _S(e,l.shape,!1,s),m=[[c]],f=d;d=n.runWebGLProgram(h,[d],d.dtype,m),n.disposeIntermediateTensorInfo(f)}if(r){let c=new _S(e,l.shape,r,s),h=d;d=n.runWebGLProgram(c,[d],d.dtype),n.disposeIntermediateTensorInfo(h)}if(o!=null){let c=N.getUndoAxesPermutation(o),h=Nn({inputs:{x:d},backend:n,attrs:{perm:c}});return n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(l),h}return d}function pne(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{axis:s,exclusive:i,reverse:o}=a;return zA(Dc.Prod,r,n,s,i,o)}var cne={kernelName:vu,backendName:"webgl",kernelFunc:pne};function dne(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{axis:s,exclusive:i,reverse:o}=a;return zA(Dc.Sum,r,n,s,i,o)}var hne={kernelName:Ui,backendName:"webgl",kernelFunc:dne};function mne(e){let{inputs:t,backend:n,attrs:a}=e,{x:r,weights:s}=t,{size:i,binaryOutput:o}=a;if(r.shape.length===1){let l=n.readSync(r.dataId),u=n.readSync(s.dataId),p=yA(l,u,s.dtype,s.shape,i);return n.makeTensorInfo([i],s.dtype,p)}else if(r.shape.length===2){let l=n.bufferSync(r),u=n.bufferSync(s),p=g9(l,u,i,o);return n.makeTensorInfo(p.shape,s.dtype,p.values)}throw new Error(`Error in denseBincount: input must be at most rank 2, but got rank${r.shape.length}.`)}var fne={kernelName:Bc,backendName:"webgl",kernelFunc:mne},gne=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 bne(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{blockSize:s,dataFormat:i}=a,o=r.shape[0],l=i==="NHWC"?r.shape[1]:r.shape[2],u=i==="NHWC"?r.shape[2]:r.shape[3],p=i==="NHWC"?r.shape[3]:r.shape[1],d=l*s,c=u*s,h=p/(s*s),m=i==="NHWC"?[o,d,c,h]:[o,h,d,c],f=new gne(m,s,i);return n.runWebGLProgram(f,[r],r.dtype)}var yne={kernelName:ku,backendName:"webgl",kernelFunc:bne},WA=class{constructor(e,t=!1,n=null,a=!1,r=!1){this.variableNames=["x","W"],this.customUniforms=[{name:"pads",type:"ivec2"},{name:"strides",type:"ivec2"},{name:"dilations",type:"ivec2"},{name:"inDims",type:"ivec2"}],this.outputShape=e.outShape,this.enableShapeUniforms=vn(this.outputShape.length);let s=e.filterHeight,i=e.filterWidth,o=e.outChannels/e.inChannels,l="",u="";n&&(a?l=`float activation(float a) {
| float b = getPreluActivationWeightsAtOutCoords();
| ${n}
| }`:r?l=`float activation(float a) {
| float b = getLeakyreluAlphaAtOutCoords();
| ${n}
| }`:l=`
| float activation(float x) {
| ${n}
| }
| `,u="result = activation(result);");let p=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),a&&this.variableNames.push("preluActivationWeights"),r&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
| ${l}
|
| void main() {
| ivec4 coords = getOutputCoords();
| int batch = coords.x;
| ivec2 xRCCorner = coords.yz * strides - pads;
| int d2 = coords.w;
| int d1 = d2 / ${o};
| int q = d2 - d1 * ${o};
|
| int xRCorner = xRCCorner.x;
| int xCCorner = xRCCorner.y;
|
| // Convolve x(?, ?, d1) with w(:, :, d1, q) to get y(yR, yC, d2).
| // ? = to be determined. : = across all values in that axis.
| float dotProd = 0.0;
| // TO DO(dsmilkov): Flatten the two for loops and vec4 the operations.
| for (int wR = 0; wR < ${s}; wR++) {
| int xR = xRCorner + wR * dilations[0];
|
| if (xR < 0 || xR >= inDims[0]) {
| continue;
| }
|
| for (int wC = 0; wC < ${i}; wC++) {
| int xC = xCCorner + wC * dilations[1];
|
| if (xC < 0 || xC >= inDims[1]) {
| continue;
| }
|
| float xVal = getX(batch, xR, xC, d1);
| float wVal = getW(wR, wC, d1, q);
| dotProd += xVal * wVal;
| }
| }
|
| float result = dotProd;
| ${p}
| ${u}
| setOutput(result);
| }
| `}},BA=class{constructor(e,t=!1,n=null,a=!1,r=!1){this.variableNames=["x","W"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"pads",type:"ivec2"},{name:"strides",type:"ivec2"},{name:"dilations",type:"ivec2"},{name:"inDims",type:"ivec2"}],this.outputShape=e.outShape,this.enableShapeUniforms=vn(this.outputShape.length);let s=e.outChannels/e.inChannels,i=e.padInfo.left,o=e.strideWidth,l=e.dilationWidth,u=e.filterHeight,p=e.filterWidth,d=p,c=`
| int xR; int xC; int xCOffset;
| vec4 wTexel; vec4 previous; vec4 final;`;for(let g=0;g<p;g++)c+=`
| vec4 xTexelC${g*2};
| int xTexelC${g*2}Ready;
| vec4 xTexelC${g*2+1};
| int xTexelC${g*2+1}Ready;
| vec4 xC${g};`;c+=`
| for (int r = 0; r < ${u}; r++) {
| `;for(let g=0;g<p;g++)c+=`
| xTexelC${g*2} = vec4(0.0);
| xTexelC${g*2}Ready = 0;
| xTexelC${g*2+1} = vec4(0.0);
| xTexelC${g*2+1}Ready = 0;
| xC${g} = vec4(0.0);`;c+=`
| xR = xRCorner + r * dilations[0];
| if (xR >=0 && xR < inDims[0]) {
| `;for(let g=0;g<(d+1)/2;g++){let b=g*2;if(c+=`
| xC = xCCorner + ${b*l};
| `,o===1){if(b<p&&(i%2===1?(c+=`
| xCOffset = xC + 1;
| if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${b}Ready == 0) {
| xTexelC${b} = getX(batch, xR, xCOffset, d1);
|
| // Need to manually clear unused channels in case
| // we're reading from recycled texture.
| if (xCOffset + 1 >= inDims[1]) {
| xTexelC${b}.zw = vec2(0.0);
| }
| xTexelC${b}Ready = 1;
| }
| `,l===1&&b>0?c+=`
| xC${b} = vec4(xTexelC${b-2}.zw, xTexelC${b}.xy);
| `:c+=`
| xCOffset = xC + 1 - 2;
|
| if (xCOffset >= 0 && xCOffset < inDims[1]) {
| previous = getX(batch, xR, xCOffset, d1);
|
| // Need to manually clear unused channels in case
| // we're reading from recycled texture.
| if (xCOffset + 1 >= inDims[1]) {
| previous.zw = vec2(0.0);
| }
|
| xC${b} = vec4(previous.zw, xTexelC${b}.xy);
| } else {
| xC${b} = vec4(0.0, 0.0, xTexelC${b}.xy);
| }
| `):c+=`
| if (xC >= 0 && xC < inDims[1] && xTexelC${b}Ready == 0) {
| xTexelC${b} = getX(batch, xR, xC, d1);
| if (xC + 1 >= inDims[1]) {
| xTexelC${b}.zw = vec2(0.0);
| }
| xTexelC${b}Ready = 1;
| }
|
| xC${b} = xTexelC${b};
| `,b+1<p)){let y=i%2===0?w.nearestLargerEven(l):l;l%2===0&&i%2===1||l%2!==0&&i%2!==1?(c+=`
| xCOffset = xC + imod(pads[1], 2) + ${y};
|
| if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${b+1}Ready == 0) {
| xTexelC${b+1} = getX(batch, xR, xCOffset, d1);
|
| // Need to manually clear unused channels in case
| // we're reading from recycled texture.
| if (xCOffset + 1 >= inDims[1]) {
| xTexelC${b+1}.zw = vec2(0.0);
| }
| xTexelC${b+1}Ready = 1;
| }
| `,l>1?c+=`
| xCOffset -= 2;
| if (xCOffset >= 0 && xCOffset < inDims[1]) {
| previous = getX(batch, xR, xCOffset, d1);
| xC${b+1} = vec4(previous.zw, xTexelC${b+1}.xy);
| } else {
| xC${b+1} = vec4(0.0, 0.0, xTexelC${b+1}.xy);
| }
| `:c+=`
| xC${b+1} = vec4(xTexelC${b}.zw, xTexelC${b+1}.xy);
| `):y===1?c+=`
| xC${b+1} = xTexelC${b};
| `:c+=`
| xCOffset = xC + ${y};
|
| if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${b+1}Ready == 0) {
| xTexelC${b+1} = getX(batch, xR, xCOffset, d1);
| if (xCOffset + 1 >= inDims[1]) {
| xTexelC${b+1}.zw = vec2(0.0);
| }
| xTexelC${b+1}Ready = 1;
| }
|
| xC${b+1} = xTexelC${b+1};
| `}}else b<p&&(i%2===1?(c+=`
| xCOffset = xC + 1 - strides[1];
| if(xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${b}Ready == 0) {
| xTexelC${b} = getX(batch, xR, xCOffset, d1);
| // Need to manually clear unused channels in case
| // we're reading from recycled texture.
| if (xCOffset + 1 >= inDims[1]) {
| xTexelC${b}.zw = vec2(0.0);
| }
| xTexelC${b}Ready = 1;
| }
|
| if(xC + 1 >= 0 && xC + 1 < inDims[1] && xTexelC${b+1}Ready == 0) {
| xTexelC${b+1} = getX(batch, xR, xC + 1, d1);
| // Need to manually clear unused channels in case
| // we're reading from recycled texture.
| if (xC + 2 >= inDims[1]) {
| xTexelC${b+1}.zw = vec2(0.0);
| }
| xTexelC${b+1}Ready = 1;
| }
|
| xC${b} = vec4(xTexelC${b}.zw, xTexelC${b+1}.zw);
| `,b+1<p&&(c+=`
| final = vec4(0.0);
| xCOffset = xC + 1 + strides[1];
| if(xCOffset >= 0 && xCOffset < inDims[1]) {
| final = getX(batch, xR, xCOffset, d1);
| }
| xC${b+1} = vec4(xTexelC${b+1}.xy, final.xy);
| `)):(c+=`
| if(xC >= 0 && xC < inDims[1] && xTexelC${b}Ready == 0) {
| xTexelC${b} = getX(batch, xR, xC, d1);
| if (xC + 1 >= inDims[1]) {
| xTexelC${b}.zw = vec2(0.0);
| }
| xTexelC${b}Ready = 1;
| }
|
| xCOffset = xC + strides[1];
| if(xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${b+1}Ready == 0) {
| xTexelC${b+1} = getX(batch, xR, xCOffset, d1);
| if (xCOffset + 1 >= inDims[1]) {
| xTexelC${b+1}.zw = vec2(0.);
| }
| xTexelC${b+1}Ready = 1;
| }
|
| xC${b} = vec4(
| xTexelC${b}.xy, xTexelC${b+1}.xy);
| `,b+1<p&&(c+=`
| xC${b+1} = vec4(xTexelC${b}.zw, xTexelC${b+1}.zw);
| `)));b<p&&(c+=`
| wTexel = getW(r, ${b}, d1, q);
| dotProd += xC${b} * vec4(wTexel.xz, wTexel.xz);
| `,b+1<p&&(c+=`
| wTexel = getW(r, ${b+1}, d1, q);
| dotProd += xC${b+1} * vec4(wTexel.xz, wTexel.xz);
| `))}c+=`
| }
| `,c+=`
| }
| `;let h="",m="";n&&(a?h=`vec4 activation(vec4 a) {
| vec4 b = getPreluActivationWeightsAtOutCoords();
| ${n}
| }`:r?h=`vec4 activation(vec4 a) {
| vec4 b = getLeakyreluAlphaAtOutCoords();
| ${n}
| }`:h=`vec4 activation(vec4 x) {
| ${n}
| }`,m="result = activation(result);");let f=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),a&&this.variableNames.push("preluActivationWeights"),r&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
| ${h}
|
| void main() {
| ivec4 coords = getOutputCoords();
| int batch = coords.x;
| ivec2 xRCCorner = coords.yz * strides - pads;
| int d2 = coords.w;
| int d1 = d2 / ${s};
| int q = d2 - d1 * ${s};
| int xRCorner = xRCCorner.x;
| int xCCorner = xRCCorner.y;
|
| //intialize dotProd with a small epsilon seems to reduce GPU accuracy loss.
| vec4 dotProd = vec4(0.000000000000001);
|
| ${c}
|
| vec4 result = dotProd - vec4(0.000000000000001);
| ${f}
| ${m}
| setOutput(result);
| }
| `}};function xne(e){let{inputs:t,backend:n,attrs:a}=e,{x:r,filter:s}=t,{strides:i,pad:o,dilations:l,dimRoundingMode:u}=a,p=l;p==null&&(p=[1,1]),w.assert(N.eitherStridesOrDilationsAreOne(i,p),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${i} and dilations '${p}'`);let d=N.computeConv2DInfo(r.shape,s.shape,i,p,o,u,!0),c;G().getBool("WEBGL_PACK_DEPTHWISECONV")&&d.strideWidth<=2&&d.outChannels/d.inChannels===1?c=new BA(d):c=new WA(d);let h=[[d.padInfo.top,d.padInfo.left],[d.strideHeight,d.strideWidth],[d.dilationHeight,d.dilationWidth],[d.inHeight,d.inWidth]];return n.runWebGLProgram(c,[r,s],"float32",h)}var vne={kernelName:Gi,backendName:"webgl",kernelFunc:xne},wne=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideHeight,n=e.strideWidth,a=e.padInfo.top,r=e.padInfo.left,s=e.outChannels/e.inChannels;this.userCode=`
| void main() {
| ivec4 coords = getOutputCoords();
| int wR = coords.x;
| int wC = coords.y;
| int d1 = coords.z;
| int dm = coords.w;
| int d2 = d1 * ${s} + dm;
|
| float dotProd = 0.0;
|
| // TO DO: Vec4 over the batch size
| for (int b = 0; b < ${e.batchSize}; b++) {
| for (int yR = 0; yR < ${e.outHeight}; yR++) {
| int xR = wR + yR * ${t} - ${a};
|
| if (xR < 0 || xR >= ${e.inHeight}) {
| continue;
| }
|
| for (int yC = 0; yC < ${e.outWidth}; yC++) {
| int xC = wC + yC * ${n} - ${r};
|
| if (xC < 0 || xC >= ${e.inWidth}) {
| continue;
| }
|
| float dyValue = getDy(b, yR, yC, d2);
| float xValue = getX(b, xR, xC, d1);
| dotProd += (xValue * dyValue);
| }
| }
| }
| setOutput(dotProd);
| }
| `}},kne=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterHeight,n=e.filterWidth,a=e.strideHeight,r=e.strideWidth,s=t-1-e.padInfo.top,i=n-1-e.padInfo.left,o=e.outChannels/e.inChannels;this.userCode=`
| const ivec2 pads = ivec2(${s}, ${i});
|
| void main() {
| ivec4 coords = getOutputCoords();
| int batch = coords[0];
| int d1 = coords[3];
| ivec2 dyCorner = coords.yz - pads;
| int dyRCorner = dyCorner.x;
| int dyCCorner = dyCorner.y;
|
| float dotProd = 0.0;
|
| for (int wR = 0; wR < ${t}; wR++) {
| float dyR = float(dyRCorner + wR) / ${a}.0;
|
| if (dyR < 0.0 || dyR >= ${e.outHeight}.0 || fract(dyR) > 0.0) {
| continue;
| }
| int idyR = int(dyR);
|
| int wRPerm = ${t} - 1 - wR;
|
| for (int wC = 0; wC < ${n}; wC++) {
| float dyC = float(dyCCorner + wC) / ${r}.0;
|
| if (dyC < 0.0 || dyC >= ${e.outWidth}.0 ||
| fract(dyC) > 0.0) {
| continue;
| }
| int idyC = int(dyC);
|
| int wCPerm = ${n} - 1 - wC;
|
| // TO DO: Vec4 over the channelMul
| for (int dm = 0; dm < ${o}; dm++) {
| int d2 = d1 * ${o} + dm;
| float xValue = getDy(batch, idyR, idyC, d2);
| float wValue = getW(wRPerm, wCPerm, d1, dm);
| dotProd += xValue * wValue;
| }
| }
| }
| setOutput(dotProd);
| }
| `}};function Ine(e){let{inputs:t,backend:n,attrs:a}=e,{x:r,dy:s}=t,{strides:i,dilations:o,pad:l,dimRoundingMode:u,filterShape:p}=a,d=N.computeConv2DInfo(r.shape,p,i,o,l,u,!0),c=new wne(d);return n.runWebGLProgram(c,[r,s],"float32")}var Sne={kernelName:zm,backendName:"webgl",kernelFunc:Ine};function Nne(e){let{inputs:t,backend:n,attrs:a}=e,{dy:r,filter:s}=t,{strides:i,dilations:o,pad:l,dimRoundingMode:u,inputShape:p}=a,d=N.computeConv2DInfo(p,s.shape,i,o,l,u,!0),c=new kne(d);return n.runWebGLProgram(c,[r,s],"float32")}var Tne={kernelName:Wm,backendName:"webgl",kernelFunc:Nne},Cne=class{constructor(e){this.variableNames=["X"],this.outputShape=[e,e],this.userCode=`
| void main() {
| ivec2 coords = getOutputCoords();
| float val = coords[0] == coords[1] ? getX(coords[0]) : 0.0;
| setOutput(val);
| }
| `}};function _ne(e){let{inputs:t,backend:n}=e,{x:a}=t,r=[...a.shape,...a.shape],s=w.sizeFromShape(a.shape),i=ce({inputs:{x:a},backend:n,attrs:{shape:[s]}}),o=new Cne(s),l=n.runWebGLProgram(o,[i],i.dtype),u=ce({inputs:{x:l},backend:n,attrs:{shape:r}});return n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(l),u}var Ene={kernelName:Vc,backendName:"webgl",kernelFunc:_ne},Ane=class{constructor(e){this.variableNames=["x","W"],this.outputShape=e.outShape;let{inHeight:t,inWidth:n,padInfo:a,strideHeight:r,strideWidth:s,filterHeight:i,filterWidth:o,dilationHeight:l,dilationWidth:u}=e,{top:p,left:d}=a;this.userCode=`
| const ivec2 strides = ivec2(${r}, ${s});
| const ivec2 pads = ivec2(${p}, ${d});
| const float neg_infinity = -3.4e38;
|
| void main() {
| ivec4 coords = getOutputCoords();
| int batch = coords.x;
| int d1 = coords.w;
| ivec2 outTopLeftCorner =
| coords.yz * strides - pads;
| int hBeg = outTopLeftCorner.x;
| int wBeg = outTopLeftCorner.y;
|
| float curVal = neg_infinity;
| for (int h = 0; h < ${i}; h++) {
| int hIn = hBeg + h * ${l};
|
| if (hIn >= 0 && hIn < ${t}) {
| for (int w = 0; w < ${o}; w++) {
| int wIn = wBeg + w * ${u};
|
| if (wIn >= 0 && wIn < ${n}) {
| float xVal = getX(batch, hIn, wIn, d1);
| float wVal = getW(h, w, d1);
|
| float val = xVal + wVal;
| if (val > curVal) {
| curVal = val;
| }
| }
| }
| }
| }
|
| float result = curVal;
| setOutput(result);
| }
| `}};function Fne(e){let{inputs:t,backend:n,attrs:a}=e,{x:r,filter:s}=t,{strides:i,pad:o,dilations:l}=a,u=N.computeDilation2DInfo(r.shape,s.shape,i,o,"NHWC",l),p,d=new Ane(u);p=n.runWebGLProgram(d,[r,s],"float32");let c=ce({inputs:{x:p},backend:n,attrs:{shape:u.outShape}});return n.disposeIntermediateTensorInfo(p),c}var $ne={kernelName:Hi,backendName:"webgl",kernelFunc:Fne};function Dne(e){let{inputs:t,backend:n,attrs:a}=e,{equation:r}=a,s=t,{allDims:i,summedDims:o,idDims:l}=N.decodeEinsumEquation(r,s.length);N.checkEinsumDimSizes(i.length,l,s);let{path:u,steps:p}=N.getEinsumComputePath(o,l),d=p.length,c=null,h=i.length,m=[];for(let f=0;f<d;++f){for(let g of p[f]){let{permutationIndices:b,expandDims:y}=N.getEinsumPermutation(h,l[g]),x;N.isIdentityPermutation(b)?x=s[g]:(x=Nn({inputs:{x:s[g]},backend:n,attrs:{perm:b}}),m.push(x));let v=x.shape.slice();for(let I=0;I<y.length;++I)v.splice(y[I],0,1);w.arraysEqual(x.shape,v)||(x=ce({inputs:{x},backend:n,attrs:{shape:v}}),m.push(x)),c===null?c=x:(c=pk({inputs:{a:x,b:c},backend:n}),m.push(c))}f<d-1&&(u[f]>=0&&(c=tg({inputs:{x:c},backend:n,attrs:{axis:u[f]-(i.length-h),keepDims:!1}}),m.push(c)),h--)}for(let f of m)f!==c&&n.disposeIntermediateTensorInfo(f);return c}var Rne={kernelName:Bm,backendName:"webgl",kernelFunc:Dne},Mne="return (x >= 0.0) ? x : (exp(x) - 1.0);",Pne=`
| 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;
| `,One=Ze({opSnippet:Mne,packedOpSnippet:Pne}),Lne={kernelName:ji,backendName:"webgl",kernelFunc:One},zne="return (b >= 0.0) ? a : a * (b + 1.0);",Wne=`
| vec4 bGTEZero = vec4(greaterThanEqual(b, vec4(0.)));
| return (bGTEZero * a) + ((vec4(1.0) - bGTEZero) * (a * (b + vec4(1.0))));
| `,Bne=e=>{let{inputs:t,backend:n}=e,{dy:a,y:r}=t,s=G().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new Np(Wne,a.shape,r.shape):new Ii(zne,a.shape,r.shape);return n.runWebGLProgram(s,[a,r],a.dtype)},Vne={kernelName:Iu,backendName:"webgl",kernelFunc:Bne},Une=`
| return vec4(equal(a, b));
| `,Gne="return float(a == b);",Hne=fn({opSnippet:Gne,packedOpSnippet:Une,dtype:"bool",cpuKernelImpl:w9}),qne={kernelName:Su,backendName:"webgl",kernelFunc:Hne},jne=`
| // Error function is calculated approximately with elementary function.
| // See "Handbook of Mathematical Functions with Formulas,
| // Graphs, and Mathematical Tables", Abramowitz and Stegun.
| float p = ${N.ERF_P};
| float a1 = ${N.ERF_A1};
| float a2 = ${N.ERF_A2};
| float a3 = ${N.ERF_A3};
| float a4 = ${N.ERF_A4};
| float a5 = ${N.ERF_A5};
|
| float sign = sign(x);
| x = abs(x);
| float t = 1.0 / (1.0 + p * x);
| return sign * (1.0 - (((((a5*t + a4)*t) + a3)*t + a2)*t + a1)*t*exp(-x*x));
| `,Kne=Ze({opSnippet:jne}),Xne={kernelName:Ki,backendName:"webgl",kernelFunc:Kne},Yne=Tp+`
| return exp(x);
| `,Zne=`
| vec4 result = exp(x);
| bvec4 isNaN = isnan(x);
| result.r = isNaN.r ? x.r : result.r;
| result.g = isNaN.g ? x.g : result.g;
| result.b = isNaN.b ? x.b : result.b;
| result.a = isNaN.a ? x.a : result.a;
|
| return result;
| `,VA=Ze({opSnippet:Yne,packedOpSnippet:Zne,cpuKernelImpl:k9,dtype:"float32"}),Jne={kernelName:Xi,backendName:"webgl",kernelFunc:VA};function yv(e){let{inputs:t,attrs:n,backend:a}=e,{dim:r}=n,{input:s}=t,i=s.shape.length,o=s.shape.slice(),l=r;return r<0&&(w.assert(-(i+1)<=r,()=>`Axis must be in the interval [${-(i+1)}, ${i}]`),l=i+r+1),o.splice(l,0,1),ce({inputs:{x:s},backend:a,attrs:{shape:o}})}var Qne={kernelName:Nu,backendName:"webgl",kernelFunc:yv},FS="return exp(x) - 1.0;",eae=Ze({opSnippet:FS,packedOpSnippet:FS,cpuKernelImpl:I9}),tae={kernelName:Yi,backendName:"webgl",kernelFunc:eae},$S=class{constructor(e,t,n){this.variableNames=["real","imag"];let a=t[1];this.outputShape=t;let r=n?`2.0 * ${Math.PI}`:`-2.0 * ${Math.PI}`,s=n?`${a}.0`:"1.0",i;if(e==="real")i="return real * expR - imag * expI;";else if(e==="imag")i="return real * expI + imag * expR;";else throw new Error(`FFT component must be either "real" or "imag", got ${e}.`);this.userCode=`
| const float exponentMultiplier = ${r};
|
| float unaryOpComplex(float real, float expR, float imag, float expI) {
| ${i}
| }
|
| float mulMatDFT(int batch, int index) {
| float indexRatio = float(index) / float(${a});
| float exponentMultiplierTimesIndexRatio =
| exponentMultiplier * indexRatio;
|
| float result = 0.0;
|
| for (int i = 0; i < ${a}; i++) {
| // x = (-2|2 * PI / N) * index * i;
| float x = exponentMultiplierTimesIndexRatio * float(i);
| float expR = cos(x);
| float expI = sin(x);
| float real = getReal(batch, i);
| float imag = getImag(batch, i);
|
| result +=
| unaryOpComplex(real, expR, imag, expI) / ${s};
| }
|
| return result;
| }
|
| void main() {
| ivec2 coords = getOutputCoords();
| setOutput(mulMatDFT(coords[0], coords[1]));
| }
| `}};function UA(e,t,n){let a=n.texData.get(e.dataId),r=w.sizeFromShape(e.shape),s=e.shape[e.shape.length-1],i=r/s,o=ce({inputs:{x:e},backend:n,attrs:{shape:[i,s]}}),l=o.shape,u=new $S("real",l,t),p=new $S("imag",l,t),d=[{dataId:a.complexTensorInfos.real.dataId,dtype:a.complexTensorInfos.real.dtype,shape:l},{dataId:a.complexTensorInfos.imag.dataId,dtype:a.complexTensorInfos.imag.dtype,shape:l}],c=n.runWebGLProgram(u,d,"float32"),h=n.runWebGLProgram(p,d,"float32"),m=Ms({inputs:{real:c,imag:h},backend:n});n.disposeIntermediateTensorInfo(c),n.disposeIntermediateTensorInfo(h);let f=ce({inputs:{x:m},backend:n,attrs:{shape:e.shape}});return n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(m),f}function nae(e){let{inputs:t,backend:n}=e,{input:a}=t;return UA(a,!1,n)}var aae={kernelName:Vm,backendName:"webgl",kernelFunc:nae},rae=class{constructor(e,t){this.outputShape=[],this.customUniforms=[{name:"value",type:"float"}],this.variableNames=["x"],this.outputShape=e,this.userCode=`
| void main() {
| // Input can be obtained from uniform value.
| setOutput(value);
| }
| `}};function Ld(e){let{backend:t,attrs:n}=e,{shape:a,value:r}=n,{dtype:s}=n;if(s=s||w.inferDtype(r),s==="string"){let i=w.getArrayFromDType(s,w.sizeFromShape(a));return i.fill(r),t.makeTensorInfo(a,s,i)}else{let i=new rae(a,r),o=[[r]];return t.runWebGLProgram(i,[],s,o)}}var sae={kernelName:Uc,backendName:"webgl",kernelFunc:Ld},iae=class{constructor(e){this.variableNames=["Image"],this.outputShape=[];let t=e[2];this.outputShape=e,this.userCode=`
| void main() {
| ivec4 coords = getOutputCoords();
| int x = coords[2];
|
| int coordX = ${t} - x - 1;
| float outputValue;
| if(coordX >= 0 && coordX < ${t}) {
| outputValue = getImage(coords[0], coords[1], coordX, coords[3]);
| } else {
| outputValue = getImage(coords[0], coords[1], coords[2], coords[3]);
| }
| setOutput(outputValue);
| }
| `}},oae={kernelName:Tu,backendName:"webgl",kernelFunc:({inputs:e,backend:t})=>{let{image:n}=e,a=t,r=new iae(n.shape);return a.runWebGLProgram(r,[n],n.dtype)}},DS="return floor(x);",lae=Ze({opSnippet:DS,packedOpSnippet:DS,cpuKernelImpl:S9}),uae={kernelName:Zi,backendName:"webgl",kernelFunc:lae},pae=`
| float s = sign(a) * sign(b);
| int ia = round(a);
| int ib = round(b);
| if (ib != 0) {
| // Windows (D3D) wants guaranteed non-zero int division at compile-time.
| return float(idiv(ia, ib, s));
| } else {
| return NAN;
| }
| `,cae=`
| ivec4 ia = round(a);
| ivec4 ib = round(b);
| bvec4 cond = notEqual(ib, ivec4(0));
| ivec4 result = ivec4(0);
| vec4 s = sign(a) * sign(b);
|
| // Windows (D3D) wants guaranteed non-zero int division at compile-time.
| if (cond[0]) {
| result[0] = idiv(ia[0], ib[0], s[0]);
| }
| if (cond[1]) {
| result[1] = idiv(ia[1], ib[1], s[1]);
| }
| if (cond[2]) {
| result[2] = idiv(ia[2], ib[2], s[2]);
| }
| if (cond[3]) {
| result[3] = idiv(ia[3], ib[3], s[3]);
| }
| return vec4(result);
| `,dae=fn({opSnippet:pae,packedOpSnippet:cae,dtype:"int32"}),hae={kernelName:Ji,backendName:"webgl",kernelFunc:dae},mae=class{constructor(e){this.variableNames=["A"];let t=En(),[n,a]=e;this.outputShape=e,this.userCode=`
| void main() {
| ivec3 coords = getOutputCoords();
| int texR = coords[0];
| int texC = coords[1];
| int depth = coords[2];
| vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${a}.0, ${n}.0);
|
| vec4 values = ${t.texture2D}(A, uv);
| float value;
| if (depth == 0) {
| value = values.r;
| } else if (depth == 1) {
| value = values.g;
| } else if (depth == 2) {
| value = values.b;
| } else if (depth == 3) {
| value = values.a;
| }
|
| setOutput(floor(value * 255.0 + 0.5));
| }
| `}},fae=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0;let t=En(),[n,a]=e;this.outputShape=e,this.userCode=`
| void main() {
| ivec3 coords = getOutputCoords();
| int texR = coords[0];
| int texC = coords[1];
| int depth = coords[2];
|
| vec4 result = vec4(0.);
|
| for(int row=0; row<=1; row++) {
| for(int col=0; col<=1; col++) {
| texC = coords[1] + row;
| depth = coords[2] + col;
|
| vec2 uv = (vec2(texC, texR) + halfCR) /
| vec2(${a}.0, ${n}.0);
| vec4 values = ${t.texture2D}(A, uv);
| float value;
| if (depth == 0) {
| value = values.r;
| } else if (depth == 1) {
| value = values.g;
| } else if (depth == 2) {
| value = values.b;
| } else if (depth == 3) {
| value = values.a;
| }
|
| result[row * 2 + col] = floor(value * 255.0 + 0.5);
| }
| }
|
| ${t.output} = result;
| }
| `}},gae={kernelName:im,backendName:"webgl",kernelFunc:bae},Rl,Nx=G().getBool("CANVAS2D_WILL_READ_FREQUENTLY_FOR_GPU");function bae(e){let{inputs:t,backend:n,attrs:a}=e,{pixels:r}=t,{numChannels:s}=a,i=typeof HTMLVideoElement!="undefined"&&r instanceof HTMLVideoElement,o=typeof HTMLImageElement!="undefined"&&r instanceof HTMLImageElement,[l,u]=i?[r.videoWidth,r.videoHeight]:[r.width,r.height],p=[u,l],d=[u,l,s];if(o||i){let f=G().getBool("CANVAS2D_WILL_READ_FREQUENTLY_FOR_GPU");(Rl==null||f!==Nx)&&(Nx=f,Rl=document.createElement("canvas").getContext("2d",{willReadFrequently:Nx})),Rl.canvas.width=l,Rl.canvas.height=u,Rl.drawImage(r,0,0,l,u),r=Rl.canvas}let c=n.makeTensorInfo(p,"int32");n.texData.get(c.dataId).usage=ha.PIXELS,n.gpgpu.uploadPixelDataToTexture(n.getTexture(c.dataId),r);let h=G().getBool("WEBGL_PACK")?new fae(d):new mae(d),m=n.runWebGLProgram(h,[c],"int32");return n.disposeData(c.dataId),m}function yae(e){let{inputs:t,backend:n,attrs:a}=e,{x:r,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:u,dataFormat:p,dilations:d,dimRoundingMode:c,activation:h,leakyreluAlpha:m}=a,f=N.convertConv2DDataFormat(p),g=N.computeConv2DInfo(r.shape,s.shape,l,d,u,c,!1,f),b,y=[],x=i!=null,v=o!=null,I=h==="leakyrelu",T=()=>{let E=[r,s],F=(D,$)=>{if($==="NCHW"&&D.shape.length===1&&D.shape[0]!==1){let S=ce({inputs:{x:D},backend:n,attrs:{shape:[D.shape[0],1,1]}});return y.push(S),S}return D};if(x&&E.push(F(i,p)),v&&E.push(F(o,p)),I){let D=n.makeTensorInfo([],"float32",w.createScalarValue(m,"float32"));E.push(D),y.push(D)}return E};if(g.filterHeight===1&&g.filterWidth===1&&g.dilationHeight===1&&g.dilationWidth===1&&g.strideHeight===1&&g.strideWidth===1&&(g.padInfo.type==="SAME"||g.padInfo.type==="VALID"))b=OA({x:r,filter:s,convInfo:g,backend:n,bias:i,activation:h,preluActivationWeights:o,leakyreluAlpha:m});else if(g.strideWidth<=2&&f==="channelsLast"&&G().getBool("WEBGL_EXP_CONV")){let E=h?Fc(h,!0):null,F=new PA(g,x,E,v,I),D=[[g.padInfo.top,g.padInfo.left],[g.strideHeight,g.strideWidth],[g.dilationHeight,g.dilationWidth],[g.inHeight,g.inWidth]],$=T();b=n.runWebGLProgram(F,$,"float32",D)}else if(G().getBool("WEBGL_CONV_IM2COL"))b=LA({x:r,filter:s,convInfo:g,backend:n,bias:i,activation:h,preluActivationWeights:o,leakyreluAlpha:m});else{let E=h?Fc(h,!1):null,F=new MA(g,x,E,v,I),D=T();b=n.runWebGLProgram(F,D,"float32")}let C=ce({inputs:{x:b},backend:n,attrs:{shape:g.outShape}});return y.push(b),y.forEach(E=>n.disposeIntermediateTensorInfo(E)),C}var xae={kernelName:li,backendName:"webgl",kernelFunc:yae};function vae(e){let{inputs:t,backend:n,attrs:a}=e,{x:r,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:u,dilations:p,dimRoundingMode:d,activation:c,leakyreluAlpha:h}=a,m=[],f=p;f==null&&(f=[1,1]),w.assert(N.eitherStridesOrDilationsAreOne(l,f),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${l} and dilations '${f}'`);let g=N.computeConv2DInfo(r.shape,s.shape,l,f,u,d,!0),b=G().getBool("WEBGL_PACK_DEPTHWISECONV")&&g.strideWidth<=2&&g.outChannels/g.inChannels===1,y=c?Fc(c,b):null,x=[r,s],v=i!=null,I=o!=null,T=c==="leakyrelu";if(v&&x.push(i),I&&x.push(o),T){let D=n.makeTensorInfo([],"float32",w.createScalarValue(h,"float32"));x.push(D),m.push(D)}let C;b?C=new BA(g,v,y,I,T):C=new WA(g,v,y,I,T);let E=[[g.padInfo.top,g.padInfo.left],[g.strideHeight,g.strideWidth],[g.dilationHeight,g.dilationWidth],[g.inHeight,g.inWidth]],F=n.runWebGLProgram(C,x,"float32",E);return m.forEach(D=>n.disposeIntermediateTensorInfo(D)),F}var wae={kernelName:ui,backendName:"webgl",kernelFunc:vae},kae=class{constructor(e,t,n,a){this.sliceDim=e,this.strides=t,this.paramsShape=a,this.variableNames=["x","indices"],this.outputShape=n;let r=dt(n.length),s=`
| int index;`;for(let i=0;i<this.sliceDim;i++)s+=`
| index = round(getIndices(coords[0], ${i}));
| out_of_bounds = out_of_bounds || index < 0;
| out_of_bounds = out_of_bounds || index >= ${this.paramsShape[i]};
| flattenIndex += index * ${this.strides[i]};`;this.userCode=`
| void main() {
| ${r} coords = getOutputCoords();
| int flattenIndex = 0;
| bool out_of_bounds = false;
|
| ${s}
|
| setOutput(out_of_bounds ? 0.0 : getX(flattenIndex, coords[1]));
| }
| `}};function Iae(e){let{inputs:t,backend:n}=e,{params:a,indices:r}=t,s=r.shape,i=s[s.length-1],o=w.sizeFromShape(a.shape),[l,u,p,d]=N.prepareAndValidate(a,r),c=ce({inputs:{x:r},backend:n,attrs:{shape:[u,i]}}),h=ce({inputs:{x:a},backend:n,attrs:{shape:[w.sizeFromShape(a.shape)/p,p]}});if(n.shouldExecuteOnCPU([a,r])||a.dtype==="string"){let b=n.readSync(r.dataId),y=n.bufferSync(a),x=N9(b,y,a.dtype,u,i,p,d,a.shape,o);return n.makeTensorInfo(l,a.dtype,x.values)}let m=new kae(i,d,[u,p],a.shape),f=n.runWebGLProgram(m,[h,c],h.dtype),g=ce({inputs:{x:f},backend:n,attrs:{shape:l}});return n.disposeIntermediateTensorInfo(c),n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(f),g}var Sae={kernelName:_u,backendName:"webgl",kernelFunc:Iae},Nae=class{constructor(e,t){this.variableNames=["A","indices"],this.outputShape=t,this.rank=t.length;let n=dt(this.rank),a=Tae(e,2);this.userCode=`
| void main() {
| ${n} resRC = getOutputCoords();
| int index = int(getIndices(resRC.x, resRC.z));
| float inBounds = (index >= 0) && (index < ${e[2]}) ? 1.0 : 0.0;
| setOutput(inBounds * getA(${a}));
| }
| `}};function Tae(e,t){let n=["resRC.x","resRC.y","resRC.z","resRC.w"],a=[];for(let r=0;r<e.length;r++)r===2?a.push("index"):a.push(`${n[r]}`);return a.join()}function GA(e){let{inputs:t,backend:n,attrs:a}=e,{x:r,indices:s}=t,{axis:i,batchDims:o}=a,l=w.parseAxisParam(i,r.shape)[0];if(G().get("DEBUG")){let y=n.readSync(s.dataId),x=r.shape[l];for(let v=0;v<y.length;++v){let I=y[v];w.assert(I<=x-1&&I>=0,()=>`GatherV2: the index value ${I} is not in [0, ${x-1}]`)}}let u=N.segment_util.collectGatherOpShapeInfo(r,s,l,o),p=w.sizeFromShape(s.shape),d=[],c=ce({inputs:{x:r},backend:n,attrs:{shape:[u.batchSize,u.outerSize,u.dimSize,u.sliceSize]}}),h=ce({inputs:{x:s},backend:n,attrs:{shape:[u.batchSize,p/u.batchSize]}});d.push(c),d.push(h);let m=[u.batchSize,u.outerSize,p/u.batchSize,u.sliceSize];if(n.shouldExecuteOnCPU([r,s])||r.dtype==="string"){let y=n.bufferSync(h),x=n.bufferSync(c),v=T9(x,y,m);return d.forEach(I=>n.disposeIntermediateTensorInfo(I)),n.makeTensorInfo(u.outputShape,v.dtype,v.values)}let f=new Nae(c.shape,m),g=n.runWebGLProgram(f,[c,h],c.dtype);d.push(g);let b=ce({inputs:{x:g},backend:n,attrs:{shape:u.outputShape}});return d.forEach(y=>n.disposeIntermediateTensorInfo(y)),b}var Cae={kernelName:Cu,backendName:"webgl",kernelFunc:GA},_ae="return float(a > b);",Eae=`
| return vec4(greaterThan(a, b));
| `,Aae=fn({opSnippet:_ae,packedOpSnippet:Eae,cpuKernelImpl:C9,dtype:"bool"}),Fae={kernelName:Eu,backendName:"webgl",kernelFunc:Aae},$ae="return float(a >= b);",Dae=`
| return vec4(greaterThanEqual(a, b));
| `,Rae=fn({opSnippet:$ae,packedOpSnippet:Dae,dtype:"bool",cpuKernelImpl:_9}),Mae={kernelName:eo,backendName:"webgl",kernelFunc:Rae};function Pae(e){let{inputs:t,backend:n}=e,{input:a}=t;return UA(a,!0,n)}var Oae={kernelName:Um,backendName:"webgl",kernelFunc:Pae},Lae="return float(!isnan(x) && !isinf(x));",zae=Ze({opSnippet:Lae,dtype:"bool"}),Wae={kernelName:no,backendName:"webgl",kernelFunc:zae},Bae="return float(isinf(x));",Vae=Ze({opSnippet:Bae,dtype:"bool"}),Uae={kernelName:ao,backendName:"webgl",kernelFunc:Vae},Gae="return float(isnan(x));",Hae=Ze({opSnippet:Gae,dtype:"bool"}),qae={kernelName:ro,backendName:"webgl",kernelFunc:Hae},jae="return float(a < b);",Kae=`
| return vec4(lessThan(a, b));
| `,Xae=fn({opSnippet:jae,packedOpSnippet:Kae,cpuKernelImpl:E9,dtype:"bool"}),Yae={kernelName:Au,backendName:"webgl",kernelFunc:Xae},Zae="return float(a <= b);",Jae=`
| return vec4(lessThanEqual(a, b));
| `,Qae=fn({opSnippet:Zae,packedOpSnippet:Jae,cpuKernelImpl:A9,dtype:"bool"}),ere={kernelName:Fu,backendName:"webgl",kernelFunc:Qae};function tre(e){let{backend:t,attrs:n}=e,{start:a,stop:r,num:s}=n,i=F9(a,r,s);return t.makeTensorInfo([i.length],"float32",i)}var nre={kernelName:$u,backendName:"webgl",kernelFunc:tre},are=Tp+`
| return x < 0.0 ? 0./0. : log(x);
| `,rre=`
| vec4 result = log(x);
| bvec4 isNaN = isnan(x);
| result.r = isNaN.r ? x.r : (x.r < 0.0 ? 0./0. : result.r);
| result.g = isNaN.g ? x.g : (x.g < 0.0 ? 0./0. : result.g);
| result.b = isNaN.b ? x.b : (x.b < 0.0 ? 0./0. : result.b);
| result.a = isNaN.a ? x.a : (x.a < 0.0 ? 0./0. : result.a);
| return result;
| `,sre=Ze({opSnippet:are,packedOpSnippet:rre,cpuKernelImpl:$9}),ire={kernelName:io,backendName:"webgl",kernelFunc:sre},ore=Tp+`
| return log(1.0 + x);
| `,lre=Ze({opSnippet:ore}),ure={kernelName:oo,backendName:"webgl",kernelFunc:lre},pre="return float(a >= 1.0 && b >= 1.0);",cre=`
| return vec4(
| vec4(greaterThanEqual(a, vec4(1.0))) *
| vec4(greaterThanEqual(b, vec4(1.0))));
| `,dre=fn({opSnippet:pre,packedOpSnippet:cre,dtype:"bool"}),hre={kernelName:Du,backendName:"webgl",kernelFunc:dre},mre="return float(!(x >= 1.0));",fre=Ze({opSnippet:mre}),gre={kernelName:Ru,backendName:"webgl",kernelFunc:fre},bre="return float(a >= 1.0 || b >= 1.0);",yre=`
| return min(
| vec4(greaterThanEqual(a, vec4(1.0))) +
| vec4(greaterThanEqual(b, vec4(1.0))),
| vec4(1.0));
| `,xre=fn({opSnippet:bre,packedOpSnippet:yre,dtype:"bool"}),vre={kernelName:Mu,backendName:"webgl",kernelFunc:xre},wre=class{constructor(e,t,n,a,r){this.variableNames=["x"],this.outputShape=[];let s=t,i=e[3]-1;this.outputShape=e;let o,l=`float(${n}) + float(${a}) * sum`;r===.5?o=`inversesqrt(${l})`:r===1?o=`1.0/(${l})`:o=`exp(log(${l}) * float(-${r}));`,this.userCode=`
| void main() {
| ivec4 coords = getOutputCoords();
| int b = coords[0];
| int r = coords[1];
| int c = coords[2];
| int d = coords[3];
| float x = getX(b, r, c, d);
| float sum = 0.0;
| for (int j = -${s}; j <= ${s}; j++) {
| int idx = d + j;
| if (idx >= 0 && idx <= ${i}) {
| float z = getX(b, r, c, idx);
| sum += z * z;
| }
| }
| float val = x * ${o};
| setOutput(val);
| }
| `}},kre=class{constructor(e,t,n,a,r){this.variableNames=["x"],this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0;let s=t,i=e[3]-1;this.outputShape=e;let o,l=`float(${n}) + float(${a}) * sum`;r===.5?o=`inversesqrt(${l})`:r===1?o=`1.0/(${l})`:o=`exp(log(${l}) * float(-${r}));`,this.userCode=`
| void main() {
| ivec4 coords = getOutputCoords();
| int b = coords.x;
| int r = coords.y;
| int c = coords.z;
| int d = coords.w;
|
| bool hasNextCol = d < ${this.outputShape[3]};
| bool hasNextRow = c < ${this.outputShape[2]};
|
| vec4 sum = vec4(0.);
| vec4 xFragAtOutputCoords = getX(b, r, c, d);
|
| vec4 xAtOutputCoords = vec4(
| getChannel(xFragAtOutputCoords, vec2(c, d)),
| hasNextCol ?
| getChannel(xFragAtOutputCoords, vec2(c, d + 1)) : 0.0,
| hasNextRow ?
| getChannel(xFragAtOutputCoords , vec2(c + 1, d)) : 0.0,
| (hasNextRow && hasNextCol) ?
| getChannel(xFragAtOutputCoords, vec2(c + 1, d + 1)) : 0.0
| );
|
| int firstChannel = d - ${s};
| vec2 cache = vec2(0.);
| if(firstChannel >= 0){
| vec4 firstChannelFrag = getX(b, r, c, firstChannel);
| cache.x = getChannel(firstChannelFrag, vec2(c, firstChannel));
| if(hasNextRow){
| cache.y = getChannel(firstChannelFrag, vec2(c + 1, firstChannel));
| }
| }
|
| ivec2 depth = ivec2(d, d + 1);
| for (int j = - ${s}; j <= ${s}; j++) {
| ivec2 idx = depth + j;
| bvec2 aboveLowerBound = greaterThanEqual(idx, ivec2(0));
| bvec2 belowUpperBound = lessThanEqual(idx, ivec2(${i}));
|
| bool depthInRange = aboveLowerBound.x && belowUpperBound.x;
| bool depthPlusOneInRange = aboveLowerBound.y && belowUpperBound.y;
|
| if(depthInRange || depthPlusOneInRange){
| vec4 z = vec4(0.);
| vec4 xFragAtCurrentDepth;
| z.xz = cache.xy;
| if(depthPlusOneInRange && hasNextCol){
| xFragAtCurrentDepth = idx.y != d ?
| getX(b, r, c, idx.y) : xFragAtOutputCoords;
| z.y = getChannel(xFragAtCurrentDepth, vec2(c, idx.y));
| if(hasNextRow){
| z.w = getChannel(xFragAtCurrentDepth, vec2(c + 1, idx.y));
| }
| }
| cache.xy = z.yw;
| sum += z * z;
| }
| }
| vec4 result = xAtOutputCoords * ${o};
| setOutput(result);
| }
| `}},Ire=e=>{let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{depthRadius:s,bias:i,alpha:o,beta:l}=a,u=G().getBool("WEBGL_PACK_NORMALIZATION")?new kre(r.shape,s,i,o,l):new wre(r.shape,s,i,o,l);return n.runWebGLProgram(u,[r],r.dtype)},Sre={kernelName:lo,backendName:"webgl",kernelFunc:Ire},Nre=class{constructor(e,t,n,a,r){this.variableNames=["inputImage","outputImage","dy"],this.outputShape=[],this.outputShape=e,this.depth=e[3],this.depthRadius=t,this.bias=n,this.alpha=a,this.beta=r,this.userCode=`
| void main() {
| ivec4 coords = getOutputCoords();
| int b = coords[0];
| int r = coords[1];
| int c = coords[2];
|
| float result = 0.0;
| for (int d = 0; d < ${this.depth}; ++d) {
| int depthBegin = int(max(0.0, float(d - ${t})));
| int depthEnd = int(min(float(${this.depth}),
| float(d + ${t} + 1)));
|
| const int MIN_DEPTH_BEGIN = 0;
| const int MAX_DEPTH_END = ${this.depth};
|
| float norm = 0.0;
| for (int k = MIN_DEPTH_BEGIN; k < MAX_DEPTH_END; ++k) {
| if (k < depthBegin){
| continue;
| }
| else if (k >= depthBegin && k < depthEnd) {
| norm += getInputImage(b, r, c, k) * getInputImage(b, r, c, k);
| }
| else {
| break;
| }
| }
|
| norm = float(${a}) * norm + float(${n});
|
| for(int k = MIN_DEPTH_BEGIN; k < MAX_DEPTH_END; ++k){
| if (k < depthBegin){
| continue;
| }
| else if (k >= depthBegin && k < depthEnd){
| float dyi = -2.0 * float(${a})
| * float(${r})
| * getInputImage(b, r, c, k) * getOutputImage(b, r, c, d)
| / norm;
| if (k == d) {
| dyi += pow(norm, -1.0 * ${r});
| }
| if (k == coords[3]) {
| dyi *= getDy(b, r, c, d);
| result += dyi;
| }
| }
| else {
| break;
| }
| }
| }
| setOutput(result);
| }
| `}},Tre=e=>{let{inputs:t,backend:n,attrs:a}=e,{x:r,y:s,dy:i}=t,{depthRadius:o,bias:l,alpha:u,beta:p}=a,d=new Nre(r.shape,o,l,u,p);return n.runWebGLProgram(d,[r,s,i],r.dtype)},Cre={kernelName:Pu,backendName:"webgl",kernelFunc:Tre};function _re(e,t,n,a){let r=w.sizeFromShape(t),s=w.sizeFromShape(e.shape)/r,i=ce({inputs:{x:e},attrs:{shape:[s,r]},backend:a}),o=tl(i,e.dtype,"max",a),l=ce({inputs:{x:o},attrs:{shape:n},backend:a});return a.disposeIntermediateTensorInfo(i),a.disposeIntermediateTensorInfo(o),l}function HA(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{reductionIndices:s,keepDims:i}=a,o=r.shape.length,l=w.parseAxisParam(s,r.shape),u=l,p=N.getAxesPermutation(u,o),d=p!=null,c=n.shouldExecuteOnCPU([r]),h=r;if(d){if(c){let y=n.texData.get(h.dataId).values,x=new Array(o);for(let T=0;T<x.length;T++)x[T]=r.shape[p[T]];let v=lk(y,r.shape,r.dtype,p,x);h=n.makeTensorInfo(x,r.dtype);let I=n.texData.get(h.dataId);I.values=v}else h=eg(r,p,n);u=N.getInnerMostAxes(u.length,o)}N.assertAxesAreInnerMostDims("max",u,o);let[m,f]=N.computeOutAndReduceShapes(h.shape,u),g=m;i&&(g=N.expandShapeToKeepDim(m,l));let b;if(c){let y=n.texData.get(h.dataId).values,x=D9(y,w.sizeFromShape(f),g,r.dtype);b=n.makeTensorInfo(g,r.dtype);let v=n.texData.get(b.dataId);v.values=x}else b=_re(h,f,g,n);return d&&n.disposeIntermediateTensorInfo(h),b}var Ere={kernelName:uo,backendName:"webgl",kernelFunc:HA},Are=uk+`
| return max(a, b);
| `,Fre=`
| vec4 result = vec4(max(a, b));
| bvec4 isNaNA = isnan(a);
| bvec4 isNaNB = isnan(b);
| bvec4 isNaN = bvec4(isNaNA.x || isNaNB.x, isNaNA.y || isNaNB.y, isNaNA.z || isNaNB.z, isNaNA.w || isNaNB.w);
| `+el+`
| return result;
| `,$re=fn({opSnippet:Are,packedOpSnippet:Fre,cpuKernelImpl:R9}),Dre={kernelName:po,backendName:"webgl",kernelFunc:$re};function Rre(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t;vp(r,"maxPool");let{filterSize:s,strides:i,pad:o,dimRoundingMode:l}=a,u=1;w.assert(N.eitherStridesOrDilationsAreOne(i,u),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${i} and dilations '${u}'`);let p=N.computePool2DInfo(r.shape,s,i,u,o,l);if(p.filterWidth===1&&p.filterHeight===1&&w.arraysEqual(p.inShape,p.outShape))return ra({inputs:{x:r},backend:n});let d=new $c(p,"max",!1);return n.runWebGLProgram(d,[r],r.dtype)}var Mre={kernelName:co,backendName:"webgl",kernelFunc:Rre};function Pre(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{filterSize:s,strides:i,pad:o,dataFormat:l,dimRoundingMode:u}=a,p=[1,1,1],d=N.computePool3DInfo(r.shape,s,i,p,o,u,l),c=new ck(d,"max",!1);return n.runWebGLProgram(c,[r],r.dtype)}var Ore={kernelName:Ou,backendName:"webgl",kernelFunc:Pre},Lre=class{constructor(e){this.variableNames=["dy","maxPos"],this.outputShape=e.inShape;let t=e.strideHeight,n=e.strideWidth,a=e.dilationHeight,r=e.effectiveFilterHeight,s=e.effectiveFilterWidth,i=r-1-e.padInfo.top,o=s-1-e.padInfo.left,l=r*s-1;this.userCode=`
| const ivec2 pads = ivec2(${i}, ${o});
|
| void main() {
| ivec4 coords = getOutputCoords();
| int b = coords[0];
| int d = coords[3];
|
| ivec2 dyRCCorner = coords.yz - pads;
| int dyRCorner = dyRCCorner.x;
| int dyCCorner = dyRCCorner.y;
|
| // Convolve dy(?, ?, d) with pos mask(:, :, d) to get dx(xR, xC, d).
| // ? = to be determined. : = across all values in that axis.
| float dotProd = 0.0;
| for (int wR = 0; wR < ${r};
| wR += ${a}) {
| float dyR = float(dyRCorner + wR) / ${t}.0;
|
| if (dyR < 0.0 || dyR >= ${e.outHeight}.0 || fract(dyR) > 0.0) {
| continue;
| }
| int idyR = int(dyR);
|
| for (int wC = 0; wC < ${s}; wC++) {
| float dyC = float(dyCCorner + wC) / ${n}.0;
|
| if (dyC < 0.0 || dyC >= ${e.outWidth}.0 ||
| fract(dyC) > 0.0) {
| continue;
| }
| int idyC = int(dyC);
|
| float dyValue = getDy(b, idyR, idyC, d);
| int maxPosValue = ${l} - int(getMaxPos(b, idyR, idyC, d));
|
| // Get the current value, check it against the value from the
| // position matrix.
| int curPosValue = wR * ${s} + wC;
| float mask = float(maxPosValue == curPosValue ? 1.0 : 0.0);
|
| dotProd += dyValue * mask;
| }
| }
| setOutput(dotProd);
| }
| `}},zre=class{constructor(e){this.variableNames=["dy","maxPos"],this.outputShape=e.inShape;let t=e.strideDepth,n=e.strideHeight,a=e.strideWidth,r=e.dilationDepth,s=e.dilationHeight,i=e.dilationWidth,o=e.effectiveFilterDepth,l=e.effectiveFilterHeight,u=e.effectiveFilterWidth,p=o-1-e.padInfo.front,d=l-1-e.padInfo.top,c=u-1-e.padInfo.left,h=o*l*u-1;this.userCode=`
| const ivec3 pads = ivec3(${p}, ${d}, ${c});
|
| void main() {
| ivec5 coords = getOutputCoords();
| int batch = coords.x;
| int ch = coords.u;
|
| ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads;
| int dyDCorner = dyCorner.x;
| int dyRCorner = dyCorner.y;
| int dyCCorner = dyCorner.z;
|
| // Convolve dy(?, ?, ?, ch) with pos mask(:, :, :, d) to get
| // dx(xD, xR, xC, ch).
| // ? = to be determined. : = across all values in that axis.
| float dotProd = 0.0;
|
| for (int wD = 0; wD < ${o};
| wD += ${r}) {
| float dyD = float(dyDCorner + wD) / ${t}.0;
|
| if (dyD < 0.0 || dyD >= ${e.outDepth}.0 || fract(dyD) > 0.0) {
| continue;
| }
| int idyD = int(dyD);
|
| for (int wR = 0; wR < ${l};
| wR += ${s}) {
| float dyR = float(dyRCorner + wR) / ${n}.0;
|
| if (dyR < 0.0 || dyR >= ${e.outHeight}.0 ||
| fract(dyR) > 0.0) {
| continue;
| }
| int idyR = int(dyR);
|
| for (int wC = 0; wC < ${u};
| wC += ${i}) {
| float dyC = float(dyCCorner + wC) / ${a}.0;
|
| if (dyC < 0.0 || dyC >= ${e.outWidth}.0 ||
| fract(dyC) > 0.0) {
| continue;
| }
| int idyC = int(dyC);
|
| float dyValue = getDy(batch, idyD, idyR, idyC, ch);
| int maxPosValue = ${h} -
| int(getMaxPos(batch, idyD, idyR, idyC, ch));
|
| // Get the current value, check it against the value from the
| // position matrix.
| int curPosValue =
| wD * ${l} * ${u} +
| wR * ${u} + wC;
| float mask = float(maxPosValue == curPosValue ? 1.0 : 0.0);
|
| dotProd += dyValue * mask;
| }
| }
| }
| setOutput(dotProd);
| }
| `}};function Wre(e){let{inputs:t,backend:n,attrs:a}=e,{dy:r,input:s}=t,i=s,{filterSize:o,strides:l,pad:u,dimRoundingMode:p}=a,d=[1,1,1],c=N.computePool3DInfo(i.shape,o,l,d,u,p),h=new ck(c,"max",!0),m=n.runWebGLProgram(h,[i],i.dtype),f=new zre(c),g=n.runWebGLProgram(f,[r,m],i.dtype);return n.disposeIntermediateTensorInfo(m),g}var Bre={kernelName:Hc,backendName:"webgl",kernelFunc:Wre};function Vre(e){let{inputs:t,backend:n,attrs:a}=e,{dy:r,input:s,output:i}=t,o=s;vp([s,i],"maxPoolGrad");let{filterSize:l,strides:u,pad:p,dimRoundingMode:d}=a,c=N.computePool2DInfo(o.shape,l,u,1,p,d),h=!0,m=new $c(c,"max",h),f=n.runWebGLProgram(m,[o],o.dtype),g=new Lre(c),b=n.runWebGLProgram(g,[r,f],o.dtype);return n.disposeIntermediateTensorInfo(f),b}var Ure={kernelName:Gc,backendName:"webgl",kernelFunc:Vre};function Gre(e,t,n,a){let r=new $c(n,"max",!1),s=a.runWebGLProgram(r,[e],"float32");r=new $c(n,"max",!0,!0,t);let i=a.runWebGLProgram(r,[e],"float32");return[s,i]}var Hre={kernelName:qc,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{x:a}=e,{filterSize:r,strides:s,pad:i,includeBatchInIndex:o}=t,l=n;w.assert(a.shape.length===4,()=>`Error in maxPool: input must be rank 4 but got rank ${a.shape.length}.`);let u=[1,1];w.assert(N.eitherStridesOrDilationsAreOne(s,u),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${s} and dilations '${u}'`);let p=N.computePool2DInfo(a.shape,r,s,u,i),[d,c]=Gre(a,o,p,l);return[d,c]}};function qre(e,t,n,a){let r=w.sizeFromShape(t),s=w.sizeFromShape(e.shape)/r,i=ce({inputs:{x:e},attrs:{shape:[s,r]},backend:a}),o=tl(i,"float32","mean",a),l=ce({inputs:{x:o},attrs:{shape:n},backend:a});return a.disposeIntermediateTensorInfo(i),a.disposeIntermediateTensorInfo(o),l}var jre={kernelName:ho,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{x:a}=e,{keepDims:r,axis:s}=t,i=n,o=a.shape.length,l=w.parseAxisParam(s,a.shape),u=l,p=N.getAxesPermutation(u,o),d=p!=null,c=i.shouldExecuteOnCPU([a]),h=[],m=a;if(d){if(c){let x=i.texData.get(m.dataId).values,v=new Array(o);for(let C=0;C<v.length;C++)v[C]=a.shape[p[C]];let I=lk(x,a.shape,a.dtype,p,v);m=i.makeTensorInfo(v,a.dtype);let T=i.texData.get(m.dataId);T.values=I}else m=eg(a,p,i);h.push(m),u=N.getInnerMostAxes(u.length,o)}N.assertAxesAreInnerMostDims("sum",u,o);let[f,g]=N.computeOutAndReduceShapes(m.shape,u),b=f;r&&(b=N.expandShapeToKeepDim(f,l));let y=qre(m,g,b,i);for(let x of h)i.disposeIntermediateTensorInfo(x);return y}};function Kre(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{axis:s,keepDims:i}=a,o=r.shape.length,l=w.parseAxisParam(s,r.shape),u=l,p=N.getAxesPermutation(u,o),d=r;p!=null&&(d=Nn({inputs:{x:r},backend:n,attrs:{perm:p}}),u=N.getInnerMostAxes(u.length,r.shape.length)),N.assertAxesAreInnerMostDims("min",u,o);let[c,h]=N.computeOutAndReduceShapes(d.shape,u),m=w.sizeFromShape(h),f=ce({inputs:{x:d},backend:n,attrs:{shape:[-1,m]}}),g=tl(f,f.dtype,"min",n),b;if(i){let y=N.expandShapeToKeepDim(c,l);b=ce({inputs:{x:g},backend:n,attrs:{shape:y}})}else b=ce({inputs:{x:g},backend:n,attrs:{shape:c}});return n.disposeIntermediateTensorInfo(f),n.disposeIntermediateTensorInfo(g),p!=null&&n.disposeIntermediateTensorInfo(d),b}var Xre={kernelName:mo,backendName:"webgl",kernelFunc:Kre},Yre=uk+`
| return min(a, b);
| `,Zre=`
| vec4 result = vec4(min(a, b));
| bvec4 isNaNA = isnan(a);
| bvec4 isNaNB = isnan(b);
| bvec4 isNaN = bvec4(isNaNA.x || isNaNB.x, isNaNA.y || isNaNB.y, isNaNA.z || isNaNB.z, isNaNA.w || isNaNB.w);
| `+el+`
| return result;
| `,Jre=fn({opSnippet:Yre,packedOpSnippet:Zre,cpuKernelImpl:M9}),Qre={kernelName:fo,backendName:"webgl",kernelFunc:Jre},ese=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=t.map((u,p)=>u[0]+e[p]+u[1]);let a=e.length,r=dt(a),s=t.map(u=>u[0]).join(","),i=t.map((u,p)=>u[0]+e[p]).join(","),o=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,a),l=n==="reflect"?0:1;if(a===1){this.userCode=`
| int start = ${s};
| int end = ${i};
|
| void main() {
| int outC = getOutputCoords();
| if (outC < start) {
| outC = start * 2 - outC - ${l};
| } else if(outC >= end) {
| outC = (end - 1) * 2 - outC + ${l};
| }
| setOutput(getX(outC - start));
| }
| `;return}this.userCode=`
| ${r} start = ${r}(${s});
| ${r} end = ${r}(${i});
|
| void main() {
| ${r} outC = getOutputCoords();
| for (int i = 0; i < ${a}; i++) {
| if (outC[i] < start[i]) {
| outC[i] = start[i] * 2 - outC[i] - ${l};
| } else if(outC[i] >= end[i]) {
| outC[i] = (end[i] - 1) * 2 - outC[i] + ${l};
| }
| }
| ${r} coords = outC - start;
| setOutput(getX(${o}));
| }
| `}},tse=class{constructor(e,t,n){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t.map((h,m)=>h[0]+e[m]+h[1]);let a=e.length,r=dt(a),s=t.map(h=>h[0]).join(","),i=t.map((h,m)=>h[0]+e[m]).join(","),o=Sn("rc",a),l=Sn("source",a),u=`${o[a-1]} < ${this.outputShape[a-1]}`,p=a===1?"source":`vec2(${l.slice(-2).join()})`,d=n==="reflect"?0:1,c="";if(a===1){let h=`
| ${r} source = rc;
| if (source < start) {
| source = start * 2 - source - ${d};
| } else if (source >= end) {
| source = (end - 1) * 2 - source + ${d};
| }
| source -= start;
| `;c=`
| ${r} rc = outputLoc;
| ${h}
| result[0] = getChannel(getX(${l.join()}), ${p});
| ${o[a-1]} += 1;
| if(${u}) {
| ${h}
| result[1] = getChannel(getX(${l.join()}), ${p});
| }
| `}else{let h=`
| ${r} source = rc;
| ${r} lt = ${r}(lessThan(source, start));
| ${r} gte = ${r}(greaterThanEqual(source, end));
| ${r} orig = 1 - (lt + gte);
| source = orig * source +
| lt * (start * 2 - source - ${d}) +
| gte * ((end - 1) * 2 - source + ${d});
| source -= start;
| `;c=`
| ${r} rc = outputLoc;
| ${h}
| result[0] = getChannel(getX(${l.join()}), ${p});
| ${o[a-1]} += 1;
| if(${u}) {
| ${h}
| result[1] = getChannel(getX(${l.join()}), ${p});
| }
| rc = outputLoc;
| ${o[a-2]} += 1;
| if(${o[a-2]} < ${this.outputShape[a-2]}) {
| ${h}
| result[2] = getChannel(getX(${l.join()}), ${p});
| ${o[a-1]} += 1;
| if(${u}) {
| ${h}
| result[3] = getChannel(getX(${l.join()}), ${p});
| }
| }
| `}this.userCode=`
| const ${r} start = ${r}(${s});
| const ${r} end = ${r}(${i});
|
| void main() {
| ${r} outputLoc = getOutputCoords();
| vec4 result = vec4(0.);
| ${c}
| setOutput(result);
| }
| `}},nse=({inputs:e,backend:t,attrs:n})=>{let{x:a}=e,{paddings:r,mode:s}=n,i=G().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new tse(a.shape,r,s):new ese(a.shape,r,s);return t.runWebGLProgram(i,[a],a.dtype)},ase={kernelName:go,backendName:"webgl",kernelFunc:nse},rse=`if (b == 0.0) return NAN;
| return mod(a, b);`,sse=`
| vec4 result = mod(a, b);
| bvec4 isNaN = equal(b, vec4(0.0));
| `+el+`
| return result;
| `,ise=fn({opSnippet:rse,packedOpSnippet:sse}),ose={kernelName:bo,backendName:"webgl",kernelFunc:ise},lse=class{constructor(e,t,n){this.variableNames=["probs"],this.customUniforms=[{name:"seed",type:"float"}],this.outputShape=[e,n],this.userCode=`
| void main() {
| ivec2 coords = getOutputCoords();
| int batch = coords[0];
|
| float r = random(seed);
| float cdf = 0.0;
|
| for (int i = 0; i < ${t-1}; i++) {
| cdf += getProbs(batch, i);
|
| if (r < cdf) {
| setOutput(float(i));
| return;
| }
| }
|
| // If no other event happened, last event happened.
| setOutput(float(${t-1}));
| }
| `}},use=`
| if (a == b) {
| return 1.0;
| };
| return a / b;`,pse=`
| // 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;
| `,qA=fn({opSnippet:use,packedOpSnippet:pse,checkOutOfBounds:!0}),cse={kernelName:qi,backendName:"webgl",kernelFunc:qA},RS="return a - b;",jA=fn({opSnippet:RS,packedOpSnippet:RS,supportsComplex:!0,cpuKernelImpl:nQ}),dse={kernelName:Vo,backendName:"webgl",kernelFunc:jA};function KA(e){let{inputs:t,backend:n,attrs:a}=e,{logits:r}=t,{dim:s}=a,i=w.parseAxisParam([s],r.shape),o=HA({inputs:{x:r},backend:n,attrs:{reductionIndices:i,keepDims:!1}}),l=N.expandShapeToKeepDim(o.shape,i),u=ce({inputs:{x:o},backend:n,attrs:{shape:l}}),p=jA({inputs:{a:r,b:u},backend:n}),d=VA({inputs:{x:p},backend:n}),c=tg({inputs:{x:d},backend:n,attrs:{axis:i,keepDims:!1}}),h=ce({inputs:{x:c},backend:n,attrs:{shape:l}}),m=qA({inputs:{a:d,b:h},backend:n});return n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(u),n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(c),n.disposeIntermediateTensorInfo(h),m}var hse={kernelName:Wo,backendName:"webgl",kernelFunc:KA};function mse(e){let{inputs:t,backend:n,attrs:a}=e,{logits:r}=t,{numSamples:s,seed:i,normalized:o}=a,l=o?r:KA({inputs:{logits:r},backend:n,attrs:{dim:r.shape.length-1}}),u=l.shape[0],p=l.shape[1],d=new lse(u,p,s),c=[[i]],h=n.runWebGLProgram(d,[l],"int32",c);return o||n.disposeIntermediateTensorInfo(l),h}var fse={kernelName:Lu,backendName:"webgl",kernelFunc:mse},gse=Oa+`
| return -x;
| `,bse=`
| vec4 result = -x;
| bvec4 isNaN = isnan(x);
|
| result.r = isNaN.r ? x.r : result.r;
| result.g = isNaN.g ? x.g : result.g;
| result.b = isNaN.b ? x.b : result.b;
| result.a = isNaN.a ? x.a : result.a;
|
| return result;
| `;function yse(e){let{inputs:t,backend:n}=e,{x:a}=t;if(n.shouldExecuteOnCPU([a])){let s=n.texData.get(a.dataId),[i,o]=O9(s.values,a.shape,a.dtype);return n.makeTensorInfo(o,a.dtype,i)}let r;return G().getBool("WEBGL_PACK_UNARY_OPERATIONS")?r=new os(a.shape,bse):r=new ir(a.shape,gse),n.runWebGLProgram(r,[a],a.dtype)}var xse={kernelName:zu,backendName:"webgl",kernelFunc:yse},vse=gr.nonMaxSuppressionV3Impl;function wse(e){N.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:a}=e,{boxes:r,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l}=a,u=n.readSync(r.dataId),p=n.readSync(s.dataId),{selectedIndices:d}=vse(u,p,i,o,l);return n.makeTensorInfo([d.length],"int32",new Int32Array(d))}var kse={kernelName:Bu,backendName:"webgl",kernelFunc:wse},Ise=gr.nonMaxSuppressionV4Impl;function Sse(e){N.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:a}=e,{boxes:r,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l,padToMaxOutputSize:u}=a,p=n.readSync(r.dataId),d=n.readSync(s.dataId),{selectedIndices:c,validOutputs:h}=Ise(p,d,i,o,l,u);return[n.makeTensorInfo([c.length],"int32",new Int32Array(c)),n.makeTensorInfo([],"int32",new Int32Array([h]))]}var Nse={kernelName:Vu,backendName:"webgl",kernelFunc:Sse},Tse=gr.nonMaxSuppressionV5Impl;function Cse(e){N.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:a}=e,{boxes:r,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l,softNmsSigma:u}=a,p=n.readSync(r.dataId),d=n.readSync(s.dataId),c=i,h=o,m=l,f=u,{selectedIndices:g,selectedScores:b}=Tse(p,d,c,h,m,f);return[n.makeTensorInfo([g.length],"int32",new Int32Array(g)),n.makeTensorInfo([b.length],"float32",new Float32Array(b))]}var _se={kernelName:Uu,backendName:"webgl",kernelFunc:Cse},Ese=class{constructor(e,t,n,a){this.variableNames=["indices"],this.outputShape=[e,t],this.userCode=`
| void main() {
| ivec2 coords = getOutputCoords();
| int index = round(getIndices(coords.x));
| setOutput(mix(float(${a}), float(${n}),
| float(index == coords.y)));
| }
| `}},Ase=e=>{let{inputs:t,backend:n,attrs:a}=e,{indices:r}=t,{dtype:s,depth:i,onValue:o,offValue:l}=a,u=w.sizeFromShape(r.shape),p=new Ese(u,i,o,l),d=ce({inputs:{x:r},backend:n,attrs:{shape:[u]}}),c=n.runWebGLProgram(p,[d],s);n.disposeIntermediateTensorInfo(d);let h=[...r.shape,i],m=ce({inputs:{x:c},backend:n,attrs:{shape:h}});return n.disposeIntermediateTensorInfo(c),m},Fse={kernelName:xo,backendName:"webgl",kernelFunc:Ase};function Fm(e){let{inputs:t,backend:n}=e,{x:a}=t;if(a.dtype==="complex64"){let r=Od({inputs:{input:a},backend:n}),s=Fm({inputs:{x:r},backend:n}),i=ng({inputs:{input:a},backend:n}),o=Fm({inputs:{x:i},backend:n}),l=Ms({inputs:{real:s,imag:o},backend:n});return n.disposeIntermediateTensorInfo(r),n.disposeIntermediateTensorInfo(s),n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(o),l}else return Ld({attrs:{shape:a.shape,dtype:a.dtype,value:a.dtype==="string"?"":0},backend:n})}var $se={kernelName:lp,backendName:"webgl",kernelFunc:Fm};function XA(e){let{inputs:t,backend:n}=e,{x:a}=t;if(a.dtype==="string")throw new Error("onesLike is not supported under string dtype");if(a.dtype==="complex64"){let r=Od({inputs:{input:a},backend:n}),s=XA({inputs:{x:r},backend:n}),i=ng({inputs:{input:a},backend:n}),o=Fm({inputs:{x:i},backend:n}),l=Ms({inputs:{real:s,imag:o},backend:n});return n.disposeIntermediateTensorInfo(r),n.disposeIntermediateTensorInfo(s),n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(o),l}else return Ld({attrs:{shape:a.shape,dtype:a.dtype,value:1},backend:n})}var Dse={kernelName:Gu,backendName:"webgl",kernelFunc:XA};function Rse(e){let{inputs:t,backend:n,attrs:a}=e,{axis:r}=a;if(t.length===1)return yv({inputs:{input:t[0]},backend:n,attrs:{dim:r}});let s=t[0].shape,i=t[0].dtype;t.forEach(p=>{w.assertShapesMatch(s,p.shape,"All tensors passed to stack must have matching shapes"),w.assert(i===p.dtype,()=>"All tensors passed to stack must have matching dtypes")});let o=[],l=t.map(p=>{let d=yv({inputs:{input:p},backend:n,attrs:{dim:r}});return o.push(d),d}),u=RA({inputs:l,backend:n,attrs:{axis:r}});return o.forEach(p=>n.disposeIntermediateTensorInfo(p)),u}var Mse={kernelName:Hu,backendName:"webgl",kernelFunc:Rse},Pse=class{constructor(e,t,n){this.variableNames=["x"],this.customUniforms=[{name:"value",type:"float"}],this.outputShape=t.map((l,u)=>l[0]+e[u]+l[1]);let a=e.length,r=dt(a),s=t.map(l=>l[0]).join(","),i=t.map((l,u)=>l[0]+e[u]).join(","),o=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,a);if(a===1){this.userCode=`
| int start = ${s};
| int end = ${i};
|
| void main() {
| int outC = getOutputCoords();
| if (outC < start || outC >= end) {
| setOutput(value);
| } else {
| setOutput(getX(outC - start));
| }
| }
| `;return}this.userCode=`
| ${r} start = ${r}(${s});
| ${r} end = ${r}(${i});
|
| void main() {
| ${r} outC = getOutputCoords();
| if (any(lessThan(outC, start)) || any(greaterThanEqual(outC, end))) {
| setOutput(value);
| } else {
| ${r} coords = outC - start;
| setOutput(getX(${o}));
| }
| }
| `}},Ose=class{constructor(e,t,n){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"value",type:"float"}],this.outputShape=t.map((m,f)=>m[0]+e[f]+m[1]);let a=e.length,r=dt(a),s=t.map(m=>m[0]).join(","),i=t.map((m,f)=>m[0]+e[f]).join(","),o=Sn("rc",a),l=Sn("source",a),u=`${o[a-1]} < ${this.outputShape[a-1]}`,p=a===1?"source":`vec2(${l.slice(-2).join()})`,d=[`${r} rc = outputLoc;`,`${o[a-1]} += 1;
| if(${u}) {
| `,a===1?"":`}
| rc = outputLoc;
| ${o[a-2]} += 1;
| if(${o[a-2]} < ${this.outputShape[a-2]}) {`,a===1?"":` ${o[a-1]} += 1;
| if(${u}) {`],c=a===1?"rc < start || rc >= end":"any(lessThan(rc, start)) || any(greaterThanEqual(rc, end))",h="";for(let m=0,f=a===1?2:4;m<f;m++)h+=`
| ${d[m]}
| if (${c}) {
| result[${m}] = float(value);
| } else {
| ${r} source = rc - start;
| result[${m}] = getChannel(getX(${l.join()}), ${p});
| }
| `;h+=a===1?"} ":"}}",this.userCode=`
| const ${r} start = ${r}(${s});
| const ${r} end = ${r}(${i});
|
| void main() {
| ${r} outputLoc = getOutputCoords();
| vec4 result = vec4(0.);
| ${h}
| setOutput(result);
| }
| `}},YA=e=>{let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{paddings:s,constantValue:i}=a;if(w.sizeFromShape(r.shape)===0){let u=s.map((p,d)=>p[0]+r.shape[d]+p[1]);return Ld({backend:n,attrs:{shape:u,value:i,dtype:r.dtype}})}let o=G().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new Ose(r.shape,s,i):new Pse(r.shape,s,i),l=[[i]];return n.runWebGLProgram(o,[r],r.dtype,l)},Lse={kernelName:vo,backendName:"webgl",kernelFunc:YA},zse=`
| 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);
| `,Wse=`
| // isModRound1 has 1 for components with round(mod(b, 2.0)) == 1, 0 otherwise.
| vec4 isModRound1 = vec4(equal(round(mod(b, 2.0)), ivec4(1)));
| vec4 multiplier = sign(a) * isModRound1 + (vec4(1.0) - isModRound1);
| vec4 result = multiplier * pow(abs(a), b);
|
| // Ensure that a^0 = 1, including 0^0 = 1 as this correspond to TF and JS
| bvec4 isExpZero = equal(b, vec4(0.0));
| result.r = isExpZero.r ? 1.0 : result.r;
| result.g = isExpZero.g ? 1.0 : result.g;
| result.b = isExpZero.b ? 1.0 : result.b;
| result.a = isExpZero.a ? 1.0 : result.a;
|
| bvec4 isNaN1 = lessThan(a, vec4(0.0));
| bvec4 isNaN2 = lessThan(floor(b), b);
| bvec4 isNaN = bvec4(isNaN1.x && isNaN2.x, isNaN1.y && isNaN2.y, isNaN1.z && isNaN2.z, isNaN1.w && isNaN2.w);
| `+el+`
| return result;
| `,Bse=fn({opSnippet:zse,packedOpSnippet:Wse}),Vse={kernelName:wo,backendName:"webgl",kernelFunc:Bse};function Use(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{axis:s,keepDims:i}=a,o=r.shape.length,l=[],u=w.parseAxisParam(s,r.shape),p=u,d=N.getAxesPermutation(p,o),c=r;d!=null&&(c=Nn({inputs:{x:r},backend:n,attrs:{perm:d}}),p=N.getInnerMostAxes(p.length,o),l.push(c)),N.assertAxesAreInnerMostDims("prod",p,o);let h;if(n.shouldExecuteOnCPU([c])){let m=n.texData.get(c.dataId).values,{outVals:f,outShape:g,outDtype:b}=z9(c.shape,c.dtype,m,p);h=n.makeTensorInfo(g,b,f)}else{let[m,f]=N.computeOutAndReduceShapes(c.shape,p),g=w.sizeFromShape(f),b=ce({inputs:{x:c},backend:n,attrs:{shape:[-1,g]}}),y=Ym(r.dtype),x=tl(b,y,"prod",n);h=ce({inputs:{x},backend:n,attrs:{shape:m}}),l.push(b),l.push(x)}if(i){l.push(h);let m=N.expandShapeToKeepDim(h.shape,u);h=ce({inputs:{x:h},backend:n,attrs:{shape:m}})}return l.forEach(m=>n.disposeIntermediateTensorInfo(m)),h}var Gse={kernelName:Io,backendName:"webgl",kernelFunc:Use};function Hse(e){let{inputs:t,backend:n,attrs:a}=e,{paramsNestedSplits:r,paramsDenseValues:s,indices:i}=t,{outputRaggedRank:o}=a,l=r.map(b=>n.readSync(b.dataId)),u=r.map(b=>b.shape),p=n.readSync(s.dataId),d=n.readSync(i.dataId),[c,h,m]=W9(l,u,p,s.shape,s.dtype,d,i.shape,o),f=c.map(b=>n.makeTensorInfo([b.length],"int32",b)),g=n.makeTensorInfo(m,s.dtype,h);return f.concat([g])}var qse={kernelName:Hm,backendName:"webgl",kernelFunc:Hse};function jse(e){let{inputs:t,backend:n}=e,{starts:a,limits:r,deltas:s}=t,i=n.readSync(a.dataId),o=n.readSync(r.dataId),l=n.readSync(s.dataId),[u,p]=B9(i,a.shape,a.dtype,o,r.shape,l,s.shape),d=n.makeTensorInfo([u.length],"int32",u),c=n.makeTensorInfo([p.length],a.dtype,p);return[d,c]}var Kse={kernelName:qm,backendName:"webgl",kernelFunc:jse};function Xse(e){let{inputs:t,backend:n,attrs:a}=e,{shape:r,values:s,defaultValue:i,rowPartitionTensors:o}=t,{rowPartitionTypes:l}=a,u=n.readSync(r.dataId),p=n.readSync(s.dataId),d=n.readSync(i.dataId),c=o.map(g=>n.readSync(g.dataId)),h=o.map(g=>g.shape),[m,f]=V9(u,r.shape,p,s.shape,s.dtype,d,i.shape,c,h,l);return n.makeTensorInfo(m,s.dtype,f)}var Yse={kernelName:jm,backendName:"webgl",kernelFunc:Xse},ZA=e=>{let{backend:t,attrs:n}=e,{start:a,stop:r,step:s,dtype:i}=n,o=U9(a,r,s,i);return t.makeTensorInfo([o.length],i,o)},Zse={kernelName:jc,backendName:"webgl",kernelFunc:ZA},Jse="return 1.0 / x;",Qse=Ze({opSnippet:Jse}),eie={kernelName:So,backendName:"webgl",kernelFunc:Qse},tie=Oa+`
| return (x < 0.0) ? 0.0 : x;
| `,nie=`
| 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;
| `,aie=Ze({opSnippet:tie,packedOpSnippet:nie}),rie={kernelName:No,backendName:"webgl",kernelFunc:aie},sie=Oa+`
| return (x < 0.0) ? 0.0 : min(6.0, x);
| `,iie=`
| 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;
| `,oie=Ze({opSnippet:sie,packedOpSnippet:iie}),lie={kernelName:_o,backendName:"webgl",kernelFunc:oie},uie=class{constructor(e,t,n,a,r){this.variableNames=["A"],this.outputShape=[];let[s,i,o,l]=e;this.outputShape=[s,t,n,l];let u=[a&&t>1?i-1:i,a&&n>1?o-1:o],p=[a&&t>1?t-1:t,a&&n>1?n-1:n],d;r?d="(vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC - vec2(0.5)":d="vec2(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
| const vec2 effectiveInputOverOutputRatioRC = vec2(
| ${u[0]/p[0]},
| ${u[1]/p[1]});
| const vec2 inputShapeRC = vec2(${i}.0, ${o}.0);
|
| void main() {
| ivec4 coords = getOutputCoords();
| int b = coords[0];
| int d = coords[3];
| ivec2 yRC = coords.yz;
|
| // Fractional source index.
| vec2 sourceFracIndexRC = ${d};
|
| // Compute the four integer indices.
| ivec2 sourceFloorRC = ivec2(max(sourceFracIndexRC, vec2(0.0)));
| ivec2 sourceCeilRC = ivec2(
| min(inputShapeRC - 1.0, ceil(sourceFracIndexRC)));
|
| float topLeft = getA(b, sourceFloorRC.x, sourceFloorRC.y, d);
| float bottomLeft = getA(b, sourceCeilRC.x, sourceFloorRC.y, d);
| float topRight = getA(b, sourceFloorRC.x, sourceCeilRC.y, d);
| float bottomRight = getA(b, sourceCeilRC.x, sourceCeilRC.y, d);
|
| vec2 fracRC = sourceFracIndexRC - vec2(sourceFloorRC);
|
| float top = topLeft + (topRight - topLeft) * fracRC.y;
| float bottom = bottomLeft + (bottomRight - bottomLeft) * fracRC.y;
| float newValue = top + (bottom - top) * fracRC.x;
|
| setOutput(newValue);
| }
| `}},pie=class{constructor(e,t,n,a,r){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[];let[s,i,o,l]=e;this.outputShape=[s,t,n,l];let u=[a&&t>1?i-1:i,a&&n>1?o-1:o],p=[a&&t>1?t-1:t,a&&n>1?n-1:n],d;r?d="(vec3(yRC) + vec3(0.5)) * effectiveInputOverOutputRatioRC - vec3(0.5)":d="vec3(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
| const vec3 effectiveInputOverOutputRatioRC = vec3(
| ${u[0]/p[0]},
| ${u[1]/p[1]},
| ${u[1]/p[1]});
| const vec3 inputShapeRC = vec3(${i}.0, ${o}.0,
| ${o}.0);
|
| float getAValue(int b, int r, int c, int d) {
| return getChannel(getA(b, r, c, d), vec2(c, d));
| }
|
| void main() {
| ivec4 coords = getOutputCoords();
| int b = coords[0];
| int d = coords[3];
| // Calculate values for next column in yRC.z.
| ivec3 yRC = coords.yzz + ivec3(0, 0, 1);
|
| // Fractional source index.
| vec3 sourceFracIndexRC = ${d};
|
| // Compute the four integer indices.
| ivec3 sourceFloorRC = ivec3(max(sourceFracIndexRC, vec3(0.0)));
| ivec3 sourceCeilRC = ivec3(
| min(inputShapeRC - 1.0, ceil(sourceFracIndexRC)));
|
| // Should we calculate next column and row elements in 2x2 packed cell.
| bool hasNextCol = d < ${l-1};
| bool hasNextRow = coords.z < ${n-1};
|
| // In parallel, construct four corners for all four components in
| // packed 2x2 cell.
| vec4 topLeft = vec4(
| getAValue(b, sourceFloorRC.x, sourceFloorRC.y, d),
| hasNextCol ? getAValue(b, sourceFloorRC.x, sourceFloorRC.y, d + 1)
| : 0.0,
| hasNextRow ? getAValue(b, sourceFloorRC.x, sourceFloorRC.z, d)
| : 0.0,
| (hasNextRow && hasNextCol) ?
| getAValue(b, sourceFloorRC.x, sourceFloorRC.z, d + 1) : 0.0);
|
| vec4 bottomLeft = vec4(
| getAValue(b, sourceCeilRC.x, sourceFloorRC.y, d),
| hasNextCol ? getAValue(b, sourceCeilRC.x, sourceFloorRC.y, d + 1)
| : 0.0,
| hasNextRow ? getAValue(b, sourceCeilRC.x, sourceFloorRC.z, d)
| : 0.0,
| (hasNextRow && hasNextCol) ?
| getAValue(b, sourceCeilRC.x, sourceFloorRC.z, d + 1) : 0.0);
|
| vec4 topRight = vec4(
| getAValue(b, sourceFloorRC.x, sourceCeilRC.y, d),
| hasNextCol ? getAValue(b, sourceFloorRC.x, sourceCeilRC.y, d + 1)
| : 0.0,
| hasNextRow ? getAValue(b, sourceFloorRC.x, sourceCeilRC.z, d)
| : 0.0,
| (hasNextRow && hasNextCol) ?
| getAValue(b, sourceFloorRC.x, sourceCeilRC.z, d + 1) : 0.0);
|
| vec4 bottomRight = vec4(
| getAValue(b, sourceCeilRC.x, sourceCeilRC.y, d),
| hasNextCol ? getAValue(b, sourceCeilRC.x, sourceCeilRC.y, d + 1)
| : 0.0,
| hasNextRow ? getAValue(b, sourceCeilRC.x, sourceCeilRC.z, d)
| : 0.0,
| (hasNextRow && hasNextCol) ?
| getAValue(b, sourceCeilRC.x, sourceCeilRC.z, d + 1) : 0.0);
|
| vec3 fracRC = sourceFracIndexRC - vec3(sourceFloorRC);
|
| vec4 top = mix(topLeft, topRight, fracRC.yyzz);
| vec4 bottom = mix(bottomLeft, bottomRight, fracRC.yyzz);
| vec4 newValue = mix(top, bottom, fracRC.x);
|
| setOutput(newValue);
| }
| `}};function cie(e){let{inputs:t,backend:n,attrs:a}=e,{images:r}=t,{alignCorners:s,halfPixelCenters:i,size:o}=a,[l,u]=o,p=G().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new pie(r.shape,l,u,s,i):new uie(r.shape,l,u,s,i);return n.runWebGLProgram(p,[r],"float32")}var die={kernelName:Co,backendName:"webgl",kernelFunc:cie},hie=class{constructor(e,t,n){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t;let[,a,r]=t,[,s,i]=e,o=[n&&s>1?a-1:a,n&&i>1?r-1:r],l=[n&&s>1?s-1:s,n&&i>1?i-1:i],u=o[0]/l[0],p=o[1]/l[1],d=1/u,c=1/p,h=Math.ceil(d)*2+2,m=Math.ceil(c)*2+2;this.userCode=`
| void main() {
| ivec4 coords = getOutputCoords();
| int b = coords[0];
| int d = coords[3];
| int r = coords[1];
| int c = coords[2];
|
| float accumulator = 0.0;
|
| const float heightScale = float(${u});
| const float widthScale = float(${p});
|
| const float invHeightScale = float(${d});
| const float invWidthScale = float(${c});
|
| const int winHeight = int(${h});
| const int winWidth = int(${m});
|
| // Compute bounds for where in dy we will look
| float startRLerp = floor(float(r) * invHeightScale);
| int startDyR = int(startRLerp - float(winHeight / 2));
|
| float startCLerp = floor(float(c) * invWidthScale);
| int startDyC = int(startCLerp - float(winWidth / 2));
|
| // Loop over dy
| for (int dyROffset = 0; dyROffset < winHeight; dyROffset++) {
| int dyR = dyROffset + startDyR;
|
| // Guard against the window exceeding the bounds of dy
| if (dyR < 0 || dyR >= ${s}) {
| continue;
| }
|
| for (int dyCOffset = 0; dyCOffset < winWidth; dyCOffset++) {
| int dyC = dyCOffset + startDyC;
|
| // Guard against the window exceeding the bounds of dy
| if (dyC < 0 || dyC >= ${i}) {
| continue;
| }
|
| float dxR = float(dyR) * heightScale;
| int topDxRIndex = int(floor(dxR));
| int bottomDxRIndex = int(min(ceil(dxR), ${a-1}.0));
| float dxRLerp = dxR - float(topDxRIndex);
| float inverseDxRLerp = 1.0 - dxRLerp;
|
| float dxC = float(dyC) * widthScale;
| int leftDxCIndex = int(floor(dxC));
| int rightDxCIndex = int(min(ceil(dxC), ${r-1}.0));
| float dxCLerp = dxC - float(leftDxCIndex);
| float inverseDxCLerp = 1.0 - dxCLerp;
|
| if (r == topDxRIndex && c == leftDxCIndex) {
| // topLeft
| accumulator +=
| getDy(b, dyR, dyC, d) * inverseDxRLerp * inverseDxCLerp;
| }
|
| if (r == topDxRIndex && c == rightDxCIndex) {
| // topRight
| accumulator += getDy(b, dyR, dyC, d) * inverseDxRLerp * dxCLerp;
| }
|
| if (r == bottomDxRIndex && c == leftDxCIndex) {
| // bottomLeft
| accumulator += getDy(b, dyR, dyC, d) * dxRLerp * inverseDxCLerp;
| }
|
| if (r == bottomDxRIndex && c == rightDxCIndex) {
| // bottomRight
| accumulator += getDy(b, dyR, dyC, d) * dxRLerp * dxCLerp;
| }
| }
| }
| // End loop over dy
|
| setOutput(accumulator);
| }
| `}};function mie(e){let{inputs:t,backend:n,attrs:a}=e,{images:r,dy:s}=t,{alignCorners:i}=a,o=new hie(s.shape,r.shape,i);return n.runWebGLProgram(o,[s],s.dtype)}var fie={kernelName:Ku,backendName:"webgl",kernelFunc:mie},gie=class{constructor(e,t,n,a,r){this.variableNames=["A"],this.outputShape=[];let[s,i,o,l]=e;this.outputShape=[s,t,n,l];let u=[a&&t>1?i-1:i,a&&n>1?o-1:o],p=[a&&t>1?t-1:t,a&&n>1?n-1:n],d=a?"0.5":"0.0",c;r?c="max((vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC, vec2(0.0))":c="vec2(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
| const vec2 effectiveInputOverOutputRatioRC = vec2(
| ${u[0]/p[0]},
| ${u[1]/p[1]});
| const vec2 inputShapeRC = vec2(${i}.0, ${o}.0);
|
| void main() {
| ivec4 coords = getOutputCoords();
| int b = coords[0];
| int d = coords[3];
| ivec2 yRC = coords.yz;
|
| // Fractional source index.
| vec2 sourceFracIndexRC = ${c};
|
| // Compute the coordinators of nearest neighbor point.
| ivec2 sourceNearestRC = ivec2(
| min(inputShapeRC - 1.0, floor(sourceFracIndexRC + ${d})));
| float newValue = getA(b, sourceNearestRC.x, sourceNearestRC.y, d);
|
| setOutput(newValue);
| }
| `}},bie=class{constructor(e,t,n,a,r){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[];let[s,i,o,l]=e;this.outputShape=[s,t,n,l];let u=[a&&t>1?i-1:i,a&&n>1?o-1:o],p=[a&&t>1?t-1:t,a&&n>1?n-1:n],d=a?"0.5":"0.0",c;r?c="max((vec3(yRC) + vec3(0.5)) * effectiveInputOverOutputRatioRC, vec3(0.0))":c="vec3(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
| const vec3 effectiveInputOverOutputRatioRC = vec3(
| ${u[0]/p[0]},
| ${u[1]/p[1]},
| ${u[1]/p[1]});
| const vec3 inputShapeRC = vec3(${i}.0, ${o}.0,
| ${o}.0);
|
| float getAValue(int b, int r, int c, int d) {
| return getChannel(getA(b, r, c, d), vec2(c, d));
| }
|
| void main() {
| ivec4 coords = getOutputCoords();
| int b = coords[0];
| int d = coords[3];
| // Calculate values for next column in yRC.z.
| ivec3 yRC = coords.yzz + ivec3(0, 0, 1);
|
| // Fractional source index.
| vec3 sourceFracIndexRC = ${c};
|
| // Compute the coordinators of nearest neighbor point.
| ivec3 sourceNearestRC = ivec3(
| min(inputShapeRC - 1.0, floor(sourceFracIndexRC + ${d})));
|
| // Should we calculate next column and row elements in 2x2 packed cell.
| bool hasNextCol = d < ${l-1};
| bool hasNextRow = coords.z < ${n-1};
|
| vec4 newValue = vec4(
| getAValue(b, sourceNearestRC.x, sourceNearestRC.y, d),
| hasNextCol ? getAValue(b, sourceNearestRC.x, sourceNearestRC.y, d + 1)
| : 0.0,
| hasNextRow ? getAValue(b, sourceNearestRC.x, sourceNearestRC.z, d)
| : 0.0,
| (hasNextRow && hasNextCol) ?
| getAValue(b, sourceNearestRC.x, sourceNearestRC.z, d + 1) : 0.0);
|
| setOutput(newValue);
| }
| `}};function yie(e){let{inputs:t,backend:n,attrs:a}=e,{images:r}=t,{alignCorners:s,halfPixelCenters:i,size:o}=a,[l,u]=o,p=G().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new bie(r.shape,l,u,s,i):new gie(r.shape,l,u,s,i);return n.runWebGLProgram(p,[r],r.dtype)}var xie={kernelName:To,backendName:"webgl",kernelFunc:yie},vie=class{constructor(e,t,n){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t;let[,a,r]=t,[,s,i]=e,o=[n&&s>1?a-1:a,n&&i>1?r-1:r],l=[n&&s>1?s-1:s,n&&i>1?i-1:i],u=o[0]/l[0],p=o[1]/l[1],d=1/u,c=1/p,h=Math.ceil(d)*2+2,m=Math.ceil(c)*2+2;this.userCode=`
| void main() {
| ivec4 coords = getOutputCoords();
| int b = coords[0];
| int d = coords[3];
| int r = coords[1];
| int c = coords[2];
|
| float accumulator = 0.0;
|
| const float heightScale = float(${u});
| const float widthScale = float(${p});
|
| const float invHeightScale = float(${d});
| const float invWidthScale = float(${c});
|
| const int winHeight = int(${h});
| const int winWidth = int(${m});
|
| // Compute bounds for where in dy we will look
| float startRLerp = floor(float(r) * invHeightScale);
| int startDyR = int(floor(startRLerp - float(winHeight / 2)));
|
| float startCLerp = floor(float(c) * invWidthScale);
| int startDyC = int(floor(startCLerp - float(winWidth / 2)));
|
| // Loop over dy
| for (int dyROffset = 0; dyROffset < winHeight; dyROffset++) {
| int dyR = dyROffset + startDyR;
|
| // Guard against the window exceeding the bounds of dy
| if (dyR < 0 || dyR >= ${s}) {
| continue;
| }
|
| for (int dyCOffset = 0; dyCOffset < winWidth; dyCOffset++) {
| int dyC = dyCOffset + startDyC;
|
| // Guard against the window exceeding the bounds of dy
| if (dyC < 0 || dyC >= ${i}) {
| continue;
| }
|
| float sourceFracRow =
| float(${o[0]}) *
| (float(dyR) / float(${l[0]}));
|
| float sourceFracCol =
| float(${o[1]}) *
| (float(dyC) / float(${l[1]}));
|
| int sourceNearestRow = int(min(
| float(int(${a}) - 1),
| ${n} ? float(round(sourceFracRow)) :
| float(floor(sourceFracRow))));
|
| int sourceNearestCol = int(min(
| float(int(${r}) - 1),
| ${n} ? float(round(sourceFracCol)) :
| float(floor(sourceFracCol))));
|
| if (r == sourceNearestRow && c == sourceNearestCol) {
| accumulator += getDy(b, dyR, dyC, d);
| }
| }
| }
| // End loop over dy
|
| setOutput(accumulator);
| }
| `}};function wie(e){let{inputs:t,backend:n,attrs:a}=e,{images:r,dy:s}=t,{alignCorners:i}=a,o=new vie(s.shape,r.shape,i);return n.runWebGLProgram(o,[s],s.dtype)}var kie={kernelName:ju,backendName:"webgl",kernelFunc:wie},Iie=class{constructor(e,t){this.variableNames=["x"];let n=e.length;if(n>4)throw new Error(`WebGL backend: Reverse of rank-${n} tensor is not yet supported`);if(this.outputShape=e,n===1){this.userCode=`
| void main() {
| int coord = getOutputCoords();
| setOutput(getX(${e[0]} - coord - 1));
| }
| `;return}let a=i=>t.indexOf(i)!==-1&&e[i]!==1?`${e[i]} - coords[${i}] - 1`:`coords[${i}]`,r=e.map((i,o)=>a(o)).join(","),s=dt(n);this.userCode=`
| void main() {
| ${s} coords = getOutputCoords();
| setOutput(getX(${r}));
| }
| `}},Sie=class{constructor(e,t){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0;let n=e.length;if(n>4)throw new Error(`WebGL backend: Reverse of rank-${n} tensor is not yet supported`);this.outputShape=e;let a=Sn("rc",n),r=`${a[n-1]} + 1 < ${this.outputShape[n-1]}`,s=`${a[n-2]} + 1 < ${this.outputShape[n-2]}`,i=dt(n);n===1?this.userCode=`
| void main(){
| int rc = getOutputCoords();
| vec4 result = vec4(0.);
| result.r = getChannel(getX(${e[0]} - rc - 1),
| ${e[0]} - rc - 1);
| if(${r}){
| result.g = getChannel(getX(${e[0]} - (rc + 1) - 1),
| ${e[0]} - (rc + 1) - 1);
| }
| setOutput(result);
| }
| `:this.userCode=`
| void main() {
| ${i} rc = getOutputCoords();
| vec4 result = vec4(0.);
| result.r = ${o(a.slice())};
| if(${r}){
| result.g = ${l(a.slice())};
| }
| if(${s}) {
| result.b = ${u(a.slice())};
| if(${r}) {
| result.a = ${p(a.slice())};
| }
| }
| setOutput(result);
| }
| `;function o(h){return d(h)}function l(h){return h[n-1]="("+h[n-1]+" + 1)",d(h)}function u(h){return h[n-2]="("+h[n-2]+" + 1)",d(h)}function p(h){return h[n-1]="("+h[n-1]+" + 1)",h[n-2]="("+h[n-2]+" + 1)",d(h)}function d(h){let m=e.map((b,y)=>c(y,h)),f=m.join(","),g=m.slice(-2).join(",");return`getChannel(getX(${f}), vec2(${g}))`}function c(h,m){return t.indexOf(h)!==-1&&e[h]!==1?`${e[h]} - ${m[h]} - 1`:`${m[h]}`}}};function Nie(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{dims:s}=a,i=r.shape.length,o=w.parseAxisParam(s,r.shape);if(i===0)return ra({inputs:{x:r},backend:n});let l=G().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new Sie(r.shape,o):new Iie(r.shape,o);return n.runWebGLProgram(l,[r],r.dtype)}var Tie={kernelName:Eo,backendName:"webgl",kernelFunc:Nie},Cie=class{constructor(e,t){this.variableNames=["Image"],this.outputShape=[],this.customUniforms=[{name:"params",type:"vec4"}];let n=e[1],a=e[2];this.outputShape=e;let r="";typeof t=="number"?r=`float outputValue = ${t.toFixed(2)};`:r=`
| vec3 fill = vec3(${t.join(",")});
| float outputValue = fill[coords[3]];`,this.userCode=`
| void main() {
| ivec4 coords = getOutputCoords();
| int x = coords[2];
| int y = coords[1];
| float coordXFloat = (float(x) - params[0]) * params[3] -
| (float(y) - params[1]) * params[2];
| float coordYFloat = (float(x) - params[0]) * params[2] +
| (float(y) - params[1]) * params[3];
| int coordX = int(round(coordXFloat + params[0]));
| int coordY = int(round(coordYFloat + params[1]));
| ${r}
| if(coordX >= 0 && coordX < ${a} && coordY >= 0 && coordY < ${n}) {
| outputValue = getImage(coords[0], coordY, coordX, coords[3]);
| }
| setOutput(outputValue);
| }
| `}},_ie={kernelName:up,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{image:a}=e,{radians:r,fillValue:s,center:i}=t,o=n,l=new Cie(a.shape,s),[u,p]=N.getImageCenter(i,a.shape[1],a.shape[2]),d=[[u,p,Math.sin(r),Math.cos(r)]];return o.runWebGLProgram(l,[a],a.dtype,d)}},Eie=`
| // OpenGL ES does not support round function.
| // The algorithm is based on banker's rounding.
| float base = floor(x);
| if ((x - base) < 0.5) {
| return floor(x);
| } else if ((x - base) > 0.5) {
| return ceil(x);
| } else {
| if (mod(base, 2.0) == 0.0) {
| return base;
| } else {
| return base + 1.0;
| }
| }
| `,Aie=Ze({opSnippet:Eie}),Fie={kernelName:Ao,backendName:"webgl",kernelFunc:Aie},$ie="return inversesqrt(x);",Die=Ze({opSnippet:$ie,cpuKernelImpl:G9}),Rie={kernelName:Fo,backendName:"webgl",kernelFunc:Die},dk=class{constructor(e,t,n,a,r,s,i=!0,o=!1){this.variableNames=["updates","indices","defaultValue"],this.outputShape=s;let l=dt(r.length),u=dt(s.length),p="";n===1?p="i":n===2&&(p="i, j");let d=`getIndices(${p})`,c="";a===1?c="i":a===2&&(c="i, coords[1]");let h=`getUpdates(${c})`,m="";o&&(m="coords[0], coords[1]");let f=`getDefaultValue(${m})`,g=t>1?"strides[j]":"strides";this.userCode=`
| ${l} strides = ${l}(${r});
|
| void main() {
| ${u} coords = getOutputCoords();
| float sum = 0.0;
| bool found = false;
| for (int i = 0; i < ${e}; i++) {
| int flattenedIndex = 0;
| for (int j = 0; j < ${t}; j++) {
| int index = round(${d});
| flattenedIndex += index * ${g};
| }
| if (flattenedIndex == coords[0]) {
| sum += ${h};
| found = true;
| }
| }
| setOutput(mix(${f}, sum, float(found)));
| }
| `}},Mie=class{constructor(e,t,n,a,r,s,i=!0,o=!1){this.variableNames=["updates","indices","defaultValue"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=s;let l=dt(r.length),u=dt(s.length),p="";n===1?p="i":n===2&&(p="i, j");let d=`getIndices(${p})`,c="";a===1?c="i":a===2&&(c="i, coords[1]");let h=`getUpdates(${c})`,m="";o&&(m="coords[0], coords[1]");let f=`getDefaultValue(${m})`,g=t>1?"strides[j]":"strides",b=t>1?"strides[j + 1]":"strides";this.userCode=`
| ${l} strides = ${l}(${r});
|
| void main() {
| ${u} coords = getOutputCoords();
| vec4 sum = vec4(0.);
| vec4 found = vec4(0.);
| for (int i = 0; i < ${e}; i+=2) {
| ivec2 flattenedIndex = ivec2(0);
| for (int j = 0; j < ${t}; j+=2) {
| ivec4 index = round(${d});
| flattenedIndex += index.xz * ${g};
| if (j + 1 < ${t}) {
| flattenedIndex += index.yw * ${b};
| }
| }
| if (flattenedIndex[0] == coords[0] || flattenedIndex[1] == coords[0] ||
| flattenedIndex[0] == coords[0] + 1 || flattenedIndex[1] == coords[0] + 1) {
| vec4 updVals = ${h};
| if (flattenedIndex[0] == coords[0]) {
| sum.xy += updVals.xy;
| found.xy = vec2(1.);
| } else if (flattenedIndex[0] == coords[0] + 1) {
| sum.zw += updVals.xy;
| found.zw = vec2(1.);
| }
| if (flattenedIndex[1] == coords[0]) {
| sum.xy += updVals.zw;
| found.xy = vec2(1.);
| } else if (flattenedIndex[1] == coords[0] + 1) {
| sum.zw += updVals.zw;
| found.zw = vec2(1.);
| }
| }
| }
| setOutput(mix(${f}, sum, found));
| }
| `}};function Pie(e){let{inputs:t,backend:n,attrs:a}=e,{indices:r,updates:s}=t,{shape:i}=a,{sliceRank:o,numUpdates:l,sliceSize:u,strides:p,outputSize:d}=N.calculateShapes(s,r,i),c=[d/u,u];if(d===0)return n.makeTensorInfo(i,r.dtype);let h=ce({inputs:{x:r},backend:n,attrs:{shape:[l,o]}}),m=ce({inputs:{x:s},backend:n,attrs:{shape:[l,u]}}),f=n.makeTensorInfo([],"float32",new Float32Array([0])),g;G().getBool("WEBGL_PACK")?g=new Mie(l,o,h.shape.length,m.shape.length,p,c):g=new dk(l,o,h.shape.length,m.shape.length,p,c);let b=n.runWebGLProgram(g,[m,h,f],m.dtype),y=ce({inputs:{x:b},backend:n,attrs:{shape:i}});return n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(b),n.disposeIntermediateTensorInfo(f),y}var Oie={kernelName:Xu,backendName:"webgl",kernelFunc:Pie},Lie=class{constructor(e,t,n,a){this.variableNames=["sortedSequence","values"],this.customUniforms=[{name:"numInputs",type:"int"}],this.outputShape=[e,n];let r="while (left < right) {",s=`for (int i = 0; i < ${Math.ceil(Math.log2(t+1))}; ++i) { if (left >= right) break;`,i=G().getNumber("WEBGL_VERSION")===2?r:s,o=a==="left"?"<":"<=";this.userCode=`
| int findBound(int batch, float value) {
| int left = 0;
| int right = numInputs;
| int mid;
| ${i}
| mid = (left + right) / 2;
| if (getSortedSequence(batch, mid) ${o} value) {
| left = mid + 1;
| } else {
| right = mid;
| }
| }
| return right;
| }
|
| void main() {
| ivec2 coords = getOutputCoords();
| int batch = coords[0];
| int valueIndex = coords[1];
|
| float value = getValues(batch, valueIndex);
|
| setOutput(float(findBound(batch, value)));
| }
| `}};function zie(e){let{inputs:t,backend:n,attrs:a}=e,{sortedSequence:r,values:s}=t,{side:i}=a,o=new Lie(r.shape[0],r.shape[1],s.shape[1],i),l=[[r.shape[1]]];return n.runWebGLProgram(o,[r,s],"int32",l)}var Wie={kernelName:Zu,backendName:"webgl",kernelFunc:zie},Bie=class{constructor(e,t,n){this.variableNames=["c","a","b"],this.outputShape=t;let a,r;if(n>4)throw Error(`Where for rank ${n} is not yet supported`);if(n===1)r="resRC",a="resRC";else{let i=["resRC.x","resRC.y","resRC.z","resRC.w"],o=[],l=[];for(let u=0;u<t.length;u++)l.push(`${i[u]}`),u<e&&o.push(`${i[u]}`);a=o.join(),r=l.join()}let s=dt(n);this.userCode=`
| void main() {
| ${s} resRC = getOutputCoords();
| float cVal = getC(${a});
| if (cVal >= 1.0) {
| setOutput(getA(${r}));
| } else {
| setOutput(getB(${r}));
| }
| }
| `}};function Vie(e){let{inputs:t,backend:n}=e,{condition:a,t:r,e:s}=t,i=new Bie(a.shape.length,r.shape,r.shape.length);return n.runWebGLProgram(i,[a,r,s],ba(r.dtype,s.dtype))}var Uie={kernelName:Ju,backendName:"webgl",kernelFunc:Vie},Gie=`
| // Stable and Attracting Fixed Point (0, 1) for Normalized Weights.
| // see: https://arxiv.org/abs/1706.02515
| float scaleAlpha = ${N.SELU_SCALEALPHA};
| float scale = ${N.SELU_SCALE};
| return (x >= 0.0) ? scale * x : scaleAlpha * (exp(x) - 1.0);
| `,Hie=Ze({opSnippet:Gie}),qie={kernelName:$o,backendName:"webgl",kernelFunc:Hie},jie=Tp+`
| return 1.0 / (1.0 + exp(-1.0 * x));
| `,Kie=`
| vec4 result = 1.0 / (1.0 + exp(-1.0 * x));
| bvec4 isNaN = isnan(x);
|
| result.r = isNaN.r ? x.r : result.r;
| result.g = isNaN.g ? x.g : result.g;
| result.b = isNaN.b ? x.b : result.b;
| result.a = isNaN.a ? x.a : result.a;
|
| return result;
| `,Xie=Ze({opSnippet:jie,packedOpSnippet:Kie,cpuKernelImpl:q9}),Yie={kernelName:Po,backendName:"webgl",kernelFunc:Xie},Zie=`
| if (isnan(x)) { return 0.0; }
| return sign(x);
| `,Jie=Ze({opSnippet:Zie}),Qie={kernelName:Mo,backendName:"webgl",kernelFunc:Jie},eoe=Tp+`
| return sin(x);
| `,toe=`
| vec4 result = sin(x);
| bvec4 isNaN = isnan(x);
| ${el}
| return result;
| `,noe=Ze({opSnippet:eoe,packedOpSnippet:toe}),aoe={kernelName:Do,backendName:"webgl",kernelFunc:noe},roe=`
| float e2x = exp(x);
| return (e2x - 1.0 / e2x) / 2.0;
| `,soe=Ze({opSnippet:roe}),ioe={kernelName:Ro,backendName:"webgl",kernelFunc:soe},ooe=`
| 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;
| `,loe=Ze({opSnippet:ooe}),uoe={kernelName:Oo,backendName:"webgl",kernelFunc:loe},poe=e=>{let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{blockShape:s,paddings:i}=a;w.assert(r.shape.length<=4,()=>"spaceToBatchND for rank > 4 with a WebGL backend not implemented yet");let o=s.reduce((b,y)=>b*y),l=[[0,0]];l.push(...i);for(let b=1+s.length;b<r.shape.length;++b)l.push([0,0]);let u=[],p=YA({inputs:{x:r},backend:n,attrs:{paddings:l,constantValue:0}}),d=N.getReshaped(p.shape,s,o,!1),c=N.getPermuted(d.length,s.length,!1),h=N.getReshapedPermuted(p.shape,s,o,!1),m=ce({inputs:{x:p},backend:n,attrs:{shape:d}}),f=Nn({inputs:{x:m},backend:n,attrs:{perm:c}}),g=ce({inputs:{x:f},backend:n,attrs:{shape:h}});return u.push(p),u.push(m),u.push(f),u.forEach(b=>n.disposeIntermediateTensorInfo(b)),g},coe={kernelName:ep,backendName:"webgl",kernelFunc:poe};function doe(e){let{inputs:t,backend:n}=e,{indices:a,values:r,denseShape:s,defaultValue:i}=t;if(s.shape.length!==1)throw new Error(`Dense shape must be a vector, saw:
| ${s.shape}`);if(a.shape.length!==2)throw new Error(`Indices must be a matrix, saw:
| ${a.shape}`);if(r.shape.length!==1)throw new Error(`Values must be a vector, saw:
| ${r.shape}`);if(i.shape.length!==0)throw new Error(`Default value must be a scalar, saw:
| ${i.shape}`);let o=n.readSync(a.dataId),l=n.readSync(r.dataId),u=n.readSync(s.dataId),p=n.readSync(i.dataId)[0],[d,c,h,m,f]=K9(o,a.shape,a.dtype,l,r.dtype,u,p);return[n.makeTensorInfo(c,a.dtype,d),n.makeTensorInfo([c[0]],r.dtype,h),n.makeTensorInfo([m.length],"bool",new Uint8Array(m.map(g=>Number(g)))),n.makeTensorInfo([f.length],a.dtype,new Int32Array(f))]}var hoe={kernelName:Kc,backendName:"webgl",kernelFunc:doe};function moe(e){let{inputs:t,backend:n}=e,{inputIndices:a,inputShape:r,newShape:s}=t;if(a.shape.length!==2)throw new Error(`Input indices should be a matrix but received shape ${a.shape}`);if(r.shape.length!==1)throw new Error(`Input shape should be a vector but received shape ${r.shape}`);if(s.shape.length!==1)throw new Error(`Target shape should be a vector but received shape ${s.shape}`);let i=Array.from(n.readSync(r.dataId)),o=n.readSync(a.dataId),l=Array.from(n.readSync(s.dataId)),[u,p,d]=X9(o,a.shape,a.dtype,i,l);return[n.makeTensorInfo(p,a.dtype,u),n.makeTensorInfo([d.length],s.dtype,new Int32Array(d))]}var foe={kernelName:np,backendName:"webgl",kernelFunc:moe};function goe(e){let{inputs:t,backend:n}=e,{data:a,indices:r,segmentIds:s}=t;if(a.shape.length<1)throw new Error("Data should be at least 1 dimensional but received scalar");if(r.shape.length!==1)throw new Error(`Indices should be a vector but received shape
| ${r.shape}`);if(s.shape.length!==1)throw new Error(`Segment ids should be a vector but received shape
| ${s.shape}`);let i=n.readSync(a.dataId),o=n.readSync(r.dataId),l=n.readSync(s.dataId),[u,p]=vA(i,a.shape,a.dtype,o,l,!0);return n.makeTensorInfo(p,a.dtype,u)}var boe={kernelName:Xc,backendName:"webgl",kernelFunc:goe};function yoe(e){let{inputs:t,backend:n}=e,{data:a,indices:r,segmentIds:s}=t;if(a.shape.length<1)throw new Error("Data should be at least 1 dimensional but received scalar");if(r.shape.length!==1)throw new Error(`Indices should be a vector but received shape
| ${r.shape}`);if(s.shape.length!==1)throw new Error(`Segment ids should be a vector but received shape
| ${s.shape}`);let i=n.readSync(a.dataId),o=n.readSync(r.dataId),l=n.readSync(s.dataId),[u,p]=vA(i,a.shape,a.dtype,o,l);return n.makeTensorInfo(p,a.dtype,u)}var xoe={kernelName:Yc,backendName:"webgl",kernelFunc:yoe};function voe(e){let{inputs:t,backend:n,attrs:a}=e,{sparseIndices:r,sparseValues:s,defaultValue:i}=t,{outputShape:o}=a,{sliceRank:l,numUpdates:u,sliceSize:p,strides:d,outputSize:c}=N.calculateShapes(s,r,o),h=!1;if(s.dtype==="string"){let b=n.bufferSync(r),y=n.bufferSync(s),x=w.decodeString(n.readSync(i.dataId)[0]),v=H9(b,y,o,c,p,u,l,d,x,h);return n.makeTensorInfo(o,v.dtype,v.values)}let m=new dk(u,l,r.shape.length,s.shape.length,d,[c,1],h),f=n.runWebGLProgram(m,[s,r,i],s.dtype),g=ce({inputs:{x:f},backend:n,attrs:{shape:o}});return n.disposeIntermediateTensorInfo(f),g}var woe={kernelName:ap,backendName:"webgl",kernelFunc:voe};function koe(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{numOrSizeSplits:s,axis:i}=a,o=w.parseAxisParam(i,r.shape)[0],l=N.prepareSplitSize(r,s,o),u=r.shape.length,p=new Array(u).fill(0),d=r.shape.slice();return l.map(c=>{let h=[...d];h[o]=c;let m=Cp({inputs:{x:r},backend:n,attrs:{begin:p,size:h}});return p[o]+=c,m})}var Ioe={kernelName:tp,backendName:"webgl",kernelFunc:koe},MS="return sqrt(x);",Soe=Ze({opSnippet:MS,packedOpSnippet:MS,cpuKernelImpl:Y9}),Noe={kernelName:Lo,backendName:"webgl",kernelFunc:Soe},Toe="return x * x;",Coe=Ze({opSnippet:Toe}),_oe={kernelName:Zc,backendName:"webgl",kernelFunc:Coe},PS="return (a - b) * (a - b);",Eoe=fn({opSnippet:PS,packedOpSnippet:PS}),Aoe={kernelName:Bo,backendName:"webgl",kernelFunc:Eoe};function Foe(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t;if(r.dtype!=="string")throw new Error("Input must be of datatype string");let s=n.readSync(r.dataId),i=N.fromUint8ToStringArray(s),o=Z9(i,"string",a);return n.makeTensorInfo(r.shape,"string",o)}var $oe={kernelName:Jc,backendName:"webgl",kernelFunc:Foe};function Doe({inputs:e,attrs:t,backend:n}){let{x:a}=e,r=Oa+`
| return x > 0.0 ? 1.0 : float(${t.alpha});
| `,s=new ir(a.shape,r);return n.runWebGLProgram(s,[a],a.dtype)}var Roe={kernelName:Ts,backendName:"webgl",kernelFunc:Doe},Moe=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=n;let a=n.length,r=dt(n.length),s=dt(n.length),i="";if(a===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=`
| ${r} begin = ${r}(${e});
| ${r} strides = ${r}(${t});
|
| void main() {
| ${s} coords = getOutputCoords();
| setOutput(getX(${i}));
| }
| `}};function Poe(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{begin:s,end:i,strides:o,beginMask:l,endMask:u,ellipsisMask:p,newAxisMask:d,shrinkAxisMask:c}=a,{finalShapeSparse:h,finalShape:m,isIdentity:f,sliceDim0:g,isSimpleSlice:b,begin:y,end:x,strides:v}=Xt.sliceInfo(r.shape,s,i,o,l,u,p,d,c),I;if(f)I=ce({inputs:{x:r},backend:n,attrs:{shape:m}});else if(g||b){w.assert(r.shape.length>=1,()=>`Input must have rank at least 1, got: ${r.shape.length}`);let C=Xt.computeOutShape(y,x,v),E=Cp({inputs:{x:r},backend:n,attrs:{begin:y,size:C}});I=ce({inputs:{x:E},backend:n,attrs:{shape:m}}),n.disposeIntermediateTensorInfo(E)}else if(n.shouldExecuteOnCPU([r])){let C=n.readSync(r.dataId),E=ze(r.shape,r.dtype,C),F=J9(h,E,v,y);I=n.makeTensorInfo(m,r.dtype,F.values)}else{let C=new Moe(y,v,h);I=n.runWebGLProgram(C,[r],r.dtype)}let T=ce({inputs:{x:I},backend:n,attrs:{shape:m}});return n.disposeIntermediateTensorInfo(I),T}var Ooe={kernelName:rp,backendName:"webgl",kernelFunc:Poe};function Loe(e){let{inputs:t,backend:n,attrs:a}=e,{separator:r,nGramWidths:s,leftPad:i,rightPad:o,padWidth:l,preserveShortSequences:u}=a,{data:p,dataSplits:d}=t,c=n.readSync(p.dataId),h=n.readSync(d.dataId),[m,f]=Q9(c,h,r,s,i,o,l,u);return[n.makeTensorInfo([m.length],"string",m),n.makeTensorInfo(d.shape,"int32",f)]}var zoe={kernelName:Qc,backendName:"webgl",kernelFunc:Loe};function Woe(e){let{inputs:t,backend:n,attrs:a}=e,{skipEmpty:r}=a,{input:s,delimiter:i}=t;if(s.dtype!=="string")throw new Error("Input must be of datatype string");if(s.shape.length!==1)throw new Error(`Input must be a vector, got shape: ${s.shape}`);if(i.shape.length!==0)throw new Error(`Delimiter must be a scalar, got shape: ${i.shape}`);let o=n.readSync(s.dataId),l=n.readSync(i.dataId)[0],[u,p,d]=eQ(o,l,r),c=p.length;return[n.makeTensorInfo([c,2],"int32",u),n.makeTensorInfo([c],"string",p),n.makeTensorInfo([2],"int32",new Int32Array(d))]}var Boe={kernelName:ed,backendName:"webgl",kernelFunc:Woe};function Voe(e){let{inputs:t,backend:n,attrs:a}=e,{numBuckets:r}=a,{input:s}=t;if(s.dtype!=="string")throw new Error("Input must be of datatype string");if(r<=0)throw new Error("Number of buckets must be at least 1");let i=n.readSync(s.dataId),o=tQ(i,r);return n.makeTensorInfo(s.shape,"int32",o)}var Uoe={kernelName:td,backendName:"webgl",kernelFunc:Voe},Goe="return tan(x);",Hoe=Ze({opSnippet:Goe}),qoe={kernelName:Uo,backendName:"webgl",kernelFunc:Hoe},joe=`
| float e2x = exp(-2.0 * abs(x));
| return sign(x) * (1.0 - e2x) / (1.0 + e2x);
| `,Koe=Ze({opSnippet:joe}),Xoe={kernelName:Go,backendName:"webgl",kernelFunc:Koe};function Yoe(e){let{inputs:t,backend:n,attrs:a}=e,{tensor:r,indices:s,updates:i}=t,{}=a,{sliceRank:o,numUpdates:l,sliceSize:u,strides:p,outputSize:d}=N.calculateShapes(i,s,r.shape),c=[d/u,u];if(d===0)return n.makeTensorInfo(r.shape,s.dtype);let h=ce({inputs:{x:s},backend:n,attrs:{shape:[l,o]}}),m=ce({inputs:{x:i},backend:n,attrs:{shape:[l,u]}}),f=ce({inputs:{x:r},backend:n,attrs:{shape:c}}),g=new dk(l,o,h.shape.length,m.shape.length,p,c,!1,!0),b=n.runWebGLProgram(g,[m,h,f],f.dtype),y=ce({inputs:{x:b},backend:n,attrs:{shape:r.shape}});return n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(f),n.disposeIntermediateTensorInfo(b),y}var Zoe={kernelName:Yu,backendName:"webgl",kernelFunc:Yoe},Joe=class{constructor(e,t){this.variableNames=["A"];let n=new Array(e.length);for(let s=0;s<n.length;s++)n[s]=e[s]*t[s];this.outputShape=n,this.rank=n.length;let a=dt(this.rank),r=Qoe(e);this.userCode=`
| void main() {
| ${a} resRC = getOutputCoords();
| setOutput(getA(${r}));
| }
| `}};function Qoe(e){let t=e.length;if(t>5)throw Error(`Tile for rank ${t} is not yet supported`);if(t===1)return`imod(resRC, ${e[0]})`;let n=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u"],a=[];for(let r=0;r<e.length;r++)a.push(`imod(${n[r]}, ${e[r]})`);return a.join()}function JA(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{reps:s}=a;if(r.dtype==="string"||r.shape.length>5){let o=n.readSync(r.dataId),l=r.dtype==="string"?o.map(d=>w.decodeString(d)):o,u=ze(r.shape,r.dtype,l),p=aQ(u,s);return n.makeTensorInfo(p.shape,p.dtype,p.values)}let i=new Joe(r.shape,s);return n.runWebGLProgram(i,[r],r.dtype)}var ele={kernelName:Ns,backendName:"webgl",kernelFunc:JA},tle=class{constructor(e){this.variableNames=["x","indices"],this.customUniforms=[{name:"n",type:"int"},{name:"firstPass",type:"int"},{name:"negativeInf",type:"float"},{name:"dir",type:"int"},{name:"inc",type:"int"}],this.outputShape=e,this.userCode=`
| void main() {
| ivec2 coords = getOutputCoords();
| int batch = coords[0];
| int elemIdx = coords[1];
|
| // We compare elements pair-wise within a group of size 2 * inc.
| // The comparing rule for each group alternates between ascending
| // and descending. Within each group, we compare each pair at
| // positions i and i+inc. To decide whether an element at position i
| // is x0 or x1, we mod it by 2 * inc, if the result is smaller than
| // inc, it is in the first half of the group, we denote it as x0,
| // otherwise we denote it as x1.
| // For example, as shown in the Bitonic top K paper referenced above,
| // Figure5(a) shows that element[1] is in the
| // second half of the group when group size is 2, but it is in the
| // first half of the group when group size is 4.
|
| bool isFirstInPair = imod(elemIdx, 2 * inc) < inc;
| int i = isFirstInPair ? elemIdx : elemIdx - inc;
|
| int i0 = firstPass == 1 ? i : int(getIndices(batch, i));
| int i1 = firstPass == 1 ? i + inc : int(getIndices(batch, i + inc));
| float x0 = i0 < n ? getX(batch, i0) : negativeInf;
| float x1 = i1 < n ? getX(batch, i1) : negativeInf;
|
| // Denotes which direction indices are in (ascending or descending).
| bool reverse = imod(elemIdx, 2 * dir) >= dir;
| bool isGreater = x0 > x1 || (x0 == x1 && i1 > i0);
| if (reverse == isGreater) { // Elements in opposite order of direction
| int iTemp = i0;
| i0 = i1;
| i1 = iTemp;
| }
| if (isFirstInPair) {
| setOutput(float(i0));
| } else {
| setOutput(float(i1));
| }
| }
| `}},nle=class{constructor(e){this.variableNames=["x","indices"],this.customUniforms=[{name:"n",type:"int"},{name:"firstPass",type:"int"},{name:"k",type:"int"}],this.outputShape=e,this.userCode=`
| void main() {
| // Takes max of indices (0, k), (1, k + 1), (2, k + 2) ...
| ivec2 coords = getOutputCoords();
| int batch = coords[0];
| int elemIdx = coords[1];
|
| // The output size is half of the previous size.
| // If the previous sequence is | | | | _ _ _ _ | | | | _ _ _ _ (k=4),
| // we only need to output the indices at positions |, the indices at
| // positions _ can be thrown away, see Figure5(b) After Phase 2
| // (Merge phase) in the Bitonic Top K paper referenced above.
| // For example, the paper shows we only need to output the orange bars.
| // The output sequence should look like this | | | | | | | |.
| // Because the sequence is halved, to map the output index back
| // to the previous sequence to find the corresponding value,
| // we need to double the index. When we double the index,
| // we basically interpolate a position, so 2i looks like
| // | _ | _ | _ | _ | _ | _ | _. We move the | to the first k position
| // of each 2k positions by - elemIdx % k. E.g. for output at
| // index 4,5,6,7, we want to get the corresponding element at
| // original index 8,9,10,11, for output at index 8,9,10,11,
| // we want to get the corresponding element at original index
| // 16,17,18,19, so on and so forth.
|
| int i = elemIdx < k ? elemIdx : (elemIdx * 2 - imod(elemIdx, k));
| int i0 = firstPass == 1 ? i : int(getIndices(batch, i));
| int i1 = firstPass == 1 ? i + k : int(getIndices(batch, i + k));
|
| float x0 = getX(batch, i0);
| float x1 = i1 < n ? getX(batch, i1) : x0;
|
| setOutput(x0 >= x1 ? float(i0) : float(i1));
| }
| `}};function js(e,t){t!==null&&e.disposeIntermediateTensorInfo(t)}function OS(e){let t=1;for(;t<e;)t*=2;return t}function ale(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{k:s,sorted:i}=a,o=G().getNumber("TOPK_LAST_DIM_CPU_HANDOFF_SIZE_THRESHOLD"),l=G().getNumber("TOPK_K_CPU_HANDOFF_THRESHOLD"),u=r.shape,p=u[u.length-1];if(n.shouldExecuteOnCPU([r])||p<o||s>l){let F=n.readSync(r.dataId),[D,$]=rQ(F,u,r.dtype,s,i);return[n.makeTensorInfo(D.shape,D.dtype,D.values),n.makeTensorInfo($.shape,$.dtype,$.values)]}if(s===0)return u[u.length-1]=0,[n.makeTensorInfo(u,r.dtype,[]),n.makeTensorInfo(u,"int32",[])];if(p===1)return[r,Ld({attrs:{shape:u,dtype:"int32",value:0},backend:n})];let d=n.texData.get(r.dataId),c=d!==null&&d.isPacked,h=c?n.unpackTensor(r):r,m=w.sizeFromShape(u)/p,f=ce({inputs:{x:h},attrs:{shape:[m,p]},backend:n});c&&js(n,h);let g=OS(s),b=OS(p),y=null,x=()=>y===null?[f,f]:[f,y],v=(F,D,$)=>{let S=x(),M=new tle($),B=[[p],[y===null?1:0],[Number.NEGATIVE_INFINITY],[F],[D]],U=y;y=n.runWebGLProgram(M,S,"int32",B),js(n,U)};for(let F=1;F<g;F*=2){let D=F*2;for(let $=F;$>=1;$/=2)v(D,$,[m,b])}for(let F=b;F>g;F/=2){let D=x(),$=new nle([m,F/2]),S=[[p],[y===null?1:0],[g]],M=y;y=n.runWebGLProgram($,D,"int32",S),js(n,M);let B=g/2,U=B*2;for(let H=B;H>=1;H/=2)v(U,H,y.shape)}let I=y;y=Cp({inputs:{x:y},backend:n,attrs:{begin:0,size:[m,s]}}),js(n,I);let T=GA({inputs:{x:f,indices:y},backend:n,attrs:{axis:1,batchDims:1}});js(n,f);let C=u.slice(0,-1);C.push(s),I=y,y=ce({inputs:{x:y},attrs:{shape:C},backend:n}),js(n,I);let E=T;return T=ce({inputs:{x:T},attrs:{shape:C},backend:n}),js(n,E),[T,y]}var rle={kernelName:sp,backendName:"webgl",kernelFunc:ale},sle=class{constructor(e,t,n,a,r,s){this.variableNames=["Image","Transforms"],this.outputShape=s;let i=n==="nearest"?1:2,o;switch(a){case"constant":o=1;break;case"reflect":o=2;break;case"wrap":o=3;break;case"nearest":o=4;break;default:o=1;break}this.userCode=`
| float mapCoord(float outCoord, float len) {
| float inCoord = outCoord;
| if(${o} == 2) {
| if (inCoord < 0.0) {
| if (len <= 1.0) {
| inCoord = 0.0;
| } else {
| float sz2 = 2.0 * len;
| if (inCoord < sz2) {
| inCoord = sz2 * float(int(float(-inCoord / sz2))) +
| inCoord;
| }
| inCoord = inCoord < -len ? inCoord + sz2 : -inCoord - 1.0;
| }
| } else if (inCoord > len - 1.0) {
| if (len <= 1.0) {
| inCoord = 0.0;
| } else {
| float sz2 = 2.0 * len;
| inCoord -= sz2 * float(int(float(inCoord / sz2)));
| if (inCoord >= len) {
| inCoord = sz2 - inCoord - 1.0;
| }
| }
| }
| return clamp(inCoord, 0.0, len - 1.0);
| } else if (${o} == 3) {
| if (inCoord < 0.0) {
| if (len <= 1.0) {
| inCoord = 0.0;
| } else {
| float sz = len - 1.0;
| inCoord += len * (float(int(float(-inCoord / sz))) + 1.0);
| }
| } else if (inCoord > len - 1.0) {
| if (len <= 1.0) {
| inCoord = 0.0;
| } else {
| float sz = len - 1.0;
| inCoord -= len * float(int(float(inCoord / sz)));
| }
| }
| return clamp(inCoord, 0.0, len - 1.0);
| } else if (${o} == 4) {
| return clamp(outCoord, 0.0, len - 1.0);
| } else {
| return outCoord;
| }
| }
|
| float readWithFillValue(int batch, int coordY, int coordX,
| int channel) {
| float outputValue;
| if (0 <= coordY && coordY < ${e} && 0 <= coordX && coordX < ${t}) {
| outputValue = getImage(batch, coordY, coordX, channel);
| } else {
| outputValue = float(${r});
| }
| return outputValue;
| }
|
| void main() {
| ivec4 coords = getOutputCoords();
| float outputValue;
| int batch = coords[0];
| int x = coords[2];
| int y = coords[1];
| int channel = coords[3];
| float xf = float(x);
| float yf = float(y);
| float a1 = getTransforms(batch, 0);
| float a2 = getTransforms(batch, 1);
| float a3 = getTransforms(batch, 2);
| float b1 = getTransforms(batch, 3);
| float b2 = getTransforms(batch, 4);
| float b3 = getTransforms(batch, 5);
| float c1 = getTransforms(batch, 6);
| float c2 = getTransforms(batch, 7);
| float projection = c1 * xf + c2 * yf + 1.0;
| if (projection == 0.0) {
| outputValue = float(${r});
| } else {
| float inX = (a1 * xf + a2 * yf + a3) / projection;
| float inY = (b1 * xf + b2 * yf + b3) / projection;
| float mapX = mapCoord(inX, float(${t}));
| float mapY = mapCoord(inY, float(${e}));
|
| if (${i} == 1) {
| int coordY = int(round(mapY));
| int coordX = int(round(mapX));
| outputValue = readWithFillValue(batch, coordY, coordX,
| channel);
| } else {
| float yFloor = floor(mapY);
| float xFloor = floor(mapX);
| float yCeil = yFloor + 1.0;
| float xCeil = xFloor + 1.0;
| float valueYFloor = (xCeil - mapX) *
| readWithFillValue(batch, int(yFloor), int(xFloor), channel) +
| (mapX - xFloor) *
| readWithFillValue(batch, int(yFloor), int(xCeil), channel);
| float valueYCeil = (xCeil - mapX) *
| readWithFillValue(batch, int(yCeil), int(xFloor), channel) +
| (mapX - xFloor) *
| readWithFillValue(batch, int(yCeil), int(xCeil), channel);
| outputValue = (yCeil - mapY) * valueYFloor +
| (mapY - yFloor) * valueYCeil;
| }
| }
| setOutput(outputValue);
| }
| `}};function ile(e){let{inputs:t,backend:n,attrs:a}=e,{image:r,transforms:s}=t,{interpolation:i,fillMode:o,fillValue:l,outputShape:u}=a,[p,d,c,h]=r.shape,[m,f]=u!=null?u:[d,c],g=[p,m,f,h],b=new sle(d,c,i,o,l,g);return n.runWebGLProgram(b,[r,s],"float32")}var ole={kernelName:ip,backendName:"webgl",kernelFunc:ile};function lle(e){let{inputs:t,attrs:n,backend:a}=e,{axis:r}=n,{x:s}=t;vp(s,"unique"),console.warn("WARNING: ","UI might be locked temporarily as data is being downloaded");let i=a.readSync(s.dataId),{outputValues:o,outputShape:l,indices:u}=sQ(i,r,s.shape,s.dtype);return[a.makeTensorInfo(l,s.dtype,o),a.makeTensorInfo([u.length],"int32",u)]}var ule={kernelName:nd,backendName:"webgl",kernelFunc:lle};function ple(e){let{inputs:t,backend:n,attrs:a}=e,{value:r}=t,{axis:s}=a;s<0&&(s+=r.shape.length);let i=r,o=i.shape.length,l=r.shape[s],u=new Array(o-1),p=0;for(let f=0;f<o;f++)f!==s&&(u[p++]=i.shape[f]);let d=[],c=new Array(o).fill(0),h=i.shape.slice();h[s]=1;let m=new Array(l);for(let f=0;f<m.length;f++){c[s]=f;let g=Cp({inputs:{x:i},backend:n,attrs:{begin:c,size:h}}),b=ce({inputs:{x:g},backend:n,attrs:{shape:u}});m[f]=b,d.push(g)}return d.forEach(f=>n.disposeIntermediateTensorInfo(f)),m}var cle={kernelName:op,backendName:"webgl",kernelFunc:ple},dle=class{constructor(e,t){this.variableNames=["x","segmentIds"];let n=e.windowSize,a=e.batchSize,r=e.inSize,s=e.numSegments,i=s*Math.ceil(r/n);this.outputShape=[a,i];let o="0.0",l="sumValue",u=Math.floor(n/4)*4,p=n%4,d=`
| sumValue += dot(values, segFilter);
| `,c="";r%n>0&&(c=`
| if (inIdx < 0 || inIdx >= ${r}) {
| return initializationValue;
| }
| `);let h="";r%n>0&&(h=`
| if (inIdx < 0 || inIdx >= ${r}) {
| return -1.0;
| }
| `),this.userCode=`
| const float initializationValue = ${o};
|
| float getValue(int batch, int inIdx) {
| ${c}
| return getX(batch, inIdx);
| }
|
| float getSegmentIdAtIndex(int inIdx) {
| ${h}
| return getSegmentIds(inIdx);
| }
|
| void main() {
| ivec2 coords = getOutputCoords();
| int batch = coords[0];
| int outIdx = coords[1];
| int inOffset = int(floor(float(outIdx) / float(
| ${s})) * float(${n}));
| int currentSeg = int(mod(float(outIdx), float(${s})));
|
| float sumValue = 0.0;
|
| for (int i = 0; i < ${u}; i += 4) {
| int inIdx = inOffset + i;
| vec4 values = vec4(
| getValue(batch, inIdx),
| getValue(batch, inIdx + 1),
| getValue(batch, inIdx + 2),
| getValue(batch, inIdx + 3)
| );
|
| vec4 segFilter = vec4(
| int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,
| int(getSegmentIdAtIndex(inIdx + 1)) == currentSeg ? 1 : 0,
| int(getSegmentIdAtIndex(inIdx + 2)) == currentSeg ? 1 : 0,
| int(getSegmentIdAtIndex(inIdx + 3)) == currentSeg ? 1 : 0
| );
|
| ${d}
| }
|
| int inIdx = inOffset + ${u};
| if (${p===1}) {
| vec4 values = vec4(
| getValue(batch, inIdx),
| initializationValue,
| initializationValue,
| initializationValue
| );
|
| int inIdxSeg = int(getSegmentIdAtIndex(inIdx));
|
| vec4 segFilter = vec4(
| int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,
| 0,
| 0,
| 0
| );
|
| ${d}
| } else if (${p===2}) {
| vec4 values = vec4(
| getValue(batch, inIdx),
| getValue(batch, inIdx + 1),
| initializationValue,
| initializationValue
| );
|
| vec4 segFilter = vec4(
| int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,
| int(getSegmentIdAtIndex(inIdx + 1)) == currentSeg ? 1 : 0,
| 0,
| 0
| );
|
| ${d}
| } else if (${p===3}) {
| vec4 values = vec4(
| getValue(batch, inIdx),
| getValue(batch, inIdx + 1),
| getValue(batch, inIdx + 2),
| initializationValue
| );
|
| vec4 segFilter = vec4(
| int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,
| int(getSegmentIdAtIndex(inIdx + 1)) == currentSeg ? 1 : 0,
| int(getSegmentIdAtIndex(inIdx + 2)) == currentSeg ? 1 : 0,
| 0
| );
|
| ${d}
| }
| setOutput(${l});
| }
| `}};function hle(e){let{inputs:t,backend:n,attrs:a}=e,{x:r,segmentIds:s}=t,{numSegments:i}=a,o=r.shape.length,l=[],u=0,p=N.getAxesPermutation([u],o),d=r;p!=null&&(d=Nn({inputs:{x:r},backend:n,attrs:{perm:p}}),l.push(d),u=N.getInnerMostAxes(1,o)[0]);let c=N.segment_util.computeOutShape(d.shape,u,i),h=w.sizeFromShape([d.shape[u]]),m=ce({inputs:{x:d},backend:n,attrs:{shape:[-1,h]}});l.push(m);let f=Ym(r.dtype),g=(v,I,T,C,E)=>{let F=v.shape[0],D=v.shape[1],$=N.segment_util.segOpComputeOptimalWindowSize(D,E),S={windowSize:$,inSize:D,batchSize:F,numSegments:E},M=new dle(S,I),B=n.compileAndRun(M,[v,T],C);if(l.push(B),B.shape[1]===E)return B;let U=ZA({backend:n,attrs:{start:0,stop:E,step:1,dtype:"float32"}}),H=JA({inputs:{x:U},backend:n,attrs:{reps:[D/$]}});return l.push(U),l.push(H),g(B,I,H,C,E)},b=g(m,"unsortedSegmentSum",s,f,i),y=ce({inputs:{x:b},backend:n,attrs:{shape:c}}),x=y;if(p!=null){l.push(y);let v=N.getUndoAxesPermutation(p);x=Nn({inputs:{x},backend:n,attrs:{perm:v}})}return l.forEach(v=>n.disposeIntermediateTensorInfo(v)),x}var mle={kernelName:ad,backendName:"webgl",kernelFunc:hle},fle=[JQ,eee,aee,iee,lee,cee,hee,fee,xee,wee,See,Cee,Aee,Ree,Oee,zee,Bee,Hee,jee,Xee,Qee,ite,lte,dte,mte,vte,kte,Tte,MQ,Ete,Rte,Lte,Gte,jte,Xte,Zte,Qte,ane,ine,une,cne,hne,fne,yne,vne,Sne,Tne,Ene,$ne,Rne,Lne,Vne,qne,Xne,Jne,Qne,tae,aae,sae,oae,uae,hae,gae,xae,wae,Sae,Cae,Fae,Mae,RQ,Oae,$te,Wae,Uae,qae,OQ,Yae,ere,nre,ire,ure,hre,gre,vre,Sre,Cre,Ere,Dre,Mre,Ore,Bre,Ure,Hre,jre,Xre,Qre,ase,ose,fse,WQ,xse,kse,Nse,_se,gte,Fse,Dse,Mse,Lse,Vse,zQ,Gse,qse,Kse,Yse,Zse,bte,cse,eie,rie,lie,VQ,die,fie,xie,kie,Tie,_ie,Fie,Rie,Oie,Wie,Uie,qie,Yie,Qie,aoe,ioe,rte,hse,uoe,coe,hoe,foe,boe,xoe,woe,Ioe,Noe,_oe,Aoe,$oe,Roe,Ooe,zoe,Boe,Uoe,dse,XQ,qoe,Xoe,Zoe,ele,rle,ole,YQ,ule,cle,mle,$se];for(let e of fle)rd(e);var Qe;(function(e){e[e.float32=0]="float32",e[e.int32=1]="int32",e[e.bool=2]="bool",e[e.string=3]="string",e[e.complex64=4]="complex64"})(Qe||(Qe={}));var Rc;(function(e){e[e.linear=0]="linear",e[e.relu=1]="relu",e[e.relu6=2]="relu6",e[e.prelu=3]="prelu",e[e.leakyrelu=4]="leakyrelu",e[e.sigmoid=5]="sigmoid",e[e.elu=6]="elu"})(Rc||(Rc={}));var QA;function gle(e){QA=e.wasm.cwrap(oi,null,["number","array","number","number","array","number","number","number","number","number","number","number","number"])}function ble(e){let{inputs:t,backend:n,attrs:a}=e,{a:r,b:s,bias:i,preluActivationWeights:o}=t;if(r.dtype!=="float32"||s.dtype!=="float32")throw new Error("_FusedMatMul for non non-float32 tensors not yet supported.");let{transposeA:l,transposeB:u,activation:p,leakyreluAlpha:d}=a,c=n.dataIdMap.get(r.dataId).id,h=n.dataIdMap.get(s.dataId).id,m=0;if(i!=null){let E=n.dataIdMap.get(i.dataId);if(E.shape.length!==1)throw new Error(`_FusedMatMul only supports rank-1 bias but got rank ${E.shape.length}.`);m=E.id}let f=o==null?0:n.dataIdMap.get(o.dataId).id,g=Rc[p];if(g==null)throw new Error(`${p} activation not yet supported for FusedConv2D in the wasm backend.`);let b=l?r.shape[2]:r.shape[1],y=u?s.shape[1]:s.shape[2],x=pp.assertAndGetBroadcastShape(r.shape.slice(0,-2),s.shape.slice(0,-2)),v=n.makeOutput([...x,b,y],r.dtype),I=n.dataIdMap.get(v.dataId).id,T=new Uint8Array(new Int32Array(r.shape).buffer),C=new Uint8Array(new Int32Array(s.shape).buffer);return QA(c,T,r.shape.length,h,C,s.shape.length,l,u,g,m,f,d||0,I),v}var yle={kernelName:oi,backendName:"wasm",setupFunc:gle,kernelFunc:ble};function Xe(e,t){let n;function a(s){n=s.wasm.cwrap(e,null,["number","number","number"])}function r(s){let{backend:i,inputs:{x:o}}=s,l=i.dataIdMap.get(o.dataId).id,u=i.makeOutput(o.shape,t||o.dtype),p=i.dataIdMap.get(u.dataId).id;return w.sizeFromShape(u.shape)===0||n(l,Qe[o.dtype],p),u}return{kernelName:e,backendName:"wasm",setupFunc:a,kernelFunc:r}}var xle=Xe(lu),vle=Xe(Ti),wle=Xe(Ci);function Ht(e,t,n){let a;function r(i){a=i.wasm.cwrap(e,null,["number","array","number","number","array","number","number","number"])}function s(i){let{backend:o,inputs:l}=i,{a:u,b:p}=l,d=o.dataIdMap.get(u.dataId).id,c=o.dataIdMap.get(p.dataId).id,h=n!=null?n:u.dtype,m=N.assertAndGetBroadcastShape(u.shape,p.shape),f=o.makeOutput(m,h);if(w.sizeFromShape(m)===0)return f;let g=new Uint8Array(new Int32Array(u.shape).buffer),b=new Uint8Array(new Int32Array(p.shape).buffer),y=o.dataIdMap.get(f.dataId).id;return a(d,g,u.shape.length,c,b,p.shape.length,Qe[u.dtype],y),f}return{kernelName:e,backendName:"wasm",setupFunc:r,kernelFunc:s}}var kle=!0,Ile=Ht(Is,kle),eF;function Sle(e){eF=e.wasm.cwrap(_i,null,["array","number","number","number"])}function Nle(e){let{inputs:t,backend:n}=e,a=n.makeOutput(t[0].shape,t[0].dtype);if(w.sizeFromShape(a.shape)===0)return a;let r=t.map(o=>n.dataIdMap.get(o.dataId).id),s=new Uint8Array(new Int32Array(r).buffer),i=n.dataIdMap.get(a.dataId).id;return eF(s,r.length,Qe[a.dtype],i),a}var Tle={kernelName:_i,backendName:"wasm",setupFunc:Sle,kernelFunc:Nle};function ag(e){let{inputs:{x:t},backend:n}=e;if(t.dtype==="string")return bn(n.readSync(t.dataId),t.shape,t.dtype);let a=n.makeOutput(t.shape,t.dtype),r=n.typedArrayFromHeap(t);return n.typedArrayFromHeap(a).set(r),a}var Cle={kernelName:to,backendName:"wasm",kernelFunc:ag},tF;function _le(e){tF=e.wasm.cwrap($r,null,["number","array","number","number","number","array","number"])}function ws(e){let{inputs:t,backend:n,attrs:a}=e,[r,s]=Ale(t.x.shape,a.perm),i=!0;for(let m=0;m<s.length;m++)s[m]!==m&&(i=!1);let o=Ele(t.x.shape,a.perm),l={dataId:t.x.dataId,shape:r,dtype:t.x.dtype};if(i){let m=ag({inputs:t,backend:n});return m.shape=o,m}let u=n.makeOutput(o,l.dtype),p=n.dataIdMap.get(l.dataId).id,d=n.dataIdMap.get(u.dataId).id,c=new Uint8Array(new Int32Array(s).buffer),h=new Uint8Array(new Int32Array(l.shape).buffer);return tF(p,h,l.shape.length,Qe[l.dtype],d,c,s.length),u}function Ele(e,t){let n=new Array(e.length);for(let a=0;a<n.length;a++)n[a]=e[t[a]];return n}function Ale(e,t){let n=[],a=[];for(let r=0;r<e.length;++r)e[r]!==1&&n.push(e[r]),e[t[r]]!==1&&a.push(t[r]);for(let r=0;r<a.length;++r){let s=-1;for(let i=0;i<a.length;++i)a[i]>=r&&(s===-1||a[s]>a[i])&&(s=i);a[s]=r}return[n,a]}var Fle={kernelName:$r,backendName:"wasm",kernelFunc:ws,setupFunc:_le};function Ps(e,t,n){let a=e.shape,r=e.shape.length,s=w.parseAxisParam(t,a),i=s,o=N.getAxesPermutation(i,r),l=null,u=!1;if(o!=null){let p=new Array(r);for(let c=0;c<p.length;c++)p[c]=a[o[c]];i=N.getInnerMostAxes(i.length,r),l=ws({inputs:{x:e},attrs:{perm:o},backend:n});let d=n.dataIdMap.get(e.dataId).id;n.dataIdMap.get(l.dataId).id!==d&&(u=!0)}return{transposed:l,originalAxes:s,axes:i,inputWasTransposed:u}}var nF;function $le(e){nF=e.wasm.cwrap(uu,null,["number, number, number"])}function Dle(e){let{backend:t,inputs:n,attrs:a}=e,{axis:r,keepDims:s}=a,{x:i}=n,o=t.dataIdMap.get(i.dataId).id,l=i,{transposed:u,axes:p,originalAxes:d,inputWasTransposed:c}=Ps(i,r,t);if(c){let y=t.dataIdMap.get(u.dataId).id;l=u,o=y}let h=l.shape.length;N.assertAxesAreInnerMostDims("all",p,h);let[m,f]=N.computeOutAndReduceShapes(l.shape,p),g=w.sizeFromShape(f),b=t.makeOutput(m,i.dtype);if(w.sizeFromShape(l.shape)!==0){let y=t.dataIdMap.get(b.dataId).id;nF(o,g,y)}if(c&&t.disposeData(u.dataId),s){let y=N.expandShapeToKeepDim(b.shape,d);b.shape=y}return b}var Rle={kernelName:uu,backendName:"wasm",setupFunc:$le,kernelFunc:Dle},aF;function Mle(e){aF=e.wasm.cwrap(pu,null,["number, number, number"])}function Ple(e){let{backend:t,inputs:n,attrs:a}=e,{axis:r,keepDims:s}=a,{x:i}=n,o=t.dataIdMap.get(i.dataId).id,l=i,{transposed:u,axes:p,originalAxes:d,inputWasTransposed:c}=Ps(i,r,t);if(c){let y=t.dataIdMap.get(u.dataId).id;l=u,o=y}let h=l.shape.length;N.assertAxesAreInnerMostDims("any",p,h);let[m,f]=N.computeOutAndReduceShapes(l.shape,p),g=w.sizeFromShape(f),b=t.makeOutput(m,i.dtype);if(w.sizeFromShape(l.shape)!==0){let y=t.dataIdMap.get(b.dataId).id;aF(o,g,y)}if(c&&t.disposeData(u.dataId),s){let y=N.expandShapeToKeepDim(b.shape,d);b.shape=y}return b}var Ole={kernelName:pu,backendName:"wasm",setupFunc:Mle,kernelFunc:Ple};function rF(e){let t;function n(r){t=r.wasm.cwrap(e,null,["number","number","number","number","number"])}function a(r){let{backend:s,inputs:i,attrs:o}=r,{axis:l}=o,{x:u}=i,p=s.dataIdMap.get(u.dataId).id,d=p,c=u,{transposed:h,axes:m,inputWasTransposed:f}=Ps(u,l,s);if(f){let I=s.dataIdMap.get(h.dataId).id;I!==p&&(c=h,d=I)}let g=c.shape.slice(0,-1),b=s.makeOutput(g,"int32"),y=s.dataIdMap.get(b.dataId).id,x=w.sizeFromShape(b.shape),v=c.shape[m[0]];return t(d,Qe[c.dtype],x,v,y),f&&s.disposeData(h.dataId),b}return{kernelName:e,backendName:"wasm",setupFunc:n,kernelFunc:a}}var Lle=rF(cu),zle=rF(du),Wle=Xe(Ei),Ble=Xe(Ai),Vle=Xe(Fi),Ule=Ht(Di,!1),Gle=Xe($i),sF;function Hle(e){sF=e.wasm.cwrap(Ri,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function qle(e){let{inputs:t,attrs:n,backend:a}=e,r=t.x,s=a.dataIdMap.get(r.dataId).id,{filterSize:i,strides:o,pad:l,dimRoundingMode:u}=n,p=N.computePool2DInfo(r.shape,i,o,1,l,u),d=p.filterHeight,c=p.filterWidth,h=p.padInfo.top,m=p.padInfo.right,f=p.padInfo.bottom,g=p.padInfo.left,b=p.strideHeight,y=p.strideWidth,x=p.inChannels;if(p.dataFormat!=="channelsLast")throw new Error(`wasm backend does not support dataFormat:'${p.dataFormat}'. Please use 'channelsLast'.`);if(p.dilationWidth!==1||p.dilationHeight!==1)throw new Error(`was backend only supports average pooling with dilation = [1, 1], got [${p.dilationHeight}, ${p.dilationWidth}].`);let v=a.makeOutput(p.outShape,"float32"),I=a.dataIdMap.get(v.dataId).id;return sF(s,r.shape[0],r.shape[1],r.shape[2],d,c,h,m,f,g,b,y,x,I),v}var jle={kernelName:Ri,backendName:"wasm",setupFunc:Hle,kernelFunc:qle},iF;function Kle(e){iF=e.wasm.cwrap("AvgPool3D",null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function Xle(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{filterSize:s,strides:i,pad:o,dimRoundingMode:l,dataFormat:u}=a,p=N.computePool3DInfo(r.shape,s,i,1,o,l,u),d=n.makeOutput(p.outShape,r.dtype);return iF(n.dataIdMap.get(r.dataId).id,n.dataIdMap.get(d.dataId).id,p.batchSize,p.inChannels,p.inDepth,p.inHeight,p.inWidth,p.outDepth,p.outHeight,p.outWidth,p.strideDepth,p.strideHeight,p.strideWidth,p.dilationDepth,p.dilationHeight,p.dilationWidth,p.effectiveFilterDepth,p.effectiveFilterHeight,p.effectiveFilterWidth,p.padInfo.front,p.padInfo.top,p.padInfo.left),d}var Yle={kernelName:hu,backendName:"wasm",setupFunc:Kle,kernelFunc:Xle},oF;function Zle(e){oF=e.wasm.cwrap("AvgPool3DGrad",null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function Jle(e){let{inputs:t,backend:n,attrs:a}=e,{dy:r,input:s}=t,{filterSize:i,strides:o,pad:l,dimRoundingMode:u}=a,p=N.computePool3DInfo(s.shape,i,o,1,l,u),d=n.makeOutput(s.shape,s.dtype);return oF(n.dataIdMap.get(r.dataId).id,n.dataIdMap.get(d.dataId).id,p.batchSize,p.inChannels,p.inDepth,p.inHeight,p.inWidth,p.outDepth,p.outHeight,p.outWidth,p.strideDepth,p.strideHeight,p.strideWidth,p.dilationDepth,p.dilationHeight,p.dilationWidth,p.effectiveFilterDepth,p.effectiveFilterHeight,p.effectiveFilterWidth,p.padInfo.front,p.padInfo.top,p.padInfo.left,p.filterDepth,p.filterHeight,p.filterWidth),d}var Qle={kernelName:Lc,backendName:"wasm",setupFunc:Zle,kernelFunc:Jle},lF;function eue(e){lF=e.wasm.cwrap("AvgPoolGrad",null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function tue(e){let{inputs:t,backend:n,attrs:a}=e,{dy:r,input:s}=t,{filterSize:i,strides:o,pad:l}=a,u=N.computePool2DInfo(s.shape,i,o,1,l),p=n.makeOutput(s.shape,s.dtype);return lF(n.dataIdMap.get(r.dataId).id,n.dataIdMap.get(p.dataId).id,u.batchSize,u.inChannels,u.inHeight,u.inWidth,u.outHeight,u.outWidth,u.strideHeight,u.strideWidth,u.dilationHeight,u.dilationWidth,u.effectiveFilterHeight,u.effectiveFilterWidth,u.padInfo.top,u.padInfo.left,u.filterHeight,u.filterWidth),p}var nue={kernelName:Oc,backendName:"wasm",setupFunc:eue,kernelFunc:tue};function Wn(e){let{inputs:t,attrs:n}=e,{x:a}=t,{shape:r}=n,s=w.sizeFromShape(a.shape),i=w.inferFromImplicitShape(r,s);return w.assert(s===w.sizeFromShape(i),()=>`new shape: ${i}, old shape: ${a.shape}. New shape and old shape must have the same number of elements.`),e.backend.incRef(a.dataId),{dataId:a.dataId,shape:i,dtype:a.dtype}}var aue={kernelName:qu,backendName:"wasm",kernelFunc:Wn},uF;function rue(e){uF=e.wasm.cwrap(Mi,null,["number","array","number","number","array","number","number","number","number"])}function sue(e){let{inputs:t,backend:n,attrs:a}=e,{a:r,b:s}=t,{transposeA:i,transposeB:o}=a;if(r.dtype!=="float32"||s.dtype!=="float32")throw new Error("BatchMatMul for non non-float32 tensors not yet supported.");let l=r.shape.length,u=s.shape.length,p=i?r.shape[l-2]:r.shape[l-1],d=o?s.shape[u-1]:s.shape[u-2],c=i?r.shape[l-1]:r.shape[l-2],h=o?s.shape[u-2]:s.shape[u-1],m=r.shape.slice(0,-2),f=s.shape.slice(0,-2),g=w.sizeFromShape(m),b=w.sizeFromShape(f),y=pp.assertAndGetBroadcastShape(r.shape.slice(0,-2),s.shape.slice(0,-2)).concat([c,h]);w.assert(p===d,()=>`Error in matMul: inner shapes (${p}) and (${d}) of Tensors with shapes ${r.shape} and ${s.shape} and transposeA=${i} and transposeB=${o} must match.`);let x=i?[g,p,c]:[g,c,p],v=o?[b,h,d]:[b,d,h],I=Wn({inputs:{x:r},backend:n,attrs:{shape:x}}),T=Wn({inputs:{x:s},backend:n,attrs:{shape:v}}),C=n.dataIdMap.get(I.dataId).id,E=n.dataIdMap.get(T.dataId).id,F=i?I.shape[2]:I.shape[1],D=o?T.shape[1]:T.shape[2],$=Math.max(g,b),S=n.makeOutput([$,F,D],I.dtype),M=n.dataIdMap.get(S.dataId).id,B=new Uint8Array(new Int32Array(I.shape).buffer),U=new Uint8Array(new Int32Array(T.shape).buffer);return uF(C,B,I.shape.length,E,U,T.shape.length,i,o,M),n.disposeData(I.dataId),n.disposeData(T.dataId),S.shape=y,S}var iue={kernelName:Mi,backendName:"wasm",setupFunc:rue,kernelFunc:sue};function Si(e){let{inputs:{x:t},attrs:{begin:n,size:a},backend:r}=e,[s,i]=Xt.parseSliceParams(t,n,a),o=Xt.isSliceContinous(t.shape,s,i),l=r.readSync(t.dataId),u=r.makeOutput(i,t.dtype),p=w.computeStrides(t.shape),d=r.dataIdMap.get(u.dataId);if(o){let m=Xt.computeFlatOffset(s,p);return t.dtype==="string"?d.stringBytes=l.slice(m,m+w.sizeFromShape(i)):r.typedArrayFromHeap(u).set(l.subarray(m,m+w.sizeFromShape(i))),u}if(t.dtype==="string"){let m=Nm(l,s,i,t.shape,t.dtype);return d.stringBytes=m,u}let c=r.typedArrayFromHeap(u),h=t.shape.length;if(h===2)oue(l,p[0],c,s,i);else if(h===3)lue(l,p[0],p[1],c,s,i);else if(h===4)uue(l,p[0],p[1],p[2],c,s,i);else{let m=Nm(l,s,i,t.shape,t.dtype);c.set(m)}return u}function oue(e,t,n,a,r){let s=0,i=a[0],o=a[1],l=i+r[0];for(let u=i;u<l;u++){let p=u*t+o;n.set(e.subarray(p,p+r[1]),s),s+=r[1]}}function lue(e,t,n,a,r,s){let i=0,o=r[0],l=r[1],u=r[2],p=o+s[0],d=l+s[1];for(let c=o;c<p;c++)for(let h=l;h<d;h++){let m=c*t+h*n+u;a.set(e.subarray(m,m+s[2]),i),i+=s[2]}}function uue(e,t,n,a,r,s,i){let o=0,l=s[0],u=s[1],p=s[2],d=l+i[0],c=u+i[1],h=p+i[2],m=s[3];for(let f=l;f<d;f++)for(let g=u;g<c;g++)for(let b=p;b<h;b++){let y=f*t+g*n+b*a+m;r.set(e.subarray(y,y+i[3]),o),o+=i[3]}}var pue={kernelName:Qu,backendName:"wasm",kernelFunc:Si};function cue(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{blockShape:s,crops:i}=a,o=s.reduce((b,y)=>b*y),l=N.getReshaped(r.shape,s,o),u=N.getPermuted(l.length,s.length),p=N.getReshapedPermuted(r.shape,s,o),d=N.getSliceBeginCoords(i,s.length),c=N.getSliceSize(p,i,s.length),h=Wn({inputs:{x:r},backend:n,attrs:{shape:l}}),m=ws({inputs:{x:h},backend:n,attrs:{perm:u}}),f=Wn({inputs:{x:m},backend:n,attrs:{shape:p}}),g=Si({inputs:{x:f},backend:n,attrs:{begin:d,size:c}});return n.disposeData(h.dataId),n.disposeData(m.dataId),n.disposeData(h.dataId),g}var due={kernelName:mu,backendName:"wasm",kernelFunc:cue},pF;function hue(e){pF=e.wasm.cwrap(fu,null,["number","number","boolean","number","number","number"])}function mue(e){let{backend:t,inputs:n,attrs:a}=e,{x:r,weights:s}=n,{size:i}=a,o=s.shape.reduce((d,c)=>d*c,1)!==0,l=r.shape.length===1?[i]:[r.shape[0],i],u=t.makeOutput(l,s.dtype);function p(d){return t.dataIdMap.get(d.dataId).id}return pF(p(r),i,o,p(s),Qe[s.dtype],p(u)),u}var fue={kernelName:fu,backendName:"wasm",setupFunc:hue,kernelFunc:mue},gue=!0,bue=Ht(gu,gue);function yue(e){let{inputs:t,backend:n}=e,{s0:a,s1:r}=t,s=n.typedArrayFromHeap(a),i=n.typedArrayFromHeap(r),o=N.assertAndGetBroadcastShape(Array.from(s),Array.from(i));return n.makeOutput([o.length],"int32",void 0,new Int32Array(o))}var xue={kernelName:zc,backendName:"wasm",kernelFunc:yue};function Os(e){let{inputs:{x:t},attrs:{dtype:n},backend:a}=e,r=a.makeOutput(t.shape,n),s=a.typedArrayFromHeap(t);return a.typedArrayFromHeap(r).set(s),r}var vue={kernelName:Pi,backendName:"wasm",kernelFunc:Os},wue=Xe(Oi),cF;function kue(e){cF=e.wasm.cwrap(Ss,null,["number","number","number","number"])}function Iue(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{clipValueMin:s,clipValueMax:i}=a,o=n.dataIdMap.get(r.dataId).id,l=n.makeOutput(r.shape,r.dtype),u=n.dataIdMap.get(l.dataId).id;return cF(o,s,i,u),l}var Sue={kernelName:Ss,backendName:"wasm",setupFunc:kue,kernelFunc:Iue};function dF(e){let{inputs:t,backend:n}=e,a=w.parseAxisParam(e.attrs.axis,t[0].shape)[0],r=t.map(h=>h.shape);N.assertParamsConsistent(r,a);let s=N.computeOutShape(t.map(h=>h.shape),a),i=t.filter(h=>w.sizeFromShape(h.shape)>0);if(i.length===1)return ag({inputs:{x:i[0]},backend:n});let o=n.makeOutput(s,t[0].dtype);if(w.sizeFromShape(s)===0)return o;if(i[0].dtype==="string"){let h=i.map(x=>{let v=[-1,w.sizeFromShape(x.shape.slice(a))];return Wn({inputs:{x},backend:n,attrs:{shape:v}})}),m=h.map(x=>({vals:n.readSync(x.dataId),shape:x.shape}));s=N.computeOutShape(h.map(x=>x.shape),1);let f=h[0].shape[0]===1,g=z1(m,s,t[0].dtype,f),b=N.computeOutShape(i.map(x=>x.shape),a);o.shape=b;let y=n.dataIdMap.get(o.dataId);return y.stringBytes=N.fromStringArrayToUint8(g),h.forEach(x=>n.disposeData(x.dataId)),o}let l=w.sizeFromShape(i[0].shape.slice(0,a)),u=0,p=i.map(h=>{let m=w.sizeFromShape(h.shape.slice(a));return u+=m,m}),d=i.map(h=>n.typedArrayFromHeap(h)),c=n.typedArrayFromHeap(o);for(let h=0;h<l;h++){let m=h*u;for(let f=0;f<d.length;f++){let g=p[f],b=h*g,y=d[f].subarray(b,b+g);c.set(y,m),m+=g}}return o}var Nue={kernelName:bu,backendName:"wasm",kernelFunc:dF},hF;function Tue(e){hF=e.wasm.cwrap(Li,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function Cue(e){let{inputs:t,attrs:n,backend:a}=e,{x:r,filter:s}=t,i=a.dataIdMap.get(r.dataId).id,o=a.dataIdMap.get(s.dataId).id,{strides:l,dilations:u,pad:p,dimRoundingMode:d,dataFormat:c}=n,h=N.convertConv2DDataFormat(c),m=N.computeConv2DInfo(r.shape,s.shape,l,u,p,d,!1,h),f=m.filterHeight,g=m.filterWidth,b=m.padInfo.top,y=m.padInfo.right,x=m.padInfo.bottom,v=m.padInfo.left,I=m.dilationHeight,T=m.dilationWidth,C=m.strideHeight,E=m.strideWidth,F=m.inChannels,D=m.outChannels,$=m.padInfo.type==="SAME"?1:0;if(m.dataFormat!=="channelsLast")throw new Error(`wasm backend Conv2D does not support dataFormat:'${m.dataFormat}'. Please use 'channelsLast'.`);let S=a.makeOutput(m.outShape,"float32"),M=a.dataIdMap.get(S.dataId).id;return hF(i,r.shape[0],r.shape[1],r.shape[2],o,f,g,b,y,x,v,$,I,T,C,E,F,D,M),S}var _ue={kernelName:Li,backendName:"wasm",setupFunc:Tue,kernelFunc:Cue},mF;function Eue(e){mF=e.wasm.cwrap(zi,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function Aue(e){let{backend:t,inputs:n,attrs:a}=e,{dy:r,filter:s}=n,{strides:i,pad:o,dataFormat:l,dimRoundingMode:u,inputShape:p}=a,d=1,c=N.convertConv2DDataFormat(l),h=N.computeConv2DInfo(p,s.shape,i,d,o,u,!1,c),{batchSize:m,filterHeight:f,filterWidth:g,inChannels:b,inHeight:y,inWidth:x,outChannels:v,outHeight:I,outWidth:T,strideHeight:C,strideWidth:E}=h,F=f-1-h.padInfo.top,D=g-1-h.padInfo.left,$=h.dataFormat==="channelsLast",S=w.computeStrides(h.inShape),M=w.computeStrides(r.shape),[B,U,H]=w.computeStrides(s.shape),j=S[0],K=$?S[1]:S[2],Z=$?S[2]:1,J=$?1:S[1],ee=M[0],ae=$?M[1]:M[2],te=$?M[2]:1,re=$?1:M[1],ie=t.makeOutput(h.inShape,"float32"),ye=t.dataIdMap.get(ie.dataId).id,ue=t.dataIdMap.get(r.dataId).id,be=t.dataIdMap.get(s.dataId).id;return mF(ue,be,m,f,g,y,x,b,I,T,v,C,E,F,D,B,U,H,j,K,Z,J,ee,ae,te,re,ye),ie}var Fue={kernelName:zi,backendName:"wasm",setupFunc:Eue,kernelFunc:Aue},fF;function $ue(e){fF=e.wasm.cwrap(Wi,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function Due(e){let{inputs:t,backend:n,attrs:a}=e,{x:r,filter:s}=t,{strides:i,pad:o,dilations:l}=a;if(r.dtype!=="float32")throw new Error(`Tensor x must have dtype float32, got ${r.dtype}`);if(s.dtype!=="float32")throw new Error(`Tensor filter must have dtype float32, got ${s.dtype}`);let u=N.computeConv3DInfo(r.shape,s.shape,i,l,o),p=n.makeOutput(u.outShape,r.dtype);return fF(n.dataIdMap.get(r.dataId).id,n.dataIdMap.get(s.dataId).id,n.dataIdMap.get(p.dataId).id,u.batchSize,u.inDepth,u.inHeight,u.inWidth,u.inChannels,u.outDepth,u.outHeight,u.outWidth,u.outChannels,u.strideDepth,u.strideHeight,u.strideWidth,u.dilationDepth,u.dilationHeight,u.dilationWidth,u.filterDepth,u.filterHeight,u.filterWidth,u.padInfo.front,u.padInfo.top,u.padInfo.left),p}var Rue={kernelName:Wi,backendName:"wasm",setupFunc:$ue,kernelFunc:Due},gF;function Mue(e){gF=e.wasm.cwrap(yu,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function Pue(e){let{inputs:t,backend:n,attrs:a}=e,{x:r,dy:s}=t,{strides:i,pad:o,filterShape:l}=a;if(r.dtype!=="float32")throw new Error(`Tensor dy must have dtype float32, got ${r.dtype}`);if(s.dtype!=="float32")throw new Error(`Tensor filter must have dtype float32, got ${s.dtype}`);let u=N.computeConv3DInfo(r.shape,l,i,1,o),p=n.makeOutput(u.filterShape,s.dtype);return gF(n.dataIdMap.get(r.dataId).id,n.dataIdMap.get(s.dataId).id,n.dataIdMap.get(p.dataId).id,u.batchSize,u.inDepth,u.inHeight,u.inWidth,u.inChannels,u.outDepth,u.outHeight,u.outWidth,u.outChannels,u.strideDepth,u.strideHeight,u.strideWidth,u.dilationDepth,u.dilationHeight,u.dilationWidth,u.filterDepth,u.filterHeight,u.filterWidth,u.padInfo.front,u.padInfo.top,u.padInfo.left),p}var Oue={kernelName:yu,backendName:"wasm",setupFunc:Mue,kernelFunc:Pue},bF;function Lue(e){bF=e.wasm.cwrap(xu,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function zue(e){let{inputs:t,backend:n,attrs:a}=e,{dy:r,filter:s}=t,{pad:i,strides:o,inputShape:l}=a;if(r.dtype!=="float32")throw new Error(`Tensor dy must have dtype float32, got ${r.dtype}`);if(s.dtype!=="float32")throw new Error(`Tensor filter must have dtype float32, got ${s.dtype}`);let u=N.computeConv3DInfo(l,s.shape,o,1,i),p=n.makeOutput(u.inShape,r.dtype);return bF(n.dataIdMap.get(s.dataId).id,n.dataIdMap.get(r.dataId).id,n.dataIdMap.get(p.dataId).id,u.batchSize,u.inDepth,u.inHeight,u.inWidth,u.inChannels,u.outDepth,u.outHeight,u.outWidth,u.outChannels,u.strideDepth,u.strideHeight,u.strideWidth,u.dilationDepth,u.dilationHeight,u.dilationWidth,u.filterDepth,u.filterHeight,u.filterWidth,u.padInfo.front,u.padInfo.top,u.padInfo.left),p}var Wue={kernelName:xu,backendName:"wasm",setupFunc:Lue,kernelFunc:zue},Bue=Xe(Bi),Vue=Xe(Vi),xv;(function(e){e[e.bilinear=0]="bilinear",e[e.nearest=1]="nearest"})(xv||(xv={}));var yF;function Uue(e){yF=e.wasm.cwrap(wu,null,["number","number","number","number","array","number","number","number","number","number"])}function Gue(e){let{backend:t,inputs:n,attrs:a}=e,{method:r,extrapolationValue:s,cropSize:i}=a,{image:o,boxes:l,boxInd:u}=n,p=l.shape[0],[d,c]=i,h=[p,d,c,o.shape[3]],m=t.dataIdMap.get(o.dataId),f;o.dtype!=="float32"&&(f=Os({backend:t,inputs:{x:o},attrs:{dtype:"float32"}}),m=t.dataIdMap.get(f.dataId));let g=m.id,b=t.dataIdMap.get(l.dataId).id,y=t.dataIdMap.get(u.dataId).id,x=t.makeOutput(h,"float32"),v=t.dataIdMap.get(x.dataId).id,I=new Uint8Array(new Int32Array(o.shape).buffer);return yF(g,b,y,p,I,d,c,xv[r],s,v),f!=null&&t.disposeData(f.dataId),x}var Hue={kernelName:wu,backendName:"wasm",setupFunc:Uue,kernelFunc:Gue},xF;function que(e){xF=e.wasm.cwrap(vu,null,["number","number","number","number","number","number"])}function jue(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{axis:s,exclusive:i,reverse:o}=a,l=r.shape.length;w.assert(r.dtype==="float32"||r.dtype==="int32",()=>`cumprod does not support ${r.dtype} tensors in the WASM backend`);let u=N.getAxesPermutation([s],l),p=r;u!==null&&(p=ws({inputs:{x:r},attrs:{perm:u},backend:n}));let d=N.getInnerMostAxes(1,l)[0];N.assertAxesAreInnerMostDims("cumprod",[d],l);let c=n.makeOutput(p.shape,p.dtype),h=p.shape[d],m=n.dataIdMap.get(p.dataId).id,f=n.dataIdMap.get(c.dataId).id;xF(m,i?1:0,o?1:0,h,f,Qe[r.dtype]);let g=c;if(u!==null){let b=N.getUndoAxesPermutation(u);g=ws({inputs:{x:c},attrs:{perm:b},backend:n}),n.disposeData(p.dataId),n.disposeData(c.dataId)}return g}var Kue={kernelName:vu,backendName:"wasm",setupFunc:que,kernelFunc:jue},vF;function Xue(e){vF=e.wasm.cwrap(Ui,null,["number","number","number","number","number","number"])}function Yue(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{axis:s,exclusive:i,reverse:o}=a,l=r.shape.length;w.assert(r.dtype==="float32"||r.dtype==="int32",()=>`cumsum does not support ${r.dtype} tensors in the WASM backend`);let u=N.getAxesPermutation([s],l),p=r;u!==null&&(p=ws({inputs:{x:r},attrs:{perm:u},backend:n}));let d=N.getInnerMostAxes(1,l)[0];N.assertAxesAreInnerMostDims("cumsum",[d],l);let c=n.makeOutput(p.shape,p.dtype),h=p.shape[d],m=n.dataIdMap.get(p.dataId).id,f=n.dataIdMap.get(c.dataId).id;vF(m,i?1:0,o?1:0,h,f,Qe[r.dtype]);let g=c;if(u!==null){let b=N.getUndoAxesPermutation(u);g=ws({inputs:{x:c},attrs:{perm:b},backend:n}),n.disposeData(p.dataId),n.disposeData(c.dataId)}return g}var Zue={kernelName:Ui,backendName:"wasm",setupFunc:Xue,kernelFunc:Yue},wF;function Jue(e){wF=e.wasm.cwrap("DenseBincount",null,["number","array","number","number","boolean","number","number","boolean","number"])}function Que(e){let{backend:t,inputs:n,attrs:a}=e,{x:r,weights:s}=n,{size:i,binaryOutput:o}=a,l=s.shape.reduce((c,h)=>c*h,1)!==0,u=r.shape.length===1?[i]:[r.shape[0],i],p=t.makeOutput(u,s.dtype);function d(c){return t.dataIdMap.get(c.dataId).id}return wF(d(r),new Uint8Array(new Int32Array(r.shape).buffer),r.shape.length,i,l,d(s),Qe[s.dtype],o,d(p)),p}var epe={kernelName:Bc,backendName:"wasm",setupFunc:Jue,kernelFunc:Que},kF;function tpe(e){kF=e.wasm.cwrap(ku,null,["number","number","number","array","number","array","array","number","number"])}function npe(e){let{backend:t,inputs:n,attrs:a}=e,{x:r}=n,{blockSize:s,dataFormat:i}=a,o=r.shape[0],l=i==="NHWC"?r.shape[1]:r.shape[2],u=i==="NHWC"?r.shape[2]:r.shape[3],p=i==="NHWC"?r.shape[3]:r.shape[1],d=l*s,c=u*s,h=p/(s*s),m=i==="NHWC"?[o,d,c,h]:[o,h,d,c],f=t.makeOutput(m,"float32"),g=t.dataIdMap.get(r.dataId).id,b=new Uint8Array(new Int32Array(w.computeStrides(r.shape)).buffer),y=new Uint8Array(new Int32Array(m).buffer),x=new Uint8Array(new Int32Array(w.computeStrides(m)).buffer),v=t.dataIdMap.get(f.dataId).id;return kF(g,s,i==="NHWC"?1:0,b,r.shape.length-1,y,x,m.length,v),f}var ape={kernelName:ku,backendName:"wasm",setupFunc:tpe,kernelFunc:npe},IF;function rpe(e){IF=e.wasm.cwrap(Gi,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function spe(e){let{inputs:t,attrs:n,backend:a}=e,{x:r,filter:s}=t,i=a.dataIdMap.get(r.dataId).id,o=a.dataIdMap.get(s.dataId).id,{strides:l,dilations:u,pad:p,dimRoundingMode:d}=n,c=u==null?[1,1]:u,h=N.computeConv2DInfo(r.shape,s.shape,l,c,p,d,!0),m=h.filterHeight,f=h.filterWidth,g=h.padInfo.top,b=h.padInfo.right,y=h.padInfo.bottom,x=h.padInfo.left,v=h.dilationHeight,I=h.dilationWidth,T=h.strideHeight,C=h.strideWidth,E=h.inChannels,F=h.outChannels,D=h.padInfo.type==="SAME"?1:0;if(h.dataFormat!=="channelsLast")throw new Error(`wasm backend DepthwiseConv2dNative does not support dataFormat:'${h.dataFormat}'. Please use 'channelsLast'.`);let $=a.makeOutput(h.outShape,"float32"),S=a.dataIdMap.get($.dataId).id;return IF(i,r.shape[0],r.shape[1],r.shape[2],o,m,f,g,b,y,x,D,v,I,T,C,E,F,S),$}var ipe={kernelName:Gi,backendName:"wasm",setupFunc:rpe,kernelFunc:spe},SF;function ope(e){SF=e.wasm.cwrap("Diag",null,["number","number","number","number"])}function lpe(e){let{inputs:t,backend:n}=e,{x:a}=t,r=w.sizeFromShape(a.shape),s=n.makeOutput([...a.shape,...a.shape],a.dtype);return SF(n.dataIdMap.get(a.dataId).id,Qe[a.dtype],r,n.dataIdMap.get(s.dataId).id),s}var upe={kernelName:Vc,backendName:"wasm",setupFunc:ope,kernelFunc:lpe},NF;function ppe(e){NF=e.wasm.cwrap(Hi,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function cpe(e){let{inputs:t,backend:n,attrs:a}=e,{x:r,filter:s}=t,{strides:i,pad:o,dilations:l}=a;if(r.dtype!==s.dtype)throw new Error(`Dilation2D error: x must have the same dtype as filter. Got ${r.dtype} and ${s.dtype}`);let u=N.computeDilation2DInfo(r.shape,s.shape,i,o,"NHWC",l),p=n.makeOutput(u.outShape,r.dtype);return NF(n.dataIdMap.get(r.dataId).id,n.dataIdMap.get(s.dataId).id,n.dataIdMap.get(p.dataId).id,Qe[r.dtype],u.batchSize,u.inChannels,u.inHeight,u.inWidth,u.outHeight,u.outWidth,u.strideHeight,u.strideWidth,u.dilationHeight,u.dilationWidth,u.filterHeight,u.filterWidth,u.padInfo.top,u.padInfo.left),p}var dpe={kernelName:Hi,backendName:"wasm",setupFunc:ppe,kernelFunc:cpe},TF;function hpe(e){TF=e.wasm.cwrap(Ul,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function mpe(e){let{inputs:t,backend:n,attrs:a}=e,{x:r,filter:s,dy:i}=t,{strides:o,pad:l,dilations:u}=a;if(r.dtype!==s.dtype||r.dtype!==i.dtype)throw new Error(`Dilation2DBackpropFilter error: x must have the same dtype as filter and dy. Got ${r.dtype}, ${s.dtype}, and ${i.dtype}`);let p=N.computeDilation2DInfo(r.shape,s.shape,o,l,"NHWC",u),d=n.makeOutput(s.shape,s.dtype);return TF(n.dataIdMap.get(r.dataId).id,n.dataIdMap.get(s.dataId).id,n.dataIdMap.get(i.dataId).id,n.dataIdMap.get(d.dataId).id,Qe[r.dtype],p.batchSize,p.inChannels,p.inHeight,p.inWidth,p.outHeight,p.outWidth,p.strideHeight,p.strideWidth,p.dilationHeight,p.dilationWidth,p.filterHeight,p.filterWidth,p.padInfo.top,p.padInfo.left),d}var fpe={kernelName:Ul,backendName:"wasm",setupFunc:hpe,kernelFunc:mpe},CF;function gpe(e){CF=e.wasm.cwrap(Vl,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function bpe(e){let{inputs:t,backend:n,attrs:a}=e,{x:r,filter:s,dy:i}=t,{strides:o,pad:l,dilations:u}=a;if(r.dtype!==s.dtype||r.dtype!==i.dtype)throw new Error(`Dilation2DBackpropInput error: x must have the same dtype as filter and dy. Got ${r.dtype}, ${s.dtype}, and ${i.dtype}`);let p=N.computeDilation2DInfo(r.shape,s.shape,o,l,"NHWC",u),d=n.makeOutput(r.shape,r.dtype);return CF(n.dataIdMap.get(r.dataId).id,n.dataIdMap.get(s.dataId).id,n.dataIdMap.get(i.dataId).id,n.dataIdMap.get(d.dataId).id,Qe[r.dtype],p.batchSize,p.inChannels,p.inHeight,p.inWidth,p.outHeight,p.outWidth,p.strideHeight,p.strideWidth,p.dilationHeight,p.dilationWidth,p.filterHeight,p.filterWidth,p.padInfo.top,p.padInfo.left),d}var ype={kernelName:Vl,backendName:"wasm",setupFunc:gpe,kernelFunc:bpe},xpe=Xe(ji),_F;function vpe(e){_F=e.wasm.cwrap(Iu,null,["number","number","number"])}function wpe(e){let{inputs:t,backend:n}=e,{dy:a,y:r}=t,s=n.makeOutput(r.shape,"float32"),i=o=>n.dataIdMap.get(o.dataId).id;return _F(i(r),i(a),i(s)),s}var kpe={kernelName:Iu,backendName:"wasm",setupFunc:vpe,kernelFunc:wpe},Ipe=!1,Spe=Ht(Su,Ipe,"bool"),Npe=Xe(Ki),Tpe=Xe(Xi,"float32");function vv(e){let{inputs:t,attrs:n,backend:a}=e,{input:r}=t,{dim:s}=n,i=r.shape.length,o=r.shape.slice(),l=s;return s<0&&(w.assert(-(i+1)<=s,()=>`Axis must be in the interval [${-(i+1)}, ${i}]`),l=i+s+1),o.splice(l,0,1),Wn({inputs:{x:r},backend:a,attrs:{shape:o}})}var Cpe={kernelName:Nu,backendName:"wasm",kernelFunc:vv},_pe=Xe(Yi,"float32");function EF(e){let{attrs:{shape:t,value:n,dtype:a},backend:r}=e,s=r.makeOutput(t,a);return r.typedArrayFromHeap(s).fill(n),s}var Epe={kernelName:Uc,backendName:"wasm",kernelFunc:EF},AF;function Ape(e){AF=e.wasm.cwrap(Tu,null,["number","number","number","number","number","number"])}function Fpe(e){let{inputs:t,backend:n}=e,{image:a}=t,r=n.makeOutput(a.shape,a.dtype),s=n.dataIdMap.get(a.dataId).id,i=n.dataIdMap.get(r.dataId).id,[o,l,u,p]=a.shape;return AF(s,o,l,u,p,i),r}var $pe={kernelName:Tu,backendName:"wasm",kernelFunc:Fpe,setupFunc:Ape},Dpe=Xe(Zi),Rpe=!1,Mpe=Ht(Ji,Rpe),FF;function Ppe(e){FF=e.wasm.cwrap(Qi,null,["number","number","number","number","number","number","number"])}function Ope(e){let{backend:t,inputs:n,attrs:a}=e,{varianceEpsilon:r}=a,{x:s,mean:i,variance:o,offset:l,scale:u}=n,p=t.dataIdMap.get(s.dataId).id,d=t.dataIdMap.get(i.dataId).id,c=t.dataIdMap.get(o.dataId).id,h=l!=null?t.dataIdMap.get(l.dataId).id:0,m=u!=null?t.dataIdMap.get(u.dataId).id:0,f=t.makeOutput(s.shape,s.dtype);if(w.sizeFromShape(s.shape)===0)return f;let g=t.dataIdMap.get(f.dataId).id;return FF(p,d,c,h,m,r,g),f}var Lpe={kernelName:Qi,backendName:"wasm",setupFunc:Ppe,kernelFunc:Ope},$F;function zpe(e){$F=e.wasm.cwrap(li,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function Wpe(e){let{inputs:t,attrs:n,backend:a}=e,{x:r,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:u,dilations:p,dataFormat:d,dimRoundingMode:c,activation:h,leakyreluAlpha:m}=n,f=N.computeConv2DInfo(r.shape,s.shape,l,p,u,c),g=Rc[h];if(g==null)throw new Error(`${h} activation not yet supported for FusedConv2D in the wasm backend.`);let b=a.dataIdMap.get(r.dataId).id,y=a.dataIdMap.get(s.dataId).id,x=f.outChannels,v=0;if(i!=null){let te=a.dataIdMap.get(i.dataId);if(te.shape.length!==1)throw new Error(`FusedConv2D only supports rank-1 bias but got rank ${te.shape.length}.`);if(te.shape[0]!==x)throw new Error(`FusedConv2D bias shape (${te.shape}) does not match the number of output channels (${x})`);v=te.id}let I=f.filterHeight,T=f.filterWidth,C=f.padInfo.top,E=f.padInfo.right,F=f.padInfo.bottom,D=f.padInfo.left,$=f.dilationHeight,S=f.dilationWidth,M=f.strideHeight,B=f.strideWidth,U=f.inChannels,H=f.padInfo.type==="SAME"?1:0,j=f.batchSize,K=f.inHeight,Z=f.inWidth;if(d!=="NHWC")throw new Error(`wasm backend FusedConv2D does not support dataFormat:'${d}'. Please use 'NHWC'.`);let J=a.makeOutput(f.outShape,"float32"),ee=a.dataIdMap.get(J.dataId).id,ae=o==null?0:a.dataIdMap.get(o.dataId).id;return $F(b,j,K,Z,y,I,T,v,C,E,F,D,H,$,S,M,B,U,x,g,ae,m||0,ee),J}var Bpe={kernelName:li,backendName:"wasm",setupFunc:zpe,kernelFunc:Wpe},DF;function Vpe(e){DF=e.wasm.cwrap(ui,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 Upe(e){let{inputs:t,attrs:n,backend:a}=e,{x:r,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:u,dilations:p,dataFormat:d,dimRoundingMode:c,activation:h,leakyreluAlpha:m}=n,f=N.computeConv2DInfo(r.shape,s.shape,l,p,u,c,!0),g=Rc[h];if(g==null)throw new Error(`${h} activation not yet supported for FusedDepthwiseConv2D in the wasm backend.`);let b=a.dataIdMap.get(r.dataId).id,y=a.dataIdMap.get(s.dataId).id,x=f.outChannels,v=0;if(i!=null){let te=a.dataIdMap.get(i.dataId);if(te.shape.length!==1)throw new Error(`FusedDepthwiseConv2D only supports rank-1 bias but got rank ${te.shape.length}.`);if(te.shape[0]!==x)throw new Error(`FusedDepthwiseConv2D bias shape (${te.shape}) does not match the number of output channels (${x})`);v=te.id}let I=f.filterHeight,T=f.filterWidth,C=f.padInfo.top,E=f.padInfo.right,F=f.padInfo.bottom,D=f.padInfo.left,$=f.dilationHeight,S=f.dilationWidth,M=f.strideHeight,B=f.strideWidth,U=f.inChannels,H=f.padInfo.type==="SAME"?1:0,j=f.batchSize,K=f.inHeight,Z=f.inWidth;if(d!=="NHWC")throw new Error(`wasm backend FusedDepthwiseConv2D does not support dataFormat:'${d}'. Please use 'NHWC'.`);let J=a.makeOutput(f.outShape,"float32"),ee=a.dataIdMap.get(J.dataId).id,ae=o==null?0:a.dataIdMap.get(o.dataId).id;return DF(b,j,K,Z,y,I,T,v,C,E,F,D,H,$,S,M,B,U,x,g,ae,m||0,ee),J}var Gpe={kernelName:ui,backendName:"wasm",setupFunc:Vpe,kernelFunc:Upe},RF;function Hpe(e){RF=e.wasm.cwrap(_u,null,["number","number","number","number","number","number","array","number"])}function qpe(e){let{backend:t,inputs:n}=e,{params:a,indices:r}=n,[s,i,o,l]=Jw.prepareAndValidate(a,r),u=t.makeOutput(s,a.dtype);if(i===0)return u;let p=r.shape,d=p[p.length-1],c=t.dataIdMap.get(a.dataId).id,h=t.dataIdMap.get(r.dataId).id,m=new Uint8Array(new Int32Array(l).buffer),f=t.dataIdMap.get(u.dataId).id;return RF(c,Qe[a.dtype],h,i,d,o,m,f),u}var jpe={kernelName:_u,backendName:"wasm",setupFunc:Hpe,kernelFunc:qpe},MF;function Kpe(e){MF=e.wasm.cwrap("Gather",null,["number","number","array","number","number","number","array","number"])}function Xpe(e){let{backend:t,inputs:n,attrs:a}=e,{x:r,indices:s}=n,{axis:i,batchDims:o}=a,l=w.parseAxisParam(i,r.shape)[0],u=t.readSync(s.dataId),p=r.shape[l];for(let C=0;C<u.length;++C){let E=u[C];w.assert(E<=p-1&&E>=0,()=>`GatherV2: the index value ${E} is not in [0, ${p-1}]`)}let d=N.segment_util.collectGatherOpShapeInfo(r,s,l,o),c=Wn({inputs:{x:r},attrs:{shape:[d.batchSize,d.outerSize,d.dimSize,d.sliceSize]},backend:t}),h=w.sizeFromShape(s.shape),m=Wn({inputs:{x:s},attrs:{shape:[d.batchSize,h/d.batchSize]},backend:t}),f=[d.batchSize,d.outerSize,h/d.batchSize,d.sliceSize],g=t.makeOutput(f,r.dtype);if(w.sizeFromShape(r.shape)===0)return g;let b=c.shape.length-1,y=t.dataIdMap.get(c.dataId).id,x=t.dataIdMap.get(m.dataId).id,v=t.dataIdMap.get(g.dataId).id,I=new Uint8Array(new Int32Array(w.computeStrides(c.shape)).buffer),T=new Uint8Array(new Int32Array(w.computeStrides(f)).buffer);return MF(y,Qe[r.dtype],I,b,x,d.batchSize,T,v),t.disposeData(c.dataId),t.disposeData(m.dataId),g.shape=d.outputShape,g}var Ype={kernelName:Cu,backendName:"wasm",setupFunc:Kpe,kernelFunc:Xpe},Zpe=!1,Jpe=Ht(Eu,Zpe,"bool"),Qpe=!1,ece=Ht(eo,Qpe,"bool"),tce=Xe(no,"bool"),nce=Xe(ao,"bool"),ace=Xe(ro,"bool"),PF;function rce(e){PF=e.wasm.cwrap(so,null,["number","number","number","number"])}function sce(e){let{inputs:{x:t},attrs:{alpha:n},backend:a}=e,r=a.dataIdMap.get(t.dataId).id,s=a.makeOutput(t.shape,"float32");if(w.sizeFromShape(t.shape)!==0){let i=a.dataIdMap.get(s.dataId).id;PF(r,Qe[t.dtype],n,i)}return s}var ice={kernelName:so,backendName:"wasm",setupFunc:rce,kernelFunc:sce},oce=!1,lce=Ht(Au,oce,"bool"),uce=!1,pce=Ht(Fu,uce,"bool"),OF;function cce(e){OF=e.wasm.cwrap($u,null,["number","number","number","number"])}function dce(e){let{attrs:t,backend:n}=e,{start:a,stop:r,num:s}=t,i=Math.floor(s),o=n.makeOutput([i],"float32");return OF(n.dataIdMap.get(o.dataId).id,a,r,i),o}var hce={kernelName:$u,backendName:"wasm",setupFunc:cce,kernelFunc:dce},mce=Xe(io),fce=Xe(oo),gce=!1,bce=Ht(Du,gce,"bool"),yce=Xe(Ru),xce=!1,vce=Ht(Mu,xce,"bool"),wce=!1,kce=Ht(rN,wce,"bool"),LF;function Ice(e){LF=e.wasm.cwrap(lo,null,["number","number","number","number","number","number","number"])}function Sce(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{depthRadius:s,bias:i,alpha:o,beta:l}=a;if(r.dtype!=="float32")throw new Error("LRN error: x must have dtype float32");let u=n.makeOutput(r.shape,r.dtype);return LF(n.dataIdMap.get(r.dataId).id,n.dataIdMap.get(u.dataId).id,r.shape[3],s,i,o,l),u}var Nce={kernelName:lo,backendName:"wasm",setupFunc:Ice,kernelFunc:Sce},zF;function Tce(e){zF=e.wasm.cwrap(Pu,null,["number","number","number","number","number","number","number","number","number"])}function Cce(e){let{inputs:t,backend:n,attrs:a}=e,{x:r,y:s,dy:i}=t,{depthRadius:o,bias:l,alpha:u,beta:p}=a;if(r.dtype!=="float32"||s.dtype!=="float32"||i.dtype!=="float32")throw new Error("LRNGrad 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Fce={kernelName:uo,backendName:"wasm",setupFunc:Ece,kernelFunc:Ace},$ce=!1,Dce=Ht(po,$ce),BF;function Rce(e){BF=e.wasm.cwrap(co,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function Mce(e){let{inputs:t,attrs:n,backend:a}=e,r=t.x,s=a.dataIdMap.get(r.dataId).id;w.assert(r.dtype==="float32",()=>`Error in MaxPool: only float32 input is supported. 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v=t.dataIdMap.get(p.dataId).id;v!==o&&(u=p,l=v,m=N.getInnerMostAxes(m.length,u.shape.length))}N.assertAxesAreInnerMostDims("mean",m,u.shape.length);let[f,g]=N.computeOutAndReduceShapes(u.shape,m),b=w.sizeFromShape(g),y=u;u.dtype!=="float32"&&(y=Os({backend:t,inputs:{x:u},attrs:{dtype:"float32"}}),l=t.dataIdMap.get(y.dataId).id);let x=t.makeOutput(f,"float32");if(w.sizeFromShape(u.shape)!==0){let v=t.dataIdMap.get(x.dataId).id;qF(l,b,v)}if(h&&t.disposeData(p.dataId),s){let v=N.expandShapeToKeepDim(x.shape,c);x.shape=v}return u.dtype!=="float32"&&t.disposeData(y.dataId),x}var Zce={kernelName:ho,backendName:"wasm",setupFunc:Xce,kernelFunc:Yce},jF;function Jce(e){jF=e.wasm.cwrap(mo,null,["number","number","number","number"])}function Qce(e){let{backend:t,inputs:n,attrs:a}=e,{axis:r,keepDims:s}=a,{x:i}=n,o=t.dataIdMap.get(i.dataId).id,l=o,u=i,{transposed:p,axes:d,originalAxes:c,inputWasTransposed:h}=Ps(i,r,t);if(h){let x=t.dataIdMap.get(p.dataId).id;x!==o&&(u=p,l=x)}let m=u.shape.length;N.assertAxesAreInnerMostDims("min",d,m);let[f,g]=N.computeOutAndReduceShapes(u.shape,d),b=w.sizeFromShape(g),y=t.makeOutput(f,u.dtype);if(w.sizeFromShape(u.shape)!==0){let x=t.dataIdMap.get(y.dataId).id;jF(l,Qe[i.dtype],b,x)}if(h&&t.disposeData(p.dataId),s){let x=N.expandShapeToKeepDim(y.shape,c);y.shape=x}return y}var ede={kernelName:mo,backendName:"wasm",setupFunc:Jce,kernelFunc:Qce},tde=!1,nde=Ht(fo,tde),wv;(function(e){e[e.reflect=0]="reflect",e[e.symmetric=1]="symmetric"})(wv||(wv={}));var KF;function ade(e){KF=e.wasm.cwrap(go,null,["number","array","number","number","array","array","number","number"])}function rde(e){let{inputs:{x:t},backend:n,attrs:{paddings:a,mode:r}}=e,s=a.map((m,f)=>m[0]+t.shape[f]+m[1]),i=n.dataIdMap.get(t.dataId).id,o=n.makeOutput(s,t.dtype),l=n.dataIdMap.get(o.dataId).id,u=new Uint8Array(new Int32Array(t.shape).buffer),p=a.map(m=>m[0]),d=a.map(m=>m[1]),c=new Uint8Array(new Int32Array(p).buffer),h=new Uint8Array(new Int32Array(d).buffer);return KF(i,u,t.shape.length,Qe[t.dtype],c,h,wv[r],l),o}var sde={kernelName:go,backendName:"wasm",kernelFunc:rde,setupFunc:ade},XF;function ide(e){XF=e.wasm.cwrap(Wo,null,["number","number","number","number"])}function YF(e){let{backend:t,inputs:{logits:n},attrs:{dim:a}}=e,r=t.dataIdMap.get(n.dataId).id,s=t.makeOutput(n.shape,n.dtype),i=t.dataIdMap.get(s.dataId).id,o=n.shape[a],l=w.sizeFromShape(n.shape)/o;return w.sizeFromShape(s.shape)===0||XF(r,i,o,l),s}var ode={kernelName:Wo,backendName:"wasm",setupFunc:ide,kernelFunc:YF},ZF;function lde(e){ZF=e.wasm.cwrap(Lu,null,["number","number","number","number","number","number"])}function ude(e){let{inputs:t,backend:n,attrs:a}=e,{logits:r}=t,{numSamples:s,seed:i,normalized:o}=a;if(r.dtype!=="float32")throw new Error(`Tensor logits must have dtype float32, got ${r.dtype}`);let l=o?r:YF({inputs:{logits:r},backend:n,attrs:{dim:r.shape.length-1}}),[u,p]=l.shape,d=n.makeOutput([u,s],"int32");return ZF(n.dataIdMap.get(l.dataId).id,u,p,s,i,n.dataIdMap.get(d.dataId).id),o||n.disposeData(l.dataId),d}var pde={kernelName:Lu,backendName:"wasm",setupFunc:lde,kernelFunc:ude},cde=Ht(bo,!0),dde=!0,hde=Ht(yo,dde),mde=Xe(zu);function hk(e,t){let n=new Int32Array(e.wasm.HEAPU8.buffer,t,4),a=n[0],r=n[1],s=n[2],i=n[3];return e.wasm._free(t),{pSelectedIndices:a,selectedSize:r,pSelectedScores:s,pValidOutputs:i}}var JF;function fde(e){JF=e.wasm.cwrap(Bu,"number",["number","number","number","number","number"])}function gde(e){let{backend:t,inputs:n,attrs:a}=e,{iouThreshold:r,maxOutputSize:s,scoreThreshold:i}=a,{boxes:o,scores:l}=n,u=t.dataIdMap.get(o.dataId).id,p=t.dataIdMap.get(l.dataId).id,d=JF(u,p,s,r,i),{pSelectedIndices:c,selectedSize:h,pSelectedScores:m,pValidOutputs:f}=hk(t,d);return t.wasm._free(m),t.wasm._free(f),t.makeOutput([h],"int32",c)}var bde={kernelName:Bu,backendName:"wasm",setupFunc:fde,kernelFunc:gde},QF;function yde(e){QF=e.wasm.cwrap(Vu,"number",["number","number","number","number","number","bool"])}function xde(e){let{backend:t,inputs:n,attrs:a}=e,{iouThreshold:r,maxOutputSize:s,scoreThreshold:i,padToMaxOutputSize:o}=a,{boxes:l,scores:u}=n,p=t.dataIdMap.get(l.dataId).id,d=t.dataIdMap.get(u.dataId).id,c=QF(p,d,s,r,i,o),{pSelectedIndices:h,selectedSize:m,pSelectedScores:f,pValidOutputs:g}=hk(t,c);t.wasm._free(f);let b=t.makeOutput([m],"int32",h),y=t.makeOutput([],"int32",g);return[b,y]}var vde={kernelName:Vu,backendName:"wasm",setupFunc:yde,kernelFunc:xde},e$;function wde(e){e$=e.wasm.cwrap(Uu,"number",["number","number","number","number","number","number"])}function kde(e){let{backend:t,inputs:n,attrs:a}=e,{iouThreshold:r,maxOutputSize:s,scoreThreshold:i,softNmsSigma:o}=a,{boxes:l,scores:u}=n,p=t.dataIdMap.get(l.dataId).id,d=t.dataIdMap.get(u.dataId).id,c=e$(p,d,s,r,i,o),{pSelectedIndices:h,selectedSize:m,pSelectedScores:f,pValidOutputs:g}=hk(t,c);t.wasm._free(g);let b=t.makeOutput([m],"int32",h),y=t.makeOutput([m],"float32",f);return[b,y]}var Ide={kernelName:Uu,backendName:"wasm",setupFunc:wde,kernelFunc:kde},Sde=!1,Nde=Ht(Wu,Sde,"bool"),t$;function Tde(e){t$=e.wasm.cwrap(xo,null,["number","number","number","number","number"])}function Cde(e){let{inputs:t,backend:n,attrs:a}=e,{indices:r}=t,{dtype:s,depth:i,onValue:o,offValue:l}=a,u=n.makeOutput([...r.shape,i],s),p=n.dataIdMap.get(u.dataId).id,d=n.dataIdMap.get(r.dataId).id;return t$(d,i,o,l,p),u}var _de={kernelName:xo,backendName:"wasm",setupFunc:Tde,kernelFunc:Cde};function Ede(e){let{inputs:{x:t},backend:n}=e,a=n.makeOutput(t.shape,t.dtype);return n.typedArrayFromHeap(a).fill(1),a}var Ade={kernelName:Gu,backendName:"wasm",kernelFunc:Ede};function Fde(e){let{inputs:t,backend:n,attrs:a}=e,{axis:r}=a;if(t.length===1)return vv({inputs:{input:t[0]},backend:n,attrs:{dim:r}});let s=t[0].shape,i=t[0].dtype;t.forEach(p=>{w.assertShapesMatch(s,p.shape,"All tensors passed to stack must have matching 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a$={kernelName:vo,backendName:"wasm",kernelFunc:Rde,setupFunc:Dde},Mde=!1,Pde=Ht(wo,Mde),r$;function Ode(e){r$=e.wasm.cwrap(ko,null,["number","number","number"])}function Lde(e){let{inputs:t,backend:n}=e,{x:a,alpha:r}=t,s=n.dataIdMap.get(a.dataId).id,i=n.dataIdMap.get(r.dataId).id,o=s,l=a,u=l;l.dtype!=="float32"&&(u=Os({backend:n,inputs:{x:a},attrs:{dtype:"float32"}}),o=n.dataIdMap.get(u.dataId).id);let p=n.makeOutput(a.shape,"float32"),d=n.dataIdMap.get(p.dataId).id;return r$(o,i,d),l.dtype!=="float32"&&n.disposeData(u.dataId),p}var zde={kernelName:ko,backendName:"wasm",setupFunc:Ode,kernelFunc:Lde},s$;function Wde(e){s$=e.wasm.cwrap(Io,null,["number","number","number","number"])}function Bde(e){let{backend:t,inputs:n,attrs:a}=e,{axis:r,keepDims:s}=a,{x:i}=n,o=t.dataIdMap.get(i.dataId).id,l=o,u=i,{transposed:p,axes:d,originalAxes:c,inputWasTransposed:h}=Ps(i,r,t),m=d;if(h){let 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imageDims(){return this._imageDims}get imageWidth(){return this.imageDims.width}get imageHeight(){return this.imageDims.height}get relativeBox(){return new ot(this._box).rescale(this.imageDims.reverse())}forSize(t,n){return new Ur(this.score,this.classScore,this.className,this.relativeBox,{width:t,height:n})}};var vt=class extends Ur{constructor(t,n,a){super(t,t,"",n,a)}forSize(t,n){let{score:a,relativeBox:r,imageDims:s}=super.forSize(t,n);return new vt(a,r,s)}};function xk(e,t,n=!0){let a=Math.max(0,Math.min(e.right,t.right)-Math.max(e.left,t.left)),r=Math.max(0,Math.min(e.bottom,t.bottom)-Math.max(e.top,t.top)),s=a*r;return n?s/(e.area+t.area-s):s/Math.min(e.area,t.area)}function vk(e){let t=e.map(o=>o.x),n=e.map(o=>o.y),a=t.reduce((o,l)=>l<o?l:o,1/0),r=n.reduce((o,l)=>l<o?l:o,1/0),s=t.reduce((o,l)=>o<l?l:o,0),i=n.reduce((o,l)=>o<l?l:o,0);return new sl(a,r,s,i)}function wk(e,t,n,a=!0){let r=t.map((i,o)=>({score:i,boxIndex:o})).sort((i,o)=>i.score-o.score).map(i=>i.boxIndex),s=[];for(;r.length>0;){let i=r.pop();s.push(i);let o=r,l=[];for(let u=0;u<o.length;u++){let p=o[u],d=e[i],c=e[p];l.push(xk(d,c,a))}r=r.filter((u,p)=>l[p]<=n)}return s}function Ja(e,t){return P(()=>{let[n,a,r]=t,s=xn([...e.shape.slice(0,3),1],n,"float32"),i=xn([...e.shape.slice(0,3),1],a,"float32"),o=xn([...e.shape.slice(0,3),1],r,"float32"),l=et([s,i,o],3);return pe(e,l)})}function kk(e,t=!1){return P(()=>{let[n,a]=e.shape.slice(1);if(n===a)return e;let r=Math.abs(n-a),s=Math.round(r*(t?.5:1)),i=n>a?2:1,o=c=>{let h=e.shape.slice();return h[i]=c,xn(h,0,"float32")},l=o(s),u=r-l.shape[i],d=[t&&u?o(u):null,e,l].filter(c=>!!c).map(c=>se(c,"float32"));return et(d,i)})}function nfe(e){let t=e.slice();for(let n=t.length-1;n>0;n--){let a=Math.floor(Math.random()*(n+1)),r=t[n];t[n]=t[a],t[a]=r}return t}function zd(e){return 1/(1+Math.exp(-e))}function afe(e){return Math.log(e/(1-e))}var il=class extends ot{constructor(t,n,a,r,s=!1){super({x:t,y:n,width:a,height:r},s)}};var rfe=.5,sfe=.43,ife=.45,ia=class{constructor(t,n,a=new Re(0,0)){let{width:r,height:s}=n;this._imgDims=new wn(r,s),this._shift=a,this._positions=t.map(i=>i.mul(new Re(r,s)).add(a))}get shift(){return new Re(this._shift.x,this._shift.y)}get imageWidth(){return this._imgDims.width}get imageHeight(){return this._imgDims.height}get positions(){return this._positions}get relativePositions(){return this._positions.map(t=>t.sub(this._shift).div(new Re(this.imageWidth,this.imageHeight)))}forSize(t,n){return new this.constructor(this.relativePositions,{width:t,height:n})}shiftBy(t,n){return new this.constructor(this.relativePositions,this._imgDims,new Re(t,n))}shiftByPoint(t){return this.shiftBy(t.x,t.y)}align(t,n={}){if(t){let s=t instanceof vt?t.box.floor():new ot(t);return this.shiftBy(s.x,s.y).align(null,n)}let{useDlibAlignment:a,minBoxPadding:r}={useDlibAlignment:!1,minBoxPadding:.2,...n};return a?this.alignDlib():this.alignMinBbox(r)}alignDlib(){let t=this.getRefPointsForAlignment(),[n,a,r]=t,s=d=>r.sub(d).magnitude(),i=(s(n)+s(a))/2,o=Math.floor(i/ife),l=rl(t),u=Math.floor(Math.max(0,l.x-rfe*o)),p=Math.floor(Math.max(0,l.y-sfe*o));return new il(u,p,Math.min(o,this.imageWidth+u),Math.min(o,this.imageHeight+p))}alignMinBbox(t){let n=vk(this.positions);return n.pad(n.width*t,n.height*t)}getRefPointsForAlignment(){throw new Error("getRefPointsForAlignment not implemented by base class")}};var Ik=class extends ia{getRefPointsForAlignment(){let t=this.positions;return[t[0],t[1],rl([t[3],t[4]])]}};var ol=class extends ia{getJawOutline(){return this.positions.slice(0,17)}getLeftEyeBrow(){return this.positions.slice(17,22)}getRightEyeBrow(){return this.positions.slice(22,27)}getNose(){return this.positions.slice(27,36)}getLeftEye(){return this.positions.slice(36,42)}getRightEye(){return this.positions.slice(42,48)}getMouth(){return this.positions.slice(48,68)}getRefPointsForAlignment(){return[this.getLeftEye(),this.getRightEye(),this.getMouth()].map(rl)}};var Ep=class{constructor(t,n){this._label=t,this._distance=n}get label(){return this._label}get distance(){return this._distance}toString(t=!0){return`${this.label}${t?` (${al(this.distance)})`:""}`}};var Ap=class extends ot{constructor(n,a){super(n);this._label=a}static assertIsValidLabeledBox(n,a){if(ot.assertIsValidBox(n,a),!Za(n.label))throw new Error(`${a} - expected property label (${n.label}) to be a number`)}get label(){return this._label}};var vr=class{constructor(t,n){if(typeof t!="string")throw new Error("LabeledFaceDescriptors - constructor expected label to be a string");if(!Array.isArray(n)||n.some(a=>!(a instanceof Float32Array)))throw new Error("LabeledFaceDescriptors - constructor expected descriptors to be an array of Float32Array");this._label=t,this._descriptors=n}get label(){return this._label}get descriptors(){return this._descriptors}toJSON(){return{label:this.label,descriptors:this.descriptors.map(t=>Array.from(t))}}static fromJSON(t){let n=t.descriptors.map(a=>new Float32Array(a));return new vr(t.label,n)}};var Sk=class extends Ap{constructor(n,a,r,s){super(n,a);this._score=r,this._classScore=s}static assertIsValidPredictedBox(n,a){if(Ap.assertIsValidLabeledBox(n,a),!_p(n.score)||!_p(n.classScore))throw new Error(`${a} - expected properties score (${n.score}) and (${n.classScore}) to be a number between [0, 1]`)}get score(){return this._score}get classScore(){return this._classScore}};function wr(e){return e.detection instanceof vt}function ll(e,t){return{...e,...{detection:t}}}function Nk(){let e=window.fetch;if(!e)throw new Error("fetch - missing fetch implementation for browser environment");return{Canvas:HTMLCanvasElement,CanvasRenderingContext2D,Image:HTMLImageElement,ImageData,Video:HTMLVideoElement,createCanvasElement:()=>document.createElement("canvas"),createImageElement:()=>document.createElement("img"),createVideoElement:()=>document.createElement("video"),fetch:e,readFile:()=>{throw new Error("readFile - filesystem not available for browser environment")}}}function Wd(){return typeof global=="object"&&typeof process!="undefined"&&process.versions!=null&&process.versions.node!=null}function ig(e){let t="";if(!e&&Wd())try{e=QD("fs")}catch(a){t=a.toString()}return{readFile:e?a=>new Promise((r,s)=>{e.readFile(a,(i,o)=>i?s(i):r(o))}):()=>{throw new Error(`readFile - failed to require fs in nodejs environment with error: ${t}`)}}}function Tk(){let e=global.Canvas||global.HTMLCanvasElement,t=global.Image||global.HTMLImageElement,n=global.Video||global.HTMLVideoElement,a=()=>{if(e)return new e;throw new Error("createCanvasElement - missing Canvas implementation for nodejs environment")},r=()=>{if(t)return new t;throw new Error("createImageElement - missing Image implementation for nodejs environment")},s=()=>{if(n)return new n;throw new Error("createVideoElement - missing Video implementation for nodejs environment")},i=global.fetch,o=ig();return{Canvas:e||class{},CanvasRenderingContext2D:global.CanvasRenderingContext2D||class{},Image:t||class{},ImageData:global.ImageData||class{},Video:global.HTMLVideoElement||class{},createCanvasElement:a,createImageElement:r,createVideoElement:s,fetch:i,...o}}function Ck(){return typeof window=="object"&&typeof document!="undefined"&&typeof HTMLImageElement!="undefined"&&typeof HTMLCanvasElement!="undefined"&&typeof HTMLVideoElement!="undefined"&&typeof ImageData!="undefined"&&typeof CanvasRenderingContext2D!="undefined"}var un;function ofe(){if(!un)throw new Error("getEnv - environment is not defined, check isNodejs() and isBrowser()");return un}function _k(e){un=e}function Ek(){return Ck()?_k(Nk()):Wd()?_k(Tk()):null}function lfe(e){if(un||Ek(),!un)throw new Error("monkeyPatch - environment is not defined, check isNodejs() and isBrowser()");let{Canvas:t=un.Canvas,Image:n=un.Image}=e;un.Canvas=t,un.Image=n,un.createCanvasElement=e.createCanvasElement||(()=>new t),un.createImageElement=e.createImageElement||(()=>new n),un.ImageData=e.ImageData||un.ImageData,un.Video=e.Video||un.Video,un.fetch=e.fetch||un.fetch,un.readFile=e.readFile||un.readFile}var tt={getEnv:ofe,setEnv:_k,initialize:Ek,createBrowserEnv:Nk,createFileSystem:ig,createNodejsEnv:Tk,monkeyPatch:lfe,isBrowser:Ck,isNodejs:Wd};Ek();function ul(e){return!tt.isNodejs()&&typeof e=="string"?document.getElementById(e):e}function Hn(e){let{Canvas:t,CanvasRenderingContext2D:n}=tt.getEnv();if(e instanceof n)return e;let a=ul(e);if(!(a instanceof t))throw new Error("resolveContext2d - expected canvas to be of instance of Canvas");let r=a.getContext("2d",{willReadFrequently:!0});if(!r)throw new Error("resolveContext2d - canvas 2d context is null");return r}var Ak=(r=>(r.TOP_LEFT="TOP_LEFT",r.TOP_RIGHT="TOP_RIGHT",r.BOTTOM_LEFT="BOTTOM_LEFT",r.BOTTOM_RIGHT="BOTTOM_RIGHT",r))(Ak||{}),Fp=class{constructor(t={}){let{anchorPosition:n,backgroundColor:a,fontColor:r,fontSize:s,fontStyle:i,padding:o}=t;this.anchorPosition=n||"TOP_LEFT",this.backgroundColor=a||"rgba(0, 0, 0, 0.5)",this.fontColor=r||"rgba(255, 255, 255, 1)",this.fontSize=s||14,this.fontStyle=i||"Georgia",this.padding=o||4}},Gr=class{constructor(t,n,a={}){this.text=typeof t=="string"?[t]:t instanceof Gr?t.text:t,this.anchor=n,this.options=new Fp(a)}measureWidth(t){let{padding:n}=this.options;return this.text.map(a=>t.measureText(a).width).reduce((a,r)=>a<r?r:a,0)+2*n}measureHeight(){let{fontSize:t,padding:n}=this.options;return this.text.length*t+2*n}getUpperLeft(t,n){let{anchorPosition:a}=this.options,r=a==="BOTTOM_RIGHT"||a==="TOP_RIGHT",s=a==="BOTTOM_LEFT"||a==="BOTTOM_RIGHT",i=this.measureWidth(t),o=this.measureHeight(),l=r?this.anchor.x-i:this.anchor.x,u=s?this.anchor.y-o:this.anchor.y;if(n){let{width:p,height:d}=n,c=Math.max(Math.min(l,p-i),0),h=Math.max(Math.min(u,d-o),0);return{x:c,y:h}}return{x:l,y:u}}draw(t){let n=ul(t),a=Hn(n),{backgroundColor:r,fontColor:s,fontSize:i,fontStyle:o,padding:l}=this.options;a.font=`${i}px ${o}`;let u=this.measureWidth(a),p=this.measureHeight();a.fillStyle=r;let d=this.getUpperLeft(a,n);a.fillRect(d.x,d.y,u,p),a.fillStyle=s,this.text.forEach((c,h)=>{let m=l+d.x,f=l+d.y+(h+1)*i;a.fillText(c,m,f)})}};var og=class{constructor(t={}){let{boxColor:n,lineWidth:a,label:r,drawLabelOptions:s}=t;this.boxColor=n||"rgba(0, 0, 255, 1)",this.lineWidth=a||2,this.label=r;let i={anchorPosition:"BOTTOM_LEFT",backgroundColor:this.boxColor};this.drawLabelOptions=new Fp({...i,...s})}},Bd=class{constructor(t,n={}){this.box=new ot(t),this.options=new og(n)}draw(t){let n=Hn(t),{boxColor:a,lineWidth:r}=this.options,{x:s,y:i,width:o,height:l}=this.box;n.strokeStyle=a,n.lineWidth=r,n.strokeRect(s,i,o,l);let{label:u}=this.options;u&&new Gr([u],{x:s-r/2,y:i},this.options.drawLabelOptions).draw(t)}};function ufe(e,t){(Array.isArray(t)?t:[t]).forEach(a=>{let r=a instanceof vt?a.score:wr(a)?a.detection.score:void 0,s=a instanceof vt?a.box:wr(a)?a.detection.box:new ot(a),i=r?`${al(r)}`:void 0;new Bd(s,{label:i}).draw(e)})}function Vd(e){let{Image:t,Video:n}=tt.getEnv();return e instanceof t&&e.complete||e instanceof n&&e.readyState>=3}function Fk(e){return new Promise((t,n)=>{(e instanceof tt.getEnv().Canvas||Vd(e))&&t(null);function a(s){s.currentTarget&&(s.currentTarget.removeEventListener("load",r),s.currentTarget.removeEventListener("error",a),n(s))}function r(s){s.currentTarget&&(s.currentTarget.removeEventListener("load",r),s.currentTarget.removeEventListener("error",a),t(s))}e.addEventListener("load",r),e.addEventListener("error",a)})}function $k(e){return new Promise((t,n)=>{e instanceof Blob||n(new Error("bufferToImage - expected buf to be of type: Blob"));let a=new FileReader;a.onload=()=>{typeof a.result!="string"&&n(new Error("bufferToImage - expected reader.result to be a string, in onload"));let r=tt.getEnv().createImageElement();r.onload=()=>t(r),r.onerror=n,r.src=a.result},a.onerror=n,a.readAsDataURL(e)})}function pl(e){let{Image:t,Video:n}=tt.getEnv();return e instanceof t?new wn(e.naturalWidth,e.naturalHeight):e instanceof n?new wn(e.videoWidth,e.videoHeight):new wn(e.width,e.height)}function cl({width:e,height:t}){let{createCanvasElement:n}=tt.getEnv(),a=n();return a.width=e,a.height=t,a}function Ud(e,t){let{ImageData:n}=tt.getEnv();if(!(e instanceof n)&&!Vd(e))throw new Error("createCanvasFromMedia - media has not finished loading yet");let{width:a,height:r}=t||pl(e),s=cl({width:a,height:r});return e instanceof n?Hn(s).putImageData(e,0,0):Hn(s).drawImage(e,0,0,a,r),s}async function Dk(e,t){let n=t||tt.getEnv().createCanvasElement(),[a,r,s]=e.shape.slice(ka(e)?1:0),i=P(()=>e.as3D(a,r,s).toInt());return await Ko.toPixels(i,n),i.dispose(),n}function lg(e){let{Image:t,Canvas:n,Video:a}=tt.getEnv();return e instanceof t||e instanceof n||e instanceof a}function Rk(e,t,n=!1){let{Image:a,Canvas:r}=tt.getEnv();if(!(e instanceof a||e instanceof r))throw new Error("imageToSquare - expected arg0 to be HTMLImageElement | HTMLCanvasElement");if(t<=0)return cl({width:1,height:1});let s=pl(e),i=t/Math.max(s.height,s.width),o=i*s.width,l=i*s.height,u=cl({width:t,height:t}),p=e instanceof r?e:Ud(e),d=Math.abs(o-l)/2,c=n&&o<l?d:0,h=n&&l<o?d:0;return p.width>0&&p.height>0&&Hn(u).drawImage(p,c,h,o,l),u}var kr=class{constructor(t,n=!1){this._imageTensors=[];this._canvases=[];this._treatAsBatchInput=!1;this._inputDimensions=[];this._inputSize=0;if(!Array.isArray(t))throw new Error(`NetInput.constructor - expected inputs to be an Array of TResolvedNetInput or to be instanceof tf.Tensor4D, instead have ${t}`);this._treatAsBatchInput=n,this._batchSize=t.length,t.forEach((a,r)=>{if(Vr(a)){this._imageTensors[r]=a,this._inputDimensions[r]=a.shape;return}if(ka(a)){let i=a.shape[0];if(i!==1)throw new Error(`NetInput - tf.Tensor4D with batchSize ${i} passed, but not supported in input array`);this._imageTensors[r]=a,this._inputDimensions[r]=a.shape.slice(1);return}let s=a instanceof tt.getEnv().Canvas?a:Ud(a);this._canvases[r]=s,this._inputDimensions[r]=[s.height,s.width,3]})}get imageTensors(){return this._imageTensors}get canvases(){return this._canvases}get isBatchInput(){return this.batchSize>1||this._treatAsBatchInput}get batchSize(){return this._batchSize}get inputDimensions(){return this._inputDimensions}get inputSize(){return this._inputSize}get reshapedInputDimensions(){return xr(this.batchSize,0,1).map((t,n)=>this.getReshapedInputDimensions(n))}getInput(t){return this.canvases[t]||this.imageTensors[t]}getInputDimensions(t){return this._inputDimensions[t]}getInputHeight(t){return this._inputDimensions[t][0]}getInputWidth(t){return this._inputDimensions[t][1]}getReshapedInputDimensions(t){if(typeof this.inputSize!="number")throw new Error("getReshapedInputDimensions - inputSize not set, toBatchTensor has not been called yet");let n=this.getInputWidth(t),a=this.getInputHeight(t);return bk({width:n,height:a},this.inputSize)}toBatchTensor(t,n=!0){return this._inputSize=t,P(()=>{let a=xr(this.batchSize,0,1).map(s=>{let i=this.getInput(s);if(i instanceof Te){let o=ka(i)?i:nn(i);return o=kk(o,n),(o.shape[1]!==t||o.shape[2]!==t)&&(o=ea.resizeBilinear(o,[t,t],!1,!1)),o.as3D(t,t,3)}if(i instanceof tt.getEnv().Canvas)return Ko.fromPixels(Rk(i,t,n));throw new Error(`toBatchTensor - at batchIdx ${s}, expected input to be instanceof tf.Tensor or instanceof HTMLCanvasElement, instead have ${i}`)});return Dt(a.map(s=>se(s,"float32"))).as4D(this.batchSize,t,t,3)})}};async function wt(e){if(e instanceof kr)return e;let t=Array.isArray(e)?e:[e];if(!t.length)throw new Error("toNetInput - empty array passed as input");let n=r=>Array.isArray(e)?` at input index ${r}:`:"",a=t.map(ul);return a.forEach((r,s)=>{if(!lg(r)&&!Vr(r)&&!ka(r))throw typeof t[s]=="string"?new Error(`toNetInput -${n(s)} string passed, but could not resolve HTMLElement for element id ${t[s]}`):new Error(`toNetInput -${n(s)} expected media to be of type HTMLImageElement | HTMLVideoElement | HTMLCanvasElement | tf.Tensor3D, or to be an element id`);if(ka(r)){let i=r.shape[0];if(i!==1)throw new Error(`toNetInput -${n(s)} tf.Tensor4D with batchSize ${i} passed, but not supported in input array`)}}),await Promise.all(a.map(r=>lg(r)&&Fk(r))),new kr(a,Array.isArray(e))}async function $p(e,t){let{Canvas:n}=tt.getEnv(),a=e;if(!(e instanceof n)){let i=await wt(e);if(i.batchSize>1)throw new Error("extractFaces - batchSize > 1 not supported");let o=i.getInput(0);a=o instanceof n?o:await Dk(o)}let r=Hn(a);return t.map(i=>i instanceof vt?i.forSize(a.width,a.height).box.floor():i).map(i=>i.clipAtImageBorders(a.width,a.height)).map(({x:i,y:o,width:l,height:u})=>{let p=cl({width:l,height:u});return l>0&&u>0&&Hn(p).putImageData(r.getImageData(i,o,l,u),0,0),p})}async function Dp(e,t){if(!Vr(e)&&!ka(e))throw new Error("extractFaceTensors - expected image tensor to be 3D or 4D");if(ka(e)&&e.shape[0]>1)throw new Error("extractFaceTensors - batchSize > 1 not supported");return P(()=>{let[n,a,r]=e.shape.slice(ka(e)?1:0);return t.map(o=>o instanceof vt?o.forSize(a,n).box:o).map(o=>o.clipAtImageBorders(a,n)).filter(o=>o.width>0&&o.height>0).map(({x:o,y:l,width:u,height:p})=>qo(e.as3D(n,a,r),[l,o,0],[p,u,r]))})}async function Hr(e,t){let{fetch:n}=tt.getEnv(),a=await 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a=se(t.toBatchTensor(112,!0),"float32"),s=Ja(a,[122.782,117.001,104.298]).div(255),i=Gd(s,n.dense0,!0);return i=Gd(i,n.dense1),i=Gd(i,n.dense2),i=Gd(i,n.dense3),i=xa(i,[7,7],[2,2],"valid"),i})}async forward(t){return this.forwardInput(await wt(t))}getDefaultModelName(){return"face_feature_extractor_model"}extractParamsFromWeightMap(t){return D$(t)}extractParams(t){return $$(t)}};function qd(e,t){return P(()=>X($e(e,t.weights),t.bias))}function R$(e,t,n){let a=[],{extractWeights:r,getRemainingWeights:s}=Fn(e),o=cg(r,a)(t,n,"fc");if(s().length!==0)throw new Error(`weights remaing after extract: ${s().length}`);return{paramMappings:a,params:{fc:o}}}function M$(e){let t=[],n=oa(e,t);function a(s){let i=n(`${s}/weights`,2),o=n(`${s}/bias`,1);return{weights:i,bias:o}}let r={fc:a("fc")};return An(e,t),{params:r,paramMappings:t}}function fg(e){let t={},n={};return Object.keys(e).forEach(a=>{let r=a.startsWith("fc")?n:t;r[a]=e[a]}),{featureExtractorMap:t,classifierMap:n}}var Lp=class extends pn{constructor(n,a){super(n);this._faceFeatureExtractor=a}get faceFeatureExtractor(){return this._faceFeatureExtractor}runNet(n){let{params:a}=this;if(!a)throw new Error(`${this._name} - load model before inference`);return P(()=>{let r=n instanceof kr?this.faceFeatureExtractor.forwardInput(n):n;return qd(r.as2D(r.shape[0],-1),a.fc)})}dispose(n=!0){this.faceFeatureExtractor.dispose(n),super.dispose(n)}loadClassifierParams(n){let{params:a,paramMappings:r}=this.extractClassifierParams(n);this._params=a,this._paramMappings=r}extractClassifierParams(n){return R$(n,this.getClassifierChannelsIn(),this.getClassifierChannelsOut())}extractParamsFromWeightMap(n){let{featureExtractorMap:a,classifierMap:r}=fg(n);return this.faceFeatureExtractor.loadFromWeightMap(a),M$(r)}extractParams(n){let a=this.getClassifierChannelsIn(),r=this.getClassifierChannelsOut(),s=r*a+r,i=n.slice(0,n.length-s),o=n.slice(n.length-s);return this.faceFeatureExtractor.extractWeights(i),this.extractClassifierParams(o)}};var Ok=["neutral","happy","sad","angry","fearful","disgusted","surprised"],qr=class{constructor(t){this.neutral=0;this.happy=0;this.sad=0;this.angry=0;this.fearful=0;this.disgusted=0;this.surprised=0;if(t.length!==7)throw new Error(`FaceExpressions.constructor - expected probabilities.length to be 7, have: ${t.length}`);Ok.forEach((n,a)=>{this[n]=t[a]})}asSortedArray(){return Ok.map(t=>({expression:t,probability:this[t]})).sort((t,n)=>n.probability-t.probability)}};var jd=class extends Lp{constructor(t=new Op){super("FaceExpressionNet",t)}forwardInput(t){return P(()=>Xa(this.runNet(t)))}async forward(t){return this.forwardInput(await wt(t))}async predictExpressions(t){let n=await wt(t),a=await this.forwardInput(n),r=await Promise.all(ct(a).map(async i=>{let o=i.dataSync();return i.dispose(),o}));a.dispose();let s=r.map(i=>new qr(i));return n.isBatchInput?s:s[0]}getDefaultModelName(){return"face_expression_model"}getClassifierChannelsIn(){return 256}getClassifierChannelsOut(){return 7}};function Lk(e){return e.expressions instanceof qr}function gg(e,t){return{...e,...{expressions:t}}}function mfe(e,t,n=.1,a){(Array.isArray(t)?t:[t]).forEach(s=>{let i=s instanceof qr?s:Lk(s)?s.expressions:void 0;if(!i)throw new Error("drawFaceExpressions - expected faceExpressions to be FaceExpressions | WithFaceExpressions<{}> or array thereof");let l=i.asSortedArray().filter(d=>d.probability>n),u=wr(s)?s.detection.box.bottomLeft:a||new Re(0,0);new Gr(l.map(d=>`${d.expression} (${al(d.probability)})`),u).draw(e)})}function hl(e){return wr(e)&&e.landmarks instanceof ia&&e.unshiftedLandmarks instanceof ia&&e.alignedRect instanceof vt}function ffe(e){let t=l=>l*180/Math.PI,n=(l,u)=>Math.sqrt((l._x-u._x)**2+(l._y-u._y)**2),a={roll:void 0,pitch:void 0,yaw:void 0},r=(l,u,p)=>{let d=Math.floor(l._x-u._x),c=Math.floor(u._x-p._x);return d-c},s=(l,u)=>{let p=Math.hypot(u._x-l._x,u._y-l._y),d=u._y-l._y,c=Math.asin(d/p),h=t(c),m=Math.floor(90-h),f=u._x-l._x<0?-1:1;return m*f},i=(l,u,p)=>{let d=n(l,p),c={_x:(l._x+p._x)/2,_y:(l._y+p._y)/2},h=n(u,c),m=Math.atan(h/d),f=Math.floor(t(m)),g=c._y-u._y<0?-1:1;return f*g};if(!e||!e._positions||e._positions.length!==68)return a;let o=e._positions;return a.roll=s(o[27],o[66]),a.pitch=i(o[14],o[30],o[2]),a.yaw=r(o[14],o[33],o[2]),a}function zp(e,t){let{box:n}=e.detection,a=t.shiftBy(n.x,n.y),r=a.align(),{imageDims:s}=e.detection,i=new vt(e.detection.score,r.rescale(s.reverse()),s),o=ffe(t);return{...e,...{landmarks:a,unshiftedLandmarks:t,alignedRect:i,angle:o}}}var bg=class{constructor(t={}){let{drawLines:n=!0,drawPoints:a=!0,lineWidth:r,lineColor:s,pointSize:i,pointColor:o}=t;this.drawLines=n,this.drawPoints=a,this.lineWidth=r||1,this.pointSize=i||2,this.lineColor=s||"rgba(0, 255, 255, 1)",this.pointColor=o||"rgba(255, 0, 255, 1)"}},yg=class{constructor(t,n={}){this.faceLandmarks=t,this.options=new bg(n)}draw(t){let n=Hn(t),{drawLines:a,drawPoints:r,lineWidth:s,lineColor:i,pointSize:o,pointColor:l}=this.options;if(a&&this.faceLandmarks instanceof ol&&(n.strokeStyle=i,n.lineWidth=s,Br(n,this.faceLandmarks.getJawOutline()),Br(n,this.faceLandmarks.getLeftEyeBrow()),Br(n,this.faceLandmarks.getRightEyeBrow()),Br(n,this.faceLandmarks.getNose()),Br(n,this.faceLandmarks.getLeftEye(),!0),Br(n,this.faceLandmarks.getRightEye(),!0),Br(n,this.faceLandmarks.getMouth(),!0)),r){n.strokeStyle=l,n.fillStyle=l;let u=p=>{n.beginPath(),n.arc(p.x,p.y,o,0,2*Math.PI),n.fill()};this.faceLandmarks.positions.forEach(u)}}};function gfe(e,t){(Array.isArray(t)?t:[t]).forEach(a=>{let r=a instanceof ia?a:hl(a)?a.landmarks:void 0;if(!r)throw new Error("drawFaceLandmarks - expected faceExpressions to be FaceLandmarks | WithFaceLandmarks<WithFaceDetection<{}>> or array thereof");new yg(r).draw(e)})}var P$="1.7.12";function xfe(e,t){let n=Rp(e,t),a=Mp(e,t);function r(i,o,l){let 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n=[],{extractConvParams:a,extractSeparableConvParams:r,extractReductionBlockParams:s,extractMainBlockParams:i}=vfe(e,n),o=a("entry_flow/conv_in"),l=s("entry_flow/reduction_block_0"),u=s("entry_flow/reduction_block_1"),p={conv_in:o,reduction_block_0:l,reduction_block_1:u},d={};xr(t,0,1).forEach(f=>{d[`main_block_${f}`]=i(`middle_flow/main_block_${f}`)});let c=s("exit_flow/reduction_block"),h=r("exit_flow/separable_conv"),m={reduction_block:c,separable_conv:h};return An(e,n),{params:{entry_flow:p,middle_flow:d,exit_flow:m},paramMappings:n}}function z$(e,t,n){return X(Rt(e,t.filters,n,"same"),t.bias)}function Wk(e,t,n=!0){let a=n?Ke(e):e;return a=qn(a,t.separable_conv0,[1,1]),a=qn(Ke(a),t.separable_conv1,[1,1]),a=Mt(a,[3,3],[2,2],"same"),a=X(a,z$(e,t.expansion_conv,[2,2])),a}function wfe(e,t){let n=qn(Ke(e),t.separable_conv0,[1,1]);return n=qn(Ke(n),t.separable_conv1,[1,1]),n=qn(Ke(n),t.separable_conv2,[1,1]),n=X(n,e),n}var xg=class extends pn{constructor(n){super("TinyXception");this._numMainBlocks=n}forwardInput(n){let{params:a}=this;if(!a)throw new Error("TinyXception - load model before inference");return P(()=>{let r=se(n.toBatchTensor(112,!0),"float32"),i=Ja(r,[122.782,117.001,104.298]).div(255),o=Ke(z$(i,a.entry_flow.conv_in,[2,2]));return o=Wk(o,a.entry_flow.reduction_block_0,!1),o=Wk(o,a.entry_flow.reduction_block_1),xr(this._numMainBlocks,0,1).forEach(l=>{o=wfe(o,a.middle_flow[`main_block_${l}`])}),o=Wk(o,a.exit_flow.reduction_block),o=Ke(qn(o,a.exit_flow.separable_conv,[1,1])),o})}async forward(n){return this.forwardInput(await wt(n))}getDefaultModelName(){return"tiny_xception_model"}extractParamsFromWeightMap(n){return L$(n,this._numMainBlocks)}extractParams(n){return O$(n,this._numMainBlocks)}};function W$(e){let t=[],{extractWeights:n,getRemainingWeights:a}=Fn(e),r=cg(n,t),s=r(512,1,"fc/age"),i=r(512,2,"fc/gender");if(a().length!==0)throw new Error(`weights remaing after extract: 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Dfe(e){let t=ct(De(e,[1,0])),n=[pe(t[2],t[0]),pe(t[3],t[1])],a=[X(t[0],he(n[0],2)),X(t[1],he(n[1],2))];return{sizes:n,centers:a}}function Rfe(e,t){let{sizes:n,centers:a}=Dfe(e),r=ct(De(t,[1,0])),s=he(z(yn(he(r[2],5)),n[0]),2),i=X(z(he(r[0],10),n[0]),a[0]),o=he(z(yn(he(r[3],5)),n[1]),2),l=X(z(he(r[1],10),n[1]),a[1]);return De(Dt([pe(i,s),pe(l,o),X(i,s),X(l,o)]),[1,0])}function J$(e,t,n){return P(()=>{let a=e.shape[0],r=Rfe(W(Ln(n.extra_dim,[a,1,1]),[-1,4]),W(e,[-1,4]));r=W(r,[a,r.shape[0]/a,4]);let s=fa(Ue(t,[0,0,1],[-1,-1,-1])),i=Ue(s,[0,0,0],[-1,-1,1]);i=W(i,[a,i.shape[1]]);let o=ct(r),l=ct(i);return{boxes:o,scores:l}})}function gl(e,t){return P(()=>{let n=e.shape[0],a=W(dl(e,t.box_encoding_predictor),[n,-1,1,4]),r=W(dl(e,t.class_predictor),[n,-1,3]);return{boxPredictionEncoding:a,classPrediction:r}})}function Q$(e,t,n){return P(()=>{let 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p=Array.from(u.dataSync()),c=Z$(l,p,a,.5,r),h=s.getReshapedInputDimensions(0),m=s.inputSize,f=m/h.width,g=m/h.height,b=l.arraySync(),y=c.map(x=>{let[v,I]=[Math.max(0,b[x][0]),Math.min(1,b[x][2])].map(E=>E*g),[T,C]=[Math.max(0,b[x][1]),Math.min(1,b[x][3])].map(E=>E*f);return new vt(p[x],new il(T,v,C-T,I-v),{height:s.getInputHeight(0),width:s.getInputWidth(0)})});return l.dispose(),u.dispose(),y}getDefaultModelName(){return"ssd_mobilenetv1_model"}extractParamsFromWeightMap(t){return X$(t)}extractParams(t){return K$(t)}};function eD(e){let t=new Ls;return t.extractWeights(e),t}function Mfe(e){return eD(e)}var Gk=class extends Ls{};var tD=.4,nD=[new Re(.738768,.874946),new Re(2.42204,2.65704),new Re(4.30971,7.04493),new Re(10.246,4.59428),new Re(12.6868,11.8741)],aD=[new Re(1.603231,2.094468),new Re(6.041143,7.080126),new Re(2.882459,3.518061),new Re(4.266906,5.178857),new Re(9.041765,10.66308)],rD=[117.001,114.697,97.404],sD="tiny_yolov2_model",iD="tiny_yolov2_separable_conv_model";var Tg=e=>typeof e=="number";function Hk(e){if(!e)throw new Error(`invalid config: ${e}`);if(typeof e.withSeparableConvs!="boolean")throw new Error(`config.withSeparableConvs has to be a boolean, have: ${e.withSeparableConvs}`);if(!Tg(e.iouThreshold)||e.iouThreshold<0||e.iouThreshold>1)throw new Error(`config.iouThreshold has to be a number between [0, 1], have: ${e.iouThreshold}`);if(!Array.isArray(e.classes)||!e.classes.length||!e.classes.every(t=>typeof t=="string"))throw new Error(`config.classes has to be an array class names: string[], have: ${JSON.stringify(e.classes)}`);if(!Array.isArray(e.anchors)||!e.anchors.length||!e.anchors.map(t=>t||{}).every(t=>Tg(t.x)&&Tg(t.y)))throw new Error(`config.anchors has to be an array of { x: number, y: number }, have: ${JSON.stringify(e.anchors)}`);if(e.meanRgb&&(!Array.isArray(e.meanRgb)||e.meanRgb.length!==3||!e.meanRgb.every(Tg)))throw new Error(`config.meanRgb has to be an array of shape [number, number, number], have: 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oD(e,t,n,a){let{extractWeights:r,getRemainingWeights:s}=Fn(e),i=[],{extractConvParams:o,extractConvWithBatchNormParams:l,extractSeparableConvParams:u}=Pfe(r,i),p;if(t.withSeparableConvs){let[d,c,h,m,f,g,b,y,x]=a,v=t.isFirstLayerConv2d?o(d,c,3,"conv0"):u(d,c,"conv0"),I=u(c,h,"conv1"),T=u(h,m,"conv2"),C=u(m,f,"conv3"),E=u(f,g,"conv4"),F=u(g,b,"conv5"),D=y?u(b,y,"conv6"):void 0,$=x?u(y,x,"conv7"):void 0,S=o(x||y||b,5*n,1,"conv8");p={conv0:v,conv1:I,conv2:T,conv3:C,conv4:E,conv5:F,conv6:D,conv7:$,conv8:S}}else{let[d,c,h,m,f,g,b,y,x]=a,v=l(d,c,"conv0"),I=l(c,h,"conv1"),T=l(h,m,"conv2"),C=l(m,f,"conv3"),E=l(f,g,"conv4"),F=l(g,b,"conv5"),D=l(b,y,"conv6"),$=l(y,x,"conv7"),S=o(x,5*n,1,"conv8");p={conv0:v,conv1:I,conv2:T,conv3:C,conv4:E,conv5:F,conv6:D,conv7:$,conv8:S}}if(s().length!==0)throw new Error(`weights remaing after extract: ${s().length}`);return{params:p,paramMappings:i}}function Ofe(e,t){let n=oa(e,t);function a(o){let l=n(`${o}/sub`,1),u=n(`${o}/truediv`,1);return{sub:l,truediv:u}}function r(o){let l=n(`${o}/filters`,4),u=n(`${o}/bias`,1);return{filters:l,bias:u}}function s(o){let l=r(`${o}/conv`),u=a(`${o}/bn`);return{conv:l,bn:u}}let i=Pp(n);return{extractConvParams:r,extractConvWithBatchNormParams:s,extractSeparableConvParams:i}}function lD(e,t){let n=[],{extractConvParams:a,extractConvWithBatchNormParams:r,extractSeparableConvParams:s}=Ofe(e,n),i;if(t.withSeparableConvs){let o=t.filterSizes&&t.filterSizes.length||9;i={conv0:t.isFirstLayerConv2d?a("conv0"):s("conv0"),conv1:s("conv1"),conv2:s("conv2"),conv3:s("conv3"),conv4:s("conv4"),conv5:s("conv5"),conv6:o>7?s("conv6"):void 0,conv7:o>8?s("conv7"):void 0,conv8:a("conv8")}}else i={conv0:r("conv0"),conv1:r("conv1"),conv2:r("conv2"),conv3:r("conv3"),conv4:r("conv4"),conv5:r("conv5"),conv6:r("conv6"),conv7:r("conv7"),conv8:a("conv8")};return An(e,n),{params:i,paramMappings:n}}var er=class{constructor({inputSize:t,scoreThreshold:n}={}){this._name="TinyYolov2Options";if(this._inputSize=t||416,this._scoreThreshold=n||.5,typeof this._inputSize!="number"||this._inputSize%32!==0)throw new Error(`${this._name} - expected inputSize to be a number divisible by 32`);if(typeof this._scoreThreshold!="number"||this._scoreThreshold<=0||this._scoreThreshold>=1)throw new Error(`${this._name} - expected scoreThreshold to be a number between 0 and 1`)}get inputSize(){return this._inputSize}get scoreThreshold(){return this._scoreThreshold}};var qk=class extends pn{constructor(n){super("TinyYolov2");Hk(n),this._config=n}get config(){return this._config}get withClassScores(){return this.config.withClassScores||this.config.classes.length>1}get boxEncodingSize(){return 5+(this.withClassScores?this.config.classes.length:0)}runTinyYolov2(n,a){let r=jr(n,a.conv0);return r=Mt(r,[2,2],[2,2],"same"),r=jr(r,a.conv1),r=Mt(r,[2,2],[2,2],"same"),r=jr(r,a.conv2),r=Mt(r,[2,2],[2,2],"same"),r=jr(r,a.conv3),r=Mt(r,[2,2],[2,2],"same"),r=jr(r,a.conv4),r=Mt(r,[2,2],[2,2],"same"),r=jr(r,a.conv5),r=Mt(r,[2,2],[1,1],"same"),r=jr(r,a.conv6),r=jr(r,a.conv7),dl(r,a.conv8,"valid",!1)}runMobilenet(n,a){let r=this.config.isFirstLayerConv2d?Bp(dl(n,a.conv0,"valid",!1)):Kr(n,a.conv0);return r=Mt(r,[2,2],[2,2],"same"),r=Kr(r,a.conv1),r=Mt(r,[2,2],[2,2],"same"),r=Kr(r,a.conv2),r=Mt(r,[2,2],[2,2],"same"),r=Kr(r,a.conv3),r=Mt(r,[2,2],[2,2],"same"),r=Kr(r,a.conv4),r=Mt(r,[2,2],[2,2],"same"),r=Kr(r,a.conv5),r=Mt(r,[2,2],[1,1],"same"),r=a.conv6?Kr(r,a.conv6):r,r=a.conv7?Kr(r,a.conv7):r,dl(r,a.conv8,"valid",!1)}forwardInput(n,a){let{params:r}=this;if(!r)throw new Error("TinyYolov2 - load model before inference");return P(()=>{let s=se(n.toBatchTensor(a,!1),"float32");return s=this.config.meanRgb?Ja(s,this.config.meanRgb):s,s=s.div(255),this.config.withSeparableConvs?this.runMobilenet(s,r):this.runTinyYolov2(s,r)})}async forward(n,a){return this.forwardInput(await wt(n),a)}async detect(n,a={}){let{inputSize:r,scoreThreshold:s}=new er(a),i=await wt(n),o=await this.forwardInput(i,r),l=P(()=>ct(o)[0].expandDims()),u={width:i.getInputWidth(0),height:i.getInputHeight(0)},p=await this.extractBoxes(l,i.getReshapedInputDimensions(0),s);o.dispose(),l.dispose();let d=p.map(b=>b.box),c=p.map(b=>b.score),h=p.map(b=>b.classScore),m=p.map(b=>this.config.classes[b.label]);return wk(d.map(b=>b.rescale(r)),c,this.config.iouThreshold,!0).map(b=>new Ur(c[b],h[b],m[b],d[b],u))}getDefaultModelName(){return""}extractParamsFromWeightMap(n){return lD(n,this.config)}extractParams(n){let a=this.config.filterSizes||qk.DEFAULT_FILTER_SIZES,r=a?a.length:void 0;if(r!==7&&r!==8&&r!==9)throw new Error(`TinyYolov2 - expected 7 | 8 | 9 convolutional filters, but found ${r} filterSizes in config`);return oD(n,this.config,this.boxEncodingSize,a)}async extractBoxes(n,a,r){let{width:s,height:i}=a,o=Math.max(s,i),l=o/s,u=o/i,p=n.shape[1],d=this.config.anchors.length,[c,h,m]=P(()=>{let y=n.reshape([p,p,d,this.boxEncodingSize]),x=y.slice([0,0,0,0],[p,p,d,4]),v=y.slice([0,0,0,4],[p,p,d,1]),I=this.withClassScores?Xa(y.slice([0,0,0,5],[p,p,d,this.config.classes.length]),3):ve(0);return[x,v,I]}),f=[],g=await h.array(),b=await c.array();for(let y=0;y<p;y++)for(let x=0;x<p;x++)for(let v=0;v<d;v++){let I=zd(g[y][x][v][0]);if(!r||I>r){let T=(x+zd(b[y][x][v][0]))/p*l,C=(y+zd(b[y][x][v][1]))/p*u,E=Math.exp(b[y][x][v][2])*this.config.anchors[v].x/p*l,F=Math.exp(b[y][x][v][3])*this.config.anchors[v].y/p*u,D=T-E/2,$=C-F/2,S={row:y,col:x,anchor:v},{classScore:M,label:B}=this.withClassScores?await this.extractPredictedClass(m,S):{classScore:1,label:0};f.push({box:new sl(D,$,D+E,$+F),score:I,classScore:I*M,label:B,...S})}}return c.dispose(),h.dispose(),m.dispose(),f}async extractPredictedClass(n,a){let{row:r,col:s,anchor:i}=a,o=await n.array();return Array(this.config.classes.length).fill(0).map((l,u)=>o[r][s][i][u]).map((l,u)=>({classScore:l,label:u})).reduce((l,u)=>l.classScore>u.classScore?l:u)}},bl=qk;bl.DEFAULT_FILTER_SIZES=[3,16,32,64,128,256,512,1024,1024];var yl=class extends bl{constructor(t=!0){let n={withSeparableConvs:t,iouThreshold:tD,classes:["face"],...t?{anchors:aD,meanRgb:rD}:{anchors:nD,withClassScores:!0}};super(n)}get withSeparableConvs(){return this.config.withSeparableConvs}get anchors(){return this.config.anchors}async locateFaces(t,n){return(await this.detect(t,n)).map(r=>new vt(r.score,r.relativeBox,{width:r.imageWidth,height:r.imageHeight}))}getDefaultModelName(){return this.withSeparableConvs?iD:sD}extractParamsFromWeightMap(t){return super.extractParamsFromWeightMap(t)}};function Lfe(e,t=!0){let n=new yl(t);return n.extractWeights(e),n}var Zd=class extends er{constructor(){super(...arguments);this._name="TinyFaceDetectorOptions"}};var Sa=class{async then(t){return t(await this.run())}async run(){throw new Error("ComposableTask - run is not implemented")}};async function xl(e,t,n,a,r=({alignedRect:s})=>s){let s=e.map(l=>hl(l)?r(l):l.detection),i=a||(t instanceof Te?await Dp(t,s):await $p(t,s)),o=await n(i);return i.forEach(l=>l instanceof Te&&l.dispose()),o}async function Vp(e,t,n,a,r){return xl([e],t,async s=>n(s[0]),a,r)}var uD=.4,pD=[new Re(1.603231,2.094468),new Re(6.041143,7.080126),new Re(2.882459,3.518061),new Re(4.266906,5.178857),new Re(9.041765,10.66308)],cD=[117.001,114.697,97.404];var vl=class extends bl{constructor(){let t={withSeparableConvs:!0,iouThreshold:uD,classes:["face"],anchors:pD,meanRgb:cD,isFirstLayerConv2d:!0,filterSizes:[3,16,32,64,128,256,512]};super(t)}get anchors(){return this.config.anchors}async locateFaces(t,n){return(await this.detect(t,n)).map(r=>new vt(r.score,r.relativeBox,{width:r.imageWidth,height:r.imageHeight}))}getDefaultModelName(){return"tiny_face_detector_model"}extractParamsFromWeightMap(t){return super.extractParamsFromWeightMap(t)}};var nt={ssdMobilenetv1:new Ls,tinyFaceDetector:new vl,tinyYolov2:new yl,faceLandmark68Net:new ml,faceLandmark68TinyNet:new Xd,faceRecognitionNet:new fl,faceExpressionNet:new jd,ageGenderNet:new Kd},dD=(e,t)=>nt.ssdMobilenetv1.locateFaces(e,t),zfe=(e,t)=>nt.tinyFaceDetector.locateFaces(e,t),Wfe=(e,t)=>nt.tinyYolov2.locateFaces(e,t),hD=e=>nt.faceLandmark68Net.detectLandmarks(e),Bfe=e=>nt.faceLandmark68TinyNet.detectLandmarks(e),Vfe=e=>nt.faceRecognitionNet.computeFaceDescriptor(e),Ufe=e=>nt.faceExpressionNet.predictExpressions(e),Gfe=e=>nt.ageGenderNet.predictAgeAndGender(e),mD=e=>nt.ssdMobilenetv1.load(e),Hfe=e=>nt.tinyFaceDetector.load(e),qfe=e=>nt.tinyYolov2.load(e),jfe=e=>nt.faceLandmark68Net.load(e),Kfe=e=>nt.faceLandmark68TinyNet.load(e),Xfe=e=>nt.faceRecognitionNet.load(e),Yfe=e=>nt.faceExpressionNet.load(e),Zfe=e=>nt.ageGenderNet.load(e),Jfe=mD,Qfe=dD,ege=hD;var Cg=class extends Sa{constructor(n,a,r){super();this.parentTask=n;this.input=a;this.extractedFaces=r}},wl=class extends Cg{async run(){let t=await this.parentTask,n=await xl(t,this.input,async a=>Promise.all(a.map(r=>nt.faceExpressionNet.predictExpressions(r))),this.extractedFaces);return t.map((a,r)=>gg(a,n[r]))}withAgeAndGender(){return new Il(this,this.input)}},kl=class extends Cg{async run(){let t=await this.parentTask;if(!t)return;let n=await Vp(t,this.input,a=>nt.faceExpressionNet.predictExpressions(a),this.extractedFaces);return gg(t,n)}withAgeAndGender(){return new Sl(this,this.input)}},zs=class extends wl{withAgeAndGender(){return new Bs(this,this.input)}withFaceDescriptors(){return new Xr(this,this.input)}},Ws=class extends kl{withAgeAndGender(){return new Vs(this,this.input)}withFaceDescriptor(){return new Yr(this,this.input)}};var _g=class extends Sa{constructor(n,a,r){super();this.parentTask=n;this.input=a;this.extractedFaces=r}},Il=class extends _g{async run(){let t=await this.parentTask,n=await xl(t,this.input,async a=>Promise.all(a.map(r=>nt.ageGenderNet.predictAgeAndGender(r))),this.extractedFaces);return t.map((a,r)=>{let{age:s,gender:i,genderProbability:o}=n[r];return Sg(Ng(a,i,o),s)})}withFaceExpressions(){return new wl(this,this.input)}},Sl=class extends _g{async run(){let t=await this.parentTask;if(!t)return;let{age:n,gender:a,genderProbability:r}=await Vp(t,this.input,s=>nt.ageGenderNet.predictAgeAndGender(s),this.extractedFaces);return Sg(Ng(t,a,r),n)}withFaceExpressions(){return new kl(this,this.input)}},Bs=class extends Il{withFaceExpressions(){return new zs(this,this.input)}withFaceDescriptors(){return new Xr(this,this.input)}},Vs=class extends Sl{withFaceExpressions(){return new Ws(this,this.input)}withFaceDescriptor(){return new Yr(this,this.input)}};var Jd=class extends Sa{constructor(n,a){super();this.parentTask=n;this.input=a}},Xr=class extends Jd{async run(){let t=await this.parentTask;return(await xl(t,this.input,a=>Promise.all(a.map(r=>nt.faceRecognitionNet.computeFaceDescriptor(r))),null,a=>a.landmarks.align(null,{useDlibAlignment:!0}))).map((a,r)=>Ig(t[r],a))}withFaceExpressions(){return new zs(this,this.input)}withAgeAndGender(){return new Bs(this,this.input)}},Yr=class extends Jd{async run(){let t=await this.parentTask;if(!t)return;let n=await Vp(t,this.input,a=>nt.faceRecognitionNet.computeFaceDescriptor(a),null,a=>a.landmarks.align(null,{useDlibAlignment:!0}));return Ig(t,n)}withFaceExpressions(){return new Ws(this,this.input)}withAgeAndGender(){return new Vs(this,this.input)}};var Qd=class extends Sa{constructor(n,a,r){super();this.parentTask=n;this.input=a;this.useTinyLandmarkNet=r}get landmarkNet(){return this.useTinyLandmarkNet?nt.faceLandmark68TinyNet:nt.faceLandmark68Net}},eh=class extends Qd{async run(){let t=await this.parentTask,n=t.map(i=>i.detection),a=this.input instanceof Te?await Dp(this.input,n):await $p(this.input,n),r=await Promise.all(a.map(i=>this.landmarkNet.detectLandmarks(i)));return a.forEach(i=>i instanceof Te&&i.dispose()),t.filter((i,o)=>r[o]).map((i,o)=>zp(i,r[o]))}withFaceExpressions(){return new zs(this,this.input)}withAgeAndGender(){return new Bs(this,this.input)}withFaceDescriptors(){return new Xr(this,this.input)}},th=class extends Qd{async run(){let t=await this.parentTask;if(!t)return;let{detection:n}=t,a=this.input instanceof Te?await Dp(this.input,[n]):await $p(this.input,[n]),r=await this.landmarkNet.detectLandmarks(a[0]);return a.forEach(s=>s instanceof Te&&s.dispose()),zp(t,r)}withFaceExpressions(){return new Ws(this,this.input)}withAgeAndGender(){return new Vs(this,this.input)}withFaceDescriptor(){return new Yr(this,this.input)}};var nh=class extends Sa{constructor(n,a=new Ia){super();this.input=n;this.options=a}},Up=class extends nh{async run(){let{input:t,options:n}=this,a;if(n instanceof Zd)a=nt.tinyFaceDetector.locateFaces(t,n);else if(n instanceof Ia)a=nt.ssdMobilenetv1.locateFaces(t,n);else if(n instanceof er)a=nt.tinyYolov2.locateFaces(t,n);else throw new Error("detectFaces - expected options to be instance of TinyFaceDetectorOptions | SsdMobilenetv1Options | TinyYolov2Options");return a}runAndExtendWithFaceDetections(){return new Promise((t,n)=>{this.run().then(a=>t(a.map(r=>ll({},r)))).catch(a=>n(a))})}withFaceLandmarks(t=!1){return new eh(this.runAndExtendWithFaceDetections(),this.input,t)}withFaceExpressions(){return new wl(this.runAndExtendWithFaceDetections(),this.input)}withAgeAndGender(){return new Il(this.runAndExtendWithFaceDetections(),this.input)}},ah=class extends nh{async run(){let t=await new Up(this.input,this.options),n=t[0];return t.forEach(a=>{a.score>n.score&&(n=a)}),n}runAndExtendWithFaceDetection(){return new Promise(async t=>{let n=await this.run();t(n?ll({},n):void 0)})}withFaceLandmarks(t=!1){return new th(this.runAndExtendWithFaceDetection(),this.input,t)}withFaceExpressions(){return new kl(this.runAndExtendWithFaceDetection(),this.input)}withAgeAndGender(){return new Sl(this.runAndExtendWithFaceDetection(),this.input)}};function tge(e,t=new Ia){return new ah(e,t)}function Eg(e,t=new Ia){return new Up(e,t)}async function fD(e,t){return Eg(e,new Ia(t?{minConfidence:t}:{})).withFaceLandmarks().withFaceDescriptors()}async function nge(e,t={}){return Eg(e,new er(t)).withFaceLandmarks().withFaceDescriptors()}var age=fD;function jk(e,t){if(e.length!==t.length)throw new Error("euclideanDistance: arr1.length !== arr2.length");let n=Array.from(e),a=Array.from(t);return Math.sqrt(n.map((r,s)=>r-a[s]).reduce((r,s)=>r+s*s,0))}var rh=class{constructor(t,n=.6){this._distanceThreshold=n;let a=Array.isArray(t)?t:[t];if(!a.length)throw new Error("FaceRecognizer.constructor - expected atleast one input");let r=1,s=()=>`person ${r++}`;this._labeledDescriptors=a.map(i=>{if(i instanceof vr)return i;if(i instanceof Float32Array)return new vr(s(),[i]);if(i.descriptor&&i.descriptor instanceof Float32Array)return new vr(s(),[i.descriptor]);throw new Error("FaceRecognizer.constructor - expected inputs to be of type LabeledFaceDescriptors | WithFaceDescriptor<any> | Float32Array | Array<LabeledFaceDescriptors | WithFaceDescriptor<any> | Float32Array>")})}get labeledDescriptors(){return this._labeledDescriptors}get distanceThreshold(){return this._distanceThreshold}computeMeanDistance(t,n){return n.map(a=>jk(a,t)).reduce((a,r)=>a+r,0)/(n.length||1)}matchDescriptor(t){return this.labeledDescriptors.map(({descriptors:n,label:a})=>new Ep(a,this.computeMeanDistance(t,n))).reduce((n,a)=>n.distance<a.distance?n:a)}findBestMatch(t){let n=this.matchDescriptor(t);return n.distance<this._distanceThreshold?n:new Ep("unknown",n.distance)}toJSON(){return{distanceThreshold:this._distanceThreshold,labeledDescriptors:this._labeledDescriptors.map(t=>t.toJSON())}}static fromJSON(t){let n=t.labeledDescriptors.map(a=>vr.fromJSON(a));return new rh(n,t.distanceThreshold)}};function rge(e){let t=new vl;return t.extractWeights(e),t}function gD(e,t){let{width:n,height:a}=new wn(t.width,t.height);if(n<=0||a<=0)throw new Error(`resizeResults - invalid dimensions: ${JSON.stringify({width:n,height:a})}`);if(Array.isArray(e))return e.map(r=>gD(r,{width:n,height:a}));if(hl(e)){let r=e.detection.forSize(n,a),s=e.unshiftedLandmarks.forSize(r.box.width,r.box.height);return zp(ll(e,r),s)}return wr(e)?ll(e,e.detection.forSize(n,a)):e instanceof ia||e instanceof vt?e.forSize(n,a):e}var sge=P$;return tR(ige);})();
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