face-api/dist/tfjs.esm.js

/*
  Face-API
  homepage: <https://github.com/vladmandic/face-api>
  author: <https://github.com/vladmandic>'
*/

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o=++this.pendingBackendInitId,s=n.then(i=>o<this.pendingBackendInitId?!1:(this.registry[t]=i,this.pendingBackendInit=null,!0)).catch(i=>(o<this.pendingBackendInitId||(this.pendingBackendInit=null,_i(`Initialization of backend ${t} failed`),_i(i.stack||i.message)),!1));return this.pendingBackendInit=s,{success:s,asyncInit:!0}}else return this.registry[t]=n,{success:!0,asyncInit:!1}}catch(n){return _i(`Initialization of backend ${t} failed`),_i(n.stack||n.message),{success:!1,asyncInit:!1}}}removeBackend(t){if(!(t in this.registryFactory))throw new Error(`${t} backend not found in registry`);this.backendName===t&&this.pendingBackendInit!=null&&this.pendingBackendInitId++,t in this.registry&&(this.disposeRegisteredKernels(t),this.registry[t].dispose(),delete this.registry[t]),delete this.registryFactory[t],this.backendName===t&&(this.pendingBackendInit=null,this.backendName=null,this.backendInstance=null)}getSortedBackends(){if(Object.keys(this.registryFactory).length===0)throw new Error("No backend found in registry.");return Object.keys(this.registryFactory).sort((t,e)=>this.registryFactory[e].priority-this.registryFactory[t].priority)}initializeBackendsAndReturnBest(){let t=this.getSortedBackends();for(let e=0;e<t.length;e++){let n=t[e],{success:o,asyncInit:s}=this.initializeBackend(n);if(s||o)return{name:n,asyncInit:s}}throw new Error("Could not initialize any backends, all backend initializations failed.")}moveData(t,e){let n=this.state.tensorInfo.get(e),o=n.backend,s=this.readSync(e),i=o.refCount(e);o.disposeData(e,!0),n.backend=t,t.move(e,s,n.shape,n.dtype,i),this.shouldCheckForMemLeaks()&&this.state.numDataMovesStack[this.state.numDataMovesStack.length-1]++}tidy(t,e){let n=null;if(e==null){if(typeof t!="function")throw new Error("Please provide a function to tidy()");e=t}else{if(typeof t!="string"&&!(t instanceof String))throw new Error("When calling with two arguments, the first argument to tidy() must be a string");if(typeof e!="function")throw new 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o=this.backend.numDataIds(),s=0;n.forEach(u=>{s+=u.dtype==="complex64"?3:1});let i=this.state.numDataMovesStack[this.state.numDataMovesStack.length-1],a=o-e-s-i;if(a>0)throw new Error(`Backend '${this.backendName}' has an internal memory leak (${a} data ids) after running '${t}'`)}runKernelFunc(t){let e,n=[],o=this.isTapeOn(),s=this.state.numBytes,i=this.state.numTensors;this.shouldCheckForMemLeaks()&&this.state.numDataMovesStack.push(0);let a;this.backendName==null&&this.backend;let u,l=_0(t)?t.kernelName:this.state.activeScope!=null?this.state.activeScope.name:"";if(_0(t)){let{kernelName:d,inputs:h,attrs:g}=t;this.backendName==null&&this.backend;let y=nh(d,this.backendName);A(y!=null,()=>`Cannot find registered kernel '${d}' for backend '${this.backendName}'`),a=()=>{let b=this.backend.numDataIds();u=y.kernelFunc({inputs:h,attrs:g,backend:this.backend});let w=Array.isArray(u)?u:[u];this.shouldCheckForMemLeaks()&&this.checkKernelForMemLeak(d,b,w);let v=w.map(N=>N.rank!=null?N:this.makeTensorFromTensorInfo(N));if(o){let N=this.getTensorsForGradient(d,h,v);n=this.saveTensorsForBackwardMode(N)}return v}}else{let{forwardFunc:d}=t,h=g=>{!o||(n=g.map(y=>this.keep(this.clone(y))))};a=()=>{let g=this.backend.numDataIds();u=this.tidy(()=>d(this.backend,h));let y=Array.isArray(u)?u:[u];return this.shouldCheckForMemLeaks()&&this.checkKernelForMemLeak(l,g,y),y}}let{inputs:c,attrs:p}=t,m=_0(t)?null:t.backwardsFunc,f;return this.scopedRun(()=>this.state.kernelDepth++,()=>this.state.kernelDepth--,()=>{!this.ENV.getBool("DEBUG")&&!this.state.profiling?e=a():(f=this.profiler.profileKernel(l,c,()=>a()),this.ENV.getBool("DEBUG")&&this.profiler.logKernelProfile(f),e=f.outputs)}),o&&this.addTapeNode(l,c,e,m,n,p),this.state.profiling&&this.state.activeProfile.kernels.push({name:l,bytesAdded:this.state.numBytes-s,totalBytesSnapshot:this.state.numBytes,tensorsAdded:this.state.numTensors-i,totalTensorsSnapshot:this.state.numTensors,inputShapes:Object.keys(c).map(d=>c[d]!=null?c[d].shape:null),outputShapes:e.map(d=>d.shape),kernelTimeMs:f.timeMs,extraInfo:f.extraInfo}),Array.isArray(u)?e:e[0]}saveTensorsForBackwardMode(t){return t.map(n=>this.keep(this.clone(n)))}getTensorsForGradient(t,e,n){let o=d0(t);if(o!=null){let s=o.inputsToSave||[],i=o.outputsToSave||[],a;o.saveAllInputs?(A(Array.isArray(e),()=>"saveAllInputs is true, expected inputs to be an array."),a=Object.keys(e).map(l=>e[l])):a=s.map(l=>e[l]);let 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e={track:[],name:"unnamed scope",id:this.state.nextScopeId++};t&&(e.name=t),this.state.scopeStack.push(e),this.state.activeScope=e}endScope(t){let e=lh(t),n=new Set(e.map(s=>s.id));for(let s=0;s<this.state.activeScope.track.length;s++){let i=this.state.activeScope.track[s];!i.kept&&!n.has(i.id)&&i.dispose()}let o=this.state.scopeStack.pop();this.state.activeScope=this.state.scopeStack.length===0?null:this.state.scopeStack[this.state.scopeStack.length-1],e.forEach(s=>{!s.kept&&s.scopeId===o.id&&this.track(s)})}gradients(t,e,n,o=!1){if(A(e.length>0,()=>"gradients() received an empty list of xs."),n!=null&&n.dtype!=="float32")throw new Error(`dy must have 'float32' dtype, but has '${n.dtype}'`);let s=this.scopedRun(()=>this.startTape(),()=>this.endTape(),()=>this.tidy("forward",t));A(s instanceof Pt,()=>"The result y returned by f() must be a tensor.");let i=P1(this.state.activeTape,e,s);if(!o&&i.length===0&&e.length>0)throw new Error("Cannot compute gradient of y=f(x) with respect to x. 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2 or rank 1 but got rank ${l.rank}.`),c!=null&&A(c.rank===2||c.rank===1,()=>`Error in batchNorm2D: offset must be rank 2 or rank 1 but got rank ${c.rank}.`),Li(i,a,u,c,l,s)}var kx=k({batchNorm2d_:pq});function mq(r,t,e,n,o,s){let i=I(r,"x","batchNorm"),a=I(t,"mean","batchNorm"),u=I(e,"variance","batchNorm"),l;o!=null&&(l=I(o,"scale","batchNorm"));let c;return n!=null&&(c=I(n,"offset","batchNorm")),A(i.rank===3,()=>`Error in batchNorm3D: x must be rank 3 but got rank ${i.rank}.`),A(a.rank===3||a.rank===1,()=>`Error in batchNorm3D: mean must be rank 3 or rank 1 but got rank ${a.rank}.`),A(u.rank===3||u.rank===1,()=>`Error in batchNorm3D: variance must be rank 3 or rank 1 but got rank ${u.rank}.`),l!=null&&A(l.rank===3||l.rank===1,()=>`Error in batchNorm3D: scale must be rank 3 or rank 1 but got rank ${l.rank}.`),c!=null&&A(c.rank===3||c.rank===1,()=>`Error in batchNorm3D: offset must be rank 3 or rank 1 but got rank ${c.rank}.`),Li(i,a,u,c,l,s)}var Tx=k({batchNorm3d_:mq});function fq(r,t,e,n,o,s){let i=I(r,"x","batchNorm"),a=I(t,"mean","batchNorm"),u=I(e,"variance","batchNorm"),l;o!=null&&(l=I(o,"scale","batchNorm"));let c;return n!=null&&(c=I(n,"offset","batchNorm")),A(i.rank===4,()=>`Error in batchNorm4D: x must be rank 4 but got rank ${i.rank}.`),A(a.rank===4||a.rank===1,()=>`Error in batchNorm4D: mean must be rank 4 or rank 1 but got rank ${a.rank}.`),A(u.rank===4||u.rank===1,()=>`Error in batchNorm4D: variance must be rank 4 or rank 1 but got rank ${u.rank}.`),l!=null&&A(l.rank===4||l.rank===1,()=>`Error in batchNorm4D: scale must be rank 4 or rank 1 but got rank ${l.rank}.`),c!=null&&A(c.rank===4||c.rank===1,()=>`Error in batchNorm4D: offset must be rank 4 or rank 1 but got rank ${c.rank}.`),Li(i,a,u,c,l,s)}var _x=k({batchNorm4d_:fq});function dq(r,t,e){let n=I(r,"x","bincount"),o=I(t,"weights","bincount");A(n.dtype==="int32",()=>`Error in bincount: input dtype must be int32, but got ${n.dtype}`),A(e>=0,()=>`size must be non-negative, but got 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Its own _trainableWeights must remain an empty Array.");if(!this.trainable)return[];let t=[];for(let e of this.layers)t=t.concat(e.trainableWeights);return t}get nonTrainableWeights(){let t=[];for(let e of this.layers)t.push(...e.nonTrainableWeights);if(!this.trainable){let e=[];for(let n of this.layers)e.push(...n.trainableWeights);return e.concat(t)}return t}get weights(){return this.trainableWeights.concat(this.nonTrainableWeights)}loadWeights(t,e=!0){let n={},o=0;for(let i of this.layers)for(let a of i.weights){if(n[a.originalName]!=null)throw new z(`Duplicate weight name: ${a.originalName}`);n[a.originalName]=a,o++}let s=[];for(let i in t){let a=i;if(n[i]==null){let u=i.split("/");a=u.slice(0,-2).concat([u[u.length-1]]).join("/")}if(n[a]!=null)s.push([n[a],t[i]]);else if(e)throw new z(`Provided weight data has no target variable: ${i}`);delete n[a]}if(e){let i=[];for(let a in n)i.push(a);if(i.length>0)throw new z(`${i.length} of ${o} weights are not set: ${i}`)}qm(s)}updatedConfig(){let t=this.getConfig(),e={};return e.className=this.getClassName(),e.config=t,e.kerasVersion=`tfjs-layers ${tf}`,e.backend="TensorFlow.js",e}toJSON(t,e=!0){let n=eb(this.updatedConfig());return e?JSON.stringify(n):n}call(t,e){return W(()=>{t=be(t);let n=new ko;for(let o=0;o<this.inputs.length;++o)n.add(this.inputs[o],t[o]);return vc(this.outputs,n,e)})}computeMask(t,e){return W(()=>{t=be(t);let n;return e==null?n=vo(null,t.length):n=be(e),this.runInternalGraph(t,n)[1]})}computeOutputShape(t){let e=Um(t);if(e.length!==this.inputLayers.length)throw new z(`Invalid inputShape argument ${t}: model has ${this.inputLayers.length} tensor inputs.`);let n={};for(let a=0;a<e.length;a++){let u=this.inputLayers[a],l=e[a],c=u.name+"_0_0";n[c]=l}let o=Object.keys(this.nodesByDepth).map(a=>parseInt(a,10)).sort(Ch);if(o.length>1)for(let a of o){let u=this.nodesByDepth[a];for(let l of u){let c=l.outboundLayer;if(this.inputLayers.map(h=>h.id).indexOf(c.id)!==-1)continue;let p=[];for(let h=0;h<l.inboundLayers.length;h++){let g=l.inboundLayers[h],y=l.nodeIndices[h],b=l.tensorIndices[h],w=`${g.name}_${y}_${b}`,v=n[w];p.push(v)}let m=c.computeOutputShape(kr(p)),f=Um(m),d=c.inboundNodes.indexOf(l);for(let h=0;h<f.length;h++){let g=`${c.name}_${d}_${h}`;n[g]=f[h]}}}let s=[],i=[];for(let a=0;a<this.outputLayers.length;a++){let u=this.outputLayers[a],l=this.outputLayersNodeIndices[a],c=this.outputLayersTensorIndices[a],p=`${u.name}_${l}_${c}`;i.push(p)}for(let a=0;a<i.length;a++){let u=i[a];Qn(u in n),s.push(n[u])}return kr(s)}runInternalGraph(t,e){e==null&&(e=vo(null,t.length));let n={};for(let u=0;u<this.inputs.length;++u){let l=this.inputs[u],c=t[u],p=e[u];n[l.id]=[c,p]}let o=Object.keys(this.nodesByDepth).map(u=>parseInt(u,10)).sort(Ch);for(let u of o){let l=this.nodesByDepth[u];for(let c of l){let p=c.outboundLayer,m=c.inputTensors,f=c.outputTensors,d=new Array;for(let h of m)h.id in n&&d.push(n[h.id]);if(d.length===m.length){let h={},g,y,b,w;if(c.callArgs!=null&&(h=c.callArgs),d.length===1){let[v,N]=d[0];h.mask==null&&(h.mask=N),b=be(p.call(v,h)),w=be(p.computeMask(v,N)),g=[v],y=[N]}else g=d.map(v=>v[0]),y=d.map(v=>v[1]),h.mask==null&&(h.mask=y),b=be(p.call(g,h)),w=be(p.computeMask(g,y));if(p.activityRegularizer)throw new kt("LayersModel invocation with concrete Tensor value(s) in the presence of activity regularizer(s) is not supported yet.");for(let v=0;v<f.length;++v){let N=f[v],E=b[v],$=w[v];n[N.id]=[E,$]}}}}let s=[],i=[],a=[];for(let u of this.outputs){Qn(u.id in n,`Could not compute output ${u.name} : ${u.id}`);let[l,c]=n[u.id];a.push(l.shape),s.push(l),i.push(c)}return[s,i,a]}buildNodeConversionMap(t){let e={},n;for(let o of this.layers){n=o instanceof zn?1:0;for(let s=0;s<o.inboundNodes.length;s++){let i=zn.nodeKey(o,s);this.containerNodes.has(i)&&(e[i]=n,n+=1)}}return e}getLayer(t,e){if(e!=null){if(this.layers.length<=e)throw new z(`Was asked to retrieve layer at index ${e}, but model only has ${this.layers.length} layer(s).`);return this.layers[e]}else if(t==null)throw new z("Provide either a layer name or layer index");for(let n of this.layers)if(n.name===t)return n;throw new z(`No such layer: ${t}`)}calculateLosses(){return W(()=>{let t=[];for(let e of this.layers)for(let n=0;n<e.inboundNodes.length;++n){let o=zn.nodeKey(e,n);this.containerNodes.has(o)&&t.push(...e.calculateLosses())}return t})}getConfig(){let t={name:this.name},e=this.buildNodeConversionMap(this.layers),n=[];for(let i of this.layers){let a=i.getClassName(),u=i.getConfig(),l=[];for(let p=0;p<i.inboundNodes.length;p++){let m=i.inboundNodes[p],f=zn.nodeKey(i,p),d={};if(this.containerNodes.has(f)){if(m.callArgs)try{JSON.stringify(m.callArgs),d=m.callArgs}catch(h){console.warn(`Layer ${i.name} was passed non-serializable keyword arguments: ${m.callArgs}. 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t={theta:this.theta},e=super.getConfig();return Object.assign(t,e),t}};lf.className="ThresholdedReLU";et.registerClass(lf);var uf=class extends Bt{constructor(t){super(t==null?{}:t),this.DEFAULT_AXIS=1,t==null&&(t={}),this.softmax=new rf().apply,this.axis=t.axis==null?this.DEFAULT_AXIS:t.axis}call(t,e){let n=Lt(t);return this.softmax(n,this.axis)}computeOutputShape(t){return t}getConfig(){let t={axis:this.axis},e=super.getConfig();return Object.assign(t,e),t}};uf.className="Softmax";et.registerClass(uf);function yu(r,t,e){if(typeof r=="number")return vo(r,t);if(r.length!==t)throw new z(`The ${e} argument must be an integer or tuple of ${t} integers. 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Received: ${JSON.stringify(r)} including a non-integer number ${o}`)}return r}function Tn(r,t,e,n,o=1){if(r==null)return r;let s=t+(t-1)*(o-1),i;return e==="same"?i=r:i=r-s+1,Math.floor((i+n-1)/n)}function ti(r,t,e,n){if(r==null)return null;if(n==="valid")r=r*t+Ys([e-t,0]);else if(n==="same")r=r*t;else throw new z(`Unsupport padding mode: ${n}.`);return r}function Rh(r,t){return W(()=>(Le(t),t==="channelsFirst"?Mt(r,[0,2,3,1]):r))}function WS(r,t){return W(()=>(Le(t),t==="channelsFirst"?Mt(r,[0,2,3,4,1]):r))}function q8(r,t,e,n=1,o="valid",s,i=1){return W(()=>{if(s==null&&(s=mn()),Le(s),r.shape.length!==3)throw new z(`The input of a conv1dWithBias operation should be 3, but is ${r.shape.length} instead.`);if(t.shape.length!==3)throw new z(`The kernel for a conv1dWithBias operation should be 3, but is ${t.shape.length} instead`);if(e!=null&&e.shape.length!==1)throw new z(`The bias for a conv1dWithBias operation should be 1, but is ${t.shape.length} instead`);if(s==="channelsFirst"&&(r=Mt(r,[0,2,1])),o==="causal")throw new kt("The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.");let a=um(r,t,n,o==="same"?"same":"valid","NWC",i);return e!=null&&(a=fn(a,e)),a})}function ND(r,t,e,n=[1,1],o="valid",s,i,a=null){return W(()=>{if(s==null&&(s=mn()),Le(s),r.rank!==3&&r.rank!==4)throw new z(`conv2dWithBiasActivation expects input to be of rank 3 or 4, but received ${r.rank}.`);if(t.rank!==3&&t.rank!==4)throw new z(`conv2dWithBiasActivation expects kernel to be of rank 3 or 4, but received ${r.rank}.`);let u=Rh(r,s);if(o==="causal")throw new kt("The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.");return u=su.conv2d({x:u,filter:t,strides:n,pad:o==="same"?"same":"valid",dilations:i,dataFormat:"NHWC",bias:e,activation:a}),s==="channelsFirst"&&(u=Mt(u,[0,3,1,2])),u})}function K8(r,t,e,n=[1,1,1],o="valid",s,i){return W(()=>{if(s==null&&(s=mn()),Le(s),r.rank!==4&&r.rank!==5)throw new z(`conv3dWithBias expects input to be of rank 4 or 5, but received ${r.rank}.`);if(t.rank!==4&&t.rank!==5)throw new z(`conv3dWithBias expects kernel to be of rank 4 or 5, but received ${r.rank}.`);let a=WS(r,s);if(o==="causal")throw new kt("The support for CAUSAL padding mode in conv3dWithBias is not implemented yet.");return a=Ox(a,t,n,o==="same"?"same":"valid","NDHWC",i),e!=null&&(a=fn(a,e)),s==="channelsFirst"&&(a=Mt(a,[0,4,1,2,3])),a})}var Nc=class extends Bt{constructor(t,e){if(super(e),this.bias=null,this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_BIAS_INITIALIZER="zeros",Nc.verifyArgs(e),this.rank=t,Je(this.rank,"rank"),this.rank!==1&&this.rank!==2&&this.rank!==3)throw new kt(`Convolution layer for rank other than 1, 2, or 3 (${this.rank}) is not implemented yet.`);if(this.kernelSize=yu(e.kernelSize,t,"kernelSize"),this.strides=yu(e.strides==null?1:e.strides,t,"strides"),this.padding=e.padding==null?"valid":e.padding,pn(this.padding),this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,Le(this.dataFormat),this.activation=Qs(e.activation),this.useBias=e.useBias==null?!0:e.useBias,this.biasInitializer=ge(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.biasConstraint=We(e.biasConstraint),this.biasRegularizer=ve(e.biasRegularizer),this.activityRegularizer=ve(e.activityRegularizer),this.dilationRate=yu(e.dilationRate==null?1:e.dilationRate,t,"dilationRate"),this.rank===1&&Array.isArray(this.dilationRate)&&this.dilationRate.length!==1)throw new z(`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 z(`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 z(`dilationRate must be a number or array of three numbers for 3D convolution, but received ${JSON.stringify(this.dilationRate)}`)}}static verifyArgs(t){if(Qn("kernelSize"in t,"required key 'kernelSize' not in config"),typeof t.kernelSize!="number"&&!Ay(t.kernelSize,"number",1,3))throw new z(`BaseConv expects config.kernelSize to be number or number[] with length 1, 2, or 3, but received ${JSON.stringify(t.kernelSize)}.`)}getConfig(){let t={kernelSize:this.kernelSize,strides:this.strides,padding:this.padding,dataFormat:this.dataFormat,dilationRate:this.dilationRate,activation:Js(this.activation),useBias:this.useBias,biasInitializer:_e(this.biasInitializer),biasRegularizer:de(this.biasRegularizer),activityRegularizer:de(this.activityRegularizer),biasConstraint:Ge(this.biasConstraint)},e=super.getConfig();return Object.assign(t,e),t}},bu=class extends Nc{constructor(t,e){super(t,e),this.kernel=null,bu.verifyArgs(e),this.filters=e.filters,Je(this.filters,"filters"),this.kernelInitializer=ge(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.kernelConstraint=We(e.kernelConstraint),this.kernelRegularizer=ve(e.kernelRegularizer)}build(t){t=te(t);let e=this.dataFormat==="channelsFirst"?1:t.length-1;if(t[e]==null)throw new z(`The channel dimension of the input should be defined. Found ${t[e]}`);let n=t[e],o=this.kernelSize.concat([n,this.filters]);this.kernel=this.addWeight("kernel",o,null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[{ndim:this.rank+2,axes:{[e]:n}}],this.built=!0}call(t,e){return W(()=>{t=Lt(t);let n,o=this.bias==null?null:this.bias.read(),s=$y(this.activation.getClassName());if(s!=null&&this.rank===2)n=ND(t,this.kernel.read(),o,this.strides,this.padding,this.dataFormat,this.dilationRate,s);else{if(this.rank===1)n=q8(t,this.kernel.read(),o,this.strides[0],this.padding,this.dataFormat,this.dilationRate[0]);else if(this.rank===2)n=ND(t,this.kernel.read(),o,this.strides,this.padding,this.dataFormat,this.dilationRate);else if(this.rank===3)n=K8(t,this.kernel.read(),o,this.strides,this.padding,this.dataFormat,this.dilationRate);else throw new kt("convolutions greater than 3D are not implemented yet.");this.activation!=null&&(n=this.activation.apply(n))}return n})}computeOutputShape(t){t=te(t);let e=[],n=this.dataFormat==="channelsLast"?t.slice(1,t.length-1):t.slice(2);for(let s=0;s<n.length;++s){let i=Tn(n[s],this.kernelSize[s],this.padding,this.strides[s],typeof this.dilationRate=="number"?this.dilationRate:this.dilationRate[s]);e.push(i)}let o=[t[0]];return this.dataFormat==="channelsLast"?(o=o.concat(e),o.push(this.filters)):(o.push(this.filters),o=o.concat(e)),o}getConfig(){let t={filters:this.filters,kernelInitializer:_e(this.kernelInitializer),kernelRegularizer:de(this.kernelRegularizer),kernelConstraint:Ge(this.kernelConstraint)},e=super.getConfig();return Object.assign(t,e),t}static verifyArgs(t){if(!("filters"in t)||typeof t.filters!="number"||t.filters<1)throw new z(`Convolution layer expected config.filters to be a 'number' > 0 but got ${JSON.stringify(t.filters)}`)}},rl=class extends bu{constructor(t){super(2,t),rl.verifyArgs(t)}getConfig(){let t=super.getConfig();return delete t.rank,t}static verifyArgs(t){if(typeof t.kernelSize!="number"&&!Ay(t.kernelSize,"number",1,2))throw new z(`Conv2D expects config.kernelSize to be number or number[] with length 1 or 2, but received ${JSON.stringify(t.kernelSize)}.`)}};rl.className="Conv2D";et.registerClass(rl);var nl=class extends bu{constructor(t){super(3,t),nl.verifyArgs(t)}getConfig(){let t=super.getConfig();return delete t.rank,t}static verifyArgs(t){if(typeof t.kernelSize!="number"&&!(Array.isArray(t.kernelSize)&&(t.kernelSize.length===1||t.kernelSize.length===3)))throw new z(`Conv3D expects config.kernelSize to be number or [number, number, number], but received ${JSON.stringify(t.kernelSize)}.`)}};nl.className="Conv3D";et.registerClass(nl);var cf=class extends rl{constructor(t){if(super(t),this.inputSpec=[new we({ndim:4})],this.padding!=="same"&&this.padding!=="valid")throw new z(`Conv2DTranspose currently supports only padding modes 'same' and 'valid', but received padding mode ${this.padding}`)}build(t){if(t=te(t),t.length!==4)throw new z("Input should have rank 4; Received input shape: "+JSON.stringify(t));let e=this.dataFormat==="channelsFirst"?1:t.length-1;if(t[e]==null)throw new z("The channel dimension of the inputs should be defined. Found `None`.");let n=t[e],o=this.kernelSize.concat([this.filters,n]);this.kernel=this.addWeight("kernel",o,"float32",this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[new we({ndim:4,axes:{[e]:n}})],this.built=!0}call(t,e){return W(()=>{let n=Lt(t);if(n.shape.length!==4)throw new z(`Conv2DTranspose.call() expects input tensor to be rank-4, but received a tensor of rank-${n.shape.length}`);let o=n.shape,s=o[0],i,a;this.dataFormat==="channelsFirst"?(i=2,a=3):(i=1,a=2);let u=o[i],l=o[a],c=this.kernelSize[0],p=this.kernelSize[1],m=this.strides[0],f=this.strides[1],d=ti(u,m,c,this.padding),h=ti(l,f,p,this.padding),g=[s,d,h,this.filters];this.dataFormat!=="channelsLast"&&(n=Mt(n,[0,2,3,1]));let y=pm(n,this.kernel.read(),g,this.strides,this.padding);return this.dataFormat!=="channelsLast"&&(y=Mt(y,[0,3,1,2])),this.bias!=null&&(y=fn(y,this.bias.read(),this.dataFormat)),this.activation!=null&&(y=this.activation.apply(y)),y})}computeOutputShape(t){t=te(t);let e=t.slice(),n,o,s;this.dataFormat==="channelsFirst"?(n=1,o=2,s=3):(n=3,o=1,s=2);let i=this.kernelSize[0],a=this.kernelSize[1],u=this.strides[0],l=this.strides[1];return e[n]=this.filters,e[o]=ti(e[o],u,i,this.padding),e[s]=ti(e[s],l,a,this.padding),e}getConfig(){let t=super.getConfig();return delete t.dilationRate,t}};cf.className="Conv2DTranspose";et.registerClass(cf);var pf=class extends nl{constructor(t){if(super(t),this.inputSpec=[new we({ndim:5})],this.padding!=="same"&&this.padding!=="valid")throw new z(`Conv3DTranspose currently supports only padding modes 'same' and 'valid', but received padding mode ${this.padding}`)}build(t){if(t=te(t),t.length!==5)throw new z("Input should have rank 5; Received input shape: "+JSON.stringify(t));let e=this.dataFormat==="channelsFirst"?1:t.length-1;if(t[e]==null)throw new z("The channel dimension of the inputs should be defined. Found `None`.");let n=t[e],o=this.kernelSize.concat([this.filters,n]);this.kernel=this.addWeight("kernel",o,"float32",this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[new we({ndim:5,axes:{[e]:n}})],this.built=!0}call(t,e){return W(()=>{let n=Lt(t);if(n.shape.length!==5)throw new z(`Conv3DTranspose.call() expects input tensor to be rank-4, but received a tensor of rank-${n.shape.length}`);let o=n.shape,s=o[0],i,a,u;this.dataFormat==="channelsFirst"?(u=2,i=3,a=4):(u=1,i=2,a=3);let l=o[u],c=o[i],p=o[a],m=this.kernelSize[0],f=this.kernelSize[1],d=this.kernelSize[2],h=this.strides[0],g=this.strides[1],y=this.strides[2],b=ti(l,h,m,this.padding),w=ti(c,g,f,this.padding),v=ti(p,y,d,this.padding),N=[s,b,w,v,this.filters];this.dataFormat!=="channelsLast"&&(n=Mt(n,[0,2,3,4,1]));let E=Px(n,this.kernel.read(),N,this.strides,this.padding);return this.dataFormat!=="channelsLast"&&(E=Mt(E,[0,4,1,2,3])),this.bias!==null&&(E=fn(E,this.bias.read(),this.dataFormat)),this.activation!==null&&(E=this.activation.apply(E)),E})}computeOutputShape(t){t=te(t);let e=t.slice(),n,o,s,i;this.dataFormat==="channelsFirst"?(n=1,o=2,s=3,i=4):(n=4,o=1,s=2,i=3);let a=this.kernelSize[0],u=this.kernelSize[1],l=this.kernelSize[2],c=this.strides[0],p=this.strides[1],m=this.strides[2];return e[n]=this.filters,e[o]=ti(e[o],c,a,this.padding),e[s]=ti(e[s],p,u,this.padding),e[i]=ti(e[i],m,l,this.padding),e}getConfig(){let t=super.getConfig();return delete t.dilationRate,t}};pf.className="Conv3DTranspose";et.registerClass(pf);var Cb=class extends bu{constructor(t,e){if(super(t,e),this.DEFAULT_DEPTHWISE_INITIALIZER="glorotUniform",this.DEFAULT_POINTWISE_INITIALIZER="glorotUniform",this.depthwiseKernel=null,this.pointwiseKernel=null,e.filters==null)throw new z("The `filters` configuration field is required by SeparableConv, but is unspecified.");if(e.kernelInitializer!=null||e.kernelRegularizer!=null||e.kernelConstraint!=null)throw new z("Fields kernelInitializer, kernelRegularizer and kernelConstraint are invalid for SeparableConv2D. Use depthwiseInitializer, depthwiseRegularizer, depthwiseConstraint, pointwiseInitializer, pointwiseRegularizer and pointwiseConstraint instead.");if(e.padding!=null&&e.padding!=="same"&&e.padding!=="valid")throw new z(`SeparableConv${this.rank}D supports only padding modes: 'same' and 'valid', but received ${JSON.stringify(e.padding)}`);this.depthMultiplier=e.depthMultiplier==null?1:e.depthMultiplier,this.depthwiseInitializer=ge(e.depthwiseInitializer||this.DEFAULT_DEPTHWISE_INITIALIZER),this.depthwiseRegularizer=ve(e.depthwiseRegularizer),this.depthwiseConstraint=We(e.depthwiseConstraint),this.pointwiseInitializer=ge(e.depthwiseInitializer||this.DEFAULT_POINTWISE_INITIALIZER),this.pointwiseRegularizer=ve(e.pointwiseRegularizer),this.pointwiseConstraint=We(e.pointwiseConstraint)}build(t){if(t=te(t),t.length<this.rank+2)throw new z(`Inputs to SeparableConv${this.rank}D should have rank ${this.rank+2}, but received input shape: ${JSON.stringify(t)}`);let e=this.dataFormat==="channelsFirst"?1:t.length-1;if(t[e]==null||t[e]<0)throw new z(`The channel dimension of the inputs should be defined, but found ${JSON.stringify(t[e])}`);let n=t[e],o=this.kernelSize.concat([n,this.depthMultiplier]),s=[];for(let a=0;a<this.rank;++a)s.push(1);s.push(n*this.depthMultiplier,this.filters);let i=!0;this.depthwiseKernel=this.addWeight("depthwise_kernel",o,"float32",this.depthwiseInitializer,this.depthwiseRegularizer,i,this.depthwiseConstraint),this.pointwiseKernel=this.addWeight("pointwise_kernel",s,"float32",this.pointwiseInitializer,this.pointwiseRegularizer,i,this.pointwiseConstraint),this.useBias?this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,i,this.biasConstraint):this.bias=null,this.inputSpec=[new we({ndim:this.rank+2,axes:{[e]:n}})],this.built=!0}call(t,e){return W(()=>{t=Lt(t);let n;if(this.rank===1)throw new kt("1D separable convolution is not implemented yet.");return this.rank===2&&(this.dataFormat==="channelsFirst"&&(t=Mt(t,[0,2,3,1])),n=Cm(t,this.depthwiseKernel.read(),this.pointwiseKernel.read(),this.strides,this.padding,this.dilationRate,"NHWC")),this.useBias&&(n=fn(n,this.bias.read(),this.dataFormat)),this.activation!=null&&(n=this.activation.apply(n)),this.dataFormat==="channelsFirst"&&(n=Mt(n,[0,3,1,2])),n})}getConfig(){let t=super.getConfig();return delete t.rank,delete t.kernelInitializer,delete t.kernelRegularizer,delete t.kernelConstraint,t.depthwiseInitializer=_e(this.depthwiseInitializer),t.pointwiseInitializer=_e(this.pointwiseInitializer),t.depthwiseRegularizer=de(this.depthwiseRegularizer),t.pointwiseRegularizer=de(this.pointwiseRegularizer),t.depthwiseConstraint=Ge(this.depthwiseConstraint),t.pointwiseConstraint=Ge(this.pointwiseConstraint),t}};Cb.className="SeparableConv";var mf=class extends Cb{constructor(t){super(2,t)}};mf.className="SeparableConv2D";et.registerClass(mf);var wu=class extends bu{constructor(t){super(1,t),wu.verifyArgs(t),this.inputSpec=[{ndim:3}]}getConfig(){let t=super.getConfig();return delete t.rank,delete t.dataFormat,t}static verifyArgs(t){if(typeof t.kernelSize!="number"&&!Ay(t.kernelSize,"number",1,1))throw new z(`Conv1D expects config.kernelSize to be number or number[] with length 1, but received ${JSON.stringify(t.kernelSize)}.`)}};wu.className="Conv1D";et.registerClass(wu);var ff=class extends Bt{constructor(t){super(t),typeof t.cropping=="number"?this.cropping=[[t.cropping,t.cropping],[t.cropping,t.cropping]]:typeof t.cropping[0]=="number"?this.cropping=[[t.cropping[0],t.cropping[0]],[t.cropping[1],t.cropping[1]]]:this.cropping=t.cropping,this.dataFormat=t.dataFormat===void 0?"channelsLast":t.dataFormat,this.inputSpec=[{ndim:4}]}computeOutputShape(t){return this.dataFormat==="channelsFirst"?[t[0],t[1],t[2]-this.cropping[0][0]-this.cropping[0][1],t[3]-this.cropping[1][0]-this.cropping[1][1]]:[t[0],t[1]-this.cropping[0][0]-this.cropping[0][1],t[2]-this.cropping[1][0]-this.cropping[1][1],t[3]]}call(t,e){return W(()=>{if(t=Lt(t),this.dataFormat==="channelsLast"){let n=Sh(t,this.cropping[0][0],t.shape[1]-this.cropping[0][0]-this.cropping[0][1],2);return Sh(n,this.cropping[1][0],t.shape[2]-this.cropping[1][1]-this.cropping[1][0],3)}else{let n=Sh(t,this.cropping[0][0],t.shape[2]-this.cropping[0][0]-this.cropping[0][1],3);return Sh(n,this.cropping[1][0],t.shape[3]-this.cropping[1][1]-this.cropping[1][0],4)}})}getConfig(){let t={cropping:this.cropping,dataFormat:this.dataFormat},e=super.getConfig();return Object.assign(t,e),t}};ff.className="Cropping2D";et.registerClass(ff);var df=class extends Bt{constructor(t){super(t),this.DEFAULT_SIZE=[2,2],this.inputSpec=[{ndim:4}],this.size=t.size==null?this.DEFAULT_SIZE:t.size,this.dataFormat=t.dataFormat==null?"channelsLast":t.dataFormat,Le(this.dataFormat),this.interpolation=t.interpolation==null?"nearest":t.interpolation,F$(this.interpolation)}computeOutputShape(t){if(this.dataFormat==="channelsFirst"){let e=t[2]==null?null:this.size[0]*t[2],n=t[3]==null?null:this.size[1]*t[3];return[t[0],t[1],e,n]}else{let e=t[1]==null?null:this.size[0]*t[1],n=t[2]==null?null:this.size[1]*t[2];return[t[0],e,n,t[3]]}}call(t,e){return W(()=>{let n=Lt(t),o=n.shape;if(this.dataFormat==="channelsFirst"){n=Mt(n,[0,2,3,1]);let s=this.size[0]*o[2],i=this.size[1]*o[3],a=this.interpolation==="nearest"?iu.resizeNearestNeighbor(n,[s,i]):iu.resizeBilinear(n,[s,i]);return Mt(a,[0,3,1,2])}else{let s=this.size[0]*o[1],i=this.size[1]*o[2];return this.interpolation==="nearest"?iu.resizeNearestNeighbor(n,[s,i]):iu.resizeBilinear(n,[s,i])}})}getConfig(){let t={size:this.size,dataFormat:this.dataFormat,interpolation:this.interpolation},e=super.getConfig();return Object.assign(t,e),t}};df.className="UpSampling2D";et.registerClass(df);function j8(r,t,e=[1,1],n="valid",o,s){return W(()=>{o==null&&(o=mn()),Le(o);let i=Rh(r,o);if(r.rank!==4)throw new z(`Input for depthwiseConv2d is required to be 4-D, but is instead ${r.rank}-D`);if(t.rank!==4)throw new z(`depthwiseKernel is required to be 4-D, but is instead ${t.rank}-D`);return i=Pi(i,t,e,n==="same"?"same":"valid","NHWC",s),o==="channelsFirst"&&(i=Mt(i,[0,3,1,2])),i})}var hf=class extends Nc{constructor(t){super(2,t),this.depthwiseKernel=null,this.depthMultiplier=t.depthMultiplier==null?1:t.depthMultiplier,this.depthwiseInitializer=ge(t.depthwiseInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.depthwiseConstraint=We(t.depthwiseConstraint),this.depthwiseRegularizer=ve(t.depthwiseRegularizer)}build(t){if(t=te(t),t.length<4)throw new z(`Inputs to DepthwiseConv2D should have rank 4. Received input shape: ${JSON.stringify(t)}.`);let e=this.dataFormat==="channelsFirst"?1:3;if(t[e]==null||t[e]<0)throw new z(`The channel dimension of the inputs to DepthwiseConv2D should be defined, but is not (${t[e]}).`);let n=t[e],o=[this.kernelSize[0],this.kernelSize[1],n,this.depthMultiplier];this.depthwiseKernel=this.addWeight("depthwise_kernel",o,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(t,e){return W(()=>{t=Lt(t);let n=j8(t,this.depthwiseKernel.read(),this.strides,this.padding,this.dataFormat,null);return this.useBias&&(n=fn(n,this.bias.read(),this.dataFormat)),this.activation!=null&&(n=this.activation.apply(n)),n})}computeOutputShape(t){t=te(t);let e=this.dataFormat==="channelsFirst"?t[2]:t[1],n=this.dataFormat==="channelsFirst"?t[3]:t[2],o=this.dataFormat==="channelsFirst"?t[1]*this.depthMultiplier:t[3]*this.depthMultiplier,s=Tn(e,this.kernelSize[0],this.padding,this.strides[0]),i=Tn(n,this.kernelSize[1],this.padding,this.strides[1]);return this.dataFormat==="channelsFirst"?[t[0],o,s,i]:[t[0],s,i,o]}getConfig(){let t=super.getConfig();return t.depthMultiplier=this.depthMultiplier,t.depthwiseInitializer=_e(this.depthwiseInitializer),t.depthwiseRegularizer=de(this.depthwiseRegularizer),t.depthwiseConstraint=Ge(this.depthwiseRegularizer),t}};hf.className="DepthwiseConv2D";et.registerClass(hf);function US(r,t,e,n){if(Array.isArray(r)){if(t!=null||e!=null)throw new z("When inputs is an array, neither initialState or constants should be provided");n!=null&&(e=r.slice(r.length-n,r.length),r=r.slice(0,r.length-n)),r.length>1&&(t=r.slice(1,r.length)),r=r[0]}function o(s){return s==null||Array.isArray(s)?s:[s]}return t=o(t),e=o(e),{inputs:r,initialState:t,constants:e}}function HS(r,t,e,n=!1,o,s,i=!1,a=!1){return W(()=>{let u=t.shape.length;if(u<3)throw new z(`Input should be at least 3D, but is ${u}D.`);let l=[1,0].concat(jr(2,u));if(t=Mt(t,l),s!=null)throw new kt("The rnn() functoin of the deeplearn.js backend does not support constants yet.");i&&console.warn("Backend rnn(): the unroll = true option is not applicable to the imperative deeplearn.js backend."),o!=null&&(o=tt(tt(o,"bool"),"float32"),o.rank===u-1&&(o=yr(o,-1)),o=Mt(o,l)),n&&(t=pr(t,0),o!=null&&(o=pr(o,0)));let c=[],p,m=e,f=t.shape[0],d=Nr(t),h;o!=null&&(h=Nr(o));for(let y=0;y<f;++y){let b=d[y],w=W(()=>r(b,m));if(o==null)p=w[0],m=w[1];else{let v=W(()=>{let N=h[y],E=ut(br(N),N),$=Z(O(w[0],N),O(m[0],E)),D=m.map((L,M)=>Z(O(w[1][M],N),O(L,E)));return{output:$,newStates:D}});p=v.output,m=v.newStates}a&&c.push(p)}let g;return a&&(g=sr(c,1)),[p,g,m]})}var _n=class extends Bt{constructor(t){super(t);let e;if(t.cell==null)throw new z("cell property is missing for the constructor of RNN.");if(Array.isArray(t.cell)?e=new _c({cells:t.cell}):e=t.cell,e.stateSize==null)throw new z("The RNN cell should have an attribute `stateSize` (tuple of integers, one integer per RNN state).");this.cell=e,this.returnSequences=t.returnSequences==null?!1:t.returnSequences,this.returnState=t.returnState==null?!1:t.returnState,this.goBackwards=t.goBackwards==null?!1:t.goBackwards,this._stateful=t.stateful==null?!1:t.stateful,this.unroll=t.unroll==null?!1:t.unroll,this.supportsMasking=!0,this.inputSpec=[new we({ndim:3})],this.stateSpec=null,this.states_=null,this.numConstants=null,this.keptStates=[]}getStates(){if(this.states_==null){let t=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1;return jr(0,t).map(e=>null)}else return this.states_}setStates(t){this.states_=t}computeOutputShape(t){By(t)&&(t=t[0]),t=t;let e=this.cell.stateSize;Array.isArray(e)||(e=[e]);let n=e[0],o;if(this.returnSequences?o=[t[0],t[1],n]:o=[t[0],n],this.returnState){let s=[];for(let i of e)s.push([t[0],i]);return[o].concat(s)}else return o}computeMask(t,e){return W(()=>{Array.isArray(e)&&(e=e[0]);let n=this.returnSequences?e:null;if(this.returnState){let o=this.states.map(s=>null);return[n].concat(o)}else return n})}get states(){if(this.states_==null){let t=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1,e=[];for(let n=0;n<t;++n)e.push(null);return e}else return this.states_}set states(t){this.states_=t}build(t){if(this.numConstants!=null)throw new kt("Constants support is not implemented in RNN yet.");By(t)&&(t=t[0]),t=t;let n=this.stateful?t[0]:null,o=t.slice(2);this.inputSpec[0]=new we({shape:[n,null,...o]});let s=[t[0]].concat(t.slice(2));this.cell.build(s);let i;if(Array.isArray(this.cell.stateSize)?i=this.cell.stateSize:i=[this.cell.stateSize],this.stateSpec!=null){if(!x.arraysEqual(this.stateSpec.map(a=>a.shape[a.shape.length-1]),i))throw new z(`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=i.map(a=>new we({shape:[null,a]}));this.stateful&&this.resetStates()}resetStates(t,e=!1){W(()=>{if(!this.stateful)throw new kn("Cannot call resetStates() on an RNN Layer that is not stateful.");let n=this.inputSpec[0].shape[0];if(n==null)throw new z("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(o=>Te([n,o])):this.states_=[Te([n,this.cell.stateSize])];else if(t==null)_t(this.states_),this.keptStates!=null&&(_t(this.keptStates),this.keptStates=[]),Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(o=>Te([n,o])):this.states_[0]=Te([n,this.cell.stateSize]);else{if(Array.isArray(t)||(t=[t]),t.length!==this.states_.length)throw new z(`Layer ${this.name} expects ${this.states_.length} state(s), but it received ${t.length} state value(s). Input received: ${t}`);e===!0?this.keptStates.push(this.states_.slice()):_t(this.states_);for(let o=0;o<this.states_.length;++o){let s=t[o],i=Array.isArray(this.cell.stateSize)?this.cell.stateSize[o]:this.cell.stateSize,a=[n,i];if(!x.arraysEqual(s.shape,a))throw new z(`State ${o} is incompatible with layer ${this.name}: expected shape=${a}, received shape=${s.shape}`);this.states_[o]=s}}this.states_=this.states_.map(o=>Oe(o.clone()))})}apply(t,e){let n=e==null?null:e.initialState,o=e==null?null:e.constants;e==null&&(e={});let s=US(t,n,o,this.numConstants);t=s.inputs,n=s.initialState,o=s.constants;let i=[],a=[];if(n!=null){e.initialState=n,i=i.concat(n),this.stateSpec=[];for(let l of n)this.stateSpec.push(new we({shape:l.shape}));a=a.concat(this.stateSpec)}if(o!=null&&(e.constants=o,i=i.concat(o),this.numConstants=o.length),i[0]instanceof Xr){let l=[t].concat(i),c=this.inputSpec.concat(a),p=this.inputSpec;this.inputSpec=c;let m=super.apply(l,e);return this.inputSpec=p,m}else return super.apply(t,e)}call(t,e){return W(()=>{let n=e==null?null:e.mask,o=e==null?null:e.training,s=e==null?null:e.initialState;t=Lt(t),s==null&&(this.stateful?s=this.states_:s=this.getInitialState(t));let i=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1;if(s.length!==i)throw new z(`RNN Layer has ${i} state(s) but was passed ${s.length} initial state(s).`);this.unroll&&console.warn("Ignoring unroll = true for RNN layer, due to imperative backend.");let a={training:o},l=HS((d,h)=>{let g=this.cell.call([d].concat(h),a);return[g[0],g.slice(1)]},t,s,this.goBackwards,n,null,this.unroll,this.returnSequences),c=l[0],p=l[1],m=l[2];this.stateful&&this.resetStates(m,o);let f=this.returnSequences?p:c;return this.returnState?[f].concat(m):f})}getInitialState(t){return W(()=>{let e=Te(t.shape);return e=mt(e,[1,2]),e=Qa(e),Array.isArray(this.cell.stateSize)?this.cell.stateSize.map(n=>n>1?Py(e,[1,n]):e):this.cell.stateSize>1?[Py(e,[1,this.cell.stateSize])]:[e]})}get trainableWeights(){return this.trainable?this.cell.trainableWeights:[]}get nonTrainableWeights(){return this.trainable?this.cell.nonTrainableWeights:this.cell.weights}setFastWeightInitDuringBuild(t){super.setFastWeightInitDuringBuild(t),this.cell!=null&&this.cell.setFastWeightInitDuringBuild(t)}getConfig(){let t=super.getConfig(),e={returnSequences:this.returnSequences,returnState:this.returnState,goBackwards:this.goBackwards,stateful:this.stateful,unroll:this.unroll};this.numConstants!=null&&(e.numConstants=this.numConstants);let n=this.cell.getConfig();return this.getClassName()===_n.className&&(e.cell={className:this.cell.getClassName(),config:n}),Object.assign({},n,t,e)}static fromConfig(t,e,n={}){let o=e.cell,s=xn(o,n);return new t(Object.assign(e,{cell:s}))}};_n.className="RNN";et.registerClass(_n);var ol=class extends Bt{},kc=class extends ol{constructor(t){super(t),this.DEFAULT_ACTIVATION="tanh",this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_RECURRENT_INITIALIZER="orthogonal",this.DEFAULT_BIAS_INITIALIZER="zeros",this.units=t.units,Je(this.units,"units"),this.activation=Qs(t.activation==null?this.DEFAULT_ACTIVATION:t.activation),this.useBias=t.useBias==null?!0:t.useBias,this.kernelInitializer=ge(t.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=ge(t.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=ge(t.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelRegularizer=ve(t.kernelRegularizer),this.recurrentRegularizer=ve(t.recurrentRegularizer),this.biasRegularizer=ve(t.biasRegularizer),this.kernelConstraint=We(t.kernelConstraint),this.recurrentConstraint=We(t.recurrentConstraint),this.biasConstraint=We(t.biasConstraint),this.dropout=mc([1,Ys([0,t.dropout==null?0:t.dropout])]),this.recurrentDropout=mc([1,Ys([0,t.recurrentDropout==null?0:t.recurrentDropout])]),this.dropoutFunc=t.dropoutFunc,this.stateSize=this.units,this.dropoutMask=null,this.recurrentDropoutMask=null}build(t){t=te(t),this.kernel=this.addWeight("kernel",[t[t.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(t,e){return W(()=>{if(t=t,t.length!==2)throw new z(`SimpleRNNCell expects 2 input Tensors, got ${t.length}.`);let n=t[1];t=t[0];let o=e.training==null?!1:e.training;0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=il({ones:()=>br(t),rate:this.dropout,training:o,dropoutFunc:this.dropoutFunc})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=il({ones:()=>br(n),rate:this.recurrentDropout,training:o,dropoutFunc:this.dropoutFunc}));let s,i=this.dropoutMask,a=this.recurrentDropoutMask;i!=null?s=No(O(t,i),this.kernel.read()):s=No(t,this.kernel.read()),this.bias!=null&&(s=fn(s,this.bias.read())),a!=null&&(n=O(n,a));let u=Z(s,No(n,this.recurrentKernel.read()));return this.activation!=null&&(u=this.activation.apply(u)),[u,u]})}getConfig(){let t=super.getConfig(),e={units:this.units,activation:Js(this.activation),useBias:this.useBias,kernelInitializer:_e(this.kernelInitializer),recurrentInitializer:_e(this.recurrentInitializer),biasInitializer:_e(this.biasInitializer),kernelRegularizer:de(this.kernelRegularizer),recurrentRegularizer:de(this.recurrentRegularizer),biasRegularizer:de(this.biasRegularizer),activityRegularizer:de(this.activityRegularizer),kernelConstraint:Ge(this.kernelConstraint),recurrentConstraint:Ge(this.recurrentConstraint),biasConstraint:Ge(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout};return Object.assign({},t,e)}};kc.className="SimpleRNNCell";et.registerClass(kc);var gf=class extends _n{constructor(t){t.cell=new kc(t),super(t)}call(t,e){return W(()=>{this.cell.dropoutMask!=null&&(_t(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(_t(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=e==null?null:e.mask,o=e==null?null:e.training,s=e==null?null:e.initialState;return super.call(t,{mask:n,training:o,initialState:s})})}static fromConfig(t,e){return new t(e)}};gf.className="SimpleRNN";et.registerClass(gf);var Tc=class extends ol{constructor(t){if(super(t),this.DEFAULT_ACTIVATION="tanh",this.DEFAULT_RECURRENT_ACTIVATION="hardSigmoid",this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_RECURRENT_INITIALIZER="orthogonal",this.DEFAULT_BIAS_INITIALIZER="zeros",t.resetAfter)throw new z("GRUCell does not support reset_after parameter set to true.");this.units=t.units,Je(this.units,"units"),this.activation=Qs(t.activation===void 0?this.DEFAULT_ACTIVATION:t.activation),this.recurrentActivation=Qs(t.recurrentActivation===void 0?this.DEFAULT_RECURRENT_ACTIVATION:t.recurrentActivation),this.useBias=t.useBias==null?!0:t.useBias,this.kernelInitializer=ge(t.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=ge(t.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=ge(t.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelRegularizer=ve(t.kernelRegularizer),this.recurrentRegularizer=ve(t.recurrentRegularizer),this.biasRegularizer=ve(t.biasRegularizer),this.kernelConstraint=We(t.kernelConstraint),this.recurrentConstraint=We(t.recurrentConstraint),this.biasConstraint=We(t.biasConstraint),this.dropout=mc([1,Ys([0,t.dropout==null?0:t.dropout])]),this.recurrentDropout=mc([1,Ys([0,t.recurrentDropout==null?0:t.recurrentDropout])]),this.dropoutFunc=t.dropoutFunc,this.implementation=t.implementation,this.stateSize=this.units,this.dropoutMask=null,this.recurrentDropoutMask=null}build(t){t=te(t);let e=t[t.length-1];this.kernel=this.addWeight("kernel",[e,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(t,e){return W(()=>{if(t=t,t.length!==2)throw new z(`GRUCell expects 2 input Tensors (inputs, h, c), got ${t.length}.`);let n=e.training==null?!1:e.training,o=t[1];t=t[0],0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=il({ones:()=>br(t),rate:this.dropout,training:n,count:3,dropoutFunc:this.dropoutFunc})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=il({ones:()=>br(o),rate:this.recurrentDropout,training:n,count:3,dropoutFunc:this.dropoutFunc}));let s=this.dropoutMask,i=this.recurrentDropoutMask,a,u,l;0<this.dropout&&this.dropout<1&&(t=O(t,s[0]));let c=No(t,this.kernel.read());this.useBias&&(c=fn(c,this.bias.read())),0<this.recurrentDropout&&this.recurrentDropout<1&&(o=O(o,i[0]));let p=this.recurrentKernel.read(),[m,f]=mr(p,[2*this.units,this.units],p.rank-1),d=No(o,m),[h,g,y]=mr(c,3,c.rank-1),[b,w]=mr(d,2,d.rank-1);a=this.recurrentActivation.apply(Z(h,b)),u=this.recurrentActivation.apply(Z(g,w));let v=No(O(u,o),f);l=this.activation.apply(Z(y,v));let N=Z(O(a,o),O(Z(1,Yt(a)),l));return[N,N]})}getConfig(){let t=super.getConfig(),e={units:this.units,activation:Js(this.activation),recurrentActivation:Js(this.recurrentActivation),useBias:this.useBias,kernelInitializer:_e(this.kernelInitializer),recurrentInitializer:_e(this.recurrentInitializer),biasInitializer:_e(this.biasInitializer),kernelRegularizer:de(this.kernelRegularizer),recurrentRegularizer:de(this.recurrentRegularizer),biasRegularizer:de(this.biasRegularizer),activityRegularizer:de(this.activityRegularizer),kernelConstraint:Ge(this.kernelConstraint),recurrentConstraint:Ge(this.recurrentConstraint),biasConstraint:Ge(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation,resetAfter:!1};return Object.assign({},t,e)}};Tc.className="GRUCell";et.registerClass(Tc);var xf=class extends _n{constructor(t){t.implementation===0&&console.warn("`implementation=0` has been deprecated, and now defaults to `implementation=1`. 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Please update your layer call."),t.cell=new sl(t),super(t)}call(t,e){return W(()=>{this.cell.dropoutMask!=null&&(_t(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(_t(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=e==null?null:e.mask,o=e==null?null:e.training,s=e==null?null:e.initialState;return super.call(t,{mask:n,training:o,initialState:s})})}static fromConfig(t,e){return e.implmentation===0&&(e.implementation=1),new t(e)}};yf.className="LSTM";et.registerClass(yf);var _c=class extends ol{constructor(t){super(t),this.cells=t.cells}get stateSize(){let t=[];for(let e of this.cells.slice().reverse())Array.isArray(e.stateSize)?t.push(...e.stateSize):t.push(e.stateSize);return t}call(t,e){return W(()=>{t=t;let n=t.slice(1),o=[];for(let a of this.cells.slice().reverse())Array.isArray(a.stateSize)?o.push(n.splice(0,a.stateSize.length)):o.push(n.splice(0,1));o.reverse();let s=[],i;for(let a=0;a<this.cells.length;++a){let u=this.cells[a];n=o[a],a===0?i=[t[0]].concat(n):i=[i[0]].concat(n),i=u.call(i,e),s.push(i.slice(1))}n=[];for(let a of s.slice().reverse())n.push(...a);return[i[0]].concat(n)})}build(t){By(t)&&(t=t[0]),t=t;let e;this.cells.forEach((n,o)=>{Xs(`RNNCell_${o}`,()=>{n.build(t),Array.isArray(n.stateSize)?e=n.stateSize[0]:e=n.stateSize,t=[t[0],e]})}),this.built=!0}getConfig(){let t=super.getConfig(),e=s=>({className:s.getClassName(),config:s.getConfig()}),o={cells:this.cells.map(e)};return Object.assign({},t,o)}static fromConfig(t,e,n={}){let o=[];for(let s of e.cells)o.push(xn(s,n));return new t({cells:o})}get trainableWeights(){if(!this.trainable)return[];let t=[];for(let e of this.cells)t.push(...e.trainableWeights);return t}get nonTrainableWeights(){let t=[];for(let e of this.cells)t.push(...e.nonTrainableWeights);if(!this.trainable){let e=[];for(let n of this.cells)e.push(...n.trainableWeights);return e.concat(t)}return t}getWeights(){let t=[];for(let e of this.cells)t.push(...e.weights);return kh(t)}setWeights(t){let e=[];for(let n of this.cells){let o=n.weights.length,s=t.splice(o);for(let i=0;i<n.weights.length;++i)e.push([n.weights[i],s[i]])}qm(e)}};_c.className="StackedRNNCells";et.registerClass(_c);function il(r){let{ones:t,rate:e,training:n=!1,count:o=1,dropoutFunc:s}=r,i=()=>s!=null?s(t(),e):zy(t(),e),a=()=>du(i,t,n);return!o||o<=1?Oe(a().clone()):Array(o).fill(void 0).map(a).map(l=>Oe(l.clone()))}var X8=function(r,t){var e={};for(var n in r)Object.prototype.hasOwnProperty.call(r,n)&&t.indexOf(n)<0&&(e[n]=r[n]);if(r!=null&&typeof Object.getOwnPropertySymbols=="function")for(var o=0,n=Object.getOwnPropertySymbols(r);o<n.length;o++)t.indexOf(n[o])<0&&Object.prototype.propertyIsEnumerable.call(r,n[o])&&(e[n[o]]=r[n[o]]);return e};var Ib=class extends _n{constructor(t){if(t.unroll)throw new kt("Unrolling is not possible with convolutional RNNs.");if(Array.isArray(t.cell))throw new kt("It is not possible at the moment to stack convolutional cells.");super(t),this.inputSpec=[new we({ndim:5})]}call(t,e){return W(()=>{if(this.cell.dropoutMask!=null&&(_t(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(_t(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null),e&&e.constants)throw new z("ConvRNN2D cell does not support constants");let n=e==null?null:e.mask,o=e==null?null:e.training,s=e==null?null:e.initialState;return super.call(t,{mask:n,training:o,initialState:s})})}computeOutputShape(t){let e=this.computeSingleOutputShape(t);return this.returnSequences||(e=[e[0],...e.slice(2)]),this.returnState&&(e=[e,...Array(2).fill([t[0],...e.slice(-3)])]),e}getInitialState(t){return W(()=>{let{stateSize:e}=this.cell,n=t.shape,o=this.computeSingleOutputShape(n),s=[o[0],...o.slice(2)],i=Te(s);return Array.isArray(e)?Array(e.length).fill(i):[i]})}resetStates(t,e=!1){W(()=>{if(!this.stateful)throw new kn("Cannot call resetStates() on an RNN Layer that is not stateful.");let n=this.inputSpec[0].shape,o=this.computeSingleOutputShape(n),s=[o[0],...o.slice(2)];if(n[0]==null)throw new z("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(()=>Te(s)):this.states_=[Te(s)];else if(t==null)_t(this.states_),this.keptStates!=null&&(_t(this.keptStates),this.keptStates=[]),Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(()=>Te(s)):this.states_[0]=Te(s);else{if(Array.isArray(t)||(t=[t]),t.length!==this.states_.length)throw new z(`Layer ${this.name} expects ${this.states_.length} state(s), but it received ${t.length} state value(s). Input received: ${t}`);e?this.keptStates.push(this.states_.slice()):_t(this.states_);for(let a=0;a<this.states_.length;++a){let u=t[a],l=s;if(!x.arraysEqual(u.shape,l))throw new z(`State ${a} is incompatible with layer ${this.name}: expected shape=${l}, received shape=${u.shape}`);this.states_[a]=u}}this.states_=this.states_.map(a=>Oe(a.clone()))})}computeSingleOutputShape(t){let{dataFormat:e,filters:n,kernelSize:o,padding:s,strides:i,dilationRate:a}=this.cell,u=e==="channelsFirst",l=t[u?3:2],c=t[u?4:3],p=Tn(l,o[0],s,i[0],a[0]),m=Tn(c,o[1],s,i[1],a[1]);return[...t.slice(0,2),...u?[n,p,m]:[p,m,n]]}};Ib.className="ConvRNN2D";var Ec=class extends sl{constructor(t){let{filters:e,kernelSize:n,strides:o,padding:s,dataFormat:i,dilationRate:a}=t;super(Object.assign({},t,{units:e})),this.filters=e,Je(this.filters,"filters"),this.kernelSize=yu(n,2,"kernelSize"),this.kernelSize.forEach(u=>Je(u,"kernelSize")),this.strides=yu(o||1,2,"strides"),this.strides.forEach(u=>Je(u,"strides")),this.padding=s||"valid",pn(this.padding),this.dataFormat=i||"channelsLast",Le(this.dataFormat),this.dilationRate=yu(a||1,2,"dilationRate"),this.dilationRate.forEach(u=>Je(u,"dilationRate"))}build(t){var e;t=te(t);let n=this.dataFormat==="channelsFirst"?1:t.length-1;if(t[n]==null)throw new z(`The channel dimension of the input should be defined. Found ${t[n]}`);let o=t[n],s=4,i=this.kernelSize.concat([o,this.filters*s]);this.kernel=this.addWeight("kernel",i,null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint);let a=this.kernelSize.concat([this.filters,this.filters*s]);if(this.recurrentKernel=this.addWeight("recurrent_kernel",a,null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint),this.useBias){let u;if(this.unitForgetBias){let l=this.biasInitializer,c=this.filters;u=new(e=class extends hn{apply(m,f){let d=l.apply([c]),h=cr([c]),g=l.apply([c*2]);return Om([d,h,g])}},e.className="CustomInit",e)}else u=this.biasInitializer;this.bias=this.addWeight("bias",[this.filters*s],null,u,this.biasRegularizer,!0,this.biasConstraint)}this.built=!0}call(t,e){return W(()=>{if(t.length!==3)throw new z(`ConvLSTM2DCell expects 3 input Tensors (inputs, h, c), got ${t.length}.`);let n=e.training||!1,o=t[0],s=t[1],i=t[2],a=4;0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=il({ones:()=>br(o),rate:this.dropout,training:n,count:a,dropoutFunc:this.dropoutFunc}));let u=this.dropoutMask,l=(st,it,ft)=>!it||!it[ft]?st:O(it[ft],st),c=l(o,u,0),p=l(o,u,1),m=l(o,u,2),f=l(o,u,3);0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=il({ones:()=>br(s),rate:this.recurrentDropout,training:n,count:a,dropoutFunc:this.dropoutFunc}));let d=this.recurrentDropoutMask,h=l(s,d,0),g=l(s,d,1),y=l(s,d,2),b=l(s,d,3),w=3,[v,N,E,$]=mr(this.kernel.read(),a,w),[D,L,M,G]=this.useBias?mr(this.bias.read(),a):[null,null,null,null];c=this.inputConv(c,v,D,this.padding),p=this.inputConv(p,N,L,this.padding),m=this.inputConv(m,E,M,this.padding),f=this.inputConv(f,$,G,this.padding);let[H,q,X,j]=mr(this.recurrentKernel.read(),a,w);h=this.recurrentConv(h,H),g=this.recurrentConv(g,q),y=this.recurrentConv(y,X),b=this.recurrentConv(b,j);let J=this.recurrentActivation.apply(Z(c,h)),nt=this.recurrentActivation.apply(Z(p,g)),K=Z(O(nt,i),O(J,this.activation.apply(Z(m,y)))),ot=O(this.recurrentActivation.apply(Z(f,b)),this.activation.apply(K));return[ot,ot,K]})}getConfig(){let t=super.getConfig(),{units:e}=t,n=X8(t,["units"]),o={filters:this.filters,kernelSize:this.kernelSize,padding:this.padding,dataFormat:this.dataFormat,dilationRate:this.dilationRate,strides:this.strides};return Object.assign({},n,o)}inputConv(t,e,n,o){let s=Sn(t,e,this.strides,o||"valid",this.dataFormat==="channelsFirst"?"NCHW":"NHWC",this.dilationRate);return n?fn(s,n,this.dataFormat):s}recurrentConv(t,e){return Sn(t,e,1,"same",this.dataFormat==="channelsFirst"?"NCHW":"NHWC")}};Ec.className="ConvLSTM2DCell";et.registerClass(Ec);var bf=class extends Ib{constructor(t){let e=new Ec(t);super(Object.assign({},t,{cell:e}))}static fromConfig(t,e){return new t(e)}};bf.className="ConvLSTM2D";et.registerClass(bf);var Ac=class extends Bt{constructor(t){super(t),this.rate=Math.max(Math.min(t.rate,1),0),this.noiseShape=t.noiseShape,this.seed=t.seed,this.supportsMasking=!0}getNoiseShape(t){if(this.noiseShape==null)return this.noiseShape;let e=t.shape,n=[];for(let o=0;o<this.noiseShape.length;++o)n.push(this.noiseShape[o]==null?e[o]:this.noiseShape[o]);return n}call(t,e){return W(()=>{this.invokeCallHook(t,e);let n=Lt(t);if(0<this.rate&&this.rate<1){let o=e.training==null?!1:e.training,s=this.getNoiseShape(n);return du(()=>zy(n,this.rate,s,this.seed),()=>n,o)}return t})}getConfig(){let t={rate:this.rate,noiseShape:this.noiseShape,seed:this.seed},e=super.getConfig();return Object.assign(t,e),t}dispose(){return super.dispose()}};Ac.className="Dropout";et.registerClass(Ac);var wf=class extends Ac{constructor(t){super(t),this.inputSpec=[{ndim:3}]}getNoiseShape(t){let e=t.shape;return[e[0],1,e[2]]}};wf.className="SpatialDropout1D";et.registerClass(wf);var vf=class extends Bt{constructor(t){if(super(t),this.activation=null,this.useBias=!0,this.kernel=null,this.bias=null,this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_BIAS_INITIALIZER="zeros",t.batchInputShape==null&&t.inputShape==null&&t.inputDim!=null){let e=null;t.batchSize!=null&&(e=t.batchSize),this.batchInputShape=[e,t.inputDim]}this.units=t.units,Je(this.units,"units"),this.activation=Qs(t.activation),t.useBias!=null&&(this.useBias=t.useBias),this.kernelInitializer=ge(t.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.biasInitializer=ge(t.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelConstraint=We(t.kernelConstraint),this.biasConstraint=We(t.biasConstraint),this.kernelRegularizer=ve(t.kernelRegularizer),this.biasRegularizer=ve(t.biasRegularizer),this.activityRegularizer=ve(t.activityRegularizer),this.supportsMasking=!0,this.inputSpec=[{minNDim:2}]}build(t){t=te(t);let e=t[t.length-1];this.kernel==null&&(this.kernel=this.addWeight("kernel",[e,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]:e}}],this.built=!0}computeOutputShape(t){t=te(t);let e=t.slice();return e[e.length-1]=this.units,e}call(t,e){return W(()=>{this.invokeCallHook(t,e);let n=Lt(t),o=$y(this.activation.getClassName()),s;return o!=null?s=No(n,this.kernel.read(),o,this.bias?this.bias.read():null):(s=No(n,this.kernel.read()),this.bias!=null&&(s=fn(s,this.bias.read())),this.activation!=null&&(s=this.activation.apply(s))),s})}getConfig(){let t={units:this.units,activation:Js(this.activation),useBias:this.useBias,kernelInitializer:_e(this.kernelInitializer),biasInitializer:_e(this.biasInitializer),kernelRegularizer:de(this.kernelRegularizer),biasRegularizer:de(this.biasRegularizer),activityRegularizer:de(this.activityRegularizer),kernelConstraint:Ge(this.kernelConstraint),biasConstraint:Ge(this.biasConstraint)},e=super.getConfig();return Object.assign(t,e),t}};vf.className="Dense";et.registerClass(vf);var Cf=class extends Bt{constructor(t){t=t||{},super(t),this.inputSpec=[{minNDim:3}],this.dataFormat=t.dataFormat}computeOutputShape(t){t=te(t);for(let e of t.slice(1))if(e==null)throw new z(`The shape of the input to "Flatten" is not fully defined (got ${t.slice(1)}). 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n=Lt(t),o=n.shape,s=o.slice(0,1).concat(this.fixUnknownDimension(o.slice(1),this.targetShape));return R(n,s)})}getConfig(){let t={targetShape:this.targetShape},e=super.getConfig();return Object.assign(t,e),t}};Nf.className="Reshape";et.registerClass(Nf);var kf=class extends Bt{constructor(t){if(super(t),t.dims==null)throw new Error("Required configuration field `dims` is missing during Permute constructor call.");if(!Array.isArray(t.dims))throw new Error(`Permute constructor requires \`dims\` to be an Array, but received ${t.dims} instead.`);let e=jr(1,t.dims.length+1);if(!x.arraysEqual(t.dims.slice().sort(),e))throw new Error("Invalid permutation `dims`: "+JSON.stringify(t.dims)+" `dims` must contain consecutive integers starting from 1.");this.dims=t.dims,this.dimsIncludingBatch=[0].concat(this.dims),this.inputSpec=[new we({ndim:this.dims.length+1})]}computeOutputShape(t){t=te(t);let e=t.slice();return this.dims.forEach((n,o)=>{e[o+1]=t[n]}),e}call(t,e){return Mt(Lt(t),this.dimsIncludingBatch)}getConfig(){let t={dims:this.dims},e=super.getConfig();return Object.assign(t,e),t}};kf.className="Permute";et.registerClass(kf);var Tf=class extends Bt{constructor(t){super(t==null?{}:t),this.supportsMasking=!0,t!=null?this.maskValue=t.maskValue==null?0:t.maskValue:this.maskValue=0}computeOutputShape(t){return t}getConfig(){let t=super.getConfig(),e={maskValue:this.maskValue};return Object.assign(e,t),e}computeMask(t,e){let n=Lt(t),o=-1;return Yu(Hs(n,this.maskValue),o)}call(t,e){return W(()=>{this.invokeCallHook(t,e);let n=Lt(t),o=-1,s=!0,i=Yu(Hs(n,this.maskValue),o,s);return O(n,tt(i,n.dtype))})}};Tf.className="Masking";et.registerClass(Tf);var _f=class extends Bt{constructor(t){if(super(t),this.embeddings=null,this.DEFAULT_EMBEDDINGS_INITIALIZER="randomUniform",t.batchInputShape==null&&t.inputShape==null){let 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al=class extends Bt{constructor(t){super(t||{}),this.supportsMasking=!0}mergeFunction(t){throw new kt}computeElementwiseOpOutputShape(t,e){if(t==null||e==null)return null;if(t.length<e.length)return this.computeElementwiseOpOutputShape(e,t);if(e.length===0)return t;let n=t.slice(0,t.length-e.length);for(let o=0;o<e.length;++o){let s=t[t.length-e.length+o],i=e[o];if(s==null||i==null||s<0||i<0)n.push(null);else if(s===1)n.push(i);else if(i===1)n.push(s);else{if(s!==i)throw new z("Operands could not be broadcast together with shapes "+JSON.stringify(t)+" "+JSON.stringify(e));n.push(s)}}return n}build(t){if(Array.isArray(t)&&!Array.isArray(t[0])&&(t=[te(t)]),t=t,t.length<2)throw new z(`A merge layer should be called on an Array of at least 2 inputs. 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t={axis:this.axis},e=super.getConfig();return Object.assign(t,e),t}};Rf.className="Concatenate";et.registerClass(Rf);function Oh(r,t){for(;r<0;)r+=t;return r}function Y8(r,t,e){if(r.shape.length>3||t.shape.length>3)throw new kt("batchDot is not implemented for tensors of 4D or higher rank yet");if(x.assert(r.shape.length>=2,()=>`batchDot requires the rank of x to be >= 2, but got ${r.shape.length}`),x.assert(r.shape.length>=2,()=>`batchDot requires the rank of y to be >= 2, but got ${t.shape.length}`),typeof e=="number"&&(e=[e,e]),r.dtype==="complex64"||t.dtype==="complex64")throw new kt("batchDot is not implemented for complex64-type Tensors yet.");let n=r.shape.length,o=t.shape.length;e==null&&(e=[n-1,o-2]);let s=e;return W(()=>{let i;if(n>o){i=n-o;let u=[];for(let l=0;l<i;++l)u.push(1);t=R(t,t.shape.concat(u))}else if(o>n){i=o-n;let u=[];for(let l=0;l<i;++l)u.push(1);r=R(r,r.shape.concat(u))}else i=0;let a;if(r.shape.length===2&&t.shape.length===2)s[0]===s[1]?a=mt(O(r,t),s[0]):a=mt(O(Mt(r,[1,0]),t),s[1]);else{let u=s[0]!==r.shape.length-1,l=s[1]===t.shape.length-1;a=Gt(r,t,u,l)}if(i>0){let u;n>o?u=n+o-3:u=n-1;let l=[];for(let c=u;c<u+i;++c)l.push(c);a=Mn(a,l)}return a.shape.length===1&&(a=yr(a,1)),a})}var Of=class extends al{constructor(t){super(t),this.axes=t.axes,this.normalize=t.normalize==null?!1:t.normalize,this.supportsMasking=!0,this.reshapeRequired=!1}build(t){x.assert(Array.isArray(t)&&t.length===2&&Array.isArray(t[0])&&Array.isArray(t[1]),()=>"A `Dot` layer should be called on a list of exactly 2 inputs.");let e=t[0],n=t[1];if(e.length>3||n.length>3)throw new kt("Dot layer does not support tensors of 4D or higher rank yet.");let o=this.interpretAxes(e,n);if(e[o[0]]!==n[o[1]])throw new z(`Dimension incompatibility: ${e[o[0]]} !== ${n[o[1]]}`)}mergeFunction(t){if(t.length!==2)throw new z(`A \`Dot\` layer must be called on exactly 2 inputs, but received ${t.length} 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Bt{constructor(t){super(t),this.supportsMasking=!0,this.stddev=t.stddev}computeOutputShape(t){return t}getConfig(){let t=super.getConfig(),e={stddev:this.stddev};return Object.assign(e,t),e}call(t,e){return W(()=>{this.invokeCallHook(t,e);let n=Lt(t);return du(()=>Z(Lm(n.shape,0,this.stddev),n),()=>n,e.training||!1)})}};Lf.className="GaussianNoise";et.registerClass(Lf);var Pf=class extends Bt{constructor(t){super(t),this.supportsMasking=!0,this.rate=t.rate}computeOutputShape(t){return t}getConfig(){let t=super.getConfig(),e={rate:this.rate};return Object.assign(e,t),e}call(t,e){return W(()=>{this.invokeCallHook(t,e);let n=Lt(t);return this.rate>0&&this.rate<1?du(()=>{let s=Math.sqrt(this.rate/(1-this.rate));return O(n,Lm(n.shape,1,s))},()=>n,e.training||!1):n})}};Pf.className="GaussianDropout";et.registerClass(Pf);var Mf=class extends Bt{constructor(t){super(t),this.supportsMasking=!0,this.rate=t.rate,this.noiseShape=t.noiseShape}_getNoiseShape(t){return this.noiseShape||Lt(t).shape}computeOutputShape(t){return t}getConfig(){let t=super.getConfig(),e={rate:this.rate};return Object.assign(e,t),e}call(t,e){return W(()=>{if(this.rate<1&&this.rate>0){let n=this._getNoiseShape(t);return du(()=>{let s=Lt(t),i=1.6732632423543772,a=1.0507009873554805,u=-i*a,l=Ln(Wi(n),this.rate);l=fc(l,"float32");let c=((1-this.rate)*(1+this.rate*u**2))**-.5,p=-c*u*this.rate,m=Z(O(s,l),O(Z(l,-1),u));return Z(O(m,c),p)},()=>Lt(t),e.training||!1)}return t})}};Mf.className="AlphaDropout";et.registerClass(Mf);function Lh(r,t,e,n,o,s=.001){let i;if(r.rank===2)i=kx(r,t,e,n,o,s);else if(r.rank===3)i=Tx(r,t,e,n,o,s);else if(r.rank===4)i=_x(r,t,e,n,o,s);else throw new kt(`batchNormalization is not implemented for array of rank ${r.rank} yet`);return i}function Z8(r,t,e,n,o=.001){return W(()=>{let s=rc(r,n),i=s.mean,a=s.variance;return[Lh(r,i,a,e,t,o),i,a]})}function J8(r,t,e,n,o=.001){return W(()=>{let s=rc(r,n),i=s.mean,a=s.variance,u=[];for(let d of 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e=this.axis>=0?this.axis:this.axis+t.length,n=t[e];if(n==null)throw new z(`Axis ${e} of input tensor should have a defined dimension but the layer received an input with shape ${JSON.stringify(t)}.`);this.inputSpec=[new we({ndim:t.length,axes:{[e]:n}})];let o=[n];this.scale&&(this.gamma=this.addWeight("gamma",o,null,this.gammaInitializer,this.gammaRegularizer,!0,this.gammaConstraint)),this.center&&(this.beta=this.addWeight("beta",o,null,this.betaInitializer,this.betaRegularizer,!0,this.betaConstraint)),this.movingMean=this.addWeight("moving_mean",o,null,this.movingMeanInitializer,null,!1),this.movingVariance=this.addWeight("moving_variance",o,null,this.movingVarianceInitializer,null,!1),this.built=!0}call(t,e){return W(()=>{let n=e.training==null?!1:e.training,o=Lt(t),s=o.shape,i=s.length,a=jr(0,i),u=this.axis>=0?this.axis:this.axis+i;a.splice(u,1);let l=vo(1,i);l[u]=s[u];let c=a.slice();c.sort();let p=!x.arraysEqual(c,jr(0,i).slice(0,i-1)),m=()=>{if(p){let 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t={axis:this.axis,momentum:this.momentum,epsilon:this.epsilon,center:this.center,scale:this.scale,betaInitializer:_e(this.betaInitializer),gammaInitializer:_e(this.gammaInitializer),movingMeanInitializer:_e(this.movingMeanInitializer),movingVarianceInitializer:_e(this.movingVarianceInitializer),betaRegularizer:de(this.betaRegularizer),gammaRegularizer:de(this.gammaRegularizer),betaConstraint:Ge(this.betaConstraint),gammaConstraint:Ge(this.gammaConstraint)},e=super.getConfig();return Object.assign(t,e),t}};zf.className="BatchNormalization";et.registerClass(zf);var Bf=class extends Bt{constructor(t){if(t==null&&(t={}),super(t),this.axis=t.axis==null?-1:t.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 e of this.axis)if(!Number.isInteger(e))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=t.epsilon==null?.001:t.epsilon,this.center=t.center==null?!0:t.center,this.scale=t.scale==null?!0:t.scale,this.betaInitializer=ge(t.betaInitializer||"zeros"),this.gammaInitializer=ge(t.gammaInitializer||"ones"),this.betaRegularizer=ve(t.betaRegularizer),this.gammaRegularizer=ve(t.gammaRegularizer),this.supportsMasking=!0}build(t){t=te(t);let e=t.length;typeof this.axis=="number"&&(this.axis=[this.axis]);for(let s=0;s<this.axis.length;++s)this.axis[s]<0&&(this.axis[s]+=e);for(let s of this.axis)if(s<0||s>=e)throw new Error(`Invalid axis: ${s}`);if(this.axis.length!==Io(this.axis).length)throw new Error(`Found duplicate axes in: ${this.axis}`);let n=this.axis.map(s=>t[s]),o=!0;this.scale?this.gamma=this.addWeight("gamma",n,"float32",this.gammaInitializer,this.gammaRegularizer,o):this.gamma=null,this.center?this.beta=this.addWeight("beta",n,"float32",this.betaInitializer,this.betaRegularizer,o):this.beta=null,this.built=!0}call(t,e){let n=Lt(t),o=n.shape,s=o.length;return W(()=>{let{mean:a,variance:u}=rc(n,this.axis,!0),l=vo(1,s);for(let h of this.axis)l[h]=o[h];let c=h=>h!=null&&h.shape.length!==s?R(h,l):h,p=this.scale?c(this.gamma.read()):null,m=this.center?c(this.beta.read()):null,f=[],d=[];for(let h=0;h<s;++h)this.axis.indexOf(h)!==-1?(f.push(o[h]),d.push(1)):(f.push(1),d.push(o[h]));return a=$r(a,f),u=$r(u,f),p!=null&&(p=$r(p,d)),m!=null&&(m=$r(m,d)),Lh(n,a,u,m,p,this.epsilon)})}getConfig(){let t={axis:this.axis,epsilon:this.epsilon,center:this.center,scale:this.scale,betaInitializer:_e(this.betaInitializer),gammaInitializer:_e(this.gammaInitializer),betaRegularizer:de(this.betaRegularizer),gammaRegularizer:de(this.gammaRegularizer)},e=super.getConfig();return Object.assign(t,e),t}};Bf.className="LayerNormalization";et.registerClass(Bf);function tY(r,t,e){return W(()=>{if(r.rank!==4)throw new z(`temporalPadding expects input tensor to be 4-D, but received a ${r.rank}-D tensor.`);if(t==null&&(t=[[1,1],[1,1]]),t.length!==2||t[0].length!==2||t[1].length!==2)throw new z("spatial2dPadding expects `padding` to be an Array of two Arrays, each of which is an Array of two integers.");if(e==null&&(e=mn()),e!=="channelsLast"&&e!=="channelsFirst")throw new z(`Unknown data format: ${e}. 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s==="max"?i=Jl(r,t,e,a):i=Hl(r,t,e,a),o==="channelsFirst"&&(i=Mt(i,[0,3,1,2])),i})}function kD(r,t,e,n,o,s){return W(()=>{Le(o),kS(s),pn(n),e==null&&(e=[1,1,1]),n==null&&(n="valid"),o==null&&(o=mn()),s==null&&(s="max"),r=WS(r,o);let i,a=n==="same"?"same":"valid";return s==="max"?i=ty(r,t,e,a):i=Nx(r,t,e,a),o==="channelsFirst"&&(i=Mt(i,[0,4,1,2,3])),i})}var Sb=class extends Bt{constructor(t){if(t.poolSize==null&&(t.poolSize=2),super(t),typeof t.poolSize=="number")this.poolSize=[t.poolSize];else if(Array.isArray(t.poolSize)&&t.poolSize.length===1&&typeof t.poolSize[0]=="number")this.poolSize=t.poolSize;else throw new z(`poolSize for 1D convolutional layer must be a number or an Array of a single number, but received ${JSON.stringify(t.poolSize)}`);if(Je(this.poolSize,"poolSize"),t.strides==null)this.strides=this.poolSize;else if(typeof t.strides=="number")this.strides=[t.strides];else if(Array.isArray(t.strides)&&t.strides.length===1&&typeof t.strides[0]=="number")this.strides=t.strides;else throw new z(`strides for 1D convolutional layer must be a number or an Array of a single number, but received ${JSON.stringify(t.strides)}`);Je(this.strides,"strides"),this.padding=t.padding==null?"valid":t.padding,pn(this.padding),this.inputSpec=[new we({ndim:3})]}computeOutputShape(t){t=te(t);let e=Tn(t[1],this.poolSize[0],this.padding,this.strides[0]);return[t[0],e,t[2]]}call(t,e){return W(()=>{this.invokeCallHook(t,e),t=Qa(Lt(t),2);let n=this.poolingFunction(Lt(t),[this.poolSize[0],1],[this.strides[0],1],this.padding,"channelsLast");return Mn(n,[2])})}getConfig(){let t={poolSize:this.poolSize,padding:this.padding,strides:this.strides},e=super.getConfig();return Object.assign(t,e),t}},Gf=class extends Sb{constructor(t){super(t)}poolingFunction(t,e,n,o,s){return Le(s),pn(o),Eb(t,e,n,o,s,"max")}};Gf.className="MaxPooling1D";et.registerClass(Gf);var Wf=class extends Sb{constructor(t){super(t)}poolingFunction(t,e,n,o,s){return 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e=Tn(e,this.poolSize[0],this.padding,this.strides[0]),n=Tn(n,this.poolSize[1],this.padding,this.strides[1]),this.dataFormat==="channelsFirst"?[t[0],t[1],e,n]:[t[0],e,n,t[3]]}call(t,e){return W(()=>(this.invokeCallHook(t,e),this.poolingFunction(Lt(t),this.poolSize,this.strides,this.padding,this.dataFormat)))}getConfig(){let t={poolSize:this.poolSize,padding:this.padding,strides:this.strides,dataFormat:this.dataFormat},e=super.getConfig();return Object.assign(t,e),t}},Uf=class extends Nb{constructor(t){super(t)}poolingFunction(t,e,n,o,s){return Le(s),pn(o),Eb(t,e,n,o,s,"max")}};Uf.className="MaxPooling2D";et.registerClass(Uf);var Hf=class extends Nb{constructor(t){super(t)}poolingFunction(t,e,n,o,s){return Le(s),pn(o),Eb(t,e,n,o,s,"avg")}};Hf.className="AveragePooling2D";et.registerClass(Hf);var kb=class extends Bt{constructor(t){if(t.poolSize==null&&(t.poolSize=[2,2,2]),super(t),this.poolSize=Array.isArray(t.poolSize)?t.poolSize:[t.poolSize,t.poolSize,t.poolSize],t.strides==null)this.strides=this.poolSize;else if(Array.isArray(t.strides)){if(t.strides.length!==3)throw new z(`If the strides property of a 3D pooling layer is an Array, it is expected to have a length of 3, but received length ${t.strides.length}.`);this.strides=t.strides}else this.strides=[t.strides,t.strides,t.strides];Je(this.poolSize,"poolSize"),Je(this.strides,"strides"),this.padding=t.padding==null?"valid":t.padding,this.dataFormat=t.dataFormat==null?"channelsLast":t.dataFormat,Le(this.dataFormat),pn(this.padding),this.inputSpec=[new we({ndim:5})]}computeOutputShape(t){t=te(t);let e=this.dataFormat==="channelsFirst"?t[2]:t[1],n=this.dataFormat==="channelsFirst"?t[3]:t[2],o=this.dataFormat==="channelsFirst"?t[4]:t[3];return e=Tn(e,this.poolSize[0],this.padding,this.strides[0]),n=Tn(n,this.poolSize[1],this.padding,this.strides[1]),o=Tn(o,this.poolSize[2],this.padding,this.strides[2]),this.dataFormat==="channelsFirst"?[t[0],t[1],e,n,o]:[t[0],e,n,o,t[4]]}call(t,e){return W(()=>(this.invokeCallHook(t,e),this.poolingFunction(Lt(t),this.poolSize,this.strides,this.padding,this.dataFormat)))}getConfig(){let t={poolSize:this.poolSize,padding:this.padding,strides:this.strides,dataFormat:this.dataFormat},e=super.getConfig();return Object.assign(t,e),t}},qf=class extends kb{constructor(t){super(t)}poolingFunction(t,e,n,o,s){return Le(s),pn(o),kD(t,e,n,o,s,"max")}};qf.className="MaxPooling3D";et.registerClass(qf);var Kf=class extends kb{constructor(t){super(t)}poolingFunction(t,e,n,o,s){return Le(s),pn(o),kD(t,e,n,o,s,"avg")}};Kf.className="AveragePooling3D";et.registerClass(Kf);var Tb=class extends Bt{constructor(t){super(t),this.inputSpec=[new we({ndim:3})]}computeOutputShape(t){return[t[0],t[2]]}call(t,e){throw new kt}},jf=class extends Tb{constructor(t){super(t||{})}call(t,e){return W(()=>{let n=Lt(t);return ke(n,1)})}};jf.className="GlobalAveragePooling1D";et.registerClass(jf);var Xf=class extends Tb{constructor(t){super(t||{})}call(t,e){return W(()=>{let n=Lt(t);return Mr(n,1)})}};Xf.className="GlobalMaxPooling1D";et.registerClass(Xf);var _b=class extends Bt{constructor(t){super(t),this.dataFormat=t.dataFormat==null?"channelsLast":t.dataFormat,Le(this.dataFormat),this.inputSpec=[new we({ndim:4})]}computeOutputShape(t){return t=t,this.dataFormat==="channelsLast"?[t[0],t[3]]:[t[0],t[1]]}call(t,e){throw new kt}getConfig(){let t={dataFormat:this.dataFormat},e=super.getConfig();return Object.assign(t,e),t}},Yf=class extends _b{call(t,e){return W(()=>{let n=Lt(t);return this.dataFormat==="channelsLast"?ke(n,[1,2]):ke(n,[2,3])})}};Yf.className="GlobalAveragePooling2D";et.registerClass(Yf);var Zf=class extends _b{call(t,e){return W(()=>{let n=Lt(t);return 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t(i)}},Jf=class extends Ab{constructor(t){super(t),this.supportsMasking=!0}build(t){if(t=te(t),t.length<3)throw new z(`TimeDistributed layer expects an input shape >= 3D, but received input shape ${JSON.stringify(t)}`);this.inputSpec=[{shape:t}];let e=[t[0]].concat(t.slice(2));this.layer.built||(this.layer.build(e),this.layer.built=!0),super.build(t)}computeOutputShape(t){t=te(t);let e=[t[0]].concat(t.slice(2)),n=this.layer.computeOutputShape(e),o=t[1];return[n[0],o].concat(n.slice(1))}call(t,e){return W(()=>(t=Lt(t),HS((i,a)=>[Lt(this.layer.call(i,e)),[]],t,[],!1,null,null,!1,!0)[1]))}};Jf.className="TimeDistributed";et.registerClass(Jf);function eY(r){qi($$,"BidirectionalMergeMode",r)}var rY="concat",Qf=class extends Ab{constructor(t){super(t);let e=t.layer.getConfig(),n={};n.className=t.layer.getClassName(),n.config=e,this.forwardLayer=xn(n),e.goBackwards=e.goBackwards!==!0;let o={};if(o.className=t.layer.getClassName(),o.config=e,this.backwardLayer=xn(o),this.forwardLayer.name="forward_"+this.forwardLayer.name,this.backwardLayer.name="backward_"+this.backwardLayer.name,this.mergeMode=t.mergeMode===void 0?rY:t.mergeMode,eY(this.mergeMode),t.weights)throw new kt("weights support is not implemented for Bidirectional layer yet.");this._stateful=t.layer.stateful,this.returnSequences=t.layer.returnSequences,this.returnState=t.layer.returnState,this.supportsMasking=!0,this._trainable=!0,this.inputSpec=t.layer.inputSpec,this.numConstants=null}get trainable(){return this._trainable}set trainable(t){this._trainable=t,this.forwardLayer!=null&&(this.forwardLayer.trainable=t),this.backwardLayer!=null&&(this.backwardLayer.trainable=t)}getWeights(){return this.forwardLayer.getWeights().concat(this.backwardLayer.getWeights())}setWeights(t){let e=t.length,n=Math.floor(e/2);this.forwardLayer.setWeights(t.slice(0,n)),this.backwardLayer.setWeights(t.slice(n))}computeOutputShape(t){let e=this.forwardLayer.computeOutputShape(t);Array.isArray(e)&&Array.isArray(e[0])||(e=[e]),e=e;let n,o,s;return this.returnState&&(s=e.slice(1)),n=e[0],n=n,this.mergeMode==="concat"?(n[n.length-1]*=2,o=[n]):this.mergeMode==null?o=[n,n.slice()]:o=[n],this.returnState?this.mergeMode==null?o.concat(s).concat(s.slice()):[n].concat(s).concat(s.slice()):kr(o)}apply(t,e){let n=e==null?null:e.initialState,o=e==null?null:e.constants;e==null&&(e={});let s=US(t,n,o,this.numConstants);if(t=s.inputs,n=s.initialState,o=s.constants,Array.isArray(t)&&(n=t.slice(1),t=t[0]),(n==null||n.length===0)&&o==null)return super.apply(t,e);let i=[],a=[];if(n!=null){let l=n.length;if(l%2>0)throw new z("When passing `initialState` to a Bidrectional RNN, the state should be an Array containing the states of the underlying RNNs.");e.initialState=n,i.push(...n);let c=n.map(p=>new 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e.functionMap[n].executeFunctionAsync(l,e.tensorArrayMap,e.tensorListMap);let p=l.map(f=>f.id);c.forEach(f=>{!f.kept&&a.indexOf(f.id)===-1&&p.indexOf(f.id)===-1&&f.dispose()});let m=await e.functionMap[o].executeFunctionAsync(l,e.tensorArrayMap,e.tensorListMap);u=await m[0].data(),m.forEach(f=>{!f.kept&&a.indexOf(f.id)===-1&&p.indexOf(f.id)===-1&&f.dispose()})}return l}case"LoopCond":{let n=C("pred",r,t,e);return[ei(n)]}case"Switch":{let n=C("pred",r,t,e),o=C("data",r,t,e);return o.kept||(o=ei(o)),(await n.data())[0]?[void 0,o]:[o,void 0]}case"Merge":{let n=r.inputNames.find(o=>wr(o,t,e)!==void 0);if(n){let o=wr(n,t,e);return[ei(o)]}return}case"Enter":{let n=C("frameName",r,t,e),o=C("tensor",r,t,e);return e.enterFrame(n),[ei(o)]}case"Exit":{let n=C("tensor",r,t,e);return e.exitFrame(),[ei(n)]}case"NextIteration":{let n=C("tensor",r,t,e);return e.nextIteration(),[ei(n)]}case"TensorArrayV3":{let n=C("size",r,t,e),o=C("dtype",r,t,e),s=C("elementShape",r,t,e),i=C("dynamicSize",r,t,e),a=C("clearAfterRead",r,t,e),u=C("identicalElementShapes",r,t,e),l=C("name",r,t,e),c=new jb(l,o,n,s,u,i,a);return e.addTensorArray(c),[c.idTensor,pt(1)]}case"TensorArrayWriteV3":{let n=C("tensorArrayId",r,t,e),o=C("index",r,t,e),s=C("tensor",r,t,e),i=e.getTensorArray(n.id);return i.write(o,s),[i.idTensor]}case"TensorArrayReadV3":{let n=C("tensorArrayId",r,t,e),o=C("index",r,t,e);return[e.getTensorArray(n.id).read(o)]}case"TensorArrayGatherV3":{let n=C("tensorArrayId",r,t,e),o=C("indices",r,t,e),s=C("dtype",r,t,e);return[e.getTensorArray(n.id).gather(o,s)]}case"TensorArrayScatterV3":{let n=C("tensorArrayId",r,t,e),o=C("indices",r,t,e),s=C("tensor",r,t,e),i=e.getTensorArray(n.id);return i.scatter(o,s),[i.idTensor]}case"TensorArrayConcatV3":{let n=C("tensorArrayId",r,t,e),o=e.getTensorArray(n.id),s=C("dtype",r,t,e);return[o.concat(s)]}case"TensorArraySplitV3":{let n=C("tensorArrayId",r,t,e),o=C("tensor",r,t,e),s=C("lengths",r,t,e),i=e.getTensorArray(n.id);return i.split(s,o),[i.idTensor]}case"TensorArraySizeV3":{let n=C("tensorArrayId",r,t,e),o=e.getTensorArray(n.id);return[pt(o.size(),"int32")]}case"TensorArrayCloseV3":{let n=C("tensorArrayId",r,t,e),o=e.getTensorArray(n.id);return o.clearAndClose(),[o.idTensor]}case"TensorListSetItem":{let n=C("tensorListId",r,t,e),o=C("index",r,t,e),s=C("tensor",r,t,e),i=e.getTensorList(n.id);return i.setItem(o,s),[i.idTensor]}case"TensorListGetItem":{let n=C("tensorListId",r,t,e),o=C("index",r,t,e),s=C("elementShape",r,t,e),i=C("elementDType",r,t,e);return[e.getTensorList(n.id).getItem(o,s,i)]}case"TensorListScatterV2":case"TensorListScatter":{let n=C("indices",r,t,e),o=C("tensor",r,t,e),s=C("elementShape",r,t,e),i=C("numElements",r,t,e),a=qD(o,n,s,i);return e.addTensorList(a),[a.idTensor]}case"TensorListReserve":case"EmptyTensorList":{let n=C("elementShape",r,t,e),o=C("elementDType",r,t,e),s;r.op==="TensorListReserve"?s="numElements":s="maxNumElements";let i=C(s,r,t,e),a=r.op==="TensorListReserve"?-1:i,u=HD(n,o,i,a);return e.addTensorList(u),[u.idTensor]}case"TensorListGather":{let n=C("tensorListId",r,t,e),o=C("indices",r,t,e),s=C("elementShape",r,t,e),i=C("elementDType",r,t,e);return[e.getTensorList(n.id).gather(o,i,s)]}case"TensorListStack":{let n=C("tensorListId",r,t,e),o=C("elementShape",r,t,e),s=C("elementDType",r,t,e),i=C("numElements",r,t,e);return[e.getTensorList(n.id).stack(o,s,i)]}case"TensorListFromTensor":{let n=C("tensor",r,t,e),o=C("elementShape",r,t,e),s=C("elementDType",r,t,e),i=UD(n,o,s);return e.addTensorList(i),[i.idTensor]}case"TensorListConcat":case"TensorListConcatV2":{let n=C("tensorListId",r,t,e),o=e.getTensorList(n.id),s=C("dtype",r,t,e),i=C("elementShape",r,t,e);return[o.concat(s,i)]}case"TensorListPushBack":{let n=C("tensorListId",r,t,e),o=C("tensor",r,t,e),s=e.getTensorList(n.id);return s.pushBack(o),[s.idTensor]}case"TensorListPopBack":{let n=C("tensorListId",r,t,e),o=C("elementShape",r,t,e),s=C("elementDType",r,t,e);return[e.getTensorList(n.id).popBack(o,s)]}case"TensorListSplit":{let n=C("tensor",r,t,e),o=C("elementShape",r,t,e),s=C("lengths",r,t,e),i=KD(n,s,o);return e.addTensorList(i),[i.idTensor]}case"TensorListLength":{let n=C("tensorListId",r,t,e),o=e.getTensorList(n.id);return[pt(o.size(),"int32")]}case"TensorListResize":{let n=C("tensorListId",r,t,e),o=C("size",r,t,e),i=e.getTensorList(n.id).resize(o);return e.addTensorList(i),[i.idTensor]}default:throw TypeError(`Node type ${r.op} is not implemented`)}};function XD(r,t,e){let[n,o]=C("fusedOps",r,t,e),s=n==="biasadd",i=!s,a=o==="prelu",u=n==="fusedbatchnorm",l=C("numArgs",r,t,e);if(s){if(a&&l!==2)throw new Error("FusedConv2d and DepthwiseConv2d with BiasAdd and Prelu must have two extra arguments: bias and alpha.");if(!a&&s&&l!==1)throw new Error("FusedConv2d and DepthwiseConv2d with BiasAdd must have one extra argument: bias.")}if(u)throw new Error("FusedConv2d and DepthwiseConv2d with FusedBatchNorm is not supported");let c=C("strides",r,t,e),p=Ph(r,t,e),m=C("dataFormat",r,t,e).toUpperCase(),f=C("dilations",r,t,e),[d,h]=C("args",r,t,e);i&&(h=d,d=void 0);let g=C("leakyreluAlpha",r,t,e);return{stride:c,pad:p,dataFormat:m,dilations:f,biasArg:d,preluArg:h,activationFunc:o,leakyreluAlpha:g}}var YD=(r,t,e,n=ue)=>{switch(r.op){case"Conv1D":{let o=C("stride",r,t,e),s=C("pad",r,t,e),i=C("dataFormat",r,t,e).toUpperCase(),a=C("dilation",r,t,e);return[n.conv1d(C("x",r,t,e),C("filter",r,t,e),o,s,i,a)]}case"Conv2D":{let o=C("strides",r,t,e),s=Ph(r,t,e),i=C("dataFormat",r,t,e).toUpperCase(),a=C("dilations",r,t,e);return[n.conv2d(C("x",r,t,e),C("filter",r,t,e),[o[1],o[2]],s,i,[a[1],a[2]])]}case"_FusedConv2D":{let{stride:o,pad:s,dataFormat:i,dilations:a,biasArg:u,preluArg:l,activationFunc:c,leakyreluAlpha:p}=XD(r,t,e);return[n.fused.conv2d({x:C("x",r,t,e),filter:C("filter",r,t,e),strides:[o[1],o[2]],pad:s,dataFormat:i,dilations:[a[1],a[2]],bias:u,activation:c,preluActivationWeights:l,leakyreluAlpha:p})]}case"FusedDepthwiseConv2dNative":{let{stride:o,pad:s,dataFormat:i,dilations:a,biasArg:u,preluArg:l,activationFunc:c,leakyreluAlpha:p}=XD(r,t,e);return[n.fused.depthwiseConv2d({x:C("x",r,t,e),filter:C("filter",r,t,e),strides:[o[1],o[2]],pad:s,dataFormat:i,dilations:[a[1],a[2]],bias:u,activation:c,preluActivationWeights:l,leakyreluAlpha:p})]}case"Conv2DBackpropInput":case"Conv2dTranspose":{let o=C("outputShape",r,t,e),s=C("strides",r,t,e),i=Ph(r,t,e);return[n.conv2dTranspose(C("x",r,t,e),C("filter",r,t,e),o,[s[1],s[2]],i)]}case"DepthwiseConv2dNative":case"DepthwiseConv2d":{let o=C("strides",r,t,e),s=Ph(r,t,e),i=C("dilations",r,t,e),a=C("dataFormat",r,t,e).toUpperCase();return[n.depthwiseConv2d(C("input",r,t,e),C("filter",r,t,e),[o[1],o[2]],s,a,[i[1],i[2]])]}case"Conv3D":{let o=C("strides",r,t,e),s=C("pad",r,t,e),i=C("dataFormat",r,t,e).toUpperCase(),a=C("dilations",r,t,e);return[n.conv3d(C("x",r,t,e),C("filter",r,t,e),[o[1],o[2],o[3]],s,i,[a[1],a[2],a[3]])]}case"AvgPool":{let o=C("strides",r,t,e),s=C("pad",r,t,e),i=C("kernelSize",r,t,e);return[n.avgPool(C("x",r,t,e),[i[1],i[2]],[o[1],o[2]],s)]}case"MaxPool":{let o=C("strides",r,t,e),s=C("pad",r,t,e),i=C("kernelSize",r,t,e);return[n.maxPool(C("x",r,t,e),[i[1],i[2]],[o[1],o[2]],s)]}case"MaxPoolWithArgmax":{let o=C("strides",r,t,e),s=C("pad",r,t,e),i=C("kernelSize",r,t,e),a=C("includeBatchInIndex",r,t,e),{result:u,indexes:l}=n.maxPoolWithArgmax(C("x",r,t,e),[i[1],i[2]],[o[1],o[2]],s,a);return[u,l]}case"AvgPool3D":{let o=C("strides",r,t,e),s=C("pad",r,t,e),i=C("kernelSize",r,t,e);return[n.avgPool3d(C("x",r,t,e),[i[1],i[2],i[3]],[o[1],o[2],o[3]],s)]}case"MaxPool3D":{let o=C("strides",r,t,e),s=C("pad",r,t,e),i=C("kernelSize",r,t,e);return[n.maxPool3d(C("x",r,t,e),[i[1],i[2],i[3]],[o[1],o[2],o[3]],s)]}case"Dilation2D":{let o=C("strides",r,t,e),s=C("pad",r,t,e),i=C("dilations",r,t,e),a=o[1],u=o[2],l=i[1],c=i[2];return[n.dilation2d(C("x",r,t,e),C("filter",r,t,e),[a,u],s,[l,c],"NHWC")]}default:throw TypeError(`Node type ${r.op} is not implemented`)}};var ZD=(r,t,e,n=ue)=>{switch(r.op){case"Fill":{let o=C("shape",r,t,e),s=C("dtype",r,t,e),i=C("value",r,t,e);return[n.fill(o,i,s)]}case"LinSpace":{let o=C("start",r,t,e),s=C("stop",r,t,e),i=C("num",r,t,e);return[n.linspace(o,s,i)]}case"Multinomial":{let 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Xb=class{constructor(t,e){this.keyDType=t,this.valueDType=e,this.handle=pt(0),this.tensorMap=new Map,Oe(this.handle)}get id(){return this.handle.id}clearAndClose(){this.tensorMap.forEach(t=>t.dispose()),this.tensorMap.clear(),this.handle.dispose()}size(){return this.tensorMap.size}tensorSize(){return pt(this.size(),"int32")}async import(t,e){this.checkKeyAndValueTensor(t,e);let n=await t.data();return this.tensorMap.forEach(o=>o.dispose()),this.tensorMap.clear(),W(()=>{let o=Nr(e),s=n.length,i=o.length;x.assert(s===i,()=>`The number of elements doesn't match, keys has ${s} elements, the values has ${i} elements.`);for(let a=0;a<s;a++){let u=n[a],l=o[a];Oe(l),this.tensorMap.set(u,l)}return this.handle})}async find(t,e){this.checkKeyAndValueTensor(t,e);let n=await t.data();return W(()=>{let o=[];for(let s=0;s<n.length;s++){let i=n[s],a=this.findWithDefault(i,e);o.push(a)}return sr(o)})}findWithDefault(t,e){let n=this.tensorMap.get(t);return 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rF=(r,t,e,n=ue)=>{switch(r.op){case"ResizeBilinear":{let o=C("images",r,t,e),s=C("size",r,t,e),i=C("alignCorners",r,t,e),a=C("halfPixelCenters",r,t,e);return[n.image.resizeBilinear(o,[s[0],s[1]],i,a)]}case"ResizeNearestNeighbor":{let o=C("images",r,t,e),s=C("size",r,t,e),i=C("alignCorners",r,t,e),a=C("halfPixelCenters",r,t,e);return[n.image.resizeNearestNeighbor(o,[s[0],s[1]],i,a)]}case"CropAndResize":{let o=C("image",r,t,e),s=C("boxes",r,t,e),i=C("boxInd",r,t,e),a=C("cropSize",r,t,e),u=C("method",r,t,e),l=C("extrapolationValue",r,t,e);return[n.image.cropAndResize(o,s,i,a,u,l)]}case"ImageProjectiveTransformV3":{let o=C("images",r,t,e),s=C("transforms",r,t,e),i=C("outputShape",r,t,e),a=C("fillValue",r,t,e),u=C("interpolation",r,t,e),l=C("fillMode",r,t,e);return[n.image.transform(o,s,u.toLowerCase(),l.toLowerCase(),a,i)]}default:throw TypeError(`Node type ${r.op} is not implemented`)}};var nF=(r,t,e,n=ue)=>{switch(r.op){case"Equal":return[n.equal(C("a",r,t,e),C("b",r,t,e))];case"NotEqual":return[n.notEqual(C("a",r,t,e),C("b",r,t,e))];case"Greater":return[n.greater(C("a",r,t,e),C("b",r,t,e))];case"GreaterEqual":return[n.greaterEqual(C("a",r,t,e),C("b",r,t,e))];case"Less":return[n.less(C("a",r,t,e),C("b",r,t,e))];case"LessEqual":return[n.lessEqual(C("a",r,t,e),C("b",r,t,e))];case"LogicalAnd":return[n.logicalAnd(C("a",r,t,e),C("b",r,t,e))];case"LogicalNot":return[n.logicalNot(C("a",r,t,e))];case"LogicalOr":return[n.logicalOr(C("a",r,t,e),C("b",r,t,e))];case"Select":case"SelectV2":return[n.where(C("condition",r,t,e),C("a",r,t,e),C("b",r,t,e))];default:throw TypeError(`Node type ${r.op} is not implemented`)}};var oF=(r,t,e,n=ue)=>{switch(r.op){case"BatchMatMul":case"BatchMatMulV2":case"MatMul":return[n.matMul(C("a",r,t,e),C("b",r,t,e),C("transposeA",r,t,e),C("transposeB",r,t,e))];case"Einsum":return[n.einsum(C("equation",r,t,e),...C("tensors",r,t,e))];case"Transpose":return[n.transpose(C("x",r,t,e),C("perm",r,t,e))];case"_FusedMatMul":let[o,s]=C("fusedOps",r,t,e),i=o==="biasadd",a=s==="prelu",u=C("numArgs",r,t,e),l=C("leakyreluAlpha",r,t,e);if(i){if(a&&u!==2)throw new Error("Fused MatMul with BiasAdd and Prelu must have two extra arguments: bias and alpha.");if(!a&&u!==1)throw new Error("Fused MatMul with BiasAdd must have one extra argument: bias.")}let[c,p]=C("args",r,t,e);return[n.fused.matMul({a:C("a",r,t,e),b:C("b",r,t,e),transposeA:C("transposeA",r,t,e),transposeB:C("transposeB",r,t,e),bias:c,activation:s,preluActivationWeights:p,leakyreluAlpha:l})];default:throw TypeError(`Node type ${r.op} is not implemented`)}};var sF=(r,t,e,n=ue)=>{switch(r.op){case"EuclideanNorm":return[n.euclideanNorm(C("x",r,t,e),C("axis",r,t,e),C("keepDims",r,t,e))];case"FusedBatchNorm":case"FusedBatchNormV2":return[n.batchNorm(C("x",r,t,e),C("mean",r,t,e),C("variance",r,t,e),C("offset",r,t,e),C("scale",r,t,e),C("epsilon",r,t,e))];case"FusedBatchNormV3":return[n.batchNorm(C("x",r,t,e),C("mean",r,t,e),C("variance",r,t,e),C("offset",r,t,e),C("scale",r,t,e),C("epsilon",r,t,e))];case"LRN":return[n.localResponseNormalization(C("x",r,t,e),C("radius",r,t,e),C("bias",r,t,e),C("alpha",r,t,e),C("beta",r,t,e))];case"Softmax":return[n.softmax(C("x",r,t,e))];case"LogSoftmax":return[n.logSoftmax(C("x",r,t,e))];case"SparseToDense":return[n.sparseToDense(C("sparseIndices",r,t,e),C("outputShape",r,t,e),C("sparseValues",r,t,e),C("defaultValue",r,t,e))];default:throw TypeError(`Node type ${r.op} is not implemented`)}};var iF=(r,t,e,n=ue)=>{switch(r.op){case"Max":{let 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o=C("x",r,t,e),s=C("weights",r,t,e),i=C("size",r,t,e);return[n.bincount(o,s,i)];case"DenseBincount":{let a=C("x",r,t,e),u=C("weights",r,t,e),l=C("size",r,t,e),c=C("binaryOutput",r,t,e);return[n.denseBincount(a,u,l,c)]}default:throw TypeError(`Node type ${r.op} is not implemented`)}};var aF=(r,t,e,n=ue)=>{switch(r.op){case"ConcatV2":case"Concat":{let o=C("n",r,t,e),s=C("axis",r,t,e),i=C("tensors",r,t,e);return i=i.slice(0,o),[n.concat(i,s)]}case"Gather":{let o=C("x",r,t,e),s=C("indices",r,t,e);return[n.gather(o,n.cast(s,"int32"),0)]}case"GatherV2":{let o=C("axis",r,t,e),s=C("batchDims",r,t,e),i=C("x",r,t,e),a=C("indices",r,t,e);return[n.gather(i,n.cast(a,"int32"),o,s)]}case"Reverse":{let o=C("dims",r,t,e),s=[];for(let a=0;a<o.length;a++)o[a]&&s.push(a);let i=C("x",r,t,e);return[n.reverse(i,s)]}case"ReverseV2":{let o=C("axis",r,t,e),s=C("x",r,t,e);return[n.reverse(s,o)]}case"Slice":{let o=C("begin",r,t,e),s=C("size",r,t,e);return[n.slice(C("x",r,t,e),o,s)]}case"StridedSlice":{let 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o=C("x",r,t,e),s=C("indices",r,t,e);return[n.gatherND(o,s)]}case"SparseToDense":{let o=C("sparseIndices",r,t,e),s=C("outputShape",r,t,e),i=C("sparseValues",r,t,e),a=C("defaultValue",r,t,e);return[n.sparseToDense(o,i,s,i.dtype===a.dtype?a:n.cast(a,i.dtype))]}default:throw TypeError(`Node type ${r.op} is not implemented`)}};var lF=(r,t,e,n=ue)=>{switch(r.op){case"SparseFillEmptyRows":{let{outputIndices:o,outputValues:s,emptyRowIndicator:i,reverseIndexMap:a}=n.sparse.sparseFillEmptyRows(C("indices",r,t,e),C("values",r,t,e),C("denseShape",r,t,e),C("defaultValue",r,t,e));return[o,s,i,a]}case"SparseReshape":{let{outputIndices:o,outputShape:s}=n.sparse.sparseReshape(C("inputIndices",r,t,e),C("inputShape",r,t,e),C("newShape",r,t,e));return[o,s]}case"SparseSegmentMean":return[n.sparse.sparseSegmentMean(C("data",r,t,e),C("indices",r,t,e),C("segmentIds",r,t,e))];case"SparseSegmentSum":return[n.sparse.sparseSegmentSum(C("data",r,t,e),C("indices",r,t,e),C("segmentIds",r,t,e))];default:throw TypeError(`Node type ${r.op} is not implemented`)}};var uF=(r,t,e,n=ue)=>{switch(r.op){case"FFT":return[n.fft(C("x",r,t,e))];case"IFFT":return[n.ifft(C("x",r,t,e))];case"RFFT":return[n.rfft(C("x",r,t,e))];case"IRFFT":return[n.irfft(C("x",r,t,e))];default:throw TypeError(`Node type ${r.op} is not implemented`)}};var cF=(r,t,e,n=ue)=>{switch(r.op){case"StringNGrams":{let{nGrams:o,nGramsSplits:s}=n.string.stringNGrams(C("data",r,t,e),C("dataSplits",r,t,e),C("separator",r,t,e),C("nGramWidths",r,t,e),C("leftPad",r,t,e),C("rightPad",r,t,e),C("padWidth",r,t,e),C("preserveShortSequences",r,t,e));return[o,s]}case"StringSplit":{let{indices:o,values:s,shape:i}=n.string.stringSplit(C("input",r,t,e),C("delimiter",r,t,e),C("skipEmpty",r,t,e));return[o,s,i]}case"StringToHashBucketFast":return[n.string.stringToHashBucketFast(C("input",r,t,e),C("numBuckets",r,t,e))];default:throw TypeError(`Node type ${r.op} is not implemented`)}};var pF=(r,t,e,n=ue)=>{switch(r.op){case"Cast":return[n.cast(C("x",r,t,e),C("dtype",r,t,e))];case"ExpandDims":{let o=C("axis",r,t,e);return[n.expandDims(C("x",r,t,e),o)]}case"Squeeze":{let o=C("axis",r,t,e);return[n.squeeze(C("x",r,t,e),o)]}case"Reshape":return[n.reshape(C("x",r,t,e),C("shape",r,t,e))];case"MirrorPad":return[n.mirrorPad(C("x",r,t,e),C("padding",r,t,e),C("mode",r,t,e))];case"PadV2":case"Pad":return[n.pad(C("x",r,t,e),C("padding",r,t,e),C("constantValue",r,t,e))];case"SpaceToBatchND":{let o=C("blockShape",r,t,e),s=C("paddings",r,t,e);return[n.spaceToBatchND(C("x",r,t,e),o,s)]}case"BatchToSpaceND":{let o=C("blockShape",r,t,e),s=C("crops",r,t,e);return[n.batchToSpaceND(C("x",r,t,e),o,s)]}case"DepthToSpace":{let o=C("blockSize",r,t,e),s=C("dataFormat",r,t,e).toUpperCase();return[n.depthToSpace(C("x",r,t,e),o,s)]}case"BroadcastTo":return[n.broadcastTo(C("x",r,t,e),C("shape",r,t,e))];case"BroadcastArgs":return[n.broadcastArgs(C("s0",r,t,e),C("s1",r,t,e))];default:throw TypeError(`Node type ${r.op} is not implemented`)}};function xN(r,t,e,n,o=W){let s=((i,a,u)=>{switch(i.category){case"arithmetic":return o(()=>VD(i,a,u));case"basic_math":return o(()=>GD(i,a,u));case"control":return jD(i,a,u);case"convolution":return o(()=>YD(i,a,u));case"creation":return o(()=>ZD(i,a,u));case"dynamic":return JD(i,a,u);case"evaluation":return o(()=>QD(i,a,u));case"image":return o(()=>rF(i,a,u));case"graph":return o(()=>tF(i,a,u));case"logical":return o(()=>nF(i,a,u));case"matrices":return o(()=>oF(i,a,u));case"normalization":return o(()=>sF(i,a,u));case"reduction":return o(()=>iF(i,a,u));case"slice_join":return o(()=>aF(i,a,u));case"sparse":return o(()=>lF(i,a,u));case"spectral":return o(()=>uF(i,a,u));case"string":return o(()=>cF(i,a,u));case"transformation":return o(()=>pF(i,a,u));case"hash_table":return eF(i,a,u,n);case"custom":let l=Rb(i.op);if(l&&l.customExecutor)return l.customExecutor(new qb(i,a,u));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()`)}})(r,t,e);return x.isPromise(s)?s.then(i=>[].concat(i)):[].concat(s)}var zh=class{constructor(t={},e={},n={},o={}){this.weightMap=t,this.tensorArrayMap=e,this.tensorListMap=n,this.functionMap=o,this.rootContext={id:0,frameName:"",iterationId:0},this.contexts=[this.rootContext],this.lastId=0,this.generateCurrentContextIds()}newFrame(t,e){return{id:t,frameName:e,iterationId:0}}set currentContext(t){this.contexts!==t&&(this.contexts=t,this.generateCurrentContextIds())}get currentContext(){return this.contexts}get currentContextId(){return this._currentContextIds[0]}get currentContextIds(){return this._currentContextIds}generateCurrentContextIds(){let t=[];for(let e=0;e<this.contexts.length-1;e++){let n=this.contexts.slice(0,this.contexts.length-e);t.push(this.contextIdforContexts(n))}t.push(""),this._currentContextIds=t}contextIdforContexts(t){return t?t.map(e=>e.id===0&&e.iterationId===0?"":`${e.frameName}-${e.iterationId}`).join("/"):""}enterFrame(t){this.contexts&&(this.lastId++,this.contexts=this.contexts.slice(),this.contexts.push(this.newFrame(this.lastId,t)),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 t=Object.assign({},this.contexts[this.contexts.length-1]);t.iterationId+=1,t.id=this.lastId,this.contexts.splice(-1,1,t),this._currentContextIds.splice(0,1,this.contextIdforContexts(this.contexts))}else throw new Error("Cannot increase frame iteration, the context is empty")}getWeight(t){return this.weightMap[t]}addTensorArray(t){this.tensorArrayMap[t.id]=t}getTensorArray(t){return this.tensorArrayMap[t]}addTensorList(t){this.tensorListMap[t.id]=t}getTensorList(t){return this.tensorListMap[t]}dispose(t){for(let e in this.tensorArrayMap)this.tensorArrayMap[e].clearAndClose(t);for(let e in this.tensorListMap)this.tensorListMap[e].clearAndClose(t)}};function yN(r,t,e,n){let o=new Set,s=[],i=null,a=null,u=new Set,l=Object.keys(r).map(m=>yn(m)[0]),c=[];n!=null&&(c=n.map(m=>yn(m.name)[0]));let p=[...t];for(;p.length>0;){let m=p.pop();if((bN(m)||NZ(m)||kZ(m))&&i==null&&(i=m,a=i.children.map(f=>f.name).filter(f=>o.has(f))),o.add(m.name),e[m.name]==null&&l.indexOf(m.name)===-1&&c.indexOf(m.name)===-1){if(m.inputs.length===0){s.push(m.name);continue}m.inputs.forEach(f=>{u.has(f.name)||(u.add(f.name),p.push(f))})}}return{inputs:r,outputs:t,usedNodes:o,missingInputs:s,dynamicNode:i,syncInputs:a}}function mF(r,t,e){let{usedNodes:n,inputs:o}=e,s=[],i=Object.keys(o).map(c=>yn(c)[0]).map(c=>r.nodes[c]),a=r.initNodes;i.forEach(c=>{n.has(c.name)&&s.push(c)}),r.weights.forEach(c=>{n.has(c.name)&&s.push(c)}),a!=null&&a.forEach(c=>{n.has(c.name)&&s.push(c)});let u=new Set,l=[];for(;s.length>0;){let c=s.pop();u.add(c.name),t[c.name]||l.push(c),c.children.forEach(p=>{!u.has(p.name)&&n.has(p.name)&&p.inputs.every(m=>u.has(m.name))&&s.push(p)})}return l}var CZ=["Switch","Merge","Enter","Exit","NextIteration","StatelessIf","StatelessWhile","if","While"],IZ=["NonMaxSuppressionV2","NonMaxSuppressionV3","NonMaxSuppressionV5","Where"],SZ=["HashTable","HashTableV2","LookupTableImport","LookupTableImportV2","LookupTableFind","LookupTableFindV2","LookupTableSize","LookupTableSizeV2"];function bN(r){return CZ.indexOf(r.op)>=0}function NZ(r){return IZ.indexOf(r.op)>=0}function kZ(r){return SZ.indexOf(r.op)>=0}var $c=class{constructor(t,e){this.graph=t,this.parent=e,this.compiledMap=new Map,this._weightMap={},this.SEPERATOR=",",this._functions={},this._functionExecutorMap={},this.intermediateTensors={},this.keepTensorForDebug=!1,this._outputs=t.outputs,this._inputs=t.inputs,this._initNodes=t.initNodes,this._signature=t.signature,this._functions=t.functions,t.functions!=null&&Object.keys(t.functions).forEach(n=>{this._functionExecutorMap[n]=new $c(t.functions[n],this)})}get weightIds(){return this.parent?this.parent.weightIds:this._weightIds}get functionExecutorMap(){return this.parent?this.parent.functionExecutorMap:this._functionExecutorMap}get weightMap(){return this.parent?this.parent.weightMap:this._weightMap}set weightMap(t){let e=Object.keys(t).map(n=>t[n].map(o=>o.id));this._weightIds=[].concat(...e),this._weightMap=t}set resourceManager(t){this._resourceManager=t}get inputs(){return this._inputs.map(t=>({name:t.name,shape:t.attrParams.shape?t.attrParams.shape.value:void 0,dtype:t.attrParams.dtype?t.attrParams.dtype.value:void 0}))}get outputs(){return this._outputs.map(t=>({name:t.name,shape:t.attrParams.shape?t.attrParams.shape.value:void 0,dtype:t.attrParams.dtype?t.attrParams.dtype.value:void 0}))}get inputNodes(){return this._inputs.map(t=>t.signatureKey||t.name)}get outputNodes(){return this._outputs.map(t=>{let e=t.signatureKey||t.name;return t.defaultOutput?`${e}:${t.defaultOutput}`:e})}get functions(){return Object.keys(this._functions).reduce((t,e)=>(t[e]=this._functions[e].signature,t),{})}getCompilationKey(t,e){let n=t.map(s=>s.name).sort(),o=e.map(s=>s.name).sort();return n.join(this.SEPERATOR)+"--"+o.join(this.SEPERATOR)}compile(t,e){let n=yN(t,e,this.weightMap,this._initNodes),{missingInputs:o,dynamicNode:s,syncInputs:i}=n;if(s!=null)throw new Error(`This execution contains the node '${s.name}', which has the dynamic op '${s.op}'. Please use model.executeAsync() instead. Alternatively, to avoid the dynamic ops, specify the inputs [${i}]`);if(o.length>0){let a=e.map(l=>l.name),u=Object.keys(t);throw new Error(`Cannot compute the outputs [${a}] from the provided inputs [${u}]. Missing the following inputs: [${o}]`)}return mF(this.graph,this.weightMap,n)}execute(t,e){t=this.mapInputs(t);let n=Object.keys(t).sort();this.checkInputs(t),this.checkInputShapeAndType(t),e=this.mapOutputs(e),this.checkOutputs(e);let o=n.map(p=>this.graph.nodes[yn(p)[0]]),s=e.map(p=>yn(p)[0]),i=s.map(p=>this.graph.nodes[p]);this.resetIntermediateTensors(),i.length===0&&(i=this._outputs);let a=this.getCompilationKey(o,i),u=this.compiledMap.get(a);u==null&&(u=this.compile(t,i),this.compiledMap.set(a,u));let l={},c={};return W(()=>{let p=new zh(this.weightMap,l,c,this.functionExecutorMap),m=Object.assign({},this.weightMap);Object.keys(t).forEach(h=>{let[g,y]=yn(h),b=[];b[y]=t[h],m[g]=b});let f=this.getFrozenTensorIds(m),d={};for(let h=0;h<u.length;h++){let g=u[h];if(!m[g.name]){let y=xN(g,m,p,this._resourceManager);if(x.isPromise(y))throw new Error(`The execution of the op '${g.op}' returned a promise. Please use model.executeAsync() instead.`);m[g.name]=y,this.checkTensorForDisposal(g.name,g,m,p,f,s,d)}}return this.parent==null&&p.dispose(f),e.map(h=>wr(h,m,p))})}getFrozenTensorIds(t){let e=[].concat.apply([],Object.keys(t).map(n=>t[n]).map(n=>n.map(o=>o.id)));return new Set(e)}checkTensorForDisposal(t,e,n,o,s,i,a){e.category==="control"||i.indexOf(t)!==-1||(n[t].forEach(u=>{u!=null&&(a[u.id]=(a[u.id]||0)+e.children.length)}),e.inputs.forEach(u=>{if(u.category!=="control"){let l=PD(u.name,n,o);l!=null&&l.forEach(c=>{if(c&&!c.kept&&!s.has(c.id)){let p=a[c.id];if(p===1){if(!this.keepTensorForDebug)c.dispose();else{let[m,f]=_o(e.name,o);this.intermediateTensors[m]?this.intermediateTensors[m][f]=c:(this.intermediateTensors[m]=[],this.intermediateTensors[m][f]=c)}delete a[c.id]}else p!=null&&a[c.id]--}})}}))}async executeAsync(t,e){return this._executeAsync(t,e)}disposeIntermediateTensors(){!this.intermediateTensors||(Object.keys(this.intermediateTensors).forEach(t=>this.intermediateTensors[t].forEach(e=>e.dispose())),this.disposeTensorsMap())}disposeTensorsMap(){!this.tensorsMap||Object.keys(this.tensorsMap).forEach(t=>{this.tensorsMap[t].forEach(n=>{n&&!n.kept&&!n.isDisposed&&!this.keepIds.has(n.id)&&n.dispose()})})}getIntermediateTensors(){return this.tensorsMap}resetIntermediateTensors(){for(let t in this.intermediateTensors)this.intermediateTensors[t].forEach(e=>e.dispose()),delete this.intermediateTensors[t]}async _executeAsync(t,e,n=!1,o={},s={}){n||(t=this.mapInputs(t),this.checkInputs(t),this.checkInputShapeAndType(t),e=this.mapOutputs(e),this.checkOutputs(e));try{this.keepTensorForDebug=B().getBool("KEEP_INTERMEDIATE_TENSORS")}catch(c){console.warn(c.message)}this.resetIntermediateTensors();let i=new zh(this.weightMap,o,s,this.functionExecutorMap);this.tensorsMap=await this.executeWithControlFlow(t,i,e,n);let a=e.map(c=>wr(c,this.tensorsMap,i)),u=a.map(c=>c.id),l=Object.keys(t).map(c=>t[c].id);return this.keepIds=new Set([...u,...l,...this.weightIds]),this.keepTensorForDebug||this.disposeTensorsMap(),this.parent==null&&i.dispose(this.keepIds),a}async executeFunctionAsync(t,e,n){let o=t.reduce((s,i,a)=>(s[this.inputs[a].name]=i,s),{});return this._executeAsync(o,this.outputNodes,!0,e,n)}async executeWithControlFlow(t,e,n,o){let s=Object.keys(t),i=s.map(w=>this.graph.nodes[yn(w)[0]]),a=n.map(w=>yn(w)[0]),u=a.map(w=>this.graph.nodes[w]);u.length===0&&(u=this._outputs);let{usedNodes:l,missingInputs:c,dynamicNode:p,syncInputs:m}=yN(t,u,this.weightMap,this._initNodes),f=[...i,...this.graph.weights,...this._initNodes||[]].map(w=>({node:w,contexts:e.currentContext})),d=Object.assign({},this.weightMap);Object.keys(t).forEach(w=>{let[v,N]=yn(w),E=[];E[N]=t[w],d[v]=E});let h={},g=this.getFrozenTensorIds(d),y={};for(;f.length>0;){let w=this.processStack(i,f,e,d,y,g,a,h,l);await Promise.all(w)}p==null&&!o&&console.warn("This model execution did not contain any nodes with control flow or dynamic output shapes. You can use model.execute() instead.");let b=u.filter(w=>!bN(w)&&!wr(w.name,d,e)).map(w=>w.name);if(b.length>0){let w="";throw p!=null&&(w=`Alternatively, to avoid the dynamic ops, use model.execute() and specify the inputs [${m}]`),new Error(`Cannot compute the outputs [${b}] from the provided inputs [${s}]. Consider providing the following inputs: [${c}]. ${w}`)}return d}processStack(t,e,n,o,s,i,a,u,l){let c=[];for(;e.length>0;){let p=e.pop();n.currentContext=p.contexts;let m="";if(p.node.op==="Enter"&&C("isConstant",p.node,o,n)&&([m]=_o(p.node.name,n)),o[p.node.name]==null){let f=xN(p.node,o,n,this._resourceManager);m||([m]=_o(p.node.name,n));let d=n.currentContext;x.isPromise(f)?c.push(f.then(h=>(o[m]=h,n.currentContext=d,this.checkTensorForDisposal(m,p.node,o,n,i,a,u),this.processChildNodes(p.node,e,n,o,s,l),h))):(o[m]=f,this.checkTensorForDisposal(m,p.node,o,n,i,a,u),this.processChildNodes(p.node,e,n,o,s,l))}else this.processChildNodes(p.node,e,n,o,s,l)}return c}processChildNodes(t,e,n,o,s,i){t.children.forEach(a=>{let[u]=_o(a.name,n);s[u]||!i.has(a.name)||(a.op==="Merge"?a.inputNames.some(l=>!!wr(l,o,n))&&(s[u]=!0,e.push({contexts:n.currentContext,node:a})):a.inputNames.every(l=>!!wr(l,o,n))&&(s[u]=!0,e.push({contexts:n.currentContext,node:a})))})}dispose(){Object.keys(this.weightMap).forEach(t=>this.weightMap[t].forEach(e=>e.dispose()))}checkInputShapeAndType(t){Object.keys(t).forEach(e=>{let n=t[e],[o]=yn(e),s=this.graph.nodes[o];if(s.attrParams.shape&&s.attrParams.shape.value){let i=s.attrParams.shape.value,a=i.length===n.shape.length&&n.shape.every((u,l)=>i[l]===-1||i[l]===u);x.assert(a,()=>`The shape of dict['${s.name}'] provided in model.execute(dict) must be [${i}], but was [${n.shape}]`)}s.attrParams.dtype&&s.attrParams.dtype.value&&x.assert(n.dtype===s.attrParams.dtype.value,()=>`The dtype of dict['${s.name}'] provided in model.execute(dict) must be ${s.attrParams.dtype.value}, but was ${n.dtype}`)})}mapInputs(t){let e={};for(let n in t)if(this._signature!=null&&this._signature.inputs!=null&&this._signature.inputs[n]!=null){let o=this._signature.inputs[n];e[o.name]=t[n]}else e[n]=t[n];return e}checkInputs(t){let e=Object.keys(t).filter(n=>{let[o]=yn(n);return this.graph.nodes[o]==null});if(e.length>0)throw new Error(`The dict provided in model.execute(dict) has keys: [${e}] that are not part of graph`)}mapOutputs(t){return t.map(e=>this._signature!=null&&this._signature.outputs!=null&&this._signature.outputs[e]!=null?this._signature.outputs[e].name:e,{})}checkOutputs(t){t.forEach(e=>{let[n]=yn(e);if(!this.graph.nodes[n])throw new Error(`The output '${e}' is not found in the graph`)})}};var Yb=class{constructor(t={},e={}){this.hashTableNameToHandle=t,this.hashTableMap=e}addHashTable(t,e){this.hashTableNameToHandle[t]=e.handle,this.hashTableMap[e.id]=e}getHashTableHandleByName(t){return this.hashTableNameToHandle[t]}getHashTableById(t){return this.hashTableMap[t]}dispose(){for(let t in this.hashTableMap)this.hashTableMap[t].clearAndClose(),delete this.hashTableMap[t];for(let t in this.hashTableNameToHandle)this.hashTableNameToHandle[t].dispose(),delete this.hashTableNameToHandle[t]}};var TZ="?tfjs-format=file",_Z="model.json",Bh=class{constructor(t,e={},n=Cn){this.modelUrl=t,this.loadOptions=e,this.version="n/a",this.io=n,e==null&&(this.loadOptions={}),this.resourceManager=new Yb}get modelVersion(){return this.version}get inputNodes(){return this.executor.inputNodes}get outputNodes(){return this.executor.outputNodes}get inputs(){return this.executor.inputs}get outputs(){return this.executor.outputs}get weights(){return this.executor.weightMap}get metadata(){return this.artifacts.userDefinedMetadata}get modelSignature(){return this.signature}get modelStructuredOutputKeys(){return this.structuredOutputKeys}findIOHandler(){let t=this.modelUrl;if(t.load!=null)this.handler=t;else if(this.loadOptions.requestInit!=null)this.handler=this.io.browserHTTPRequest(t,this.loadOptions);else{let e=this.io.getLoadHandlers(t,this.loadOptions);if(e.length===0)e.push(this.io.browserHTTPRequest(t,this.loadOptions));else if(e.length>1)throw new Error(`Found more than one (${e.length}) load handlers for URL '${[t]}'`);this.handler=e[0]}}load(){if(this.findIOHandler(),this.handler.load==null)throw new Error("Cannot proceed with model loading because the IOHandler provided does not have the `load` method implemented.");let t=this.handler.load();return x.isPromise(t)?t.then(e=>this.loadSync(e)):this.loadSync(t)}loadSync(t){this.artifacts=t;let e=this.artifacts.modelTopology,n=this.artifacts.signature;if(this.artifacts.userDefinedMetadata!=null){let s=this.artifacts.userDefinedMetadata;s.signature!=null&&(n=s.signature),s.structuredOutputKeys!=null&&(this.structuredOutputKeys=s.structuredOutputKeys)}this.signature=n,this.version=`${e.versions.producer}.${e.versions.minConsumer}`;let o=this.io.decodeWeights(this.artifacts.weightData,this.artifacts.weightSpecs);if(this.executor=new $c(Mh.Instance.transformGraph(e,this.signature)),this.executor.weightMap=this.convertTensorMapToTensorsMap(o),this.executor.resourceManager=this.resourceManager,t.modelInitializer!=null&&t.modelInitializer.node!=null){let s=Mh.Instance.transformGraph(t.modelInitializer);this.initializer=new $c(s),this.initializer.weightMap=this.executor.weightMap,this.initializer.resourceManager=this.resourceManager,this.initializer.executeAsync({},[])}return!0}async save(t,e){if(typeof t=="string"){let n=this.io.getSaveHandlers(t);if(n.length===0)throw new Error(`Cannot find any save handlers for URL '${t}'`);if(n.length>1)throw new Error(`Found more than one (${n.length}) save handlers for URL '${t}'`);t=n[0]}if(t.save==null)throw new Error("GraphModel.save() cannot proceed because the IOHandler provided does not have the `save` attribute defined.");return t.save(this.artifacts)}predict(t,e){let n=this.execute(t,this.outputNodes);if(this.structuredOutputKeys){let o=n instanceof Pt?[n]:n,s={};return o.forEach((i,a)=>s[this.structuredOutputKeys[a]]=i),s}return n}normalizeInputs(t){if(!(t instanceof Pt)&&!Array.isArray(t))return t;if(t=Array.isArray(t)?t:[t],t.length!==this.inputNodes.length)throw new Error(`Input tensor count mismatch,the graph model has ${this.inputNodes.length} placeholders, while there are ${t.length} input tensors.`);return this.inputNodes.reduce((e,n,o)=>(e[n]=t[o],e),{})}normalizeOutputs(t){return t=t||this.outputNodes,Array.isArray(t)?t:[t]}execute(t,e){t=this.normalizeInputs(t),e=this.normalizeOutputs(e);let n=this.executor.execute(t,e);return n.length>1?n:n[0]}async executeAsync(t,e){t=this.normalizeInputs(t),e=this.normalizeOutputs(e);let n=await this.executor.executeAsync(t,e);return n.length>1?n:n[0]}getIntermediateTensors(){return 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Should have ${this.fullColumnNames.length} elements in a row, but got ${n}`);return n}};var od=class extends Qe{constructor(t){super(),this.microphoneConfig=t,this.isClosed=!1,this.fftSize=t.fftSize||1024;let e=Math.log2(this.fftSize);if(this.fftSize<0||e<4||e>14||!Number.isInteger(e))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=t.numFramesPerSpectrogram||43,this.sampleRateHz=t.sampleRateHz,this.columnTruncateLength=t.columnTruncateLength||this.fftSize,this.audioTrackConstraints=t.audioTrackConstraints,this.smoothingTimeConstant=t.smoothingTimeConstant||0,this.includeSpectrogram=t.includeSpectrogram!==!1,this.includeWaveform=t.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(t={}){if(!B().get("IS_BROWSER"))throw new Error("microphone API is only supported in browser environment.");let e=new od(t);return await e.start(),e}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 t=window.AudioContext||window.webkitAudioContext;if(this.audioContext=new t,!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 e=this.audioContext.createMediaStreamSource(this.stream);this.analyser=this.audioContext.createAnalyser(),this.analyser.fftSize=this.fftSize*2,this.analyser.smoothingTimeConstant=this.smoothingTimeConstant,e.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 t,e,n=await this.getAudioData();if(this.includeSpectrogram){let o=this.flattenQueue(n.freqDataQueue);t=this.getTensorFromAudioDataArray(o,[this.numFrames,this.columnTruncateLength,1])}if(this.includeWaveform){let o=this.flattenQueue(n.timeDataQueue);e=this.getTensorFromAudioDataArray(o,[this.numFrames*this.fftSize,1])}return{value:{spectrogram:t,waveform:e},done:!1}}async capture(){return(await this.next()).value}async getAudioData(){let t=[],e=[],n=0;return new Promise(o=>{let s=setInterval(()=>{this.includeSpectrogram&&(this.analyser.getFloatFrequencyData(this.freqData),this.freqData[0]===-1/0&&o({freqDataQueue:t,timeDataQueue:e}),t.push(this.freqData.slice(0,this.columnTruncateLength))),this.includeWaveform&&(this.analyser.getFloatTimeDomainData(this.timeData),e.push(this.timeData.slice())),++n===this.numFrames&&(clearInterval(s),o({freqDataQueue:t,timeDataQueue:e}))},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(t){let e=t[0].length,n=new Float32Array(t.length*e);return t.forEach((o,s)=>n.set(o,s*e)),n}getTensorFromAudioDataArray(t,e){let n=new Float32Array(x.sizeFromShape(e));return n.set(t,n.length-t.length),Cr(n,e)}};var sd=class extends Qe{constructor(t,e){if(super(),this.webcamVideoElement=t,this.webcamConfig=e,this.isClosed=!0,this.resize=!1,this.needToResize())if(this.resize=!0,this.cropSize=[this.webcamConfig.resizeHeight,this.webcamConfig.resizeWidth],this.cropBoxInd=Ve([0],"int32"),this.webcamConfig.centerCrop){let n=this.webcamConfig.resizeWidth*1/this.webcamVideoElement.width,o=this.webcamConfig.resizeHeight*1/this.webcamVideoElement.height,s=(1-n)/2,i=(1-o)/2,a=s+n,u=o+i;this.cropBox=qs([i,s,u,a],[1,4])}else this.cropBox=qs([0,0,1,1],[1,4])}summary(){return"webcam"}static async create(t,e={}){if(!B().get("IS_BROWSER"))throw new Error("tf.data.webcam is only supported in browser environment.");if(!t){if(t=document.createElement("video"),!e.resizeWidth||!e.resizeHeight)throw new Error("Please provide webcam video element, or resizeWidth and resizeHeight to create a hidden video element.");t.width=e.resizeWidth,t.height=e.resizeHeight}let n=new sd(t,e);return await n.start(),n}async start(){this.webcamConfig.facingMode&&x.assert(this.webcamConfig.facingMode==="user"||this.webcamConfig.facingMode==="environment",()=>`Invalid webcam facing mode: ${this.webcamConfig.facingMode}. Please provide 'user' or 'environment'`);try{this.stream=await navigator.mediaDevices.getUserMedia({video:{deviceId:this.webcamConfig.deviceId,facingMode:this.webcamConfig.facingMode?this.webcamConfig.facingMode:"user",width:this.webcamVideoElement.width,height:this.webcamVideoElement.height}})}catch(t){throw t.message=`Error thrown while initializing video stream: ${t.message}`,t}if(!this.stream)throw new Error("Could not obtain video from webcam.");try{this.webcamVideoElement.srcObject=this.stream}catch(t){console.log(t),this.webcamVideoElement.src=window.URL.createObjectURL(this.stream)}return this.webcamVideoElement.play(),this.isClosed=!1,new Promise(t=>{this.webcamVideoElement.onloadedmetadata=()=>{t()}})}async next(){if(this.isClosed)return{value:null,done:!0};let t;try{t=mx.fromPixels(this.webcamVideoElement)}catch(e){throw new Error(`Error thrown converting video to pixels: ${JSON.stringify(e)}`)}if(this.resize)try{return{value:this.cropAndResizeFrame(t),done:!1}}catch(e){throw new Error(`Error thrown cropping the video: ${e.message}`)}finally{t.dispose()}else return{value:t,done:!1}}needToResize(){return!!(this.webcamConfig.resizeWidth&&this.webcamConfig.resizeHeight&&(this.webcamVideoElement.width!==this.webcamConfig.resizeWidth||this.webcamVideoElement.height!==this.webcamConfig.resizeHeight))}cropAndResizeFrame(t){return W(()=>{let e=yr(tt(t,"float32"),0),n;n=iu.cropAndResize(e,this.cropBox,this.cropBoxInd,this.cropSize,"bilinear");let o=n.shape;return R(n,o.slice(1))})}async capture(){return(await this.next()).value}stop(){this.stream.getTracks().forEach(e=>e.stop());try{this.webcamVideoElement.srcObject=null}catch(e){console.log(e),this.webcamVideoElement.src=null}this.isClosed=!0}toArray(){throw new Error("Can not convert infinite video stream to array.")}};var id=class{};var Wh=class extends Qe{split(t){return new LN(this,t)}},LN=class extends Wh{constructor(t,e){super(),this.upstream=t,this.impl=new PN(t,e)}summary(){return this.impl.summary()}async next(){return this.impl.next()}},PN=class extends Fc{constructor(t,e){super(),this.upstream=t,this.separator=e,this.carryover=""}summary(){return`${this.upstream.summary()} -> Split('${this.separator}')`}async pump(){let t=await this.upstream.next();if(t.done)return this.carryover===""?!1:(this.outputQueue.push(this.carryover),this.carryover="",!0);let e=t.value.split(this.separator);e[0]=this.carryover+e[0];for(let n of e.slice(0,-1))this.outputQueue.push(n);return this.carryover=e[e.length-1],!0}};var ow=class extends Qe{decodeUTF8(){return new MN(this)}},MN=class extends Wh{constructor(t){super(),this.upstream=t,this.impl=new zN(t)}summary(){return this.impl.summary()}async next(){return this.impl.next()}},zN=class extends Fc{constructor(t){if(super(),this.upstream=t,B().get("IS_BROWSER"))this.decoder=new TextDecoder("utf-8");else{let{StringDecoder:e}=wN();this.decoder=new e("utf8")}}summary(){return`${this.upstream.summary()} -> Utf8`}async pump(){let t=await this.upstream.next(),e;if(t.done)return!1;e=t.value;let n;return B().get("IS_BROWSER")?n=this.decoder.decode(e,{stream:!0}):n=this.decoder.write(Buffer.from(e.buffer)),this.outputQueue.push(n),!0}};var ad=class extends ow{constructor(t,e={}){super(),this.file=t,this.options=e,x.assert(t instanceof Uint8Array||(B().get("IS_BROWSER")?t instanceof File||t instanceof Blob:!1),()=>"FileChunkIterator only supports File, Blob and Uint8Array right now."),this.offset=e.offset||0,this.chunkSize=e.chunkSize||1024*1024}summary(){return`FileChunks ${this.file}`}async next(){return this.offset>=(this.file instanceof Uint8Array?this.file.byteLength:this.file.size)?{value:null,done:!0}:{value:await new Promise((e,n)=>{let o=this.offset+this.chunkSize;if(this.file instanceof Uint8Array)e(new Uint8Array(this.file.slice(this.offset,o)));else{let s=new FileReader;s.onload=a=>{let u=s.result;if(u instanceof ArrayBuffer&&(u=new Uint8Array(u)),!(u instanceof Uint8Array))return n(new TypeError("FileReader returned unknown type."));e(u)},s.onabort=a=>n(new Error("Aborted")),s.onerror=a=>n(new Error(a.type));let i=this.file.slice(this.offset,o);s.readAsArrayBuffer(i)}this.offset=o}),done:!1}}};async function TF(r,t={},e){let n,o;typeof r=="string"?n=r:(n=r.url,o=LZ(r));let s=await(e||x.fetch)(n,o);if(s.ok){let i=new Uint8Array(await s.arrayBuffer());return new ad(i,t)}else throw new Error(s.statusText)}var LZ=r=>({method:r.method,headers:r.headers,body:r.body,mode:r.mode,credentials:r.credentials,cache:r.cache,redirect:r.redirect,referrer:r.referrer,integrity:r.integrity});function sw(r){return typeof r=="string"&&r.slice(0,7)==="file://"}var ld=class extends id{constructor(t,e={}){super(),this.input=t,this.options=e}async iterator(){if(sw(this.input)&&B().get("IS_NODE")){let t=iw();this.input=t.readFileSync(this.input.slice(7))}return new ad(this.input,this.options)}};var ud=class extends id{constructor(t,e={}){super(),this.url=t,this.fileOptions=e}async iterator(){return sw(this.url)?new ld(this.url,this.fileOptions).iterator():TF(this.url,this.fileOptions)}};function _F(r,t={}){return new nd(new ud(r),t)}function EF(r){let t=Vh(r);return En(async()=>t)}function AF(r){return En(async()=>{let t=await r();return Vh(()=>t.next())})}async function $F(r,t){return sd.create(r,t)}async function DF(r){return od.create(r)}var BN="3.19.0";function rt(r,t){Array.isArray(r)||(r=[r]),r.forEach(e=>{e!=null&&x.assert(e.dtype!=="complex64",()=>`${t} does not support complex64 tensors in the CPU backend.`)})}var PZ=Vr.whereImpl,Cu=class extends Uo{constructor(){super(),this.blockSize=48,this.firstUse=!0,this.data=new Qi(this,go())}nextDataId(){return Cu.nextDataId++}write(t,e,n){this.firstUse&&(this.firstUse=!1,B().get("IS_NODE")&&S.warn(`
============================
Hi, looks like you are running TensorFlow.js in Node.js. To speed things up dramatically, install our node backend, visit https://github.com/tensorflow/tfjs-node for more details. 
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y9=re((r,t)=>Math.atan2(r,t)),b9=ie(ua,y9),AR={kernelName:ua,backendName:"cpu",kernelFunc:b9};var w9=Et(la,r=>Math.atanh(r)),$R={kernelName:la,backendName:"cpu",kernelFunc:w9};function hd(r,t,e,n,o,s){let i=o.strideHeight,a=o.strideWidth,u=o.dilationHeight,l=o.dilationWidth,c=o.effectiveFilterHeight,p=o.effectiveFilterWidth,m=o.padInfo.top,f=o.padInfo.left,d=s==="max"?Number.NEGATIVE_INFINITY:Number.POSITIVE_INFINITY,h=Ct(o.outShape,e),g=h.values,y=o.outShape[1]*o.outShape[2]*o.outShape[3],b=o.outShape[2]*o.outShape[3],w=o.outShape[3];for(let v=0;v<o.batchSize;++v){let N=v*y,E=v*n[0];for(let $=0;$<o.inChannels;++$)for(let D=0;D<o.outHeight;++D){let L=D*i-m,M=Math.max(0,L),G=Math.min(o.inHeight,c+L),H=N+D*b;for(let q=0;q<o.outWidth;++q){let X=q*a-f,j=Math.max(0,X),J=Math.min(o.inWidth,p+X),nt=d,K=0,ot=0;for(let it=M;it<G;it+=u){let ft=E+it*n[1];for(let lt=j;lt<J;lt+=l){let xt=ft+lt*n[2],dt=r[xt+$];s==="max"&&dt>nt?nt=dt:s==="avg"&&(K+=dt,ot++)}if(isNaN(nt))break}let st=H+q*w+$;g[st]=s==="avg"?K/ot:nt}}}return h}function bw(r,t,e,n,o=!1,s=!1){let i=Ct(n.outShape,"int32"),a=n.strideHeight,u=n.strideWidth,l=n.dilationHeight,c=n.dilationWidth,p=n.effectiveFilterHeight,m=n.effectiveFilterWidth,f=n.padInfo.top,d=n.padInfo.left,h=Ct(t,e,r);for(let g=0;g<n.batchSize;++g)for(let y=0;y<n.inChannels;++y)for(let b=0;b<n.outHeight;++b){let w=b*a-f,v=w;for(;v<0;)v+=l;let N=Math.min(n.inHeight,p+w);for(let E=0;E<n.outWidth;++E){let $=E*u-d,D=$;for(;D<0;)D+=c;let L=Math.min(n.inWidth,m+$),M=Number.NEGATIVE_INFINITY,G=-1;for(let H=v;H<N;H+=l){let q=H-w;for(let X=D;X<L;X+=c){let j=X-$,J=h.get(g,H,X,y);J>M&&(M=J,o?G=s?((g*n.inHeight+H)*n.inWidth+X)*n.inChannels+y:(H*n.inWidth+X)*n.inChannels+y:G=q*m+j)}}i.set(G,g,b,E,y)}}return i}function ww(r,t,e,n,o,s){let 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le=dt;le<bt;le+=p){let qe=Ce+le*n[3],Fe=r[qe+H];if(s==="max"&&Fe>At?At=Fe:s==="avg"&&(Dt+=Fe,qt++),isNaN(At))break}if(isNaN(At))break}if(isNaN(At))break}let Kt=Nt+H;v[Kt]=s==="avg"?Dt/qt:At}}}}return w}function DR(r,t){let e=Ct(t.outShape,"int32"),n=t.strideDepth,o=t.strideHeight,s=t.strideWidth,i=t.dilationDepth,a=t.dilationHeight,u=t.dilationWidth,l=t.effectiveFilterDepth,c=t.effectiveFilterHeight,p=t.effectiveFilterWidth,m=t.padInfo.front,f=t.padInfo.top,d=t.padInfo.left;for(let h=0;h<t.batchSize;++h)for(let g=0;g<t.inChannels;++g)for(let y=0;y<t.outDepth;++y){let b=y*n-m,w=b;for(;w<0;)w+=i;let v=Math.min(t.inDepth,l+b);for(let N=0;N<t.outHeight;++N){let E=N*o-f,$=E;for(;$<0;)$+=a;let D=Math.min(t.inHeight,c+E);for(let L=0;L<t.outWidth;++L){let M=L*s-d,G=M;for(;G<0;)G+=u;let H=Math.min(t.inWidth,p+M),q=Number.NEGATIVE_INFINITY,X=-1;for(let j=w;j<v;j+=i){let J=j-b;for(let nt=$;nt<D;nt+=a){let K=nt-E;for(let ot=G;ot<H;ot+=u){let 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c=S.computePool3DInfo(s.shape,i,a,1,u,l),p=c.strideDepth,m=c.strideHeight,f=c.strideWidth,d=c.filterDepth,h=c.filterHeight,g=c.filterWidth,y=c.dilationDepth,b=c.dilationHeight,w=c.dilationWidth,v=c.effectiveFilterDepth,N=c.effectiveFilterHeight,E=c.effectiveFilterWidth,$=v-1-c.padInfo.front,D=E-1-c.padInfo.left,L=N-1-c.padInfo.top,M=Ct(s.shape,"float32"),G=1/(d*h*g),H=e.bufferSync(o);for(let q=0;q<c.batchSize;++q)for(let X=0;X<c.inChannels;++X)for(let j=0;j<c.inDepth;++j)for(let J=0;J<c.inHeight;++J)for(let nt=0;nt<c.inWidth;++nt){let K=j-$,ot=J-L,st=nt-D,it=0;for(let ft=0;ft<v;ft+=y){let lt=(K+ft)/p;if(!(lt<0||lt>=c.outDepth||Math.floor(lt)!==lt))for(let xt=0;xt<N;xt+=b){let dt=(ot+xt)/m;if(!(dt<0||dt>=c.outHeight||Math.floor(dt)!==dt))for(let bt=0;bt<E;bt+=w){let Nt=(st+bt)/f;if(Nt<0||Nt>=c.outWidth||Math.floor(Nt)!==Nt)continue;it+=H.get(q,lt,dt,Nt,X)}}}M.set(it*G,q,j,J,nt,X)}return e.makeTensorInfo(M.shape,M.dtype,M.values)}var OR={kernelName:vp,backendName:"cpu",kernelFunc:I9};function S9(r){let{inputs:t,backend:e,attrs:n}=r,{dy:o,input:s}=t,i=s;rt([o,s],"avgPoolGrad");let{filterSize:a,strides:u,pad:l}=n,c=S.computePool2DInfo(i.shape,a,u,1,l),p=c.strideHeight,m=c.strideWidth,f=c.filterHeight,d=c.filterWidth,h=c.dilationHeight,g=c.dilationWidth,y=c.effectiveFilterHeight,b=c.effectiveFilterWidth,w=b-1-c.padInfo.left,v=y-1-c.padInfo.top,N=Ct(i.shape,"float32"),E=1/(f*d),$=e.data.get(o.dataId).values,D=Ct(o.shape,"float32",$);for(let L=0;L<c.batchSize;++L)for(let M=0;M<c.inChannels;++M)for(let G=0;G<c.inHeight;++G)for(let H=0;H<c.inWidth;++H){let q=G-v,X=H-w,j=0;for(let J=0;J<y;J+=h){let nt=(q+J)/p;if(!(nt<0||nt>=c.outHeight||Math.floor(nt)!==nt))for(let K=0;K<b;K+=g){let ot=(X+K)/m;if(ot<0||ot>=c.outWidth||Math.floor(ot)!==ot)continue;j+=D.get(L,nt,ot,M)}}N.set(j*E,L,G,H,M)}return e.makeTensorInfo(N.shape,N.dtype,N.values)}var LR={kernelName:wp,backendName:"cpu",kernelFunc:S9};function 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e.makeTensorInfo(o.shape,o.dtype,h)}var PR={kernelName:us,backendName:"cpu",kernelFunc:N9};function k9(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{blockShape:s,crops:i}=n;rt([o],"batchToSpaceND");let a=s.reduce((y,b)=>y*b),u=S.getReshaped(o.shape,s,a),l=S.getPermuted(u.length,s.length),c=S.getReshapedPermuted(o.shape,s,a),p=S.getSliceBeginCoords(i,s.length),m=S.getSliceSize(c,i,s.length),f=Jt({inputs:{x:o},backend:e,attrs:{shape:u}}),d=Ue({inputs:{x:f},backend:e,attrs:{perm:l}}),h=Jt({inputs:{x:d},backend:e,attrs:{shape:c}}),g=Do({inputs:{x:h},backend:e,attrs:{begin:p,size:m}});return e.disposeIntermediateTensorInfo(f),e.disposeIntermediateTensorInfo(d),e.disposeIntermediateTensorInfo(h),g}var MR={kernelName:pi,backendName:"cpu",kernelFunc:k9};function T9(r){let{inputs:t,backend:e,attrs:n}=r,{x:o,weights:s}=t,{size:i}=n,a=e.data.get(o.dataId).values,u=e.data.get(s.dataId).values,l=md(a,u,s.dtype,s.shape,i);return e.makeTensorInfo([i],s.dtype,l)}var zR={kernelName:Cp,backendName:"cpu",kernelFunc:T9};function _9(r){let{inputs:t,backend:e}=r,{s0:n,s1:o}=t,s=e.data.get(n.dataId).values,i=e.data.get(o.dataId).values,a=S.assertAndGetBroadcastShape(Array.from(s),Array.from(i));return e.makeTensorInfo([a.length],"int32",Int32Array.from(a))}var BR={kernelName:Ip,backendName:"cpu",kernelFunc:_9};var E9=Et(ao,(r,t)=>{let e=t;return r>e.clipValueMax?e.clipValueMax:r<e.clipValueMin?e.clipValueMin:r}),VR={kernelName:ao,backendName:"cpu",kernelFunc:E9};var A9=r=>{let{x:t}=r.inputs,e=r.backend,n=new Float32Array(x.sizeFromShape(t.shape)),o=e.data.get(t.dataId),s=o.complexTensorInfos.real,i=o.complexTensorInfos.imag,a=e.data.get(s.dataId).values,u=e.data.get(i.dataId).values;for(let l=0;l<a.length;l++){let c=a[l],p=u[l];n[l]=Math.hypot(c,p)}return e.makeOutput(n,t.shape,"float32")},GR={kernelName:Sl,backendName:"cpu",kernelFunc:A9};function 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h.forEach(v=>e.disposeIntermediateTensorInfo(v)),g.forEach(v=>e.disposeIntermediateTensorInfo(v)),e.disposeIntermediateTensorInfo(y),e.disposeIntermediateTensorInfo(b),w}let l=a.map(h=>{let g=x.sizeFromShape(h.shape.slice(s));return Jt({inputs:{x:h},backend:e,attrs:{shape:[-1,g]}})}),c=l.map(h=>({vals:e.data.get(h.dataId).values,shape:h.shape}));i=S.computeOutShape(l.map(h=>h.shape),1);let p=l[0].shape[0]===1,m=Rc(c,i,t[0].dtype,p),f=S.computeOutShape(a.map(h=>h.shape),s),d=e.makeTensorInfo(f,t[0].dtype,m);return l.forEach(h=>e.disposeIntermediateTensorInfo(h)),d}var UR={kernelName:mi,backendName:"cpu",kernelFunc:Iu};function xk(r){let{inputs:t,backend:e,attrs:n}=r,{x:o,filter:s}=t,{strides:i,pad:a,dataFormat:u,dilations:l,dimRoundingMode:c}=n;rt([o,s],"conv2d");let p=S.convertConv2DDataFormat(u),m=S.computeConv2DInfo(o.shape,s.shape,i,l,a,c,!1,p),f=m.filterHeight,d=m.filterWidth,h=m.dilationHeight,g=m.dilationWidth,y=m.padInfo.left,b=m.padInfo.top,w=m.dataFormat==="channelsLast",v=new 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$9(r){let{inputs:t,backend:e,attrs:n}=r,{x:o,dy:s}=t,{strides:i,pad:a,dataFormat:u,dimRoundingMode:l,filterShape:c}=n;rt([o,s],"conv2dBackpropFilter");let p=S.convertConv2DDataFormat(u),m=S.computeConv2DInfo(o.shape,c,i,1,a,l,!1,p),{strideHeight:f,strideWidth:d,filterHeight:h,filterWidth:g}=m,y=m.dataFormat==="channelsLast",b=new fe(m.filterShape,"float32"),w=m.padInfo.left,v=m.padInfo.top,N=e.data.get(o.dataId).values,E=e.data.get(s.dataId).values,$=new fe(o.shape,o.dtype,N),D=new fe(s.shape,s.dtype,E);for(let L=0;L<h;++L){let M=Math.max(0,Math.ceil((v-L)/f)),G=Math.min(m.outHeight,(m.inHeight+v-L)/f);for(let H=0;H<g;++H){let q=Math.max(0,Math.ceil((w-H)/d)),X=Math.min(m.outWidth,(m.inWidth+w-H)/d);for(let j=0;j<m.inChannels;++j)for(let J=0;J<m.outChannels;++J){let nt=0;for(let K=0;K<m.batchSize;++K)for(let ot=M;ot<G;++ot){let st=L+ot*f-v;for(let it=q;it<X;++it){let ft=H+it*d-w;y?nt+=$.get(K,st,ft,j)*D.get(K,ot,it,J):nt+=$.get(K,j,st,ft)*D.get(K,J,ot,it)}}b.set(nt,L,H,j,J)}}}return e.makeTensorInfo(b.shape,b.dtype,b.values)}var qR={kernelName:Np,backendName:"cpu",kernelFunc:$9};function D9(r){let{inputs:t,backend:e,attrs:n}=r,{dy:o,filter:s}=t,{inputShape:i,strides:a,pad:u,dataFormat:l,dimRoundingMode:c}=n;rt([o,s],"conv2dBackpropInput");let p=x.computeStrides(s.shape),m=x.computeStrides(o.shape),f=S.convertConv2DDataFormat(l),d=S.computeConv2DInfo(i,s.shape,a,1,u,c,!1,f),h=new fe(d.inShape,"float32"),g=h.values,y=e.data.get(o.dataId).values,b=e.data.get(s.dataId).values,[w,v,N]=p,{batchSize:E,filterHeight:$,filterWidth:D,inChannels:L,inHeight:M,inWidth:G,outChannels:H,outHeight:q,outWidth:X,strideHeight:j,strideWidth:J}=d;f=d.dataFormat;let nt=$-1-d.padInfo.top,K=D-1-d.padInfo.left,ot=f==="channelsLast",st=h.strides[0],it=ot?h.strides[1]:h.strides[2],ft=ot?h.strides[2]:1,lt=ot?1:h.strides[1],xt=m[0],dt=ot?m[1]:m[2],bt=ot?m[2]:1,Nt=ot?1:m[1];for(let At=0;At<E;++At)for(let Dt=0;Dt<L;++Dt)for(let qt=0;qt<M;++qt){let Kt=qt-nt,me=Math.max(0,Math.ceil(Kt/j)),Rt=Math.min(q,($+Kt)/j);for(let Ee=0;Ee<G;++Ee){let Ce=Ee-K,le=Math.max(0,Math.ceil(Ce/J)),qe=Math.min(X,(D+Ce)/J),Fe=0;for(let Me=me;Me<Rt;++Me){let Lo=Me*j-Kt;for(let Or=le;Or<qe;++Or){let Qr=Or*J-Ce,tn=xt*At+dt*Me+bt*Or,qr=w*($-1-Lo)+v*(D-1-Qr)+N*Dt;for(let oo=0;oo<H;++oo){let $n=y[tn+Nt*oo],Po=b[qr+oo];Fe+=$n*Po}}}let Jr=st*At+it*qt+ft*Ee+lt*Dt;g[Jr]=Fe}}return e.makeTensorInfo(h.shape,h.dtype,h.values)}var KR={kernelName:Qo,backendName:"cpu",kernelFunc:D9};function F9(r){let{inputs:t,backend:e,attrs:n}=r,{x:o,filter:s}=t,{strides:i,pad:a,dilations:u}=n;rt([o,s],"conv3d");let l=S.computeConv3DInfo(o.shape,s.shape,i,u,a),{filterDepth:c,filterHeight:p,filterWidth:m,dilationDepth:f,dilationHeight:d,dilationWidth:h,padInfo:g}=l,y=g.front,b=g.left,w=g.top,v=new fe(l.outShape,o.dtype),N=e.data.get(o.dataId).values,E=e.data.get(s.dataId).values,$=v.values,D=x.computeStrides(o.shape),L=x.computeStrides(s.shape);for(let M=0;M<l.batchSize;++M){let G=M*D[0],H=M*v.strides[0];for(let q=0;q<l.outDepth;++q){let X=H+q*v.strides[1],j=q*l.strideDepth-y;for(let J=0;J<c;++J){let nt=j+J*f;if(nt<0||nt>=l.inDepth)continue;let K=J*L[0],ot=G+nt*D[1];for(let st=0;st<l.outHeight;++st){let it=X+st*v.strides[2],ft=st*l.strideHeight-w;for(let lt=0;lt<p;++lt){let xt=ft+lt*d;if(xt<0||xt>=l.inHeight)continue;let dt=K+lt*L[1],bt=ot+xt*D[2];for(let Nt=0;Nt<l.outWidth;++Nt){let At=it+Nt*l.outChannels,Dt=Nt*l.strideWidth-b;for(let qt=0;qt<m;++qt){let Kt=Dt+qt*h;if(Kt<0||Kt>=l.inWidth)continue;let me=dt+qt*L[2],Rt=bt+Kt*l.inChannels,Ee=me;for(let Ce=0;Ce<l.inChannels;++Ce){let le=N[Rt+Ce];for(let qe=0;qe<l.outChannels;++qe)$[At+qe]+=le*E[Ee+qe];Ee+=l.outChannels}}}}}}}}return e.makeTensorInfo(v.shape,v.dtype,v.values)}var jR={kernelName:Nl,backendName:"cpu",kernelFunc:F9};function R9(r){let{inputs:t,backend:e,attrs:n}=r,{x:o,dy:s}=t,{strides:i,pad:a,filterShape:u}=n;rt([o,s],"conv3dBackpropFilterV2");let l=x.computeStrides(o.shape),c=x.computeStrides(s.shape),p=S.computeConv3DInfo(o.shape,u,i,1,a),m=p.strideDepth,f=p.strideHeight,d=p.strideWidth,h=p.filterDepth,g=p.filterHeight,y=p.filterWidth,b=new fe(p.filterShape,"float32"),w=b.values,[v,N,E,$]=b.strides,D=e.data.get(s.dataId).values,[L,M,G,H]=c,q=e.data.get(o.dataId).values,[X,j,J,nt]=l,K=p.padInfo.front,ot=p.padInfo.left,st=p.padInfo.top;for(let it=0;it<h;++it){let ft=Math.max(0,Math.ceil((K-it)/m)),lt=Math.min(p.outDepth,(p.inDepth+K-it)/m),xt=it*v;for(let dt=0;dt<g;++dt){let bt=Math.max(0,Math.ceil((st-dt)/f)),Nt=Math.min(p.outHeight,(p.inHeight+st-dt)/f),At=dt*N+xt;for(let Dt=0;Dt<y;++Dt){let qt=Math.max(0,Math.ceil((ot-Dt)/d)),Kt=Math.min(p.outWidth,(p.inWidth+ot-Dt)/d),me=Dt*E+At;for(let Rt=0;Rt<p.inChannels;++Rt){let Ee=Rt*$+me;for(let Ce=0;Ce<p.outChannels;++Ce){let le=0;for(let qe=0;qe<p.batchSize;++qe){let Fe=qe*X,Jr=qe*L;for(let Me=ft;Me<lt;++Me){let Or=(it+Me*m-K)*j+Fe,Qr=Me*M+Jr;for(let tn=bt;tn<Nt;++tn){let oo=(dt+tn*f-st)*J+Or,$n=tn*G+Qr;for(let Po=qt;Po<Kt;++Po){let xl=(Dt+Po*d-ot)*nt+oo,Du=Po*H+$n;le+=q[xl+Rt]*D[Du+Ce]}}}}w[Ee+Ce]=le}}}}}return e.makeTensorInfo(b.shape,b.dtype,b.values)}var XR={kernelName:kp,backendName:"cpu",kernelFunc:R9};function O9(r){let{inputs:t,backend:e,attrs:n}=r,{dy:o,filter:s}=t,{pad:i,strides:a,inputShape:u}=n;rt([o],"conv3dBackpropInputV2");let l=x.computeStrides(o.shape),c=x.computeStrides(s.shape),p=S.computeConv3DInfo(u,s.shape,a,1,i),m=new fe(p.inShape,"float32"),f=m.values,[d,h,g,y]=m.strides,b=e.data.get(o.dataId).values,[w,v,N,E]=l,$=e.data.get(s.dataId).values,[D,L,M,G]=c,{batchSize:H,filterDepth:q,filterHeight:X,filterWidth:j,inChannels:J,inDepth:nt,inHeight:K,inWidth:ot,outChannels:st,outDepth:it,outHeight:ft,outWidth:lt,strideDepth:xt,strideHeight:dt,strideWidth:bt}=p,Nt=q-1-p.padInfo.front,At=X-1-p.padInfo.top,Dt=j-1-p.padInfo.left;for(let qt=0;qt<H;++qt)for(let Kt=0;Kt<J;++Kt)for(let me=0;me<nt;++me){let Rt=me-Nt,Ee=Math.max(0,Math.ceil(Rt/xt)),Ce=Math.min(it,(q+Rt)/xt);for(let le=0;le<K;++le){let qe=le-At,Fe=Math.max(0,Math.ceil(qe/dt)),Jr=Math.min(ft,(X+qe)/dt);for(let Me=0;Me<ot;++Me){let Lo=Me-Dt,Or=Math.max(0,Math.ceil(Lo/bt)),Qr=Math.min(lt,(j+Lo)/bt),tn=0;for(let qr=Ee;qr<Ce;++qr){let oo=qr*xt-Rt;for(let $n=Fe;$n<Jr;++$n){let Po=$n*dt-qe;for(let so=Or;so<Qr;++so){let xl=so*bt-Lo,Du=w*qt+v*qr+N*$n+E*so,ep=D*(q-1-oo)+L*(X-1-Po)+M*(j-1-xl)+G*Kt;for(let dr=0;dr<st;++dr){let rp=b[Du+dr],np=$[ep+dr];tn+=rp*np}}}}f[d*qt+h*me+g*le+y*Me+Kt]=tn}}}return e.makeTensorInfo(m.shape,m.dtype,m.values)}var YR={kernelName:Tp,backendName:"cpu",kernelFunc:O9};var L9=Et(ts,r=>Math.cos(r)),ZR={kernelName:ts,backendName:"cpu",kernelFunc:L9};var P9=Et(es,r=>Math.cosh(r)),JR={kernelName:es,backendName:"cpu",kernelFunc:P9};function M9(r){let{inputs:t,backend:e,attrs:n}=r,{image:o,boxes:s,boxInd:i}=t,{cropSize:a,method:u,extrapolationValue:l}=n,[c,p,m,f]=o.shape,d=s.shape[0],[h,g]=a,y=Ct([d,h,g,f],"float32"),b=e.data.get(s.dataId).values,w=e.data.get(i.dataId).values,v=e.data.get(o.dataId).values,N=x.computeStrides(o.shape),E=x.computeStrides(y.shape);for(let $=0;$<d;$++){let D=$*4,L=b[D],M=b[D+1],G=b[D+2],H=b[D+3],q=w[$];if(q>=c)continue;let X=h>1?(G-L)*(p-1)/(h-1):0,j=g>1?(H-M)*(m-1)/(g-1):0;for(let J=0;J<h;J++){let nt=h>1?L*(p-1)+J*X:.5*(L+G)*(p-1);if(nt<0||nt>p-1){for(let K=0;K<g;K++)for(let ot=0;ot<f;ot++){let st=ot+K*E[2]+J*E[1]+$*E[0];y.values[st]=l}continue}if(u==="bilinear"){let K=Math.floor(nt),ot=Math.ceil(nt),st=nt-K;for(let it=0;it<g;it++){let ft=g>1?M*(m-1)+it*j:.5*(M+H)*(m-1);if(ft<0||ft>m-1){for(let bt=0;bt<f;bt++){let Nt=bt+it*E[2]+J*E[1]+$*E[0];y.values[Nt]=l}continue}let lt=Math.floor(ft),xt=Math.ceil(ft),dt=ft-lt;for(let bt=0;bt<f;bt++){let Nt=bt+lt*N[2]+K*N[1]+q*N[0],At=v[Nt];Nt=bt+xt*N[2]+K*N[1]+q*N[0];let Dt=v[Nt];Nt=bt+lt*N[2]+ot*N[1]+q*N[0];let qt=v[Nt];Nt=bt+xt*N[2]+ot*N[1]+q*N[0];let Kt=v[Nt],me=At+(Dt-At)*dt,Rt=qt+(Kt-qt)*dt;Nt=bt+it*E[2]+J*E[1]+$*E[0],y.values[Nt]=me+(Rt-me)*st}}}else for(let K=0;K<g;++K){let ot=g>1?M*(m-1)+K*j:.5*(M+H)*(m-1);if(ot<0||ot>m-1){for(let ft=0;ft<f;ft++){let lt=ft+K*E[2]+J*E[1]+$*E[0];y.values[lt]=l}continue}let st=Math.round(ot),it=Math.round(nt);for(let ft=0;ft<f;ft++){let lt=ft+st*N[2]+it*N[1]+q*N[0],xt=ft+K*E[2]+J*E[1]+$*E[0];y.values[xt]=v[lt]}}}}return e.makeTensorInfo(y.shape,y.dtype,y.values)}var QR={kernelName:pa,backendName:"cpu",kernelFunc:M9};function z9(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{axis:s,exclusive:i,reverse:a}=n;rt(o,"cumprod");let u=S.getAxesPermutation([s],o.shape.length),l=o;u!=null&&(l=Ue({inputs:{x:o},backend:e,attrs:{perm:u}}));let c=S.getInnerMostAxes(1,o.shape.length)[0];if(c!==l.shape.length-1)throw new Error(`backend.cumprod in CPU expects an inner-most axis=${l.shape.length-1} but got axis=${c}`);let p=ir(l.dtype,"int32"),m=x.makeOnesTypedArray(x.sizeFromShape(l.shape),p),f=e.data.get(l.dataId).values,d=l.shape[l.shape.length-1],h=a?(y,b)=>y+d-b-1:(y,b)=>y+b;for(let y=0;y<f.length;y+=d)for(let b=0;b<d;b++){let w=h(y,b);if(b===0)m[w]=i?1:f[w];else{let v=h(y,b-1);m[w]=i?f[v]*m[v]:f[w]*m[v]}}let g=e.makeTensorInfo(l.shape,p,m);if(u!=null){let y=S.getUndoAxesPermutation(u),b=Ue({inputs:{x:g},backend:e,attrs:{perm:y}});return e.disposeIntermediateTensorInfo(g),e.disposeIntermediateTensorInfo(l),b}return g}var tO={kernelName:ca,backendName:"cpu",kernelFunc:z9};function B9(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{axis:s,exclusive:i,reverse:a}=n;rt(o,"cumsum");let u=S.getAxesPermutation([s],o.shape.length),l=o;u!=null&&(l=Ue({inputs:{x:o},backend:e,attrs:{perm:u}}));let c=S.getInnerMostAxes(1,o.shape.length)[0];if(c!==l.shape.length-1)throw new Error(`backend.cumsum in CPU expects an inner-most axis=${l.shape.length-1} but got axis=${c}`);let p=ir(l.dtype,"int32"),m=x.makeZerosTypedArray(x.sizeFromShape(l.shape),p),f=e.data.get(l.dataId).values,d=l.shape[l.shape.length-1],h=a?(y,b)=>y+d-b-1:(y,b)=>y+b;for(let y=0;y<f.length;y+=d)for(let b=0;b<d;b++){let w=h(y,b);if(b===0)m[w]=i?0:f[w];else{let v=h(y,b-1);m[w]=i?f[v]+m[v]:f[w]+m[v]}}let g=e.makeTensorInfo(l.shape,p,m);if(u!=null){let y=S.getUndoAxesPermutation(u),b=Ue({inputs:{x:g},backend:e,attrs:{perm:y}});return e.disposeIntermediateTensorInfo(g),e.disposeIntermediateTensorInfo(l),b}return g}var eO={kernelName:rs,backendName:"cpu",kernelFunc:B9};function V9(r){let{inputs:t,backend:e,attrs:n}=r,{x:o,weights:s}=t,{size:i,binaryOutput:a}=n;if(o.shape.length===1){let u=e.data.get(o.dataId).values,l=e.data.get(s.dataId).values,c=md(u,l,s.dtype,s.shape,i);return e.makeTensorInfo([i],s.dtype,c)}else if(o.shape.length===2){let u=e.bufferSync(o),l=e.bufferSync(s),c=aw(u,l,i,a);return e.makeTensorInfo(c.shape,s.dtype,c.values)}throw new Error(`Error in denseBincount: input must be at most rank 2, but got rank${o.shape.length}.`)}var rO={kernelName:_p,backendName:"cpu",kernelFunc:V9};function G9(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{blockSize:s,dataFormat:i}=n;x.assert(i==="NHWC",()=>`Only NHWC dataFormat supported on CPU for depthToSpace. Got ${i}`);let a=o.shape[0],u=o.shape[1],l=o.shape[2],c=o.shape[3],p=u*s,m=l*s,f=c/(s*s),d=e.data.get(o.dataId).values,h=new Float32Array(a*p*m*f),g=0;for(let y=0;y<a;++y)for(let b=0;b<p;++b){let w=Math.floor(b/s),v=b%s;for(let N=0;N<m;++N){let E=Math.floor(N/s),$=N%s,D=(v*s+$)*f;for(let L=0;L<f;++L){let G=L+D+c*(E+l*(w+u*y));h[g++]=d[G]}}}return e.makeTensorInfo([a,p,m,f],o.dtype,h)}var nO={kernelName:ma,backendName:"cpu",kernelFunc:G9};function yk(r){let{inputs:t,backend:e,attrs:n}=r,{x:o,filter:s}=t,{strides:i,pad:a,dilations:u,dimRoundingMode:l}=n;rt([o,s],"depthwiseConv2DNative");let c=x.computeStrides(o.shape),p=x.computeStrides(s.shape),m=u;m==null&&(m=[1,1]),x.assert(S.eitherStridesOrDilationsAreOne(i,m),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. 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n=1,o=1;r.texImage2D(r.TEXTURE_2D,0,t.internalFormatFloat,n,o,0,t.textureFormatFloat,t.textureTypeFloat,null);let s=r.createFramebuffer();r.bindFramebuffer(r.FRAMEBUFFER,s),r.framebufferTexture2D(r.FRAMEBUFFER,r.COLOR_ATTACHMENT0,r.TEXTURE_2D,e,0);let i=r.checkFramebufferStatus(r.FRAMEBUFFER)===r.FRAMEBUFFER_COMPLETE;return r.bindTexture(r.TEXTURE_2D,null),r.bindFramebuffer(r.FRAMEBUFFER,null),r.deleteTexture(e),r.deleteFramebuffer(s),i}function ZQ(r,t){let e=Qh(r,t),n=r.createTexture();r.bindTexture(r.TEXTURE_2D,n);let o=1,s=1;r.texImage2D(r.TEXTURE_2D,0,e.internalFormatHalfFloat,o,s,0,e.textureFormatFloat,e.textureTypeHalfFloat,null);let i=r.createFramebuffer();r.bindFramebuffer(r.FRAMEBUFFER,i),r.framebufferTexture2D(r.FRAMEBUFFER,r.COLOR_ATTACHMENT0,r.TEXTURE_2D,n,0);let a=r.checkFramebufferStatus(r.FRAMEBUFFER)===r.FRAMEBUFFER_COMPLETE;return r.bindTexture(r.TEXTURE_2D,null),r.bindFramebuffer(r.FRAMEBUFFER,null),r.deleteTexture(n),r.deleteFramebuffer(i),a}function qk(r){return r!==2?!1:Gn(r).fenceSync!=null}function ni(r,t){Array.isArray(r)||(r=[r]),r.forEach(e=>{e!=null&&x.assert(e.dtype!=="complex64",()=>`${t} does not support complex64 tensors in the WebGL backend.`)})}var Ft=B();Ft.registerFlag("HAS_WEBGL",()=>Ft.getNumber("WEBGL_VERSION")>0);Ft.registerFlag("WEBGL_VERSION",()=>Ew(2)?2:Ew(1)?1:0);Ft.registerFlag("WEBGL_CHECK_NUMERICAL_PROBLEMS",()=>!1);Ft.registerFlag("WEBGL_BUFFER_SUPPORTED",()=>Ft.get("WEBGL_VERSION")===2);Ft.registerFlag("WEBGL_CPU_FORWARD",()=>!0);Ft.registerFlag("WEBGL_FORCE_F16_TEXTURES",()=>!1);Ft.registerFlag("WEBGL_PACK",()=>Ft.getBool("HAS_WEBGL"));Ft.registerFlag("WEBGL_PACK_NORMALIZATION",()=>Ft.getBool("WEBGL_PACK"));Ft.registerFlag("WEBGL_PACK_CLIP",()=>Ft.getBool("WEBGL_PACK"));Ft.registerFlag("WEBGL_PACK_DEPTHWISECONV",()=>Ft.getBool("WEBGL_PACK"));Ft.registerFlag("WEBGL_PACK_BINARY_OPERATIONS",()=>Ft.getBool("WEBGL_PACK"));Ft.registerFlag("WEBGL_PACK_UNARY_OPERATIONS",()=>Ft.getBool("WEBGL_PACK"));Ft.registerFlag("WEBGL_PACK_ARRAY_OPERATIONS",()=>Ft.getBool("WEBGL_PACK"));Ft.registerFlag("WEBGL_PACK_IMAGE_OPERATIONS",()=>Ft.getBool("WEBGL_PACK"));Ft.registerFlag("WEBGL_PACK_REDUCE",()=>Ft.getBool("WEBGL_PACK"));Ft.registerFlag("WEBGL_LAZILY_UNPACK",()=>Ft.getBool("WEBGL_PACK"));Ft.registerFlag("WEBGL_CONV_IM2COL",()=>Ft.getBool("WEBGL_PACK"));Ft.registerFlag("WEBGL_MAX_TEXTURE_SIZE",()=>Vk(Ft.getNumber("WEBGL_VERSION")));Ft.registerFlag("WEBGL_MAX_TEXTURES_IN_SHADER",()=>Gk(Ft.getNumber("WEBGL_VERSION")));Ft.registerFlag("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION",()=>{let 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      bool isnan_custom(float val) {
        uint floatToUint = floatBitsToUint(val);
        return (floatToUint & 0x7fffffffu) > 0x7f800000u;
      }

      bvec4 isnan_custom(vec4 val) {
        return bvec4(isnan_custom(val.x),
          isnan_custom(val.y), isnan_custom(val.z), isnan_custom(val.w));
      }

      #define isnan(value) isnan_custom(value)
    `,u="",l=`
      #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)));
      }
    `):(r="",t="attribute",e="varying",n="varying",o="texture2D",s="gl_FragColor",i="",a=`
      #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));
      }
    `,u=`
      uniform float INFINITY;

      bool isinf(float val) {
        return abs(val) == INFINITY;
      }
      bvec4 isinf(vec4 val) {
        return equal(abs(val), vec4(INFINITY));
      }
    `,l=`
      int round(float value) {
        return int(floor(value + 0.5));
      }

      ivec4 round(vec4 value) {
        return ivec4(floor(value + vec4(0.5)));
      }
    `),{version:r,attribute:t,varyingVs:e,varyingFs:n,texture2D:o,output:s,defineOutput:i,defineSpecialNaN:a,defineSpecialInf:u,defineRound:l}}function oi(r,t,e="index"){let n=x.computeStrides(t);return n.map((o,s)=>{let i=`int ${r[s]} = ${e} / ${o}`,a=s===n.length-1?`int ${r[s+1]} = ${e} - ${r[s]} * ${o}`:`index -= ${r[s]} * ${o}`;return`${i}; ${a};`}).join("")}function Uc(r,t,e="index"){let n=x.computeStrides(t);return n.map((o,s)=>{let i=`int ${r[s]} = ${e} / outShapeStrides[${s}]`,a=s===n.length-1?`int ${r[s+1]} = ${e} - ${r[s]} * outShapeStrides[${s}]`:`index -= ${r[s]} * outShapeStrides[${s}]`;return`${i}; ${a};`}).join("")}function JQ(r,t){let e=r.length,n=r.map(s=>`${t}[${s}]`),o=new Array(e-1);o[e-2]=n[e-1];for(let s=e-3;s>=0;--s)o[s]=`(${o[s+1]} * ${n[s+1]})`;return o}function ZL(r,t,e="index"){let n=r.map((s,i)=>i),o=JQ(n,t);return o.map((s,i)=>{let a=`int ${r[i]} = ${e} / ${o[i]}`,u=i===o.length-1?`int ${r[i+1]} = ${e} - ${r[i]} * ${o[i]}`:`index -= ${r[i]} * ${o[i]}`;return`${a}; ${u};`}).join("")}function wd(r){let t=x.computeStrides(r).map(e=>e.toString());return`
  int getFlatIndex(ivec3 coords) {
    return coords.x * ${t[0]} + coords.y * ${t[1]} + coords.z;
  }
`}function vd(){return`
  int getFlatIndex(ivec3 coords) {
    return coords.x * outShapeStrides[0] + coords.y * outShapeStrides[1] + coords.z;
  }
`}var Aw=`
  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;
  }
`;var{getBroadcastDims:JL}=S;function QL(r,t,e){let n=[];if(r.forEach(f=>{let d=x.sizeFromShape(f.shapeInfo.logicalShape);if(f.shapeInfo.isUniform?n.push(`uniform float ${f.name}${d>1?`[${d}]`:""};`):(n.push(`uniform sampler2D ${f.name};`),n.push(`uniform int offset${f.name};`)),e.enableShapeUniforms){let{uniformShape:h}=$w(e.packedInputs,f.shapeInfo.logicalShape,f.shapeInfo.texShape);switch(h.length){case 1:n.push(`uniform int ${f.name}Shape;`);break;case 2:n.push(`uniform ivec2 ${f.name}Shape;`);break;case 3:n.push(`uniform ivec3 ${f.name}Shape;`);break;case 4:n.push(`uniform ivec4 ${f.name}Shape;`);break;default:break}n.push(`uniform ivec2 ${f.name}TexShape;`)}}),e.enableShapeUniforms){switch(t.logicalShape.length){case 1:n.push("uniform int outShape;");break;case 2:n.push("uniform ivec2 outShape;"),n.push("uniform int outShapeStrides;");break;case 3:n.push("uniform ivec3 outShape;"),n.push("uniform ivec2 outShapeStrides;");break;case 4:n.push("uniform ivec4 outShape;"),n.push("uniform ivec3 outShapeStrides;");break;default:break}n.push("uniform ivec2 outTexShape;")}e.customUniforms&&e.customUniforms.forEach(f=>{n.push(`uniform ${f.type} ${f.name}${f.arrayIndex?`[${f.arrayIndex}]`:""};`)});let o=n.join(`
`),s=r.map(f=>QQ(f,t,e.packedInputs,e.enableShapeUniforms)).join(`
`),i=t.texShape,a=He(),u=rtt(a),l,c,p=stt(a);return t.isPacked?(l=ttt(t.logicalShape,i,e.enableShapeUniforms),c=ott(a)):(l=ett(t.logicalShape,i,e.enableShapeUniforms),c=ntt(a)),e.packedInputs&&(p+=utt),[p,u,c,o,l,s,e.userCode].join(`
`)}function Id(r,t=!1){let e=r.shapeInfo.logicalShape;switch(e.length){case 0:return vtt(r,t);case 1:return Itt(r,t);case 2:return Ntt(r,t);case 3:return Ttt(r,t);case 4:return Ett(r,t);case 5:return Att(r);case 6:return $tt(r);default:throw new Error(`${e.length}-D input sampling is not yet supported`)}}function tP(r,t){switch(r.shapeInfo.logicalShape.length){case 0:return wtt(r);case 1:return Ctt(r,t);case 2:return Stt(r,t);case 3:return ktt(r,t);default:return _tt(r,t)}}function QQ(r,t,e=!1,n){let o="";e?o+=tP(r,n):o+=Id(r,n);let s=r.shapeInfo.logicalShape,i=t.logicalShape;return s.length<=i.length&&(e?o+=Dtt(r,t):o+=Ftt(r,t)),o}function ttt(r,t,e){switch(r.length){case 0:return eP();case 1:return ctt(r,t,e);case 2:return ytt(r,t,e);case 3:return mtt(r,t,e);default:return dtt(r,t,e)}}function ett(r,t,e){switch(r.length){case 0:return eP();case 1:return ptt(r,t,e);case 2:return btt(r,t,e);case 3:return ftt(r,t,e);case 4:return htt(r,t,e);case 5:return gtt(r,t);case 6:return xtt(r,t);default:throw new Error(`${r.length}-D output sampling is not yet supported`)}}function rtt(r){return`
    float sampleTexture(sampler2D textureSampler, vec2 uv) {
      return ${r.texture2D}(textureSampler, uv).r;
    }
  `}function ntt(r){return`
    void setOutput(float val) {
      ${r.output} = vec4(val, 0, 0, 0);
    }
  `}function ott(r){return`
    void setOutput(vec4 val) {
      ${r.output} = val;
    }
  `}function stt(r){return`${r.version}
    precision highp float;
    precision highp int;
    precision highp sampler2D;
    ${r.varyingFs} vec2 resultUV;
    ${r.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;
    ${r.defineSpecialNaN}
    ${r.defineSpecialInf}
    ${r.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);
    }

    ${itt}
    ${att}
    ${ltt}
  `}var itt=`
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);
}
`,att=`
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);
}
`,ltt=`
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);
}
`,utt=`
  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 eP(){return`
    int getOutputCoords() {
      return 0;
    }
  `}function ctt(r,t,e){let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)];return n[0]===1?e?`
      int getOutputCoords() {
        return 2 * int(resultUV.x * ceil(float(outTexShape[1]) / 2.0));
      }
    `:`
      int getOutputCoords() {
        return 2 * int(resultUV.x * ${n[1]}.0);
      }
    `:n[1]===1?e?`
      int getOutputCoords() {
        return 2 * int(resultUV.y * ceil(float(outTexShape[0]) / 2.0));
      }
    `:`
      int getOutputCoords() {
        return 2 * int(resultUV.y * ${n[0]}.0);
      }
    `:e?`
    int getOutputCoords() {
      ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(packedTexShape[0], packedTexShape[1]));
      return 2 * (resTexRC.x * packedTexShape[1] + resTexRC.y);
    }
  `:`
    int getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(${n[0]}, ${n[1]}));
      return 2 * (resTexRC.x * ${n[1]} + resTexRC.y);
    }
  `}function ptt(r,t,e){return t[0]===1?e?`
      int getOutputCoords() {
        return int(resultUV.x * float(outTexShape[1]));
      }
    `:`
      int getOutputCoords() {
        return int(resultUV.x * ${t[1]}.0);
      }
    `:t[1]===1?e?`
      int getOutputCoords() {
        return int(resultUV.y * float(outTexShape[0]));
      }
    `:`
      int getOutputCoords() {
        return int(resultUV.y * ${t[0]}.0);
      }
    `:e?`
    int getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(outTexShape[0], outTexShape[1]));
      return resTexRC.x * outTexShape[1] + resTexRC.y;
    }
  `:`
    int getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(${t[0]}, ${t[1]}));
      return resTexRC.x * ${t[1]} + resTexRC.y;
    }
  `}function mtt(r,t,e){if(e)return`
    ivec3 getOutputCoords() {
      ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));
      int texelsInLogicalRow = int(ceil(float(outShape[2]) / 2.0));
      int texelsInBatch = texelsInLogicalRow * int(ceil(float(outShape[1]) / 2.0));
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(packedTexShape[0], packedTexShape[1]));
      int index = resTexRC.x * packedTexShape[1] + resTexRC.y;

      int b = index / texelsInBatch;
      index -= b * texelsInBatch;

      int r = 2 * (index / texelsInLogicalRow);
      int c = imod(index, texelsInLogicalRow) * 2;

      return ivec3(b, r, c);
    }
  `;let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)],o=Math.ceil(r[2]/2),s=o*Math.ceil(r[1]/2);return`
    ivec3 getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(${n[0]}, ${n[1]}));
      int index = resTexRC.x * ${n[1]} + resTexRC.y;

      int b = index / ${s};
      index -= b * ${s};

      int r = 2 * (index / ${o});
      int c = imod(index, ${o}) * 2;

      return ivec3(b, r, c);
    }
  `}function ftt(r,t,e){if(e)return`
  ivec3 getOutputCoords() {
    ivec2 resTexRC = ivec2(resultUV.yx *
                           vec2(outTexShape[0], outTexShape[1]));
    int index = resTexRC.x * outTexShape[1] + resTexRC.y;
    ${Uc(["r","c","d"],r)}
    return ivec3(r, c, d);
  }
`;let n=oi(["r","c","d"],r);return`
    ivec3 getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(${t[0]}, ${t[1]}));
      int index = resTexRC.x * ${t[1]} + resTexRC.y;
      ${n}
      return ivec3(r, c, d);
    }
  `}function dtt(r,t,e){if(e)return`
    ivec4 getOutputCoords() {
      ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(packedTexShape[0], packedTexShape[1]));
      int index = resTexRC.x * packedTexShape[1] + resTexRC.y;

      int texelsInLogicalRow = int(ceil(float(outShape[3]) / 2.0));
      int texelsInBatch = texelsInLogicalRow * int(ceil(float(outShape[2]) / 2.0));
      int texelsInBatchN = texelsInBatch * outShape[1];

      int b2 = index / texelsInBatchN;
      index -= b2 * texelsInBatchN;

      int b = index / texelsInBatch;
      index -= b * texelsInBatch;

      int r = 2 * (index / texelsInLogicalRow);
      int c = imod(index, texelsInLogicalRow) * 2;

      return ivec4(b2, b, r, c);
    }
  `;let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)],o=Math.ceil(r[r.length-1]/2),s=o*Math.ceil(r[r.length-2]/2),i=s,a="",u="b, r, c";for(let l=2;l<r.length-1;l++)i*=r[r.length-l-1],a=`
      int b${l} = index / ${i};
      index -= b${l} * ${i};
    `+a,u=`b${l}, `+u;return`
    ivec${r.length} getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(${n[0]}, ${n[1]}));
      int index = resTexRC.x * ${n[1]} + resTexRC.y;

      ${a}

      int b = index / ${s};
      index -= b * ${s};

      int r = 2 * (index / ${o});
      int c = imod(index, ${o}) * 2;

      return ivec${r.length}(${u});
    }
  `}function htt(r,t,e){if(e)return`
    ivec4 getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
        vec2(outTexShape[0], outTexShape[1]));
      int index = resTexRC.x * outTexShape[1] + resTexRC.y;
      ${Uc(["r","c","d","d2"],r)}
      return ivec4(r, c, d, d2);
    }
  `;let n=oi(["r","c","d","d2"],r);return`
    ivec4 getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
        vec2(${t[0]}, ${t[1]}));
      int index = resTexRC.x * ${t[1]} + resTexRC.y;
      ${n}
      return ivec4(r, c, d, d2);
    }
  `}function gtt(r,t){let e=oi(["r","c","d","d2","d3"],r);return`
    ivec5 getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx * vec2(${t[0]},
                             ${t[1]}));

      int index = resTexRC.x * ${t[1]} + resTexRC.y;

      ${e}

      ivec5 outShape = ivec5(r, c, d, d2, d3);
      return outShape;
    }
  `}function xtt(r,t){let e=oi(["r","c","d","d2","d3","d4"],r);return`
    ivec6 getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
        vec2(${t[0]}, ${t[1]}));
      int index = resTexRC.x * ${t[1]} + resTexRC.y;

      ${e}

      ivec6 result = ivec6(r, c, d, d2, d3, d4);
      return result;
    }
  `}function ytt(r,t,e){let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)];if(x.arraysEqual(r,t))return e?`
      ivec2 getOutputCoords() {
        ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));
        return 2 * ivec2(resultUV.yx * vec2(packedTexShape[0], packedTexShape[1]));
      }
    `:`
      ivec2 getOutputCoords() {
        return 2 * ivec2(resultUV.yx * vec2(${n[0]}, ${n[1]}));
      }
    `;let o=Math.ceil(r[1]/2);return e?`
    ivec2 getOutputCoords() {
      ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));
      int texelsInLogicalRow = int(ceil(float(outShape[1]) / 2.0));
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(packedTexShape[0], packedTexShape[1]));

      int index = resTexRC.x * packedTexShape[1] + resTexRC.y;
      int r = 2 * (index / texelsInLogicalRow);
      int c = imod(index, texelsInLogicalRow) * 2;

      return ivec2(r, c);
    }
  `:`
    ivec2 getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(${n[0]}, ${n[1]}));

      int index = resTexRC.x * ${n[1]} + resTexRC.y;
      int r = 2 * (index / ${o});
      int c = imod(index, ${o}) * 2;

      return ivec2(r, c);
    }
  `}function btt(r,t,e){return x.arraysEqual(r,t)?e?`
      ivec2 getOutputCoords() {
        return ivec2(resultUV.yx * vec2(outTexShape[0], outTexShape[1]));
      }
    `:`
      ivec2 getOutputCoords() {
        return ivec2(resultUV.yx * vec2(${t[0]}, ${t[1]}));
      }
    `:r[1]===1?e?`
      ivec2 getOutputCoords() {
        ivec2 resTexRC = ivec2(resultUV.yx *
                               vec2(outTexShape[0], outTexShape[1]));
        int index = resTexRC.x * outTexShape[1] + resTexRC.y;
        return ivec2(index, 0);
      }
    `:`
      ivec2 getOutputCoords() {
        ivec2 resTexRC = ivec2(resultUV.yx *
                               vec2(${t[0]}, ${t[1]}));
        int index = resTexRC.x * ${t[1]} + resTexRC.y;
        return ivec2(index, 0);
      }
    `:r[0]===1?e?`
      ivec2 getOutputCoords() {
        ivec2 resTexRC = ivec2(resultUV.yx *
                               vec2(outTexShape[0], outTexShape[1]));
        int index = resTexRC.x * outTexShape[1] + resTexRC.y;
        return ivec2(0, index);
      }
    `:`
      ivec2 getOutputCoords() {
        ivec2 resTexRC = ivec2(resultUV.yx *
                               vec2(${t[0]}, ${t[1]}));
        int index = resTexRC.x * ${t[1]} + resTexRC.y;
        return ivec2(0, index);
      }
    `:e?`
    ivec2 getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(outTexShape[0], outTexShape[1]));
      int index = resTexRC.x * outTexShape[1] + resTexRC.y;
      int r = index / outShape[1];
      int c = index - r * outShape[1];
      return ivec2(r, c);
    }
  `:`
    ivec2 getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(${t[0]}, ${t[1]}));
      int index = resTexRC.x * ${t[1]} + resTexRC.y;
      int r = index / ${r[1]};
      int c = index - r * ${r[1]};
      return ivec2(r, c);
    }
  `}function Hc(r){return`offset${r}`}function wtt(r){let t=r.name,e="get"+t.charAt(0).toUpperCase()+t.slice(1),n=He();return`
    vec4 ${e}() {
      return ${n.texture2D}(${t}, halfCR);
    }
  `}function vtt(r,t){let e=r.name,n="get"+e.charAt(0).toUpperCase()+e.slice(1);if(r.shapeInfo.isUniform)return`float ${n}() {return ${e};}`;let[o,s]=r.shapeInfo.texShape;if(o===1&&s===1)return`
      float ${n}() {
        return sampleTexture(${e}, halfCR);
      }
    `;let i=Hc(e);if(t)return`
    float ${n}() {
      vec2 uv = uvFromFlat(${e}TexShape[0], ${e}TexShape[1], ${i});
      return sampleTexture(${e}, uv);
    }
  `;let[a,u]=r.shapeInfo.texShape;return`
    float ${n}() {
      vec2 uv = uvFromFlat(${a}, ${u}, ${i});
      return sampleTexture(${e}, uv);
    }
  `}function Ctt(r,t){let e=r.name,n="get"+e.charAt(0).toUpperCase()+e.slice(1),o=r.shapeInfo.texShape,s=He();if(t)return`
    vec4 ${n}(int index) {
      ivec2 packedTexShape = ivec2(ceil(float(${e}TexShape[0]) / 2.0), ceil(float(${e}TexShape[1]) / 2.0));
      vec2 uv = packedUVfrom1D(
        packedTexShape[0], packedTexShape[1], index);
      return ${s.texture2D}(${e}, uv);
    }
  `;let i=[Math.ceil(o[0]/2),Math.ceil(o[1]/2)];return`
    vec4 ${n}(int index) {
      vec2 uv = packedUVfrom1D(
        ${i[0]}, ${i[1]}, index);
      return ${s.texture2D}(${e}, uv);
    }
  `}function Itt(r,t){let e=r.name,n="get"+e.charAt(0).toUpperCase()+e.slice(1);if(r.shapeInfo.isUniform)return`
      float ${n}(int index) {
        ${Sd(r)}
      }
    `;let o=r.shapeInfo.texShape,s=o[0],i=o[1];if(i===1&&s===1)return`
      float ${n}(int index) {
        return sampleTexture(${e}, halfCR);
      }
    `;let a=Hc(e);return i===1?t?`
      float ${n}(int index) {
        vec2 uv = vec2(0.5, (float(index + ${a}) + 0.5) / float(${e}TexShape[0]));
        return sampleTexture(${e}, uv);
      }
    `:`
      float ${n}(int index) {
        vec2 uv = vec2(0.5, (float(index + ${a}) + 0.5) / ${s}.0);
        return sampleTexture(${e}, uv);
      }
    `:s===1?t?`
      float ${n}(int index) {
        vec2 uv = vec2((float(index + ${a}) + 0.5) / float(${e}TexShape[1]), 0.5);
        return sampleTexture(${e}, uv);
      }
    `:`
      float ${n}(int index) {
        vec2 uv = vec2((float(index + ${a}) + 0.5) / ${i}.0, 0.5);
        return sampleTexture(${e}, uv);
      }
    `:t?`
    float ${n}(int index) {
      vec2 uv = uvFromFlat(${e}TexShape[0], ${e}TexShape[1], index + ${a});
      return sampleTexture(${e}, uv);
    }
  `:`
    float ${n}(int index) {
      vec2 uv = uvFromFlat(${s}, ${i}, index + ${a});
      return sampleTexture(${e}, uv);
    }
  `}function Stt(r,t){let e=r.shapeInfo.logicalShape,n=r.name,o="get"+n.charAt(0).toUpperCase()+n.slice(1),s=r.shapeInfo.texShape,i=s[0],a=s[1],u=He();if(s!=null&&x.arraysEqual(e,s))return t?`
      vec4 ${o}(int row, int col) {
        vec2 uv = (vec2(col, row) + halfCR) / vec2(${n}TexShape[1], ${n}TexShape[0]);

        return ${u.texture2D}(${n}, uv);
      }
    `:`
      vec4 ${o}(int row, int col) {
        vec2 uv = (vec2(col, row) + halfCR) / vec2(${a}.0, ${i}.0);

        return ${u.texture2D}(${n}, uv);
      }
    `;if(t)return`
    vec4 ${o}(int row, int col) {
      ivec2 packedTexShape = ivec2(ceil(float(${n}TexShape[0]) / 2.0), ceil(float(${n}TexShape[1]) / 2.0));
      int valuesPerRow = int(ceil(float(${n}Shape[1]) / 2.0));
      vec2 uv = packedUVfrom2D(valuesPerRow, packedTexShape[0], packedTexShape[1], row, col);
      return ${u.texture2D}(${n}, uv);
    }
  `;let l=[Math.ceil(s[0]/2),Math.ceil(s[1]/2)],c=Math.ceil(e[1]/2);return`
    vec4 ${o}(int row, int col) {
      vec2 uv = packedUVfrom2D(${c}, ${l[0]}, ${l[1]}, row, col);
      return ${u.texture2D}(${n}, uv);
    }
  `}function Ntt(r,t){let e=r.shapeInfo.logicalShape,n=r.name,o="get"+n.charAt(0).toUpperCase()+n.slice(1),s=r.shapeInfo.texShape;if(s!=null&&x.arraysEqual(e,s)){if(t)return`
      float ${o}(int row, int col) {
        vec2 uv = (vec2(col, row) + halfCR) / vec2(${n}TexShape[1], ${n}TexShape[0]);
        return sampleTexture(${n}, uv);
      }
    `;let m=s[0],f=s[1];return`
    float ${o}(int row, int col) {
      vec2 uv = (vec2(col, row) + halfCR) / vec2(${f}.0, ${m}.0);
      return sampleTexture(${n}, uv);
    }
  `}let{newShape:i,keptDims:a}=x.squeezeShape(e),u=i;if(u.length<e.length){let m=Nd(r,u),f=["row","col"];return`
      ${Id(m,t)}
      float ${o}(int row, int col) {
        return ${o}(${kd(f,a)});
      }
    `}if(r.shapeInfo.isUniform)return`
      float ${o}(int row, int col) {
        int index = round(dot(vec2(row, col), vec2(${e[1]}, 1)));
        ${Sd(r)}
      }
    `;let l=s[0],c=s[1],p=Hc(n);return c===1?t?`
      float ${o}(int row, int col) {
        float index = dot(vec3(row, col, ${p}), vec3(${n}Shape[1], 1, 1));
        vec2 uv = vec2(0.5, (index + 0.5) / float(${n}TexShape[0]));
        return sampleTexture(${n}, uv);
      }
    `:`
    float ${o}(int row, int col) {
      float index = dot(vec3(row, col, ${p}), vec3(${e[1]}, 1, 1));
      vec2 uv = vec2(0.5, (index + 0.5) / ${l}.0);
      return sampleTexture(${n}, uv);
    }
  `:l===1?t?`
      float ${o}(int row, int col) {
        float index = dot(vec3(row, col, ${p}), vec3(${n}Shape[1], 1, 1));
        vec2 uv = vec2((index + 0.5) / float(${n}TexShape[1]), 0.5);
        return sampleTexture(${n}, uv);
      }
    `:`
    float ${o}(int row, int col) {
      float index = dot(vec3(row, col, ${p}), vec3(${e[1]}, 1, 1));
      vec2 uv = vec2((index + 0.5) / ${c}.0, 0.5);
      return sampleTexture(${n}, uv);
    }
  `:t?`
      float ${o}(int row, int col) {
        // Explicitly use integer operations as dot() only works on floats.
        int index = row * ${n}Shape[1] + col + ${p};
        vec2 uv = uvFromFlat(${n}TexShape[0], ${n}TexShape[1], index);
        return sampleTexture(${n}, uv);
      }
    `:`
  float ${o}(int row, int col) {
    // Explicitly use integer operations as dot() only works on floats.
    int index = row * ${e[1]} + col + ${p};
    vec2 uv = uvFromFlat(${l}, ${c}, index);
    return sampleTexture(${n}, uv);
  }
`}function ktt(r,t){let e=r.shapeInfo.logicalShape,n=r.name,o="get"+n.charAt(0).toUpperCase()+n.slice(1),s=r.shapeInfo.texShape,i=[Math.ceil(s[0]/2),Math.ceil(s[1]/2)];if(e[0]===1){let m=e.slice(1),f=[1,2],d=Nd(r,m),h=["b","row","col"];return`
        ${tP(d,t)}
        vec4 ${o}(int b, int row, int col) {
          return ${o}(${kd(h,f)});
        }
      `}let a=He();if(t)return`
    vec4 ${o}(int b, int row, int col) {
      ivec2 packedTexShape = ivec2(ceil(float(${n}TexShape[0]) / 2.0), ceil(float(${n}TexShape[1]) / 2.0));
      int valuesPerRow = int(ceil(float(${n}Shape[2]) / 2.0));
      int texelsInBatch = valuesPerRow * int(ceil(float(${n}Shape[1]) / 2.0));
      vec2 uv = packedUVfrom3D(
        packedTexShape[0], packedTexShape[1], texelsInBatch, valuesPerRow, b, row, col);
      return ${a.texture2D}(${n}, uv);
    }
  `;let u=i[0],l=i[1],c=Math.ceil(e[2]/2),p=c*Math.ceil(e[1]/2);return`
    vec4 ${o}(int b, int row, int col) {
      vec2 uv = packedUVfrom3D(
        ${u}, ${l}, ${p}, ${c}, b, row, col);
      return ${a.texture2D}(${n}, uv);
    }
  `}function Ttt(r,t){let e=r.shapeInfo.logicalShape,n=r.name,o="get"+n.charAt(0).toUpperCase()+n.slice(1),s=e[1]*e[2],i=e[2],{newShape:a,keptDims:u}=x.squeezeShape(e),l=a;if(l.length<e.length){let h=Nd(r,l),g=["row","col","depth"];return`
        ${Id(h,t)}
        float ${o}(int row, int col, int depth) {
          return ${o}(${kd(g,u)});
        }
      `}if(r.shapeInfo.isUniform)return`
      float ${o}(int row, int col, int depth) {
        int index = round(dot(vec3(row, col, depth),
                          vec3(${s}, ${i}, 1)));
        ${Sd(r)}
      }
    `;let c=r.shapeInfo.texShape,p=c[0],m=c[1],f=r.shapeInfo.flatOffset;if(m===s&&f==null)return t?`
      float ${o}(int row, int col, int depth) {
        int stride1 = ${n}Shape[2];
        float texR = float(row);
        float texC = dot(vec2(col, depth), vec2(stride1, 1));
        vec2 uv = (vec2(texC, texR) + halfCR) /
                   vec2(${n}TexShape[1], ${n}TexShape[0]);
        return sampleTexture(${n}, uv);
      }
    `:`
        float ${o}(int row, int col, int depth) {
          float texR = float(row);
          float texC = dot(vec2(col, depth), vec2(${i}, 1));
          vec2 uv = (vec2(texC, texR) + halfCR) /
                     vec2(${m}.0, ${p}.0);
          return sampleTexture(${n}, uv);
        }
      `;if(m===i&&f==null)return t?`
      float ${o}(int row, int col, int depth) {
        float texR = dot(vec2(row, col), vec2(${n}Shape[1], 1));
        float texC = float(depth);
        vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${n}TexShape[1], ${n}TexShape[0]);
        return sampleTexture(${n}, uv);
      }
    `:`
    float ${o}(int row, int col, int depth) {
      float texR = dot(vec2(row, col), vec2(${e[1]}, 1));
      float texC = float(depth);
      vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${m}.0, ${p}.0);
      return sampleTexture(${n}, uv);
    }
  `;let d=Hc(n);return t?`
    float ${o}(int row, int col, int depth) {
      // Explicitly use integer operations as dot() only works on floats.
      int stride0 = ${n}Shape[1] * ${n}Shape[2];
      int stride1 = ${n}Shape[2];
      int index = row * ${s} + col * ${i} + depth + ${d};
      vec2 uv = uvFromFlat(${n}TexShape[0], ${n}TexShape[1], index);
      return sampleTexture(${n}, uv);
    }
    `:`
      float ${o}(int row, int col, int depth) {
        // Explicitly use integer operations as dot() only works on floats.
        int index = row * ${s} + col * ${i} + depth + ${d};
        vec2 uv = uvFromFlat(${p}, ${m}, index);
        return sampleTexture(${n}, uv);
      }
  `}function _tt(r,t){let e=r.name,n="get"+e.charAt(0).toUpperCase()+e.slice(1),o=He();if(t)return`
    vec4 ${n}(int b2, int b, int row, int col) {
      int valuesPerRow = int(ceil(float(${e}Shape[3]) / 2.0));
      int texelsInBatch = valuesPerRow * int(ceil(float(${e}Shape[2]) / 2.0));
      int index = b * texelsInBatch + (row / 2) * valuesPerRow + (col / 2);
      texelsInBatch *= ${e}Shape[1];
      index = b2 * texelsInBatch + index;
      ivec2 packedTexShape = ivec2(ceil(float(${e}TexShape[0]) / 2.0), ceil(float(${e}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 ${o.texture2D}(${e}, uv);
    }
  `;let s=r.shapeInfo.logicalShape,i=s.length,a=r.shapeInfo.texShape,u=[Math.ceil(a[0]/2),Math.ceil(a[1]/2)],l=u[0],c=u[1],p=Math.ceil(s[i-1]/2),m=p*Math.ceil(s[i-2]/2),f="int b, int row, int col",d=`b * ${m} + (row / 2) * ${p} + (col / 2)`;for(let h=2;h<i-1;h++)f=`int b${h}, `+f,m*=s[i-h-1],d=`b${h} * ${m} + `+d;return`
    vec4 ${n}(${f}) {
      int index = ${d};
      int texR = index / ${c};
      int texC = index - texR * ${c};
      vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${c}, ${l});
      return ${o.texture2D}(${e}, uv);
    }
  `}function Ett(r,t){let e=r.shapeInfo.logicalShape,n=r.name,o="get"+n.charAt(0).toUpperCase()+n.slice(1),s=e[3],i=e[2]*s,a=e[1]*i,{newShape:u,keptDims:l}=x.squeezeShape(e);if(u.length<e.length){let b=Nd(r,u),w=["row","col","depth","depth2"];return`
      ${Id(b,t)}
      float ${o}(int row, int col, int depth, int depth2) {
        return ${o}(${kd(w,l)});
      }
    `}if(r.shapeInfo.isUniform)return`
      float ${o}(int row, int col, int depth, int depth2) {
        int index = round(dot(vec4(row, col, depth, depth2),
                          vec4(${a}, ${i}, ${s}, 1)));
        ${Sd(r)}
      }
    `;let c=r.shapeInfo.flatOffset,p=r.shapeInfo.texShape,m=p[0],f=p[1],d=`int stride2 = ${n}Shape[3];`,h=`int stride1 = ${n}Shape[2] * stride2;`,g=`int stride0 = ${n}Shape[1] * stride1;`;if(f===a&&c==null)return t?`
      float ${o}(int row, int col, int depth, int depth2) {
        ${d}
        ${h}
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        float texC =
            dot(vec3(col, depth, depth2),
                vec3(stride1, stride2, 1));
        vec2 uv = (vec2(texC, texR) + halfCR) /
                   vec2(${n}TexShape[1], ${n}TexShape[0]);
        return sampleTexture(${n}, uv);
      }
    `:`
      float ${o}(int row, int col, int depth, int depth2) {
        float texR = float(row);
        float texC =
            dot(vec3(col, depth, depth2),
                vec3(${i}, ${s}, 1));
        vec2 uv = (vec2(texC, texR) + halfCR) /
                   vec2(${f}.0, ${m}.0);
        return sampleTexture(${n}, uv);
      }
    `;if(f===s&&c==null)return t?`
      float ${o}(int row, int col, int depth, int depth2) {
        float texR = dot(vec3(row, col, depth),
                         vec3(${n}Shape[1] * ${n}Shape[2], ${n}Shape[2], 1));
        float texC = float(depth2);
        vec2 uv = (vec2(texC, texR) + halfCR) /
                  vec2(${n}TexShape[1], ${n}TexShape[0]);
        return sampleTexture(${n}, uv);
      }
    `:`
      float ${o}(int row, int col, int depth, int depth2) {
        float texR = dot(vec3(row, col, depth),
                         vec3(${e[1]*e[2]}, ${e[2]}, 1));
        float texC = float(depth2);
        vec2 uv = (vec2(texC, texR) + halfCR) /
                  vec2(${f}.0, ${m}.0);
        return sampleTexture(${n}, uv);
      }
    `;let y=Hc(n);return t?`
    float ${o}(int row, int col, int depth, int depth2) {
      // Explicitly use integer operations as dot() only works on floats.
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      ${h}
      ${g}
      int index = row * stride0 + col * stride1 +
          depth * stride2 + depth2;
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    }
  `:`
    float ${o}(int row, int col, int depth, int depth2) {
      // Explicitly use integer operations as dot() only works on floats.
      int index = row * ${a} + col * ${i} +
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      vec2 uv = uvFromFlat(${m}, ${f}, index + ${y});
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    }
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        return ${n}(${kd(g,l)});
      }
    `}if(r.shapeInfo.isUniform)return`
      float ${n}(int row, int col, int depth, int depth2, int depth3) {
        float index = dot(
          vec4(row, col, depth, depth2),
          vec4(${a}, ${i}, ${s}, ${o})) +
          depth3;
        ${Sd(r)}
      }
    `;let c=r.shapeInfo.flatOffset,p=r.shapeInfo.texShape,m=p[0],f=p[1];if(f===a&&c==null)return`
      float ${n}(int row, int col, int depth, int depth2, int depth3) {
        int texR = row;
        float texC = dot(vec4(col, depth, depth2, depth3),
                         vec4(${i}, ${s}, ${o}, 1));
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                   vec2(${f}.0, ${m}.0);
        return sampleTexture(${e}, uv);
      }
    `;if(f===o&&c==null)return`
      float ${n}(int row, int col, int depth, int depth2, int depth3) {
        float texR = dot(
          vec4(row, col, depth, depth2),
          vec4(${t[1]*t[2]*t[3]},
               ${t[2]*t[3]}, ${t[3]}, 1));
        int texC = depth3;
        vec2 uv = (vec2(texC, texR) + halfCR) /
                  vec2(${f}.0, ${m}.0);
        return sampleTexture(${e}, uv);
      }
    `;let d=Hc(e);return`
    float ${n}(int row, int col, int depth, int depth2, int depth3) {
      // Explicitly use integer operations as dot() only works on floats.
      int index = row * ${a} + col * ${i} + depth * ${s} +
          depth2 * ${o} + depth3 + ${d};
      vec2 uv = uvFromFlat(${m}, ${f}, index);
      return sampleTexture(${e}, uv);
    }
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      ${Id(g)}
      float ${n}(int row, int col, int depth,
                    int depth2, int depth3, int depth4) {
        return ${n}(${kd(y,s)});
      }
    `}let i=t[5],a=t[4]*i,u=t[3]*a,l=t[2]*u,c=t[1]*l;if(r.shapeInfo.isUniform)return`
      float ${n}(int row, int col, int depth,
                  int depth2, int depth3, int depth4) {
        int index = round(dot(
          vec4(row, col, depth, depth2),
          vec4(${c}, ${l}, ${u}, ${a})) +
          dot(
            vec2(depth3, depth4),
            vec2(${i}, 1)));
        ${Sd(r)}
      }
    `;let p=r.shapeInfo.flatOffset,m=r.shapeInfo.texShape,f=m[0],d=m[1];if(d===c&&p==null)return`
      float ${n}(int row, int col, int depth,
                    int depth2, int depth3, int depth4) {
        int texR = row;
        float texC = dot(vec4(col, depth, depth2, depth3),
          vec4(${l}, ${u}, ${a}, ${i})) +
               float(depth4);
        vec2 uv = (vec2(texC, texR) + halfCR) /
                   vec2(${d}.0, ${f}.0);
        return sampleTexture(${e}, uv);
      }
    `;if(d===i&&p==null)return`
      float ${n}(int row, int col, int depth,
                    int depth2, int depth3, int depth4) {
        float texR = dot(vec4(row, col, depth, depth2),
          vec4(${t[1]*t[2]*t[3]*t[4]},
               ${t[2]*t[3]*t[4]},
               ${t[3]*t[4]},
               ${t[4]})) + float(depth3);
        int texC = depth4;
        vec2 uv = (vec2(texC, texR) + halfCR) /
                  vec2(${d}.0, ${f}.0);
        return sampleTexture(${e}, uv);
      }
    `;let h=Hc(e);return`
    float ${n}(int row, int col, int depth,
                  int depth2, int depth3, int depth4) {
      // Explicitly use integer operations as dot() only works on floats.
      int index = row * ${c} + col * ${l} + depth * ${u} +
          depth2 * ${a} + depth3 * ${i} + depth4 + ${h};
      vec2 uv = uvFromFlat(${f}, ${d}, index);
      return sampleTexture(${e}, uv);
    }
  `}function Sd(r){let t=r.name,e=x.sizeFromShape(r.shapeInfo.logicalShape);return e<2?`return ${t};`:`
    for (int i = 0; i < ${e}; i++) {
      if (i == index) {
        return ${t}[i];
      }
    }
  `}function Dtt(r,t){let e=r.name,n=e.charAt(0).toUpperCase()+e.slice(1),o="get"+n+"AtOutCoords",s=r.shapeInfo.logicalShape.length,i=t.logicalShape.length,a=JL(r.shapeInfo.logicalShape,t.logicalShape),u=Wt(i),l=i-s,c,p=["x","y","z","w","u","v"];s===0?c="":i<2&&a.length>=1?c="coords = 0;":c=a.map(b=>`coords.${p[b+l]} = 0;`).join(`
`);let m="";i<2&&s>0?m="coords":m=r.shapeInfo.logicalShape.map((b,w)=>`coords.${p[w+l]}`).join(", ");let f="return outputValue;",h=x.sizeFromShape(r.shapeInfo.logicalShape)===1,y=x.sizeFromShape(t.logicalShape)===1;if(s===1&&!h&&!y)f=`
      return vec4(outputValue.xy, outputValue.xy);
    `;else if(h&&!y)i===1?f=`
        return vec4(outputValue.x, outputValue.x, 0., 0.);
      `:f=`
        return vec4(outputValue.x);
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    vec4 ${o}() {
      ${u} coords = getOutputCoords();
      ${c}
      vec4 outputValue = get${n}(${m});
      ${f}
    }
  `}function Ftt(r,t){let e=r.name,n=e.charAt(0).toUpperCase()+e.slice(1),o="get"+n+"AtOutCoords",s=t.texShape,i=r.shapeInfo.texShape,a=r.shapeInfo.logicalShape.length,u=t.logicalShape.length;if(!r.shapeInfo.isUniform&&a===u&&r.shapeInfo.flatOffset==null&&x.arraysEqual(i,s))return`
      float ${o}() {
        return sampleTexture(${e}, resultUV);
      }
    `;let l=Wt(u),c=JL(r.shapeInfo.logicalShape,t.logicalShape),p=u-a,m,f=["x","y","z","w","u","v"];a===0?m="":u<2&&c.length>=1?m="coords = 0;":m=c.map(h=>`coords.${f[h+p]} = 0;`).join(`
`);let d="";return u<2&&a>0?d="coords":d=r.shapeInfo.logicalShape.map((h,g)=>`coords.${f[g+p]}`).join(", "),`
    float ${o}() {
      ${l} coords = getOutputCoords();
      ${m}
      return get${n}(${d});
    }
  `}function Wt(r){if(r<=1)return"int";if(r===2)return"ivec2";if(r===3)return"ivec3";if(r===4)return"ivec4";if(r===5)return"ivec5";if(r===6)return"ivec6";throw Error(`GPU for rank ${r} is not yet supported`)}function $w(r,t,e){let{newShape:n,keptDims:o}=x.squeezeShape(t),s=t.length,i=r&&s===3&&t[0]===1,a=i?t.slice(1):n,u=!r&&s>1&&!x.arraysEqual(t,e)&&n.length<s||i;return{useSqueezeShape:u,uniformShape:u?a:t,keptDims:o}}function Nd(r,t){let e=JSON.parse(JSON.stringify(r));return e.shapeInfo.logicalShape=t,e}function kd(r,t){return t.map(e=>r[e]).join(", ")}function nP(r,t,e,n){let o=e.map((c,p)=>{let m={logicalShape:c.shape,texShape:c.isUniform?null:c.texData.texShape,isUniform:c.isUniform,isPacked:c.isUniform?!1:c.texData.isPacked,flatOffset:null};return c.texData!=null&&c.texData.slice!=null&&c.texData.slice.flatOffset>0&&(m.flatOffset=c.texData.slice.flatOffset),{name:t.variableNames[p],shapeInfo:m}}),s=o.map(c=>c.shapeInfo),i={logicalShape:n.shape,texShape:n.texData.texShape,isUniform:!1,isPacked:n.texData.isPacked,flatOffset:null},a=QL(o,i,t),u=Ek(r.gl,a),l=r.createProgram(u);return B().get("ENGINE_COMPILE_ONLY")?{program:t,fragmentShader:u,source:a,webGLProgram:l,inShapeInfos:s,outShapeInfo:i,uniformLocations:null,customUniformLocations:null,infLoc:null,nanLoc:null,inShapesLocations:null,inTexShapesLocations:null,outShapeLocation:null,outShapeStridesLocation:null,outTexShapeLocation:null}:Object.assign({program:t,fragmentShader:u,source:a,webGLProgram:l,inShapeInfos:s,outShapeInfo:i},Kk(r,t,l))}function Kk(r,t,e){let n={},o={},s={},i=[],a,u,l,c=null,p=null;p=r.getUniformLocation(e,"NAN",!1),B().getNumber("WEBGL_VERSION")===1&&(c=r.getUniformLocation(e,"INFINITY",!1));let m=!1;for(let f=0;f<t.variableNames.length;f++){let d=t.variableNames[f];n[d]=r.getUniformLocation(e,d,m),n[`offset${d}`]=r.getUniformLocation(e,`offset${d}`,m),t.enableShapeUniforms&&(o[`${d}Shape`]=r.getUniformLocation(e,`${d}Shape`,m),s[`${d}TexShape`]=r.getUniformLocation(e,`${d}TexShape`,m))}return t.enableShapeUniforms&&(a=r.getUniformLocation(e,"outShape",m),l=r.getUniformLocation(e,"outShapeStrides",m),u=r.getUniformLocation(e,"outTexShape",m)),t.customUniforms&&t.customUniforms.forEach((f,d)=>{i[d]=r.getUniformLocation(e,f.name,m)}),{uniformLocations:n,customUniformLocations:i,infLoc:c,nanLoc:p,inShapesLocations:o,inTexShapesLocations:s,outShapeLocation:a,outShapeStridesLocation:l,outTexShapeLocation:u}}function rP(r,t){if(r.length!==t.length)throw Error(`Binary was compiled with ${r.length} inputs, but was executed with ${t.length} inputs`);r.forEach((e,n)=>{let o=e.logicalShape,s=t[n],i=s.shape;if(!x.arraysEqual(o,i))throw Error(`Binary was compiled with different shapes than the current args. Shapes ${o} and ${i} must match`);if(e.isUniform&&s.isUniform)return;let a=e.texShape,u=s.isUniform?null:s.texData.texShape;if(!x.arraysEqual(a,u))throw Error(`Binary was compiled with different texture shapes than the current args. Shape ${a} and ${u} must match`)})}function oP(r,t,e,n,o){t.program.enableShapeUniforms||(rP(t.inShapeInfos,e),rP([t.outShapeInfo],[n]));let s=n.texData.texture,i=n.texData.texShape;n.texData.isPacked?r.setOutputPackedMatrixTexture(s.texture,i[0],i[1]):r.setOutputMatrixTexture(s.texture,i[0],i[1]),r.setProgram(t.webGLProgram),B().getNumber("WEBGL_VERSION")===1&&t.infLoc!==null&&r.gl.uniform1f(t.infLoc,1/0),t.nanLoc!==null&&r.gl.uniform1f(t.nanLoc,NaN),e.forEach((u,l)=>{let c=t.program.variableNames[l],p=t.uniformLocations[c],m=t.uniformLocations[`offset${c}`],f=t.inShapesLocations[`${c}Shape`],d=t.inTexShapesLocations[`${c}TexShape`];if(f){let{uniformShape:h}=$w(t.program.packedInputs,u.shape,u.texData.texShape);switch(h.length){case 1:r.gl.uniform1iv(f,new Int32Array(h));break;case 2:r.gl.uniform2iv(f,new Int32Array(h));break;case 3:r.gl.uniform3iv(f,new Int32Array(h));break;case 4:r.gl.uniform4iv(f,new Int32Array(h));break;default:break}}if(d&&r.gl.uniform2i(d,u.texData.texShape[0],u.texData.texShape[1]),p!=null){if(u.isUniform){if(x.sizeFromShape(u.shape)<2)r.gl.uniform1f(p,u.uniformValues[0]);else{let h=u.uniformValues;h instanceof Float32Array||(h=new Float32Array(h)),r.gl.uniform1fv(p,h)}return}u.texData.slice!=null&&m!=null&&r.gl.uniform1i(m,u.texData.slice.flatOffset),r.setInputMatrixTexture(u.texData.texture.texture,p,l)}});let a=t.outShapeLocation;if(a)switch(n.shape.length){case 1:r.gl.uniform1iv(a,new Int32Array(n.shape));break;case 2:r.gl.uniform2iv(a,new Int32Array(n.shape));break;case 3:r.gl.uniform3iv(a,new Int32Array(n.shape));break;case 4:r.gl.uniform4iv(a,new Int32Array(n.shape));break;default:break}if(t.outShapeStridesLocation){let u=x.computeStrides(n.shape);switch(n.shape.length){case 2:r.gl.uniform1iv(t.outShapeStridesLocation,new Int32Array(u));break;case 3:r.gl.uniform2iv(t.outShapeStridesLocation,new Int32Array(u));break;case 4:r.gl.uniform3iv(t.outShapeStridesLocation,new Int32Array(u));break;default:break}}t.outTexShapeLocation&&r.gl.uniform2i(t.outTexShapeLocation,n.texData.texShape[0],n.texData.texShape[1]),t.program.customUniforms&&o&&t.program.customUniforms.forEach((u,l)=>{let c=t.customUniformLocations[l],p=o[l];if(u.type==="float")r.gl.uniform1fv(c,p);else if(u.type==="vec2")r.gl.uniform2fv(c,p);else if(u.type==="vec3")r.gl.uniform3fv(c,p);else if(u.type==="vec4")r.gl.uniform4fv(c,p);else if(u.type==="int")r.gl.uniform1iv(c,p);else if(u.type==="ivec2")r.gl.uniform2iv(c,p);else if(u.type==="ivec3")r.gl.uniform3iv(c,p);else if(u.type==="ivec4")r.gl.uniform4iv(c,p);else throw Error(`uniform type ${u.type} is not supported yet.`)}),r.executeProgram()}function sP(r,t,e){let n="";t.concat(e).forEach(i=>{let a=i.texData!=null&&i.texData.slice!=null&&i.texData.slice.flatOffset>0;if(r.enableShapeUniforms&&!i.isUniform){let u=i.texData.texShape,{useSqueezeShape:l,uniformShape:c,keptDims:p}=$w(r.packedInputs,i.shape,u),m="",f="",d="";if(c.length===1&&r.packedInputs){let N=[Math.ceil(u[0]/2),Math.ceil(u[1]/2)];m=`${N[0]>1}_${N[1]>1}`}else if(c.length===2&&!r.packedInputs)f=`${c[0]>1}_${c[1]>1}`;else if(c.length>2&&!r.packedInputs){let N=x.computeStrides(c);d=`${N[0]===u[1]}_${N[N.length-1]===u[1]}`}let h=i.shape.length,g=c.length===2&&x.arraysEqual(i.shape,u),y=x.sizeFromShape(i.shape)===1,b=S.getBroadcastDims(i.shape,e.shape),w=!r.packedInputs&&h===e.shape.length&&x.arraysEqual(u,e.texData.texShape),v=r.packedInputs||c.length>2?"":`${u[0]>1}_${u[1]>1}`;n+=`${h}_${w}_${l?p:""}_${c.length}_${y}_${b}_${g}_${m}_${f}_${d}_${v}_${a}`}else{let u=i.isUniform?"uniform":i.texData.texShape;n+=`${i.shape}_${u}_${a}`}});let o=r.userCode,s=r.constructor.name;return s+="_"+n+"_"+o+`${B().getNumber("WEBGL_VERSION")}`,s}function De(r){return B().getBool("WEBGL_USE_SHAPES_UNIFORMS")&&r<=4}var Dw=class{constructor(t){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outPackingScheme=Su.DENSE,this.customUniforms=[{name:"texShape",type:"ivec2"}];let e=He();this.outputShape=t,this.enableShapeUniforms=De(this.outputShape.length),this.userCode=`
      ivec3 outCoordsFromFlatIndex(int index) {
        ${this.enableShapeUniforms?Uc(["r","c","d"],t):oi(["r","c","d"],t)}
        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);
        }

        ${e.output} = result;
      }
    `}};var Fw=class{constructor(t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outPackingScheme=Su.DENSE,this.customUniforms=[{name:"texShape",type:"ivec2"}];let e=He();this.outputShape=t,this.enableShapeUniforms=De(this.outputShape.length),this.userCode=`
      ivec3 outCoordsFromFlatIndex(int index) {
        ${this.enableShapeUniforms?Uc(["r","c","d"],t):oi(["r","c","d"],t)}
        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));
        }

        ${e.output} = result;
      }
    `}};var Rw=class{constructor(t){this.variableNames=["A"],this.outTexUsage=Hr.DOWNLOAD;let e=He();this.outputShape=t,this.userCode=`
      ${Aw}

      void main() {
        float x = getAAtOutCoords();
        ${e.output} = encode_float(x);
      }
    `}};var Ow=class{constructor(t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outTexUsage=Hr.DOWNLOAD;let e=He();this.outputShape=t,this.userCode=`
      ${Aw}

      void main() {
        ivec3 coords = getOutputCoords();
        float x = getChannel(getAAtOutCoords(), vec2(coords.y, coords.z));
        ${e.output} = encode_float(x);
      }
    `}};var Lw=class{constructor(t,e=!1){this.variableNames=["A"],this.customUniforms=[{name:"texShape",type:"ivec2"}];let n=He();this.outputShape=t,this.enableShapeUniforms=De(this.outputShape.length);let o="result";e&&(o="floor(result * 255. + 0.5)"),this.userCode=`
      ${this.enableShapeUniforms?vd():wd(t)}

      void main() {
        ivec3 coords = getOutputCoords();

        int flatIndex = getFlatIndex(coords);
        int offset = imod(flatIndex, 4);

        flatIndex = idiv(flatIndex, 4, 1.);

        int r = flatIndex / texShape[1];
        int c = imod(flatIndex, texShape[1]);
        vec2 uv = (vec2(c, r) + halfCR) / vec2(texShape[1], texShape[0]);
        vec4 values = ${n.texture2D}(A, uv);

        float result;

        if(offset == 0) {
          result = values[0];
        } else if(offset == 1) {
          result = values[1];
        } else if(offset == 2) {
          result = values[2];
        } else {
          result = values[3];
        }

        ${n.output} = vec4(${o}, 0., 0., 0.);
      }
    `}};var Pw=class{constructor(t,e=!1){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.customUniforms=[{name:"texShape",type:"ivec2"}];let n=He();this.outputShape=t,this.enableShapeUniforms=De(this.outputShape.length);let o="",s="result";e&&(s="floor(result * 255. + 0.5)");for(let i=0;i<=1;i++)for(let a=0;a<=1;a++){let u=i*2+a;o+=`
          localCoords = coords;
          if(localCoords[2] + ${a} < ${this.enableShapeUniforms?"outShape[2]":`${t[2]}`}) {
          localCoords[2] += ${a};
          if (localCoords[1] + ${i} < ${this.enableShapeUniforms?"outShape[1]":`${t[1]}`}) {
            localCoords[1] += ${i};

            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[${u}] = values[0];
            } else if (offset == 1) {
              result[${u}] = values[1];
            } else if (offset == 2) {
              result[${u}] = values[2];
            } else {
              result[${u}] = values[3];
            }
          }
        }
        `}this.userCode=`
        ${this.enableShapeUniforms?vd():wd(t)}

        void main() {
          ivec3 coords = getOutputCoords();

          vec4 result = vec4(0.);
          int flatIndex, r, c, offset;
          ivec3 localCoords;
          vec2 uv;
          vec4 values;

          ${o}

          ${n.output} = ${s};
        }
    `}};var cT={};jt(cT,{bindVertexProgramAttributeStreams:()=>rT,createBufferFromOutputTexture:()=>sT,createFloat16MatrixTexture:()=>Jk,createFloat16PackedMatrixTexture:()=>eT,createFloat32MatrixTexture:()=>Zk,createIndexBuffer:()=>Yk,createPackedMatrixTexture:()=>tT,createUnsignedBytesMatrixTexture:()=>Qk,createVertexBuffer:()=>Xk,createVertexShader:()=>jk,downloadByteEncodedFloatMatrixFromOutputTexture:()=>aT,downloadFloat32MatrixFromBuffer:()=>iT,downloadMatrixFromPackedOutputTexture:()=>uT,downloadPackedMatrixFromBuffer:()=>lT,getInternalFormatForFloat16MatrixTexture:()=>zw,getInternalFormatForFloat16PackedMatrixTexture:()=>Gw,getInternalFormatForFloat32MatrixTexture:()=>Mw,getInternalFormatForPackedMatrixTexture:()=>Vw,getInternalFormatForUnsignedBytesMatrixTexture:()=>Bw,uploadDenseMatrixToTexture:()=>nT,uploadPixelDataToTexture:()=>oT});function jk(r){let t=He(),e=`${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 _k(r,e)}function Xk(r){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 Dk(r,t)}function Yk(r){let t=new Uint16Array([0,1,2,2,1,3]);return Fk(r,t)}function ng(r,t,e,n,o,s){Ok(t,e);let i=Rk(r),a=r.TEXTURE_2D;return vt(r,()=>r.bindTexture(a,i)),vt(r,()=>r.texParameteri(a,r.TEXTURE_WRAP_S,r.CLAMP_TO_EDGE)),vt(r,()=>r.texParameteri(a,r.TEXTURE_WRAP_T,r.CLAMP_TO_EDGE)),vt(r,()=>r.texParameteri(a,r.TEXTURE_MIN_FILTER,r.NEAREST)),vt(r,()=>r.texParameteri(a,r.TEXTURE_MAG_FILTER,r.NEAREST)),B().getNumber("WEBGL_VERSION")===1?vt(r,()=>r.texImage2D(a,0,n,t,e,0,o,s,null)):vt(r,()=>r.texStorage2D(a,1,n,t,e)),vt(r,()=>r.bindTexture(r.TEXTURE_2D,null)),{texture:i,texShape:[e,t]}}function Mw(r){return r.internalFormatFloat}function Zk(r,t,e,n){let[o,s]=Wc(t,e);return ng(r,o,s,Mw(n),n.textureFormatFloat,r.FLOAT)}function zw(r){return r.internalFormatHalfFloat}function Jk(r,t,e,n){let[o,s]=Wc(t,e);return ng(r,o,s,zw(n),n.textureFormatFloat,n.textureTypeHalfFloat)}function Bw(r){return r.downloadTextureFormat}function Qk(r,t,e,n){let[o,s]=Wc(t,e);return ng(r,o,s,Bw(n),r.RGBA,r.UNSIGNED_BYTE)}function Vw(r){return r.internalFormatPackedFloat}function tT(r,t,e,n){let[o,s]=Ji(t,e);return ng(r,o,s,Vw(n),r.RGBA,r.FLOAT)}function Gw(r){return r.internalFormatPackedHalfFloat}function eT(r,t,e,n){let[o,s]=Ji(t,e);return ng(r,o,s,Gw(n),r.RGBA,n.textureTypeHalfFloat)}function rT(r,t,e){return vt(r,()=>r.bindBuffer(r.ARRAY_BUFFER,e)),Tw(r,t,"clipSpacePos",e,3,20,0)&&Tw(r,t,"uv",e,2,20,12)}function nT(r,t,e,n,o,s){vt(r,()=>r.bindTexture(r.TEXTURE_2D,t));let i,a,u;o instanceof Uint8Array?(i=new Uint8Array(e*n*4),a=r.UNSIGNED_BYTE,u=r.RGBA):(i=new Float32Array(e*n*4),a=r.FLOAT,u=s.internalFormatPackedFloat),i.set(o),B().getNumber("WEBGL_VERSION")===2?vt(r,()=>r.texSubImage2D(r.TEXTURE_2D,0,0,0,e,n,r.RGBA,a,i)):vt(r,()=>r.texImage2D(r.TEXTURE_2D,0,u,e,n,0,r.RGBA,a,i)),vt(r,()=>r.bindTexture(r.TEXTURE_2D,null))}function oT(r,t,e){vt(r,()=>r.bindTexture(r.TEXTURE_2D,t)),e.data instanceof Uint8Array?B().getNumber("WEBGL_VERSION")===2?vt(r,()=>r.texSubImage2D(r.TEXTURE_2D,0,0,0,e.width,e.height,r.RGBA,r.UNSIGNED_BYTE,e.data)):vt(r,()=>r.texImage2D(r.TEXTURE_2D,0,r.RGBA,e.width,e.height,0,r.RGBA,r.UNSIGNED_BYTE,e.data)):B().getNumber("WEBGL_VERSION")===2?vt(r,()=>r.texSubImage2D(r.TEXTURE_2D,0,0,0,r.RGBA,r.UNSIGNED_BYTE,e)):vt(r,()=>r.texImage2D(r.TEXTURE_2D,0,r.RGBA,r.RGBA,r.UNSIGNED_BYTE,e)),vt(r,()=>r.bindTexture(r.TEXTURE_2D,null))}function sT(r,t,e,n){let o=r.createBuffer();vt(r,()=>r.bindBuffer(r.PIXEL_PACK_BUFFER,o));let a=4*4*t*e;return vt(r,()=>r.bufferData(r.PIXEL_PACK_BUFFER,a,r.STREAM_READ)),vt(r,()=>r.readPixels(0,0,e,t,r.RGBA,r.FLOAT,0)),vt(r,()=>r.bindBuffer(r.PIXEL_PACK_BUFFER,null)),o}function iT(r,t,e){let n=r,o=new Float32Array(e);return n.bindBuffer(n.PIXEL_PACK_BUFFER,t),n.getBufferSubData(n.PIXEL_PACK_BUFFER,0,o),n.bindBuffer(n.PIXEL_PACK_BUFFER,null),o}function aT(r,t,e,n){let[o,s]=Wc(t,e),i=4,a=new Uint8Array(HL(t*e,i));return vt(r,()=>r.readPixels(0,0,o,s,n.downloadTextureFormat,r.UNSIGNED_BYTE,a)),new Float32Array(a.buffer)}function lT(r,t,e,n,o,s,i,a){let u=r,l=new Float32Array(qL(s,i));return u.bindBuffer(u.PIXEL_PACK_BUFFER,t),u.getBufferSubData(u.PIXEL_PACK_BUFFER,0,l),u.bindBuffer(u.PIXEL_PACK_BUFFER,null),l}function uT(r,t,e){let n=new Float32Array(t*e*4);return vt(r,()=>r.readPixels(0,0,e,t,r.RGBA,r.FLOAT,n)),n}var qc=class{constructor(t){this.outputTexture=null,this.program=null,this.disposed=!1,this.vertexAttrsAreBound=!1,this.itemsToPoll=[];let e=B().getNumber("WEBGL_VERSION");t!=null?(this.gl=t,Sk(e,t)):this.gl=Gn(e);let n="WEBGL_color_buffer_float",o="EXT_color_buffer_half_float";if(this.parallelCompilationExtension=this.gl.getExtension("KHR_parallel_shader_compile"),B().getNumber("WEBGL_VERSION")===1){let s="OES_texture_float",i="OES_texture_half_float";if(this.textureFloatExtension=xd(this.gl,s),Wn(this.gl,i))this.textureHalfFloatExtension=xd(this.gl,i);else if(B().get("WEBGL_FORCE_F16_TEXTURES"))throw new Error("GL context does not support half float textures, yet the environment flag WEBGL_FORCE_F16_TEXTURES is set to true.");if(this.colorBufferFloatExtension=this.gl.getExtension(n),Wn(this.gl,o))this.colorBufferHalfFloatExtension=xd(this.gl,o);else if(B().get("WEBGL_FORCE_F16_TEXTURES"))throw new Error("GL context does not support color renderable half floats, yet the environment flag WEBGL_FORCE_F16_TEXTURES is set to true.")}else if(n="EXT_color_buffer_float",Wn(this.gl,n))this.colorBufferFloatExtension=this.gl.getExtension(n);else if(Wn(this.gl,o))this.colorBufferHalfFloatExtension=this.gl.getExtension(o);else throw new Error("GL context does not support color renderable floats");this.vertexBuffer=Xk(this.gl),this.indexBuffer=Yk(this.gl),this.framebuffer=Lk(this.gl),this.textureConfig=Qh(this.gl,this.textureHalfFloatExtension)}get debug(){return B().getBool("DEBUG")}dispose(){if(this.disposed)return;this.program!=null&&console.warn("Disposing a GPGPUContext that still has a bound WebGLProgram. This is probably a resource leak, delete the program with GPGPUContext.deleteProgram before disposing."),this.outputTexture!=null&&console.warn("Disposing a GPGPUContext that still has a bound output matrix texture.  This is probably a resource leak, delete the output matrix texture with GPGPUContext.deleteMatrixTexture before disposing.");let t=this.gl;vt(t,()=>t.finish()),vt(t,()=>t.bindFramebuffer(t.FRAMEBUFFER,null)),vt(t,()=>t.deleteFramebuffer(this.framebuffer)),vt(t,()=>t.bindBuffer(t.ARRAY_BUFFER,null)),vt(t,()=>t.bindBuffer(t.ELEMENT_ARRAY_BUFFER,null)),vt(t,()=>t.deleteBuffer(this.indexBuffer)),this.disposed=!0}createFloat32MatrixTexture(t,e){return this.throwIfDisposed(),Zk(this.gl,t,e,this.textureConfig)}createFloat16MatrixTexture(t,e){return this.throwIfDisposed(),Jk(this.gl,t,e,this.textureConfig)}createUnsignedBytesMatrixTexture(t,e){return this.throwIfDisposed(),Qk(this.gl,t,e,this.textureConfig)}uploadPixelDataToTexture(t,e){this.throwIfDisposed(),oT(this.gl,t,e)}uploadDenseMatrixToTexture(t,e,n,o){this.throwIfDisposed(),nT(this.gl,t,e,n,o,this.textureConfig)}createFloat16PackedMatrixTexture(t,e){return this.throwIfDisposed(),eT(this.gl,t,e,this.textureConfig)}createPackedMatrixTexture(t,e){return this.throwIfDisposed(),tT(this.gl,t,e,this.textureConfig)}deleteMatrixTexture(t){this.throwIfDisposed(),this.outputTexture===t&&(_w(this.gl,this.framebuffer),this.outputTexture=null),vt(this.gl,()=>this.gl.deleteTexture(t))}downloadByteEncodedFloatMatrixFromOutputTexture(t,e,n){return this.downloadMatrixDriver(t,()=>aT(this.gl,e,n,this.textureConfig))}downloadPackedMatrixFromBuffer(t,e,n,o,s,i){return lT(this.gl,t,e,n,o,s,i,this.textureConfig)}downloadFloat32MatrixFromBuffer(t,e){return iT(this.gl,t,e)}createBufferFromTexture(t,e,n){this.bindTextureToFrameBuffer(t);let o=sT(this.gl,e,n,this.textureConfig);return this.unbindTextureToFrameBuffer(),o}createAndWaitForFence(){let t=this.createFence(this.gl);return this.pollFence(t)}createFence(t){let e,n;if(B().getBool("WEBGL_FENCE_API_ENABLED")){let o=t,s=o.fenceSync(o.SYNC_GPU_COMMANDS_COMPLETE,0);t.flush(),n=()=>{let i=o.clientWaitSync(s,0,0);return i===o.ALREADY_SIGNALED||i===o.CONDITION_SATISFIED},e=s}else B().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")>0?(e=this.beginQuery(),this.endQuery(),n=()=>this.isQueryAvailable(e,B().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))):n=()=>!0;return{query:e,isFencePassed:n}}downloadMatrixFromPackedTexture(t,e,n){return this.downloadMatrixDriver(t,()=>uT(this.gl,e,n))}createProgram(t){this.throwIfDisposed();let e=this.gl;this.vertexShader==null&&(this.vertexShader=jk(e));let n=Ak(e);return vt(e,()=>e.attachShader(n,this.vertexShader)),vt(e,()=>e.attachShader(n,t)),$k(e,n),this.debug&&tg(e,n),this.vertexAttrsAreBound||(this.setProgram(n),this.vertexAttrsAreBound=rT(e,this.program,this.vertexBuffer)),n}deleteProgram(t){this.throwIfDisposed(),t===this.program&&(this.program=null),t!=null&&vt(this.gl,()=>this.gl.deleteProgram(t))}setProgram(t){this.throwIfDisposed(),this.program=t,this.program!=null&&this.debug&&tg(this.gl,this.program),vt(this.gl,()=>this.gl.useProgram(t))}getUniformLocation(t,e,n=!0){return this.throwIfDisposed(),n?Pk(this.gl,t,e):Mk(this.gl,t,e)}getAttributeLocation(t,e){return this.throwIfDisposed(),vt(this.gl,()=>this.gl.getAttribLocation(t,e))}getUniformLocationNoThrow(t,e){return this.throwIfDisposed(),this.gl.getUniformLocation(t,e)}setInputMatrixTexture(t,e,n){this.throwIfDisposed(),this.throwIfNoProgram(),zk(this.gl,t,e,n)}setOutputMatrixTexture(t,e,n){this.setOutputMatrixTextureDriver(t,n,e)}setOutputPackedMatrixTexture(t,e,n){this.throwIfDisposed();let[o,s]=Ji(e,n);this.setOutputMatrixTextureDriver(t,o,s)}setOutputMatrixWriteRegion(t,e,n,o){this.setOutputMatrixWriteRegionDriver(n,t,o,e)}setOutputPackedMatrixWriteRegion(t,e,n,o){throw new Error("setOutputPackedMatrixWriteRegion not implemented.")}debugValidate(){this.program!=null&&tg(this.gl,this.program),yd(this.gl)}executeProgram(){this.throwIfDisposed(),this.throwIfNoProgram();let t=this.gl;this.debug&&this.debugValidate(),vt(t,()=>t.drawElements(t.TRIANGLES,6,t.UNSIGNED_SHORT,0))}blockUntilAllProgramsCompleted(){this.throwIfDisposed(),vt(this.gl,()=>this.gl.finish())}getQueryTimerExtension(){return this.disjointQueryTimerExtension==null&&(this.disjointQueryTimerExtension=xd(this.gl,B().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")===2?"EXT_disjoint_timer_query_webgl2":"EXT_disjoint_timer_query")),this.disjointQueryTimerExtension}getQueryTimerExtensionWebGL2(){return this.getQueryTimerExtension()}getQueryTimerExtensionWebGL1(){return this.getQueryTimerExtension()}beginQuery(){if(B().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")===2){let n=this.gl,o=this.getQueryTimerExtensionWebGL2(),s=n.createQuery();return n.beginQuery(o.TIME_ELAPSED_EXT,s),s}let t=this.getQueryTimerExtensionWebGL1(),e=t.createQueryEXT();return t.beginQueryEXT(t.TIME_ELAPSED_EXT,e),e}endQuery(){if(B().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")===2){let e=this.gl,n=this.getQueryTimerExtensionWebGL2();e.endQuery(n.TIME_ELAPSED_EXT);return}let t=this.getQueryTimerExtensionWebGL1();t.endQueryEXT(t.TIME_ELAPSED_EXT)}async waitForQueryAndGetTime(t){return await x.repeatedTry(()=>this.disposed||this.isQueryAvailable(t,B().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))),this.getQueryTime(t,B().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))}getQueryTime(t,e){if(e===0)return null;if(e===2){let n=this.gl;return n.getQueryParameter(t,n.QUERY_RESULT)/1e6}else{let n=this.getQueryTimerExtensionWebGL1();return n.getQueryObjectEXT(t,n.QUERY_RESULT_EXT)/1e6}}isQueryAvailable(t,e){if(e===0)return!0;if(e===2){let n=this.gl,o=this.getQueryTimerExtensionWebGL2(),s=n.getQueryParameter(t,n.QUERY_RESULT_AVAILABLE);return this.disjoint==null&&(this.disjoint=this.gl.getParameter(o.GPU_DISJOINT_EXT)),s&&!this.disjoint}else{let n=this.getQueryTimerExtensionWebGL1(),o=n.getQueryObjectEXT(t,n.QUERY_RESULT_AVAILABLE_EXT);return this.disjoint==null&&(this.disjoint=this.gl.getParameter(n.GPU_DISJOINT_EXT)),o&&!this.disjoint}}pollFence(t){return new Promise(e=>{this.addItemToPoll(()=>t.isFencePassed(),()=>e())})}pollItems(){let t=Ltt(this.itemsToPoll.map(e=>e.isDoneFn));for(let e=0;e<=t;++e){let{resolveFn:n}=this.itemsToPoll[e];n()}this.itemsToPoll=this.itemsToPoll.slice(t+1)}addItemToPoll(t,e){this.itemsToPoll.push({isDoneFn:t,resolveFn:e}),!(this.itemsToPoll.length>1)&&x.repeatedTry(()=>(this.pollItems(),this.itemsToPoll.length===0))}bindTextureToFrameBuffer(t){this.throwIfDisposed(),eg(this.gl,t,this.framebuffer),this.debug&&yd(this.gl)}unbindTextureToFrameBuffer(){this.outputTexture!=null?(eg(this.gl,this.outputTexture,this.framebuffer),this.debug&&yd(this.gl)):_w(this.gl,this.framebuffer)}downloadMatrixDriver(t,e){this.bindTextureToFrameBuffer(t);let n=e();return this.unbindTextureToFrameBuffer(),n}setOutputMatrixTextureDriver(t,e,n){this.throwIfDisposed();let o=this.gl;eg(o,t,this.framebuffer),this.debug&&yd(o),this.outputTexture=t,vt(o,()=>o.viewport(0,0,e,n)),vt(o,()=>o.scissor(0,0,e,n))}setOutputMatrixWriteRegionDriver(t,e,n,o){this.throwIfDisposed(),vt(this.gl,()=>this.gl.scissor(t,e,n,o))}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 Ltt(r){let t=0;for(;t<r.length&&r[t]();++t);return t-1}var{addImpl:iP,bincountImpl:Ww,bincountReduceImpl:aP,ceilImpl:lP,concatImpl:uP,equalImpl:cP,expImpl:pP,expm1Impl:mP,floorImpl:fP,gatherNdImpl:dP,gatherV2Impl:hP,greaterImpl:gP,greaterEqualImpl:xP,lessImpl:yP,lessEqualImpl:bP,linSpaceImpl:wP,logImpl:vP,maxImpl:CP,maximumImpl:IP,minimumImpl:SP,multiplyImpl:NP,negImpl:kP,notEqualImpl:TP,prodImpl:_P,rangeImpl:EP,rsqrtImpl:AP,scatterImpl:$P,sigmoidImpl:DP,simpleAbsImpl:Uw,sliceImpl:FP,sparseFillEmptyRowsImpl:RP,sparseReshapeImpl:OP,sparseSegmentReductionImpl:Hw,sqrtImpl:LP,stridedSliceImpl:PP,stringNGramsImpl:MP,stringSplitImpl:zP,stringToHashBucketFastImpl:BP,subImpl:VP,tileImpl:GP,topKImpl:WP,transposeImpl:Kc,uniqueImpl:UP}=yw;function pT(r,t){return["x","y","z","w","u","v"].slice(0,t).map(e=>`${r}.${e}`)}function tr(r,t){return t===1?[r]:pT(r,t)}function HP(r,t){if(r===1)return"rc";let e="";for(let n=0;n<r;n++)e+=t[n],n<r-1&&(e+=",");return e}var qw=class{constructor(t){if(this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outputShape=t,this.rank=t.length,this.enableShapeUniforms=De(this.outputShape.length),this.rank===0)this.userCode=`
        void main() {
          setOutput(vec4(getA(), 0., 0., 0.));
        }
      `;else{let e=tr("rc",this.rank),n=Wt(this.rank),o=this.getOutOfBoundsCondition(e),s=this.getSetup(e),i=this.getOutput(e);this.userCode=`
        void main() {
          ${n} rc = getOutputCoords();

          if(${o}) {
            setOutput(vec4(0));
          } else {
            ${s}

            setOutput(vec4(${i}));
          }
        }
      `}}getSourceCoordsArr(t){let e=[];for(let n=0;n<=1;n++)for(let o=0;o<=1;o++){let s=`${n===0?"r":"rp1"}, ${o===0?"c":"cp1"}`;for(let i=2;i<this.rank;i++)s=`${t[t.length-1-i]},`+s;e.push(s)}return e}getOutOfBoundsCondition(t){if(this.rank===1)return`rc > ${this.enableShapeUniforms?"outShape":this.outputShape[0]}`;let e="";for(let n=this.rank-2;n<this.rank;n++)e+=`${t[n]} >= ${this.enableShapeUniforms?`outShape[${n}]`:this.outputShape[n]}`,n<this.rank-1&&(e+="||");return e}getSetup(t){if(this.rank===1)return"";let e=t.slice(-2),n=this.enableShapeUniforms?`outShape[${this.rank} - 1]`:this.outputShape[this.rank-1],o=this.enableShapeUniforms?`outShape[${this.rank} - 2]`:this.outputShape[this.rank-2];return`
      int r = ${e[0]};
      int c = ${e[1]};
      int rp1 = r + 1;
      int cp1 = c + 1;

      bool cEdge = cp1 >= ${n};
      bool rEdge = rp1 >= ${o};
    `}getOutput(t){let e=this.getSourceCoordsArr(t);return this.rank===1?`getA(rc), (rc + 1 >= ${this.enableShapeUniforms?"outShape":this.outputShape[0]} ? 0. : getA(rc + 1)), 0, 0`:`getA(${e[0]}),
            cEdge ? 0. : getA(${e[1]}),
            rEdge ? 0. : getA(${e[2]}),
            rEdge || cEdge ? 0. : getA(${e[3]})`}};var Td=class{constructor(t,e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"inputShape",type:"ivec3"}],this.outputShape=t,this.enableShapeUniforms=De(this.outputShape.length);let n="";for(let o=0;o<4;o++){let s="thisRC = rc;";o%2===1&&(s+="thisRC.z += 1;"),o>1&&(s+="thisRC.y += 1;"),n+=`
        ${s}
        ${o>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[${o}] =
            getChannel(getA(inputRC.x, inputRC.y, inputRC.z), inputRCInnerDims);
        ${o>0?"}":""}
      `}this.userCode=`
      ${Ptt(e,this.enableShapeUniforms)}
      ${this.enableShapeUniforms?vd():wd(t)}

      void main() {
        ivec3 rc = getOutputCoords();

        vec4 result = vec4(0.);

        ivec3 thisRC;
        int rows = ${this.enableShapeUniforms?"outShape[1]":t[1]};
        int cols = ${this.enableShapeUniforms?"outShape[2]":t[2]};

        ${n}

        setOutput(result);
      }
    `}};function Ptt(r,t){return`
    ivec3 inputCoordsFromReshapedOutCoords(int index) {
      ${t?ZL(["r","c","d"],"inputShape"):oi(["r","c","d"],r)}
      return ivec3(r, c, d);
    }
  `}var Kw=class{constructor(t){this.gpgpu=t,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0,this.freeTextures={},this.logEnabled=!1,this.usedTextures={}}acquireTexture(t,e,n){let o=KP(e,n),s=jP(t,o,n);s in this.freeTextures||(this.freeTextures[s]=[]),s in this.usedTextures||(this.usedTextures[s]=[]);let i=qP(t,o,this.gpgpu.gl,this.gpgpu.textureConfig,n);if(this.freeTextures[s].length>0){this.numFreeTextures--,this.numUsedTextures++,this._numBytesFree-=i,this.log();let u=this.freeTextures[s].shift();return this.usedTextures[s].push(u),u}let a;return o===Rr.PACKED_2X2_FLOAT32?a=this.gpgpu.createPackedMatrixTexture(t[0],t[1]):o===Rr.PACKED_2X2_FLOAT16?a=this.gpgpu.createFloat16PackedMatrixTexture(t[0],t[1]):o===Rr.UNPACKED_FLOAT32?a=this.gpgpu.createFloat32MatrixTexture(t[0],t[1]):o===Rr.UNPACKED_FLOAT16?a=this.gpgpu.createFloat16MatrixTexture(t[0],t[1]):o===Rr.PACKED_4X1_UNSIGNED_BYTE&&(a=this.gpgpu.createUnsignedBytesMatrixTexture(t[0],t[1])),this.usedTextures[s].push(a),this.numUsedTextures++,this._numBytesAllocated+=i,this.log(),a}releaseTexture(t,e,n,o){if(this.freeTextures==null)return;let s=KP(n,o),i=jP(e,s,o);i in this.freeTextures||(this.freeTextures[i]=[]);let a=qP(e,s,this.gpgpu.gl,this.gpgpu.textureConfig,o),u=B().get("WEBGL_DELETE_TEXTURE_THRESHOLD");u!==-1&&this._numBytesAllocated>u?(this.gpgpu.deleteMatrixTexture(t.texture),this._numBytesAllocated-=a):(this.freeTextures[i].push(t),this.numFreeTextures++,this._numBytesFree+=a),this.numUsedTextures--;let l=this.usedTextures[i],c=l.indexOf(t);if(c<0)throw new Error("Cannot release a texture that was never provided by this texture manager");l.splice(c,1),this.log()}log(){if(!this.logEnabled)return;let t=this.numFreeTextures+this.numUsedTextures;console.log("Free/Used",`${this.numFreeTextures} / ${this.numUsedTextures}`,`(${t})`);let e=this._numBytesFree/this._numBytesAllocated;console.log(`Bytes allocated: ${this._numBytesAllocated}`),console.log(`Bytes unused: ${this._numBytesFree} (${Math.round(100*e)}%)`)}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 t in this.freeTextures)this.freeTextures[t].forEach(e=>{this.gpgpu.deleteMatrixTexture(e.texture)});for(let t in this.usedTextures)this.usedTextures[t].forEach(e=>{this.gpgpu.deleteMatrixTexture(e.texture)});this.freeTextures=null,this.usedTextures=null,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0}}};function Mtt(r,t){let e=r;if(t===e.R32F)return 4;if(t===e.R16F)return 2;if(t===e.RGBA32F)return 16;if(t===r.RGBA)return 16;if(t===e.RGBA16F)return 8;if(t===e.RGBA8)return 4;throw new Error(`Unknown internal format ${t}`)}function qP(r,t,e,n,o){let s=ztt(t,n),i;if(o){let[u,l]=Ji(r[0],r[1]);i=u*l}else{let[u,l]=Wc(r[0],r[1]);i=u*l}let a=Mtt(e,s);return i*a}function ztt(r,t){switch(r){case Rr.PACKED_2X2_FLOAT32:return Vw(t);case Rr.PACKED_2X2_FLOAT16:return Gw(t);case Rr.UNPACKED_FLOAT32:return Mw(t);case Rr.UNPACKED_FLOAT16:return zw(t);case Rr.PACKED_4X1_UNSIGNED_BYTE:return Bw(t);default:throw new Error(`Unknown physical texture type ${r}`)}}function Btt(r){return B().getBool("WEBGL_RENDER_FLOAT32_ENABLED")?r?Rr.PACKED_2X2_FLOAT32:Rr.UNPACKED_FLOAT32:r?Rr.PACKED_2X2_FLOAT16:Rr.UNPACKED_FLOAT16}function KP(r,t){if(r===Hr.UPLOAD)return Rr.PACKED_2X2_FLOAT32;if(r===Hr.RENDER||r==null)return Btt(t);if(r===Hr.DOWNLOAD||r===Hr.PIXELS)return Rr.PACKED_4X1_UNSIGNED_BYTE;throw new Error(`Unknown logical texture type ${r}`)}function jP(r,t,e){return`${r[0]}_${r[1]}_${t}_${e}`}var Zr=class{constructor(t,e){this.variableNames=["A"],this.outputShape=t,this.enableShapeUniforms=De(this.outputShape.length),this.userCode=`
      float unaryOperation(float x) {
        ${e}
      }

      void main() {
        float x = getAAtOutCoords();
        float y = unaryOperation(x);

        setOutput(y);
      }
    `}},fr="if (isnan(x)) return x;",XP="return x;",mT="return abs(x);";var YP="return (x >= 0.0) ? x : (exp(x) - 1.0);",ZP=fr+`
  return (x < 0.0) ? 0.0 : x;
`,JP=fr+`
  return (x < 0.0) ? 0.0 : min(6.0, x);
`,jc="return x;",QP="return 1.0 / (1.0 + exp(-1.0 * x));";var eM="return x;",rM=`
  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;
`,nM=`
  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;
`,oM=`
  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;
`,sM="return 1.0 / (1.0 + exp(-1.0 * x));",eo=class{constructor(t,e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t,this.enableShapeUniforms=De(this.outputShape.length),this.userCode=`
      vec4 unaryOperation(vec4 x) {
        ${e}
      }

      void main() {
        vec4 x = getAAtOutCoords();
        vec4 y = unaryOperation(x);

        setOutput(y);
      }
    `}};var jw=class{constructor(t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outputShape=t,this.enableShapeUniforms=De(this.outputShape.length);let e=t.length,n=tr("rc",e),o=Wt(e),s=HP(e,n),i=n.slice(-2),a=e<=1?"rc":`vec2(${i.join(",")})`;this.userCode=`
      void main() {
        ${o} rc = getOutputCoords();
        vec4 packedInput = getA(${s});

        setOutput(getChannel(packedInput, ${a}));
      }
    `}};var Gtt=Vr.whereImpl,Wtt=1e-7,Utt=1e-4,Xw={};function Htt(r){return r in Xw||(Xw[r]={}),Xw[r]}var qtt=B().getNumber("CPU_HANDOFF_SIZE_THRESHOLD"),Ktt=600;function jtt(){return B().global.screen==null?1024:B().global.screen.height*B().global.screen.width*window.devicePixelRatio*Ktt/1024/1024}var ku=class extends Uo{constructor(t){if(super(),this.pendingRead=new WeakMap,this.pendingDisposal=new WeakSet,this.dataRefCount=new WeakMap,this.numBytesInGPU=0,this.uploadWaitMs=0,this.downloadWaitMs=0,this.lastGlFlushTime=0,this.warnedAboutMemory=!1,this.pendingDeletes=0,this.disposed=!1,!B().getBool("HAS_WEBGL"))throw new Error("WebGL is not supported on this device");let e;if(t!=null){if(t instanceof qc)e=t;else{let n=Gn(B().getNumber("WEBGL_VERSION"),t);e=new qc(n)}this.binaryCache={},this.gpgpuCreatedLocally=!1}else{let n=Gn(B().getNumber("WEBGL_VERSION"));e=new qc(n),this.binaryCache=Htt(B().getNumber("WEBGL_VERSION")),this.gpgpuCreatedLocally=!0}this.gpgpu=e,this.canvas=this.gpgpu.gl.canvas,this.textureManager=new Kw(this.gpgpu),this.numMBBeforeWarning=jtt(),this.texData=new Qi(this,go())}nextDataId(){return ku.nextDataId++}numDataIds(){return this.texData.numDataIds()-this.pendingDeletes}write(t,e,n){if((B().getBool("WEBGL_CHECK_NUMERICAL_PROBLEMS")||B().getBool("DEBUG"))&&this.checkNumericalProblems(t),n==="complex64"&&t!=null)throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");let o={id:this.nextDataId()};return this.texData.set(o,{shape:e,dtype:n,values:t,usage:Hr.UPLOAD,refCount:1}),o}refCount(t){return this.texData.has(t)?this.texData.get(t).refCount:0}incRef(t){let e=this.texData.get(t);e.refCount++}decRef(t){if(this.texData.has(t)){let e=this.texData.get(t);e.refCount--}}move(t,e,n,o,s){if(B().getBool("DEBUG")&&this.checkNumericalProblems(e),o==="complex64")throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");this.texData.set(t,{shape:n,dtype:o,values:e,usage:Hr.UPLOAD,refCount:s})}disposeIntermediateTensorInfo(t){this.disposeData(t.dataId)}readSync(t){let e=this.texData.get(t),{values:n,dtype:o,complexTensorInfos:s,slice:i,shape:a,isPacked:u}=e;if(i!=null){let m;u?m=new eo(a,jc):m=new Zr(a,jc);let f=this.runWebGLProgram(m,[{dataId:t,shape:a,dtype:o}],o),d=this.readSync(f.dataId);return this.disposeIntermediateTensorInfo(f),d}if(n!=null)return this.convertAndCacheOnCPU(t);if(o==="string")return n;let l=this.activeTimers!=null,c;l&&(c=x.now());let p;if(o==="complex64"){let m=this.readSync(s.real.dataId),f=this.readSync(s.imag.dataId);p=S.mergeRealAndImagArrays(m,f)}else p=this.getValuesFromTexture(t);return l&&(this.downloadWaitMs+=x.now()-c),this.convertAndCacheOnCPU(t,p)}async read(t){if(this.pendingRead.has(t)){let d=this.pendingRead.get(t);return new Promise(h=>d.push(h))}let e=this.texData.get(t),{values:n,shape:o,slice:s,dtype:i,complexTensorInfos:a,isPacked:u}=e;if(s!=null){let d;u?d=new eo(o,jc):d=new Zr(o,jc);let h=this.runWebGLProgram(d,[{dataId:t,shape:o,dtype:i}],i),g=this.read(h.dataId);return this.disposeIntermediateTensorInfo(h),g}if(n!=null)return this.convertAndCacheOnCPU(t);if(B().getBool("DEBUG")&&!B().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")&&B().getNumber("WEBGL_VERSION")===2)throw new Error("tensor.data() with WEBGL_DOWNLOAD_FLOAT_ENABLED=false and WEBGL_VERSION=2 not yet supported.");let l=null,c;if(i!=="complex64"&&B().get("WEBGL_BUFFER_SUPPORTED")){c=this.decode(t);let d=this.texData.get(c.dataId);l=this.gpgpu.createBufferFromTexture(d.texture.texture,...Jh(o))}this.pendingRead.set(t,[]),i!=="complex64"&&await this.gpgpu.createAndWaitForFence();let p;if(i==="complex64"){let d=await Promise.all([this.read(a.real.dataId),this.read(a.imag.dataId)]),h=d[0],g=d[1];p=S.mergeRealAndImagArrays(h,g)}else if(l==null)p=this.getValuesFromTexture(t);else{let d=x.sizeFromShape(o);p=this.gpgpu.downloadFloat32MatrixFromBuffer(l,d)}if(c!=null&&this.disposeIntermediateTensorInfo(c),l!=null){let d=this.gpgpu.gl;vt(d,()=>d.deleteBuffer(l))}let m=this.convertAndCacheOnCPU(t,p),f=this.pendingRead.get(t);return this.pendingRead.delete(t),f.forEach(d=>d(m)),this.pendingDisposal.has(t)&&(this.pendingDisposal.delete(t),this.disposeData(t)&&go().removeDataId(t,this),this.pendingDeletes--),m}readToGPU(t,e={}){let n=this.texData.get(t),{values:o,shape:s,slice:i,dtype:a,isPacked:u,texture:l}=n;if(a==="complex64")throw new Error("Does not support reading texture for complex64 dtype.");if(i!=null){let f;u?f=new eo(s,jc):f=new Zr(s,jc);let d=this.runWebGLProgram(f,[{dataId:t,shape:s,dtype:a}],a),h=this.readToGPU(d,e);return this.disposeIntermediateTensorInfo(d),h}if(l==null)throw o!=null?new Error("Data is not on GPU but on CPU."):new Error("There is no data on GPU or CPU.");let c=this.decode(t,e.customTexShape),p=go().makeTensorFromTensorInfo(c),m=this.texData.get(c.dataId);return Object.assign({tensorRef:p},m.texture)}bufferSync(t){let e=this.readSync(t.dataId);if(t.dtype==="string")try{let n=e.map(o=>x.decodeString(o));return Ct(t.shape,t.dtype,n)}catch(n){throw new Error("Failed to decode encoded string bytes into utf-8")}return Ct(t.shape,t.dtype,e)}checkNumericalProblems(t){if(t!=null)for(let e=0;e<t.length;e++){let n=t[e];if(!Tk(n))throw B().getBool("WEBGL_RENDER_FLOAT32_CAPABLE")?Error(`The value ${n} cannot be represented with your current settings. Consider enabling float32 rendering: 'tf.env().set('WEBGL_RENDER_FLOAT32_ENABLED', true);'`):Error(`The value ${n} cannot be represented on this device.`)}}getValuesFromTexture(t){let{shape:e,dtype:n,isPacked:o}=this.texData.get(t),s=x.sizeFromShape(e);if(B().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")){let m=this.decode(t),f=this.texData.get(m.dataId),d=this.gpgpu.downloadMatrixFromPackedTexture(f.texture.texture,...Jh(e)).subarray(0,s);return this.disposeIntermediateTensorInfo(m),d}let i=B().getBool("WEBGL_PACK")&&o===!0,a=i?rg(e):e,u=i?new Ow(a):new Rw(a),l=this.runWebGLProgram(u,[{shape:a,dtype:n,dataId:t}],"float32"),c=this.texData.get(l.dataId),p=this.gpgpu.downloadByteEncodedFloatMatrixFromOutputTexture(c.texture.texture,c.texShape[0],c.texShape[1]).subarray(0,s);return this.disposeIntermediateTensorInfo(l),p}timerAvailable(){return B().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0}time(t){let e=this.activeTimers,n=[],o=!1;this.programTimersStack==null?(this.programTimersStack=n,o=!0):this.activeTimers.push(n),this.activeTimers=n,t();let s=x.flatten(this.activeTimers.map(u=>u.query)).filter(u=>u!=null),i=x.flatten(this.activeTimers.map(u=>u.name)).filter(u=>u!=null);this.activeTimers=e,o&&(this.programTimersStack=null);let a={uploadWaitMs:this.uploadWaitMs,downloadWaitMs:this.downloadWaitMs,kernelMs:null,wallMs:null};return(async()=>{if(B().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0){let u=await Promise.all(s);a.kernelMs=x.sum(u),a.getExtraProfileInfo=()=>u.map((l,c)=>({name:i[c],ms:l})).map(l=>`${l.name}: ${l.ms}`).join(", ")}else a.kernelMs={error:"WebGL query timers are not supported in this environment."};return this.uploadWaitMs=0,this.downloadWaitMs=0,a})()}memory(){return{unreliable:!1,numBytesInGPU:this.numBytesInGPU,numBytesInGPUAllocated:this.textureManager.numBytesAllocated,numBytesInGPUFree:this.textureManager.numBytesFree}}startTimer(){return B().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?this.gpgpu.beginQuery():{startMs:x.now(),endMs:null}}endTimer(t){return B().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?(this.gpgpu.endQuery(),t):(t.endMs=x.now(),t)}async getQueryTime(t){if(B().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0)return this.gpgpu.waitForQueryAndGetTime(t);let e=t;return e.endMs-e.startMs}disposeData(t,e=!1){if(this.pendingDisposal.has(t))return!1;if(!this.texData.has(t))return!0;if(e?this.texData.get(t).refCount=0:this.texData.get(t).refCount--,!e&&this.texData.get(t).refCount>0)return!1;if(this.pendingRead.has(t))return this.pendingDisposal.add(t),this.pendingDeletes++,!1;this.releaseGPUData(t);let{complexTensorInfos:n}=this.texData.get(t);return n!=null&&(this.disposeData(n.real.dataId,e),this.disposeData(n.imag.dataId,e)),this.texData.delete(t),!0}releaseGPUData(t){let{texture:e,dtype:n,texShape:o,usage:s,isPacked:i,slice:a}=this.texData.get(t),u=a&&a.origDataId||t,l=this.dataRefCount.get(u);l>1?this.dataRefCount.set(u,l-1):(this.dataRefCount.delete(u),e!=null&&(this.numBytesInGPU-=this.computeBytes(o,n),this.textureManager.releaseTexture(e,o,s,i)));let c=this.texData.get(t);c.texture=null,c.texShape=null,c.isPacked=!1,c.slice=null}getTexture(t){return this.uploadToGPU(t),this.texData.get(t).texture.texture}getDataInfo(t){return this.texData.get(t)}shouldExecuteOnCPU(t,e=qtt){return B().getBool("WEBGL_CPU_FORWARD")&&t.every(n=>this.texData.get(n.dataId).texture==null&&x.sizeFromShape(n.shape)<e)}getGPGPUContext(){return this.gpgpu}where(t){S.warn("tf.where() in webgl locks the UI thread. Call tf.whereAsync() instead");let e=t.dataSync();return Gtt(t.shape,e)}packedUnaryOp(t,e,n){let o=new eo(t.shape,e),s=this.compileAndRun(o,[t],n);return go().makeTensorFromTensorInfo(s)}abs(t){if(this.shouldExecuteOnCPU([t])&&t.dtype!=="complex64"){let o=Uw(this.texData.get(t.dataId).values);return this.makeOutput(t.shape,t.dtype,o)}if(B().getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(t,mT,t.dtype);let e=new Zr(t.shape,mT),n=this.compileAndRun(e,[t]);return go().makeTensorFromTensorInfo(n)}makeTensorInfo(t,e,n){let o;if(e==="string"&&n!=null&&n.length>0&&x.isString(n[0])){let s=n.map(i=>x.encodeString(i));o=this.write(s,t,e)}else o=this.write(n,t,e);return this.texData.get(o).usage=null,{dataId:o,shape:t,dtype:e}}makeOutput(t,e,n){return go().makeTensorFromTensorInfo(this.makeTensorInfo(t,e,n),this)}unpackTensor(t){let e=new jw(t.shape);return this.runWebGLProgram(e,[t],t.dtype)}packTensor(t){let e=new qw(t.shape),n=!0;return this.runWebGLProgram(e,[t],t.dtype,null,n)}packedReshape(t,e){let n=[fl(t.shape),...dl(t.shape)],o={dtype:t.dtype,shape:n,dataId:t.dataId},s=[fl(e),...dl(e)],i=new Td(s,n),a=!0,u=[n],l=this.runWebGLProgram(i,[o],t.dtype,u,a);return{dataId:l.dataId,shape:e,dtype:l.dtype}}decode(t,e){let n=this.texData.get(t),{isPacked:o,shape:s,dtype:i}=n;if(e!=null){let m=x.sizeFromShape(s),f=e[0]*e[1]*4;x.assert(m<=f,()=>"customTexShape is too small. Row * Column * 4 should be equal or larger than the size of the tensor data.")}let a=rg(s),u;o?u=new Fw(a):u=new Dw(a);let l=!0,c=[e!=null?e:Jh(a)],p=this.runWebGLProgram(u,[{shape:a,dtype:i,dataId:t}],i,c,l,e);return{dtype:i,shape:s,dataId:p.dataId}}runWebGLProgram(t,e,n,o,s=!1,i){let a=this.makeTensorInfo(t.outputShape,n),u=this.texData.get(a.dataId);if(t.packedOutput&&(u.isPacked=!0),t.outPackingScheme===Su.DENSE){let y=i!=null?i:Jh(t.outputShape);u.texShape=y.map(b=>b*2)}if(t.outTexUsage!=null&&(u.usage=t.outTexUsage),x.sizeFromShape(a.shape)===0)return u.values=x.getTypedArrayFromDType(a.dtype,0),a;let l=[],c=e.map(y=>{if(y.dtype==="complex64")throw new Error("GPGPUProgram does not support complex64 input. For complex64 dtypes, please separate the program into real and imaginary parts.");let b=this.texData.get(y.dataId);if(b.texture==null){if(!t.packedInputs&&x.sizeFromShape(y.shape)<=B().getNumber("WEBGL_SIZE_UPLOAD_UNIFORM"))return{shape:y.shape,texData:null,isUniform:!0,uniformValues:b.values};t.packedInputs&&(b.isPacked=!0,b.shape=y.shape)}if(this.uploadToGPU(y.dataId),!!b.isPacked!=!!t.packedInputs)y=b.isPacked?this.unpackTensor(y):this.packTensor(y),l.push(y),b=this.texData.get(y.dataId);else if(b.isPacked&&!Nu(b.shape,y.shape)){let w=y,v=y.shape;y.shape=b.shape,y=this.packedReshape(y,v),l.push(y),b=this.texData.get(y.dataId),w.shape=v}return{shape:y.shape,texData:b,isUniform:!1}});this.uploadToGPU(a.dataId);let p={shape:a.shape,texData:u,isUniform:!1},m=sP(t,c,p),f=this.getAndSaveBinary(m,()=>nP(this.gpgpu,t,c,p)),d=this.activeTimers!=null,h;d&&(h=this.startTimer()),B().get("ENGINE_COMPILE_ONLY")||oP(this.gpgpu,f,c,p,o),l.forEach(y=>this.disposeIntermediateTensorInfo(y)),d&&(h=this.endTimer(h),this.activeTimers.push({name:t.constructor.name,query:this.getQueryTime(h)}));let g=B().get("WEBGL_FLUSH_THRESHOLD");if(g>0){let y=x.now();y-this.lastGlFlushTime>g&&(this.gpgpu.gl.flush(),this.lastGlFlushTime=y)}if(!B().getBool("WEBGL_LAZILY_UNPACK")&&u.isPacked&&s===!1){let y=this.unpackTensor(a);return this.disposeIntermediateTensorInfo(a),y}return a}compileAndRun(t,e,n,o,s=!1){return n=n||e[0].dtype,this.runWebGLProgram(t,e,n,o,s)}getAndSaveBinary(t,e){return t in this.binaryCache||(this.binaryCache[t]=e()),this.binaryCache[t]}getTextureManager(){return this.textureManager}dispose(){this.disposed||(B().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=W(()=>{if(!B().get("WEBGL_RENDER_FLOAT32_ENABLED")){let t=B().getBool("DEBUG");B().set("DEBUG",!1);let e=this.abs(pt(1e-8)).dataSync()[0];if(B().set("DEBUG",t),e>0)return 32}return 16})),this.floatPrecisionValue}epsilon(){return this.floatPrecision()===32?Wtt:Utt}uploadToGPU(t){let e=this.texData.get(t),{shape:n,dtype:o,values:s,texture:i,usage:a,isPacked:u}=e;if(i!=null)return;let l=this.activeTimers!=null,c;l&&(c=x.now());let p=e.texShape;if(p==null&&(p=Bk(n,u),e.texShape=p),s!=null){let m=rg(n),f,d=p[1],h=p[0],g=s instanceof Uint8Array||s instanceof Uint8ClampedArray;(u||!g)&&([d,h]=Ji(p[0],p[1])),u?f=new Pw(m,g):f=new Lw(m,g);let y=g?[h,d]:p,b=this.makeTensorInfo(y,o),w=this.texData.get(b.dataId);g?w.usage=Hr.PIXELS:w.usage=Hr.UPLOAD,w.texShape=y,this.gpgpu.uploadDenseMatrixToTexture(this.getTexture(b.dataId),d,h,s);let v=[[h,d]],N=!0,E=this.runWebGLProgram(f,[b],o,v,N),$=this.texData.get(E.dataId);e.texShape=$.texShape,e.isPacked=$.isPacked,e.usage=$.usage,B().get("ENGINE_COMPILE_ONLY")?this.disposeData(E.dataId):(e.texture=$.texture,e.values=null,this.texData.delete(E.dataId)),this.disposeIntermediateTensorInfo(b),l&&(this.uploadWaitMs+=x.now()-c)}else{let m=this.acquireTexture(p,a,o,u);e.texture=m}}convertAndCacheOnCPU(t,e){let n=this.texData.get(t),{dtype:o}=n;return this.releaseGPUData(t),e!=null&&(n.values=Xtt(e,o)),n.values}acquireTexture(t,e,n,o){if(this.numBytesInGPU+=this.computeBytes(t,n),!this.warnedAboutMemory&&this.numBytesInGPU>this.numMBBeforeWarning*1024*1024){let s=(this.numBytesInGPU/1024/1024).toFixed(2);this.warnedAboutMemory=!0,console.warn(`High memory usage in GPU: ${s} MB, most likely due to a memory leak`)}return this.textureManager.acquireTexture(t,e,o)}computeBytes(t,e){return t[0]*t[1]*x.bytesPerElement(e)}checkCompileCompletion(){for(let[,t]of Object.entries(this.binaryCache))this.checkCompletion_(t)}async checkCompileCompletionAsync(){let t=[];if(this.gpgpu.parallelCompilationExtension){for(let[,e]of Object.entries(this.binaryCache))t.push(this.checkCompletionAsync_(e));return Promise.all(t)}else{for(let[,e]of Object.entries(this.binaryCache)){let n=new Promise(o=>{try{this.checkCompletion_(e),o(!0)}catch(s){throw s}});t.push(n)}return Promise.all(t)}}async checkCompletionAsync_(t){return this.gpgpu.gl.getProgramParameter(t.webGLProgram,this.gpgpu.parallelCompilationExtension.COMPLETION_STATUS_KHR)?this.checkCompletion_(t):(await wh(),this.checkCompletionAsync_(t))}checkCompletion_(t){if(this.gpgpu.gl.getProgramParameter(t.webGLProgram,this.gpgpu.gl.LINK_STATUS)===!1)throw console.log(this.gpgpu.gl.getProgramInfoLog(t.webGLProgram)),this.gpgpu.gl.getShaderParameter(t.fragmentShader,this.gpgpu.gl.COMPILE_STATUS)===!1?(kw(t.source,this.gpgpu.gl.getShaderInfoLog(t.fragmentShader)),new Error("Failed to compile fragment shader.")):new Error("Failed to link vertex and fragment shaders.");return!0}getUniformLocations(){for(let[,t]of Object.entries(this.binaryCache)){let{uniformLocations:e,customUniformLocations:n,infLoc:o,nanLoc:s,inShapesLocations:i,inTexShapesLocations:a,outShapeLocation:u,outShapeStridesLocation:l,outTexShapeLocation:c}=Kk(this.gpgpu,t.program,t.webGLProgram);t.uniformLocations=e,t.customUniformLocations=n,t.infLoc=o,t.nanLoc=s,t.inShapesLocations=i,t.inTexShapesLocations=a,t.outShapeLocation=u,t.outShapeStridesLocation=l,t.outTexShapeLocation=c}}};ku.nextDataId=0;function Xtt(r,t){if(t==="float32"||t==="complex64")return r;if(t==="int32"||t==="bool"){let e=t==="int32"?new Int32Array(r.length):new Uint8Array(r.length);for(let n=0;n<e.length;++n)e[n]=Math.round(r[n]);return e}else throw new Error(`Unknown dtype ${t}`)}var iM="3.19.0";function aM(){B().set("WEBGL_FORCE_F16_TEXTURES",!0)}Gl.isBrowser()&&sm("webgl",()=>new ku,2);var bke={forceHalfFloat:aM};var Yw=`
  if (isnan(a)) return a;
  if (isnan(b)) return b;
`;var ro=class{constructor(t,e,n){this.variableNames=["A","B"],this.outputShape=S.assertAndGetBroadcastShape(e,n),this.enableShapeUniforms=De(this.outputShape.length),this.userCode=`
      float binaryOperation(float a, float b) {
        ${t}
      }

      void main() {
        float a = getAAtOutCoords();
        float b = getBAtOutCoords();
        setOutput(binaryOperation(a, b));
      }
    `}};var Tu=`
  result.r = isNaN.r > 0. ? NAN : result.r;
  result.g = isNaN.g > 0. ? NAN : result.g;
  result.b = isNaN.b > 0. ? NAN : result.b;
  result.a = isNaN.a > 0. ? NAN : result.a;
`;var Fo=class{constructor(t,e,n,o=!1){this.variableNames=["A","B"],this.supportsBroadcasting=!0,this.packedInputs=!0,this.packedOutput=!0,this.outputShape=S.assertAndGetBroadcastShape(e,n);let s=this.outputShape.length;this.enableShapeUniforms=De(s);let i="";if(o)if(s===0||x.sizeFromShape(this.outputShape)===1)i=`
          result.y = 0.;
          result.z = 0.;
          result.w = 0.;
        `;else if(i=`
          ${Wt(s)} coords = getOutputCoords();
        `,s===1)this.enableShapeUniforms?i+=`
            result.y = (coords + 1) >= outShape ? 0. : result.y;
            result.z = 0.;
            result.w = 0.;
          `:i+=`
            result.y = (coords + 1) >= ${this.outputShape[0]} ? 0. : result.y;
            result.z = 0.;
            result.w = 0.;
          `;else{let u=tr("coords",s);this.enableShapeUniforms?i+=`
            bool nextRowOutOfBounds =
              (${u[s-2]} + 1) >= outShape[${s} - 2];
            bool nextColOutOfBounds =
              (${u[s-1]} + 1) >= outShape[${s} - 1];
            result.y = nextColOutOfBounds ? 0. : result.y;
            result.z = nextRowOutOfBounds ? 0. : result.z;
            result.w = nextColOutOfBounds || nextRowOutOfBounds ? 0. : result.w;
          `:i+=`
            bool nextRowOutOfBounds =
              (${u[s-2]} + 1) >= ${this.outputShape[s-2]};
            bool nextColOutOfBounds =
              (${u[s-1]} + 1) >= ${this.outputShape[s-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) {
        ${t}
      }

      void main() {
        vec4 a = getAAtOutCoords();
        vec4 b = getBAtOutCoords();

        vec4 result = binaryOperation(a, b);
        ${i}

        setOutput(result);
      }
    `}};function er(r){let{inputs:t,backend:e}=r,{x:n}=t;return e.incRef(n.dataId),{dataId:n.dataId,shape:n.shape,dtype:n.dtype}}var lM={kernelName:lo,backendName:"webgl",kernelFunc:er};function An(r){let{inputs:t,backend:e}=r,{real:n,imag:o}=t,s=e.makeTensorInfo(n.shape,"complex64"),i=e.texData.get(s.dataId),a=er({inputs:{x:n},backend:e}),u=er({inputs:{x:o},backend:e});return i.complexTensorInfos={real:a,imag:u},s}var uM={kernelName:Sp,backendName:"webgl",kernelFunc:An};var fT="return (a < 0.) ? b * a : a;",dT=`
  vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));
  return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);
`;function Ytt(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{alpha:s}=n,i=e.makeTensorInfo([],"float32",x.createScalarValue(s,"float32")),a=B().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new Fo(dT,o.shape,i.shape):new ro(fT,o.shape,i.shape),u=e.runWebGLProgram(a,[o,i],"float32");return e.disposeIntermediateTensorInfo(i),u}var cM={kernelName:ps,backendName:"webgl",kernelFunc:Ytt};var hT="return (a < 0.) ? b * a : a;",gT=`
  vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));
  return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);
`;function Ztt(r){let{inputs:t,backend:e}=r,{x:n,alpha:o}=t,s=B().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new Fo(gT,n.shape,o.shape):new ro(hT,n.shape,o.shape);return e.runWebGLProgram(s,[n,o],"float32")}var pM={kernelName:Ss,backendName:"webgl",kernelFunc:Ztt};var Ro="if (isnan(x)) return x;",mM=`
  if (isnan(a)) return a;
  if (isnan(b)) return b;
`,fM=`
  result.r = isNaN.r > 0. ? NAN : result.r;
  result.g = isNaN.g > 0. ? NAN : result.g;
  result.b = isNaN.b > 0. ? NAN : result.b;
  result.a = isNaN.a > 0. ? NAN : result.a;
`;function It({opSnippet:r,packedOpSnippet:t,cpuKernelImpl:e,dtype:n}){return({inputs:o,backend:s})=>{let{x:i}=o,a=s,u=n||i.dtype;if(a.shouldExecuteOnCPU([i])&&e!=null){let p=a.texData.get(i.dataId),m=e(p.values,u);return a.makeTensorInfo(i.shape,u,m)}let l=B().getBool("WEBGL_PACK_UNARY_OPERATIONS")&&t!=null,c;return l?c=new eo(i.shape,t):c=new Zr(i.shape,r),a.runWebGLProgram(c,[i],u)}}function ce({opSnippet:r,packedOpSnippet:t,checkOutOfBounds:e=!1,supportsComplex:n=!1,cpuKernelImpl:o,dtype:s}){return({inputs:i,backend:a})=>{let{a:u,b:l}=i,c=a;if(n&&u.dtype==="complex64"){let d=c.texData.get(u.dataId),h=c.texData.get(l.dataId),[g,y]=[[d.complexTensorInfos.real,h.complexTensorInfos.real],[d.complexTensorInfos.imag,h.complexTensorInfos.imag]].map(w=>{let[v,N]=w,E={dataId:v.dataId,dtype:v.dtype,shape:u.shape},$={dataId:N.dataId,dtype:N.dtype,shape:l.shape},D=new ro(r,u.shape,l.shape);return c.runWebGLProgram(D,[E,$],ir(v.dtype,N.dtype))}),b=An({inputs:{real:g,imag:y},backend:c});return c.disposeIntermediateTensorInfo(g),c.disposeIntermediateTensorInfo(y),b}let p=s||ir(u.dtype,l.dtype);if((u.dtype==="string"||l.dtype==="string"||c.shouldExecuteOnCPU([u,l]))&&o!=null){let d=c.texData.get(u.dataId).values,h=c.texData.get(l.dataId).values,g=u.dtype==="string"?S.fromUint8ToStringArray(d):d,y=u.dtype==="string"?S.fromUint8ToStringArray(h):h,[b,w]=o(u.shape,l.shape,g,y,p),v=c.makeTensorInfo(w,p),N=c.texData.get(v.dataId);return N.values=b,v}let m=B().getBool("WEBGL_PACK_BINARY_OPERATIONS")&&t!=null,f;return m?f=new Fo(t,u.shape,l.shape,e):f=new ro(r,u.shape,l.shape),c.runWebGLProgram(f,[u,l],p)}}function _u(r,t=!1){if(r==="linear")return t?eM:XP;if(r==="relu")return t?nM:ZP;if(r==="elu")return t?rM:YP;if(r==="relu6")return t?oM:JP;if(r==="prelu")return t?gT:hT;if(r==="leakyrelu")return t?dT:fT;if(r==="sigmoid")return t?sM:QP;throw new Error(`Activation ${r} has not been implemented for the WebGL backend.`)}var _d=class{constructor(t,e,n,o=!1,s=!1,i=!1,a=null,u=!1,l=!1){this.variableNames=["matrixA","matrixB"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=n,this.enableShapeUniforms=De(this.outputShape.length);let c=o?t[1]:t[2],p=Math.ceil(c/2),m=o?"i * 2, rc.y":"rc.y, i * 2",f=s?"rc.z, i * 2":"i * 2, rc.z",d=o?["a.xxyy","a.zzww"]:["a.xxzz","a.yyww"],h=s?["b.xzxz","b.ywyw"]:["b.xyxy","b.zwzw"],g="",y="";a&&(u?g=`vec4 activation(vec4 a) {
          vec4 b = getPreluActivationWeightsAtOutCoords();
          ${a}
        }`:l?g=`vec4 activation(vec4 a) {
          vec4 b = getLeakyreluAlphaAtOutCoords();
          ${a}
        }`:g=`vec4 activation(vec4 x) {
          ${a}
        }`,y="result = activation(result);");let b=i?"result += getBiasAtOutCoords();":"";i&&this.variableNames.push("bias"),u&&this.variableNames.push("preluActivationWeights"),l&&this.variableNames.push("leakyreluAlpha");let w="rc.x",v="rc.x";t[0]<e[0]?w=`int(min(float(rc.x), ${t[0]-1}.))`:e[0]<t[0]&&(v=`int(min(float(rc.x), ${e[0]-1}.))`),this.userCode=`
      ${g}
      // Don't use uniform for sharedDimensionPacked for performance.
      const float sharedDimension = ${p}.0;

      vec4 dot2x2ARowBCol(ivec3 rc) {
        vec4 result = vec4(0);
        for (int i = 0; i < ${p}; i++) {
          int batchA = ${w};
          int batchB = ${v};
          vec4 a = getMatrixA(batchA, ${m});
          vec4 b = getMatrixB(batchB, ${f});

          // These swizzled products need to be separately added.
          // See: https://github.com/tensorflow/tfjs/issues/1735
          result += (${d[0]} * ${h[0]});
          result += (${d[1]} * ${h[1]});
        }
        return result;
      }

      void main() {
        ivec3 rc = getOutputCoords();
        vec4 result = dot2x2ARowBCol(rc);

        ${b}

        ${y}

        setOutput(result);
      }
    `}};var xT={REAL:"return areal * breal - aimag * bimag;",IMAG:"return areal * bimag + aimag * breal;"},og=class{constructor(t,e,n){this.variableNames=["AReal","AImag","BReal","BImag"],this.outputShape=S.assertAndGetBroadcastShape(e,n),this.userCode=`
      float binaryOpComplex(
          float areal, float aimag, float breal, float bimag) {
        ${t}
      }

      void main() {
        float areal = getARealAtOutCoords();
        float aimag = getAImagAtOutCoords();
        float breal = getBRealAtOutCoords();
        float bimag = getBImagAtOutCoords();
        setOutput(binaryOpComplex(areal, aimag, breal, bimag));
      }
    `}};var dM="return a * b;";function sg(r){let{inputs:t,backend:e}=r,{a:n,b:o}=t,s=S.upcastType(n.dtype,o.dtype);if(n.dtype==="complex64"){let a=e.texData.get(n.dataId),u=e.texData.get(o.dataId),l=new og(xT.REAL,n.shape,o.shape),c=new og(xT.IMAG,n.shape,o.shape),p=[{dataId:a.complexTensorInfos.real.dataId,dtype:a.complexTensorInfos.real.dtype,shape:n.shape},{dataId:a.complexTensorInfos.imag.dataId,dtype:a.complexTensorInfos.imag.dtype,shape:n.shape},{dataId:u.complexTensorInfos.real.dataId,dtype:u.complexTensorInfos.real.dtype,shape:o.shape},{dataId:u.complexTensorInfos.imag.dataId,dtype:u.complexTensorInfos.imag.dtype,shape:o.shape}],m=e.runWebGLProgram(l,p,"float32"),f=e.runWebGLProgram(c,p,"float32"),d=An({inputs:{real:m,imag:f},backend:e});return e.disposeIntermediateTensorInfo(m),e.disposeIntermediateTensorInfo(f),d}if(e.shouldExecuteOnCPU([n,o])){let a=e.texData.get(n.dataId),u=e.texData.get(o.dataId),[l,c]=NP(n.shape,o.shape,a.values,u.values,s),p=e.makeTensorInfo(c,s),m=e.texData.get(p.dataId);return m.values=l,p}let i;return B().getBool("WEBGL_PACK_BINARY_OPERATIONS")?i=new Fo(dM,n.shape,o.shape):i=new ro(dM,n.shape,o.shape),e.runWebGLProgram(i,[n,o],s)}var hM={kernelName:ws,backendName:"webgl",kernelFunc:sg};function gM(r,t,e){let n=[fl(r.shape),...dl(r.shape)],o={dtype:r.dtype,shape:n,dataId:r.dataId},s=[fl(t),...dl(t)],i=new Td(s,n),a=!0,u=[n],l=e.runWebGLProgram(i,[o],r.dtype,u,a);return{dataId:l.dataId,shape:t,dtype:l.dtype}}function at(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{shape:s}=n,i=e,a=x.sizeFromShape(o.shape),u=x.inferFromImplicitShape(s,a),l=x.sizeFromShape(u);x.assert(a===l,()=>`The new shape (${u}) has ${l} elements and the old shape (${o.shape}) has ${a} elements. The new shape and old shape must have the same number of elements.`);let c=i.texData.get(o.dataId);return c.isPacked&&!Nu(o.shape,u)&&!(c.texture!==null&&Nu(c.shape,u))?gM(o,u,i):(i.incRef(o.dataId),{dataId:o.dataId,shape:u,dtype:o.dtype})}var xM={kernelName:yi,backendName:"webgl",kernelFunc:at};var ig=class{constructor(t,e){this.variableNames=["x"];let{windowSize:n,batchSize:o,inSize:s,outSize:i}=t;this.outputShape=[o,i];let a=Math.floor(n/4)*4,u=n%4,l="sumValue += dot(values, ones);";if(e!=null){let p=1/e;l=`sumValue += dot(values * ${x.isInt(p)?p.toPrecision(2):p}, ones);`}let c="";s%n>0&&(c=`
        if (inIdx < 0 || inIdx >= ${s}) {
          return 0.0;
        }
      `),this.userCode=`
      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);

      float getValue(int batch, int inIdx) {
        ${c}
        return getX(batch, inIdx);
      }

      void main() {
        ivec2 coords = getOutputCoords();
        int batch = coords[0];
        int outIdx = coords[1];
        int inOffset = outIdx * ${n};

        float sumValue = 0.0;

        for (int i = 0; i < ${a}; 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 + ${a};
        if (${u===1}) {
          vec4 values = vec4(getValue(batch, inIdx), 0.0, 0.0, 0.0);

          ${l}
        } else if (${u===2}) {
          vec4 values = vec4(
            getValue(batch, inIdx),
            getValue(batch, inIdx + 1), 0.0, 0.0);

          ${l}
        } else if (${u===3}) {
          vec4 values = vec4(
            getValue(batch, inIdx),
            getValue(batch, inIdx + 1),
            getValue(batch, inIdx + 2), 0.0);

          ${l}
        }
        setOutput(sumValue);
      }
    `}};var Zw=class{constructor(t,e){this.variableNames=["x"];let{windowSize:n,batchSize:o,inSize:s,outSize:i}=t;this.outputShape=[o,i];let a="0.0",u="";e==="prod"?a="1.0":e==="min"?(a="1.0 / 1e-20",u="min"):e==="max"&&(a="-1.0 / 1e-20",u="max");let l=`${e}(${e}(${e}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;e==="sum"?l="sumValue":e==="prod"?l="prodValue":e==="all"?l="allValue":e==="any"&&(l="anyValue");let c=Math.floor(n/4)*4,p=n%4,m=`
      if (${e==="sum"}) {
        sumValue += dot(values, ones);
      } else if (${e==="prod"}) {
        vec2 tmp = vec2(values[0], values[1]) * vec2(values[2], values[3]);
        prodValue *= tmp[0] * tmp[1];
      } else {
        minMaxValue = ${u}(values, minMaxValue);
        if (${e==="min"} || ${e==="max"}) {
          minMaxValue = ${u}(values, minMaxValue);
          bvec4 isNaN = isnan(values);
          if (isNaN.r || isNaN.g || isNaN.b || isNaN.a) {
            minMaxValue = vec4(NAN);
          }
        }
      }
    `,f="vec4";e==="all"?(a="1.0",m=`
        bool reducedAllValue = all(values);
        float floatedReducedAllValue = float(reducedAllValue);
        allValue = float(allValue >= 1.0 && floatedReducedAllValue >= 1.0);
      `,f="bvec4"):e==="any"&&(a="0.0",m=`
        bool reducedAnyValue = any(values);
        float floatedReducedAnyValue = float(reducedAnyValue);
        anyValue = float(anyValue >= 1.0 || floatedReducedAnyValue >= 1.0);
      `,f="bvec4");let d="";s%n>0&&(d=`
        if (inIdx < 0 || inIdx >= ${s}) {
          return initializationValue;
        }
      `),this.userCode=`
      const float initializationValue = ${a};
      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);

      float getValue(int batch, int inIdx) {
        ${d}
        return getX(batch, inIdx);
      }

      void main() {
        ivec2 coords = getOutputCoords();
        int batch = coords[0];
        int outIdx = coords[1];
        int inOffset = outIdx * ${n};

        vec4 minMaxValue = vec4(${a});
        float prodValue = 1.0;
        float sumValue = 0.0;
        float allValue = 1.0;
        float anyValue = 0.0;

        for (int i = 0; i < ${c}; i += 4) {
          int inIdx = inOffset + i;
          ${f} values = ${f}(
            getValue(batch, inIdx),
            getValue(batch, inIdx + 1),
            getValue(batch, inIdx + 2),
            getValue(batch, inIdx + 3)
          );

          ${m}
        }

        int inIdx = inOffset + ${c};
        if (${p===1}) {
          ${f} values = ${f}(
            getValue(batch, inIdx),
            initializationValue,
            initializationValue,
            initializationValue
          );

          ${m}
        } else if (${p===2}) {
          ${f} values = ${f}(
            getValue(batch, inIdx),
            getValue(batch, inIdx + 1),
            initializationValue,
            initializationValue
          );

          ${m}
        } else if (${p===3}) {
          ${f} values = ${f}(
            getValue(batch, inIdx),
            getValue(batch, inIdx + 1),
            getValue(batch, inIdx + 2),
            initializationValue
          );

          ${m}
        }
        setOutput(${l});
      }
    `}};function Qtt(r){let t=[];for(;t.length===0||t[t.length-1].outSize!==1;){let e=t.length?t[t.length-1].outSize:r[1],n=S.computeOptimalWindowSize(e);t.push({inSize:e,windowSize:n,outSize:Math.ceil(e/n)})}return t}function Un(r,t,e,n){let o=Qtt(r.shape),s=r;for(let i=0;i<o.length;i++){let{inSize:a,windowSize:u,outSize:l}=o[i],c,p;e==="mean"?c=i===0?new ig({windowSize:u,inSize:a,batchSize:r.shape[0],outSize:l},a):new ig({windowSize:u,inSize:a,batchSize:r.shape[0],outSize:l}):c=new Zw({windowSize:u,inSize:a,batchSize:r.shape[0],outSize:l},e),p=s,s=n.runWebGLProgram(c,[s],t),p.dataId!==r.dataId&&n.disposeIntermediateTensorInfo(p)}return s}var Jw=class{constructor(t,e){this.variableNames=["A"];let n=new Array(t.length);for(let i=0;i<n.length;i++)n[i]=t[e[i]];this.outputShape=n,this.rank=n.length;let o=Wt(this.rank),s=tet(e);this.userCode=`
    void main() {
      ${o} resRC = getOutputCoords();
      setOutput(getA(${s}));
    }
    `}};function tet(r){let t=r.length;if(t>6)throw Error(`Transpose for rank ${t} is not yet supported`);let e=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u","resRC.v"],n=new Array(t);for(let o=0;o<r.length;o++)n[r[o]]=e[o];return n.join()}var Qw=class{constructor(t,e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0;let n=new Array(t.length);for(let c=0;c<n.length;c++)n[c]=t[e[c]];if(this.outputShape=n,this.rank=n.length,this.rank>6)throw Error(`Packed transpose for rank ${this.rank} is not yet supported.`);let o=Wt(this.rank),s=pT("rc",this.rank),i=new Array(this.rank);for(let c=0;c<e.length;c++)i[e[c]]=s[c];let a=`vec2(${i.slice(-2).join()})`,u=`++${s[this.rank-1]} < ${n[this.rank-1]}`,l=`getChannel(getA(${i.join()}), ${a})`;this.userCode=`
    void main() {
      ${o} rc = getOutputCoords();
      vec4 result = vec4(0.);
      result[0] = ${l};
      if(${u}) {
        result[1] = ${l};
      }
      --${s[this.rank-1]};
      if(++${s[this.rank-2]} < ${n[this.rank-2]}) {
        result[2] = ${l};
        if(${u}) {
          result[3] = ${l};
        }
      }
      setOutput(result);
    }
    `}};function Eu(r,t,e){let n=B().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new Qw(r.shape,t):new Jw(r.shape,t);return e.runWebGLProgram(n,[r],r.dtype)}function yM(r,t,e,n){let o=t,s=r.shape.length,i=x.parseAxisParam(o,r.shape),a=i,u=S.getAxesPermutation(a,s),l=u!=null,c=r;l&&(c=Eu(r,u,n),a=S.getInnerMostAxes(a.length,s)),S.assertAxesAreInnerMostDims("sum",a,s);let[p,m]=S.computeOutAndReduceShapes(c.shape,a),f=p;e&&(f=S.expandShapeToKeepDim(p,i));let d=x.sizeFromShape(m),g=x.sizeFromShape(r.shape)/d,y=at({inputs:{x:c},attrs:{shape:[g,d]},backend:n}),b=Ku(r.dtype),w=Un(y,b,"sum",n),v=at({inputs:{x:w},attrs:{shape:f},backend:n});return n.disposeIntermediateTensorInfo(y),n.disposeIntermediateTensorInfo(w),l&&n.disposeIntermediateTensorInfo(c),v}function Xc(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{axis:s,keepDims:i}=n;return yM(o,s,i,e)}var bM={kernelName:Ls,backendName:"webgl",kernelFunc:Xc};function Pe(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{perm:s}=n,i=e,a=o.shape.length,u=new Array(a);for(let c=0;c<u.length;c++)u[c]=o.shape[s[c]];let l;if(i.shouldExecuteOnCPU([o])){let p=i.texData.get(o.dataId).values,m=Kc(p,o.shape,o.dtype,s,u);l=i.makeTensorInfo(u,o.dtype);let f=i.texData.get(l.dataId);f.values=m}else l=Eu(o,s,i);return l}var wM={kernelName:Yn,backendName:"webgl",kernelFunc:Pe};var yT=1e3;function Yc({a:r,b:t,transposeA:e,transposeB:n,backend:o,bias:s=null,preluActivationWeights:i=null,leakyreluAlpha:a=0,activation:u=null}){let l=r.shape.length,c=t.shape.length,p=e?r.shape[l-2]:r.shape[l-1],m=n?t.shape[c-1]:t.shape[c-2],f=e?r.shape[l-1]:r.shape[l-2],d=n?t.shape[c-2]:t.shape[c-1],h=r.shape.slice(0,-2),g=t.shape.slice(0,-2),y=x.sizeFromShape(h),b=x.sizeFromShape(g),v=Pr.assertAndGetBroadcastShape(r.shape.slice(0,-2),t.shape.slice(0,-2)).concat([f,d]);x.assert(p===m,()=>`Error in matMul: inner shapes (${p}) and (${m}) of Tensors with shapes ${r.shape} and ${t.shape} and transposeA=${e} and transposeB=${n} must match.`);let N=e?[y,p,f]:[y,f,p],E=n?[b,d,m]:[b,m,d],$=at({inputs:{x:r},backend:o,attrs:{shape:N}}),D=at({inputs:{x:t},backend:o,attrs:{shape:E}}),L=[$,D],M=Math.max(y,b),G=e?$.shape[1]:$.shape[2],H=s!=null,q=i!=null,X=u==="leakyrelu",j=u!=null?_u(u,!0):null,J=H||q||X||j!=null,nt;if((f===1||d===1)&&G>yT&&J===!1){let ot=$,st=D;e&&(ot=Pe({inputs:{x:$},backend:o,attrs:{perm:[0,2,1]}}),L.push(ot)),n&&(st=Pe({inputs:{x:D},backend:o,attrs:{perm:[0,2,1]}}),L.push(st));let it=d!==1,ft=d===1,lt=ot;it&&(lt=at({inputs:{x:ot},backend:o,attrs:{shape:[M,G,1]}}),L.push(lt));let xt=d===1?2:1,dt=st;ft&&(dt=at({inputs:{x:st},backend:o,attrs:{shape:[M,1,G]}}),L.push(dt));let bt=sg({inputs:{a:lt,b:dt},backend:o});nt=Xc({inputs:{x:bt},backend:o,attrs:{axis:xt,keepDims:!0}}),L.push(bt)}else{let ot=ir(r.dtype,t.dtype),st=new _d(N,E,[M,f,d],e,n,H,j,q,X),it=[$,D];if(s!=null&&it.push(s),q&&it.push(i),X){let ft=o.makeTensorInfo([],"float32",x.createScalarValue(a,"float32"));it.push(ft),L.push(ft)}nt=o.runWebGLProgram(st,it,ot)}let K=at({inputs:{x:nt},backend:o,attrs:{shape:v}});L.push(nt);for(let ot of L)o.disposeIntermediateTensorInfo(ot);return K}function eet(r){let{inputs:t,backend:e,attrs:n}=r,{a:o,b:s,bias:i,preluActivationWeights:a}=t,{transposeA:u,transposeB:l,activation:c,leakyreluAlpha:p}=n;return Yc({a:o,b:s,transposeA:u,transposeB:l,backend:e,bias:i,preluActivationWeights:a,leakyreluAlpha:p,activation:c})}var vM={kernelName:Ni,backendName:"webgl",kernelFunc:eet};var CM="return abs(x);";function ret(r){let{inputs:t,backend:e}=r,{x:n}=t;if(e.shouldExecuteOnCPU([n])&&n.dtype!=="complex64"){let s=e.texData.get(n.dataId),i=Uw(s.values);return e.makeTensorInfo(n.shape,n.dtype,i)}let o;return B().getBool("WEBGL_PACK_UNARY_OPERATIONS")?o=new eo(n.shape,CM):o=new Zr(n.shape,CM),e.runWebGLProgram(o,[n],n.dtype)}var IM={kernelName:ci,backendName:"webgl",kernelFunc:ret};var net=fr+`
  if (abs(x) > 1.) {
    return NAN;
  }
  return acos(x);
`,oet=It({opSnippet:net}),SM={kernelName:ea,backendName:"webgl",kernelFunc:oet};var set=fr+`
  if (x < 1.0) return NAN;
return log(x + sqrt(x * x - 1.0));`,iet=It({opSnippet:set}),NM={kernelName:ra,backendName:"webgl",kernelFunc:iet};var kM="return a + b;",aet=ce({opSnippet:kM,packedOpSnippet:kM,supportsComplex:!0,cpuKernelImpl:iP}),TM={kernelName:jn,backendName:"webgl",kernelFunc:aet};var tv=class{constructor(t,e){this.outputShape=[],this.outputShape=t,this.variableNames=e.map((s,i)=>`T${i}`);let n=[];this.variableNames.forEach(s=>{n.push(`float v${s} = get${s}AtOutCoords();`)});let o=this.variableNames.map(s=>`v${s}`).join(" + ");this.userCode=`
      void main() {
        ${n.join(`
        `)}

        float result = ${o};
        setOutput(result);
      }
    `}};var ev=class{constructor(t,e){this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t,this.variableNames=e.map((s,i)=>`T${i}`);let n=[];this.variableNames.forEach(s=>{n.push(`vec4 v${s} = get${s}AtOutCoords();`)});let o=this.variableNames.map(s=>`v${s}`).join(" + ");this.userCode=`
      void main() {
        ${n.join(`
        `)}

        vec4 result = ${o};
        setOutput(result);
      }
    `}};function rv(r){let{inputs:t,backend:e}=r,n=t;if(n.length===1)return er({inputs:{x:n[0]},backend:e});if(n.length>B().get("WEBGL_MAX_TEXTURES_IN_SHADER")){let u=Math.floor(n.length/2),l=rv({inputs:n.slice(0,u),backend:e}),c=rv({inputs:n.slice(u),backend:e});return rv({inputs:[l,c],backend:e})}let o=n.map(u=>u.dtype).reduce((u,l)=>ir(u,l)),s=n.map(u=>u.shape),a=B().getBool("WEBGL_PACK")?new ev(n[0].shape,s):new tv(n[0].shape,s);return e.runWebGLProgram(a,n,o)}var _M={kernelName:Ko,backendName:"webgl",kernelFunc:rv};function uet(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{axis:s,keepDims:i}=n,a=o.shape.length,u=x.parseAxisParam(s,o.shape),l=u,c=S.getAxesPermutation(l,a),p=o;c!=null&&(p=Pe({inputs:{x:o},backend:e,attrs:{perm:c}}),l=S.getInnerMostAxes(l.length,a)),S.assertAxesAreInnerMostDims("all",l,a);let[m,f]=S.computeOutAndReduceShapes(p.shape,l),d=x.sizeFromShape(f),h=at({inputs:{x:p},backend:e,attrs:{shape:[-1,d]}}),g=Un(h,h.dtype,"all",e),y;if(i){let b=S.expandShapeToKeepDim(m,u);y=at({inputs:{x:g},backend:e,attrs:{shape:b}})}else y=at({inputs:{x:g},backend:e,attrs:{shape:m}});return e.disposeIntermediateTensorInfo(h),e.disposeIntermediateTensorInfo(g),c!=null&&e.disposeIntermediateTensorInfo(p),y}var EM={kernelName:na,backendName:"webgl",kernelFunc:uet};function cet(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{axis:s,keepDims:i}=n,a=o.shape.length,u=x.parseAxisParam(s,o.shape),l=u,c=S.getAxesPermutation(l,a),p=o;c!=null&&(p=Pe({inputs:{x:o},backend:e,attrs:{perm:c}}),l=S.getInnerMostAxes(l.length,a)),S.assertAxesAreInnerMostDims("any",l,a);let[m,f]=S.computeOutAndReduceShapes(p.shape,l),d=x.sizeFromShape(f),h=at({inputs:{x:p},backend:e,attrs:{shape:[-1,d]}}),g=Un(h,h.dtype,"any",e),y;if(i){let b=S.expandShapeToKeepDim(m,u);y=at({inputs:{x:g},backend:e,attrs:{shape:b}})}else y=at({inputs:{x:g},backend:e,attrs:{shape:m}});return e.disposeIntermediateTensorInfo(h),e.disposeIntermediateTensorInfo(g),c!=null&&e.disposeIntermediateTensorInfo(p),y}var AM={kernelName:oa,backendName:"webgl",kernelFunc:cet};var nv=class{constructor(t,e,n){this.variableNames=["A"];let{windowSize:o,batchSize:s,outSize:i}=t;n||this.variableNames.push("bestIndicesA"),this.outputShape=[s,i];let a=e==="max"?">":"<",u=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 * ${o};

        int bestIndex = inOffset;
        float bestValue = getA(batch, bestIndex);

        for (int i = 0; i < ${o}; i++) {
          int inIdx = ${u};
          float candidate = getA(batch, inIdx);
          if (candidate ${a} bestValue) {
            bestValue = candidate;
            bestIndex = inIdx;
          }
        }
        setOutput(float(bestIndex));
      }
    `}};var ov=class{constructor(t,e,n,o){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,x.assert(t.length>2,()=>`Packed arg${n.charAt(0).toUpperCase()+n.slice(1)} supports only inputs with rank above 2.`);let s=t[t.length-1],i=Math.ceil(s/e);this.outputShape=t.slice(0,-1),i>1&&this.outputShape.push(i),o||this.variableNames.push("bestIndicesA");let a=this.outputShape,u=a.length,l=Wt(u),c=tr("coords",u),p,m;if(i===1){m=u+1;let D=Wt(m);p=`
        ${D} sourceLocR = ${D}(${c.join()}, 0);
        ++${c[u-1]};
        ${D} sourceLocG = ${D}(${c.join()}, 0);
        ++${c[u-2]};
        ${D} sourceLocA = ${D}(${c.join()}, 0);
        --${c[u-1]};
        ${D} sourceLocB = ${D}(${c.join()}, 0);
        --${c[u-2]};`}else m=u,p=`
        ${l} sourceLocR = coords;
        ++${c[u-1]};
        ${l} sourceLocG = coords;
        ++${c[u-2]};
        ${l} sourceLocA = coords;
        --${c[u-1]};
        ${l} sourceLocB = coords;
        --${c[u-2]};`;let f=["x","y","z","w","u","v"].slice(0,m),d="."+f[m-1],h=f.map(D=>"int "+D),g=tr("sourceLocR",m-1).concat("inIdx.r"),y=tr("sourceLocG",m-1).concat("inIdx.g"),b=tr("sourceLocB",m-1).concat("inIdx.b"),w=tr("sourceLocA",m-1).concat("inIdx.a"),v=n==="max"?"greaterThan":"lessThan",N=o?"":`
          inIdx = round(vec4(getBestIndicesAChannel(${g.join()}),
                             getBestIndicesAChannel(${y.join()}),
                             getBestIndicesAChannel(${b.join()}),
                             getBestIndicesAChannel(${w.join()})));`,E=`vec4(
            getAChannel(${g.join()}),
            hasNextCol ? getAChannel(${y.join()}) : 0.,
            hasNextRow ? getAChannel(${b.join()}) : 0.,
            hasNextRow && hasNextCol ? getAChannel(${w.join()}) : 0.)`,$=o?"":`
      float getBestIndicesAChannel(${h.join()}) {
        return getChannel(getBestIndicesA(${f.join()}),
                                          vec2(${f.slice(-2).join()}));
      }`;this.userCode=`
      float getAChannel(${h.join()}) {
        return getChannel(getA(${f.join()}),
                               vec2(${f.slice(-2).join()}));
      }
      ${$}
      void main() {
        ${l} coords = getOutputCoords();
        bool hasNextCol = ${c[u-1]} < ${a[u-1]-1};
        bool hasNextRow = ${c[u-2]} < ${a[u-2]-1};
        ${p}
        ivec4 srcIdx = ivec4(sourceLocR${d}, sourceLocG${d},
          sourceLocB${d}, sourceLocA${d}) * ${e};
        ivec4 inIdx = srcIdx;
        vec4 bestIndex = vec4(inIdx);
        vec4 bestValue = ${E};

        for (int i = 0; i < ${e}; i++) {
          inIdx = srcIdx;
          ${N}
          vec4 candidate = ${E};
          bvec4 nan = isnan(candidate);
          bvec4 replace = bvec4(
            vec4(${v}(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 $M(r,t,e,n=null){let o=t.shape[0],s=t.shape[1];n!=null&&(o=n.shape[0],s=n.shape[1]);let i=S.computeOptimalWindowSize(s),a={windowSize:i,inSize:s,batchSize:o,outSize:Math.ceil(s/i)},u=new nv(a,e,n==null),l=[t];n!=null&&l.push(n);let c=r.runWebGLProgram(u,l,"int32");if(c.shape[1]===1)return c;let p=$M(r,t,e,c);return r.disposeIntermediateTensorInfo(c),p}function DM(r,t,e,n=null){let o=n!=null?n.shape:t.shape,s=o[o.length-1],i=S.computeOptimalWindowSize(s),a=new ov(o,i,e,n==null),u=n==null?[t]:[t,n],l=r.runWebGLProgram(a,u,"int32");if(l.shape.length===t.shape.length){let c=DM(r,t,e,l);return r.disposeIntermediateTensorInfo(l),c}return l}function sv(r,t,e,n){let o=[e];if(S.assertAxesAreInnerMostDims("arg"+n.charAt(0).toUpperCase()+n.slice(1),o,t.shape.length),!B().getBool("WEBGL_PACK_REDUCE")||t.shape.length<=2){let s=[],i=r.texData.get(t.dataId),a=i!==null&&i.isPacked,u=t;a&&(u=r.unpackTensor(t),s.push(u));let[l,c]=S.computeOutAndReduceShapes(u.shape,o),p=x.sizeFromShape(c),m=at({inputs:{x:u},backend:r,attrs:{shape:[-1,p]}});s.push(m);let f=$M(r,m,n);s.push(f);let d=at({inputs:{x:f},backend:r,attrs:{shape:l}});return s.forEach(h=>r.disposeIntermediateTensorInfo(h)),d}return DM(r,t,n)}function pet(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{axis:s}=n,i=x.parseAxisParam(s,o.shape),a=S.getAxesPermutation(i,o.shape.length),u=o,l=[];a!=null&&(u=Pe({inputs:{x:o},backend:e,attrs:{perm:a}}),l.push(u),i=S.getInnerMostAxes(i.length,u.shape.length)),S.assertAxesAreInnerMostDims("argMax",[i[0]],u.shape.length);let c=sv(e,u,i[0],"max");return l.forEach(p=>e.disposeIntermediateTensorInfo(p)),c}var FM={kernelName:jo,backendName:"webgl",kernelFunc:pet};function met(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{axis:s}=n,i=x.parseAxisParam(s,o.shape),a=S.getAxesPermutation(i,o.shape.length),u=o,l=[];a!=null&&(u=Pe({inputs:{x:o},backend:e,attrs:{perm:a}}),l.push(u),i=S.getInnerMostAxes(i.length,u.shape.length)),S.assertAxesAreInnerMostDims("argMin",[i[0]],u.shape.length);let c=sv(e,u,i[0],"min");return l.forEach(p=>e.disposeIntermediateTensorInfo(p)),c}var RM={kernelName:Cl,backendName:"webgl",kernelFunc:met};var fet=fr+`
  if (abs(x) > 1.) {
    return NAN;
  }
  return asin(x);
`,det=It({opSnippet:fet}),OM={kernelName:sa,backendName:"webgl",kernelFunc:det};var het=fr+"return log(x + sqrt(x * x + 1.0));",get=It({opSnippet:het}),LM={kernelName:ia,backendName:"webgl",kernelFunc:get};var xet=fr+`
  return atan(x);
`,yet=It({opSnippet:xet}),PM={kernelName:aa,backendName:"webgl",kernelFunc:yet};var bet=mM+`
  return atan(a, b);
`,wet=`
  vec4 result = atan(a, b);
  vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
  `+fM+`
  return result;
`,vet=ce({opSnippet:bet,packedOpSnippet:wet}),MM={kernelName:ua,backendName:"webgl",kernelFunc:vet};var Cet=fr+`
  if ((x < -1.0) || (x > 1.0)) return NAN;
return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,Iet=It({opSnippet:Cet}),zM={kernelName:la,backendName:"webgl",kernelFunc:Iet};var si=class{constructor(t,e,n,o=!1,s=!1){if(this.variableNames=["x"],e==="avg"&&n)throw new Error("Cannot compute positions for average pool.");let i=t.filterWidth,a=t.strideHeight,u=t.strideWidth,l=t.dilationHeight,c=t.dilationWidth,p=t.effectiveFilterHeight,m=t.effectiveFilterWidth,f=t.padInfo.top,d=t.padInfo.left;this.outputShape=t.outShape;let h=e==="avg",g=`((batch  * ${t.inHeight} + xR) * ${t.inWidth} + xC) * ${t.inChannels} + d`,y=`(xR * ${t.inWidth} + xC) * ${t.inChannels} + d`,b="0.0";if(h||(b="-1.0 / 1e-20"),n){let D=">=";this.userCode=`
        const ivec2 strides = ivec2(${a}, ${u});
        const ivec2 pads = ivec2(${f}, ${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
          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 >= ${t.inHeight}) {
              continue;
            }

            for (int wC = 0; wC < ${m};
                wC += ${c}) {
              int xC = xCCorner + wC;

              if (xC < 0 || xC >= ${t.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 ${D} currMinMaxValue) {
                minMaxValue = value;
                minMaxValueFound = 1.0;
                minMaxPosition = ${o?s?g:y:`wR * ${m} + wC`};
              }
            }
          }
          setOutput(float(minMaxPosition));
        }
      `;return}let w="max",v=`${e}(${e}(${e}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;e==="avg"&&(v="avgValue / count");let N=Math.floor(i/4)*4,E=i%4,$=`
      if (${h}) {
        avgValue += dot(values, ones);
      } else {
        minMaxValue = ${w}(values, minMaxValue);
      }
    `;this.userCode=`
      const ivec2 strides = ivec2(${a}, ${u});
      const ivec2 pads = ivec2(${f}, ${d});
      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 >= ${t.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 >= ${t.inHeight}) {
            continue;
          }

          for (int wC = 0; wC < ${N}; wC += 4) {
            int xC = xCCorner + wC * ${c};

            vec4 values = vec4(
              getValue(batch, xR, xC, d),
              getValue(batch, xR, xC + ${c}, d),
              getValue(batch, xR, xC + 2 * ${c}, d),
              getValue(batch, xR, xC + 3 * ${c}, d)
            );

            ${$}
          }

          int xC = xCCorner + ${N};
          if (${E===1}) {
            vec4 values = vec4(
              getValue(batch, xR, xC, d),
              initializationValue,
              initializationValue,
              initializationValue
            );

            ${$}
          } else if (${E===2}) {
            vec4 values = vec4(
              getValue(batch, xR, xC, d),
              getValue(batch, xR, xC + ${c}, d),
              initializationValue,
              initializationValue
            );

            ${$}
          } else if (${E===3}) {
            vec4 values = vec4(
              getValue(batch, xR, xC, d),
              getValue(batch, xR, xC + ${c}, d),
              getValue(batch, xR, xC + 2 * ${c}, d),
              initializationValue
            );

            ${$}
          }
        }
        setOutput(${v});
      }
    `}},Au=class{constructor(t,e,n,o=!1,s=!1){if(this.variableNames=["x"],e==="avg"&&n)throw new Error("Cannot compute positions for average pool.");let i=t.filterWidth,a=t.strideDepth,u=t.strideHeight,l=t.strideWidth,c=t.dilationDepth,p=t.dilationHeight,m=t.dilationWidth,f=t.effectiveFilterDepth,d=t.effectiveFilterHeight,h=t.effectiveFilterWidth,g=t.padInfo.front,y=t.padInfo.top,b=t.padInfo.left;this.outputShape=t.outShape;let w=e==="avg",v="0.0";if(w||(v="-1.0 / 1e-20"),n){let M=">=";this.userCode=`
        const ivec3 strides =
            ivec3(${a}, ${u}, ${l});
        const ivec3 pads = ivec3(${g}, ${y}, ${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 < ${f};
              wD += ${c}) {
            int xD = xDCorner + wD;

            if (xD < 0 || xD >= ${t.inDepth}) {
              continue;
            }

            for (int wR = 0; wR < ${d};
                wR += ${p}) {
              int xR = xRCorner + wR;

              if (xR < 0 || xR >= ${t.inHeight}) {
                continue;
              }

              for (int wC = 0; wC < ${h};
                  wC += ${m}) {
                int xC = xCCorner + wC;

                if (xC < 0 || xC >= ${t.inWidth}) {
                  continue;
                }

                float value = getX(batch, xD, xR, xC, ch);

                // If a min / max value has already been found, use it. If not,
                // use the current value.
                float currMinMaxValue = mix(
                    value, minMaxValue, minMaxValueFound);
                if (value ${M} currMinMaxValue) {
                  minMaxValue = value;
                  minMaxValueFound = 1.0;
                  minMaxPosition = ${o?s?`(((batch * ${t.inDepth} + xD) * ${t.inHeight} + xR) * ${t.inWidth} + xC) * ${t.inChannels} + ch`:`((xD * ${t.inHeight} + xR) * ${t.inWidth} + xC) * ${t.inChannels} + ch`:`wD * ${d} * ${h} +
                      wR * ${h} + wC`};
                }
              }
            }
          }
          setOutput(float(minMaxPosition));
        }
      `;return}let N="max",E=`${e}(${e}(${e}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;e==="avg"&&(E="avgValue / count");let $=Math.floor(i/4)*4,D=i%4,L=`
      if (${w}) {
        avgValue += dot(values, ones);
      } else {
        minMaxValue = ${N}(values, minMaxValue);
      }
    `;this.userCode=`
      const ivec3 strides =
        ivec3(${a}, ${u}, ${l});
      const ivec3 pads = ivec3(${g}, ${y}, ${b});
      const float initializationValue = ${v};
      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 >= ${t.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(${v});
        float avgValue = 0.0;
        count = 0.0;

        for (int wD = 0; wD < ${f};
            wD += ${c}) {
          int xD = xDCorner + wD;

          if (xD < 0 || xD >= ${t.inDepth}) {
            continue;
          }

          for (int wR = 0; wR < ${d};
            wR += ${p}) {
            int xR = xRCorner + wR;

            if (xR < 0 || xR >= ${t.inHeight}) {
              continue;
            }

            for (int wC = 0; wC < ${$}; wC += 4) {
              int xC = xCCorner + wC * ${m};

              vec4 values = vec4(
                getValue(batch, xD, xR, xC, ch),
                getValue(batch, xD, xR, xC + ${m}, ch),
                getValue(batch, xD, xR, xC + 2 * ${m}, ch),
                getValue(batch, xD, xR, xC + 3 * ${m}, ch)
              );

              ${L}
            }

            int xC = xCCorner + ${$};
            if (${D===1}) {
              vec4 values = vec4(
                getValue(batch, xD, xR, xC, ch),
                initializationValue,
                initializationValue,
                initializationValue
              );

              ${L}
            } else if (${D===2}) {
              vec4 values = vec4(
                getValue(batch, xD, xR, xC, ch),
                getValue(batch, xD, xR, xC + ${m}, ch),
                initializationValue,
                initializationValue
              );

              ${L}
            } else if (${D===3}) {
              vec4 values = vec4(
                getValue(batch, xD, xR, xC, ch),
                getValue(batch, xD, xR, xC + ${m}, ch),
                getValue(batch, xD, xR, xC + 2 * ${m}, ch),
                initializationValue
              );

              ${L}
            }
          }
          setOutput(${E});
        }
      }
    `}};function Net(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t;ni(o,"avgPool");let{filterSize:s,strides:i,pad:a,dimRoundingMode:u}=n,l=1;x.assert(S.eitherStridesOrDilationsAreOne(i,l),()=>`Error in avgPool: Either strides or dilations must be 1. Got strides ${i} and dilations '${l}'`);let c=S.computePool2DInfo(o.shape,s,i,l,a,u);if(c.filterWidth===1&&c.filterHeight===1&&x.arraysEqual(c.inShape,c.outShape))return er({inputs:{x:o},backend:e});let p=new si(c,"avg",!1);return e.runWebGLProgram(p,[o],"float32")}var BM={kernelName:Xo,backendName:"webgl",kernelFunc:Net};function ket(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{filterSize:s,strides:i,pad:a,dimRoundingMode:u,dataFormat:l}=n,c=[1,1,1],p=S.computePool3DInfo(o.shape,s,i,c,a,u,l),m=new Au(p,"avg",!1);return e.runWebGLProgram(m,[o],"float32")}var VM={kernelName:Il,backendName:"webgl",kernelFunc:ket};var iv=class{constructor(t){this.variableNames=["dy"],this.outputShape=t.inShape;let e=t.filterHeight,n=t.filterWidth,o=t.strideHeight,s=t.strideWidth,i=t.dilationHeight,a=t.dilationWidth,u=t.effectiveFilterHeight,l=t.effectiveFilterWidth,c=u-1-t.padInfo.top,p=l-1-t.padInfo.left,m=1/(e*n);this.userCode=`
      const ivec2 pads = ivec2(${c}, ${p});
      const float avgMultiplier = float(${m});

      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 < ${u};
            wR += ${i}) {
          float dyR = float(dyRCorner + wR) / ${o}.0;

          if (dyR < 0.0 || dyR >= ${t.outHeight}.0 || fract(dyR) > 0.0) {
            continue;
          }
          int idyR = int(dyR);

          for (int wC = 0; wC < ${l};
            wC+= ${a}) {
            float dyC = float(dyCCorner + wC) / ${s}.0;

            if (dyC < 0.0 || dyC >= ${t.outWidth}.0 ||
                fract(dyC) > 0.0) {
              continue;
            }
            int idyC = int(dyC);

            float dyValue = getDy(b, idyR, idyC, d);

            dotProd += dyValue * avgMultiplier;
          }
        }
        setOutput(dotProd);
      }
    `}},av=class{constructor(t){this.variableNames=["dy"],this.outputShape=t.inShape;let e=t.filterDepth,n=t.filterHeight,o=t.filterWidth,s=t.strideDepth,i=t.strideHeight,a=t.strideWidth,u=t.dilationDepth,l=t.dilationHeight,c=t.dilationWidth,p=t.effectiveFilterDepth,m=t.effectiveFilterHeight,f=t.effectiveFilterWidth,d=p-1-t.padInfo.front,h=m-1-t.padInfo.top,g=f-1-t.padInfo.left,y=1/(e*n*o);this.userCode=`
      const ivec3 pads = ivec3(${d}, ${h}, ${g});
      const float avgMultiplier = float(${y});

      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 += ${u}) {
          float dyD = float(dyDCorner + wD) / ${s}.0;

          if (dyD < 0.0 || dyD >= ${t.outDepth}.0 || fract(dyD) > 0.0) {
            continue;
          }
          int idyD = int(dyD);

          for (int wR = 0; wR < ${m};
              wR += ${l}) {
            float dyR = float(dyRCorner + wR) / ${i}.0;

            if (dyR < 0.0 || dyR >= ${t.outHeight}.0 ||
                fract(dyR) > 0.0) {
              continue;
            }
            int idyR = int(dyR);

            for (int wC = 0; wC < ${f};
                wC += ${c}) {
              float dyC = float(dyCCorner + wC) / ${a}.0;

              if (dyC < 0.0 || dyC >= ${t.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 Tet(r){let{inputs:t,backend:e,attrs:n}=r,{dy:o,input:s}=t,i=s,{filterSize:a,strides:u,pad:l,dimRoundingMode:c}=n,p=[1,1,1],m=S.computePool3DInfo(i.shape,a,u,p,l,c),f=new av(m);return e.runWebGLProgram(f,[o],i.dtype)}var GM={kernelName:vp,backendName:"webgl",kernelFunc:Tet};function _et(r){let{inputs:t,backend:e,attrs:n}=r,{dy:o,input:s}=t,i=s;ni([o,s],"avgPoolGrad");let{filterSize:a,strides:u,pad:l}=n,c=S.computePool2DInfo(i.shape,a,u,1,l),p=new iv(c);return e.runWebGLProgram(p,[o],i.dtype)}var WM={kernelName:wp,backendName:"webgl",kernelFunc:_et};function Eet(r){let{inputs:t,backend:e,attrs:n}=r,{a:o,b:s}=t,{transposeA:i,transposeB:a}=n;return Yc({a:o,b:s,transposeA:i,transposeB:a,backend:e})}var UM={kernelName:Yo,backendName:"webgl",kernelFunc:Eet};var lv=class{constructor(t,e,n,o,s,i){this.outputShape=[],this.variableNames=["x","mean","variance"],S.assertAndGetBroadcastShape(t,e),S.assertAndGetBroadcastShape(t,n);let a="0.0";o!=null&&(S.assertAndGetBroadcastShape(t,o),this.variableNames.push("offset"),a="getOffsetAtOutCoords()");let u="1.0";s!=null&&(S.assertAndGetBroadcastShape(t,s),this.variableNames.push("scale"),u="getScaleAtOutCoords()"),this.outputShape=t,this.userCode=`
      void main() {
        float x = getXAtOutCoords();
        float mean = getMeanAtOutCoords();
        float variance = getVarianceAtOutCoords();
        float offset = ${a};
        float scale = ${u};
        float inv = scale * inversesqrt(variance + float(${i}));
        setOutput(dot(vec3(x, -mean, offset), vec3(inv, inv, 1)));
      }
    `}};var uv=class{constructor(t,e,n,o,s,i){this.packedInputs=!0,this.packedOutput=!0,this.variableNames=["x","mean","variance"],S.assertAndGetBroadcastShape(t,e),S.assertAndGetBroadcastShape(t,n);let a="vec4(0.0)";o!=null&&(S.assertAndGetBroadcastShape(t,o),this.variableNames.push("offset"),a="getOffsetAtOutCoords()");let u="vec4(1.0)";s!=null&&(S.assertAndGetBroadcastShape(t,s),this.variableNames.push("scale"),u="getScaleAtOutCoords()"),this.outputShape=t,this.userCode=`
      void main() {
        vec4 offset = ${a};
        vec4 scale = ${u};

        vec4 x = getXAtOutCoords();
        vec4 mean = getMeanAtOutCoords();
        vec4 variance = getVarianceAtOutCoords();

        vec4 inv = scale * inversesqrt(variance + vec4(${i}));

        setOutput((x - mean) * inv + offset);
      }
    `}};var Aet=({inputs:r,backend:t,attrs:e})=>{let{x:n,mean:o,variance:s,offset:i,scale:a}=r;x.assert(o.shape.length===s.shape.length,()=>"Batch normalization gradient requires mean and variance to have equal ranks."),x.assert(i==null||o.shape.length===i.shape.length,()=>"Batch normalization gradient requires mean and offset to have equal ranks."),x.assert(a==null||o.shape.length===a.shape.length,()=>"Batch normalization gradient requires mean and scale to have equal ranks.");let{varianceEpsilon:u}=e;u==null&&(u=.001);let l=[n,o,s],c=null;i!=null&&(c=i.shape,l.push(i));let p=null;a!=null&&(p=a.shape,l.push(a));let m=B().getBool("WEBGL_PACK_NORMALIZATION")?new uv(n.shape,o.shape,s.shape,c,p,u):new lv(n.shape,o.shape,s.shape,c,p,u);return t.runWebGLProgram(m,l,l[0].dtype)},HM={kernelName:us,backendName:"webgl",kernelFunc:Aet};var cv=class{constructor(t){this.variableNames=["source"],this.outputShape=t,this.rank=t.length;let e=Wt(this.rank);this.customUniforms=[{name:"start",arrayIndex:this.rank,type:"int"}];let n=$et(this.rank),o,s=t.map((i,a)=>`sourceLoc.${bT[a]} = start[${a}] + coords.${bT[a]};`);o=`
        ${e} sourceLoc;
        ${e} coords = getOutputCoords();
        ${s.join(`
`)}
      `,this.userCode=`
      void main() {
        ${o}
        setOutput(getSource(${n}));
      }
    `}},bT=["x","y","z","w","u","v"];function $et(r){if(r===1)return"sourceLoc";if(r<=6)return bT.slice(0,r).map(t=>"sourceLoc."+t).join(",");throw Error(`Slicing for rank ${r} is not yet supported`)}var pv=class{constructor(t){this.variableNames=["source"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t,this.rank=t.length,this.customUniforms=[{name:"start",arrayIndex:this.rank,type:"int"}];let e=Wt(this.rank),n=tr("coords",this.rank),o=tr("sourceLoc",this.rank),s=this.rank===1?"sourceLoc":`vec2(${o.slice(-2).join()})`,i=`getChannel(getSource(${o.join()}), ${s})`,a=`
      result.x = ${i};
      if (++${n[this.rank-1]} < ${t[this.rank-1]}) {
        ++${o[this.rank-1]};
        result.y = ${i};
        --${o[this.rank-1]};
      }
    `,u=this.rank===1?"":`
      --${n[this.rank-1]};
      if (++${n[this.rank-2]} < ${t[this.rank-2]}) {
        ++${o[this.rank-2]};
        result.z = ${i};
        if (++${n[this.rank-1]} < ${t[this.rank-1]}) {
          ++${o[this.rank-1]};
          result.w = ${i};
        }
      }
    `,l=this.rank<=4?`sourceLoc = coords +
            ${e}(${t.map((c,p)=>`start[${p}]`).join()});`:t.map((c,p)=>`${o[p]} = ${n[p]} + start[${p}];`).join(`
`);this.userCode=`
      void main() {
        ${e} coords = getOutputCoords();
        ${e} sourceLoc;
        ${l}
        vec4 result = vec4(0.);
        ${a}
        ${u}
        setOutput(result);
      }
    `}};function Det(r,t,e,n){let o=n.texData.get(r.dataId),s=n.makeTensorInfo(e,r.dtype),i=n.texData.get(s.dataId);Object.assign(i,o),i.refCount=1,i.shape=e,i.dtype=r.dtype;let a=Be.computeFlatOffset(t,x.computeStrides(r.shape));o.slice&&(a+=o.slice.flatOffset),i.slice={flatOffset:a,origDataId:o.slice&&o.slice.origDataId||r.dataId};let u=n.dataRefCount.get(i.slice.origDataId)||1;return n.dataRefCount.set(i.slice.origDataId,u+1),s}function ii(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{begin:s,size:i}=n,[a,u]=Be.parseSliceParams(o,s,i);if(Be.assertParamsValid(o,a,u),x.sizeFromShape(u)===0)return e.makeTensorInfo(u,o.dtype,[]);if(e.shouldExecuteOnCPU([o])||o.dtype==="string"){let p=e.texData.get(o.dataId),m=FP(p.values,a,u,o.shape,o.dtype);return e.makeTensorInfo(u,o.dtype,m)}let{isPacked:l}=e.texData.get(o.dataId),c=Be.isSliceContinous(o.shape,a,u);if(l||!c){let p=B().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new pv(u):new cv(u),m=[a];return e.runWebGLProgram(p,[o],o.dtype,m)}return e.uploadToGPU(o.dataId),Det(o,a,u,e)}var qM={kernelName:wi,backendName:"webgl",kernelFunc:ii};var Fet=r=>{let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{blockShape:s,crops:i}=n;x.assert(o.shape.length<=4,()=>"batchToSpaceND for rank > 4 with a WebGL backend not implemented yet");let a=s.reduce((b,w)=>b*w),u=S.getReshaped(o.shape,s,a),l=S.getPermuted(u.length,s.length),c=S.getReshapedPermuted(o.shape,s,a),p=S.getSliceBeginCoords(i,s.length),m=S.getSliceSize(c,i,s.length),f=[],d=at({inputs:{x:o},backend:e,attrs:{shape:u}}),h=Pe({inputs:{x:d},backend:e,attrs:{perm:l}}),g=at({inputs:{x:h},backend:e,attrs:{shape:c}}),y=ii({inputs:{x:g},backend:e,attrs:{begin:p,size:m}});return f.push(d),f.push(h),f.push(g),f.forEach(b=>e.disposeIntermediateTensorInfo(b)),y},KM={kernelName:pi,backendName:"webgl",kernelFunc:Fet};function Ret(r){let{inputs:t,backend:e,attrs:n}=r,{x:o,weights:s}=t,{size:i}=n,a=e.readSync(o.dataId),u=e.readSync(s.dataId),l=Ww(a,u,s.dtype,s.shape,i);return e.makeTensorInfo([i],s.dtype,l)}var jM={kernelName:Cp,backendName:"webgl",kernelFunc:Ret};function Oet(r){let{inputs:t,backend:e}=r,{s0:n,s1:o}=t,s=e.readSync(n.dataId),i=e.readSync(o.dataId),a=S.assertAndGetBroadcastShape(Array.from(s),Array.from(i));return e.makeTensorInfo([a.length],"int32",Int32Array.from(a))}var XM={kernelName:Ip,backendName:"webgl",kernelFunc:Oet};var Let="return float(a != b);",wT=ce({opSnippet:Let,cpuKernelImpl:TP,dtype:"bool"}),YM={kernelName:Ea,backendName:"webgl",kernelFunc:wT};function hl(r){let{inputs:t,backend:e}=r,{input:n}=t,o=e.texData.get(n.dataId);return er({inputs:{x:o.complexTensorInfos.real},backend:e})}var ZM={kernelName:Wp,backendName:"webgl",kernelFunc:hl};var Pet="return float(int(x));";function JM(r,t){let e=new Zr(r.shape,Pet),n=t.runWebGLProgram(e,[r],"int32");return{dataId:n.dataId,shape:n.shape,dtype:n.dtype}}function vT(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{dtype:s}=n;if(s==="complex64"){if(o.dtype==="complex64")return er({inputs:{x:o},backend:e});let i=Te(o.shape),a=vT({inputs:{x:o},backend:e,attrs:{dtype:"float32"}}),u=An({inputs:{real:a,imag:i},backend:e});return i.dispose(),e.disposeIntermediateTensorInfo(a),u}if(o.dtype==="complex64"){let i=hl({inputs:{input:o},backend:e}),a=vT({inputs:{x:i},backend:e,attrs:{dtype:s}});return e.disposeIntermediateTensorInfo(i),a}if(!x.hasEncodingLoss(o.dtype,s)){let i=er({inputs:{x:o},backend:e});return{dataId:i.dataId,shape:i.shape,dtype:s}}if(s==="int32")return JM(o,e);if(s==="bool"){let i=e.makeTensorInfo([],"bool",x.getTypedArrayFromDType("bool",1)),u=wT({inputs:{a:o,b:i},backend:e});return e.disposeIntermediateTensorInfo(i),u}throw new Error(`Error in Cast: failed to cast ${o.dtype} to ${s}`)}var QM={kernelName:io,backendName:"webgl",kernelFunc:vT};var tz="return ceil(x);",Met=It({opSnippet:tz,packedOpSnippet:tz,cpuKernelImpl:lP}),ez={kernelName:Zo,backendName:"webgl",kernelFunc:Met};var mv=class{constructor(t){this.variableNames=["A"],this.customUniforms=[{name:"minVal",type:"float"},{name:"maxVal",type:"float"}],this.outputShape=t,this.userCode=`

      void main() {
        float value = getAAtOutCoords();
        if (isnan(value)) {
          setOutput(value);
          return;
        }

        setOutput(clamp(value, minVal, maxVal));
      }
    `}};var fv=class{constructor(t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"minVal",type:"float"},{name:"maxVal",type:"float"}],this.outputShape=t,this.userCode=`
      void main() {
        vec4 value = getAAtOutCoords();

        if (any(isnan(value))) {
          setOutput(value);
          return;
        }

        setOutput(clamp(value, vec4(minVal), vec4(maxVal)));
      }
    `}};function zet(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{clipValueMin:s,clipValueMax:i}=n,a;B().getBool("WEBGL_PACK_CLIP")?a=new fv(o.shape):a=new mv(o.shape);let u=[[s],[i]];return e.runWebGLProgram(a,[o],o.dtype,u)}var rz={kernelName:ao,backendName:"webgl",kernelFunc:zet};var dv=class{constructor(t){this.variableNames=["real","imag"],this.outputShape=t,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 nz(r,t){return{dataId:t.dataId,dtype:t.dtype,shape:r.shape}}function Bet(r){let{inputs:t,backend:e}=r,{x:n}=t,o=e.texData.get(n.dataId),s=new dv(n.shape),i=[nz(n,o.complexTensorInfos.real),nz(n,o.complexTensorInfos.imag)];return e.runWebGLProgram(s,i,i[0].dtype)}var oz={kernelName:Sl,backendName:"webgl",kernelFunc:Bet};var hv=class{constructor(t){this.outputShape=[],this.outputShape=S.computeOutShape(t,1),this.variableNames=t.map((i,a)=>`T${a}`);let e=new Array(t.length-1);e[0]=t[0][1];for(let i=1;i<e.length;i++)e[i]=e[i-1]+t[i][1];let n=[`if (yC < ${e[0]}) setOutput(getT0(yR, yC));`];for(let i=1;i<e.length;i++){let a=e[i-1];n.push(`else if (yC < ${e[i]}) setOutput(getT${i}(yR, yC-${a}));`)}let o=e.length,s=e[e.length-1];n.push(`else setOutput(getT${o}(yR, yC-${s}));`),this.userCode=`
      void main() {
        ivec2 coords = getOutputCoords();
        int yR = coords.x;
        int yC = coords.y;

        ${n.join(`
        `)}
      }
    `}};var xv=class{constructor(t,e){this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[],this.outputShape=S.computeOutShape(t,e);let n=this.outputShape,o=n.length,s=Wt(o),i=tr("coords",o),a=["x","y","z","w","u","v"].slice(0,o);this.variableNames=t.map((h,g)=>`T${g}`);let u=new Array(t.length-1);u[0]=t[0][e];for(let h=1;h<u.length;h++)u[h]=u[h-1]+t[h][e];let l=a[e],c=a.slice(-2),p=a.join(),m=`if (${l} < ${u[0]}) {
        return getChannel(
            getT0(${p}), vec2(${c.join()}));
        }`;for(let h=1;h<u.length;h++){let g=u[h-1];m+=`
        if (${l} < ${u[h]}  && ${l} >= ${u[h-1]}) {
          return getChannel(
            getT${h}(${gv(a,l,g)}),
            vec2(${gv(c,l,g)}));
        }`}let f=u.length,d=u[u.length-1];m+=`
        return getChannel(
          getT${f}(${gv(a,l,d)}),
          vec2(${gv(c,l,d)}));`,this.userCode=`
      float getValue(${a.map(h=>"int "+h)}) {
        ${m}
      }

      void main() {
        ${s} coords = getOutputCoords();
        vec4 result = vec4(getValue(${i}), 0., 0., 0.);

        ${i[o-1]} = ${i[o-1]} + 1;
        if (${i[o-1]} < ${n[o-1]}) {
          result.g = getValue(${i});
        }

        ${i[o-2]} = ${i[o-2]} + 1;
        if (${i[o-2]} < ${n[o-2]}) {
          result.a = getValue(${i});
        }

        ${i[o-1]} = ${i[o-1]} - 1;
        if (${i[o-2]} < ${n[o-2]} &&
            ${i[o-1]} < ${n[o-1]}) {
          result.b = getValue(${i});
        }
        setOutput(result);
      }
    `}};function gv(r,t,e){let n=r.indexOf(t);return r.map((s,i)=>i===n?`${s} - ${e}`:s).join()}function Zc(r){let{inputs:t,backend:e}=r,{input:n}=t,o=e.texData.get(n.dataId);return er({inputs:{x:o.complexTensorInfos.imag},backend:e})}var sz={kernelName:Lp,backendName:"webgl",kernelFunc:Zc};function Ed(r,t,e){let n=r[0].dtype;if(n==="complex64"){let p=r.map(g=>hl({inputs:{input:g},backend:e})),m=r.map(g=>Zc({inputs:{input:g},backend:e})),f=Ed(p,t,e),d=Ed(m,t,e),h=An({inputs:{real:f,imag:d},backend:e});return p.forEach(g=>e.disposeIntermediateTensorInfo(g)),m.forEach(g=>e.disposeIntermediateTensorInfo(g)),e.disposeIntermediateTensorInfo(f),e.disposeIntermediateTensorInfo(d),h}let o=e.shouldExecuteOnCPU(r);if(n==="string"&&(o=!0),o){let p=r.map(b=>{let w=x.sizeFromShape(b.shape.slice(t));return at({inputs:{x:b},backend:e,attrs:{shape:[-1,w]}})}),m=p.map(b=>({vals:e.readSync(b.dataId),shape:b.shape})),f=S.computeOutShape(p.map(b=>b.shape),1),d=p[0].shape[0]===1,h=uP(m,f,n,d),g=S.computeOutShape(r.map(b=>b.shape),t),y=e.makeTensorInfo(g,n,h);return p.forEach(b=>e.disposeIntermediateTensorInfo(b)),y}let s=B().getNumber("WEBGL_MAX_TEXTURES_IN_SHADER");if(r.length>s){let p=[];for(let f=0;f<r.length;f+=s){let d=r.slice(f,f+s);p.push(Ed(d,t,e))}let m=Ed(p,t,e);for(let f of p)e.disposeIntermediateTensorInfo(f);return m}if(B().getBool("WEBGL_PACK_ARRAY_OPERATIONS")&&r[0].shape.length>1){let p=new xv(r.map(m=>m.shape),t);return e.runWebGLProgram(p,r,n)}let{tensors2D:i,outShape:a}=Vet(r,t,e),u=new hv(i.map(p=>p.shape)),l=e.runWebGLProgram(u,i,n);i.forEach(p=>e.disposeIntermediateTensorInfo(p));let c=at({inputs:{x:l},attrs:{shape:a},backend:e});return e.disposeIntermediateTensorInfo(l),c}function Vet(r,t,e){let n=S.computeOutShape(r.map(s=>s.shape),t);return{tensors2D:r.map(s=>at({inputs:{x:s},attrs:{shape:[-1,x.sizeFromShape(s.shape.slice(t))]},backend:e})),outShape:n}}function CT(r){let{inputs:t,backend:e,attrs:n}=r,{axis:o}=n,s=x.parseAxisParam(o,t[0].shape)[0],i=S.computeOutShape(t.map(l=>l.shape),s);if(x.sizeFromShape(i)===0)return e.makeTensorInfo(i,t[0].dtype,[]);let a=t.filter(l=>x.sizeFromShape(l.shape)>0);if(a.length===1)return er({inputs:{x:a[0]},backend:e});let u=a.map(l=>l.shape);return S.assertParamsConsistent(u,s),Ed(a,s,e)}var iz={kernelName:mi,backendName:"webgl",kernelFunc:CT};var Ad=class{constructor(t,e=!1,n=null,o=!1,s=!1){this.variableNames=["x","W"],this.outputShape=t.outShape;let i=t.padInfo.top,a=t.padInfo.left,u=t.strideHeight,l=t.strideWidth,c=t.dilationHeight,p=t.dilationWidth,m=t.filterHeight,f=t.filterWidth,d=Math.floor(t.inChannels/4)*4,h=t.inChannels%4,g=t.dataFormat==="channelsLast",y=g?1:2,b=g?2:3,w=g?3:1,v="",N="";n&&(o?v=`float activation(float a) {
          float b = getPreluActivationWeightsAtOutCoords();
          ${n}
        }`:s?v=`float activation(float a) {
          float b = getLeakyreluAlphaAtOutCoords();
          ${n}
        }`:v=`
          float activation(float x) {
            ${n}
          }
        `,N="result = activation(result);");let E=e?"result += getBiasAtOutCoords();":"";e&&this.variableNames.push("bias"),o&&this.variableNames.push("preluActivationWeights"),s&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
      ${v}

      const ivec2 strides = ivec2(${u}, ${l});
      const ivec2 pads = ivec2(${i}, ${a});

      void main() {
        ivec4 coords = getOutputCoords();
        int batch = coords[0];
        int d2 = coords[${w}];

        ivec2 xRCCorner =
            ivec2(coords[${y}], coords[${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 < ${m}; wR++) {
          int xR = xRCorner + wR * ${c};

          if (xR < 0 || xR >= ${t.inHeight}) {
            continue;
          }

          for (int wC = 0; wC < ${f}; wC++) {
            int xC = xCCorner + wC * ${p};

            if (xC < 0 || xC >= ${t.inWidth}) {
              continue;
            }

            for (int d1 = 0; d1 < ${d}; 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 (${g}) {
                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 (${h===1}) {

              if (${g}) {
                dotProd +=
                    getX(batch, xR, xC, ${d}) *
                    getW(wR, wC, ${d}, d2);
              } else {
                dotProd +=
                    getX(batch, ${d}, xR, xC) *
                    getW(wR, wC, ${d}, d2);
              }

            } else if (${h===2}) {
              vec2 wValues = vec2(
                getW(wR, wC, ${d}, d2),
                getW(wR, wC, ${d} + 1, d2)
              );

              if (${g}) {
                vec2 xValues = vec2(
                  getX(batch, xR, xC, ${d}),
                  getX(batch, xR, xC, ${d} + 1)
                );
                dotProd += dot(xValues, wValues);
              } else {
                vec2 xValues = vec2(
                  getX(batch, ${d}, xR, xC),
                  getX(batch, ${d} + 1, xR, xC)
                );
                dotProd += dot(xValues, wValues);
              }

            } else if (${h===3}) {
              vec3 wValues = vec3(
                getW(wR, wC, ${d}, d2),
                getW(wR, wC, ${d} + 1, d2),
                getW(wR, wC, ${d} + 2, d2)
              );

              if (${g}) {
                vec3 xValues = vec3(
                  getX(batch, xR, xC, ${d}),
                  getX(batch, xR, xC, ${d} + 1),
                  getX(batch, xR, xC, ${d} + 2)
                );
                dotProd += dot(xValues, wValues);
              } else {
                vec3 xValues = vec3(
                  getX(batch, ${d}, xR, xC),
                  getX(batch, ${d} + 1, xR, xC),
                  getX(batch, ${d} + 2, xR, xC)
                );
                dotProd += dot(xValues, wValues);
              }

            }
          }
        }

        float result = dotProd;
        ${E}
        ${N}
        setOutput(result);
      }
    `}},yv=class{constructor(t){this.variableNames=["x","W"],this.outputShape=t.outShape;let e=t.padInfo.front,n=t.padInfo.top,o=t.padInfo.left,s=t.strideDepth,i=t.strideHeight,a=t.strideWidth,u=t.dilationDepth,l=t.dilationHeight,c=t.dilationWidth,p=t.filterDepth,m=t.filterHeight,f=t.filterWidth,d=Math.floor(t.inChannels/4)*4,h=t.inChannels%4;this.userCode=`
      const ivec3 strides = ivec3(${s}, ${i}, ${a});
      const ivec3 pads = ivec3(${e}, ${n}, ${o});

      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 * ${u};

          if (xF < 0 || xF >= ${t.inDepth}) {
            continue;
          }

          for (int wR = 0; wR < ${m}; wR++) {
            int xR = xRCorner + wR * ${l};

            if (xR < 0 || xR >= ${t.inHeight}) {
              continue;
            }

            for (int wC = 0; wC < ${f}; wC++) {
              int xC = xCCorner + wC * ${c};

              if (xC < 0 || xC >= ${t.inWidth}) {
                continue;
              }

              for (int d1 = 0; d1 < ${d}; 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 (${h===1}) {
                dotProd +=
                  getX(batch, xF, xR, xC, ${d}) *
                  getW(wF, wR, wC, ${d}, d2);
              } else if (${h===2}) {
                vec2 xValues = vec2(
                  getX(batch, xF, xR, xC, ${d}),
                  getX(batch, xF, xR, xC, ${d} + 1)
                );
                vec2 wValues = vec2(
                  getW(wF, wR, wC, ${d}, d2),
                  getW(wF, wR, wC, ${d} + 1, d2)
                );
                dotProd += dot(xValues, wValues);
              } else if (${h===3}) {
                vec3 xValues = vec3(
                  getX(batch, xF, xR, xC, ${d}),
                  getX(batch, xF, xR, xC, ${d} + 1),
                  getX(batch, xF, xR, xC, ${d} + 2)
                );
                vec3 wValues = vec3(
                  getW(wF, wR, wC, ${d}, d2),
                  getW(wF, wR, wC, ${d} + 1, d2),
                  getW(wF, wR, wC, ${d} + 2, d2)
                );
                dotProd += dot(xValues, wValues);
              }
            }
          }
        }
        setOutput(dotProd);
      }
    `}};var bv=class{constructor(t,e){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=t,this.enableShapeUniforms=De(this.outputShape.length);let{dataFormat:n}=e,o=He(),s=n==="channelsLast",i=s?1:2,a=s?2:3,u=this.enableShapeUniforms?"if(blockIndex < outShape[2] && pos < outShape[1]) {":`if(blockIndex < ${t[2]} && pos < ${t[1]}) {`,l="";for(let c=0;c<=1;c++)for(let p=0;p<=1;p++)l+=`
          blockIndex = rc.z + ${p};
          pos = rc.y + ${c};

          ${u}
            offsetY = int(blockIndex / outWidth) * stride[0] - pad[0];
            d0 = offsetY + dilation[0] * (pos / itemsPerBlockRow);

            if(d0 < inputShape[${i}] && 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[${a}] && d1 >= 0) {

                ch = imod(pos, inChannels);

                if (${s}) {
                  innerDims = vec2(d1, ch);
                  result[${c*2+p}] = getChannel(
                    getA(rc.x, d0, int(innerDims.x),
                    int(innerDims.y)), innerDims);
                } else {
                  innerDims = vec2(d0, d1);
                  result[${c*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}

        ${o.output} = result;
      }
    `}};function wv(r,t){let e=r.length;return e>=3?t?[...r.slice(0,-3),r[e-3]*r[e-2],r[e-1]]:[...r.slice(0,-3),r[e-3],r[e-2]*r[e-1]]:!t&&e===1&&r[0]>1?[r[0],1]:null}function vv({x:r,filter:t,convInfo:e,backend:n,bias:o=null,preluActivationWeights:s=null,leakyreluAlpha:i=0,activation:a=null}){let u=r.shape,l=n.texData.get(r.dataId),c=e.inChannels,p=u[0]*u[1]*u[2],m=e.outChannels,f=e.dataFormat==="channelsLast",d=!1,h=!1,g,y=[];if(s!=null){let v=wv(s.shape,f);v!=null&&(s=at({inputs:{x:s},backend:n,attrs:{shape:v}}),y.push(s))}if(o!=null){let v=wv(o.shape,f);v!=null&&(o=at({inputs:{x:o},backend:n,attrs:{shape:v}}),y.push(o))}if(!((p===1||m===1)&&c>yT)&&l.isPacked&&f&&l.texture!=null&&u[2]%2!==0&&x.arraysEqual(l.shape.slice(-3),u.slice(-3))){let v=u[0]*u[1]*(u[2]+1),N={dataId:r.dataId,shape:[1,v,e.inChannels],dtype:r.dtype},E=l.shape;l.shape=l.shape.slice(),l.shape[l.shape.length-2]++,x.assert(Nu(l.shape,N.shape),()=>`packed reshape ${l.shape} to ${N.shape} isn't free`);let $=at({inputs:{x:t},backend:n,attrs:{shape:[1,e.inChannels,e.outChannels]}});y.push($);let D=Yc({a:N,b:$,backend:n,transposeA:d,transposeB:h,bias:o,activation:a,preluActivationWeights:s,leakyreluAlpha:i}),L=n.texData.get(D.dataId);x.assert(L.isPacked,()=>"batchMatMul result is expected to be packed"),l.shape=E,L.shape=e.outShape,g=er({inputs:{x:D},backend:n}),g.shape=e.outShape,y.push(D)}else{let v=e.outHeight*e.outWidth,N=at({inputs:{x:r},backend:n,attrs:{shape:f?[e.batchSize,v,e.inChannels]:[e.batchSize,e.inChannels,v]}}),E=at({inputs:{x:t},backend:n,attrs:{shape:[1,e.inChannels,e.outChannels]}}),$=Yc({a:f?N:E,b:f?E:N,transposeA:!f,transposeB:h,backend:n,bias:o,activation:a,preluActivationWeights:s,leakyreluAlpha:i});g=at({inputs:{x:$},backend:n,attrs:{shape:e.outShape}}),y.push(N),y.push(E),y.push($)}for(let v of y)n.disposeIntermediateTensorInfo(v);return g}function Cv({x:r,filter:t,convInfo:e,backend:n,bias:o=null,preluActivationWeights:s=null,leakyreluAlpha:i=0,activation:a=null}){let{filterWidth:u,filterHeight:l,inChannels:c,outWidth:p,outHeight:m,dataFormat:f}=e,d=f==="channelsLast",h=u*l*c,g=m*p,y=[e.batchSize,h,g],b=!0,w=!1,v=[];if(s!=null){let K=wv(s.shape,d);K!=null&&(s=at({inputs:{x:s},backend:n,attrs:{shape:K}}),v.push(s))}if(o!=null){let K=wv(o.shape,d);K!=null&&(o=at({inputs:{x:o},backend:n,attrs:{shape:K}}),v.push(o))}let N=at({inputs:{x:t},backend:n,attrs:{shape:[1,h,x.sizeFromShape(t.shape)/h]}});v.push(N);let E=new bv(y,e),$=[r.shape,[e.padInfo.top,e.padInfo.left],[e.strideHeight,e.strideWidth],[e.dilationHeight,e.dilationWidth],[e.inChannels],[e.filterWidth*e.inChannels],[e.outWidth]],D=n.runWebGLProgram(E,[r],"float32",$),L=at({inputs:{x:D},backend:n,attrs:{shape:y}});v.push(D),v.push(L);let M=o!=null,G=s!=null,H=a==="leakyrelu",q=a?_u(a,!0):null,X=new _d(d?L.shape:N.shape,d?N.shape:L.shape,d?[e.batchSize,g,e.outChannels]:[e.batchSize,e.outChannels,g],b,w,M,q,G,H),j=d?[L,N]:[N,L];if(o&&j.push(o),G&&j.push(s),H){let K=n.makeTensorInfo([],"float32",x.createScalarValue(i,"float32"));j.push(K),v.push(K)}let J=n.runWebGLProgram(X,j,"float32"),nt=at({inputs:{x:J},backend:n,attrs:{shape:e.outShape}});v.push(J);for(let K of v)n.disposeIntermediateTensorInfo(K);return nt}function Get(r){let{inputs:t,backend:e,attrs:n}=r,{x:o,filter:s}=t,{strides:i,pad:a,dataFormat:u,dilations:l,dimRoundingMode:c}=n,p=S.convertConv2DDataFormat(u),m=S.computeConv2DInfo(o.shape,s.shape,i,l,a,c,!1,p),f;if(m.filterHeight===1&&m.filterWidth===1&&m.dilationHeight===1&&m.dilationWidth===1&&m.strideHeight===1&&m.strideWidth===1&&(m.padInfo.type==="SAME"||m.padInfo.type==="VALID"))f=vv({x:o,filter:s,convInfo:m,backend:e});else if(B().getBool("WEBGL_CONV_IM2COL"))f=Cv({x:o,filter:s,convInfo:m,backend:e});else{let h=new Ad(m);f=e.runWebGLProgram(h,[o,s],"float32")}let d=at({inputs:{x:f},backend:e,attrs:{shape:m.outShape}});return e.disposeIntermediateTensorInfo(f),d}var az={kernelName:Jo,backendName:"webgl",kernelFunc:Get};var Iv=class{constructor(t){this.variableNames=["x","dy"],this.outputShape=t.filterShape;let e=t.strideHeight,n=t.strideWidth,o=t.padInfo.top,s=t.padInfo.left,i=t.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 < ${t.batchSize}; b++) {
          for (int yR = 0; yR < ${t.outHeight}; yR++) {
            int xR = wR + yR * ${e} - ${o};

            if (xR < 0 || xR >= ${t.inHeight}) {
              continue;
            }

            for (int yC = 0; yC < ${t.outWidth}; yC++) {
              int xC = wC + yC * ${n} - ${s};

              if (xC < 0 || xC >= ${t.inWidth}) {
                continue;
              }

              if (${i}) {
                float dyValue = getDy(b, yR, yC, d2);
                float xValue = getX(b, xR, xC, d1);
                dotProd += (xValue * dyValue);
              } else {
                float dyValue = getDy(b, d2, yR, yC);
                float xValue = getX(b, d1, xR, xC);
                dotProd += (xValue * dyValue);
              }

            }
          }
        }
        setOutput(dotProd);
      }
    `}},Sv=class{constructor(t){this.variableNames=["dy","W"],this.outputShape=t.inShape;let e=t.filterHeight,n=t.filterWidth,o=t.strideHeight,s=t.strideWidth,i=t.dataFormat==="channelsLast",a=e-1-t.padInfo.top,u=n-1-t.padInfo.left,l=i?1:2,c=i?2:3,p=i?3:1;this.userCode=`
      const ivec2 pads = ivec2(${a}, ${u});

      void main() {
        ivec4 coords = getOutputCoords();
        int batch = coords[0];
        int d1 = coords[${p}];

        ivec2 dyCorner = ivec2(coords[${l}], coords[${c}]) - 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 < ${e}; wR++) {
          float dyR = float(dyRCorner + wR) / ${o}.0;

          if (dyR < 0.0 || dyR >= ${t.outHeight}.0 || fract(dyR) > 0.0) {
            continue;
          }
          int idyR = int(dyR);

          int wRPerm = ${e} - 1 - wR;

          for (int wC = 0; wC < ${n}; wC++) {
            float dyC = float(dyCCorner + wC) / ${s}.0;

            if (dyC < 0.0 || dyC >= ${t.outWidth}.0 ||
                fract(dyC) > 0.0) {
              continue;
            }
            int idyC = int(dyC);

            int wCPerm = ${n} - 1 - wC;

            for (int d2 = 0; d2 < ${t.outChannels}; d2++) {

              if (${i}) {
                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);
      }
    `}},Nv=class{constructor(t){this.variableNames=["x","dy"],this.outputShape=t.filterShape;let e=t.strideDepth,n=t.strideHeight,o=t.strideWidth,s=t.padInfo.front,i=t.padInfo.top,a=t.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 < ${t.batchSize}; b++) {
          for (int yF = 0; yF < ${t.outDepth}; yF++) {
            int xF = wF + yF * ${e} - ${s};

            if (xF < 0 || xF >= ${t.inDepth}) {
              continue;
            }

            for (int yR = 0; yR < ${t.outHeight}; yR++) {
              int xR = wR + yR * ${n} - ${i};

              if (xR < 0 || xR >= ${t.inHeight}) {
                continue;
              }

              for (int yC = 0; yC < ${t.outWidth}; yC++) {
                int xC = wC + yC * ${o} - ${a};

                if (xC < 0 || xC >= ${t.inWidth}) {
                  continue;
                }

                float dyValue = getDy(b, yF, yR, yC, d2);
                float xValue = getX(b, xF, xR, xC, d1);
                dotProd += (xValue * dyValue);
              }
            }
          }
        }
        setOutput(dotProd);
      }
    `}},kv=class{constructor(t){this.variableNames=["dy","W"],this.outputShape=t.inShape;let e=t.filterDepth,n=t.filterHeight,o=t.filterWidth,s=t.strideDepth,i=t.strideHeight,a=t.strideWidth,u=e-1-t.padInfo.front,l=n-1-t.padInfo.top,c=o-1-t.padInfo.left;this.userCode=`
      const ivec3 pads = ivec3(${u}, ${l}, ${c});

      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 < ${e}; wF++) {
          float dyF = float(dyFCorner + wF) / ${s}.0;

          if (dyF < 0.0 || dyF >= ${t.outDepth}.0 || fract(dyF) > 0.0) {
            continue;
          }
          int idyF = int(dyF);

          int wFPerm = ${e} - 1 - wF;

          for (int wR = 0; wR < ${n}; wR++) {
            float dyR = float(dyRCorner + wR) / ${i}.0;

            if (dyR < 0.0 || dyR >= ${t.outHeight}.0 ||
              fract(dyR) > 0.0) {
              continue;
            }
            int idyR = int(dyR);

            int wRPerm = ${n} - 1 - wR;

            for (int wC = 0; wC < ${o}; wC++) {
              float dyC = float(dyCCorner + wC) / ${a}.0;

              if (dyC < 0.0 || dyC >= ${t.outWidth}.0 ||
                  fract(dyC) > 0.0) {
                continue;
              }
              int idyC = int(dyC);

              int wCPerm = ${o} - 1 - wC;

              for (int d2 = 0; d2 < ${t.outChannels}; d2++) {
                float xValue = getDy(batch, idyF, idyR, idyC, d2);
                float wValue = getW(wFPerm, wRPerm, wCPerm, d1, d2);
                dotProd += xValue * wValue;
              }
            }
          }
        }
        setOutput(dotProd);
      }
    `}};function Wet(r){let{inputs:t,backend:e,attrs:n}=r,{x:o,dy:s}=t,{strides:i,pad:a,dataFormat:u,dimRoundingMode:l,filterShape:c}=n,p=S.convertConv2DDataFormat(u),m=S.computeConv2DInfo(o.shape,c,i,1,a,l,!1,p),f=new Iv(m);return e.runWebGLProgram(f,[o,s],"float32")}var lz={kernelName:Np,backendName:"webgl",kernelFunc:Wet};function Uet(r){let{inputs:t,backend:e,attrs:n}=r,{dy:o,filter:s}=t,{inputShape:i,strides:a,pad:u,dataFormat:l,dimRoundingMode:c}=n,p=S.convertConv2DDataFormat(l),m=S.computeConv2DInfo(i,s.shape,a,1,u,c,!1,p),f=new Sv(m);return e.runWebGLProgram(f,[o,s],"float32")}var uz={kernelName:Qo,backendName:"webgl",kernelFunc:Uet};function Het(r){let{inputs:t,backend:e,attrs:n}=r,{x:o,filter:s}=t,{strides:i,pad:a,dilations:u}=n,l=S.computeConv3DInfo(o.shape,s.shape,i,u,a),c=new yv(l);return e.runWebGLProgram(c,[o,s],"float32")}var cz={kernelName:Nl,backendName:"webgl",kernelFunc:Het};function qet(r){let{inputs:t,backend:e,attrs:n}=r,{x:o,dy:s}=t,{strides:i,pad:a,filterShape:u}=n,l=S.computeConv3DInfo(o.shape,u,i,1,a),c=new Nv(l);return e.runWebGLProgram(c,[o,s],"float32")}var pz={kernelName:kp,backendName:"webgl",kernelFunc:qet};function Ket(r){let{inputs:t,backend:e,attrs:n}=r,{dy:o,filter:s}=t,{pad:i,strides:a,inputShape:u}=n,l=S.computeConv3DInfo(u,s.shape,a,1,i),c=new kv(l);return e.runWebGLProgram(c,[o,s],"float32")}var mz={kernelName:Tp,backendName:"webgl",kernelFunc:Ket};var jet=Ro+`
  return cos(x);
`,Xet=It({opSnippet:jet}),fz={kernelName:ts,backendName:"webgl",kernelFunc:Xet};var Yet=`
  float e2x = exp(-x);
  return (e2x + 1.0 / e2x) / 2.0;
`,Zet=It({opSnippet:Yet}),dz={kernelName:es,backendName:"webgl",kernelFunc:Zet};var Tv=class{constructor(t,e,n,o,s){this.variableNames=["Image","Boxes","BoxInd"],this.outputShape=[];let[i,a,u,l]=t,[c]=e,[p,m]=n;this.outputShape=[c,p,m,l];let f=o==="bilinear"?1:0,[d,h]=[`${a-1}.0`,`${u-1}.0`],[g,y,b]=p>1?[`${(a-1)/(p-1)}`,"(y2-y1) * height_ratio",`y1*${d} + float(y)*(height_scale)`]:["0.0","0.0",`0.5 * (y1+y2) * ${d}`],[w,v,N]=m>1?[`${(u-1)/(m-1)}`,"(x2-x1) * width_ratio",`x1*${h} + float(x)*(width_scale)`]:["0.0","0.0",`0.5 * (x1+x2) * ${h}`];this.userCode=`
      const float height_ratio = float(${g});
      const float width_ratio = float(${w});
      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 >= ${i}) {
          return;
        }

        float height_scale = ${y};
        float width_scale = ${v};

        float in_y = ${b};
        if( in_y < 0.0 || in_y > ${d} ) {
          setOutput(float(${s}));
          return;
        }
        float in_x = ${N};
        if( in_x < 0.0 || in_x > ${h} ) {
          setOutput(float(${s}));
          return;
        }

        vec2 sourceFracIndexCR = vec2(in_x,in_y);
        if(${f} == 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);
        }
      }
    `}};var Jet=r=>{let{inputs:t,backend:e,attrs:n}=r,{image:o,boxes:s,boxInd:i}=t,{cropSize:a,method:u,extrapolationValue:l}=n,c=new Tv(o.shape,s.shape,a,u,l);return e.runWebGLProgram(c,[o,s,i],"float32")},hz={kernelName:pa,backendName:"webgl",kernelFunc:Jet};var Jc;(function(r){r.Prod="*",r.Sum="+"})(Jc||(Jc={}));var ag=class{constructor(t,e,n,o){this.op=t,this.outputShape=e,this.variableNames=["x"],this.customUniforms=[{name:"index",type:"float"}];let s=this.outputShape.length,i=this.op===Jc.Prod?"1.0":"0.0",a=n?i:`getX(${gz(s,"coords",this.op)})`,u=this.outputShape[this.outputShape.length-1],l="",c="";n?(l=o?`end != ${u-1}`:"end != 0",c=o?"end + 1":"end - 1"):(l=o?`end + pow2 < ${u}`:"end >= pow2",c=o?"end + pow2":"end - pow2"),this.userCode=`
      void main() {
        ${Wt(s)} coords = getOutputCoords();
        int end = ${xz(s,"coords",this.op)};
        float val = ${a};
        int pow2 = int(pow(2.0, index));
        if (${l}) {
          int idx = ${c};
          ${xz(s,"coords",this.op)} = idx;
          val ${this.op}= getX(${gz(s,"coords",this.op)});
        }
        setOutput(val);
      }
    `}};function gz(r,t,e){if(r===1)return`${t}`;if(r===2)return`${t}.x, ${t}.y`;if(r===3)return`${t}.x, ${t}.y, ${t}.z`;if(r===4)return`${t}.x, ${t}.y, ${t}.z, ${t}.w`;throw new Error(`Cumulative ${e} for rank ${r} is not yet supported`)}function xz(r,t,e){if(r===1)return`${t}`;if(r===2)return`${t}.y`;if(r===3)return`${t}.z`;if(r===4)return`${t}.w`;throw new Error(`Cumulative ${e} for rank ${r} is not yet supported`)}function _v(r,t,e,n,o,s){let i=t.shape.length,a=S.getAxesPermutation([n],i),u=t;a!=null&&(u=Pe({inputs:{x:t},backend:e,attrs:{perm:a}}));let l=S.getInnerMostAxes(1,i)[0];if(l!==i-1)throw new Error(`WebGL cumprod shader expects an inner-most axis=${t.shape.length-1} but got axis=${n}`);let c=u.shape[l],p=er({inputs:{x:u},backend:e});for(let m=0;m<=Math.ceil(Math.log2(c))-1;m++){let f=new ag(r,u.shape,!1,s),d=[[m]],h=p;p=e.runWebGLProgram(f,[p],p.dtype,d),e.disposeIntermediateTensorInfo(h)}if(o){let m=new ag(r,u.shape,o,s),f=p;p=e.runWebGLProgram(m,[p],p.dtype),e.disposeIntermediateTensorInfo(f)}if(a!=null){let m=S.getUndoAxesPermutation(a),f=Pe({inputs:{x:p},backend:e,attrs:{perm:m}});return e.disposeIntermediateTensorInfo(p),e.disposeIntermediateTensorInfo(u),f}return p}function Qet(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{axis:s,exclusive:i,reverse:a}=n;return _v(Jc.Prod,o,e,s,i,a)}var yz={kernelName:ca,backendName:"webgl",kernelFunc:Qet};function trt(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{axis:s,exclusive:i,reverse:a}=n;return _v(Jc.Sum,o,e,s,i,a)}var bz={kernelName:rs,backendName:"webgl",kernelFunc:trt};function ert(r){let{inputs:t,backend:e,attrs:n}=r,{x:o,weights:s}=t,{size:i,binaryOutput:a}=n;if(o.shape.length===1){let u=e.readSync(o.dataId),l=e.readSync(s.dataId),c=Ww(u,l,s.dtype,s.shape,i);return e.makeTensorInfo([i],s.dtype,c)}else if(o.shape.length===2){let u=e.bufferSync(o),l=e.bufferSync(s),c=aP(u,l,i,a);return e.makeTensorInfo(c.shape,s.dtype,c.values)}throw new Error(`Error in denseBincount: input must be at most rank 2, but got rank${o.shape.length}.`)}var wz={kernelName:_p,backendName:"webgl",kernelFunc:ert};var Ev=class{constructor(t,e,n){this.variableNames=["x"],this.outputShape=[],this.outputShape=t,this.blockSize=e,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 / ${e};
      int offset_h = imod(h, ${e});
      int in_w = w / ${e};
      int offset_w = imod(w, ${e});
      int offset_d = (offset_h * ${e} + 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 rrt(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{blockSize:s,dataFormat:i}=n,a=o.shape[0],u=i==="NHWC"?o.shape[1]:o.shape[2],l=i==="NHWC"?o.shape[2]:o.shape[3],c=i==="NHWC"?o.shape[3]:o.shape[1],p=u*s,m=l*s,f=c/(s*s),d=i==="NHWC"?[a,p,m,f]:[a,f,p,m],h=new Ev(d,s,i);return e.runWebGLProgram(h,[o],o.dtype)}var vz={kernelName:ma,backendName:"webgl",kernelFunc:rrt};var $d=class{constructor(t,e=!1,n=null,o=!1,s=!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=t.outShape,this.enableShapeUniforms=De(this.outputShape.length);let i=t.filterHeight,a=t.filterWidth,u=t.outChannels/t.inChannels,l="",c="";n&&(o?l=`float activation(float a) {
          float b = getPreluActivationWeightsAtOutCoords();
          ${n}
        }`:s?l=`float activation(float a) {
          float b = getLeakyreluAlphaAtOutCoords();
          ${n}
        }`:l=`
          float activation(float x) {
            ${n}
          }
        `,c="result = activation(result);");let p=e?"result += getBiasAtOutCoords();":"";e&&this.variableNames.push("bias"),o&&this.variableNames.push("preluActivationWeights"),s&&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 / ${u};
        int q = d2 - d1 * ${u};

        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 < ${i}; wR++) {
          int xR = xRCorner + wR * dilations[0];

          if (xR < 0 || xR >= inDims[0]) {
            continue;
          }

          for (int wC = 0; wC < ${a}; 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}
        ${c}
        setOutput(result);
      }
    `}};var Dd=class{constructor(t,e=!1,n=null,o=!1,s=!1){this.variableNames=["x","W"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"pads",type:"ivec2"},{name:"strides",type:"ivec2"},{name:"dilations",type:"ivec2"},{name:"inDims",type:"ivec2"}],this.outputShape=t.outShape,this.enableShapeUniforms=De(this.outputShape.length);let i=t.outChannels/t.inChannels,a=t.padInfo.left,u=t.strideWidth,l=t.dilationWidth,c=t.filterHeight,p=t.filterWidth,m=p,f=`
      int xR; int xC; int xCOffset;
      vec4 wTexel; vec4 previous; vec4 final;`;for(let y=0;y<p;y++)f+=`
          vec4 xTexelC${y*2};
          int xTexelC${y*2}Ready;
          vec4 xTexelC${y*2+1};
          int xTexelC${y*2+1}Ready;
          vec4 xC${y};`;f+=`
    for (int r = 0; r < ${c}; r++) {
      `;for(let y=0;y<p;y++)f+=`
          xTexelC${y*2} = vec4(0.0);
          xTexelC${y*2}Ready = 0;
          xTexelC${y*2+1} = vec4(0.0);
          xTexelC${y*2+1}Ready = 0;
          xC${y} = vec4(0.0);`;f+=`
        xR = xRCorner + r * dilations[0];
        if (xR >=0 && xR < inDims[0]) {
      `;for(let y=0;y<(m+1)/2;y++){let b=y*2;if(f+=`
          xC = xCCorner + ${b*l};
          `,u===1){if(b<p&&(a%2===1?(f+=`
                xCOffset = xC + 1;
                if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${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?f+=`
                xC${b} = vec4(xTexelC${b-2}.zw, xTexelC${b}.xy);
                `:f+=`
                  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);
                  }
                  `):f+=`
                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 w=a%2===0?x.nearestLargerEven(l):l;l%2===0&&a%2===1||l%2!==0&&a%2!==1?(f+=`
                  xCOffset = xC + imod(pads[1], 2) + ${w};

                  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&&(f+=`
                    xCOffset -= 2;
                    if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${b}Ready == 0) {
                      xTexelC${b} = getX(batch, xR, xCOffset, d1);
                      xTexelC${b}Ready = 1;
                    }
                    `),f+=`
                  xC${b+1} = vec4(xTexelC${b}.zw, xTexelC${b+1}.xy);
                  `):w===1?f+=`
                    xC${b+1} = xTexelC${b};
                    `:f+=`
                    xCOffset = xC + ${w};

                    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&&(a%2===1?(f+=`
                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${b+1}.zw);
              `,b+1<p&&(f+=`
                  final = vec4(0.0);
                  xCOffset = xC + 1 + strides[1];
                  if(xCOffset >= 0 && xCOffset < inDims[1]) {
                    final = getX(batch, xR, xCOffset, d1);
                  }
                  xC${b+1} = vec4(xTexelC${b+1}.xy, final.xy);
                `)):(f+=`
                if(xC >= 0 && xC < inDims[1] && xTexelC${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${b+1}.xy);
              `,b+1<p&&(f+=`
                  xC${b+1} = vec4(xTexelC${b}.zw, xTexelC${b+1}.zw);
                `)));b<p&&(f+=`
            wTexel = getW(r, ${b}, d1, q);
            dotProd += xC${b} * vec4(wTexel.xz, wTexel.xz);
          `,b+1<p&&(f+=`
              wTexel = getW(r, ${b+1}, d1, q);
              dotProd += xC${b+1} * vec4(wTexel.xz, wTexel.xz);
            `))}f+=`
    }
  `,f+=`
      }
    `;let d="",h="";n&&(o?d=`vec4 activation(vec4 a) {
          vec4 b = getPreluActivationWeightsAtOutCoords();
          ${n}
        }`:s?d=`vec4 activation(vec4 a) {
          vec4 b = getLeakyreluAlphaAtOutCoords();
          ${n}
        }`:d=`vec4 activation(vec4 x) {
          ${n}
        }`,h="result = activation(result);");let g=e?"result += getBiasAtOutCoords();":"";e&&this.variableNames.push("bias"),o&&this.variableNames.push("preluActivationWeights"),s&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
      ${d}

      void main() {
        ivec4 coords = getOutputCoords();
        int batch = coords.x;
        ivec2 xRCCorner = coords.yz * strides - pads;
        int d2 = coords.w;
        int d1 = d2 / ${i};
        int q = d2 - d1 * ${i};
        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);

        ${f}

        vec4 result = dotProd - vec4(0.000000000000001);
        ${g}
        ${h}
        setOutput(result);
      }
    `}};function nrt(r){let{inputs:t,backend:e,attrs:n}=r,{x:o,filter:s}=t,{strides:i,pad:a,dilations:u,dimRoundingMode:l}=n,c=u;c==null&&(c=[1,1]),x.assert(S.eitherStridesOrDilationsAreOne(i,c),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${i} and dilations '${c}'`);let p=S.computeConv2DInfo(o.shape,s.shape,i,c,a,l,!0),m;B().getBool("WEBGL_PACK_DEPTHWISECONV")&&p.strideWidth<=2&&p.outChannels/p.inChannels===1?m=new Dd(p):m=new $d(p);let f=[[p.padInfo.top,p.padInfo.left],[p.strideHeight,p.strideWidth],[p.dilationHeight,p.dilationWidth],[p.inHeight,p.inWidth]];return e.runWebGLProgram(m,[o,s],"float32",f)}var Cz={kernelName:ns,backendName:"webgl",kernelFunc:nrt};var Av=class{constructor(t){this.variableNames=["x","dy"],this.outputShape=t.filterShape;let e=t.strideHeight,n=t.strideWidth,o=t.padInfo.top,s=t.padInfo.left,i=t.outChannels/t.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 * ${i} + dm;

        float dotProd = 0.0;

        // TO DO: Vec4 over the batch size
        for (int b = 0; b < ${t.batchSize}; b++) {
          for (int yR = 0; yR < ${t.outHeight}; yR++) {
            int xR = wR + yR * ${e} - ${o};

            if (xR < 0 || xR >= ${t.inHeight}) {
              continue;
            }

            for (int yC = 0; yC < ${t.outWidth}; yC++) {
              int xC = wC + yC * ${n} - ${s};

              if (xC < 0 || xC >= ${t.inWidth}) {
                continue;
              }

              float dyValue = getDy(b, yR, yC, d2);
              float xValue = getX(b, xR, xC, d1);
              dotProd += (xValue * dyValue);
            }
          }
        }
        setOutput(dotProd);
      }
    `}},$v=class{constructor(t){this.variableNames=["dy","W"],this.outputShape=t.inShape;let e=t.filterHeight,n=t.filterWidth,o=t.strideHeight,s=t.strideWidth,i=e-1-t.padInfo.top,a=n-1-t.padInfo.left,u=t.outChannels/t.inChannels;this.userCode=`
      const ivec2 pads = ivec2(${i}, ${a});

      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 < ${e}; wR++) {
          float dyR = float(dyRCorner + wR) / ${o}.0;

          if (dyR < 0.0 || dyR >= ${t.outHeight}.0 || fract(dyR) > 0.0) {
            continue;
          }
          int idyR = int(dyR);

          int wRPerm = ${e} - 1 - wR;

          for (int wC = 0; wC < ${n}; wC++) {
            float dyC = float(dyCCorner + wC) / ${s}.0;

            if (dyC < 0.0 || dyC >= ${t.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 < ${u}; dm++) {
              int d2 = d1 * ${u} + dm;
              float xValue = getDy(batch, idyR, idyC, d2);
              float wValue = getW(wRPerm, wCPerm, d1, dm);
              dotProd += xValue * wValue;
            }
          }
        }
        setOutput(dotProd);
      }
    `}};function ort(r){let{inputs:t,backend:e,attrs:n}=r,{x:o,dy:s}=t,{strides:i,dilations:a,pad:u,dimRoundingMode:l,filterShape:c}=n,p=S.computeConv2DInfo(o.shape,c,i,a,u,l,!0),m=new Av(p);return e.runWebGLProgram(m,[o,s],"float32")}var Iz={kernelName:Ep,backendName:"webgl",kernelFunc:ort};function srt(r){let{inputs:t,backend:e,attrs:n}=r,{dy:o,filter:s}=t,{strides:i,dilations:a,pad:u,dimRoundingMode:l,inputShape:c}=n,p=S.computeConv2DInfo(c,s.shape,i,a,u,l,!0),m=new $v(p);return e.runWebGLProgram(m,[o,s],"float32")}var Sz={kernelName:Ap,backendName:"webgl",kernelFunc:srt};var Dv=class{constructor(t){this.variableNames=["X"],this.outputShape=[t,t],this.userCode=`
      void main() {
          ivec2 coords = getOutputCoords();
          float val = coords[0] == coords[1] ? getX(coords[0]) : 0.0;
          setOutput(val);
      }
    `}};function irt(r){let{inputs:t,backend:e}=r,{x:n}=t,o=[...n.shape,...n.shape],s=x.sizeFromShape(n.shape),i=at({inputs:{x:n},backend:e,attrs:{shape:[s]}}),a=new Dv(s),u=e.runWebGLProgram(a,[i],i.dtype),l=at({inputs:{x:u},backend:e,attrs:{shape:o}});return e.disposeIntermediateTensorInfo(i),e.disposeIntermediateTensorInfo(u),l}var Nz={kernelName:$p,backendName:"webgl",kernelFunc:irt};var Fv=class{constructor(t){this.variableNames=["x","W"],this.outputShape=t.outShape;let{inHeight:e,inWidth:n,padInfo:o,strideHeight:s,strideWidth:i,filterHeight:a,filterWidth:u,dilationHeight:l,dilationWidth:c}=t,{top:p,left:m}=o;this.userCode=`
      const ivec2 strides = ivec2(${s}, ${i});
      const ivec2 pads = ivec2(${p}, ${m});
      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 < ${a}; h++) {
          int hIn = hBeg + h * ${l};

          if (hIn >= 0 && hIn < ${e}) {
            for (int w = 0; w < ${u}; w++) {
              int wIn = wBeg + w * ${c};

              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 art(r){let{inputs:t,backend:e,attrs:n}=r,{x:o,filter:s}=t,{strides:i,pad:a,dilations:u}=n,l=S.computeDilation2DInfo(o.shape,s.shape,i,a,"NHWC",u),c,p=new Fv(l);c=e.runWebGLProgram(p,[o,s],"float32");let m=at({inputs:{x:c},backend:e,attrs:{shape:l.outShape}});return e.disposeIntermediateTensorInfo(c),m}var kz={kernelName:kl,backendName:"webgl",kernelFunc:art};function lrt(r){let{inputs:t,backend:e,attrs:n}=r,{equation:o}=n,s=t,{allDims:i,summedDims:a,idDims:u}=S.decodeEinsumEquation(o,s.length);S.checkEinsumDimSizes(i.length,u,s);let{path:l,steps:c}=S.getEinsumComputePath(a,u),p=c.length,m=null,f=i.length,d=[];for(let h=0;h<p;++h){for(let g of c[h]){let{permutationIndices:y,expandDims:b}=S.getEinsumPermutation(f,u[g]),w;S.isIdentityPermutation(y)?w=s[g]:(w=Pe({inputs:{x:s[g]},backend:e,attrs:{perm:y}}),d.push(w));let v=w.shape.slice();for(let N=0;N<b.length;++N)v.splice(b[N],0,1);x.arraysEqual(w.shape,v)||(w=at({inputs:{x:w},backend:e,attrs:{shape:v}}),d.push(w)),m===null?m=w:(m=sg({inputs:{a:w,b:m},backend:e}),d.push(m))}h<p-1&&(l[h]>=0&&(m=Xc({inputs:{x:m},backend:e,attrs:{axis:l[h]-(i.length-f),keepDims:!1}}),d.push(m)),f--)}for(let h of d)h!==m&&e.disposeIntermediateTensorInfo(h);return m}var Tz={kernelName:Dp,backendName:"webgl",kernelFunc:lrt};var urt="return (x >= 0.0) ? x : (exp(x) - 1.0);",crt=`
  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;
`,prt=It({opSnippet:urt,packedOpSnippet:crt}),_z={kernelName:ss,backendName:"webgl",kernelFunc:prt};var mrt="return (b >= 1.0) ? a : a * (b + 1.0);",frt=`
  vec4 bGTEZero = vec4(greaterThanEqual(b, vec4(0.)));
  return (bGTEZero * a) + ((vec4(1.0) - bGTEZero) * (a * (b + vec4(1.0))));
`,drt=r=>{let{inputs:t,backend:e}=r,{dy:n,y:o}=t,s=B().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new Fo(frt,n.shape,o.shape):new ro(mrt,n.shape,o.shape);return e.runWebGLProgram(s,[n,o],n.dtype)},Ez={kernelName:Fp,backendName:"webgl",kernelFunc:drt};var hrt=`
  return vec4(equal(a, b));
`,grt="return float(a == b);",xrt=ce({opSnippet:grt,packedOpSnippet:hrt,dtype:"bool",cpuKernelImpl:cP}),Az={kernelName:da,backendName:"webgl",kernelFunc:xrt};var yrt=`
  // Error function is calculated approximately with elementary function.
  // See "Handbook of Mathematical Functions with Formulas,
  // Graphs, and Mathematical Tables", Abramowitz and Stegun.
  float p = ${S.ERF_P};
  float a1 = ${S.ERF_A1};
  float a2 = ${S.ERF_A2};
  float a3 = ${S.ERF_A3};
  float a4 = ${S.ERF_A4};
  float a5 = ${S.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));
`,brt=It({opSnippet:yrt}),$z={kernelName:fa,backendName:"webgl",kernelFunc:brt};var wrt=Ro+`
  return exp(x);
`,vrt=`
  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;
`,IT=It({opSnippet:wrt,packedOpSnippet:vrt,cpuKernelImpl:pP,dtype:"float32"}),Dz={kernelName:is,backendName:"webgl",kernelFunc:IT};function Rv(r){let{inputs:t,attrs:e,backend:n}=r,{dim:o}=e,{input:s}=t,i=s.shape.length,a=s.shape.slice(),u=o;return o<0&&(x.assert(-(i+1)<=o,()=>`Axis must be in the interval [${-(i+1)}, ${i}]`),u=i+o+1),a.splice(u,0,1),at({inputs:{x:s},backend:n,attrs:{shape:a}})}var Fz={kernelName:fi,backendName:"webgl",kernelFunc:Rv};var Rz="return exp(x) - 1.0;",Crt=It({opSnippet:Rz,packedOpSnippet:Rz,cpuKernelImpl:mP}),Oz={kernelName:ha,backendName:"webgl",kernelFunc:Crt};var lg=class{constructor(t,e,n){this.variableNames=["real","imag"];let o=e[1];this.outputShape=e;let s=n?`2.0 * ${Math.PI}`:`-2.0 * ${Math.PI}`,i=n?`${o}.0`:"1.0",a;if(t==="real")a="return real * expR - imag * expI;";else if(t==="imag")a="return real * expI + imag * expR;";else throw new Error(`FFT component must be either "real" or "imag", got ${t}.`);this.userCode=`
      const float exponentMultiplier = ${s};

      float unaryOpComplex(float real, float expR, float imag, float expI) {
        ${a}
      }

      float mulMatDFT(int batch, int index) {
        float indexRatio = float(index) / float(${o});
        float exponentMultiplierTimesIndexRatio =
            exponentMultiplier * indexRatio;

        float result = 0.0;

        for (int i = 0; i < ${o}; 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) / ${i};
        }

        return result;
      }

      void main() {
        ivec2 coords = getOutputCoords();
        setOutput(mulMatDFT(coords[0], coords[1]));
      }
    `}};function Ov(r,t,e){let n=e.texData.get(r.dataId),o=x.sizeFromShape(r.shape),s=r.shape[r.shape.length-1],i=o/s,a=at({inputs:{x:r},backend:e,attrs:{shape:[i,s]}}),u=a.shape,l=new lg("real",u,t),c=new lg("imag",u,t),p=[{dataId:n.complexTensorInfos.real.dataId,dtype:n.complexTensorInfos.real.dtype,shape:u},{dataId:n.complexTensorInfos.imag.dataId,dtype:n.complexTensorInfos.imag.dtype,shape:u}],m=e.runWebGLProgram(l,p,"float32"),f=e.runWebGLProgram(c,p,"float32"),d=An({inputs:{real:m,imag:f},backend:e});e.disposeIntermediateTensorInfo(m),e.disposeIntermediateTensorInfo(f);let h=at({inputs:{x:d},backend:e,attrs:{shape:r.shape}});return e.disposeIntermediateTensorInfo(a),e.disposeIntermediateTensorInfo(d),h}function Irt(r){let{inputs:t,backend:e}=r,{input:n}=t;return Ov(n,!1,e)}var Lz={kernelName:Rp,backendName:"webgl",kernelFunc:Irt};var Lv=class{constructor(t,e){this.outputShape=[],this.customUniforms=[{name:"value",type:"float"}],this.variableNames=["x"],this.outputShape=t,this.userCode=`
      void main() {
        // Input can be obtained from uniform value.
        setOutput(value);
      }
    `}};function gl(r){let{backend:t,attrs:e}=r,{shape:n,value:o}=e,{dtype:s}=e;if(s=s||x.inferDtype(o),s==="string"){let i=x.getArrayFromDType(s,x.sizeFromShape(n));return i.fill(o),t.makeTensorInfo(n,s,i)}else{let i=new Lv(n,o),a=[[o]];return t.runWebGLProgram(i,[],s,a)}}var Pz={kernelName:Tl,backendName:"webgl",kernelFunc:gl};var Pv=class{constructor(t){this.variableNames=["Image"],this.outputShape=[];let e=t[2];this.outputShape=t,this.userCode=`
        void main() {
          ivec4 coords = getOutputCoords();
          int x = coords[2];

          int coordX = ${e} - x - 1;
          float outputValue;
          if(coordX >= 0 && coordX < ${e}) {
            outputValue = getImage(coords[0], coords[1], coordX, coords[3]);
          } else {
            outputValue = getImage(coords[0], coords[1], coords[2], coords[3]);
          }
          setOutput(outputValue);
        }
    `}};var Mz={kernelName:ga,backendName:"webgl",kernelFunc:({inputs:r,backend:t})=>{let{image:e}=r,n=t,o=new Pv(e.shape);return n.runWebGLProgram(o,[e],e.dtype)}};var zz="return floor(x);",Srt=It({opSnippet:zz,packedOpSnippet:zz,cpuKernelImpl:fP}),Bz={kernelName:as,backendName:"webgl",kernelFunc:Srt};var Nrt=`
  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;
  }
`,krt=`
  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);
`,Trt=ce({opSnippet:Nrt,packedOpSnippet:krt,dtype:"int32"}),Vz={kernelName:ls,backendName:"webgl",kernelFunc:Trt};var Mv=class{constructor(t){this.variableNames=["A"];let e=He(),[n,o]=t;this.outputShape=t,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(${o}.0, ${n}.0);

        vec4 values = ${e.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));
      }
    `}};var zv=class{constructor(t){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0;let e=He(),[n,o]=t;this.outputShape=t,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(${o}.0, ${n}.0);
            vec4 values = ${e.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);
          }
        }

        ${e.output} = result;
      }
    `}};var Gz={kernelName:eh,backendName:"webgl",kernelFunc:_rt},Fd;function _rt(r){let{inputs:t,backend:e,attrs:n}=r,{pixels:o}=t,{numChannels:s}=n,i=typeof HTMLVideoElement!="undefined"&&o instanceof HTMLVideoElement,a=typeof HTMLImageElement!="undefined"&&o instanceof HTMLImageElement,[u,l]=i?[o.videoWidth,o.videoHeight]:[o.width,o.height],c=[l,u],p=[l,u,s];(a||i)&&(Fd==null&&(Fd=document.createElement("canvas").getContext("2d")),Fd.canvas.width=u,Fd.canvas.height=l,Fd.drawImage(o,0,0,u,l),o=Fd.canvas);let m=e.makeTensorInfo(c,"int32");e.texData.get(m.dataId).usage=Hr.PIXELS,e.gpgpu.uploadPixelDataToTexture(e.getTexture(m.dataId),o);let f=B().getBool("WEBGL_PACK")?new zv(p):new Mv(p),d=e.runWebGLProgram(f,[m],"int32");return e.disposeData(m.dataId),d}function Ert(r){let{inputs:t,backend:e,attrs:n}=r,{x:o,filter:s,bias:i,preluActivationWeights:a}=t,{strides:u,pad:l,dataFormat:c,dilations:p,dimRoundingMode:m,activation:f,leakyreluAlpha:d}=n,h=S.convertConv2DDataFormat(c),g=S.computeConv2DInfo(o.shape,s.shape,u,p,l,m,!1,h),y,b=[];if(g.filterHeight===1&&g.filterWidth===1&&g.dilationHeight===1&&g.dilationWidth===1&&g.strideHeight===1&&g.strideWidth===1&&(g.padInfo.type==="SAME"||g.padInfo.type==="VALID"))y=vv({x:o,filter:s,convInfo:g,backend:e,bias:i,activation:f,preluActivationWeights:a,leakyreluAlpha:d});else if(B().getBool("WEBGL_CONV_IM2COL"))y=Cv({x:o,filter:s,convInfo:g,backend:e,bias:i,activation:f,preluActivationWeights:a,leakyreluAlpha:d});else{let v=i!=null,N=a!=null,E=f==="leakyrelu",$=f?_u(f,!1):null,D=new Ad(g,v,$,N,E),L=[o,s],M=(G,H)=>{if(H==="NCHW"&&G.shape.length===1&&G.shape[0]!==1){let q=at({inputs:{x:G},backend:e,attrs:{shape:[G.shape[0],1,1]}});return b.push(q),q}return G};if(v&&L.push(M(i,c)),N&&L.push(M(a,c)),E){let G=e.makeTensorInfo([],"float32",x.createScalarValue(d,"float32"));L.push(G),b.push(G)}y=e.runWebGLProgram(D,L,"float32")}let w=at({inputs:{x:y},backend:e,attrs:{shape:g.outShape}});return b.push(y),b.forEach(v=>e.disposeIntermediateTensorInfo(v)),w}var Wz={kernelName:ki,backendName:"webgl",kernelFunc:Ert};function Art(r){let{inputs:t,backend:e,attrs:n}=r,{x:o,filter:s,bias:i,preluActivationWeights:a}=t,{strides:u,pad:l,dilations:c,dimRoundingMode:p,activation:m,leakyreluAlpha:f}=n,d=[],h=c;h==null&&(h=[1,1]),x.assert(S.eitherStridesOrDilationsAreOne(u,h),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${u} and dilations '${h}'`);let g=S.computeConv2DInfo(o.shape,s.shape,u,h,l,p,!0),y=B().getBool("WEBGL_PACK_DEPTHWISECONV")&&g.strideWidth<=2&&g.outChannels/g.inChannels===1,b=m?_u(m,y):null,w=[o,s],v=i!=null,N=a!=null,E=m==="leakyrelu";if(v&&w.push(i),N&&w.push(a),E){let M=e.makeTensorInfo([],"float32",x.createScalarValue(f,"float32"));w.push(M),d.push(M)}let $;y?$=new Dd(g,v,b,N,E):$=new $d(g,v,b,N,E);let D=[[g.padInfo.top,g.padInfo.left],[g.strideHeight,g.strideWidth],[g.dilationHeight,g.dilationWidth],[g.inHeight,g.inWidth]],L=e.runWebGLProgram($,w,"float32",D);return d.forEach(M=>e.disposeIntermediateTensorInfo(M)),L}var Uz={kernelName:Ti,backendName:"webgl",kernelFunc:Art};var Bv=class{constructor(t,e,n,o){this.sliceDim=t,this.strides=e,this.paramsShape=o,this.variableNames=["x","indices"],this.outputShape=n;let s=Wt(e.length),i=Wt(n.length),a=this.sliceDim>1?"strides[j]":"strides",u=Wt(o.length),l=o.length>1?"paramsShape[j]":"paramsShape";this.userCode=`
        ${s} strides = ${s}(${this.strides});
        ${u} paramsShape = ${u}(${this.paramsShape});
         void main() {
          ${i} coords = getOutputCoords();
          int flattenIndex = 0;
          bool out_of_bounds = false;
          for (int j = 0; j < ${this.sliceDim}; j++) {
            int index = round(getIndices(coords[0], j));
            out_of_bounds = out_of_bounds || index < 0;
            out_of_bounds = out_of_bounds || index >= ${l};
            flattenIndex += index * ${a};
          }
          setOutput(out_of_bounds ? 0.0 : getX(flattenIndex, coords[1]));
        }
      `}};function $rt(r){let{inputs:t,backend:e}=r,{params:n,indices:o}=t,s=o.shape,i=s[s.length-1],a=x.sizeFromShape(n.shape),[u,l,c,p]=S.prepareAndValidate(n,o),m=at({inputs:{x:o},backend:e,attrs:{shape:[l,i]}}),f=at({inputs:{x:n},backend:e,attrs:{shape:[x.sizeFromShape(n.shape)/c,c]}});if(e.shouldExecuteOnCPU([n,o])||n.dtype==="string"){let y=e.readSync(o.dataId),b=e.bufferSync(n),w=dP(y,b,n.dtype,l,i,c,p,n.shape,a);return e.makeTensorInfo(u,n.dtype,w.values)}let d=new Bv(i,p,[l,c],n.shape),h=e.runWebGLProgram(d,[f,m],f.dtype),g=at({inputs:{x:h},backend:e,attrs:{shape:u}});return e.disposeIntermediateTensorInfo(m),e.disposeIntermediateTensorInfo(f),e.disposeIntermediateTensorInfo(h),g}var Hz={kernelName:xa,backendName:"webgl",kernelFunc:$rt};var Vv=class{constructor(t,e){this.variableNames=["A","indices"],this.outputShape=e,this.rank=e.length;let n=Wt(this.rank),o=Drt(t,2);this.userCode=`
      void main() {
        ${n} resRC = getOutputCoords();
        int index = int(getIndices(resRC.x, resRC.z));
        float inBounds = (index >= 0) && (index < ${t[2]}) ? 1.0 : 0.0;
        setOutput(inBounds * getA(${o}));
      }
    `}};function Drt(r,t){let e=["resRC.x","resRC.y","resRC.z","resRC.w"],n=[];for(let o=0;o<r.length;o++)o===2?n.push("index"):n.push(`${e[o]}`);return n.join()}function ST(r){let{inputs:t,backend:e,attrs:n}=r,{x:o,indices:s}=t,{axis:i,batchDims:a}=n,u=x.parseAxisParam(i,o.shape)[0];if(B().get("DEBUG")){let b=e.readSync(s.dataId),w=o.shape[u];for(let v=0;v<b.length;++v){let N=b[v];x.assert(N<=w-1&&N>=0,()=>`GatherV2: the index value ${N} is not in [0, ${w-1}]`)}}let l=S.segment_util.collectGatherOpShapeInfo(o,s,u,a),c=x.sizeFromShape(s.shape),p=[],m=at({inputs:{x:o},backend:e,attrs:{shape:[l.batchSize,l.outerSize,l.dimSize,l.sliceSize]}}),f=at({inputs:{x:s},backend:e,attrs:{shape:[l.batchSize,c/l.batchSize]}});p.push(m),p.push(f);let d=[l.batchSize,l.outerSize,c/l.batchSize,l.sliceSize];if(e.shouldExecuteOnCPU([o,s])||o.dtype==="string"){let b=e.bufferSync(f),w=e.bufferSync(m),v=hP(w,b,d);return p.forEach(N=>e.disposeIntermediateTensorInfo(N)),e.makeTensorInfo(l.outputShape,v.dtype,v.values)}let h=new Vv(m.shape,d),g=e.runWebGLProgram(h,[m,f],m.dtype);p.push(g);let y=at({inputs:{x:g},backend:e,attrs:{shape:l.outputShape}});return p.forEach(b=>e.disposeIntermediateTensorInfo(b)),y}var qz={kernelName:di,backendName:"webgl",kernelFunc:ST};var Frt="return float(a > b);",Rrt=`
  return vec4(greaterThan(a, b));
`,Ort=ce({opSnippet:Frt,packedOpSnippet:Rrt,cpuKernelImpl:gP,dtype:"bool"}),Kz={kernelName:ya,backendName:"webgl",kernelFunc:Ort};var Lrt="return float(a >= b);",Prt=`
  return vec4(greaterThanEqual(a, b));
`,Mrt=ce({opSnippet:Lrt,packedOpSnippet:Prt,dtype:"bool",cpuKernelImpl:xP}),jz={kernelName:cs,backendName:"webgl",kernelFunc:Mrt};function zrt(r){let{inputs:t,backend:e}=r,{input:n}=t;return Ov(n,!0,e)}var Xz={kernelName:Op,backendName:"webgl",kernelFunc:zrt};var Brt="return float(!isnan(x) && !isinf(x));",Vrt=It({opSnippet:Brt,dtype:"bool"}),Yz={kernelName:ba,backendName:"webgl",kernelFunc:Vrt};var Grt="return float(isinf(x));",Wrt=It({opSnippet:Grt,dtype:"bool"}),Zz={kernelName:wa,backendName:"webgl",kernelFunc:Wrt};var Urt="return float(isnan(x));",Hrt=It({opSnippet:Urt,dtype:"bool"}),Jz={kernelName:va,backendName:"webgl",kernelFunc:Hrt};var qrt="return float(a < b);",Krt=`
  return vec4(lessThan(a, b));
`,jrt=ce({opSnippet:qrt,packedOpSnippet:Krt,cpuKernelImpl:yP,dtype:"bool"}),Qz={kernelName:Ca,backendName:"webgl",kernelFunc:jrt};var Xrt="return float(a <= b);",Yrt=`
  return vec4(lessThanEqual(a, b));
`,Zrt=ce({opSnippet:Xrt,packedOpSnippet:Yrt,cpuKernelImpl:bP,dtype:"bool"}),t3={kernelName:Ia,backendName:"webgl",kernelFunc:Zrt};function Jrt(r){let{backend:t,attrs:e}=r,{start:n,stop:o,num:s}=e,i=wP(n,o,s);return t.makeTensorInfo([i.length],"float32",i)}var e3={kernelName:Pp,backendName:"webgl",kernelFunc:Jrt};var Qrt=Ro+`
  return x < 0.0 ? 0./0. : log(x);
`,tnt=`
  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;
`,ent=It({opSnippet:Qrt,packedOpSnippet:tnt,cpuKernelImpl:vP}),r3={kernelName:ms,backendName:"webgl",kernelFunc:ent};var rnt=Ro+`
  return log(1.0 + x);
`,nnt=It({opSnippet:rnt}),n3={kernelName:Sa,backendName:"webgl",kernelFunc:nnt};var ont="return float(a >= 1.0 && b >= 1.0);",snt=`
  return vec4(
    vec4(greaterThanEqual(a, vec4(1.0))) *
    vec4(greaterThanEqual(b, vec4(1.0))));
`,int=ce({opSnippet:ont,packedOpSnippet:snt,dtype:"bool"}),o3={kernelName:Na,backendName:"webgl",kernelFunc:int};var ant="return float(!(x >= 1.0));",lnt=It({opSnippet:ant}),s3={kernelName:ka,backendName:"webgl",kernelFunc:lnt};var unt="return float(a >= 1.0 || b >= 1.0);",cnt=`
  return min(
    vec4(greaterThanEqual(a, vec4(1.0))) +
    vec4(greaterThanEqual(b, vec4(1.0))),
    vec4(1.0));
`,pnt=ce({opSnippet:unt,packedOpSnippet:cnt,dtype:"bool"}),i3={kernelName:Ta,backendName:"webgl",kernelFunc:pnt};var Gv=class{constructor(t,e,n,o,s){this.variableNames=["x"],this.outputShape=[];let i=e,a=t[3]-1;this.outputShape=t;let u,l=`float(${n}) + float(${o}) * sum`;s===.5?u=`inversesqrt(${l})`:s===1?u=`1.0/(${l})`:u=`exp(log(${l}) * float(-${s}));`,this.userCode=`
      void main() {
        ivec4 coords = getOutputCoords();
        int b = coords[0];
        int r = coords[1];
        int c = coords[2];
        int d = coords[3];
        float x = getX(b, r, c, d);
        float sum = 0.0;
        for (int j = -${i}; j <= ${i}; j++) {
          int idx = d + j;
          if (idx >= 0 && idx <=  ${a}) {
            float z = getX(b, r, c, idx);
            sum += z * z;
          }
        }
        float val = x * ${u};
        setOutput(val);
      }
    `}};var Wv=class{constructor(t,e,n,o,s){this.variableNames=["x"],this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0;let i=e,a=t[3]-1;this.outputShape=t;let u,l=`float(${n}) + float(${o}) * sum`;s===.5?u=`inversesqrt(${l})`:s===1?u=`1.0/(${l})`:u=`exp(log(${l}) * float(-${s}));`,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 - ${i};
        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 = - ${i}; j <= ${i}; j++) {
          ivec2 idx = depth + j;
          bvec2 aboveLowerBound = greaterThanEqual(idx, ivec2(0));
          bvec2 belowUpperBound = lessThanEqual(idx, ivec2(${a}));

          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 * ${u};
        setOutput(result);
      }
    `}};var mnt=r=>{let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{depthRadius:s,bias:i,alpha:a,beta:u}=n,l=B().getBool("WEBGL_PACK_NORMALIZATION")?new Wv(o.shape,s,i,a,u):new Gv(o.shape,s,i,a,u);return e.runWebGLProgram(l,[o],o.dtype)},a3={kernelName:_l,backendName:"webgl",kernelFunc:mnt};var Uv=class{constructor(t,e,n,o,s){this.variableNames=["inputImage","outputImage","dy"],this.outputShape=[],this.outputShape=t,this.depth=t[3],this.depthRadius=e,this.bias=n,this.alpha=o,this.beta=s,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 - ${e})));
          int depthEnd = int(min(float(${this.depth}),
              float(d + ${e} + 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(${o}) * norm + float(${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(${o})
                * float(${s})
                * getInputImage(b ,r ,c, k) * getOutputImage(b, r, c, d)
                / norm;
              if (k == d) {
                dyi += pow(norm, -1.0 * ${s});
              }
              if (k == coords[3]) {
                dyi *= getDy(b, r, c, d);
                result += dyi;
              }
            }
            else {
              break;
            }
          }
      }
      setOutput(result);
      }
    `}};var fnt=r=>{let{inputs:t,backend:e,attrs:n}=r,{x:o,y:s,dy:i}=t,{depthRadius:a,bias:u,alpha:l,beta:c}=n,p=new Uv(o.shape,a,u,l,c);return e.runWebGLProgram(p,[o,s,i],o.dtype)},l3={kernelName:Mp,backendName:"webgl",kernelFunc:fnt};function u3(r,t,e,n){let o=x.sizeFromShape(t),i=x.sizeFromShape(r.shape)/o,a=at({inputs:{x:r},attrs:{shape:[i,o]},backend:n}),u=Un(a,r.dtype,"max",n),l=at({inputs:{x:u},attrs:{shape:e},backend:n});return n.disposeIntermediateTensorInfo(a),n.disposeIntermediateTensorInfo(u),l}function NT(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{reductionIndices:s,keepDims:i}=n,a=o.shape.length,u=x.parseAxisParam(s,o.shape),l=u,c=S.getAxesPermutation(l,a),p=c!=null,m=e.shouldExecuteOnCPU([o]),f=o;if(p){if(m){let w=e.texData.get(f.dataId).values,v=new Array(a);for(let $=0;$<v.length;$++)v[$]=o.shape[c[$]];let N=Kc(w,o.shape,o.dtype,c,v);f=e.makeTensorInfo(v,o.dtype);let E=e.texData.get(f.dataId);E.values=N}else f=Eu(o,c,e);l=S.getInnerMostAxes(l.length,a)}S.assertAxesAreInnerMostDims("max",l,a);let[d,h]=S.computeOutAndReduceShapes(f.shape,l),g=d;i&&(g=S.expandShapeToKeepDim(d,u));let y;if(m){let w=e.texData.get(f.dataId).values,v=CP(w,x.sizeFromShape(h),g,o.dtype);y=e.makeTensorInfo(g,o.dtype);let N=e.texData.get(y.dataId);N.values=v}else y=u3(f,h,g,e);return p&&e.disposeIntermediateTensorInfo(f),y}var c3={kernelName:fs,backendName:"webgl",kernelFunc:NT};var dnt=Yw+`
  return max(a, b);
`,hnt=`
  vec4 result = vec4(max(a, b));
  vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
  `+Tu+`
  return result;
`,gnt=ce({opSnippet:dnt,packedOpSnippet:hnt,cpuKernelImpl:IP}),p3={kernelName:ds,backendName:"webgl",kernelFunc:gnt};function xnt(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t;ni(o,"maxPool");let{filterSize:s,strides:i,pad:a,dimRoundingMode:u}=n,l=1;x.assert(S.eitherStridesOrDilationsAreOne(i,l),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${i} and dilations '${l}'`);let c=S.computePool2DInfo(o.shape,s,i,l,a,u);if(c.filterWidth===1&&c.filterHeight===1&&x.arraysEqual(c.inShape,c.outShape))return er({inputs:{x:o},backend:e});let p=new si(c,"max",!1);return e.runWebGLProgram(p,[o],o.dtype)}var m3={kernelName:hs,backendName:"webgl",kernelFunc:xnt};function ynt(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{filterSize:s,strides:i,pad:a,dataFormat:u,dimRoundingMode:l}=n,c=[1,1,1],p=S.computePool3DInfo(o.shape,s,i,c,a,l,u),m=new Au(p,"max",!1);return e.runWebGLProgram(m,[o],o.dtype)}var f3={kernelName:El,backendName:"webgl",kernelFunc:ynt};var Hv=class{constructor(t){this.variableNames=["dy","maxPos"],this.outputShape=t.inShape;let e=t.strideHeight,n=t.strideWidth,o=t.dilationHeight,s=t.effectiveFilterHeight,i=t.effectiveFilterWidth,a=s-1-t.padInfo.top,u=i-1-t.padInfo.left,l=s*i-1;this.userCode=`
      const ivec2 pads = ivec2(${a}, ${u});

      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 < ${s};
          wR += ${o}) {
          float dyR = float(dyRCorner + wR) / ${e}.0;

          if (dyR < 0.0 || dyR >= ${t.outHeight}.0 || fract(dyR) > 0.0) {
            continue;
          }
          int idyR = int(dyR);

          for (int wC = 0; wC < ${i}; wC++) {
            float dyC = float(dyCCorner + wC) / ${n}.0;

            if (dyC < 0.0 || dyC >= ${t.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 * ${i} + wC;
            float mask = float(maxPosValue == curPosValue ? 1.0 : 0.0);

            dotProd += dyValue * mask;
          }
        }
        setOutput(dotProd);
      }
    `}},qv=class{constructor(t){this.variableNames=["dy","maxPos"],this.outputShape=t.inShape;let e=t.strideDepth,n=t.strideHeight,o=t.strideWidth,s=t.dilationDepth,i=t.dilationHeight,a=t.dilationWidth,u=t.effectiveFilterDepth,l=t.effectiveFilterHeight,c=t.effectiveFilterWidth,p=u-1-t.padInfo.front,m=l-1-t.padInfo.top,f=c-1-t.padInfo.left,d=u*l*c-1;this.userCode=`
      const ivec3 pads = ivec3(${p}, ${m}, ${f});

      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 < ${u};
           wD += ${s}) {
          float dyD = float(dyDCorner + wD) / ${e}.0;

          if (dyD < 0.0 || dyD >= ${t.outDepth}.0 || fract(dyD) > 0.0) {
            continue;
          }
          int idyD = int(dyD);

          for (int wR = 0; wR < ${l};
              wR += ${i}) {
            float dyR = float(dyRCorner + wR) / ${n}.0;

            if (dyR < 0.0 || dyR >= ${t.outHeight}.0 ||
                fract(dyR) > 0.0) {
              continue;
            }
            int idyR = int(dyR);

            for (int wC = 0; wC < ${c};
                wC += ${a}) {
              float dyC = float(dyCCorner + wC) / ${o}.0;

              if (dyC < 0.0 || dyC >= ${t.outWidth}.0 ||
                  fract(dyC) > 0.0) {
                continue;
              }
              int idyC = int(dyC);

              float dyValue = getDy(batch, idyD, idyR, idyC, ch);
              int maxPosValue = ${d} -
                  int(getMaxPos(batch, idyD, idyR, idyC, ch));

              // Get the current value, check it against the value from the
              // position matrix.
              int curPosValue =
                  wD * ${l} * ${c} +
                  wR * ${c} + wC;
              float mask = float(maxPosValue == curPosValue ? 1.0 : 0.0);

              dotProd += dyValue * mask;
            }
          }
        }
        setOutput(dotProd);
      }
    `}};function bnt(r){let{inputs:t,backend:e,attrs:n}=r,{dy:o,input:s}=t,i=s,{filterSize:a,strides:u,pad:l,dimRoundingMode:c}=n,p=[1,1,1],m=S.computePool3DInfo(i.shape,a,u,p,l,c),f=new Au(m,"max",!0),d=e.runWebGLProgram(f,[i],i.dtype),h=new qv(m),g=e.runWebGLProgram(h,[o,d],i.dtype);return e.disposeIntermediateTensorInfo(d),g}var d3={kernelName:Bp,backendName:"webgl",kernelFunc:bnt};function wnt(r){let{inputs:t,backend:e,attrs:n}=r,{dy:o,input:s,output:i}=t,a=s;ni([s,i],"maxPoolGrad");let{filterSize:u,strides:l,pad:c,dimRoundingMode:p}=n,m=S.computePool2DInfo(a.shape,u,l,1,c,p),f=!0,d=new si(m,"max",f),h=e.runWebGLProgram(d,[a],a.dtype),g=new Hv(m),y=e.runWebGLProgram(g,[o,h],a.dtype);return e.disposeIntermediateTensorInfo(h),y}var h3={kernelName:zp,backendName:"webgl",kernelFunc:wnt};function g3(r,t,e,n){let o=new si(e,"max",!1),s=n.runWebGLProgram(o,[r],"float32");o=new si(e,"max",!0,!0,t);let i=n.runWebGLProgram(o,[r],"float32");return[s,i]}var x3={kernelName:Vp,backendName:"webgl",kernelFunc:({inputs:r,attrs:t,backend:e})=>{let{x:n}=r,{filterSize:o,strides:s,pad:i,includeBatchInIndex:a}=t,u=e;x.assert(n.shape.length===4,()=>`Error in maxPool: input must be rank 4 but got rank ${n.shape.length}.`);let l=[1,1];x.assert(S.eitherStridesOrDilationsAreOne(s,l),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${s} and dilations '${l}'`);let c=S.computePool2DInfo(n.shape,o,s,l,i),[p,m]=g3(n,a,c,u);return[p,m]}};function y3(r,t,e,n){let o=x.sizeFromShape(t),i=x.sizeFromShape(r.shape)/o,a=at({inputs:{x:r},attrs:{shape:[i,o]},backend:n}),u=Un(a,"float32","mean",n),l=at({inputs:{x:u},attrs:{shape:e},backend:n});return n.disposeIntermediateTensorInfo(a),n.disposeIntermediateTensorInfo(u),l}var b3={kernelName:gs,backendName:"webgl",kernelFunc:({inputs:r,attrs:t,backend:e})=>{let{x:n}=r,{keepDims:o,axis:s}=t,i=e,a=n.shape.length,u=x.parseAxisParam(s,n.shape),l=u,c=S.getAxesPermutation(l,a),p=c!=null,m=i.shouldExecuteOnCPU([n]),f=[],d=n;if(p){if(m){let v=i.texData.get(d.dataId).values,N=new Array(a);for(let D=0;D<N.length;D++)N[D]=n.shape[c[D]];let E=Kc(v,n.shape,n.dtype,c,N);d=i.makeTensorInfo(N,n.dtype);let $=i.texData.get(d.dataId);$.values=E}else d=Eu(n,c,i);f.push(d),l=S.getInnerMostAxes(l.length,a)}S.assertAxesAreInnerMostDims("sum",l,a);let[h,g]=S.computeOutAndReduceShapes(d.shape,l),y=h;o&&(y=S.expandShapeToKeepDim(h,u));let b=y3(d,g,y,i);for(let w of f)i.disposeIntermediateTensorInfo(w);return b}};function vnt(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{axis:s,keepDims:i}=n,a=o.shape.length,u=x.parseAxisParam(s,o.shape),l=u,c=S.getAxesPermutation(l,a),p=o;c!=null&&(p=Pe({inputs:{x:o},backend:e,attrs:{perm:c}}),l=S.getInnerMostAxes(l.length,o.shape.length)),S.assertAxesAreInnerMostDims("min",l,a);let[m,f]=S.computeOutAndReduceShapes(p.shape,l),d=x.sizeFromShape(f),h=at({inputs:{x:p},backend:e,attrs:{shape:[-1,d]}}),g=Un(h,h.dtype,"min",e),y;if(i){let b=S.expandShapeToKeepDim(m,u);y=at({inputs:{x:g},backend:e,attrs:{shape:b}})}else y=at({inputs:{x:g},backend:e,attrs:{shape:m}});return e.disposeIntermediateTensorInfo(h),e.disposeIntermediateTensorInfo(g),c!=null&&e.disposeIntermediateTensorInfo(p),y}var w3={kernelName:xs,backendName:"webgl",kernelFunc:vnt};var Cnt=Yw+`
  return min(a, b);
`,Int=`
  vec4 result = vec4(min(a, b));
  vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
  `+Tu+`
  return result;
`,Snt=ce({opSnippet:Cnt,packedOpSnippet:Int,cpuKernelImpl:SP}),v3={kernelName:ys,backendName:"webgl",kernelFunc:Snt};var Kv=class{constructor(t,e,n){this.variableNames=["x"],this.outputShape=e.map((c,p)=>c[0]+t[p]+c[1]);let o=t.length,s=Wt(o),i=e.map(c=>c[0]).join(","),a=e.map((c,p)=>c[0]+t[p]).join(","),u=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,o),l=n==="reflect"?0:1;if(o===1){this.userCode=`
        int start = ${i};
        int end = ${a};

        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=`
      ${s} start = ${s}(${i});
      ${s} end = ${s}(${a});

      void main() {
        ${s} outC = getOutputCoords();
        for (int i = 0; i < ${o}; 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};
          }
        }
        ${s} coords = outC - start;
        setOutput(getX(${u}));
      }
    `}};var jv=class{constructor(t,e,n){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e.map((d,h)=>d[0]+t[h]+d[1]);let o=t.length,s=Wt(o),i=e.map(d=>d[0]).join(","),a=e.map((d,h)=>d[0]+t[h]).join(","),u=tr("rc",o),l=tr("source",o),c=`${u[o-1]} < ${this.outputShape[o-1]}`,p=o===1?"source":`vec2(${l.slice(-2).join()})`,m=n==="reflect"?0:1,f="";if(o===1){let d=`
        ${s} source = rc;
        if (source < start) {
          source = start * 2 - source - ${m};
        } else if (source >= end) {
          source = (end - 1) * 2 - source + ${m};
        }
        source -= start;
      `;f=`
        ${s} rc = outputLoc;
        ${d}
        result[0] = getChannel(getX(${l.join()}), ${p});
        ${u[o-1]} += 1;
        if(${c}) {
          ${d}
          result[1] = getChannel(getX(${l.join()}), ${p});
        }
      `}else{let d=`
        ${s} source = rc;
        ${s} lt = ${s}(lessThan(source, start));
        ${s} gte = ${s}(greaterThanEqual(source, end));
        ${s} orig = 1 - (lt + gte);
        source = orig * source +
                lt * (start * 2 - source - ${m}) +
                gte * ((end - 1) * 2 - source + ${m});
        source -= start;
      `;f=`
        ${s} rc = outputLoc;
        ${d}
        result[0] = getChannel(getX(${l.join()}), ${p});
        ${u[o-1]} += 1;
        if(${c}) {
          ${d}
          result[1] = getChannel(getX(${l.join()}), ${p});
        }
        rc = outputLoc;
        ${u[o-2]} += 1;
        if(${u[o-2]} < ${this.outputShape[o-2]}) {
          ${d}
          result[2] = getChannel(getX(${l.join()}), ${p});
          ${u[o-1]} += 1;
          if(${c}) {
            ${d}
            result[3] = getChannel(getX(${l.join()}), ${p});
          }
        }
      `}this.userCode=`
      const ${s} start = ${s}(${i});
      const ${s} end = ${s}(${a});

      void main() {
        ${s} outputLoc = getOutputCoords();
        vec4 result = vec4(0.);
        ${f}
        setOutput(result);
      }
    `}};var Nnt=({inputs:r,backend:t,attrs:e})=>{let{x:n}=r,{paddings:o,mode:s}=e,i=B().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new jv(n.shape,o,s):new Kv(n.shape,o,s);return t.runWebGLProgram(i,[n],n.dtype)},C3={kernelName:bs,backendName:"webgl",kernelFunc:Nnt};var knt=`if (b == 0.0) return NAN;
  return mod(a, b);`,Tnt=`
  vec4 result = mod(a, b);
  vec4 isNaN = vec4(equal(b, vec4(0.0)));
  `+Tu+`
  return result;
`,_nt=ce({opSnippet:knt,packedOpSnippet:Tnt}),I3={kernelName:_a,backendName:"webgl",kernelFunc:_nt};var Xv=class{constructor(t,e,n){this.variableNames=["probs"],this.customUniforms=[{name:"seed",type:"float"}],this.outputShape=[t,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 < ${e-1}; i++) {
          cdf += getProbs(batch, i);

          if (r < cdf) {
            setOutput(float(i));
            return;
          }
        }

        // If no other event happened, last event happened.
        setOutput(float(${e-1}));
      }
    `}};var Ent=`
if (a == b) {
  return 1.0;
};
return a / b;`,Ant=`
  // 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;
`,kT=ce({opSnippet:Ent,packedOpSnippet:Ant,checkOutOfBounds:!0}),S3={kernelName:os,backendName:"webgl",kernelFunc:kT};var N3="return a - b;",TT=ce({opSnippet:N3,packedOpSnippet:N3,supportsComplex:!0,cpuKernelImpl:VP}),k3={kernelName:zs,backendName:"webgl",kernelFunc:TT};function _T(r){let{inputs:t,backend:e,attrs:n}=r,{logits:o}=t,{dim:s}=n,i=x.parseAxisParam([s],o.shape),a=NT({inputs:{x:o},backend:e,attrs:{reductionIndices:i,keepDims:!1}}),u=S.expandShapeToKeepDim(a.shape,i),l=at({inputs:{x:a},backend:e,attrs:{shape:u}}),c=TT({inputs:{a:o,b:l},backend:e}),p=IT({inputs:{x:c},backend:e}),m=Xc({inputs:{x:p},backend:e,attrs:{axis:i,keepDims:!1}}),f=at({inputs:{x:m},backend:e,attrs:{shape:u}}),d=kT({inputs:{a:p,b:f},backend:e});return e.disposeIntermediateTensorInfo(a),e.disposeIntermediateTensorInfo(l),e.disposeIntermediateTensorInfo(c),e.disposeIntermediateTensorInfo(p),e.disposeIntermediateTensorInfo(m),e.disposeIntermediateTensorInfo(f),d}var T3={kernelName:Ps,backendName:"webgl",kernelFunc:_T};function $nt(r){let{inputs:t,backend:e,attrs:n}=r,{logits:o}=t,{numSamples:s,seed:i,normalized:a}=n,u=a?o:_T({inputs:{logits:o},backend:e,attrs:{dim:o.shape.length-1}}),l=u.shape[0],c=u.shape[1],p=new Xv(l,c,s),m=[[i]],f=e.runWebGLProgram(p,[u],"int32",m);return a||e.disposeIntermediateTensorInfo(u),f}var _3={kernelName:Gp,backendName:"webgl",kernelFunc:$nt};var Dnt=fr+`
  return -x;
`,Fnt=`
  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 Rnt(r){let{inputs:t,backend:e}=r,{x:n}=t;if(e.shouldExecuteOnCPU([n])){let s=e.texData.get(n.dataId),[i,a]=kP(s.values,n.shape,n.dtype);return e.makeTensorInfo(a,n.dtype,i)}let o;return B().getBool("WEBGL_PACK_UNARY_OPERATIONS")?o=new eo(n.shape,Fnt):o=new Zr(n.shape,Dnt),e.runWebGLProgram(o,[n],n.dtype)}var E3={kernelName:hi,backendName:"webgl",kernelFunc:Rnt};var Ont=Vr.nonMaxSuppressionV3Impl;function Lnt(r){S.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:e,attrs:n}=r,{boxes:o,scores:s}=t,{maxOutputSize:i,iouThreshold:a,scoreThreshold:u}=n,l=e.readSync(o.dataId),c=e.readSync(s.dataId),{selectedIndices:p}=Ont(l,c,i,a,u);return e.makeTensorInfo([p.length],"int32",new Int32Array(p))}var A3={kernelName:Aa,backendName:"webgl",kernelFunc:Lnt};var Pnt=Vr.nonMaxSuppressionV4Impl;function Mnt(r){S.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:e,attrs:n}=r,{boxes:o,scores:s}=t,{maxOutputSize:i,iouThreshold:a,scoreThreshold:u,padToMaxOutputSize:l}=n,c=e.readSync(o.dataId),p=e.readSync(s.dataId),{selectedIndices:m,validOutputs:f}=Pnt(c,p,i,a,u,l);return[e.makeTensorInfo([m.length],"int32",new Int32Array(m)),e.makeTensorInfo([],"int32",new Int32Array([f]))]}var $3={kernelName:$a,backendName:"webgl",kernelFunc:Mnt};var znt=Vr.nonMaxSuppressionV5Impl;function Bnt(r){S.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:e,attrs:n}=r,{boxes:o,scores:s}=t,{maxOutputSize:i,iouThreshold:a,scoreThreshold:u,softNmsSigma:l}=n,c=e.readSync(o.dataId),p=e.readSync(s.dataId),m=i,f=a,d=u,h=l,{selectedIndices:g,selectedScores:y}=znt(c,p,m,f,d,h);return[e.makeTensorInfo([g.length],"int32",new Int32Array(g)),e.makeTensorInfo([y.length],"float32",new Float32Array(y))]}var D3={kernelName:Da,backendName:"webgl",kernelFunc:Bnt};var Yv=class{constructor(t,e,n,o){this.variableNames=["indices"],this.outputShape=[t,e],this.userCode=`
      void main() {
        ivec2 coords = getOutputCoords();
        int index = round(getIndices(coords.x));
        setOutput(mix(float(${o}), float(${n}),
                      float(index == coords.y)));
      }
    `}};var Vnt=r=>{let{inputs:t,backend:e,attrs:n}=r,{indices:o}=t,{depth:s,onValue:i,offValue:a}=n,u=x.sizeFromShape(o.shape),l=new Yv(u,s,i,a),c=at({inputs:{x:o},backend:e,attrs:{shape:[u]}}),p=e.runWebGLProgram(l,[c],o.dtype);e.disposeIntermediateTensorInfo(c);let m=[...o.shape,s],f=at({inputs:{x:p},backend:e,attrs:{shape:m}});return e.disposeIntermediateTensorInfo(p),f},F3={kernelName:vs,backendName:"webgl",kernelFunc:Vnt};function ug(r){let{inputs:t,backend:e}=r,{x:n}=t;if(n.dtype==="complex64"){let o=hl({inputs:{input:n},backend:e}),s=ug({inputs:{x:o},backend:e}),i=Zc({inputs:{input:n},backend:e}),a=ug({inputs:{x:i},backend:e}),u=An({inputs:{real:s,imag:a},backend:e});return e.disposeIntermediateTensorInfo(o),e.disposeIntermediateTensorInfo(s),e.disposeIntermediateTensorInfo(i),e.disposeIntermediateTensorInfo(a),u}else return gl({attrs:{shape:n.shape,dtype:n.dtype,value:n.dtype==="string"?"":0},backend:e})}var R3={kernelName:Si,backendName:"webgl",kernelFunc:ug};function O3(r){let{inputs:t,backend:e}=r,{x:n}=t;if(n.dtype==="string")throw new Error("onesLike is not supported under string dtype");if(n.dtype==="complex64"){let o=hl({inputs:{input:n},backend:e}),s=O3({inputs:{x:o},backend:e}),i=Zc({inputs:{input:n},backend:e}),a=ug({inputs:{x:i},backend:e}),u=An({inputs:{real:s,imag:a},backend:e});return e.disposeIntermediateTensorInfo(o),e.disposeIntermediateTensorInfo(s),e.disposeIntermediateTensorInfo(i),e.disposeIntermediateTensorInfo(a),u}else return gl({attrs:{shape:n.shape,dtype:n.dtype,value:1},backend:e})}var L3={kernelName:gi,backendName:"webgl",kernelFunc:O3};function Gnt(r){let{inputs:t,backend:e,attrs:n}=r,{axis:o}=n;if(t.length===1)return Rv({inputs:{input:t[0]},backend:e,attrs:{dim:o}});let s=t[0].shape,i=t[0].dtype;t.forEach(c=>{x.assertShapesMatch(s,c.shape,"All tensors passed to stack must have matching shapes"),x.assert(i===c.dtype,()=>"All tensors passed to stack must have matching dtypes")});let a=[],u=t.map(c=>{let p=Rv({inputs:{input:c},backend:e,attrs:{dim:o}});return a.push(p),p}),l=CT({inputs:u,backend:e,attrs:{axis:o}});return a.forEach(c=>e.disposeIntermediateTensorInfo(c)),l}var P3={kernelName:xi,backendName:"webgl",kernelFunc:Gnt};var Zv=class{constructor(t,e,n){this.variableNames=["x"],this.customUniforms=[{name:"value",type:"float"}],this.outputShape=e.map((l,c)=>l[0]+t[c]+l[1]);let o=t.length,s=Wt(o),i=e.map(l=>l[0]).join(","),a=e.map((l,c)=>l[0]+t[c]).join(","),u=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,o);if(o===1){this.userCode=`
        int start = ${i};
        int end = ${a};

        void main() {
          int outC = getOutputCoords();
          if (outC < start || outC >= end) {
            setOutput(value);
          } else {
            setOutput(getX(outC - start));
          }
        }
      `;return}this.userCode=`
      ${s} start = ${s}(${i});
      ${s} end = ${s}(${a});

      void main() {
        ${s} outC = getOutputCoords();
        if (any(lessThan(outC, start)) || any(greaterThanEqual(outC, end))) {
          setOutput(value);
        } else {
          ${s} coords = outC - start;
          setOutput(getX(${u}));
        }
      }
    `}};var Jv=class{constructor(t,e,n){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"value",type:"float"}],this.outputShape=e.map((h,g)=>h[0]+t[g]+h[1]);let o=t.length,s=Wt(o),i=e.map(h=>h[0]).join(","),a=e.map((h,g)=>h[0]+t[g]).join(","),u=tr("rc",o),l=tr("source",o),c=`${u[o-1]} < ${this.outputShape[o-1]}`,p=o===1?"source":`vec2(${l.slice(-2).join()})`,m=[`${s} rc = outputLoc;`,`${u[o-1]} += 1;
       if(${c}) {
      `,o===1?"":`}
       rc = outputLoc;
       ${u[o-2]} += 1;
       if(${u[o-2]} < ${this.outputShape[o-2]}) {`,o===1?"":`  ${u[o-1]} += 1;
         if(${c}) {`],f=o===1?"rc < start || rc >= end":"any(lessThan(rc, start)) || any(greaterThanEqual(rc, end))",d="";for(let h=0,g=o===1?2:4;h<g;h++)d+=`
        ${m[h]}
        if (${f}) {
          result[${h}] = float(value);
        } else {
          ${s} source = rc - start;
          result[${h}] = getChannel(getX(${l.join()}), ${p});
        }
      `;d+=o===1?"} ":"}}",this.userCode=`
      const ${s} start = ${s}(${i});
      const ${s} end = ${s}(${a});

      void main() {
        ${s} outputLoc = getOutputCoords();
        vec4 result = vec4(0.);
        ${d}
        setOutput(result);
      }
    `}};var ET=r=>{let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{paddings:s,constantValue:i}=n;if(x.sizeFromShape(o.shape)===0){let l=s.map((c,p)=>c[0]+o.shape[p]+c[1]);return gl({backend:e,attrs:{shape:l,value:i,dtype:o.dtype}})}let a=B().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new Jv(o.shape,s,i):new Zv(o.shape,s,i),u=[[i]];return e.runWebGLProgram(a,[o],o.dtype,u)},M3={kernelName:Cs,backendName:"webgl",kernelFunc:ET};var Wnt=`
  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);
`,Unt=`
  // isModRound1 has 1 for components with round(mod(b, 2.0)) == 1, 0 otherwise.
  vec4 isModRound1 = vec4(equal(round(mod(b, 2.0)), ivec4(1)));
  vec4 multiplier = sign(a) * isModRound1 + (vec4(1.0) - isModRound1);
  vec4 result = multiplier * pow(abs(a), b);

  // Ensure that a^0 = 1, including 0^0 = 1 as this correspond to TF and JS
  bvec4 isExpZero = equal(b, vec4(0.0));
  result.r = isExpZero.r ? 1.0 : result.r;
  result.g = isExpZero.g ? 1.0 : result.g;
  result.b = isExpZero.b ? 1.0 : result.b;
  result.a = isExpZero.a ? 1.0 : result.a;

  vec4 isNaN = vec4(lessThan(a, vec4(0.0))) * vec4(lessThan(floor(b), b));
  `+Tu+`
  return result;
`,Hnt=ce({opSnippet:Wnt,packedOpSnippet:Unt}),z3={kernelName:Is,backendName:"webgl",kernelFunc:Hnt};function qnt(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{axis:s,keepDims:i}=n,a=o.shape.length,u=[],l=x.parseAxisParam(s,o.shape),c=l,p=S.getAxesPermutation(c,a),m=o;p!=null&&(m=Pe({inputs:{x:o},backend:e,attrs:{perm:p}}),c=S.getInnerMostAxes(c.length,a),u.push(m)),S.assertAxesAreInnerMostDims("prod",c,a);let f;if(e.shouldExecuteOnCPU([m])){let d=e.texData.get(m.dataId).values,{outVals:h,outShape:g,outDtype:y}=_P(m.shape,m.dtype,d,c);f=e.makeTensorInfo(g,y,h)}else{let[d,h]=S.computeOutAndReduceShapes(m.shape,c),g=x.sizeFromShape(h),y=at({inputs:{x:m},backend:e,attrs:{shape:[-1,g]}}),b=Ku(o.dtype),w=Un(y,b,"prod",e);f=at({inputs:{x:w},backend:e,attrs:{shape:d}}),u.push(y),u.push(w)}if(i){u.push(f);let d=S.expandShapeToKeepDim(f.shape,l);f=at({inputs:{x:f},backend:e,attrs:{shape:d}})}return u.forEach(d=>e.disposeIntermediateTensorInfo(d)),f}var B3={kernelName:Ns,backendName:"webgl",kernelFunc:qnt};var AT=r=>{let{backend:t,attrs:e}=r,{start:n,stop:o,step:s,dtype:i}=e,a=EP(n,o,s,i);return t.makeTensorInfo([a.length],i,a)},V3={kernelName:Al,backendName:"webgl",kernelFunc:AT};var Knt="return 1.0 / x;",jnt=It({opSnippet:Knt}),G3={kernelName:Fa,backendName:"webgl",kernelFunc:jnt};var Xnt=fr+`
  return (x < 0.0) ? 0.0 : x;
`,Ynt=`
  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;
`,Znt=It({opSnippet:Xnt,packedOpSnippet:Ynt}),W3={kernelName:ks,backendName:"webgl",kernelFunc:Znt};var Jnt=fr+`
  return (x < 0.0) ? 0.0 : min(6.0, x);
`,Qnt=`
  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;
`,tot=It({opSnippet:Jnt,packedOpSnippet:Qnt}),U3={kernelName:Es,backendName:"webgl",kernelFunc:tot};var Qv=class{constructor(t,e,n,o,s){this.variableNames=["A"],this.outputShape=[];let[i,a,u,l]=t;this.outputShape=[i,e,n,l];let c=[o&&e>1?a-1:a,o&&n>1?u-1:u],p=[o&&e>1?e-1:e,o&&n>1?n-1:n],m;s?m="(vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC - vec2(0.5)":m="vec2(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
      const vec2 effectiveInputOverOutputRatioRC = vec2(
          ${c[0]/p[0]},
          ${c[1]/p[1]});
      const vec2 inputShapeRC = vec2(${a}.0, ${u}.0);

      void main() {
        ivec4 coords = getOutputCoords();
        int b = coords[0];
        int d = coords[3];
        ivec2 yRC = coords.yz;

        // Fractional source index.
        vec2 sourceFracIndexRC = ${m};

        // 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);
      }
    `}};var tC=class{constructor(t,e,n,o,s){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[];let[i,a,u,l]=t;this.outputShape=[i,e,n,l];let c=[o&&e>1?a-1:a,o&&n>1?u-1:u],p=[o&&e>1?e-1:e,o&&n>1?n-1:n],m;s?m="(vec3(yRC) + vec3(0.5)) * effectiveInputOverOutputRatioRC - vec3(0.5)":m="vec3(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
      const vec3 effectiveInputOverOutputRatioRC = vec3(
          ${c[0]/p[0]},
          ${c[1]/p[1]},
          ${c[1]/p[1]});
      const vec3 inputShapeRC = vec3(${a}.0, ${u}.0,
                                     ${u}.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 = ${m};

        // 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 eot(r){let{inputs:t,backend:e,attrs:n}=r,{images:o}=t,{alignCorners:s,halfPixelCenters:i,size:a}=n,[u,l]=a,c=B().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new tC(o.shape,u,l,s,i):new Qv(o.shape,u,l,s,i);return e.runWebGLProgram(c,[o],"float32")}var H3={kernelName:_s,backendName:"webgl",kernelFunc:eot};var eC=class{constructor(t,e,n){this.variableNames=["dy"],this.outputShape=[],this.outputShape=e;let[,o,s]=e,[,i,a]=t,u=[n&&i>1?o-1:o,n&&a>1?s-1:s],l=[n&&i>1?i-1:i,n&&a>1?a-1:a],c=u[0]/l[0],p=u[1]/l[1],m=1/c,f=1/p,d=Math.ceil(m)*2+2,h=Math.ceil(f)*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(${c});
        const float widthScale = float(${p});

        const float invHeightScale = float(${m});
        const float invWidthScale = float(${f});

        const int winHeight = int(${d});
        const int winWidth = int(${h});

        // 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 >= ${i}) {
            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 >= ${a}) {
              continue;
            }

            float dxR = float(dyR) * heightScale;
            int topDxRIndex = int(floor(dxR));
            int bottomDxRIndex = int(min(ceil(dxR), ${o-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), ${s-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 rot(r){let{inputs:t,backend:e,attrs:n}=r,{images:o,dy:s}=t,{alignCorners:i}=n,a=new eC(s.shape,o.shape,i);return e.runWebGLProgram(a,[s],s.dtype)}var q3={kernelName:Hp,backendName:"webgl",kernelFunc:rot};var rC=class{constructor(t,e,n,o,s){this.variableNames=["A"],this.outputShape=[];let[i,a,u,l]=t;this.outputShape=[i,e,n,l];let c=[o&&e>1?a-1:a,o&&n>1?u-1:u],p=[o&&e>1?e-1:e,o&&n>1?n-1:n],m=o?"0.5":"0.0",f;s?f="max((vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC, vec2(0.0))":f="vec2(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
      const vec2 effectiveInputOverOutputRatioRC = vec2(
          ${c[0]/p[0]},
          ${c[1]/p[1]});
      const vec2 inputShapeRC = vec2(${a}.0, ${u}.0);

      void main() {
        ivec4 coords = getOutputCoords();
        int b = coords[0];
        int d = coords[3];
        ivec2 yRC = coords.yz;

        // Fractional source index.
        vec2 sourceFracIndexRC = ${f};

        // Compute the coordinators of nearest neighbor point.
        ivec2 sourceNearestRC = ivec2(
          min(inputShapeRC - 1.0, floor(sourceFracIndexRC + ${m})));
        float newValue = getA(b, sourceNearestRC.x, sourceNearestRC.y, d);

        setOutput(newValue);
      }
    `}};var nC=class{constructor(t,e,n,o,s){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[];let[i,a,u,l]=t;this.outputShape=[i,e,n,l];let c=[o&&e>1?a-1:a,o&&n>1?u-1:u],p=[o&&e>1?e-1:e,o&&n>1?n-1:n],m=o?"0.5":"0.0",f;s?f="max((vec3(yRC) + vec3(0.5)) * effectiveInputOverOutputRatioRC, vec3(0.0))":f="vec3(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
      const vec3 effectiveInputOverOutputRatioRC = vec3(
          ${c[0]/p[0]},
          ${c[1]/p[1]},
          ${c[1]/p[1]});
      const vec3 inputShapeRC = vec3(${a}.0, ${u}.0,
                                     ${u}.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 = ${f};

        // Compute the coordinators of nearest neighbor point.
        ivec3 sourceNearestRC = ivec3(
          min(inputShapeRC - 1.0, floor(sourceFracIndexRC + ${m})));

        // 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 not(r){let{inputs:t,backend:e,attrs:n}=r,{images:o}=t,{alignCorners:s,halfPixelCenters:i,size:a}=n,[u,l]=a,c=B().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new nC(o.shape,u,l,s,i):new rC(o.shape,u,l,s,i);return e.runWebGLProgram(c,[o],o.dtype)}var K3={kernelName:Ts,backendName:"webgl",kernelFunc:not};var oC=class{constructor(t,e,n){this.variableNames=["dy"],this.outputShape=[],this.outputShape=e;let[,o,s]=e,[,i,a]=t,u=[n&&i>1?o-1:o,n&&a>1?s-1:s],l=[n&&i>1?i-1:i,n&&a>1?a-1:a],c=u[0]/l[0],p=u[1]/l[1],m=1/c,f=1/p,d=Math.ceil(m)*2+2,h=Math.ceil(f)*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(${c});
        const float widthScale = float(${p});

        const float invHeightScale = float(${m});
        const float invWidthScale = float(${f});

        const int winHeight = int(${d});
        const int winWidth = int(${h});

        // 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 >= ${i}) {
            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 >= ${a}) {
              continue;
            }

            float sourceFracRow =
              float(${u[0]}) *
                (float(dyR) / float(${l[0]}));

            float sourceFracCol =
                float(${u[1]}) *
                  (float(dyC) / float(${l[1]}));

            int sourceNearestRow = int(min(
                float(int(${o}) - 1),
                ${n} ? float(round(sourceFracRow)) :
                                  float(floor(sourceFracRow))));

            int sourceNearestCol = int(min(
                float(int(${s}) - 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 oot(r){let{inputs:t,backend:e,attrs:n}=r,{images:o,dy:s}=t,{alignCorners:i}=n,a=new oC(s.shape,o.shape,i);return e.runWebGLProgram(a,[s],s.dtype)}var j3={kernelName:Up,backendName:"webgl",kernelFunc:oot};var sC=class{constructor(t,e){this.variableNames=["x"];let n=t.length;if(n>4)throw new Error(`WebGL backend: Reverse of rank-${n} tensor is not yet supported`);if(this.outputShape=t,n===1){this.userCode=`
        void main() {
          int coord = getOutputCoords();
          setOutput(getX(${t[0]} - coord - 1));
        }
      `;return}let o=a=>e.indexOf(a)!==-1&&t[a]!==1?`${t[a]} - coords[${a}] - 1`:`coords[${a}]`,s=t.map((a,u)=>o(u)).join(","),i=Wt(n);this.userCode=`
      void main() {
        ${i} coords = getOutputCoords();
        setOutput(getX(${s}));
      }
    `}};var iC=class{constructor(t,e){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0;let n=t.length;if(n>4)throw new Error(`WebGL backend: Reverse of rank-${n} tensor is not yet supported`);this.outputShape=t;let o=tr("rc",n),s=`${o[n-1]} + 1 < ${this.outputShape[n-1]}`,i=`${o[n-2]} + 1 < ${this.outputShape[n-2]}`,a=Wt(n);n===1?this.userCode=`
        void main(){
          int rc = getOutputCoords();
          vec4 result = vec4(0.);
          result.r = getChannel(getX(${t[0]} - rc - 1),
            ${t[0]} - rc - 1);
          if(${s}){
              result.g = getChannel(getX(${t[0]} - (rc  + 1) - 1),
                ${t[0]} - (rc  + 1) - 1);
          }
          setOutput(result);
        }
      `:this.userCode=`
        void main() {
          ${a} rc = getOutputCoords();
          vec4 result = vec4(0.);
          result.r = ${u(o.slice())};
          if(${s}){
            result.g = ${l(o.slice())};
          }
          if(${i}) {
            result.b = ${c(o.slice())};
            if(${s}) {
              result.a = ${p(o.slice())};
            }
          }
          setOutput(result);
        }
    `;function u(d){return m(d)}function l(d){return d[n-1]="("+d[n-1]+" + 1)",m(d)}function c(d){return d[n-2]="("+d[n-2]+" + 1)",m(d)}function p(d){return d[n-1]="("+d[n-1]+" + 1)",d[n-2]="("+d[n-2]+" + 1)",m(d)}function m(d){let h=t.map((b,w)=>f(w,d)),g=h.join(","),y=h.slice(-2).join(",");return`getChannel(getX(${g}), vec2(${y}))`}function f(d,h){return e.indexOf(d)!==-1&&t[d]!==1?`${t[d]} - ${h[d]} - 1`:`${h[d]}`}}};function sot(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{dims:s}=n,i=o.shape.length,a=x.parseAxisParam(s,o.shape);if(i===0)return er({inputs:{x:o},backend:e});let u=B().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new iC(o.shape,a):new sC(o.shape,a);return e.runWebGLProgram(u,[o],o.dtype)}var X3={kernelName:As,backendName:"webgl",kernelFunc:sot};var aC=class{constructor(t,e){this.variableNames=["Image"],this.outputShape=[],this.customUniforms=[{name:"params",type:"vec4"}];let n=t[1],o=t[2];this.outputShape=t;let s="";typeof e=="number"?s=`float outputValue = ${e.toFixed(2)};`:s=`
        vec3 fill = vec3(${e.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]));
          ${s}
          if(coordX >= 0 && coordX < ${o} && coordY >= 0 && coordY < ${n}) {
            outputValue = getImage(coords[0], coordY, coordX, coords[3]);
          }
          setOutput(outputValue);
        }
    `}};var Y3={kernelName:Wa,backendName:"webgl",kernelFunc:({inputs:r,attrs:t,backend:e})=>{let{image:n}=r,{radians:o,fillValue:s,center:i}=t,a=e,u=new aC(n.shape,s),[l,c]=S.getImageCenter(i,n.shape[1],n.shape[2]),p=[[l,c,Math.sin(o),Math.cos(o)]];return a.runWebGLProgram(u,[n],n.dtype,p)}};var iot=`
  // OpenGL ES does not support round function.
  // The algorithm is based on banker's rounding.
  float base = floor(x);
  if ((x - base) < 0.5) {
    return floor(x);
  } else if ((x - base) > 0.5) {
    return ceil(x);
  } else {
    if (mod(base, 2.0) == 0.0) {
      return base;
    } else {
      return base + 1.0;
    }
  }
`,aot=It({opSnippet:iot}),Z3={kernelName:$s,backendName:"webgl",kernelFunc:aot};var lot="return inversesqrt(x);",uot=It({opSnippet:lot,cpuKernelImpl:AP}),J3={kernelName:Ds,backendName:"webgl",kernelFunc:uot};var Rd=class{constructor(t,e,n,o,s,i,a=!0){this.variableNames=["updates","indices","defaultValue"],this.outputShape=i;let u=Wt(s.length),l=Wt(i.length),c="";n===1?c="i":n===2&&(c="i, j");let p=`getIndices(${c})`,m="";o===1?m="i":o===2&&(m="i, coords[1]");let f=`getUpdates(${m})`,d=e>1?"strides[j]":"strides";this.userCode=`
        ${u} strides = ${u}(${s});

        void main() {
          ${l} coords = getOutputCoords();
          float sum = 0.0;
          bool found = false;
          for (int i = 0; i < ${t}; i++) {
            int flattenedIndex = 0;
            for (int j = 0; j < ${e}; j++) {
              int index = round(${p});
              flattenedIndex += index * ${d};
            }
            if (flattenedIndex == coords[0]) {
              sum += ${f};
              found = true;
            }
          }
          setOutput(mix(getDefaultValue(), sum, float(found)));
        }
      `}};function cot(r){let{inputs:t,backend:e,attrs:n}=r,{indices:o,updates:s}=t,{shape:i}=n,{sliceRank:a,numUpdates:u,sliceSize:l,strides:c,outputSize:p}=S.calculateShapes(s,o,i),m=[p/l,l];if(p===0)return e.makeTensorInfo(i,o.dtype);let f=at({inputs:{x:o},backend:e,attrs:{shape:[u,a]}}),d=at({inputs:{x:s},backend:e,attrs:{shape:[u,l]}}),h=e.makeTensorInfo([],"float32",new Float32Array([0])),g=new Rd(u,a,f.shape.length,d.shape.length,c,m),y=e.runWebGLProgram(g,[d,f,h],d.dtype),b=at({inputs:{x:y},backend:e,attrs:{shape:i}});return e.disposeIntermediateTensorInfo(f),e.disposeIntermediateTensorInfo(d),e.disposeIntermediateTensorInfo(y),e.disposeIntermediateTensorInfo(h),b}var Q3={kernelName:Ra,backendName:"webgl",kernelFunc:cot};var lC=class{constructor(t,e,n,o){this.variableNames=["sortedSequence","values"],this.customUniforms=[{name:"numInputs",type:"int"}],this.outputShape=[t,n];let s="while (left < right) {",i=`for (int i = 0; i < ${Math.ceil(Math.log2(e+1))}; ++i) { if (left >= right) break;`,a=B().getNumber("WEBGL_VERSION")===2?s:i,u=o==="left"?"<":"<=";this.userCode=`
       int findBound(int batch, float value) {
         int left = 0;
         int right = numInputs;
         int mid;
         ${a}
           mid = (left + right) / 2;
           if (getSortedSequence(batch, mid) ${u} 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 pot(r){let{inputs:t,backend:e,attrs:n}=r,{sortedSequence:o,values:s}=t,{side:i}=n,a=new lC(o.shape[0],o.shape[1],s.shape[1],i),u=[[o.shape[1]]];return e.runWebGLProgram(a,[o,s],"int32",u)}var tB={kernelName:qp,backendName:"webgl",kernelFunc:pot};var uC=class{constructor(t,e,n){this.variableNames=["c","a","b"],this.outputShape=e;let o,s;if(n>4)throw Error(`Where for rank ${n} is not yet supported`);if(n===1)s="resRC",o="resRC";else{let a=["resRC.x","resRC.y","resRC.z","resRC.w"],u=[],l=[];for(let c=0;c<e.length;c++)l.push(`${a[c]}`),c<t&&u.push(`${a[c]}`);o=u.join(),s=l.join()}let i=Wt(n);this.userCode=`
      void main() {
        ${i} resRC = getOutputCoords();
        float cVal = getC(${o});
        if (cVal >= 1.0) {
          setOutput(getA(${s}));
        } else {
          setOutput(getB(${s}));
        }
      }
    `}};function mot(r){let{inputs:t,backend:e}=r,{condition:n,t:o,e:s}=t,i=new uC(n.shape.length,o.shape,o.shape.length);return e.runWebGLProgram(i,[n,o,s],ir(o.dtype,s.dtype))}var eB={kernelName:bi,backendName:"webgl",kernelFunc:mot};var fot=`
  // Stable and Attracting Fixed Point (0, 1) for Normalized Weights.
  // see: https://arxiv.org/abs/1706.02515
  float scaleAlpha = ${S.SELU_SCALEALPHA};
  float scale = ${S.SELU_SCALE};
  return (x >= 0.0) ? scale * x : scaleAlpha * (exp(x) - 1.0);
`,dot=It({opSnippet:fot}),rB={kernelName:Oa,backendName:"webgl",kernelFunc:dot};var hot=Ro+`
  return 1.0 / (1.0 + exp(-1.0 * x));
`,got=`
  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;
`,xot=It({opSnippet:hot,packedOpSnippet:got,cpuKernelImpl:DP}),nB={kernelName:Rs,backendName:"webgl",kernelFunc:xot};var yot=`
  if (isnan(x)) { return 0.0; }
  return sign(x);
`,bot=It({opSnippet:yot}),oB={kernelName:Pa,backendName:"webgl",kernelFunc:bot};var wot=Ro+`
  return sin(x);
`,vot=It({opSnippet:wot}),sB={kernelName:Fs,backendName:"webgl",kernelFunc:vot};var Cot=`
  float e2x = exp(x);
  return (e2x - 1.0 / e2x) / 2.0;
`,Iot=It({opSnippet:Cot}),iB={kernelName:La,backendName:"webgl",kernelFunc:Iot};var Sot=`
  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;
`,Not=It({opSnippet:Sot}),aB={kernelName:Ma,backendName:"webgl",kernelFunc:Not};var kot=r=>{let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{blockShape:s,paddings:i}=n;x.assert(o.shape.length<=4,()=>"spaceToBatchND for rank > 4 with a WebGL backend not implemented yet");let a=s.reduce((y,b)=>y*b),u=[[0,0]];u.push(...i);for(let y=1+s.length;y<o.shape.length;++y)u.push([0,0]);let l=[],c=ET({inputs:{x:o},backend:e,attrs:{paddings:u,constantValue:0}}),p=S.getReshaped(c.shape,s,a,!1),m=S.getPermuted(p.length,s.length,!1),f=S.getReshapedPermuted(c.shape,s,a,!1),d=at({inputs:{x:c},backend:e,attrs:{shape:p}}),h=Pe({inputs:{x:d},backend:e,attrs:{perm:m}}),g=at({inputs:{x:h},backend:e,attrs:{shape:f}});return l.push(c),l.push(d),l.push(h),l.forEach(y=>e.disposeIntermediateTensorInfo(y)),g},lB={kernelName:vi,backendName:"webgl",kernelFunc:kot};function Tot(r){let{inputs:t,backend:e}=r,{indices:n,values:o,denseShape:s,defaultValue:i}=t;if(s.shape.length!==1)throw new Error(`Dense shape must be a vector, saw:
         ${s.shape}`);if(n.shape.length!==2)throw new Error(`Indices must be a matrix, saw:
         ${n.shape}`);if(o.shape.length!==1)throw new Error(`Values must be a vector, saw:
         ${o.shape}`);if(i.shape.length!==0)throw new Error(`Default value must be a scalar, saw:
        ${i.shape}`);let a=e.readSync(n.dataId),u=e.readSync(o.dataId),l=e.readSync(s.dataId),c=e.readSync(i.dataId)[0],[p,m,f,d,h]=RP(a,n.shape,n.dtype,u,o.dtype,l,c);return[e.makeTensorInfo(m,n.dtype,p),e.makeTensorInfo([m[0]],o.dtype,f),e.makeTensorInfo([d.length],"bool",new Uint8Array(d.map(g=>Number(g)))),e.makeTensorInfo([h.length],n.dtype,new Int32Array(h))]}var uB={kernelName:$l,backendName:"webgl",kernelFunc:Tot};function _ot(r){let{inputs:t,backend:e}=r,{inputIndices:n,inputShape:o,newShape:s}=t;if(n.shape.length!==2)throw new Error(`Input indices should be a matrix but received shape ${n.shape}`);if(o.shape.length!==1)throw new Error(`Input shape should be a vector but received shape ${o.shape}`);if(s.shape.length!==1)throw new Error(`Target shape should be a vector but received shape ${s.shape}`);let i=Array.from(e.readSync(o.dataId)),a=e.readSync(n.dataId),u=Array.from(e.readSync(s.dataId)),[l,c,p]=OP(a,n.shape,n.dtype,i,u);return[e.makeTensorInfo(c,n.dtype,l),e.makeTensorInfo([p.length],s.dtype,new Int32Array(p))]}var cB={kernelName:za,backendName:"webgl",kernelFunc:_ot};function Eot(r){let{inputs:t,backend:e}=r,{data:n,indices:o,segmentIds:s}=t;if(n.shape.length<1)throw new Error("Data should be at least 1 dimensional but received scalar");if(o.shape.length!==1)throw new Error(`Indices should be a vector but received shape
              ${o.shape}`);if(s.shape.length!==1)throw new Error(`Segment ids should be a vector but received shape
              ${s.shape}`);let i=e.readSync(n.dataId),a=e.readSync(o.dataId),u=e.readSync(s.dataId),[l,c]=Hw(i,n.shape,n.dtype,a,u,!0);return e.makeTensorInfo(c,n.dtype,l)}var pB={kernelName:Dl,backendName:"webgl",kernelFunc:Eot};function Aot(r){let{inputs:t,backend:e}=r,{data:n,indices:o,segmentIds:s}=t;if(n.shape.length<1)throw new Error("Data should be at least 1 dimensional but received scalar");if(o.shape.length!==1)throw new Error(`Indices should be a vector but received shape
             ${o.shape}`);if(s.shape.length!==1)throw new Error(`Segment ids should be a vector but received shape
             ${s.shape}`);let i=e.readSync(n.dataId),a=e.readSync(o.dataId),u=e.readSync(s.dataId),[l,c]=Hw(i,n.shape,n.dtype,a,u);return e.makeTensorInfo(c,n.dtype,l)}var mB={kernelName:Fl,backendName:"webgl",kernelFunc:Aot};function $ot(r){let{inputs:t,backend:e,attrs:n}=r,{sparseIndices:o,sparseValues:s,defaultValue:i}=t,{outputShape:a}=n,{sliceRank:u,numUpdates:l,sliceSize:c,strides:p,outputSize:m}=S.calculateShapes(s,o,a),f=!1;if(s.dtype==="string"){let y=e.bufferSync(o),b=e.bufferSync(s),w=x.decodeString(e.readSync(i.dataId)[0]),v=$P(y,b,a,m,c,l,u,p,w,f);return e.makeTensorInfo(a,v.dtype,v.values)}let d=new Rd(l,u,o.shape.length,s.shape.length,p,[m,1],f),h=e.runWebGLProgram(d,[s,o,i],s.dtype),g=at({inputs:{x:h},backend:e,attrs:{shape:a}});return e.disposeIntermediateTensorInfo(h),g}var fB={kernelName:Kp,backendName:"webgl",kernelFunc:$ot};function Dot(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{numOrSizeSplits:s,axis:i}=n,a=x.parseAxisParam(i,o.shape)[0],u=S.prepareSplitSize(o,s,a),l=o.shape.length,c=new Array(l).fill(0),p=o.shape.slice();return u.map(m=>{let f=[...p];f[a]=m;let d=ii({inputs:{x:o},backend:e,attrs:{begin:c,size:f}});return c[a]+=m,d})}var dB={kernelName:Ci,backendName:"webgl",kernelFunc:Dot};var hB="return sqrt(x);",Fot=It({opSnippet:hB,packedOpSnippet:hB,cpuKernelImpl:LP}),gB={kernelName:Os,backendName:"webgl",kernelFunc:Fot};var Rot="return x * x;",Oot=It({opSnippet:Rot}),xB={kernelName:Rl,backendName:"webgl",kernelFunc:Oot};var yB="return (a - b) * (a - b);",Lot=ce({opSnippet:yB,packedOpSnippet:yB}),bB={kernelName:Ms,backendName:"webgl",kernelFunc:Lot};function Pot({inputs:r,attrs:t,backend:e}){let{x:n}=r,o=fr+`
    return x > 0.0 ? 1.0 : float(${t.alpha});
  `,s=new Zr(n.shape,o);return e.runWebGLProgram(s,[n],n.dtype)}var wB={kernelName:uo,backendName:"webgl",kernelFunc:Pot};var cC=class{constructor(t,e,n){this.variableNames=["x"],this.outputShape=n;let o=n.length,s=Wt(n.length),i=Wt(n.length),a="";if(o===1)a="coords * strides + begin";else{let u=0;a=n.map((l,c)=>(u++,n.length===1?`coords * strides[${c}] + begin[${c}]`:`coords[${u-1}] * strides[${c}] + begin[${c}]`)).join(",")}this.userCode=`
      ${s} begin = ${s}(${t});
      ${s} strides = ${s}(${e});

      void main() {
        ${i} coords = getOutputCoords();
        setOutput(getX(${a}));
      }
    `}};function Mot(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{begin:s,end:i,strides:a,beginMask:u,endMask:l,ellipsisMask:c,newAxisMask:p,shrinkAxisMask:m}=n,{finalShapeSparse:f,finalShape:d,isIdentity:h,sliceDim0:g,isSimpleSlice:y,begin:b,end:w,strides:v}=Be.sliceInfo(o.shape,s,i,a,u,l,c,p,m),N;if(h)N=at({inputs:{x:o},backend:e,attrs:{shape:d}});else if(g||y){x.assert(o.shape.length>=1,()=>`Input must have rank at least 1, got: ${o.shape.length}`);let $=Be.computeOutShape(b,w,v),D=ii({inputs:{x:o},backend:e,attrs:{begin:b,size:$}});N=at({inputs:{x:D},backend:e,attrs:{shape:d}}),e.disposeIntermediateTensorInfo(D)}else if(e.shouldExecuteOnCPU([o])){let D=e.readSync(o.dataId),L=Ct(o.shape,o.dtype,D),M=PP(f,L,v,b);N=e.makeTensorInfo(d,o.dtype,M.values)}else{let D=new cC(b,v,f);N=e.runWebGLProgram(D,[o],o.dtype)}let E=at({inputs:{x:N},backend:e,attrs:{shape:d}});return e.disposeIntermediateTensorInfo(N),E}var vB={kernelName:Ba,backendName:"webgl",kernelFunc:Mot};function zot(r){let{inputs:t,backend:e,attrs:n}=r,{separator:o,nGramWidths:s,leftPad:i,rightPad:a,padWidth:u,preserveShortSequences:l}=n,{data:c,dataSplits:p}=t,m=e.readSync(c.dataId),f=e.readSync(p.dataId),[d,h]=MP(m,f,o,s,i,a,u,l);return[e.makeTensorInfo([d.length],"string",d),e.makeTensorInfo(p.shape,"int32",h)]}var CB={kernelName:Ol,backendName:"webgl",kernelFunc:zot};function Bot(r){let{inputs:t,backend:e,attrs:n}=r,{skipEmpty:o}=n,{input:s,delimiter:i}=t;if(s.dtype!=="string")throw new Error("Input must be of datatype string");if(s.shape.length!==1)throw new Error(`Input must be a vector, got shape: ${s.shape}`);if(i.shape.length!==0)throw new Error(`Delimiter must be a scalar, got shape: ${i.shape}`);let a=e.readSync(s.dataId),u=e.readSync(i.dataId)[0],[l,c,p]=zP(a,u,o),m=c.length;return[e.makeTensorInfo([m,2],"int32",l),e.makeTensorInfo([m],"string",c),e.makeTensorInfo([2],"int32",new Int32Array(p))]}var IB={kernelName:Ll,backendName:"webgl",kernelFunc:Bot};function Vot(r){let{inputs:t,backend:e,attrs:n}=r,{numBuckets:o}=n,{input:s}=t;if(s.dtype!=="string")throw new Error("Input must be of datatype string");if(o<=0)throw new Error("Number of buckets must be at least 1");let i=e.readSync(s.dataId),a=BP(i,o);return e.makeTensorInfo(s.shape,"int32",a)}var SB={kernelName:Pl,backendName:"webgl",kernelFunc:Vot};var Got="return tan(x);",Wot=It({opSnippet:Got}),NB={kernelName:Bs,backendName:"webgl",kernelFunc:Wot};var Uot=`
  float e2x = exp(-2.0 * abs(x));
  return sign(x) * (1.0 - e2x) / (1.0 + e2x);
`,Hot=It({opSnippet:Uot}),kB={kernelName:Vs,backendName:"webgl",kernelFunc:Hot};var pC=class{constructor(t,e){this.variableNames=["A"];let n=new Array(t.length);for(let i=0;i<n.length;i++)n[i]=t[i]*e[i];this.outputShape=n,this.rank=n.length;let o=Wt(this.rank),s=qot(t);this.userCode=`
      void main() {
        ${o} resRC = getOutputCoords();
        setOutput(getA(${s}));
      }
    `}};function qot(r){let t=r.length;if(t>5)throw Error(`Tile for rank ${t} is not yet supported`);if(t===1)return`imod(resRC, ${r[0]})`;let e=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u"],n=[];for(let o=0;o<r.length;o++)n.push(`imod(${e[o]}, ${r[o]})`);return n.join()}function $T(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{reps:s}=n;if(o.dtype==="string"||o.shape.length>5){let u=e.readSync(o.dataId),l=o.dtype==="string"?u.map(m=>x.decodeString(m)):u,c=Ct(o.shape,o.dtype,l),p=GP(c,s);return e.makeTensorInfo(p.shape,p.dtype,p.values)}let i=new pC(o.shape,s);return e.runWebGLProgram(i,[o],o.dtype)}var TB={kernelName:Xn,backendName:"webgl",kernelFunc:$T};var mC=class{constructor(t){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=t,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));
         }
       }
     `}},fC=class{constructor(t){this.variableNames=["x","indices"],this.customUniforms=[{name:"n",type:"int"},{name:"firstPass",type:"int"},{name:"k",type:"int"}],this.outputShape=t,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 Qc(r,t){t!==null&&r.disposeIntermediateTensorInfo(t)}function _B(r){let t=1;for(;t<r;)t*=2;return t}function Kot(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{k:s,sorted:i}=n,a=B().getNumber("TOPK_LAST_DIM_CPU_HANDOFF_SIZE_THRESHOLD"),u=B().getNumber("TOPK_K_CPU_HANDOFF_THRESHOLD"),l=o.shape,c=l[l.length-1];if(e.shouldExecuteOnCPU([o])||c<a||s>u){let M=e.readSync(o.dataId),[G,H]=WP(M,l,o.dtype,s,i);return[e.makeTensorInfo(G.shape,G.dtype,G.values),e.makeTensorInfo(H.shape,H.dtype,H.values)]}if(s===0)return l[l.length-1]=0,[e.makeTensorInfo(l,o.dtype,[]),e.makeTensorInfo(l,"int32",[])];if(c===1)return[o,gl({attrs:{shape:l,dtype:"int32",value:0},backend:e})];let p=e.texData.get(o.dataId),m=p!==null&&p.isPacked,f=m?e.unpackTensor(o):o,h=x.sizeFromShape(l)/c,g=at({inputs:{x:f},attrs:{shape:[h,c]},backend:e});m&&Qc(e,f);let y=_B(s),b=_B(c),w=null,v=()=>w===null?[g,g]:[g,w],N=(M,G,H)=>{let q=v(),X=new mC(H),J=[[c],[w===null?1:0],[Number.NEGATIVE_INFINITY],[M],[G]],nt=w;w=e.runWebGLProgram(X,q,"int32",J),Qc(e,nt)};for(let M=1;M<y;M*=2){let G=M*2;for(let H=M;H>=1;H/=2)N(G,H,[h,b])}for(let M=b;M>y;M/=2){let G=v(),H=new fC([h,M/2]),X=[[c],[w===null?1:0],[y]],j=w;w=e.runWebGLProgram(H,G,"int32",X),Qc(e,j);let J=y/2,nt=J*2;for(let K=J;K>=1;K/=2)N(nt,K,w.shape)}let E=w;w=ii({inputs:{x:w},backend:e,attrs:{begin:0,size:[h,s]}}),Qc(e,E);let $=ST({inputs:{x:g,indices:w},backend:e,attrs:{axis:1,batchDims:1}});Qc(e,g);let D=l.slice(0,-1);D.push(s),E=w,w=at({inputs:{x:w},attrs:{shape:D},backend:e}),Qc(e,E);let L=$;return $=at({inputs:{x:$},attrs:{shape:D},backend:e}),Qc(e,L),[$,w]}var EB={kernelName:Va,backendName:"webgl",kernelFunc:Kot};var dC=class{constructor(t,e,n,o,s,i){this.variableNames=["Image","Transforms"],this.outputShape=i;let a=n==="nearest"?1:2,u;switch(o){case"constant":u=1;break;case"reflect":u=2;break;case"wrap":u=3;break;case"nearest":u=4;break;default:u=1;break}this.userCode=`
            float mapCoord(float outCoord, float len) {
              float inCoord = outCoord;
              if(${u} == 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 (${u} == 3) {
                if (inCoord < 0.0) {
                  if (len <= 1.0) {
                    inCoord = 0.0;
                  } else {
                    float sz = len - 1.0;
                    inCoord += len * (float(int(float(-inCoord / sz))) + 1.0);
                  }
                } else if (inCoord > len - 1.0) {
                  if (len <= 1.0) {
                    inCoord = 0.0;
                  } else {
                    float sz = len - 1.0;
                    inCoord -= len * float(int(float(inCoord / sz)));
                  }
                }
                return clamp(inCoord, 0.0, len - 1.0);
              } else if (${u} == 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 < ${t} && 0 <= coordX && coordX < ${e}) {
                  outputValue = getImage(batch, coordY, coordX, channel);
              } else {
                outputValue = float(${s});
              }
              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(${s});
              } else {
                float inX = (a1 * xf + a2 * yf + a3) / projection;
                float inY = (b1 * xf + b2 * yf + b3) / projection;
                float mapX = mapCoord(inX, float(${e}));
                float mapY = mapCoord(inY, float(${t}));

                if (${a} == 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 jot(r){let{inputs:t,backend:e,attrs:n}=r,{image:o,transforms:s}=t,{interpolation:i,fillMode:a,fillValue:u,outputShape:l}=n,[c,p,m,f]=o.shape,[d,h]=l!=null?l:[p,m],g=[c,d,h,f],y=new dC(p,m,i,a,u,g);return e.runWebGLProgram(y,[o,s],"float32")}var AB={kernelName:Ga,backendName:"webgl",kernelFunc:jot};function Xot(r){let{inputs:t,attrs:e,backend:n}=r,{axis:o}=e,{x:s}=t;ni(s,"unique"),console.warn("WARNING: ","UI might be locked temporarily as data is being downloaded");let i=n.readSync(s.dataId),{outputValues:a,outputShape:u,indices:l}=UP(i,o,s.shape,s.dtype);return[n.makeTensorInfo(u,s.dtype,a),n.makeTensorInfo([l.length],"int32",l)]}var $B={kernelName:jp,backendName:"webgl",kernelFunc:Xot};function Yot(r){let{inputs:t,backend:e,attrs:n}=r,{value:o}=t,{axis:s}=n;s<0&&(s+=o.shape.length);let i=o,a=i.shape.length,u=o.shape[s],l=new Array(a-1),c=0;for(let h=0;h<a;h++)h!==s&&(l[c++]=i.shape[h]);let p=[],m=new Array(a).fill(0),f=i.shape.slice();f[s]=1;let d=new Array(u);for(let h=0;h<d.length;h++){m[s]=h;let g=ii({inputs:{x:i},backend:e,attrs:{begin:m,size:f}}),y=at({inputs:{x:g},backend:e,attrs:{shape:l}});d[h]=y,p.push(g)}return p.forEach(h=>e.disposeIntermediateTensorInfo(h)),d}var DB={kernelName:Ii,backendName:"webgl",kernelFunc:Yot};var hC=class{constructor(t,e){this.variableNames=["x","segmentIds"];let n=t.windowSize,o=t.batchSize,s=t.inSize,i=t.numSegments,a=i*Math.ceil(s/n);this.outputShape=[o,a];let u="0.0",l="sumValue",c=Math.floor(n/4)*4,p=n%4,m=`
        sumValue += dot(values, segFilter);
    `,f="";s%n>0&&(f=`
        if (inIdx < 0 || inIdx >= ${s}) {
          return initializationValue;
        }
      `);let d="";s%n>0&&(d=`
        if (inIdx < 0 || inIdx >= ${s}) {
          return -1.0;
        }
      `),this.userCode=`
      const float initializationValue = ${u};

      float getValue(int batch, int inIdx) {
        ${f}
        return getX(batch, inIdx);
      }

      float getSegmentIdAtIndex(int inIdx) {
        ${d}
        return getSegmentIds(inIdx);
      }

      void main() {
        ivec2 coords = getOutputCoords();
        int batch = coords[0];
        int outIdx = coords[1];
        int inOffset = int(floor(float(outIdx) / float(
          ${i})) * float(${n}));
        int currentSeg = int(mod(float(outIdx), float(${i})));

        float sumValue = 0.0;

        for (int i = 0; i < ${c}; 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
          );

          ${m}
        }

        int inIdx = inOffset + ${c};
        if (${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
          );

          ${m}
        } else if (${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
          );

          ${m}
        } else if (${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
          );

          ${m}
        }
        setOutput(${l});
      }
    `}};function Zot(r){let{inputs:t,backend:e,attrs:n}=r,{x:o,segmentIds:s}=t,{numSegments:i}=n,a=o.shape.length,u=[],l=0,c=S.getAxesPermutation([l],a),p=o;c!=null&&(p=Pe({inputs:{x:o},backend:e,attrs:{perm:c}}),u.push(p),l=S.getInnerMostAxes(1,a)[0]);let m=S.segment_util.computeOutShape(p.shape,l,i),f=x.sizeFromShape([p.shape[l]]),d=at({inputs:{x:p},backend:e,attrs:{shape:[-1,f]}});u.push(d);let h=Ku(o.dtype),g=(v,N,E,$,D)=>{let L=v.shape[0],M=v.shape[1],G=S.segment_util.segOpComputeOptimalWindowSize(M,D),H={windowSize:G,inSize:M,batchSize:L,numSegments:D},q=new hC(H,N),X=e.compileAndRun(q,[v,E],$);if(u.push(X),X.shape[1]===D)return X;let j=AT({backend:e,attrs:{start:0,stop:D,step:1,dtype:"float32"}}),J=$T({inputs:{x:j},backend:e,attrs:{reps:[M/G]}});return u.push(j),u.push(J),g(X,N,J,$,D)},y=g(d,"unsortedSegmentSum",s,h,i),b=at({inputs:{x:y},backend:e,attrs:{shape:m}}),w=b;if(c!=null){u.push(b);let v=S.getUndoAxesPermutation(c);w=Pe({inputs:{x:w},backend:e,attrs:{perm:v}})}return u.forEach(v=>e.disposeIntermediateTensorInfo(v)),w}var FB={kernelName:Ml,backendName:"webgl",kernelFunc:Zot};var Jot=[vM,IM,SM,NM,TM,_M,EM,AM,FM,RM,OM,LM,PM,MM,zM,BM,VM,GM,WM,UM,HM,KM,jM,XM,QM,ez,rz,uM,oz,iz,az,lz,uz,cz,pz,mz,fz,dz,hz,yz,bz,wz,vz,Cz,Iz,Sz,Nz,kz,Tz,_z,Ez,Az,$z,Dz,Fz,Oz,Lz,Pz,Mz,Bz,Vz,Gz,Wz,Uz,Hz,qz,Kz,jz,lM,Xz,sz,Yz,Zz,Jz,cM,Qz,t3,e3,r3,n3,o3,s3,i3,a3,l3,c3,p3,m3,f3,d3,h3,x3,b3,w3,v3,C3,I3,_3,hM,E3,A3,$3,D3,YM,F3,L3,P3,M3,z3,pM,B3,V3,ZM,S3,G3,W3,U3,xM,H3,q3,K3,j3,X3,Y3,Z3,J3,Q3,tB,eB,rB,nB,oB,sB,iB,qM,T3,aB,lB,uB,cB,pB,mB,fB,dB,gB,xB,bB,wB,vB,CB,IB,SB,k3,bM,NB,kB,TB,EB,AB,wM,$B,DB,FB,R3];for(let r of Jot)Vu(r);var Zt;(function(r){r[r.float32=0]="float32",r[r.int32=1]="int32",r[r.bool=2]="bool",r[r.string=3]="string",r[r.complex64=4]="complex64"})(Zt||(Zt={}));var $u;(function(r){r[r.linear=0]="linear",r[r.relu=1]="relu",r[r.relu6=2]="relu6",r[r.prelu=3]="prelu",r[r.leakyrelu=4]="leakyrelu",r[r.sigmoid=5]="sigmoid",r[r.elu=6]="elu"})($u||($u={}));var RB;function 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Sst(r){let{inputs:t,attrs:e,backend:n}=r,{x:o,filter:s}=t,i=n.dataIdMap.get(o.dataId).id,a=n.dataIdMap.get(s.dataId).id,{strides:u,dilations:l,pad:c,dimRoundingMode:p,dataFormat:m}=e,f=S.convertConv2DDataFormat(m),d=S.computeConv2DInfo(o.shape,s.shape,u,l,c,p,!1,f),h=d.filterHeight,g=d.filterWidth,y=d.padInfo.top,b=d.padInfo.right,w=d.padInfo.bottom,v=d.padInfo.left,N=d.dilationHeight,E=d.dilationWidth,$=d.strideHeight,D=d.strideWidth,L=d.inChannels,M=d.outChannels,G=d.padInfo.type==="SAME"?1:0;if(d.dataFormat!=="channelsLast")throw new Error(`wasm backend Conv2D does not support dataFormat:'${d.dataFormat}'. 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kst(r){let{backend:t,inputs:e,attrs:n}=r,{dy:o,filter:s}=e,{strides:i,pad:a,dataFormat:u,dimRoundingMode:l,inputShape:c}=n,p=1,m=S.convertConv2DDataFormat(u),f=S.computeConv2DInfo(c,s.shape,i,p,a,l,!1,m),{batchSize:d,filterHeight:h,filterWidth:g,inChannels:y,inHeight:b,inWidth:w,outChannels:v,outHeight:N,outWidth:E,strideHeight:$,strideWidth:D}=f,L=h-1-f.padInfo.top,M=g-1-f.padInfo.left,G=f.dataFormat==="channelsLast",H=x.computeStrides(f.inShape),q=x.computeStrides(o.shape),[X,j,J]=x.computeStrides(s.shape),nt=H[0],K=G?H[1]:H[2],ot=G?H[2]:1,st=G?1:H[1],it=q[0],ft=G?q[1]:q[2],lt=G?q[2]:1,xt=G?1:q[1],dt=t.makeOutput(f.inShape,"float32"),bt=t.dataIdMap.get(dt.dataId).id,Nt=t.dataIdMap.get(o.dataId).id,At=t.dataIdMap.get(s.dataId).id;return uV(Nt,At,d,h,g,b,w,y,N,E,v,$,D,L,M,X,j,J,nt,K,ot,st,it,ft,lt,xt,bt),dt}var cV={kernelName:Qo,backendName:"wasm",setupFunc:Nst,kernelFunc:kst};var pV=ae(ts);var mV=ae(es);var FT;(function(r){r[r.bilinear=0]="bilinear",r[r.nearest=1]="nearest"})(FT||(FT={}));var fV;function Tst(r){fV=r.wasm.cwrap(pa,null,["number","number","number","number","array","number","number","number","number","number"])}function _st(r){let{backend:t,inputs:e,attrs:n}=r,{method:o,extrapolationValue:s,cropSize:i}=n,{image:a,boxes:u,boxInd:l}=e,c=u.shape[0],[p,m]=i,f=[c,p,m,a.shape[3]],d=t.dataIdMap.get(a.dataId),h;a.dtype!=="float32"&&(h=ai({backend:t,inputs:{x:a},attrs:{dtype:"float32"}}),d=t.dataIdMap.get(h.dataId));let g=d.id,y=t.dataIdMap.get(u.dataId).id,b=t.dataIdMap.get(l.dataId).id,w=t.makeOutput(f,"float32"),v=t.dataIdMap.get(w.dataId).id,N=new Uint8Array(new Int32Array(a.shape).buffer);return fV(g,y,b,c,N,p,m,FT[o],s,v),h!=null&&t.disposeData(h.dataId),w}var dV={kernelName:pa,backendName:"wasm",setupFunc:Tst,kernelFunc:_st};var hV;function Est(r){hV=r.wasm.cwrap(ca,null,["number","number","number","number","number","number"])}function Ast(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{axis:s,exclusive:i,reverse:a}=n,u=o.shape.length;x.assert(o.dtype==="float32"||o.dtype==="int32",()=>`cumprod does not support ${o.dtype} tensors in the WASM backend`);let l=S.getAxesPermutation([s],u),c=o;l!==null&&(c=no({inputs:{x:o},attrs:{perm:l},backend:e}));let p=S.getInnerMostAxes(1,u)[0];S.assertAxesAreInnerMostDims("cumprod",[p],u);let m=e.makeOutput(c.shape,c.dtype),f=c.shape[p],d=e.dataIdMap.get(c.dataId).id,h=e.dataIdMap.get(m.dataId).id;hV(d,i?1:0,a?1:0,f,h,Zt[o.dtype]);let g=m;if(l!==null){let y=S.getUndoAxesPermutation(l);g=no({inputs:{x:m},attrs:{perm:y},backend:e}),e.disposeData(c.dataId),e.disposeData(m.dataId)}return g}var gV={kernelName:ca,backendName:"wasm",setupFunc:Est,kernelFunc:Ast};var xV;function $st(r){xV=r.wasm.cwrap(rs,null,["number","number","number","number","number","number"])}function 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Rst(r){let{backend:t,inputs:e,attrs:n}=r,{x:o}=e,{blockSize:s,dataFormat:i}=n,a=o.shape[0],u=i==="NHWC"?o.shape[1]:o.shape[2],l=i==="NHWC"?o.shape[2]:o.shape[3],c=i==="NHWC"?o.shape[3]:o.shape[1],p=u*s,m=l*s,f=c/(s*s),d=i==="NHWC"?[a,p,m,f]:[a,f,p,m],h=t.makeOutput(d,"float32"),y=t.dataIdMap.get(o.dataId).id,b=new Uint8Array(new Int32Array(x.computeStrides(o.shape)).buffer),w=new Uint8Array(new Int32Array(d).buffer),v=new Uint8Array(new Int32Array(x.computeStrides(d)).buffer),N=t.dataIdMap.get(h.dataId).id;return bV(y,s,i==="NHWC"?1:0,b,o.shape.length-1,w,v,d.length,N),h}var wV={kernelName:ma,backendName:"wasm",setupFunc:Fst,kernelFunc:Rst};var vV;function Ost(r){vV=r.wasm.cwrap(ns,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function 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GPGPUContext,xa as GatherNd,di as GatherV2,Bh as GraphModel,ya as Greater,cs as GreaterEqual,qy as History,Op as IFFT,lo as Identity,Lp as Imag,we as InputSpec,ba as IsFinite,wa as IsInf,va as IsNan,Uo as KernelBackend,_l as LRN,Mp as LRNGrad,Nh as LayerVariable,Bn as LayersModel,ps as LeakyRelu,Ca as Less,Ia as LessEqual,Pp as LinSpace,ms as Log,Sa as Log1p,w1 as LogSoftmax,Na as LogicalAnd,ka as LogicalNot,Ta as LogicalOr,b1 as LogicalXor,Qat as LowerBound,ku as MathBackendWebGL,fs as Max,hs as MaxPool,El as MaxPool3D,Bp as MaxPool3DGrad,zp as MaxPoolGrad,Vp as MaxPoolWithArgmax,ds as Maximum,gs as Mean,xs as Min,ys as Minimum,bs as MirrorPad,_a as Mod,pu as MomentumOptimizer,Gp as Multinomial,ws as Multiply,hi as Neg,Aa as NonMaxSuppressionV3,$a as NonMaxSuppressionV4,Da as NonMaxSuppressionV5,Ea as NotEqual,D0 as OP_SCOPE_SUFFIX,vs as OneHot,gi as OnesLike,Br as Optimizer,Ks as OptimizerConstructors,xi as Pack,Cs as PadV2,tlt as Pool,Is as Pow,Ss as Prelu,Ns as Prod,mu as RMSPropOptimizer,_n as RNN,Al as Range,C0 as Rank,Wp as Real,os as RealDiv,Fa as Reciprocal,Ye as Reduction,ks as Relu,Es as Relu6,yi as Reshape,_s as ResizeBilinear,Hp as ResizeBilinearGrad,Ts as ResizeNearestNeighbor,Up as ResizeNearestNeighborGrad,As as Reverse,Wa as RotateWithOffset,$s as Round,Ds as Rsqrt,Ui as SGDOptimizer,Ra as ScatterNd,qp as SearchSorted,bi as Select,Oa as Selu,Xi as Sequential,Rs as Sigmoid,Pa as Sign,Fs as Sin,La as Sinh,wi as Slice,Ps as Softmax,Ma as Softplus,vi as SpaceToBatchND,$l as SparseFillEmptyRows,za as SparseReshape,Dl as SparseSegmentMean,Fl as SparseSegmentSum,Kp as SparseToDense,Ci as SplitV,Os as Sqrt,Rl as Square,Ms as SquaredDifference,uo as Step,Ba as StridedSlice,Ol as StringNGrams,Ll as StringSplit,Pl as StringToHashBucketFast,zs as Sub,Ls as Sum,Xr as SymbolicTensor,Bs as Tan,Vs as Tanh,Pt as Tensor,fe as TensorBuffer,Xn as Tile,Va as TopK,Ga as Transform,Yn as Transpose,jp as Unique,Ii as Unpack,Ml as UnsortedSegmentSum,elt as UpperBound,Ua as Variable,Si as ZerosLike,Ni as _FusedMatMul,Ae as abs,gx as acos,xx as acosh,Z as add,U_ as addN,am as all,Yu as any,Ri as argMax,yx as argMin,bx as asin,wx as asinh,vx as atan,Cx as atan2,Ix as atanh,Hl as avgPool,Nx as avgPool3d,I_ as backend,S as backend_util,K_ as basicLSTMCell,Li as batchNorm,kx as batchNorm2d,Tx as batchNorm3d,_x as batchNorm4d,ql as batchToSpaceND,Ex as bincount,r6 as booleanMaskAsync,X_ as broadcastArgs,Kl as broadcastTo,Pr as broadcast_util,mx as browser,Ct as buffer,D7 as callbacks,tt as cast,Ax as ceil,Ir as clipByValue,an as clone,vn as complex,se as concat,$x as concat1d,Dx as concat2d,Fx as concat3d,Rx as concat4d,J$ as constraints,um as conv1d,Sn as conv2d,pm as conv2dTranspose,Ox as conv3d,Px as conv3dTranspose,llt as copyRegisteredKernels,jl as cos,mm as cosh,bh as cosineWindow,Qu as cumprod,fm as cumsum,un as customGrad,FF as data,Y_ as denseBincount,K0 as deprecationWarn,Mx as depthToSpace,Pi as depthwiseConv2d,L7 as deregisterOp,Gl as device_util,Z_ as diag,zx as dilation2d,Jct as disableDeprecationWarnings,_t as dispose,Qct as disposeVariables,ct as div,Bx as divNoNan,Vx as dot,mS as dropout,J_ as einsum,Mi as elu,Zct as enableDebugMode,Yct as enableProdMode,fS as enclosingPowerOfTwo,go as engine,B as env,Ar as equal,Gx as erf,Wx as euclideanNorm,or as exp,yr as expandDims,Ux as expm1,ec as eye,nu as fft,zi as fill,spt as findBackend,ipt as findBackendFactory,Bi as floor,im as floorDiv,aM as forceHalfFloat,su as fused,Vi as gather,p6 as gatherND,fx as gather_util,npt as getBackend,d0 as getGradient,nh as getKernel,Xg as getKernelsForBackend,Lat as getThreadsCount,cT as gpgpu_util,vK as grad,CK as grads,Xe as greater,Ln as greaterEqual,Ya as ifft,Ul as imag,iu as image,d6 as inTopKAsync,Q$ as initializers,BS as input,Cn as io,Tm as irfft,Hx as isFinite,qx as isInf,Kx as isNaN,Oe as keep,Vr as kernel_impls,$D as layers,Xl as leakyRelu,dm as less,Pn as lessEqual,hS as linalg,eE as linspace,EZ as loadGraphModel,AZ as loadGraphModelSync,W8 as loadLayersModel,jx as localResponseNormalization,Sr as log,Yl as log1p,Zx as logSigmoid,hm as logSoftmax,gm as logSumExp,Dr as logicalAnd,Zl as logicalNot,xm as logicalOr,Jx as logicalXor,d5 as losses,rE as lowerBound,Gt as matMul,N_ as math,Mr as max,Jl as maxPool,ty as maxPool3d,nE as maxPoolWithArgmax,Nn as maximum,ke as mean,mh as memory,oE as meshgrid,DD as metrics,tc as min,Gi as minimum,ey as mirrorPad,ry as mod,V8 as model,FD as models,rc as moments,o6 as movingAverage,O as mul,sE as multiRNNCell,iE as multinomial,Yt as neg,wh as nextFrame,Xa as norm,Hs as notEqual,Di as oneHot,cr as ones,br as onesLike,k as op,aE as outerProduct,cn as pad,lE as pad1d,uE as pad2d,cE as pad3d,pE as pad4d,ny as pool,ln as pow,tu as prelu,ax as print,oy as prod,tpt as profile,mE as rand,EE as randomGamma,sc as randomNormal,AE as randomStandardNormal,Wi as randomUniform,eu as range,rpt as ready,ja as real,uy as reciprocal,sm as registerBackend,U8 as registerCallbackConstructor,C1 as registerGradient,Vu as registerKernel,O7 as registerOp,RD as regularizers,Fr as relu,ym as relu6,opt as removeBackend,R as reshape,pr as reverse,$E as reverse1d,DE as reverse2d,FE as reverse3d,RE as reverse4d,ou as rfft,bm as round,wm as rsqrt,pt as scalar,i6 as scatterND,fh as scatter_util,gh as searchSorted,vm as selu,Cm as separableConv2d,G8 as sequential,et as serialization,oH as setBackend,apt as setPlatform,Oat as setThreadsCount,Fat as setWasmPath,Rat as setWasmPaths,Sk as setWebGLContext,OE as setdiff1dAsync,Kr as sigmoid,cy as sign,f5 as signal,Im as sin,Sm as sinh,Ot as slice,Nm as slice1d,yh as slice2d,km as slice3d,ic as slice4d,Be as slice_util,ru as softmax,Us as softplus,Ql as spaceToBatchND,h5 as sparse,u6 as sparseToDense,m5 as spectral,mr as split,Ne as sqrt,Ht as square,_m as squaredDifference,Mn as squeeze,sr as stack,yo as step,py as stridedSlice,g5 as string,ut as sub,mt as sum,Ku as sumOutType,my as tan,Oi as tanh,Cr as tensor,Ve as tensor1d,qs as tensor2d,px as tensor3d,LE as tensor4d,PE as tensor5d,ME as tensor6d,fo as tensor_util,G_ as test_util,W as tidy,$r as tile,ept as time,fy as topk,pc as train,Mt as transpose,Em as truncatedNormal,dy as unique,alt as unregisterGradient,ilt as unregisterKernel,Am as unsortedSegmentSum,Nr as unstack,ir as upcastType,zE as upperBound,x as util,IK as valueAndGrad,SK as valueAndGrads,hy as variable,Xx as variableGrads,Kat as version,fF as version_converter,W_ as version_core,tf as version_layers,Pat as version_wasm,iM as version_webgl,bke as webgl,bd as webgl_util,$e as where,xy as whereAsync,Te as zeros,St as zerosLike};