face-api/dist/face-api.js

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

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Error("No backend found in registry.");return Object.keys(this.registryFactory).sort((e,t)=>this.registryFactory[t].priority-this.registryFactory[e].priority)}initializeBackendsAndReturnBest(){let e=this.getSortedBackends();for(let t=0;t<e.length;t++){let n=e[t],{success:a,asyncInit:r}=this.initializeBackend(n);if(r||a)return{name:n,asyncInit:r}}throw new Error("Could not initialize any backends, all backend initializations failed.")}moveData(e,t){let n=this.state.tensorInfo.get(t),a=n.backend,r=this.readSync(t),s=a.refCount(t);a.disposeData(t,!0),n.backend=e,e.move(t,r,n.shape,n.dtype,s),this.shouldCheckForMemLeaks()&&this.state.numDataMovesStack[this.state.numDataMovesStack.length-1]++}tidy(e,t){let n=null;if(t==null){if(typeof e!="function")throw new Error("Please provide a function to tidy()");t=e}else{if(typeof e!="string"&&!(e instanceof String))throw new Error("When calling with two arguments, the first argument to tidy() must be a string");if(typeof t!="function")throw new Error("When calling with two arguments, the 2nd argument to tidy() must be a function");n=e}let a;return this.scopedRun(()=>this.startScope(n),()=>this.endScope(a),()=>(a=t(),a instanceof Promise&&console.error("Cannot return a Promise inside of tidy."),a))}scopedRun(e,t,n){e();try{let a=n();return t(),a}catch(a){throw t(),a}}nextTensorId(){return Zp.nextTensorId++}nextVariableId(){return Zp.nextVariableId++}clone(e){let t=O.runKernel(Ri,{x:e}),n={x:e},a=s=>({x:()=>{let i="float32",o={x:s},l={dtype:i};return O.runKernel(xi,o,l)}}),r=[];return this.addTapeNode(this.state.activeScope.name,n,[t],a,r,{}),t}runKernel(e,t,n){if(this.backendName==null&&this.backend,Dh(e,this.backendName)==null)throw new Error(`Kernel '${e}' not registered for backend '${this.backendName}'`);return this.runKernelFunc({kernelName:e,inputs:t,attrs:n})}shouldCheckForMemLeaks(){return this.ENV.getBool("IS_TEST")}checkKernelForMemLeak(e,t,n){let a=this.backend.numDataIds(),r=0;n.forEach(o=>{r+=o.dtype==="complex64"?3:1});let s=this.state.numDataMovesStack[this.state.numDataMovesStack.length-1],i=a-t-r-s;if(i>0)throw new Error(`Backend '${this.backendName}' has an internal memory leak (${i} data ids) after running '${e}'`)}runKernelFunc(e){let t,n=[],a=this.isTapeOn(),r=this.state.numBytes,s=this.state.numTensors;this.shouldCheckForMemLeaks()&&this.state.numDataMovesStack.push(0);let i;this.backendName==null&&this.backend;let o,l=my(e)?e.kernelName:this.state.activeScope!=null?this.state.activeScope.name:"";if(my(e)){let{kernelName:h,inputs:m,attrs:f}=e;this.backendName==null&&this.backend;let g=Dh(h,this.backendName);$(g!=null,()=>`Cannot find registered kernel '${h}' for backend '${this.backendName}'`),i=()=>{let b=this.backend.numDataIds();o=g.kernelFunc({inputs:m,attrs:f,backend:this.backend});let y=Array.isArray(o)?o:[o];this.shouldCheckForMemLeaks()&&this.checkKernelForMemLeak(h,b,y);let x=y.map(w=>w.rank!=null?w:this.makeTensorFromTensorInfo(w));if(a){let w=this.getTensorsForGradient(h,m,x);n=this.saveTensorsForBackwardMode(w)}return x}}else{let{forwardFunc:h}=e,m=f=>{!a||(n=f.map(g=>this.keep(this.clone(g))))};i=()=>{let f=this.backend.numDataIds();o=this.tidy(()=>h(this.backend,m));let g=Array.isArray(o)?o:[o];return this.shouldCheckForMemLeaks()&&this.checkKernelForMemLeak(l,f,g),g}}let{inputs:u,attrs:p}=e,d=my(e)?null:e.backwardsFunc,c;return this.scopedRun(()=>this.state.kernelDepth++,()=>this.state.kernelDepth--,()=>{!this.ENV.getBool("DEBUG")&&!this.state.profiling?t=i():(c=this.profiler.profileKernel(l,u,()=>i()),this.ENV.getBool("DEBUG")&&this.profiler.logKernelProfile(c),t=c.outputs)}),a&&this.addTapeNode(l,u,t,d,n,p),this.state.profiling&&this.state.activeProfile.kernels.push({name:l,bytesAdded:this.state.numBytes-r,totalBytesSnapshot:this.state.numBytes,tensorsAdded:this.state.numTensors-s,totalTensorsSnapshot:this.state.numTensors,inputShapes:Object.keys(u).map(h=>u[h]!=null?u[h].shape:null),outputShapes:t.map(h=>h.shape),kernelTimeMs:c.timeMs,extraInfo:c.extraInfo}),Array.isArray(o)?t:t[0]}saveTensorsForBackwardMode(e){return e.map(t=>this.keep(this.clone(t)))}getTensorsForGradient(e,t,n){let a=Cy(e);if(a!=null){let r=a.inputsToSave||[],s=a.outputsToSave||[],i;a.saveAllInputs?($(Array.isArray(t),()=>"saveAllInputs is true, expected inputs to be an array."),i=Object.keys(t).map(l=>t[l])):i=r.map(l=>t[l]);let o=n.filter((l,u)=>s[u]);return i.concat(o)}return[]}makeTensor(e,t,n,a){if(e==null)throw new Error("Values passed to engine.makeTensor() are null");n=n||"float32",a=a||this.backend;let r=e;n==="string"&&Qr(e[0])&&(r=e.map(o=>Ac(o)));let s=a.write(r,t,n),i=new Te(t,n,s,this.nextTensorId());if(this.trackTensor(i,a),n==="string"){let o=this.state.tensorInfo.get(s),l=KI(r);this.state.numBytes+=l-o.bytes,o.bytes=l}return i}makeTensorFromDataId(e,t,n,a){n=n||"float32";let r={dataId:e,shape:t,dtype:n};return this.makeTensorFromTensorInfo(r,a)}makeTensorFromTensorInfo(e,t){let{dataId:n,shape:a,dtype:r}=e,s=new Te(a,r,n,this.nextTensorId());return this.trackTensor(s,t),s}makeVariable(e,t=!0,n,a){n=n||this.nextVariableId().toString(),a!=null&&a!==e.dtype&&(e=e.cast(a));let r=new is(e,t,n,this.nextTensorId());if(this.state.registeredVariables[r.name]!=null)throw new Error(`Variable with name ${r.name} was already registered`);return this.state.registeredVariables[r.name]=r,this.incRef(r,this.backend),r}trackTensor(e,t){this.state.numTensors++,e.dtype==="string"&&this.state.numStringTensors++;let n=0;e.dtype!=="complex64"&&e.dtype!=="string"&&(n=e.size*Ny(e.dtype)),this.state.numBytes+=n,this.state.tensorInfo.has(e.dataId)||(this.state.numDataBuffers++,this.state.tensorInfo.set(e.dataId,{backend:t||this.backend,dtype:e.dtype,shape:e.shape,bytes:n})),e instanceof is||this.track(e)}incRef(e,t){this.trackTensor(e,t),this.backend.incRef(e.dataId)}removeDataId(e,t){this.state.tensorInfo.has(e)&&this.state.tensorInfo.get(e).backend===t&&(this.state.tensorInfo.delete(e),this.state.numDataBuffers--)}disposeTensor(e){if(!this.state.tensorInfo.has(e.dataId))return;let t=this.state.tensorInfo.get(e.dataId);if(this.state.numTensors--,e.dtype==="string"&&(this.state.numStringTensors--,this.state.numBytes-=t.bytes),e.dtype!=="complex64"&&e.dtype!=="string"){let n=e.size*Ny(e.dtype);this.state.numBytes-=n}t.backend.disposeData(e.dataId)&&this.removeDataId(e.dataId,t.backend)}disposeVariables(){for(let e in this.state.registeredVariables){let t=this.state.registeredVariables[e];this.disposeVariable(t)}}disposeVariable(e){this.disposeTensor(e),this.state.registeredVariables[e.name]!=null&&delete this.state.registeredVariables[e.name]}memory(){let e=this.backend.memory();return e.numTensors=this.state.numTensors,e.numDataBuffers=this.state.numDataBuffers,e.numBytes=this.state.numBytes,this.state.numStringTensors>0&&(e.unreliable=!0,e.reasons==null&&(e.reasons=[]),e.reasons.push("Memory usage by string tensors is approximate (2 bytes per character)")),e}async profile(e){this.state.profiling=!0;let t=this.state.numBytes,n=this.state.numTensors;this.state.activeProfile.kernels=[],this.state.activeProfile.result=await e(),this.state.profiling=!1,this.state.activeProfile.peakBytes=Math.max(...this.state.activeProfile.kernels.map(a=>a.totalBytesSnapshot)),this.state.activeProfile.newBytes=this.state.numBytes-t,this.state.activeProfile.newTensors=this.state.numTensors-n;for(let a of this.state.activeProfile.kernels)a.kernelTimeMs=await a.kernelTimeMs,a.extraInfo=await a.extraInfo;return this.state.activeProfile}isTapeOn(){return this.state.gradientDepth>0&&this.state.kernelDepth===0}addTapeNode(e,t,n,a,r,s){let i={id:this.state.nextTapeNodeId++,kernelName:e,inputs:t,outputs:n,saved:r},o=Cy(e);o!=null&&(a=o.gradFunc),a!=null&&(i.gradient=l=>(l=l.map((u,p)=>{if(u==null){let d=n[p],c=um(d.size,d.dtype);return this.makeTensor(c,d.shape,d.dtype)}return u}),a(l.length>1?l:l[0],r,s))),this.state.activeTape.push(i)}keep(e){return e.kept=!0,e}startTape(){this.state.gradientDepth===0&&(this.state.activeTape=[]),this.state.gradientDepth++}endTape(){this.state.gradientDepth--}startScope(e){let t={track:[],name:"unnamed scope",id:this.state.nextScopeId++};e&&(t.name=e),this.state.scopeStack.push(t),this.state.activeScope=t}endScope(e){let t=Rx(e),n=new Set(t.map(r=>r.id));for(let r=0;r<this.state.activeScope.track.length;r++){let s=this.state.activeScope.track[r];!s.kept&&!n.has(s.id)&&s.dispose()}let a=this.state.scopeStack.pop();this.state.activeScope=this.state.scopeStack.length===0?null:this.state.scopeStack[this.state.scopeStack.length-1],t.forEach(r=>{!r.kept&&r.scopeId===a.id&&this.track(r)})}gradients(e,t,n,a=!1){if($(t.length>0,()=>"gradients() received an empty list of xs."),n!=null&&n.dtype!=="float32")throw new Error(`dy must have 'float32' dtype, but has '${n.dtype}'`);let r=this.scopedRun(()=>this.startTape(),()=>this.endTape(),()=>this.tidy("forward",e));$(r instanceof Te,()=>"The result y returned by f() must be a tensor.");let s=wD(this.state.activeTape,t,r);if(!a&&s.length===0&&t.length>0)throw new Error("Cannot compute gradient of y=f(x) with respect to x. Make sure that the f you passed encloses all operations that lead from x to y.");return this.tidy("backward",()=>{let i={};i[r.id]=n==null?FD(r.shape):n,kD(i,s,l=>this.tidy(l),DD);let o=t.map(l=>i[l.id]);return this.state.gradientDepth===0&&(this.state.activeTape.forEach(l=>{for(let u of l.saved)u.dispose()}),this.state.activeTape=null),{value:r,grads:o}})}customGrad(e){return $(ss(e),()=>"The f passed in customGrad(f) must be a function."),(...t)=>{$(t.every(i=>i instanceof Te),()=>"The args passed in customGrad(f)(x1, x2,...) must all be tensors");let n,a={};t.forEach((i,o)=>{a[o]=i});let r=(i,o)=>(n=e(...t,o),$(n.value instanceof Te,()=>"The function f passed in customGrad(f) must return an object where `obj.value` is a tensor"),$(ss(n.gradFunc),()=>"The function f passed in customGrad(f) must return an object where `obj.gradFunc` is a function."),n.value),s=(i,o)=>{let l=n.gradFunc(i,o),u=Array.isArray(l)?l:[l];$(u.length===t.length,()=>"The function f passed in customGrad(f) must return an object where `obj.gradFunc` is a function that returns the same number of tensors as inputs passed to f(...)."),$(u.every(d=>d instanceof Te),()=>"The function f passed in customGrad(f) must return an object where `obj.gradFunc` is a function that returns a list of only tensors.");let p={};return u.forEach((d,c)=>{p[c]=()=>d}),p};return this.runKernelFunc({forwardFunc:r,backwardsFunc:s,inputs:a})}}readSync(e){return this.state.tensorInfo.get(e).backend.readSync(e)}read(e){return this.state.tensorInfo.get(e).backend.read(e)}readToGPU(e,t){return this.state.tensorInfo.get(e).backend.readToGPU(e,t)}async time(e){let t=Yp(),n=await this.backend.time(e);return n.wallMs=Yp()-t,n}track(e){return this.state.activeScope!=null&&(e.scopeId=this.state.activeScope.id,this.state.activeScope.track.push(e)),e}get registeredVariables(){return this.state.registeredVariables}reset(){this.pendingBackendInitId++,this.state.dispose(),this.ENV.reset(),this.state=new ck;for(let e in 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Error("getWeights() is not implemented for Adamax yet.")}async setWeights(e){throw new Error("setWeights() is not implemented for Adamax yet.")}getConfig(){return{learningRate:this.learningRate,beta1:this.beta1,beta2:this.beta2,epsilon:this.epsilon,decay:this.decay}}static fromConfig(e,t){return new e(t.learningRate,t.beta1,t.beta2,t.epsilon,t.decay)}};Tf.className="Adamax";ws(Tf);var qc=class extends Rr{constructor(e){super(),this.learningRate=e,this.setLearningRate(e)}applyGradients(e){(Array.isArray(e)?e.map(t=>t.name):Object.keys(e)).forEach((t,n)=>{let a=Array.isArray(e)?e[n].tensor:e[t];if(a==null)return;let r=O.registeredVariables[t];P(()=>{let s=Y(z(this.c,a),r);r.assign(s)})}),this.incrementIterations()}setLearningRate(e){this.learningRate=e,this.c!=null&&this.c.dispose(),this.c=Jt(ye(-e))}dispose(){this.c.dispose()}async getWeights(){return[await this.saveIterations()]}async setWeights(e){if(e=await this.extractIterations(e),e.length!==0)throw new Error("SGD optimizer does 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Its own _trainableWeights must remain an empty Array.");if(!this.trainable)return[];let e=[];for(let t of this.layers)e=e.concat(t.trainableWeights);return e}get nonTrainableWeights(){let e=[];for(let t of this.layers)e.push(...t.nonTrainableWeights);if(!this.trainable){let t=[];for(let n of this.layers)t.push(...n.trainableWeights);return t.concat(e)}return e}get weights(){return this.trainableWeights.concat(this.nonTrainableWeights)}loadWeights(e,t=!0){let n={},a=0;for(let s of this.layers)for(let i of s.weights){if(n[i.originalName]!=null)throw new V(`Duplicate weight name: ${i.originalName}`);n[i.originalName]=i,a++}let r=[];for(let s in e){let i=s;if(n[s]==null){let o=s.split("/");i=o.slice(0,-2).concat([o[o.length-1]]).join("/")}if(n[i]!=null)r.push([n[i],e[s]]);else if(t)throw new V(`Provided weight data has no target variable: ${s}`);delete n[i]}if(t){let s=[];for(let i in n)s.push(i);if(s.length>0)throw new V(`${s.length} of ${a} weights are not set: ${s}`)}pw(r)}updatedConfig(){let e=this.getConfig(),t={};return t.className=this.getClassName(),t.config=e,t.kerasVersion=`tfjs-layers ${vw}`,t.backend="TensorFlow.js",t}toJSON(e,t=!0){let n=Xy(this.updatedConfig());return t?JSON.stringify(n):n}call(e,t){return P(()=>{e=xt(e);let n=new js;for(let a=0;a<this.inputs.length;++a)n.add(this.inputs[a],e[a]);return Mp(this.outputs,n,t)})}computeMask(e,t){return P(()=>{e=xt(e);let n;return t==null?n=li(null,e.length):n=xt(t),this.runInternalGraph(e,n)[1]})}computeOutputShape(e){let t=Wh(e);if(t.length!==this.inputLayers.length)throw new V(`Invalid inputShape argument ${e}: model has ${this.inputLayers.length} tensor inputs.`);let n={};for(let i=0;i<t.length;i++){let o=this.inputLayers[i],l=t[i],u=o.name+"_0_0";n[u]=l}let a=Object.keys(this.nodesByDepth).map(i=>parseInt(i,10)).sort(oh);if(a.length>1)for(let i of a){let o=this.nodesByDepth[i];for(let l of o){let u=l.outboundLayer;if(this.inputLayers.map(m=>m.id).indexOf(u.id)!==-1)continue;let p=[];for(let m=0;m<l.inboundLayers.length;m++){let f=l.inboundLayers[m],g=l.nodeIndices[m],b=l.tensorIndices[m],y=`${f.name}_${g}_${b}`,x=n[y];p.push(x)}let d=u.computeOutputShape(On(p)),c=Wh(d),h=u.inboundNodes.indexOf(l);for(let m=0;m<c.length;m++){let f=`${u.name}_${h}_${m}`;n[f]=c[m]}}}let r=[],s=[];for(let i=0;i<this.outputLayers.length;i++){let o=this.outputLayers[i],l=this.outputLayersNodeIndices[i],u=this.outputLayersTensorIndices[i],p=`${o.name}_${l}_${u}`;s.push(p)}for(let i=0;i<s.length;i++){let o=s[i];ar(o in n),r.push(n[o])}return On(r)}runInternalGraph(e,t){t==null&&(t=li(null,e.length));let n={};for(let o=0;o<this.inputs.length;++o){let l=this.inputs[o],u=e[o],p=t[o];n[l.id]=[u,p]}let a=Object.keys(this.nodesByDepth).map(o=>parseInt(o,10)).sort(oh);for(let o of a){let l=this.nodesByDepth[o];for(let u of l){let p=u.outboundLayer,d=u.inputTensors,c=u.outputTensors,h=new Array;for(let m of d)m.id in n&&h.push(n[m.id]);if(h.length===d.length){let m={},f,g,b,y;if(u.callArgs!=null&&(m=u.callArgs),h.length===1){let[x,w]=h[0];m.mask==null&&(m.mask=w),b=xt(p.call(x,m)),y=xt(p.computeMask(x,w)),f=[x],g=[w]}else f=h.map(x=>x[0]),g=h.map(x=>x[1]),m.mask==null&&(m.mask=g),b=xt(p.call(f,m)),y=xt(p.computeMask(f,g));if(p.activityRegularizer)throw new Me("LayersModel invocation with concrete Tensor value(s) in the presence of activity regularizer(s) is not supported yet.");for(let x=0;x<c.length;++x){let w=c[x],I=b[x],T=y[x];n[w.id]=[I,T]}}}}let r=[],s=[],i=[];for(let o of this.outputs){ar(o.id in n,`Could not compute output ${o.name} : ${o.id}`);let[l,u]=n[o.id];i.push(l.shape),r.push(l),s.push(u)}return[r,s,i]}buildNodeConversionMap(e){let t={},n;for(let a of this.layers){n=a instanceof tr?1:0;for(let r=0;r<a.inboundNodes.length;r++){let s=tr.nodeKey(a,r);this.containerNodes.has(s)&&(t[s]=n,n+=1)}}return t}getLayer(e,t){if(t!=null){if(this.layers.length<=t)throw new V(`Was asked to retrieve layer at index ${t}, but model only has ${this.layers.length} layer(s).`);return this.layers[t]}else if(e==null)throw new V("Provide either a layer name or layer index");for(let n of this.layers)if(n.name===e)return n;throw new V(`No such layer: ${e}`)}calculateLosses(){return P(()=>{let e=[];for(let t of this.layers)for(let n=0;n<t.inboundNodes.length;++n){let a=tr.nodeKey(t,n);this.containerNodes.has(a)&&e.push(...t.calculateLosses())}return e})}getConfig(){let e={name:this.name},t=this.buildNodeConversionMap(this.layers),n=[];for(let s of this.layers){let i=s.getClassName(),o=s.getConfig(),l=[];for(let p=0;p<s.inboundNodes.length;p++){let d=s.inboundNodes[p],c=tr.nodeKey(s,p),h={};if(this.containerNodes.has(c)){if(d.callArgs)try{JSON.stringify(d.callArgs),h=d.callArgs}catch(m){console.warn(`Layer ${s.name} was passed non-serializable keyword arguments: ${d.callArgs}. They will not be included in the serialized model (and thus will be missing at deserialization time).`),h={}}if(d.inboundLayers.length>0){let m=[];for(let f=0;f<d.inboundLayers.length;f++){let g=d.inboundLayers[f],b=d.nodeIndices[f],y=d.tensorIndices[f],x=tr.nodeKey(g,b),w=t[x];w==null&&(w=0),m.push([g.name,w,y,h])}l.push(m)}}}let u={};u.name=s.name,u.className=i,u.config=o,u.inboundNodes=l,n.push(u)}e.layers=n;let a=[];for(let s=0;s<this.inputLayers.length;s++){let i=this.inputLayers[s],o=this.inputLayersNodeIndices[s],l=tr.nodeKey(i,o);if(!this.containerNodes.has(l))continue;let u=t[l];u==null&&(u=0);let p=this.inputLayersTensorIndices[s];a.push([i.name,u,p])}e.inputLayers=a;let r=[];for(let s=0;s<this.outputLayers.length;s++){let i=this.outputLayers[s],o=this.outputLayersNodeIndices[s],l=tr.nodeKey(i,o);if(!this.containerNodes.has(l))continue;let u=t[l];u==null&&(u=0);let p=this.outputLayersTensorIndices[s];r.push([i.name,u,p])}return e.outputLayers=r,e}static fromConfig(e,t,n={},a=!1){let r={},s={};function i(f,g){f.name in s?s[f.name].push(g):s[f.name]=[g]}function o(f,g){let b=[],y;for(let x of g){let w=x[0],I=x[1],T=x[2];if(y=x[3]==null?{}:x[3],!(w in r)){i(f,g);return}let C=r[w];if(C.inboundNodes.length<=I){i(f,g);return}let E=C.inboundNodes[I];b.push(E.outputTensors[T])}b.length>0&&f.apply(On(b),y)}function l(f){let g=f.name,b=Ua(f,t.customObjects!=null?t.customObjects:{});b.setFastWeightInitDuringBuild(a),r[g]=b,f.inboundNodes.forEach(y=>{if(!(y instanceof Array))throw new V(`Corrupted configuration, expected array for nodeData: ${y}`);i(b,y)})}let u=t.name,p=t.layers;for(let f of p)l(f);for(;!B4(s);)for(let f of p){let g=r[f.name];if(g.name in s){let b=s[g.name];delete s[g.name];for(let y of b)o(g,y)}}let d=[],c=[],h=t.inputLayers;for(let f of h){let g=f[0],b=f[1],y=f[2];ar(g in r);let x=r[g].inboundNodes[b].outputTensors;d.push(x[y])}let m=t.outputLayers;for(let f of m){let g=f[0],b=f[1],y=f[2];ar(g in r);let x=r[g].inboundNodes[b].outputTensors;c.push(x[y])}return new e({inputs:d,outputs:c,name:u})}get stateful(){if(this._stateful)throw new V("Container instance unexpectedly has _stateful = true. The statefulness of a Container is determined by the Layers it contains. Its _stateful property must remain the default false.");for(let e of this.layers)if(e.stateful)return!0;return!1}resetStates(){P(()=>{this.layers.forEach(e=>{e.stateful&&e.resetStates()})})}};function hU(e,t,n){let a=t.length;if(e==null||Array.isArray(e)&&e.length===0)return t.map(r=>null);if(a===1)return Array.isArray(e)&&e.length===1?e:typeof e=="object"&&t[0]in e?[e[t[0]]]:[e];if(Array.isArray(e)){if(e.length!==a)throw new Error(`Provided ${n} is an array of ${e.length} element(s), but the model has ${a} outputs. Make sure a set of weights is provided for each model output.`);return e}else if(typeof e=="object"&&Object.keys(e).length>0&&typeof e[Object.keys(e)[0]]=="object"){let r=[];return t.forEach(s=>{s in e?r.push(e[s]):r.push(null)}),r}else throw new Error(`The model has multiple (${a}) outputs, so ${n} must be either an array with ${a} elements or an object with ${t} keys. Provided ${n} not understood: ${JSON.stringify(e)}`)}function DN(e,t){return hU(e,t,"classWeight")}async function RN(e,t,n,a){if(t!=null||a!=null)throw new Error("Support sampleWeight is not implemented yet");if(n!=null){let r=P(()=>{if(e.shape.length===1)return ir(e);if(e.shape.length===2){if(e.shape[1]>1)return ri(e,1);if(e.shape[1]===1)return W(e,[e.shape[0]]);throw new Error(`Encountered unexpected last-dimension size (${e.shape[1]}) during handling of class weights. The size is expected to be >= 1.`)}else throw new Error(`Unexpected rank of target (y) tensor (${e.rank}) during handling of class weights. The rank is expected to be 1 or 2.`)}),s=Array.from(await r.data());_e(r);let i=[];return s.forEach(o=>{if(n[o]==null)throw new Error(`classWeight must contain all classes in the training data. The class ${o} exists in the data but not in classWeight`);i.push(n[o])}),Ke(i,"float32")}else return null}function mU(e,t){return z(e,t)}var fU=32;function MN(e,t){let n,a,r=t;n=r.xs,a=r.ys,v.assert(n!=null&&a!=null,()=>`A Dataset iterator for fitDataset() is expected to generate objects of the form \`{xs: xVal, ys: yVal}\`, where the two values may be \`tf.Tensor\`, an array of Tensors, or a map of string to Tensor.  The provided Dataset instead generates ${t}`);let s=zk("input",e.inputNames,n),i=zk("output",e.outputNames,a),o=s[0].shape[0];v.assert(s.length===e.inputs.length,()=>`LayersModel has ${e.inputs.length} inputs, but the dataset provides ${s.length} inputs.  (Expected input keys: ${JSON.stringify(e.inputNames)})`),v.assert(i.length===e.outputs.length,()=>`LayersModel has ${e.outputs.length} outputs, but the dataset provides ${i.length} outputs.  (Expected output keys: ${JSON.stringify(e.outputNames)})`);for(let l=0;l<s.length;l++)v.assert(s[l].shape[0]===o,()=>`Batch size mismatch: input ${e.inputNames[l]} has ${s[l].shape[0]}; expected  ${o} based on input ${e.inputNames[0]}.`);for(let l=0;l<i.length;l++)v.assert(i[l].shape[0]===o,()=>`Batch size mismatch: output ${e.outputNames[l]} has ${i[l].shape[0]}; expected  ${o} based on input ${e.inputNames[0]}.`);return{xs:s,ys:i}}function zk(e,t,n){if(n instanceof Te)return[n];if(Array.isArray(n))return v.assert(n.length===t.length,()=>`Received an array of ${n.length} Tensors, but expected ${t.length} to match the ${e} keys ${t}.`),n;{let a=[];for(let r of t){if(n[r]==null)throw new V(`The feature data generated by the dataset lacks the required ${e} key '${r}'.`);a.push(n[r])}return a}}function gU(e){if(e.length===3)throw new Me("Validation with sample weights is not implemented yet.");return{xs:e[0],ys:e[1]}}async function bU(e,t,n){let a=n.batchesPerEpoch!=null;if(v.assert(e.optimizer!=null,()=>"You must compile a model before training/testing. Use LayersModel.compile(modelCompileConfig)."),v.assert(n!=null,()=>"For fitDataset(), the 2nd argument (config) is required, but it is not provided in this call."),v.assert(n.epochs!=null&&n.epochs>0&&Number.isInteger(n.epochs),()=>`For fitDataset(), config.epochs is expected to be a positive integer, but got ${n.epochs}`),v.assert(!a||n.batchesPerEpoch>0&&Number.isInteger(n.batchesPerEpoch),()=>`For fitDataset(), config.batchesPerEpoch is expected to be a positive integer if specified, but got ${n.batchesPerEpoch}`),v.assert(n.validationSplit==null,()=>"`validationSplit` is not supported by `fitDataset()`. Use validationData instead."),e.isTraining)throw new Error("Cannot start training because another fit() call is ongoing.");e.isTraining=!0;try{let r=n.validationData!=null,s,i;if(r)if(Wk(n.validationData))v.assert(n.validationBatches==null||n.validationBatches>0&&Number.isInteger(n.validationBatches),()=>`For fitDataset() with dataset-based validation, config.validationBatches is expected not to be provided, or to be a positive integer, but got ${n.validationBatches}`);else{let g=gU(n.validationData);s=g.xs,i=g.ys}let o=e.makeTrainFunction(),l=e.getDedupedMetricsNames(),u;r?u=l.slice().concat(l.map(g=>"val_"+g)):u=l.slice();let p=TN(n.callbacks,n.yieldEvery),d=n.verbose==null?1:n.verbose,{callbackList:c,history:h}=NN(p,d,n.epochs,null,null,yU(t,n),null,r,u);c.setModel(e),e.history=h,await c.onTrainBegin(),e.stopTraining_=!1;let m=n.initialEpoch==null?0:n.initialEpoch,f=await t.iterator();for(;m<n.epochs;){let g={};await c.onEpochBegin(m);let b=0,y=0;for(a||(f=await t.iterator());!a||b<n.batchesPerEpoch;){let x=await f.next();if(a&&x.done){console.warn(`You provided \`batchesPerEpoch\` as ${n.batchesPerEpoch}, but your dataset iterator ran out of data after ${b} batches; interrupting training. Make sure that your dataset can generate at least \`batchesPerEpoch * epochs\` batches (in this case, ${n.batchesPerEpoch*n.epochs} batches). 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e={theta:this.theta},t=super.getConfig();return Object.assign(e,t),e}};_w.className="ThresholdedReLU";ne.registerClass(_w);var Ew=class extends Ge{constructor(e){super(e==null?{}:e),this.DEFAULT_AXIS=1,e==null&&(e={}),this.softmax=new kw().apply,this.axis=e.axis==null?this.DEFAULT_AXIS:e.axis}call(e,t){let n=Ne(e);return this.softmax(n,this.axis)}computeOutputShape(e){return e}getConfig(){let e={axis:this.axis},t=super.getConfig();return Object.assign(e,t),e}};Ew.className="Softmax";ne.registerClass(Ew);function dl(e,t,n){if(typeof e=="number")return li(e,t);if(e.length!==t)throw new V(`The ${n} argument must be an integer or tuple of ${t} integers. Received: ${e.length} elements.`);for(let a=0;a<t;++a){let r=e[a];if(!J4(r))throw new V(`The ${n} argument must be an integer or tuple of ${t} integers. Received: ${JSON.stringify(e)} including a non-integer number ${r}`)}return e}function Ga(e,t,n,a,r=1){if(e==null)return e;let s=t+(t-1)*(r-1),i;return n==="same"?i=e:i=e-s+1,Math.floor((i+a-1)/a)}function rr(e,t,n,a){if(e==null)return null;if(a==="valid")e=e*t+ls([n-t,0]);else if(a==="same")e=e*t;else throw new V(`Unsupport padding mode: ${a}.`);return e}function Aw(e,t){return P(()=>(Rt(t),t==="channelsFirst"?Ee(e,[0,2,3,1]):e))}function QN(e,t){return P(()=>(Rt(t),t==="channelsFirst"?Ee(e,[0,2,3,4,1]):e))}function OU(e,t,n,a=1,r="valid",s,i=1){return P(()=>{if(s==null&&(s=ja()),Rt(s),e.shape.length!==3)throw new V(`The input of a conv1dWithBias operation should be 3, but is ${e.shape.length} instead.`);if(t.shape.length!==3)throw new V(`The kernel for a conv1dWithBias operation should be 3, but is ${t.shape.length} instead`);if(n!=null&&n.shape.length!==1)throw new V(`The bias for a conv1dWithBias operation should be 1, but is ${t.shape.length} instead`);if(s==="channelsFirst"&&(e=Ee(e,[0,2,1])),r==="causal")throw new Me("The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.");let o=qm(e,t,a,r==="same"?"same":"valid","NWC",i);return n!=null&&(o=Xa(o,n)),o})}function jk(e,t,n,a=[1,1],r="valid",s,i,o=null){return P(()=>{if(s==null&&(s=ja()),Rt(s),e.rank!==3&&e.rank!==4)throw new V(`conv2dWithBiasActivation expects input to be of rank 3 or 4, but received ${e.rank}.`);if(t.rank!==3&&t.rank!==4)throw new V(`conv2dWithBiasActivation expects kernel to be of rank 3 or 4, but received ${e.rank}.`);let l=Aw(e,s);if(r==="causal")throw new Me("The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.");return l=kl.conv2d({x:l,filter:t,strides:a,pad:r==="same"?"same":"valid",dilations:i,dataFormat:"NHWC",bias:n,activation:o}),s==="channelsFirst"&&(l=Ee(l,[0,3,1,2])),l})}function LU(e,t,n,a=[1,1,1],r="valid",s,i){return P(()=>{if(s==null&&(s=ja()),Rt(s),e.rank!==4&&e.rank!==5)throw new V(`conv3dWithBias expects input to be of rank 4 or 5, but received ${e.rank}.`);if(t.rank!==4&&t.rank!==5)throw new V(`conv3dWithBias expects kernel to be of rank 4 or 5, but received ${e.rank}.`);let o=QN(e,s);if(r==="causal")throw new Me("The support for CAUSAL padding mode in conv3dWithBias is not implemented yet.");return o=fv(o,t,a,r==="same"?"same":"valid","NDHWC",i),n!=null&&(o=Xa(o,n)),s==="channelsFirst"&&(o=Ee(o,[0,4,1,2,3])),o})}var $w=class extends Ge{constructor(e,t){if(super(t),this.bias=null,this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_BIAS_INITIALIZER="zeros",$w.verifyArgs(t),this.rank=e,Qt(this.rank,"rank"),this.rank!==1&&this.rank!==2&&this.rank!==3)throw new Me(`Convolution layer for rank other than 1, 2, or 3 (${this.rank}) is not implemented yet.`);if(this.kernelSize=dl(t.kernelSize,e,"kernelSize"),this.strides=dl(t.strides==null?1:t.strides,e,"strides"),this.padding=t.padding==null?"valid":t.padding,xa(this.padding),this.dataFormat=t.dataFormat==null?"channelsLast":t.dataFormat,Rt(this.dataFormat),this.activation=ps(t.activation),this.useBias=t.useBias==null?!0:t.useBias,this.biasInitializer=St(t.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.biasConstraint=Kt(t.biasConstraint),this.biasRegularizer=Tt(t.biasRegularizer),this.activityRegularizer=Tt(t.activityRegularizer),this.dilationRate=dl(t.dilationRate==null?1:t.dilationRate,e,"dilationRate"),this.rank===1&&Array.isArray(this.dilationRate)&&this.dilationRate.length!==1)throw new V(`dilationRate must be a number or an array of a single number for 1D convolution, but received ${JSON.stringify(this.dilationRate)}`);if(this.rank===2){if(typeof this.dilationRate=="number")this.dilationRate=[this.dilationRate,this.dilationRate];else if(this.dilationRate.length!==2)throw new V(`dilationRate must be a number or array of two numbers for 2D convolution, but received ${JSON.stringify(this.dilationRate)}`)}else if(this.rank===3){if(typeof this.dilationRate=="number")this.dilationRate=[this.dilationRate,this.dilationRate,this.dilationRate];else if(this.dilationRate.length!==3)throw new V(`dilationRate must be a number or array of three numbers for 3D convolution, but received ${JSON.stringify(this.dilationRate)}`)}}static verifyArgs(e){if(ar("kernelSize"in e,"required key 'kernelSize' not in config"),typeof e.kernelSize!="number"&&!tw(e.kernelSize,"number",1,3))throw new V(`BaseConv expects config.kernelSize to be number or number[] with length 1, 2, or 3, but received ${JSON.stringify(e.kernelSize)}.`)}getConfig(){let e={kernelSize:this.kernelSize,strides:this.strides,padding:this.padding,dataFormat:this.dataFormat,dilationRate:this.dilationRate,activation:us(this.activation),useBias:this.useBias,biasInitializer:Ct(this.biasInitializer),biasRegularizer:pt(this.biasRegularizer),activityRegularizer:pt(this.activityRegularizer),biasConstraint:qt(this.biasConstraint)},t=super.getConfig();return Object.assign(e,t),e}},ed=class extends $w{constructor(e,t){super(e,t),this.kernel=null,ed.verifyArgs(t),this.filters=t.filters,Qt(this.filters,"filters"),this.kernelInitializer=St(t.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.kernelConstraint=Kt(t.kernelConstraint),this.kernelRegularizer=Tt(t.kernelRegularizer)}build(e){e=tt(e);let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null)throw new V(`The channel dimension of the input should be defined. Found ${e[t]}`);let n=e[t],a=this.kernelSize.concat([n,this.filters]);this.kernel=this.addWeight("kernel",a,null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[{ndim:this.rank+2,axes:{[t]:n}}],this.built=!0}call(e,t){return P(()=>{e=Ne(e);let n,a=this.bias==null?null:this.bias.read(),r=oN(this.activation.getClassName());if(r!=null&&this.rank===2)n=jk(e,this.kernel.read(),a,this.strides,this.padding,this.dataFormat,this.dilationRate,r);else{if(this.rank===1)n=OU(e,this.kernel.read(),a,this.strides[0],this.padding,this.dataFormat,this.dilationRate[0]);else if(this.rank===2)n=jk(e,this.kernel.read(),a,this.strides,this.padding,this.dataFormat,this.dilationRate);else if(this.rank===3)n=LU(e,this.kernel.read(),a,this.strides,this.padding,this.dataFormat,this.dilationRate);else throw new Me("convolutions greater than 3D are not implemented yet.");this.activation!=null&&(n=this.activation.apply(n))}return n})}computeOutputShape(e){e=tt(e);let t=[],n=this.dataFormat==="channelsLast"?e.slice(1,e.length-1):e.slice(2);for(let r=0;r<n.length;++r){let s=Ga(n[r],this.kernelSize[r],this.padding,this.strides[r],typeof this.dilationRate=="number"?this.dilationRate:this.dilationRate[r]);t.push(s)}let a=[e[0]];return this.dataFormat==="channelsLast"?(a=a.concat(t),a.push(this.filters)):(a.push(this.filters),a=a.concat(t)),a}getConfig(){let e={filters:this.filters,kernelInitializer:Ct(this.kernelInitializer),kernelRegularizer:pt(this.kernelRegularizer),kernelConstraint:qt(this.kernelConstraint)},t=super.getConfig();return Object.assign(e,t),e}static verifyArgs(e){if(!("filters"in e)||typeof e.filters!="number"||e.filters<1)throw new V(`Convolution layer expected config.filters to be a 'number' > 0 but got ${JSON.stringify(e.filters)}`)}},td=class extends ed{constructor(e){super(2,e),td.verifyArgs(e)}getConfig(){let e=super.getConfig();return delete e.rank,e}static verifyArgs(e){if(typeof e.kernelSize!="number"&&!tw(e.kernelSize,"number",1,2))throw new V(`Conv2D expects config.kernelSize to be number or number[] with length 1 or 2, but received ${JSON.stringify(e.kernelSize)}.`)}};td.className="Conv2D";ne.registerClass(td);var nd=class extends ed{constructor(e){super(3,e),nd.verifyArgs(e)}getConfig(){let e=super.getConfig();return delete e.rank,e}static verifyArgs(e){if(typeof e.kernelSize!="number"&&!(Array.isArray(e.kernelSize)&&(e.kernelSize.length===1||e.kernelSize.length===3)))throw new V(`Conv3D expects config.kernelSize to be number or [number, number, number], but received ${JSON.stringify(e.kernelSize)}.`)}};nd.className="Conv3D";ne.registerClass(nd);var Fw=class extends td{constructor(e){if(super(e),this.inputSpec=[new zt({ndim:4})],this.padding!=="same"&&this.padding!=="valid")throw new V(`Conv2DTranspose currently supports only padding modes 'same' and 'valid', but received padding mode ${this.padding}`)}build(e){if(e=tt(e),e.length!==4)throw new V("Input should have rank 4; Received input shape: "+JSON.stringify(e));let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null)throw new V("The channel dimension of the inputs should be defined. Found `None`.");let n=e[t],a=this.kernelSize.concat([this.filters,n]);this.kernel=this.addWeight("kernel",a,"float32",this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[new zt({ndim:4,axes:{[t]:n}})],this.built=!0}call(e,t){return P(()=>{let n=Ne(e);if(n.shape.length!==4)throw new V(`Conv2DTranspose.call() expects input tensor to be rank-4, but received a tensor of rank-${n.shape.length}`);let a=n.shape,r=a[0],s,i;this.dataFormat==="channelsFirst"?(s=2,i=3):(s=1,i=2);let o=a[s],l=a[i],u=this.kernelSize[0],p=this.kernelSize[1],d=this.strides[0],c=this.strides[1],h=rr(o,d,u,this.padding),m=rr(l,c,p,this.padding),f=[r,h,m,this.filters];this.dataFormat!=="channelsLast"&&(n=Ee(n,[0,2,3,1]));let g=Km(n,this.kernel.read(),f,this.strides,this.padding);return this.dataFormat!=="channelsLast"&&(g=Ee(g,[0,3,1,2])),this.bias!=null&&(g=Xa(g,this.bias.read(),this.dataFormat)),this.activation!=null&&(g=this.activation.apply(g)),g})}computeOutputShape(e){e=tt(e);let t=e.slice(),n,a,r;this.dataFormat==="channelsFirst"?(n=1,a=2,r=3):(n=3,a=1,r=2);let s=this.kernelSize[0],i=this.kernelSize[1],o=this.strides[0],l=this.strides[1];return t[n]=this.filters,t[a]=rr(t[a],o,s,this.padding),t[r]=rr(t[r],l,i,this.padding),t}getConfig(){let e=super.getConfig();return delete e.dilationRate,e}};Fw.className="Conv2DTranspose";ne.registerClass(Fw);var Dw=class extends nd{constructor(e){if(super(e),this.inputSpec=[new zt({ndim:5})],this.padding!=="same"&&this.padding!=="valid")throw new V(`Conv3DTranspose currently supports only padding modes 'same' and 'valid', but received padding mode ${this.padding}`)}build(e){if(e=tt(e),e.length!==5)throw new V("Input should have rank 5; Received input shape: "+JSON.stringify(e));let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null)throw new V("The channel dimension of the inputs should be defined. Found `None`.");let n=e[t],a=this.kernelSize.concat([this.filters,n]);this.kernel=this.addWeight("kernel",a,"float32",this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[new zt({ndim:5,axes:{[t]:n}})],this.built=!0}call(e,t){return P(()=>{let n=Ne(e);if(n.shape.length!==5)throw new V(`Conv3DTranspose.call() expects input tensor to be rank-4, but received a tensor of rank-${n.shape.length}`);let a=n.shape,r=a[0],s,i,o;this.dataFormat==="channelsFirst"?(o=2,s=3,i=4):(o=1,s=2,i=3);let l=a[o],u=a[s],p=a[i],d=this.kernelSize[0],c=this.kernelSize[1],h=this.kernelSize[2],m=this.strides[0],f=this.strides[1],g=this.strides[2],b=rr(l,m,d,this.padding),y=rr(u,f,c,this.padding),x=rr(p,g,h,this.padding),w=[r,b,y,x,this.filters];this.dataFormat!=="channelsLast"&&(n=Ee(n,[0,2,3,4,1]));let I=gv(n,this.kernel.read(),w,this.strides,this.padding);return this.dataFormat!=="channelsLast"&&(I=Ee(I,[0,4,1,2,3])),this.bias!==null&&(I=Xa(I,this.bias.read(),this.dataFormat)),this.activation!==null&&(I=this.activation.apply(I)),I})}computeOutputShape(e){e=tt(e);let t=e.slice(),n,a,r,s;this.dataFormat==="channelsFirst"?(n=1,a=2,r=3,s=4):(n=4,a=1,r=2,s=3);let i=this.kernelSize[0],o=this.kernelSize[1],l=this.kernelSize[2],u=this.strides[0],p=this.strides[1],d=this.strides[2];return t[n]=this.filters,t[a]=rr(t[a],u,i,this.padding),t[r]=rr(t[r],p,o,this.padding),t[s]=rr(t[s],d,l,this.padding),t}getConfig(){let e=super.getConfig();return delete e.dilationRate,e}};Dw.className="Conv3DTranspose";ne.registerClass(Dw);var e2=class extends ed{constructor(e,t){if(super(e,t),this.DEFAULT_DEPTHWISE_INITIALIZER="glorotUniform",this.DEFAULT_POINTWISE_INITIALIZER="glorotUniform",this.depthwiseKernel=null,this.pointwiseKernel=null,t.filters==null)throw new V("The `filters` configuration field is required by SeparableConv, but is unspecified.");if(t.kernelInitializer!=null||t.kernelRegularizer!=null||t.kernelConstraint!=null)throw new V("Fields kernelInitializer, kernelRegularizer and kernelConstraint are invalid for SeparableConv2D. Use depthwiseInitializer, depthwiseRegularizer, depthwiseConstraint, pointwiseInitializer, pointwiseRegularizer and pointwiseConstraint instead.");if(t.padding!=null&&t.padding!=="same"&&t.padding!=="valid")throw new V(`SeparableConv${this.rank}D supports only padding modes: 'same' and 'valid', but received ${JSON.stringify(t.padding)}`);this.depthMultiplier=t.depthMultiplier==null?1:t.depthMultiplier,this.depthwiseInitializer=St(t.depthwiseInitializer||this.DEFAULT_DEPTHWISE_INITIALIZER),this.depthwiseRegularizer=Tt(t.depthwiseRegularizer),this.depthwiseConstraint=Kt(t.depthwiseConstraint),this.pointwiseInitializer=St(t.depthwiseInitializer||this.DEFAULT_POINTWISE_INITIALIZER),this.pointwiseRegularizer=Tt(t.pointwiseRegularizer),this.pointwiseConstraint=Kt(t.pointwiseConstraint)}build(e){if(e=tt(e),e.length<this.rank+2)throw new V(`Inputs to SeparableConv${this.rank}D should have rank ${this.rank+2}, but received input shape: ${JSON.stringify(e)}`);let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null||e[t]<0)throw new V(`The channel dimension of the inputs should be defined, but found ${JSON.stringify(e[t])}`);let n=e[t],a=this.kernelSize.concat([n,this.depthMultiplier]),r=[];for(let i=0;i<this.rank;++i)r.push(1);r.push(n*this.depthMultiplier,this.filters);let s=!0;this.depthwiseKernel=this.addWeight("depthwise_kernel",a,"float32",this.depthwiseInitializer,this.depthwiseRegularizer,s,this.depthwiseConstraint),this.pointwiseKernel=this.addWeight("pointwise_kernel",r,"float32",this.pointwiseInitializer,this.pointwiseRegularizer,s,this.pointwiseConstraint),this.useBias?this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,s,this.biasConstraint):this.bias=null,this.inputSpec=[new zt({ndim:this.rank+2,axes:{[t]:n}})],this.built=!0}call(e,t){return P(()=>{e=Ne(e);let n;if(this.rank===1)throw new Me("1D separable convolution is not implemented yet.");return this.rank===2&&(this.dataFormat==="channelsFirst"&&(e=Ee(e,[0,2,3,1])),n=Ts(e,this.depthwiseKernel.read(),this.pointwiseKernel.read(),this.strides,this.padding,this.dilationRate,"NHWC")),this.useBias&&(n=Xa(n,this.bias.read(),this.dataFormat)),this.activation!=null&&(n=this.activation.apply(n)),this.dataFormat==="channelsFirst"&&(n=Ee(n,[0,3,1,2])),n})}getConfig(){let e=super.getConfig();return delete e.rank,delete e.kernelInitializer,delete e.kernelRegularizer,delete e.kernelConstraint,e.depthwiseInitializer=Ct(this.depthwiseInitializer),e.pointwiseInitializer=Ct(this.pointwiseInitializer),e.depthwiseRegularizer=pt(this.depthwiseRegularizer),e.pointwiseRegularizer=pt(this.pointwiseRegularizer),e.depthwiseConstraint=qt(this.depthwiseConstraint),e.pointwiseConstraint=qt(this.pointwiseConstraint),e}};e2.className="SeparableConv";var Rw=class extends e2{constructor(e){super(2,e)}};Rw.className="SeparableConv2D";ne.registerClass(Rw);var Wf=class extends ed{constructor(e){super(1,e),Wf.verifyArgs(e),this.inputSpec=[{ndim:3}]}getConfig(){let e=super.getConfig();return delete e.rank,delete e.dataFormat,e}static verifyArgs(e){if(typeof e.kernelSize!="number"&&!tw(e.kernelSize,"number",1,1))throw new V(`Conv1D expects config.kernelSize to be number or number[] with length 1, but received ${JSON.stringify(e.kernelSize)}.`)}};Wf.className="Conv1D";ne.registerClass(Wf);var Mw=class extends Ge{constructor(e){super(e),typeof e.cropping=="number"?this.cropping=[[e.cropping,e.cropping],[e.cropping,e.cropping]]:typeof e.cropping[0]=="number"?this.cropping=[[e.cropping[0],e.cropping[0]],[e.cropping[1],e.cropping[1]]]:this.cropping=e.cropping,this.dataFormat=e.dataFormat===void 0?"channelsLast":e.dataFormat,this.inputSpec=[{ndim:4}]}computeOutputShape(e){return this.dataFormat==="channelsFirst"?[e[0],e[1],e[2]-this.cropping[0][0]-this.cropping[0][1],e[3]-this.cropping[1][0]-this.cropping[1][1]]:[e[0],e[1]-this.cropping[0][0]-this.cropping[0][1],e[2]-this.cropping[1][0]-this.cropping[1][1],e[3]]}call(e,t){return P(()=>{if(e=Ne(e),this.dataFormat==="channelsLast"){let n=uh(e,this.cropping[0][0],e.shape[1]-this.cropping[0][0]-this.cropping[0][1],2);return uh(n,this.cropping[1][0],e.shape[2]-this.cropping[1][1]-this.cropping[1][0],3)}else{let n=uh(e,this.cropping[0][0],e.shape[2]-this.cropping[0][0]-this.cropping[0][1],3);return uh(n,this.cropping[1][0],e.shape[3]-this.cropping[1][1]-this.cropping[1][0],4)}})}getConfig(){let e={cropping:this.cropping,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}};Mw.className="Cropping2D";ne.registerClass(Mw);var Pw=class extends Ge{constructor(e){super(e),this.DEFAULT_SIZE=[2,2],this.inputSpec=[{ndim:4}],this.size=e.size==null?this.DEFAULT_SIZE:e.size,this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,Rt(this.dataFormat),this.interpolation=e.interpolation==null?"nearest":e.interpolation,X4(this.interpolation)}computeOutputShape(e){if(this.dataFormat==="channelsFirst"){let t=e[2]==null?null:this.size[0]*e[2],n=e[3]==null?null:this.size[1]*e[3];return[e[0],e[1],t,n]}else{let t=e[1]==null?null:this.size[0]*e[1],n=e[2]==null?null:this.size[1]*e[2];return[e[0],t,n,e[3]]}}call(e,t){return P(()=>{let n=Ne(e),a=n.shape;if(this.dataFormat==="channelsFirst"){n=Ee(n,[0,2,3,1]);let r=this.size[0]*a[2],s=this.size[1]*a[3],i=this.interpolation==="nearest"?za.resizeNearestNeighbor(n,[r,s]):za.resizeBilinear(n,[r,s]);return Ee(i,[0,3,1,2])}else{let r=this.size[0]*a[1],s=this.size[1]*a[2];return this.interpolation==="nearest"?za.resizeNearestNeighbor(n,[r,s]):za.resizeBilinear(n,[r,s])}})}getConfig(){let e={size:this.size,dataFormat:this.dataFormat,interpolation:this.interpolation},t=super.getConfig();return Object.assign(e,t),e}};Pw.className="UpSampling2D";ne.registerClass(Pw);function zU(e,t,n=[1,1],a="valid",r,s){return P(()=>{r==null&&(r=ja()),Rt(r);let i=Aw(e,r);if(e.rank!==4)throw new V(`Input for depthwiseConv2d is required to be 4-D, but is instead ${e.rank}-D`);if(t.rank!==4)throw new V(`depthwiseKernel is required to be 4-D, but is instead ${t.rank}-D`);return i=Is(i,t,n,a==="same"?"same":"valid","NHWC",s),r==="channelsFirst"&&(i=Ee(i,[0,3,1,2])),i})}var Ow=class extends $w{constructor(e){super(2,e),this.depthwiseKernel=null,this.depthMultiplier=e.depthMultiplier==null?1:e.depthMultiplier,this.depthwiseInitializer=St(e.depthwiseInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.depthwiseConstraint=Kt(e.depthwiseConstraint),this.depthwiseRegularizer=Tt(e.depthwiseRegularizer)}build(e){if(e=tt(e),e.length<4)throw new V(`Inputs to DepthwiseConv2D should have rank 4. Received input shape: ${JSON.stringify(e)}.`);let t=this.dataFormat==="channelsFirst"?1:3;if(e[t]==null||e[t]<0)throw new V(`The channel dimension of the inputs to DepthwiseConv2D should be defined, but is not (${e[t]}).`);let n=e[t],a=[this.kernelSize[0],this.kernelSize[1],n,this.depthMultiplier];this.depthwiseKernel=this.addWeight("depthwise_kernel",a,null,this.depthwiseInitializer,this.depthwiseRegularizer,!0,this.depthwiseConstraint),this.useBias?this.bias=this.addWeight("bias",[n*this.depthMultiplier],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint):this.bias=null,this.built=!0}call(e,t){return P(()=>{e=Ne(e);let n=zU(e,this.depthwiseKernel.read(),this.strides,this.padding,this.dataFormat,null);return this.useBias&&(n=Xa(n,this.bias.read(),this.dataFormat)),this.activation!=null&&(n=this.activation.apply(n)),n})}computeOutputShape(e){e=tt(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],n=this.dataFormat==="channelsFirst"?e[3]:e[2],a=this.dataFormat==="channelsFirst"?e[1]*this.depthMultiplier:e[3]*this.depthMultiplier,r=Ga(t,this.kernelSize[0],this.padding,this.strides[0]),s=Ga(n,this.kernelSize[1],this.padding,this.strides[1]);return this.dataFormat==="channelsFirst"?[e[0],a,r,s]:[e[0],r,s,a]}getConfig(){let e=super.getConfig();return e.depthMultiplier=this.depthMultiplier,e.depthwiseInitializer=Ct(this.depthwiseInitializer),e.depthwiseRegularizer=pt(this.depthwiseRegularizer),e.depthwiseConstraint=qt(this.depthwiseRegularizer),e}};Ow.className="DepthwiseConv2D";ne.registerClass(Ow);function t2(e,t,n,a){if(Array.isArray(e)){if(t!=null||n!=null)throw new V("When inputs is an array, neither initialState or constants should be provided");a!=null&&(n=e.slice(e.length-a,e.length),e=e.slice(0,e.length-a)),e.length>1&&(t=e.slice(1,e.length)),e=e[0]}function r(s){return s==null||Array.isArray(s)?s:[s]}return t=r(t),n=r(n),{inputs:e,initialState:t,constants:n}}function n2(e,t,n,a=!1,r,s,i=!1,o=!1){return P(()=>{let l=t.shape.length;if(l<3)throw new V(`Input should be at least 3D, but is ${l}D.`);let u=[1,0].concat(Ha(2,l));if(t=Ee(t,u),s!=null)throw new Me("The rnn() functoin of the deeplearn.js backend does not support constants yet.");i&&console.warn("Backend rnn(): the unroll = true option is not applicable to the imperative deeplearn.js backend."),r!=null&&(r=oe(oe(r,"bool"),"float32"),r.rank===l-1&&(r=Zt(r,-1)),r=Ee(r,u)),a&&(t=ga(t,0),r!=null&&(r=ga(r,0)));let p=[],d,c=n,h=t.shape[0],m=ct(t),f;r!=null&&(f=ct(r));for(let b=0;b<h;++b){let y=m[b],x=P(()=>e(y,c));if(r==null)d=x[0],c=x[1];else{let w=P(()=>{let I=f[b],T=pe(na(I),I),C=Y(z(x[0],I),z(c[0],T)),E=c.map((A,R)=>Y(z(x[1][R],I),z(A,T)));return{output:C,newStates:E}});d=w.output,c=w.newStates}o&&p.push(d)}let g;return o&&(g=Ft(p,1)),[d,g,c]})}var mr=class extends Ge{constructor(e){super(e);let t;if(e.cell==null)throw new V("cell property is missing for the constructor of RNN.");if(Array.isArray(e.cell)?t=new Uf({cells:e.cell}):t=e.cell,t.stateSize==null)throw new V("The RNN cell should have an attribute `stateSize` (tuple of integers, one integer per RNN state).");this.cell=t,this.returnSequences=e.returnSequences==null?!1:e.returnSequences,this.returnState=e.returnState==null?!1:e.returnState,this.goBackwards=e.goBackwards==null?!1:e.goBackwards,this._stateful=e.stateful==null?!1:e.stateful,this.unroll=e.unroll==null?!1:e.unroll,this.supportsMasking=!0,this.inputSpec=[new zt({ndim:3})],this.stateSpec=null,this.states_=null,this.numConstants=null,this.keptStates=[]}getStates(){if(this.states_==null){let e=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1;return Ha(0,e).map(t=>null)}else return this.states_}setStates(e){this.states_=e}computeOutputShape(e){jy(e)&&(e=e[0]),e=e;let t=this.cell.stateSize;Array.isArray(t)||(t=[t]);let n=t[0],a;if(this.returnSequences?a=[e[0],e[1],n]:a=[e[0],n],this.returnState){let r=[];for(let s of t)r.push([e[0],s]);return[a].concat(r)}else return a}computeMask(e,t){return P(()=>{Array.isArray(t)&&(t=t[0]);let n=this.returnSequences?t:null;if(this.returnState){let a=this.states.map(r=>null);return[n].concat(a)}else return n})}get states(){if(this.states_==null){let e=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1,t=[];for(let n=0;n<e;++n)t.push(null);return t}else return this.states_}set states(e){this.states_=e}build(e){if(this.numConstants!=null)throw new Me("Constants support is not implemented in RNN yet.");jy(e)&&(e=e[0]),e=e;let t=this.stateful?e[0]:null,n=e.slice(2);this.inputSpec[0]=new zt({shape:[t,null,...n]});let a=[e[0]].concat(e.slice(2));this.cell.build(a);let r;if(Array.isArray(this.cell.stateSize)?r=this.cell.stateSize:r=[this.cell.stateSize],this.stateSpec!=null){if(!v.arraysEqual(this.stateSpec.map(s=>s.shape[s.shape.length-1]),r))throw new V(`An initialState was passed that is not compatible with cell.stateSize. Received stateSpec=${this.stateSpec}; However cell.stateSize is ${this.cell.stateSize}`)}else this.stateSpec=r.map(s=>new zt({shape:[null,s]}));this.stateful&&this.resetStates()}resetStates(e,t=!1){P(()=>{if(!this.stateful)throw new Ir("Cannot call resetStates() on an RNN Layer that is not stateful.");let n=this.inputSpec[0].shape[0];if(n==null)throw new V("If an RNN is stateful, it needs to know its batch size. Specify the batch size of your input tensors: \n- If using a Sequential model, specify the batch size by passing a `batchInputShape` option to your first layer.\n- If using the functional API, specify the batch size by passing a `batchShape` option to your Input layer.");if(this.states_==null)Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(a=>It([n,a])):this.states_=[It([n,this.cell.stateSize])];else if(e==null)_e(this.states_),this.keptStates!=null&&(_e(this.keptStates),this.keptStates=[]),Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(a=>It([n,a])):this.states_[0]=It([n,this.cell.stateSize]);else{if(Array.isArray(e)||(e=[e]),e.length!==this.states_.length)throw new V(`Layer ${this.name} expects ${this.states_.length} state(s), but it received ${e.length} state value(s). Input received: ${e}`);t===!0?this.keptStates.push(this.states_.slice()):_e(this.states_);for(let a=0;a<this.states_.length;++a){let r=e[a],s=Array.isArray(this.cell.stateSize)?this.cell.stateSize[a]:this.cell.stateSize,i=[n,s];if(!v.arraysEqual(r.shape,i))throw new V(`State ${a} is incompatible with layer ${this.name}: expected shape=${i}, received shape=${r.shape}`);this.states_[a]=r}}this.states_=this.states_.map(a=>Jt(a.clone()))})}apply(e,t){let n=t==null?null:t.initialState,a=t==null?null:t.constants;t==null&&(t={});let r=t2(e,n,a,this.numConstants);e=r.inputs,n=r.initialState,a=r.constants;let s=[],i=[];if(n!=null){t.initialState=n,s=s.concat(n),this.stateSpec=[];for(let o of n)this.stateSpec.push(new zt({shape:o.shape}));i=i.concat(this.stateSpec)}if(a!=null&&(t.constants=a,s=s.concat(a),this.numConstants=a.length),s[0]instanceof Ba){let o=[e].concat(s),l=this.inputSpec.concat(i),u=this.inputSpec;this.inputSpec=l;let p=super.apply(o,t);return this.inputSpec=u,p}else return super.apply(e,t)}call(e,t){return P(()=>{let n=t==null?null:t.mask,a=t==null?null:t.training,r=t==null?null:t.initialState;e=Ne(e),r==null&&(this.stateful?r=this.states_:r=this.getInitialState(e));let s=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1;if(r.length!==s)throw new V(`RNN Layer has ${s} state(s) but was passed ${r.length} initial state(s).`);this.unroll&&console.warn("Ignoring unroll = true for RNN layer, due to imperative backend.");let i={training:a},o=n2((c,h)=>{let m=this.cell.call([c].concat(h),i);return[m[0],m.slice(1)]},e,r,this.goBackwards,n,null,this.unroll,this.returnSequences),l=o[0],u=o[1],p=o[2];this.stateful&&this.resetStates(p,a);let d=this.returnSequences?u:l;return this.returnState?[d].concat(p):d})}getInitialState(e){return P(()=>{let t=It(e.shape);return t=fe(t,[1,2]),t=Xc(t),Array.isArray(this.cell.stateSize)?this.cell.stateSize.map(n=>n>1?Gy(t,[1,n]):t):this.cell.stateSize>1?[Gy(t,[1,this.cell.stateSize])]:[t]})}get trainableWeights(){return this.trainable?this.cell.trainableWeights:[]}get nonTrainableWeights(){return this.trainable?this.cell.nonTrainableWeights:this.cell.weights}setFastWeightInitDuringBuild(e){super.setFastWeightInitDuringBuild(e),this.cell!=null&&this.cell.setFastWeightInitDuringBuild(e)}getConfig(){let e=super.getConfig(),t={returnSequences:this.returnSequences,returnState:this.returnState,goBackwards:this.goBackwards,stateful:this.stateful,unroll:this.unroll};this.numConstants!=null&&(t.numConstants=this.numConstants);let n=this.cell.getConfig();return this.getClassName()===mr.className&&(t.cell={className:this.cell.getClassName(),config:n}),Object.assign(Object.assign(Object.assign({},n),e),t)}static fromConfig(e,t,n={}){let a=t.cell,r=Ua(a,n);return new e(Object.assign(t,{cell:r}))}};mr.className="RNN";ne.registerClass(mr);var ad=class extends Ge{},Bf=class extends ad{constructor(e){super(e),this.DEFAULT_ACTIVATION="tanh",this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_RECURRENT_INITIALIZER="orthogonal",this.DEFAULT_BIAS_INITIALIZER="zeros",this.units=e.units,Qt(this.units,"units"),this.activation=ps(e.activation==null?this.DEFAULT_ACTIVATION:e.activation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=St(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=St(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=St(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelRegularizer=Tt(e.kernelRegularizer),this.recurrentRegularizer=Tt(e.recurrentRegularizer),this.biasRegularizer=Tt(e.biasRegularizer),this.kernelConstraint=Kt(e.kernelConstraint),this.recurrentConstraint=Kt(e.recurrentConstraint),this.biasConstraint=Kt(e.biasConstraint),this.dropout=Il([1,ls([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=Il([1,ls([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.dropoutFunc=e.dropoutFunc,this.stateSize=this.units,this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){e=tt(e),this.kernel=this.addWeight("kernel",[e[e.length-1],this.units],null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.recurrentKernel=this.addWeight("recurrent_kernel",[this.units,this.units],null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint),this.useBias?this.bias=this.addWeight("bias",[this.units],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint):this.bias=null,this.built=!0}call(e,t){return P(()=>{if(e=e,e.length!==2)throw new V(`SimpleRNNCell expects 2 input Tensors, got ${e.length}.`);let n=e[1];e=e[0];let a=t.training==null?!1:t.training;0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=cs({ones:()=>na(e),rate:this.dropout,training:a,dropoutFunc:this.dropoutFunc})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=cs({ones:()=>na(n),rate:this.recurrentDropout,training:a,dropoutFunc:this.dropoutFunc}));let r,s=this.dropoutMask,i=this.recurrentDropoutMask;s!=null?r=or(z(e,s),this.kernel.read()):r=or(e,this.kernel.read()),this.bias!=null&&(r=Xa(r,this.bias.read())),i!=null&&(n=z(n,i));let o=Y(r,or(n,this.recurrentKernel.read()));return this.activation!=null&&(o=this.activation.apply(o)),[o,o]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:us(this.activation),useBias:this.useBias,kernelInitializer:Ct(this.kernelInitializer),recurrentInitializer:Ct(this.recurrentInitializer),biasInitializer:Ct(this.biasInitializer),kernelRegularizer:pt(this.kernelRegularizer),recurrentRegularizer:pt(this.recurrentRegularizer),biasRegularizer:pt(this.biasRegularizer),activityRegularizer:pt(this.activityRegularizer),kernelConstraint:qt(this.kernelConstraint),recurrentConstraint:qt(this.recurrentConstraint),biasConstraint:qt(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout};return Object.assign(Object.assign({},e),t)}};Bf.className="SimpleRNNCell";ne.registerClass(Bf);var Lw=class extends mr{constructor(e){e.cell=new Bf(e),super(e)}call(e,t){return P(()=>{this.cell.dropoutMask!=null&&(_e(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(_e(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=t==null?null:t.mask,a=t==null?null:t.training,r=t==null?null:t.initialState;return super.call(e,{mask:n,training:a,initialState:r})})}static fromConfig(e,t){return new e(t)}};Lw.className="SimpleRNN";ne.registerClass(Lw);var Vf=class extends ad{constructor(e){if(super(e),this.DEFAULT_ACTIVATION="tanh",this.DEFAULT_RECURRENT_ACTIVATION="hardSigmoid",this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_RECURRENT_INITIALIZER="orthogonal",this.DEFAULT_BIAS_INITIALIZER="zeros",e.resetAfter)throw new V("GRUCell does not support reset_after parameter set to true.");this.units=e.units,Qt(this.units,"units"),this.activation=ps(e.activation===void 0?this.DEFAULT_ACTIVATION:e.activation),this.recurrentActivation=ps(e.recurrentActivation===void 0?this.DEFAULT_RECURRENT_ACTIVATION:e.recurrentActivation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=St(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=St(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=St(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelRegularizer=Tt(e.kernelRegularizer),this.recurrentRegularizer=Tt(e.recurrentRegularizer),this.biasRegularizer=Tt(e.biasRegularizer),this.kernelConstraint=Kt(e.kernelConstraint),this.recurrentConstraint=Kt(e.recurrentConstraint),this.biasConstraint=Kt(e.biasConstraint),this.dropout=Il([1,ls([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=Il([1,ls([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.dropoutFunc=e.dropoutFunc,this.implementation=e.implementation,this.stateSize=this.units,this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){e=tt(e);let t=e[e.length-1];this.kernel=this.addWeight("kernel",[t,this.units*3],null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.recurrentKernel=this.addWeight("recurrent_kernel",[this.units,this.units*3],null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint),this.useBias?this.bias=this.addWeight("bias",[this.units*3],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint):this.bias=null,this.built=!0}call(e,t){return P(()=>{if(e=e,e.length!==2)throw new V(`GRUCell expects 2 input Tensors (inputs, h, c), got ${e.length}.`);let n=t.training==null?!1:t.training,a=e[1];e=e[0],0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=cs({ones:()=>na(e),rate:this.dropout,training:n,count:3,dropoutFunc:this.dropoutFunc})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=cs({ones:()=>na(a),rate:this.recurrentDropout,training:n,count:3,dropoutFunc:this.dropoutFunc}));let r=this.dropoutMask,s=this.recurrentDropoutMask,i,o,l;0<this.dropout&&this.dropout<1&&(e=z(e,r[0]));let u=or(e,this.kernel.read());this.useBias&&(u=Xa(u,this.bias.read())),0<this.recurrentDropout&&this.recurrentDropout<1&&(a=z(a,s[0]));let p=this.recurrentKernel.read(),[d,c]=zn(p,[2*this.units,this.units],p.rank-1),h=or(a,d),[m,f,g]=zn(u,3,u.rank-1),[b,y]=zn(h,2,h.rank-1);i=this.recurrentActivation.apply(Y(m,b)),o=this.recurrentActivation.apply(Y(f,y));let x=or(z(o,a),c);l=this.activation.apply(Y(g,x));let w=Y(z(i,a),z(Y(1,vt(i)),l));return[w,w]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:us(this.activation),recurrentActivation:us(this.recurrentActivation),useBias:this.useBias,kernelInitializer:Ct(this.kernelInitializer),recurrentInitializer:Ct(this.recurrentInitializer),biasInitializer:Ct(this.biasInitializer),kernelRegularizer:pt(this.kernelRegularizer),recurrentRegularizer:pt(this.recurrentRegularizer),biasRegularizer:pt(this.biasRegularizer),activityRegularizer:pt(this.activityRegularizer),kernelConstraint:qt(this.kernelConstraint),recurrentConstraint:qt(this.recurrentConstraint),biasConstraint:qt(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation,resetAfter:!1};return Object.assign(Object.assign({},e),t)}};Vf.className="GRUCell";ne.registerClass(Vf);var zw=class extends mr{constructor(e){e.implementation===0&&console.warn("`implementation=0` has been deprecated, and now defaults to `implementation=1`. Please update your layer call."),e.cell=new Vf(e),super(e)}call(e,t){return P(()=>{this.cell.dropoutMask!=null&&(_e(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(_e(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=t==null?null:t.mask,a=t==null?null:t.training,r=t==null?null:t.initialState;return super.call(e,{mask:n,training:a,initialState:r})})}static fromConfig(e,t){return t.implmentation===0&&(t.implementation=1),new e(t)}};zw.className="GRU";ne.registerClass(zw);var rd=class extends ad{constructor(e){super(e),this.DEFAULT_ACTIVATION="tanh",this.DEFAULT_RECURRENT_ACTIVATION="hardSigmoid",this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_RECURRENT_INITIALIZER="orthogonal",this.DEFAULT_BIAS_INITIALIZER="zeros",this.units=e.units,Qt(this.units,"units"),this.activation=ps(e.activation===void 0?this.DEFAULT_ACTIVATION:e.activation),this.recurrentActivation=ps(e.recurrentActivation===void 0?this.DEFAULT_RECURRENT_ACTIVATION:e.recurrentActivation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=St(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=St(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=St(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.unitForgetBias=e.unitForgetBias,this.kernelRegularizer=Tt(e.kernelRegularizer),this.recurrentRegularizer=Tt(e.recurrentRegularizer),this.biasRegularizer=Tt(e.biasRegularizer),this.kernelConstraint=Kt(e.kernelConstraint),this.recurrentConstraint=Kt(e.recurrentConstraint),this.biasConstraint=Kt(e.biasConstraint),this.dropout=Il([1,ls([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=Il([1,ls([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.dropoutFunc=e.dropoutFunc,this.implementation=e.implementation,this.stateSize=[this.units,this.units],this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){var t;e=tt(e);let n=e[e.length-1];this.kernel=this.addWeight("kernel",[n,this.units*4],null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.recurrentKernel=this.addWeight("recurrent_kernel",[this.units,this.units*4],null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint);let a;if(this.useBias){if(this.unitForgetBias){let r=this.biasInitializer,s=this.units;a=new(t=class extends Ra{apply(i,o){let l=r.apply([s]),u=new Af().apply([s]),p=r.apply([s*2]);return Ak(Ak(l,u),p)}},t.className="CustomInit",t)}else a=this.biasInitializer;this.bias=this.addWeight("bias",[this.units*4],null,a,this.biasRegularizer,!0,this.biasConstraint)}else this.bias=null;this.built=!0}call(e,t){return P(()=>{let n=t.training==null?!1:t.training;if(e=e,e.length!==3)throw new V(`LSTMCell expects 3 input Tensors (inputs, h, c), got ${e.length}.`);let a=e[1],r=e[2];e=e[0],0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=cs({ones:()=>na(e),rate:this.dropout,training:n,count:4,dropoutFunc:this.dropoutFunc})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=cs({ones:()=>na(a),rate:this.recurrentDropout,training:n,count:4,dropoutFunc:this.dropoutFunc}));let s=this.dropoutMask,i=this.recurrentDropoutMask,o,l,u,p;0<this.dropout&&this.dropout<1&&(e=z(e,s[0]));let d=or(e,this.kernel.read());0<this.recurrentDropout&&this.recurrentDropout<1&&(a=z(a,i[0])),d=Y(d,or(a,this.recurrentKernel.read())),this.useBias&&(d=Xa(d,this.bias.read()));let[c,h,m,f]=zn(d,4,d.rank-1);o=this.recurrentActivation.apply(c),l=this.recurrentActivation.apply(h),u=Y(z(l,r),z(o,this.activation.apply(m))),p=this.recurrentActivation.apply(f);let g=z(p,this.activation.apply(u));return[g,g,u]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:us(this.activation),recurrentActivation:us(this.recurrentActivation),useBias:this.useBias,kernelInitializer:Ct(this.kernelInitializer),recurrentInitializer:Ct(this.recurrentInitializer),biasInitializer:Ct(this.biasInitializer),unitForgetBias:this.unitForgetBias,kernelRegularizer:pt(this.kernelRegularizer),recurrentRegularizer:pt(this.recurrentRegularizer),biasRegularizer:pt(this.biasRegularizer),activityRegularizer:pt(this.activityRegularizer),kernelConstraint:qt(this.kernelConstraint),recurrentConstraint:qt(this.recurrentConstraint),biasConstraint:qt(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation};return Object.assign(Object.assign({},e),t)}};rd.className="LSTMCell";ne.registerClass(rd);var Ww=class extends mr{constructor(e){e.implementation===0&&console.warn("`implementation=0` has been deprecated, and now defaults to `implementation=1`. Please update your layer call."),e.cell=new rd(e),super(e)}call(e,t){return P(()=>{this.cell.dropoutMask!=null&&(_e(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(_e(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=t==null?null:t.mask,a=t==null?null:t.training,r=t==null?null:t.initialState;return super.call(e,{mask:n,training:a,initialState:r})})}static fromConfig(e,t){return t.implmentation===0&&(t.implementation=1),new e(t)}};Ww.className="LSTM";ne.registerClass(Ww);var Uf=class extends ad{constructor(e){super(e),this.cells=e.cells}get stateSize(){let e=[];for(let t of this.cells.slice().reverse())Array.isArray(t.stateSize)?e.push(...t.stateSize):e.push(t.stateSize);return e}call(e,t){return P(()=>{e=e;let n=e.slice(1),a=[];for(let i of this.cells.slice().reverse())Array.isArray(i.stateSize)?a.push(n.splice(0,i.stateSize.length)):a.push(n.splice(0,1));a.reverse();let r=[],s;for(let i=0;i<this.cells.length;++i){let o=this.cells[i];n=a[i],i===0?s=[e[0]].concat(n):s=[s[0]].concat(n),s=o.call(s,t),r.push(s.slice(1))}n=[];for(let i of r.slice().reverse())n.push(...i);return[s[0]].concat(n)})}build(e){jy(e)&&(e=e[0]),e=e;let t;this.cells.forEach((n,a)=>{Ys(`RNNCell_${a}`,()=>{n.build(e),Array.isArray(n.stateSize)?t=n.stateSize[0]:t=n.stateSize,e=[e[0],t]})}),this.built=!0}getConfig(){let e=super.getConfig(),t=a=>({className:a.getClassName(),config:a.getConfig()}),n={cells:this.cells.map(t)};return Object.assign(Object.assign({},e),n)}static fromConfig(e,t,n={}){let a=[];for(let r of t.cells)a.push(Ua(r,n));return new e({cells:a})}get trainableWeights(){if(!this.trainable)return[];let e=[];for(let t of this.cells)e.push(...t.trainableWeights);return e}get nonTrainableWeights(){let e=[];for(let t of this.cells)e.push(...t.nonTrainableWeights);if(!this.trainable){let t=[];for(let n of this.cells)t.push(...n.trainableWeights);return t.concat(e)}return e}getWeights(){let e=[];for(let t of this.cells)e.push(...t.weights);return qy(e)}setWeights(e){let t=[];for(let n of this.cells){let a=n.weights.length,r=e.splice(a);for(let s=0;s<n.weights.length;++s)t.push([n.weights[s],r[s]])}pw(t)}};Uf.className="StackedRNNCells";ne.registerClass(Uf);function cs(e){let{ones:t,rate:n,training:a=!1,count:r=1,dropoutFunc:s}=e,i=()=>s!=null?s(t(),n):mN(t(),n),o=()=>Zc(i,t,a);return!r||r<=1?Jt(o().clone()):Array(r).fill(void 0).map(o).map(l=>Jt(l.clone()))}var WU=function(e,t){var n={};for(var a in e)Object.prototype.hasOwnProperty.call(e,a)&&t.indexOf(a)<0&&(n[a]=e[a]);if(e!=null&&typeof Object.getOwnPropertySymbols=="function")for(var r=0,a=Object.getOwnPropertySymbols(e);r<a.length;r++)t.indexOf(a[r])<0&&Object.prototype.propertyIsEnumerable.call(e,a[r])&&(n[a[r]]=e[a[r]]);return n},a2=class extends mr{constructor(e){if(e.unroll)throw new Me("Unrolling is not possible with convolutional RNNs.");if(Array.isArray(e.cell))throw new Me("It is not possible at the moment to stack convolutional cells.");super(e),this.inputSpec=[new zt({ndim:5})]}call(e,t){return P(()=>{if(this.cell.dropoutMask!=null&&(_e(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(_e(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null),t&&t.constants)throw new V("ConvRNN2D cell does not support constants");let n=t==null?null:t.mask,a=t==null?null:t.training,r=t==null?null:t.initialState;return super.call(e,{mask:n,training:a,initialState:r})})}computeOutputShape(e){let t=this.computeSingleOutputShape(e);return this.returnSequences||(t=[t[0],...t.slice(2)]),this.returnState&&(t=[t,...Array(2).fill([e[0],...t.slice(-3)])]),t}getInitialState(e){return P(()=>{let{stateSize:t}=this.cell,n=e.shape,a=this.computeSingleOutputShape(n),r=[a[0],...a.slice(2)],s=It(r);return Array.isArray(t)?Array(t.length).fill(s):[s]})}resetStates(e,t=!1){P(()=>{if(!this.stateful)throw new Ir("Cannot call resetStates() on an RNN Layer that is not stateful.");let n=this.inputSpec[0].shape,a=this.computeSingleOutputShape(n),r=[a[0],...a.slice(2)];if(n[0]==null)throw new V("If an RNN is stateful, it needs to know its batch size. Specify the batch size of your input tensors: \n- If using a Sequential model, specify the batch size by passing a `batchInputShape` option to your first layer.\n- If using the functional API, specify the batch size by passing a `batchShape` option to your Input layer.");if(this.getStates()==null)Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(()=>It(r)):this.states_=[It(r)];else if(e==null)_e(this.states_),this.keptStates!=null&&(_e(this.keptStates),this.keptStates=[]),Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(()=>It(r)):this.states_[0]=It(r);else{if(Array.isArray(e)||(e=[e]),e.length!==this.states_.length)throw new V(`Layer ${this.name} expects ${this.states_.length} state(s), but it received ${e.length} state value(s). Input received: ${e}`);t?this.keptStates.push(this.states_.slice()):_e(this.states_);for(let s=0;s<this.states_.length;++s){let i=e[s],o=r;if(!v.arraysEqual(i.shape,o))throw new V(`State ${s} is incompatible with layer ${this.name}: expected shape=${o}, received shape=${i.shape}`);this.states_[s]=i}}this.states_=this.states_.map(s=>Jt(s.clone()))})}computeSingleOutputShape(e){let{dataFormat:t,filters:n,kernelSize:a,padding:r,strides:s,dilationRate:i}=this.cell,o=t==="channelsFirst",l=e[o?3:2],u=e[o?4:3],p=Ga(l,a[0],r,s[0],i[0]),d=Ga(u,a[1],r,s[1],i[1]);return[...e.slice(0,2),...o?[n,p,d]:[p,d,n]]}};a2.className="ConvRNN2D";var Gf=class extends rd{constructor(e){let{filters:t,kernelSize:n,strides:a,padding:r,dataFormat:s,dilationRate:i}=e;super(Object.assign(Object.assign({},e),{units:t})),this.filters=t,Qt(this.filters,"filters"),this.kernelSize=dl(n,2,"kernelSize"),this.kernelSize.forEach(o=>Qt(o,"kernelSize")),this.strides=dl(a||1,2,"strides"),this.strides.forEach(o=>Qt(o,"strides")),this.padding=r||"valid",xa(this.padding),this.dataFormat=s||"channelsLast",Rt(this.dataFormat),this.dilationRate=dl(i||1,2,"dilationRate"),this.dilationRate.forEach(o=>Qt(o,"dilationRate"))}build(e){var t;e=tt(e);let n=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[n]==null)throw new V(`The channel dimension of the input should be defined. Found ${e[n]}`);let a=e[n],r=4,s=this.kernelSize.concat([a,this.filters*r]);this.kernel=this.addWeight("kernel",s,null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint);let i=this.kernelSize.concat([this.filters,this.filters*r]);if(this.recurrentKernel=this.addWeight("recurrent_kernel",i,null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint),this.useBias){let o;if(this.unitForgetBias){let l=this.biasInitializer,u=this.filters;o=new(t=class extends Ra{apply(p,d){let c=l.apply([u]),h=Jn([u]),m=l.apply([u*2]);return nw([c,h,m])}},t.className="CustomInit",t)}else o=this.biasInitializer;this.bias=this.addWeight("bias",[this.filters*r],null,o,this.biasRegularizer,!0,this.biasConstraint)}this.built=!0}call(e,t){return P(()=>{if(e.length!==3)throw new V(`ConvLSTM2DCell expects 3 input Tensors (inputs, h, c), got ${e.length}.`);let n=t.training||!1,a=e[0],r=e[1],s=e[2],i=4;0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=cs({ones:()=>na(a),rate:this.dropout,training:n,count:i,dropoutFunc:this.dropoutFunc}));let o=this.dropoutMask,l=(Z,Q,ee)=>!Q||!Q[ee]?Z:z(Q[ee],Z),u=l(a,o,0),p=l(a,o,1),d=l(a,o,2),c=l(a,o,3);0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=cs({ones:()=>na(r),rate:this.recurrentDropout,training:n,count:i,dropoutFunc:this.dropoutFunc}));let h=this.recurrentDropoutMask,m=l(r,h,0),f=l(r,h,1),g=l(r,h,2),b=l(r,h,3),y=3,[x,w,I,T]=zn(this.kernel.read(),i,y),[C,E,A,R]=this.useBias?zn(this.bias.read(),i):[null,null,null,null];u=this.inputConv(u,x,C,this.padding),p=this.inputConv(p,w,E,this.padding),d=this.inputConv(d,I,A,this.padding),c=this.inputConv(c,T,R,this.padding);let[F,S,M,B]=zn(this.recurrentKernel.read(),i,y);m=this.recurrentConv(m,F),f=this.recurrentConv(f,S),g=this.recurrentConv(g,M),b=this.recurrentConv(b,B);let U=this.recurrentActivation.apply(Y(u,m)),G=this.recurrentActivation.apply(Y(p,f)),q=Y(z(G,s),z(U,this.activation.apply(Y(d,g)))),K=z(this.recurrentActivation.apply(Y(c,b)),this.activation.apply(q));return[K,K,q]})}getConfig(){let e=super.getConfig(),{units:t}=e,n=WU(e,["units"]),a={filters:this.filters,kernelSize:this.kernelSize,padding:this.padding,dataFormat:this.dataFormat,dilationRate:this.dilationRate,strides:this.strides};return Object.assign(Object.assign({},n),a)}inputConv(e,t,n,a){let r=$t(e,t,this.strides,a||"valid",this.dataFormat==="channelsFirst"?"NCHW":"NHWC",this.dilationRate);return n?Xa(r,n,this.dataFormat):r}recurrentConv(e,t){return $t(e,t,1,"same",this.dataFormat==="channelsFirst"?"NCHW":"NHWC")}};Gf.className="ConvLSTM2DCell";ne.registerClass(Gf);var Bw=class extends a2{constructor(e){let t=new Gf(e);super(Object.assign(Object.assign({},e),{cell:t}))}static fromConfig(e,t){return new e(t)}};Bw.className="ConvLSTM2D";ne.registerClass(Bw);var Hf=class extends Ge{constructor(e){super(e),this.rate=Math.max(Math.min(e.rate,1),0),this.noiseShape=e.noiseShape,this.seed=e.seed,this.supportsMasking=!0}getNoiseShape(e){if(this.noiseShape==null)return this.noiseShape;let t=e.shape,n=[];for(let a=0;a<this.noiseShape.length;++a)n.push(this.noiseShape[a]==null?t[a]:this.noiseShape[a]);return n}call(e,t){return P(()=>{this.invokeCallHook(e,t);let n=Ne(e);if(0<this.rate&&this.rate<1){let a=t.training==null?!1:t.training,r=this.getNoiseShape(n);return Zc(()=>mN(n,this.rate,r,this.seed),()=>n,a)}return e})}getConfig(){let e={rate:this.rate,noiseShape:this.noiseShape,seed:this.seed},t=super.getConfig();return Object.assign(e,t),e}dispose(){return super.dispose()}};Hf.className="Dropout";ne.registerClass(Hf);var Vw=class extends Hf{constructor(e){super(e),this.inputSpec=[{ndim:3}]}getNoiseShape(e){let t=e.shape;return[t[0],1,t[2]]}};Vw.className="SpatialDropout1D";ne.registerClass(Vw);var Uw=class extends Ge{constructor(e){if(super(e),this.activation=null,this.useBias=!0,this.kernel=null,this.bias=null,this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_BIAS_INITIALIZER="zeros",e.batchInputShape==null&&e.inputShape==null&&e.inputDim!=null){let t=null;e.batchSize!=null&&(t=e.batchSize),this.batchInputShape=[t,e.inputDim]}this.units=e.units,Qt(this.units,"units"),this.activation=ps(e.activation),e.useBias!=null&&(this.useBias=e.useBias),this.kernelInitializer=St(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.biasInitializer=St(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelConstraint=Kt(e.kernelConstraint),this.biasConstraint=Kt(e.biasConstraint),this.kernelRegularizer=Tt(e.kernelRegularizer),this.biasRegularizer=Tt(e.biasRegularizer),this.activityRegularizer=Tt(e.activityRegularizer),this.supportsMasking=!0,this.inputSpec=[{minNDim:2}]}build(e){e=tt(e);let t=e[e.length-1];this.kernel==null&&(this.kernel=this.addWeight("kernel",[t,this.units],null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.units],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint))),this.inputSpec=[{minNDim:2,axes:{[-1]:t}}],this.built=!0}computeOutputShape(e){e=tt(e);let t=e.slice();return t[t.length-1]=this.units,t}call(e,t){return P(()=>{this.invokeCallHook(e,t);let n=Ne(e),a=oN(this.activation.getClassName()),r;return a!=null?r=or(n,this.kernel.read(),a,this.bias?this.bias.read():null):(r=or(n,this.kernel.read()),this.bias!=null&&(r=Xa(r,this.bias.read())),this.activation!=null&&(r=this.activation.apply(r))),r})}getConfig(){let e={units:this.units,activation:us(this.activation),useBias:this.useBias,kernelInitializer:Ct(this.kernelInitializer),biasInitializer:Ct(this.biasInitializer),kernelRegularizer:pt(this.kernelRegularizer),biasRegularizer:pt(this.biasRegularizer),activityRegularizer:pt(this.activityRegularizer),kernelConstraint:qt(this.kernelConstraint),biasConstraint:qt(this.biasConstraint)},t=super.getConfig();return Object.assign(e,t),e}};Uw.className="Dense";ne.registerClass(Uw);var Gw=class extends Ge{constructor(e){e=e||{},super(e),this.inputSpec=[{minNDim:3}],this.dataFormat=e.dataFormat}computeOutputShape(e){e=tt(e);for(let t of e.slice(1))if(t==null)throw new V(`The shape of the input to "Flatten" is not fully defined (got ${e.slice(1)}). Make sure to pass a complete "input_shape" or "batch_input_shape" argument to the first layer in your model.`);return[e[0],rs(e,1)]}call(e,t){return P(()=>{this.invokeCallHook(e,t);let n=Ne(e);if(this.dataFormat==="channelsFirst"&&n.rank>1){let a=[0];for(let r=2;r<n.rank;++r)a.push(r);a.push(1),n=Ee(n,a)}return tV(n)})}getConfig(){let e={};this.dataFormat!=null&&(e.dataFormat=this.dataFormat);let t=super.getConfig();return Object.assign(e,t),e}};Gw.className="Flatten";ne.registerClass(Gw);var Hw=class extends Ge{constructor(e){super(e),this.supportsMasking=!0,this.activation=ps(e.activation)}call(e,t){return P(()=>{this.invokeCallHook(e,t);let n=Ne(e);return this.activation.apply(n)})}getConfig(){let e={activation:us(this.activation)},t=super.getConfig();return Object.assign(e,t),e}};Hw.className="Activation";ne.registerClass(Hw);var jw=class extends Ge{constructor(e){super(e),this.n=e.n,this.inputSpec=[{ndim:2}]}computeOutputShape(e){return[e[0],this.n,e[1]]}call(e,t){return P(()=>(e=Ne(e),Q4(e,this.n)))}getConfig(){let e={n:this.n},t=super.getConfig();return Object.assign(e,t),e}};jw.className="RepeatVector";ne.registerClass(jw);var qw=class extends Ge{constructor(e){super(e),this.targetShape=e.targetShape;for(let t=0;t<this.targetShape.length;++t)this.isUnknown(this.targetShape[t])&&(this.targetShape[t]=null)}isUnknown(e){return e<0||e==null}fixUnknownDimension(e,t){let n="Total size of new array must be unchanged.",a=t.slice(),r=1,s=null;for(let o=0;o<a.length;++o){let l=a[o];if(this.isUnknown(l))if(s===null)s=o;else throw new V("Can only specifiy one unknown dimension.");else r*=l}let i=rs(e);if(s!==null){if(r===0||i%r!==0)throw new V(n);a[s]=i/r}else if(i!==r)throw new V(n);return a}computeOutputShape(e){let t=!1;for(let n=0;n<e.length;++n)if(this.isUnknown(e[n])){t=!0;break}return t?e.slice(0,1).concat(this.targetShape):e.slice(0,1).concat(this.fixUnknownDimension(e.slice(1),this.targetShape))}call(e,t){return P(()=>{this.invokeCallHook(e,t);let n=Ne(e),a=n.shape,r=a.slice(0,1).concat(this.fixUnknownDimension(a.slice(1),this.targetShape));return W(n,r)})}getConfig(){let e={targetShape:this.targetShape},t=super.getConfig();return Object.assign(e,t),e}};qw.className="Reshape";ne.registerClass(qw);var Kw=class extends Ge{constructor(e){if(super(e),e.dims==null)throw new Error("Required configuration field `dims` is missing during Permute constructor call.");if(!Array.isArray(e.dims))throw new Error(`Permute constructor requires \`dims\` to be an Array, but received ${e.dims} instead.`);let t=Ha(1,e.dims.length+1);if(!v.arraysEqual(e.dims.slice().sort(),t))throw new Error("Invalid permutation `dims`: "+JSON.stringify(e.dims)+" `dims` must contain consecutive integers starting from 1.");this.dims=e.dims,this.dimsIncludingBatch=[0].concat(this.dims),this.inputSpec=[new zt({ndim:this.dims.length+1})]}computeOutputShape(e){e=tt(e);let t=e.slice();return this.dims.forEach((n,a)=>{t[a+1]=e[n]}),t}call(e,t){return Ee(Ne(e),this.dimsIncludingBatch)}getConfig(){let e={dims:this.dims},t=super.getConfig();return Object.assign(e,t),e}};Kw.className="Permute";ne.registerClass(Kw);var Xw=class extends Ge{constructor(e){super(e==null?{}:e),this.supportsMasking=!0,e!=null?this.maskValue=e.maskValue==null?0:e.maskValue:this.maskValue=0}computeOutputShape(e){return e}getConfig(){let e=super.getConfig(),t={maskValue:this.maskValue};return Object.assign(t,e),t}computeMask(e,t){let n=Ne(e),a=-1;return Qp(oi(n,this.maskValue),a)}call(e,t){return P(()=>{this.invokeCallHook(e,t);let n=Ne(e),a=-1,r=!0,s=Qp(oi(n,this.maskValue),a,r);return z(n,oe(s,n.dtype))})}};Xw.className="Masking";ne.registerClass(Xw);var Yw=class extends Ge{constructor(e){if(super(e),this.embeddings=null,this.DEFAULT_EMBEDDINGS_INITIALIZER="randomUniform",e.batchInputShape==null&&e.inputShape==null){let t=null;e.batchSize!=null&&(t=e.batchSize),e.inputLength==null?this.batchInputShape=[t,null]:this.batchInputShape=[t].concat(xt(e.inputLength))}this.inputDim=e.inputDim,Qt(this.inputDim,"inputDim"),this.outputDim=e.outputDim,Qt(this.outputDim,"outputDim"),this.embeddingsInitializer=St(e.embeddingsInitializer||this.DEFAULT_EMBEDDINGS_INITIALIZER),this.embeddingsRegularizer=Tt(e.embeddingsRegularizer),this.activityRegularizer=Tt(e.activityRegularizer),this.embeddingsConstraint=Kt(e.embeddingsConstraint),this.maskZero=e.maskZero,this.supportsMasking=e.maskZero,this.inputLength=e.inputLength}build(e){this.embeddings=this.addWeight("embeddings",[this.inputDim,this.outputDim],this.dtype,this.embeddingsInitializer,this.embeddingsRegularizer,!0,this.embeddingsConstraint),this.built=!0}warnOnIncompatibleInputShape(e){}computeMask(e,t){return P(()=>this.maskZero?(e=Ne(e),oi(e,qe(e))):null)}computeOutputShape(e){if(e=tt(e),this.inputLength==null)return[...e,this.outputDim];let t=xt(this.inputLength);if(t.length!==e.length-1)throw new V(`"inputLength" is ${this.inputLength}, but received input shape has shape ${e}`);{let n=0;for(let a=0;a<t.length;++a){let r=t[a],s=e[a+1];if(r!=null&&s!=null&&r!==s)throw new V(`"inputLength" is ${this.inputLength}, but received input shape has shape ${e}`);r==null&&(t[n]=s),n++}}return[e[0],...t,this.outputDim]}call(e,t){return P(()=>{this.invokeCallHook(e,t);let n=Ne(e);n.dtype!=="int32"&&(n=yo(n,"int32"));let a=hN(this.embeddings.read(),W(n,[n.size]));return W(a,tt(this.computeOutputShape(n.shape)))})}getConfig(){let e={inputDim:this.inputDim,outputDim:this.outputDim,embeddingsInitializer:Ct(this.embeddingsInitializer),embeddingsRegularizer:pt(this.embeddingsRegularizer),activityRegularizer:pt(this.activityRegularizer),embeddingsConstraint:qt(this.embeddingsConstraint),maskZero:this.maskZero,inputLength:this.inputLength},t=super.getConfig();return Object.assign(e,t),e}};Yw.className="Embedding";ne.registerClass(Yw);var vo=class extends Ge{constructor(e){super(e||{}),this.supportsMasking=!0}mergeFunction(e){throw new Me}computeElementwiseOpOutputShape(e,t){if(e==null||t==null)return null;if(e.length<t.length)return this.computeElementwiseOpOutputShape(t,e);if(t.length===0)return e;let n=e.slice(0,e.length-t.length);for(let a=0;a<t.length;++a){let r=e[e.length-t.length+a],s=t[a];if(r==null||s==null||r<0||s<0)n.push(null);else if(r===1)n.push(s);else if(s===1)n.push(r);else{if(r!==s)throw new V("Operands could not be broadcast together with shapes "+JSON.stringify(e)+" "+JSON.stringify(t));n.push(r)}}return n}build(e){if(Array.isArray(e)&&!Array.isArray(e[0])&&(e=[tt(e)]),e=e,e.length<2)throw new V(`A merge layer should be called on an Array of at least 2 inputs. 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e={axis:this.axis},t=super.getConfig();return Object.assign(e,t),e}};n0.className="Concatenate";ne.registerClass(n0);function Ap(e,t){for(;e<0;)e+=t;return e}function BU(e,t,n){if(e.shape.length>3||t.shape.length>3)throw new Me("batchDot is not implemented for tensors of 4D or higher rank yet");if(v.assert(e.shape.length>=2,()=>`batchDot requires the rank of x to be >= 2, but got ${e.shape.length}`),v.assert(e.shape.length>=2,()=>`batchDot requires the rank of y to be >= 2, but got ${t.shape.length}`),typeof n=="number"&&(n=[n,n]),e.dtype==="complex64"||t.dtype==="complex64")throw new Me("batchDot is not implemented for complex64-type Tensors yet.");let a=e.shape.length,r=t.shape.length;n==null&&(n=[a-1,r-2]);let s=n;return P(()=>{let i;if(a>r){i=a-r;let l=[];for(let u=0;u<i;++u)l.push(1);t=W(t,t.shape.concat(l))}else if(r>a){i=r-a;let l=[];for(let u=0;u<i;++u)l.push(1);e=W(e,e.shape.concat(l))}else i=0;let o;if(e.shape.length===2&&t.shape.length===2)s[0]===s[1]?o=fe(z(e,t),s[0]):o=fe(z(Ee(e,[1,0]),t),s[1]);else{let l=s[0]!==e.shape.length-1,u=s[1]===t.shape.length-1;o=Fe(e,t,l,u)}if(i>0){let l;a>r?l=a+r-3:l=a-1;let u=[];for(let p=l;p<l+i;++p)u.push(p);o=Ns(o,u)}return o.shape.length===1&&(o=Zt(o,1)),o})}var a0=class extends vo{constructor(e){super(e),this.axes=e.axes,this.normalize=e.normalize==null?!1:e.normalize,this.supportsMasking=!0,this.reshapeRequired=!1}build(e){v.assert(Array.isArray(e)&&e.length===2&&Array.isArray(e[0])&&Array.isArray(e[1]),()=>"A `Dot` layer should be called on a list of exactly 2 inputs.");let t=e[0],n=e[1];if(t.length>3||n.length>3)throw new Me("Dot layer does not support tensors of 4D or higher rank yet.");let a=this.interpretAxes(t,n);if(t[a[0]]!==n[a[1]])throw new V(`Dimension incompatibility: ${t[a[0]]} !== ${n[a[1]]}`)}mergeFunction(e){if(e.length!==2)throw new V(`A \`Dot\` layer must be called on exactly 2 inputs, but received ${e.length} 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Ge{constructor(e){super(e),this.supportsMasking=!0,this.stddev=e.stddev}computeOutputShape(e){return e}getConfig(){let e=super.getConfig(),t={stddev:this.stddev};return Object.assign(t,e),t}call(e,t){return P(()=>{this.invokeCallHook(e,t);let n=Ne(e);return Zc(()=>Y(Ef(n.shape,0,this.stddev),n),()=>n,t.training||!1)})}};r0.className="GaussianNoise";ne.registerClass(r0);var s0=class extends Ge{constructor(e){super(e),this.supportsMasking=!0,this.rate=e.rate}computeOutputShape(e){return e}getConfig(){let e=super.getConfig(),t={rate:this.rate};return Object.assign(t,e),t}call(e,t){return P(()=>{this.invokeCallHook(e,t);let n=Ne(e);return this.rate>0&&this.rate<1?Zc(()=>{let a=Math.sqrt(this.rate/(1-this.rate));return z(n,Ef(n.shape,1,a))},()=>n,t.training||!1):n})}};s0.className="GaussianDropout";ne.registerClass(s0);var i0=class extends Ge{constructor(e){super(e),this.supportsMasking=!0,this.rate=e.rate,this.noiseShape=e.noiseShape}_getNoiseShape(e){return this.noiseShape||Ne(e).shape}computeOutputShape(e){return e}getConfig(){let e=super.getConfig(),t={rate:this.rate};return Object.assign(t,e),t}call(e,t){return P(()=>{if(this.rate<1&&this.rate>0){let n=this._getNoiseShape(e);return Zc(()=>{let a=Ne(e),r=1.6732632423543772,s=1.0507009873554805,i=-r*s,o=Fr(Uu(n),this.rate);o=yo(o,"float32");let l=((1-this.rate)*(1+this.rate*i**2))**-.5,u=-l*i*this.rate,p=Y(z(a,o),z(Y(o,-1),i));return Y(z(p,l),u)},()=>Ne(e),t.training||!1)}return e})}};i0.className="AlphaDropout";ne.registerClass(i0);function ac(e,t,n,a,r,s=.001){let i;if(e.rank===2)i=sv(e,t,n,a,r,s);else if(e.rank===3)i=iv(e,t,n,a,r,s);else if(e.rank===4)i=ov(e,t,n,a,r,s);else throw new Me(`batchNormalization is not implemented for array of rank ${e.rank} yet`);return i}function VU(e,t,n,a,r=.001){return P(()=>{let s=Bc(e,a),i=s.mean,o=s.variance;return[ac(e,i,o,n,t,r),i,o]})}function UU(e,t,n,a,r=.001){return P(()=>{let s=Bc(e,a),i=s.mean,o=s.variance,l=[];for(let h of 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t=this.axis>=0?this.axis:this.axis+e.length,n=e[t];if(n==null)throw new V(`Axis ${t} of input tensor should have a defined dimension but the layer received an input with shape ${JSON.stringify(e)}.`);this.inputSpec=[new zt({ndim:e.length,axes:{[t]:n}})];let a=[n];this.scale&&(this.gamma=this.addWeight("gamma",a,null,this.gammaInitializer,this.gammaRegularizer,!0,this.gammaConstraint)),this.center&&(this.beta=this.addWeight("beta",a,null,this.betaInitializer,this.betaRegularizer,!0,this.betaConstraint)),this.movingMean=this.addWeight("moving_mean",a,null,this.movingMeanInitializer,null,!1),this.movingVariance=this.addWeight("moving_variance",a,null,this.movingVarianceInitializer,null,!1),this.built=!0}call(e,t){return P(()=>{let n=t.training==null?!1:t.training,a=Ne(e),r=a.shape,s=r.length,i=Ha(0,s),o=this.axis>=0?this.axis:this.axis+s;i.splice(o,1);let l=li(1,s);l[o]=r[o];let u=i.slice();u.sort();let p=!v.arraysEqual(u,Ha(0,s).slice(0,s-1)),d=()=>{if(p){let g=W(this.movingMean.read(),l),b=W(this.movingVariance.read(),l),y=this.center?W(this.beta.read(),l):null,x=this.scale?W(this.gamma.read(),l):null;return ac(a,g,b,y,x,this.epsilon)}else return ac(a,this.movingMean.read(),this.movingVariance.read(),this.beta==null?null:this.beta.read(),this.gamma==null?null:this.gamma.read(),this.epsilon)};if(!n)return d();let[c,h,m]=GU(a,this.gamma.read(),this.beta.read(),i,this.epsilon),f=(g,b,y)=>{P(()=>{let x=1-y,w=g.read(),I=z(pe(w,b),x);g.write(pe(w,I))})};return f(this.movingMean,h,this.momentum),f(this.movingVariance,m,this.momentum),c})}getConfig(){let e={axis:this.axis,momentum:this.momentum,epsilon:this.epsilon,center:this.center,scale:this.scale,betaInitializer:Ct(this.betaInitializer),gammaInitializer:Ct(this.gammaInitializer),movingMeanInitializer:Ct(this.movingMeanInitializer),movingVarianceInitializer:Ct(this.movingVarianceInitializer),betaRegularizer:pt(this.betaRegularizer),gammaRegularizer:pt(this.gammaRegularizer),betaConstraint:qt(this.betaConstraint),gammaConstraint:qt(this.gammaConstraint)},t=super.getConfig();return Object.assign(e,t),e}};o0.className="BatchNormalization";ne.registerClass(o0);var l0=class extends Ge{constructor(e){if(e==null&&(e={}),super(e),this.axis=e.axis==null?-1:e.axis,typeof this.axis=="number"){if(!Number.isInteger(this.axis))throw new Error(`Expected axis to be an integer, but received ${this.axis}`)}else if(Array.isArray(this.axis)){for(let t of this.axis)if(!Number.isInteger(t))throw new Error(`Expected axis to be an array of integers, but received ${JSON.stringify(this.axis)}`)}else throw new Error(`Expected axis to be an integer or an array of integers, but received ${JSON.stringify(this.axis)}`);this.epsilon=e.epsilon==null?.001:e.epsilon,this.center=e.center==null?!0:e.center,this.scale=e.scale==null?!0:e.scale,this.betaInitializer=St(e.betaInitializer||"zeros"),this.gammaInitializer=St(e.gammaInitializer||"ones"),this.betaRegularizer=Tt(e.betaRegularizer),this.gammaRegularizer=Tt(e.gammaRegularizer),this.supportsMasking=!0}build(e){e=tt(e);let t=e.length;typeof this.axis=="number"&&(this.axis=[this.axis]);for(let r=0;r<this.axis.length;++r)this.axis[r]<0&&(this.axis[r]+=t);for(let r of this.axis)if(r<0||r>=t)throw new Error(`Invalid axis: ${r}`);if(this.axis.length!==as(this.axis).length)throw new Error(`Found duplicate axes in: ${this.axis}`);let n=this.axis.map(r=>e[r]),a=!0;this.scale?this.gamma=this.addWeight("gamma",n,"float32",this.gammaInitializer,this.gammaRegularizer,a):this.gamma=null,this.center?this.beta=this.addWeight("beta",n,"float32",this.betaInitializer,this.betaRegularizer,a):this.beta=null,this.built=!0}call(e,t){let n=Ne(e),a=n.shape,r=a.length;return P(()=>{let{mean:s,variance:i}=Bc(n,this.axis,!0),o=li(1,r);for(let h of this.axis)o[h]=a[h];let l=h=>h!=null&&h.shape.length!==r?W(h,o):h,u=this.scale?l(this.gamma.read()):null,p=this.center?l(this.beta.read()):null,d=[],c=[];for(let h=0;h<r;++h)this.axis.indexOf(h)!==-1?(d.push(a[h]),c.push(1)):(d.push(1),c.push(a[h]));return s=Ln(s,d),i=Ln(i,d),u!=null&&(u=Ln(u,c)),p!=null&&(p=Ln(p,c)),ac(n,s,i,p,u,this.epsilon)})}getConfig(){let e={axis:this.axis,epsilon:this.epsilon,center:this.center,scale:this.scale,betaInitializer:Ct(this.betaInitializer),gammaInitializer:Ct(this.gammaInitializer),betaRegularizer:pt(this.betaRegularizer),gammaRegularizer:pt(this.gammaRegularizer)},t=super.getConfig();return Object.assign(e,t),e}};l0.className="LayerNormalization";ne.registerClass(l0);function HU(e,t,n){return P(()=>{if(e.rank!==4)throw new V(`temporalPadding expects input tensor to be 4-D, but received a ${e.rank}-D tensor.`);if(t==null&&(t=[[1,1],[1,1]]),t.length!==2||t[0].length!==2||t[1].length!==2)throw new V("spatial2dPadding expects `padding` to be an Array of two Arrays, each of which is an Array of two integers.");if(n==null&&(n=ja()),n!=="channelsLast"&&n!=="channelsFirst")throw new V(`Unknown data format: ${n}. Supported data formats are 'channelsLast' and 'channelsFirst.`);let a;return n==="channelsFirst"?a=[[0,0],[0,0],t[0],t[1]]:a=[[0,0],t[0],t[1],[0,0]],ya(e,a)})}var u0=class extends Ge{constructor(e){if(e==null&&(e={}),super(e),this.dataFormat=e.dataFormat==null?ja():e.dataFormat,e.padding==null)this.padding=[[1,1],[1,1]];else if(typeof e.padding=="number")this.padding=[[e.padding,e.padding],[e.padding,e.padding]];else{if(e.padding=e.padding,e.padding.length!==2)throw new V(`ZeroPadding2D expects padding to be a length-2 array, but received a length-${e.padding.length} array.`);let t,n;if(typeof e.padding[0]=="number")t=[e.padding[0],e.padding[0]],n=[e.padding[1],e.padding[1]];else{if(e.padding=e.padding,e.padding[0].length!==2)throw new V(`ZeroPadding2D expects height padding to be a length-2 array, but received a length-${e.padding[0].length} array.`);if(t=e.padding[0],e.padding[1].length!==2)throw new V(`ZeroPadding2D expects width padding to be a length-2 array, but received a length-${e.padding[1].length} array.`);n=e.padding[1]}this.padding=[t,n]}this.inputSpec=[new zt({ndim:4})]}computeOutputShape(e){e=tt(e);let t,n;return this.dataFormat==="channelsFirst"?(e[2]!=null&&e[2]>=0?t=e[2]+this.padding[0][0]+this.padding[0][1]:t=null,e[3]!=null&&e[3]>=0?n=e[3]+this.padding[1][0]+this.padding[1][1]:n=null,[e[0],e[1],t,n]):(e[1]!=null&&e[1]>=0?t=e[1]+this.padding[0][0]+this.padding[0][1]:t=null,e[2]!=null&&e[2]>=0?n=e[2]+this.padding[1][0]+this.padding[1][1]:n=null,[e[0],t,n,e[3]])}call(e,t){return P(()=>HU(Ne(e),this.padding,this.dataFormat))}getConfig(){let e={padding:this.padding,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}};u0.className="ZeroPadding2D";ne.registerClass(u0);function jf(e,t,n,a,r,s){return P(()=>{Rt(r),uN(s),xa(a),n==null&&(n=[1,1]),a==null&&(a="valid"),r==null&&(r=ja()),s==null&&(s="max"),e=Aw(e,r);let i,o=a==="same"?"same":"valid";return s==="max"?i=Dt(e,t,n,o):i=ba(e,t,n,o),r==="channelsFirst"&&(i=Ee(i,[0,3,1,2])),i})}function r2(e,t,n,a,r,s){return P(()=>{Rt(r),uN(s),xa(a),n==null&&(n=[1,1,1]),a==null&&(a="valid"),r==null&&(r=ja()),s==null&&(s="max"),e=QN(e,r);let i,o=a==="same"?"same":"valid";return s==="max"?i=Fv(e,t,n,o):i=rv(e,t,n,o),r==="channelsFirst"&&(i=Ee(i,[0,4,1,2,3])),i})}var s2=class extends Ge{constructor(e){if(e.poolSize==null&&(e.poolSize=2),super(e),typeof e.poolSize=="number")this.poolSize=[e.poolSize];else if(Array.isArray(e.poolSize)&&e.poolSize.length===1&&typeof e.poolSize[0]=="number")this.poolSize=e.poolSize;else throw new V(`poolSize for 1D convolutional layer must be a number or an Array of a single number, but received ${JSON.stringify(e.poolSize)}`);if(Qt(this.poolSize,"poolSize"),e.strides==null)this.strides=this.poolSize;else if(typeof e.strides=="number")this.strides=[e.strides];else if(Array.isArray(e.strides)&&e.strides.length===1&&typeof e.strides[0]=="number")this.strides=e.strides;else throw new V(`strides for 1D convolutional layer must be a number or an Array of a single number, but received ${JSON.stringify(e.strides)}`);Qt(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,xa(this.padding),this.inputSpec=[new zt({ndim:3})]}computeOutputShape(e){e=tt(e);let t=Ga(e[1],this.poolSize[0],this.padding,this.strides[0]);return[e[0],t,e[2]]}call(e,t){return P(()=>{this.invokeCallHook(e,t),e=Xc(Ne(e),2);let n=this.poolingFunction(Ne(e),[this.poolSize[0],1],[this.strides[0],1],this.padding,"channelsLast");return Ns(n,[2])})}getConfig(){let e={poolSize:this.poolSize,padding:this.padding,strides:this.strides},t=super.getConfig();return Object.assign(e,t),e}},p0=class extends s2{constructor(e){super(e)}poolingFunction(e,t,n,a,r){return Rt(r),xa(a),jf(e,t,n,a,r,"max")}};p0.className="MaxPooling1D";ne.registerClass(p0);var c0=class extends s2{constructor(e){super(e)}poolingFunction(e,t,n,a,r){return Rt(r),xa(a),jf(e,t,n,a,r,"avg")}};c0.className="AveragePooling1D";ne.registerClass(c0);var i2=class extends Ge{constructor(e){if(e.poolSize==null&&(e.poolSize=[2,2]),super(e),this.poolSize=Array.isArray(e.poolSize)?e.poolSize:[e.poolSize,e.poolSize],e.strides==null)this.strides=this.poolSize;else if(Array.isArray(e.strides)){if(e.strides.length!==2)throw new V(`If the strides property of a 2D pooling layer is an Array, it is expected to have a length of 2, but received length ${e.strides.length}.`);this.strides=e.strides}else this.strides=[e.strides,e.strides];Qt(this.poolSize,"poolSize"),Qt(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,Rt(this.dataFormat),xa(this.padding),this.inputSpec=[new zt({ndim:4})]}computeOutputShape(e){e=tt(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],n=this.dataFormat==="channelsFirst"?e[3]:e[2];return t=Ga(t,this.poolSize[0],this.padding,this.strides[0]),n=Ga(n,this.poolSize[1],this.padding,this.strides[1]),this.dataFormat==="channelsFirst"?[e[0],e[1],t,n]:[e[0],t,n,e[3]]}call(e,t){return P(()=>(this.invokeCallHook(e,t),this.poolingFunction(Ne(e),this.poolSize,this.strides,this.padding,this.dataFormat)))}getConfig(){let e={poolSize:this.poolSize,padding:this.padding,strides:this.strides,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}},d0=class extends i2{constructor(e){super(e)}poolingFunction(e,t,n,a,r){return Rt(r),xa(a),jf(e,t,n,a,r,"max")}};d0.className="MaxPooling2D";ne.registerClass(d0);var h0=class extends i2{constructor(e){super(e)}poolingFunction(e,t,n,a,r){return Rt(r),xa(a),jf(e,t,n,a,r,"avg")}};h0.className="AveragePooling2D";ne.registerClass(h0);var o2=class extends Ge{constructor(e){if(e.poolSize==null&&(e.poolSize=[2,2,2]),super(e),this.poolSize=Array.isArray(e.poolSize)?e.poolSize:[e.poolSize,e.poolSize,e.poolSize],e.strides==null)this.strides=this.poolSize;else if(Array.isArray(e.strides)){if(e.strides.length!==3)throw new V(`If the strides property of a 3D pooling layer is an Array, it is expected to have a length of 3, but received length ${e.strides.length}.`);this.strides=e.strides}else this.strides=[e.strides,e.strides,e.strides];Qt(this.poolSize,"poolSize"),Qt(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,Rt(this.dataFormat),xa(this.padding),this.inputSpec=[new zt({ndim:5})]}computeOutputShape(e){e=tt(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],n=this.dataFormat==="channelsFirst"?e[3]:e[2],a=this.dataFormat==="channelsFirst"?e[4]:e[3];return t=Ga(t,this.poolSize[0],this.padding,this.strides[0]),n=Ga(n,this.poolSize[1],this.padding,this.strides[1]),a=Ga(a,this.poolSize[2],this.padding,this.strides[2]),this.dataFormat==="channelsFirst"?[e[0],e[1],t,n,a]:[e[0],t,n,a,e[4]]}call(e,t){return P(()=>(this.invokeCallHook(e,t),this.poolingFunction(Ne(e),this.poolSize,this.strides,this.padding,this.dataFormat)))}getConfig(){let e={poolSize:this.poolSize,padding:this.padding,strides:this.strides,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}},m0=class extends o2{constructor(e){super(e)}poolingFunction(e,t,n,a,r){return Rt(r),xa(a),r2(e,t,n,a,r,"max")}};m0.className="MaxPooling3D";ne.registerClass(m0);var f0=class extends o2{constructor(e){super(e)}poolingFunction(e,t,n,a,r){return Rt(r),xa(a),r2(e,t,n,a,r,"avg")}};f0.className="AveragePooling3D";ne.registerClass(f0);var l2=class extends Ge{constructor(e){super(e),this.inputSpec=[new zt({ndim:3})]}computeOutputShape(e){return[e[0],e[2]]}call(e,t){throw new Me}},g0=class extends l2{constructor(e){super(e||{})}call(e,t){return P(()=>{let n=Ne(e);return Nt(n,1)})}};g0.className="GlobalAveragePooling1D";ne.registerClass(g0);var b0=class extends l2{constructor(e){super(e||{})}call(e,t){return P(()=>{let n=Ne(e);return ma(n,1)})}};b0.className="GlobalMaxPooling1D";ne.registerClass(b0);var u2=class extends Ge{constructor(e){super(e),this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,Rt(this.dataFormat),this.inputSpec=[new zt({ndim:4})]}computeOutputShape(e){return e=e,this.dataFormat==="channelsLast"?[e[0],e[3]]:[e[0],e[1]]}call(e,t){throw new Me}getConfig(){let e={dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}},y0=class extends u2{call(e,t){return P(()=>{let n=Ne(e);return this.dataFormat==="channelsLast"?Nt(n,[1,2]):Nt(n,[2,3])})}};y0.className="GlobalAveragePooling2D";ne.registerClass(y0);var x0=class extends u2{call(e,t){return P(()=>{let n=Ne(e);return this.dataFormat==="channelsLast"?ma(n,[1,2]):ma(n,[2,3])})}};x0.className="GlobalMaxPooling2D";ne.registerClass(x0);var p2=class extends Ge{constructor(e){super(e),this.layer=e.layer}build(e){this.built=!0}get trainable(){return this.layer!=null?this.layer.trainable:!1}set trainable(e){this.layer!=null&&(this.layer.trainable=e)}get trainableWeights(){return this.layer.trainableWeights}get nonTrainableWeights(){return this.layer.nonTrainableWeights}get updates(){return this.layer._updates}get losses(){return this.layer.losses}getWeights(){return this.layer.getWeights()}setWeights(e){this.layer.setWeights(e)}getConfig(){let e={layer:{className:this.layer.getClassName(),config:this.layer.getConfig()}},t=super.getConfig();return Object.assign(e,t),e}setFastWeightInitDuringBuild(e){super.setFastWeightInitDuringBuild(e),this.layer!=null&&this.layer.setFastWeightInitDuringBuild(e)}static fromConfig(e,t,n={}){let a=t.layer,r=Ua(a,n);delete t.layer;let s={layer:r};return Object.assign(s,t),new e(s)}},v0=class extends p2{constructor(e){super(e),this.supportsMasking=!0}build(e){if(e=tt(e),e.length<3)throw new V(`TimeDistributed layer expects an input shape >= 3D, but received input shape ${JSON.stringify(e)}`);this.inputSpec=[{shape:e}];let t=[e[0]].concat(e.slice(2));this.layer.built||(this.layer.build(t),this.layer.built=!0),super.build(e)}computeOutputShape(e){e=tt(e);let t=[e[0]].concat(e.slice(2)),n=this.layer.computeOutputShape(t),a=e[1];return[n[0],a].concat(n.slice(1))}call(e,t){return P(()=>(e=Ne(e),n2((n,a)=>[Ne(this.layer.call(n,t)),[]],e,[],!1,null,null,!1,!0)[1]))}};v0.className="TimeDistributed";ne.registerClass(v0);function jU(e){bo(K4,"BidirectionalMergeMode",e)}var qU="concat",w0=class extends p2{constructor(e){super(e);let t=e.layer.getConfig(),n={};n.className=e.layer.getClassName(),n.config=t,this.forwardLayer=Ua(n),t.goBackwards=t.goBackwards!==!0;let a={};if(a.className=e.layer.getClassName(),a.config=t,this.backwardLayer=Ua(a),this.forwardLayer.name="forward_"+this.forwardLayer.name,this.backwardLayer.name="backward_"+this.backwardLayer.name,this.mergeMode=e.mergeMode===void 0?qU:e.mergeMode,jU(this.mergeMode),e.weights)throw new Me("weights support is not implemented for Bidirectional layer yet.");this._stateful=e.layer.stateful,this.returnSequences=e.layer.returnSequences,this.returnState=e.layer.returnState,this.supportsMasking=!0,this._trainable=!0,this.inputSpec=e.layer.inputSpec,this.numConstants=null}get trainable(){return this._trainable}set trainable(e){this._trainable=e,this.forwardLayer!=null&&(this.forwardLayer.trainable=e),this.backwardLayer!=null&&(this.backwardLayer.trainable=e)}getWeights(){return this.forwardLayer.getWeights().concat(this.backwardLayer.getWeights())}setWeights(e){let t=e.length,n=Math.floor(t/2);this.forwardLayer.setWeights(e.slice(0,n)),this.backwardLayer.setWeights(e.slice(n))}computeOutputShape(e){let t=this.forwardLayer.computeOutputShape(e);Array.isArray(t)&&Array.isArray(t[0])||(t=[t]),t=t;let n,a,r;return this.returnState&&(r=t.slice(1)),n=t[0],n=n,this.mergeMode==="concat"?(n[n.length-1]*=2,a=[n]):this.mergeMode==null?a=[n,n.slice()]:a=[n],this.returnState?this.mergeMode==null?a.concat(r).concat(r.slice()):[n].concat(r).concat(r.slice()):On(a)}apply(e,t){let n=t==null?null:t.initialState,a=t==null?null:t.constants;t==null&&(t={});let r=t2(e,n,a,this.numConstants);if(e=r.inputs,n=r.initialState,a=r.constants,Array.isArray(e)&&(n=e.slice(1),e=e[0]),(n==null||n.length===0)&&a==null)return super.apply(e,t);let s=[],i=[];if(n!=null){let l=n.length;if(l%2>0)throw new V("When passing `initialState` to a Bidrectional RNN, the state should be an Array containing the states of the underlying RNNs.");t.initialState=n,s.push(...n);let u=n.map(p=>new zt({shape:p.shape}));this.forwardLayer.stateSpec=u.slice(0,l/2),this.backwardLayer.stateSpec=u.slice(l/2),i.push(...u)}if(a!=null)throw new Me("Support for constants in Bidirectional layers is not implemented yet.");let o=s[0]instanceof Ba;for(let l of s)if(l instanceof Ba!==o)throw new V("The initial state of a Bidirectional layer cannot be specified as a mix of symbolic and non-symbolic tensors");if(o){let l=[e].concat(s),u=this.inputSpec.concat(i),p=this.inputSpec;this.inputSpec=u;let d=super.apply(l,t);return this.inputSpec=p,d}else return super.apply(e,t)}call(e,t){return P(()=>{let n=t.initialState,a,r;if(n==null)a=this.forwardLayer.call(e,t),r=this.backwardLayer.call(e,t);else{let o=n.slice(0,n.length/2),l=n.slice(n.length/2);a=this.forwardLayer.call(e,Object.assign(t,{initialState:o})),r=this.backwardLayer.call(e,Object.assign(t,{initialState:l}))}let s;this.returnState&&(Array.isArray(a)&&(s=a.slice(1).concat(r.slice(1))),a=a[0],r=r[0]),this.returnSequences&&(r=ga(r,1));let i;return this.mergeMode==="concat"?i=nw([a,r]):this.mergeMode==="sum"?i=Y(a,r):this.mergeMode==="ave"?i=z(.5,Y(a,r)):this.mergeMode==="mul"?i=z(a,r):this.mergeMode==null&&(i=[a,r]),this.returnState?this.mergeMode==null?i.concat(s):[i].concat(s):i})}resetStates(e){this.forwardLayer.resetStates(),this.backwardLayer.resetStates()}build(e){Ys(this.forwardLayer.name,()=>{this.forwardLayer.build(e)}),Ys(this.backwardLayer.name,()=>{this.backwardLayer.build(e)}),this.built=!0}computeMask(e,t){Array.isArray(t)&&(t=t[0]);let n;if(this.returnSequences?this.mergeMode==null?n=[t,t]:n=t:this.mergeMode==null?n=[null,null]:n=null,this.returnState){let a=this.forwardLayer.states.map(r=>null);return Array.isArray(n)?n.concat(a).concat(a):[n].concat(a).concat(a)}else return n}get trainableWeights(){return this.forwardLayer.trainableWeights.concat(this.backwardLayer.trainableWeights)}get nonTrainableWeights(){return 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r=k("default",e,t,n);return[wn(e.name,t,n)||r];case"Placeholder":return[wn(e.name,t,n)];case"Identity":case"StopGradient":case"FakeQuantWithMinMaxVars":{let p=k("x",e,t,n);return[Tr(p)]}case"IdentityN":return k("x",e,t,n).map(p=>Tr(p));case"Snapshot":let s=k("x",e,t,n);return[Tr(s)];case"Shape":return[a.tensor1d(k("x",e,t,n).shape,"int32")];case"ShapeN":return k("x",e,t,n).map(p=>a.tensor1d(p.shape));case"Size":return[a.scalar(k("x",e,t,n).size,"int32")];case"Rank":return[a.scalar(k("x",e,t,n).rank,"int32")];case"NoOp":return[a.scalar(1)];case"Print":let i=k("x",e,t,n),o=k("data",e,t,n),l=k("message",e,t,n),u=k("summarize",e,t,n);console.warn("The graph has a tf.print() operation,usually used for debugging, which slows down performance."),console.log(l);for(let p=0;p<o.length;p++)console.log(Array.prototype.slice.call(o[p].dataSync()).slice(0,u));return[i];default:throw TypeError(`Node type ${e.op} is not 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r=k("x",e,t,n),s=k("weights",e,t,n),i=k("size",e,t,n);return[a.bincount(r,s,i)];case"DenseBincount":{let o=k("x",e,t,n),l=k("weights",e,t,n),u=k("size",e,t,n),p=k("binaryOutput",e,t,n);return[a.denseBincount(o,l,u,p)]}default:throw TypeError(`Node type ${e.op} is not implemented`)}},v6=(e,t,n,a=pn)=>{switch(e.op){case"ConcatV2":case"Concat":{let r=k("n",e,t,n),s=k("axis",e,t,n),i=k("tensors",e,t,n);return i=i.slice(0,r),[a.concat(i,s)]}case"Gather":{let r=k("x",e,t,n),s=k("indices",e,t,n);return[a.gather(r,a.cast(s,"int32"),0)]}case"GatherV2":{let r=k("axis",e,t,n),s=k("batchDims",e,t,n),i=k("x",e,t,n),o=k("indices",e,t,n);return[a.gather(i,a.cast(o,"int32"),r,s)]}case"Reverse":{let r=k("dims",e,t,n),s=[];for(let o=0;o<r.length;o++)r[o]&&s.push(o);let i=k("x",e,t,n);return[a.reverse(i,s)]}case"ReverseV2":{let r=k("axis",e,t,n),s=k("x",e,t,n);return[a.reverse(s,r)]}case"Slice":{let r=k("begin",e,t,n),s=k("size",e,t,n);return[a.slice(k("x",e,t,n),r,s)]}case"StridedSlice":{let 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r=k("x",e,t,n),s=k("indices",e,t,n);return[a.gatherND(r,s)]}case"SparseToDense":{let r=k("sparseIndices",e,t,n),s=k("outputShape",e,t,n),i=k("sparseValues",e,t,n),o=k("defaultValue",e,t,n);return[a.sparseToDense(r,i,s,i.dtype===o.dtype?o:a.cast(o,i.dtype))]}default:throw TypeError(`Node type ${e.op} is not implemented`)}},w6=(e,t,n,a=pn)=>{switch(e.op){case"SparseFillEmptyRows":{let{outputIndices:r,outputValues:s,emptyRowIndicator:i,reverseIndexMap:o}=a.sparse.sparseFillEmptyRows(k("indices",e,t,n),k("values",e,t,n),k("denseShape",e,t,n),k("defaultValue",e,t,n));return[r,s,i,o]}case"SparseReshape":{let{outputIndices:r,outputShape:s}=a.sparse.sparseReshape(k("inputIndices",e,t,n),k("inputShape",e,t,n),k("newShape",e,t,n));return[r,s]}case"SparseSegmentMean":return[a.sparse.sparseSegmentMean(k("data",e,t,n),k("indices",e,t,n),k("segmentIds",e,t,n))];case"SparseSegmentSum":return[a.sparse.sparseSegmentSum(k("data",e,t,n),k("indices",e,t,n),k("segmentIds",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}},k6=(e,t,n,a=pn)=>{switch(e.op){case"FFT":return[a.fft(k("x",e,t,n))];case"IFFT":return[a.ifft(k("x",e,t,n))];case"RFFT":return[a.rfft(k("x",e,t,n))];case"IRFFT":return[a.irfft(k("x",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}},I6=(e,t,n,a=pn)=>{switch(e.op){case"StringNGrams":{let{nGrams:r,nGramsSplits:s}=a.string.stringNGrams(k("data",e,t,n),k("dataSplits",e,t,n),k("separator",e,t,n),k("nGramWidths",e,t,n),k("leftPad",e,t,n),k("rightPad",e,t,n),k("padWidth",e,t,n),k("preserveShortSequences",e,t,n));return[r,s]}case"StringSplit":{let{indices:r,values:s,shape:i}=a.string.stringSplit(k("input",e,t,n),k("delimiter",e,t,n),k("skipEmpty",e,t,n));return[r,s,i]}case"StringToHashBucketFast":return[a.string.stringToHashBucketFast(k("input",e,t,n),k("numBuckets",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}},S6=(e,t,n,a=pn)=>{switch(e.op){case"Cast":return[a.cast(k("x",e,t,n),k("dtype",e,t,n))];case"ExpandDims":{let r=k("axis",e,t,n);return[a.expandDims(k("x",e,t,n),r)]}case"Squeeze":{let r=k("axis",e,t,n);return[a.squeeze(k("x",e,t,n),r)]}case"Reshape":return[a.reshape(k("x",e,t,n),k("shape",e,t,n))];case"MirrorPad":return[a.mirrorPad(k("x",e,t,n),k("padding",e,t,n),k("mode",e,t,n))];case"PadV2":case"Pad":return[a.pad(k("x",e,t,n),k("padding",e,t,n),k("constantValue",e,t,n))];case"SpaceToBatchND":{let r=k("blockShape",e,t,n),s=k("paddings",e,t,n);return[a.spaceToBatchND(k("x",e,t,n),r,s)]}case"BatchToSpaceND":{let r=k("blockShape",e,t,n),s=k("crops",e,t,n);return[a.batchToSpaceND(k("x",e,t,n),r,s)]}case"DepthToSpace":{let r=k("blockSize",e,t,n),s=k("dataFormat",e,t,n).toUpperCase();return[a.depthToSpace(k("x",e,t,n),r,s)]}case"BroadcastTo":return[a.broadcastTo(k("x",e,t,n),k("shape",e,t,n))];case"BroadcastArgs":return[a.broadcastArgs(k("s0",e,t,n),k("s1",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}};function eI(e,t,n,a,r=P){let s=((i,o,l)=>{switch(i.category){case"arithmetic":return r(()=>e6(i,o,l));case"basic_math":return r(()=>t6(i,o,l));case"control":return o6(i,o,l);case"convolution":return r(()=>l6(i,o,l));case"creation":return r(()=>u6(i,o,l));case"dynamic":return p6(i,o,l);case"evaluation":return r(()=>c6(i,o,l));case"image":return r(()=>f6(i,o,l));case"graph":return r(()=>d6(i,o,l));case"logical":return r(()=>g6(i,o,l));case"matrices":return r(()=>b6(i,o,l));case"normalization":return r(()=>y6(i,o,l));case"reduction":return r(()=>x6(i,o,l));case"slice_join":return r(()=>v6(i,o,l));case"sparse":return r(()=>w6(i,o,l));case"spectral":return r(()=>k6(i,o,l));case"string":return r(()=>I6(i,o,l));case"transformation":return r(()=>S6(i,o,l));case"hash_table":return m6(i,o,l,a);case"custom":let u=v2(i.op);if(u&&u.customExecutor)return u.customExecutor(new QH(i,o,l));throw TypeError(`Custom op ${i.op} is not registered.`);default:throw TypeError(`Unknown op '${i.op}'. File an issue at https://github.com/tensorflow/tfjs/issues so we can add it, or register a custom execution with tf.registerOp()`)}})(e,t,n);return v.isPromise(s)?s.then(i=>[].concat(i)):[].concat(s)}var tI=class{constructor(e={},t={},n={},a={}){this.weightMap=e,this.tensorArrayMap=t,this.tensorListMap=n,this.functionMap=a,this.rootContext={id:0,frameName:"",iterationId:0},this.contexts=[this.rootContext],this.lastId=0,this.generateCurrentContextIds()}newFrame(e,t){return{id:e,frameName:t,iterationId:0}}set currentContext(e){this.contexts!==e&&(this.contexts=e,this.generateCurrentContextIds())}get currentContext(){return this.contexts}get currentContextId(){return this._currentContextIds[0]}get currentContextIds(){return this._currentContextIds}generateCurrentContextIds(){let e=[];for(let t=0;t<this.contexts.length-1;t++){let n=this.contexts.slice(0,this.contexts.length-t);e.push(this.contextIdforContexts(n))}e.push(""),this._currentContextIds=e}contextIdforContexts(e){return e?e.map(t=>t.id===0&&t.iterationId===0?"":`${t.frameName}-${t.iterationId}`).join("/"):""}enterFrame(e){this.contexts&&(this.lastId++,this.contexts=this.contexts.slice(),this.contexts.push(this.newFrame(this.lastId,e)),this._currentContextIds.unshift(this.contextIdforContexts(this.contexts)))}exitFrame(){if(this.contexts&&this.contexts.length>1)this.contexts=this.contexts.slice(),this.contexts.splice(-1),this.currentContextIds.shift();else throw new Error("Cannot exit frame, the context is empty")}nextIteration(){if(this.contexts&&this.contexts.length>0){this.contexts=this.contexts.slice(),this.lastId++;let e=Object.assign({},this.contexts[this.contexts.length-1]);e.iterationId+=1,e.id=this.lastId,this.contexts.splice(-1,1,e),this._currentContextIds.splice(0,1,this.contextIdforContexts(this.contexts))}else throw new Error("Cannot increase frame iteration, the context is empty")}getWeight(e){return this.weightMap[e]}addTensorArray(e){this.tensorArrayMap[e.id]=e}getTensorArray(e){return this.tensorArrayMap[e]}addTensorList(e){this.tensorListMap[e.id]=e}getTensorList(e){return this.tensorListMap[e]}dispose(e){for(let t in this.tensorArrayMap)this.tensorArrayMap[t].clearAndClose(e);for(let t in this.tensorListMap)this.tensorListMap[t].clearAndClose(e)}};function nI(e,t,n,a){let r=new Set,s=[],i=null,o=null,l=new Set,u=Object.keys(e).map(c=>Yn(c)[0]),p=[];a!=null&&(p=a.map(c=>Yn(c.name)[0]));let d=[...t];for(;d.length>0;){let c=d.pop();if((V2(c)||E6(c)||A6(c))&&i==null&&(i=c,o=i.children.map(h=>h.name).filter(h=>r.has(h))),r.add(c.name),n[c.name]==null&&u.indexOf(c.name)===-1&&p.indexOf(c.name)===-1){if(c.inputs.length===0){s.push(c.name);continue}c.inputs.forEach(h=>{l.has(h.name)||(l.add(h.name),d.push(h))})}}return{inputs:e,outputs:t,usedNodes:r,missingInputs:s,dynamicNode:i,syncInputs:o}}function T6(e,t,n){let{usedNodes:a,inputs:r}=n,s=[],i=Object.keys(r).map(p=>Yn(p)[0]).map(p=>e.nodes[p]),o=e.initNodes;i.forEach(p=>{a.has(p.name)&&s.push(p)}),e.weights.forEach(p=>{a.has(p.name)&&s.push(p)}),o!=null&&o.forEach(p=>{a.has(p.name)&&s.push(p)});let l=new Set,u=[];for(;s.length>0;){let p=s.pop();l.add(p.name),t[p.name]||u.push(p),p.children.forEach(d=>{!l.has(d.name)&&a.has(d.name)&&d.inputs.every(c=>l.has(c.name))&&s.push(d)})}return u}var N6=["Switch","Merge","Enter","Exit","NextIteration","StatelessIf","StatelessWhile","if","While"],C6=["NonMaxSuppressionV2","NonMaxSuppressionV3","NonMaxSuppressionV5","Where"],_6=["HashTable","HashTableV2","LookupTableImport","LookupTableImportV2","LookupTableFind","LookupTableFindV2","LookupTableSize","LookupTableSizeV2"];function V2(e){return N6.indexOf(e.op)>=0}function E6(e){return C6.indexOf(e.op)>=0}function A6(e){return _6.indexOf(e.op)>=0}var px=class{constructor(e,t){this.graph=e,this.parent=t,this.compiledMap=new Map,this._weightMap={},this.SEPERATOR=",",this._functions={},this._functionExecutorMap={},this.intermediateTensors={},this.keepTensorForDebug=!1,this._outputs=e.outputs,this._inputs=e.inputs,this._initNodes=e.initNodes,this._signature=e.signature,this._functions=e.functions,e.functions!=null&&Object.keys(e.functions).forEach(n=>{this._functionExecutorMap[n]=new px(e.functions[n],this)})}get weightIds(){return this.parent?this.parent.weightIds:this._weightIds}get functionExecutorMap(){return this.parent?this.parent.functionExecutorMap:this._functionExecutorMap}get weightMap(){return this.parent?this.parent.weightMap:this._weightMap}set weightMap(e){let t=Object.keys(e).map(n=>e[n].map(a=>a.id));this._weightIds=[].concat(...t),this._weightMap=e}set resourceManager(e){this._resourceManager=e}get inputs(){return this._inputs.map(e=>({name:e.name,shape:e.attrParams.shape?e.attrParams.shape.value:void 0,dtype:e.attrParams.dtype?e.attrParams.dtype.value:void 0}))}get outputs(){return this._outputs.map(e=>({name:e.name,shape:e.attrParams.shape?e.attrParams.shape.value:void 0,dtype:e.attrParams.dtype?e.attrParams.dtype.value:void 0}))}get inputNodes(){return this._inputs.map(e=>e.signatureKey||e.name)}get outputNodes(){return this._outputs.map(e=>{let t=e.signatureKey||e.name;return e.defaultOutput?`${t}:${e.defaultOutput}`:t})}get functions(){return Object.keys(this._functions).reduce((e,t)=>(e[t]=this._functions[t].signature,e),{})}getCompilationKey(e,t){let n=e.map(r=>r.name).sort(),a=t.map(r=>r.name).sort();return n.join(this.SEPERATOR)+"--"+a.join(this.SEPERATOR)}compile(e,t){let n=nI(e,t,this.weightMap,this._initNodes),{missingInputs:a,dynamicNode:r,syncInputs:s}=n;if(r!=null)throw new Error(`This execution contains the node '${r.name}', which has the dynamic op '${r.op}'. Please use model.executeAsync() instead. Alternatively, to avoid the dynamic ops, specify the inputs [${s}]`);if(a.length>0){let i=t.map(l=>l.name),o=Object.keys(e);throw new Error(`Cannot compute the outputs [${i}] from the provided inputs [${o}]. Missing the following inputs: [${a}]`)}return T6(this.graph,this.weightMap,n)}execute(e,t){e=this.mapInputs(e);let n=Object.keys(e).sort();this.checkInputs(e),this.checkInputShapeAndType(e),t=this.mapOutputs(t),this.checkOutputs(t);let a=n.map(p=>this.graph.nodes[Yn(p)[0]]),r=t.map(p=>Yn(p)[0]),s=r.map(p=>this.graph.nodes[p]);this.resetIntermediateTensors(),s.length===0&&(s=this._outputs);let i=this.getCompilationKey(a,s),o=this.compiledMap.get(i);o==null&&(o=this.compile(e,s),this.compiledMap.set(i,o));let l={},u={};return P(()=>{let p=new tI(this.weightMap,l,u,this.functionExecutorMap),d=Object.assign({},this.weightMap);Object.keys(e).forEach(m=>{let[f,g]=Yn(m),b=[];b[g]=e[m],d[f]=b});let c=this.getFrozenTensorIds(d),h={};for(let m=0;m<o.length;m++){let f=o[m];if(!d[f.name]){let g=eI(f,d,p,this._resourceManager);if(v.isPromise(g))throw new Error(`The execution of the op '${f.op}' returned a promise. Please use model.executeAsync() instead.`);d[f.name]=g,this.checkTensorForDisposal(f.name,f,d,p,c,r,h)}}return this.parent==null&&p.dispose(c),t.map(m=>wn(m,d,p))})}getFrozenTensorIds(e){let t=[].concat.apply([],Object.keys(e).map(n=>e[n]).map(n=>n.map(a=>a.id)));return new Set(t)}checkTensorForDisposal(e,t,n,a,r,s,i){t.category==="control"||s.indexOf(e)!==-1||(n[e].forEach(o=>{o!=null&&(i[o.id]=(i[o.id]||0)+t.children.length)}),t.inputs.forEach(o=>{if(o.category!=="control"){let l=FH(o.name,n,a);l!=null&&l.forEach(u=>{if(u&&!u.kept&&!r.has(u.id)){let p=i[u.id];if(p===1){if(!this.keepTensorForDebug)u.dispose();else{let[d,c]=sr(t.name,a);this.intermediateTensors[d]?this.intermediateTensors[d][c]=u:(this.intermediateTensors[d]=[],this.intermediateTensors[d][c]=u)}delete i[u.id]}else p!=null&&i[u.id]--}})}}))}async executeAsync(e,t){return this._executeAsync(e,t)}disposeIntermediateTensors(){!this.intermediateTensors||(Object.keys(this.intermediateTensors).forEach(e=>this.intermediateTensors[e].forEach(t=>t.dispose())),this.disposeTensorsMap())}disposeTensorsMap(){!this.tensorsMap||Object.keys(this.tensorsMap).forEach(e=>{this.tensorsMap[e].forEach(t=>{t&&!t.kept&&!t.isDisposed&&!this.keepIds.has(t.id)&&t.dispose()})})}getIntermediateTensors(){return this.tensorsMap}resetIntermediateTensors(){for(let e in this.intermediateTensors)this.intermediateTensors[e].forEach(t=>t.dispose()),delete this.intermediateTensors[e]}async _executeAsync(e,t,n=!1,a={},r={}){n||(e=this.mapInputs(e),this.checkInputs(e),this.checkInputShapeAndType(e),t=this.mapOutputs(t),this.checkOutputs(t));try{this.keepTensorForDebug=H().getBool("KEEP_INTERMEDIATE_TENSORS")}catch(u){console.warn(u.message)}this.resetIntermediateTensors();let s=new tI(this.weightMap,a,r,this.functionExecutorMap);this.tensorsMap=await this.executeWithControlFlow(e,s,t,n);let i=t.map(u=>wn(u,this.tensorsMap,s)),o=i.map(u=>u.id),l=Object.keys(e).map(u=>e[u].id);return this.keepIds=new Set([...o,...l,...this.weightIds]),this.keepTensorForDebug||this.disposeTensorsMap(),this.parent==null&&s.dispose(this.keepIds),i}async executeFunctionAsync(e,t,n){let a=e.reduce((r,s,i)=>(r[this.inputs[i].name]=s,r),{});return this._executeAsync(a,this.outputNodes,!0,t,n)}async executeWithControlFlow(e,t,n,a){let r=Object.keys(e),s=r.map(y=>this.graph.nodes[Yn(y)[0]]),i=n.map(y=>Yn(y)[0]),o=i.map(y=>this.graph.nodes[y]);o.length===0&&(o=this._outputs);let{usedNodes:l,missingInputs:u,dynamicNode:p,syncInputs:d}=nI(e,o,this.weightMap,this._initNodes),c=[...s,...this.graph.weights,...this._initNodes||[]].map(y=>({node:y,contexts:t.currentContext})),h=Object.assign({},this.weightMap);Object.keys(e).forEach(y=>{let[x,w]=Yn(y),I=[];I[w]=e[y],h[x]=I});let m={},f=this.getFrozenTensorIds(h),g={};for(;c.length>0;){let y=this.processStack(s,c,t,h,g,f,i,m,l);await Promise.all(y)}p==null&&!a&&console.warn("This model execution did not contain any nodes with control flow or dynamic output shapes. You can use model.execute() instead.");let b=o.filter(y=>!V2(y)&&!wn(y.name,h,t)).map(y=>y.name);if(b.length>0){let y="";throw p!=null&&(y=`Alternatively, to avoid the dynamic ops, use model.execute() and specify the inputs [${d}]`),new Error(`Cannot compute the outputs [${b}] from the provided inputs [${r}]. Consider providing the following inputs: [${u}]. ${y}`)}return h}processStack(e,t,n,a,r,s,i,o,l){let u=[];for(;t.length>0;){let p=t.pop();n.currentContext=p.contexts;let d="";if(p.node.op==="Enter"&&k("isConstant",p.node,a,n)&&([d]=sr(p.node.name,n)),a[p.node.name]==null){let c=eI(p.node,a,n,this._resourceManager);d||([d]=sr(p.node.name,n));let h=n.currentContext;v.isPromise(c)?u.push(c.then(m=>(a[d]=m,n.currentContext=h,this.checkTensorForDisposal(d,p.node,a,n,s,i,o),this.processChildNodes(p.node,t,n,a,r,l),m))):(a[d]=c,this.checkTensorForDisposal(d,p.node,a,n,s,i,o),this.processChildNodes(p.node,t,n,a,r,l))}else this.processChildNodes(p.node,t,n,a,r,l)}return u}processChildNodes(e,t,n,a,r,s){e.children.forEach(i=>{let[o]=sr(i.name,n);r[o]||!s.has(i.name)||(i.op==="Merge"?i.inputNames.some(l=>!!wn(l,a,n))&&(r[o]=!0,t.push({contexts:n.currentContext,node:i})):i.inputNames.every(l=>!!wn(l,a,n))&&(r[o]=!0,t.push({contexts:n.currentContext,node:i})))})}dispose(){Object.keys(this.weightMap).forEach(e=>this.weightMap[e].forEach(t=>t.dispose()))}checkInputShapeAndType(e){Object.keys(e).forEach(t=>{let n=e[t],[a]=Yn(t),r=this.graph.nodes[a];if(r.attrParams.shape&&r.attrParams.shape.value){let s=r.attrParams.shape.value,i=s.length===n.shape.length&&n.shape.every((o,l)=>s[l]===-1||s[l]===o);v.assert(i,()=>`The shape of dict['${r.name}'] provided in model.execute(dict) must be [${s}], but was [${n.shape}]`)}r.attrParams.dtype&&r.attrParams.dtype.value&&v.assert(n.dtype===r.attrParams.dtype.value,()=>`The dtype of dict['${r.name}'] provided in model.execute(dict) must be ${r.attrParams.dtype.value}, but was ${n.dtype}`)})}mapInputs(e){let t={};for(let n in e)if(this._signature!=null&&this._signature.inputs!=null&&this._signature.inputs[n]!=null){let a=this._signature.inputs[n];t[a.name]=e[n]}else t[n]=e[n];return t}checkInputs(e){let t=Object.keys(e).filter(n=>{let[a]=Yn(n);return this.graph.nodes[a]==null});if(t.length>0)throw new Error(`The dict provided in model.execute(dict) has keys: [${t}] that are not part of graph`)}mapOutputs(e){return e.map(t=>this._signature!=null&&this._signature.outputs!=null&&this._signature.outputs[t]!=null?this._signature.outputs[t].name:t,{})}checkOutputs(e){e.forEach(t=>{let[n]=Yn(t);if(!this.graph.nodes[n])throw new Error(`The output '${t}' is not found in the graph`)})}},$6=class{constructor(e={},t={}){this.hashTableNameToHandle=e,this.hashTableMap=t}addHashTable(e,t){this.hashTableNameToHandle[e]=t.handle,this.hashTableMap[t.id]=t}getHashTableHandleByName(e){return this.hashTableNameToHandle[e]}getHashTableById(e){return this.hashTableMap[e]}dispose(){for(let e in this.hashTableMap)this.hashTableMap[e].clearAndClose(),delete this.hashTableMap[e];for(let e in this.hashTableNameToHandle)this.hashTableNameToHandle[e].dispose(),delete this.hashTableNameToHandle[e]}},F6="?tfjs-format=file",D6="model.json",A0=class{constructor(e,t={},n=Ut){this.modelUrl=e,this.loadOptions=t,this.version="n/a",this.io=n,t==null&&(this.loadOptions={}),this.resourceManager=new $6}get modelVersion(){return this.version}get inputNodes(){return this.executor.inputNodes}get outputNodes(){return this.executor.outputNodes}get inputs(){return this.executor.inputs}get outputs(){return this.executor.outputs}get weights(){return this.executor.weightMap}get metadata(){return this.artifacts.userDefinedMetadata}get modelSignature(){return this.signature}get modelStructuredOutputKeys(){return this.structuredOutputKeys}findIOHandler(){let e=this.modelUrl;if(e.load!=null)this.handler=e;else if(this.loadOptions.requestInit!=null)this.handler=this.io.browserHTTPRequest(e,this.loadOptions);else{let t=this.io.getLoadHandlers(e,this.loadOptions);if(t.length===0)t.push(this.io.browserHTTPRequest(e,this.loadOptions));else if(t.length>1)throw new Error(`Found more than one (${t.length}) load handlers for URL '${[e]}'`);this.handler=t[0]}}load(){if(this.findIOHandler(),this.handler.load==null)throw new Error("Cannot proceed with model loading because the IOHandler provided does not have the `load` method implemented.");let e=this.handler.load();return v.isPromise(e)?e.then(t=>this.loadSync(t)):this.loadSync(e)}loadSync(e){this.artifacts=e;let t=this.artifacts.modelTopology,n=this.artifacts.signature;if(this.artifacts.userDefinedMetadata!=null){let r=this.artifacts.userDefinedMetadata;r.signature!=null&&(n=r.signature),r.structuredOutputKeys!=null&&(this.structuredOutputKeys=r.structuredOutputKeys)}this.signature=n,this.version=`${t.versions.producer}.${t.versions.minConsumer}`;let a=this.io.decodeWeights(this.artifacts.weightData,this.artifacts.weightSpecs);if(this.executor=new px(Yk.Instance.transformGraph(t,this.signature)),this.executor.weightMap=this.convertTensorMapToTensorsMap(a),this.executor.resourceManager=this.resourceManager,e.modelInitializer!=null&&e.modelInitializer.node!=null){let r=Yk.Instance.transformGraph(e.modelInitializer);this.initializer=new px(r),this.initializer.weightMap=this.executor.weightMap,this.initializer.resourceManager=this.resourceManager,this.initializerSignature=e.initializerSignature}return!0}async save(e,t){if(typeof e=="string"){let n=this.io.getSaveHandlers(e);if(n.length===0)throw new Error(`Cannot find any save handlers for URL '${e}'`);if(n.length>1)throw new Error(`Found more than one (${n.length}) save handlers for URL '${e}'`);e=n[0]}if(e.save==null)throw new Error("GraphModel.save() cannot proceed because the IOHandler provided does not have the `save` attribute defined.");return e.save(this.artifacts)}predict(e,t){let n=this.execute(e,this.outputNodes);if(this.structuredOutputKeys){let a=n instanceof Te?[n]:n,r={};return a.forEach((s,i)=>r[this.structuredOutputKeys[i]]=s),r}return n}normalizeInputs(e){if(!(e instanceof Te)&&!Array.isArray(e)){if(this.signature!=null&&this.signature.inputs!=null)for(let a in this.signature.inputs){let r=this.signature.inputs[a];r.resourceId!=null&&(e[a]=this.resourceIdToCapturedInput[r.resourceId])}return e}e=Array.isArray(e)?e:[e];let t=Object.keys(this.resourceIdToCapturedInput).length;if(e.length+t!==this.inputNodes.length)throw new Error(`Input tensor count mismatch, the graph model has ${this.inputNodes.length-t} non-resource placeholders, while there are ${e.length} input tensors provided.`);let n=0;return this.inputNodes.reduce((a,r)=>{let s=this.signature?this.signature.inputs[r]:null;return s!=null&&s.resourceId!=null?a[r]=this.resourceIdToCapturedInput[s.resourceId]:a[r]=e[n++],a},{})}normalizeOutputs(e){return e=e||this.outputNodes,Array.isArray(e)?e:[e]}executeInitializerGraph(){return this.initializer==null?[]:this.initializerSignature==null?this.initializer.execute({},[]):this.initializer.execute({},Object.keys(this.initializerSignature.outputs))}async executeInitializerGraphAsync(){return this.initializer==null?[]:this.initializerSignature==null?this.initializer.executeAsync({},[]):this.initializer.executeAsync({},Object.keys(this.initializerSignature.outputs))}setResourceIdToCapturedInput(e){if(this.resourceIdToCapturedInput={},this.initializerSignature){let t=Object.keys(this.initializerSignature.outputs);for(let n=0;n<t.length;n++){let a=t[n],r=this.initializerSignature.outputs[a];this.resourceIdToCapturedInput[r.resourceId]=e[n]}}}execute(e,t){this.resourceIdToCapturedInput==null&&this.setResourceIdToCapturedInput(this.executeInitializerGraph()),e=this.normalizeInputs(e),t=this.normalizeOutputs(t);let n=this.executor.execute(e,t);return n.length>1?n:n[0]}async 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Should have ${this.fullColumnNames.length} elements in a row, but got ${n}`);return n}},Q2=class extends tn{constructor(e){super(),this.microphoneConfig=e,this.isClosed=!1,this.fftSize=e.fftSize||1024;let t=Math.log2(this.fftSize);if(this.fftSize<0||t<4||t>14||!Number.isInteger(t))throw new Error(`Invalid fftSize: it must be a power of 2 between 2 to 4 and 2 to 14, but got ${this.fftSize}`);if(this.numFrames=e.numFramesPerSpectrogram||43,this.sampleRateHz=e.sampleRateHz,this.columnTruncateLength=e.columnTruncateLength||this.fftSize,this.audioTrackConstraints=e.audioTrackConstraints,this.smoothingTimeConstant=e.smoothingTimeConstant||0,this.includeSpectrogram=e.includeSpectrogram!==!1,this.includeWaveform=e.includeWaveform===!0,!this.includeSpectrogram&&!this.includeWaveform)throw new Error("Both includeSpectrogram and includeWaveform are false. At least one type of data should be returned.")}summary(){return"microphone"}static async create(e={}){if(!H().get("IS_BROWSER"))throw new Error("microphone API is only supported in browser environment.");let t=new Q2(e);return await t.start(),t}async start(){try{this.stream=await navigator.mediaDevices.getUserMedia({audio:this.audioTrackConstraints==null?!0:this.audioTrackConstraints,video:!1})}catch(n){throw new Error(`Error thrown while initializing video stream: ${n.message}`)}if(!this.stream)throw new Error("Could not obtain audio from microphone.");let e=window.AudioContext||window.webkitAudioContext;if(this.audioContext=new e,!this.sampleRateHz)this.sampleRateHz=this.audioContext.sampleRate;else if(this.audioContext.sampleRate!==this.sampleRateHz)throw new Error(`Mismatch in sampling rate: Expected: ${this.sampleRateHz}; Actual: ${this.audioContext.sampleRate}`);let t=this.audioContext.createMediaStreamSource(this.stream);this.analyser=this.audioContext.createAnalyser(),this.analyser.fftSize=this.fftSize*2,this.analyser.smoothingTimeConstant=this.smoothingTimeConstant,t.connect(this.analyser),this.freqData=new Float32Array(this.fftSize),this.timeData=new Float32Array(this.fftSize)}async next(){if(this.isClosed)return{value:null,done:!0};let e,t,n=await this.getAudioData();if(this.includeSpectrogram){let a=this.flattenQueue(n.freqDataQueue);e=this.getTensorFromAudioDataArray(a,[this.numFrames,this.columnTruncateLength,1])}if(this.includeWaveform){let a=this.flattenQueue(n.timeDataQueue);t=this.getTensorFromAudioDataArray(a,[this.numFrames*this.fftSize,1])}return{value:{spectrogram:e,waveform:t},done:!1}}async capture(){return(await this.next()).value}async getAudioData(){let e=[],t=[],n=0;return new Promise(a=>{let r=setInterval(()=>{this.includeSpectrogram&&(this.analyser.getFloatFrequencyData(this.freqData),this.freqData[0]===-1/0&&a({freqDataQueue:e,timeDataQueue:t}),e.push(this.freqData.slice(0,this.columnTruncateLength))),this.includeWaveform&&(this.analyser.getFloatTimeDomainData(this.timeData),t.push(this.timeData.slice())),++n===this.numFrames&&(clearInterval(r),a({freqDataQueue:e,timeDataQueue:t}))},this.fftSize/this.sampleRateHz*1e3)})}stop(){this.isClosed||(this.isClosed=!0,this.analyser.disconnect(),this.audioContext.close(),this.stream!=null&&this.stream.getTracks().length>0&&this.stream.getTracks()[0].stop())}toArray(){throw new Error("Can not convert infinite audio stream to array.")}getSampleRate(){return this.sampleRateHz}flattenQueue(e){let t=e[0].length,n=new Float32Array(e.length*t);return e.forEach((a,r)=>n.set(a,r*t)),n}getTensorFromAudioDataArray(e,t){let n=new Float32Array(v.sizeFromShape(t));return n.set(e,n.length-e.length),In(n,t)}},eC=class extends tn{constructor(e,t){if(super(),this.webcamVideoElement=e,this.webcamConfig=t,this.isClosed=!0,this.resize=!1,this.needToResize())if(this.resize=!0,this.cropSize=[this.webcamConfig.resizeHeight,this.webcamConfig.resizeWidth],this.cropBoxInd=Ke([0],"int32"),this.webcamConfig.centerCrop){let n=this.webcamConfig.resizeWidth*1/this.webcamVideoElement.width,a=this.webcamConfig.resizeHeight*1/this.webcamVideoElement.height,r=(1-n)/2,s=(1-a)/2,i=r+n,o=a+s;this.cropBox=Aa([s,r,o,i],[1,4])}else this.cropBox=Aa([0,0,1,1],[1,4])}summary(){return"webcam"}static async create(e,t={}){if(!H().get("IS_BROWSER"))throw new Error("tf.data.webcam is only supported in browser environment.");if(!e){if(e=document.createElement("video"),!t.resizeWidth||!t.resizeHeight)throw new Error("Please provide webcam video element, or resizeWidth and resizeHeight to create a hidden video element.");e.width=t.resizeWidth,e.height=t.resizeHeight}let n=new eC(e,t);return await n.start(),n}async start(){this.webcamConfig.facingMode&&v.assert(this.webcamConfig.facingMode==="user"||this.webcamConfig.facingMode==="environment",()=>`Invalid webcam facing mode: ${this.webcamConfig.facingMode}. Please provide 'user' or 'environment'`);try{this.stream=await navigator.mediaDevices.getUserMedia({video:{deviceId:this.webcamConfig.deviceId,facingMode:this.webcamConfig.facingMode?this.webcamConfig.facingMode:"user",width:this.webcamVideoElement.width,height:this.webcamVideoElement.height}})}catch(e){throw e.message=`Error thrown while initializing video stream: ${e.message}`,e}if(!this.stream)throw new Error("Could not obtain video from webcam.");try{this.webcamVideoElement.srcObject=this.stream}catch(e){console.log(e),this.webcamVideoElement.src=window.URL.createObjectURL(this.stream)}return this.webcamVideoElement.play(),this.isClosed=!1,new Promise(e=>{this.webcamVideoElement.onloadedmetadata=()=>{e()}})}async next(){if(this.isClosed)return{value:null,done:!0};let e;try{e=ho.fromPixels(this.webcamVideoElement)}catch(t){throw new Error(`Error thrown converting video to pixels: ${JSON.stringify(t)}`)}if(this.resize)try{return{value:this.cropAndResizeFrame(e),done:!1}}catch(t){throw new Error(`Error thrown cropping the video: ${t.message}`)}finally{e.dispose()}else return{value:e,done:!1}}needToResize(){return!!(this.webcamConfig.resizeWidth&&this.webcamConfig.resizeHeight&&(this.webcamVideoElement.width!==this.webcamConfig.resizeWidth||this.webcamVideoElement.height!==this.webcamConfig.resizeHeight))}cropAndResizeFrame(e){return P(()=>{let t=Zt(oe(e,"float32"),0),n;n=za.cropAndResize(t,this.cropBox,this.cropBoxInd,this.cropSize,"bilinear");let a=n.shape;return W(n,a.slice(1))})}async capture(){return(await this.next()).value}stop(){this.stream.getTracks().forEach(e=>e.stop());try{this.webcamVideoElement.srcObject=null}catch(e){console.log(e),this.webcamVideoElement.src=null}this.isClosed=!0}toArray(){throw new Error("Can not convert infinite video stream to array.")}},tC=class{},nC=class extends tn{split(e){return new pj(this,e)}},pj=class extends nC{constructor(e,t){super(),this.upstream=e,this.impl=new cj(e,t)}summary(){return this.impl.summary()}async next(){return this.impl.next()}},cj=class extends D0{constructor(e,t){super(),this.upstream=e,this.separator=t,this.carryover=""}summary(){return`${this.upstream.summary()} -> Split('${this.separator}')`}async pump(){let e=await this.upstream.next();if(e.done)return this.carryover===""?!1:(this.outputQueue.push(this.carryover),this.carryover="",!0);let t=e.value.split(this.separator);t[0]=this.carryover+t[0];for(let n of t.slice(0,-1))this.outputQueue.push(n);return this.carryover=t[t.length-1],!0}},dj=class extends tn{decodeUTF8(){return new hj(this)}},hj=class extends nC{constructor(e){super(),this.upstream=e,this.impl=new mj(e)}summary(){return this.impl.summary()}async next(){return this.impl.next()}},mj=class extends D0{constructor(e){if(super(),this.upstream=e,H().get("IS_BROWSER"))this.decoder=new TextDecoder("utf-8");else{let{StringDecoder:t}=BI();this.decoder=new t("utf8")}}summary(){return`${this.upstream.summary()} -> Utf8`}async pump(){let e=await this.upstream.next(),t;if(e.done)return!1;t=e.value;let n;return H().get("IS_BROWSER")?n=this.decoder.decode(t,{stream:!0}):n=this.decoder.write(Buffer.from(t.buffer)),this.outputQueue.push(n),!0}},aC=class extends dj{constructor(e,t={}){super(),this.file=e,this.options=t,v.assert(e instanceof Uint8Array||(H().get("IS_BROWSER")?e instanceof File||e instanceof Blob:!1),()=>"FileChunkIterator only supports File, Blob and Uint8Array right now."),this.offset=t.offset||0,this.chunkSize=t.chunkSize||1024*1024}summary(){return`FileChunks ${this.file}`}async next(){return this.offset>=(this.file instanceof Uint8Array?this.file.byteLength:this.file.size)?{value:null,done:!0}:{value:await new Promise((e,t)=>{let n=this.offset+this.chunkSize;if(this.file instanceof Uint8Array)e(new Uint8Array(this.file.slice(this.offset,n)));else{let a=new FileReader;a.onload=s=>{let i=a.result;if(i instanceof ArrayBuffer&&(i=new Uint8Array(i)),!(i instanceof Uint8Array))return t(new TypeError("FileReader returned unknown type."));e(i)},a.onabort=s=>t(new Error("Aborted")),a.onerror=s=>t(new Error(s.type));let r=this.file.slice(this.offset,n);a.readAsArrayBuffer(r)}this.offset=n}),done:!1}}};async function fj(e,t={},n){let a,r;typeof e=="string"?a=e:(a=e.url,r=gj(e));let s=await(n||v.fetch)(a,r);if(s.ok){let i=new Uint8Array(await s.arrayBuffer());return new aC(i,t)}else throw new Error(s.statusText)}var gj=e=>({method:e.method,headers:e.headers,body:e.body,mode:e.mode,credentials:e.credentials,cache:e.cache,redirect:e.redirect,referrer:e.referrer,integrity:e.integrity});function rC(e){return typeof e=="string"&&e.slice(0,7)==="file://"}var sC=class extends tC{constructor(e,t={}){super(),this.input=e,this.options=t}async iterator(){if(rC(this.input)&&H().get("IS_NODE")){let e=Cx();this.input=e.readFileSync(this.input.slice(7))}return new aC(this.input,this.options)}},iC=class extends tC{constructor(e,t={}){super(),this.url=e,this.fileOptions=t}async iterator(){return rC(this.url)?new sC(this.url,this.fileOptions).iterator():fj(this.url,this.fileOptions)}};function bj(e,t={}){return new J2(new iC(e),t)}function yj(e){let t=F0(e);return Xn(async()=>t)}function xj(e){return Xn(async()=>{let t=await e();return F0(()=>t.next())})}async function vj(e,t){return eC.create(e,t)}async function wj(e){return Q2.create(e)}var kj="4.0.0";function ge(e,t){Array.isArray(e)||(e=[e]),e.forEach(n=>{n!=null&&v.assert(n.dtype!=="complex64",()=>`${t} does not support complex64 tensors in the CPU backend.`)})}var Ij=hr.whereImpl,R0=class extends pc{constructor(){super(),this.blockSize=48,this.firstUse=!0,this.data=new om(this,_a())}nextDataId(){return R0.nextDataId++}write(e,t,n){this.firstUse&&(this.firstUse=!1,H().get("IS_NODE")&&N.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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hC=Vt((e,t)=>e===t?1:0),mC=nn(Xl,hC,null,"bool"),Rj={kernelName:Xl,backendName:"cpu",kernelFunc:mC},fC=Cs(e=>Math.exp(e)),gC=Ku(Ei,fC,"float32"),Mj={kernelName:Ei,backendName:"cpu",kernelFunc:gC},bC=Cs(e=>Math.expm1(e)),Pj=Ku(Zl,bC),Oj={kernelName:Zl,backendName:"cpu",kernelFunc:Pj},yC=Cs(e=>Math.floor(e)),Lj=Ku(Ai,yC),zj={kernelName:Ai,backendName:"cpu",kernelFunc:Lj};function xC(e,t,n,a,r,s,i,o,l){let u=Oe([a,s],n);for(let p=0;p<a;p++){let d=[],c=0;for(let h=0;h<r;h++){let m=e[p*r+h];c+=m*i[h],d.push(m)}if(c<0||c>=l/s)throw new Error(`Invalid indices: ${d} does not index into ${o}`);for(let h=0;h<s;h++)u.values[p*s+h]=t.get(...t.indexToLoc(c*s+h))}return u}function vC(e,t,n){let a=Oe(n,e.dtype);for(let r=0;r<a.size;++r){let s=a.indexToLoc(r).slice(),i=s[0],o=s[2],l=t.locToIndex([i,o]);s[2]=t.values[l];let u=e.locToIndex(s);0<=u&&u<e.values.length&&(a.values[r]=e.values[u])}return a}var 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p=t[u+1];for(let d=1;d<l+1;++d)o[u].push(d*p)}for(let u=0;u<e.length;++u){let p=e[u],d=e[u]+1;for(let c=0;c<n.length;++c){let h=n[c],m=c+t.length-1;if(m>=0){let f=o[m],g=f[f.length-1]-h[p];for(let b=p;b<d;++b)o[m].push(h[b+1]+g)}p=h[p],d=h[d]}d!==p&&(r.push([p,d]),s+=d-p)}return{outSplits:o,valueSlices:r,numValues:s}}function dq(e){let t=[];for(let n=0;n<e.length;++n){let a=e[n].length,r=v.getArrayFromDType("int32",a);t.push(r),e[n].forEach((s,i)=>r[i]=s)}return t}function iI(e,t){let n=e.slice(0,t);for(;n.length<t;)n.push(1);for(let a=t;a<e.length;a++)n[t-1]*=e[a];return n}function hq(e,t,n,a,r,s){let i=iI(t,2)[1],o=iI(s,2)[1],l=0;for(let u of n)for(let p=u[0];p<u[1];++p){for(let d=0;d<a;++d)r[l*o+d]=e[p*i+d];++l}}function mq(e,t,n,a,r){let s=t.slice();s[0]=r;let i=v.getArrayFromDType(n,v.sizeFromShape(s)),o=e.length,l=o===0?0:o/t[0];return hq(e,t,a,l,i,s),[i,s]}function DC(e,t,n,a,r,s,i,o){if(e.length===0)throw new Error("paramsNestedSplits must be non empty");if(t[0].length===0)throw new Error("Split tensors must not be scalars");let l=t[0][0]-1;if(uq(s,i,l),a.length===0)throw new Error("params.rank must be nonzero");let u=a[0],{outSplits:p,valueSlices:d,numValues:c}=cq(s,i,e,u),h=dq(p),m=mq(n,a,r,d,c);return[h,m[0],m[1]]}var oI=2147483647;function RC(e,t,n,a,r,s,i){if(t.length>1)throw new Error("starts must be a scalar or vector");if(r.length>1)throw new Error("limits must be a scalar or vector");if(i.length>1)throw new Error("deltas must be a scalar or vector");let o=t.length===0,l=r.length===0,u=i.length===0,p=[];o||p.push(t[0]),l||p.push(r[0]),u||p.push(i[0]);for(let g=1;g<p.length;++g)if(p[g]!==p[g-1])throw new Error("starts, limits, and deltas must have the same shape");let d=p.length===0?1:p[0],c=v.getArrayFromDType("int32",d+1);c[0]=0;for(let g=0;g<d;++g){let b=o?e[0]:e[g],y=l?a[0]:a[g],x=u?s[0]:s[g];if(x===0)throw new Error("Requires delta != 0");let w;if(x>0&&y<b||x<0&&y>b)w=0;else if(w=Math.ceil(Math.abs((y-b)/x)),w>oI)throw new Error(`Requires ((limit - start) / delta) <= ${oI}`);c[g+1]=c[g]+w}let h=c[d],m=v.getArrayFromDType(n,h),f=0;for(let g=0;g<d;++g){let b=c[g+1]-c[g],y=o?e[0]:e[g],x=u?s[0]:s[g];for(let w=0;w<b;++w)m[f++]=y,y+=x}return[c,m]}var Ta=N.RowPartitionType,cx=class{constructor(e,t,n,a,r,s,i,o,l,u){this.shape=e,this.shapeShape=t,this.values=n,this.valuesShape=a,this.valuesDType=r,this.defaultValue=s,this.defaultValueShape=i,this.rowPartitionValues=o,this.rowPartitionValuesShapes=l,this.rowPartitionTypes=N.getRowPartitionTypesHelper(u),this.raggedRank=N.getRaggedRank(this.rowPartitionTypes)}getRowPartitionTypeByDimension(e){return this.rowPartitionTypes[0]===Ta.FIRST_DIM_SIZE?this.rowPartitionTypes[e+1]:this.rowPartitionTypes[e]}getRowPartitionTensor(e){return this.rowPartitionTypes[0]===Ta.FIRST_DIM_SIZE?this.rowPartitionValues[e+1]:this.rowPartitionValues[e]}getMaxWidth(e){let t=this.getRowPartitionTensor(e-1);switch(this.getRowPartitionTypeByDimension(e-1)){case Ta.VALUE_ROWIDS:return cx.getMaxWidthValueRowID(t);case Ta.ROW_SPLITS:return cx.getMaxWidthRowSplit(t);default:throw new Error(`Cannot handle partition type ${Ta[this.getRowPartitionTypeByDimension(e-1)]}`)}}static getMaxWidthRowSplit(e){let t=e.length;if(t===0||t===1)return 0;let n=0;for(let a=0;a<t-1;++a){let r=e[a+1]-e[a];r>n&&(n=r)}return n}static getMaxWidthValueRowID(e){let t=e.length;if(t===0)return 0;let n=0,a=e[0],r=0;for(let s=1;s<t;++s){let i=e[s];i!==a&&(a=i,r=Math.max(s-n,r),n=s)}return Math.max(t-n,r)}tensorShapeFromTensor(e,t,n=!0){if(t.length===0){if(e[0]===-1)return[];throw new Error("The only valid scalar shape tensor is the fully unknown shape specified as -1.")}return uI(e,n)}calculateOutputSize(e){let t=this.valuesShape,n=this.defaultValueShape;N.validateDefaultValueShape(n,t);let a=this.tensorShapeFromTensor(this.shape,this.shapeShape),r=N.combineRaggedTensorToTensorShapes(this.raggedRank,a,t);r[0]<0&&(r[0]=e);for(let s=1;s<=this.raggedRank;++s)r[s]<0&&(r[s]=this.getMaxWidth(s));return r}calculateFirstParentOutputIndex(e,t,n){let a=Math.min(e,n),r=[],s=0;for(let i=0;i<a;++i,s+=t)r.push(s);for(let i=a;i<e;++i)r.push(-1);return v.assert(r.length===e,()=>"Final length of result must be equal to firstDimension."),r}calculateOutputIndexRowSplit(e,t,n,a){let r=e.length,s=[];for(let i=0;i<r-1;++i){let o=e[i+1]-e[i],l=Math.min(a,o),u=t[i];u===-1&&(l=0);for(let p=0;p<l;++p)s.push(u),u+=n;for(let p=0;p<o-l;++p)s.push(-1)}if(r>0&&s.length!==e[r-1])throw new Error("Invalid row split size.");return s}calculateOutputIndexValueRowID(e,t,n,a){let r=e.length,s=[];if(r===0)return[];let i=0,o=e[0];if(o>=t.length)throw new Error(`Got currentValueRowId=${o}, which is not less than ${t.length}`);let l=t[o];s.push(l);for(let u=1;u<r;++u){let p=e[u];if(p===o)l>=0&&(++i,i<a?l+=n:l=-1);else{if(i=0,o=p,p>=t.length)throw new Error(`Got nextValueRowId=${p} which is not less than ${t.length}`);l=t[p]}s.push(l)}if(s.length!==e.length)throw new Error("Invalid row ids.");return s}calculateOutputIndex(e,t,n,a){let r=this.getRowPartitionTensor(e),s=this.getRowPartitionTypeByDimension(e);switch(s){case Ta.VALUE_ROWIDS:return this.calculateOutputIndexValueRowID(r,t,n,a);case Ta.ROW_SPLITS:if(r.length-1>t.length)throw new Error(`Row partition size is greater than output size: ${r.length-1} > ${t.length}`);return this.calculateOutputIndexRowSplit(r,t,n,a);default:throw new Error(`Unsupported partition type: ${Ta[s]}`)}}getFirstDimensionSize(){let e=this.rowPartitionValues[0];if(this.rowPartitionTypes.length===0)throw new Error("No row_partition_types given.");let t=this.rowPartitionTypes[0];switch(t){case Ta.FIRST_DIM_SIZE:return e[0];case Ta.VALUE_ROWIDS:throw new Error("Cannot handle VALUE_ROWIDS in first dimension.");case Ta.ROW_SPLITS:return this.rowPartitionValuesShapes[0][0]-1;default:throw new Error(`Cannot handle type ${Ta[t]}`)}}compute(){if(this.rowPartitionValues[0].length<=0)throw new Error("Invalid first partition input. Tensor requires at least one element.");let e=this.getFirstDimensionSize(),t=this.calculateOutputSize(e),n=new Array(this.raggedRank+1);n[n.length-1]=1;for(let s=n.length-2;s>=0;--s)n[s]=n[s+1]*t[s+1];let a=uI(t,!1),r=v.getArrayFromDType(this.valuesDType,v.sizeFromShape(a));if(n[0]*t[0]>0){let s=this.calculateFirstParentOutputIndex(e,n[0],t[0]);for(let i=1;i<=this.raggedRank;++i)s=this.calculateOutputIndex(i-1,s,n[i],t[i]);this.setOutput(this.raggedRank,s,r,a)}return[a,r]}setOutput(e,t,n,a){if(n.length===0)return;let r=this.values,s=n,i=a.slice();i=i.slice(e+1);let o=v.sizeFromShape(i),l=t.length,u=this.defaultValue;if(u.length!==o&&u.length!==1){let h=this.defaultValueShape;P(()=>{let m=W(u,h);u=Xs(m,i).dataSync()})}let p=0,d=0,c=0;for(let h=0;h<=l;++h){let m=h<l?t[h]:-1;if(m===c){++c;continue}if(d<c){let f=r.subarray(p*o),g=s.subarray(d*o),b=(c-d)*o;lI(g,f,b)}if(h>=l){let f=n.length;m=Math.floor(f/o)}if(m>c)if(this.defaultValue.length===1)s.subarray(c*o,m*o).fill(this.defaultValue[0]),c=m;else for(;m>c;){let f=s.slice(c*o);lI(f,u,o),++c}m<0?(p=h+1,d=c):(p=h,d=c,c=d+1)}}};function lI(e,t,n){for(let a=0;a<n;a++)e[a]=t[a]}function uI(e,t){let n=[];for(let a of e){if(a<0){if(!t)throw new Error(`Dimension ${a} must be >= 0`);if(a<-1)throw new Error(`Dimension ${a} must be >= -1`);a=-1}n.push(a)}return n}function MC(e,t,n,a,r,s,i,o,l,u){return new cx(e,t,n,a,r,s,i,o,l,u).compute()}function W0(e,t,n,a){let r=e===t,s=e<t&&n<0,i=t<e&&n>1;if(r||s||i)return v.makeZerosTypedArray(0,a);let o=Math.abs(Math.ceil((t-e)/n)),l=v.makeZerosTypedArray(o,a);t<e&&n===1&&(n=-1),l[0]=e;for(let u=1;u<l.length;u++)l[u]=l[u-1]+n;return l}var PC=Cs(e=>1/Math.sqrt(e)),fq=Ku(no,PC),gq={kernelName:no,backendName:"cpu",kernelFunc:fq};function ll(e,t,n,a,r,s,i,o,l,u){let p=[a/r,r],d=e.values,c=t.values;if(a===0)return Oe(n,t.dtype);let h=Oe(p,t.dtype);typeof l=="string"||typeof l=="number"?h.values.fill(l):typeof l=="boolean"&&h.values.fill(+l);for(let m=0;m<s;m++){let f=[],g=0;for(let b=0;b<i;b++){let y=d[m*i+b];f.push(y),g+=y*o[b]}if(g<0||g>=a/r)throw new Error(`Invalid indices: ${f} does not index into ${n}`);for(let b=0;b<r;b++)u?h.values[g*r+b]+=c[m*r+b]:h.values[g*r+b]=t.rank===0?c[0]:c[m*r+b]}return h}var bq=Cs(e=>1/(1+Math.exp(-e))),OC=rt(ro,e=>1/(1+Math.exp(-e))),yq={kernelName:ro,backendName:"cpu",kernelFunc:OC};function Jh(e,t,n,a,r){let s=jt.isSliceContinous(a,t,n),i=v.sizeFromShape(n),o=v.computeStrides(a);if(s){let d=jt.computeFlatOffset(t,o);return r==="string"?e.slice(d,d+i):e.subarray(d,d+i)}let l=r==="string"?N.fromUint8ToStringArray(e):e,u=Oe(a,r,l),p=Oe(n,r);for(let d=0;d<p.size;++d){let c=p.indexToLoc(d),h=c.map((m,f)=>m+t[f]);p.set(u.get(...h),...c)}return r==="string"?N.fromStringArrayToUint8(p.values):p.values}function pi(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{begin:s,size:i}=a;ge(r,"slice");let[o,l]=jt.parseSliceParams(r,s,i);jt.assertParamsValid(r,o,l);let u=n.data.get(r.dataId).values,p=Jh(u,o,l,r.shape,r.dtype);return n.makeTensorInfo(l,r.dtype,p)}var xq={kernelName:Su,backendName:"cpu",kernelFunc:pi};function LC(e,t,n,a,r,s,i){let o=t[0],l=s[0],u=new Array(l),p=new Array(o),d=t[1];if(l===0){if(o!==0)throw new Error(N.getSparseFillEmptyRowsIndicesDenseShapeMismatch(o));let g=v.getArrayFromDType(n,0),b=v.getArrayFromDType(r,0);return[g,[0,d],b,u,p]}let c=!0,h=0,m=new Array(l).fill(0);for(let g=0;g<o;++g){let b=e[g*d];if(b<0)throw new Error(N.getSparseFillEmptyRowsNegativeIndexErrorMessage(g,b));if(b>=l)throw new Error(N.getSparseFillEmptyRowsOutOfRangeIndexErrorMessage(g,b,l));++m[b],c=c&&b>=h,h=b}let f=!0;for(let g=0;g<l;++g){let b=m[g]===0;u[g]=b,f=f&&!b,m[g]=Math.max(m[g],1),g>0&&(m[g]+=m[g-1])}if(f&&c){let g=e,b=a;for(let y=0;y<o;++y)p[y]=y;return[g,[o,d],b,u,p]}else{let g=m[l-1],b=v.getArrayFromDType(n,g*d),y=v.getArrayFromDType(r,g),x=new Array(l).fill(0);for(let w=0;w<o;++w){let I=e[w*d],T=x[I],C=(I===0?0:m[I-1])+T;x[I]++;for(let E=0;E<d;++E)b[C*d+E]=e[w*d+E];y[C]=a[w],p[w]=C}for(let w=0;w<l;++w)if(x[w]===0){let I=w===0?0:m[w-1];b[I*d+0]=w;for(let T=1;T<d;++T)b[I*d+T]=0;y[I]=i}return[b,[g,d],y,u,p]}}function zC(e,t,n,a,r){let s=v.sizeFromShape(a),i=t[0],o=r.length,l=[],u=1,p=-1;for(let f=0;f<o;++f){let g=r[f];if(g===-1){if(p!==-1)throw new Error(N.getSparseReshapeMultipleNegativeOneOutputDimErrorMessage(p,f));p=f,l.push(1)}else{if(g<0)throw new Error(N.getSparseReshapeNegativeOutputDimErrorMessage(f,g));u*=g,l.push(g)}}if(p!==-1){if(u<=0)throw new Error(N.getSparseReshapeEmptyTensorZeroOutputDimErrorMessage());let f=Math.trunc(s/u);if(u*f!==s)throw new Error(N.getSparseReshapeInputOutputMultipleErrorMessage(a,l));l[p]=f}if(v.sizeFromShape(l)!==s)throw new Error(N.getSparseReshapeInputOutputMismatchErrorMessage(a,l));let d=a.length,c=[];if(d>0){c[d-1]=1;for(let f=d-2;f>=0;--f)c[f]=c[f+1]*a[f+1]}let h=[];if(o>0){h[o-1]=1;for(let f=o-2;f>=0;--f)h[f]=h[f+1]*l[f+1]}let m=v.getArrayFromDType(n,i*o);for(let f=0;f<i;++f){let g=0;for(let b=0;b<d;++b)g+=e[f*d+b]*c[b];for(let b=0;b<o;++b)m[f*o+b]=Math.trunc(g/h[b]),g%=h[b]}return[m,[i,o],l]}function B0(e,t,n,a,r,s=!1,i=0){let o=a.length,l=[t[0],e.length/t[0]],u=l[1],p=o>0?r[o-1]+1:0;if(p<0)throw new Error(N.getSparseSegmentReductionNegativeSegmentIdsErrorMessage());let d=t.slice();d[0]=p;let c=d.reduce((y,x)=>y*x,1),h=v.getArrayFromDType(n,c);if(o===0)return p>0&&h.fill(i),[h,d];if(p<=0)throw new Error(N.getSparseSegmentReductionNegativeSegmentIdsErrorMessage());let m=0,f=1,g=0,b=r[m];for(;;){let y=0;if(f<o){if(y=r[f],b===y){++f;continue}if(b>=y)throw new Error(N.getSparseSegmentReductionNonIncreasingSegmentIdsErrorMessage())}if(b<0||b>=p)throw new Error(N.getSparseSegmentReductionSegmentIdOutOfRangeErrorMessage(b,p));b>g&&h.fill(i,g*u,b*u);for(let x=m;x<f;++x){let w=a[x];if(w<0||w>=l[0])throw new Error(N.getSparseSegmentReductionIndicesOutOfRangeErrorMessage(x,a[x],l[0]));for(let I=0;I<u;I++)h[b*u+I]+=e[w*u+I]}if(s)for(let x=0;x<u;x++)h[b*u+x]/=f-m;if(m=f,++f,g=b+1,b=y,f>o)break}return g<p&&h.fill(i,g*u,p*u),[h,d]}var vq=Cs(e=>Math.sqrt(e)),wq=rt(so,e=>Math.sqrt(e)),kq={kernelName:so,backendName:"cpu",kernelFunc:wq},WC=Vt((e,t)=>{let n=e-t;return n*n}),Iq=nn(lo,WC),Sq={kernelName:lo,backendName:"cpu",kernelFunc:Iq};function BC(e,t,n,a){let r=Oe(e,t.dtype);for(let s=0;s<r.size;s++){let i=r.indexToLoc(s),o=new Array(i.length);for(let l=0;l<o.length;l++)o[l]=i[l]*n[l]+a[l];r.set(t.get(...o),...i)}return r}var Tq=class{constructor(e,t,n,a,r,s){this.separator=v.encodeString(e),this.nGramWidths=t,this.leftPad=v.encodeString(n),this.rightPad=v.encodeString(a),this.padWidth=r,this.preserveShort=s}getPadWidth(e){return Math.min(this.padWidth<0?e-1:this.padWidth,e-1)}getNumNGrams(e,t){let n=this.getPadWidth(t);return Math.max(0,e+2*n-t+1)}createNGrams(e,t,n,a,r,s){for(let i=0;i<r;++i){let o=this.getPadWidth(s),l=Math.max(0,o-i),u=Math.max(0,o-(r-(i+1))),p=s-(l+u),d=t+(l>0?0:i-o),c=0;c+=l*this.leftPad.length;for(let g=0;g<p;++g)c+=e[d+g].length;c+=u*this.rightPad.length,c+=(l+u+p-1)*this.separator.length,n[a+i]=new Uint8Array(c);let h=n[a+i],m=0,f=g=>g.forEach(b=>h[m++]=b);for(let g=0;g<l;++g)f(this.leftPad),f(this.separator);for(let g=0;g<p-1;++g)f(e[d+g]),f(this.separator);if(p>0){f(e[d+p-1]);for(let g=0;g<u;++g)f(this.separator),f(this.rightPad)}else{for(let g=0;g<u-1;++g)f(this.rightPad),f(this.separator);f(this.rightPad)}}}compute(e,t){let n=e.length,a=t.length;if(a>0){let o=t[0];if(o!==0)throw new Error(`First split value must be 0, got ${o}`);for(let l=1;l<a;++l){let u=t[l]>=o;if(u=u&&t[l]<=n,!u)throw new Error(`Invalid split value ${t[l]}, must be in [${o}, ${n}]`);o=t[l]}if(o!==n)throw new Error(`Last split value must be data size. Expected ${n}, got ${o}`)}let r=a-1,s=v.getArrayFromDType("int32",a);if(n===0||a===0){let o=new Array(n);for(let l=0;l<=r;++l)s[l]=0;return[o,s]}s[0]=0;for(let o=1;o<=r;++o){let l=t[o]-t[o-1],u=0;this.nGramWidths.forEach(p=>{u+=this.getNumNGrams(l,p)}),this.preserveShort&&l>0&&u===0&&(u=1),s[o]=s[o-1]+u}let i=new Array(s[r]);for(let o=0;o<r;++o){let l=t[o],u=s[o];if(this.nGramWidths.forEach(p=>{let d=t[o+1]-t[o],c=this.getNumNGrams(d,p);this.createNGrams(e,l,i,u,c,p),u+=c}),this.preserveShort&&u===s[o]){let p=t[o+1]-t[o];if(p===0)continue;let d=p+2*this.padWidth,c=1;this.createNGrams(e,l,i,u,c,d)}}return[i,s]}};function V0(e,t,n,a,r,s,i,o){return new Tq(n,a,r,s,i,o).compute(e,t)}function Nq(e,t,n,a){if(!e.length)return;if(t.length===0){for(let s=0;s<e.length;++s)a.push(e.subarray(s,s+1));return}if(t.length===1){let s=t[0],i=e.indexOf(s);for(;i!==-1;){let o=e.subarray(0,i);(!n||o.length!==0)&&a.push(o),e=e.subarray(i+1),i=e.indexOf(s)}(!n||e.length!==0)&&a.push(e);return}let r=0;for(let s=0;s<e.length+1;s++)if(s===e.length||t.indexOf(e[s])!==-1){let i=e.subarray(r,s);(!n||i.length!==0)&&a.push(i),r=s+1}}function U0(e,t,n){let a=e.length,r=[],s=0,i=0,o=new Array(a);for(let c=0;c<a;++c){let h=r.length;Nq(e[c],t,n,r);let m=r.length-h;o[c]=m,s+=m,i=Math.max(i,m)}let l=v.getArrayFromDType("int32",s*2),u=new Array(s),p=[a,i],d=0;for(let c=0;c<a;++c)for(let h=0;h<o[c];++h)l[d*2]=c,l[d*2+1]=h,u[d]=r[d],++d;return[l,u,p]}function G0(e,t){let n=v.getArrayFromDType("int32",e.length);for(let a=0;a<e.length;++a)n[a]=v.fingerPrint64(e[a]).modulo(t).getLowBitsUnsigned();return n}var VC=Vt((e,t)=>e-t),Cq=M0((e,t,n,a)=>({real:e-n,imag:t-a})),H0=nn(uo,VC,Cq),_q={kernelName:uo,backendName:"cpu",kernelFunc:H0};function UC(e,t){let n=new Array(e.rank);for(let r=0;r<n.length;r++)n[r]=e.shape[r]*t[r];let a=Oe(n,e.dtype);for(let r=0;r<a.values.length;++r){let s=a.indexToLoc(r),i=new Array(e.rank);for(let l=0;l<i.length;l++)i[l]=s[l]%e.shape[l];let o=e.locToIndex(i);a.values[r]=e.values[o]}return a}var Op=(e,t)=>{let n=t.value-e.value;return n===0?e.index-t.index:n};function GC(e,t,n=0,a=e.length-1){for(;a>n;){if(a-n>600){let o=a-n+1,l=t-n+1,u=Math.log(o),p=.5*Math.exp(2*u/3),d=.5*Math.sqrt(u*p*(o-p)/o)*Math.sign(l-o/2),c=Math.max(n,Math.floor(t-l*p/o+d)),h=Math.min(a,Math.floor(t+(o-l)*p/o+d));GC(e,t,c,h)}let r=e[t],s=n,i=a;for(v.swap(e,n,t),Op(e[a],r)>0&&v.swap(e,n,a);s<i;){for(v.swap(e,s,i),s++,i--;Op(e[s],r)<0;)s=s+1;for(;Op(e[i],r)>0;)i=i-1}Op(e[n],r)===0?v.swap(e,n,i):(i=i+1,v.swap(e,i,a)),i<=t&&(n=i+1),t<=i&&(a=i-1)}}function HC(e,t,n,a,r){let s=t[t.length-1],[i,o]=[e.length/s,s],l=v.getTypedArrayFromDType(n,i*a),u=v.getTypedArrayFromDType("int32",i*a);for(let d=0;d<i;d++){let c=d*o,h=e.subarray(c,c+o),m=new Array(h.length);h.forEach((y,x)=>m[x]={value:y,index:x}),a<m.length&&(GC(m,a),m=m.slice(0,a)),r&&m.sort(Op);let f=d*a,g=l.subarray(f,f+a),b=u.subarray(f,f+a);for(let y=0;y<a;y++)g[y]=m[y].value,b[y]=m[y].index}let 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i=v.sizeFromShape(r.shape),o=n.data.get(r.dataId).values,l=v.getTypedArrayFromDType("float32",i);for(let u=0;u<o.length;u++)l[u]=o[u]<0?s*o[u]:o[u];return n.makeTensorInfo(r.shape,"float32",l)}var Aq={kernelName:Mi,backendName:"cpu",kernelFunc:KC},$q=Vt((e,t)=>e<0?t*e:e);function XC(e){let{inputs:t,backend:n}=e,{x:a,alpha:r}=t;ge([a,r],"prelu");let s=n.data.get(a.dataId).values,i=n.data.get(r.dataId).values,[o,l]=$q(a.shape,r.shape,s,i,"float32");return n.makeTensorInfo(l,"float32",o)}var Fq={kernelName:Ki,backendName:"cpu",kernelFunc:XC},YC=rt(Yi,e=>Math.max(0,e)),Dq={kernelName:Yi,backendName:"cpu",kernelFunc:YC},ZC=rt(Qi,e=>Math.min(Math.max(0,e),6)),Rq={kernelName:Qi,backendName:"cpu",kernelFunc:ZC};function Qh(e,t,n,a,r){if(n==="linear")return pr({inputs:{x:t},backend:e});if(n==="relu")return YC({inputs:{x:t},backend:e});if(n==="elu")return qC({inputs:{x:t},backend:e});if(n==="relu6")return ZC({inputs:{x:t},backend:e});if(n==="prelu")return 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x=i?[g,p,c]:[g,c,p],w=o?[b,h,d]:[b,d,h],I=ft({inputs:{x:r},backend:n,attrs:{shape:x}}),T=ft({inputs:{x:s},backend:n,attrs:{shape:w}}),C=i?I.shape[1]:I.shape[2],E=i?I.shape[2]:I.shape[1],A=o?T.shape[1]:T.shape[2],R=Math.max(g,b),F=n.data.get(I.dataId).values,S=n.data.get(T.dataId).values,M=v.computeStrides(I.shape),B=v.computeStrides(T.shape),[U,G,q]=i?[M[0],1,M[1]]:[M[0],M[1],1],[K,Z,Q]=o?[1,B[1],B[0]]:[B[1],1,B[0]],ee=E*A,ae=Oe([R,E,A],I.dtype),te=ae.values,le=n.blockSize;for(let ie=0;ie<R;ie++)for(let be=0;be<E;be+=le)for(let ue=0;ue<A;ue+=le)for(let xe=0;xe<C;xe+=le){let Ie=Math.min(be+le,E),Se=Math.min(ue+le,A),Le=Math.min(xe+le,C);for(let Ve=be;Ve<Ie;Ve++)for(let nt=ue;nt<Se;nt++){let it=0;for(let et=xe;et<Le;et++){let at=Math.min(ie,g-1)*U,ze=Math.min(ie,b-1)*Q,dt=F[at+Ve*G+et*q],jn=S[et*K+nt*Z+ze];it+=dt*jn}te[ie*ee+(Ve*A+nt)]+=it}}return n.disposeIntermediateTensorInfo(I),n.disposeIntermediateTensorInfo(T),n.makeTensorInfo(y,ae.dtype,ae.values)}var Pq={kernelName:yi,backendName:"cpu",kernelFunc:JC};function Oq(e){let{inputs:t,backend:n,attrs:a}=e,{a:r,b:s,bias:i,preluActivationWeights:o}=t,{transposeA:l,transposeB:u,activation:p,leakyreluAlpha:d}=a,c,h,m,f=[];c=JC({inputs:{a:r,b:s},attrs:{transposeA:l,transposeB:u},backend:n}),i&&(h=_l({inputs:{a:c,b:i},backend:n}),f.push(c),c=h),p&&(m=Qh(n,c,p,o,d),f.push(c),c=m);for(let g of f)n.disposeIntermediateTensorInfo(g);return c}var Lq={kernelName:Qs,backendName:"cpu",kernelFunc:Oq},zq=rt(Rl,e=>Math.acos(e)),Wq={kernelName:Rl,backendName:"cpu",kernelFunc:zq},Bq=rt(Ml,e=>Math.acosh(e)),Vq={kernelName:Ml,backendName:"cpu",kernelFunc:Bq};function Uq(e){let{inputs:t,backend:n}=e,a=t;ge(t,"addN");let r=a.map(o=>n.data.get(o.dataId).values),s=Oe(a[0].shape,a[0].dtype),i=s.values;for(let o=0;o<a.length;o++){let l=r[o];for(let u=0;u<i.length;u++)i[u]+=l[u]}return n.makeTensorInfo(s.shape,s.dtype,s.values)}var Gq={kernelName:fi,backendName:"cpu",kernelFunc:Uq};function 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U=B-C,G=f.get(g,S,B,b);G>R&&(R=G,r?F=s?((g*a.inHeight+S)*a.inWidth+B)*a.inChannels+b:(S*a.inWidth+B)*a.inChannels+b:F=M*c+U)}}i.set(F,g,y,T,b)}}return i}function e_(e,t,n,a,r,s){let i=r.strideDepth,o=r.strideHeight,l=r.strideWidth,u=r.dilationDepth,p=r.dilationHeight,d=r.dilationWidth,c=r.effectiveFilterDepth,h=r.effectiveFilterHeight,m=r.effectiveFilterWidth,f=r.padInfo.front,g=r.padInfo.top,b=r.padInfo.left,y=s==="max"?Number.NEGATIVE_INFINITY:Number.POSITIVE_INFINITY,x=Oe(r.outShape,n),w=x.values,I=r.outShape[1]*r.outShape[2]*r.outShape[3]*r.outShape[4],T=r.outShape[2]*r.outShape[3]*r.outShape[4],C=r.outShape[3]*r.outShape[4],E=r.outShape[4];for(let A=0;A<r.batchSize;++A){let R=A*I,F=A*a[0];for(let S=0;S<r.inChannels;++S)for(let M=0;M<r.outDepth;++M){let B=M*i-f,U=B;for(;U<0;)U+=u;let G=Math.min(r.inDepth,c+B),q=R+M*T;for(let K=0;K<r.outHeight;++K){let Z=K*o-g,Q=Z;for(;Q<0;)Q+=p;let ee=Math.min(r.inHeight,h+Z),ae=q+K*C;for(let te=0;te<r.outWidth;++te){let le=te*l-b,ie=le;for(;ie<0;)ie+=d;let be=Math.min(r.inWidth,m+le),ue=ae+te*E,xe=y,Ie=0,Se=0;for(let Ve=U;Ve<G;Ve+=u){let nt=F+Ve*a[1];for(let it=Q;it<ee;it+=p){let et=nt+it*a[2];for(let at=ie;at<be;at+=d){let ze=et+at*a[3],dt=e[ze+S];if(s==="max"&&dt>xe?xe=dt:s==="avg"&&(Ie+=dt,Se++),isNaN(xe))break}if(isNaN(xe))break}if(isNaN(xe))break}let Le=ue+S;w[Le]=s==="avg"?Ie/Se:xe}}}}return x}function p5(e,t){let n=Oe(t.outShape,"int32"),a=t.strideDepth,r=t.strideHeight,s=t.strideWidth,i=t.dilationDepth,o=t.dilationHeight,l=t.dilationWidth,u=t.effectiveFilterDepth,p=t.effectiveFilterHeight,d=t.effectiveFilterWidth,c=t.padInfo.front,h=t.padInfo.top,m=t.padInfo.left;for(let f=0;f<t.batchSize;++f)for(let g=0;g<t.inChannels;++g)for(let b=0;b<t.outDepth;++b){let y=b*a-c,x=y;for(;x<0;)x+=i;let w=Math.min(t.inDepth,u+y);for(let I=0;I<t.outHeight;++I){let T=I*r-h,C=T;for(;C<0;)C+=o;let E=Math.min(t.inHeight,p+T);for(let A=0;A<t.outWidth;++A){let R=A*s-m,F=R;for(;F<0;)F+=l;let S=Math.min(t.inWidth,d+R),M=Number.NEGATIVE_INFINITY,B=-1;for(let U=x;U<w;U+=i){let G=U-y;for(let q=C;q<E;q+=o){let K=q-T;for(let Z=F;Z<S;Z+=l){let Q=Z-R,ee=e.get(f,U,q,Z,g);ee>=M&&(M=ee,B=G*p*d+K*p+Q)}}}n.set(B,f,b,I,A,g)}}}return n}function c5(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t;ge(r,"avgPool");let{filterSize:s,strides:i,pad:o,dimRoundingMode:l}=a,u=1;v.assert(N.eitherStridesOrDilationsAreOne(i,u),()=>`Error in avgPool: Either strides or dilations must be 1. 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p=N.computePool3DInfo(s.shape,i,o,1,l,u),d=p.strideDepth,c=p.strideHeight,h=p.strideWidth,m=p.filterDepth,f=p.filterHeight,g=p.filterWidth,b=p.dilationDepth,y=p.dilationHeight,x=p.dilationWidth,w=p.effectiveFilterDepth,I=p.effectiveFilterHeight,T=p.effectiveFilterWidth,C=w-1-p.padInfo.front,E=T-1-p.padInfo.left,A=I-1-p.padInfo.top,R=Oe(s.shape,"float32"),F=1/(m*f*g),S=n.bufferSync(r);for(let M=0;M<p.batchSize;++M)for(let B=0;B<p.inChannels;++B)for(let U=0;U<p.inDepth;++U)for(let G=0;G<p.inHeight;++G)for(let q=0;q<p.inWidth;++q){let K=U-C,Z=G-A,Q=q-E,ee=0;for(let ae=0;ae<w;ae+=b){let te=(K+ae)/d;if(!(te<0||te>=p.outDepth||Math.floor(te)!==te))for(let le=0;le<I;le+=y){let ie=(Z+le)/c;if(!(ie<0||ie>=p.outHeight||Math.floor(ie)!==ie))for(let be=0;be<T;be+=x){let ue=(Q+be)/h;ue<0||ue>=p.outWidth||Math.floor(ue)!==ue||(ee+=S.get(M,te,ie,ue,B))}}}R.set(ee*F,M,U,G,q,B)}return n.makeTensorInfo(R.shape,R.dtype,R.values)}var g5={kernelName:cm,backendName:"cpu",kernelFunc:f5};function b5(e){let{inputs:t,backend:n,attrs:a}=e,{dy:r,input:s}=t,i=s;ge([r,s],"avgPoolGrad");let{filterSize:o,strides:l,pad:u}=a,p=N.computePool2DInfo(i.shape,o,l,1,u),d=p.strideHeight,c=p.strideWidth,h=p.filterHeight,m=p.filterWidth,f=p.dilationHeight,g=p.dilationWidth,b=p.effectiveFilterHeight,y=p.effectiveFilterWidth,x=y-1-p.padInfo.left,w=b-1-p.padInfo.top,I=Oe(i.shape,"float32"),T=1/(h*m),C=n.data.get(r.dataId).values,E=Oe(r.shape,"float32",C);for(let A=0;A<p.batchSize;++A)for(let R=0;R<p.inChannels;++R)for(let F=0;F<p.inHeight;++F)for(let S=0;S<p.inWidth;++S){let M=F-w,B=S-x,U=0;for(let G=0;G<b;G+=f){let q=(M+G)/d;if(!(q<0||q>=p.outHeight||Math.floor(q)!==q))for(let K=0;K<y;K+=g){let Z=(B+K)/c;Z<0||Z>=p.outWidth||Math.floor(Z)!==Z||(U+=E.get(A,q,Z,R))}}I.set(U*T,A,F,S,R)}return n.makeTensorInfo(I.shape,I.dtype,I.values)}var y5={kernelName:pm,backendName:"cpu",kernelFunc:b5};function 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n.makeTensorInfo(r.shape,r.dtype,f)}var v5={kernelName:Fi,backendName:"cpu",kernelFunc:x5};function w5(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{blockShape:s,crops:i}=a;ge([r],"batchToSpaceND");let o=s.reduce((b,y)=>b*y),l=N.getReshaped(r.shape,s,o),u=N.getPermuted(l.length,s.length),p=N.getReshapedPermuted(r.shape,s,o),d=N.getSliceBeginCoords(i,s.length),c=N.getSliceSize(p,i,s.length),h=ft({inputs:{x:r},backend:n,attrs:{shape:l}}),m=Vn({inputs:{x:h},backend:n,attrs:{perm:u}}),f=ft({inputs:{x:m},backend:n,attrs:{shape:p}}),g=pi({inputs:{x:f},backend:n,attrs:{begin:d,size:c}});return n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(f),g}var k5={kernelName:Ul,backendName:"cpu",kernelFunc:w5};function I5(e){let{inputs:t,backend:n,attrs:a}=e,{x:r,weights:s}=t,{size:i}=a,o=n.data.get(r.dataId).values,l=n.data.get(s.dataId).values,u=P0(o,l,s.dtype,s.shape,i);return n.makeTensorInfo([i],s.dtype,u)}var S5={kernelName:dm,backendName:"cpu",kernelFunc:I5};function T5(e){let{inputs:t,backend:n}=e,{s0:a,s1:r}=t,s=n.data.get(a.dataId).values,i=n.data.get(r.dataId).values,o=N.assertAndGetBroadcastShape(Array.from(s),Array.from(i));return n.makeTensorInfo([o.length],"int32",Int32Array.from(o))}var N5={kernelName:hm,backendName:"cpu",kernelFunc:T5},C5=rt(bs,(e,t)=>{let n=t;return e>n.clipValueMax?n.clipValueMax:e<n.clipValueMin?n.clipValueMin:e}),_5={kernelName:bs,backendName:"cpu",kernelFunc:C5},E5=e=>{let{x:t}=e.inputs,n=e.backend,a=new Float32Array(v.sizeFromShape(t.shape)),r=n.data.get(t.dataId),s=r.complexTensorInfos.real,i=r.complexTensorInfos.imag,o=n.data.get(s.dataId).values,l=n.data.get(i.dataId).values;for(let u=0;u<o.length;u++){let p=o[u],d=l[u];a[u]=Math.hypot(p,d)}return n.makeOutput(a,t.shape,"float32")},A5={kernelName:hc,backendName:"cpu",kernelFunc:E5};function El(e){let{inputs:t,backend:n}=e,{input:a}=t,r=n.data.get(a.dataId).complexTensorInfos.imag,s=n.data.get(r.dataId).values;return n.makeTensorInfo(r.shape,r.dtype,s)}var $5={kernelName:Nm,backendName:"cpu",kernelFunc:El};function Al(e){let{inputs:t,backend:n,attrs:a}=e,{axis:r}=a,s=v.parseAxisParam(r,t[0].shape)[0],i=t.map(f=>f.shape);N.assertParamsConsistent(i,s);let o=N.computeOutShape(t.map(f=>f.shape),s);if(v.sizeFromShape(o)===0)return n.makeTensorInfo(o,t[0].dtype,[]);let l=t.filter(f=>v.sizeFromShape(f.shape)>0);if(l.length===1)return pr({inputs:{x:l[0]},backend:n});if(l[0].dtype==="complex64"){let f=l.map(w=>ui({inputs:{input:w},backend:n})),g=l.map(w=>El({inputs:{input:w},backend:n})),b=Al({inputs:f,backend:n,attrs:{axis:s}}),y=Al({inputs:g,backend:n,attrs:{axis:s}}),x=Zn({inputs:{real:b,imag:y},backend:n});return 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R5(e){let{inputs:t,backend:n,attrs:a}=e,{x:r,dy:s}=t,{strides:i,pad:o,dataFormat:l,dimRoundingMode:u,filterShape:p}=a;ge([r,s],"conv2dBackpropFilter");let d=N.convertConv2DDataFormat(l),c=N.computeConv2DInfo(r.shape,p,i,1,o,u,!1,d),{strideHeight:h,strideWidth:m,filterHeight:f,filterWidth:g}=c,b=c.dataFormat==="channelsLast",y=new Ht(c.filterShape,"float32"),x=c.padInfo.left,w=c.padInfo.top,I=n.data.get(r.dataId).values,T=n.data.get(s.dataId).values,C=new Ht(r.shape,r.dtype,I),E=new Ht(s.shape,s.dtype,T);for(let A=0;A<f;++A){let R=Math.max(0,Math.ceil((w-A)/h)),F=Math.min(c.outHeight,(c.inHeight+w-A)/h);for(let S=0;S<g;++S){let M=Math.max(0,Math.ceil((x-S)/m)),B=Math.min(c.outWidth,(c.inWidth+x-S)/m);for(let U=0;U<c.inChannels;++U)for(let G=0;G<c.outChannels;++G){let q=0;for(let K=0;K<c.batchSize;++K)for(let Z=R;Z<F;++Z){let Q=A+Z*h-w;for(let ee=M;ee<B;++ee){let ae=S+ee*m-x;b?q+=C.get(K,Q,ae,U)*E.get(K,Z,ee,G):q+=C.get(K,U,Q,ae)*E.get(K,G,Z,ee)}}y.set(q,A,S,U,G)}}}return n.makeTensorInfo(y.shape,y.dtype,y.values)}var M5={kernelName:fm,backendName:"cpu",kernelFunc:R5};function P5(e){let{inputs:t,backend:n,attrs:a}=e,{dy:r,filter:s}=t,{inputShape:i,strides:o,pad:l,dataFormat:u,dimRoundingMode:p}=a;ge([r,s],"conv2dBackpropInput");let d=v.computeStrides(s.shape),c=v.computeStrides(r.shape),h=N.convertConv2DDataFormat(u),m=N.computeConv2DInfo(i,s.shape,o,1,l,p,!1,h),f=new Ht(m.inShape,"float32"),g=f.values,b=n.data.get(r.dataId).values,y=n.data.get(s.dataId).values,[x,w,I]=d,{batchSize:T,filterHeight:C,filterWidth:E,inChannels:A,inHeight:R,inWidth:F,outChannels:S,outHeight:M,outWidth:B,strideHeight:U,strideWidth:G}=m;h=m.dataFormat;let q=C-1-m.padInfo.top,K=E-1-m.padInfo.left,Z=h==="channelsLast",Q=f.strides[0],ee=Z?f.strides[1]:f.strides[2],ae=Z?f.strides[2]:1,te=Z?1:f.strides[1],le=c[0],ie=Z?c[1]:c[2],be=Z?c[2]:1,ue=Z?1:c[1];for(let xe=0;xe<T;++xe)for(let Ie=0;Ie<A;++Ie)for(let Se=0;Se<R;++Se){let 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F=R*E[0],S=R*w.strides[0];for(let M=0;M<u.outDepth;++M){let B=S+M*w.strides[1],U=M*u.strideDepth-b;for(let G=0;G<p;++G){let q=U+G*h;if(q<0||q>=u.inDepth)continue;let K=G*A[0],Z=F+q*E[1];for(let Q=0;Q<u.outHeight;++Q){let ee=B+Q*w.strides[2],ae=Q*u.strideHeight-x;for(let te=0;te<d;++te){let le=ae+te*m;if(le<0||le>=u.inHeight)continue;let ie=K+te*A[1],be=Z+le*E[2];for(let ue=0;ue<u.outWidth;++ue){let xe=ee+ue*u.outChannels,Ie=ue*u.strideWidth-y;for(let Se=0;Se<c;++Se){let Le=Ie+Se*f;if(Le<0||Le>=u.inWidth)continue;let Ve=ie+Se*A[2],nt=be+Le*u.inChannels,it=Ve;for(let et=0;et<u.inChannels;++et){let at=I[nt+et];for(let ze=0;ze<u.outChannels;++ze)C[xe+ze]+=at*T[it+ze];it+=u.outChannels}}}}}}}}return n.makeTensorInfo(w.shape,w.dtype,w.values)}var z5={kernelName:mc,backendName:"cpu",kernelFunc:L5};function W5(e){let{inputs:t,backend:n,attrs:a}=e,{x:r,dy:s}=t,{strides:i,pad:o,filterShape:l}=a;ge([r,s],"conv3dBackpropFilterV2");let u=v.computeStrides(r.shape),p=v.computeStrides(s.shape),d=N.computeConv3DInfo(r.shape,l,i,1,o),c=d.strideDepth,h=d.strideHeight,m=d.strideWidth,f=d.filterDepth,g=d.filterHeight,b=d.filterWidth,y=new Ht(d.filterShape,"float32"),x=y.values,[w,I,T,C]=y.strides,E=n.data.get(s.dataId).values,[A,R,F,S]=p,M=n.data.get(r.dataId).values,[B,U,G,q]=u,K=d.padInfo.front,Z=d.padInfo.left,Q=d.padInfo.top;for(let ee=0;ee<f;++ee){let ae=Math.max(0,Math.ceil((K-ee)/c)),te=Math.min(d.outDepth,(d.inDepth+K-ee)/c),le=ee*w;for(let ie=0;ie<g;++ie){let be=Math.max(0,Math.ceil((Q-ie)/h)),ue=Math.min(d.outHeight,(d.inHeight+Q-ie)/h),xe=ie*I+le;for(let Ie=0;Ie<b;++Ie){let Se=Math.max(0,Math.ceil((Z-Ie)/m)),Le=Math.min(d.outWidth,(d.inWidth+Z-Ie)/m),Ve=Ie*T+xe;for(let nt=0;nt<d.inChannels;++nt){let it=nt*C+Ve;for(let et=0;et<d.outChannels;++et){let at=0;for(let ze=0;ze<d.batchSize;++ze){let dt=ze*B,jn=ze*A;for(let Mt=ae;Mt<te;++Mt){let ia=(ee+Mt*c-K)*U+dt,on=Mt*R+jn;for(let Fn=be;Fn<ue;++Fn){let oa=(ie+Fn*h-Q)*G+ia,Dn=Fn*F+on;for(let ot=Se;ot<Le;++ot){let Rn=(Ie+ot*m-Z)*q+oa,qn=ot*S+Dn;at+=M[Rn+nt]*E[qn+et]}}}}x[it+et]=at}}}}}return n.makeTensorInfo(y.shape,y.dtype,y.values)}var B5={kernelName:gm,backendName:"cpu",kernelFunc:W5};function V5(e){let{inputs:t,backend:n,attrs:a}=e,{dy:r,filter:s}=t,{pad:i,strides:o,inputShape:l}=a;ge([r],"conv3dBackpropInputV2");let u=v.computeStrides(r.shape),p=v.computeStrides(s.shape),d=N.computeConv3DInfo(l,s.shape,o,1,i),c=new Ht(d.inShape,"float32"),h=c.values,[m,f,g,b]=c.strides,y=n.data.get(r.dataId).values,[x,w,I,T]=u,C=n.data.get(s.dataId).values,[E,A,R,F]=p,{batchSize:S,filterDepth:M,filterHeight:B,filterWidth:U,inChannels:G,inDepth:q,inHeight:K,inWidth:Z,outChannels:Q,outDepth:ee,outHeight:ae,outWidth:te,strideDepth:le,strideHeight:ie,strideWidth:be}=d,ue=M-1-d.padInfo.front,xe=B-1-d.padInfo.top,Ie=U-1-d.padInfo.left;for(let Se=0;Se<S;++Se)for(let Le=0;Le<G;++Le)for(let Ve=0;Ve<q;++Ve){let nt=Ve-ue,it=Math.max(0,Math.ceil(nt/le)),et=Math.min(ee,(M+nt)/le);for(let at=0;at<K;++at){let ze=at-xe,dt=Math.max(0,Math.ceil(ze/ie)),jn=Math.min(ae,(B+ze)/ie);for(let Mt=0;Mt<Z;++Mt){let ia=Mt-Ie,on=Math.max(0,Math.ceil(ia/be)),Fn=Math.min(te,(U+ia)/be),oa=0;for(let Dn=it;Dn<et;++Dn){let ot=Dn*le-nt;for(let Rn=dt;Rn<jn;++Rn){let qn=Rn*ie-ze;for(let xr=on;xr<Fn;++xr){let qo=xr*be-ia,er=x*Se+w*Dn+I*Rn+T*xr,vp=E*(M-1-ot)+A*(B-1-qn)+R*(U-1-qo)+F*Le;for(let Ia=0;Ia<Q;++Ia){let Ko=y[er+Ia],Xt=C[vp+Ia];oa+=Ko*Xt}}}}h[m*Se+f*Ve+g*at+b*Mt+Le]=oa}}}return n.makeTensorInfo(c.shape,c.dtype,c.values)}var U5={kernelName:bm,backendName:"cpu",kernelFunc:V5},G5=rt(Ii,e=>Math.cos(e)),H5={kernelName:Ii,backendName:"cpu",kernelFunc:G5},j5=rt(Si,e=>Math.cosh(e)),q5={kernelName:Si,backendName:"cpu",kernelFunc:j5};function K5(e){let{inputs:t,backend:n,attrs:a}=e,{image:r,boxes:s,boxInd:i}=t,{cropSize:o,method:l,extrapolationValue:u}=a,[p,d,c,h]=r.shape,m=s.shape[0],[f,g]=o,b=Oe([m,f,g,h],"float32"),y=n.data.get(s.dataId).values,x=n.data.get(i.dataId).values,w=n.data.get(r.dataId).values,I=v.computeStrides(r.shape),T=v.computeStrides(b.shape);for(let C=0;C<m;C++){let E=C*4,A=y[E],R=y[E+1],F=y[E+2],S=y[E+3],M=x[C];if(M>=p)continue;let B=f>1?(F-A)*(d-1)/(f-1):0,U=g>1?(S-R)*(c-1)/(g-1):0;for(let G=0;G<f;G++){let q=f>1?A*(d-1)+G*B:.5*(A+F)*(d-1);if(q<0||q>d-1){for(let K=0;K<g;K++)for(let Z=0;Z<h;Z++){let Q=Z+K*T[2]+G*T[1]+C*T[0];b.values[Q]=u}continue}if(l==="bilinear"){let K=Math.floor(q),Z=Math.ceil(q),Q=q-K;for(let ee=0;ee<g;ee++){let ae=g>1?R*(c-1)+ee*U:.5*(R+S)*(c-1);if(ae<0||ae>c-1){for(let be=0;be<h;be++){let ue=be+ee*T[2]+G*T[1]+C*T[0];b.values[ue]=u}continue}let te=Math.floor(ae),le=Math.ceil(ae),ie=ae-te;for(let be=0;be<h;be++){let ue=be+te*I[2]+K*I[1]+M*I[0],xe=w[ue];ue=be+le*I[2]+K*I[1]+M*I[0];let Ie=w[ue];ue=be+te*I[2]+Z*I[1]+M*I[0];let Se=w[ue];ue=be+le*I[2]+Z*I[1]+M*I[0];let Le=w[ue],Ve=xe+(Ie-xe)*ie,nt=Se+(Le-Se)*ie;ue=be+ee*T[2]+G*T[1]+C*T[0],b.values[ue]=Ve+(nt-Ve)*Q}}}else for(let K=0;K<g;++K){let Z=g>1?R*(c-1)+K*U:.5*(R+S)*(c-1);if(Z<0||Z>c-1){for(let ae=0;ae<h;ae++){let te=ae+K*T[2]+G*T[1]+C*T[0];b.values[te]=u}continue}let Q=Math.round(Z),ee=Math.round(q);for(let ae=0;ae<h;ae++){let te=ae+Q*I[2]+ee*I[1]+M*I[0],le=ae+K*T[2]+G*T[1]+C*T[0];b.values[le]=w[te]}}}}return n.makeTensorInfo(b.shape,b.dtype,b.values)}var X5={kernelName:jl,backendName:"cpu",kernelFunc:K5};function Y5(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{axis:s,exclusive:i,reverse:o}=a;ge(r,"cumprod");let l=N.getAxesPermutation([s],r.shape.length),u=r;l!=null&&(u=Vn({inputs:{x:r},backend:n,attrs:{perm:l}}));let p=N.getInnerMostAxes(1,r.shape.length)[0];if(p!==u.shape.length-1)throw new Error(`backend.cumprod in CPU expects an inner-most axis=${u.shape.length-1} but got axis=${p}`);let d=fa(u.dtype,"int32"),c=v.makeOnesTypedArray(v.sizeFromShape(u.shape),d),h=n.data.get(u.dataId).values,m=u.shape[u.shape.length-1],f=o?(b,y)=>b+m-y-1:(b,y)=>b+y;for(let b=0;b<h.length;b+=m)for(let y=0;y<m;y++){let x=f(b,y);if(y===0)c[x]=i?1:h[x];else{let w=f(b,y-1);c[x]=i?h[w]*c[w]:h[x]*c[w]}}let g=n.makeTensorInfo(u.shape,d,c);if(l!=null){let b=N.getUndoAxesPermutation(l),y=Vn({inputs:{x:g},backend:n,attrs:{perm:b}});return n.disposeIntermediateTensorInfo(g),n.disposeIntermediateTensorInfo(u),y}return g}var Z5={kernelName:Hl,backendName:"cpu",kernelFunc:Y5};function J5(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{axis:s,exclusive:i,reverse:o}=a;ge(r,"cumsum");let l=N.getAxesPermutation([s],r.shape.length),u=r;l!=null&&(u=Vn({inputs:{x:r},backend:n,attrs:{perm:l}}));let p=N.getInnerMostAxes(1,r.shape.length)[0];if(p!==u.shape.length-1)throw new Error(`backend.cumsum in CPU expects an inner-most axis=${u.shape.length-1} but got axis=${p}`);let d=fa(u.dtype,"int32"),c=v.makeZerosTypedArray(v.sizeFromShape(u.shape),d),h=n.data.get(u.dataId).values,m=u.shape[u.shape.length-1],f=o?(b,y)=>b+m-y-1:(b,y)=>b+y;for(let b=0;b<h.length;b+=m)for(let y=0;y<m;y++){let x=f(b,y);if(y===0)c[x]=i?0:h[x];else{let w=f(b,y-1);c[x]=i?h[w]+c[w]:h[x]+c[w]}}let g=n.makeTensorInfo(u.shape,d,c);if(l!=null){let b=N.getUndoAxesPermutation(l),y=Vn({inputs:{x:g},backend:n,attrs:{perm:b}});return n.disposeIntermediateTensorInfo(g),n.disposeIntermediateTensorInfo(u),y}return g}var Q5={kernelName:Ti,backendName:"cpu",kernelFunc:J5};function e8(e){let{inputs:t,backend:n,attrs:a}=e,{x:r,weights:s}=t,{size:i,binaryOutput:o}=a;if(r.shape.length===1){let l=n.data.get(r.dataId).values,u=n.data.get(s.dataId).values,p=P0(l,u,s.dtype,s.shape,i);return n.makeTensorInfo([i],s.dtype,p)}else if(r.shape.length===2){let l=n.bufferSync(r),u=n.bufferSync(s),p=cC(l,u,i,o);return n.makeTensorInfo(p.shape,s.dtype,p.values)}throw new Error(`Error in denseBincount: input must be at most rank 2, but got rank${r.shape.length}.`)}var t8={kernelName:ym,backendName:"cpu",kernelFunc:e8};function n8(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{blockSize:s,dataFormat:i}=a;v.assert(i==="NHWC",()=>`Only NHWC dataFormat supported on CPU for depthToSpace. Got ${i}`);let o=r.shape[0],l=r.shape[1],u=r.shape[2],p=r.shape[3],d=l*s,c=u*s,h=p/(s*s),m=n.data.get(r.dataId).values,f=new Float32Array(o*d*c*h),g=0;for(let b=0;b<o;++b)for(let y=0;y<d;++y){let x=Math.floor(y/s),w=y%s;for(let I=0;I<c;++I){let T=Math.floor(I/s),C=I%s,E=(w*s+C)*h;for(let A=0;A<h;++A){let R=A+E+p*(T+u*(x+l*b));f[g++]=m[R]}}}return n.makeTensorInfo([o,d,c,h],r.dtype,f)}var a8={kernelName:ql,backendName:"cpu",kernelFunc:n8};function n_(e){let{inputs:t,backend:n,attrs:a}=e,{x:r,filter:s}=t,{strides:i,pad:o,dilations:l,dimRoundingMode:u}=a;ge([r,s],"depthwiseConv2DNative");let p=v.computeStrides(r.shape),d=v.computeStrides(s.shape),c=l;c==null&&(c=[1,1]),v.assert(N.eitherStridesOrDilationsAreOne(i,c),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${i} and dilations '${c}'`);let h=N.computeConv2DInfo(r.shape,s.shape,i,c,o,u,!0),{filterHeight:m,filterWidth:f,dilationHeight:g,dilationWidth:b,padInfo:y}=h,x=y.left,w=y.top,I=h.outChannels/h.inChannels,T=new Ht(h.outShape,r.dtype),C=n.data.get(r.dataId).values,E=n.data.get(s.dataId).values,A=T.values;for(let R=0;R<h.batchSize;++R){let F=R*p[0],S=R*T.strides[0];for(let M=0;M<h.outHeight;++M){let B=S+M*T.strides[1],U=M*h.strideHeight-w;for(let G=0;G<m;++G){let q=U+G*g;if(q<0||q>=h.inHeight)continue;let K=G*d[0],Z=F+q*p[1];for(let Q=0;Q<h.outWidth;++Q){let ee=B+Q*T.strides[2],ae=Q*h.strideWidth-x;for(let te=0;te<f;++te){let le=ae+te*b;if(le<0||le>=h.inWidth)continue;let ie=K+te*d[1],be=Z+le*h.inChannels,ue=ee,xe=ie;for(let Ie=0;Ie<h.inChannels;++Ie){let Se=C[be+Ie];for(let Le=0;Le<I;++Le)A[ue+Le]+=Se*E[xe+Le];ue+=I,xe+=I}}}}}}return n.makeTensorInfo(T.shape,T.dtype,T.values)}var r8={kernelName:Ni,backendName:"cpu",kernelFunc:n_};function s8(e){let{inputs:t,backend:n,attrs:a}=e,{x:r,dy:s}=t,{strides:i,dilations:o,pad:l,dimRoundingMode:u,filterShape:p}=a;ge([r,s],"depthwiseConv2dNativeBackpropFilter");let d=N.computeConv2DInfo(r.shape,p,i,o,l,u,!0),{strideHeight:c,strideWidth:h,filterHeight:m,filterWidth:f}=d,g=new Ht(d.filterShape,"float32"),b=d.padInfo.left,y=d.padInfo.top,x=d.outChannels/d.inChannels,w=n.data.get(r.dataId).values,I=new Ht(r.shape,r.dtype,w),T=n.data.get(s.dataId).values,C=new Ht(s.shape,s.dtype,T);for(let E=0;E<m;++E){let A=Math.max(0,Math.ceil((y-E)/c)),R=Math.min(d.outHeight,(d.inHeight+y-E)/c);for(let F=0;F<f;++F){let S=Math.max(0,Math.ceil((b-F)/h)),M=Math.min(d.outWidth,(d.inWidth+b-F)/h);for(let B=0;B<d.outChannels;++B){let U=Math.trunc(B/x),G=B%x,q=0;for(let K=0;K<d.batchSize;++K)for(let Z=A;Z<R;++Z){let Q=E+Z*c-y;for(let ee=S;ee<M;++ee){let ae=F+ee*h-b;q+=I.get(K,Q,ae,U)*C.get(K,Z,ee,B)}}g.set(q,E,F,U,G)}}}return n.makeTensorInfo(g.shape,g.dtype,g.values)}var i8={kernelName:xm,backendName:"cpu",kernelFunc:s8};function o8(e){let{inputs:t,backend:n,attrs:a}=e,{dy:r,filter:s}=t,{strides:i,dilations:o,pad:l,dimRoundingMode:u,inputShape:p}=a;ge([r,s],"depthwiseConv2DNativeBackpropInput");let d=v.computeStrides(r.shape),c=v.computeStrides(s.shape),h=N.computeConv2DInfo(p,s.shape,i,o,l,u,!0),m=new Ht(h.inShape,"float32"),f=m.values,[g,b,y]=m.strides,x=n.data.get(r.dataId).values,[w,I,T]=d,C=n.data.get(s.dataId).values,[E,A,R]=c,{batchSize:F,filterHeight:S,filterWidth:M,inChannels:B,inHeight:U,inWidth:G,outChannels:q,outHeight:K,outWidth:Z,strideHeight:Q,strideWidth:ee}=h,ae=S-1-h.padInfo.top,te=M-1-h.padInfo.left,le=q/B;for(let ie=0;ie<F;++ie)for(let be=0;be<B;++be)for(let ue=0;ue<U;++ue){let xe=ue-ae,Ie=Math.max(0,Math.ceil(xe/Q)),Se=Math.min(K,(S+xe)/Q);for(let Le=0;Le<G;++Le){let Ve=Le-te,nt=Math.max(0,Math.ceil(Ve/ee)),it=Math.min(Z,(M+Ve)/ee),et=0;for(let at=Ie;at<Se;++at){let ze=at*Q-xe;for(let dt=nt;dt<it;++dt){let jn=dt*ee-Ve,Mt=w*ie+I*at+T*dt,ia=E*(S-1-ze)+A*(M-1-jn)+R*be;for(let on=0;on<le;++on){let Fn=be*le+on,oa=x[Mt+Fn],Dn=C[ia+on];et+=oa*Dn}}}f[g*ie+b*ue+y*Le+be]=et}}return n.makeTensorInfo(m.shape,m.dtype,m.values)}var l8={kernelName:vm,backendName:"cpu",kernelFunc:o8};function u8(e){let{inputs:t,backend:n}=e,{x:a}=t,r=v.sizeFromShape(a.shape),s=n.data.get(a.dataId).values,i=Oe([r,r],a.dtype),o=i.values;for(let u=0;u<s.length;u++)o[u*r+u]=s[u];let l=[...a.shape,...a.shape];return n.makeTensorInfo(l,i.dtype,i.values)}var p8={kernelName:wm,backendName:"cpu",kernelFunc:u8},c8={kernelName:fc,backendName:"cpu",kernelFunc:({inputs:e,backend:t,attrs:n})=>{let{x:a,filter:r}=e,{strides:s,pad:i,dilations:o}=n,l=t,u=l.data.get(a.dataId).values,p=a.shape.length,d=l.data.get(r.dataId).values,c=r.shape.length,{batchSize:h,inHeight:m,inWidth:f,inChannels:g,outHeight:b,outWidth:y,padInfo:x,strideHeight:w,strideWidth:I,filterHeight:T,filterWidth:C,dilationHeight:E,dilationWidth:A,outShape:R}=N.computeDilation2DInfo(a.shape,r.shape,s,i,"NHWC",o),F=v.sizeFromShape(R),S=R.length,M=v.getArrayFromDType(a.dtype,F);for(let B=0;B<h;++B)for(let U=0;U<b;++U){let G=U*w-x.top;for(let q=0;q<y;++q){let K=q*I-x.left;for(let Z=0;Z<g;++Z){let Q=Number.MIN_SAFE_INTEGER;for(let ae=0;ae<T;++ae){let te=G+ae*E;if(te>=0&&te<m)for(let le=0;le<C;++le){let ie=K+le*A;if(ie>=0&&ie<f){let be=v.locToIndex([B,te,ie,Z],p,v.computeStrides(a.shape)),ue=v.locToIndex([ae,le,Z],c,v.computeStrides(r.shape)),xe=u[be]+d[ue];xe>Q&&(Q=xe)}}}let 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SK={kernelName:Am,backendName:"cpu",kernelFunc:IK};function TK(e){let{inputs:t,backend:n,attrs:a}=e,{dy:r,input:s,output:i}=t,o=s;ge([s,i],"maxPoolGrad");let{filterSize:l,strides:u,pad:p,dimRoundingMode:d}=a,c=N.computePool2DInfo(o.shape,l,u,1,p,d),h=n.data.get(o.dataId).values,m=Oe(c.outShape,o.dtype,QC(h,o.shape,o.dtype,c).values),f=c.strideHeight,g=c.strideWidth,b=c.dilationHeight,y=c.dilationWidth,x=c.effectiveFilterHeight,w=c.effectiveFilterWidth,I=w-1-c.padInfo.left,T=x-1-c.padInfo.top,C=Oe(o.shape,"float32"),E=n.data.get(r.dataId).values,A=Oe(r.shape,"float32",E);for(let R=0;R<c.batchSize;++R)for(let F=0;F<c.inChannels;++F)for(let S=0;S<c.inHeight;++S)for(let M=0;M<c.inWidth;++M){let B=S-T,U=M-I,G=0;for(let q=0;q<x;q+=b){let K=(B+q)/f;if(!(K<0||K>=c.outHeight||Math.floor(K)!==K))for(let Z=0;Z<w;Z+=y){let Q=(U+Z)/g;if(Q<0||Q>=c.outWidth||Math.floor(Q)!==Q)continue;let ee=x*w-1-m.get(R,K,Q,F),ae=q*w+Z,te=ee===ae?1:0;te!==0&&(G+=A.get(R,K,Q,F)*te)}}C.set(G,R,S,M,F)}return 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if(!da(t,"EXT_color_buffer_float"))return!1;return bx(t)}function D_(e){if(e===0)return!1;let t=qa(e);if(e===1){if(!da(t,"OES_texture_float")||!da(t,"WEBGL_color_buffer_float"))return!1}else{if(da(t,"EXT_color_buffer_float"))return bx(t);let n="EXT_color_buffer_half_float";if(da(t,n)){let a=t.getExtension(n);return rZ(t,a)}return!1}return bx(t)}function bx(e){let t=X0(e),n=e.createTexture();e.bindTexture(e.TEXTURE_2D,n);let a=1,r=1;e.texImage2D(e.TEXTURE_2D,0,t.internalFormatFloat,a,r,0,t.textureFormatFloat,t.textureTypeFloat,null);let s=e.createFramebuffer();e.bindFramebuffer(e.FRAMEBUFFER,s),e.framebufferTexture2D(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0,e.TEXTURE_2D,n,0);let i=e.checkFramebufferStatus(e.FRAMEBUFFER)===e.FRAMEBUFFER_COMPLETE;return e.bindTexture(e.TEXTURE_2D,null),e.bindFramebuffer(e.FRAMEBUFFER,null),e.deleteTexture(n),e.deleteFramebuffer(s),i}function rZ(e,t){let n=X0(e,t),a=e.createTexture();e.bindTexture(e.TEXTURE_2D,a);let 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ve=H();ve.registerFlag("HAS_WEBGL",()=>ve.getNumber("WEBGL_VERSION")>0);ve.registerFlag("WEBGL_VERSION",()=>gx(2)?2:gx(1)?1:0);ve.registerFlag("WEBGL_CHECK_NUMERICAL_PROBLEMS",()=>!1);ve.registerFlag("WEBGL_BUFFER_SUPPORTED",()=>ve.get("WEBGL_VERSION")===2);ve.registerFlag("WEBGL_CPU_FORWARD",()=>!0);ve.registerFlag("WEBGL_FORCE_F16_TEXTURES",()=>!1);ve.registerFlag("WEBGL_PACK",()=>ve.getBool("HAS_WEBGL"));ve.registerFlag("WEBGL_PACK_NORMALIZATION",()=>ve.getBool("WEBGL_PACK"));ve.registerFlag("WEBGL_PACK_CLIP",()=>ve.getBool("WEBGL_PACK"));ve.registerFlag("WEBGL_PACK_DEPTHWISECONV",()=>ve.getBool("WEBGL_PACK"));ve.registerFlag("WEBGL_PACK_BINARY_OPERATIONS",()=>ve.getBool("WEBGL_PACK"));ve.registerFlag("WEBGL_PACK_UNARY_OPERATIONS",()=>ve.getBool("WEBGL_PACK"));ve.registerFlag("WEBGL_PACK_ARRAY_OPERATIONS",()=>ve.getBool("WEBGL_PACK"));ve.registerFlag("WEBGL_PACK_IMAGE_OPERATIONS",()=>ve.getBool("WEBGL_PACK"));ve.registerFlag("WEBGL_PACK_REDUCE",()=>ve.getBool("WEBGL_PACK"));ve.registerFlag("WEBGL_LAZILY_UNPACK",()=>ve.getBool("WEBGL_PACK"));ve.registerFlag("WEBGL_CONV_IM2COL",()=>ve.getBool("WEBGL_PACK"));ve.registerFlag("WEBGL_MAX_TEXTURE_SIZE",()=>E_(ve.getNumber("WEBGL_VERSION")));ve.registerFlag("WEBGL_MAX_TEXTURES_IN_SHADER",()=>A_(ve.getNumber("WEBGL_VERSION")));ve.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)
    `:"",l="",u=`
      #define round(value) newRound(value)
      int newRound(float value) {
        return int(floor(value + 0.5));
      }

      ivec4 newRound(vec4 value) {
        return ivec4(floor(value + vec4(0.5)));
      }
    `):(e="",t="attribute",n="varying",a="varying",r="texture2D",s="gl_FragColor",i="",o=`
      #define isnan(value) isnan_custom(value)
      bool isnan_custom(float val) {
        return (val > 0. || val < 1. || val == 0.) ? false : true;
      }
      bvec4 isnan_custom(vec4 val) {
        return bvec4(isnan(val.x), isnan(val.y), isnan(val.z), isnan(val.w));
      }
    `,l=`
      uniform float INFINITY;

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

      ivec4 round(vec4 value) {
        return ivec4(floor(value + vec4(0.5)));
      }
    `),{version:e,attribute:t,varyingVs:n,varyingFs:a,texture2D:r,output:s,defineOutput:i,defineSpecialNaN:o,defineSpecialInf:l,defineRound:u}}function wo(e,t,n="index"){let a=v.computeStrides(t);return a.map((r,s)=>{let i=`int ${e[s]} = ${n} / ${r}`,o=s===a.length-1?`int ${e[s+1]} = ${n} - ${e[s]} * ${r}`:`index -= ${e[s]} * ${r}`;return`${i}; ${o};`}).join("")}function Kf(e,t,n="index"){let a=v.computeStrides(t);return a.map((r,s)=>{let i=`int ${e[s]} = ${n} / outShapeStrides[${s}]`,o=s===a.length-1?`int ${e[s+1]} = ${n} - ${e[s]} * outShapeStrides[${s}]`:`index -= ${e[s]} * outShapeStrides[${s}]`;return`${i}; ${o};`}).join("")}function sZ(e,t){let n=e.length,a=e.map(s=>`${t}[${s}]`),r=new Array(n-1);r[n-2]=a[n-1];for(let s=n-3;s>=0;--s)r[s]=`(${r[s+1]} * ${a[s+1]})`;return r}function iZ(e,t,n="index"){let a=e.map((s,i)=>i),r=sZ(a,t);return r.map((s,i)=>{let o=`int ${e[i]} = ${n} / ${r[i]}`,l=i===r.length-1?`int ${e[i+1]} = ${n} - ${e[i]} * ${r[i]}`:`index -= ${e[i]} * ${r[i]}`;return`${o}; ${l};`}).join("")}function Z0(e){let t=v.computeStrides(e).map(n=>n.toString());return`
  int getFlatIndex(ivec3 coords) {
    return coords.x * ${t[0]} + coords.y * ${t[1]} + coords.z;
  }
`}function J0(){return`
  int getFlatIndex(ivec3 coords) {
    return coords.x * outShapeStrides[0] + coords.y * outShapeStrides[1] + coords.z;
  }
`}var M_=`
  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;
  }
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`),s=e.map(c=>lZ(c,t,n.packedInputs,n.enableShapeUniforms)).join(`
`),i=t.texShape,o=_n(),l=cZ(o),u,p,d=mZ(o);return t.isPacked?(u=uZ(t.logicalShape,i,n.enableShapeUniforms),p=hZ(o)):(u=pZ(t.logicalShape,i,n.enableShapeUniforms),p=dZ(o)),n.packedInputs&&(d+=yZ),[d,l,p,r,u,s,n.userCode].join(`
`)}function Zu(e,t=!1){let n=e.shapeInfo.logicalShape;switch(n.length){case 0:return AZ(e,t);case 1:return FZ(e,t);case 2:return RZ(e,t);case 3:return PZ(e,t);case 4:return LZ(e,t);case 5:return zZ(e);case 6:return WZ(e);default:throw new Error(`${n.length}-D input sampling is not yet supported`)}}function O_(e,t){switch(e.shapeInfo.logicalShape.length){case 0:return EZ(e);case 1:return $Z(e,t);case 2:return DZ(e,t);case 3:return MZ(e,t);default:return OZ(e,t)}}function lZ(e,t,n=!1,a){let r="";n?r+=O_(e,a):r+=Zu(e,a);let s=e.shapeInfo.logicalShape,i=t.logicalShape;return s.length<=i.length&&(n?r+=BZ(e,t):r+=VZ(e,t)),r}function uZ(e,t,n){switch(e.length){case 0:return L_();case 1:return xZ(e,t,n);case 2:return CZ(e,t,n);case 3:return wZ(e,t,n);default:return IZ(e,t,n)}}function pZ(e,t,n){switch(e.length){case 0:return L_();case 1:return vZ(e,t,n);case 2:return _Z(e,t,n);case 3:return kZ(e,t,n);case 4:return SZ(e,t,n);case 5:return TZ(e,t);case 6:return NZ(e,t);default:throw new Error(`${e.length}-D output sampling is not yet supported`)}}function cZ(e){return`
    float sampleTexture(sampler2D textureSampler, vec2 uv) {
      return ${e.texture2D}(textureSampler, uv).r;
    }
  `}function dZ(e){return`
    void setOutput(float val) {
      ${e.output} = vec4(val, 0, 0, 0);
    }
  `}function hZ(e){return`
    void setOutput(vec4 val) {
      ${e.output} = val;
    }
  `}function mZ(e){return`${e.version}
    precision highp float;
    precision highp int;
    precision highp sampler2D;
    ${e.varyingFs} vec2 resultUV;
    ${e.defineOutput}
    const vec2 halfCR = vec2(0.5, 0.5);

    struct ivec5
    {
      int x;
      int y;
      int z;
      int w;
      int u;
    };

    struct ivec6
    {
      int x;
      int y;
      int z;
      int w;
      int u;
      int v;
    };

    uniform float NAN;
    ${e.defineSpecialNaN}
    ${e.defineSpecialInf}
    ${e.defineRound}

    int imod(int x, int y) {
      return x - y * (x / y);
    }

    int idiv(int a, int b, float sign) {
      int res = a / b;
      int mod = imod(a, b);
      if (sign < 0. && mod != 0) {
        res -= 1;
      }
      return res;
    }

    //Based on the work of Dave Hoskins
    //https://www.shadertoy.com/view/4djSRW
    #define HASHSCALE1 443.8975
    float random(float seed){
      vec2 p = resultUV * seed;
      vec3 p3  = fract(vec3(p.xyx) * HASHSCALE1);
      p3 += dot(p3, p3.yzx + 19.19);
      return fract((p3.x + p3.y) * p3.z);
    }

    ${fZ}
    ${gZ}
    ${bZ}
  `}var fZ=`
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);
}
`,gZ=`
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);
}
`,bZ=`
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);
}
`,yZ=`
  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 L_(){return`
    int getOutputCoords() {
      return 0;
    }
  `}function xZ(e,t,n){let a=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)];return a[0]===1?n?`
      int getOutputCoords() {
        return 2 * int(resultUV.x * ceil(float(outTexShape[1]) / 2.0));
      }
    `:`
      int getOutputCoords() {
        return 2 * int(resultUV.x * ${a[1]}.0);
      }
    `:a[1]===1?n?`
      int getOutputCoords() {
        return 2 * int(resultUV.y * ceil(float(outTexShape[0]) / 2.0));
      }
    `:`
      int getOutputCoords() {
        return 2 * int(resultUV.y * ${a[0]}.0);
      }
    `:n?`
    int getOutputCoords() {
      ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(packedTexShape[0], packedTexShape[1]));
      return 2 * (resTexRC.x * packedTexShape[1] + resTexRC.y);
    }
  `:`
    int getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(${a[0]}, ${a[1]}));
      return 2 * (resTexRC.x * ${a[1]} + resTexRC.y);
    }
  `}function vZ(e,t,n){return t[0]===1?n?`
      int getOutputCoords() {
        return int(resultUV.x * float(outTexShape[1]));
      }
    `:`
      int getOutputCoords() {
        return int(resultUV.x * ${t[1]}.0);
      }
    `:t[1]===1?n?`
      int getOutputCoords() {
        return int(resultUV.y * float(outTexShape[0]));
      }
    `:`
      int getOutputCoords() {
        return int(resultUV.y * ${t[0]}.0);
      }
    `:n?`
    int getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(outTexShape[0], outTexShape[1]));
      return resTexRC.x * outTexShape[1] + resTexRC.y;
    }
  `:`
    int getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(${t[0]}, ${t[1]}));
      return resTexRC.x * ${t[1]} + resTexRC.y;
    }
  `}function wZ(e,t,n){if(n)return`
    ivec3 getOutputCoords() {
      ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));
      int texelsInLogicalRow = int(ceil(float(outShape[2]) / 2.0));
      int texelsInBatch = texelsInLogicalRow * int(ceil(float(outShape[1]) / 2.0));
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(packedTexShape[0], packedTexShape[1]));
      int index = resTexRC.x * packedTexShape[1] + resTexRC.y;

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

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

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

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

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

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

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

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

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

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

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

      ${o}

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

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

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

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

      ${n}

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

      ${n}

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

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

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

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

      return ivec2(r, c);
    }
  `}function _Z(e,t,n){return v.arraysEqual(e,t)?n?`
      ivec2 getOutputCoords() {
        return ivec2(resultUV.yx * vec2(outTexShape[0], outTexShape[1]));
      }
    `:`
      ivec2 getOutputCoords() {
        return ivec2(resultUV.yx * vec2(${t[0]}, ${t[1]}));
      }
    `:e[1]===1?n?`
      ivec2 getOutputCoords() {
        ivec2 resTexRC = ivec2(resultUV.yx *
                               vec2(outTexShape[0], outTexShape[1]));
        int index = resTexRC.x * outTexShape[1] + resTexRC.y;
        return ivec2(index, 0);
      }
    `:`
      ivec2 getOutputCoords() {
        ivec2 resTexRC = ivec2(resultUV.yx *
                               vec2(${t[0]}, ${t[1]}));
        int index = resTexRC.x * ${t[1]} + resTexRC.y;
        return ivec2(index, 0);
      }
    `:e[0]===1?n?`
      ivec2 getOutputCoords() {
        ivec2 resTexRC = ivec2(resultUV.yx *
                               vec2(outTexShape[0], outTexShape[1]));
        int index = resTexRC.x * outTexShape[1] + resTexRC.y;
        return ivec2(0, index);
      }
    `:`
      ivec2 getOutputCoords() {
        ivec2 resTexRC = ivec2(resultUV.yx *
                               vec2(${t[0]}, ${t[1]}));
        int index = resTexRC.x * ${t[1]} + resTexRC.y;
        return ivec2(0, index);
      }
    `:n?`
    ivec2 getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(outTexShape[0], outTexShape[1]));
      int index = resTexRC.x * outTexShape[1] + resTexRC.y;
      int r = index / outShape[1];
      int c = index - r * outShape[1];
      return ivec2(r, c);
    }
  `:`
    ivec2 getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(${t[0]}, ${t[1]}));
      int index = resTexRC.x * ${t[1]} + resTexRC.y;
      int r = index / ${e[1]};
      int c = index - r * ${e[1]};
      return ivec2(r, c);
    }
  `}function ko(e){return`offset${e}`}function EZ(e){let t=e.name,n="get"+t.charAt(0).toUpperCase()+t.slice(1),a=_n();return`
    vec4 ${n}() {
      return ${a.texture2D}(${t}, halfCR);
    }
  `}function AZ(e,t){let n=e.name,a="get"+n.charAt(0).toUpperCase()+n.slice(1);if(e.shapeInfo.isUniform)return`float ${a}() {return ${n};}`;let[r,s]=e.shapeInfo.texShape;if(r===1&&s===1)return`
      float ${a}() {
        return sampleTexture(${n}, halfCR);
      }
    `;let i=ko(n);if(t)return`
    float ${a}() {
      vec2 uv = uvFromFlat(${n}TexShape[0], ${n}TexShape[1], ${i});
      return sampleTexture(${n}, uv);
    }
  `;let[o,l]=e.shapeInfo.texShape;return`
    float ${a}() {
      vec2 uv = uvFromFlat(${o}, ${l}, ${i});
      return sampleTexture(${n}, uv);
    }
  `}function $Z(e,t){let n=e.name,a="get"+n.charAt(0).toUpperCase()+n.slice(1),r=e.shapeInfo.texShape,s=_n();if(t)return`
    vec4 ${a}(int index) {
      ivec2 packedTexShape = ivec2(ceil(float(${n}TexShape[0]) / 2.0), ceil(float(${n}TexShape[1]) / 2.0));
      vec2 uv = packedUVfrom1D(
        packedTexShape[0], packedTexShape[1], index);
      return ${s.texture2D}(${n}, uv);
    }
  `;let i=[Math.ceil(r[0]/2),Math.ceil(r[1]/2)];return`
    vec4 ${a}(int index) {
      vec2 uv = packedUVfrom1D(
        ${i[0]}, ${i[1]}, index);
      return ${s.texture2D}(${n}, uv);
    }
  `}function FZ(e,t){let n=e.name,a="get"+n.charAt(0).toUpperCase()+n.slice(1);if(e.shapeInfo.isUniform)return`
      float ${a}(int index) {
        ${Ju(e)}
      }
    `;let r=e.shapeInfo.texShape,s=r[0],i=r[1];if(i===1&&s===1)return`
      float ${a}(int index) {
        return sampleTexture(${n}, halfCR);
      }
    `;let o=ko(n);return i===1?t?`
      float ${a}(int index) {
        vec2 uv = vec2(0.5, (float(index + ${o}) + 0.5) / float(${n}TexShape[0]));
        return sampleTexture(${n}, uv);
      }
    `:`
      float ${a}(int index) {
        vec2 uv = vec2(0.5, (float(index + ${o}) + 0.5) / ${s}.0);
        return sampleTexture(${n}, uv);
      }
    `:s===1?t?`
      float ${a}(int index) {
        vec2 uv = vec2((float(index + ${o}) + 0.5) / float(${n}TexShape[1]), 0.5);
        return sampleTexture(${n}, uv);
      }
    `:`
      float ${a}(int index) {
        vec2 uv = vec2((float(index + ${o}) + 0.5) / ${i}.0, 0.5);
        return sampleTexture(${n}, uv);
      }
    `:t?`
    float ${a}(int index) {
      vec2 uv = uvFromFlat(${n}TexShape[0], ${n}TexShape[1], index + ${o});
      return sampleTexture(${n}, uv);
    }
  `:`
    float ${a}(int index) {
      vec2 uv = uvFromFlat(${s}, ${i}, index + ${o});
      return sampleTexture(${n}, uv);
    }
  `}function DZ(e,t){let n=e.shapeInfo.logicalShape,a=e.name,r="get"+a.charAt(0).toUpperCase()+a.slice(1),s=e.shapeInfo.texShape,i=s[0],o=s[1],l=_n();if(s!=null&&v.arraysEqual(n,s))return t?`
      vec4 ${r}(int row, int col) {
        vec2 uv = (vec2(col, row) + halfCR) / vec2(${a}TexShape[1], ${a}TexShape[0]);

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

        return ${l.texture2D}(${a}, uv);
      }
    `;if(t)return`
    vec4 ${r}(int row, int col) {
      ivec2 packedTexShape = ivec2(ceil(float(${a}TexShape[0]) / 2.0), ceil(float(${a}TexShape[1]) / 2.0));
      int valuesPerRow = int(ceil(float(${a}Shape[1]) / 2.0));
      vec2 uv = packedUVfrom2D(valuesPerRow, packedTexShape[0], packedTexShape[1], row, col);
      return ${l.texture2D}(${a}, uv);
    }
  `;let u=[Math.ceil(s[0]/2),Math.ceil(s[1]/2)],p=Math.ceil(n[1]/2);return`
    vec4 ${r}(int row, int col) {
      vec2 uv = packedUVfrom2D(${p}, ${u[0]}, ${u[1]}, row, col);
      return ${l.texture2D}(${a}, uv);
    }
  `}function RZ(e,t){let n=e.shapeInfo.logicalShape,a=e.name,r="get"+a.charAt(0).toUpperCase()+a.slice(1),s=e.shapeInfo.texShape;if(s!=null&&v.arraysEqual(n,s)){if(t)return`
      float ${r}(int row, int col) {
        vec2 uv = (vec2(col, row) + halfCR) / vec2(${a}TexShape[1], ${a}TexShape[0]);
        return sampleTexture(${a}, uv);
      }
    `;let c=s[0],h=s[1];return`
    float ${r}(int row, int col) {
      vec2 uv = (vec2(col, row) + halfCR) / vec2(${h}.0, ${c}.0);
      return sampleTexture(${a}, uv);
    }
  `}let{newShape:i,keptDims:o}=v.squeezeShape(n),l=i;if(l.length<n.length){let c=Qu(e,l),h=["row","col"];return`
      ${Zu(c,t)}
      float ${r}(int row, int col) {
        return ${r}(${ep(h,o)});
      }
    `}if(e.shapeInfo.isUniform)return`
      float ${r}(int row, int col) {
        int index = round(dot(vec2(row, col), vec2(${n[1]}, 1)));
        ${Ju(e)}
      }
    `;let u=s[0],p=s[1],d=ko(a);return p===1?t?`
      float ${r}(int row, int col) {
        float index = dot(vec3(row, col, ${d}), vec3(${a}Shape[1], 1, 1));
        vec2 uv = vec2(0.5, (index + 0.5) / float(${a}TexShape[0]));
        return sampleTexture(${a}, uv);
      }
    `:`
    float ${r}(int row, int col) {
      float index = dot(vec3(row, col, ${d}), vec3(${n[1]}, 1, 1));
      vec2 uv = vec2(0.5, (index + 0.5) / ${u}.0);
      return sampleTexture(${a}, uv);
    }
  `:u===1?t?`
      float ${r}(int row, int col) {
        float index = dot(vec3(row, col, ${d}), vec3(${a}Shape[1], 1, 1));
        vec2 uv = vec2((index + 0.5) / float(${a}TexShape[1]), 0.5);
        return sampleTexture(${a}, uv);
      }
    `:`
    float ${r}(int row, int col) {
      float index = dot(vec3(row, col, ${d}), vec3(${n[1]}, 1, 1));
      vec2 uv = vec2((index + 0.5) / ${p}.0, 0.5);
      return sampleTexture(${a}, uv);
    }
  `:t?`
      float ${r}(int row, int col) {
        // Explicitly use integer operations as dot() only works on floats.
        int index = row * ${a}Shape[1] + col + ${d};
        vec2 uv = uvFromFlat(${a}TexShape[0], ${a}TexShape[1], index);
        return sampleTexture(${a}, uv);
      }
    `:`
  float ${r}(int row, int col) {
    // Explicitly use integer operations as dot() only works on floats.
    int index = row * ${n[1]} + col + ${d};
    vec2 uv = uvFromFlat(${u}, ${p}, index);
    return sampleTexture(${a}, uv);
  }
`}function MZ(e,t){let n=e.shapeInfo.logicalShape,a=e.name,r="get"+a.charAt(0).toUpperCase()+a.slice(1),s=e.shapeInfo.texShape,i=[Math.ceil(s[0]/2),Math.ceil(s[1]/2)];if(n[0]===1){let c=n.slice(1),h=[1,2],m=Qu(e,c),f=["b","row","col"];return`
        ${O_(m,t)}
        vec4 ${r}(int b, int row, int col) {
          return ${r}(${ep(f,h)});
        }
      `}let o=_n();if(t)return`
    vec4 ${r}(int b, int row, int col) {
      ivec2 packedTexShape = ivec2(ceil(float(${a}TexShape[0]) / 2.0), ceil(float(${a}TexShape[1]) / 2.0));
      int valuesPerRow = int(ceil(float(${a}Shape[2]) / 2.0));
      int texelsInBatch = valuesPerRow * int(ceil(float(${a}Shape[1]) / 2.0));
      vec2 uv = packedUVfrom3D(
        packedTexShape[0], packedTexShape[1], texelsInBatch, valuesPerRow, b, row, col);
      return ${o.texture2D}(${a}, uv);
    }
  `;let l=i[0],u=i[1],p=Math.ceil(n[2]/2),d=p*Math.ceil(n[1]/2);return`
    vec4 ${r}(int b, int row, int col) {
      vec2 uv = packedUVfrom3D(
        ${l}, ${u}, ${d}, ${p}, b, row, col);
      return ${o.texture2D}(${a}, uv);
    }
  `}function PZ(e,t){let n=e.shapeInfo.logicalShape,a=e.name,r="get"+a.charAt(0).toUpperCase()+a.slice(1),s=n[1]*n[2],i=n[2],{newShape:o,keptDims:l}=v.squeezeShape(n),u=o;if(u.length<n.length){let f=Qu(e,u),g=["row","col","depth"];return`
        ${Zu(f,t)}
        float ${r}(int row, int col, int depth) {
          return ${r}(${ep(g,l)});
        }
      `}if(e.shapeInfo.isUniform)return`
      float ${r}(int row, int col, int depth) {
        int index = round(dot(vec3(row, col, depth),
                          vec3(${s}, ${i}, 1)));
        ${Ju(e)}
      }
    `;let p=e.shapeInfo.texShape,d=p[0],c=p[1],h=e.shapeInfo.flatOffset;if(c===s&&h==null)return t?`
      float ${r}(int row, int col, int depth) {
        int stride1 = ${a}Shape[2];
        float texR = float(row);
        float texC = dot(vec2(col, depth), vec2(stride1, 1));
        vec2 uv = (vec2(texC, texR) + halfCR) /
                   vec2(${a}TexShape[1], ${a}TexShape[0]);
        return sampleTexture(${a}, uv);
      }
    `:`
        float ${r}(int row, int col, int depth) {
          float texR = float(row);
          float texC = dot(vec2(col, depth), vec2(${i}, 1));
          vec2 uv = (vec2(texC, texR) + halfCR) /
                     vec2(${c}.0, ${d}.0);
          return sampleTexture(${a}, uv);
        }
      `;if(c===i&&h==null)return t?`
      float ${r}(int row, int col, int depth) {
        float texR = dot(vec2(row, col), vec2(${a}Shape[1], 1));
        float texC = float(depth);
        vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${a}TexShape[1], ${a}TexShape[0]);
        return sampleTexture(${a}, uv);
      }
    `:`
    float ${r}(int row, int col, int depth) {
      float texR = dot(vec2(row, col), vec2(${n[1]}, 1));
      float texC = float(depth);
      vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${c}.0, ${d}.0);
      return sampleTexture(${a}, uv);
    }
  `;let m=ko(a);return t?`
    float ${r}(int row, int col, int depth) {
      // Explicitly use integer operations as dot() only works on floats.
      int stride0 = ${a}Shape[1] * ${a}Shape[2];
      int stride1 = ${a}Shape[2];
      int index = row * stride0 + col * stride1 + depth + ${m};
      vec2 uv = uvFromFlat(${a}TexShape[0], ${a}TexShape[1], index);
      return sampleTexture(${a}, uv);
    }
    `:`
      float ${r}(int row, int col, int depth) {
        // Explicitly use integer operations as dot() only works on floats.
        int index = row * ${s} + col * ${i} + depth + ${m};
        vec2 uv = uvFromFlat(${d}, ${c}, index);
        return sampleTexture(${a}, uv);
      }
  `}function OZ(e,t){let n=e.name,a="get"+n.charAt(0).toUpperCase()+n.slice(1),r=_n();if(t)return`
    vec4 ${a}(int b2, int b, int row, int col) {
      int valuesPerRow = int(ceil(float(${n}Shape[3]) / 2.0));
      int texelsInBatch = valuesPerRow * int(ceil(float(${n}Shape[2]) / 2.0));
      int index = b * texelsInBatch + (row / 2) * valuesPerRow + (col / 2);
      texelsInBatch *= ${n}Shape[1];
      index = b2 * texelsInBatch + index;
      ivec2 packedTexShape = ivec2(ceil(float(${n}TexShape[0]) / 2.0), ceil(float(${n}TexShape[1]) / 2.0));
      int texR = index / packedTexShape[1];
      int texC = index - texR * packedTexShape[1];
      vec2 uv = (vec2(texC, texR) + halfCR) / vec2(packedTexShape[1], packedTexShape[0]); return ${r.texture2D}(${n}, uv);
    }
  `;let s=e.shapeInfo.logicalShape,i=s.length,o=e.shapeInfo.texShape,l=[Math.ceil(o[0]/2),Math.ceil(o[1]/2)],u=l[0],p=l[1],d=Math.ceil(s[i-1]/2),c=d*Math.ceil(s[i-2]/2),h="int b, int row, int col",m=`b * ${c} + (row / 2) * ${d} + (col / 2)`;for(let f=2;f<i-1;f++)h=`int b${f}, `+h,c*=s[i-f-1],m=`b${f} * ${c} + `+m;return`
    vec4 ${a}(${h}) {
      int index = ${m};
      int texR = index / ${p};
      int texC = index - texR * ${p};
      vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${p}, ${u});
      return ${r.texture2D}(${n}, uv);
    }
  `}function LZ(e,t){let n=e.shapeInfo.logicalShape,a=e.name,r="get"+a.charAt(0).toUpperCase()+a.slice(1),s=n[3],i=n[2]*s,o=n[1]*i,{newShape:l,keptDims:u}=v.squeezeShape(n);if(l.length<n.length){let y=Qu(e,l),x=["row","col","depth","depth2"];return`
      ${Zu(y,t)}
      float ${r}(int row, int col, int depth, int depth2) {
        return ${r}(${ep(x,u)});
      }
    `}if(e.shapeInfo.isUniform)return`
      float ${r}(int row, int col, int depth, int depth2) {
        int index = round(dot(vec4(row, col, depth, depth2),
                          vec4(${o}, ${i}, ${s}, 1)));
        ${Ju(e)}
      }
    `;let p=e.shapeInfo.flatOffset,d=e.shapeInfo.texShape,c=d[0],h=d[1],m=`int stride2 = ${a}Shape[3];`,f=`int stride1 = ${a}Shape[2] * stride2;`,g=`int stride0 = ${a}Shape[1] * stride1;`;if(h===o&&p==null)return t?`
      float ${r}(int row, int col, int depth, int depth2) {
        ${m}
        ${f}
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        float texC =
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                vec3(stride1, stride2, 1));
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        return sampleTexture(${a}, uv);
      }
    `:`
      float ${r}(int row, int col, int depth, int depth2) {
        float texR = float(row);
        float texC =
            dot(vec3(col, depth, depth2),
                vec3(${i}, ${s}, 1));
        vec2 uv = (vec2(texC, texR) + halfCR) /
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        return sampleTexture(${a}, uv);
      }
    `;if(h===s&&p==null)return t?`
      float ${r}(int row, int col, int depth, int depth2) {
        float texR = dot(vec3(row, col, depth),
                         vec3(${a}Shape[1] * ${a}Shape[2], ${a}Shape[2], 1));
        float texC = float(depth2);
        vec2 uv = (vec2(texC, texR) + halfCR) /
                  vec2(${a}TexShape[1], ${a}TexShape[0]);
        return sampleTexture(${a}, uv);
      }
    `:`
      float ${r}(int row, int col, int depth, int depth2) {
        float texR = dot(vec3(row, col, depth),
                         vec3(${n[1]*n[2]}, ${n[2]}, 1));
        float texC = float(depth2);
        vec2 uv = (vec2(texC, texR) + halfCR) /
                  vec2(${h}.0, ${c}.0);
        return sampleTexture(${a}, uv);
      }
    `;let b=ko(a);return t?`
    float ${r}(int row, int col, int depth, int depth2) {
      // Explicitly use integer operations as dot() only works on floats.
      ${m}
      ${f}
      ${g}
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    }
  `:`
    float ${r}(int row, int col, int depth, int depth2) {
      // Explicitly use integer operations as dot() only works on floats.
      int index = row * ${o} + col * ${i} +
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    }
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      ${Zu(f)}
      float ${a}(int row, int col, int depth, int depth2, int depth3) {
        return ${a}(${ep(g,u)});
      }
    `}if(e.shapeInfo.isUniform)return`
      float ${a}(int row, int col, int depth, int depth2, int depth3) {
        float index = dot(
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          vec4(${o}, ${i}, ${s}, ${r})) +
          depth3;
        ${Ju(e)}
      }
    `;let p=e.shapeInfo.flatOffset,d=e.shapeInfo.texShape,c=d[0],h=d[1];if(h===o&&p==null)return`
      float ${a}(int row, int col, int depth, int depth2, int depth3) {
        int texR = row;
        float texC = dot(vec4(col, depth, depth2, depth3),
                         vec4(${i}, ${s}, ${r}, 1));
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                   vec2(${h}.0, ${c}.0);
        return sampleTexture(${n}, uv);
      }
    `;if(h===r&&p==null)return`
      float ${a}(int row, int col, int depth, int depth2, int depth3) {
        float texR = dot(
          vec4(row, col, depth, depth2),
          vec4(${t[1]*t[2]*t[3]},
               ${t[2]*t[3]}, ${t[3]}, 1));
        int texC = depth3;
        vec2 uv = (vec2(texC, texR) + halfCR) /
                  vec2(${h}.0, ${c}.0);
        return sampleTexture(${n}, uv);
      }
    `;let m=ko(n);return`
    float ${a}(int row, int col, int depth, int depth2, int depth3) {
      // Explicitly use integer operations as dot() only works on floats.
      int index = row * ${o} + col * ${i} + depth * ${s} +
          depth2 * ${r} + depth3 + ${m};
      vec2 uv = uvFromFlat(${c}, ${h}, index);
      return sampleTexture(${n}, uv);
    }
  `}function WZ(e){let t=e.shapeInfo.logicalShape,n=e.name,a="get"+n.charAt(0).toUpperCase()+n.slice(1),{newShape:r,keptDims:s}=v.squeezeShape(t);if(r.length<t.length){let g=Qu(e,r),b=["row","col","depth","depth2","depth3","depth4"];return`
      ${Zu(g)}
      float ${a}(int row, int col, int depth,
                    int depth2, int depth3, int depth4) {
        return ${a}(${ep(b,s)});
      }
    `}let i=t[5],o=t[4]*i,l=t[3]*o,u=t[2]*l,p=t[1]*u;if(e.shapeInfo.isUniform)return`
      float ${a}(int row, int col, int depth,
                  int depth2, int depth3, int depth4) {
        int index = round(dot(
          vec4(row, col, depth, depth2),
          vec4(${p}, ${u}, ${l}, ${o})) +
          dot(
            vec2(depth3, depth4),
            vec2(${i}, 1)));
        ${Ju(e)}
      }
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      float ${a}(int row, int col, int depth,
                    int depth2, int depth3, int depth4) {
        int texR = row;
        float texC = dot(vec4(col, depth, depth2, depth3),
          vec4(${u}, ${l}, ${o}, ${i})) +
               float(depth4);
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                   vec2(${m}.0, ${h}.0);
        return sampleTexture(${n}, uv);
      }
    `;if(m===i&&d==null)return`
      float ${a}(int row, int col, int depth,
                    int depth2, int depth3, int depth4) {
        float texR = dot(vec4(row, col, depth, depth2),
          vec4(${t[1]*t[2]*t[3]*t[4]},
               ${t[2]*t[3]*t[4]},
               ${t[3]*t[4]},
               ${t[4]})) + float(depth3);
        int texC = depth4;
        vec2 uv = (vec2(texC, texR) + halfCR) /
                  vec2(${m}.0, ${h}.0);
        return sampleTexture(${n}, uv);
      }
    `;let f=ko(n);return`
    float ${a}(int row, int col, int depth,
                  int depth2, int depth3, int depth4) {
      // Explicitly use integer operations as dot() only works on floats.
      int index = row * ${p} + col * ${u} + depth * ${l} +
          depth2 * ${o} + depth3 * ${i} + depth4 + ${f};
      vec2 uv = uvFromFlat(${h}, ${m}, index);
      return sampleTexture(${n}, uv);
    }
  `}function Ju(e){let t=e.name,n=v.sizeFromShape(e.shapeInfo.logicalShape);return n<2?`return ${t};`:`
    for (int i = 0; i < ${n}; i++) {
      if (i == index) {
        return ${t}[i];
      }
    }
  `}function BZ(e,t){let n=e.name,a=n.charAt(0).toUpperCase()+n.slice(1),r="get"+a+"AtOutCoords",s=e.shapeInfo.logicalShape.length,i=t.logicalShape.length,o=P_(e.shapeInfo.logicalShape,t.logicalShape),l=gt(i),u=i-s,p,d=["x","y","z","w","u","v"];s===0?p="":i<2&&o.length>=1?p="coords = 0;":p=o.map(g=>`coords.${d[g+u]} = 0;`).join(`
`);let c="";i<2&&s>0?c="coords":c=e.shapeInfo.logicalShape.map((g,b)=>`coords.${d[b+u]}`).join(", ");let h="return outputValue;",m=v.sizeFromShape(e.shapeInfo.logicalShape)===1,f=v.sizeFromShape(t.logicalShape)===1;if(s===1&&!m&&!f)h=`
      return vec4(outputValue.xy, outputValue.xy);
    `;else if(m&&!f)i===1?h=`
        return vec4(outputValue.x, outputValue.x, 0., 0.);
      `:h=`
        return vec4(outputValue.x);
      `;else if(o.length){let g=s-2,b=s-1;o.indexOf(g)>-1&&o.indexOf(b)>-1?h="return vec4(outputValue.x);":o.indexOf(g)>-1?h="return vec4(outputValue.x, outputValue.y, outputValue.x, outputValue.y);":o.indexOf(b)>-1&&(h="return vec4(outputValue.xx, outputValue.zz);")}return`
    vec4 ${r}() {
      ${l} coords = getOutputCoords();
      ${p}
      vec4 outputValue = get${a}(${c});
      ${h}
    }
  `}function VZ(e,t){let n=e.name,a=n.charAt(0).toUpperCase()+n.slice(1),r="get"+a+"AtOutCoords",s=t.texShape,i=e.shapeInfo.texShape,o=e.shapeInfo.logicalShape.length,l=t.logicalShape.length;if(!e.shapeInfo.isUniform&&o===l&&e.shapeInfo.flatOffset==null&&v.arraysEqual(i,s))return`
      float ${r}() {
        return sampleTexture(${n}, resultUV);
      }
    `;let u=gt(l),p=P_(e.shapeInfo.logicalShape,t.logicalShape),d=l-o,c,h=["x","y","z","w","u","v"];o===0?c="":l<2&&p.length>=1?c="coords = 0;":c=p.map(f=>`coords.${h[f+d]} = 0;`).join(`
`);let m="";return l<2&&o>0?m="coords":m=e.shapeInfo.logicalShape.map((f,g)=>`coords.${h[g+d]}`).join(", "),`
    float ${r}() {
      ${u} coords = getOutputCoords();
      ${c}
      return get${a}(${m});
    }
  `}function gt(e){if(e<=1)return"int";if(e===2)return"ivec2";if(e===3)return"ivec3";if(e===4)return"ivec4";if(e===5)return"ivec5";if(e===6)return"ivec6";throw Error(`GPU for rank ${e} is not yet supported`)}function Q0(e,t,n){let{newShape:a,keptDims:r}=v.squeezeShape(t),s=t.length,i=e&&s===3&&t[0]===1,o=i?t.slice(1):a,l=!e&&s>1&&!v.arraysEqual(t,n)&&a.length<s||i;return{useSqueezeShape:l,uniformShape:l?o:t,keptDims:r}}function Qu(e,t){let n=JSON.parse(JSON.stringify(e));return n.shapeInfo.logicalShape=t,n}function ep(e,t){return t.map(n=>e[n]).join(", ")}function UZ(e,t,n,a){let r=n.map((p,d)=>{let c={logicalShape:p.shape,texShape:p.isUniform?null:p.texData.texShape,isUniform:p.isUniform,isPacked:p.isUniform?!1:p.texData.isPacked,flatOffset:null};return p.texData!=null&&p.texData.slice!=null&&p.texData.slice.flatOffset>0&&(c.flatOffset=p.texData.slice.flatOffset),{name:t.variableNames[d],shapeInfo:c}}),s=r.map(p=>p.shapeInfo),i={logicalShape:a.shape,texShape:a.texData.texShape,isUniform:!1,isPacked:a.texData.isPacked,flatOffset:null},o=oZ(r,i,t),l=m_(e.gl,o),u=e.createProgram(l);return H().get("ENGINE_COMPILE_ONLY")?{program:t,fragmentShader:l,source:o,webGLProgram:u,inShapeInfos:s,outShapeInfo:i,uniformLocations:null,customUniformLocations:null,infLoc:null,nanLoc:null,inShapesLocations:null,inTexShapesLocations:null,outShapeLocation:null,outShapeStridesLocation:null,outTexShapeLocation:null}:Object.assign({program:t,fragmentShader:l,source:o,webGLProgram:u,inShapeInfos:s,outShapeInfo:i},z_(e,t,u))}function z_(e,t,n){let a={},r={},s={},i=[],o,l,u,p=null,d=null;d=e.getUniformLocation(n,"NAN",!1),H().getNumber("WEBGL_VERSION")===1&&(p=e.getUniformLocation(n,"INFINITY",!1));let c=!1;for(let h=0;h<t.variableNames.length;h++){let m=t.variableNames[h];a[m]=e.getUniformLocation(n,m,c),a[`offset${m}`]=e.getUniformLocation(n,`offset${m}`,c),t.enableShapeUniforms&&(r[`${m}Shape`]=e.getUniformLocation(n,`${m}Shape`,c),s[`${m}TexShape`]=e.getUniformLocation(n,`${m}TexShape`,c))}return t.enableShapeUniforms&&(o=e.getUniformLocation(n,"outShape",c),u=e.getUniformLocation(n,"outShapeStrides",c),l=e.getUniformLocation(n,"outTexShape",c)),t.customUniforms&&t.customUniforms.forEach((h,m)=>{i[m]=e.getUniformLocation(n,h.name,c)}),{uniformLocations:a,customUniformLocations:i,infLoc:p,nanLoc:d,inShapesLocations:r,inTexShapesLocations:s,outShapeLocation:o,outShapeStridesLocation:u,outTexShapeLocation:l}}function dI(e,t){if(e.length!==t.length)throw Error(`Binary was compiled with ${e.length} inputs, but was executed with ${t.length} inputs`);e.forEach((n,a)=>{let r=n.logicalShape,s=t[a],i=s.shape;if(!v.arraysEqual(r,i))throw Error(`Binary was compiled with different shapes than the current args. Shapes ${r} and ${i} must match`);if(n.isUniform&&s.isUniform)return;let o=n.texShape,l=s.isUniform?null:s.texData.texShape;if(!v.arraysEqual(o,l))throw Error(`Binary was compiled with different texture shapes than the current args. Shape ${o} and ${l} must match`)})}function GZ(e,t,n,a,r){t.program.enableShapeUniforms||(dI(t.inShapeInfos,n),dI([t.outShapeInfo],[a]));let s=a.texData.texture,i=a.texData.texShape;a.texData.isPacked?e.setOutputPackedMatrixTexture(s.texture,i[0],i[1]):e.setOutputMatrixTexture(s.texture,i[0],i[1]),e.setProgram(t.webGLProgram),H().getNumber("WEBGL_VERSION")===1&&t.infLoc!==null&&e.gl.uniform1f(t.infLoc,1/0),t.nanLoc!==null&&e.gl.uniform1f(t.nanLoc,NaN),n.forEach((l,u)=>{let p=t.program.variableNames[u],d=t.uniformLocations[p],c=t.uniformLocations[`offset${p}`],h=t.inShapesLocations[`${p}Shape`],m=t.inTexShapesLocations[`${p}TexShape`];if(h){let{uniformShape:f}=Q0(t.program.packedInputs,l.shape,l.texData.texShape);switch(f.length){case 1:e.gl.uniform1iv(h,new Int32Array(f));break;case 2:e.gl.uniform2iv(h,new Int32Array(f));break;case 3:e.gl.uniform3iv(h,new Int32Array(f));break;case 4:e.gl.uniform4iv(h,new Int32Array(f));break;default:break}}if(m&&e.gl.uniform2i(m,l.texData.texShape[0],l.texData.texShape[1]),d!=null){if(l.isUniform){if(v.sizeFromShape(l.shape)<2)e.gl.uniform1f(d,l.uniformValues[0]);else{let f=l.uniformValues;f instanceof Float32Array||(f=new Float32Array(f)),e.gl.uniform1fv(d,f)}return}l.texData.slice!=null&&c!=null&&e.gl.uniform1i(c,l.texData.slice.flatOffset),e.setInputMatrixTexture(l.texData.texture.texture,d,u)}});let o=t.outShapeLocation;if(o)switch(a.shape.length){case 1:e.gl.uniform1iv(o,new Int32Array(a.shape));break;case 2:e.gl.uniform2iv(o,new Int32Array(a.shape));break;case 3:e.gl.uniform3iv(o,new Int32Array(a.shape));break;case 4:e.gl.uniform4iv(o,new Int32Array(a.shape));break;default:break}if(t.outShapeStridesLocation){let l=v.computeStrides(a.shape);switch(a.shape.length){case 2:e.gl.uniform1iv(t.outShapeStridesLocation,new Int32Array(l));break;case 3:e.gl.uniform2iv(t.outShapeStridesLocation,new Int32Array(l));break;case 4:e.gl.uniform3iv(t.outShapeStridesLocation,new Int32Array(l));break;default:break}}t.outTexShapeLocation&&e.gl.uniform2i(t.outTexShapeLocation,a.texData.texShape[0],a.texData.texShape[1]),t.program.customUniforms&&r&&t.program.customUniforms.forEach((l,u)=>{let p=t.customUniformLocations[u],d=r[u];if(l.type==="float")e.gl.uniform1fv(p,d);else if(l.type==="vec2")e.gl.uniform2fv(p,d);else if(l.type==="vec3")e.gl.uniform3fv(p,d);else if(l.type==="vec4")e.gl.uniform4fv(p,d);else if(l.type==="int")e.gl.uniform1iv(p,d);else if(l.type==="ivec2")e.gl.uniform2iv(p,d);else if(l.type==="ivec3")e.gl.uniform3iv(p,d);else if(l.type==="ivec4")e.gl.uniform4iv(p,d);else throw Error(`uniform type ${l.type} is not supported yet.`)}),e.executeProgram()}function HZ(e,t,n){let a="";t.concat(n).forEach(i=>{let o=i.texData!=null&&i.texData.slice!=null&&i.texData.slice.flatOffset>0;if(e.enableShapeUniforms&&!i.isUniform){let l=i.texData.texShape,{useSqueezeShape:u,uniformShape:p,keptDims:d}=Q0(e.packedInputs,i.shape,l),c="",h="",m="";if(p.length===1&&e.packedInputs){let I=[Math.ceil(l[0]/2),Math.ceil(l[1]/2)];c=`${I[0]>1}_${I[1]>1}`}else if(p.length===2&&!e.packedInputs)h=`${p[0]>1}_${p[1]>1}`;else if(p.length>2&&!e.packedInputs){let I=v.computeStrides(p);m=`${I[0]===l[1]}_${I[I.length-1]===l[1]}`}let f=i.shape.length,g=p.length===2&&v.arraysEqual(i.shape,l),b=v.sizeFromShape(i.shape)===1,y=N.getBroadcastDims(i.shape,n.shape),x=!e.packedInputs&&f===n.shape.length&&v.arraysEqual(l,n.texData.texShape),w=e.packedInputs||p.length>2?"":`${l[0]>1}_${l[1]>1}`;a+=`${f}_${x}_${u?d:""}_${p.length}_${b}_${y}_${g}_${c}_${h}_${m}_${w}_${o}`}else{let l=i.isUniform?"uniform":i.texData.texShape;a+=`${i.shape}_${l}_${o}`}});let r=e.userCode,s=e.constructor.name;return s+="_"+a+"_"+r+`${H().getNumber("WEBGL_VERSION")}`,s}function En(e){return H().getBool("WEBGL_USE_SHAPES_UNIFORMS")&&e<=4}var jZ=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outPackingScheme=rc.DENSE,this.customUniforms=[{name:"texShape",type:"ivec2"}];let t=_n();this.outputShape=e,this.enableShapeUniforms=En(this.outputShape.length),this.userCode=`
      ivec3 outCoordsFromFlatIndex(int index) {
        ${this.enableShapeUniforms?Kf(["r","c","d"],e):wo(["r","c","d"],e)}
        return ivec3(r, c, d);
      }

      void main() {
        ivec2 resTexRC = ivec2(resultUV.yx * vec2(texShape[0], texShape[1]));
        int index = 4 * (resTexRC.x * texShape[1] + resTexRC.y);

        vec4 result = vec4(0.);

        for (int i=0; i<4; i++) {
          int flatIndex = index + i;
          ivec3 rc = outCoordsFromFlatIndex(flatIndex);
          result[i] = getA(rc.x, rc.y, rc.z);
        }

        ${t.output} = result;
      }
    `}},qZ=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outPackingScheme=rc.DENSE,this.customUniforms=[{name:"texShape",type:"ivec2"}];let t=_n();this.outputShape=e,this.enableShapeUniforms=En(this.outputShape.length),this.userCode=`
      ivec3 outCoordsFromFlatIndex(int index) {
        ${this.enableShapeUniforms?Kf(["r","c","d"],e):wo(["r","c","d"],e)}
        return ivec3(r, c, d);
      }

      void main() {
        ivec2 resTexRC = ivec2(resultUV.yx * vec2(texShape[0], texShape[1]));
        int index = 4 * (resTexRC.x * texShape[1] + resTexRC.y);

        vec4 result = vec4(0.);

        for (int i=0; i<4; i++) {
          int flatIndex = index + i;
          ivec3 rc = outCoordsFromFlatIndex(flatIndex);
          result[i] = getChannel(getA(rc.x, rc.y, rc.z), vec2(rc.y, rc.z));
        }

        ${t.output} = result;
      }
    `}},KZ=class{constructor(e){this.variableNames=["A"],this.outTexUsage=ca.DOWNLOAD;let t=_n();this.outputShape=e,this.userCode=`
      ${M_}

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

      void main() {
        ivec3 coords = getOutputCoords();
        float x = getChannel(getAAtOutCoords(), vec2(coords.y, coords.z));
        ${t.output} = encode_float(x);
      }
    `}},YZ={R:0,G:1,B:2,A:3},hI=class{constructor(e,t=!1,n="RGBA"){this.variableNames=["A"],this.customUniforms=[{name:"texShape",type:"ivec2"}];let a=_n();this.outputShape=e,this.enableShapeUniforms=En(this.outputShape.length);let r="result";t&&(r="floor(result * 255. + 0.5)");let s="";for(let i=0;i<n.length;i++){let o=n[i];s+=`
          if(offset == ${i}) {
            result = values[${YZ[o]}];
          }`}this.userCode=`
      ${this.enableShapeUniforms?J0():Z0(e)}

      void main() {
        ivec3 coords = getOutputCoords();
        int flatIndex = getFlatIndex(coords);
        float result = 0.;
        int offset = imod(flatIndex, ${n.length});

        flatIndex = idiv(flatIndex, ${n.length}, 1.);

        int r = flatIndex / texShape[1];
        if (r < texShape[0]) {
          int c = imod(flatIndex, texShape[1]);
          vec2 uv = (vec2(c, r) + halfCR) / vec2(texShape[1], texShape[0]);
          vec4 values = ${a.texture2D}(A, uv);
          ${s}
        }
        ${a.output} = vec4(${r}, 0., 0., 0.);
      }
    `}},ZZ=class{constructor(e,t=!1){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.customUniforms=[{name:"texShape",type:"ivec2"}];let n=_n();this.outputShape=e,this.enableShapeUniforms=En(this.outputShape.length);let a="",r="result";t&&(r="floor(result * 255. + 0.5)");for(let s=0;s<=1;s++)for(let i=0;i<=1;i++){let o=s*2+i;a+=`
          localCoords = coords;
          if(localCoords[2] + ${i} < ${this.enableShapeUniforms?"outShape[2]":`${e[2]}`}) {
          localCoords[2] += ${i};
          if (localCoords[1] + ${s} < ${this.enableShapeUniforms?"outShape[1]":`${e[1]}`}) {
            localCoords[1] += ${s};

            flatIndex = getFlatIndex(localCoords);
            offset = imod(flatIndex, 4);

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

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

            if (offset == 0) {
              result[${o}] = values[0];
            } else if (offset == 1) {
              result[${o}] = values[1];
            } else if (offset == 2) {
              result[${o}] = values[2];
            } else {
              result[${o}] = values[3];
            }
          }
        }
        `}this.userCode=`
        ${this.enableShapeUniforms?J0():Z0(e)}

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

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

          ${a}

          ${n.output} = ${r};
        }
    `}},W_={};Ae(W_,{bindVertexProgramAttributeStreams:()=>X_,createBufferFromOutputTexture:()=>J_,createFloat16MatrixTexture:()=>H_,createFloat16PackedMatrixTexture:()=>K_,createFloat32MatrixTexture:()=>G_,createIndexBuffer:()=>U_,createPackedMatrixTexture:()=>q_,createUnsignedBytesMatrixTexture:()=>j_,createVertexBuffer:()=>V_,createVertexShader:()=>B_,downloadByteEncodedFloatMatrixFromOutputTexture:()=>eE,downloadFloat32MatrixFromBuffer:()=>Q_,downloadMatrixFromPackedOutputTexture:()=>nE,downloadPackedMatrixFromBuffer:()=>tE,getInternalFormatForFloat16MatrixTexture:()=>t1,getInternalFormatForFloat16PackedMatrixTexture:()=>r1,getInternalFormatForFloat32MatrixTexture:()=>e1,getInternalFormatForPackedMatrixTexture:()=>a1,getInternalFormatForUnsignedBytesMatrixTexture:()=>n1,uploadDenseMatrixToTexture:()=>Y_,uploadPixelDataToTexture:()=>Z_});function B_(e){let t=_n(),n=`${t.version}
    precision highp float;
    ${t.attribute} vec3 clipSpacePos;
    ${t.attribute} vec2 uv;
    ${t.varyingVs} vec2 resultUV;

    void main() {
      gl_Position = vec4(clipSpacePos, 1);
      resultUV = uv;
    }`;return h_(e,n)}function V_(e){let t=new Float32Array([-1,1,0,0,1,-1,-1,0,0,0,1,1,0,1,1,1,-1,0,1,0]);return b_(e,t)}function U_(e){let t=new Uint16Array([0,1,2,2,1,3]);return y_(e,t)}function od(e,t,n,a,r,s){v_(t,n);let i=x_(e),o=e.TEXTURE_2D;return me(e,()=>e.bindTexture(o,i)),me(e,()=>e.texParameteri(o,e.TEXTURE_WRAP_S,e.CLAMP_TO_EDGE)),me(e,()=>e.texParameteri(o,e.TEXTURE_WRAP_T,e.CLAMP_TO_EDGE)),me(e,()=>e.texParameteri(o,e.TEXTURE_MIN_FILTER,e.NEAREST)),me(e,()=>e.texParameteri(o,e.TEXTURE_MAG_FILTER,e.NEAREST)),H().getNumber("WEBGL_VERSION")===1?me(e,()=>e.texImage2D(o,0,a,t,n,0,r,s,null)):me(e,()=>e.texStorage2D(o,1,a,t,n)),me(e,()=>e.bindTexture(e.TEXTURE_2D,null)),{texture:i,texShape:[n,t]}}function e1(e){return e.internalFormatFloat}function G_(e,t,n,a){let[r,s]=id(t,n);return od(e,r,s,e1(a),a.textureFormatFloat,e.FLOAT)}function t1(e){return e.internalFormatHalfFloat}function H_(e,t,n,a){let[r,s]=id(t,n);return od(e,r,s,t1(a),a.textureFormatFloat,a.textureTypeHalfFloat)}function n1(e){return e.downloadTextureFormat}function j_(e,t,n,a){let[r,s]=id(t,n);return od(e,r,s,n1(a),e.RGBA,e.UNSIGNED_BYTE)}function a1(e){return e.internalFormatPackedFloat}function q_(e,t,n,a){let[r,s]=Xu(t,n);return od(e,r,s,a1(a),e.RGBA,e.FLOAT)}function r1(e){return e.internalFormatPackedHalfFloat}function K_(e,t,n,a){let[r,s]=Xu(t,n);return od(e,r,s,r1(a),e.RGBA,a.textureTypeHalfFloat)}function X_(e,t,n){return me(e,()=>e.bindBuffer(e.ARRAY_BUFFER,n)),mx(e,t,"clipSpacePos",n,3,20,0)&&mx(e,t,"uv",n,2,20,12)}function Y_(e,t,n,a,r,s){me(e,()=>e.bindTexture(e.TEXTURE_2D,t));let i,o,l;r instanceof Uint8Array?(i=new Uint8Array(n*a*4),o=e.UNSIGNED_BYTE,l=e.RGBA):(i=new Float32Array(n*a*4),o=e.FLOAT,l=s.internalFormatPackedFloat),i.set(r),H().getNumber("WEBGL_VERSION")===2?me(e,()=>e.texSubImage2D(e.TEXTURE_2D,0,0,0,n,a,e.RGBA,o,i)):me(e,()=>e.texImage2D(e.TEXTURE_2D,0,l,n,a,0,e.RGBA,o,i)),me(e,()=>e.bindTexture(e.TEXTURE_2D,null))}function Z_(e,t,n){me(e,()=>e.bindTexture(e.TEXTURE_2D,t)),n.data instanceof Uint8Array?H().getNumber("WEBGL_VERSION")===2?me(e,()=>e.texSubImage2D(e.TEXTURE_2D,0,0,0,n.width,n.height,e.RGBA,e.UNSIGNED_BYTE,n.data)):me(e,()=>e.texImage2D(e.TEXTURE_2D,0,e.RGBA,n.width,n.height,0,e.RGBA,e.UNSIGNED_BYTE,n.data)):H().getNumber("WEBGL_VERSION")===2?me(e,()=>e.texSubImage2D(e.TEXTURE_2D,0,0,0,e.RGBA,e.UNSIGNED_BYTE,n)):me(e,()=>e.texImage2D(e.TEXTURE_2D,0,e.RGBA,e.RGBA,e.UNSIGNED_BYTE,n)),me(e,()=>e.bindTexture(e.TEXTURE_2D,null))}function J_(e,t,n,a){let r=e.createBuffer();me(e,()=>e.bindBuffer(e.PIXEL_PACK_BUFFER,r));let s=4*4*t*n;return me(e,()=>e.bufferData(e.PIXEL_PACK_BUFFER,s,e.STREAM_READ)),me(e,()=>e.readPixels(0,0,n,t,e.RGBA,e.FLOAT,0)),me(e,()=>e.bindBuffer(e.PIXEL_PACK_BUFFER,null)),r}function Q_(e,t,n){let a=e,r=new Float32Array(n);return a.bindBuffer(a.PIXEL_PACK_BUFFER,t),a.getBufferSubData(a.PIXEL_PACK_BUFFER,0,r),a.bindBuffer(a.PIXEL_PACK_BUFFER,null),r}function eE(e,t,n,a){let[r,s]=id(t,n),i=4,o=new Uint8Array(qY(t*n,i));return me(e,()=>e.readPixels(0,0,r,s,a.downloadTextureFormat,e.UNSIGNED_BYTE,o)),new Float32Array(o.buffer)}function tE(e,t,n,a,r,s,i,o){let l=e,u=new Float32Array(KY(s,i));return l.bindBuffer(l.PIXEL_PACK_BUFFER,t),l.getBufferSubData(l.PIXEL_PACK_BUFFER,0,u),l.bindBuffer(l.PIXEL_PACK_BUFFER,null),u}function nE(e,t,n){let a=new Float32Array(t*n*4);return me(e,()=>e.readPixels(0,0,n,t,e.RGBA,e.FLOAT,a)),a}var Th=class{constructor(e){this.outputTexture=null,this.program=null,this.disposed=!1,this.vertexAttrsAreBound=!1,this.itemsToPoll=[];let t=H().getNumber("WEBGL_VERSION");e!=null?(this.gl=e,p_(t,e)):this.gl=qa(t);let n="WEBGL_color_buffer_float",a="EXT_color_buffer_half_float";if(this.parallelCompilationExtension=this.gl.getExtension("KHR_parallel_shader_compile"),H().getNumber("WEBGL_VERSION")===1){let r="OES_texture_float",s="OES_texture_half_float";if(this.textureFloatExtension=zp(this.gl,r),da(this.gl,s))this.textureHalfFloatExtension=zp(this.gl,s);else if(H().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),da(this.gl,a))this.colorBufferHalfFloatExtension=zp(this.gl,a);else if(H().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",da(this.gl,n))this.colorBufferFloatExtension=this.gl.getExtension(n);else if(da(this.gl,a))this.colorBufferHalfFloatExtension=this.gl.getExtension(a);else throw new Error("GL context does not support color renderable floats");this.vertexBuffer=V_(this.gl),this.indexBuffer=U_(this.gl),this.framebuffer=w_(this.gl),this.textureConfig=X0(this.gl,this.textureHalfFloatExtension)}get debug(){return H().getBool("DEBUG")}dispose(){if(this.disposed)return;this.program!=null&&console.warn("Disposing a GPGPUContext that still has a bound WebGLProgram. 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This is probably a resource leak, delete the output matrix texture with GPGPUContext.deleteMatrixTexture before disposing.");let e=this.gl;me(e,()=>e.finish()),me(e,()=>e.bindFramebuffer(e.FRAMEBUFFER,null)),me(e,()=>e.deleteFramebuffer(this.framebuffer)),me(e,()=>e.bindBuffer(e.ARRAY_BUFFER,null)),me(e,()=>e.bindBuffer(e.ELEMENT_ARRAY_BUFFER,null)),me(e,()=>e.deleteBuffer(this.indexBuffer)),this.disposed=!0}createFloat32MatrixTexture(e,t){return this.throwIfDisposed(),G_(this.gl,e,t,this.textureConfig)}createFloat16MatrixTexture(e,t){return this.throwIfDisposed(),H_(this.gl,e,t,this.textureConfig)}createUnsignedBytesMatrixTexture(e,t){return this.throwIfDisposed(),j_(this.gl,e,t,this.textureConfig)}uploadPixelDataToTexture(e,t){this.throwIfDisposed(),Z_(this.gl,e,t)}uploadDenseMatrixToTexture(e,t,n,a){this.throwIfDisposed(),Y_(this.gl,e,t,n,a,this.textureConfig)}createFloat16PackedMatrixTexture(e,t){return this.throwIfDisposed(),K_(this.gl,e,t,this.textureConfig)}createPackedMatrixTexture(e,t){return this.throwIfDisposed(),q_(this.gl,e,t,this.textureConfig)}deleteMatrixTexture(e){this.throwIfDisposed(),this.outputTexture===e&&(fx(this.gl,this.framebuffer),this.outputTexture=null),me(this.gl,()=>this.gl.deleteTexture(e))}downloadByteEncodedFloatMatrixFromOutputTexture(e,t,n){return this.downloadMatrixDriver(e,()=>eE(this.gl,t,n,this.textureConfig))}downloadPackedMatrixFromBuffer(e,t,n,a,r,s){return tE(this.gl,e,t,n,a,r,s,this.textureConfig)}downloadFloat32MatrixFromBuffer(e,t){return Q_(this.gl,e,t)}createBufferFromTexture(e,t,n){this.bindTextureToFrameBuffer(e);let a=J_(this.gl,t,n,this.textureConfig);return this.unbindTextureToFrameBuffer(),a}createAndWaitForFence(){let e=this.createFence(this.gl);return this.pollFence(e)}createFence(e){let t,n;if(H().getBool("WEBGL_FENCE_API_ENABLED")){let a=e,r=a.fenceSync(a.SYNC_GPU_COMMANDS_COMPLETE,0);e.flush(),n=()=>{let 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me(t,()=>t.attachShader(n,this.vertexShader)),me(t,()=>t.attachShader(n,e)),g_(t,n),this.debug&&wh(t,n),this.vertexAttrsAreBound||(this.setProgram(n),this.vertexAttrsAreBound=X_(t,this.program,this.vertexBuffer)),n}deleteProgram(e){this.throwIfDisposed(),e===this.program&&(this.program=null),e!=null&&me(this.gl,()=>this.gl.deleteProgram(e))}setProgram(e){this.throwIfDisposed(),this.program=e,this.program!=null&&this.debug&&wh(this.gl,this.program),me(this.gl,()=>this.gl.useProgram(e))}getUniformLocation(e,t,n=!0){return this.throwIfDisposed(),n?I_(this.gl,e,t):S_(this.gl,e,t)}getAttributeLocation(e,t){return this.throwIfDisposed(),me(this.gl,()=>this.gl.getAttribLocation(e,t))}getUniformLocationNoThrow(e,t){return this.throwIfDisposed(),this.gl.getUniformLocation(e,t)}setInputMatrixTexture(e,t,n){this.throwIfDisposed(),this.throwIfNoProgram(),T_(this.gl,e,t,n)}setOutputMatrixTexture(e,t,n){this.setOutputMatrixTextureDriver(e,n,t)}setOutputPackedMatrixTexture(e,t,n){this.throwIfDisposed();let[a,r]=Xu(t,n);this.setOutputMatrixTextureDriver(e,a,r)}setOutputMatrixWriteRegion(e,t,n,a){this.setOutputMatrixWriteRegionDriver(n,e,a,t)}setOutputPackedMatrixWriteRegion(e,t,n,a){throw new Error("setOutputPackedMatrixWriteRegion not implemented.")}debugValidate(){this.program!=null&&wh(this.gl,this.program),Wp(this.gl)}executeProgram(){this.throwIfDisposed(),this.throwIfNoProgram();let e=this.gl;this.debug&&this.debugValidate(),me(e,()=>e.drawElements(e.TRIANGLES,6,e.UNSIGNED_SHORT,0))}blockUntilAllProgramsCompleted(){this.throwIfDisposed(),me(this.gl,()=>this.gl.finish())}getQueryTimerExtension(){return this.disjointQueryTimerExtension==null&&(this.disjointQueryTimerExtension=zp(this.gl,H().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(H().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")===2){let n=this.gl,a=this.getQueryTimerExtensionWebGL2(),r=n.createQuery();return n.beginQuery(a.TIME_ELAPSED_EXT,r),r}let e=this.getQueryTimerExtensionWebGL1(),t=e.createQueryEXT();return e.beginQueryEXT(e.TIME_ELAPSED_EXT,t),t}endQuery(){if(H().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")===2){let t=this.gl,n=this.getQueryTimerExtensionWebGL2();t.endQuery(n.TIME_ELAPSED_EXT);return}let e=this.getQueryTimerExtensionWebGL1();e.endQueryEXT(e.TIME_ELAPSED_EXT)}async waitForQueryAndGetTime(e){return await 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e=JZ(this.itemsToPoll.map(t=>t.isDoneFn));for(let t=0;t<=e;++t){let{resolveFn:n}=this.itemsToPoll[t];n()}this.itemsToPoll=this.itemsToPoll.slice(e+1)}addItemToPoll(e,t){if(this.itemsToPoll.push({isDoneFn:e,resolveFn:t}),this.itemsToPoll.length>1)return;let n;"setTimeoutCustom"in H().platform&&(n=H().platform.setTimeoutCustom.bind(H().platform)),v.repeatedTry(()=>(this.pollItems(),this.itemsToPoll.length===0),()=>0,null,n)}bindTextureToFrameBuffer(e){this.throwIfDisposed(),kh(this.gl,e,this.framebuffer),this.debug&&Wp(this.gl)}unbindTextureToFrameBuffer(){this.outputTexture!=null?(kh(this.gl,this.outputTexture,this.framebuffer),this.debug&&Wp(this.gl)):fx(this.gl,this.framebuffer)}downloadMatrixDriver(e,t){this.bindTextureToFrameBuffer(e);let n=t();return this.unbindTextureToFrameBuffer(),n}setOutputMatrixTextureDriver(e,t,n){this.throwIfDisposed();let a=this.gl;kh(a,e,this.framebuffer),this.debug&&Wp(a),this.outputTexture=e,me(a,()=>a.viewport(0,0,t,n)),me(a,()=>a.scissor(0,0,t,n))}setOutputMatrixWriteRegionDriver(e,t,n,a){this.throwIfDisposed(),me(this.gl,()=>this.gl.scissor(e,t,n,a))}throwIfDisposed(){if(this.disposed)throw new Error("Attempted to use disposed GPGPUContext.")}throwIfNoProgram(){if(this.program==null)throw new Error("No GPU program is currently set.")}};function JZ(e){let t=0;for(;t<e.length&&e[t]();++t);return t-1}var{addImpl:QZ,bincountImpl:aE,bincountReduceImpl:e7,castImpl:t7,ceilImpl:n7,concatImpl:a7,equalImpl:r7,expImpl:s7,expm1Impl:i7,floorImpl:o7,gatherNdImpl:l7,gatherV2Impl:u7,greaterImpl:p7,greaterEqualImpl:c7,lessImpl:d7,lessEqualImpl:h7,linSpaceImpl:m7,logImpl:f7,maxImpl:g7,maximumImpl:b7,minimumImpl:y7,multiplyImpl:x7,negImpl:v7,notEqualImpl:w7,prodImpl:k7,raggedGatherImpl:I7,raggedRangeImpl:S7,raggedTensorToTensorImpl:T7,rangeImpl:N7,rsqrtImpl:C7,scatterImpl:_7,sigmoidImpl:E7,simpleAbsImpl:rE,sliceImpl:A7,sparseFillEmptyRowsImpl:$7,sparseReshapeImpl:F7,sparseSegmentReductionImpl:sE,sqrtImpl:D7,stridedSliceImpl:R7,stringNGramsImpl:M7,stringSplitImpl:P7,stringToHashBucketFastImpl:O7,subImpl:L7,tileImpl:z7,topKImpl:W7,transposeImpl:s1,uniqueImpl:B7}=oC;function iE(e,t){return["x","y","z","w","u","v"].slice(0,t).map(n=>`${e}.${n}`)}function kn(e,t){return t===1?[e]:iE(e,t)}function V7(e,t){if(e===1)return"rc";let n="";for(let a=0;a<e;a++)n+=t[a],a<e-1&&(n+=",");return n}var U7=class{constructor(e){if(this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outputShape=e,this.rank=e.length,this.enableShapeUniforms=En(this.outputShape.length),this.rank===0)this.userCode=`
        void main() {
          setOutput(vec4(getA(), 0., 0., 0.));
        }
      `;else{let t=kn("rc",this.rank),n=gt(this.rank),a=this.getOutOfBoundsCondition(t),r=this.getSetup(t),s=this.getOutput(t);this.userCode=`
        void main() {
          ${n} rc = getOutputCoords();

          if(${a}) {
            setOutput(vec4(0));
          } else {
            ${r}

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

      bool cEdge = cp1 >= ${n};
      bool rEdge = rp1 >= ${a};
    `}getOutput(e){let t=this.getSourceCoordsArr(e);return this.rank===1?`getA(rc), (rc + 1 >= ${this.enableShapeUniforms?"outShape":this.outputShape[0]} ? 0. : getA(rc + 1)), 0, 0`:`getA(${t[0]}),
            cEdge ? 0. : getA(${t[1]}),
            rEdge ? 0. : getA(${t[2]}),
            rEdge || cEdge ? 0. : getA(${t[3]})`}},oE=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"inputShape",type:"ivec3"}],this.outputShape=e,this.enableShapeUniforms=En(this.outputShape.length);let n="";for(let a=0;a<4;a++){let r="thisRC = rc;";a%2===1&&(r+="thisRC.z += 1;"),a>1&&(r+="thisRC.y += 1;"),n+=`
        ${r}
        ${a>0?"if(thisRC.y < rows && thisRC.z < cols){":""}
          int flatIndex = getFlatIndex(thisRC);

          ivec3 inputRC = inputCoordsFromReshapedOutCoords(flatIndex);
          vec2 inputRCInnerDims = vec2(float(inputRC.y),float(inputRC.z));

          result[${a}] =
            getChannel(getA(inputRC.x, inputRC.y, inputRC.z), inputRCInnerDims);
        ${a>0?"}":""}
      `}this.userCode=`
      ${G7(t,this.enableShapeUniforms)}
      ${this.enableShapeUniforms?J0():Z0(e)}

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

        vec4 result = vec4(0.);

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

        ${n}

        setOutput(result);
      }
    `}};function G7(e,t){return`
    ivec3 inputCoordsFromReshapedOutCoords(int index) {
      ${t?iZ(["r","c","d"],"inputShape"):wo(["r","c","d"],e)}
      return ivec3(r, c, d);
    }
  `}var H7=class{constructor(e){this.gpgpu=e,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0,this.freeTextures={},this.logEnabled=!1,this.usedTextures={}}acquireTexture(e,t,n){let a=fI(t,n),r=gI(e,a,n);r in this.freeTextures||(this.freeTextures[r]=[]),r in this.usedTextures||(this.usedTextures[r]=[]);let s=mI(e,a,this.gpgpu.gl,this.gpgpu.textureConfig,n);if(this.freeTextures[r].length>0){this.numFreeTextures--,this.numUsedTextures++,this._numBytesFree-=s,this.log();let o=this.freeTextures[r].shift();return this.usedTextures[r].push(o),o}let i;return a===ln.PACKED_2X2_FLOAT32?i=this.gpgpu.createPackedMatrixTexture(e[0],e[1]):a===ln.PACKED_2X2_FLOAT16?i=this.gpgpu.createFloat16PackedMatrixTexture(e[0],e[1]):a===ln.UNPACKED_FLOAT32?i=this.gpgpu.createFloat32MatrixTexture(e[0],e[1]):a===ln.UNPACKED_FLOAT16?i=this.gpgpu.createFloat16MatrixTexture(e[0],e[1]):a===ln.PACKED_4X1_UNSIGNED_BYTE&&(i=this.gpgpu.createUnsignedBytesMatrixTexture(e[0],e[1])),this.usedTextures[r].push(i),this.numUsedTextures++,this._numBytesAllocated+=s,this.log(),i}releaseTexture(e,t,n,a){if(this.freeTextures==null)return;let r=fI(n,a),s=gI(t,r,a);s in this.freeTextures||(this.freeTextures[s]=[]);let i=mI(t,r,this.gpgpu.gl,this.gpgpu.textureConfig,a),o=H().get("WEBGL_DELETE_TEXTURE_THRESHOLD");o!==-1&&this._numBytesAllocated>o?(this.gpgpu.deleteMatrixTexture(e.texture),this._numBytesAllocated-=i):(this.freeTextures[s].push(e),this.numFreeTextures++,this._numBytesFree+=i),this.numUsedTextures--;let l=this.usedTextures[s],u=l.indexOf(e);if(u<0)throw new Error("Cannot release a texture that was never provided by this texture manager");l.splice(u,1),this.log()}log(){if(!this.logEnabled)return;let e=this.numFreeTextures+this.numUsedTextures;console.log("Free/Used",`${this.numFreeTextures} / ${this.numUsedTextures}`,`(${e})`);let t=this._numBytesFree/this._numBytesAllocated;console.log(`Bytes allocated: ${this._numBytesAllocated}`),console.log(`Bytes unused: ${this._numBytesFree} (${Math.round(100*t)}%)`)}get numBytesAllocated(){return this._numBytesAllocated}get numBytesFree(){return this._numBytesFree}getNumUsedTextures(){return this.numUsedTextures}getNumFreeTextures(){return this.numFreeTextures}dispose(){if(this.freeTextures!=null){for(let e in this.freeTextures)this.freeTextures[e].forEach(t=>{this.gpgpu.deleteMatrixTexture(t.texture)});for(let e in this.usedTextures)this.usedTextures[e].forEach(t=>{this.gpgpu.deleteMatrixTexture(t.texture)});this.freeTextures=null,this.usedTextures=null,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0}}};function j7(e,t){let n=e;if(t===n.R32F)return 4;if(t===n.R16F)return 2;if(t===n.RGBA32F||t===e.RGBA)return 16;if(t===n.RGBA16F)return 8;if(t===n.RGBA8)return 4;throw new Error(`Unknown internal format ${t}`)}function mI(e,t,n,a,r){let s=q7(t,a),i;if(r){let[l,u]=Xu(e[0],e[1]);i=l*u}else{let[l,u]=id(e[0],e[1]);i=l*u}let o=j7(n,s);return i*o}function q7(e,t){switch(e){case ln.PACKED_2X2_FLOAT32:return a1(t);case ln.PACKED_2X2_FLOAT16:return r1(t);case ln.UNPACKED_FLOAT32:return e1(t);case ln.UNPACKED_FLOAT16:return t1(t);case ln.PACKED_4X1_UNSIGNED_BYTE:return n1(t);default:throw new Error(`Unknown physical texture type ${e}`)}}function K7(e){return H().getBool("WEBGL_RENDER_FLOAT32_ENABLED")?e?ln.PACKED_2X2_FLOAT32:ln.UNPACKED_FLOAT32:e?ln.PACKED_2X2_FLOAT16:ln.UNPACKED_FLOAT16}function fI(e,t){if(e===ca.UPLOAD)return ln.PACKED_2X2_FLOAT32;if(e===ca.RENDER||e==null)return K7(t);if(e===ca.DOWNLOAD||e===ca.PIXELS)return ln.PACKED_4X1_UNSIGNED_BYTE;throw new Error(`Unknown logical texture type ${e}`)}function gI(e,t,n){return`${e[0]}_${e[1]}_${t}_${n}`}var Cr=class{constructor(e,t){this.variableNames=["A"],this.outputShape=e,this.enableShapeUniforms=En(this.outputShape.length),this.userCode=`
      float unaryOperation(float x) {
        ${t}
      }

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

        setOutput(y);
      }
    `}},Ma="if (isnan(x)) return x;",X7="return x;",bI="return abs(x);",Y7="return (x >= 0.0) ? x : (exp(x) - 1.0);",Z7=Ma+`
  return (x < 0.0) ? 0.0 : x;
`,J7=Ma+`
  return (x < 0.0) ? 0.0 : min(6.0, x);
`,rl="return x;",Q7="return 1.0 / (1.0 + exp(-1.0 * x));",eJ="return x;",tJ=`
  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;
`,nJ=`
  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;
`,aJ=`
  vec4 result = min(x, vec4(6.)) * vec4(greaterThanEqual(x, vec4(0.0)));
  bvec4 isNaN = isnan(x);

  result.r = isNaN.r ? x.r : result.r;
  result.g = isNaN.g ? x.g : result.g;
  result.b = isNaN.b ? x.b : result.b;
  result.a = isNaN.a ? x.a : result.a;

  return result;
`,rJ="return 1.0 / (1.0 + exp(-1.0 * x));",qs=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.enableShapeUniforms=En(this.outputShape.length),this.userCode=`
      vec4 unaryOperation(vec4 x) {
        ${t}
      }

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

        setOutput(y);
      }
    `}},sJ=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outputShape=e,this.enableShapeUniforms=En(this.outputShape.length);let t=e.length,n=kn("rc",t),a=gt(t),r=V7(t,n),s=n.slice(-2),i=t<=1?"rc":`vec2(${s.join(",")})`;this.userCode=`
      void main() {
        ${a} rc = getOutputCoords();
        vec4 packedInput = getA(${r});

        setOutput(getChannel(packedInput, ${i}));
      }
    `}},iJ=hr.whereImpl,oJ=1e-7,lJ=1e-4,Sy={};function uJ(e){return e in Sy||(Sy[e]={}),Sy[e]}var pJ=H().getNumber("CPU_HANDOFF_SIZE_THRESHOLD"),cJ=600;function dJ(){return H().global.screen==null?1024:H().global.screen.height*H().global.screen.width*window.devicePixelRatio*cJ/1024/1024}var Xf=class extends pc{constructor(e){if(super(),this.pendingRead=new WeakMap,this.pendingDisposal=new WeakSet,this.dataRefCount=new WeakMap,this.numBytesInGPU=0,this.uploadWaitMs=0,this.downloadWaitMs=0,this.lastGlFlushTime=0,this.warnedAboutMemory=!1,this.pendingDeletes=0,this.disposed=!1,!H().getBool("HAS_WEBGL"))throw new Error("WebGL is not supported on this device");let t;if(e!=null){if(e instanceof Th)t=e;else{let n=qa(H().getNumber("WEBGL_VERSION"),e);t=new Th(n)}this.binaryCache={},this.gpgpuCreatedLocally=!1}else{let n=qa(H().getNumber("WEBGL_VERSION"));t=new Th(n),this.binaryCache=uJ(H().getNumber("WEBGL_VERSION")),this.gpgpuCreatedLocally=!0}this.gpgpu=t,this.canvas=this.gpgpu.gl.canvas,this.textureManager=new H7(this.gpgpu),this.numMBBeforeWarning=dJ(),this.texData=new om(this,_a())}nextDataId(){return Xf.nextDataId++}numDataIds(){return this.texData.numDataIds()-this.pendingDeletes}writeTexture(e,t,n,a,r,s){let i=this.makeTensorInfo(t,n),o=this.texData.get(i.dataId);o.isPacked=!1,o.texture={texture:e,texShape:[a,r]},o.texShape=[a,r];let l=Bp(t),u=new hI(l,!1,s),p=this.runWebGLProgram(u,[i],n,[[a,r]]);return p.shape=t,o.texture=null,this.disposeIntermediateTensorInfo(i),p.dataId}write(e,t,n){if((H().getBool("WEBGL_CHECK_NUMERICAL_PROBLEMS")||H().getBool("DEBUG"))&&this.checkNumericalProblems(e),n==="complex64"&&e!=null)throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");let a={id:this.nextDataId()};return this.texData.set(a,{shape:t,dtype:n,values:e,usage:ca.UPLOAD,refCount:1}),a}refCount(e){return this.texData.has(e)?this.texData.get(e).refCount:0}incRef(e){let t=this.texData.get(e);t.refCount++}decRef(e){if(this.texData.has(e)){let t=this.texData.get(e);t.refCount--}}move(e,t,n,a,r){if(H().getBool("DEBUG")&&this.checkNumericalProblems(t),a==="complex64")throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");this.texData.set(e,{shape:n,dtype:a,values:t,usage:ca.UPLOAD,refCount:r})}disposeIntermediateTensorInfo(e){this.disposeData(e.dataId)}readSync(e){let t=this.texData.get(e),{values:n,dtype:a,complexTensorInfos:r,slice:s,shape:i,isPacked:o}=t;if(s!=null){let d;o?d=new qs(i,rl):d=new Cr(i,rl);let c=this.runWebGLProgram(d,[{dataId:e,shape:i,dtype:a}],a),h=this.readSync(c.dataId);return this.disposeIntermediateTensorInfo(c),h}if(n!=null)return this.convertAndCacheOnCPU(e);if(a==="string")return n;let l=this.activeTimers!=null,u;l&&(u=v.now());let p;if(a==="complex64"){let d=this.readSync(r.real.dataId),c=this.readSync(r.imag.dataId);p=N.mergeRealAndImagArrays(d,c)}else p=this.getValuesFromTexture(e);return l&&(this.downloadWaitMs+=v.now()-u),this.convertAndCacheOnCPU(e,p)}async read(e){if(this.pendingRead.has(e)){let h=this.pendingRead.get(e);return new Promise(m=>h.push(m))}let t=this.texData.get(e),{values:n,shape:a,slice:r,dtype:s,complexTensorInfos:i,isPacked:o}=t;if(r!=null){let h;o?h=new qs(a,rl):h=new Cr(a,rl);let m=this.runWebGLProgram(h,[{dataId:e,shape:a,dtype:s}],s),f=this.read(m.dataId);return this.disposeIntermediateTensorInfo(m),f}if(n!=null)return this.convertAndCacheOnCPU(e);if(H().getBool("DEBUG")&&!H().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")&&H().getNumber("WEBGL_VERSION")===2)throw new Error("tensor.data() with WEBGL_DOWNLOAD_FLOAT_ENABLED=false and WEBGL_VERSION=2 not yet supported.");let l=null,u;if(s!=="complex64"&&H().get("WEBGL_BUFFER_SUPPORTED")){u=this.decode(e);let h=this.texData.get(u.dataId);l=this.gpgpu.createBufferFromTexture(h.texture.texture,...fh(a))}this.pendingRead.set(e,[]),s!=="complex64"&&await this.gpgpu.createAndWaitForFence();let p;if(s==="complex64"){let h=await Promise.all([this.read(i.real.dataId),this.read(i.imag.dataId)]),m=h[0],f=h[1];p=N.mergeRealAndImagArrays(m,f)}else if(l==null)p=this.getValuesFromTexture(e);else{let h=v.sizeFromShape(a);p=this.gpgpu.downloadFloat32MatrixFromBuffer(l,h)}if(u!=null&&this.disposeIntermediateTensorInfo(u),l!=null){let h=this.gpgpu.gl;me(h,()=>h.deleteBuffer(l))}let d=this.convertAndCacheOnCPU(e,p),c=this.pendingRead.get(e);return this.pendingRead.delete(e),c.forEach(h=>h(d)),this.pendingDisposal.has(e)&&(this.pendingDisposal.delete(e),this.disposeData(e)&&_a().removeDataId(e,this),this.pendingDeletes--),d}readToGPU(e,t={}){let n=this.texData.get(e),{values:a,shape:r,slice:s,dtype:i,isPacked:o,texture:l}=n;if(i==="complex64")throw new Error("Does not support reading texture for complex64 dtype.");if(s!=null){let c;o?c=new qs(r,rl):c=new Cr(r,rl);let h=this.runWebGLProgram(c,[{dataId:e,shape:r,dtype:i}],i),m=this.readToGPU(h,t);return this.disposeIntermediateTensorInfo(h),m}if(l==null)throw a!=null?new Error("Data is not on GPU but on CPU."):new Error("There is no data on GPU or CPU.");let u=this.decode(e,t.customTexShape),p=_a().makeTensorFromTensorInfo(u),d=this.texData.get(u.dataId);return Object.assign({tensorRef:p},d.texture)}bufferSync(e){let t=this.readSync(e.dataId);if(e.dtype==="string")try{let n=t.map(a=>v.decodeString(a));return Oe(e.shape,e.dtype,n)}catch(n){throw new Error("Failed to decode encoded string bytes into utf-8")}return Oe(e.shape,e.dtype,t)}checkNumericalProblems(e){if(e!=null)for(let t=0;t<e.length;t++){let n=e[t];if(!c_(n))throw H().getBool("WEBGL_RENDER_FLOAT32_CAPABLE")?Error(`The value ${n} cannot be represented with your current settings. Consider enabling float32 rendering: 'tf.env().set('WEBGL_RENDER_FLOAT32_ENABLED', true);'`):Error(`The value ${n} cannot be represented on this device.`)}}getValuesFromTexture(e){let{shape:t,dtype:n,isPacked:a}=this.texData.get(e),r=v.sizeFromShape(t);if(H().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")){let d=this.decode(e),c=this.texData.get(d.dataId),h=this.gpgpu.downloadMatrixFromPackedTexture(c.texture.texture,...fh(t)).subarray(0,r);return this.disposeIntermediateTensorInfo(d),h}let s=H().getBool("WEBGL_PACK")&&a===!0,i=s?Bp(t):t,o=s?new XZ(i):new KZ(i),l=this.runWebGLProgram(o,[{shape:i,dtype:n,dataId:e}],"float32"),u=this.texData.get(l.dataId),p=this.gpgpu.downloadByteEncodedFloatMatrixFromOutputTexture(u.texture.texture,u.texShape[0],u.texShape[1]).subarray(0,r);return this.disposeIntermediateTensorInfo(l),p}timerAvailable(){return H().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0}time(e){let t=this.activeTimers,n=[],a=!1;this.programTimersStack==null?(this.programTimersStack=n,a=!0):this.activeTimers.push(n),this.activeTimers=n,e();let r=v.flatten(this.activeTimers.map(o=>o.query)).filter(o=>o!=null),s=v.flatten(this.activeTimers.map(o=>o.name)).filter(o=>o!=null);this.activeTimers=t,a&&(this.programTimersStack=null);let i={uploadWaitMs:this.uploadWaitMs,downloadWaitMs:this.downloadWaitMs,kernelMs:null,wallMs:null};return(async()=>{if(H().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0){let o=await Promise.all(r);i.kernelMs=v.sum(o),i.getExtraProfileInfo=()=>o.map((l,u)=>({name:s[u],ms:l})).map(l=>`${l.name}: ${l.ms}`).join(", ")}else i.kernelMs={error:"WebGL query timers are not supported in this environment."};return this.uploadWaitMs=0,this.downloadWaitMs=0,i})()}memory(){return{unreliable:!1,numBytesInGPU:this.numBytesInGPU,numBytesInGPUAllocated:this.textureManager.numBytesAllocated,numBytesInGPUFree:this.textureManager.numBytesFree}}startTimer(){return H().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?this.gpgpu.beginQuery():{startMs:v.now(),endMs:null}}endTimer(e){return H().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?(this.gpgpu.endQuery(),e):(e.endMs=v.now(),e)}async getQueryTime(e){if(H().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0)return this.gpgpu.waitForQueryAndGetTime(e);let t=e;return t.endMs-t.startMs}disposeData(e,t=!1){if(this.pendingDisposal.has(e))return!1;if(!this.texData.has(e))return!0;if(t?this.texData.get(e).refCount=0:this.texData.get(e).refCount--,!t&&this.texData.get(e).refCount>0)return!1;if(this.pendingRead.has(e))return this.pendingDisposal.add(e),this.pendingDeletes++,!1;this.releaseGPUData(e);let{complexTensorInfos:n}=this.texData.get(e);return n!=null&&(this.disposeData(n.real.dataId,t),this.disposeData(n.imag.dataId,t)),this.texData.delete(e),!0}releaseGPUData(e){let{texture:t,dtype:n,texShape:a,usage:r,isPacked:s,slice:i}=this.texData.get(e),o=i&&i.origDataId||e,l=this.dataRefCount.get(o);l>1?this.dataRefCount.set(o,l-1):(this.dataRefCount.delete(o),t!=null&&(this.numBytesInGPU-=this.computeBytes(a,n),this.textureManager.releaseTexture(t,a,r,s)));let u=this.texData.get(e);u.texture=null,u.texShape=null,u.isPacked=!1,u.slice=null}getTexture(e){return this.uploadToGPU(e),this.texData.get(e).texture.texture}getDataInfo(e){return this.texData.get(e)}shouldExecuteOnCPU(e,t=pJ){return H().getBool("WEBGL_CPU_FORWARD")&&e.every(n=>this.texData.get(n.dataId).texture==null&&v.sizeFromShape(n.shape)<t)}getGPGPUContext(){return this.gpgpu}where(e){N.warn("tf.where() in webgl locks the UI thread. Call tf.whereAsync() instead");let t=e.dataSync();return iJ(e.shape,t)}packedUnaryOp(e,t,n){let a=new qs(e.shape,t),r=this.compileAndRun(a,[e],n);return _a().makeTensorFromTensorInfo(r)}abs(e){if(this.shouldExecuteOnCPU([e])&&e.dtype!=="complex64"){let a=rE(this.texData.get(e.dataId).values);return this.makeOutput(e.shape,e.dtype,a)}if(H().getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(e,bI,e.dtype);let t=new Cr(e.shape,bI),n=this.compileAndRun(t,[e]);return _a().makeTensorFromTensorInfo(n)}makeTensorInfo(e,t,n){let a;if(t==="string"&&n!=null&&n.length>0&&v.isString(n[0])){let r=n.map(s=>v.encodeString(s));a=this.write(r,e,t)}else a=this.write(n,e,t);return this.texData.get(a).usage=null,{dataId:a,shape:e,dtype:t}}makeOutput(e,t,n){return _a().makeTensorFromTensorInfo(this.makeTensorInfo(e,t,n),this)}unpackTensor(e){let t=new sJ(e.shape);return this.runWebGLProgram(t,[e],e.dtype)}packTensor(e){let t=new U7(e.shape),n=!0;return this.runWebGLProgram(t,[e],e.dtype,null,n)}packedReshape(e,t){let n=[ci(e.shape),...di(e.shape)],a={dtype:e.dtype,shape:n,dataId:e.dataId},r=[ci(t),...di(t)],s=new oE(r,n),i=!0,o=[n],l=this.runWebGLProgram(s,[a],e.dtype,o,i);return{dataId:l.dataId,shape:t,dtype:l.dtype}}decode(e,t){let n=this.texData.get(e),{isPacked:a,shape:r,dtype:s}=n;if(t!=null){let d=v.sizeFromShape(r),c=t[0]*t[1]*4;v.assert(d<=c,()=>"customTexShape is too small. Row * Column * 4 should be equal or larger than the size of the tensor data.")}let i=Bp(r),o;a?o=new qZ(i):o=new jZ(i);let l=!0,u=[t!=null?t:fh(i)],p=this.runWebGLProgram(o,[{shape:i,dtype:s,dataId:e}],s,u,l,t);return{dtype:s,shape:r,dataId:p.dataId}}runWebGLProgram(e,t,n,a,r=!1,s){let i=this.makeTensorInfo(e.outputShape,n),o=this.texData.get(i.dataId);if(e.packedOutput&&(o.isPacked=!0),e.outPackingScheme===rc.DENSE){let g=s!=null?s:fh(e.outputShape);o.texShape=g.map(b=>b*2)}if(e.outTexUsage!=null&&(o.usage=e.outTexUsage),v.sizeFromShape(i.shape)===0)return o.values=v.getTypedArrayFromDType(i.dtype,0),i;let l=[],u=t.map(g=>{if(g.dtype==="complex64")throw new Error("GPGPUProgram does not support complex64 input. For complex64 dtypes, please separate the program into real and imaginary parts.");let b=this.texData.get(g.dataId);if(b.texture==null){if(!e.packedInputs&&v.sizeFromShape(g.shape)<=H().getNumber("WEBGL_SIZE_UPLOAD_UNIFORM"))return{shape:g.shape,texData:null,isUniform:!0,uniformValues:b.values};e.packedInputs&&(b.isPacked=!0,b.shape=g.shape)}if(this.uploadToGPU(g.dataId),!!b.isPacked!=!!e.packedInputs)g=b.isPacked?this.unpackTensor(g):this.packTensor(g),l.push(g),b=this.texData.get(g.dataId);else if(b.isPacked&&!sc(b.shape,g.shape)){let y=g,x=g.shape;g.shape=b.shape,g=this.packedReshape(g,x),l.push(g),b=this.texData.get(g.dataId),y.shape=x}return{shape:g.shape,texData:b,isUniform:!1}});this.uploadToGPU(i.dataId);let p={shape:i.shape,texData:o,isUniform:!1},d=HZ(e,u,p),c=this.getAndSaveBinary(d,()=>UZ(this.gpgpu,e,u,p)),h=this.activeTimers!=null,m;h&&(m=this.startTimer()),H().get("ENGINE_COMPILE_ONLY")||GZ(this.gpgpu,c,u,p,a),l.forEach(g=>this.disposeIntermediateTensorInfo(g)),h&&(m=this.endTimer(m),this.activeTimers.push({name:e.constructor.name,query:this.getQueryTime(m)}));let f=H().get("WEBGL_FLUSH_THRESHOLD");if(f>0){let g=v.now();g-this.lastGlFlushTime>f&&(this.gpgpu.gl.flush(),this.lastGlFlushTime=g)}if(!H().getBool("WEBGL_LAZILY_UNPACK")&&o.isPacked&&r===!1){let g=this.unpackTensor(i);return this.disposeIntermediateTensorInfo(i),g}return i}compileAndRun(e,t,n,a,r=!1){return n=n||t[0].dtype,this.runWebGLProgram(e,t,n,a,r)}getAndSaveBinary(e,t){return e in this.binaryCache||(this.binaryCache[e]=t()),this.binaryCache[e]}getTextureManager(){return this.textureManager}dispose(){this.disposed||(H().getBool("IS_TEST")||Object.keys(this.binaryCache).forEach(e=>{this.gpgpu.deleteProgram(this.binaryCache[e].webGLProgram),delete this.binaryCache[e]}),this.textureManager.dispose(),this.canvas!=null&&typeof HTMLCanvasElement!="undefined"&&this.canvas instanceof HTMLCanvasElement?this.canvas.remove():this.canvas=null,this.gpgpuCreatedLocally&&(this.gpgpu.program=null,this.gpgpu.dispose()),this.disposed=!0)}floatPrecision(){return this.floatPrecisionValue==null&&(this.floatPrecisionValue=P(()=>{if(!H().get("WEBGL_RENDER_FLOAT32_ENABLED")){let e=H().getBool("DEBUG");H().set("DEBUG",!1);let t=this.abs(ye(1e-8)).dataSync()[0];if(H().set("DEBUG",e),t>0)return 32}return 16})),this.floatPrecisionValue}epsilon(){return this.floatPrecision()===32?oJ:lJ}uploadToGPU(e){let t=this.texData.get(e),{shape:n,dtype:a,values:r,texture:s,usage:i,isPacked:o}=t;if(s!=null)return;let l=this.activeTimers!=null,u;l&&(u=v.now());let p=t.texShape;if(p==null&&(p=__(n,o),t.texShape=p),r!=null){let d=Bp(n),c,h=p[1],m=p[0],f=r instanceof Uint8Array||r instanceof Uint8ClampedArray;(o||!f)&&([h,m]=Xu(p[0],p[1])),o?c=new ZZ(d,f):c=new hI(d,f);let g=f?[m,h]:p,b=this.makeTensorInfo(g,a),y=this.texData.get(b.dataId);f?y.usage=ca.PIXELS:y.usage=ca.UPLOAD,y.texShape=g,this.gpgpu.uploadDenseMatrixToTexture(this.getTexture(b.dataId),h,m,r);let x=[[m,h]],w=!0,I=this.runWebGLProgram(c,[b],a,x,w),T=this.texData.get(I.dataId);t.texShape=T.texShape,t.isPacked=T.isPacked,t.usage=T.usage,H().get("ENGINE_COMPILE_ONLY")?this.disposeData(I.dataId):(t.texture=T.texture,t.values=null,this.texData.delete(I.dataId)),this.disposeIntermediateTensorInfo(b),l&&(this.uploadWaitMs+=v.now()-u)}else{let d=this.acquireTexture(p,i,a,o);t.texture=d}}convertAndCacheOnCPU(e,t){let n=this.texData.get(e),{dtype:a}=n;return this.releaseGPUData(e),t!=null&&(n.values=hJ(t,a)),n.values}acquireTexture(e,t,n,a){if(this.numBytesInGPU+=this.computeBytes(e,n),!this.warnedAboutMemory&&this.numBytesInGPU>this.numMBBeforeWarning*1024*1024){let r=(this.numBytesInGPU/1024/1024).toFixed(2);this.warnedAboutMemory=!0,console.warn(`High memory usage in GPU: ${r} MB, most likely due to a memory leak`)}return this.textureManager.acquireTexture(e,t,a)}computeBytes(e,t){return e[0]*e[1]*v.bytesPerElement(t)}checkCompileCompletion(){for(let[,e]of Object.entries(this.binaryCache))this.checkCompletion_(e)}async checkCompileCompletionAsync(){let e=[];if(this.gpgpu.parallelCompilationExtension){for(let[,t]of Object.entries(this.binaryCache))e.push(this.checkCompletionAsync_(t));return Promise.all(e)}else{for(let[,t]of Object.entries(this.binaryCache)){let n=new Promise(a=>{try{this.checkCompletion_(t),a(!0)}catch(r){throw r}});e.push(n)}return Promise.all(e)}}async checkCompletionAsync_(e){return this.gpgpu.gl.getProgramParameter(e.webGLProgram,this.gpgpu.parallelCompilationExtension.COMPLETION_STATUS_KHR)?this.checkCompletion_(e):(await Jv(),this.checkCompletionAsync_(e))}checkCompletion_(e){if(this.gpgpu.gl.getProgramParameter(e.webGLProgram,this.gpgpu.gl.LINK_STATUS)===!1)throw console.log(this.gpgpu.gl.getProgramInfoLog(e.webGLProgram)),this.gpgpu.gl.getShaderParameter(e.fragmentShader,this.gpgpu.gl.COMPILE_STATUS)===!1?(Y0(e.source,this.gpgpu.gl.getShaderInfoLog(e.fragmentShader)),new Error("Failed to compile fragment shader.")):new Error("Failed to link vertex and fragment shaders.");return!0}getUniformLocations(){for(let[,e]of Object.entries(this.binaryCache)){let{uniformLocations:t,customUniformLocations:n,infLoc:a,nanLoc:r,inShapesLocations:s,inTexShapesLocations:i,outShapeLocation:o,outShapeStridesLocation:l,outTexShapeLocation:u}=z_(this.gpgpu,e.program,e.webGLProgram);e.uniformLocations=t,e.customUniformLocations=n,e.infLoc=a,e.nanLoc=r,e.inShapesLocations=s,e.inTexShapesLocations=i,e.outShapeLocation=o,e.outShapeStridesLocation=l,e.outTexShapeLocation=u}}createTensorFromTexture(e,t,n){let{texture:a,height:r,width:s,channels:i}=e,o=_a().backend;if(!o.gpgpu.gl.isTexture(a))throw new Error("The texture is invalid. Also, please make sure the texture and the TFJS WebGL backend are using the same canvas. If you want to use your own custom canvas, you have to create and use the custom TFJS WebGL backend created from the canvas through 'new tf.MathBackendWebGL(customCanvas)'.");let l=o.writeTexture(a,t,n,r,s,i);return _a().makeTensorFromDataId(l,t,n,o)}};Xf.nextDataId=0;function hJ(e,t){if(t==="float32"||t==="complex64")return e;if(t==="int32"||t==="bool"){let n=t==="int32"?new Int32Array(e.length):new Uint8Array(e.length);for(let a=0;a<n.length;++a)n[a]=Math.round(e[a]);return n}else throw new Error(`Unknown dtype ${t}`)}var mJ="4.0.0";function lE(){H().set("WEBGL_FORCE_F16_TEXTURES",!0)}$c.isBrowser()&&Gm("webgl",()=>new Xf,2);var fJ={forceHalfFloat:lE},i1=`
  if (isnan(a)) return a;
  if (isnan(b)) return b;
`,$l=class{constructor(e,t,n){this.variableNames=["A","B"],this.outputShape=N.assertAndGetBroadcastShape(t,n),this.enableShapeUniforms=En(this.outputShape.length),this.userCode=`
      float binaryOperation(float a, float b) {
        ${e}
      }

      void main() {
        float a = getAAtOutCoords();
        float b = getBAtOutCoords();
        setOutput(binaryOperation(a, b));
      }
    `}},ld=`
  result.r = isNaN.r ? NAN : result.r;
  result.g = isNaN.g ? NAN : result.g;
  result.b = isNaN.b ? NAN : result.b;
  result.a = isNaN.a ? NAN : result.a;
`,ud=class{constructor(e,t,n,a=!1){this.variableNames=["A","B"],this.supportsBroadcasting=!0,this.packedInputs=!0,this.packedOutput=!0,this.outputShape=N.assertAndGetBroadcastShape(t,n);let r=this.outputShape.length;this.enableShapeUniforms=En(r);let s="";if(a)if(r===0||v.sizeFromShape(this.outputShape)===1)s=`
          result.y = 0.;
          result.z = 0.;
          result.w = 0.;
        `;else if(s=`
          ${gt(r)} coords = getOutputCoords();
        `,r===1)this.enableShapeUniforms?s+=`
            result.y = (coords + 1) >= outShape ? 0. : result.y;
            result.z = 0.;
            result.w = 0.;
          `:s+=`
            result.y = (coords + 1) >= ${this.outputShape[0]} ? 0. : result.y;
            result.z = 0.;
            result.w = 0.;
          `;else{let i=kn("coords",r);this.enableShapeUniforms?s+=`
            bool nextRowOutOfBounds =
              (${i[r-2]} + 1) >= outShape[${r} - 2];
            bool nextColOutOfBounds =
              (${i[r-1]} + 1) >= outShape[${r} - 1];
            result.y = nextColOutOfBounds ? 0. : result.y;
            result.z = nextRowOutOfBounds ? 0. : result.z;
            result.w = nextColOutOfBounds || nextRowOutOfBounds ? 0. : result.w;
          `:s+=`
            bool nextRowOutOfBounds =
              (${i[r-2]} + 1) >= ${this.outputShape[r-2]};
            bool nextColOutOfBounds =
              (${i[r-1]} + 1) >= ${this.outputShape[r-1]};
            result.y = nextColOutOfBounds ? 0. : result.y;
            result.z = nextRowOutOfBounds ? 0. : result.z;
            result.w = nextColOutOfBounds || nextRowOutOfBounds ? 0. : result.w;
          `}this.userCode=`
      vec4 binaryOperation(vec4 a, vec4 b) {
        ${e}
      }

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

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

        setOutput(result);
      }
    `}};function aa(e){let{inputs:t,backend:n}=e,{x:a}=t;return n.incRef(a.dataId),{dataId:a.dataId,shape:a.shape,dtype:a.dtype}}var gJ={kernelName:Ri,backendName:"webgl",kernelFunc:aa};function _s(e){let{inputs:t,backend:n}=e,{real:a,imag:r}=t,s=n.makeTensorInfo(a.shape,"complex64"),i=n.texData.get(s.dataId),o=aa({inputs:{x:a},backend:n}),l=aa({inputs:{x:r},backend:n});return i.complexTensorInfos={real:o,imag:l},s}var bJ={kernelName:mm,backendName:"webgl",kernelFunc:_s},uE="return (a < 0.) ? b * a : a;",pE=`
  vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));
  return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);
`;function yJ(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{alpha:s}=a,i=n.makeTensorInfo([],"float32",v.createScalarValue(s,"float32")),o=H().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new ud(pE,r.shape,i.shape):new $l(uE,r.shape,i.shape),l=n.runWebGLProgram(o,[r,i],"float32");return n.disposeIntermediateTensorInfo(i),l}var xJ={kernelName:Mi,backendName:"webgl",kernelFunc:yJ},cE="return (a < 0.) ? b * a : a;",dE=`
  vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));
  return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);
`;function vJ(e){let{inputs:t,backend:n}=e,{x:a,alpha:r}=t,s=H().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new ud(dE,a.shape,r.shape):new $l(cE,a.shape,r.shape);return n.runWebGLProgram(s,[a,r],"float32")}var wJ={kernelName:Ki,backendName:"webgl",kernelFunc:vJ},tp="if (isnan(x)) return x;";function Ye({opSnippet:e,packedOpSnippet:t,cpuKernelImpl:n,dtype:a}){return({inputs:r,backend:s})=>{let{x:i}=r,o=s,l=a||i.dtype;if(o.shouldExecuteOnCPU([i])&&n!=null){let d=o.texData.get(i.dataId),c=n(d.values,l);return o.makeTensorInfo(i.shape,l,c)}let u=H().getBool("WEBGL_PACK_UNARY_OPERATIONS")&&t!=null,p;return u?p=new qs(i.shape,t):p=new Cr(i.shape,e),o.runWebGLProgram(p,[i],l)}}function cn({opSnippet:e,packedOpSnippet:t,checkOutOfBounds:n=!1,supportsComplex:a=!1,cpuKernelImpl:r,dtype:s}){return({inputs:i,backend:o})=>{let{a:l,b:u}=i,p=o;if(a&&l.dtype==="complex64"){let m=p.texData.get(l.dataId),f=p.texData.get(u.dataId),[g,b]=[[m.complexTensorInfos.real,f.complexTensorInfos.real],[m.complexTensorInfos.imag,f.complexTensorInfos.imag]].map(x=>{let[w,I]=x,T={dataId:w.dataId,dtype:w.dtype,shape:l.shape},C={dataId:I.dataId,dtype:I.dtype,shape:u.shape},E=new $l(e,l.shape,u.shape);return p.runWebGLProgram(E,[T,C],fa(w.dtype,I.dtype))}),y=_s({inputs:{real:g,imag:b},backend:p});return p.disposeIntermediateTensorInfo(g),p.disposeIntermediateTensorInfo(b),y}let d=s||fa(l.dtype,u.dtype);if((l.dtype==="string"||u.dtype==="string"||p.shouldExecuteOnCPU([l,u]))&&r!=null){let m=p.texData.get(l.dataId).values,f=p.texData.get(u.dataId).values,g=l.dtype==="string"?N.fromUint8ToStringArray(m):m,b=l.dtype==="string"?N.fromUint8ToStringArray(f):f,[y,x]=r(l.shape,u.shape,g,b,d),w=p.makeTensorInfo(x,d),I=p.texData.get(w.dataId);return I.values=y,w}let c=H().getBool("WEBGL_PACK_BINARY_OPERATIONS")&&t!=null,h;return c?h=new ud(t,l.shape,u.shape,n):h=new $l(e,l.shape,u.shape),p.runWebGLProgram(h,[l,u],d)}}function ic(e,t=!1){if(e==="linear")return t?eJ:X7;if(e==="relu")return t?nJ:Z7;if(e==="elu")return t?tJ:Y7;if(e==="relu6")return t?aJ:J7;if(e==="prelu")return t?dE:cE;if(e==="leakyrelu")return t?pE:uE;if(e==="sigmoid")return t?rJ:Q7;throw new Error(`Activation ${e} has not been implemented for the WebGL backend.`)}var hE=class{constructor(e,t,n,a=!1,r=!1,s=!1,i=null,o=!1,l=!1){this.variableNames=["matrixA","matrixB"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=n,this.enableShapeUniforms=En(this.outputShape.length);let u=a?e[1]:e[2],p=Math.ceil(u/2),d=a?"i * 2, rc.y":"rc.y, i * 2",c=r?"rc.z, i * 2":"i * 2, rc.z",h=a?["a.xxyy","a.zzww"]:["a.xxzz","a.yyww"],m=r?["b.xzxz","b.ywyw"]:["b.xyxy","b.zwzw"],f="",g="";i&&(o?f=`vec4 activation(vec4 a) {
          vec4 b = getPreluActivationWeightsAtOutCoords();
          ${i}
        }`:l?f=`vec4 activation(vec4 a) {
          vec4 b = getLeakyreluAlphaAtOutCoords();
          ${i}
        }`:f=`vec4 activation(vec4 x) {
          ${i}
        }`,g="result = activation(result);");let b=s?"result += getBiasAtOutCoords();":"";s&&this.variableNames.push("bias"),o&&this.variableNames.push("preluActivationWeights"),l&&this.variableNames.push("leakyreluAlpha");let y="rc.x",x="rc.x";e[0]<t[0]?y=`int(min(float(rc.x), ${e[0]-1}.))`:t[0]<e[0]&&(x=`int(min(float(rc.x), ${t[0]-1}.))`),this.userCode=`
      ${f}
      // Don't use uniform for sharedDimensionPacked for performance.
      const float sharedDimension = ${p}.0;

      vec4 dot2x2ARowBCol(ivec3 rc) {
        vec4 result = vec4(0);
        for (int i = 0; i < ${p}; i++) {
          int batchA = ${y};
          int batchB = ${x};
          vec4 a = getMatrixA(batchA, ${d});
          vec4 b = getMatrixB(batchB, ${c});

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

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

        ${b}

        ${g}

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

      void main() {
        float areal = getARealAtOutCoords();
        float aimag = getAImagAtOutCoords();
        float breal = getBRealAtOutCoords();
        float bimag = getBImagAtOutCoords();
        setOutput(binaryOpComplex(areal, aimag, breal, bimag));
      }
    `}},vI="return a * b;";function o1(e){let{inputs:t,backend:n}=e,{a,b:r}=t,s=N.upcastType(a.dtype,r.dtype);if(a.dtype==="complex64"){let o=n.texData.get(a.dataId),l=n.texData.get(r.dataId),u=new xI(yI.REAL,a.shape,r.shape),p=new xI(yI.IMAG,a.shape,r.shape),d=[{dataId:o.complexTensorInfos.real.dataId,dtype:o.complexTensorInfos.real.dtype,shape:a.shape},{dataId:o.complexTensorInfos.imag.dataId,dtype:o.complexTensorInfos.imag.dtype,shape:a.shape},{dataId:l.complexTensorInfos.real.dataId,dtype:l.complexTensorInfos.real.dtype,shape:r.shape},{dataId:l.complexTensorInfos.imag.dataId,dtype:l.complexTensorInfos.imag.dtype,shape:r.shape}],c=n.runWebGLProgram(u,d,"float32"),h=n.runWebGLProgram(p,d,"float32"),m=_s({inputs:{real:c,imag:h},backend:n});return n.disposeIntermediateTensorInfo(c),n.disposeIntermediateTensorInfo(h),m}if(n.shouldExecuteOnCPU([a,r])){let o=n.texData.get(a.dataId),l=n.texData.get(r.dataId),[u,p]=x7(a.shape,r.shape,o.values,l.values,s),d=n.makeTensorInfo(p,s),c=n.texData.get(d.dataId);return c.values=u,d}let i;return H().getBool("WEBGL_PACK_BINARY_OPERATIONS")?i=new ud(vI,a.shape,r.shape):i=new $l(vI,a.shape,r.shape),n.runWebGLProgram(i,[a,r],s)}var kJ={kernelName:Gi,backendName:"webgl",kernelFunc:o1};function IJ(e,t,n){let a=[ci(e.shape),...di(e.shape)],r={dtype:e.dtype,shape:a,dataId:e.dataId},s=[ci(t),...di(t)],i=new oE(s,a),o=!0,l=[a],u=n.runWebGLProgram(i,[r],e.dtype,l,o);return{dataId:u.dataId,shape:t,dtype:u.dtype}}function de(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{shape:s}=a,i=n,o=v.sizeFromShape(r.shape),l=v.inferFromImplicitShape(s,o),u=v.sizeFromShape(l);v.assert(o===u,()=>`The new shape (${l}) has ${u} elements and the old shape (${r.shape}) has ${o} elements. The new shape and old shape must have the same number of elements.`);let p=i.texData.get(r.dataId);return p.isPacked&&!sc(r.shape,l)&&!(p.texture!==null&&sc(p.shape,l))?IJ(r,l,i):(i.incRef(r.dataId),{dataId:r.dataId,shape:l,dtype:r.dtype})}var SJ={kernelName:vu,backendName:"webgl",kernelFunc:de},wI=class{constructor(e,t){this.variableNames=["x"];let{windowSize:n,batchSize:a,inSize:r,outSize:s}=e;this.outputShape=[a,s];let i=Math.floor(n/4)*4,o=n%4,l="sumValue += dot(values, ones);";if(t!=null){let p=1/t;l=`sumValue += dot(values * ${v.isInt(p)?p.toPrecision(2):p}, ones);`}let u="";r%n>0&&(u=`
        if (inIdx < 0 || inIdx >= ${r}) {
          return 0.0;
        }
      `),this.userCode=`
      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);

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

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

        float sumValue = 0.0;

        for (int i = 0; i < ${i}; i += 4) {
          int inIdx = inOffset + i;
          vec4 values = vec4(
            getValue(batch, inIdx),
            getValue(batch, inIdx + 1),
            getValue(batch, inIdx + 2),
            getValue(batch, inIdx + 3)
          );

          ${l}
        }

        int inIdx = inOffset + ${i};
        if (${o===1}) {
          vec4 values = vec4(getValue(batch, inIdx), 0.0, 0.0, 0.0);

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

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

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

      float getValue(int batch, int inIdx) {
        ${h}
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      }

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

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

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

          ${d}
        }

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

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

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

          ${d}
        }
        setOutput(${l});
      }
    `}};function NJ(e){let t=[];for(;t.length===0||t[t.length-1].outSize!==1;){let n=t.length?t[t.length-1].outSize:e[1],a=N.computeOptimalWindowSize(n);t.push({inSize:n,windowSize:a,outSize:Math.ceil(n/a)})}return t}function Io(e,t,n,a){let r=NJ(e.shape),s=e;for(let i=0;i<r.length;i++){let{inSize:o,windowSize:l,outSize:u}=r[i],p,d;n==="mean"?p=i===0?new wI({windowSize:l,inSize:o,batchSize:e.shape[0],outSize:u},o):new wI({windowSize:l,inSize:o,batchSize:e.shape[0],outSize:u}):p=new TJ({windowSize:l,inSize:o,batchSize:e.shape[0],outSize:u},n),d=s,s=a.runWebGLProgram(p,[s],t),d.dataId!==e.dataId&&a.disposeIntermediateTensorInfo(d)}return s}var CJ=class{constructor(e,t){this.variableNames=["A"];let n=new Array(e.length);for(let s=0;s<n.length;s++)n[s]=e[t[s]];this.outputShape=n,this.rank=n.length;let a=gt(this.rank),r=_J(t);this.userCode=`
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      vec4 result = vec4(0.);
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          result[3] = ${l};
        }
      }
      setOutput(result);
    }
    `}};function Yf(e,t,n){let a=H().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new EJ(e.shape,t):new CJ(e.shape,t);return n.runWebGLProgram(a,[e],e.dtype)}function AJ(e,t,n,a){let r=t,s=e.shape.length,i=v.parseAxisParam(r,e.shape),o=i,l=N.getAxesPermutation(o,s),u=l!=null,p=e;u&&(p=Yf(e,l,a),o=N.getInnerMostAxes(o.length,s)),N.assertAxesAreInnerMostDims("sum",o,s);let[d,c]=N.computeOutAndReduceShapes(p.shape,o),h=d;n&&(h=N.expandShapeToKeepDim(d,i));let m=v.sizeFromShape(c),f=v.sizeFromShape(e.shape)/m,g=de({inputs:{x:p},attrs:{shape:[f,m]},backend:a}),b=Um(e.dtype),y=Io(g,b,"sum",a),x=de({inputs:{x:y},attrs:{shape:h},backend:a});return a.disposeIntermediateTensorInfo(g),a.disposeIntermediateTensorInfo(y),u&&a.disposeIntermediateTensorInfo(p),x}function Zf(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{axis:s,keepDims:i}=a;return AJ(r,s,i,n)}var $J={kernelName:io,backendName:"webgl",kernelFunc:Zf};function Sn(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{perm:s}=a,i=n,o=r.shape.length,l=new Array(o);for(let p=0;p<l.length;p++)l[p]=r.shape[s[p]];let u;if(i.shouldExecuteOnCPU([r])){let p=i.texData.get(r.dataId).values,d=s1(p,r.shape,r.dtype,s,l);u=i.makeTensorInfo(l,r.dtype);let c=i.texData.get(u.dataId);c.values=d}else u=Yf(r,s,i);return u}var FJ={kernelName:_r,backendName:"webgl",kernelFunc:Sn},mE=1e3;function nm({a:e,b:t,transposeA:n,transposeB:a,backend:r,bias:s=null,preluActivationWeights:i=null,leakyreluAlpha:o=0,activation:l=null}){let u=e.shape.length,p=t.shape.length,d=n?e.shape[u-2]:e.shape[u-1],c=a?t.shape[p-1]:t.shape[p-2],h=n?e.shape[u-1]:e.shape[u-2],m=a?t.shape[p-2]:t.shape[p-1],f=e.shape.slice(0,-2),g=t.shape.slice(0,-2),b=v.sizeFromShape(f),y=v.sizeFromShape(g),x=Ou.assertAndGetBroadcastShape(e.shape.slice(0,-2),t.shape.slice(0,-2)).concat([h,m]);v.assert(d===c,()=>`Error in matMul: inner shapes (${d}) and (${c}) of Tensors with shapes ${e.shape} and ${t.shape} and transposeA=${n} and transposeB=${a} must match.`);let w=n?[b,d,h]:[b,h,d],I=a?[y,m,c]:[y,c,m],T=de({inputs:{x:e},backend:r,attrs:{shape:w}}),C=de({inputs:{x:t},backend:r,attrs:{shape:I}}),E=[T,C],A=Math.max(b,y),R=n?T.shape[1]:T.shape[2],F=s!=null,S=i!=null,M=l==="leakyrelu",B=l!=null?ic(l,!0):null,U=F||S||M||B!=null,G;if((h===1||m===1)&&R>mE&&U===!1){let K=T,Z=C;n&&(K=Sn({inputs:{x:T},backend:r,attrs:{perm:[0,2,1]}}),E.push(K)),a&&(Z=Sn({inputs:{x:C},backend:r,attrs:{perm:[0,2,1]}}),E.push(Z));let Q=m!==1,ee=m===1,ae=K;Q&&(ae=de({inputs:{x:K},backend:r,attrs:{shape:[A,R,1]}}),E.push(ae));let te=m===1?2:1,le=Z;ee&&(le=de({inputs:{x:Z},backend:r,attrs:{shape:[A,1,R]}}),E.push(le));let ie=o1({inputs:{a:ae,b:le},backend:r});G=Zf({inputs:{x:ie},backend:r,attrs:{axis:te,keepDims:!0}}),E.push(ie)}else{let K=fa(e.dtype,t.dtype),Z=new hE(w,I,[A,h,m],n,a,F,B,S,M),Q=[T,C];if(s!=null&&Q.push(s),S&&Q.push(i),M){let ee=r.makeTensorInfo([],"float32",v.createScalarValue(o,"float32"));Q.push(ee),E.push(ee)}G=r.runWebGLProgram(Z,Q,K)}let q=de({inputs:{x:G},backend:r,attrs:{shape:x}});E.push(G);for(let K of E)r.disposeIntermediateTensorInfo(K);return q}function DJ(e){let{inputs:t,backend:n,attrs:a}=e,{a:r,b:s,bias:i,preluActivationWeights:o}=t,{transposeA:l,transposeB:u,activation:p,leakyreluAlpha:d}=a;return nm({a:r,b:s,transposeA:l,transposeB:u,backend:n,bias:i,preluActivationWeights:o,leakyreluAlpha:d,activation:p})}var RJ={kernelName:Qs,backendName:"webgl",kernelFunc:DJ},kI="return abs(x);";function MJ(e){let{inputs:t,backend:n}=e,{x:a}=t;if(n.shouldExecuteOnCPU([a])&&a.dtype!=="complex64"){let s=n.texData.get(a.dataId),i=rE(s.values);return n.makeTensorInfo(a.shape,a.dtype,i)}let r;return H().getBool("WEBGL_PACK_UNARY_OPERATIONS")?r=new qs(a.shape,kI):r=new Cr(a.shape,kI),n.runWebGLProgram(r,[a],a.dtype)}var PJ={kernelName:Dl,backendName:"webgl",kernelFunc:MJ},OJ=Ma+`
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      void main() {
        ${n.join(`
        `)}

        float result = ${a};
        setOutput(result);
      }
    `}},jJ=class{constructor(e,t){this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.variableNames=t.map((r,s)=>`T${s}`);let n=[];this.variableNames.forEach(r=>{n.push(`vec4 v${r} = get${r}AtOutCoords();`)});let a=this.variableNames.map(r=>`v${r}`).join(" + ");this.userCode=`
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        vec4 result = ${a};
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    `}};function Nh(e){let{inputs:t,backend:n}=e,a=t;if(a.length===1)return aa({inputs:{x:a[0]},backend:n});if(a.length>H().get("WEBGL_MAX_TEXTURES_IN_SHADER")){let o=Math.floor(a.length/2),l=Nh({inputs:a.slice(0,o),backend:n}),u=Nh({inputs:a.slice(o),backend:n});return Nh({inputs:[l,u],backend:n})}let r=a.map(o=>o.dtype).reduce((o,l)=>fa(o,l)),s=a.map(o=>o.shape),i=H().getBool("WEBGL_PACK")?new jJ(a[0].shape,s):new HJ(a[0].shape,s);return n.runWebGLProgram(i,a,r)}var qJ={kernelName:fi,backendName:"webgl",kernelFunc:Nh};function KJ(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{axis:s,keepDims:i}=a,o=r.shape.length,l=v.parseAxisParam(s,r.shape),u=l,p=N.getAxesPermutation(u,o),d=r;p!=null&&(d=Sn({inputs:{x:r},backend:n,attrs:{perm:p}}),u=N.getInnerMostAxes(u.length,o)),N.assertAxesAreInnerMostDims("all",u,o);let[c,h]=N.computeOutAndReduceShapes(d.shape,u),m=v.sizeFromShape(h),f=de({inputs:{x:d},backend:n,attrs:{shape:[-1,m]}}),g=Io(f,f.dtype,"all",n),b;if(i){let y=N.expandShapeToKeepDim(c,l);b=de({inputs:{x:g},backend:n,attrs:{shape:y}})}else b=de({inputs:{x:g},backend:n,attrs:{shape:c}});return n.disposeIntermediateTensorInfo(f),n.disposeIntermediateTensorInfo(g),p!=null&&n.disposeIntermediateTensorInfo(d),b}var XJ={kernelName:Pl,backendName:"webgl",kernelFunc:KJ};function YJ(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{axis:s,keepDims:i}=a,o=r.shape.length,l=v.parseAxisParam(s,r.shape),u=l,p=N.getAxesPermutation(u,o),d=r;p!=null&&(d=Sn({inputs:{x:r},backend:n,attrs:{perm:p}}),u=N.getInnerMostAxes(u.length,o)),N.assertAxesAreInnerMostDims("any",u,o);let[c,h]=N.computeOutAndReduceShapes(d.shape,u),m=v.sizeFromShape(h),f=de({inputs:{x:d},backend:n,attrs:{shape:[-1,m]}}),g=Io(f,f.dtype,"any",n),b;if(i){let y=N.expandShapeToKeepDim(c,l);b=de({inputs:{x:g},backend:n,attrs:{shape:y}})}else b=de({inputs:{x:g},backend:n,attrs:{shape:c}});return n.disposeIntermediateTensorInfo(f),n.disposeIntermediateTensorInfo(g),p!=null&&n.disposeIntermediateTensorInfo(d),b}var ZJ={kernelName:Ol,backendName:"webgl",kernelFunc:YJ},JJ=class{constructor(e,t,n){this.variableNames=["A"];let{windowSize:a,batchSize:r,outSize:s}=e;n||this.variableNames.push("bestIndicesA"),this.outputShape=[r,s];let i=t==="max"?">":"<",o=n?"inOffset + i;":"round(getBestIndicesA(batch, inOffset + i));";this.userCode=`
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        ivec2 coords = getOutputCoords();
        int batch = coords[0];
        int outIdx = coords[1];
        int inOffset = outIdx * ${a};

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

        for (int i = 0; i < ${a}; i++) {
          int inIdx = ${o};
          float candidate = getA(batch, inIdx);
          if (candidate ${i} bestValue) {
            bestValue = candidate;
            bestIndex = inIdx;
          }
        }
        setOutput(float(bestIndex));
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    `}},QJ=class{constructor(e,t,n,a){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,v.assert(e.length>2,()=>`Packed arg${n.charAt(0).toUpperCase()+n.slice(1)} supports only inputs with rank above 2.`);let r=e[e.length-1],s=Math.ceil(r/t);this.outputShape=e.slice(0,-1),s>1&&this.outputShape.push(s),a||this.variableNames.push("bestIndicesA");let i=this.outputShape,o=i.length,l=gt(o),u=kn("coords",o),p,d;if(s===1){d=o+1;let C=gt(d);p=`
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        ${C} sourceLocB = ${C}(${u.join()}, 0);
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        ${l} sourceLocG = coords;
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        ${l} sourceLocB = coords;
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          inIdx = round(vec4(getBestIndicesAChannel(${f.join()}),
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      }
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        ${l} coords = getOutputCoords();
        bool hasNextCol = ${u[o-1]} < ${i[o-1]-1};
        bool hasNextRow = ${u[o-2]} < ${i[o-2]-1};
        ${p}
        ivec4 srcIdx = ivec4(sourceLocR${h}, sourceLocG${h},
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        ivec4 inIdx = srcIdx;
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        vec4 bestValue = ${I};

        for (int i = 0; i < ${t}; i++) {
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          vec4 candidate = ${I};
          bvec4 nan = isnan(candidate);
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          srcIdx++;
        }
        setOutput(bestIndex);
      }
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return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,y9=Ye({opSnippet:b9}),x9={kernelName:Bl,backendName:"webgl",kernelFunc:y9},oc=class{constructor(e,t,n,a=!1,r=!1){if(this.variableNames=["x"],t==="avg"&&n)throw new Error("Cannot compute positions for average pool.");let s=e.filterWidth,i=e.strideHeight,o=e.strideWidth,l=e.dilationHeight,u=e.dilationWidth,p=e.effectiveFilterHeight,d=e.effectiveFilterWidth,c=e.padInfo.top,h=e.padInfo.left;this.outputShape=e.outShape;let m=t==="avg",f=`((batch  * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + d`,g=`(xR * ${e.inWidth} + xC) * ${e.inChannels} + d`,b="0.0";if(m||(b="-1.0 / 1e-20"),n){let C=">=";this.userCode=`
        const ivec2 strides = ivec2(${i}, ${o});
        const ivec2 pads = ivec2(${c}, ${h});

        void main() {
          ivec4 coords = getOutputCoords();
          int batch = coords[0];
          int d = coords[3];

          ivec2 xRCCorner = coords.yz * strides - pads;
          int xRCorner = xRCCorner.x;
          int xCCorner = xRCCorner.y;

          // max/min x(?, ?, d) to get y(yR, yC, d).
          // ? = to be determined
          float minMaxValue = 0.0;
          float minMaxValueFound = 0.0;
          int minMaxPosition = 0;
          float avgValue = 0.0;

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

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

            for (int wC = 0; wC < ${d};
                wC += ${u}) {
              int xC = xCCorner + wC;

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

              float value = getX(batch, xR, xC, d);

              // If a min / max value has already been found, use it. If not,
              // use the current value.
              float currMinMaxValue = mix(
                  value, minMaxValue, minMaxValueFound);
              if (value ${C} currMinMaxValue) {
                minMaxValue = value;
                minMaxValueFound = 1.0;
                minMaxPosition = ${a?r?f:g:`wR * ${d} + wC`};
              }
            }
          }
          setOutput(float(minMaxPosition));
        }
      `;return}let y="max",x=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="avg"&&(x="avgValue / count");let w=Math.floor(s/4)*4,I=s%4,T=`
      if (${m}) {
        avgValue += dot(values, ones);
      } else {
        minMaxValue = ${y}(values, minMaxValue);
      }
    `;this.userCode=`
      const ivec2 strides = ivec2(${i}, ${o});
      const ivec2 pads = ivec2(${c}, ${h});
      const float initializationValue = ${b};
      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);

      float count = 0.0;

      float getValue(int batch, int xR, int xC, int d) {
        if (xC < 0 || xC >= ${e.inWidth}) {
          return initializationValue;
        }
        count += 1.0;
        return getX(batch, xR, xC, d);
      }

      void main() {
        ivec4 coords = getOutputCoords();
        int batch = coords[0];
        int d = coords[3];

        ivec2 xRCCorner = coords.yz * strides - pads;
        int xRCorner = xRCCorner.x;
        int xCCorner = xRCCorner.y;

        // max/min x(?, ?, d) to get y(yR, yC, d).
        // ? = to be determined
        vec4 minMaxValue = vec4(${b});
        float avgValue = 0.0;
        count = 0.0;

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

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

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

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

            ${T}
          }

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

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

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

            ${T}
          }
        }
        setOutput(${x});
      }
    `}},l1=class{constructor(e,t,n,a=!1,r=!1){if(this.variableNames=["x"],t==="avg"&&n)throw new Error("Cannot compute positions for average pool.");let s=e.filterWidth,i=e.strideDepth,o=e.strideHeight,l=e.strideWidth,u=e.dilationDepth,p=e.dilationHeight,d=e.dilationWidth,c=e.effectiveFilterDepth,h=e.effectiveFilterHeight,m=e.effectiveFilterWidth,f=e.padInfo.front,g=e.padInfo.top,b=e.padInfo.left;this.outputShape=e.outShape;let y=t==="avg",x="0.0";if(y||(x="-1.0 / 1e-20"),n){let A=">=";this.userCode=`
        const ivec3 strides =
            ivec3(${i}, ${o}, ${l});
        const ivec3 pads = ivec3(${f}, ${g}, ${b});

        void main() {
          ivec5 coords = getOutputCoords();
          int batch = coords.x;
          int ch = coords.u;

          ivec3 xCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;
          int xDCorner = xCorner.x;
          int xRCorner = xCorner.y;
          int xCCorner = xCorner.z;

          // max/min x(?, ?, ?, ch) to get y(yD, yR, yC, ch).
          // ? = to be determined
          float minMaxValue = 0.0;
          float minMaxValueFound = 0.0;
          int minMaxPosition = 0;

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

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

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

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

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

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

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

                // If a min / max value has already been found, use it. If not,
                // use the current value.
                float currMinMaxValue = mix(
                    value, minMaxValue, minMaxValueFound);
                if (value ${A} currMinMaxValue) {
                  minMaxValue = value;
                  minMaxValueFound = 1.0;
                  minMaxPosition = ${a?r?`(((batch * ${e.inDepth} + xD) * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + ch`:`((xD * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + ch`:`wD * ${h} * ${m} +
                      wR * ${m} + wC`};
                }
              }
            }
          }
          setOutput(float(minMaxPosition));
        }
      `;return}let w="max",I=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="avg"&&(I="avgValue / count");let T=Math.floor(s/4)*4,C=s%4,E=`
      if (${y}) {
        avgValue += dot(values, ones);
      } else {
        minMaxValue = ${w}(values, minMaxValue);
      }
    `;this.userCode=`
      const ivec3 strides =
        ivec3(${i}, ${o}, ${l});
      const ivec3 pads = ivec3(${f}, ${g}, ${b});
      const float initializationValue = ${x};
      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);

      float count = 0.0;

      float getValue(int batch, int xD, int xR, int xC, int ch) {
        if (xC < 0 || xC >= ${e.inWidth}) {
          return initializationValue;
        }
        count += 1.0;
        return getX(batch, xD, xR, xC, ch);
      }

      void main() {
        ivec5 coords = getOutputCoords();
        int batch = coords.x;
        int ch = coords.u;

        ivec3 xCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;
        int xDCorner = xCorner.x;
        int xRCorner = xCorner.y;
        int xCCorner = xCorner.z;

        // max/min x(?, ?, ?, d) to get y(yD, yR, yC, ch).
        // ? = to be determined
        vec4 minMaxValue = vec4(${x});
        float avgValue = 0.0;
        count = 0.0;

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

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

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

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

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

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

              ${E}
            }

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

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

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

              ${E}
            }
          }
          setOutput(${I});
        }
      }
    `}};function v9(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t;Yu(r,"avgPool");let{filterSize:s,strides:i,pad:o,dimRoundingMode:l}=a,u=1;v.assert(N.eitherStridesOrDilationsAreOne(i,u),()=>`Error in avgPool: Either strides or dilations must be 1. Got strides ${i} and dilations '${u}'`);let p=N.computePool2DInfo(r.shape,s,i,u,o,l);if(p.filterWidth===1&&p.filterHeight===1&&v.arraysEqual(p.inShape,p.outShape))return aa({inputs:{x:r},backend:n});let d=new oc(p,"avg",!1);return n.runWebGLProgram(d,[r],"float32")}var w9={kernelName:bi,backendName:"webgl",kernelFunc:v9};function k9(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{filterSize:s,strides:i,pad:o,dimRoundingMode:l,dataFormat:u}=a,p=[1,1,1],d=N.computePool3DInfo(r.shape,s,i,p,o,l,u),c=new l1(d,"avg",!1);return n.runWebGLProgram(c,[r],"float32")}var I9={kernelName:dc,backendName:"webgl",kernelFunc:k9},S9=class{constructor(e){this.variableNames=["dy"],this.outputShape=e.inShape;let t=e.filterHeight,n=e.filterWidth,a=e.strideHeight,r=e.strideWidth,s=e.dilationHeight,i=e.dilationWidth,o=e.effectiveFilterHeight,l=e.effectiveFilterWidth,u=o-1-e.padInfo.top,p=l-1-e.padInfo.left,d=1/(t*n);this.userCode=`
      const ivec2 pads = ivec2(${u}, ${p});
      const float avgMultiplier = float(${d});

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

        ivec2 dyRCCorner = coords.yz - pads;
        int dyRCorner = dyRCCorner.x;
        int dyCCorner = dyRCCorner.y;

        // Convolve dy(?, ?, d) with pos mask(:, :, d) to get dx(xR, xC, d).
        // ? = to be determined. : = across all values in that axis.
        float dotProd = 0.0;
        for (int wR = 0; wR < ${o};
            wR += ${s}) {
          float dyR = float(dyRCorner + wR) / ${a}.0;

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

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

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

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

            dotProd += dyValue * avgMultiplier;
          }
        }
        setOutput(dotProd);
      }
    `}},T9=class{constructor(e){this.variableNames=["dy"],this.outputShape=e.inShape;let t=e.filterDepth,n=e.filterHeight,a=e.filterWidth,r=e.strideDepth,s=e.strideHeight,i=e.strideWidth,o=e.dilationDepth,l=e.dilationHeight,u=e.dilationWidth,p=e.effectiveFilterDepth,d=e.effectiveFilterHeight,c=e.effectiveFilterWidth,h=p-1-e.padInfo.front,m=d-1-e.padInfo.top,f=c-1-e.padInfo.left,g=1/(t*n*a);this.userCode=`
      const ivec3 pads = ivec3(${h}, ${m}, ${f});
      const float avgMultiplier = float(${g});

      void main() {
        ivec5 coords = getOutputCoords();
        int batch = coords.x;
        int ch = coords.u;

        ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads;
        int dyDCorner = dyCorner.x;
        int dyRCorner = dyCorner.y;
        int dyCCorner = dyCorner.z;

        // Convolve dy(?, ?, ?, d) with pos mask(:, :, :, ch) to get
        // dx(xD, xR, xC, ch).
        // ? = to be determined. : = across all values in that axis.
        float dotProd = 0.0;

        for (int wD = 0; wD < ${p};
            wD += ${o}) {
          float dyD = float(dyDCorner + wD) / ${r}.0;

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

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

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

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

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

              float dyValue = getDy(batch, idyD, idyR, idyC, ch);

              dotProd += dyValue * avgMultiplier;
            }
          }
        }
        setOutput(dotProd);
      }
    `}};function N9(e){let{inputs:t,backend:n,attrs:a}=e,{dy:r,input:s}=t,i=s,{filterSize:o,strides:l,pad:u,dimRoundingMode:p}=a,d=[1,1,1],c=N.computePool3DInfo(i.shape,o,l,d,u,p),h=new T9(c);return n.runWebGLProgram(h,[r],i.dtype)}var C9={kernelName:cm,backendName:"webgl",kernelFunc:N9};function _9(e){let{inputs:t,backend:n,attrs:a}=e,{dy:r,input:s}=t,i=s;Yu([r,s],"avgPoolGrad");let{filterSize:o,strides:l,pad:u}=a,p=N.computePool2DInfo(i.shape,o,l,1,u),d=new S9(p);return n.runWebGLProgram(d,[r],i.dtype)}var E9={kernelName:pm,backendName:"webgl",kernelFunc:_9};function A9(e){let{inputs:t,backend:n,attrs:a}=e,{a:r,b:s}=t,{transposeA:i,transposeB:o}=a;return nm({a:r,b:s,transposeA:i,transposeB:o,backend:n})}var $9={kernelName:yi,backendName:"webgl",kernelFunc:A9},F9=class{constructor(e,t,n,a,r,s){this.outputShape=[],this.variableNames=["x","mean","variance"],N.assertAndGetBroadcastShape(e,t),N.assertAndGetBroadcastShape(e,n);let i="0.0";a!=null&&(N.assertAndGetBroadcastShape(e,a),this.variableNames.push("offset"),i="getOffsetAtOutCoords()");let o="1.0";r!=null&&(N.assertAndGetBroadcastShape(e,r),this.variableNames.push("scale"),o="getScaleAtOutCoords()"),this.outputShape=e,this.userCode=`
      void main() {
        float x = getXAtOutCoords();
        float mean = getMeanAtOutCoords();
        float variance = getVarianceAtOutCoords();
        float offset = ${i};
        float scale = ${o};
        float inv = scale * inversesqrt(variance + float(${s}));
        setOutput(dot(vec3(x, -mean, offset), vec3(inv, inv, 1)));
      }
    `}},D9=class{constructor(e,t,n,a,r,s){this.packedInputs=!0,this.packedOutput=!0,this.variableNames=["x","mean","variance"],N.assertAndGetBroadcastShape(e,t),N.assertAndGetBroadcastShape(e,n);let i="vec4(0.0)";a!=null&&(N.assertAndGetBroadcastShape(e,a),this.variableNames.push("offset"),i="getOffsetAtOutCoords()");let o="vec4(1.0)";r!=null&&(N.assertAndGetBroadcastShape(e,r),this.variableNames.push("scale"),o="getScaleAtOutCoords()"),this.outputShape=e,this.userCode=`
      void main() {
        vec4 offset = ${i};
        vec4 scale = ${o};

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

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

        setOutput((x - mean) * inv + offset);
      }
    `}},R9=({inputs:e,backend:t,attrs:n})=>{let{x:a,mean:r,variance:s,offset:i,scale:o}=e;v.assert(r.shape.length===s.shape.length,()=>"Batch normalization gradient requires mean and variance to have equal ranks."),v.assert(i==null||r.shape.length===i.shape.length,()=>"Batch normalization gradient requires mean and offset to have equal ranks."),v.assert(o==null||r.shape.length===o.shape.length,()=>"Batch normalization gradient requires mean and scale to have equal ranks.");let{varianceEpsilon:l}=n;l==null&&(l=.001);let u=[a,r,s],p=null;i!=null&&(p=i.shape,u.push(i));let d=null;o!=null&&(d=o.shape,u.push(o));let c=H().getBool("WEBGL_PACK_NORMALIZATION")?new D9(a.shape,r.shape,s.shape,p,d,l):new F9(a.shape,r.shape,s.shape,p,d,l);return t.runWebGLProgram(c,u,u[0].dtype)},M9={kernelName:Fi,backendName:"webgl",kernelFunc:R9},P9=class{constructor(e){this.variableNames=["source"],this.outputShape=e,this.rank=e.length;let t=gt(this.rank);this.customUniforms=[{name:"start",arrayIndex:this.rank,type:"int"}];let n=O9(this.rank),a,r=e.map((s,i)=>`sourceLoc.${yx[i]} = start[${i}] + coords.${yx[i]};`);a=`
        ${t} sourceLoc;
        ${t} coords = getOutputCoords();
        ${r.join(`
`)}
      `,this.userCode=`
      void main() {
        ${a}
        setOutput(getSource(${n}));
      }
    `}},yx=["x","y","z","w","u","v"];function O9(e){if(e===1)return"sourceLoc";if(e<=6)return yx.slice(0,e).map(t=>"sourceLoc."+t).join(",");throw Error(`Slicing for rank ${e} is not yet supported`)}var L9=class{constructor(e){this.variableNames=["source"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.rank=e.length,this.customUniforms=[{name:"start",arrayIndex:this.rank,type:"int"}];let t=gt(this.rank),n=kn("coords",this.rank),a=kn("sourceLoc",this.rank),r=this.rank===1?"sourceLoc":`vec2(${a.slice(-2).join()})`,s=`getChannel(getSource(${a.join()}), ${r})`,i=`
      result.x = ${s};
      if (++${n[this.rank-1]} < ${e[this.rank-1]}) {
        ++${a[this.rank-1]};
        result.y = ${s};
        --${a[this.rank-1]};
      }
    `,o=this.rank===1?"":`
      --${n[this.rank-1]};
      if (++${n[this.rank-2]} < ${e[this.rank-2]}) {
        ++${a[this.rank-2]};
        result.z = ${s};
        if (++${n[this.rank-1]} < ${e[this.rank-1]}) {
          ++${a[this.rank-1]};
          result.w = ${s};
        }
      }
    `,l=this.rank<=4?`sourceLoc = coords +
            ${t}(${e.map((u,p)=>`start[${p}]`).join()});`:e.map((u,p)=>`${a[p]} = ${n[p]} + start[${p}];`).join(`
`);this.userCode=`
      void main() {
        ${t} coords = getOutputCoords();
        ${t} sourceLoc;
        ${l}
        vec4 result = vec4(0.);
        ${i}
        ${o}
        setOutput(result);
      }
    `}};function z9(e,t,n,a){let r=a.texData.get(e.dataId),s=a.makeTensorInfo(n,e.dtype),i=a.texData.get(s.dataId);Object.assign(i,r),i.refCount=1,i.shape=n,i.dtype=e.dtype;let o=jt.computeFlatOffset(t,v.computeStrides(e.shape));r.slice&&(o+=r.slice.flatOffset),i.slice={flatOffset:o,origDataId:r.slice&&r.slice.origDataId||e.dataId};let l=a.dataRefCount.get(i.slice.origDataId)||1;return a.dataRefCount.set(i.slice.origDataId,l+1),s}function np(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{begin:s,size:i}=a,[o,l]=jt.parseSliceParams(r,s,i);if(jt.assertParamsValid(r,o,l),v.sizeFromShape(l)===0)return n.makeTensorInfo(l,r.dtype,[]);if(n.shouldExecuteOnCPU([r])||r.dtype==="string"){let d=n.texData.get(r.dataId),c=A7(d.values,o,l,r.shape,r.dtype);return n.makeTensorInfo(l,r.dtype,c)}let{isPacked:u}=n.texData.get(r.dataId),p=jt.isSliceContinous(r.shape,o,l);if(u||!p){let d=H().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new L9(l):new P9(l),c=[o];return n.runWebGLProgram(d,[r],r.dtype,c)}return n.uploadToGPU(r.dataId),z9(r,o,l,n)}var W9={kernelName:Su,backendName:"webgl",kernelFunc:np},B9=e=>{let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{blockShape:s,crops:i}=a;v.assert(r.shape.length<=4,()=>"batchToSpaceND for rank > 4 with a WebGL backend not implemented yet");let o=s.reduce((y,x)=>y*x),l=N.getReshaped(r.shape,s,o),u=N.getPermuted(l.length,s.length),p=N.getReshapedPermuted(r.shape,s,o),d=N.getSliceBeginCoords(i,s.length),c=N.getSliceSize(p,i,s.length),h=[],m=de({inputs:{x:r},backend:n,attrs:{shape:l}}),f=Sn({inputs:{x:m},backend:n,attrs:{perm:u}}),g=de({inputs:{x:f},backend:n,attrs:{shape:p}}),b=np({inputs:{x:g},backend:n,attrs:{begin:d,size:c}});return h.push(m),h.push(f),h.push(g),h.forEach(y=>n.disposeIntermediateTensorInfo(y)),b},V9={kernelName:Ul,backendName:"webgl",kernelFunc:B9};function U9(e){let{inputs:t,backend:n,attrs:a}=e,{x:r,weights:s}=t,{size:i}=a,o=n.readSync(r.dataId),l=n.readSync(s.dataId),u=aE(o,l,s.dtype,s.shape,i);return n.makeTensorInfo([i],s.dtype,u)}var G9={kernelName:dm,backendName:"webgl",kernelFunc:U9};function H9(e){let{inputs:t,backend:n}=e,{s0:a,s1:r}=t,s=n.readSync(a.dataId),i=n.readSync(r.dataId),o=N.assertAndGetBroadcastShape(Array.from(s),Array.from(i));return n.makeTensorInfo([o.length],"int32",Int32Array.from(o))}var j9={kernelName:hm,backendName:"webgl",kernelFunc:H9},q9="return float(a != b);",yE=cn({opSnippet:q9,cpuKernelImpl:w7,dtype:"bool"}),K9={kernelName:hu,backendName:"webgl",kernelFunc:yE};function pd(e){let{inputs:t,backend:n}=e,{input:a}=t,r=n.texData.get(a.dataId);return aa({inputs:{x:r.complexTensorInfos.real},backend:n})}var X9={kernelName:Pm,backendName:"webgl",kernelFunc:pd},Y9="return float(int(x));";function Z9(e,t){let n=new Cr(e.shape,Y9),a=t.runWebGLProgram(n,[e],"int32");return{dataId:a.dataId,shape:a.shape,dtype:a.dtype}}function xx(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{dtype:s}=a;if(s==="complex64"){if(r.dtype==="complex64")return aa({inputs:{x:r},backend:n});let i=It(r.shape),o=xx({inputs:{x:r},backend:n,attrs:{dtype:"float32"}}),l=_s({inputs:{real:o,imag:i},backend:n});return i.dispose(),n.disposeIntermediateTensorInfo(o),l}if(r.dtype==="complex64"){let i=pd({inputs:{input:r},backend:n}),o=xx({inputs:{x:i},backend:n,attrs:{dtype:s}});return n.disposeIntermediateTensorInfo(i),o}if(!v.hasEncodingLoss(r.dtype,s)){let i=aa({inputs:{x:r},backend:n});return{dataId:i.dataId,shape:i.shape,dtype:s}}if(n.shouldExecuteOnCPU([r])){let i=n.texData.get(r.dataId).values,[o,l,u]=t7(i,r.shape,r.dtype,s);return n.makeTensorInfo(o,l,u)}if(s==="int32")return Z9(r,n);if(s==="bool"){let i=n.makeTensorInfo([],"bool",v.getTypedArrayFromDType("bool",1)),o=yE({inputs:{a:r,b:i},backend:n});return n.disposeIntermediateTensorInfo(i),o}throw new Error(`Error in Cast: failed to cast ${r.dtype} to ${s}`)}var J9={kernelName:xi,backendName:"webgl",kernelFunc:xx},SI="return ceil(x);",Q9=Ye({opSnippet:SI,packedOpSnippet:SI,cpuKernelImpl:n7}),eQ={kernelName:vi,backendName:"webgl",kernelFunc:Q9},tQ=class{constructor(e){this.variableNames=["A"],this.customUniforms=[{name:"minVal",type:"float"},{name:"maxVal",type:"float"}],this.outputShape=e,this.userCode=`

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

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

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

        setOutput(clamp(value, vec4(minVal), vec4(maxVal)));
      }
    `}};function aQ(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{clipValueMin:s,clipValueMax:i}=a,o;H().getBool("WEBGL_PACK_CLIP")?o=new nQ(r.shape):o=new tQ(r.shape);let l=[[s],[i]];return n.runWebGLProgram(o,[r],r.dtype,l)}var rQ={kernelName:bs,backendName:"webgl",kernelFunc:aQ},sQ=class{constructor(e){this.variableNames=["real","imag"],this.outputShape=e,this.userCode=`
      void main() {
        float re = abs(getRealAtOutCoords());
        float im = abs(getImagAtOutCoords());
        float mx = max(re, im);

        // sadly the length function in glsl is not underflow-safe
        // (at least not on Intel GPUs). So the safe solution is
        // to ensure underflow-safety in all cases.
        setOutput(
          mx == 0.0 ? 0.0 : mx * length(vec2(1, min(re, im)/mx))
        );
      }
    `}};function TI(e,t){return{dataId:t.dataId,dtype:t.dtype,shape:e.shape}}function iQ(e){let{inputs:t,backend:n}=e,{x:a}=t,r=n.texData.get(a.dataId),s=new sQ(a.shape),i=[TI(a,r.complexTensorInfos.real),TI(a,r.complexTensorInfos.imag)];return n.runWebGLProgram(s,i,i[0].dtype)}var oQ={kernelName:hc,backendName:"webgl",kernelFunc:iQ},lQ=class{constructor(e){this.outputShape=[],this.outputShape=N.computeOutShape(e,1),this.variableNames=e.map((s,i)=>`T${i}`);let t=new Array(e.length-1);t[0]=e[0][1];for(let s=1;s<t.length;s++)t[s]=t[s-1]+e[s][1];let n=[`if (yC < ${t[0]}) setOutput(getT0(yR, yC));`];for(let s=1;s<t.length;s++){let i=t[s-1];n.push(`else if (yC < ${t[s]}) setOutput(getT${s}(yR, yC-${i}));`)}let a=t.length,r=t[t.length-1];n.push(`else setOutput(getT${a}(yR, yC-${r}));`),this.userCode=`
      void main() {
        ivec2 coords = getOutputCoords();
        int yR = coords.x;
        int yC = coords.y;

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

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

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

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

        ${s[a-1]} = ${s[a-1]} - 1;
        if (${s[a-2]} < ${n[a-2]} &&
            ${s[a-1]} < ${n[a-1]}) {
          result.b = getValue(${s});
        }
        setOutput(result);
      }
    `}};function bh(e,t,n){let a=e.indexOf(t);return e.map((r,s)=>s===a?`${r} - ${n}`:r).join()}function Jf(e){let{inputs:t,backend:n}=e,{input:a}=t,r=n.texData.get(a.dataId);return aa({inputs:{x:r.complexTensorInfos.imag},backend:n})}var pQ={kernelName:Nm,backendName:"webgl",kernelFunc:Jf};function Vp(e,t,n){let a=e[0].dtype;if(a==="complex64"){let d=e.map(g=>pd({inputs:{input:g},backend:n})),c=e.map(g=>Jf({inputs:{input:g},backend:n})),h=Vp(d,t,n),m=Vp(c,t,n),f=_s({inputs:{real:h,imag:m},backend:n});return d.forEach(g=>n.disposeIntermediateTensorInfo(g)),c.forEach(g=>n.disposeIntermediateTensorInfo(g)),n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(m),f}let r=n.shouldExecuteOnCPU(e);if(a==="string"&&(r=!0),r){let d=e.map(y=>{let x=v.sizeFromShape(y.shape.slice(t));return de({inputs:{x:y},backend:n,attrs:{shape:[-1,x]}})}),c=d.map(y=>({vals:n.readSync(y.dataId),shape:y.shape})),h=N.computeOutShape(d.map(y=>y.shape),1),m=d[0].shape[0]===1,f=a7(c,h,a,m),g=N.computeOutShape(e.map(y=>y.shape),t),b=n.makeTensorInfo(g,a,f);return d.forEach(y=>n.disposeIntermediateTensorInfo(y)),b}let s=H().getNumber("WEBGL_MAX_TEXTURES_IN_SHADER");if(e.length>s){let d=[];for(let h=0;h<e.length;h+=s){let m=e.slice(h,h+s);d.push(Vp(m,t,n))}let c=Vp(d,t,n);for(let h of d)n.disposeIntermediateTensorInfo(h);return c}if(H().getBool("WEBGL_PACK_ARRAY_OPERATIONS")&&e[0].shape.length>1){let d=new uQ(e.map(c=>c.shape),t);return n.runWebGLProgram(d,e,a)}let{tensors2D:i,outShape:o}=cQ(e,t,n),l=new lQ(i.map(d=>d.shape)),u=n.runWebGLProgram(l,i,a);i.forEach(d=>n.disposeIntermediateTensorInfo(d));let p=de({inputs:{x:u},attrs:{shape:o},backend:n});return n.disposeIntermediateTensorInfo(u),p}function cQ(e,t,n){let a=N.computeOutShape(e.map(r=>r.shape),t);return{tensors2D:e.map(r=>de({inputs:{x:r},attrs:{shape:[-1,v.sizeFromShape(r.shape.slice(t))]},backend:n})),outShape:a}}function xE(e){let{inputs:t,backend:n,attrs:a}=e,{axis:r}=a,s=v.parseAxisParam(r,t[0].shape)[0],i=t.map(u=>u.shape);N.assertParamsConsistent(i,s);let o=N.computeOutShape(t.map(u=>u.shape),s);if(v.sizeFromShape(o)===0)return n.makeTensorInfo(o,t[0].dtype,[]);let l=t.filter(u=>v.sizeFromShape(u.shape)>0);return l.length===1?aa({inputs:{x:l[0]},backend:n}):Vp(l,s,n)}var dQ={kernelName:Gl,backendName:"webgl",kernelFunc:xE},vE=class{constructor(e,t=!1,n=null,a=!1,r=!1){this.variableNames=["x","W"],this.outputShape=e.outShape;let s=e.padInfo.top,i=e.padInfo.left,o=e.strideHeight,l=e.strideWidth,u=e.dilationHeight,p=e.dilationWidth,d=e.filterHeight,c=e.filterWidth,h=Math.floor(e.inChannels/4)*4,m=e.inChannels%4,f=e.dataFormat==="channelsLast",g=f?1:2,b=f?2:3,y=f?3:1,x="",w="";n&&(a?x=`float activation(float a) {
          float b = getPreluActivationWeightsAtOutCoords();
          ${n}
        }`:r?x=`float activation(float a) {
          float b = getLeakyreluAlphaAtOutCoords();
          ${n}
        }`:x=`
          float activation(float x) {
            ${n}
          }
        `,w="result = activation(result);");let I=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),a&&this.variableNames.push("preluActivationWeights"),r&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
      ${x}

      const ivec2 strides = ivec2(${o}, ${l});
      const ivec2 pads = ivec2(${s}, ${i});

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

        ivec2 xRCCorner =
            ivec2(coords[${g}], coords[${b}]) * strides - pads;
        int xRCorner = xRCCorner.x;
        int xCCorner = xRCCorner.y;

        // Convolve x(?, ?, d1) with w(:, :, d1, d2) to get y(yR, yC, d2).
        // ? = to be determined. : = across all values in that axis.
        float dotProd = 0.0;
        for (int wR = 0; wR < ${d}; wR++) {
          int xR = xRCorner + wR * ${u};

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

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

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

            for (int d1 = 0; d1 < ${h}; d1 += 4) {
              vec4 wValues = vec4(
                getW(wR, wC, d1, d2),
                getW(wR, wC, d1 + 1, d2),
                getW(wR, wC, d1 + 2, d2),
                getW(wR, wC, d1 + 3, d2)
              );

              if (${f}) {
                vec4 xValues = vec4(
                  getX(batch, xR, xC, d1),
                  getX(batch, xR, xC, d1 + 1),
                  getX(batch, xR, xC, d1 + 2),
                  getX(batch, xR, xC, d1 + 3)
                );
                dotProd += dot(xValues, wValues);
              } else {
                vec4 xValues = vec4(
                  getX(batch, d1, xR, xC),
                  getX(batch, d1 + 1, xR, xC),
                  getX(batch, d1 + 2, xR, xC),
                  getX(batch, d1 + 3, xR, xC)
                );
                dotProd += dot(xValues, wValues);
              }
            }

            if (${m===1}) {

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

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

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

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

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

            }
          }
        }

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

      void main() {
        ivec5 coords = getOutputCoords();
        int batch = coords.x;
        int d2 = coords.u;

        ivec3 xFRCCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;
        int xFCorner = xFRCCorner.x;
        int xRCorner = xFRCCorner.y;
        int xCCorner = xFRCCorner.z;

        // Convolve x(?, ?, ?, d1) with w(:, :, :, d1, d2) to get
        // y(yF, yR, yC, d2). ? = to be determined. : = across all
        // values in that axis.
        float dotProd = 0.0;
        for (int wF = 0; wF < ${p}; wF++) {
          int xF = xFCorner + wF * ${o};

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

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

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

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

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

              for (int d1 = 0; d1 < ${h}; d1 += 4) {
                vec4 xValues = vec4(
                  getX(batch, xF, xR, xC, d1),
                  getX(batch, xF, xR, xC, d1 + 1),
                  getX(batch, xF, xR, xC, d1 + 2),
                  getX(batch, xF, xR, xC, d1 + 3)
                );
                vec4 wValues = vec4(
                  getW(wF, wR, wC, d1, d2),
                  getW(wF, wR, wC, d1 + 1, d2),
                  getW(wF, wR, wC, d1 + 2, d2),
                  getW(wF, wR, wC, d1 + 3, d2)
                );

                dotProd += dot(xValues, wValues);
              }

              if (${m===1}) {
                dotProd +=
                  getX(batch, xF, xR, xC, ${h}) *
                  getW(wF, wR, wC, ${h}, d2);
              } else if (${m===2}) {
                vec2 xValues = vec2(
                  getX(batch, xF, xR, xC, ${h}),
                  getX(batch, xF, xR, xC, ${h} + 1)
                );
                vec2 wValues = vec2(
                  getW(wF, wR, wC, ${h}, d2),
                  getW(wF, wR, wC, ${h} + 1, d2)
                );
                dotProd += dot(xValues, wValues);
              } else if (${m===3}) {
                vec3 xValues = vec3(
                  getX(batch, xF, xR, xC, ${h}),
                  getX(batch, xF, xR, xC, ${h} + 1),
                  getX(batch, xF, xR, xC, ${h} + 2)
                );
                vec3 wValues = vec3(
                  getW(wF, wR, wC, ${h}, d2),
                  getW(wF, wR, wC, ${h} + 1, d2),
                  getW(wF, wR, wC, ${h} + 2, d2)
                );
                dotProd += dot(xValues, wValues);
              }
            }
          }
        }
        setOutput(dotProd);
      }
    `}},wE=class{constructor(e,t=!1,n=null,a=!1,r=!1){this.variableNames=["x","W"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"pads",type:"ivec2"},{name:"strides",type:"ivec2"},{name:"dilations",type:"ivec2"},{name:"inDims",type:"ivec2"}],this.outputShape=e.outShape,this.enableShapeUniforms=En(this.outputShape.length);let s=e.padInfo.left,i=e.strideWidth,o=e.dilationWidth,l=e.filterHeight,u=e.filterWidth,p=u,d=`
       int xR; int xC; int xCOffset;
       vec4 wTexel; vec4 previous; vec4 final;`;for(let f=0;f<u;f++)d+=`
           vec4 xTexelC${f*2};
           int xTexelC${f*2}Ready;
           vec4 xTexelC${f*2+1};
           int xTexelC${f*2+1}Ready;
           vec4 xC${f};`;d+=`
     for (int r = 0; r < ${l}; r++) {
      for (int d1 = 0; d1 < ${e.inChannels}; d1 += 2) {
       `;for(let f=0;f<u;f++)d+=`
           xTexelC${f*2} = vec4(0.0);
           xTexelC${f*2}Ready = 0;
           xTexelC${f*2+1} = vec4(0.0);
           xTexelC${f*2+1}Ready = 0;
           xC${f} = vec4(0.0);`;d+=`
         xR = xRCorner + r * dilations[0];
         if (xR >=0 && xR < inDims[0]) {
       `;for(let f=0;f<(p+1)/2;f++){let g=f*2;if(d+=`
           xC = xCCorner + ${g*o};
           `,i===1){if(g<u&&(s%2===1?(d+=`
                 xCOffset = xC + 1;
                 if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${g}Ready == 0) {
                   xTexelC${g} = getX(batch, xR, xCOffset, d1);

                   // Need to manually clear unused channels in case
                   // we're reading from recycled texture.
                   if (xCOffset + 1 >= inDims[1]) {
                     xTexelC${g}.zw = vec2(0.0);
                   }
                   xTexelC${g}Ready = 1;
                 }
               `,o===1&&g>0?d+=`
                 xC${g} = vec4(xTexelC${g-2}.zw, xTexelC${g}.xy);
                 `:d+=`
                   xCOffset = xC + 1 - 2;

                   if (xCOffset >= 0 && xCOffset < inDims[1]) {
                     previous = getX(batch, xR, xCOffset, d1);

                     // Need to manually clear unused channels in case
                     // we're reading from recycled texture.
                     if (xCOffset + 1 >= inDims[1]) {
                       previous.zw = vec2(0.0);
                     }

                     xC${g} = vec4(previous.zw, xTexelC${g}.xy);
                   } else {
                     xC${g} = vec4(0.0, 0.0, xTexelC${g}.xy);
                   }
                   `):d+=`
                 if (xC >= 0 && xC < inDims[1] && xTexelC${g}Ready == 0) {
                   xTexelC${g} = getX(batch, xR, xC, d1);
                   if (xC + 1 >= inDims[1]) {
                     xTexelC${g}.zw = vec2(0.0);
                   }
                   xTexelC${g}Ready = 1;
                 }

                 xC${g} = xTexelC${g};
                 `,g+1<u)){let b=s%2===0?v.nearestLargerEven(o):o;o%2===0&&s%2===1||o%2!==0&&s%2!==1?(d+=`
                   xCOffset = xC + imod(pads[1], 2) + ${b};

                   if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${g+1}Ready == 0) {
                     xTexelC${g+1} = getX(batch, xR, xCOffset, d1);

                     // Need to manually clear unused channels in case
                     // we're reading from recycled texture.
                     if (xCOffset + 1 >= inDims[1]) {
                       xTexelC${g+1}.zw = vec2(0.0);
                     }
                     xTexelC${g+1}Ready = 1;
                   }
                   `,o>1?d+=`
                     xCOffset -= 2;
                     if (xCOffset >= 0 && xCOffset < inDims[1]) {
                      previous = getX(batch, xR, xCOffset, d1);
                      xC${g+1} = vec4(previous.zw, xTexelC${g+1}.xy);
                     } else {
                      xC${g+1} = vec4(0.0, 0.0, xTexelC${g+1}.xy);
                     }
                     `:d+=`
                     xC${g+1} = vec4(xTexelC${g}.zw, xTexelC${g+1}.xy);
                     `):b===1?d+=`
                     xC${g+1} = xTexelC${g};
                     `:d+=`
                     xCOffset = xC + ${b};

                     if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${g+1}Ready == 0) {
                       xTexelC${g+1} = getX(batch, xR, xCOffset, d1);
                       if (xCOffset + 1 >= inDims[1]) {
                         xTexelC${g+1}.zw = vec2(0.0);
                       }
                       xTexelC${g+1}Ready = 1;
                     }

                     xC${g+1} = xTexelC${g+1};
                     `}}else g<u&&(s%2===1?(d+=`
                 xCOffset = xC + 1 - strides[1];
                 if(xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${g}Ready == 0) {
                   xTexelC${g} = getX(batch, xR, xCOffset, d1);
                   // Need to manually clear unused channels in case
                   // we're reading from recycled texture.
                   if (xCOffset + 1 >= inDims[1]) {
                     xTexelC${g}.zw = vec2(0.0);
                   }
                   xTexelC${g}Ready = 1;
                 }

                 if(xC + 1 >= 0 && xC + 1 < inDims[1] && xTexelC${g+1}Ready == 0) {
                   xTexelC${g+1} = getX(batch, xR, xC + 1, d1);
                   // Need to manually clear unused channels in case
                   // we're reading from recycled texture.
                   if (xC + 2 >= inDims[1]) {
                     xTexelC${g+1}.zw = vec2(0.0);
                   }
                   xTexelC${g+1}Ready = 1;
                 }

                 xC${g} = vec4(xTexelC${g}.zw, xTexelC${g+1}.zw);
               `,g+1<u&&(d+=`
                   final = vec4(0.0);
                   xCOffset = xC + 1 + strides[1];
                   if(xCOffset >= 0 && xCOffset < inDims[1]) {
                     final = getX(batch, xR, xCOffset, d1);
                   }
                   xC${g+1} = vec4(xTexelC${g+1}.xy, final.xy);
                 `)):(d+=`
                 if(xC >= 0 && xC < inDims[1] && xTexelC${g}Ready == 0) {
                   xTexelC${g} = getX(batch, xR, xC, d1);
                   if (xC + 1 >= inDims[1]) {
                     xTexelC${g}.zw = vec2(0.0);
                   }
                   xTexelC${g}Ready = 1;
                 }

                 xCOffset = xC + strides[1];
                 if(xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${g+1}Ready == 0) {
                   xTexelC${g+1} = getX(batch, xR, xCOffset, d1);
                   if (xCOffset + 1 >= inDims[1]) {
                     xTexelC${g+1}.zw = vec2(0.);
                   }
                   xTexelC${g+1}Ready = 1;
                 }

                 xC${g} = vec4(
                   xTexelC${g}.xy, xTexelC${g+1}.xy);
               `,g+1<u&&(d+=`
                   xC${g+1} = vec4(xTexelC${g}.zw, xTexelC${g+1}.zw);
                 `)));g<u&&(d+=`
             wTexel = getW(r, ${g}, d1, d2);
             dotProd += xC${g}.xxzz * vec4(wTexel.xy, wTexel.xy);
             if(d1 + 1 < ${e.inChannels}) {
               dotProd += xC${g}.yyww * vec4(wTexel.zw, wTexel.zw);
             }
           `,g+1<u&&(d+=`
               wTexel = getW(r, ${g+1}, d1, d2);
               dotProd += xC${g+1}.xxzz * vec4(wTexel.xy, wTexel.xy);
               if(d1 + 1 < ${e.inChannels}) {
                 dotProd += xC${g+1}.yyww * vec4(wTexel.zw, wTexel.zw);
               }
             `))}d+=`
     }
   `,d+=`
     }
   `,d+=`
     }
   `;let c="",h="";n&&(a?c=`vec4 activation(vec4 a) {
           vec4 b = getPreluActivationWeightsAtOutCoords();
           ${n}
         }`:r?c=`vec4 activation(vec4 a) {
           vec4 b = getLeakyreluAlphaAtOutCoords();
           ${n}
         }`:c=`vec4 activation(vec4 x) {
           ${n}
         }`,h="result = activation(result);");let m=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),a&&this.variableNames.push("preluActivationWeights"),r&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
       ${c}

       void main() {
         ivec4 coords = getOutputCoords();
         int batch = coords.x;
         ivec2 xRCCorner = coords.yz * strides - pads;
         int d2 = coords.w;
         int xRCorner = xRCCorner.x;
         int xCCorner = xRCCorner.y;

         //intialize dotProd with a small epsilon seems to reduce GPU accuracy loss.
         vec4 dotProd = vec4(0.000000000000001);

         ${d}

         vec4 result = dotProd - vec4(0.000000000000001);
         ${m}
         ${h}
         setOutput(result);
       }
     `}},mQ=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"inputShape",type:"ivec4"},{name:"pad",type:"ivec2"},{name:"stride",type:"ivec2"},{name:"dilation",type:"ivec2"},{name:"inChannels",type:"int"},{name:"itemsPerBlockRow",type:"int"},{name:"outWidth",type:"int"}],this.outputShape=e,this.enableShapeUniforms=En(this.outputShape.length);let{dataFormat:n}=t,a=_n(),r=n==="channelsLast",s=r?1:2,i=r?2:3,o=this.enableShapeUniforms?"if(blockIndex < outShape[2] && pos < outShape[1]) {":`if(blockIndex < ${e[2]} && pos < ${e[1]}) {`,l="";for(let u=0;u<=1;u++)for(let p=0;p<=1;p++)l+=`
          blockIndex = rc.z + ${p};
          pos = rc.y + ${u};

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

            if(d0 < inputShape[${s}] && d0 >= 0) {
              // Use custom imod instead mod. On Intel GPU, mod may generate
              // unexpected value.
              // https://github.com/tensorflow/tfjs/issues/5447
              offsetX = imod(blockIndex, outWidth) * stride[1] - pad[1];
              d1 = offsetX + dilation[1] * (imod(pos, itemsPerBlockRow) /
                  inChannels);

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

                ch = imod(pos, inChannels);

                if (${r}) {
                  innerDims = vec2(d1, ch);
                  result[${u*2+p}] = getChannel(
                    getA(rc.x, d0, int(innerDims.x),
                    int(innerDims.y)), innerDims);
                } else {
                  innerDims = vec2(d0, d1);
                  result[${u*2+p}] = getChannel(
                    getA(rc.x, ch, int(innerDims.x),
                    int(innerDims.y)), innerDims);
                }
              }
            }
          }
        `;this.userCode=`
      void main() {
        ivec3 rc = getOutputCoords();

        vec4 result = vec4(0);

        int blockIndex, pos, offsetY, d0, offsetX, d1, ch;
        vec2 innerDims;

        ${l}

        ${a.output} = result;
      }
    `}};function am(e,t){let n=e.length;return n>=3?t?[...e.slice(0,-3),e[n-3]*e[n-2],e[n-1]]:[...e.slice(0,-3),e[n-3],e[n-2]*e[n-1]]:!t&&n===1&&e[0]>1?[e[0],1]:null}function kE({x:e,filter:t,convInfo:n,backend:a,bias:r=null,preluActivationWeights:s=null,leakyreluAlpha:i=0,activation:o=null}){let l=e.shape,u=a.texData.get(e.dataId),p=n.inChannels,d=l[0]*l[1]*l[2],c=n.outChannels,h=n.dataFormat==="channelsLast",m=!1,f=!1,g,b=[];if(s!=null){let y=am(s.shape,h);y!=null&&(s=de({inputs:{x:s},backend:a,attrs:{shape:y}}),b.push(s))}if(r!=null){let y=am(r.shape,h);y!=null&&(r=de({inputs:{x:r},backend:a,attrs:{shape:y}}),b.push(r))}if(!((d===1||c===1)&&p>mE)&&u.isPacked&&h&&u.texture!=null&&l[2]%2!==0&&v.arraysEqual(u.shape.slice(-3),l.slice(-3))){let y=l[0]*l[1]*(l[2]+1),x={dataId:e.dataId,shape:[1,y,n.inChannels],dtype:e.dtype},w=u.shape;u.shape=u.shape.slice(),u.shape[u.shape.length-2]++,v.assert(sc(u.shape,x.shape),()=>`packed reshape ${u.shape} to ${x.shape} isn't free`);let I=de({inputs:{x:t},backend:a,attrs:{shape:[1,n.inChannels,n.outChannels]}});b.push(I);let T=nm({a:x,b:I,backend:a,transposeA:m,transposeB:f,bias:r,activation:o,preluActivationWeights:s,leakyreluAlpha:i}),C=a.texData.get(T.dataId);v.assert(C.isPacked,()=>"batchMatMul result is expected to be packed"),u.shape=w,C.shape=n.outShape,g=aa({inputs:{x:T},backend:a}),g.shape=n.outShape,b.push(T)}else{let y=n.outHeight*n.outWidth,x=de({inputs:{x:e},backend:a,attrs:{shape:h?[n.batchSize,y,n.inChannels]:[n.batchSize,n.inChannels,y]}}),w=de({inputs:{x:t},backend:a,attrs:{shape:[1,n.inChannels,n.outChannels]}}),I=nm({a:h?x:w,b:h?w:x,transposeA:!h,transposeB:f,backend:a,bias:r,activation:o,preluActivationWeights:s,leakyreluAlpha:i});g=de({inputs:{x:I},backend:a,attrs:{shape:n.outShape}}),b.push(x),b.push(w),b.push(I)}for(let y of b)a.disposeIntermediateTensorInfo(y);return g}function IE({x:e,filter:t,convInfo:n,backend:a,bias:r=null,preluActivationWeights:s=null,leakyreluAlpha:i=0,activation:o=null}){let{filterWidth:l,filterHeight:u,inChannels:p,outWidth:d,outHeight:c,dataFormat:h}=n,m=h==="channelsLast",f=l*u*p,g=c*d,b=[n.batchSize,f,g],y=!0,x=!1,w=[];if(s!=null){let K=am(s.shape,m);K!=null&&(s=de({inputs:{x:s},backend:a,attrs:{shape:K}}),w.push(s))}if(r!=null){let K=am(r.shape,m);K!=null&&(r=de({inputs:{x:r},backend:a,attrs:{shape:K}}),w.push(r))}let I=de({inputs:{x:t},backend:a,attrs:{shape:[1,f,v.sizeFromShape(t.shape)/f]}});w.push(I);let T=new mQ(b,n),C=[e.shape,[n.padInfo.top,n.padInfo.left],[n.strideHeight,n.strideWidth],[n.dilationHeight,n.dilationWidth],[n.inChannels],[n.filterWidth*n.inChannels],[n.outWidth]],E=a.runWebGLProgram(T,[e],"float32",C),A=de({inputs:{x:E},backend:a,attrs:{shape:b}});w.push(E),w.push(A);let R=r!=null,F=s!=null,S=o==="leakyrelu",M=o?ic(o,!0):null,B=new hE(m?A.shape:I.shape,m?I.shape:A.shape,m?[n.batchSize,g,n.outChannels]:[n.batchSize,n.outChannels,g],y,x,R,M,F,S),U=m?[A,I]:[I,A];if(r&&U.push(r),F&&U.push(s),S){let K=a.makeTensorInfo([],"float32",v.createScalarValue(i,"float32"));U.push(K),w.push(K)}let G=a.runWebGLProgram(B,U,"float32"),q=de({inputs:{x:G},backend:a,attrs:{shape:n.outShape}});w.push(G);for(let K of w)a.disposeIntermediateTensorInfo(K);return q}function fQ(e){let{inputs:t,backend:n,attrs:a}=e,{x:r,filter:s}=t,{strides:i,pad:o,dataFormat:l,dilations:u,dimRoundingMode:p}=a,d=N.convertConv2DDataFormat(l),c=N.computeConv2DInfo(r.shape,s.shape,i,u,o,p,!1,d),h;if(c.filterHeight===1&&c.filterWidth===1&&c.dilationHeight===1&&c.dilationWidth===1&&c.strideHeight===1&&c.strideWidth===1&&(c.padInfo.type==="SAME"||c.padInfo.type==="VALID"))h=kE({x:r,filter:s,convInfo:c,backend:n});else if(c.strideWidth<=2&&d==="channelsLast"&&H().getBool("WEBGL_EXP_CONV")){let f=new wE(c),g=[[c.padInfo.top,c.padInfo.left],[c.strideHeight,c.strideWidth],[c.dilationHeight,c.dilationWidth],[c.inHeight,c.inWidth]];h=n.runWebGLProgram(f,[r,s],"float32",g)}else if(H().getBool("WEBGL_CONV_IM2COL"))h=IE({x:r,filter:s,convInfo:c,backend:n});else{let f=new vE(c);h=n.runWebGLProgram(f,[r,s],"float32")}let m=de({inputs:{x:h},backend:n,attrs:{shape:c.outShape}});return n.disposeIntermediateTensorInfo(h),m}var gQ={kernelName:wi,backendName:"webgl",kernelFunc:fQ},bQ=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideHeight,n=e.strideWidth,a=e.padInfo.top,r=e.padInfo.left,s=e.dataFormat==="channelsLast";this.userCode=`
      void main() {
        ivec4 coords = getOutputCoords();
        int wR = coords.x;
        int wC = coords.y;
        int d1 = coords.z;
        int d2 = coords.w;

        // Convolve x(?, ?, d1) with dy(:, :, d2) to get dw(wR, wC, d1, d2).
        // ? = to be determined. : = across all values in that axis.
        float dotProd = 0.0;

        for (int b = 0; b < ${e.batchSize}; b++) {
          for (int yR = 0; yR < ${e.outHeight}; yR++) {
            int xR = wR + yR * ${t} - ${a};

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

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

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

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

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

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

        ivec2 dyCorner = ivec2(coords[${l}], coords[${u}]) - pads;
        int dyRCorner = dyCorner.x;
        int dyCCorner = dyCorner.y;

        // Convolve dy(?, ?, d2) with w(:, :, d1, d2) to compute dx(xR, xC, d1).
        // ? = to be determined. : = across all values in that axis.
        float dotProd = 0.0;
        for (int wR = 0; wR < ${t}; wR++) {
          float dyR = float(dyRCorner + wR) / ${a}.0;

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

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

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

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

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

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

              if (${s}) {
                float xValue = getDy(batch, idyR, idyC, d2);
                float wValue = getW(wRPerm, wCPerm, d1, d2);
                dotProd += xValue * wValue;
              } else {
                float xValue = getDy(batch, d2, idyR, idyC);
                float wValue = getW(wRPerm, wCPerm, d1, d2);
                dotProd += xValue * wValue;
              }

            }
          }
        }
        setOutput(dotProd);
      }
    `}},xQ=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideDepth,n=e.strideHeight,a=e.strideWidth,r=e.padInfo.front,s=e.padInfo.top,i=e.padInfo.left;this.userCode=`
      void main() {
        ivec5 coords = getOutputCoords();
        int wF = coords.x;
        int wR = coords.y;
        int wC = coords.z;
        int d1 = coords.w;
        int d2 = coords.u;

        float dotProd = 0.0;

        for (int b = 0; b < ${e.batchSize}; b++) {
          for (int yF = 0; yF < ${e.outDepth}; yF++) {
            int xF = wF + yF * ${t} - ${r};

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

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

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

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

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

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

      void main() {
        ivec5 coords = getOutputCoords();
        int batch = coords.x;
        int d1 = coords.u;


        ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads;
        int dyFCorner = dyCorner.x;
        int dyRCorner = dyCorner.y;
        int dyCCorner = dyCorner.z;

        float dotProd = 0.0;
        for (int wF = 0; wF < ${t}; wF++) {
          float dyF = float(dyFCorner + wF) / ${r}.0;

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

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

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

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

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

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

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

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

              for (int d2 = 0; d2 < ${e.outChannels}; d2++) {
                float xValue = getDy(batch, idyF, idyR, idyC, d2);
                float wValue = getW(wFPerm, wRPerm, wCPerm, d1, d2);
                dotProd += xValue * wValue;
              }
            }
          }
        }
        setOutput(dotProd);
      }
    `}};function wQ(e){let{inputs:t,backend:n,attrs:a}=e,{x:r,dy:s}=t,{strides:i,pad:o,dataFormat:l,dimRoundingMode:u,filterShape:p}=a,d=N.convertConv2DDataFormat(l),c=N.computeConv2DInfo(r.shape,p,i,1,o,u,!1,d),h=new bQ(c);return n.runWebGLProgram(h,[r,s],"float32")}var kQ={kernelName:fm,backendName:"webgl",kernelFunc:wQ};function IQ(e){let{inputs:t,backend:n,attrs:a}=e,{dy:r,filter:s}=t,{inputShape:i,strides:o,pad:l,dataFormat:u,dimRoundingMode:p}=a,d=N.convertConv2DDataFormat(u),c=N.computeConv2DInfo(i,s.shape,o,1,l,p,!1,d),h=new yQ(c);return n.runWebGLProgram(h,[r,s],"float32")}var SQ={kernelName:ki,backendName:"webgl",kernelFunc:IQ};function TQ(e){let{inputs:t,backend:n,attrs:a}=e,{x:r,filter:s}=t,{strides:i,pad:o,dilations:l}=a,u=N.computeConv3DInfo(r.shape,s.shape,i,l,o),p=new hQ(u);return n.runWebGLProgram(p,[r,s],"float32")}var NQ={kernelName:mc,backendName:"webgl",kernelFunc:TQ};function CQ(e){let{inputs:t,backend:n,attrs:a}=e,{x:r,dy:s}=t,{strides:i,pad:o,filterShape:l}=a,u=N.computeConv3DInfo(r.shape,l,i,1,o),p=new xQ(u);return n.runWebGLProgram(p,[r,s],"float32")}var _Q={kernelName:gm,backendName:"webgl",kernelFunc:CQ};function EQ(e){let{inputs:t,backend:n,attrs:a}=e,{dy:r,filter:s}=t,{pad:i,strides:o,inputShape:l}=a,u=N.computeConv3DInfo(l,s.shape,o,1,i),p=new vQ(u);return n.runWebGLProgram(p,[r,s],"float32")}var AQ={kernelName:bm,backendName:"webgl",kernelFunc:EQ},$Q=tp+`
  return cos(x);
`,FQ=Ye({opSnippet:$Q}),DQ={kernelName:Ii,backendName:"webgl",kernelFunc:FQ},RQ=`
  float e2x = exp(-x);
  return (e2x + 1.0 / e2x) / 2.0;
`,MQ=Ye({opSnippet:RQ}),PQ={kernelName:Si,backendName:"webgl",kernelFunc:MQ},OQ=class{constructor(e,t,n,a,r){this.variableNames=["Image","Boxes","BoxInd"],this.outputShape=[];let[s,i,o,l]=e,[u]=t,[p,d]=n;this.outputShape=[u,p,d,l];let c=a==="bilinear"?1:0,[h,m]=[`${i-1}.0`,`${o-1}.0`],[f,g,b]=p>1?[`${(i-1)/(p-1)}`,"(y2-y1) * height_ratio",`y1*${h} + float(y)*(height_scale)`]:["0.0","0.0",`0.5 * (y1+y2) * ${h}`],[y,x,w]=d>1?[`${(o-1)/(d-1)}`,"(x2-x1) * width_ratio",`x1*${m} + float(x)*(width_scale)`]:["0.0","0.0",`0.5 * (x1+x2) * ${m}`];this.userCode=`
      const float height_ratio = float(${f});
      const float width_ratio = float(${y});
      void main() {
        ivec4 coords = getOutputCoords();
        int b = coords[0];
        int y = coords[1];
        int x = coords[2];
        int d = coords[3];

        // get box vals
        float y1 = getBoxes(b,0);
        float x1 = getBoxes(b,1);
        float y2 = getBoxes(b,2);
        float x2 = getBoxes(b,3);

        // get image in batch index
        int bInd = round(getBoxInd(b));
        if(bInd < 0 || bInd >= ${s}) {
          return;
        }

        float height_scale = ${g};
        float width_scale = ${x};

        float in_y = ${b};
        if( in_y < 0.0 || in_y > ${h} ) {
          setOutput(float(${r}));
          return;
        }
        float in_x = ${w};
        if( in_x < 0.0 || in_x > ${m} ) {
          setOutput(float(${r}));
          return;
        }

        vec2 sourceFracIndexCR = vec2(in_x,in_y);
        if(${c} == 1) {
          // Compute the four integer indices.
          ivec2 sourceFloorCR = ivec2(sourceFracIndexCR);
          ivec2 sourceCeilCR = ivec2(ceil(sourceFracIndexCR));

          float topLeft = getImage(b, sourceFloorCR.y, sourceFloorCR.x, d);
          float bottomLeft = getImage(b, sourceCeilCR.y, sourceFloorCR.x, d);
          float topRight = getImage(b, sourceFloorCR.y, sourceCeilCR.x, d);
          float bottomRight = getImage(b, sourceCeilCR.y, sourceCeilCR.x, d);

          vec2 fracCR = sourceFracIndexCR - vec2(sourceFloorCR);

          float top = topLeft + (topRight - topLeft) * fracCR.x;
          float bottom = bottomLeft + (bottomRight - bottomLeft) * fracCR.x;
          float newValue = top + (bottom - top) * fracCR.y;
          setOutput(newValue);
        } else {
          // Compute the coordinators of nearest neighbor point.
          ivec2 sourceNearestCR = ivec2(floor(
            sourceFracIndexCR + vec2(0.5,0.5)));
          float newValue = getImage(b, sourceNearestCR.y, sourceNearestCR.x, d);
          setOutput(newValue);
        }
      }
    `}},LQ=e=>{let{inputs:t,backend:n,attrs:a}=e,{image:r,boxes:s,boxInd:i}=t,{cropSize:o,method:l,extrapolationValue:u}=a,p=new OQ(r.shape,s.shape,o,l,u);return n.runWebGLProgram(p,[r,s,i],"float32")},zQ={kernelName:jl,backendName:"webgl",kernelFunc:LQ},lc;(function(e){e.Prod="*",e.Sum="+"})(lc||(lc={}));var NI=class{constructor(e,t,n,a){this.op=e,this.outputShape=t,this.variableNames=["x"],this.customUniforms=[{name:"index",type:"float"}];let r=this.outputShape.length,s=this.op===lc.Prod?"1.0":"0.0",i=n?s:`getX(${CI(r,"coords",this.op)})`,o=this.outputShape[this.outputShape.length-1],l="",u="";n?(l=a?`end != ${o-1}`:"end != 0",u=a?"end + 1":"end - 1"):(l=a?`end + pow2 < ${o}`:"end >= pow2",u=a?"end + pow2":"end - pow2"),this.userCode=`
      void main() {
        ${gt(r)} coords = getOutputCoords();
        int end = ${_I(r,"coords",this.op)};
        float val = ${i};
        int pow2 = int(pow(2.0, index));
        if (${l}) {
          int idx = ${u};
          ${_I(r,"coords",this.op)} = idx;
          val ${this.op}= getX(${CI(r,"coords",this.op)});
        }
        setOutput(val);
      }
    `}};function CI(e,t,n){if(e===1)return`${t}`;if(e===2)return`${t}.x, ${t}.y`;if(e===3)return`${t}.x, ${t}.y, ${t}.z`;if(e===4)return`${t}.x, ${t}.y, ${t}.z, ${t}.w`;throw new Error(`Cumulative ${n} for rank ${e} is not yet supported`)}function _I(e,t,n){if(e===1)return`${t}`;if(e===2)return`${t}.y`;if(e===3)return`${t}.z`;if(e===4)return`${t}.w`;throw new Error(`Cumulative ${n} for rank ${e} is not yet supported`)}function SE(e,t,n,a,r,s){let i=t.shape.length,o=N.getAxesPermutation([a],i),l=t;o!=null&&(l=Sn({inputs:{x:t},backend:n,attrs:{perm:o}}));let u=N.getInnerMostAxes(1,i)[0];if(u!==i-1)throw new Error(`WebGL cumprod shader expects an inner-most axis=${t.shape.length-1} but got axis=${a}`);let p=l.shape[u],d=aa({inputs:{x:l},backend:n});for(let c=0;c<=Math.ceil(Math.log2(p))-1;c++){let h=new NI(e,l.shape,!1,s),m=[[c]],f=d;d=n.runWebGLProgram(h,[d],d.dtype,m),n.disposeIntermediateTensorInfo(f)}if(r){let c=new NI(e,l.shape,r,s),h=d;d=n.runWebGLProgram(c,[d],d.dtype),n.disposeIntermediateTensorInfo(h)}if(o!=null){let c=N.getUndoAxesPermutation(o),h=Sn({inputs:{x:d},backend:n,attrs:{perm:c}});return n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(l),h}return d}function WQ(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{axis:s,exclusive:i,reverse:o}=a;return SE(lc.Prod,r,n,s,i,o)}var BQ={kernelName:Hl,backendName:"webgl",kernelFunc:WQ};function VQ(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{axis:s,exclusive:i,reverse:o}=a;return SE(lc.Sum,r,n,s,i,o)}var UQ={kernelName:Ti,backendName:"webgl",kernelFunc:VQ};function GQ(e){let{inputs:t,backend:n,attrs:a}=e,{x:r,weights:s}=t,{size:i,binaryOutput:o}=a;if(r.shape.length===1){let l=n.readSync(r.dataId),u=n.readSync(s.dataId),p=aE(l,u,s.dtype,s.shape,i);return n.makeTensorInfo([i],s.dtype,p)}else if(r.shape.length===2){let l=n.bufferSync(r),u=n.bufferSync(s),p=e7(l,u,i,o);return n.makeTensorInfo(p.shape,s.dtype,p.values)}throw new Error(`Error in denseBincount: input must be at most rank 2, but got rank${r.shape.length}.`)}var HQ={kernelName:ym,backendName:"webgl",kernelFunc:GQ},jQ=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=[],this.outputShape=e,this.blockSize=t,this.dataFormat=n,this.userCode=`
    void main() {
      ivec4 coords = getOutputCoords();
      int b = coords[0];
      int h = ${this.getHeightCoordString()};
      int w = ${this.getWidthCoordString()};
      int d = ${this.getDepthCoordString()};

      int in_h = h / ${t};
      int offset_h = imod(h, ${t});
      int in_w = w / ${t};
      int offset_w = imod(w, ${t});
      int offset_d = (offset_h * ${t} + offset_w) *
        ${this.getOutputDepthSize()};
      int in_d = d + offset_d;

      float result = ${this.getInputSamplingString()};
      setOutput(result);
    }
  `}getHeightCoordString(){return this.dataFormat==="NHWC"?"coords[1]":"coords[2]"}getWidthCoordString(){return this.dataFormat==="NHWC"?"coords[2]":"coords[3]"}getDepthCoordString(){return this.dataFormat==="NHWC"?"coords[3]":"coords[1]"}getOutputDepthSize(){return this.dataFormat==="NHWC"?this.outputShape[3]:this.outputShape[1]}getInputSamplingString(){return this.dataFormat==="NHWC"?"getX(b, in_h, in_w, in_d)":"getX(b, in_d, in_h, in_w)"}};function qQ(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{blockSize:s,dataFormat:i}=a,o=r.shape[0],l=i==="NHWC"?r.shape[1]:r.shape[2],u=i==="NHWC"?r.shape[2]:r.shape[3],p=i==="NHWC"?r.shape[3]:r.shape[1],d=l*s,c=u*s,h=p/(s*s),m=i==="NHWC"?[o,d,c,h]:[o,h,d,c],f=new jQ(m,s,i);return n.runWebGLProgram(f,[r],r.dtype)}var KQ={kernelName:ql,backendName:"webgl",kernelFunc:qQ},TE=class{constructor(e,t=!1,n=null,a=!1,r=!1){this.variableNames=["x","W"],this.customUniforms=[{name:"pads",type:"ivec2"},{name:"strides",type:"ivec2"},{name:"dilations",type:"ivec2"},{name:"inDims",type:"ivec2"}],this.outputShape=e.outShape,this.enableShapeUniforms=En(this.outputShape.length);let s=e.filterHeight,i=e.filterWidth,o=e.outChannels/e.inChannels,l="",u="";n&&(a?l=`float activation(float a) {
          float b = getPreluActivationWeightsAtOutCoords();
          ${n}
        }`:r?l=`float activation(float a) {
          float b = getLeakyreluAlphaAtOutCoords();
          ${n}
        }`:l=`
          float activation(float x) {
            ${n}
          }
        `,u="result = activation(result);");let p=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),a&&this.variableNames.push("preluActivationWeights"),r&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
      ${l}

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

        int xRCorner = xRCCorner.x;
        int xCCorner = xRCCorner.y;

        // Convolve x(?, ?, d1) with w(:, :, d1, q) to get y(yR, yC, d2).
        // ? = to be determined. : = across all values in that axis.
        float dotProd = 0.0;
        // TO DO(dsmilkov): Flatten the two for loops and vec4 the operations.
        for (int wR = 0; wR < ${s}; wR++) {
          int xR = xRCorner + wR * dilations[0];

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

          for (int wC = 0; wC < ${i}; wC++) {
            int xC = xCCorner + wC * dilations[1];

            if (xC < 0 || xC >= inDims[1]) {
              continue;
            }

            float xVal = getX(batch, xR, xC, d1);
            float wVal = getW(wR, wC, d1, q);
            dotProd += xVal * wVal;
          }
        }

        float result = dotProd;
        ${p}
        ${u}
        setOutput(result);
      }
    `}},NE=class{constructor(e,t=!1,n=null,a=!1,r=!1){this.variableNames=["x","W"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"pads",type:"ivec2"},{name:"strides",type:"ivec2"},{name:"dilations",type:"ivec2"},{name:"inDims",type:"ivec2"}],this.outputShape=e.outShape,this.enableShapeUniforms=En(this.outputShape.length);let s=e.outChannels/e.inChannels,i=e.padInfo.left,o=e.strideWidth,l=e.dilationWidth,u=e.filterHeight,p=e.filterWidth,d=p,c=`
      int xR; int xC; int xCOffset;
      vec4 wTexel; vec4 previous; vec4 final;`;for(let g=0;g<p;g++)c+=`
          vec4 xTexelC${g*2};
          int xTexelC${g*2}Ready;
          vec4 xTexelC${g*2+1};
          int xTexelC${g*2+1}Ready;
          vec4 xC${g};`;c+=`
    for (int r = 0; r < ${u}; r++) {
      `;for(let g=0;g<p;g++)c+=`
          xTexelC${g*2} = vec4(0.0);
          xTexelC${g*2}Ready = 0;
          xTexelC${g*2+1} = vec4(0.0);
          xTexelC${g*2+1}Ready = 0;
          xC${g} = vec4(0.0);`;c+=`
        xR = xRCorner + r * dilations[0];
        if (xR >=0 && xR < inDims[0]) {
      `;for(let g=0;g<(d+1)/2;g++){let b=g*2;if(c+=`
          xC = xCCorner + ${b*l};
          `,o===1){if(b<p&&(i%2===1?(c+=`
                xCOffset = xC + 1;
                if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${b}Ready == 0) {
                  xTexelC${b} = getX(batch, xR, xCOffset, d1);

                  // Need to manually clear unused channels in case
                  // we're reading from recycled texture.
                  if (xCOffset + 1 >= inDims[1]) {
                    xTexelC${b}.zw = vec2(0.0);
                  }
                  xTexelC${b}Ready = 1;
                }
              `,l===1&&b>0?c+=`
                xC${b} = vec4(xTexelC${b-2}.zw, xTexelC${b}.xy);
                `:c+=`
                  xCOffset = xC + 1 - 2;

                  if (xCOffset >= 0 && xCOffset < inDims[1]) {
                    previous = getX(batch, xR, xCOffset, d1);

                    // Need to manually clear unused channels in case
                    // we're reading from recycled texture.
                    if (xCOffset + 1 >= inDims[1]) {
                      previous.zw = vec2(0.0);
                    }

                    xC${b} = vec4(previous.zw, xTexelC${b}.xy);
                  } else {
                    xC${b} = vec4(0.0, 0.0, xTexelC${b}.xy);
                  }
                  `):c+=`
                if (xC >= 0 && xC < inDims[1] && xTexelC${b}Ready == 0) {
                  xTexelC${b} = getX(batch, xR, xC, d1);
                  if (xC + 1 >= inDims[1]) {
                    xTexelC${b}.zw = vec2(0.0);
                  }
                  xTexelC${b}Ready = 1;
                }

                xC${b} = xTexelC${b};
                `,b+1<p)){let y=i%2===0?v.nearestLargerEven(l):l;l%2===0&&i%2===1||l%2!==0&&i%2!==1?(c+=`
                  xCOffset = xC + imod(pads[1], 2) + ${y};

                  if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${b+1}Ready == 0) {
                    xTexelC${b+1} = getX(batch, xR, xCOffset, d1);

                    // Need to manually clear unused channels in case
                    // we're reading from recycled texture.
                    if (xCOffset + 1 >= inDims[1]) {
                      xTexelC${b+1}.zw = vec2(0.0);
                    }
                    xTexelC${b+1}Ready = 1;
                  }
                  `,l>1?c+=`
                    xCOffset -= 2;
                    if (xCOffset >= 0 && xCOffset < inDims[1]) {
                     previous = getX(batch, xR, xCOffset, d1);
                     xC${b+1} = vec4(previous.zw, xTexelC${b+1}.xy);
                    } else {
                     xC${b+1} = vec4(0.0, 0.0, xTexelC${b+1}.xy);
                    }
                    `:c+=`
                    xC${b+1} = vec4(xTexelC${b}.zw, xTexelC${b+1}.xy);
                    `):y===1?c+=`
                    xC${b+1} = xTexelC${b};
                    `:c+=`
                    xCOffset = xC + ${y};

                    if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${b+1}Ready == 0) {
                      xTexelC${b+1} = getX(batch, xR, xCOffset, d1);
                      if (xCOffset + 1 >= inDims[1]) {
                        xTexelC${b+1}.zw = vec2(0.0);
                      }
                      xTexelC${b+1}Ready = 1;
                    }

                    xC${b+1} = xTexelC${b+1};
                    `}}else b<p&&(i%2===1?(c+=`
                xCOffset = xC + 1 - strides[1];
                if(xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${b}Ready == 0) {
                  xTexelC${b} = getX(batch, xR, xCOffset, d1);
                  // Need to manually clear unused channels in case
                  // we're reading from recycled texture.
                  if (xCOffset + 1 >= inDims[1]) {
                    xTexelC${b}.zw = vec2(0.0);
                  }
                  xTexelC${b}Ready = 1;
                }

                if(xC + 1 >= 0 && xC + 1 < inDims[1] && xTexelC${b+1}Ready == 0) {
                  xTexelC${b+1} = getX(batch, xR, xC + 1, d1);
                  // Need to manually clear unused channels in case
                  // we're reading from recycled texture.
                  if (xC + 2 >= inDims[1]) {
                    xTexelC${b+1}.zw = vec2(0.0);
                  }
                  xTexelC${b+1}Ready = 1;
                }

                xC${b} = vec4(xTexelC${b}.zw, xTexelC${b+1}.zw);
              `,b+1<p&&(c+=`
                  final = vec4(0.0);
                  xCOffset = xC + 1 + strides[1];
                  if(xCOffset >= 0 && xCOffset < inDims[1]) {
                    final = getX(batch, xR, xCOffset, d1);
                  }
                  xC${b+1} = vec4(xTexelC${b+1}.xy, final.xy);
                `)):(c+=`
                if(xC >= 0 && xC < inDims[1] && xTexelC${b}Ready == 0) {
                  xTexelC${b} = getX(batch, xR, xC, d1);
                  if (xC + 1 >= inDims[1]) {
                    xTexelC${b}.zw = vec2(0.0);
                  }
                  xTexelC${b}Ready = 1;
                }

                xCOffset = xC + strides[1];
                if(xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${b+1}Ready == 0) {
                  xTexelC${b+1} = getX(batch, xR, xCOffset, d1);
                  if (xCOffset + 1 >= inDims[1]) {
                    xTexelC${b+1}.zw = vec2(0.);
                  }
                  xTexelC${b+1}Ready = 1;
                }

                xC${b} = vec4(
                  xTexelC${b}.xy, xTexelC${b+1}.xy);
              `,b+1<p&&(c+=`
                  xC${b+1} = vec4(xTexelC${b}.zw, xTexelC${b+1}.zw);
                `)));b<p&&(c+=`
            wTexel = getW(r, ${b}, d1, q);
            dotProd += xC${b} * vec4(wTexel.xz, wTexel.xz);
          `,b+1<p&&(c+=`
              wTexel = getW(r, ${b+1}, d1, q);
              dotProd += xC${b+1} * vec4(wTexel.xz, wTexel.xz);
            `))}c+=`
    }
  `,c+=`
      }
    `;let h="",m="";n&&(a?h=`vec4 activation(vec4 a) {
          vec4 b = getPreluActivationWeightsAtOutCoords();
          ${n}
        }`:r?h=`vec4 activation(vec4 a) {
          vec4 b = getLeakyreluAlphaAtOutCoords();
          ${n}
        }`:h=`vec4 activation(vec4 x) {
          ${n}
        }`,m="result = activation(result);");let f=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),a&&this.variableNames.push("preluActivationWeights"),r&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
      ${h}

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

        //intialize dotProd with a small epsilon seems to reduce GPU accuracy loss.
        vec4 dotProd = vec4(0.000000000000001);

        ${c}

        vec4 result = dotProd - vec4(0.000000000000001);
        ${f}
        ${m}
        setOutput(result);
      }
    `}};function XQ(e){let{inputs:t,backend:n,attrs:a}=e,{x:r,filter:s}=t,{strides:i,pad:o,dilations:l,dimRoundingMode:u}=a,p=l;p==null&&(p=[1,1]),v.assert(N.eitherStridesOrDilationsAreOne(i,p),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${i} and dilations '${p}'`);let d=N.computeConv2DInfo(r.shape,s.shape,i,p,o,u,!0),c;H().getBool("WEBGL_PACK_DEPTHWISECONV")&&d.strideWidth<=2&&d.outChannels/d.inChannels===1?c=new NE(d):c=new TE(d);let h=[[d.padInfo.top,d.padInfo.left],[d.strideHeight,d.strideWidth],[d.dilationHeight,d.dilationWidth],[d.inHeight,d.inWidth]];return n.runWebGLProgram(c,[r,s],"float32",h)}var YQ={kernelName:Ni,backendName:"webgl",kernelFunc:XQ},ZQ=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideHeight,n=e.strideWidth,a=e.padInfo.top,r=e.padInfo.left,s=e.outChannels/e.inChannels;this.userCode=`
      void main() {
        ivec4 coords = getOutputCoords();
        int wR = coords.x;
        int wC = coords.y;
        int d1 = coords.z;
        int dm = coords.w;
        int d2 = d1 * ${s} + dm;

        float dotProd = 0.0;

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

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

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

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

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

      void main() {
        ivec4 coords = getOutputCoords();
        int batch = coords[0];
        int d1 = coords[3];
        ivec2 dyCorner = coords.yz - pads;
        int dyRCorner = dyCorner.x;
        int dyCCorner = dyCorner.y;

        float dotProd = 0.0;

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

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

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

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

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

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

            // TO DO: Vec4 over the channelMul
            for (int dm = 0; dm < ${o}; dm++) {
              int d2 = d1 * ${o} + dm;
              float xValue = getDy(batch, idyR, idyC, d2);
              float wValue = getW(wRPerm, wCPerm, d1, dm);
              dotProd += xValue * wValue;
            }
          }
        }
        setOutput(dotProd);
      }
    `}};function QQ(e){let{inputs:t,backend:n,attrs:a}=e,{x:r,dy:s}=t,{strides:i,dilations:o,pad:l,dimRoundingMode:u,filterShape:p}=a,d=N.computeConv2DInfo(r.shape,p,i,o,l,u,!0),c=new ZQ(d);return n.runWebGLProgram(c,[r,s],"float32")}var eee={kernelName:xm,backendName:"webgl",kernelFunc:QQ};function tee(e){let{inputs:t,backend:n,attrs:a}=e,{dy:r,filter:s}=t,{strides:i,dilations:o,pad:l,dimRoundingMode:u,inputShape:p}=a,d=N.computeConv2DInfo(p,s.shape,i,o,l,u,!0),c=new JQ(d);return n.runWebGLProgram(c,[r,s],"float32")}var nee={kernelName:vm,backendName:"webgl",kernelFunc:tee},aee=class{constructor(e){this.variableNames=["X"],this.outputShape=[e,e],this.userCode=`
      void main() {
          ivec2 coords = getOutputCoords();
          float val = coords[0] == coords[1] ? getX(coords[0]) : 0.0;
          setOutput(val);
      }
    `}};function ree(e){let{inputs:t,backend:n}=e,{x:a}=t,r=[...a.shape,...a.shape],s=v.sizeFromShape(a.shape),i=de({inputs:{x:a},backend:n,attrs:{shape:[s]}}),o=new aee(s),l=n.runWebGLProgram(o,[i],i.dtype),u=de({inputs:{x:l},backend:n,attrs:{shape:r}});return n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(l),u}var see={kernelName:wm,backendName:"webgl",kernelFunc:ree},iee=class{constructor(e){this.variableNames=["x","W"],this.outputShape=e.outShape;let{inHeight:t,inWidth:n,padInfo:a,strideHeight:r,strideWidth:s,filterHeight:i,filterWidth:o,dilationHeight:l,dilationWidth:u}=e,{top:p,left:d}=a;this.userCode=`
      const ivec2 strides = ivec2(${r}, ${s});
      const ivec2 pads = ivec2(${p}, ${d});
      const float neg_infinity = -3.4e38;

      void main() {
        ivec4 coords = getOutputCoords();
        int batch = coords.x;
        int d1 = coords.w;
        ivec2 outTopLeftCorner =
            coords.yz * strides - pads;
        int hBeg = outTopLeftCorner.x;
        int wBeg = outTopLeftCorner.y;

        float curVal = neg_infinity;
        for (int h = 0; h < ${i}; h++) {
          int hIn = hBeg + h * ${l};

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

              if (wIn >= 0 && wIn < ${n}) {
                float xVal = getX(batch, hIn, wIn, d1);
                float wVal = getW(h, w, d1);

                float val = xVal + wVal;
                if (val > curVal) {
                  curVal = val;
                }
              }
            }
          }
        }

        float result = curVal;
        setOutput(result);
      }
    `}};function oee(e){let{inputs:t,backend:n,attrs:a}=e,{x:r,filter:s}=t,{strides:i,pad:o,dilations:l}=a,u=N.computeDilation2DInfo(r.shape,s.shape,i,o,"NHWC",l),p,d=new iee(u);p=n.runWebGLProgram(d,[r,s],"float32");let c=de({inputs:{x:p},backend:n,attrs:{shape:u.outShape}});return n.disposeIntermediateTensorInfo(p),c}var lee={kernelName:fc,backendName:"webgl",kernelFunc:oee};function uee(e){let{inputs:t,backend:n,attrs:a}=e,{equation:r}=a,s=t,{allDims:i,summedDims:o,idDims:l}=N.decodeEinsumEquation(r,s.length);N.checkEinsumDimSizes(i.length,l,s);let{path:u,steps:p}=N.getEinsumComputePath(o,l),d=p.length,c=null,h=i.length,m=[];for(let f=0;f<d;++f){for(let g of p[f]){let{permutationIndices:b,expandDims:y}=N.getEinsumPermutation(h,l[g]),x;N.isIdentityPermutation(b)?x=s[g]:(x=Sn({inputs:{x:s[g]},backend:n,attrs:{perm:b}}),m.push(x));let w=x.shape.slice();for(let I=0;I<y.length;++I)w.splice(y[I],0,1);v.arraysEqual(x.shape,w)||(x=de({inputs:{x},backend:n,attrs:{shape:w}}),m.push(x)),c===null?c=x:(c=o1({inputs:{a:x,b:c},backend:n}),m.push(c))}f<d-1&&(u[f]>=0&&(c=Zf({inputs:{x:c},backend:n,attrs:{axis:u[f]-(i.length-h),keepDims:!1}}),m.push(c)),h--)}for(let f of m)f!==c&&n.disposeIntermediateTensorInfo(f);return c}var pee={kernelName:km,backendName:"webgl",kernelFunc:uee},cee="return (x >= 0.0) ? x : (exp(x) - 1.0);",dee=`
  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;
`,hee=Ye({opSnippet:cee,packedOpSnippet:dee}),mee={kernelName:_i,backendName:"webgl",kernelFunc:hee},fee="return (b >= 1.0) ? a : a * (b + 1.0);",gee=`
  vec4 bGTEZero = vec4(greaterThanEqual(b, vec4(0.)));
  return (bGTEZero * a) + ((vec4(1.0) - bGTEZero) * (a * (b + vec4(1.0))));
`,bee=e=>{let{inputs:t,backend:n}=e,{dy:a,y:r}=t,s=H().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new ud(gee,a.shape,r.shape):new $l(fee,a.shape,r.shape);return n.runWebGLProgram(s,[a,r],a.dtype)},yee={kernelName:Im,backendName:"webgl",kernelFunc:bee},xee=`
  return vec4(equal(a, b));
`,vee="return float(a == b);",wee=cn({opSnippet:vee,packedOpSnippet:xee,dtype:"bool",cpuKernelImpl:r7}),kee={kernelName:Xl,backendName:"webgl",kernelFunc:wee},Iee=`
  // Error function is calculated approximately with elementary function.
  // See "Handbook of Mathematical Functions with Formulas,
  // Graphs, and Mathematical Tables", Abramowitz and Stegun.
  float p = ${N.ERF_P};
  float a1 = ${N.ERF_A1};
  float a2 = ${N.ERF_A2};
  float a3 = ${N.ERF_A3};
  float a4 = ${N.ERF_A4};
  float a5 = ${N.ERF_A5};

  float sign = sign(x);
  x = abs(x);
  float t = 1.0 / (1.0 + p * x);
  return sign * (1.0 - (((((a5*t + a4)*t) + a3)*t + a2)*t + a1)*t*exp(-x*x));
`,See=Ye({opSnippet:Iee}),Tee={kernelName:Kl,backendName:"webgl",kernelFunc:See},Nee=tp+`
  return exp(x);
`,Cee=`
  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;
`,CE=Ye({opSnippet:Nee,packedOpSnippet:Cee,cpuKernelImpl:s7,dtype:"float32"}),_ee={kernelName:Ei,backendName:"webgl",kernelFunc:CE};function vx(e){let{inputs:t,attrs:n,backend:a}=e,{dim:r}=n,{input:s}=t,i=s.shape.length,o=s.shape.slice(),l=r;return r<0&&(v.assert(-(i+1)<=r,()=>`Axis must be in the interval [${-(i+1)}, ${i}]`),l=i+r+1),o.splice(l,0,1),de({inputs:{x:s},backend:a,attrs:{shape:o}})}var Eee={kernelName:Yl,backendName:"webgl",kernelFunc:vx},EI="return exp(x) - 1.0;",Aee=Ye({opSnippet:EI,packedOpSnippet:EI,cpuKernelImpl:i7}),$ee={kernelName:Zl,backendName:"webgl",kernelFunc:Aee},AI=class{constructor(e,t,n){this.variableNames=["real","imag"];let a=t[1];this.outputShape=t;let r=n?`2.0 * ${Math.PI}`:`-2.0 * ${Math.PI}`,s=n?`${a}.0`:"1.0",i;if(e==="real")i="return real * expR - imag * expI;";else if(e==="imag")i="return real * expI + imag * expR;";else throw new Error(`FFT component must be either "real" or "imag", got ${e}.`);this.userCode=`
      const float exponentMultiplier = ${r};

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

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

        float result = 0.0;

        for (int i = 0; i < ${a}; i++) {
          // x = (-2|2 * PI / N) * index * i;
          float x = exponentMultiplierTimesIndexRatio * float(i);
          float expR = cos(x);
          float expI = sin(x);
          float real = getReal(batch, i);
          float imag = getImag(batch, i);

          result +=
              unaryOpComplex(real, expR, imag, expI) / ${s};
        }

        return result;
      }

      void main() {
        ivec2 coords = getOutputCoords();
        setOutput(mulMatDFT(coords[0], coords[1]));
      }
    `}};function _E(e,t,n){let a=n.texData.get(e.dataId),r=v.sizeFromShape(e.shape),s=e.shape[e.shape.length-1],i=r/s,o=de({inputs:{x:e},backend:n,attrs:{shape:[i,s]}}),l=o.shape,u=new AI("real",l,t),p=new AI("imag",l,t),d=[{dataId:a.complexTensorInfos.real.dataId,dtype:a.complexTensorInfos.real.dtype,shape:l},{dataId:a.complexTensorInfos.imag.dataId,dtype:a.complexTensorInfos.imag.dtype,shape:l}],c=n.runWebGLProgram(u,d,"float32"),h=n.runWebGLProgram(p,d,"float32"),m=_s({inputs:{real:c,imag:h},backend:n});n.disposeIntermediateTensorInfo(c),n.disposeIntermediateTensorInfo(h);let f=de({inputs:{x:m},backend:n,attrs:{shape:e.shape}});return n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(m),f}function Fee(e){let{inputs:t,backend:n}=e,{input:a}=t;return _E(a,!1,n)}var Dee={kernelName:Sm,backendName:"webgl",kernelFunc:Fee},Ree=class{constructor(e,t){this.outputShape=[],this.customUniforms=[{name:"value",type:"float"}],this.variableNames=["x"],this.outputShape=e,this.userCode=`
      void main() {
        // Input can be obtained from uniform value.
        setOutput(value);
      }
    `}};function cd(e){let{backend:t,attrs:n}=e,{shape:a,value:r}=n,{dtype:s}=n;if(s=s||v.inferDtype(r),s==="string"){let i=v.getArrayFromDType(s,v.sizeFromShape(a));return i.fill(r),t.makeTensorInfo(a,s,i)}else{let i=new Ree(a,r),o=[[r]];return t.runWebGLProgram(i,[],s,o)}}var Mee={kernelName:gc,backendName:"webgl",kernelFunc:cd},Pee=class{constructor(e){this.variableNames=["Image"],this.outputShape=[];let t=e[2];this.outputShape=e,this.userCode=`
        void main() {
          ivec4 coords = getOutputCoords();
          int x = coords[2];

          int coordX = ${t} - x - 1;
          float outputValue;
          if(coordX >= 0 && coordX < ${t}) {
            outputValue = getImage(coords[0], coords[1], coordX, coords[3]);
          } else {
            outputValue = getImage(coords[0], coords[1], coords[2], coords[3]);
          }
          setOutput(outputValue);
        }
    `}},Oee={kernelName:Jl,backendName:"webgl",kernelFunc:({inputs:e,backend:t})=>{let{image:n}=e,a=t,r=new Pee(n.shape);return a.runWebGLProgram(r,[n],n.dtype)}},$I="return floor(x);",Lee=Ye({opSnippet:$I,packedOpSnippet:$I,cpuKernelImpl:o7}),zee={kernelName:Ai,backendName:"webgl",kernelFunc:Lee},Wee=`
  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;
  }
`,Bee=`
  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);
`,Vee=cn({opSnippet:Wee,packedOpSnippet:Bee,dtype:"int32"}),Uee={kernelName:$i,backendName:"webgl",kernelFunc:Vee},Gee=class{constructor(e){this.variableNames=["A"];let t=_n(),[n,a]=e;this.outputShape=e,this.userCode=`
      void main() {
        ivec3 coords = getOutputCoords();
        int texR = coords[0];
        int texC = coords[1];
        int depth = coords[2];
        vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${a}.0, ${n}.0);

        vec4 values = ${t.texture2D}(A, uv);
        float value;
        if (depth == 0) {
          value = values.r;
        } else if (depth == 1) {
          value = values.g;
        } else if (depth == 2) {
          value = values.b;
        } else if (depth == 3) {
          value = values.a;
        }

        setOutput(floor(value * 255.0 + 0.5));
      }
    `}},Hee=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0;let t=_n(),[n,a]=e;this.outputShape=e,this.userCode=`
      void main() {
        ivec3 coords = getOutputCoords();
        int texR = coords[0];
        int texC = coords[1];
        int depth = coords[2];

        vec4 result = vec4(0.);

        for(int row=0; row<=1; row++) {
          for(int col=0; col<=1; col++) {
            texC = coords[1] + row;
            depth = coords[2] + col;

            vec2 uv = (vec2(texC, texR) + halfCR) /
                       vec2(${a}.0, ${n}.0);
            vec4 values = ${t.texture2D}(A, uv);
            float value;
            if (depth == 0) {
              value = values.r;
            } else if (depth == 1) {
              value = values.g;
            } else if (depth == 2) {
              value = values.b;
            } else if (depth == 3) {
              value = values.a;
            }

            result[row * 2 + col] = floor(value * 255.0 + 0.5);
          }
        }

        ${t.output} = result;
      }
    `}},jee={kernelName:Fh,backendName:"webgl",kernelFunc:qee},sl,Ty=H().getBool("CANVAS2D_WILL_READ_FREQUENTLY_FOR_GPU");function qee(e){let{inputs:t,backend:n,attrs:a}=e,{pixels:r}=t,{numChannels:s}=a,i=typeof HTMLVideoElement!="undefined"&&r instanceof HTMLVideoElement,o=typeof HTMLImageElement!="undefined"&&r instanceof HTMLImageElement,[l,u]=i?[r.videoWidth,r.videoHeight]:[r.width,r.height],p=[u,l],d=[u,l,s];if(o||i){let f=H().getBool("CANVAS2D_WILL_READ_FREQUENTLY_FOR_GPU");(sl==null||f!==Ty)&&(Ty=f,sl=document.createElement("canvas").getContext("2d",{willReadFrequently:Ty})),sl.canvas.width=l,sl.canvas.height=u,sl.drawImage(r,0,0,l,u),r=sl.canvas}let c=n.makeTensorInfo(p,"int32");n.texData.get(c.dataId).usage=ca.PIXELS,n.gpgpu.uploadPixelDataToTexture(n.getTexture(c.dataId),r);let h=H().getBool("WEBGL_PACK")?new Hee(d):new Gee(d),m=n.runWebGLProgram(h,[c],"int32");return n.disposeData(c.dataId),m}function Kee(e){let{inputs:t,backend:n,attrs:a}=e,{x:r,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:u,dataFormat:p,dilations:d,dimRoundingMode:c,activation:h,leakyreluAlpha:m}=a,f=N.convertConv2DDataFormat(p),g=N.computeConv2DInfo(r.shape,s.shape,l,d,u,c,!1,f),b,y=[],x=i!=null,w=o!=null,I=h==="leakyrelu",T=()=>{let E=[r,s],A=(R,F)=>{if(F==="NCHW"&&R.shape.length===1&&R.shape[0]!==1){let S=de({inputs:{x:R},backend:n,attrs:{shape:[R.shape[0],1,1]}});return y.push(S),S}return R};if(x&&E.push(A(i,p)),w&&E.push(A(o,p)),I){let R=n.makeTensorInfo([],"float32",v.createScalarValue(m,"float32"));E.push(R),y.push(R)}return E};if(g.filterHeight===1&&g.filterWidth===1&&g.dilationHeight===1&&g.dilationWidth===1&&g.strideHeight===1&&g.strideWidth===1&&(g.padInfo.type==="SAME"||g.padInfo.type==="VALID"))b=kE({x:r,filter:s,convInfo:g,backend:n,bias:i,activation:h,preluActivationWeights:o,leakyreluAlpha:m});else if(g.strideWidth<=2&&f==="channelsLast"&&H().getBool("WEBGL_EXP_CONV")){let E=h?ic(h,!0):null,A=new wE(g,x,E,w,I),R=[[g.padInfo.top,g.padInfo.left],[g.strideHeight,g.strideWidth],[g.dilationHeight,g.dilationWidth],[g.inHeight,g.inWidth]],F=T();b=n.runWebGLProgram(A,F,"float32",R)}else if(H().getBool("WEBGL_CONV_IM2COL"))b=IE({x:r,filter:s,convInfo:g,backend:n,bias:i,activation:h,preluActivationWeights:o,leakyreluAlpha:m});else{let E=h?ic(h,!1):null,A=new vE(g,x,E,w,I),R=T();b=n.runWebGLProgram(A,R,"float32")}let C=de({inputs:{x:b},backend:n,attrs:{shape:g.outShape}});return y.push(b),y.forEach(E=>n.disposeIntermediateTensorInfo(E)),C}var Xee={kernelName:ei,backendName:"webgl",kernelFunc:Kee};function Yee(e){let{inputs:t,backend:n,attrs:a}=e,{x:r,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:u,dilations:p,dimRoundingMode:d,activation:c,leakyreluAlpha:h}=a,m=[],f=p;f==null&&(f=[1,1]),v.assert(N.eitherStridesOrDilationsAreOne(l,f),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${l} and dilations '${f}'`);let g=N.computeConv2DInfo(r.shape,s.shape,l,f,u,d,!0),b=H().getBool("WEBGL_PACK_DEPTHWISECONV")&&g.strideWidth<=2&&g.outChannels/g.inChannels===1,y=c?ic(c,b):null,x=[r,s],w=i!=null,I=o!=null,T=c==="leakyrelu";if(w&&x.push(i),I&&x.push(o),T){let R=n.makeTensorInfo([],"float32",v.createScalarValue(h,"float32"));x.push(R),m.push(R)}let C;b?C=new NE(g,w,y,I,T):C=new TE(g,w,y,I,T);let E=[[g.padInfo.top,g.padInfo.left],[g.strideHeight,g.strideWidth],[g.dilationHeight,g.dilationWidth],[g.inHeight,g.inWidth]],A=n.runWebGLProgram(C,x,"float32",E);return m.forEach(R=>n.disposeIntermediateTensorInfo(R)),A}var Zee={kernelName:ti,backendName:"webgl",kernelFunc:Yee},Jee=class{constructor(e,t,n,a){this.sliceDim=e,this.strides=t,this.paramsShape=a,this.variableNames=["x","indices"],this.outputShape=n;let r=gt(n.length),s=`
    int index;`;for(let i=0;i<this.sliceDim;i++)s+=`
          index = round(getIndices(coords[0], ${i}));
          out_of_bounds = out_of_bounds || index < 0;
          out_of_bounds = out_of_bounds || index >= ${this.paramsShape[i]};
          flattenIndex += index * ${this.strides[i]};`;this.userCode=`
         void main() {
          ${r} coords = getOutputCoords();
          int flattenIndex = 0;
          bool out_of_bounds = false;

          ${s}

          setOutput(out_of_bounds ? 0.0 : getX(flattenIndex, coords[1]));
        }
      `}};function Qee(e){let{inputs:t,backend:n}=e,{params:a,indices:r}=t,s=r.shape,i=s[s.length-1],o=v.sizeFromShape(a.shape),[l,u,p,d]=N.prepareAndValidate(a,r),c=de({inputs:{x:r},backend:n,attrs:{shape:[u,i]}}),h=de({inputs:{x:a},backend:n,attrs:{shape:[v.sizeFromShape(a.shape)/p,p]}});if(n.shouldExecuteOnCPU([a,r])||a.dtype==="string"){let b=n.readSync(r.dataId),y=n.bufferSync(a),x=l7(b,y,a.dtype,u,i,p,d,a.shape,o);return n.makeTensorInfo(l,a.dtype,x.values)}let m=new Jee(i,d,[u,p],a.shape),f=n.runWebGLProgram(m,[h,c],h.dtype),g=de({inputs:{x:f},backend:n,attrs:{shape:l}});return n.disposeIntermediateTensorInfo(c),n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(f),g}var ete={kernelName:eu,backendName:"webgl",kernelFunc:Qee},tte=class{constructor(e,t){this.variableNames=["A","indices"],this.outputShape=t,this.rank=t.length;let n=gt(this.rank),a=nte(e,2);this.userCode=`
      void main() {
        ${n} resRC = getOutputCoords();
        int index = int(getIndices(resRC.x, resRC.z));
        float inBounds = (index >= 0) && (index < ${e[2]}) ? 1.0 : 0.0;
        setOutput(inBounds * getA(${a}));
      }
    `}};function nte(e,t){let n=["resRC.x","resRC.y","resRC.z","resRC.w"],a=[];for(let r=0;r<e.length;r++)r===2?a.push("index"):a.push(`${n[r]}`);return a.join()}function EE(e){let{inputs:t,backend:n,attrs:a}=e,{x:r,indices:s}=t,{axis:i,batchDims:o}=a,l=v.parseAxisParam(i,r.shape)[0];if(H().get("DEBUG")){let y=n.readSync(s.dataId),x=r.shape[l];for(let w=0;w<y.length;++w){let I=y[w];v.assert(I<=x-1&&I>=0,()=>`GatherV2: the index value ${I} is not in [0, ${x-1}]`)}}let u=N.segment_util.collectGatherOpShapeInfo(r,s,l,o),p=v.sizeFromShape(s.shape),d=[],c=de({inputs:{x:r},backend:n,attrs:{shape:[u.batchSize,u.outerSize,u.dimSize,u.sliceSize]}}),h=de({inputs:{x:s},backend:n,attrs:{shape:[u.batchSize,p/u.batchSize]}});d.push(c),d.push(h);let m=[u.batchSize,u.outerSize,p/u.batchSize,u.sliceSize];if(n.shouldExecuteOnCPU([r,s])||r.dtype==="string"){let y=n.bufferSync(h),x=n.bufferSync(c),w=u7(x,y,m);return d.forEach(I=>n.disposeIntermediateTensorInfo(I)),n.makeTensorInfo(u.outputShape,w.dtype,w.values)}let f=new tte(c.shape,m),g=n.runWebGLProgram(f,[c,h],c.dtype);d.push(g);let b=de({inputs:{x:g},backend:n,attrs:{shape:u.outputShape}});return d.forEach(y=>n.disposeIntermediateTensorInfo(y)),b}var ate={kernelName:Ql,backendName:"webgl",kernelFunc:EE},rte="return float(a > b);",ste=`
  return vec4(greaterThan(a, b));
`,ite=cn({opSnippet:rte,packedOpSnippet:ste,cpuKernelImpl:p7,dtype:"bool"}),ote={kernelName:tu,backendName:"webgl",kernelFunc:ite},lte="return float(a >= b);",ute=`
  return vec4(greaterThanEqual(a, b));
`,pte=cn({opSnippet:lte,packedOpSnippet:ute,dtype:"bool",cpuKernelImpl:c7}),cte={kernelName:Di,backendName:"webgl",kernelFunc:pte};function dte(e){let{inputs:t,backend:n}=e,{input:a}=t;return _E(a,!0,n)}var hte={kernelName:Tm,backendName:"webgl",kernelFunc:dte},mte="return float(!isnan(x) && !isinf(x));",fte=Ye({opSnippet:mte,dtype:"bool"}),gte={kernelName:nu,backendName:"webgl",kernelFunc:fte},bte="return float(isinf(x));",yte=Ye({opSnippet:bte,dtype:"bool"}),xte={kernelName:au,backendName:"webgl",kernelFunc:yte},vte="return float(isnan(x));",wte=Ye({opSnippet:vte,dtype:"bool"}),kte={kernelName:ru,backendName:"webgl",kernelFunc:wte},Ite="return float(a < b);",Ste=`
  return vec4(lessThan(a, b));
`,Tte=cn({opSnippet:Ite,packedOpSnippet:Ste,cpuKernelImpl:d7,dtype:"bool"}),Nte={kernelName:su,backendName:"webgl",kernelFunc:Tte},Cte="return float(a <= b);",_te=`
  return vec4(lessThanEqual(a, b));
`,Ete=cn({opSnippet:Cte,packedOpSnippet:_te,cpuKernelImpl:h7,dtype:"bool"}),Ate={kernelName:iu,backendName:"webgl",kernelFunc:Ete};function $te(e){let{backend:t,attrs:n}=e,{start:a,stop:r,num:s}=n,i=m7(a,r,s);return t.makeTensorInfo([i.length],"float32",i)}var Fte={kernelName:Cm,backendName:"webgl",kernelFunc:$te},Dte=tp+`
  return x < 0.0 ? 0./0. : log(x);
`,Rte=`
  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;
`,Mte=Ye({opSnippet:Dte,packedOpSnippet:Rte,cpuKernelImpl:f7}),Pte={kernelName:Pi,backendName:"webgl",kernelFunc:Mte},Ote=tp+`
  return log(1.0 + x);
`,Lte=Ye({opSnippet:Ote}),zte={kernelName:ou,backendName:"webgl",kernelFunc:Lte},Wte="return float(a >= 1.0 && b >= 1.0);",Bte=`
  return vec4(
    vec4(greaterThanEqual(a, vec4(1.0))) *
    vec4(greaterThanEqual(b, vec4(1.0))));
`,Vte=cn({opSnippet:Wte,packedOpSnippet:Bte,dtype:"bool"}),Ute={kernelName:lu,backendName:"webgl",kernelFunc:Vte},Gte="return float(!(x >= 1.0));",Hte=Ye({opSnippet:Gte}),jte={kernelName:uu,backendName:"webgl",kernelFunc:Hte},qte="return float(a >= 1.0 || b >= 1.0);",Kte=`
  return min(
    vec4(greaterThanEqual(a, vec4(1.0))) +
    vec4(greaterThanEqual(b, vec4(1.0))),
    vec4(1.0));
`,Xte=cn({opSnippet:qte,packedOpSnippet:Kte,dtype:"bool"}),Yte={kernelName:pu,backendName:"webgl",kernelFunc:Xte},Zte=class{constructor(e,t,n,a,r){this.variableNames=["x"],this.outputShape=[];let s=t,i=e[3]-1;this.outputShape=e;let o,l=`float(${n}) + float(${a}) * sum`;r===.5?o=`inversesqrt(${l})`:r===1?o=`1.0/(${l})`:o=`exp(log(${l}) * float(-${r}));`,this.userCode=`
      void main() {
        ivec4 coords = getOutputCoords();
        int b = coords[0];
        int r = coords[1];
        int c = coords[2];
        int d = coords[3];
        float x = getX(b, r, c, d);
        float sum = 0.0;
        for (int j = -${s}; j <= ${s}; j++) {
          int idx = d + j;
          if (idx >= 0 && idx <=  ${i}) {
            float z = getX(b, r, c, idx);
            sum += z * z;
          }
        }
        float val = x * ${o};
        setOutput(val);
      }
    `}},Jte=class{constructor(e,t,n,a,r){this.variableNames=["x"],this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0;let s=t,i=e[3]-1;this.outputShape=e;let o,l=`float(${n}) + float(${a}) * sum`;r===.5?o=`inversesqrt(${l})`:r===1?o=`1.0/(${l})`:o=`exp(log(${l}) * float(-${r}));`,this.userCode=`
      void main() {
        ivec4 coords = getOutputCoords();
        int b = coords.x;
        int r = coords.y;
        int c = coords.z;
        int d = coords.w;

        bool hasNextCol = d < ${this.outputShape[3]};
        bool hasNextRow = c < ${this.outputShape[2]};

        vec4 sum = vec4(0.);
        vec4 xFragAtOutputCoords = getX(b, r, c, d);

        vec4 xAtOutputCoords = vec4(
          getChannel(xFragAtOutputCoords, vec2(c, d)),
          hasNextCol ?
            getChannel(xFragAtOutputCoords, vec2(c, d + 1)) : 0.0,
          hasNextRow ?
            getChannel(xFragAtOutputCoords , vec2(c + 1, d)) : 0.0,
          (hasNextRow && hasNextCol) ?
            getChannel(xFragAtOutputCoords, vec2(c + 1, d + 1)) : 0.0
        );

        int firstChannel = d - ${s};
        vec2 cache = vec2(0.);
        if(firstChannel >= 0){
          vec4 firstChannelFrag = getX(b, r, c, firstChannel);
          cache.x = getChannel(firstChannelFrag, vec2(c, firstChannel));
            if(hasNextRow){
              cache.y = getChannel(firstChannelFrag, vec2(c + 1, firstChannel));
            }
        }

        ivec2 depth = ivec2(d, d + 1);
        for (int j = - ${s}; j <= ${s}; j++) {
          ivec2 idx = depth + j;
          bvec2 aboveLowerBound = greaterThanEqual(idx, ivec2(0));
          bvec2 belowUpperBound = lessThanEqual(idx, ivec2(${i}));

          bool depthInRange = aboveLowerBound.x && belowUpperBound.x;
          bool depthPlusOneInRange = aboveLowerBound.y && belowUpperBound.y;

          if(depthInRange || depthPlusOneInRange){
            vec4 z = vec4(0.);
            vec4 xFragAtCurrentDepth;
            z.xz = cache.xy;
            if(depthPlusOneInRange && hasNextCol){
              xFragAtCurrentDepth = idx.y != d ?
                getX(b, r, c, idx.y) : xFragAtOutputCoords;
              z.y = getChannel(xFragAtCurrentDepth, vec2(c, idx.y));
              if(hasNextRow){
                z.w = getChannel(xFragAtCurrentDepth, vec2(c + 1, idx.y));
              }
            }
            cache.xy = z.yw;
            sum += z * z;
          }
        }
        vec4 result = xAtOutputCoords * ${o};
        setOutput(result);
      }
    `}},Qte=e=>{let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{depthRadius:s,bias:i,alpha:o,beta:l}=a,u=H().getBool("WEBGL_PACK_NORMALIZATION")?new Jte(r.shape,s,i,o,l):new Zte(r.shape,s,i,o,l);return n.runWebGLProgram(u,[r],r.dtype)},ene={kernelName:bc,backendName:"webgl",kernelFunc:Qte},tne=class{constructor(e,t,n,a,r){this.variableNames=["inputImage","outputImage","dy"],this.outputShape=[],this.outputShape=e,this.depth=e[3],this.depthRadius=t,this.bias=n,this.alpha=a,this.beta=r,this.userCode=`
      void main() {
        ivec4 coords = getOutputCoords();
        int b = coords[0];
        int r = coords[1];
        int c = coords[2];

        float result = 0.0;
        for (int d = 0; d < ${this.depth}; ++d) {
          int depthBegin = int(max(0.0, float(d - ${t})));
          int depthEnd = int(min(float(${this.depth}),
              float(d + ${t} + 1)));

          const int MIN_DEPTH_BEGIN = 0;
          const int MAX_DEPTH_END = ${this.depth};

          float norm = 0.0;
          for (int k = MIN_DEPTH_BEGIN; k < MAX_DEPTH_END; ++k) {
            if (k < depthBegin){
              continue;
            }
            else if (k >= depthBegin && k < depthEnd) {
              norm += getInputImage(b, r, c, k) * getInputImage(b, r, c, k);
            }
            else {
              break;
            }
          }

          norm = float(${a}) * norm + float(${n});

          for(int k = MIN_DEPTH_BEGIN; k < MAX_DEPTH_END; ++k){
            if (k < depthBegin){
              continue;
            }
            else if (k >= depthBegin && k < depthEnd){
              float dyi = -2.0 * float(${a})
                * float(${r})
                * getInputImage(b ,r ,c, k) * getOutputImage(b, r, c, d)
                / norm;
              if (k == d) {
                dyi += pow(norm, -1.0 * ${r});
              }
              if (k == coords[3]) {
                dyi *= getDy(b, r, c, d);
                result += dyi;
              }
            }
            else {
              break;
            }
          }
      }
      setOutput(result);
      }
    `}},nne=e=>{let{inputs:t,backend:n,attrs:a}=e,{x:r,y:s,dy:i}=t,{depthRadius:o,bias:l,alpha:u,beta:p}=a,d=new tne(r.shape,o,l,u,p);return n.runWebGLProgram(d,[r,s,i],r.dtype)},ane={kernelName:_m,backendName:"webgl",kernelFunc:nne};function rne(e,t,n,a){let r=v.sizeFromShape(t),s=v.sizeFromShape(e.shape)/r,i=de({inputs:{x:e},attrs:{shape:[s,r]},backend:a}),o=Io(i,e.dtype,"max",a),l=de({inputs:{x:o},attrs:{shape:n},backend:a});return a.disposeIntermediateTensorInfo(i),a.disposeIntermediateTensorInfo(o),l}function AE(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{reductionIndices:s,keepDims:i}=a,o=r.shape.length,l=v.parseAxisParam(s,r.shape),u=l,p=N.getAxesPermutation(u,o),d=p!=null,c=n.shouldExecuteOnCPU([r]),h=r;if(d){if(c){let y=n.texData.get(h.dataId).values,x=new Array(o);for(let T=0;T<x.length;T++)x[T]=r.shape[p[T]];let w=s1(y,r.shape,r.dtype,p,x);h=n.makeTensorInfo(x,r.dtype);let I=n.texData.get(h.dataId);I.values=w}else h=Yf(r,p,n);u=N.getInnerMostAxes(u.length,o)}N.assertAxesAreInnerMostDims("max",u,o);let[m,f]=N.computeOutAndReduceShapes(h.shape,u),g=m;i&&(g=N.expandShapeToKeepDim(m,l));let b;if(c){let y=n.texData.get(h.dataId).values,x=g7(y,v.sizeFromShape(f),g,r.dtype);b=n.makeTensorInfo(g,r.dtype);let w=n.texData.get(b.dataId);w.values=x}else b=rne(h,f,g,n);return d&&n.disposeIntermediateTensorInfo(h),b}var sne={kernelName:Oi,backendName:"webgl",kernelFunc:AE},ine=i1+`
  return max(a, b);
`,one=`
  vec4 result = vec4(max(a, b));
  bvec4 isNaNA = isnan(a);
  bvec4 isNaNB = isnan(b);
  bvec4 isNaN = bvec4(isNaNA.x || isNaNB.x, isNaNA.y || isNaNB.y, isNaNA.z || isNaNB.z, isNaNA.w || isNaNB.w);
  `+ld+`
  return result;
`,lne=cn({opSnippet:ine,packedOpSnippet:one,cpuKernelImpl:b7}),une={kernelName:Li,backendName:"webgl",kernelFunc:lne};function pne(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t;Yu(r,"maxPool");let{filterSize:s,strides:i,pad:o,dimRoundingMode:l}=a,u=1;v.assert(N.eitherStridesOrDilationsAreOne(i,u),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${i} and dilations '${u}'`);let p=N.computePool2DInfo(r.shape,s,i,u,o,l);if(p.filterWidth===1&&p.filterHeight===1&&v.arraysEqual(p.inShape,p.outShape))return aa({inputs:{x:r},backend:n});let d=new oc(p,"max",!1);return n.runWebGLProgram(d,[r],r.dtype)}var cne={kernelName:zi,backendName:"webgl",kernelFunc:pne};function dne(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{filterSize:s,strides:i,pad:o,dataFormat:l,dimRoundingMode:u}=a,p=[1,1,1],d=N.computePool3DInfo(r.shape,s,i,p,o,u,l),c=new l1(d,"max",!1);return n.runWebGLProgram(c,[r],r.dtype)}var hne={kernelName:yc,backendName:"webgl",kernelFunc:dne},mne=class{constructor(e){this.variableNames=["dy","maxPos"],this.outputShape=e.inShape;let t=e.strideHeight,n=e.strideWidth,a=e.dilationHeight,r=e.effectiveFilterHeight,s=e.effectiveFilterWidth,i=r-1-e.padInfo.top,o=s-1-e.padInfo.left,l=r*s-1;this.userCode=`
      const ivec2 pads = ivec2(${i}, ${o});

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

        ivec2 dyRCCorner = coords.yz - pads;
        int dyRCorner = dyRCCorner.x;
        int dyCCorner = dyRCCorner.y;

        // Convolve dy(?, ?, d) with pos mask(:, :, d) to get dx(xR, xC, d).
        // ? = to be determined. : = across all values in that axis.
        float dotProd = 0.0;
        for (int wR = 0; wR < ${r};
          wR += ${a}) {
          float dyR = float(dyRCorner + wR) / ${t}.0;

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

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

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

            float dyValue = getDy(b, idyR, idyC, d);
            int maxPosValue = ${l} - int(getMaxPos(b, idyR, idyC, d));

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

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

      void main() {
        ivec5 coords = getOutputCoords();
        int batch = coords.x;
        int ch = coords.u;

        ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads;
        int dyDCorner = dyCorner.x;
        int dyRCorner = dyCorner.y;
        int dyCCorner = dyCorner.z;

        // Convolve dy(?, ?, ?, ch) with pos mask(:, :, :, d) to get
        // dx(xD, xR, xC, ch).
        // ? = to be determined. : = across all values in that axis.
        float dotProd = 0.0;

        for (int wD = 0; wD < ${o};
           wD += ${r}) {
          float dyD = float(dyDCorner + wD) / ${t}.0;

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

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

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

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

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

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

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

              dotProd += dyValue * mask;
            }
          }
        }
        setOutput(dotProd);
      }
    `}};function gne(e){let{inputs:t,backend:n,attrs:a}=e,{dy:r,input:s}=t,i=s,{filterSize:o,strides:l,pad:u,dimRoundingMode:p}=a,d=[1,1,1],c=N.computePool3DInfo(i.shape,o,l,d,u,p),h=new l1(c,"max",!0),m=n.runWebGLProgram(h,[i],i.dtype),f=new fne(c),g=n.runWebGLProgram(f,[r,m],i.dtype);return n.disposeIntermediateTensorInfo(m),g}var bne={kernelName:Am,backendName:"webgl",kernelFunc:gne};function yne(e){let{inputs:t,backend:n,attrs:a}=e,{dy:r,input:s,output:i}=t,o=s;Yu([s,i],"maxPoolGrad");let{filterSize:l,strides:u,pad:p,dimRoundingMode:d}=a,c=N.computePool2DInfo(o.shape,l,u,1,p,d),h=!0,m=new oc(c,"max",h),f=n.runWebGLProgram(m,[o],o.dtype),g=new mne(c),b=n.runWebGLProgram(g,[r,f],o.dtype);return n.disposeIntermediateTensorInfo(f),b}var xne={kernelName:Em,backendName:"webgl",kernelFunc:yne};function vne(e,t,n,a){let r=new oc(n,"max",!1),s=a.runWebGLProgram(r,[e],"float32");r=new oc(n,"max",!0,!0,t);let i=a.runWebGLProgram(r,[e],"float32");return[s,i]}var wne={kernelName:$m,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{x:a}=e,{filterSize:r,strides:s,pad:i,includeBatchInIndex:o}=t,l=n;v.assert(a.shape.length===4,()=>`Error in maxPool: input must be rank 4 but got rank ${a.shape.length}.`);let u=[1,1];v.assert(N.eitherStridesOrDilationsAreOne(s,u),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${s} and dilations '${u}'`);let p=N.computePool2DInfo(a.shape,r,s,u,i),[d,c]=vne(a,o,p,l);return[d,c]}};function kne(e,t,n,a){let r=v.sizeFromShape(t),s=v.sizeFromShape(e.shape)/r,i=de({inputs:{x:e},attrs:{shape:[s,r]},backend:a}),o=Io(i,"float32","mean",a),l=de({inputs:{x:o},attrs:{shape:n},backend:a});return a.disposeIntermediateTensorInfo(i),a.disposeIntermediateTensorInfo(o),l}var Ine={kernelName:Wi,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{x:a}=e,{keepDims:r,axis:s}=t,i=n,o=a.shape.length,l=v.parseAxisParam(s,a.shape),u=l,p=N.getAxesPermutation(u,o),d=p!=null,c=i.shouldExecuteOnCPU([a]),h=[],m=a;if(d){if(c){let x=i.texData.get(m.dataId).values,w=new Array(o);for(let C=0;C<w.length;C++)w[C]=a.shape[p[C]];let I=s1(x,a.shape,a.dtype,p,w);m=i.makeTensorInfo(w,a.dtype);let T=i.texData.get(m.dataId);T.values=I}else m=Yf(a,p,i);h.push(m),u=N.getInnerMostAxes(u.length,o)}N.assertAxesAreInnerMostDims("sum",u,o);let[f,g]=N.computeOutAndReduceShapes(m.shape,u),b=f;r&&(b=N.expandShapeToKeepDim(f,l));let y=kne(m,g,b,i);for(let x of h)i.disposeIntermediateTensorInfo(x);return y}};function Sne(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{axis:s,keepDims:i}=a,o=r.shape.length,l=v.parseAxisParam(s,r.shape),u=l,p=N.getAxesPermutation(u,o),d=r;p!=null&&(d=Sn({inputs:{x:r},backend:n,attrs:{perm:p}}),u=N.getInnerMostAxes(u.length,r.shape.length)),N.assertAxesAreInnerMostDims("min",u,o);let[c,h]=N.computeOutAndReduceShapes(d.shape,u),m=v.sizeFromShape(h),f=de({inputs:{x:d},backend:n,attrs:{shape:[-1,m]}}),g=Io(f,f.dtype,"min",n),b;if(i){let y=N.expandShapeToKeepDim(c,l);b=de({inputs:{x:g},backend:n,attrs:{shape:y}})}else b=de({inputs:{x:g},backend:n,attrs:{shape:c}});return n.disposeIntermediateTensorInfo(f),n.disposeIntermediateTensorInfo(g),p!=null&&n.disposeIntermediateTensorInfo(d),b}var Tne={kernelName:Bi,backendName:"webgl",kernelFunc:Sne},Nne=i1+`
  return min(a, b);
`,Cne=`
  vec4 result = vec4(min(a, b));
  bvec4 isNaNA = isnan(a);
  bvec4 isNaNB = isnan(b);
  bvec4 isNaN = bvec4(isNaNA.x || isNaNB.x, isNaNA.y || isNaNB.y, isNaNA.z || isNaNB.z, isNaNA.w || isNaNB.w);
  `+ld+`
  return result;
`,_ne=cn({opSnippet:Nne,packedOpSnippet:Cne,cpuKernelImpl:y7}),Ene={kernelName:Vi,backendName:"webgl",kernelFunc:_ne},Ane=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=t.map((u,p)=>u[0]+e[p]+u[1]);let a=e.length,r=gt(a),s=t.map(u=>u[0]).join(","),i=t.map((u,p)=>u[0]+e[p]).join(","),o=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,a),l=n==="reflect"?0:1;if(a===1){this.userCode=`
        int start = ${s};
        int end = ${i};

        void main() {
          int outC = getOutputCoords();
          if (outC < start) {
            outC = start * 2 - outC - ${l};
          } else if(outC >= end) {
            outC = (end - 1) * 2 - outC + ${l};
          }
          setOutput(getX(outC - start));
        }
      `;return}this.userCode=`
      ${r} start = ${r}(${s});
      ${r} end = ${r}(${i});

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

      void main() {
        ${r} outputLoc = getOutputCoords();
        vec4 result = vec4(0.);
        ${c}
        setOutput(result);
      }
    `}},Fne=({inputs:e,backend:t,attrs:n})=>{let{x:a}=e,{paddings:r,mode:s}=n,i=H().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new $ne(a.shape,r,s):new Ane(a.shape,r,s);return t.runWebGLProgram(i,[a],a.dtype)},Dne={kernelName:Ui,backendName:"webgl",kernelFunc:Fne},Rne=`if (b == 0.0) return NAN;
  return mod(a, b);`,Mne=`
  vec4 result = mod(a, b);
  bvec4 isNaN = equal(b, vec4(0.0));
  `+ld+`
  return result;
`,Pne=cn({opSnippet:Rne,packedOpSnippet:Mne}),One={kernelName:cu,backendName:"webgl",kernelFunc:Pne},Lne=class{constructor(e,t,n){this.variableNames=["probs"],this.customUniforms=[{name:"seed",type:"float"}],this.outputShape=[e,n],this.userCode=`
      void main() {
        ivec2 coords = getOutputCoords();
        int batch = coords[0];

        float r = random(seed);
        float cdf = 0.0;

        for (int i = 0; i < ${t-1}; i++) {
          cdf += getProbs(batch, i);

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

        // If no other event happened, last event happened.
        setOutput(float(${t-1}));
      }
    `}},zne=`
if (a == b) {
  return 1.0;
};
return a / b;`,Wne=`
  // 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;
`,$E=cn({opSnippet:zne,packedOpSnippet:Wne,checkOutOfBounds:!0}),Bne={kernelName:Ci,backendName:"webgl",kernelFunc:$E},FI="return a - b;",FE=cn({opSnippet:FI,packedOpSnippet:FI,supportsComplex:!0,cpuKernelImpl:L7}),Vne={kernelName:uo,backendName:"webgl",kernelFunc:FE};function DE(e){let{inputs:t,backend:n,attrs:a}=e,{logits:r}=t,{dim:s}=a,i=v.parseAxisParam([s],r.shape),o=AE({inputs:{x:r},backend:n,attrs:{reductionIndices:i,keepDims:!1}}),l=N.expandShapeToKeepDim(o.shape,i),u=de({inputs:{x:o},backend:n,attrs:{shape:l}}),p=FE({inputs:{a:r,b:u},backend:n}),d=CE({inputs:{x:p},backend:n}),c=Zf({inputs:{x:d},backend:n,attrs:{axis:i,keepDims:!1}}),h=de({inputs:{x:c},backend:n,attrs:{shape:l}}),m=$E({inputs:{a:d,b:h},backend:n});return n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(u),n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(c),n.disposeIntermediateTensorInfo(h),m}var Une={kernelName:oo,backendName:"webgl",kernelFunc:DE};function Gne(e){let{inputs:t,backend:n,attrs:a}=e,{logits:r}=t,{numSamples:s,seed:i,normalized:o}=a,l=o?r:DE({inputs:{logits:r},backend:n,attrs:{dim:r.shape.length-1}}),u=l.shape[0],p=l.shape[1],d=new Lne(u,p,s),c=[[i]],h=n.runWebGLProgram(d,[l],"int32",c);return o||n.disposeIntermediateTensorInfo(l),h}var Hne={kernelName:Fm,backendName:"webgl",kernelFunc:Gne},jne=Ma+`
  return -x;
`,qne=`
  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 Kne(e){let{inputs:t,backend:n}=e,{x:a}=t;if(n.shouldExecuteOnCPU([a])){let s=n.texData.get(a.dataId),[i,o]=v7(s.values,a.shape,a.dtype);return n.makeTensorInfo(o,a.dtype,i)}let r;return H().getBool("WEBGL_PACK_UNARY_OPERATIONS")?r=new qs(a.shape,qne):r=new Cr(a.shape,jne),n.runWebGLProgram(r,[a],a.dtype)}var Xne={kernelName:du,backendName:"webgl",kernelFunc:Kne},Yne=hr.nonMaxSuppressionV3Impl;function Zne(e){N.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:a}=e,{boxes:r,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l}=a,u=n.readSync(r.dataId),p=n.readSync(s.dataId),{selectedIndices:d}=Yne(u,p,i,o,l);return n.makeTensorInfo([d.length],"int32",new Int32Array(d))}var Jne={kernelName:mu,backendName:"webgl",kernelFunc:Zne},Qne=hr.nonMaxSuppressionV4Impl;function eae(e){N.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:a}=e,{boxes:r,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l,padToMaxOutputSize:u}=a,p=n.readSync(r.dataId),d=n.readSync(s.dataId),{selectedIndices:c,validOutputs:h}=Qne(p,d,i,o,l,u);return[n.makeTensorInfo([c.length],"int32",new Int32Array(c)),n.makeTensorInfo([],"int32",new Int32Array([h]))]}var tae={kernelName:fu,backendName:"webgl",kernelFunc:eae},nae=hr.nonMaxSuppressionV5Impl;function aae(e){N.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:a}=e,{boxes:r,scores:s}=t,{maxOutputSize:i,iouThreshold:o,scoreThreshold:l,softNmsSigma:u}=a,p=n.readSync(r.dataId),d=n.readSync(s.dataId),c=i,h=o,m=l,f=u,{selectedIndices:g,selectedScores:b}=nae(p,d,c,h,m,f);return[n.makeTensorInfo([g.length],"int32",new Int32Array(g)),n.makeTensorInfo([b.length],"float32",new Float32Array(b))]}var rae={kernelName:gu,backendName:"webgl",kernelFunc:aae},sae=class{constructor(e,t,n,a){this.variableNames=["indices"],this.outputShape=[e,t],this.userCode=`
      void main() {
        ivec2 coords = getOutputCoords();
        int index = round(getIndices(coords.x));
        setOutput(mix(float(${a}), float(${n}),
                      float(index == coords.y)));
      }
    `}},iae=e=>{let{inputs:t,backend:n,attrs:a}=e,{indices:r}=t,{dtype:s,depth:i,onValue:o,offValue:l}=a,u=v.sizeFromShape(r.shape),p=new sae(u,i,o,l),d=de({inputs:{x:r},backend:n,attrs:{shape:[u]}}),c=n.runWebGLProgram(p,[d],s);n.disposeIntermediateTensorInfo(d);let h=[...r.shape,i],m=de({inputs:{x:c},backend:n,attrs:{shape:h}});return n.disposeIntermediateTensorInfo(c),m},oae={kernelName:Hi,backendName:"webgl",kernelFunc:iae};function rm(e){let{inputs:t,backend:n}=e,{x:a}=t;if(a.dtype==="complex64"){let r=pd({inputs:{input:a},backend:n}),s=rm({inputs:{x:r},backend:n}),i=Jf({inputs:{input:a},backend:n}),o=rm({inputs:{x:i},backend:n}),l=_s({inputs:{real:s,imag:o},backend:n});return n.disposeIntermediateTensorInfo(r),n.disposeIntermediateTensorInfo(s),n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(o),l}else return cd({attrs:{shape:a.shape,dtype:a.dtype,value:a.dtype==="string"?"":0},backend:n})}var lae={kernelName:Mu,backendName:"webgl",kernelFunc:rm};function RE(e){let{inputs:t,backend:n}=e,{x:a}=t;if(a.dtype==="string")throw new Error("onesLike is not supported under string dtype");if(a.dtype==="complex64"){let r=pd({inputs:{input:a},backend:n}),s=RE({inputs:{x:r},backend:n}),i=Jf({inputs:{input:a},backend:n}),o=rm({inputs:{x:i},backend:n}),l=_s({inputs:{real:s,imag:o},backend:n});return n.disposeIntermediateTensorInfo(r),n.disposeIntermediateTensorInfo(s),n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(o),l}else return cd({attrs:{shape:a.shape,dtype:a.dtype,value:1},backend:n})}var uae={kernelName:bu,backendName:"webgl",kernelFunc:RE};function pae(e){let{inputs:t,backend:n,attrs:a}=e,{axis:r}=a;if(t.length===1)return vx({inputs:{input:t[0]},backend:n,attrs:{dim:r}});let s=t[0].shape,i=t[0].dtype;t.forEach(p=>{v.assertShapesMatch(s,p.shape,"All tensors passed to stack must have matching shapes"),v.assert(i===p.dtype,()=>"All tensors passed to stack must have matching dtypes")});let o=[],l=t.map(p=>{let d=vx({inputs:{input:p},backend:n,attrs:{dim:r}});return o.push(d),d}),u=xE({inputs:l,backend:n,attrs:{axis:r}});return o.forEach(p=>n.disposeIntermediateTensorInfo(p)),u}var cae={kernelName:yu,backendName:"webgl",kernelFunc:pae},dae=class{constructor(e,t,n){this.variableNames=["x"],this.customUniforms=[{name:"value",type:"float"}],this.outputShape=t.map((l,u)=>l[0]+e[u]+l[1]);let a=e.length,r=gt(a),s=t.map(l=>l[0]).join(","),i=t.map((l,u)=>l[0]+e[u]).join(","),o=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,a);if(a===1){this.userCode=`
        int start = ${s};
        int end = ${i};

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

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

      void main() {
        ${r} outputLoc = getOutputCoords();
        vec4 result = vec4(0.);
        ${h}
        setOutput(result);
      }
    `}},ME=e=>{let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{paddings:s,constantValue:i}=a;if(v.sizeFromShape(r.shape)===0){let u=s.map((p,d)=>p[0]+r.shape[d]+p[1]);return cd({backend:n,attrs:{shape:u,value:i,dtype:r.dtype}})}let o=H().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new hae(r.shape,s,i):new dae(r.shape,s,i),l=[[i]];return n.runWebGLProgram(o,[r],r.dtype,l)},mae={kernelName:ji,backendName:"webgl",kernelFunc:ME},fae=`
  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);
`,gae=`
  // isModRound1 has 1 for components with round(mod(b, 2.0)) == 1, 0 otherwise.
  vec4 isModRound1 = vec4(equal(round(mod(b, 2.0)), ivec4(1)));
  vec4 multiplier = sign(a) * isModRound1 + (vec4(1.0) - isModRound1);
  vec4 result = multiplier * pow(abs(a), b);

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

  bvec4 isNaN1 = lessThan(a, vec4(0.0));
  bvec4 isNaN2 = lessThan(floor(b), b);
  bvec4 isNaN = bvec4(isNaN1.x && isNaN2.x, isNaN1.y && isNaN2.y, isNaN1.z && isNaN2.z, isNaN1.w && isNaN2.w);
  `+ld+`
  return result;
`,bae=cn({opSnippet:fae,packedOpSnippet:gae}),yae={kernelName:qi,backendName:"webgl",kernelFunc:bae};function xae(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{axis:s,keepDims:i}=a,o=r.shape.length,l=[],u=v.parseAxisParam(s,r.shape),p=u,d=N.getAxesPermutation(p,o),c=r;d!=null&&(c=Sn({inputs:{x:r},backend:n,attrs:{perm:d}}),p=N.getInnerMostAxes(p.length,o),l.push(c)),N.assertAxesAreInnerMostDims("prod",p,o);let h;if(n.shouldExecuteOnCPU([c])){let m=n.texData.get(c.dataId).values,{outVals:f,outShape:g,outDtype:b}=k7(c.shape,c.dtype,m,p);h=n.makeTensorInfo(g,b,f)}else{let[m,f]=N.computeOutAndReduceShapes(c.shape,p),g=v.sizeFromShape(f),b=de({inputs:{x:c},backend:n,attrs:{shape:[-1,g]}}),y=Um(r.dtype),x=Io(b,y,"prod",n);h=de({inputs:{x},backend:n,attrs:{shape:m}}),l.push(b),l.push(x)}if(i){l.push(h);let m=N.expandShapeToKeepDim(h.shape,u);h=de({inputs:{x:h},backend:n,attrs:{shape:m}})}return l.forEach(m=>n.disposeIntermediateTensorInfo(m)),h}var vae={kernelName:Xi,backendName:"webgl",kernelFunc:xae};function wae(e){let{inputs:t,backend:n,attrs:a}=e,{paramsNestedSplits:r,paramsDenseValues:s,indices:i}=t,{outputRaggedRank:o}=a,l=r.map(b=>n.readSync(b.dataId)),u=r.map(b=>b.shape),p=n.readSync(s.dataId),d=n.readSync(i.dataId),[c,h,m]=I7(l,u,p,s.shape,s.dtype,d,i.shape,o),f=c.map(b=>n.makeTensorInfo([b.length],"int32",b)),g=n.makeTensorInfo(m,s.dtype,h);return f.concat([g])}var kae={kernelName:Dm,backendName:"webgl",kernelFunc:wae};function Iae(e){let{inputs:t,backend:n}=e,{starts:a,limits:r,deltas:s}=t,i=n.readSync(a.dataId),o=n.readSync(r.dataId),l=n.readSync(s.dataId),[u,p]=S7(i,a.shape,a.dtype,o,r.shape,l,s.shape),d=n.makeTensorInfo([u.length],"int32",u),c=n.makeTensorInfo([p.length],a.dtype,p);return[d,c]}var Sae={kernelName:Rm,backendName:"webgl",kernelFunc:Iae};function Tae(e){let{inputs:t,backend:n,attrs:a}=e,{shape:r,values:s,defaultValue:i,rowPartitionTensors:o}=t,{rowPartitionTypes:l}=a,u=n.readSync(r.dataId),p=n.readSync(s.dataId),d=n.readSync(i.dataId),c=o.map(g=>n.readSync(g.dataId)),h=o.map(g=>g.shape),[m,f]=T7(u,r.shape,p,s.shape,s.dtype,d,i.shape,c,h,l);return n.makeTensorInfo(m,s.dtype,f)}var Nae={kernelName:Mm,backendName:"webgl",kernelFunc:Tae},PE=e=>{let{backend:t,attrs:n}=e,{start:a,stop:r,step:s,dtype:i}=n,o=N7(a,r,s,i);return t.makeTensorInfo([o.length],i,o)},Cae={kernelName:xc,backendName:"webgl",kernelFunc:PE},_ae="return 1.0 / x;",Eae=Ye({opSnippet:_ae}),Aae={kernelName:xu,backendName:"webgl",kernelFunc:Eae},$ae=Ma+`
  return (x < 0.0) ? 0.0 : x;
`,Fae=`
  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;
`,Dae=Ye({opSnippet:$ae,packedOpSnippet:Fae}),Rae={kernelName:Yi,backendName:"webgl",kernelFunc:Dae},Mae=Ma+`
  return (x < 0.0) ? 0.0 : min(6.0, x);
`,Pae=`
  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;
`,Oae=Ye({opSnippet:Mae,packedOpSnippet:Pae}),Lae={kernelName:Qi,backendName:"webgl",kernelFunc:Oae},zae=class{constructor(e,t,n,a,r){this.variableNames=["A"],this.outputShape=[];let[s,i,o,l]=e;this.outputShape=[s,t,n,l];let u=[a&&t>1?i-1:i,a&&n>1?o-1:o],p=[a&&t>1?t-1:t,a&&n>1?n-1:n],d;r?d="(vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC - vec2(0.5)":d="vec2(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
      const vec2 effectiveInputOverOutputRatioRC = vec2(
          ${u[0]/p[0]},
          ${u[1]/p[1]});
      const vec2 inputShapeRC = vec2(${i}.0, ${o}.0);

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

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

        // Compute the four integer indices.
        ivec2 sourceFloorRC = ivec2(max(sourceFracIndexRC, vec2(0.0)));
        ivec2 sourceCeilRC = ivec2(
          min(inputShapeRC - 1.0, ceil(sourceFracIndexRC)));

        float topLeft = getA(b, sourceFloorRC.x, sourceFloorRC.y, d);
        float bottomLeft = getA(b, sourceCeilRC.x, sourceFloorRC.y, d);
        float topRight = getA(b, sourceFloorRC.x, sourceCeilRC.y, d);
        float bottomRight = getA(b, sourceCeilRC.x, sourceCeilRC.y, d);

        vec2 fracRC = sourceFracIndexRC - vec2(sourceFloorRC);

        float top = topLeft + (topRight - topLeft) * fracRC.y;
        float bottom = bottomLeft + (bottomRight - bottomLeft) * fracRC.y;
        float newValue = top + (bottom - top) * fracRC.x;

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

      float getAValue(int b, int r, int c, int d) {
        return getChannel(getA(b, r, c, d), vec2(c, d));
      }

      void main() {
        ivec4 coords = getOutputCoords();
        int b = coords[0];
        int d = coords[3];
        // Calculate values for next column in yRC.z.
        ivec3 yRC = coords.yzz + ivec3(0, 0, 1);

        // Fractional source index.
        vec3 sourceFracIndexRC = ${d};

        // Compute the four integer indices.
        ivec3 sourceFloorRC = ivec3(max(sourceFracIndexRC, vec3(0.0)));
        ivec3 sourceCeilRC = ivec3(
          min(inputShapeRC - 1.0, ceil(sourceFracIndexRC)));

        // Should we calculate next column and row elements in 2x2 packed cell.
        bool hasNextCol = d < ${l-1};
        bool hasNextRow = coords.z < ${n-1};

        // In parallel, construct four corners for all four components in
        // packed 2x2 cell.
        vec4 topLeft = vec4(
          getAValue(b, sourceFloorRC.x, sourceFloorRC.y, d),
          hasNextCol ? getAValue(b, sourceFloorRC.x, sourceFloorRC.y, d + 1)
                     : 0.0,
          hasNextRow ? getAValue(b, sourceFloorRC.x, sourceFloorRC.z, d)
                     : 0.0,
          (hasNextRow && hasNextCol) ?
            getAValue(b, sourceFloorRC.x, sourceFloorRC.z, d + 1) : 0.0);

        vec4 bottomLeft = vec4(
          getAValue(b, sourceCeilRC.x, sourceFloorRC.y, d),
          hasNextCol ? getAValue(b, sourceCeilRC.x, sourceFloorRC.y, d + 1)
                     : 0.0,
          hasNextRow ? getAValue(b, sourceCeilRC.x, sourceFloorRC.z, d)
                     : 0.0,
          (hasNextRow && hasNextCol) ?
            getAValue(b, sourceCeilRC.x, sourceFloorRC.z, d + 1) : 0.0);

        vec4 topRight = vec4(
          getAValue(b, sourceFloorRC.x, sourceCeilRC.y, d),
          hasNextCol ? getAValue(b, sourceFloorRC.x, sourceCeilRC.y, d + 1)
                     : 0.0,
          hasNextRow ? getAValue(b, sourceFloorRC.x, sourceCeilRC.z, d)
                     : 0.0,
          (hasNextRow && hasNextCol) ?
            getAValue(b, sourceFloorRC.x, sourceCeilRC.z, d + 1) : 0.0);

        vec4 bottomRight = vec4(
          getAValue(b, sourceCeilRC.x, sourceCeilRC.y, d),
          hasNextCol ? getAValue(b, sourceCeilRC.x, sourceCeilRC.y, d + 1)
                     : 0.0,
          hasNextRow ? getAValue(b, sourceCeilRC.x, sourceCeilRC.z, d)
                     : 0.0,
          (hasNextRow && hasNextCol) ?
            getAValue(b, sourceCeilRC.x, sourceCeilRC.z, d + 1) : 0.0);

        vec3 fracRC = sourceFracIndexRC - vec3(sourceFloorRC);

        vec4 top = mix(topLeft, topRight, fracRC.yyzz);
        vec4 bottom = mix(bottomLeft, bottomRight, fracRC.yyzz);
        vec4 newValue = mix(top, bottom, fracRC.x);

        setOutput(newValue);
      }
    `}};function Bae(e){let{inputs:t,backend:n,attrs:a}=e,{images:r}=t,{alignCorners:s,halfPixelCenters:i,size:o}=a,[l,u]=o,p=H().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new Wae(r.shape,l,u,s,i):new zae(r.shape,l,u,s,i);return n.runWebGLProgram(p,[r],"float32")}var Vae={kernelName:Ji,backendName:"webgl",kernelFunc:Bae},Uae=class{constructor(e,t,n){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t;let[,a,r]=t,[,s,i]=e,o=[n&&s>1?a-1:a,n&&i>1?r-1:r],l=[n&&s>1?s-1:s,n&&i>1?i-1:i],u=o[0]/l[0],p=o[1]/l[1],d=1/u,c=1/p,h=Math.ceil(d)*2+2,m=Math.ceil(c)*2+2;this.userCode=`
      void main() {
        ivec4 coords = getOutputCoords();
        int b = coords[0];
        int d = coords[3];
        int r = coords[1];
        int c = coords[2];

        float accumulator = 0.0;

        const float heightScale = float(${u});
        const float widthScale = float(${p});

        const float invHeightScale = float(${d});
        const float invWidthScale = float(${c});

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

        // Compute bounds for where in dy we will look
        float startRLerp = floor(float(r) * invHeightScale);
        int startDyR = int(startRLerp - float(winHeight / 2));

        float startCLerp = floor(float(c) * invWidthScale);
        int startDyC = int(startCLerp - float(winWidth / 2));

        // Loop over dy
        for (int dyROffset = 0; dyROffset < winHeight; dyROffset++) {
          int dyR = dyROffset + startDyR;

          // Guard against the window exceeding the bounds of dy
          if (dyR < 0 || dyR >= ${s}) {
            continue;
          }

          for (int dyCOffset = 0; dyCOffset < winWidth; dyCOffset++) {
            int dyC = dyCOffset + startDyC;

            // Guard against the window exceeding the bounds of dy
            if (dyC < 0 || dyC >= ${i}) {
              continue;
            }

            float dxR = float(dyR) * heightScale;
            int topDxRIndex = int(floor(dxR));
            int bottomDxRIndex = int(min(ceil(dxR), ${a-1}.0));
            float dxRLerp = dxR - float(topDxRIndex);
            float inverseDxRLerp = 1.0 - dxRLerp;

            float dxC = float(dyC) * widthScale;
            int leftDxCIndex = int(floor(dxC));
            int rightDxCIndex = int(min(ceil(dxC), ${r-1}.0));
            float dxCLerp = dxC - float(leftDxCIndex);
            float inverseDxCLerp = 1.0 - dxCLerp;

            if (r == topDxRIndex && c == leftDxCIndex) {
              // topLeft
              accumulator +=
                getDy(b, dyR, dyC, d) * inverseDxRLerp * inverseDxCLerp;
            }

            if (r == topDxRIndex && c == rightDxCIndex) {
              // topRight
              accumulator += getDy(b, dyR, dyC, d) * inverseDxRLerp * dxCLerp;
            }

            if (r == bottomDxRIndex && c == leftDxCIndex) {
              // bottomLeft
              accumulator += getDy(b, dyR, dyC, d) * dxRLerp * inverseDxCLerp;
            }

            if (r == bottomDxRIndex && c == rightDxCIndex) {
              // bottomRight
              accumulator += getDy(b, dyR, dyC, d) * dxRLerp * dxCLerp;
            }
          }
        }
        // End loop over dy

        setOutput(accumulator);
      }
    `}};function Gae(e){let{inputs:t,backend:n,attrs:a}=e,{images:r,dy:s}=t,{alignCorners:i}=a,o=new Uae(s.shape,r.shape,i);return n.runWebGLProgram(o,[s],s.dtype)}var Hae={kernelName:Lm,backendName:"webgl",kernelFunc:Gae},jae=class{constructor(e,t,n,a,r){this.variableNames=["A"],this.outputShape=[];let[s,i,o,l]=e;this.outputShape=[s,t,n,l];let u=[a&&t>1?i-1:i,a&&n>1?o-1:o],p=[a&&t>1?t-1:t,a&&n>1?n-1:n],d=a?"0.5":"0.0",c;r?c="max((vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC, vec2(0.0))":c="vec2(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
      const vec2 effectiveInputOverOutputRatioRC = vec2(
          ${u[0]/p[0]},
          ${u[1]/p[1]});
      const vec2 inputShapeRC = vec2(${i}.0, ${o}.0);

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

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

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

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

      float getAValue(int b, int r, int c, int d) {
        return getChannel(getA(b, r, c, d), vec2(c, d));
      }

      void main() {
        ivec4 coords = getOutputCoords();
        int b = coords[0];
        int d = coords[3];
        // Calculate values for next column in yRC.z.
        ivec3 yRC = coords.yzz + ivec3(0, 0, 1);

        // Fractional source index.
        vec3 sourceFracIndexRC = ${c};

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

        // Should we calculate next column and row elements in 2x2 packed cell.
        bool hasNextCol = d < ${l-1};
        bool hasNextRow = coords.z < ${n-1};

        vec4 newValue = vec4(
          getAValue(b, sourceNearestRC.x, sourceNearestRC.y, d),
          hasNextCol ? getAValue(b, sourceNearestRC.x, sourceNearestRC.y, d + 1)
                     : 0.0,
          hasNextRow ? getAValue(b, sourceNearestRC.x, sourceNearestRC.z, d)
                     : 0.0,
          (hasNextRow && hasNextCol) ?
            getAValue(b, sourceNearestRC.x, sourceNearestRC.z, d + 1) : 0.0);

        setOutput(newValue);
      }
    `}};function Kae(e){let{inputs:t,backend:n,attrs:a}=e,{images:r}=t,{alignCorners:s,halfPixelCenters:i,size:o}=a,[l,u]=o,p=H().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new qae(r.shape,l,u,s,i):new jae(r.shape,l,u,s,i);return n.runWebGLProgram(p,[r],r.dtype)}var Xae={kernelName:Zi,backendName:"webgl",kernelFunc:Kae},Yae=class{constructor(e,t,n){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t;let[,a,r]=t,[,s,i]=e,o=[n&&s>1?a-1:a,n&&i>1?r-1:r],l=[n&&s>1?s-1:s,n&&i>1?i-1:i],u=o[0]/l[0],p=o[1]/l[1],d=1/u,c=1/p,h=Math.ceil(d)*2+2,m=Math.ceil(c)*2+2;this.userCode=`
      void main() {
        ivec4 coords = getOutputCoords();
        int b = coords[0];
        int d = coords[3];
        int r = coords[1];
        int c = coords[2];

        float accumulator = 0.0;

        const float heightScale = float(${u});
        const float widthScale = float(${p});

        const float invHeightScale = float(${d});
        const float invWidthScale = float(${c});

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

        // Compute bounds for where in dy we will look
        float startRLerp = floor(float(r) * invHeightScale);
        int startDyR = int(floor(startRLerp - float(winHeight / 2)));

        float startCLerp = floor(float(c) * invWidthScale);
        int startDyC = int(floor(startCLerp - float(winWidth / 2)));

        // Loop over dy
        for (int dyROffset = 0; dyROffset < winHeight; dyROffset++) {
          int dyR = dyROffset + startDyR;

          // Guard against the window exceeding the bounds of dy
          if (dyR < 0 || dyR >= ${s}) {
            continue;
          }

          for (int dyCOffset = 0; dyCOffset < winWidth; dyCOffset++) {
            int dyC = dyCOffset + startDyC;

            // Guard against the window exceeding the bounds of dy
            if (dyC < 0 || dyC >= ${i}) {
              continue;
            }

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

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

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

            int sourceNearestCol = int(min(
                float(int(${r}) - 1),
                ${n} ? float(round(sourceFracCol)) :
                                  float(floor(sourceFracCol))));

            if (r == sourceNearestRow && c == sourceNearestCol) {
              accumulator += getDy(b, dyR, dyC, d);
            }
          }
        }
        // End loop over dy

        setOutput(accumulator);
      }
    `}};function Zae(e){let{inputs:t,backend:n,attrs:a}=e,{images:r,dy:s}=t,{alignCorners:i}=a,o=new Yae(s.shape,r.shape,i);return n.runWebGLProgram(o,[s],s.dtype)}var Jae={kernelName:Om,backendName:"webgl",kernelFunc:Zae},Qae=class{constructor(e,t){this.variableNames=["x"];let n=e.length;if(n>4)throw new Error(`WebGL backend: Reverse of rank-${n} tensor is not yet supported`);if(this.outputShape=e,n===1){this.userCode=`
        void main() {
          int coord = getOutputCoords();
          setOutput(getX(${e[0]} - coord - 1));
        }
      `;return}let a=i=>t.indexOf(i)!==-1&&e[i]!==1?`${e[i]} - coords[${i}] - 1`:`coords[${i}]`,r=e.map((i,o)=>a(o)).join(","),s=gt(n);this.userCode=`
      void main() {
        ${s} coords = getOutputCoords();
        setOutput(getX(${r}));
      }
    `}},ere=class{constructor(e,t){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0;let n=e.length;if(n>4)throw new Error(`WebGL backend: Reverse of rank-${n} tensor is not yet supported`);this.outputShape=e;let a=kn("rc",n),r=`${a[n-1]} + 1 < ${this.outputShape[n-1]}`,s=`${a[n-2]} + 1 < ${this.outputShape[n-2]}`,i=gt(n);n===1?this.userCode=`
        void main(){
          int rc = getOutputCoords();
          vec4 result = vec4(0.);
          result.r = getChannel(getX(${e[0]} - rc - 1),
            ${e[0]} - rc - 1);
          if(${r}){
              result.g = getChannel(getX(${e[0]} - (rc  + 1) - 1),
                ${e[0]} - (rc  + 1) - 1);
          }
          setOutput(result);
        }
      `:this.userCode=`
        void main() {
          ${i} rc = getOutputCoords();
          vec4 result = vec4(0.);
          result.r = ${o(a.slice())};
          if(${r}){
            result.g = ${l(a.slice())};
          }
          if(${s}) {
            result.b = ${u(a.slice())};
            if(${r}) {
              result.a = ${p(a.slice())};
            }
          }
          setOutput(result);
        }
    `;function o(h){return d(h)}function l(h){return h[n-1]="("+h[n-1]+" + 1)",d(h)}function u(h){return h[n-2]="("+h[n-2]+" + 1)",d(h)}function p(h){return h[n-1]="("+h[n-1]+" + 1)",h[n-2]="("+h[n-2]+" + 1)",d(h)}function d(h){let m=e.map((b,y)=>c(y,h)),f=m.join(","),g=m.slice(-2).join(",");return`getChannel(getX(${f}), vec2(${g}))`}function c(h,m){return t.indexOf(h)!==-1&&e[h]!==1?`${e[h]} - ${m[h]} - 1`:`${m[h]}`}}};function tre(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{dims:s}=a,i=r.shape.length,o=v.parseAxisParam(s,r.shape);if(i===0)return aa({inputs:{x:r},backend:n});let l=H().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new ere(r.shape,o):new Qae(r.shape,o);return n.runWebGLProgram(l,[r],r.dtype)}var nre={kernelName:eo,backendName:"webgl",kernelFunc:tre},are=class{constructor(e,t){this.variableNames=["Image"],this.outputShape=[],this.customUniforms=[{name:"params",type:"vec4"}];let n=e[1],a=e[2];this.outputShape=e;let r="";typeof t=="number"?r=`float outputValue = ${t.toFixed(2)};`:r=`
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          int x = coords[2];
          int y = coords[1];
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          float coordYFloat = (float(x) - params[0]) * params[2] +
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          int coordX = int(round(coordXFloat + params[0]));
          int coordY = int(round(coordYFloat + params[1]));
          ${r}
          if(coordX >= 0 && coordX < ${a} && coordY >= 0 && coordY < ${n}) {
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          }
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        }
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  // OpenGL ES does not support round function.
  // The algorithm is based on banker's rounding.
  float base = floor(x);
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    return floor(x);
  } else if ((x - base) > 0.5) {
    return ceil(x);
  } else {
    if (mod(base, 2.0) == 0.0) {
      return base;
    } else {
      return base + 1.0;
    }
  }
`,ire=Ye({opSnippet:sre}),ore={kernelName:to,backendName:"webgl",kernelFunc:ire},lre="return inversesqrt(x);",ure=Ye({opSnippet:lre,cpuKernelImpl:C7}),pre={kernelName:no,backendName:"webgl",kernelFunc:ure},OE=class{constructor(e,t,n,a,r,s,i=!0){this.variableNames=["updates","indices","defaultValue"],this.outputShape=s;let o=gt(r.length),l=gt(s.length),u="";n===1?u="i":n===2&&(u="i, j");let p=`getIndices(${u})`,d="";a===1?d="i":a===2&&(d="i, coords[1]");let c=`getUpdates(${d})`,h=t>1?"strides[j]":"strides";this.userCode=`
        ${o} strides = ${o}(${r});

        void main() {
          ${l} coords = getOutputCoords();
          float sum = 0.0;
          bool found = false;
          for (int i = 0; i < ${e}; i++) {
            int flattenedIndex = 0;
            for (int j = 0; j < ${t}; j++) {
              int index = round(${p});
              flattenedIndex += index * ${h};
            }
            if (flattenedIndex == coords[0]) {
              sum += ${c};
              found = true;
            }
          }
          setOutput(mix(getDefaultValue(), sum, float(found)));
        }
      `}};function cre(e){let{inputs:t,backend:n,attrs:a}=e,{indices:r,updates:s}=t,{shape:i}=a,{sliceRank:o,numUpdates:l,sliceSize:u,strides:p,outputSize:d}=N.calculateShapes(s,r,i),c=[d/u,u];if(d===0)return n.makeTensorInfo(i,r.dtype);let h=de({inputs:{x:r},backend:n,attrs:{shape:[l,o]}}),m=de({inputs:{x:s},backend:n,attrs:{shape:[l,u]}}),f=n.makeTensorInfo([],"float32",new Float32Array([0])),g=new OE(l,o,h.shape.length,m.shape.length,p,c),b=n.runWebGLProgram(g,[m,h,f],m.dtype),y=de({inputs:{x:b},backend:n,attrs:{shape:i}});return n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(b),n.disposeIntermediateTensorInfo(f),y}var dre={kernelName:wu,backendName:"webgl",kernelFunc:cre},hre=class{constructor(e,t,n,a){this.variableNames=["sortedSequence","values"],this.customUniforms=[{name:"numInputs",type:"int"}],this.outputShape=[e,n];let r="while (left < right) {",s=`for (int i = 0; i < ${Math.ceil(Math.log2(t+1))}; ++i) { if (left >= right) break;`,i=H().getNumber("WEBGL_VERSION")===2?r:s,o=a==="left"?"<":"<=";this.userCode=`
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         int left = 0;
         int right = numInputs;
         int mid;
         ${i}
           mid = (left + right) / 2;
           if (getSortedSequence(batch, mid) ${o} value) {
             left = mid + 1;
           } else {
             right = mid;
           }
         }
         return right;
       }

       void main() {
         ivec2 coords = getOutputCoords();
         int batch = coords[0];
         int valueIndex = coords[1];

         float value = getValues(batch, valueIndex);

         setOutput(float(findBound(batch, value)));
       }
     `}};function mre(e){let{inputs:t,backend:n,attrs:a}=e,{sortedSequence:r,values:s}=t,{side:i}=a,o=new hre(r.shape[0],r.shape[1],s.shape[1],i),l=[[r.shape[1]]];return n.runWebGLProgram(o,[r,s],"int32",l)}var fre={kernelName:zm,backendName:"webgl",kernelFunc:mre},gre=class{constructor(e,t,n){this.variableNames=["c","a","b"],this.outputShape=t;let a,r;if(n>4)throw Error(`Where for rank ${n} is not yet supported`);if(n===1)r="resRC",a="resRC";else{let i=["resRC.x","resRC.y","resRC.z","resRC.w"],o=[],l=[];for(let u=0;u<t.length;u++)l.push(`${i[u]}`),u<e&&o.push(`${i[u]}`);a=o.join(),r=l.join()}let s=gt(n);this.userCode=`
      void main() {
        ${s} resRC = getOutputCoords();
        float cVal = getC(${a});
        if (cVal >= 1.0) {
          setOutput(getA(${r}));
        } else {
          setOutput(getB(${r}));
        }
      }
    `}};function bre(e){let{inputs:t,backend:n}=e,{condition:a,t:r,e:s}=t,i=new gre(a.shape.length,r.shape,r.shape.length);return n.runWebGLProgram(i,[a,r,s],fa(r.dtype,s.dtype))}var yre={kernelName:ku,backendName:"webgl",kernelFunc:bre},xre=`
  // Stable and Attracting Fixed Point (0, 1) for Normalized Weights.
  // see: https://arxiv.org/abs/1706.02515
  float scaleAlpha = ${N.SELU_SCALEALPHA};
  float scale = ${N.SELU_SCALE};
  return (x >= 0.0) ? scale * x : scaleAlpha * (exp(x) - 1.0);
`,vre=Ye({opSnippet:xre}),wre={kernelName:Iu,backendName:"webgl",kernelFunc:vre},kre=tp+`
  return 1.0 / (1.0 + exp(-1.0 * x));
`,Ire=`
  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;
`,Sre=Ye({opSnippet:kre,packedOpSnippet:Ire,cpuKernelImpl:E7}),Tre={kernelName:ro,backendName:"webgl",kernelFunc:Sre},Nre=`
  if (isnan(x)) { return 0.0; }
  return sign(x);
`,Cre=Ye({opSnippet:Nre}),_re={kernelName:Nu,backendName:"webgl",kernelFunc:Cre},Ere=tp+`
  return sin(x);
`,Are=Ye({opSnippet:Ere}),$re={kernelName:ao,backendName:"webgl",kernelFunc:Are},Fre=`
  float e2x = exp(x);
  return (e2x - 1.0 / e2x) / 2.0;
`,Dre=Ye({opSnippet:Fre}),Rre={kernelName:Tu,backendName:"webgl",kernelFunc:Dre},Mre=`
  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;
`,Pre=Ye({opSnippet:Mre}),Ore={kernelName:Cu,backendName:"webgl",kernelFunc:Pre},Lre=e=>{let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{blockShape:s,paddings:i}=a;v.assert(r.shape.length<=4,()=>"spaceToBatchND for rank > 4 with a WebGL backend not implemented yet");let o=s.reduce((b,y)=>b*y),l=[[0,0]];l.push(...i);for(let b=1+s.length;b<r.shape.length;++b)l.push([0,0]);let u=[],p=ME({inputs:{x:r},backend:n,attrs:{paddings:l,constantValue:0}}),d=N.getReshaped(p.shape,s,o,!1),c=N.getPermuted(d.length,s.length,!1),h=N.getReshapedPermuted(p.shape,s,o,!1),m=de({inputs:{x:p},backend:n,attrs:{shape:d}}),f=Sn({inputs:{x:m},backend:n,attrs:{perm:c}}),g=de({inputs:{x:f},backend:n,attrs:{shape:h}});return u.push(p),u.push(m),u.push(f),u.forEach(b=>n.disposeIntermediateTensorInfo(b)),g},zre={kernelName:_u,backendName:"webgl",kernelFunc:Lre};function Wre(e){let{inputs:t,backend:n}=e,{indices:a,values:r,denseShape:s,defaultValue:i}=t;if(s.shape.length!==1)throw new Error(`Dense shape must be a vector, saw:
         ${s.shape}`);if(a.shape.length!==2)throw new Error(`Indices must be a matrix, saw:
         ${a.shape}`);if(r.shape.length!==1)throw new Error(`Values must be a vector, saw:
         ${r.shape}`);if(i.shape.length!==0)throw new Error(`Default value must be a scalar, saw:
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              ${r.shape}`);if(s.shape.length!==1)throw new Error(`Segment ids should be a vector but received shape
              ${s.shape}`);let i=n.readSync(a.dataId),o=n.readSync(r.dataId),l=n.readSync(s.dataId),[u,p]=sE(i,a.shape,a.dtype,o,l,!0);return n.makeTensorInfo(p,a.dtype,u)}var Hre={kernelName:wc,backendName:"webgl",kernelFunc:Gre};function jre(e){let{inputs:t,backend:n}=e,{data:a,indices:r,segmentIds:s}=t;if(a.shape.length<1)throw new Error("Data should be at least 1 dimensional but received scalar");if(r.shape.length!==1)throw new Error(`Indices should be a vector but received shape
             ${r.shape}`);if(s.shape.length!==1)throw new Error(`Segment ids should be a vector but received shape
             ${s.shape}`);let i=n.readSync(a.dataId),o=n.readSync(r.dataId),l=n.readSync(s.dataId),[u,p]=sE(i,a.shape,a.dtype,o,l);return n.makeTensorInfo(p,a.dtype,u)}var qre={kernelName:kc,backendName:"webgl",kernelFunc:jre};function Kre(e){let{inputs:t,backend:n,attrs:a}=e,{sparseIndices:r,sparseValues:s,defaultValue:i}=t,{outputShape:o}=a,{sliceRank:l,numUpdates:u,sliceSize:p,strides:d,outputSize:c}=N.calculateShapes(s,r,o),h=!1;if(s.dtype==="string"){let b=n.bufferSync(r),y=n.bufferSync(s),x=v.decodeString(n.readSync(i.dataId)[0]),w=_7(b,y,o,c,p,u,l,d,x,h);return n.makeTensorInfo(o,w.dtype,w.values)}let m=new OE(u,l,r.shape.length,s.shape.length,d,[c,1],h),f=n.runWebGLProgram(m,[s,r,i],s.dtype),g=de({inputs:{x:f},backend:n,attrs:{shape:o}});return n.disposeIntermediateTensorInfo(f),g}var Xre={kernelName:Wm,backendName:"webgl",kernelFunc:Kre};function Yre(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{numOrSizeSplits:s,axis:i}=a,o=v.parseAxisParam(i,r.shape)[0],l=N.prepareSplitSize(r,s,o),u=r.shape.length,p=new Array(u).fill(0),d=r.shape.slice();return l.map(c=>{let h=[...d];h[o]=c;let m=np({inputs:{x:r},backend:n,attrs:{begin:p,size:h}});return p[o]+=c,m})}var Zre={kernelName:Eu,backendName:"webgl",kernelFunc:Yre},DI="return sqrt(x);",Jre=Ye({opSnippet:DI,packedOpSnippet:DI,cpuKernelImpl:D7}),Qre={kernelName:so,backendName:"webgl",kernelFunc:Jre},ese="return x * x;",tse=Ye({opSnippet:ese}),nse={kernelName:Ic,backendName:"webgl",kernelFunc:tse},RI="return (a - b) * (a - b);",ase=cn({opSnippet:RI,packedOpSnippet:RI}),rse={kernelName:lo,backendName:"webgl",kernelFunc:ase};function sse({inputs:e,attrs:t,backend:n}){let{x:a}=e,r=Ma+`
    return x > 0.0 ? 1.0 : float(${t.alpha});
  `,s=new Cr(a.shape,r);return n.runWebGLProgram(s,[a],a.dtype)}var ise={kernelName:xs,backendName:"webgl",kernelFunc:sse},ose=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=n;let a=n.length,r=gt(n.length),s=gt(n.length),i="";if(a===1)i="coords * strides + begin";else{let o=0;i=n.map((l,u)=>(o++,n.length===1?`coords * strides[${u}] + begin[${u}]`:`coords[${o-1}] * strides[${u}] + begin[${u}]`)).join(",")}this.userCode=`
      ${r} begin = ${r}(${e});
      ${r} strides = ${r}(${t});

      void main() {
        ${s} coords = getOutputCoords();
        setOutput(getX(${i}));
      }
    `}};function lse(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{begin:s,end:i,strides:o,beginMask:l,endMask:u,ellipsisMask:p,newAxisMask:d,shrinkAxisMask:c}=a,{finalShapeSparse:h,finalShape:m,isIdentity:f,sliceDim0:g,isSimpleSlice:b,begin:y,end:x,strides:w}=jt.sliceInfo(r.shape,s,i,o,l,u,p,d,c),I;if(f)I=de({inputs:{x:r},backend:n,attrs:{shape:m}});else if(g||b){v.assert(r.shape.length>=1,()=>`Input must have rank at least 1, got: ${r.shape.length}`);let C=jt.computeOutShape(y,x,w),E=np({inputs:{x:r},backend:n,attrs:{begin:y,size:C}});I=de({inputs:{x:E},backend:n,attrs:{shape:m}}),n.disposeIntermediateTensorInfo(E)}else if(n.shouldExecuteOnCPU([r])){let C=n.readSync(r.dataId),E=Oe(r.shape,r.dtype,C),A=R7(h,E,w,y);I=n.makeTensorInfo(m,r.dtype,A.values)}else{let C=new ose(y,w,h);I=n.runWebGLProgram(C,[r],r.dtype)}let T=de({inputs:{x:I},backend:n,attrs:{shape:m}});return n.disposeIntermediateTensorInfo(I),T}var use={kernelName:$u,backendName:"webgl",kernelFunc:lse};function pse(e){let{inputs:t,backend:n,attrs:a}=e,{separator:r,nGramWidths:s,leftPad:i,rightPad:o,padWidth:l,preserveShortSequences:u}=a,{data:p,dataSplits:d}=t,c=n.readSync(p.dataId),h=n.readSync(d.dataId),[m,f]=M7(c,h,r,s,i,o,l,u);return[n.makeTensorInfo([m.length],"string",m),n.makeTensorInfo(d.shape,"int32",f)]}var cse={kernelName:Sc,backendName:"webgl",kernelFunc:pse};function dse(e){let{inputs:t,backend:n,attrs:a}=e,{skipEmpty:r}=a,{input:s,delimiter:i}=t;if(s.dtype!=="string")throw new Error("Input must be of datatype string");if(s.shape.length!==1)throw new Error(`Input must be a vector, got shape: ${s.shape}`);if(i.shape.length!==0)throw new Error(`Delimiter must be a scalar, got shape: ${i.shape}`);let o=n.readSync(s.dataId),l=n.readSync(i.dataId)[0],[u,p,d]=P7(o,l,r),c=p.length;return[n.makeTensorInfo([c,2],"int32",u),n.makeTensorInfo([c],"string",p),n.makeTensorInfo([2],"int32",new Int32Array(d))]}var hse={kernelName:Tc,backendName:"webgl",kernelFunc:dse};function mse(e){let{inputs:t,backend:n,attrs:a}=e,{numBuckets:r}=a,{input:s}=t;if(s.dtype!=="string")throw new Error("Input must be of datatype string");if(r<=0)throw new Error("Number of buckets must be at least 1");let i=n.readSync(s.dataId),o=O7(i,r);return n.makeTensorInfo(s.shape,"int32",o)}var fse={kernelName:Nc,backendName:"webgl",kernelFunc:mse},gse="return tan(x);",bse=Ye({opSnippet:gse}),yse={kernelName:po,backendName:"webgl",kernelFunc:bse},xse=`
  float e2x = exp(-2.0 * abs(x));
  return sign(x) * (1.0 - e2x) / (1.0 + e2x);
`,vse=Ye({opSnippet:xse}),wse={kernelName:co,backendName:"webgl",kernelFunc:vse},kse=class{constructor(e,t){this.variableNames=["A"];let n=new Array(e.length);for(let s=0;s<n.length;s++)n[s]=e[s]*t[s];this.outputShape=n,this.rank=n.length;let a=gt(this.rank),r=Ise(e);this.userCode=`
      void main() {
        ${a} resRC = getOutputCoords();
        setOutput(getA(${r}));
      }
    `}};function Ise(e){let t=e.length;if(t>5)throw Error(`Tile for rank ${t} is not yet supported`);if(t===1)return`imod(resRC, ${e[0]})`;let n=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u"],a=[];for(let r=0;r<e.length;r++)a.push(`imod(${n[r]}, ${e[r]})`);return a.join()}function LE(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{reps:s}=a;if(r.dtype==="string"||r.shape.length>5){let o=n.readSync(r.dataId),l=r.dtype==="string"?o.map(d=>v.decodeString(d)):o,u=Oe(r.shape,r.dtype,l),p=z7(u,s);return n.makeTensorInfo(p.shape,p.dtype,p.values)}let i=new kse(r.shape,s);return n.runWebGLProgram(i,[r],r.dtype)}var Sse={kernelName:ys,backendName:"webgl",kernelFunc:LE},Tse=class{constructor(e){this.variableNames=["x","indices"],this.customUniforms=[{name:"n",type:"int"},{name:"firstPass",type:"int"},{name:"negativeInf",type:"float"},{name:"dir",type:"int"},{name:"inc",type:"int"}],this.outputShape=e,this.userCode=`
       void main() {
         ivec2 coords = getOutputCoords();
         int batch = coords[0];
         int elemIdx = coords[1];

         // We compare elements pair-wise within a group of size 2 * inc.
         // The comparing rule for each group alternates between ascending
         // and descending. Within each group, we compare each pair at
         // positions i and i+inc. To decide whether an element at position i
         // is x0 or x1, we mod it by 2 * inc, if the result is smaller than
         // inc, it is in the first half of the group, we denote it as x0,
         // otherwise we denote it as x1.
         // For example, as shown in the Bitonic top K paper referenced above,
         // Figure5(a) shows that element[1] is in the
         // second half of the group when group size is 2, but it is in the
         // first half of the group when group size is 4.

         bool isFirstInPair = imod(elemIdx, 2 * inc) < inc;
         int i = isFirstInPair ? elemIdx : elemIdx - inc;

         int i0 = firstPass == 1 ? i : int(getIndices(batch, i));
         int i1 = firstPass == 1 ? i + inc : int(getIndices(batch, i + inc));
         float x0 = i0 < n ? getX(batch, i0) : negativeInf;
         float x1 = i1 < n ? getX(batch, i1) : negativeInf;

         // Denotes which direction indices are in (ascending or descending).
         bool reverse = imod(elemIdx, 2 * dir) >= dir;
         bool isGreater = x0 > x1 || (x0 == x1 && i1 > i0);
         if (reverse == isGreater) { // Elements in opposite order of direction
           int iTemp = i0;
           i0 = i1;
           i1 = iTemp;
         }
         if (isFirstInPair) {
            setOutput(float(i0));
         } else {
            setOutput(float(i1));
         }
       }
     `}},Nse=class{constructor(e){this.variableNames=["x","indices"],this.customUniforms=[{name:"n",type:"int"},{name:"firstPass",type:"int"},{name:"k",type:"int"}],this.outputShape=e,this.userCode=`
    void main() {
         // Takes max of indices (0, k), (1, k + 1), (2, k + 2) ...
         ivec2 coords = getOutputCoords();
         int batch = coords[0];
         int elemIdx = coords[1];

         // The output size is half of the previous size.
         // If the previous sequence is | | | | _ _ _ _  | | | |  _ _ _ _ (k=4),
         // we only need to output the indices at positions |, the indices at
         // positions _ can be thrown away, see Figure5(b) After Phase 2
         // (Merge phase) in the Bitonic Top K paper referenced above.
         // For example, the paper shows we only need to output the orange bars.
         // The output sequence should look like this | | | | | | | |.
         // Because the sequence is halved, to map the output index back
         // to the previous sequence to find the corresponding value,
         // we need to double the index. When we double the index,
         // we basically interpolate a position, so 2i looks like
         // | _ | _ | _ | _ | _ | _ | _. We move the | to the first k position
         // of each 2k positions by - elemIdx % k. E.g. for output at
         // index 4,5,6,7, we want to get the corresponding element at
         // original index 8,9,10,11, for output at index 8,9,10,11,
         // we want to get the corresponding element at original index
         // 16,17,18,19, so on and so forth.

         int i = elemIdx < k ? elemIdx : (elemIdx * 2 - imod(elemIdx, k));
         int i0 = firstPass == 1 ? i : int(getIndices(batch, i));
         int i1 = firstPass == 1 ? i + k : int(getIndices(batch, i + k));

         float x0 = getX(batch, i0);
         float x1 = i1 < n ? getX(batch, i1) : x0;

         setOutput(x0 >= x1 ? float(i0) : float(i1));
       }
     `}};function Ls(e,t){t!==null&&e.disposeIntermediateTensorInfo(t)}function MI(e){let t=1;for(;t<e;)t*=2;return t}function Cse(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{k:s,sorted:i}=a,o=H().getNumber("TOPK_LAST_DIM_CPU_HANDOFF_SIZE_THRESHOLD"),l=H().getNumber("TOPK_K_CPU_HANDOFF_THRESHOLD"),u=r.shape,p=u[u.length-1];if(n.shouldExecuteOnCPU([r])||p<o||s>l){let A=n.readSync(r.dataId),[R,F]=W7(A,u,r.dtype,s,i);return[n.makeTensorInfo(R.shape,R.dtype,R.values),n.makeTensorInfo(F.shape,F.dtype,F.values)]}if(s===0)return u[u.length-1]=0,[n.makeTensorInfo(u,r.dtype,[]),n.makeTensorInfo(u,"int32",[])];if(p===1)return[r,cd({attrs:{shape:u,dtype:"int32",value:0},backend:n})];let d=n.texData.get(r.dataId),c=d!==null&&d.isPacked,h=c?n.unpackTensor(r):r,m=v.sizeFromShape(u)/p,f=de({inputs:{x:h},attrs:{shape:[m,p]},backend:n});c&&Ls(n,h);let g=MI(s),b=MI(p),y=null,x=()=>y===null?[f,f]:[f,y],w=(A,R,F)=>{let S=x(),M=new Tse(F),B=[[p],[y===null?1:0],[Number.NEGATIVE_INFINITY],[A],[R]],U=y;y=n.runWebGLProgram(M,S,"int32",B),Ls(n,U)};for(let A=1;A<g;A*=2){let R=A*2;for(let F=A;F>=1;F/=2)w(R,F,[m,b])}for(let A=b;A>g;A/=2){let R=x(),F=new Nse([m,A/2]),S=[[p],[y===null?1:0],[g]],M=y;y=n.runWebGLProgram(F,R,"int32",S),Ls(n,M);let B=g/2,U=B*2;for(let G=B;G>=1;G/=2)w(U,G,y.shape)}let I=y;y=np({inputs:{x:y},backend:n,attrs:{begin:0,size:[m,s]}}),Ls(n,I);let T=EE({inputs:{x:f,indices:y},backend:n,attrs:{axis:1,batchDims:1}});Ls(n,f);let C=u.slice(0,-1);C.push(s),I=y,y=de({inputs:{x:y},attrs:{shape:C},backend:n}),Ls(n,I);let E=T;return T=de({inputs:{x:T},attrs:{shape:C},backend:n}),Ls(n,E),[T,y]}var _se={kernelName:Fu,backendName:"webgl",kernelFunc:Cse},Ese=class{constructor(e,t,n,a,r,s){this.variableNames=["Image","Transforms"],this.outputShape=s;let i=n==="nearest"?1:2,o;switch(a){case"constant":o=1;break;case"reflect":o=2;break;case"wrap":o=3;break;case"nearest":o=4;break;default:o=1;break}this.userCode=`
            float mapCoord(float outCoord, float len) {
              float inCoord = outCoord;
              if(${o} == 2) {
                if (inCoord < 0.0) {
                  if (len <= 1.0) {
                    inCoord = 0.0;
                  } else {
                    float sz2 = 2.0 * len;
                    if (inCoord < sz2) {
                      inCoord = sz2 * float(int(float(-inCoord / sz2))) +
                      inCoord;
                    }
                    inCoord = inCoord < -len ? inCoord + sz2 : -inCoord - 1.0;
                  }
                } else if (inCoord > len - 1.0) {
                  if (len <= 1.0) {
                    inCoord = 0.0;
                  } else {
                    float sz2 = 2.0 * len;
                    inCoord -= sz2 * float(int(float(inCoord / sz2)));
                    if (inCoord >= len) {
                      inCoord = sz2 - inCoord - 1.0;
                    }
                  }
                }
                return clamp(inCoord, 0.0, len - 1.0);
              } else if (${o} == 3) {
                if (inCoord < 0.0) {
                  if (len <= 1.0) {
                    inCoord = 0.0;
                  } else {
                    float sz = len - 1.0;
                    inCoord += len * (float(int(float(-inCoord / sz))) + 1.0);
                  }
                } else if (inCoord > len - 1.0) {
                  if (len <= 1.0) {
                    inCoord = 0.0;
                  } else {
                    float sz = len - 1.0;
                    inCoord -= len * float(int(float(inCoord / sz)));
                  }
                }
                return clamp(inCoord, 0.0, len - 1.0);
              } else if (${o} == 4) {
                return clamp(outCoord, 0.0, len - 1.0);
              } else {
                return outCoord;
              }
            }

            float readWithFillValue(int batch, int coordY, int coordX,
              int channel) {
              float outputValue;
              if (0 <= coordY && coordY < ${e} && 0 <= coordX && coordX < ${t}) {
                  outputValue = getImage(batch, coordY, coordX, channel);
              } else {
                outputValue = float(${r});
              }
              return outputValue;
            }

            void main() {
              ivec4 coords = getOutputCoords();
              float outputValue;
              int batch = coords[0];
              int x = coords[2];
              int y = coords[1];
              int channel = coords[3];
              float xf = float(x);
              float yf = float(y);
              float a1 = getTransforms(batch, 0);
              float a2 = getTransforms(batch, 1);
              float a3 = getTransforms(batch, 2);
              float b1 = getTransforms(batch, 3);
              float b2 = getTransforms(batch, 4);
              float b3 = getTransforms(batch, 5);
              float c1 = getTransforms(batch, 6);
              float c2 = getTransforms(batch, 7);
              float projection = c1 * xf + c2 * yf + 1.0;
              if (projection == 0.0) {
                outputValue = float(${r});
              } else {
                float inX = (a1 * xf + a2 * yf + a3) / projection;
                float inY = (b1 * xf + b2 * yf + b3) / projection;
                float mapX = mapCoord(inX, float(${t}));
                float mapY = mapCoord(inY, float(${e}));

                if (${i} == 1) {
                  int coordY = int(round(mapY));
                  int coordX = int(round(mapX));
                  outputValue = readWithFillValue(batch, coordY, coordX,
                    channel);
                } else {
                  float yFloor = floor(mapY);
                  float xFloor = floor(mapX);
                  float yCeil = yFloor + 1.0;
                  float xCeil = xFloor + 1.0;
                  float valueYFloor = (xCeil - mapX) *
                  readWithFillValue(batch, int(yFloor), int(xFloor), channel) +
                  (mapX - xFloor) *
                  readWithFillValue(batch, int(yFloor), int(xCeil), channel);
                  float valueYCeil = (xCeil - mapX) *
                  readWithFillValue(batch, int(yCeil), int(xFloor), channel) +
                  (mapX - xFloor) *
                  readWithFillValue(batch, int(yCeil), int(xCeil), channel);
                  outputValue = (yCeil - mapY) * valueYFloor +
                  (mapY - yFloor) * valueYCeil;
                }
              }
              setOutput(outputValue);
            }
        `}};function Ase(e){let{inputs:t,backend:n,attrs:a}=e,{image:r,transforms:s}=t,{interpolation:i,fillMode:o,fillValue:l,outputShape:u}=a,[p,d,c,h]=r.shape,[m,f]=u!=null?u:[d,c],g=[p,m,f,h],b=new Ese(d,c,i,o,l,g);return n.runWebGLProgram(b,[r,s],"float32")}var $se={kernelName:Du,backendName:"webgl",kernelFunc:Ase};function Fse(e){let{inputs:t,attrs:n,backend:a}=e,{axis:r}=n,{x:s}=t;Yu(s,"unique"),console.warn("WARNING: ","UI might be locked temporarily as data is being downloaded");let i=a.readSync(s.dataId),{outputValues:o,outputShape:l,indices:u}=B7(i,r,s.shape,s.dtype);return[a.makeTensorInfo(l,s.dtype,o),a.makeTensorInfo([u.length],"int32",u)]}var Dse={kernelName:Bm,backendName:"webgl",kernelFunc:Fse};function Rse(e){let{inputs:t,backend:n,attrs:a}=e,{value:r}=t,{axis:s}=a;s<0&&(s+=r.shape.length);let i=r,o=i.shape.length,l=r.shape[s],u=new Array(o-1),p=0;for(let f=0;f<o;f++)f!==s&&(u[p++]=i.shape[f]);let d=[],c=new Array(o).fill(0),h=i.shape.slice();h[s]=1;let m=new Array(l);for(let f=0;f<m.length;f++){c[s]=f;let g=np({inputs:{x:i},backend:n,attrs:{begin:c,size:h}}),b=de({inputs:{x:g},backend:n,attrs:{shape:u}});m[f]=b,d.push(g)}return d.forEach(f=>n.disposeIntermediateTensorInfo(f)),m}var Mse={kernelName:Ru,backendName:"webgl",kernelFunc:Rse},Pse=class{constructor(e,t){this.variableNames=["x","segmentIds"];let n=e.windowSize,a=e.batchSize,r=e.inSize,s=e.numSegments,i=s*Math.ceil(r/n);this.outputShape=[a,i];let o="0.0",l="sumValue",u=Math.floor(n/4)*4,p=n%4,d=`
        sumValue += dot(values, segFilter);
    `,c="";r%n>0&&(c=`
        if (inIdx < 0 || inIdx >= ${r}) {
          return initializationValue;
        }
      `);let h="";r%n>0&&(h=`
        if (inIdx < 0 || inIdx >= ${r}) {
          return -1.0;
        }
      `),this.userCode=`
      const float initializationValue = ${o};

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

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

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

        float sumValue = 0.0;

        for (int i = 0; i < ${u}; i += 4) {
          int inIdx = inOffset + i;
          vec4 values = vec4(
            getValue(batch, inIdx),
            getValue(batch, inIdx + 1),
            getValue(batch, inIdx + 2),
            getValue(batch, inIdx + 3)
          );

          vec4 segFilter = vec4(
            int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,
            int(getSegmentIdAtIndex(inIdx + 1)) == currentSeg ? 1 : 0,
            int(getSegmentIdAtIndex(inIdx + 2)) == currentSeg ? 1 : 0,
            int(getSegmentIdAtIndex(inIdx + 3)) == currentSeg ? 1 : 0
          );

          ${d}
        }

        int inIdx = inOffset + ${u};
        if (${p===1}) {
          vec4 values = vec4(
            getValue(batch, inIdx),
            initializationValue,
            initializationValue,
            initializationValue
          );

          int inIdxSeg = int(getSegmentIdAtIndex(inIdx));

          vec4 segFilter = vec4(
            int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,
            0,
            0,
            0
          );

          ${d}
        } else if (${p===2}) {
          vec4 values = vec4(
            getValue(batch, inIdx),
            getValue(batch, inIdx + 1),
            initializationValue,
            initializationValue
          );

          vec4 segFilter = vec4(
            int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,
            int(getSegmentIdAtIndex(inIdx + 1)) == currentSeg ? 1 : 0,
              0,
              0
          );

          ${d}
        } else if (${p===3}) {
          vec4 values = vec4(
            getValue(batch, inIdx),
            getValue(batch, inIdx + 1),
            getValue(batch, inIdx + 2),
            initializationValue
          );

          vec4 segFilter = vec4(
            int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,
            int(getSegmentIdAtIndex(inIdx + 1)) == currentSeg ? 1 : 0,
            int(getSegmentIdAtIndex(inIdx + 2)) == currentSeg ? 1 : 0,
            0
          );

          ${d}
        }
        setOutput(${l});
      }
    `}};function Ose(e){let{inputs:t,backend:n,attrs:a}=e,{x:r,segmentIds:s}=t,{numSegments:i}=a,o=r.shape.length,l=[],u=0,p=N.getAxesPermutation([u],o),d=r;p!=null&&(d=Sn({inputs:{x:r},backend:n,attrs:{perm:p}}),l.push(d),u=N.getInnerMostAxes(1,o)[0]);let c=N.segment_util.computeOutShape(d.shape,u,i),h=v.sizeFromShape([d.shape[u]]),m=de({inputs:{x:d},backend:n,attrs:{shape:[-1,h]}});l.push(m);let f=Um(r.dtype),g=(w,I,T,C,E)=>{let A=w.shape[0],R=w.shape[1],F=N.segment_util.segOpComputeOptimalWindowSize(R,E),S={windowSize:F,inSize:R,batchSize:A,numSegments:E},M=new Pse(S,I),B=n.compileAndRun(M,[w,T],C);if(l.push(B),B.shape[1]===E)return B;let U=PE({backend:n,attrs:{start:0,stop:E,step:1,dtype:"float32"}}),G=LE({inputs:{x:U},backend:n,attrs:{reps:[R/F]}});return l.push(U),l.push(G),g(B,I,G,C,E)},b=g(m,"unsortedSegmentSum",s,f,i),y=de({inputs:{x:b},backend:n,attrs:{shape:c}}),x=y;if(p!=null){l.push(y);let w=N.getUndoAxesPermutation(p);x=Sn({inputs:{x},backend:n,attrs:{perm:w}})}return l.forEach(w=>n.disposeIntermediateTensorInfo(w)),x}var Lse={kernelName:Cc,backendName:"webgl",kernelFunc:Ose},zse=[RJ,PJ,zJ,VJ,GJ,qJ,XJ,ZJ,t9,a9,i9,u9,d9,g9,x9,w9,I9,C9,E9,$9,M9,V9,G9,j9,J9,eQ,rQ,bJ,oQ,dQ,gQ,kQ,SQ,NQ,_Q,AQ,DQ,PQ,zQ,BQ,UQ,HQ,KQ,YQ,eee,nee,see,lee,pee,mee,yee,kee,Tee,_ee,Eee,$ee,Dee,Mee,Oee,zee,Uee,jee,Xee,Zee,ete,ate,ote,cte,gJ,hte,pQ,gte,xte,kte,xJ,Nte,Ate,Fte,Pte,zte,Ute,jte,Yte,ene,ane,sne,une,cne,hne,bne,xne,wne,Ine,Tne,Ene,Dne,One,Hne,kJ,Xne,Jne,tae,rae,K9,oae,uae,cae,mae,yae,wJ,vae,kae,Sae,Nae,Cae,X9,Bne,Aae,Rae,Lae,SJ,Vae,Hae,Xae,Jae,nre,rre,ore,pre,dre,fre,yre,wre,Tre,_re,$re,Rre,W9,Une,Ore,zre,Bre,Ure,Hre,qre,Xre,Zre,Qre,nse,rse,ise,use,cse,hse,fse,Vne,$J,yse,wse,Sse,_se,$se,FJ,Dse,Mse,Lse,lae];for(let e of zse)_c(e);var Et;(function(e){e[e.float32=0]="float32",e[e.int32=1]="int32",e[e.bool=2]="bool",e[e.string=3]="string",e[e.complex64=4]="complex64"})(Et||(Et={}));var uc;(function(e){e[e.linear=0]="linear",e[e.relu=1]="relu",e[e.relu6=2]="relu6",e[e.prelu=3]="prelu",e[e.leakyrelu=4]="leakyrelu",e[e.sigmoid=5]="sigmoid",e[e.elu=6]="elu"})(uc||(uc={}));var zE;function Wse(e){zE=e.wasm.cwrap(Qs,null,["number","array","number","number","array","number","number","number","number","number","number","number","number"])}function Bse(e){let{inputs:t,backend:n,attrs:a}=e,{a:r,b:s,bias:i,preluActivationWeights:o}=t;if(r.dtype!=="float32"||s.dtype!=="float32")throw new Error("_FusedMatMul for non non-float32 tensors not yet supported.");let{transposeA:l,transposeB:u,activation:p,leakyreluAlpha:d}=a,c=n.dataIdMap.get(r.dataId).id,h=n.dataIdMap.get(s.dataId).id,m=0;if(i!=null){let E=n.dataIdMap.get(i.dataId);if(E.shape.length!==1)throw new Error(`_FusedMatMul only supports rank-1 bias but got rank ${E.shape.length}.`);m=E.id}let f=o==null?0:n.dataIdMap.get(o.dataId).id,g=uc[p];if(g==null)throw new Error(`${p} activation not yet supported for FusedConv2D in the wasm backend.`);let b=l?r.shape[2]:r.shape[1],y=u?s.shape[1]:s.shape[2],x=Ou.assertAndGetBroadcastShape(r.shape.slice(0,-2),s.shape.slice(0,-2)),w=n.makeOutput([...x,b,y],r.dtype),I=n.dataIdMap.get(w.dataId).id,T=new Uint8Array(new Int32Array(r.shape).buffer),C=new Uint8Array(new Int32Array(s.shape).buffer);return zE(c,T,r.shape.length,h,C,s.shape.length,l,u,g,m,f,d||0,I),w}var Vse={kernelName:Qs,backendName:"wasm",setupFunc:Wse,kernelFunc:Bse};function an(e,t){let n;function a(s){n=s.wasm.cwrap(e,null,["number","number","number"])}function r(s){let{backend:i,inputs:{x:o}}=s,l=i.dataIdMap.get(o.dataId).id,u=i.makeOutput(o.shape,t||o.dtype),p=i.dataIdMap.get(u.dataId).id;return v.sizeFromShape(u.shape)===0||n(l,Et[o.dtype],p),u}return{kernelName:e,backendName:"wasm",setupFunc:a,kernelFunc:r}}var Use=an(Dl);function dn(e,t,n){let a;function r(i){a=i.wasm.cwrap(e,null,["number","array","number","number","array","number","number","number"])}function s(i){let{backend:o,inputs:l}=i,{a:u,b:p}=l,d=o.dataIdMap.get(u.dataId).id,c=o.dataIdMap.get(p.dataId).id,h=n!=null?n:u.dtype,m=N.assertAndGetBroadcastShape(u.shape,p.shape),f=o.makeOutput(m,h);if(v.sizeFromShape(m)===0)return f;let g=new Uint8Array(new Int32Array(u.shape).buffer),b=new Uint8Array(new Int32Array(p.shape).buffer),y=o.dataIdMap.get(f.dataId).id;return a(d,g,u.shape.length,c,b,p.shape.length,Et[u.dtype],y),f}return{kernelName:e,backendName:"wasm",setupFunc:r,kernelFunc:s}}var Gse=!0,Hse=dn(gs,Gse),WE;function jse(e){WE=e.wasm.cwrap(fi,null,["array","number","number","number"])}function qse(e){let{inputs:t,backend:n}=e,a=n.makeOutput(t[0].shape,t[0].dtype);if(v.sizeFromShape(a.shape)===0)return a;let r=t.map(o=>n.dataIdMap.get(o.dataId).id),s=new Uint8Array(new Int32Array(r).buffer),i=n.dataIdMap.get(a.dataId).id;return WE(s,r.length,Et[a.dtype],i),a}var Kse={kernelName:fi,backendName:"wasm",setupFunc:jse,kernelFunc:qse};function Qf(e){let{inputs:{x:t},backend:n}=e;if(t.dtype==="string")return In(n.readSync(t.dataId),t.shape,t.dtype);let a=n.makeOutput(t.shape,t.dtype),r=n.typedArrayFromHeap(t);return n.typedArrayFromHeap(a).set(r),a}var Xse={kernelName:Ri,backendName:"wasm",kernelFunc:Qf},BE;function Yse(e){BE=e.wasm.cwrap(_r,null,["number","array","number","number","number","array","number"])}function hs(e){let{inputs:t,backend:n,attrs:a}=e,[r,s]=Jse(t.x.shape,a.perm),i=!0;for(let m=0;m<s.length;m++)s[m]!==m&&(i=!1);let o=Zse(t.x.shape,a.perm),l={dataId:t.x.dataId,shape:r,dtype:t.x.dtype};if(i){let m=Qf({inputs:t,backend:n});return m.shape=o,m}let u=n.makeOutput(o,l.dtype),p=n.dataIdMap.get(l.dataId).id,d=n.dataIdMap.get(u.dataId).id,c=new Uint8Array(new Int32Array(s).buffer),h=new Uint8Array(new Int32Array(l.shape).buffer);return BE(p,h,l.shape.length,Et[l.dtype],d,c,s.length),u}function Zse(e,t){let n=new Array(e.length);for(let a=0;a<n.length;a++)n[a]=e[t[a]];return n}function Jse(e,t){let n=[],a=[];for(let r=0;r<e.length;++r)e[r]!==1&&n.push(e[r]),e[t[r]]!==1&&a.push(t[r]);for(let r=0;r<a.length;++r){let s=-1;for(let i=0;i<a.length;++i)a[i]>=r&&(s===-1||a[s]>a[i])&&(s=i);a[s]=r}return[n,a]}var Qse={kernelName:_r,backendName:"wasm",kernelFunc:hs,setupFunc:Yse};function Es(e,t,n){let a=e.shape,r=e.shape.length,s=v.parseAxisParam(t,a),i=s,o=N.getAxesPermutation(i,r),l=null,u=!1;if(o!=null){let p=new Array(r);for(let c=0;c<p.length;c++)p[c]=a[o[c]];i=N.getInnerMostAxes(i.length,r),l=hs({inputs:{x:e},attrs:{perm:o},backend:n});let d=n.dataIdMap.get(e.dataId).id;n.dataIdMap.get(l.dataId).id!==d&&(u=!0)}return{transposed:l,originalAxes:s,axes:i,inputWasTransposed:u}}var VE;function eie(e){VE=e.wasm.cwrap(Pl,null,["number, number, number"])}function tie(e){let{backend:t,inputs:n,attrs:a}=e,{axis:r,keepDims:s}=a,{x:i}=n,o=t.dataIdMap.get(i.dataId).id,l=i,{transposed:u,axes:p,originalAxes:d,inputWasTransposed:c}=Es(i,r,t);if(c){let y=t.dataIdMap.get(u.dataId).id;l=u,o=y}let h=l.shape.length;N.assertAxesAreInnerMostDims("all",p,h);let[m,f]=N.computeOutAndReduceShapes(l.shape,p),g=v.sizeFromShape(f),b=t.makeOutput(m,i.dtype);if(v.sizeFromShape(l.shape)!==0){let y=t.dataIdMap.get(b.dataId).id;VE(o,g,y)}if(c&&t.disposeData(u.dataId),s){let y=N.expandShapeToKeepDim(b.shape,d);b.shape=y}return b}var nie={kernelName:Pl,backendName:"wasm",setupFunc:eie,kernelFunc:tie},UE;function aie(e){UE=e.wasm.cwrap(Ol,null,["number, number, number"])}function rie(e){let{backend:t,inputs:n,attrs:a}=e,{axis:r,keepDims:s}=a,{x:i}=n,o=t.dataIdMap.get(i.dataId).id,l=i,{transposed:u,axes:p,originalAxes:d,inputWasTransposed:c}=Es(i,r,t);if(c){let y=t.dataIdMap.get(u.dataId).id;l=u,o=y}let h=l.shape.length;N.assertAxesAreInnerMostDims("any",p,h);let[m,f]=N.computeOutAndReduceShapes(l.shape,p),g=v.sizeFromShape(f),b=t.makeOutput(m,i.dtype);if(v.sizeFromShape(l.shape)!==0){let y=t.dataIdMap.get(b.dataId).id;UE(o,g,y)}if(c&&t.disposeData(u.dataId),s){let y=N.expandShapeToKeepDim(b.shape,d);b.shape=y}return b}var sie={kernelName:Ol,backendName:"wasm",setupFunc:aie,kernelFunc:rie},GE;function iie(e){GE=e.wasm.cwrap(gi,null,["number","number","number","number","number"])}function oie(e){let{backend:t,inputs:n,attrs:a}=e,{axis:r}=a,{x:s}=n,i=t.dataIdMap.get(s.dataId).id,o=i,l=s,{transposed:u,axes:p,inputWasTransposed:d}=Es(s,r,t);if(d){let b=t.dataIdMap.get(u.dataId).id;b!==i&&(l=u,o=b)}let c=l.shape.slice(0,-1),h=t.makeOutput(c,"int32"),m=t.dataIdMap.get(h.dataId).id,f=v.sizeFromShape(h.shape),g=l.shape[p[0]];return GE(o,Et[l.dtype],f,g,m),d&&t.disposeData(u.dataId),h}var lie={kernelName:gi,backendName:"wasm",kernelFunc:oie,setupFunc:iie},HE;function uie(e){HE=e.wasm.cwrap(bi,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function pie(e){let{inputs:t,attrs:n,backend:a}=e,r=t.x,s=a.dataIdMap.get(r.dataId).id,{filterSize:i,strides:o,pad:l,dimRoundingMode:u}=n,p=N.computePool2DInfo(r.shape,i,o,1,l,u),d=p.filterHeight,c=p.filterWidth,h=p.padInfo.top,m=p.padInfo.right,f=p.padInfo.bottom,g=p.padInfo.left,b=p.strideHeight,y=p.strideWidth,x=p.inChannels;if(p.dataFormat!=="channelsLast")throw new Error(`wasm backend does not support dataFormat:'${p.dataFormat}'. Please use 'channelsLast'.`);if(p.dilationWidth!==1||p.dilationHeight!==1)throw new Error(`was backend only supports average pooling with dilation = [1, 1], got [${p.dilationHeight}, ${p.dilationWidth}].`);let w=a.makeOutput(p.outShape,"float32"),I=a.dataIdMap.get(w.dataId).id;return HE(s,r.shape[0],r.shape[1],r.shape[2],d,c,h,m,f,g,b,y,x,I),w}var cie={kernelName:bi,backendName:"wasm",setupFunc:uie,kernelFunc:pie};function Wn(e){let{inputs:t,attrs:n}=e,{x:a}=t,{shape:r}=n,s=v.sizeFromShape(a.shape),i=v.inferFromImplicitShape(r,s);return v.assert(s===v.sizeFromShape(i),()=>`new shape: ${i}, old shape: ${a.shape}. New shape and old shape must have the same number of elements.`),e.backend.incRef(a.dataId),{dataId:a.dataId,shape:i,dtype:a.dtype}}var die={kernelName:vu,backendName:"wasm",kernelFunc:Wn},jE;function hie(e){jE=e.wasm.cwrap(yi,null,["number","array","number","number","array","number","number","number","number"])}function mie(e){let{inputs:t,backend:n,attrs:a}=e,{a:r,b:s}=t,{transposeA:i,transposeB:o}=a;if(r.dtype!=="float32"||s.dtype!=="float32")throw new Error("BatchMatMul for non non-float32 tensors not yet supported.");let l=r.shape.length,u=s.shape.length,p=i?r.shape[l-2]:r.shape[l-1],d=o?s.shape[u-1]:s.shape[u-2],c=i?r.shape[l-1]:r.shape[l-2],h=o?s.shape[u-2]:s.shape[u-1],m=r.shape.slice(0,-2),f=s.shape.slice(0,-2),g=v.sizeFromShape(m),b=v.sizeFromShape(f),y=Ou.assertAndGetBroadcastShape(r.shape.slice(0,-2),s.shape.slice(0,-2)).concat([c,h]);v.assert(p===d,()=>`Error in matMul: inner shapes (${p}) and (${d}) of Tensors with shapes ${r.shape} and ${s.shape} and transposeA=${i} and 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t.dtype==="string"?d.stringBytes=l.slice(m,m+v.sizeFromShape(i)):r.typedArrayFromHeap(u).set(l.subarray(m,m+v.sizeFromShape(i))),u}if(t.dtype==="string"){let m=Jh(l,s,i,t.shape,t.dtype);return d.stringBytes=m,u}let c=r.typedArrayFromHeap(u),h=t.shape.length;if(h===2)gie(l,p[0],c,s,i);else if(h===3)bie(l,p[0],p[1],c,s,i);else if(h===4)yie(l,p[0],p[1],p[2],c,s,i);else{let m=Jh(l,s,i,t.shape,t.dtype);c.set(m)}return u}function gie(e,t,n,a,r){let s=0,i=a[0],o=a[1],l=i+r[0];for(let u=i;u<l;u++){let p=u*t+o;n.set(e.subarray(p,p+r[1]),s),s+=r[1]}}function bie(e,t,n,a,r,s){let i=0,o=r[0],l=r[1],u=r[2],p=o+s[0],d=l+s[1];for(let c=o;c<p;c++)for(let h=l;h<d;h++){let m=c*t+h*n+u;a.set(e.subarray(m,m+s[2]),i),i+=s[2]}}function yie(e,t,n,a,r,s,i){let o=0,l=s[0],u=s[1],p=s[2],d=l+i[0],c=u+i[1],h=p+i[2],m=s[3];for(let f=l;f<d;f++)for(let g=u;g<c;g++)for(let b=p;b<h;b++){let y=f*t+g*n+b*a+m;r.set(e.subarray(y,y+i[3]),o),o+=i[3]}}var xie={kernelName:Su,backendName:"wasm",kernelFunc:hi};function vie(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{blockShape:s,crops:i}=a,o=s.reduce((b,y)=>b*y),l=N.getReshaped(r.shape,s,o),u=N.getPermuted(l.length,s.length),p=N.getReshapedPermuted(r.shape,s,o),d=N.getSliceBeginCoords(i,s.length),c=N.getSliceSize(p,i,s.length),h=Wn({inputs:{x:r},backend:n,attrs:{shape:l}}),m=hs({inputs:{x:h},backend:n,attrs:{perm:u}}),f=Wn({inputs:{x:m},backend:n,attrs:{shape:p}}),g=hi({inputs:{x:f},backend:n,attrs:{begin:d,size:c}});return n.disposeData(h.dataId),n.disposeData(m.dataId),n.disposeData(h.dataId),g}var wie={kernelName:Ul,backendName:"wasm",kernelFunc:vie};function ap(e){let{inputs:{x:t},attrs:{dtype:n},backend:a}=e,r=a.makeOutput(t.shape,n),s=a.typedArrayFromHeap(t);return a.typedArrayFromHeap(r).set(s),r}var kie={kernelName:xi,backendName:"wasm",kernelFunc:ap},Iie=an(vi),qE;function Sie(e){qE=e.wasm.cwrap(bs,null,["number","number","number","number"])}function Tie(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{clipValueMin:s,clipValueMax:i}=a,o=n.dataIdMap.get(r.dataId).id,l=n.makeOutput(r.shape,r.dtype),u=n.dataIdMap.get(l.dataId).id;return qE(o,s,i,u),l}var Nie={kernelName:bs,backendName:"wasm",setupFunc:Sie,kernelFunc:Tie};function KE(e){let{inputs:t,backend:n}=e,a=v.parseAxisParam(e.attrs.axis,t[0].shape)[0],r=t.map(h=>h.shape);N.assertParamsConsistent(r,a);let s=N.computeOutShape(t.map(h=>h.shape),a),i=t.filter(h=>v.sizeFromShape(h.shape)>0);if(i.length===1)return Qf({inputs:{x:i[0]},backend:n});let o=n.makeOutput(s,t[0].dtype);if(v.sizeFromShape(s)===0)return o;if(i[0].dtype==="string"){let h=i.map(x=>{let w=v.sizeFromShape(x.shape.slice(a));return Wn({inputs:{x},backend:n,attrs:{shape:[-1,w]}})}),m=h.map(x=>({vals:n.readSync(x.dataId),shape:x.shape}));s=N.computeOutShape(h.map(x=>x.shape),1);let f=h[0].shape[0]===1,g=O0(m,s,t[0].dtype,f),b=N.computeOutShape(i.map(x=>x.shape),a);o.shape=b;let y=n.dataIdMap.get(o.dataId);return y.stringBytes=N.fromStringArrayToUint8(g),h.forEach(x=>n.disposeData(x.dataId)),o}let l=v.sizeFromShape(i[0].shape.slice(0,a)),u=0,p=i.map(h=>{let m=v.sizeFromShape(h.shape.slice(a));return u+=m,m}),d=i.map(h=>n.typedArrayFromHeap(h)),c=n.typedArrayFromHeap(o);for(let h=0;h<l;h++){let m=h*u;for(let f=0;f<d.length;f++){let g=p[f],b=h*g,y=d[f].subarray(b,b+g);c.set(y,m),m+=g}}return o}var Cie={kernelName:Gl,backendName:"wasm",kernelFunc:KE},XE;function _ie(e){XE=e.wasm.cwrap(wi,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function Eie(e){let{inputs:t,attrs:n,backend:a}=e,{x:r,filter:s}=t,i=a.dataIdMap.get(r.dataId).id,o=a.dataIdMap.get(s.dataId).id,{strides:l,dilations:u,pad:p,dimRoundingMode:d,dataFormat:c}=n,h=N.convertConv2DDataFormat(c),m=N.computeConv2DInfo(r.shape,s.shape,l,u,p,d,!1,h),f=m.filterHeight,g=m.filterWidth,b=m.padInfo.top,y=m.padInfo.right,x=m.padInfo.bottom,w=m.padInfo.left,I=m.dilationHeight,T=m.dilationWidth,C=m.strideHeight,E=m.strideWidth,A=m.inChannels,R=m.outChannels,F=m.padInfo.type==="SAME"?1:0;if(m.dataFormat!=="channelsLast")throw new Error(`wasm backend Conv2D does not support dataFormat:'${m.dataFormat}'. 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Fie(e){let{backend:t,inputs:n,attrs:a}=e,{dy:r,filter:s}=n,{strides:i,pad:o,dataFormat:l,dimRoundingMode:u,inputShape:p}=a,d=1,c=N.convertConv2DDataFormat(l),h=N.computeConv2DInfo(p,s.shape,i,d,o,u,!1,c),{batchSize:m,filterHeight:f,filterWidth:g,inChannels:b,inHeight:y,inWidth:x,outChannels:w,outHeight:I,outWidth:T,strideHeight:C,strideWidth:E}=h,A=f-1-h.padInfo.top,R=g-1-h.padInfo.left,F=h.dataFormat==="channelsLast",S=v.computeStrides(h.inShape),M=v.computeStrides(r.shape),[B,U,G]=v.computeStrides(s.shape),q=S[0],K=F?S[1]:S[2],Z=F?S[2]:1,Q=F?1:S[1],ee=M[0],ae=F?M[1]:M[2],te=F?M[2]:1,le=F?1:M[1],ie=t.makeOutput(h.inShape,"float32"),be=t.dataIdMap.get(ie.dataId).id,ue=t.dataIdMap.get(r.dataId).id,xe=t.dataIdMap.get(s.dataId).id;return YE(ue,xe,m,f,g,y,x,b,I,T,w,C,E,A,R,B,U,G,q,K,Z,Q,ee,ae,te,le,be),ie}var Die={kernelName:ki,backendName:"wasm",setupFunc:$ie,kernelFunc:Fie},Rie=an(Ii),Mie=an(Si),wx;(function(e){e[e.bilinear=0]="bilinear",e[e.nearest=1]="nearest"})(wx||(wx={}));var ZE;function Pie(e){ZE=e.wasm.cwrap(jl,null,["number","number","number","number","array","number","number","number","number","number"])}function Oie(e){let{backend:t,inputs:n,attrs:a}=e,{method:r,extrapolationValue:s,cropSize:i}=a,{image:o,boxes:l,boxInd:u}=n,p=l.shape[0],[d,c]=i,h=[p,d,c,o.shape[3]],m=t.dataIdMap.get(o.dataId),f;o.dtype!=="float32"&&(f=ap({backend:t,inputs:{x:o},attrs:{dtype:"float32"}}),m=t.dataIdMap.get(f.dataId));let g=m.id,b=t.dataIdMap.get(l.dataId).id,y=t.dataIdMap.get(u.dataId).id,x=t.makeOutput(h,"float32"),w=t.dataIdMap.get(x.dataId).id,I=new Uint8Array(new Int32Array(o.shape).buffer);return ZE(g,b,y,p,I,d,c,wx[r],s,w),f!=null&&t.disposeData(f.dataId),x}var Lie={kernelName:jl,backendName:"wasm",setupFunc:Pie,kernelFunc:Oie},JE;function zie(e){JE=e.wasm.cwrap(Hl,null,["number","number","number","number","number","number"])}function Wie(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{axis:s,exclusive:i,reverse:o}=a,l=r.shape.length;v.assert(r.dtype==="float32"||r.dtype==="int32",()=>`cumprod does not support ${r.dtype} tensors in the WASM backend`);let u=N.getAxesPermutation([s],l),p=r;u!==null&&(p=hs({inputs:{x:r},attrs:{perm:u},backend:n}));let d=N.getInnerMostAxes(1,l)[0];N.assertAxesAreInnerMostDims("cumprod",[d],l);let c=n.makeOutput(p.shape,p.dtype),h=p.shape[d],m=n.dataIdMap.get(p.dataId).id,f=n.dataIdMap.get(c.dataId).id;JE(m,i?1:0,o?1:0,h,f,Et[r.dtype]);let g=c;if(u!==null){let b=N.getUndoAxesPermutation(u);g=hs({inputs:{x:c},attrs:{perm:b},backend:n}),n.disposeData(p.dataId),n.disposeData(c.dataId)}return g}var Bie={kernelName:Hl,backendName:"wasm",setupFunc:zie,kernelFunc:Wie},QE;function Vie(e){QE=e.wasm.cwrap(Ti,null,["number","number","number","number","number","number"])}function Uie(e){let{inputs:t,backend:n,attrs:a}=e,{x:r}=t,{axis:s,exclusive:i,reverse:o}=a,l=r.shape.length;v.assert(r.dtype==="float32"||r.dtype==="int32",()=>`cumsum does not support ${r.dtype} tensors in the WASM backend`);let u=N.getAxesPermutation([s],l),p=r;u!==null&&(p=hs({inputs:{x:r},attrs:{perm:u},backend:n}));let d=N.getInnerMostAxes(1,l)[0];N.assertAxesAreInnerMostDims("cumsum",[d],l);let c=n.makeOutput(p.shape,p.dtype),h=p.shape[d],m=n.dataIdMap.get(p.dataId).id,f=n.dataIdMap.get(c.dataId).id;QE(m,i?1:0,o?1:0,h,f,Et[r.dtype]);let g=c;if(u!==null){let b=N.getUndoAxesPermutation(u);g=hs({inputs:{x:c},attrs:{perm:b},backend:n}),n.disposeData(p.dataId),n.disposeData(c.dataId)}return g}var Gie={kernelName:Ti,backendName:"wasm",setupFunc:Vie,kernelFunc:Uie},eA;function Hie(e){eA=e.wasm.cwrap(ql,null,["number","number","number","array","number","array","array","number","number"])}function jie(e){let{backend:t,inputs:n,attrs:a}=e,{x:r}=n,{blockSize:s,dataFormat:i}=a,o=r.shape[0],l=i==="NHWC"?r.shape[1]:r.shape[2],u=i==="NHWC"?r.shape[2]:r.shape[3],p=i==="NHWC"?r.shape[3]:r.shape[1],d=l*s,c=u*s,h=p/(s*s),m=i==="NHWC"?[o,d,c,h]:[o,h,d,c],f=t.makeOutput(m,"float32"),g=t.dataIdMap.get(r.dataId).id,b=new Uint8Array(new Int32Array(v.computeStrides(r.shape)).buffer),y=new Uint8Array(new Int32Array(m).buffer),x=new Uint8Array(new Int32Array(v.computeStrides(m)).buffer),w=t.dataIdMap.get(f.dataId).id;return eA(g,s,i==="NHWC"?1:0,b,r.shape.length-1,y,x,m.length,w),f}var qie={kernelName:ql,backendName:"wasm",setupFunc:Hie,kernelFunc:jie},tA;function Kie(e){tA=e.wasm.cwrap(Ni,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function Xie(e){let{inputs:t,attrs:n,backend:a}=e,{x:r,filter:s}=t,i=a.dataIdMap.get(r.dataId).id,o=a.dataIdMap.get(s.dataId).id,{strides:l,dilations:u,pad:p,dimRoundingMode:d}=n,c=u==null?[1,1]:u,h=N.computeConv2DInfo(r.shape,s.shape,l,c,p,d,!0),m=h.filterHeight,f=h.filterWidth,g=h.padInfo.top,b=h.padInfo.right,y=h.padInfo.bottom,x=h.padInfo.left,w=h.dilationHeight,I=h.dilationWidth,T=h.strideHeight,C=h.strideWidth,E=h.inChannels,A=h.outChannels,R=h.padInfo.type==="SAME"?1:0;if(h.dataFormat!=="channelsLast")throw new Error(`wasm backend DepthwiseConv2dNative does not support dataFormat:'${h.dataFormat}'. Please use 'channelsLast'.`);let F=a.makeOutput(h.outShape,"float32"),S=a.dataIdMap.get(F.dataId).id;return tA(i,r.shape[0],r.shape[1],r.shape[2],o,m,f,g,b,y,x,R,w,I,T,C,E,A,S),F}var Yie={kernelName:Ni,backendName:"wasm",setupFunc:Kie,kernelFunc:Xie},Zie=an(_i),Jie=!1,Qie=dn(Xl,Jie,"bool"),eoe=an(Ei,"float32");function kx(e){let{inputs:t,attrs:n,backend:a}=e,{input:r}=t,{dim:s}=n,i=r.shape.length,o=r.shape.slice(),l=s;return s<0&&(v.assert(-(i+1)<=s,()=>`Axis must be in the interval [${-(i+1)}, ${i}]`),l=i+s+1),o.splice(l,0,1),Wn({inputs:{x:r},backend:a,attrs:{shape:o}})}var toe={kernelName:Yl,backendName:"wasm",kernelFunc:kx};function nA(e){let{attrs:{shape:t,value:n,dtype:a},backend:r}=e,s=r.makeOutput(t,a);return r.typedArrayFromHeap(s).fill(n),s}var noe={kernelName:gc,backendName:"wasm",kernelFunc:nA},aA;function aoe(e){aA=e.wasm.cwrap(Jl,null,["number","number","number","number","number","number"])}function roe(e){let{inputs:t,backend:n}=e,{image:a}=t,r=n.makeOutput(a.shape,a.dtype),s=n.dataIdMap.get(a.dataId).id,i=n.dataIdMap.get(r.dataId).id,[o,l,u,p]=a.shape;return aA(s,o,l,u,p,i),r}var soe={kernelName:Jl,backendName:"wasm",kernelFunc:roe,setupFunc:aoe},ioe=an(Ai),ooe=!1,loe=dn($i,ooe),rA;function uoe(e){rA=e.wasm.cwrap(Fi,null,["number","number","number","number","number","number","number"])}function poe(e){let{backend:t,inputs:n,attrs:a}=e,{varianceEpsilon:r}=a,{x:s,mean:i,variance:o,offset:l,scale:u}=n,p=t.dataIdMap.get(s.dataId).id,d=t.dataIdMap.get(i.dataId).id,c=t.dataIdMap.get(o.dataId).id,h=l!=null?t.dataIdMap.get(l.dataId).id:0,m=u!=null?t.dataIdMap.get(u.dataId).id:0,f=t.makeOutput(s.shape,s.dtype);if(v.sizeFromShape(s.shape)===0)return f;let g=t.dataIdMap.get(f.dataId).id;return rA(p,d,c,h,m,r,g),f}var coe={kernelName:Fi,backendName:"wasm",setupFunc:uoe,kernelFunc:poe},sA;function doe(e){sA=e.wasm.cwrap(ei,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function hoe(e){let{inputs:t,attrs:n,backend:a}=e,{x:r,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:u,dilations:p,dataFormat:d,dimRoundingMode:c,activation:h,leakyreluAlpha:m}=n,f=N.computeConv2DInfo(r.shape,s.shape,l,p,u,c),g=uc[h];if(g==null)throw new Error(`${h} activation not yet supported for FusedConv2D in the wasm backend.`);let b=a.dataIdMap.get(r.dataId).id,y=a.dataIdMap.get(s.dataId).id,x=f.outChannels,w=0;if(i!=null){let te=a.dataIdMap.get(i.dataId);if(te.shape.length!==1)throw new Error(`FusedConv2D only supports rank-1 bias but got rank ${te.shape.length}.`);if(te.shape[0]!==x)throw new Error(`FusedConv2D bias shape (${te.shape}) does not match the number of output channels (${x})`);w=te.id}let I=f.filterHeight,T=f.filterWidth,C=f.padInfo.top,E=f.padInfo.right,A=f.padInfo.bottom,R=f.padInfo.left,F=f.dilationHeight,S=f.dilationWidth,M=f.strideHeight,B=f.strideWidth,U=f.inChannels,G=f.padInfo.type==="SAME"?1:0,q=f.batchSize,K=f.inHeight,Z=f.inWidth;if(d!=="NHWC")throw new Error(`wasm backend FusedConv2D does not support dataFormat:'${d}'. Please use 'NHWC'.`);let Q=a.makeOutput(f.outShape,"float32"),ee=a.dataIdMap.get(Q.dataId).id,ae=o==null?0:a.dataIdMap.get(o.dataId).id;return sA(b,q,K,Z,y,I,T,w,C,E,A,R,G,F,S,M,B,U,x,g,ae,m||0,ee),Q}var moe={kernelName:ei,backendName:"wasm",setupFunc:doe,kernelFunc:hoe},iA;function foe(e){iA=e.wasm.cwrap(ti,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function goe(e){let{inputs:t,attrs:n,backend:a}=e,{x:r,filter:s,bias:i,preluActivationWeights:o}=t,{strides:l,pad:u,dilations:p,dataFormat:d,dimRoundingMode:c,activation:h,leakyreluAlpha:m}=n,f=N.computeConv2DInfo(r.shape,s.shape,l,p,u,c,!0),g=uc[h];if(g==null)throw new Error(`${h} activation not yet supported for FusedDepthwiseConv2D in the wasm backend.`);let b=a.dataIdMap.get(r.dataId).id,y=a.dataIdMap.get(s.dataId).id,x=f.outChannels,w=0;if(i!=null){let te=a.dataIdMap.get(i.dataId);if(te.shape.length!==1)throw new Error(`FusedDepthwiseConv2D only supports rank-1 bias but got rank ${te.shape.length}.`);if(te.shape[0]!==x)throw new Error(`FusedDepthwiseConv2D bias shape (${te.shape}) does not match the number of output channels (${x})`);w=te.id}let I=f.filterHeight,T=f.filterWidth,C=f.padInfo.top,E=f.padInfo.right,A=f.padInfo.bottom,R=f.padInfo.left,F=f.dilationHeight,S=f.dilationWidth,M=f.strideHeight,B=f.strideWidth,U=f.inChannels,G=f.padInfo.type==="SAME"?1:0,q=f.batchSize,K=f.inHeight,Z=f.inWidth;if(d!=="NHWC")throw new Error(`wasm backend FusedDepthwiseConv2D does not support dataFormat:'${d}'. Please use 'NHWC'.`);let Q=a.makeOutput(f.outShape,"float32"),ee=a.dataIdMap.get(Q.dataId).id,ae=o==null?0:a.dataIdMap.get(o.dataId).id;return iA(b,q,K,Z,y,I,T,w,C,E,A,R,G,F,S,M,B,U,x,g,ae,m||0,ee),Q}var boe={kernelName:ti,backendName:"wasm",setupFunc:foe,kernelFunc:goe},oA;function yoe(e){oA=e.wasm.cwrap(eu,null,["number","number","number","number","number","number","array","number"])}function xoe(e){let{backend:t,inputs:n}=e,{params:a,indices:r}=n,[s,i,o,l]=Ux.prepareAndValidate(a,r),u=t.makeOutput(s,a.dtype);if(i===0)return u;let p=r.shape,d=p[p.length-1],c=t.dataIdMap.get(a.dataId).id,h=t.dataIdMap.get(r.dataId).id,m=new Uint8Array(new Int32Array(l).buffer),f=t.dataIdMap.get(u.dataId).id;return oA(c,Et[a.dtype],h,i,d,o,m,f),u}var voe={kernelName:eu,backendName:"wasm",setupFunc:yoe,kernelFunc:xoe},lA;function woe(e){lA=e.wasm.cwrap("Gather",null,["number","number","array","number","number","number","array","number"])}function koe(e){let{backend:t,inputs:n,attrs:a}=e,{x:r,indices:s}=n,{axis:i,batchDims:o}=a,l=v.parseAxisParam(i,r.shape)[0],u=t.readSync(s.dataId),p=r.shape[l];for(let C=0;C<u.length;++C){let E=u[C];v.assert(E<=p-1&&E>=0,()=>`GatherV2: the index value ${E} is not in [0, ${p-1}]`)}let d=N.segment_util.collectGatherOpShapeInfo(r,s,l,o),c=Wn({inputs:{x:r},attrs:{shape:[d.batchSize,d.outerSize,d.dimSize,d.sliceSize]},backend:t}),h=v.sizeFromShape(s.shape),m=Wn({inputs:{x:s},attrs:{shape:[d.batchSize,h/d.batchSize]},backend:t}),f=[d.batchSize,d.outerSize,h/d.batchSize,d.sliceSize],g=t.makeOutput(f,r.dtype);if(v.sizeFromShape(r.shape)===0)return g;let b=c.shape.length-1,y=t.dataIdMap.get(c.dataId).id,x=t.dataIdMap.get(m.dataId).id,w=t.dataIdMap.get(g.dataId).id,I=new Uint8Array(new Int32Array(v.computeStrides(c.shape)).buffer),T=new Uint8Array(new Int32Array(v.computeStrides(f)).buffer);return lA(y,Et[r.dtype],I,b,x,d.batchSize,T,w),t.disposeData(c.dataId),t.disposeData(m.dataId),g.shape=d.outputShape,g}var Ioe={kernelName:Ql,backendName:"wasm",setupFunc:woe,kernelFunc:koe},Soe=!1,Toe=dn(tu,Soe,"bool"),Noe=!1,Coe=dn(Di,Noe,"bool"),uA;function _oe(e){uA=e.wasm.cwrap(Mi,null,["number","number","number","number"])}function Eoe(e){let{inputs:{x:t},attrs:{alpha:n},backend:a}=e,r=a.dataIdMap.get(t.dataId).id,s=a.makeOutput(t.shape,"float32");if(v.sizeFromShape(t.shape)!==0){let i=a.dataIdMap.get(s.dataId).id;uA(r,Et[t.dtype],n,i)}return s}var Aoe={kernelName:Mi,backendName:"wasm",setupFunc:_oe,kernelFunc:Eoe},$oe=!1,Foe=dn(su,$oe,"bool"),Doe=!1,Roe=dn(iu,Doe,"bool"),Moe=an(Pi),Poe=!1,Ooe=dn(lu,Poe,"bool"),Loe=an(uu),zoe=!1,Woe=dn(pu,zoe,"bool"),Boe=!1,Voe=dn(tS,Boe,"bool"),pA;function Uoe(e){pA=e.wasm.cwrap(Oi,null,["number","number","number","number"])}function Goe(e){let{backend:t,inputs:n,attrs:a}=e,{reductionIndices:r,keepDims:s}=a,{x:i}=n,o=t.dataIdMap.get(i.dataId).id,l=i,{transposed:u,axes:p,originalAxes:d,inputWasTransposed:c}=Es(i,r,t);if(c){let y=t.dataIdMap.get(u.dataId).id;l=u,o=y}let h=l.shape.length;N.assertAxesAreInnerMostDims("max",p,h);let[m,f]=N.computeOutAndReduceShapes(l.shape,p),g=v.sizeFromShape(f),b=t.makeOutput(m,i.dtype);if(v.sizeFromShape(l.shape)!==0){let y=t.dataIdMap.get(b.dataId).id;pA(o,Et[i.dtype],g,y)}if(c&&t.disposeData(u.dataId),s){let y=N.expandShapeToKeepDim(b.shape,d);b.shape=y}return b}var Hoe={kernelName:Oi,backendName:"wasm",setupFunc:Uoe,kernelFunc:Goe},joe=!1,qoe=dn(Li,joe),cA;function Koe(e){cA=e.wasm.cwrap(zi,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function Xoe(e){let{inputs:t,attrs:n,backend:a}=e,r=t.x,s=a.dataIdMap.get(r.dataId).id;v.assert(r.dtype==="float32",()=>`Error in MaxPool: only float32 input is supported. Got ${r.dtype}.`);let{filterSize:i,strides:o,pad:l,dimRoundingMode:u}=n,p=N.computePool2DInfo(r.shape,i,o,1,l,u),d=p.filterHeight,c=p.filterWidth,h=p.padInfo.top,m=p.padInfo.right,f=p.padInfo.bottom,g=p.padInfo.left,b=p.dilationHeight,y=p.dilationWidth,x=p.strideHeight,w=p.strideWidth,I=p.inChannels,T=p.outChannels;if(p.dataFormat!=="channelsLast")throw new Error(`wasm backend does not support dataFormat:'${p.dataFormat}'. 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w=N.expandShapeToKeepDim(x.shape,c);x.shape=w}return u.dtype!=="float32"&&t.disposeData(y.dataId),x}var Qoe={kernelName:Wi,backendName:"wasm",setupFunc:Zoe,kernelFunc:Joe},hA;function ele(e){hA=e.wasm.cwrap(Bi,null,["number","number","number","number"])}function tle(e){let{backend:t,inputs:n,attrs:a}=e,{axis:r,keepDims:s}=a,{x:i}=n,o=t.dataIdMap.get(i.dataId).id,l=o,u=i,{transposed:p,axes:d,originalAxes:c,inputWasTransposed:h}=Es(i,r,t);if(h){let x=t.dataIdMap.get(p.dataId).id;x!==o&&(u=p,l=x)}let m=u.shape.length;N.assertAxesAreInnerMostDims("min",d,m);let[f,g]=N.computeOutAndReduceShapes(u.shape,d),b=v.sizeFromShape(g),y=t.makeOutput(f,u.dtype);if(v.sizeFromShape(u.shape)!==0){let x=t.dataIdMap.get(y.dataId).id;hA(l,Et[i.dtype],b,x)}if(h&&t.disposeData(p.dataId),s){let x=N.expandShapeToKeepDim(y.shape,c);y.shape=x}return y}var nle={kernelName:Bi,backendName:"wasm",setupFunc:ele,kernelFunc:tle},ale=!1,rle=dn(Vi,ale),Ix;(function(e){e[e.reflect=0]="reflect",e[e.symmetric=1]="symmetric"})(Ix||(Ix={}));var mA;function sle(e){mA=e.wasm.cwrap(Ui,null,["number","array","number","number","array","array","number","number"])}function ile(e){let{inputs:{x:t},backend:n,attrs:{paddings:a,mode:r}}=e,s=a.map((m,f)=>m[0]+t.shape[f]+m[1]),i=n.dataIdMap.get(t.dataId).id,o=n.makeOutput(s,t.dtype),l=n.dataIdMap.get(o.dataId).id,u=new Uint8Array(new Int32Array(t.shape).buffer),p=a.map(m=>m[0]),d=a.map(m=>m[1]),c=new Uint8Array(new Int32Array(p).buffer),h=new Uint8Array(new Int32Array(d).buffer);return mA(i,u,t.shape.length,Et[t.dtype],c,h,Ix[r],l),o}var ole={kernelName:Ui,backendName:"wasm",kernelFunc:ile,setupFunc:sle},lle=!0,ule=dn(Gi,lle),ple=an(du);function u1(e,t){let n=new Int32Array(e.wasm.HEAPU8.buffer,t,4),a=n[0],r=n[1],s=n[2],i=n[3];return e.wasm._free(t),{pSelectedIndices:a,selectedSize:r,pSelectedScores:s,pValidOutputs:i}}var fA;function cle(e){fA=e.wasm.cwrap(mu,"number",["number","number","number","number","number"])}function dle(e){let{backend:t,inputs:n,attrs:a}=e,{iouThreshold:r,maxOutputSize:s,scoreThreshold:i}=a,{boxes:o,scores:l}=n,u=t.dataIdMap.get(o.dataId).id,p=t.dataIdMap.get(l.dataId).id,d=fA(u,p,s,r,i),{pSelectedIndices:c,selectedSize:h,pSelectedScores:m,pValidOutputs:f}=u1(t,d);return t.wasm._free(m),t.wasm._free(f),t.makeOutput([h],"int32",c)}var hle={kernelName:mu,backendName:"wasm",setupFunc:cle,kernelFunc:dle},gA;function mle(e){gA=e.wasm.cwrap(fu,"number",["number","number","number","number","number","bool"])}function fle(e){let{backend:t,inputs:n,attrs:a}=e,{iouThreshold:r,maxOutputSize:s,scoreThreshold:i,padToMaxOutputSize:o}=a,{boxes:l,scores:u}=n,p=t.dataIdMap.get(l.dataId).id,d=t.dataIdMap.get(u.dataId).id,c=gA(p,d,s,r,i,o),{pSelectedIndices:h,selectedSize:m,pSelectedScores:f,pValidOutputs:g}=u1(t,c);t.wasm._free(f);let b=t.makeOutput([m],"int32",h),y=t.makeOutput([],"int32",g);return[b,y]}var gle={kernelName:fu,backendName:"wasm",setupFunc:mle,kernelFunc:fle},bA;function ble(e){bA=e.wasm.cwrap(gu,"number",["number","number","number","number","number","number"])}function yle(e){let{backend:t,inputs:n,attrs:a}=e,{iouThreshold:r,maxOutputSize:s,scoreThreshold:i,softNmsSigma:o}=a,{boxes:l,scores:u}=n,p=t.dataIdMap.get(l.dataId).id,d=t.dataIdMap.get(u.dataId).id,c=bA(p,d,s,r,i,o),{pSelectedIndices:h,selectedSize:m,pSelectedScores:f,pValidOutputs:g}=u1(t,c);t.wasm._free(g);let b=t.makeOutput([m],"int32",h),y=t.makeOutput([m],"float32",f);return[b,y]}var xle={kernelName:gu,backendName:"wasm",setupFunc:ble,kernelFunc:yle},vle=!1,wle=dn(hu,vle,"bool"),yA;function kle(e){yA=e.wasm.cwrap(Hi,null,["number","number","number","number","number"])}function Ile(e){let{inputs:t,backend:n,attrs:a}=e,{indices:r}=t,{dtype:s,depth:i,onValue:o,offValue:l}=a,u=n.makeOutput([...r.shape,i],s),p=n.dataIdMap.get(u.dataId).id,d=n.dataIdMap.get(r.dataId).id;return yA(d,i,o,l,p),u}var Sle={kernelName:Hi,backendName:"wasm",setupFunc:kle,kernelFunc:Ile};function Tle(e){let{inputs:{x:t},backend:n}=e,a=n.makeOutput(t.shape,t.dtype);return n.typedArrayFromHeap(a).fill(1),a}var Nle={kernelName:bu,backendName:"wasm",kernelFunc:Tle};function Cle(e){let{inputs:t,backend:n,attrs:a}=e,{axis:r}=a;if(t.length===1)return kx({inputs:{input:t[0]},backend:n,attrs:{dim:r}});let s=t[0].shape,i=t[0].dtype;t.forEach(p=>{v.assertShapesMatch(s,p.shape,"All tensors passed to stack must have matching shapes"),v.assert(i===p.dtype,()=>"All tensors passed to stack must have matching 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Dle(e){wA=e.wasm.cwrap(Ki,null,["number","number","number"])}function Rle(e){let{inputs:t,backend:n}=e,{x:a,alpha:r}=t,s=n.dataIdMap.get(a.dataId).id,i=n.dataIdMap.get(r.dataId).id,o=s,l=a,u=l;l.dtype!=="float32"&&(u=ap({backend:n,inputs:{x:a},attrs:{dtype:"float32"}}),o=n.dataIdMap.get(u.dataId).id);let p=n.makeOutput(a.shape,"float32"),d=n.dataIdMap.get(p.dataId).id;return wA(o,i,d),l.dtype!=="float32"&&n.disposeData(u.dataId),p}var Mle={kernelName:Ki,backendName:"wasm",setupFunc:Dle,kernelFunc:Rle},kA;function Ple(e){kA=e.wasm.cwrap(Xi,null,["number","number","number","number"])}function Ole(e){let{backend:t,inputs:n,attrs:a}=e,{axis:r,keepDims:s}=a,{x:i}=n,o=t.dataIdMap.get(i.dataId).id,l=o,u=i,{transposed:p,axes:d,originalAxes:c,inputWasTransposed:h}=Es(i,r,t),m=d;if(h){let 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yr=class{constructor(t,n=!1){this._imageTensors=[];this._canvases=[];this._treatAsBatchInput=!1;this._inputDimensions=[];this._inputSize=0;if(!Array.isArray(t))throw new Error(`NetInput.constructor - expected inputs to be an Array of TResolvedNetInput or to be instanceof tf.Tensor4D, instead have ${t}`);this._treatAsBatchInput=n,this._batchSize=t.length,t.forEach((a,r)=>{if(Or(a)){this._imageTensors[r]=a,this._inputDimensions[r]=a.shape;return}if(va(a)){let i=a.shape[0];if(i!==1)throw new Error(`NetInput - tf.Tensor4D with batchSize ${i} passed, but not supported in input array`);this._imageTensors[r]=a,this._inputDimensions[r]=a.shape.slice(1);return}let s=a instanceof Je.getEnv().Canvas?a:gd(a);this._canvases[r]=s,this._inputDimensions[r]=[s.height,s.width,3]})}get imageTensors(){return this._imageTensors}get canvases(){return this._canvases}get isBatchInput(){return this.batchSize>1||this._treatAsBatchInput}get batchSize(){return this._batchSize}get inputDimensions(){return 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n=`${t}-weights_manifest.json`;if(!e)return{modelBaseUri:"",manifestUri:n};if(e==="/")return{modelBaseUri:"/",manifestUri:`/${n}`};let a=e.startsWith("http://")?"http://":e.startsWith("https://")?"https://":"";e=e.replace(a,"");let r=e.split("/").filter(o=>o),s=e.endsWith(".json")?r[r.length-1]:n,i=a+(e.endsWith(".json")?r.slice(0,r.length-1):r).join("/");return i=e.startsWith("/")?`/${i}`:i,{modelBaseUri:i,manifestUri:i==="/"?`/${s}`:`${i}/${s}`}}async function F1(e,t){let{manifestUri:n,modelBaseUri:a}=sg(e,t),r=await $1(n);return Ut.loadWeights(r,a)}function Kpe(e,t,n=!1){let{width:a,height:r}=n?Fo(t):t;return e.width=a,e.height=r,{width:a,height:r}}var sn=class{constructor(t){this._params=void 0;this._paramMappings=[];this._name=t}get params(){return this._params}get paramMappings(){return this._paramMappings}get isLoaded(){return!!this.params}getParamFromPath(t){let{obj:n,objProp:a}=this.traversePropertyPath(t);return 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sn{constructor(n,a){super(n);this._faceFeatureExtractor=a}get faceFeatureExtractor(){return this._faceFeatureExtractor}runNet(n){let{params:a}=this;if(!a)throw new Error(`${this._name} - load model before inference`);return P(()=>{let r=n instanceof yr?this.faceFeatureExtractor.forwardInput(n):n;return xd(r.as2D(r.shape[0],-1),a.fc)})}dispose(n=!0){this.faceFeatureExtractor.dispose(n),super.dispose(n)}loadClassifierParams(n){let{params:a,paramMappings:r}=this.extractClassifierParams(n);this._params=a,this._paramMappings=r}extractClassifierParams(n){return qA(n,this.getClassifierChannelsIn(),this.getClassifierChannelsOut())}extractParamsFromWeightMap(n){let{featureExtractorMap:a,classifierMap:r}=cg(n);return this.faceFeatureExtractor.loadFromWeightMap(a),KA(r)}extractParams(n){let a=this.getClassifierChannelsIn(),r=this.getClassifierChannelsOut(),s=r*a+r,i=n.slice(0,n.length-s),o=n.slice(n.length-s);return this.faceFeatureExtractor.extractWeights(i),this.extractClassifierParams(o)}};var D1=["neutral","happy","sad","angry","fearful","disgusted","surprised"],Br=class{constructor(t){this.neutral=0;this.happy=0;this.sad=0;this.angry=0;this.fearful=0;this.disgusted=0;this.surprised=0;if(t.length!==7)throw new Error(`FaceExpressions.constructor - expected probabilities.length to be 7, have: ${t.length}`);D1.forEach((n,a)=>{this[n]=t[a]})}asSortedArray(){return D1.map(t=>({expression:t,probability:this[t]})).sort((t,n)=>n.probability-t.probability)}};var vd=class extends mp{constructor(t=new hp){super("FaceExpressionNet",t)}forwardInput(t){return P(()=>Ka(this.runNet(t)))}async forward(t){return this.forwardInput(await yt(t))}async predictExpressions(t){let n=await yt(t),a=await this.forwardInput(n),r=await Promise.all(ct(a).map(async i=>{let o=i.dataSync();return i.dispose(),o}));a.dispose();let s=r.map(i=>new Br(i));return n.isBatchInput?s:s[0]}getDefaultModelName(){return"face_expression_model"}getClassifierChannelsIn(){return 256}getClassifierChannelsOut(){return 7}};function R1(e){return e.expressions instanceof Br}function dg(e,t){return{...e,...{expressions:t}}}function Xpe(e,t,n=.1,a){(Array.isArray(t)?t:[t]).forEach(s=>{let i=s instanceof Br?s:R1(s)?s.expressions:void 0;if(!i)throw new Error("drawFaceExpressions - expected faceExpressions to be FaceExpressions | WithFaceExpressions<{}> or array thereof");let l=i.asSortedArray().filter(d=>d.probability>n),u=br(s)?s.detection.box.bottomLeft:a||new De(0,0);new zr(l.map(d=>`${d.expression} (${To(d.probability)})`),u).draw(e)})}function Mo(e){return br(e)&&e.landmarks instanceof ra&&e.unshiftedLandmarks instanceof ra&&e.alignedRect instanceof bt}function Ype(e){let t=(o,l,u,p)=>Math.atan2(p-l,u-o)%Math.PI,n=o=>o*180/Math.PI,a={roll:void 0,pitch:void 0,yaw:void 0};if(!e||!e._positions||e._positions.length!==68)return a;let r=e._positions;a.roll=-t(r[36]._x,r[36]._y,r[45]._x,r[45]._y),a.pitch=t(0,Math.abs(r[0]._x-r[30]._x)/r[30]._x,Math.PI,Math.abs(r[16]._x-r[30]._x)/r[30]._x);let 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Eo&&(n.strokeStyle=i,n.lineWidth=s,Pr(n,this.faceLandmarks.getJawOutline()),Pr(n,this.faceLandmarks.getLeftEyeBrow()),Pr(n,this.faceLandmarks.getRightEyeBrow()),Pr(n,this.faceLandmarks.getNose()),Pr(n,this.faceLandmarks.getLeftEye(),!0),Pr(n,this.faceLandmarks.getRightEye(),!0),Pr(n,this.faceLandmarks.getMouth(),!0)),r){n.strokeStyle=l,n.fillStyle=l;let u=p=>{n.beginPath(),n.arc(p.x,p.y,o,0,2*Math.PI),n.fill()};this.faceLandmarks.positions.forEach(u)}}};function Zpe(e,t){(Array.isArray(t)?t:[t]).forEach(a=>{let r=a instanceof ra?a:Mo(a)?a.landmarks:void 0;if(!r)throw new Error("drawFaceLandmarks - expected faceExpressions to be FaceLandmarks | WithFaceLandmarks<WithFaceDetection<{}>> or array thereof");new mg(r).draw(e)})}var XA="1.7.5";function ece(e,t){let n=pp(e,t),a=cp(e,t);function r(i,o,l){let u=a(i,o,`${l}/separable_conv0`),p=a(o,o,`${l}/separable_conv1`),d=n(i,o,1,`${l}/expansion_conv`);return{separable_conv0:u,separable_conv1:p,expansion_conv:d}}function s(i,o){let l=a(i,i,`${o}/separable_conv0`),u=a(i,i,`${o}/separable_conv1`),p=a(i,i,`${o}/separable_conv2`);return{separable_conv0:l,separable_conv1:u,separable_conv2:p}}return{extractConvParams:n,extractSeparableConvParams:a,extractReductionBlockParams:r,extractMainBlockParams:s}}function YA(e,t){let n=[],{extractWeights:a,getRemainingWeights:r}=$n(e),{extractConvParams:s,extractSeparableConvParams:i,extractReductionBlockParams:o,extractMainBlockParams:l}=ece(a,n),u=s(3,32,3,"entry_flow/conv_in"),p=o(32,64,"entry_flow/reduction_block_0"),d=o(64,128,"entry_flow/reduction_block_1"),c={conv_in:u,reduction_block_0:p,reduction_block_1:d},h={};fr(t,0,1).forEach(b=>{h[`main_block_${b}`]=l(128,`middle_flow/main_block_${b}`)});let m=o(128,256,"exit_flow/reduction_block"),f=i(256,512,"exit_flow/separable_conv"),g={reduction_block:m,separable_conv:f};if(r().length!==0)throw new Error(`weights remaing after extract: ${r().length}`);return{paramMappings:n,params:{entry_flow:c,middle_flow:h,exit_flow:g}}}function tce(e,t){let n=sa(e,t),a=ug(n),r=dp(n);function s(o){let l=r(`${o}/separable_conv0`),u=r(`${o}/separable_conv1`),p=a(`${o}/expansion_conv`);return{separable_conv0:l,separable_conv1:u,expansion_conv:p}}function i(o){let l=r(`${o}/separable_conv0`),u=r(`${o}/separable_conv1`),p=r(`${o}/separable_conv2`);return{separable_conv0:l,separable_conv1:u,separable_conv2:p}}return{extractConvParams:a,extractSeparableConvParams:r,extractReductionBlockParams:s,extractMainBlockParams:i}}function ZA(e,t){let n=[],{extractConvParams:a,extractSeparableConvParams:r,extractReductionBlockParams:s,extractMainBlockParams:i}=tce(e,n),o=a("entry_flow/conv_in"),l=s("entry_flow/reduction_block_0"),u=s("entry_flow/reduction_block_1"),p={conv_in:o,reduction_block_0:l,reduction_block_1:u},d={};fr(t,0,1).forEach(f=>{d[`main_block_${f}`]=i(`middle_flow/main_block_${f}`)});let c=s("exit_flow/reduction_block"),h=r("exit_flow/separable_conv"),m={reduction_block:c,separable_conv:h};return An(e,n),{params:{entry_flow:p,middle_flow:d,exit_flow:m},paramMappings:n}}function JA(e,t,n){return Y($t(e,t.filters,n,"same"),t.bias)}function P1(e,t,n=!0){let a=n?Xe(e):e;return a=Hn(a,t.separable_conv0,[1,1]),a=Hn(Xe(a),t.separable_conv1,[1,1]),a=Dt(a,[3,3],[2,2],"same"),a=Y(a,JA(e,t.expansion_conv,[2,2])),a}function nce(e,t){let n=Hn(Xe(e),t.separable_conv0,[1,1]);return n=Hn(Xe(n),t.separable_conv1,[1,1]),n=Hn(Xe(n),t.separable_conv2,[1,1]),n=Y(n,e),n}var fg=class extends sn{constructor(n){super("TinyXception");this._numMainBlocks=n}forwardInput(n){let{params:a}=this;if(!a)throw new Error("TinyXception - load model before inference");return P(()=>{let r=oe(n.toBatchTensor(112,!0),"float32"),i=Za(r,[122.782,117.001,104.298]).div(255),o=Xe(JA(i,a.entry_flow.conv_in,[2,2]));return o=P1(o,a.entry_flow.reduction_block_0,!1),o=P1(o,a.entry_flow.reduction_block_1),fr(this._numMainBlocks,0,1).forEach(l=>{o=nce(o,a.middle_flow[`main_block_${l}`])}),o=P1(o,a.exit_flow.reduction_block),o=Xe(Hn(o,a.exit_flow.separable_conv,[1,1])),o})}async forward(n){return this.forwardInput(await yt(n))}getDefaultModelName(){return"tiny_xception_model"}extractParamsFromWeightMap(n){return ZA(n,this._numMainBlocks)}extractParams(n){return YA(n,this._numMainBlocks)}};function QA(e){let t=[],{extractWeights:n,getRemainingWeights:a}=$n(e),r=og(n,t),s=r(512,1,"fc/age"),i=r(512,2,"fc/gender");if(a().length!==0)throw new Error(`weights remaing after extract: ${a().length}`);return{paramMappings:t,params:{fc:{age:s,gender:i}}}}function e$(e){let t=[],n=sa(e,t);function a(s){let i=n(`${s}/weights`,2),o=n(`${s}/bias`,1);return{weights:i,bias:o}}let r={fc:{age:a("fc/age"),gender:a("fc/gender")}};return An(e,t),{params:r,paramMappings:t}}var gg=(n=>(n.FEMALE="female",n.MALE="male",n))(gg||{});var wd=class extends sn{constructor(n=new fg(2)){super("AgeGenderNet");this._faceFeatureExtractor=n}get faceFeatureExtractor(){return this._faceFeatureExtractor}runNet(n){let{params:a}=this;if(!a)throw new Error(`${this._name} - load model before inference`);return P(()=>{let r=n instanceof yr?this.faceFeatureExtractor.forwardInput(n):n,s=ba(r,[7,7],[2,2],"valid").as2D(r.shape[0],-1),i=xd(s,a.fc.age).as1D(),o=xd(s,a.fc.gender);return{age:i,gender:o}})}forwardInput(n){return P(()=>{let{age:a,gender:r}=this.runNet(n);return{age:a,gender:Ka(r)}})}async forward(n){return this.forwardInput(await yt(n))}async predictAgeAndGender(n){let a=await yt(n),r=await this.forwardInput(a),s=ct(r.age),i=ct(r.gender),o=s.map((u,p)=>({ageTensor:u,genderTensor:i[p]})),l=await Promise.all(o.map(async({ageTensor:u,genderTensor:p})=>{let d=u.dataSync()[0],c=p.dataSync()[0],h=c>.5,m=h?"male":"female",f=h?c:1-c;return u.dispose(),p.dispose(),{age:d,gender:m,genderProbability:f}}));return 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l=n(`${o}/sub`,1),u=n(`${o}/truediv`,1);return{sub:l,truediv:u}}function r(o){let l=n(`${o}/filters`,4),u=n(`${o}/bias`,1);return{filters:l,bias:u}}function s(o){let l=r(`${o}/conv`),u=a(`${o}/bn`);return{conv:l,bn:u}}let i=dp(n);return{extractConvParams:r,extractConvWithBatchNormParams:s,extractSeparableConvParams:i}}function w$(e,t){let n=[],{extractConvParams:a,extractConvWithBatchNormParams:r,extractSeparableConvParams:s}=yce(e,n),i;if(t.withSeparableConvs){let o=t.filterSizes&&t.filterSizes.length||9;i={conv0:t.isFirstLayerConv2d?a("conv0"):s("conv0"),conv1:s("conv1"),conv2:s("conv2"),conv3:s("conv3"),conv4:s("conv4"),conv5:s("conv5"),conv6:o>7?s("conv6"):void 0,conv7:o>8?s("conv7"):void 0,conv8:a("conv8")}}else i={conv0:r("conv0"),conv1:r("conv1"),conv2:r("conv2"),conv3:r("conv3"),conv4:r("conv4"),conv5:r("conv5"),conv6:r("conv6"),conv7:r("conv7"),conv8:a("conv8")};return An(e,n),{params:i,paramMappings:n}}var Qa=class{constructor({inputSize:t,scoreThreshold:n}={}){this._name="TinyYolov2Options";if(this._inputSize=t||416,this._scoreThreshold=n||.5,typeof this._inputSize!="number"||this._inputSize%32!==0)throw new Error(`${this._name} - expected inputSize to be a number divisible by 32`);if(typeof this._scoreThreshold!="number"||this._scoreThreshold<=0||this._scoreThreshold>=1)throw new Error(`${this._name} - expected scoreThreshold to be a number between 0 and 1`)}get inputSize(){return this._inputSize}get scoreThreshold(){return this._scoreThreshold}};var V1=class extends sn{constructor(n){super("TinyYolov2");B1(n),this._config=n}get config(){return this._config}get withClassScores(){return this.config.withClassScores||this.config.classes.length>1}get boxEncodingSize(){return 5+(this.withClassScores?this.config.classes.length:0)}runTinyYolov2(n,a){let r=Vr(n,a.conv0);return r=Dt(r,[2,2],[2,2],"same"),r=Vr(r,a.conv1),r=Dt(r,[2,2],[2,2],"same"),r=Vr(r,a.conv2),r=Dt(r,[2,2],[2,2],"same"),r=Vr(r,a.conv3),r=Dt(r,[2,2],[2,2],"same"),r=Vr(r,a.conv4),r=Dt(r,[2,2],[2,2],"same"),r=Vr(r,a.conv5),r=Dt(r,[2,2],[1,1],"same"),r=Vr(r,a.conv6),r=Vr(r,a.conv7),Ro(r,a.conv8,"valid",!1)}runMobilenet(n,a){let r=this.config.isFirstLayerConv2d?bp(Ro(n,a.conv0,"valid",!1)):Ur(n,a.conv0);return r=Dt(r,[2,2],[2,2],"same"),r=Ur(r,a.conv1),r=Dt(r,[2,2],[2,2],"same"),r=Ur(r,a.conv2),r=Dt(r,[2,2],[2,2],"same"),r=Ur(r,a.conv3),r=Dt(r,[2,2],[2,2],"same"),r=Ur(r,a.conv4),r=Dt(r,[2,2],[2,2],"same"),r=Ur(r,a.conv5),r=Dt(r,[2,2],[1,1],"same"),r=a.conv6?Ur(r,a.conv6):r,r=a.conv7?Ur(r,a.conv7):r,Ro(r,a.conv8,"valid",!1)}forwardInput(n,a){let{params:r}=this;if(!r)throw new Error("TinyYolov2 - load model before inference");return P(()=>{let s=oe(n.toBatchTensor(a,!1),"float32");return s=this.config.meanRgb?Za(s,this.config.meanRgb):s,s=s.div(255),this.config.withSeparableConvs?this.runMobilenet(s,r):this.runTinyYolov2(s,r)})}async forward(n,a){return this.forwardInput(await yt(n),a)}async detect(n,a={}){let{inputSize:r,scoreThreshold:s}=new Qa(a),i=await yt(n),o=await this.forwardInput(i,r),l=P(()=>ct(o)[0].expandDims()),u={width:i.getInputWidth(0),height:i.getInputHeight(0)},p=await this.extractBoxes(l,i.getReshapedInputDimensions(0),s);o.dispose(),l.dispose();let d=p.map(b=>b.box),c=p.map(b=>b.score),h=p.map(b=>b.classScore),m=p.map(b=>this.config.classes[b.label]);return b1(d.map(b=>b.rescale(r)),c,this.config.iouThreshold,!0).map(b=>new Lr(c[b],h[b],m[b],d[b],u))}getDefaultModelName(){return""}extractParamsFromWeightMap(n){return w$(n,this.config)}extractParams(n){let a=this.config.filterSizes||V1.DEFAULT_FILTER_SIZES,r=a?a.length:void 0;if(r!==7&&r!==8&&r!==9)throw new Error(`TinyYolov2 - expected 7 | 8 | 9 convolutional filters, but found ${r} filterSizes in config`);return v$(n,this.config,this.boxEncodingSize,a)}async extractBoxes(n,a,r){let{width:s,height:i}=a,o=Math.max(s,i),l=o/s,u=o/i,p=n.shape[1],d=this.config.anchors.length,[c,h,m]=P(()=>{let y=n.reshape([p,p,d,this.boxEncodingSize]),x=y.slice([0,0,0,0],[p,p,d,4]),w=y.slice([0,0,0,4],[p,p,d,1]),I=this.withClassScores?Ka(y.slice([0,0,0,5],[p,p,d,this.config.classes.length]),3):ye(0);return[x,w,I]}),f=[],g=await h.array(),b=await c.array();for(let y=0;y<p;y++)for(let x=0;x<p;x++)for(let w=0;w<d;w++){let I=dd(g[y][x][w][0]);if(!r||I>r){let T=(x+dd(b[y][x][w][0]))/p*l,C=(y+dd(b[y][x][w][1]))/p*u,E=Math.exp(b[y][x][w][2])*this.config.anchors[w].x/p*l,A=Math.exp(b[y][x][w][3])*this.config.anchors[w].y/p*u,R=T-E/2,F=C-A/2,S={row:y,col:x,anchor:w},{classScore:M,label:B}=this.withClassScores?await this.extractPredictedClass(m,S):{classScore:1,label:0};f.push({box:new Co(R,F,R+E,F+A),score:I,classScore:I*M,label:B,...S})}}return c.dispose(),h.dispose(),m.dispose(),f}async extractPredictedClass(n,a){let{row:r,col:s,anchor:i}=a,o=await n.array();return Array(this.config.classes.length).fill(0).map((l,u)=>o[r][s][i][u]).map((l,u)=>({classScore:l,label:u})).reduce((l,u)=>l.classScore>u.classScore?l:u)}},zo=V1;zo.DEFAULT_FILTER_SIZES=[3,16,32,64,128,256,512,1024,1024];var Wo=class extends zo{constructor(t=!0){let n={withSeparableConvs:t,iouThreshold:m$,classes:["face"],...t?{anchors:g$,meanRgb:b$}:{anchors:f$,withClassScores:!0}};super(n)}get withSeparableConvs(){return this.config.withSeparableConvs}get anchors(){return this.config.anchors}async locateFaces(t,n){return(await this.detect(t,n)).map(r=>new bt(r.score,r.relativeBox,{width:r.imageWidth,height:r.imageHeight}))}getDefaultModelName(){return this.withSeparableConvs?x$:y$}extractParamsFromWeightMap(t){return super.extractParamsFromWeightMap(t)}};function xce(e,t=!0){let n=new Wo(t);return n.extractWeights(e),n}var Sd=class extends Qa{constructor(){super(...arguments);this._name="TinyFaceDetectorOptions"}};var ka=class{async then(t){return t(await this.run())}async run(){throw new Error("ComposableTask - run is not implemented")}};async function Bo(e,t,n,a,r=({alignedRect:s})=>s){let s=e.map(l=>Mo(l)?r(l):l.detection),i=a||(t instanceof Te?await up(t,s):await lp(t,s)),o=await n(i);return i.forEach(l=>l instanceof Te&&l.dispose()),o}async function yp(e,t,n,a,r){return Bo([e],t,async s=>n(s[0]),a,r)}var k$=.4,I$=[new De(1.603231,2.094468),new De(6.041143,7.080126),new De(2.882459,3.518061),new De(4.266906,5.178857),new De(9.041765,10.66308)],S$=[117.001,114.697,97.404];var Vo=class extends zo{constructor(){let t={withSeparableConvs:!0,iouThreshold:k$,classes:["face"],anchors:I$,meanRgb:S$,isFirstLayerConv2d:!0,filterSizes:[3,16,32,64,128,256,512]};super(t)}get anchors(){return this.config.anchors}async locateFaces(t,n){return(await this.detect(t,n)).map(r=>new bt(r.score,r.relativeBox,{width:r.imageWidth,height:r.imageHeight}))}getDefaultModelName(){return"tiny_face_detector_model"}extractParamsFromWeightMap(t){return super.extractParamsFromWeightMap(t)}};var Qe={ssdMobilenetv1:new As,tinyFaceDetector:new Vo,tinyYolov2:new Wo,faceLandmark68Net:new Po,faceLandmark68TinyNet:new kd,faceRecognitionNet:new Oo,faceExpressionNet:new vd,ageGenderNet:new wd},T$=(e,t)=>Qe.ssdMobilenetv1.locateFaces(e,t),vce=(e,t)=>Qe.tinyFaceDetector.locateFaces(e,t),wce=(e,t)=>Qe.tinyYolov2.locateFaces(e,t),N$=e=>Qe.faceLandmark68Net.detectLandmarks(e),kce=e=>Qe.faceLandmark68TinyNet.detectLandmarks(e),Ice=e=>Qe.faceRecognitionNet.computeFaceDescriptor(e),Sce=e=>Qe.faceExpressionNet.predictExpressions(e),Tce=e=>Qe.ageGenderNet.predictAgeAndGender(e),C$=e=>Qe.ssdMobilenetv1.load(e),Nce=e=>Qe.tinyFaceDetector.load(e),Cce=e=>Qe.tinyYolov2.load(e),_ce=e=>Qe.faceLandmark68Net.load(e),Ece=e=>Qe.faceLandmark68TinyNet.load(e),Ace=e=>Qe.faceRecognitionNet.load(e),$ce=e=>Qe.faceExpressionNet.load(e),Fce=e=>Qe.ageGenderNet.load(e),Dce=C$,Rce=T$,Mce=N$;var Ig=class extends ka{constructor(n,a,r){super();this.parentTask=n;this.input=a;this.extractedFaces=r}},Uo=class extends Ig{async run(){let t=await this.parentTask,n=await Bo(t,this.input,async a=>Promise.all(a.map(r=>Qe.faceExpressionNet.predictExpressions(r))),this.extractedFaces);return t.map((a,r)=>dg(a,n[r]))}withAgeAndGender(){return new Ho(this,this.input)}},Go=class extends Ig{async run(){let t=await this.parentTask;if(!t)return;let n=await yp(t,this.input,a=>Qe.faceExpressionNet.predictExpressions(a),this.extractedFaces);return dg(t,n)}withAgeAndGender(){return new jo(this,this.input)}},$s=class extends Uo{withAgeAndGender(){return new Ds(this,this.input)}withFaceDescriptors(){return new Gr(this,this.input)}},Fs=class extends Go{withAgeAndGender(){return new Rs(this,this.input)}withFaceDescriptor(){return new Hr(this,this.input)}};var Sg=class extends ka{constructor(n,a,r){super();this.parentTask=n;this.input=a;this.extractedFaces=r}},Ho=class extends Sg{async run(){let t=await this.parentTask,n=await Bo(t,this.input,async a=>Promise.all(a.map(r=>Qe.ageGenderNet.predictAgeAndGender(r))),this.extractedFaces);return t.map((a,r)=>{let{age:s,gender:i,genderProbability:o}=n[r];return vg(wg(a,i,o),s)})}withFaceExpressions(){return new Uo(this,this.input)}},jo=class extends Sg{async run(){let t=await this.parentTask;if(!t)return;let{age:n,gender:a,genderProbability:r}=await yp(t,this.input,s=>Qe.ageGenderNet.predictAgeAndGender(s),this.extractedFaces);return vg(wg(t,a,r),n)}withFaceExpressions(){return new Go(this,this.input)}},Ds=class extends Ho{withFaceExpressions(){return new $s(this,this.input)}withFaceDescriptors(){return new Gr(this,this.input)}},Rs=class extends jo{withFaceExpressions(){return new Fs(this,this.input)}withFaceDescriptor(){return new Hr(this,this.input)}};var Td=class extends ka{constructor(n,a){super();this.parentTask=n;this.input=a}},Gr=class extends Td{async run(){let t=await this.parentTask;return(await Bo(t,this.input,a=>Promise.all(a.map(r=>Qe.faceRecognitionNet.computeFaceDescriptor(r))),null,a=>a.landmarks.align(null,{useDlibAlignment:!0}))).map((a,r)=>xg(t[r],a))}withFaceExpressions(){return new $s(this,this.input)}withAgeAndGender(){return new Ds(this,this.input)}},Hr=class extends Td{async run(){let t=await this.parentTask;if(!t)return;let n=await yp(t,this.input,a=>Qe.faceRecognitionNet.computeFaceDescriptor(a),null,a=>a.landmarks.align(null,{useDlibAlignment:!0}));return xg(t,n)}withFaceExpressions(){return new Fs(this,this.input)}withAgeAndGender(){return new Rs(this,this.input)}};var Nd=class extends ka{constructor(n,a,r){super();this.parentTask=n;this.input=a;this.useTinyLandmarkNet=r}get landmarkNet(){return this.useTinyLandmarkNet?Qe.faceLandmark68TinyNet:Qe.faceLandmark68Net}},Cd=class extends Nd{async run(){let t=await this.parentTask,n=t.map(i=>i.detection),a=this.input instanceof Te?await up(this.input,n):await lp(this.input,n),r=await Promise.all(a.map(i=>this.landmarkNet.detectLandmarks(i)));return a.forEach(i=>i instanceof Te&&i.dispose()),t.filter((i,o)=>r[o]).map((i,o)=>fp(i,r[o]))}withFaceExpressions(){return new $s(this,this.input)}withAgeAndGender(){return new Ds(this,this.input)}withFaceDescriptors(){return new Gr(this,this.input)}},_d=class extends Nd{async run(){let t=await this.parentTask;if(!t)return;let{detection:n}=t,a=this.input instanceof Te?await up(this.input,[n]):await lp(this.input,[n]),r=await this.landmarkNet.detectLandmarks(a[0]);return a.forEach(s=>s instanceof Te&&s.dispose()),fp(t,r)}withFaceExpressions(){return new Fs(this,this.input)}withAgeAndGender(){return new Rs(this,this.input)}withFaceDescriptor(){return new Hr(this,this.input)}};var Ed=class extends ka{constructor(n,a=new wa){super();this.input=n;this.options=a}},xp=class extends Ed{async run(){let{input:t,options:n}=this,a;if(n instanceof Sd)a=Qe.tinyFaceDetector.locateFaces(t,n);else if(n instanceof wa)a=Qe.ssdMobilenetv1.locateFaces(t,n);else if(n instanceof Qa)a=Qe.tinyYolov2.locateFaces(t,n);else throw new Error("detectFaces - expected options to be instance of TinyFaceDetectorOptions | SsdMobilenetv1Options | TinyYolov2Options");return a}runAndExtendWithFaceDetections(){return new Promise((t,n)=>{this.run().then(a=>t(a.map(r=>Ao({},r)))).catch(a=>n(a))})}withFaceLandmarks(t=!1){return new Cd(this.runAndExtendWithFaceDetections(),this.input,t)}withFaceExpressions(){return new Uo(this.runAndExtendWithFaceDetections(),this.input)}withAgeAndGender(){return new Ho(this.runAndExtendWithFaceDetections(),this.input)}},Ad=class extends Ed{async run(){let t=await new xp(this.input,this.options),n=t[0];return t.forEach(a=>{a.score>n.score&&(n=a)}),n}runAndExtendWithFaceDetection(){return new Promise(async t=>{let n=await this.run();t(n?Ao({},n):void 0)})}withFaceLandmarks(t=!1){return new _d(this.runAndExtendWithFaceDetection(),this.input,t)}withFaceExpressions(){return new Go(this.runAndExtendWithFaceDetection(),this.input)}withAgeAndGender(){return new jo(this.runAndExtendWithFaceDetection(),this.input)}};function Pce(e,t=new wa){return new Ad(e,t)}function Tg(e,t=new wa){return new xp(e,t)}async function _$(e,t){return Tg(e,new wa(t?{minConfidence:t}:{})).withFaceLandmarks().withFaceDescriptors()}async function Oce(e,t={}){return Tg(e,new Qa(t)).withFaceLandmarks().withFaceDescriptors()}var Lce=_$;function U1(e,t){if(e.length!==t.length)throw new Error("euclideanDistance: arr1.length !== arr2.length");let n=Array.from(e),a=Array.from(t);return Math.sqrt(n.map((r,s)=>r-a[s]).reduce((r,s)=>r+s*s,0))}var $d=class{constructor(t,n=.6){this._distanceThreshold=n;let a=Array.isArray(t)?t:[t];if(!a.length)throw new Error("FaceRecognizer.constructor - expected atleast one input");let r=1,s=()=>`person ${r++}`;this._labeledDescriptors=a.map(i=>{if(i instanceof gr)return i;if(i instanceof Float32Array)return new gr(s(),[i]);if(i.descriptor&&i.descriptor instanceof Float32Array)return new gr(s(),[i.descriptor]);throw new Error("FaceRecognizer.constructor - expected inputs to be of type LabeledFaceDescriptors | WithFaceDescriptor<any> | Float32Array | Array<LabeledFaceDescriptors | WithFaceDescriptor<any> | Float32Array>")})}get labeledDescriptors(){return this._labeledDescriptors}get distanceThreshold(){return this._distanceThreshold}computeMeanDistance(t,n){return n.map(a=>U1(a,t)).reduce((a,r)=>a+r,0)/(n.length||1)}matchDescriptor(t){return this.labeledDescriptors.map(({descriptors:n,label:a})=>new sp(a,this.computeMeanDistance(t,n))).reduce((n,a)=>n.distance<a.distance?n:a)}findBestMatch(t){let n=this.matchDescriptor(t);return n.distance<this._distanceThreshold?n:new sp("unknown",n.distance)}toJSON(){return{distanceThreshold:this._distanceThreshold,labeledDescriptors:this._labeledDescriptors.map(t=>t.toJSON())}}static fromJSON(t){let n=t.labeledDescriptors.map(a=>gr.fromJSON(a));return new $d(n,t.distanceThreshold)}};function zce(e){let t=new Vo;return t.extractWeights(e),t}function E$(e,t){let{width:n,height:a}=new bn(t.width,t.height);if(n<=0||a<=0)throw new Error(`resizeResults - invalid dimensions: ${JSON.stringify({width:n,height:a})}`);if(Array.isArray(e))return e.map(r=>E$(r,{width:n,height:a}));if(Mo(e)){let r=e.detection.forSize(n,a),s=e.unshiftedLandmarks.forSize(r.box.width,r.box.height);return fp(Ao(e,r),s)}return br(e)?Ao(e,e.detection.forSize(n,a)):e instanceof ra||e instanceof bt?e.forSize(n,a):e}var Wce=XA;return hF(Bce);})();