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human
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human/dist/human.esm.js

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/*
Human library
homepage: <https://github.com/vladmandic/human>
author: <https://github.com/vladmandic>'
*/
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this.runKernelFunc({kernelName:e,inputs:t,attrs:n})}shouldCheckForMemLeaks(){return this.ENV.getBool("IS_TEST")}checkKernelForMemLeak(e,t,n){let s=this.backend.numDataIds(),r=0;n.forEach(i=>{r+=i.dtype==="complex64"?3:1});let a=this.state.numDataMovesStack[this.state.numDataMovesStack.length-1],o=s-t-r-a;if(o>0)throw new Error(`Backend '${this.backendName}' has an internal memory leak (${o} data ids) after running '${e}'`)}runKernelFunc(e){let t,n=[],s=this.isTapeOn(),r=this.state.numBytes,a=this.state.numTensors;this.shouldCheckForMemLeaks()&&this.state.numDataMovesStack.push(0);let o;this.backendName==null&&this.backend;let i,l=Lm(e)?e.kernelName:this.state.activeScope!=null?this.state.activeScope.name:"";if(Lm(e)){let{kernelName:p,inputs:m,attrs:f}=e;this.backendName==null&&this.backend;let A=vh(p,this.backendName);M(A!=null,()=>`Cannot find registered kernel '${p}' for backend '${this.backendName}'`),o=()=>{let g=this.backend.numDataIds();i=A.kernelFunc({inputs:m,attrs:f,backend:this.backend});let y=Array.isArray(i)?i:[i];this.shouldCheckForMemLeaks()&&this.checkKernelForMemLeak(p,g,y);let x=y.map(b=>{if(b.rank!=null)return b;let{dataId:v,shape:k,dtype:w}=b;return this.makeTensorFromDataId(v,k,w)});if(s){let b=this.getTensorsForGradient(p,m,x);n=this.saveTensorsForBackwardMode(b)}return x}}else{let{forwardFunc:p}=e,m=f=>{!s||(n=f.map(A=>this.keep(this.clone(A))))};o=()=>{let f=this.backend.numDataIds();i=this.tidy(()=>p(this.backend,m));let A=Array.isArray(i)?i:[i];return this.shouldCheckForMemLeaks()&&this.checkKernelForMemLeak(l,f,A),A}}let{inputs:u,attrs:c}=e,d=Lm(e)?null:e.backwardsFunc,h;return this.scopedRun(()=>this.state.kernelDepth++,()=>this.state.kernelDepth--,()=>{!this.ENV.getBool("DEBUG")&&!this.state.profiling?t=o():(h=this.profiler.profileKernel(l,u,()=>o()),this.ENV.getBool("DEBUG")&&this.profiler.logKernelProfile(h),t=h.outputs)}),s&&this.addTapeNode(l,u,t,d,n,c),this.state.profiling&&this.state.activeProfile.kernels.push({name:l,bytesAdded:this.state.numBytes-r,totalBytesSnapshot:this.state.numBytes,tensorsAdded:this.state.numTensors-a,totalTensorsSnapshot:this.state.numTensors,inputShapes:Object.keys(u).map(p=>u[p]!=null?u[p].shape:null),outputShapes:t.map(p=>p.shape),kernelTimeMs:h.timeMs,extraInfo:h.extraInfo}),Array.isArray(i)?t:t[0]}saveTensorsForBackwardMode(e){return e.map(n=>this.keep(this.clone(n)))}getTensorsForGradient(e,t,n){let s=Em(e);if(s!=null){let r=s.inputsToSave||[],a=s.outputsToSave||[],o;s.saveAllInputs?(M(Array.isArray(t),()=>"saveAllInputs is true, expected inputs to be an array."),o=Object.keys(t).map(l=>t[l])):o=r.map(l=>t[l]);let 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n=0;e.dtype!=="complex64"&&e.dtype!=="string"&&(n=e.size*km(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 Ku||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*km(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(s=>s.totalBytesSnapshot)),this.state.activeProfile.newBytes=this.state.numBytes-t,this.state.activeProfile.newTensors=this.state.numTensors-n;for(let s of this.state.activeProfile.kernels)s.kernelTimeMs=await s.kernelTimeMs,s.extraInfo=await s.extraInfo;return this.state.activeProfile}isTapeOn(){return this.state.gradientDepth>0&&this.state.kernelDepth===0}addTapeNode(e,t,n,s,r,a){let o={id:this.state.nextTapeNodeId++,kernelName:e,inputs:t,outputs:n,saved:r},i=Em(e);i!=null&&(s=i.gradFunc),s!=null&&(o.gradient=l=>(l=l.map((u,c)=>{if(u==null){let d=n[c],h=Md(d.size,d.dtype);return this.makeTensor(h,d.shape,d.dtype)}return u}),s(l.length>1?l:l[0],r,a))),this.state.activeTape.push(o)}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=zm(e),n=new Set(t.map(r=>r.id));for(let r=0;r<this.state.activeScope.track.length;r++){let a=this.state.activeScope.track[r];!a.kept&&!n.has(a.id)&&a.dispose()}let s=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===s.id&&this.track(r)})}gradients(e,t,n,s=!1){if(M(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));M(r instanceof Ue,()=>"The result y returned by f() must be a tensor.");let a=$S(this.state.activeTape,t,r);if(!s&&a.length===0&&t.length>0)throw new Error("Cannot compute gradient of y=f(x) with respect to x. 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o=D(e,"x","batchNorm"),i=D(t,"mean","batchNorm"),l=D(n,"variance","batchNorm"),u;r!=null&&(u=D(r,"scale","batchNorm"));let c;return s!=null&&(c=D(s,"offset","batchNorm")),M(o.rank===4,()=>`Error in batchNorm4D: x must be rank 4 but got rank ${o.rank}.`),M(i.rank===4||i.rank===1,()=>`Error in batchNorm4D: mean must be rank 4 or rank 1 but got rank ${i.rank}.`),M(l.rank===4||l.rank===1,()=>`Error in batchNorm4D: variance must be rank 4 or rank 1 but got rank ${l.rank}.`),u!=null&&M(u.rank===4||u.rank===1,()=>`Error in batchNorm4D: scale must be rank 4 or rank 1 but got rank ${u.rank}.`),c!=null&&M(c.rank===4||c.rank===1,()=>`Error in batchNorm4D: offset must be rank 4 or rank 1 but got rank ${c.rank}.`),kl(o,i,l,c,u,a)}var _x=V({batchNorm4d_:lT});function uT(e,t,n){let s=D(e,"x","bincount"),r=D(t,"weights","bincount");M(s.dtype==="int32",()=>`Error in bincount: input dtype must be int32, but got ${s.dtype}`),M(n>=0,()=>`size must be non-negative, but got 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this.assertNotDisposed(),MO(this.val,e),this.val.id!==e.id&&(this.val.assign(e),this.constraint!=null&&this.val.assign(this.constraint.apply(this.val))),this}dispose(){this.assertNotDisposed(),this.val.dispose()}assertNotDisposed(){if(this.val.isDisposed)throw new Error(`LayersVariable ${this.name} is already disposed.`)}get trainable(){return this.trainable_}set trainable(e){this.trainable_=e,this.val.trainable=e}};function MO(e,t){if(e.shape.toString()!==t.shape.toString())throw new Error("Shape mismatch: "+JSON.stringify(e.shape)+" vs. "+JSON.stringify(t.shape))}function fg(e){return e.map(t=>t.read())}function mg(e){e.forEach(t=>{t[0].write(t[1])})}var Pt=class{constructor(e){this.dtype=e.dtype,this.shape=e.shape,e.shape!=null?this.ndim=e.shape.length:this.ndim=e.ndim,this.maxNDim=e.maxNDim,this.minNDim=e.minNDim,this.axes=e.axes||{}}},Ps=class{constructor(e,t,n,s,r,a,o){this.dtype=e,this.shape=t,this.sourceLayer=n,this.inputs=s,this.callArgs=r,this.outputTensorIndex=o,this.id=i3(),a!=null&&(this.originalName=Jb(a),this.name=Qb(this.originalName)),this.rank=t.length}},zO=0,Tp=class{constructor(e,t){this.callArgs=t,this.id=zO++,this.outboundLayer=e.outboundLayer,this.inboundLayers=e.inboundLayers,this.nodeIndices=e.nodeIndices,this.tensorIndices=e.tensorIndices,this.inputTensors=e.inputTensors,this.outputTensors=e.outputTensors,this.inputMasks=e.inputMasks,this.outputMasks=e.outputMasks,this.inputShapes=e.inputShapes,this.outputShapes=e.outputShapes;for(let n of e.inboundLayers)n!=null&&n.outboundNodes.push(this);e.outboundLayer.inboundNodes.push(this)}getConfig(){let e=[];for(let t of this.inboundLayers)t!=null?e.push(t.name):e.push(null);return{outboundLayer:this.outboundLayer?this.outboundLayer.name:null,inboundLayers:e,nodeIndices:this.nodeIndices,tensorIndices:this.tensorIndices}}},LO=0,Xe=class extends oe.Serializable{constructor(e={}){super();this._callHook=null,this._addedWeightNames=[],this._stateful=!1,this.id=LO++,this.activityRegularizer=null,this.inputSpec=null,this.supportsMasking=!1,this._trainableWeights=[],this._nonTrainableWeights=[],this._losses=[],this._updates=[],this._built=!1,this.inboundNodes=[],this.outboundNodes=[];let t=e.name;if(!t){let n=this.getClassName();t=vr(n)+"_"+Ip(n)}if(this.name=t,this.trainable_=e.trainable==null?!0:e.trainable,e.inputShape!=null||e.batchInputShape!=null){let n;if(e.batchInputShape!=null)n=e.batchInputShape;else if(e.inputShape!=null){let r=null;e.batchSize!=null&&(r=e.batchSize),n=[r].concat(e.inputShape)}this.batchInputShape=n;let s=e.dtype;s==null&&(s=e.inputDType),s==null&&(s="float32"),this.dtype=s}e.weights!=null?this.initialWeights=e.weights:this.initialWeights=null,this._refCount=null,this.fastWeightInitDuringBuild=!1}static nodeKey(e,t){return e.name+"_ib-"+t.toString()}getNodeAtIndex(e,t){if(this.inboundNodes.length===0)throw new Fs(`The layer has never been called and thus has no defined ${t}.`);if(this.inboundNodes.length<=e)throw new G(`Asked to get ${t} at node ${e}, but the layer has only ${this.inboundNodes.length} inbound nodes.`);return this.inboundNodes[e]}getInputAt(e){return En(this.getNodeAtIndex(e,"input").inputTensors)}getOutputAt(e){return En(this.getNodeAtIndex(e,"output").outputTensors)}get input(){if(this.inboundNodes.length>1)throw new br(`Layer ${this.name} has multiple inbound nodes, hence the notion of "layer input" is ill-defined. 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Input received: ${e}`);for(let n=0;n<e.length;n++){let s=e[n],r=t[n];if(r==null)continue;let a=s.rank;if(r.ndim!=null&&a!==r.ndim)throw new G(`Input ${n} is incompatible with layer ${this.name}: expected ndim=${r.ndim}, found ndim=${a}`);if(r.maxNDim!=null&&a>r.maxNDim)throw new G(`Input ${n} is incompatible with layer ${this.name}: expected max_ndim=${r.maxNDim}, found ndim=${a}`);if(r.minNDim!=null&&a<r.minNDim)throw new G(`Input ${n} is incompatible with layer ${this.name}: expected min_ndim=${r.minNDim}, found ndim=${a}.`);if(r.dtype!=null&&s.dtype!==r.dtype)throw new G(`Input ${n} is incompatible with layer ${this.name} : expected dtype=${r.dtype}, found dtype=${s.dtype}.`);if(r.axes){let o=s.shape;for(let i in r.axes){let l=Number(i),u=r.axes[i],c=l>=0?o[l]:o[o.length+l];if(u!=null&&[u,null].indexOf(c)===-1)throw new G(`Input ${n} is incompatible with layer ${this.name}: expected axis ${l} of input shape to have value ${u} but got shape ${o}.`)}}if(r.shape!=null)for(let o=0;o<r.shape.length;++o){let i=r.shape[o],l=s.shape[o];if(i!=null&&l!=null&&i!==l)throw new G(`Input ${n} is incompatible with layer ${this.name}: expected shape=${r.shape}, found shape=${s.shape}.`)}}}call(e,t){return e}invokeCallHook(e,t){this._callHook!=null&&this._callHook(e,t)}setCallHook(e){this._callHook=e}clearCallHook(){this._callHook=null}apply(e,t){t=t||{},this.assertNotDisposed();let n=At(e),s=!0;for(let a of n)if(!(a instanceof Ps)){s=!1;break}let r=!0;for(let a of n)if(a instanceof Ps){r=!1;break}if(s===r)throw new G("Arguments to apply() must be all SymbolicTensors or all Tensors");return $o(this.name,()=>{if(!this.built){this.assertInputCompatibility(e);let a=[];for(let o of At(e))a.push(o.shape);this.build(En(a)),this.built=!0,this.initialWeights&&this.setWeights(this.initialWeights),this._refCount===null&&r&&(this._refCount=1)}if(this.assertInputCompatibility(e),r){let a=this.call(e,t),o=At(a),i=[];for(let l of o)n.indexOf(l)!==-1&&(l=l.clone()),i.push(l);if(a=En(i),this.activityRegularizer!=null)throw new Oe("Layer invocation in the presence of activity regularizer(s) is not supported yet.");return a}else{let a=BO(e),o=this.computeOutputShape(a),i,l=WO(e);if(this.warnOnIncompatibleInputShape(Array.isArray(e)?a[0]:a),o!=null&&o.length>0&&Array.isArray(o[0])?i=o.map((u,c)=>new Ps(l,u,this,At(e),t,this.name,c)):i=new Ps(l,o,this,At(e),t,this.name),this.addInboundNode(e,i,null,null,a,o,t),this._refCount++,this.activityRegularizer!=null)throw new Oe("Layer invocation in the presence of activity regularizer(s) is not supported yet.");return i}})}warnOnIncompatibleInputShape(e){if(this.batchInputShape!=null)if(e.length!==this.batchInputShape.length)console.warn(`The rank of the input tensor provided (shape: ${JSON.stringify(e)}) does not match that of the batchInputShape (${JSON.stringify(this.batchInputShape)}) of the layer ${this.name}`);else{let t=!1;this.batchInputShape.forEach((n,s)=>{n!=null&&e[s]!=null&&e[s]!==n&&(t=!0)}),t&&console.warn(`The shape of the input tensor (${JSON.stringify(e)}) does not match the expectation of layer ${this.name}: ${JSON.stringify(this.batchInputShape)}`)}}get outputShape(){if(this.inboundNodes==null||this.inboundNodes.length===0)throw new br(`The layer ${this.name} has never been called and thus has no defined output shape.`);let e=[];for(let t of this.inboundNodes){let n=JSON.stringify(t.outputShapes);e.indexOf(n)===-1&&e.push(n)}if(e.length===1){let t=this.inboundNodes[0].outputShapes;return Array.isArray(t)&&Array.isArray(t[0])&&t.length===1?t[0]:t}else throw new br(`The layer ${this.name} has multiple inbound nodes with different output shapes. Hence the notion of "output shape" is ill-defined for the layer.`)}countParams(){if(!this.built)throw new Fs(`You tried to call countParams() on ${this.name}, but the layer is not built yet. Build it first by calling build(batchInputShape).`);return Cp(this.weights)}build(e){this.built=!0}getWeights(e=!1){return fg(e?this.trainableWeights:this.weights)}setWeights(e){H(()=>{let t=this.weights;if(t.length!==e.length)throw new G(`You called setWeights(weights) on layer "${this.name}" with a weight list of length ${e.length}, but the layer was expecting ${t.length} weights. 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All inputs should only appear once. Found: ${this.inputs.map(g=>g.name)}`);Xr(this.outputs).length!==this.outputs.length&&console.warn(`The list of outputs passed to the model is redundant. All outputs should only appear once. Found: ${this.outputs.map(g=>g.name)}`),this.inputLayers=[],this.inputLayersNodeIndices=[],this.inputLayersTensorIndices=[],this.outputLayers=[],this.outputLayersNodeIndices=[],this.outputLayersTensorIndices=[],this.layers=[],this.internalContainerRefs=[];for(let g of this.outputs){let y=g.sourceLayer,x=g.nodeIndex,b=g.tensorIndex;this.outputLayers.push(y),this.outputLayersNodeIndices.push(x),this.outputLayersTensorIndices.push(b)}for(let g of this.inputs){let y=g.sourceLayer,x=g.nodeIndex,b=g.tensorIndex;Qs(x===0,"input layer has >1 nodes"),Qs(b===0,"input layer has >1 tensors"),this.inputLayers.push(y),this.inputLayersNodeIndices.push(x),this.inputLayersTensorIndices.push(b)}this.inputNames=[],this.outputNames=[],this.feedInputShapes=[],this.feedInputNames=[],this.feedOutputNames=[];for(let g=0;g<this.inputLayers.length;g++){let y=this.inputLayers[g];if(!(y instanceof Dl))throw new TypeError(`Input layers to a LayersModel must be InputLayer objects. Received inputs: ${e.inputs}. Input ${g} (0-based) originates from layer type ${y.getClassName()}.`);this.inputNames.push(y.name),this.feedInputShapes.push(y.batchInputShape),this.feedInputNames.push(y.name)}for(let g of this.outputLayers)this.outputNames.push(g.name);this.internalInputShapes=this.inputs.map(g=>g.shape),this.internalOutputShapes=this.outputs.map(g=>g.shape);let t={},n={},s={},r={},a={},o=[],i=(g,y,x,b,v,k)=>{(b==null||v==null||k==null)&&(b=g.sourceLayer,v=g.nodeIndex,k=g.tensorIndex);let w=b.inboundNodes[v];if(x.indexOf(w)!==-1)throw new Fs(`The tensor ${g.name} at layer "${b.name}" is part of a cycle.`);if(y.indexOf(w)!==-1)return;this.containerNodes.add(tr.nodeKey(b,v)),b.id in a||(a[b.id]=Object.keys(a).length),x.indexOf(w)===-1&&x.push(w);let C=w.inboundLayers.length;for(let E=0;E<C;E++){let P=w.inputTensors[E],R=w.inboundLayers[E],_=w.nodeIndices[E],T=w.tensorIndices[E];i(P,y,x,R,_,T)}for(y.push(w);x.indexOf(w)>=0;)x.splice(x.indexOf(w),1);o.push(w)},l=[],u=[];for(let g of this.outputs)i(g,l,u);let c=o.slice().reverse();for(let g of c){n[g.id]=g,g.id in t||(t[g.id]=0);let y=t[g.id],x=s[g.outboundLayer.id]==null?0:s[g.outboundLayer.id];y=Math.max(y,x),s[g.outboundLayer.id]=y,r[g.outboundLayer.id]=g.outboundLayer,t[g.id]=y;for(let b=0;b<g.inboundLayers.length;b++){let v=g.inboundLayers[b],k=g.nodeIndices[b],w=v.inboundNodes[k],C=t[w.id]==null?0:t[w.id];t[w.id]=Math.max(y+1,C),n[w.id]=w}}let d={};for(let g in t){let y=t[g];y in d||(d[y]=[]),d[y].push(n[g])}let h={};for(let g in s){let y=s[g];y in h||(h[y]=[]),h[y].push(r[g])}let p=Object.keys(h).map(g=>parseInt(g,10)).sort(hp);this.layers=[];for(let g of p){let y=h[g];y.sort((x,b)=>{let v=a[x.id],k=a[b.id];return v<k?-1:v>k?1:0});for(let x of y)x instanceof tr&&this.internalContainerRefs.push(x),this.layers.push(x)}this.layersByDepth=h,p=Object.keys(d).map(g=>parseInt(g,10)).sort(hp);let m=this.inputs.slice(),f=[];for(let g of p)for(let y of d[g]){let x=y.outboundLayer;if(x!=null){for(let b of y.inputTensors)if(m.indexOf(b)===-1)throw new Fs(`Graph disconnected: cannot obtain value for tensor ${b} at layer "${x.name}". The following previous layers were accessed without issue: ${f}`);for(let b of y.outputTensors)m.push(b);f.push(x.name)}}this.nodesByDepth=d;let A=this.layers.map(g=>g.name);for(let g of A){let y=A.filter(x=>x===g).length;if(y!==1)throw new Fs(`The name "${g}" is used ${y} times in the model. All layer names should be unique. Layer names: `+JSON.stringify(A))}this.outboundNodes=[],this.inboundNodes=[],new Tp({outboundLayer:this,inboundLayers:[],nodeIndices:[],tensorIndices:[],inputTensors:this.inputs,outputTensors:this.outputs,inputMasks:this.inputs.map(g=>null),outputMasks:this.outputs.map(g=>null),inputShapes:this.inputs.map(g=>g.shape),outputShapes:this.outputs.map(g=>g.shape)}),this.built=!0,this._refCount=1}assertNotDisposed(){if(this._refCount===0)throw new Error(`Container '${this.name}' is already disposed.`)}dispose(){this.assertNotDisposed();let e={refCountAfterDispose:null,numDisposedVariables:0};if(--this._refCount==0){for(let t of this.layers)e.numDisposedVariables+=t.dispose().numDisposedVariables;for(let t of this.internalContainerRefs)e.numDisposedVariables+=t.dispose().numDisposedVariables}return e.refCountAfterDispose=this._refCount,e}get trainable(){return this.trainable_}set trainable(e){this.layers.forEach(t=>{t._trainableWeights.forEach(n=>n.trainable=e)}),this.trainable_=e}get trainableWeights(){if(this._trainableWeights.length>0)throw new G("Container instance unexpectedly contains _trainableWeights.The trainable weights of a Container are a union of the trainable weights of its consituent Layers. 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={},s=0;for(let a of this.layers)for(let o of a.weights){if(n[o.originalName]!=null)throw new G(`Duplicate weight name: ${o.originalName}`);n[o.originalName]=o,s++}let r=[];for(let a in e){let o=a;if(n[a]==null){let i=a.split("/");o=i.slice(0,-2).concat([i[i.length-1]]).join("/")}if(n[o]!=null)r.push([n[o],e[a]]);else if(t)throw new G(`Provided weight data has no target variable: ${a}`);delete n[o]}if(t){let a=[];for(let o in n)a.push(o);if(a.length>0)throw new G(`${a.length} of ${s} weights are not set: ${a}`)}mg(r)}updatedConfig(){let e=this.getConfig(),t={};return t.className=this.getClassName(),t.config=e,t.kerasVersion=`tfjs-layers ${kg}`,t.backend="TensorFlow.js",t}toJSON(e,t=!0){let n=wg(this.updatedConfig());return t?JSON.stringify(n):n}call(e,t){return H(()=>{e=At(e);let n=new Oo;for(let s=0;s<this.inputs.length;++s)n.add(this.inputs[s],e[s]);return vc(this.outputs,n,t)})}computeMask(e,t){return H(()=>{e=At(e);let n;return t==null?n=Eo(null,e.length):n=At(t),this.runInternalGraph(e,n)[1]})}computeOutputShape(e){let t=Sp(e);if(t.length!==this.inputLayers.length)throw new G(`Invalid inputShape argument ${e}: model has ${this.inputLayers.length} tensor inputs.`);let n={};for(let o=0;o<t.length;o++){let i=this.inputLayers[o],l=t[o],u=i.name+"_0_0";n[u]=l}let s=Object.keys(this.nodesByDepth).map(o=>parseInt(o,10)).sort(hp);if(s.length>1)for(let o of s){let i=this.nodesByDepth[o];for(let l of i){let u=l.outboundLayer;if(this.inputLayers.map(m=>m.id).indexOf(u.id)!==-1)continue;let c=[];for(let m=0;m<l.inboundLayers.length;m++){let f=l.inboundLayers[m],A=l.nodeIndices[m],g=l.tensorIndices[m],y=`${f.name}_${A}_${g}`,x=n[y];c.push(x)}let d=u.computeOutputShape(En(c)),h=Sp(d),p=u.inboundNodes.indexOf(l);for(let m=0;m<h.length;m++){let f=`${u.name}_${p}_${m}`;n[f]=h[m]}}}let r=[],a=[];for(let o=0;o<this.outputLayers.length;o++){let i=this.outputLayers[o],l=this.outputLayersNodeIndices[o],u=this.outputLayersTensorIndices[o],c=`${i.name}_${l}_${u}`;a.push(c)}for(let o=0;o<a.length;o++){let i=a[o];Qs(i in n),r.push(n[i])}return En(r)}runInternalGraph(e,t){t==null&&(t=Eo(null,e.length));let n={};for(let i=0;i<this.inputs.length;++i){let l=this.inputs[i],u=e[i],c=t[i];n[l.id]=[u,c]}let s=Object.keys(this.nodesByDepth).map(i=>parseInt(i,10)).sort(hp);for(let i of s){let l=this.nodesByDepth[i];for(let u of l){let c=u.outboundLayer,d=u.inputTensors,h=u.outputTensors,p=new Array;for(let m of d)m.id in n&&p.push(n[m.id]);if(p.length===d.length){let m={},f,A,g,y;if(u.callArgs!=null&&(m=u.callArgs),p.length===1){let[x,b]=p[0];m.mask==null&&(m.mask=b),g=At(c.call(x,m)),y=At(c.computeMask(x,b)),f=[x],A=[b]}else f=p.map(x=>x[0]),A=p.map(x=>x[1]),m.mask==null&&(m.mask=A),g=At(c.call(f,m)),y=At(c.computeMask(f,A));if(c.activityRegularizer)throw new Oe("LayersModel invocation with concrete Tensor value(s) in the presence of activity regularizer(s) is not supported yet.");for(let x=0;x<h.length;++x){let b=h[x],v=g[x],k=y[x];n[b.id]=[v,k]}}}}let r=[],a=[],o=[];for(let i of this.outputs){Qs(i.id in n,`Could not compute output ${i.name} : ${i.id}`);let[l,u]=n[i.id];o.push(l.shape),r.push(l),a.push(u)}return[r,a,o]}buildNodeConversionMap(e){let t={},n;for(let s of this.layers){n=s instanceof tr?1:0;for(let r=0;r<s.inboundNodes.length;r++){let a=tr.nodeKey(s,r);this.containerNodes.has(a)&&(t[a]=n,n+=1)}}return t}getLayer(e,t){if(t!=null){if(this.layers.length<=t)throw new G(`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 G("Provide either a layer name or layer index");for(let n of this.layers)if(n.name===e)return n;throw new G(`No such layer: ${e}`)}calculateLosses(){return H(()=>{let e=[];for(let t of this.layers)for(let n=0;n<t.inboundNodes.length;++n){let s=tr.nodeKey(t,n);this.containerNodes.has(s)&&e.push(...t.calculateLosses())}return e})}getConfig(){let e={name:this.name},t=this.buildNodeConversionMap(this.layers),n=[];for(let a of this.layers){let o=a.getClassName(),i=a.getConfig(),l=[];for(let c=0;c<a.inboundNodes.length;c++){let d=a.inboundNodes[c],h=tr.nodeKey(a,c),p={};if(this.containerNodes.has(h)){if(d.callArgs)try{JSON.stringify(d.callArgs),p=d.callArgs}catch(m){console.warn(`Layer ${a.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).`),p={}}if(d.inboundLayers.length>0){let m=[];for(let f=0;f<d.inboundLayers.length;f++){let A=d.inboundLayers[f],g=d.nodeIndices[f],y=d.tensorIndices[f],x=tr.nodeKey(A,g),b=t[x];b==null&&(b=0),m.push([A.name,b,y,p])}l.push(m)}}}let u={};u.name=a.name,u.className=o,u.config=i,u.inboundNodes=l,n.push(u)}e.layers=n;let s=[];for(let a=0;a<this.inputLayers.length;a++){let o=this.inputLayers[a],i=this.inputLayersNodeIndices[a],l=tr.nodeKey(o,i);if(!this.containerNodes.has(l))continue;let u=t[l];u==null&&(u=0);let c=this.inputLayersTensorIndices[a];s.push([o.name,u,c])}e.inputLayers=s;let r=[];for(let a=0;a<this.outputLayers.length;a++){let o=this.outputLayers[a],i=this.outputLayersNodeIndices[a],l=tr.nodeKey(o,i);if(!this.containerNodes.has(l))continue;let u=t[l];u==null&&(u=0);let c=this.outputLayersTensorIndices[a];r.push([o.name,u,c])}return e.outputLayers=r,e}static fromConfig(e,t,n={},s=!1){let r={},a={};function o(f,A){f.name in a?a[f.name].push(A):a[f.name]=[A]}function i(f,A){let g=[],y;for(let x of A){let b=x[0],v=x[1],k=x[2];if(y=x[3]==null?{}:x[3],!(b in r)){o(f,A);return}let w=r[b];if(w.inboundNodes.length<=v){o(f,A);return}let C=w.inboundNodes[v];g.push(C.outputTensors[k])}g.length>0&&f.apply(En(g),y)}function l(f){let A=f.name,g=Ms(f,t.customObjects!=null?t.customObjects:{});g.setFastWeightInitDuringBuild(s),r[A]=g,f.inboundNodes.forEach(x=>{if(!(x instanceof Array))throw new G(`Corrupted configuration, expected array for nodeData: ${x}`);o(g,x)})}let u=t.name,c=t.layers;for(let f of c)l(f);for(;!KD(a);)for(let f of c){let A=r[f.name];if(A.name in a){let g=a[A.name];delete a[A.name];for(let y of g)i(A,y)}}let d=[],h=[],p=t.inputLayers;for(let f of p){let A=f[0],g=f[1],y=f[2];Qs(A in r);let b=r[A].inboundNodes[g].outputTensors;d.push(b[y])}let m=t.outputLayers;for(let f of m){let A=f[0],g=f[1],y=f[2];Qs(A in r);let b=r[A].inboundNodes[g].outputTensors;h.push(b[y])}return new e({inputs:d,outputs:h,name:u})}get stateful(){if(this._stateful)throw new G("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(){H(()=>{this.layers.forEach(e=>{e.stateful&&e.resetStates()})})}};function xP(e,t,n){let s=t.length;if(e==null||Array.isArray(e)&&e.length===0)return t.map(r=>null);if(s===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!==s)throw new Error(`Provided ${n} is an array of ${e.length} element(s), but the model has ${s} outputs. Make sure a set of weights is provided for each model output.`);return e}else if(typeof e=="object"&&Object.keys(e).length>0&&typeof e[Object.keys(e)[0]]=="object"){let r=[];return t.forEach(a=>{a in e?r.push(e[a]):r.push(null)}),r}else throw new Error(`The model has multiple (${s}) outputs, so ${n} must be either an array with ${s} elements or an object with ${t} keys. Provided ${n} not understood: ${JSON.stringify(e)}`)}function E3(e,t){return xP(e,t,"classWeight")}async function R3(e,t,n,s){if(t!=null||s!=null)throw new Error("Support sampleWeight is not implemented yet");if(n!=null){let r=H(()=>{if(e.shape.length===1)return Ns(e);if(e.shape.length===2){if(e.shape[1]>1)return Xs(e,1);if(e.shape[1]===1)return U(e,[e.shape[0]]);throw new Error(`Encountered unexpected last-dimension size (${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.`)}),a=Array.from(await r.data());Z(r);let o=[];return a.forEach(i=>{if(n[i]==null)throw new Error(`classWeight must contain all classes in the training data. The class ${i} exists in the data but not in classWeight`);o.push(n[i])}),Ot(o,"float32")}else return null}function bP(e,t){return z(e,t)}var vP=32;function _3(e,t){let n,s,r=t;n=r.xs,s=r.ys,I.assert(n!=null&&s!=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 a=$3("input",e.inputNames,n),o=$3("output",e.outputNames,s),i=a[0].shape[0];I.assert(a.length===e.inputs.length,()=>`LayersModel has ${e.inputs.length} inputs, but the dataset provides ${a.length} inputs. (Expected input keys: ${JSON.stringify(e.inputNames)})`),I.assert(o.length===e.outputs.length,()=>`LayersModel has ${e.outputs.length} outputs, but the dataset provides ${o.length} outputs. (Expected output keys: ${JSON.stringify(e.outputNames)})`);for(let l=0;l<a.length;l++)I.assert(a[l].shape[0]===i,()=>`Batch size mismatch: input ${e.inputNames[l]} has ${a[l].shape[0]}; expected ${i} based on input ${e.inputNames[0]}.`);for(let l=0;l<o.length;l++)I.assert(o[l].shape[0]===i,()=>`Batch size mismatch: output ${e.outputNames[l]} has ${o[l].shape[0]}; expected ${i} based on input ${e.inputNames[0]}.`);return{xs:a,ys:o}}function $3(e,t,n){if(n instanceof Ue)return[n];if(Array.isArray(n))return I.assert(n.length===t.length,()=>`Received an array of ${n.length} Tensors, but expected ${t.length} to match the ${e} keys ${t}.`),n;{let s=[];for(let r of t){if(n[r]==null)throw new G(`The feature data generated by the dataset lacks the required ${e} key '${r}'.`);s.push(n[r])}return s}}function wP(e){if(e.length===3)throw new Oe("Validation with sample weights is not implemented yet.");return{xs:e[0],ys:e[1]}}async function kP(e,t,n){let s=n.batchesPerEpoch!=null;if(I.assert(e.optimizer!=null,()=>"You must compile a model before training/testing. Use LayersModel.compile(modelCompileConfig)."),I.assert(n!=null,()=>"For fitDataset(), the 2nd argument (config) is required, but it is not provided in this call."),I.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}`),I.assert(!s||n.batchesPerEpoch>0&&Number.isInteger(n.batchesPerEpoch),()=>`For fitDataset(), config.batchesPerEpoch is expected to be a positive integer if specified, but got ${n.batchesPerEpoch}`),I.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,a,o;if(r)if(F3(n.validationData))I.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 A=wP(n.validationData);a=A.xs,o=A.ys}let i=e.makeTrainFunction(),l=e.getDedupedMetricsNames(),u;r?u=l.slice().concat(l.map(A=>"val_"+A)):u=l.slice();let c=g3(n.callbacks,n.yieldEvery),d=n.verbose==null?1:n.verbose,{callbackList:h,history:p}=y3(c,d,n.epochs,null,null,IP(t,n),null,r,u);h.setModel(e),e.history=p,await h.onTrainBegin(),e.stopTraining_=!1;let m=n.initialEpoch==null?0:n.initialEpoch,f=await t.iterator();for(;m<n.epochs;){let A={};await h.onEpochBegin(m);let g=0,y=0;for(s||(f=await t.iterator());s?g<n.batchesPerEpoch:!0;){let x=await f.next();if(s&&x.done){console.warn(`You provided \`batchesPerEpoch\` as ${n.batchesPerEpoch}, but your dataset iterator ran out of data after ${g} batches; interrupting training. 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Use LayersModel.compile(modelCompileArgs).");let r=[];for(let a=0;a<this.feedOutputShapes.length;++a){let o=this.feedOutputShapes[a];this.feedLossFns[a]===Rp?r.push(o.slice(0,o.length-1).concat([1])):r.push(o)}if(e=P3(e,this.feedInputNames,this.feedInputShapes,!1,"input"),t=P3(t,this.feedOutputNames,r,!1,"target"),RP(e,t,null),_P(t,this.feedLossFns,this.feedOutputShapes),this.stateful&&s!=null&&s>0&&e[0].shape[0]%s!=0)throw new G(`In a stateful network, you should only pass inputs with a number of samples that is divisible by the batch size ${s}. 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t}makeTrainFunction(){return e=>{let t=[],n=e.slice(0,this.inputs.length),s=e.slice(this.inputs.length,this.inputs.length+this.outputs.length),r=e.slice(this.inputs.length+this.outputs.length,this.inputs.length+this.outputs.length*2),a=[],o=()=>{let c=[];for(let m=0;m<this.inputs.length;++m)c.push({key:this.inputs[m],value:n[m]});let d=new Oo(c),h=vc(this.outputs,d,{training:!0}),p;for(let m=0;m<this.lossFunctions.length;++m){let A=this.lossFunctions[m](s[m],h[m]);r[m]!=null&&(A=bP(A,r[m]));let g=Et(A);t.push(g),m===0?p=A:p=ae(p,A)}for(let m=0;m<this.metricsTensors.length;++m){let f;if(this.outputs.length>1&&m<this.outputs.length)f=t[m];else{let A=this.metricsTensors[m][0],g=this.metricsTensors[m][1];f=Et(A(s[g],h[g]))}Kt(f),a.push(f)}return p=Et(p),this.calculateLosses().forEach(m=>{p=ae(p,m)}),p},i=this.collectedTrainableWeights.map(c=>c.read()),l=!0;return[this.optimizer_.minimize(o,l,i)].concat(a)}}makeTestFunction(){this.testFunction=e=>H(()=>{let t=[],n,s=e.slice(0,this.inputs.length),r=e.slice(this.inputs.length,this.inputs.length+this.outputs.length),a=[];for(let l=0;l<this.inputs.length;++l)a.push({key:this.inputs[l],value:s[l]});let o=new Oo(a),i=vc(this.outputs,o);for(let l=0;l<this.lossFunctions.length;++l){let u=this.lossFunctions[l],c=Et(u(r[l],i[l]));l===0?n=c:n=ae(n,c),t.push(n)}for(let l=0;l<this.metricsTensors.length;++l){let u=this.metricsTensors[l][0],c=this.metricsTensors[l][1],d=Et(u(r[c],i[c]));t.push(d)}return t})}async fit(e,t,n={}){return NP(this,e,t,n)}async fitDataset(e,t){return kP(this,e,t)}async trainOnBatch(e,t){let n=await this.standardizeUserData(e,t),s=n[0],r=n[1],o=this.makeTrainFunction()(s.concat(r)),i=[];for(let l of o){let u=await l.data();i.push(u[0])}return Z(o),En(i)}getNamedWeights(e){let t=[],n=e!=null&&e.trainableOnly,s=n?this.trainableWeights:this.weights,r=this.getWeights(n);for(let a=0;a<s.length;++a)n&&!s[a].trainable||t.push({name:s[a].originalName,tensor:r[a]});return t}set stopTraining(e){this.stopTraining_=e}get stopTraining(){return this.stopTraining_}get optimizer(){return this.optimizer_}set optimizer(e){this.optimizer_!==e&&(this.optimizer_=e,this.isOptimizerOwned=!1)}dispose(){let e=super.dispose();if(e.refCountAfterDispose===0&&this.optimizer!=null&&this.isOptimizerOwned){let t=_h().numTensors;this.optimizer_.dispose(),e.numDisposedVariables+=t-_h().numTensors}return e}getLossIdentifiers(){let e;if(typeof this.loss=="string")e=vr(this.loss);else if(Array.isArray(this.loss)){for(let t of this.loss)if(typeof t!="string")throw new Error("Serialization of non-string loss is not supported.");e=this.loss.map(t=>vr(t))}else{let t=Object.keys(this.loss);e={};let n=this.loss;for(let s of t)if(typeof n[s]=="string")e[s]=vr(n[s]);else throw new Error("Serialization of non-string loss is not supported.")}return e}getMetricIdentifiers(){if(typeof this.metrics=="string"||typeof 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e.metrics)r[a]=Ro(e.metrics[a])}this.compile({loss:s,metrics:r,optimizer:n})}async save(e,t){if(typeof e=="string"){let l=Tn.getSaveHandlers(e);if(l.length===0)throw new G(`Cannot find any save handlers for URL '${e}'`);if(l.length>1)throw new G(`Found more than one (${l.length}) save handlers for URL '${e}'`);e=l[0]}if(e.save==null)throw new G("LayersModel.save() cannot proceed because the IOHandler provided does not have the `save` attribute defined.");let n=await Tn.encodeWeights(this.getNamedWeights(t)),s=!1,r=null,o={modelTopology:this.toJSON(r,s),format:FP,generatedBy:`TensorFlow.js tfjs-layers v${kg}`,convertedBy:null};if((t==null?!1:t.includeOptimizer)&&this.optimizer!=null){o.trainingConfig=this.getTrainingConfig();let l="optimizer",{data:u,specs:c}=await Tn.encodeWeights(await this.optimizer.getWeights(),l);n.specs.push(...c),n.data=Tn.concatenateArrayBuffers([n.data,u])}if(this.userDefinedMetadata!=null){let l=!0;S3(this.userDefinedMetadata,this.name,l),o.userDefinedMetadata=this.userDefinedMetadata}return o.weightData=n.data,o.weightSpecs=n.specs,e.save(o)}setUserDefinedMetadata(e){S3(e,this.name),this.userDefinedMetadata=e}getUserDefinedMetadata(){return this.userDefinedMetadata}};wr.className="Model";oe.registerClass(wr);var z3=class extends wr{};z3.className="Functional";oe.registerClass(z3);async function DP(e,t){"modelTopology"in e||(e={modelTopology:e}),e=e;let n=e.modelTopology;n.model_config!=null&&(n=n.model_config);let s=bc(n),r=Ms(s,t);if(e.weightsManifest!=null){let a=await Tn.loadWeights(e.weightsManifest,e.pathPrefix,r.weights.map(i=>i.originalName)),o={};for(let i of r.weights)o[i.originalName]=a[i.originalName];r.loadWeights(o),Z(a)}return r}async function OP(e,t){if(t==null&&(t={}),typeof e=="string"){let n=Tn.getLoadHandlers(e,t);if(n.length===0)n.push(Tn.browserHTTPRequest(e,t));else if(n.length>1)throw new G(`Found more than one (${n.length}) load handlers for URL '${e}'`);e=n[0]}return PP(e,void 0,t)}async function PP(e,t,n){if(n==null&&(n={}),e.load==null)throw new G("Cannot proceed with model loading because the IOHandler provided does not have the `load` method implemented.");let s=await e.load(),r=s.modelTopology;r.model_config!=null&&(r=r.model_config);let a=n.strict==null?!0:n.strict,o=s.weightData!=null&&s.weightSpecs!=null&&a,i=Ms(bc(r),t,o),l=s.trainingConfig;if(l!=null&&i.loadTrainingConfig(l),s.userDefinedMetadata!=null&&i.setUserDefinedMetadata(s.userDefinedMetadata),s.weightData!=null){if(s.weightSpecs==null)throw new G("LayersModel artifacts contains weight data, but not weight specs. Therefore loading of weights cannot proceed.");let{modelWeights:u,optimizerWeights:c}=MP(s.weightData,s.weightSpecs);i.loadWeights(u,a),i.optimizer!=null&&c.length>0&&await i.optimizer.setWeights(c),Z(u),Z(c.map(d=>d.tensor))}return i}function MP(e,t){let n=Tn.decodeWeights(e,t),s={},r=[];return t.forEach(a=>{a.group==="optimizer"?r.push({name:a.name,tensor:n[a.name]}):s[a.name]=n[a.name]}),{modelWeights:s,optimizerWeights:r}}var Ml=class extends wr{constructor(e){super({inputs:[],outputs:[]});if(e=e||{},this.trainable=!0,this.built=!1,this.name=e.name!=null?e.name:Ip("sequential_"),e.layers!=null)for(let t of e.layers)this.add(t)}checkShape(e){if(e.inboundNodes[0].outputTensors[0].shape.some(n=>n<0))throw new G(`Negative dimension size caused by adding layer ${e.name} with input shape [${e.inboundNodes[0].inputTensors[0].shape}]`)}add(e){let t=e instanceof Ml||e instanceof wr,n;if(t){if(n=e,n.outputs.length!==1)throw new G("All layers in a Sequential model should have a single output tensor. For multi-output layers, use the functional API.");if(n.inputs.length!==1)throw new G("All layers in a Sequential model should have a single input tensor. For multi-input layers, use the functional API.")}if(this.outputs.length===0){if(e.inboundNodes.length===0){if(e.batchInputShape==null)throw new G("The first layer in a Sequential model must get an `inputShape` or `batchInputShape` argument.");let s=d3({batchShape:e.batchInputShape,dtype:e.dtype,name:e.name+"_input"});e.apply(s)}if(t)this.outputs=n.outputs,this.inputs=n.inputs;else{if(e.inboundNodes.length!==1)throw new G(`A layer added to a Sequential model must not already be connected somewhere else. LayersModel received layer ${e.name} which has ${e.inboundNodes.length} pre-existing inbound connections.`);if(e.inboundNodes[0].outputTensors.length!==1)throw new G("All layers in a Sequential model should have a single output tensor. For multi-output layers, use the functional API.");this.checkShape(e),this.outputs=[e.inboundNodes[0].outputTensors[0]],this.inputs=c3(this.outputs[0])}this.inboundNodes=[],new Tp({outboundLayer:this,inboundLayers:[],nodeIndices:[],tensorIndices:[],inputTensors:this.inputs,outputTensors:this.outputs,inputMasks:Eo(null,this.inputs.length),outputMasks:[null],inputShapes:this.inputs.map(s=>s.shape),outputShapes:this.outputs[0].shape})}else{let s=e.apply(this.outputs[0]);if(Array.isArray(s))throw new TypeError("All layers in a Sequential model should have a single output tensor. For multi-output layers, use the functional API.");this.checkShape(e),this.outputs=[s],this.inboundNodes[0].outputTensors=this.outputs,this.inboundNodes[0].outputShapes=[this.outputs[0].shape]}this.layers.push(e),this.built=!1}pop(){if(this.layers.length===0)throw new TypeError("There are no layers in the model.");if(this.layers.pop(),this.layers.length===0)this.outputs=[],this.inboundNodes=[],this.outboundNodes=[];else{let e=this.layers.length-1;this.layers[e].outboundNodes=[],this.outputs=[this.layers[e].output],this.inboundNodes[0].outputTensors=this.outputs,this.inboundNodes[0].outputShapes=[this.outputs[0].shape]}}call(e,t){return this.model==null&&this.build(),this.model.call(e,t)}build(e){if(st(e),this.inputs.length===0||this.outputs.length===0)throw new TypeError("Sequential model cannot be built: model is empty. Add some layers first.");this.model=new wr({inputs:this.inputs,outputs:this.outputs[0],name:this.name+"_model"}),this.model.trainable=this.trainable,this.supportsMasking=this.model.supportsMasking,this.inputLayers=this.model.inputLayers,this.inputLayersNodeIndices=this.model.inputLayersNodeIndices,this.inputLayersTensorIndices=this.model.inputLayersTensorIndices,this.outputLayers=this.model.outputLayers,this.outputLayersNodeIndices=this.model.outputLayersNodeIndices,this.outputLayersTensorIndices=this.model.outputLayersTensorIndices,this.nodesByDepth=this.model.nodesByDepth,this.containerNodes=this.model.containerNodes,this.outputNames=this.model.outputNames,this.inputNames=this.model.inputNames,this.built=!0}countParams(){return this.built||this.build(),super.countParams()}summary(e,t,n=console.log){this.built||this.build(),super.summary(e,t,n)}setWeights(e){this.model==null&&this.build(),this.model.setWeights(e)}evaluate(e,t,n={}){if(!this.built)throw new Fs("The model needs to be compiled before being used.");return this.model.evaluate(e,t,n)}async evaluateDataset(e,t){if(!this.built)throw new Fs("The model needs to be compiled before being used.");return this.model.evaluateDataset(e,t)}predict(e,t={}){return this.model==null&&this.build(),this.model.predict(e,t)}predictOnBatch(e){return this.model==null&&this.build(),this.model.predictOnBatch(e)}compile(e){this.build(),this.model.compile(e),this.optimizer_=this.model.optimizer,this.isOptimizerOwned=this.model.isOptimizerOwned,this.loss=this.model.loss,this.metrics=this.model.metrics,this.metricsTensors=this.model.metricsTensors,this.metricsNames=this.model.metricsNames}get optimizer(){return this.model==null?void 0:this.model.optimizer}set optimizer(e){this.model.optimizer=e}async fit(e,t,n={}){if(!this.built)throw new Fs("The model needs to be compiled before being used.");return this.model.fit(e,t,n)}async fitDataset(e,t){if(!this.built)throw new Fs("The model needs to be compiled before being used.");return this.model.fitDataset(e,t)}async trainOnBatch(e,t){return this.model.trainOnBatch(e,t)}static fromConfig(e,t,n={},s=!1){let r,a={};if(t instanceof Array){if(t[0].className==null||t[0].className==="Merge")throw new G("Legacy serialization format not supported yet.");r=t}else I.assert(t.layers!=null,()=>"When the config data for a Sequential model is not an Array, it must be an Object that contains the 'layers' field."),r=t.layers,delete t.layers,a=t;let o=new e(a);if(!(o instanceof Ml))throw new Oe(`Sequential.fromConfig called on non-Sequential input: ${o}`);for(let i of r){let u=Ms(i,void 0,s);s&&u.setFastWeightInitDuringBuild(!0),o.add(u)}return o}set stopTraining(e){if(this.model==null)throw new G("Cannot set the stopTraining property of a sequential model before it is compiled.");this.model.stopTraining=e}get stopTraining(){if(this.model==null)throw new G("Cannot get the stopTraining property of a sequential model before it is compiled.");return this.model.stopTraining}getConfig(){let e=[];for(let t of this.layers){let n={};n.className=t.getClassName(),n.config=t.getConfig(),e.push(n)}return{name:this.name,layers:e}}};Ml.className="Sequential";oe.registerClass(Ml);function zP(e){return new wr(e)}function LP(e){return new Ml(e)}function BP(e,t){return t==null&&(t={}),OP(e,t)}function L3(e){return d3(e)}function WP(e,t){ks.registerCallbackConstructor(e,t)}var _n=class extends oe.Serializable{getConfig(){return{}}},B3=class extends _n{apply(e,t=1){return pO(e,t)}};B3.className="elu";oe.registerClass(B3);var W3=class extends _n{apply(e){return $A(e)}};W3.className="selu";oe.registerClass(W3);var V3=class extends _n{apply(e){return Ys(e)}};V3.className="relu";oe.registerClass(V3);var U3=class extends _n{apply(e){return H(()=>oc(6,Ys(e)))}};U3.className="relu6";oe.registerClass(U3);var H3=class extends _n{apply(e){return e}};H3.className="linear";oe.registerClass(H3);var G3=class extends _n{apply(e){return Bn(e)}};G3.className="sigmoid";oe.registerClass(G3);var j3=class extends _n{apply(e){return mO(e)}};j3.className="hardSigmoid";oe.registerClass(j3);var q3=class extends _n{apply(e){return Tl(e)}};q3.className="softplus";oe.registerClass(q3);var X3=class extends _n{apply(e){return fO(e)}};X3.className="softsign";oe.registerClass(X3);var K3=class extends _n{apply(e){return wl(e)}};K3.className="tanh";oe.registerClass(K3);var Eg=class extends _n{apply(e,t=-1){return Zh(e,t)}};Eg.className="softmax";oe.registerClass(Eg);var Z3=class extends _n{apply(e,t=-1){return vA(e,t)}};Z3.className="logSoftmax";oe.registerClass(Z3);var Y3=class extends _n{apply(e,t=1){return H(()=>z(Bn(z(e,t)),e))}};Y3.className="swish";oe.registerClass(Y3);var J3=class extends _n{apply(e){return H(()=>z(e,wl(Tl(e))))}};J3.className="mish";oe.registerClass(J3);function Jr(e){return e.getClassName()}function Rg(e,t={}){return pc(e,oe.SerializationMap.getMap().classNameMap,t,"activation")}function Qr(e){if(e==null){let t={};return t.className="linear",t.config={},Rg(t)}if(typeof e=="string"){let t={};return t.className=e,t.config={},Rg(t)}else return e instanceof _n?e:Rg(e)}function _g(e){if(e!=null&&typeof e!="object")throw new Error(`Argument to L1L2 regularizer's constructor is expected to be an object, but received: ${e}`)}var Q3=class extends oe.Serializable{},kc=class extends Q3{constructor(e){super();_g(e),this.l1=e==null||e.l1==null?.01:e.l1,this.l2=e==null||e.l2==null?.01:e.l2,this.hasL1=this.l1!==0,this.hasL2=this.l2!==0}apply(e){return H(()=>{let t=Dt([1]);return this.hasL1&&(t=ae(t,ve(z(this.l1,Wt(e))))),this.hasL2&&(t=ae(t,ve(z(this.l2,gc(e))))),U(t,[])})}getConfig(){return{l1:this.l1,l2:this.l2}}static fromConfig(e,t){return new e({l1:t.l1,l2:t.l2})}};kc.className="L1L2";oe.registerClass(kc);function VP(e){return _g(e),new kc({l1:e!=null?e.l1:null,l2:0})}function UP(e){return _g(e),new kc({l2:e!=null?e.l2:null,l1:0})}var ev={l1l2:"L1L2"};function lt(e){return XA(e)}function tv(e,t={}){return pc(e,oe.SerializationMap.getMap().classNameMap,t,"regularizer")}function vt(e){if(e==null)return null;if(typeof e=="string"){let n={className:e in ev?ev[e]:e,config:{}};return tv(n)}else return e instanceof Q3?e:tv(e)}var $g=class extends Xe{constructor(e){super(e==null?{}:e);this.supportsMasking=!0,e!=null&&(this.maxValue=e.maxValue)}call(e,t){e=ze(e);let n=Ys(e);return this.maxValue!=null&&(n=Wn(n,0,this.maxValue)),n}computeOutputShape(e){return e}getConfig(){let e={maxValue:this.maxValue},t=super.getConfig();return Object.assign(e,t),e}};$g.className="ReLU";oe.registerClass($g);var Fg=class extends Xe{constructor(e){super(e==null?{}:e);this.DEFAULT_ALPHA=.3,e==null&&(e={}),this.alpha=e.alpha==null?this.DEFAULT_ALPHA:e.alpha}call(e,t){let n=ze(e);return Lh(n,this.alpha)}computeOutputShape(e){return e}getConfig(){let e={alpha:this.alpha},t=super.getConfig();return Object.assign(e,t),e}};Fg.className="LeakyReLU";oe.registerClass(Fg);var Dg=class extends Xe{constructor(e){super(e==null?{}:e);if(this.DEFAULT_ALPHA_INITIALIZER="zeros",e==null&&(e={}),this.supportsMasking=!0,this.alphaInitializer=bt(e.alphaInitializer||this.DEFAULT_ALPHA_INITIALIZER),this.alphaRegularizer=vt(e.alphaRegularizer),this.alphaConstraint=Gt(e.alphaConstraint),e.sharedAxes==null)this.sharedAxes=null;else if(Array.isArray(e.sharedAxes))this.sharedAxes=e.sharedAxes;else if(typeof e.sharedAxes=="number")this.sharedAxes=[e.sharedAxes];else throw new G(`Expected sharedAxes to be a number or an array of numbers, but got ${e.sharedAxes}`)}build(e){e=st(e);let t=e.slice(1);if(this.sharedAxes!=null)for(let s of this.sharedAxes)t[s-1]=1;this.alpha=this.addWeight("alpha",t,"float32",this.alphaInitializer,this.alphaRegularizer,!0,this.alphaConstraint);let n={};if(this.sharedAxes!=null)for(let s=1;s<e.length;++s)n[s]=e[s];this.inputSpec=[new Pt({ndim:e.length,axes:n})],this.built=!0}call(e,t){return e=ze(e),qh(e,this.alpha.read())}getConfig(){let e={alphaInitializer:Ct(this.alphaInitializer),alphaRegularizer:lt(this.alphaRegularizer),alphaConstraint:Ht(this.alphaConstraint),sharedAxes:this.sharedAxes},t=super.getConfig();return Object.assign(e,t),e}};Dg.className="PReLU";oe.registerClass(Dg);var Og=class extends Xe{constructor(e){super(e==null?{}:e);if(this.DEFAULT_ALPHA=1,e==null&&(e={}),e.alpha!=null&&e.alpha!==this.DEFAULT_ALPHA)throw new Oe(`Non-default alpha value (${e.alpha}) is not supported by the ELU layer yet.`);this.alpha=e.alpha==null?this.DEFAULT_ALPHA:e.alpha}call(e,t){let n=ze(e);return rc(n)}computeOutputShape(e){return e}getConfig(){let e={alpha:this.alpha},t=super.getConfig();return Object.assign(e,t),e}};Og.className="ELU";oe.registerClass(Og);var Pg=class extends Xe{constructor(e){super(e==null?{}:e);this.DEFAULT_THETA=1,e==null&&(e={}),this.theta=e.theta==null?this.DEFAULT_THETA:e.theta}call(e,t){let n=ze(e);return z(n,ue(Vn(n,this.theta),"float32"))}computeOutputShape(e){return e}getConfig(){let e={theta:this.theta},t=super.getConfig();return Object.assign(e,t),e}};Pg.className="ThresholdedReLU";oe.registerClass(Pg);var Mg=class extends Xe{constructor(e){super(e==null?{}:e);this.DEFAULT_AXIS=1,e==null&&(e={}),this.softmax=new Eg().apply,this.axis=e.axis==null?this.DEFAULT_AXIS:e.axis}call(e,t){let n=ze(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}};Mg.className="Softmax";oe.registerClass(Mg);function zl(e,t,n){if(typeof e=="number")return Eo(e,t);if(e.length!==t)throw new G(`The ${n} argument must be an integer or tuple of ${t} integers. Received: ${e.length} elements.`);for(let s=0;s<t;++s){let r=e[s];if(!uO(r))throw new G(`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 zs(e,t,n,s,r=1){if(e==null)return e;let a=t+(t-1)*(r-1),o;return n==="same"?o=e:o=e-a+1,Math.floor((o+s-1)/s)}function nr(e,t,n,s){if(e==null)return null;if(s==="valid")e=e*t+Zr([n-t,0]);else if(s==="same")e=e*t;else throw new G(`Unsupport padding mode: ${s}.`);return e}function zg(e,t){return H(()=>($t(t),t==="channelsFirst"?je(e,[0,2,3,1]):e))}function nv(e,t){return H(()=>($t(t),t==="channelsFirst"?je(e,[0,2,3,4,1]):e))}function HP(e,t,n,s=1,r="valid",a,o=1){return H(()=>{if(a==null&&(a=$s()),$t(a),e.shape.length!==3)throw new G(`The input of a conv1dWithBias operation should be 3, but is ${e.shape.length} instead.`);if(t.shape.length!==3)throw new G(`The kernel for a conv1dWithBias operation should be 3, but is ${t.shape.length} instead`);if(n!=null&&n.shape.length!==1)throw new G(`The bias for a conv1dWithBias operation should be 1, but is ${t.shape.length} instead`);if(a==="channelsFirst"&&(e=je(e,[0,2,1])),r==="causal")throw new Oe("The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.");let i=pA(e,t,s,r==="same"?"same":"valid","NWC",o);return n!=null&&(i=Os(i,n)),i})}function sv(e,t,n,s=[1,1],r="valid",a,o,i=null){return H(()=>{if(a==null&&(a=$s()),$t(a),e.rank!==3&&e.rank!==4)throw new G(`conv2dWithBiasActivation expects input to be of rank 3 or 4, but received ${e.rank}.`);if(t.rank!==3&&t.rank!==4)throw new G(`conv2dWithBiasActivation expects kernel to be of rank 3 or 4, but received ${e.rank}.`);let l=zg(e,a);if(r==="causal")throw new Oe("The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.");return l=qr.conv2d({x:l,filter:t,strides:s,pad:r==="same"?"same":"valid",dilations:o,dataFormat:"NHWC",bias:n,activation:i}),a==="channelsFirst"&&(l=je(l,[0,3,1,2])),l})}function GP(e,t,n,s=[1,1,1],r="valid",a,o){return H(()=>{if(a==null&&(a=$s()),$t(a),e.rank!==4&&e.rank!==5)throw new G(`conv3dWithBias expects input to be of rank 4 or 5, but received ${e.rank}.`);if(t.rank!==4&&t.rank!==5)throw new G(`conv3dWithBias expects kernel to be of rank 4 or 5, but received ${e.rank}.`);let i=nv(e,a);if(r==="causal")throw new Oe("The support for CAUSAL padding mode in conv3dWithBias is not implemented yet.");return i=AA(i,t,s,r==="same"?"same":"valid","NDHWC",o),n!=null&&(i=Os(i,n)),a==="channelsFirst"&&(i=je(i,[0,4,1,2,3])),i})}var Lg=class extends Xe{constructor(e,t){super(t);if(this.bias=null,this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_BIAS_INITIALIZER="zeros",Lg.verifyArgs(t),this.rank=e,Zt(this.rank,"rank"),this.rank!==1&&this.rank!==2&&this.rank!==3)throw new Oe(`Convolution layer for rank other than 1, 2, or 3 (${this.rank}) is not implemented yet.`);if(this.kernelSize=zl(t.kernelSize,e,"kernelSize"),this.strides=zl(t.strides==null?1:t.strides,e,"strides"),this.padding=t.padding==null?"valid":t.padding,hs(this.padding),this.dataFormat=t.dataFormat==null?"channelsLast":t.dataFormat,$t(this.dataFormat),this.activation=Qr(t.activation),this.useBias=t.useBias==null?!0:t.useBias,this.biasInitializer=bt(t.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.biasConstraint=Gt(t.biasConstraint),this.biasRegularizer=vt(t.biasRegularizer),this.activityRegularizer=vt(t.activityRegularizer),this.dilationRate=zl(t.dilationRate==null?1:t.dilationRate,e,"dilationRate"),this.rank===1&&Array.isArray(this.dilationRate)&&this.dilationRate.length!==1)throw new G(`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 G(`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 G(`dilationRate must be a number or array of three numbers for 3D convolution, but received ${JSON.stringify(this.dilationRate)}`)}}static verifyArgs(e){if(Qs("kernelSize"in e,"required key 'kernelSize' not in config"),typeof e.kernelSize!="number"&&!ZA(e.kernelSize,"number",1,3))throw new G(`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:Jr(this.activation),useBias:this.useBias,biasInitializer:Ct(this.biasInitializer),biasRegularizer:lt(this.biasRegularizer),activityRegularizer:lt(this.activityRegularizer),biasConstraint:Ht(this.biasConstraint)},t=super.getConfig();return Object.assign(e,t),e}},Ic=class extends Lg{constructor(e,t){super(e,t);this.kernel=null,Ic.verifyArgs(t),this.filters=t.filters,Zt(this.filters,"filters"),this.kernelInitializer=bt(t.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.kernelConstraint=Gt(t.kernelConstraint),this.kernelRegularizer=vt(t.kernelRegularizer)}build(e){e=st(e);let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null)throw new G(`The channel dimension of the input should be defined. Found ${e[t]}`);let n=e[t],s=this.kernelSize.concat([n,this.filters]);this.kernel=this.addWeight("kernel",s,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 H(()=>{e=ze(e);let n,s=this.bias==null?null:this.bias.read(),r=jb(this.activation.getClassName());if(r!=null&&this.rank===2)n=sv(e,this.kernel.read(),s,this.strides,this.padding,this.dataFormat,this.dilationRate,r);else{if(this.rank===1)n=HP(e,this.kernel.read(),s,this.strides[0],this.padding,this.dataFormat,this.dilationRate[0]);else if(this.rank===2)n=sv(e,this.kernel.read(),s,this.strides,this.padding,this.dataFormat,this.dilationRate);else if(this.rank===3)n=GP(e,this.kernel.read(),s,this.strides,this.padding,this.dataFormat,this.dilationRate);else throw new Oe("convolutions greater than 3D are not implemented yet.");this.activation!=null&&(n=this.activation.apply(n))}return n})}computeOutputShape(e){e=st(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 a=zs(n[r],this.kernelSize[r],this.padding,this.strides[r],typeof this.dilationRate=="number"?this.dilationRate:this.dilationRate[r]);t.push(a)}let s=[e[0]];return this.dataFormat==="channelsLast"?(s=s.concat(t),s.push(this.filters)):(s.push(this.filters),s=s.concat(t)),s}getConfig(){let e={filters:this.filters,kernelInitializer:Ct(this.kernelInitializer),kernelRegularizer:lt(this.kernelRegularizer),kernelConstraint:Ht(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 G(`Convolution layer expected config.filters to be a 'number' > 0 but got ${JSON.stringify(e.filters)}`)}},Sc=class extends Ic{constructor(e){super(2,e);Sc.verifyArgs(e)}getConfig(){let e=super.getConfig();return delete e.rank,e}static verifyArgs(e){if(typeof e.kernelSize!="number"&&!ZA(e.kernelSize,"number",1,2))throw new G(`Conv2D expects config.kernelSize to be number or number[] with length 1 or 2, but received ${JSON.stringify(e.kernelSize)}.`)}};Sc.className="Conv2D";oe.registerClass(Sc);var Cc=class extends Ic{constructor(e){super(3,e);Cc.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 G(`Conv3D expects config.kernelSize to be number or [number, number, number], but received ${JSON.stringify(e.kernelSize)}.`)}};Cc.className="Conv3D";oe.registerClass(Cc);var Bg=class extends Sc{constructor(e){super(e);if(this.inputSpec=[new Pt({ndim:4})],this.padding!=="same"&&this.padding!=="valid")throw new G(`Conv2DTranspose currently supports only padding modes 'same' and 'valid', but received padding mode ${this.padding}`)}build(e){if(e=st(e),e.length!==4)throw new G("Input should have rank 4; Received input shape: "+JSON.stringify(e));let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null)throw new G("The channel dimension of the inputs should be defined. Found `None`.");let n=e[t],s=this.kernelSize.concat([this.filters,n]);this.kernel=this.addWeight("kernel",s,"float32",this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[new Pt({ndim:4,axes:{[t]:n}})],this.built=!0}call(e,t){return H(()=>{let n=ze(e);if(n.shape.length!==4)throw new G(`Conv2DTranspose.call() expects input tensor to be rank-4, but received a tensor of rank-${n.shape.length}`);let s=n.shape,r=s[0],a,o;this.dataFormat==="channelsFirst"?(a=2,o=3):(a=1,o=2);let i=s[a],l=s[o],u=this.kernelSize[0],c=this.kernelSize[1],d=this.strides[0],h=this.strides[1],p=nr(i,d,u,this.padding),m=nr(l,h,c,this.padding),f=[r,p,m,this.filters];this.dataFormat!=="channelsLast"&&(n=je(n,[0,2,3,1]));let A=mA(n,this.kernel.read(),f,this.strides,this.padding);return this.dataFormat!=="channelsLast"&&(A=je(A,[0,3,1,2])),this.bias!=null&&(A=Os(A,this.bias.read(),this.dataFormat)),this.activation!=null&&(A=this.activation.apply(A)),A})}computeOutputShape(e){e=st(e);let t=e.slice(),n,s,r;this.dataFormat==="channelsFirst"?(n=1,s=2,r=3):(n=3,s=1,r=2);let a=this.kernelSize[0],o=this.kernelSize[1],i=this.strides[0],l=this.strides[1];return t[n]=this.filters,t[s]=nr(t[s],i,a,this.padding),t[r]=nr(t[r],l,o,this.padding),t}getConfig(){let e=super.getConfig();return delete e.dilationRate,e}};Bg.className="Conv2DTranspose";oe.registerClass(Bg);var Wg=class extends Cc{constructor(e){super(e);if(this.inputSpec=[new Pt({ndim:5})],this.padding!=="same"&&this.padding!=="valid")throw new G(`Conv3DTranspose currently supports only padding modes 'same' and 'valid', but received padding mode ${this.padding}`)}build(e){if(e=st(e),e.length!==5)throw new G("Input should have rank 5; Received input shape: "+JSON.stringify(e));let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null)throw new G("The channel dimension of the inputs should be defined. Found `None`.");let n=e[t],s=this.kernelSize.concat([this.filters,n]);this.kernel=this.addWeight("kernel",s,"float32",this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[new Pt({ndim:5,axes:{[t]:n}})],this.built=!0}call(e,t){return H(()=>{let n=ze(e);if(n.shape.length!==5)throw new G(`Conv3DTranspose.call() expects input tensor to be rank-4, but received a tensor of rank-${n.shape.length}`);let s=n.shape,r=s[0],a,o,i;this.dataFormat==="channelsFirst"?(i=2,a=3,o=4):(i=1,a=2,o=3);let l=s[i],u=s[a],c=s[o],d=this.kernelSize[0],h=this.kernelSize[1],p=this.kernelSize[2],m=this.strides[0],f=this.strides[1],A=this.strides[2],g=nr(l,m,d,this.padding),y=nr(u,f,h,this.padding),x=nr(c,A,p,this.padding),b=[r,g,y,x,this.filters];this.dataFormat!=="channelsLast"&&(n=je(n,[0,2,3,4,1]));let v=Mx(n,this.kernel.read(),b,this.strides,this.padding);return this.dataFormat!=="channelsLast"&&(v=je(v,[0,4,1,2,3])),this.bias!==null&&(v=Os(v,this.bias.read(),this.dataFormat)),this.activation!==null&&(v=this.activation.apply(v)),v})}computeOutputShape(e){e=st(e);let t=e.slice(),n,s,r,a;this.dataFormat==="channelsFirst"?(n=1,s=2,r=3,a=4):(n=4,s=1,r=2,a=3);let o=this.kernelSize[0],i=this.kernelSize[1],l=this.kernelSize[2],u=this.strides[0],c=this.strides[1],d=this.strides[2];return t[n]=this.filters,t[s]=nr(t[s],u,o,this.padding),t[r]=nr(t[r],c,i,this.padding),t[a]=nr(t[a],d,l,this.padding),t}getConfig(){let e=super.getConfig();return delete e.dilationRate,e}};Wg.className="Conv3DTranspose";oe.registerClass(Wg);var rv=class extends Ic{constructor(e,t){super(e,t);if(this.DEFAULT_DEPTHWISE_INITIALIZER="glorotUniform",this.DEFAULT_POINTWISE_INITIALIZER="glorotUniform",this.depthwiseKernel=null,this.pointwiseKernel=null,t.filters==null)throw new G("The `filters` configuration field is required by SeparableConv, but is unspecified.");if(t.kernelInitializer!=null||t.kernelRegularizer!=null||t.kernelConstraint!=null)throw new G("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 G(`SeparableConv${this.rank}D supports only padding modes: 'same' and 'valid', but received ${JSON.stringify(t.padding)}`);this.depthMultiplier=t.depthMultiplier==null?1:t.depthMultiplier,this.depthwiseInitializer=bt(t.depthwiseInitializer||this.DEFAULT_DEPTHWISE_INITIALIZER),this.depthwiseRegularizer=vt(t.depthwiseRegularizer),this.depthwiseConstraint=Gt(t.depthwiseConstraint),this.pointwiseInitializer=bt(t.depthwiseInitializer||this.DEFAULT_POINTWISE_INITIALIZER),this.pointwiseRegularizer=vt(t.pointwiseRegularizer),this.pointwiseConstraint=Gt(t.pointwiseConstraint)}build(e){if(e=st(e),e.length<this.rank+2)throw new G(`Inputs to SeparableConv${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 G(`The channel dimension of the inputs should be defined, but found ${JSON.stringify(e[t])}`);let n=e[t],s=this.kernelSize.concat([n,this.depthMultiplier]),r=[];for(let o=0;o<this.rank;++o)r.push(1);r.push(n*this.depthMultiplier,this.filters);let a=!0;this.depthwiseKernel=this.addWeight("depthwise_kernel",s,"float32",this.depthwiseInitializer,this.depthwiseRegularizer,a,this.depthwiseConstraint),this.pointwiseKernel=this.addWeight("pointwise_kernel",r,"float32",this.pointwiseInitializer,this.pointwiseRegularizer,a,this.pointwiseConstraint),this.useBias?this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,a,this.biasConstraint):this.bias=null,this.inputSpec=[new Pt({ndim:this.rank+2,axes:{[t]:n}})],this.built=!0}call(e,t){return H(()=>{e=ze(e);let n;if(this.rank===1)throw new Oe("1D separable convolution is not implemented yet.");return this.rank===2&&(this.dataFormat==="channelsFirst"&&(e=je(e,[0,2,3,1])),n=ab(e,this.depthwiseKernel.read(),this.pointwiseKernel.read(),this.strides,this.padding,this.dilationRate,"NHWC")),this.useBias&&(n=Os(n,this.bias.read(),this.dataFormat)),this.activation!=null&&(n=this.activation.apply(n)),this.dataFormat==="channelsFirst"&&(n=je(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=lt(this.depthwiseRegularizer),e.pointwiseRegularizer=lt(this.pointwiseRegularizer),e.depthwiseConstraint=Ht(this.depthwiseConstraint),e.pointwiseConstraint=Ht(this.pointwiseConstraint),e}};rv.className="SeparableConv";var Vg=class extends rv{constructor(e){super(2,e)}};Vg.className="SeparableConv2D";oe.registerClass(Vg);var Pp=class extends Ic{constructor(e){super(1,e);Pp.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"&&!ZA(e.kernelSize,"number",1,1))throw new G(`Conv1D expects config.kernelSize to be number or number[] with length 1, but received ${JSON.stringify(e.kernelSize)}.`)}};Pp.className="Conv1D";oe.registerClass(Pp);var Ug=class extends Xe{constructor(e){super(e);typeof e.cropping=="number"?this.cropping=[[e.cropping,e.cropping],[e.cropping,e.cropping]]:typeof e.cropping[0]=="number"?this.cropping=[[e.cropping[0],e.cropping[0]],[e.cropping[1],e.cropping[1]]]:this.cropping=e.cropping,this.dataFormat=e.dataFormat===void 0?"channelsLast":e.dataFormat,this.inputSpec=[{ndim:4}]}computeOutputShape(e){return this.dataFormat==="channelsFirst"?[e[0],e[1],e[2]-this.cropping[0][0]-this.cropping[0][1],e[3]-this.cropping[1][0]-this.cropping[1][1]]:[e[0],e[1]-this.cropping[0][0]-this.cropping[0][1],e[2]-this.cropping[1][0]-this.cropping[1][1],e[3]]}call(e,t){return H(()=>{if(e=ze(e),this.dataFormat==="channelsLast"){let n=fp(e,this.cropping[0][0],e.shape[1]-this.cropping[0][0]-this.cropping[0][1],2);return fp(n,this.cropping[1][0],e.shape[2]-this.cropping[1][1]-this.cropping[1][0],3)}else{let n=fp(e,this.cropping[0][0],e.shape[2]-this.cropping[0][0]-this.cropping[0][1],3);return fp(n,this.cropping[1][0],e.shape[3]-this.cropping[1][1]-this.cropping[1][0],4)}})}getConfig(){let e={cropping:this.cropping,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}};Ug.className="Cropping2D";oe.registerClass(Ug);var Hg=class extends Xe{constructor(e){super(e);this.DEFAULT_SIZE=[2,2],this.inputSpec=[{ndim:4}],this.size=e.size==null?this.DEFAULT_SIZE:e.size,this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,$t(this.dataFormat),this.interpolation=e.interpolation==null?"nearest":e.interpolation,oO(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 H(()=>{let n=ze(e),s=n.shape;if(this.dataFormat==="channelsFirst"){n=je(n,[0,2,3,1]);let r=this.size[0]*s[2],a=this.size[1]*s[3],o=this.interpolation==="nearest"?Re.resizeNearestNeighbor(n,[r,a]):Re.resizeBilinear(n,[r,a]);return je(o,[0,3,1,2])}else{let r=this.size[0]*s[1],a=this.size[1]*s[2];return this.interpolation==="nearest"?Re.resizeNearestNeighbor(n,[r,a]):Re.resizeBilinear(n,[r,a])}})}getConfig(){let e={size:this.size,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}};Hg.className="UpSampling2D";oe.registerClass(Hg);function jP(e,t,n=[1,1],s="valid",r,a){return H(()=>{r==null&&(r=$s()),$t(r);let o=zg(e,r);if(e.rank!==4)throw new G(`Input for depthwiseConv2d is required to be 4-D, but is instead ${e.rank}-D`);if(t.rank!==4)throw new G(`depthwiseKernel is required to be 4-D, but is instead ${t.rank}-D`);return o=sc(o,t,n,s==="same"?"same":"valid","NHWC",a),r==="channelsFirst"&&(o=je(o,[0,3,1,2])),o})}var Gg=class extends Lg{constructor(e){super(2,e);this.depthwiseKernel=null,this.depthMultiplier=e.depthMultiplier==null?1:e.depthMultiplier,this.depthwiseInitializer=bt(e.depthwiseInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.depthwiseConstraint=Gt(e.depthwiseConstraint),this.depthwiseRegularizer=vt(e.depthwiseRegularizer)}build(e){if(e=st(e),e.length<4)throw new G(`Inputs to DepthwiseConv2D should have rank 4. Received input shape: ${JSON.stringify(e)}.`);let t=this.dataFormat==="channelsFirst"?1:3;if(e[t]==null||e[t]<0)throw new G(`The channel dimension of the inputs to DepthwiseConv2D should be defined, but is not (${e[t]}).`);let n=e[t],s=[this.kernelSize[0],this.kernelSize[1],n,this.depthMultiplier];this.depthwiseKernel=this.addWeight("depthwise_kernel",s,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 H(()=>{e=ze(e);let n=jP(e,this.depthwiseKernel.read(),this.strides,this.padding,this.dataFormat,null);return this.useBias&&(n=Os(n,this.bias.read(),this.dataFormat)),this.activation!=null&&(n=this.activation.apply(n)),n})}computeOutputShape(e){e=st(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],n=this.dataFormat==="channelsFirst"?e[3]:e[2],s=this.dataFormat==="channelsFirst"?e[1]*this.depthMultiplier:e[3]*this.depthMultiplier,r=zs(t,this.kernelSize[0],this.padding,this.strides[0]),a=zs(n,this.kernelSize[1],this.padding,this.strides[1]);return this.dataFormat==="channelsFirst"?[e[0],s,r,a]:[e[0],r,a,s]}getConfig(){let e=super.getConfig();return e.depthMultiplier=this.depthMultiplier,e.depthwiseInitializer=Ct(this.depthwiseInitializer),e.depthwiseRegularizer=lt(this.depthwiseRegularizer),e.depthwiseConstraint=Ht(this.depthwiseRegularizer),e}};Gg.className="DepthwiseConv2D";oe.registerClass(Gg);function av(e,t,n,s){if(Array.isArray(e)){if(t!=null||n!=null)throw new G("When inputs is an array, neither initialState or constants should be provided");s!=null&&(n=e.slice(e.length-s,e.length),e=e.slice(0,e.length-s)),e.length>1&&(t=e.slice(1,e.length)),e=e[0]}function r(a){return a==null||Array.isArray(a)?a:[a]}return t=r(t),n=r(n),{inputs:e,initialState:t,constants:n}}function ov(e,t,n,s=!1,r,a,o=!1,i=!1){return H(()=>{let l=t.shape.length;if(l<3)throw new G(`Input should be at least 3D, but is ${l}D.`);let u=[1,0].concat(Ds(2,l));if(t=je(t,u),a!=null)throw new Oe("The rnn() functoin of the deeplearn.js backend does not support constants yet.");o&&console.warn("Backend rnn(): the unroll = true option is not applicable to the imperative deeplearn.js backend."),r!=null&&(r=ue(ue(r,"bool"),"float32"),r.rank===l-1&&(r=Ft(r,-1)),r=je(r,u)),s&&(t=cs(t,0),r!=null&&(r=cs(r,0)));let c=[],d,h=n,p=t.shape[0],m=ds(t),f;r!=null&&(f=ds(r));for(let g=0;g<p;++g){let y=m[g],x=H(()=>e(y,h));if(r==null)d=x[0],h=x[1];else{let b=H(()=>{let v=f[g],k=Ae(us(v),v),w=ae(z(x[0],v),z(h[0],k)),C=h.map((E,P)=>ae(z(x[1][P],v),z(E,k)));return{output:w,newStates:C}});d=b.output,h=b.newStates}i&&c.push(d)}let A;return i&&(A=Nn(c,1)),[d,A,h]})}var sr=class extends Xe{constructor(e){super(e);let t;if(e.cell==null)throw new G("cell property is missing for the constructor of RNN.");if(Array.isArray(e.cell)?t=new Lp({cells:e.cell}):t=e.cell,t.stateSize==null)throw new G("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 Pt({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 Ds(0,e).map(t=>null)}else return this.states_}setStates(e){this.states_=e}computeOutputShape(e){pg(e)&&(e=e[0]),e=e;let t=this.cell.stateSize;Array.isArray(t)||(t=[t]);let n=t[0],s;if(this.returnSequences?s=[e[0],e[1],n]:s=[e[0],n],this.returnState){let r=[];for(let a of t)r.push([e[0],a]);return[s].concat(r)}else return s}computeMask(e,t){return H(()=>{Array.isArray(t)&&(t=t[0]);let n=this.returnSequences?t:null;if(this.returnState){let s=this.states.map(r=>null);return[n].concat(s)}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){let t=null;if(this.numConstants!=null)throw new Oe("Constants support is not implemented in RNN yet.");pg(e)&&(e=e[0]),e=e;let n=this.stateful?e[0]:null,s=e.slice(2);this.inputSpec[0]=new Pt({shape:[n,null,...s]});let r=[e[0]].concat(e.slice(2));if(t!=null)throw new Oe("Constants support is not implemented in RNN yet.");this.cell.build(r);let a;if(Array.isArray(this.cell.stateSize)?a=this.cell.stateSize:a=[this.cell.stateSize],this.stateSpec!=null){if(!I.arraysEqual(this.stateSpec.map(o=>o.shape[o.shape.length-1]),a))throw new G(`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=a.map(o=>new Pt({shape:[null,o]}));this.stateful&&this.resetStates()}resetStates(e,t=!1){H(()=>{if(!this.stateful)throw new br("Cannot call resetStates() on an RNN Layer that is not stateful.");let n=this.inputSpec[0].shape[0];if(n==null)throw new G("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(s=>Dt([n,s])):this.states_=[Dt([n,this.cell.stateSize])];else if(e==null)Z(this.states_),this.keptStates!=null&&(Z(this.keptStates),this.keptStates=[]),Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(s=>Dt([n,s])):this.states_[0]=Dt([n,this.cell.stateSize]);else{if(Array.isArray(e)||(e=[e]),e.length!==this.states_.length)throw new G(`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()):Z(this.states_);for(let s=0;s<this.states_.length;++s){let r=e[s],a=Array.isArray(this.cell.stateSize)?this.cell.stateSize[s]:this.cell.stateSize,o=[n,a];if(!I.arraysEqual(r.shape,o))throw new G(`State ${s} is incompatible with layer ${this.name}: expected shape=${o}, received shape=${r.shape}`);this.states_[s]=r}}this.states_=this.states_.map(s=>Kt(s.clone()))})}apply(e,t){let n=t==null?null:t.initialState,s=t==null?null:t.constants;t==null&&(t={});let r=av(e,n,s,this.numConstants);e=r.inputs,n=r.initialState,s=r.constants;let a=[],o=[];if(n!=null){t.initialState=n,a=a.concat(n),this.stateSpec=[];for(let l of n)this.stateSpec.push(new Pt({shape:l.shape}));o=o.concat(this.stateSpec)}if(s!=null&&(t.constants=s,a=a.concat(s),this.numConstants=s.length),a[0]instanceof Ps){let l=[e].concat(a),u=this.inputSpec.concat(o),c=this.inputSpec;this.inputSpec=u;let d=super.apply(l,t);return this.inputSpec=c,d}else return super.apply(e,t)}call(e,t){return H(()=>{let n=t==null?null:t.mask,s=t==null?null:t.training,r=t==null?null:t.initialState;e=ze(e),r==null&&(this.stateful?r=this.states_:r=this.getInitialState(e));let a=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1;if(r.length!==a)throw new G(`RNN Layer has ${a} 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 o={training:s},l=ov((p,m)=>{let f=this.cell.call([p].concat(m),o);return[f[0],f.slice(1)]},e,r,this.goBackwards,n,null,this.unroll,this.returnSequences),u=l[0],c=l[1],d=l[2];this.stateful&&this.resetStates(d,s);let h=this.returnSequences?c:u;return this.returnState?[h].concat(d):h})}getInitialState(e){return H(()=>{let t=Dt(e.shape);return t=ve(t,[1,2]),t=Ac(t),Array.isArray(this.cell.stateSize)?this.cell.stateSize.map(n=>n>1?rg(t,[1,n]):t):this.cell.stateSize>1?[rg(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()===sr.className&&(t.cell={className:this.cell.getClassName(),config:n}),Object.assign({},n,e,t)}static fromConfig(e,t,n={}){let s=t.cell,r=Ms(s,n);return new e(Object.assign(t,{cell:r}))}};sr.className="RNN";oe.registerClass(sr);var Tc=class extends Xe{},Mp=class extends Tc{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,Zt(this.units,"units"),this.activation=Qr(e.activation==null?this.DEFAULT_ACTIVATION:e.activation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=bt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=bt(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=bt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelRegularizer=vt(e.kernelRegularizer),this.recurrentRegularizer=vt(e.recurrentRegularizer),this.biasRegularizer=vt(e.biasRegularizer),this.kernelConstraint=Gt(e.kernelConstraint),this.recurrentConstraint=Gt(e.recurrentConstraint),this.biasConstraint=Gt(e.biasConstraint),this.dropout=Fl([1,Zr([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=Fl([1,Zr([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.stateSize=this.units,this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){e=st(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 H(()=>{if(e=e,e.length!==2)throw new G(`SimpleRNNCell expects 2 input Tensors, got ${e.length}.`);let n=e[1];e=e[0];let s=t.training==null?!1:t.training;0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=ea({ones:()=>us(e),rate:this.dropout,training:s})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=ea({ones:()=>us(n),rate:this.recurrentDropout,training:s}));let r,a=this.dropoutMask,o=this.recurrentDropoutMask;a!=null?r=er(z(e,a),this.kernel.read()):r=er(e,this.kernel.read()),this.bias!=null&&(r=Os(r,this.bias.read())),o!=null&&(n=z(n,o));let i=ae(r,er(n,this.recurrentKernel.read()));return this.activation!=null&&(i=this.activation.apply(i)),[i,i]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:Jr(this.activation),useBias:this.useBias,kernelInitializer:Ct(this.kernelInitializer),recurrentInitializer:Ct(this.recurrentInitializer),biasInitializer:Ct(this.biasInitializer),kernelRegularizer:lt(this.kernelRegularizer),recurrentRegularizer:lt(this.recurrentRegularizer),biasRegularizer:lt(this.biasRegularizer),activityRegularizer:lt(this.activityRegularizer),kernelConstraint:Ht(this.kernelConstraint),recurrentConstraint:Ht(this.recurrentConstraint),biasConstraint:Ht(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout};return Object.assign({},e,t)}};Mp.className="SimpleRNNCell";oe.registerClass(Mp);var jg=class extends sr{constructor(e){e.cell=new Mp(e);super(e)}call(e,t){return H(()=>{this.cell.dropoutMask!=null&&(Z(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(Z(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=t==null?null:t.mask,s=t==null?null:t.training,r=t==null?null:t.initialState;return super.call(e,{mask:n,training:s,initialState:r})})}static fromConfig(e,t){return new e(t)}};jg.className="SimpleRNN";oe.registerClass(jg);var zp=class extends Tc{constructor(e){super(e);if(this.DEFAULT_ACTIVATION="tanh",this.DEFAULT_RECURRENT_ACTIVATION="hardSigmoid",this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_RECURRENT_INITIALIZER="orthogonal",this.DEFAULT_BIAS_INITIALIZER="zeros",e.resetAfter)throw new G("GRUCell does not support reset_after parameter set to true.");this.units=e.units,Zt(this.units,"units"),this.activation=Qr(e.activation===void 0?this.DEFAULT_ACTIVATION:e.activation),this.recurrentActivation=Qr(e.recurrentActivation===void 0?this.DEFAULT_RECURRENT_ACTIVATION:e.recurrentActivation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=bt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=bt(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=bt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelRegularizer=vt(e.kernelRegularizer),this.recurrentRegularizer=vt(e.recurrentRegularizer),this.biasRegularizer=vt(e.biasRegularizer),this.kernelConstraint=Gt(e.kernelConstraint),this.recurrentConstraint=Gt(e.recurrentConstraint),this.biasConstraint=Gt(e.biasConstraint),this.dropout=Fl([1,Zr([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=Fl([1,Zr([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.implementation=e.implementation,this.stateSize=this.units,this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){e=st(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 H(()=>{if(e=e,e.length!==2)throw new G(`GRUCell expects 2 input Tensors (inputs, h, c), got ${e.length}.`);let n=t.training==null?!1:t.training,s=e[1];e=e[0],0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=ea({ones:()=>us(e),rate:this.dropout,training:n,count:3})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=ea({ones:()=>us(s),rate:this.recurrentDropout,training:n,count:3}));let r=this.dropoutMask,a=this.recurrentDropoutMask,o,i,l;0<this.dropout&&this.dropout<1&&(e=z(e,r[0]));let u=er(e,this.kernel.read());this.useBias&&(u=Os(u,this.bias.read())),0<this.recurrentDropout&&this.recurrentDropout<1&&(s=z(s,a[0]));let c=this.recurrentKernel.read(),[d,h]=nn(c,[2*this.units,this.units],c.rank-1),p=er(s,d),[m,f,A]=nn(u,3,u.rank-1),[g,y]=nn(p,2,p.rank-1);o=this.recurrentActivation.apply(ae(m,g)),i=this.recurrentActivation.apply(ae(f,y));let x=er(z(i,s),h);l=this.activation.apply(ae(A,x));let b=ae(z(o,s),z(ae(1,St(o)),l));return[b,b]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:Jr(this.activation),recurrentActivation:Jr(this.recurrentActivation),useBias:this.useBias,kernelInitializer:Ct(this.kernelInitializer),recurrentInitializer:Ct(this.recurrentInitializer),biasInitializer:Ct(this.biasInitializer),kernelRegularizer:lt(this.kernelRegularizer),recurrentRegularizer:lt(this.recurrentRegularizer),biasRegularizer:lt(this.biasRegularizer),activityRegularizer:lt(this.activityRegularizer),kernelConstraint:Ht(this.kernelConstraint),recurrentConstraint:Ht(this.recurrentConstraint),biasConstraint:Ht(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation,resetAfter:!1};return Object.assign({},e,t)}};zp.className="GRUCell";oe.registerClass(zp);var qg=class extends sr{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 zp(e);super(e)}call(e,t){return H(()=>{this.cell.dropoutMask!=null&&(Z(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(Z(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=t==null?null:t.mask,s=t==null?null:t.training,r=t==null?null:t.initialState;return super.call(e,{mask:n,training:s,initialState:r})})}static fromConfig(e,t){return t.implmentation===0&&(t.implementation=1),new e(t)}};qg.className="GRU";oe.registerClass(qg);var Nc=class extends Tc{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,Zt(this.units,"units"),this.activation=Qr(e.activation===void 0?this.DEFAULT_ACTIVATION:e.activation),this.recurrentActivation=Qr(e.recurrentActivation===void 0?this.DEFAULT_RECURRENT_ACTIVATION:e.recurrentActivation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=bt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=bt(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=bt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.unitForgetBias=e.unitForgetBias,this.kernelRegularizer=vt(e.kernelRegularizer),this.recurrentRegularizer=vt(e.recurrentRegularizer),this.biasRegularizer=vt(e.biasRegularizer),this.kernelConstraint=Gt(e.kernelConstraint),this.recurrentConstraint=Gt(e.recurrentConstraint),this.biasConstraint=Gt(e.biasConstraint),this.dropout=Fl([1,Zr([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=Fl([1,Zr([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.implementation=e.implementation,this.stateSize=[this.units,this.units],this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){var t;e=st(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 s;if(this.useBias){if(this.unitForgetBias){let r=this.biasInitializer,a=this.units;s=new(t=class extends ws{apply(i,l){let u=r.apply([a]),c=new Ap().apply([a]),d=r.apply([a*2]);return t3(t3(u,c),d)}},t.className="CustomInit",t)}else s=this.biasInitializer;this.bias=this.addWeight("bias",[this.units*4],null,s,this.biasRegularizer,!0,this.biasConstraint)}else this.bias=null;this.built=!0}call(e,t){return H(()=>{let n=t.training==null?!1:t.training;if(e=e,e.length!==3)throw new G(`LSTMCell expects 3 input Tensors (inputs, h, c), got ${e.length}.`);let s=e[1],r=e[2];e=e[0],0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=ea({ones:()=>us(e),rate:this.dropout,training:n,count:4})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=ea({ones:()=>us(s),rate:this.recurrentDropout,training:n,count:4}));let a=this.dropoutMask,o=this.recurrentDropoutMask,i,l,u,c;0<this.dropout&&this.dropout<1&&(e=z(e,a[0]));let d=er(e,this.kernel.read());0<this.recurrentDropout&&this.recurrentDropout<1&&(s=z(s,o[0])),d=ae(d,er(s,this.recurrentKernel.read())),this.useBias&&(d=Os(d,this.bias.read()));let[h,p,m,f]=nn(d,4,d.rank-1);i=this.recurrentActivation.apply(h),l=this.recurrentActivation.apply(p),u=ae(z(l,r),z(i,this.activation.apply(m))),c=this.recurrentActivation.apply(f);let A=z(c,this.activation.apply(u));return[A,A,u]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:Jr(this.activation),recurrentActivation:Jr(this.recurrentActivation),useBias:this.useBias,kernelInitializer:Ct(this.kernelInitializer),recurrentInitializer:Ct(this.recurrentInitializer),biasInitializer:Ct(this.biasInitializer),unitForgetBias:this.unitForgetBias,kernelRegularizer:lt(this.kernelRegularizer),recurrentRegularizer:lt(this.recurrentRegularizer),biasRegularizer:lt(this.biasRegularizer),activityRegularizer:lt(this.activityRegularizer),kernelConstraint:Ht(this.kernelConstraint),recurrentConstraint:Ht(this.recurrentConstraint),biasConstraint:Ht(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation};return Object.assign({},e,t)}};Nc.className="LSTMCell";oe.registerClass(Nc);var Xg=class extends sr{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 Nc(e);super(e)}call(e,t){return H(()=>{this.cell.dropoutMask!=null&&(Z(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(Z(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=t==null?null:t.mask,s=t==null?null:t.training,r=t==null?null:t.initialState;return super.call(e,{mask:n,training:s,initialState:r})})}static fromConfig(e,t){return t.implmentation===0&&(t.implementation=1),new e(t)}};Xg.className="LSTM";oe.registerClass(Xg);var Lp=class extends Tc{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 H(()=>{e=e;let n=e.slice(1),s=[];for(let o of this.cells.slice().reverse())Array.isArray(o.stateSize)?s.push(n.splice(0,o.stateSize.length)):s.push(n.splice(0,1));s.reverse();let r=[],a;for(let o=0;o<this.cells.length;++o){let i=this.cells[o];n=s[o],o===0?a=[e[0]].concat(n):a=[a[0]].concat(n),a=i.call(a,t),r.push(a.slice(1))}n=[];for(let o of r.slice().reverse())n.push(...o);return[a[0]].concat(n)})}build(e){pg(e)&&(e=e[0]),e=e;let t;this.cells.forEach((n,s)=>{$o(`RNNCell_${s}`,()=>{n.build(e),Array.isArray(n.stateSize)?t=n.stateSize[0]:t=n.stateSize,e=[e[0],t]})}),this.built=!0}getConfig(){let e=super.getConfig(),t=r=>({className:r.getClassName(),config:r.getConfig()}),s={cells:this.cells.map(t)};return Object.assign({},e,s)}static fromConfig(e,t,n={}){let s=[];for(let r of t.cells)s.push(Ms(r,n));return new e({cells:s})}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 fg(e)}setWeights(e){let t=[];for(let n of this.cells){let s=n.weights.length,r=e.splice(s);for(let a=0;a<n.weights.length;++a)t.push([n.weights[a],r[a]])}mg(t)}};Lp.className="StackedRNNCells";oe.registerClass(Lp);function ea(e){let{ones:t,rate:n,training:s=!1,count:r=1}=e,a=()=>s3(t(),n),o=()=>yc(a,t,s);return!r||r<=1?Kt(o().clone()):Array(r).fill(void 0).map(o).map(l=>Kt(l.clone()))}var qP=function(e,t){var n={};for(var s in e)Object.prototype.hasOwnProperty.call(e,s)&&t.indexOf(s)<0&&(n[s]=e[s]);if(e!=null&&typeof Object.getOwnPropertySymbols=="function")for(var r=0,s=Object.getOwnPropertySymbols(e);r<s.length;r++)t.indexOf(s[r])<0&&Object.prototype.propertyIsEnumerable.call(e,s[r])&&(n[s[r]]=e[s[r]]);return n},iv=class extends sr{constructor(e){if(e.unroll)throw new Oe("Unrolling is not possible with convolutional RNNs.");if(Array.isArray(e.cell))throw new Oe("It is not possible at the moment to stack convolutional cells.");super(e);this.inputSpec=[new Pt({ndim:5})]}call(e,t){return H(()=>{if(this.cell.dropoutMask!=null&&(Z(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(Z(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null),t&&t.constants)throw new G("ConvRNN2D cell does not support constants");let n=t==null?null:t.mask,s=t==null?null:t.training,r=t==null?null:t.initialState;return super.call(e,{mask:n,training:s,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 H(()=>{let{stateSize:t}=this.cell,n=e.shape,s=this.computeSingleOutputShape(n),r=[s[0],...s.slice(2)],a=Dt(r);return Array.isArray(t)?Array(t.length).fill(a):[a]})}resetStates(e,t=!1){H(()=>{if(!this.stateful)throw new br("Cannot call resetStates() on an RNN Layer that is not stateful.");let n=this.inputSpec[0].shape,s=this.computeSingleOutputShape(n),r=[s[0],...s.slice(2)];if(n[0]==null)throw new G("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(()=>Dt(r)):this.states_=[Dt(r)];else if(e==null)Z(this.states_),this.keptStates!=null&&(Z(this.keptStates),this.keptStates=[]),Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(()=>Dt(r)):this.states_[0]=Dt(r);else{if(Array.isArray(e)||(e=[e]),e.length!==this.states_.length)throw new G(`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()):Z(this.states_);for(let o=0;o<this.states_.length;++o){let i=e[o],l=r;if(!I.arraysEqual(i.shape,l))throw new G(`State ${o} is incompatible with layer ${this.name}: expected shape=${l}, received shape=${i.shape}`);this.states_[o]=i}}this.states_=this.states_.map(o=>Kt(o.clone()))})}computeSingleOutputShape(e){let{dataFormat:t,filters:n,kernelSize:s,padding:r,strides:a,dilationRate:o}=this.cell,i=t==="channelsFirst",l=e[i?3:2],u=e[i?4:3],c=zs(l,s[0],r,a[0],o[0]),d=zs(u,s[1],r,a[1],o[1]);return[...e.slice(0,2),...i?[n,c,d]:[c,d,n]]}};iv.className="ConvRNN2D";var Bp=class extends Nc{constructor(e){let{filters:t,kernelSize:n,strides:s,padding:r,dataFormat:a,dilationRate:o}=e;super(Object.assign({},e,{units:t}));this.filters=t,Zt(this.filters,"filters"),this.kernelSize=zl(n,2,"kernelSize"),this.kernelSize.forEach(i=>Zt(i,"kernelSize")),this.strides=zl(s||1,2,"strides"),this.strides.forEach(i=>Zt(i,"strides")),this.padding=r||"valid",hs(this.padding),this.dataFormat=a||"channelsLast",$t(this.dataFormat),this.dilationRate=zl(o||1,2,"dilationRate"),this.dilationRate.forEach(i=>Zt(i,"dilationRate"))}build(e){var t;e=st(e);let n=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[n]==null)throw new G(`The channel dimension of the input should be defined. Found ${e[n]}`);let s=e[n],r=4,a=this.kernelSize.concat([s,this.filters*r]);this.kernel=this.addWeight("kernel",a,null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint);let o=this.kernelSize.concat([this.filters,this.filters*r]);if(this.recurrentKernel=this.addWeight("recurrent_kernel",o,null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint),this.useBias){let i;if(this.unitForgetBias){let l=this.biasInitializer,u=this.filters;i=new(t=class extends ws{apply(d,h){let p=l.apply([u]),m=Un([u]),f=l.apply([u*2]);return sg([p,m,f])}},t.className="CustomInit",t)}else i=this.biasInitializer;this.bias=this.addWeight("bias",[this.filters*r],null,i,this.biasRegularizer,!0,this.biasConstraint)}this.built=!0}call(e,t){return H(()=>{if(e.length!==3)throw new G(`ConvLSTM2DCell expects 3 input Tensors (inputs, h, c), got ${e.length}.`);let n=t.training||!1,s=e[0],r=e[1],a=e[2],o=4;0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=ea({ones:()=>us(s),rate:this.dropout,training:n,count:o}));let i=this.dropoutMask,l=(Q,ne,te)=>!ne||!ne[te]?Q:z(ne[te],Q),u=l(s,i,0),c=l(s,i,1),d=l(s,i,2),h=l(s,i,3);0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=ea({ones:()=>us(r),rate:this.recurrentDropout,training:n,count:o}));let p=this.recurrentDropoutMask,m=l(r,p,0),f=l(r,p,1),A=l(r,p,2),g=l(r,p,3),y=3,[x,b,v,k]=nn(this.kernel.read(),o,y),[w,C,E,P]=this.useBias?nn(this.bias.read(),o):[null,null,null,null];u=this.inputConv(u,x,w,this.padding),c=this.inputConv(c,b,C,this.padding),d=this.inputConv(d,v,E,this.padding),h=this.inputConv(h,k,P,this.padding);let[R,_,T,O]=nn(this.recurrentKernel.read(),o,y);m=this.recurrentConv(m,R),f=this.recurrentConv(f,_),A=this.recurrentConv(A,T),g=this.recurrentConv(g,O);let W=this.recurrentActivation.apply(ae(u,m)),j=this.recurrentActivation.apply(ae(c,f)),q=ae(z(j,a),z(W,this.activation.apply(ae(d,A)))),X=z(this.recurrentActivation.apply(ae(h,g)),this.activation.apply(q));return[X,X,q]})}getConfig(){let e=super.getConfig(),{units:t}=e,n=qP(e,["units"]),s={filters:this.filters,kernelSize:this.kernelSize,padding:this.padding,dataFormat:this.dataFormat,dilationRate:this.dilationRate,strides:this.strides};return Object.assign({},n,s)}inputConv(e,t,n,s){let r=Hr(e,t,this.strides,s||"valid",this.dataFormat==="channelsFirst"?"NCHW":"NHWC",this.dilationRate);return n?Os(r,n,this.dataFormat):r}recurrentConv(e,t){return Hr(e,t,1,"same",this.dataFormat==="channelsFirst"?"NCHW":"NHWC")}};Bp.className="ConvLSTM2DCell";oe.registerClass(Bp);var Kg=class extends iv{constructor(e){let t=new Bp(e);super(Object.assign({},e,{cell:t}))}static fromConfig(e,t){return new e(t)}};Kg.className="ConvLSTM2D";oe.registerClass(Kg);var Wp=class extends Xe{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 s=0;s<this.noiseShape.length;++s)n.push(this.noiseShape[s]==null?t[s]:this.noiseShape[s]);return n}call(e,t){return H(()=>{this.invokeCallHook(e,t);let n=ze(e);if(0<this.rate&&this.rate<1){let s=t.training==null?!1:t.training,r=this.getNoiseShape(n);return yc(()=>s3(n,this.rate,r,this.seed),()=>n,s)}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()}};Wp.className="Dropout";oe.registerClass(Wp);var Zg=class extends Wp{constructor(e){super(e);this.inputSpec=[{ndim:3}]}getNoiseShape(e){let t=e.shape;return[t[0],1,t[2]]}};Zg.className="SpatialDropout1D";oe.registerClass(Zg);var Yg=class extends Xe{constructor(e){super(e);if(this.activation=null,this.useBias=!0,this.kernel=null,this.bias=null,this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_BIAS_INITIALIZER="zeros",e.batchInputShape==null&&e.inputShape==null&&e.inputDim!=null){let t=null;e.batchSize!=null&&(t=e.batchSize),this.batchInputShape=[t,e.inputDim]}this.units=e.units,Zt(this.units,"units"),this.activation=Qr(e.activation),e.useBias!=null&&(this.useBias=e.useBias),this.kernelInitializer=bt(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.biasInitializer=bt(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelConstraint=Gt(e.kernelConstraint),this.biasConstraint=Gt(e.biasConstraint),this.kernelRegularizer=vt(e.kernelRegularizer),this.biasRegularizer=vt(e.biasRegularizer),this.activityRegularizer=vt(e.activityRegularizer),this.supportsMasking=!0,this.inputSpec=[{minNDim:2}]}build(e){e=st(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=st(e);let t=e.slice();return t[t.length-1]=this.units,t}call(e,t){return H(()=>{this.invokeCallHook(e,t);let n=ze(e),s=jb(this.activation.getClassName()),r;return s!=null?r=er(n,this.kernel.read(),s,this.bias?this.bias.read():null):(r=er(n,this.kernel.read()),this.bias!=null&&(r=Os(r,this.bias.read())),this.activation!=null&&(r=this.activation.apply(r))),r})}getConfig(){let e={units:this.units,activation:Jr(this.activation),useBias:this.useBias,kernelInitializer:Ct(this.kernelInitializer),biasInitializer:Ct(this.biasInitializer),kernelRegularizer:lt(this.kernelRegularizer),biasRegularizer:lt(this.biasRegularizer),activityRegularizer:lt(this.activityRegularizer),kernelConstraint:Ht(this.kernelConstraint),biasConstraint:Ht(this.biasConstraint)},t=super.getConfig();return Object.assign(e,t),e}};Yg.className="Dense";oe.registerClass(Yg);var Jg=class extends Xe{constructor(e){e=e||{};super(e);this.inputSpec=[{minNDim:3}],this.dataFormat=e.dataFormat}computeOutputShape(e){e=st(e);for(let t of e.slice(1))if(t==null)throw new G(`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],Kr(e,1)]}call(e,t){return H(()=>{this.invokeCallHook(e,t);let n=ze(e);if(this.dataFormat==="channelsFirst"&&n.rank>1){let s=[0];for(let r=2;r<n.rank;++r)s.push(r);s.push(1),n=je(n,s)}return hO(n)})}getConfig(){let e={};this.dataFormat!=null&&(e.dataFormat=this.dataFormat);let t=super.getConfig();return Object.assign(e,t),e}};Jg.className="Flatten";oe.registerClass(Jg);var Qg=class extends Xe{constructor(e){super(e);this.supportsMasking=!0,this.activation=Qr(e.activation)}call(e,t){return H(()=>{this.invokeCallHook(e,t);let n=ze(e);return this.activation.apply(n)})}getConfig(){let e={activation:Jr(this.activation)},t=super.getConfig();return Object.assign(e,t),e}};Qg.className="Activation";oe.registerClass(Qg);var e2=class extends Xe{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 H(()=>(e=ze(e),cO(e,this.n)))}getConfig(){let e={n:this.n},t=super.getConfig();return Object.assign(e,t),e}};e2.className="RepeatVector";oe.registerClass(e2);var t2=class extends Xe{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.",s=t.slice(),r=1,a=null;for(let i=0;i<s.length;++i){let l=s[i];if(this.isUnknown(l))if(a===null)a=i;else throw new G("Can only specifiy one unknown dimension.");else r*=l}let o=Kr(e);if(a!==null){if(r===0||o%r!=0)throw new G(n);s[a]=o/r}else if(o!==r)throw new G(n);return s}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 H(()=>{this.invokeCallHook(e,t);let n=ze(e),s=n.shape,r=s.slice(0,1).concat(this.fixUnknownDimension(s.slice(1),this.targetShape));return U(n,r)})}getConfig(){let e={targetShape:this.targetShape},t=super.getConfig();return Object.assign(e,t),e}};t2.className="Reshape";oe.registerClass(t2);var n2=class extends Xe{constructor(e){super(e);if(e.dims==null)throw new Error("Required configuration field `dims` is missing during Permute constructor call.");if(!Array.isArray(e.dims))throw new Error(`Permute constructor requires \`dims\` to be an Array, but received ${e.dims} instead.`);let t=Ds(1,e.dims.length+1);if(!I.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 Pt({ndim:this.dims.length+1})]}computeOutputShape(e){e=st(e);let t=e.slice();return this.dims.forEach((n,s)=>{t[s+1]=e[n]}),t}call(e,t){return je(ze(e),this.dimsIncludingBatch)}getConfig(){let e={dims:this.dims},t=super.getConfig();return Object.assign(e,t),e}};n2.className="Permute";oe.registerClass(n2);var s2=class extends Xe{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=ze(e),s=-1;return Fh(Nl(n,this.maskValue),s)}call(e,t){return H(()=>{this.invokeCallHook(e,t);let n=ze(e),s=-1,r=!0,a=Fh(Nl(n,this.maskValue),s,r);return z(n,ue(a,n.dtype))})}};s2.className="Masking";oe.registerClass(s2);var r2=class extends Xe{constructor(e){super(e);if(this.embeddings=null,this.DEFAULT_EMBEDDINGS_INITIALIZER="randomUniform",e.batchInputShape==null&&e.inputShape==null){let t=null;e.batchSize!=null&&(t=e.batchSize),e.inputLength==null?this.batchInputShape=[t,null]:this.batchInputShape=[t].concat(At(e.inputLength))}this.inputDim=e.inputDim,Zt(this.inputDim,"inputDim"),this.outputDim=e.outputDim,Zt(this.outputDim,"outputDim"),this.embeddingsInitializer=bt(e.embeddingsInitializer||this.DEFAULT_EMBEDDINGS_INITIALIZER),this.embeddingsRegularizer=vt(e.embeddingsRegularizer),this.activityRegularizer=vt(e.activityRegularizer),this.embeddingsConstraint=Gt(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 H(()=>this.maskZero?(e=ze(e),Nl(e,qe(e))):null)}computeOutputShape(e){if(e=st(e),this.inputLength==null)return[...e,this.outputDim];let t=At(this.inputLength);if(t.length!==e.length-1)throw new G(`"inputLength" is ${this.inputLength}, but received input shape has shape ${e}`);{let n=0;for(let s=0;s<t.length;++s){let r=t[s],a=e[s+1];if(r!=null&&a!=null&&r!==a)throw new G(`"inputLength" is ${this.inputLength}, but received input shape has shape ${e}`);r==null&&(t[n]=a),n++}}return[e[0],...t,this.outputDim]}call(e,t){return H(()=>{this.invokeCallHook(e,t);let n=ze(e);n.dtype!=="int32"&&(n=pp(n,"int32"));let s=n3(this.embeddings.read(),U(n,[n.size]));return U(s,st(this.computeOutputShape(n.shape)))})}getConfig(){let e={inputDim:this.inputDim,outputDim:this.outputDim,embeddingsInitializer:Ct(this.embeddingsInitializer),embeddingsRegularizer:lt(this.embeddingsRegularizer),activityRegularizer:lt(this.activityRegularizer),embeddingsConstraint:Ht(this.embeddingsConstraint),maskZero:this.maskZero,inputLength:this.inputLength},t=super.getConfig();return Object.assign(e,t),e}};r2.className="Embedding";oe.registerClass(r2);var Mo=class extends Xe{constructor(e){super(e||{});this.supportsMasking=!0}mergeFunction(e){throw new Oe}computeElementwiseOpOutputShape(e,t){if(e==null||t==null)return null;if(e.length<t.length)return this.computeElementwiseOpOutputShape(t,e);if(t.length===0)return e;let n=e.slice(0,e.length-t.length);for(let s=0;s<t.length;++s){let r=e[e.length-t.length+s],a=t[s];if(r==null||a==null||r<0||a<0)n.push(null);else if(r===1)n.push(a);else if(a===1)n.push(r);else{if(r!==a)throw new G("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=[st(e)]),e=e,e.length<2)throw new G(`A merge layer should be called on an Array of at least 2 inputs. Got ${e.length} input(s).`);let t=[];for(let r of e)r!=null&&r[0]!==null&&t.push(r[0]);if(t=Xr(t),t.length>1)throw new G(`Can not merge tensors with different batch sizes. Got tensors with shapes: ${JSON.stringify(e)}.`);let n=e[0]==null?null:e[0].slice(1);for(let r=1;r<e.length;++r){let a=e[r]==null?null:e[r].slice(1);n=this.computeElementwiseOpOutputShape(n,a)}let s=e.map(r=>r.length);e.indexOf(null)===-1&&Xr(s).length===1?this.reshapeRequired=!1:this.reshapeRequired=!0}call(e,t){return H(()=>{if(e=e,this.reshapeRequired){let n=[],s=e.map(r=>r.rank);if(s.indexOf(null)===-1){let r=Zr(s);for(let a of e){let o=a.rank;for(let i=0;i<r-o;++i)a=Ac(a,1);n.push(a)}return this.mergeFunction(n)}else{let r=!1;for(let i of e){let l=i.rank;if(l==null){let u=i.shape,c=u[0],d=u.slice(1).concat([c]),h=U(i,[c].concat(Kr(u.slice(1))));h=je(h,[1,0]),h=U(h,d),n.push(h),r=!0}else if(l>1){let u=Ds(1,l).concat([0]);n.push(je(i,u)),r=!0}else n.push(i)}let a=this.mergeFunction(n),o=a.rank;if(r){if(o==null){let i=a.shape,l=i.length,u=i[l-1],c=[u].concat(i.slice(0,i.length-1));a=U(je(U(a,[-1,u]),[1,0]),c)}else if(o>1){let i=[o-1].concat(Ds(0,o-1));a=je(a,i)}}return a}}else return this.mergeFunction(e)})}computeOutputShape(e){e=e;let t;e[0]==null?t=null:t=e[0].slice(1);for(let s=1;s<e.length;++s){let r=e[s]==null?null:e[s].slice(1);t=this.computeElementwiseOpOutputShape(t,r)}let n=[];for(let s of e)s!=null&&s[0]!==null&&n.push(s[0]);return n=Xr(n),n.length===1?t=n.concat(t):t=[null].concat(t),t}computeMask(e,t){return H(()=>{if(t==null)return null;if(!Array.isArray(t))throw new G("`mask` should be an Array");if(!Array.isArray(e))throw new G("`inputs` should be an Array");if(t.length!==e.length)throw new G(`The Array 'inputs' and 'mask' are expected to have the same length, but have different lengths (${e.length} vs ${t.length})`);if(t.every(s=>s==null))return null;t=t.map(s=>s==null?s:Ft(s,0));let n=t[0];for(let s=1;s<t.length-1;++s)n=Rs(n,t[s]);return n})}},a2=class extends Mo{constructor(e){super(e)}mergeFunction(e){return H(()=>{let t=e[0].clone();for(let n=1;n<e.length;++n)t=ae(t,e[n]);return t})}};a2.className="Add";oe.registerClass(a2);var o2=class extends Mo{constructor(e){super(e)}mergeFunction(e){return H(()=>{let t=e[0].clone();for(let n=1;n<e.length;++n)t=z(t,e[n]);return t})}};o2.className="Multiply";oe.registerClass(o2);var i2=class extends Mo{constructor(e){super(e)}mergeFunction(e){return H(()=>{let t=e[0].clone();for(let n=1;n<e.length;++n)t=ae(t,e[n]);return z(1/e.length,t)})}};i2.className="Average";oe.registerClass(i2);var l2=class extends Mo{constructor(e){super(e)}mergeFunction(e){return H(()=>{let t=e[0];for(let n=1;n<e.length;++n)t=gr(t,e[n]);return t})}};l2.className="Maximum";oe.registerClass(l2);var u2=class extends Mo{constructor(e){super(e)}mergeFunction(e){return H(()=>{let t=e[0];for(let n=1;n<e.length;++n)t=oc(t,e[n]);return t})}};u2.className="Minimum";oe.registerClass(u2);var c2=class extends Mo{constructor(e){super(e);this.DEFAULT_AXIS=-1,e==null&&(e={}),this.axis=e.axis==null?this.DEFAULT_AXIS:e.axis,this.supportsMasking=!0,this.reshapeRequired=!1}build(e){if(!(Array.isArray(e)&&Array.isArray(e[0]))||e.length===1)throw new G("A `Concatenate` layer should be called on a list of at least 2 inputs");e=e;let t=!0;for(let s of e)if(s!=null){t=!1;break}if(t)return;let n=[];for(let s=0;s<e.length;++s){let r=e[s].slice();r.splice(this.axis,1);let a=!1;for(let o of n)if(I.arraysEqual(o,r)){a=!0;break}a||n.push(r)}if(n.length>1)throw new G("A `Concatenate` layer requires inputs with matching shapes except for the concat axis. Got input shapes: "+JSON.stringify(e))}mergeFunction(e){return H(()=>sg(e,this.axis))}computeOutputShape(e){if(!(Array.isArray(e)&&Array.isArray(e[0])))throw new G("A `Concatenate` layer should be called on a list of inputs.");let t=e,n=t[0].slice(),s=this.axis<0?n.length+this.axis:this.axis;for(let r of t.slice(1)){if(n[s]==null||r[s]==null){n[s]=null;break}n[s]+=r[s]}return n}computeMask(e,t){if(t==null)return null;if(!Array.isArray(t))throw new G("`mask` should be an array for Concatenate");if(!Array.isArray(e))throw new G("`inputs` should be an array for Concatenate");if(t.length!==e.length)throw new G(`Mismatch in the length of mask (${t.length}) and the legnth of inputs (${e.length})`);return H(()=>{let n=!0;if(t.forEach(a=>{if(a!=null){n=!1;return}}),n)return null;let s=[];for(let a=0;a<e.length;++a)t[a]==null?s.push(ue(us(e[a]),"bool")):t[a].rank<e[a].rank?s.push(Ft(t[a],-1)):s.push(t[a]);let r=dt(s,this.axis);return lA(r,-1,!1)})}getConfig(){let e={axis:this.axis},t=super.getConfig();return Object.assign(e,t),e}};c2.className="Concatenate";oe.registerClass(c2);function Ec(e,t){for(;e<0;)e+=t;return e}function XP(e,t,n){if(e.shape.length>3||t.shape.length>3)throw new Oe("batchDot is not implemented for tensors of 4D or higher rank yet");if(I.assert(e.shape.length>=2,()=>`batchDot requires the rank of x to be >= 2, but got ${e.shape.length}`),I.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 Oe("batchDot is not implemented for complex64-type Tensors yet.");let s=e.shape.length,r=t.shape.length;n==null&&(n=[s-1,r-2]);let a=n;return H(()=>{let o;if(s>r){o=s-r;let l=[];for(let u=0;u<o;++u)l.push(1);t=U(t,t.shape.concat(l))}else if(r>s){o=r-s;let l=[];for(let u=0;u<o;++u)l.push(1);e=U(e,e.shape.concat(l))}else o=0;let i;if(e.shape.length===2&&t.shape.length===2)a[0]===a[1]?i=ve(z(e,t),a[0]):i=ve(z(je(e,[1,0]),t),a[1]);else{let l=a[0]!==e.shape.length-1,u=a[1]===t.shape.length-1;i=We(e,t,l,u)}if(o>0){let l;s>r?l=s+r-3:l=s-1;let u=[];for(let c=l;c<l+o;++c)u.push(c);i=mt(i,u)}return i.shape.length===1&&(i=Ft(i,1)),i})}var d2=class extends Mo{constructor(e){super(e);this.axes=e.axes,this.normalize=e.normalize==null?!1:e.normalize,this.supportsMasking=!0,this.reshapeRequired=!1}build(e){I.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 Oe("Dot layer does not support tensors of 4D or higher rank yet.");let s=this.interpretAxes(t,n);if(t[s[0]]!==n[s[1]])throw new G(`Dimension incompatibility: ${t[s[0]]} !== ${n[s[1]]}`)}mergeFunction(e){if(e.length!==2)throw new G(`A \`Dot\` layer must be called on exactly 2 inputs, but received ${e.length} input(s).`);let t=e[0],n=e[1],s;return Array.isArray(this.axes)?s=this.axes.map((r,a)=>Ec(r,e[a].shape.length)):s=[Ec(this.axes,t.shape.length),Ec(this.axes,n.shape.length)],this.normalize&&(t=Np(t,s[0]),n=Np(n,s[1])),XP(t,n,s)}interpretAxes(e,t){let n;return Array.isArray(this.axes)?n=this.axes:n=[Ec(this.axes,e.length),Ec(this.axes,t.length)],n}computeOutputShape(e){I.assert(Array.isArray(e)&&e.length===2&&Array.isArray(e[0])&&Array.isArray(e[1]),()=>"A `Dot` layer should be called on a list of exactly 2 inputs.");let t=e[0].slice(),n=e[1].slice();if(t.length>3||n.length>3)throw new Oe("Dot layer does not support tensors of 4D or higher rank yet.");let s=this.interpretAxes(t,n);t.splice(s[0],1),n.splice(s[1],1),n.splice(0,1);let r=t.concat(n);return r.length===1&&r.push(1),r}computeMask(e,t){return null}getConfig(){let e={axes:this.axes,normalize:this.normalize},t=super.getConfig();return Object.assign(e,t),e}};d2.className="Dot";oe.registerClass(d2);var h2=class extends Xe{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 H(()=>{this.invokeCallHook(e,t);let n=ze(e);return yc(()=>ae(mp(n.shape,0,this.stddev),n),()=>n,t.training||!1)})}};h2.className="GaussianNoise";oe.registerClass(h2);var p2=class extends Xe{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 H(()=>{this.invokeCallHook(e,t);let n=ze(e);return this.rate>0&&this.rate<1?yc(()=>{let r=Math.sqrt(this.rate/(1-this.rate));return z(n,mp(n.shape,1,r))},()=>n,t.training||!1):n})}};p2.className="GaussianDropout";oe.registerClass(p2);var f2=class extends Xe{constructor(e){super(e);this.supportsMasking=!0,this.rate=e.rate,this.noiseShape=e.noiseShape}_getNoiseShape(e){return this.noiseShape||ze(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 H(()=>{if(this.rate<1&&this.rate>0){let n=this._getNoiseShape(e);return yc(()=>{let r=ze(e),a=1.6732632423543772,o=1.0507009873554805,i=-a*o,l=Io(El(n),this.rate);l=pp(l,"float32");let u=((1-this.rate)*(1+this.rate*i**2))**-.5,c=-u*i*this.rate,d=ae(z(r,l),z(ae(l,-1),i));return ae(z(d,u),c)},()=>ze(e),t.training||!1)}return e})}};f2.className="AlphaDropout";oe.registerClass(f2);function Rc(e,t,n,s,r,a=.001){let o;if(e.rank===2)o=Ex(e,t,n,s,r,a);else if(e.rank===3)o=Rx(e,t,n,s,r,a);else if(e.rank===4)o=_x(e,t,n,s,r,a);else throw new Oe(`batchNormalization is not implemented for array of rank ${e.rank} yet`);return o}function KP(e,t,n,s,r=.001){return H(()=>{let a=Gh(e,s),o=a.mean,i=a.variance;return[Rc(e,o,i,n,t,r),o,i]})}function ZP(e,t,n,s,r=.001){return H(()=>{let a=Gh(e,s),o=a.mean,i=a.variance,l=[];for(let m of Ds(0,e.rank))s.indexOf(m)!==-1?l.push(1):l.push(e.shape[m]);let u=U(o,l),c=U(i,l),d=t==null?null:U(t,l),h=n==null?null:U(n,l);return[Rc(e,u,c,h,d,r),o,i]})}function YP(e,t,n,s,r=.001){return I.arraysEqual(s.slice().sort(),Ds(0,e.rank-1))?KP(e,t,n,s,r):ZP(e,t,n,s,r)}var m2=class extends Xe{constructor(e){e==null&&(e={});super(e);this.supportsMasking=!0,this.axis=e.axis==null?-1:e.axis,this.momentum=e.momentum==null?.99:e.momentum,this.epsilon=e.epsilon==null?.001:e.epsilon,this.center=e.center==null?!0:e.center,this.scale=e.scale==null?!0:e.scale,this.betaInitializer=bt(e.betaInitializer||"zeros"),this.gammaInitializer=bt(e.gammaInitializer||"ones"),this.movingMeanInitializer=bt(e.movingMeanInitializer||"zeros"),this.movingVarianceInitializer=bt(e.movingVarianceInitializer||"ones"),this.betaConstraint=Gt(e.betaConstraint),this.gammaConstraint=Gt(e.gammaConstraint),this.betaRegularizer=vt(e.betaRegularizer),this.gammaRegularizer=vt(e.gammaRegularizer)}build(e){e=st(e);let t=this.axis>=0?this.axis:this.axis+e.length,n=e[t];if(n==null)throw new G(`Axis ${t} of input tensor should have a defined dimension but the layer received an input with shape ${JSON.stringify(e)}.`);this.inputSpec=[new Pt({ndim:e.length,axes:{[t]:n}})];let s=[n];this.scale&&(this.gamma=this.addWeight("gamma",s,null,this.gammaInitializer,this.gammaRegularizer,!0,this.gammaConstraint)),this.center&&(this.beta=this.addWeight("beta",s,null,this.betaInitializer,this.betaRegularizer,!0,this.betaConstraint)),this.movingMean=this.addWeight("moving_mean",s,null,this.movingMeanInitializer,null,!1),this.movingVariance=this.addWeight("moving_variance",s,null,this.movingVarianceInitializer,null,!1),this.built=!0}call(e,t){return H(()=>{let n=t.training==null?!1:t.training,s=ze(e),r=s.shape,a=r.length,o=Ds(0,a),i=this.axis>=0?this.axis:this.axis+a;o.splice(i,1);let l=Eo(1,a);l[i]=r[i];let u=o.slice();u.sort();let c=!I.arraysEqual(u,Ds(0,a).slice(0,a-1)),d=()=>{if(c){let g=U(this.movingMean.read(),l),y=U(this.movingVariance.read(),l),x=this.center?U(this.beta.read(),l):null,b=this.scale?U(this.gamma.read(),l):null;return Rc(s,g,y,x,b,this.epsilon)}else return Rc(s,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[h,p,m]=YP(s,this.gamma.read(),this.beta.read(),o,this.epsilon),f=(g,y,x)=>{H(()=>{let b=1-x,v=g.read(),k=z(Ae(v,y),b);g.write(Ae(v,k))})};return(()=>{f(this.movingMean,p,this.momentum),f(this.movingVariance,m,this.momentum)})(),h})}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:lt(this.betaRegularizer),gammaRegularizer:lt(this.gammaRegularizer),betaConstraint:Ht(this.betaConstraint),gammaConstraint:Ht(this.gammaConstraint)},t=super.getConfig();return Object.assign(e,t),e}};m2.className="BatchNormalization";oe.registerClass(m2);var A2=class extends Xe{constructor(e){e==null&&(e={});super(e);if(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=bt(e.betaInitializer||"zeros"),this.gammaInitializer=bt(e.gammaInitializer||"ones"),this.betaRegularizer=vt(e.betaRegularizer),this.gammaRegularizer=vt(e.gammaRegularizer),this.supportsMasking=!0}build(e){e=st(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!==Xr(this.axis).length)throw new Error(`Found duplicate axes in: ${this.axis}`);let n=this.axis.map(r=>e[r]),s=!0;this.scale?this.gamma=this.addWeight("gamma",n,"float32",this.gammaInitializer,this.gammaRegularizer,s):this.gamma=null,this.center?this.beta=this.addWeight("beta",n,"float32",this.betaInitializer,this.betaRegularizer,s):this.beta=null,this.built=!0}call(e,t){let n=ze(e),s=n.shape,r=s.length;return H(()=>{let a=!0,{mean:o,variance:i}=Gh(n,this.axis,a),l=Eo(1,r);for(let m of this.axis)l[m]=s[m];let u=m=>m!=null&&m.shape.length!==r&&this.axis!==[r-1]?U(m,l):m,c=u(this.gamma.read()),d=u(this.beta.read()),h=[],p=[];for(let m=0;m<r;++m)this.axis.indexOf(m)!==-1?(h.push(s[m]),p.push(1)):(h.push(1),p.push(s[m]));return o=Es(o,h),i=Es(i,h),c=Es(c,p),d=Es(d,p),Rc(n,o,i,d,c,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:lt(this.betaRegularizer),gammaRegularizer:lt(this.gammaRegularizer)},t=super.getConfig();return Object.assign(e,t),e}};A2.className="LayerNormalization";oe.registerClass(A2);function JP(e,t,n){return H(()=>{if(e.rank!==4)throw new G(`temporalPadding expects input tensor to be 4-D, but received a ${e.rank}-D tensor.`);if(t==null&&(t=[[1,1],[1,1]]),t.length!==2||t[0].length!==2||t[1].length!==2)throw new G("spatial2dPadding expects `padding` to be an Array of two Arrays, each of which is an Array of two integers.");if(n==null&&(n=$s()),n!=="channelsLast"&&n!=="channelsFirst")throw new G(`Unknown data format: ${n}. Supported data formats are 'channelsLast' and 'channelsFirst.`);let s;return n==="channelsFirst"?s=[[0,0],[0,0],t[0],t[1]]:s=[[0,0],t[0],t[1],[0,0]],Gr(e,s)})}var g2=class extends Xe{constructor(e){e==null&&(e={});super(e);if(this.dataFormat=e.dataFormat==null?$s():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 G(`ZeroPadding2D expects padding to be a length-2 array, but received a length-${e.padding.length} array.`);let t,n;if(typeof e.padding[0]=="number")t=[e.padding[0],e.padding[0]],n=[e.padding[1],e.padding[1]];else{if(e.padding=e.padding,e.padding[0].length!==2)throw new G(`ZeroPadding2D expects height padding to be a length-2 array, but received a length-${e.padding[0].length} array.`);if(t=e.padding[0],e.padding[1].length!==2)throw new G(`ZeroPadding2D expects width padding to be a length-2 array, but received a length-${e.padding[1].length} array.`);n=e.padding[1]}this.padding=[t,n]}this.inputSpec=[new Pt({ndim:4})]}computeOutputShape(e){e=st(e);let t,n;return this.dataFormat==="channelsFirst"?(e[2]!=null&&e[2]>=0?t=e[2]+this.padding[0][0]+this.padding[0][1]:t=null,e[3]!=null&&e[3]>=0?n=e[3]+this.padding[1][0]+this.padding[1][1]:n=null,[e[0],e[1],t,n]):(e[1]!=null&&e[1]>=0?t=e[1]+this.padding[0][0]+this.padding[0][1]:t=null,e[2]!=null&&e[2]>=0?n=e[2]+this.padding[1][0]+this.padding[1][1]:n=null,[e[0],t,n,e[3]])}call(e,t){return H(()=>JP(ze(e),this.padding,this.dataFormat))}getConfig(){let e={padding:this.padding,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}};g2.className="ZeroPadding2D";oe.registerClass(g2);function Vp(e,t,n,s,r,a){return H(()=>{$t(r),Zb(a),hs(s),n==null&&(n=[1,1]),s==null&&(s="valid"),r==null&&(r=$s()),a==null&&(a="max"),e=zg(e,r);let o,i=s==="same"?"same":"valid";return a==="max"?o=Uh(e,t,n,i):o=Oh(e,t,n,i),r==="channelsFirst"&&(o=je(o,[0,3,1,2])),o})}function lv(e,t,n,s,r,a){return H(()=>{$t(r),Zb(a),hs(s),n==null&&(n=[1,1,1]),s==null&&(s="valid"),r==null&&(r=$s()),a==null&&(a="max"),e=nv(e,r);let o,i=s==="same"?"same":"valid";return a==="max"?o=SA(e,t,n,i):o=dA(e,t,n,i),r==="channelsFirst"&&(o=je(o,[0,4,1,2,3])),o})}var uv=class extends Xe{constructor(e){e.poolSize==null&&(e.poolSize=2);super(e);if(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 G(`poolSize for 1D convolutional layer must be a number or an Array of a single number, but received ${JSON.stringify(e.poolSize)}`);if(Zt(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 G(`strides for 1D convolutional layer must be a number or an Array of a single number, but received ${JSON.stringify(e.strides)}`);Zt(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,hs(this.padding),this.inputSpec=[new Pt({ndim:3})]}computeOutputShape(e){e=st(e);let t=zs(e[1],this.poolSize[0],this.padding,this.strides[0]);return[e[0],t,e[2]]}call(e,t){return H(()=>{this.invokeCallHook(e,t),e=Ac(ze(e),2);let n=this.poolingFunction(ze(e),[this.poolSize[0],1],[this.strides[0],1],this.padding,"channelsLast");return mt(n,[2])})}getConfig(){let e={poolSize:this.poolSize,padding:this.padding,strides:this.strides},t=super.getConfig();return Object.assign(e,t),e}},y2=class extends uv{constructor(e){super(e)}poolingFunction(e,t,n,s,r){return $t(r),hs(s),Vp(e,t,n,s,r,"max")}};y2.className="MaxPooling1D";oe.registerClass(y2);var x2=class extends uv{constructor(e){super(e)}poolingFunction(e,t,n,s,r){return $t(r),hs(s),Vp(e,t,n,s,r,"avg")}};x2.className="AveragePooling1D";oe.registerClass(x2);var cv=class extends Xe{constructor(e){e.poolSize==null&&(e.poolSize=[2,2]);super(e);if(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 G(`If the strides property of a 2D pooling layer is an Array, it is expected to have a length of 2, but received length ${e.strides.length}.`);this.strides=e.strides}else this.strides=[e.strides,e.strides];Zt(this.poolSize,"poolSize"),Zt(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,$t(this.dataFormat),hs(this.padding),this.inputSpec=[new Pt({ndim:4})]}computeOutputShape(e){e=st(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],n=this.dataFormat==="channelsFirst"?e[3]:e[2];return t=zs(t,this.poolSize[0],this.padding,this.strides[0]),n=zs(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 H(()=>(this.invokeCallHook(e,t),this.poolingFunction(ze(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}},b2=class extends cv{constructor(e){super(e)}poolingFunction(e,t,n,s,r){return $t(r),hs(s),Vp(e,t,n,s,r,"max")}};b2.className="MaxPooling2D";oe.registerClass(b2);var v2=class extends cv{constructor(e){super(e)}poolingFunction(e,t,n,s,r){return $t(r),hs(s),Vp(e,t,n,s,r,"avg")}};v2.className="AveragePooling2D";oe.registerClass(v2);var dv=class extends Xe{constructor(e){e.poolSize==null&&(e.poolSize=[2,2,2]);super(e);if(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 G(`If the strides property of a 3D pooling layer is an Array, it is expected to have a length of 3, but received length ${e.strides.length}.`);this.strides=e.strides}else this.strides=[e.strides,e.strides,e.strides];Zt(this.poolSize,"poolSize"),Zt(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,$t(this.dataFormat),hs(this.padding),this.inputSpec=[new Pt({ndim:5})]}computeOutputShape(e){e=st(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],n=this.dataFormat==="channelsFirst"?e[3]:e[2],s=this.dataFormat==="channelsFirst"?e[4]:e[3];return t=zs(t,this.poolSize[0],this.padding,this.strides[0]),n=zs(n,this.poolSize[1],this.padding,this.strides[1]),s=zs(s,this.poolSize[2],this.padding,this.strides[2]),this.dataFormat==="channelsFirst"?[e[0],e[1],t,n,s]:[e[0],t,n,s,e[4]]}call(e,t){return H(()=>(this.invokeCallHook(e,t),this.poolingFunction(ze(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}},w2=class extends dv{constructor(e){super(e)}poolingFunction(e,t,n,s,r){return $t(r),hs(s),lv(e,t,n,s,r,"max")}};w2.className="MaxPooling3D";oe.registerClass(w2);var k2=class extends dv{constructor(e){super(e)}poolingFunction(e,t,n,s,r){return $t(r),hs(s),lv(e,t,n,s,r,"avg")}};k2.className="AveragePooling3D";oe.registerClass(k2);var hv=class extends Xe{constructor(e){super(e);this.inputSpec=[new Pt({ndim:3})]}computeOutputShape(e){return[e[0],e[2]]}call(e,t){throw new Oe}},I2=class extends hv{constructor(e){super(e||{})}call(e,t){return H(()=>{let n=ze(e);return Et(n,1)})}};I2.className="GlobalAveragePooling1D";oe.registerClass(I2);var S2=class extends hv{constructor(e){super(e||{})}call(e,t){return H(()=>{let n=ze(e);return ls(n,1)})}};S2.className="GlobalMaxPooling1D";oe.registerClass(S2);var pv=class extends Xe{constructor(e){super(e);this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,$t(this.dataFormat),this.inputSpec=[new Pt({ndim:4})]}computeOutputShape(e){return e=e,this.dataFormat==="channelsLast"?[e[0],e[3]]:[e[0],e[1]]}call(e,t){throw new Oe}getConfig(){let e={dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}},C2=class extends pv{call(e,t){return H(()=>{let n=ze(e);return this.dataFormat==="channelsLast"?Et(n,[1,2]):Et(n,[2,3])})}};C2.className="GlobalAveragePooling2D";oe.registerClass(C2);var T2=class extends pv{call(e,t){return H(()=>{let n=ze(e);return this.dataFormat==="channelsLast"?ls(n,[1,2]):ls(n,[2,3])})}};T2.className="GlobalMaxPooling2D";oe.registerClass(T2);var fv=class extends Xe{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 s=t.layer,r=Ms(s,n);delete t.layer;let a={layer:r};return Object.assign(a,t),new e(a)}},N2=class extends fv{constructor(e){super(e);this.supportsMasking=!0}build(e){if(e=st(e),e.length<3)throw new G(`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=st(e);let t=[e[0]].concat(e.slice(2)),n=this.layer.computeOutputShape(t),s=e[1];return[n[0],s].concat(n.slice(1))}call(e,t){return H(()=>(e=ze(e),ov((a,o)=>[ze(this.layer.call(a,t)),[]],e,[],!1,null,null,!1,!0)[1]))}};N2.className="TimeDistributed";oe.registerClass(N2);function QP(e){_o(aO,"BidirectionalMergeMode",e)}var eM="concat",E2=class extends fv{constructor(e){super(e);let t=e.layer.getConfig(),n={};n.className=e.layer.getClassName(),n.config=t,this.forwardLayer=Ms(n),t.goBackwards=t.goBackwards!==!0;let s={};if(s.className=e.layer.getClassName(),s.config=t,this.backwardLayer=Ms(s),this.forwardLayer.name="forward_"+this.forwardLayer.name,this.backwardLayer.name="backward_"+this.backwardLayer.name,this.mergeMode=e.mergeMode===void 0?eM:e.mergeMode,QP(this.mergeMode),e.weights)throw new Oe("weights support is not implemented for Bidirectional layer yet.");this._stateful=e.layer.stateful,this.returnSequences=e.layer.returnSequences,this.returnState=e.layer.returnState,this.supportsMasking=!0,this._trainable=!0,this.inputSpec=e.layer.inputSpec,this.numConstants=null}get trainable(){return this._trainable}set trainable(e){this._trainable=e,this.forwardLayer!=null&&(this.forwardLayer.trainable=e),this.backwardLayer!=null&&(this.backwardLayer.trainable=e)}getWeights(){return this.forwardLayer.getWeights().concat(this.backwardLayer.getWeights())}setWeights(e){let t=e.length,n=Math.floor(t/2);this.forwardLayer.setWeights(e.slice(0,n)),this.backwardLayer.setWeights(e.slice(n))}computeOutputShape(e){let t=this.forwardLayer.computeOutputShape(e);Array.isArray(t)&&Array.isArray(t[0])||(t=[t]),t=t;let n,s,r;return this.returnState&&(r=t.slice(1)),n=t[0],n=n,this.mergeMode==="concat"?(n[n.length-1]*=2,s=[n]):this.mergeMode==null?s=[n,n.slice()]:s=[n],this.returnState?this.mergeMode==null?s.concat(r).concat(r.slice()):[n].concat(r).concat(r.slice()):En(s)}apply(e,t){let n=t==null?null:t.initialState,s=t==null?null:t.constants;t==null&&(t={});let r=av(e,n,s,this.numConstants);if(e=r.inputs,n=r.initialState,s=r.constants,Array.isArray(e)&&(n=e.slice(1),e=e[0]),(n==null||n.length===0)&&s==null)return super.apply(e,t);let a=[],o=[];if(n!=null){let l=n.length;if(l%2>0)throw new G("When passing `initialState` to a Bidrectional RNN, the state should be an Array containing the states of the underlying RNNs.");t.initialState=n,a.push(...n);let u=n.map(c=>new Pt({shape:c.shape}));this.forwardLayer.stateSpec=u.slice(0,l/2),this.backwardLayer.stateSpec=u.slice(l/2),o.push(...u)}if(s!=null)throw new Oe("Support for constants in Bidirectional layers is not implemented yet.");let i=a[0]instanceof Ps;for(let l of a)if(l instanceof Ps!==i)throw new G("The initial state of a Bidirectional layer cannot be specified as a mix of symbolic and non-symbolic tensors");if(i){let l=[e].concat(a),u=this.inputSpec.concat(o),c=this.inputSpec;this.inputSpec=u;let d=super.apply(l,t);return this.inputSpec=c,d}else return super.apply(e,t)}call(e,t){return H(()=>{let n=t.initialState,s,r;if(n==null)s=this.forwardLayer.call(e,t),r=this.backwardLayer.call(e,t);else{let i=n.slice(0,n.length/2),l=n.slice(n.length/2);s=this.forwardLayer.call(e,Object.assign(t,{initialState:i})),r=this.backwardLayer.call(e,Object.assign(t,{initialState:l}))}let a;this.returnState&&(Array.isArray(s)&&(a=s.slice(1).concat(r.slice(1))),s=s[0],r=r[0]),this.returnSequences&&(r=cs(r,1));let o;return this.mergeMode==="concat"?o=sg([s,r]):this.mergeMode==="sum"?o=ae(s,r):this.mergeMode==="ave"?o=z(.5,ae(s,r)):this.mergeMode==="mul"?o=z(s,r):this.mergeMode==null&&(o=[s,r]),this.returnState?this.mergeMode==null?o.concat(a):[o].concat(a):o})}resetStates(e){this.forwardLayer.resetStates(),this.backwardLayer.resetStates()}build(e){$o(this.forwardLayer.name,()=>{this.forwardLayer.build(e)}),$o(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 r=this.forwardLayer.states.map(a=>null);return Array.isArray(n)?n.concat(r).concat(r):[n].concat(r).concat(r)}else return n}get trainableWeights(){return this.forwardLayer.trainableWeights.concat(this.backwardLayer.trainableWeights)}get nonTrainableWeights(){return 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s=S("axis",e,t,n);return[mt(S("x",e,t,n),s)]}case"Reshape":return[U(S("x",e,t,n),S("shape",e,t,n))];case"MirrorPad":return[eb(S("x",e,t,n),S("padding",e,t,n),S("mode",e,t,n))];case"PadV2":case"Pad":return[Gr(S("x",e,t,n),S("padding",e,t,n),S("constantValue",e,t,n))];case"SpaceToBatchND":{let s=S("blockShape",e,t,n),r=S("paddings",e,t,n);return[jh(S("x",e,t,n),s,r)]}case"BatchToSpaceND":{let s=S("blockShape",e,t,n),r=S("crops",e,t,n);return[Ph(S("x",e,t,n),s,r)]}case"DepthToSpace":{let s=S("blockSize",e,t,n),r=S("dataFormat",e,t,n).toUpperCase();return[Lx(S("x",e,t,n),s,r)]}case"BroadcastTo":return[nc(S("x",e,t,n),S("shape",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}};function Jv(e,t,n,s){let r=((a,o,i)=>{switch(a.category){case"arithmetic":return H(()=>tL(a,o,i));case"basic_math":return H(()=>nL(a,o,i));case"control":return lL(a,o,i);case"convolution":return H(()=>uL(a,o,i));case"creation":return H(()=>cL(a,o,i));case"dynamic":return dL(a,o,i);case"evaluation":return H(()=>hL(a,o,i));case"image":return H(()=>AL(a,o,i));case"graph":return H(()=>pL(a,o,i));case"logical":return H(()=>gL(a,o,i));case"matrices":return H(()=>yL(a,o,i));case"normalization":return H(()=>xL(a,o,i));case"reduction":return H(()=>bL(a,o,i));case"slice_join":return H(()=>vL(a,o,i));case"sparse":return H(()=>wL(a,o,i));case"spectral":return H(()=>kL(a,o,i));case"string":return H(()=>IL(a,o,i));case"transformation":return H(()=>SL(a,o,i));case"hash_table":return mL(a,o,i,s);case"custom":let l=Cv(a.op);if(l&&l.customExecutor)return l.customExecutor(new eL(a,o,i));throw TypeError(`Custom op ${a.op} is not registered.`);default:throw TypeError(`Unknown op '${a.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 I.isPromise(r)?r.then(a=>[].concat(a)):[].concat(r)}var Qv=class{constructor(e={},t={},n={},s={}){this.weightMap=e,this.tensorArrayMap=t,this.tensorListMap=n,this.functionMap=s,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 e7(e,t,n,s){let r=new Set,a=[],o=null,i=null,l=new Set,u=Object.keys(e).map(h=>Hn(h)[0]),c=[];s!=null&&(c=s.map(h=>Hn(h.name)[0]));let d=[...t];for(;d.length>0;){let h=d.pop();if((t7(h)||RL(h)||_L(h))&&o==null&&(o=h,i=o.children.map(p=>p.name).filter(p=>r.has(p))),r.add(h.name),n[h.name]==null&&u.indexOf(h.name)===-1&&c.indexOf(h.name)===-1){if(h.inputs.length===0){a.push(h.name);continue}h.inputs.forEach(p=>{l.has(p.name)||(l.add(p.name),d.push(p))})}}return{inputs:e,outputs:t,usedNodes:r,missingInputs:a,dynamicNode:o,syncInputs:i}}function CL(e,t,n){let{usedNodes:s,inputs:r}=n,a=[],o=Object.keys(r).map(c=>Hn(c)[0]).map(c=>e.nodes[c]),i=e.initNodes;o.forEach(c=>{s.has(c.name)&&a.push(c)}),e.weights.forEach(c=>{s.has(c.name)&&a.push(c)}),i!=null&&i.forEach(c=>{s.has(c.name)&&a.push(c)});let l=new Set,u=[];for(;a.length>0;){let c=a.pop();l.add(c.name),t[c.name]||u.push(c),c.children.forEach(d=>{!l.has(d.name)&&s.has(d.name)&&d.inputs.every(h=>l.has(h.name))&&a.push(d)})}return u}var TL=["Switch","Merge","Enter","Exit","NextIteration","StatelessIf","StatelessWhile","if","While"],NL=["NonMaxSuppressionV2","NonMaxSuppressionV3","NonMaxSuppressionV5","Where"],EL=["HashTable","HashTableV2","LookupTableImport","LookupTableImportV2","LookupTableFind","LookupTableFindV2","LookupTableSize","LookupTableSizeV2"];function t7(e){return TL.indexOf(e.op)>=0}function RL(e){return NL.indexOf(e.op)>=0}function _L(e){return EL.indexOf(e.op)>=0}var q2=class{constructor(e,t){this.graph=e,this.parent=t,this.compiledMap=new Map,this._weightMap={},this.SEPERATOR=",",this._functions={},this._functionExecutorMap={},this._outputs=e.outputs,this._inputs=e.inputs,this._initNodes=e.initNodes,this._signature=e.signature,this._functions=e.functions,e.functions!=null&&Object.keys(e.functions).forEach(n=>{this._functionExecutorMap[n]=new q2(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(s=>s.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(),s=t.map(r=>r.name).sort();return n.join(this.SEPERATOR)+"--"+s.join(this.SEPERATOR)}compile(e,t){let n=e7(e,t,this.weightMap,this._initNodes),{missingInputs:s,dynamicNode:r,syncInputs:a}=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 [${a}]`);if(s.length>0){let o=t.map(l=>l.name),i=Object.keys(e);throw new Error(`Cannot compute the outputs [${o}] from the provided inputs [${i}]. Missing the following inputs: [${s}]`)}return CL(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 s=n.map(c=>this.graph.nodes[Hn(c)[0]]),r=t.map(c=>Hn(c)[0]),a=r.map(c=>this.graph.nodes[c]);a.length===0&&(a=this._outputs);let o=this.getCompilationKey(s,a),i=this.compiledMap.get(o);i==null&&(i=this.compile(e,a),this.compiledMap.set(o,i));let l={},u={};return H(()=>{let c=new Qv(this.weightMap,l,u,this.functionExecutorMap),d=Object.assign({},this.weightMap);Object.keys(e).forEach(m=>{let[f,A]=Hn(m),g=[];g[A]=e[m],d[f]=g});let h=this.getFrozenTensorIds(d),p={};for(let m=0;m<i.length;m++){let f=i[m];if(!d[f.name]){let A=Jv(f,d,c,this._resourceManager);if(I.isPromise(A))throw new Error(`The execution of the op '${f.op}' returned a promise. Please use model.executeAsync() instead.`);d[f.name]=A,this.checkTensorForDisposal(f.name,f,d,c,h,r,p)}}return this.parent==null&&c.dispose(h),t.map(m=>xn(m,d,c))})}getFrozenTensorIds(e){let t=[].concat.apply([],Object.keys(e).map(n=>e[n]).map(n=>n.map(s=>s.id)));return new Set(t)}checkTensorForDisposal(e,t,n,s,r,a,o){t.category==="control"||a.indexOf(e)!==-1||(n[e].forEach(i=>{i!=null&&(o[i.id]=(o[i.id]||0)+t.children.length)}),t.inputs.forEach(i=>{if(i.category!=="control"){let l=Fz(i.name,n,s);l!=null&&l.forEach(u=>{if(u&&!u.kept&&!r.has(u.id)){let c=o[u.id];c===1?(u.dispose(),delete o[u.id]):c!=null&&o[u.id]--}})}}))}async executeAsync(e,t){return this._executeAsync(e,t)}async _executeAsync(e,t,n=!1,s={},r={}){n||(e=this.mapInputs(e),this.checkInputs(e),this.checkInputShapeAndType(e),t=this.mapOutputs(t),this.checkOutputs(t));let a=new Qv(this.weightMap,s,r,this.functionExecutorMap),o=await this.executeWithControlFlow(e,a,t,n),i=t.map(d=>xn(d,o,a)),l=i.map(d=>d.id),u=Object.keys(e).map(d=>e[d].id),c=new Set([...l,...u,...this.weightIds]);return Object.keys(o).forEach(d=>{o[d].forEach(p=>{p&&!p.kept&&!p.isDisposed&&!c.has(p.id)&&p.dispose()})}),this.parent==null&&a.dispose(c),i}async executeFunctionAsync(e,t,n){let s=e.reduce((r,a,o)=>(r[this.inputs[o].name]=a,r),{});return this._executeAsync(s,this.outputNodes,!0,t,n)}async executeWithControlFlow(e,t,n,s){let r=Object.keys(e),a=r.map(y=>this.graph.nodes[Hn(y)[0]]),o=n.map(y=>Hn(y)[0]),i=o.map(y=>this.graph.nodes[y]);i.length===0&&(i=this._outputs);let{usedNodes:l,missingInputs:u,dynamicNode:c,syncInputs:d}=e7(e,i,this.weightMap,this._initNodes),h=[...a,...this.graph.weights,...this._initNodes||[]].map(y=>({node:y,contexts:t.currentContext})),p=Object.assign({},this.weightMap);Object.keys(e).forEach(y=>{let[x,b]=Hn(y),v=[];v[b]=e[y],p[x]=v});let m={},f=this.getFrozenTensorIds(p),A={};for(;h.length>0;){let y=this.processStack(a,h,t,p,A,f,o,m,l);await Promise.all(y)}c==null&&!s&&console.warn("This model execution did not contain any nodes with control flow or dynamic output shapes. You can use model.execute() instead.");let g=i.filter(y=>!t7(y)&&!xn(y.name,p,t)).map(y=>y.name);if(g.length>0){let y="";throw c!=null&&(y=`Alternatively, to avoid the dynamic ops, use model.execute() and specify the inputs [${d}]`),new Error(`Cannot compute the outputs [${g}] from the provided inputs [${r}]. Consider providing the following inputs: [${u}]. ${y}`)}return p}processStack(e,t,n,s,r,a,o,i,l){let u=[];for(;t.length>0;){let c=t.pop();n.currentContext=c.contexts;let d="";if(c.node.op==="Enter"&&S("isConstant",c.node,s,n)&&([d]=kr(c.node.name,n)),s[c.node.name]==null){let h=Jv(c.node,s,n,this._resourceManager);d||([d]=kr(c.node.name,n));let p=n.currentContext;I.isPromise(h)?u.push(h.then(m=>(s[d]=m,n.currentContext=p,this.checkTensorForDisposal(d,c.node,s,n,a,o,i),this.processChildNodes(c.node,t,n,s,r,l),m))):(s[d]=h,this.checkTensorForDisposal(d,c.node,s,n,a,o,i),this.processChildNodes(c.node,t,n,s,r,l))}else this.processChildNodes(c.node,t,n,s,r,l)}return u}processChildNodes(e,t,n,s,r,a){e.children.forEach(o=>{let[i]=kr(o.name,n);r[i]||!a.has(o.name)||(o.op==="Merge"?o.inputNames.some(l=>!!xn(l,s,n))&&(r[i]=!0,t.push({contexts:n.currentContext,node:o})):o.inputNames.every(l=>!!xn(l,s,n))&&(r[i]=!0,t.push({contexts:n.currentContext,node:o})))})}dispose(){Object.keys(this.weightMap).forEach(e=>this.weightMap[e].forEach(t=>t.dispose()))}checkInputShapeAndType(e){Object.keys(e).forEach(t=>{let n=e[t],[s]=Hn(t),r=this.graph.nodes[s];if(r.attrParams.shape&&r.attrParams.shape.value){let a=r.attrParams.shape.value,o=a.length===n.shape.length&&n.shape.every((i,l)=>a[l]===-1||a[l]===i);I.assert(o,()=>`The shape of dict['${r.name}'] provided in model.execute(dict) must be [${a}], but was [${n.shape}]`)}r.attrParams.dtype&&r.attrParams.dtype.value&&I.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 ${n.dtype}`)})}mapInputs(e){let t={};for(let n in e)if(this._signature!=null&&this._signature.inputs!=null&&this._signature.inputs[n]!=null){let s=this._signature.inputs[n];t[s.name]=e[n]}else t[n]=e[n];return t}checkInputs(e){let t=Object.keys(e).filter(n=>{let[s]=Hn(n);return this.graph.nodes[s]==null});if(t.length>0)throw new Error(`The dict provided in model.execute(dict) has keys: [${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]=Hn(t);if(!this.graph.nodes[n])throw new Error(`The output '${t}' is not found in the graph`)})}},$L=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]}},FL="?tfjs-format=file",DL="model.json",n7=class{constructor(e,t={}){this.modelUrl=e,this.loadOptions=t,this.version="n/a",t==null&&(this.loadOptions={}),this.resourceManager=new $L}get modelVersion(){return this.version}get inputNodes(){return this.executor.inputNodes}get outputNodes(){return this.executor.outputNodes}get inputs(){return this.executor.inputs}get outputs(){return this.executor.outputs}get weights(){return this.executor.weightMap}get metadata(){return this.artifacts.userDefinedMetadata}get modelSignature(){return this.signature}findIOHandler(){let e=this.modelUrl;if(e.load!=null)this.handler=e;else if(this.loadOptions.requestInit!=null)this.handler=Tn.browserHTTPRequest(e,this.loadOptions);else{let t=Tn.getLoadHandlers(e,this.loadOptions);if(t.length===0)t.push(Tn.browserHTTPRequest(e,this.loadOptions));else if(t.length>1)throw new Error(`Found more than one (${t.length}) load handlers for URL '${[e]}'`);this.handler=t[0]}}async load(){if(this.findIOHandler(),this.handler.load==null)throw new Error("Cannot proceed with model loading because the IOHandler provided does not have the `load` method implemented.");let e=await this.handler.load();return this.loadSync(e)}loadSync(e){this.artifacts=e;let t=this.artifacts.modelTopology,n;this.artifacts.userDefinedMetadata!=null&&this.artifacts.userDefinedMetadata.signature!=null?n=this.artifacts.userDefinedMetadata.signature:n=this.artifacts.signature,this.signature=n,this.version=`${t.versions.producer}.${t.versions.minConsumer}`;let s=Tn.decodeWeights(this.artifacts.weightData,this.artifacts.weightSpecs);if(this.executor=new q2(jv.Instance.transformGraph(t,this.signature)),this.executor.weightMap=this.convertTensorMapToTensorsMap(s),this.executor.resourceManager=this.resourceManager,e.modelInitializer!=null&&e.modelInitializer.node!=null){let r=jv.Instance.transformGraph(e.modelInitializer);this.initializer=new q2(r),this.initializer.weightMap=this.executor.weightMap,this.initializer.resourceManager=this.resourceManager,this.initializer.executeAsync({},[])}return!0}async save(e,t){if(typeof e=="string"){let n=Tn.getSaveHandlers(e);if(n.length===0)throw new Error(`Cannot find any save handlers for URL '${e}'`);if(n.length>1)throw new Error(`Found more than one (${n.length}) save handlers for URL '${e}'`);e=n[0]}if(e.save==null)throw new Error("GraphModel.save() cannot proceed because the IOHandler provided does not have the `save` attribute defined.");return e.save(this.artifacts)}predict(e,t){return this.execute(e,this.outputNodes)}normalizeInputs(e){if(!(e instanceof Ue)&&!Array.isArray(e))return e;if(e=Array.isArray(e)?e:[e],e.length!==this.inputNodes.length)throw new Error(`Input tensor count mismatch,the graph model has ${this.inputNodes.length} placeholders, while there are ${e.length} input tensors.`);return this.inputNodes.reduce((t,n,s)=>(t[n]=e[s],t),{})}normalizeOutputs(e){return e=e||this.outputNodes,Array.isArray(e)?e:[e]}execute(e,t){e=this.normalizeInputs(e),t=this.normalizeOutputs(t);let n=this.executor.execute(e,t);return n.length>1?n:n[0]}async executeAsync(e,t){e=this.normalizeInputs(e),t=this.normalizeOutputs(t);let n=await this.executor.executeAsync(e,t);return n.length>1?n:n[0]}convertTensorMapToTensorsMap(e){return Object.keys(e).reduce((t,n)=>(t[n]=[e[n]],t),{})}dispose(){this.executor.dispose(),this.initializer&&this.initializer.dispose(),this.resourceManager.dispose()}};async function ht(e,t={}){if(e==null)throw new Error("modelUrl in loadGraphModel() cannot be null. 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Should have ${this.fullColumnNames.length} elements in a row, but got ${n}`);return n}},A7=class extends Yt{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(ee().get("IS_NODE"))throw new Error("microphone API is only supported in browser environment.");let t=new A7(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 s=this.flattenQueue(n.freqDataQueue);e=this.getTensorFromAudioDataArray(s,[this.numFrames,this.columnTruncateLength,1])}if(this.includeWaveform){let s=this.flattenQueue(n.timeDataQueue);t=this.getTensorFromAudioDataArray(s,[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(s=>{let r=setInterval(()=>{this.includeSpectrogram&&(this.analyser.getFloatFrequencyData(this.freqData),this.freqData[0]===-1/0&&s({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),s({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((s,r)=>n.set(s,r*t)),n}getTensorFromAudioDataArray(e,t){let n=new Float32Array(I.sizeFromShape(t));return n.set(e,n.length-e.length),on(n,t)}},g7=class extends Yt{constructor(e,t){super();if(this.webcamVideoElement=e,this.webcamConfig=t,this.isClosed=!0,this.resize=!1,this.needToResize())if(this.resize=!0,this.cropSize=[this.webcamConfig.resizeHeight,this.webcamConfig.resizeWidth],this.cropBoxInd=Ot([0],"int32"),this.webcamConfig.centerCrop){let n=this.webcamConfig.resizeWidth*1/this.webcamVideoElement.width,s=this.webcamConfig.resizeHeight*1/this.webcamVideoElement.height,r=(1-n)/2,a=(1-s)/2,o=r+n,i=s+a;this.cropBox=_s([a,r,i,o],[1,4])}else this.cropBox=_s([0,0,1,1],[1,4])}summary(){return"webcam"}static async create(e,t={}){if(ee().get("IS_NODE"))throw new Error("tf.data.webcam is only supported in browser environment.");if(!e){if(e=document.createElement("video"),!t.resizeWidth||!t.resizeHeight)throw new Error("Please provide webcam video element, or resizeWidth and resizeHeight to create a hidden video element.");e.width=t.resizeWidth,e.height=t.resizeHeight}let n=new g7(e,t);return await n.start(),n}async start(){this.webcamConfig.facingMode&&I.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=rs.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 H(()=>{let t=Ft(ue(e,"float32"),0),n;n=Re.cropAndResize(t,this.cropBox,this.cropBoxInd,this.cropSize,"bilinear");let s=n.shape;return U(n,s.slice(1))})}async capture(){return(await this.next()).value}stop(){this.stream.getTracks().forEach(t=>t.stop());try{this.webcamVideoElement.srcObject=null}catch(t){console.log(t),this.webcamVideoElement.src=null}this.isClosed=!0}toArray(){throw new Error("Can not convert infinite video stream to array.")}},y7=class{},x7=class extends Yt{split(e){return new lB(this,e)}},lB=class extends 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============================
Hi there \u{1F44B}. Looks like you are running TensorFlow.js in Node.js. To speed things up dramatically, install our node backend, which binds to TensorFlow C++, by running npm i @tensorflow/tfjs-node, or npm i @tensorflow/tfjs-node-gpu if you have CUDA. Then call require('@tensorflow/tfjs-node'); (-gpu suffix for CUDA) at the start of your program. Visit https://github.com/tensorflow/tfjs-node for more details.
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}
bvec4 isnan_custom(vec4 val) {
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#define isnan(value) isnan_custom(value)
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}
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const float FLOAT_MIN = 1.17549435e-38;
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c[0] = floor(8388608.0 * m);
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}
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result = values[1];
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vec2 uv;
vec4 values;
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}`;return Rw(e,n)}function n6(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 Dw(e,t)}function s6(e){let t=new Uint16Array([0,1,2,2,1,3]);return Ow(e,t)}function Hc(e,t,n,s,r,a){Mw(t,n);let o=Pw(e),i=e.TEXTURE_2D;return be(e,()=>e.bindTexture(i,o)),be(e,()=>e.texParameteri(i,e.TEXTURE_WRAP_S,e.CLAMP_TO_EDGE)),be(e,()=>e.texParameteri(i,e.TEXTURE_WRAP_T,e.CLAMP_TO_EDGE)),be(e,()=>e.texParameteri(i,e.TEXTURE_MIN_FILTER,e.NEAREST)),be(e,()=>e.texParameteri(i,e.TEXTURE_MAG_FILTER,e.NEAREST)),be(e,()=>e.texImage2D(i,0,s,t,n,0,r,a,null)),be(e,()=>e.bindTexture(e.TEXTURE_2D,null)),o}function b1(e){return e.internalFormatFloat}function r6(e,t,n,s){let[r,a]=Lc(t,n);return Hc(e,r,a,b1(s),s.textureFormatFloat,e.FLOAT)}function v1(e){return e.internalFormatHalfFloat}function a6(e,t,n,s){let[r,a]=Lc(t,n);return Hc(e,r,a,v1(s),s.textureFormatFloat,s.textureTypeHalfFloat)}function w1(e){return e.downloadTextureFormat}function o6(e,t,n,s){let[r,a]=Lc(t,n);return Hc(e,r,a,w1(s),e.RGBA,e.UNSIGNED_BYTE)}function k1(e){return e.internalFormatPackedFloat}function i6(e,t,n,s){let[r,a]=Gl(t,n);return Hc(e,r,a,k1(s),e.RGBA,e.FLOAT)}function I1(e){return e.internalFormatPackedHalfFloat}function l6(e,t,n,s){let[r,a]=Gl(t,n);return Hc(e,r,a,I1(s),e.RGBA,s.textureTypeHalfFloat)}function u6(e,t,n){let s=0,r=3*4,a=3*4+2*4;return be(e,()=>e.bindBuffer(e.ARRAY_BUFFER,n)),m1(e,t,"clipSpacePos",n,3,a,s)&&m1(e,t,"uv",n,2,a,r)}function c6(e,t,n,s,r,a){be(e,()=>e.bindTexture(e.TEXTURE_2D,t));let o,i,l;r instanceof Uint8Array?(o=new Uint8Array(n*s*4),i=e.UNSIGNED_BYTE,l=e.RGBA):(o=new Float32Array(n*s*4),i=e.FLOAT,l=a.internalFormatPackedFloat),o.set(r),be(e,()=>e.texImage2D(e.TEXTURE_2D,0,l,n,s,0,e.RGBA,i,o)),be(e,()=>e.bindTexture(e.TEXTURE_2D,null))}function d6(e,t,n){be(e,()=>e.bindTexture(e.TEXTURE_2D,t)),n.data instanceof Uint8Array?be(e,()=>e.texImage2D(e.TEXTURE_2D,0,e.RGBA,n.width,n.height,0,e.RGBA,e.UNSIGNED_BYTE,n.data)):be(e,()=>e.texImage2D(e.TEXTURE_2D,0,e.RGBA,e.RGBA,e.UNSIGNED_BYTE,n)),be(e,()=>e.bindTexture(e.TEXTURE_2D,null))}function h6(e,t,n,s){let r=e.createBuffer();be(e,()=>e.bindBuffer(e.PIXEL_PACK_BUFFER,r));let i=4*4*t*n;return be(e,()=>e.bufferData(e.PIXEL_PACK_BUFFER,i,e.STREAM_READ)),be(e,()=>e.readPixels(0,0,n,t,e.RGBA,e.FLOAT,0)),be(e,()=>e.bindBuffer(e.PIXEL_PACK_BUFFER,null)),r}function p6(e,t,n){let s=e,r=new Float32Array(n);return s.bindBuffer(s.PIXEL_PACK_BUFFER,t),s.getBufferSubData(s.PIXEL_PACK_BUFFER,0,r),s.bindBuffer(s.PIXEL_PACK_BUFFER,null),r}function f6(e,t,n,s){let[r,a]=Lc(t,n),o=4,i=new Uint8Array(kj(t*n,o));return be(e,()=>e.readPixels(0,0,r,a,s.downloadTextureFormat,e.UNSIGNED_BYTE,i)),new Float32Array(i.buffer)}function m6(e,t,n,s,r,a,o,i){let l=e,u=new Float32Array(Ij(a,o));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 A6(e,t,n){let s=new Float32Array(t*n*4);return be(e,()=>e.readPixels(0,0,n,t,e.RGBA,e.FLOAT,s)),s}var uf=class{constructor(e){this.outputTexture=null,this.program=null,this.disposed=!1,this.vertexAttrsAreBound=!1,this.itemsToPoll=[];let t=ee().getNumber("WEBGL_VERSION");e!=null?(this.gl=e,tf(t,e)):this.gl=ar(t);let n="WEBGL_color_buffer_float",s="EXT_color_buffer_half_float";if(ee().getNumber("WEBGL_VERSION")===1){let r="OES_texture_float",a="OES_texture_half_float";if(this.textureFloatExtension=Wc(this.gl,r),ms(this.gl,a))this.textureHalfFloatExtension=Wc(this.gl,a);else if(ee().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),ms(this.gl,s))this.colorBufferHalfFloatExtension=Wc(this.gl,s);else if(ee().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",ms(this.gl,n))this.colorBufferFloatExtension=this.gl.getExtension(n);else if(ms(this.gl,s))this.colorBufferHalfFloatExtension=this.gl.getExtension(s);else throw new Error("GL context does not support color renderable floats");this.vertexBuffer=n6(this.gl),this.indexBuffer=s6(this.gl),this.framebuffer=zw(this.gl),this.textureConfig=f1(this.gl,this.textureHalfFloatExtension)}get debug(){return ee().getBool("DEBUG")}dispose(){if(this.disposed)return;this.program!=null&&console.warn("Disposing a GPGPUContext that still has a bound WebGLProgram. This is probably a resource leak, delete the program with GPGPUContext.deleteProgram before disposing."),this.outputTexture!=null&&console.warn("Disposing a GPGPUContext that still has a bound output matrix texture. This is probably a resource leak, delete the output matrix texture with GPGPUContext.deleteMatrixTexture before disposing.");let e=this.gl;be(e,()=>e.finish()),be(e,()=>e.bindFramebuffer(e.FRAMEBUFFER,null)),be(e,()=>e.deleteFramebuffer(this.framebuffer)),be(e,()=>e.bindBuffer(e.ARRAY_BUFFER,null)),be(e,()=>e.bindBuffer(e.ELEMENT_ARRAY_BUFFER,null)),be(e,()=>e.deleteBuffer(this.indexBuffer)),this.disposed=!0}createFloat32MatrixTexture(e,t){return this.throwIfDisposed(),r6(this.gl,e,t,this.textureConfig)}createFloat16MatrixTexture(e,t){return this.throwIfDisposed(),a6(this.gl,e,t,this.textureConfig)}createUnsignedBytesMatrixTexture(e,t){return this.throwIfDisposed(),o6(this.gl,e,t,this.textureConfig)}uploadPixelDataToTexture(e,t){this.throwIfDisposed(),d6(this.gl,e,t)}uploadDenseMatrixToTexture(e,t,n,s){this.throwIfDisposed(),c6(this.gl,e,t,n,s,this.textureConfig)}createFloat16PackedMatrixTexture(e,t){return this.throwIfDisposed(),l6(this.gl,e,t,this.textureConfig)}createPackedMatrixTexture(e,t){return this.throwIfDisposed(),i6(this.gl,e,t,this.textureConfig)}deleteMatrixTexture(e){this.throwIfDisposed(),this.outputTexture===e&&(A1(this.gl,this.framebuffer),this.outputTexture=null),be(this.gl,()=>this.gl.deleteTexture(e))}downloadByteEncodedFloatMatrixFromOutputTexture(e,t,n){return this.downloadMatrixDriver(e,()=>f6(this.gl,t,n,this.textureConfig))}downloadPackedMatrixFromBuffer(e,t,n,s,r,a){return m6(this.gl,e,t,n,s,r,a,this.textureConfig)}downloadFloat32MatrixFromBuffer(e,t){return p6(this.gl,e,t)}createBufferFromTexture(e,t,n){this.bindTextureToFrameBuffer(e);let s=h6(this.gl,t,n,this.textureConfig);return this.unbindTextureToFrameBuffer(),s}createAndWaitForFence(){let e=this.createFence(this.gl);return this.pollFence(e)}createFence(e){let t,n;if(ee().getBool("WEBGL_FENCE_API_ENABLED")){let s=e,r=s.fenceSync(s.SYNC_GPU_COMMANDS_COMPLETE,0);e.flush(),n=()=>{let a=s.clientWaitSync(r,0,0);return a===s.ALREADY_SIGNALED||a===s.CONDITION_SATISFIED},t=r}else ee().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")>0?(t=this.beginQuery(),this.endQuery(),n=()=>this.isQueryAvailable(t,ee().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))):n=()=>!0;return{query:t,isFencePassed:n}}downloadMatrixFromPackedTexture(e,t,n){return this.downloadMatrixDriver(e,()=>A6(this.gl,t,n))}createProgram(e){this.throwIfDisposed();let t=this.gl,n=_w(t,e);this.vertexShader==null&&(this.vertexShader=t6(t));let s=$w(t);return be(t,()=>t.attachShader(s,this.vertexShader)),be(t,()=>t.attachShader(s,n)),Fw(t,s),this.debug&&nf(t,s),this.vertexAttrsAreBound||(this.setProgram(s),this.vertexAttrsAreBound=u6(t,this.program,this.vertexBuffer)),s}deleteProgram(e){this.throwIfDisposed(),e===this.program&&(this.program=null),e!=null&&be(this.gl,()=>this.gl.deleteProgram(e))}setProgram(e){this.throwIfDisposed(),this.program=e,this.program!=null&&this.debug&&nf(this.gl,this.program),be(this.gl,()=>this.gl.useProgram(e))}getUniformLocation(e,t,n=!0){return this.throwIfDisposed(),n?Bw(this.gl,e,t):Ww(this.gl,e,t)}getAttributeLocation(e,t){return this.throwIfDisposed(),be(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(),Vw(this.gl,e,t,n)}setOutputMatrixTexture(e,t,n){this.setOutputMatrixTextureDriver(e,n,t)}setOutputPackedMatrixTexture(e,t,n){this.throwIfDisposed();let[s,r]=Gl(t,n);this.setOutputMatrixTextureDriver(e,s,r)}setOutputMatrixWriteRegion(e,t,n,s){this.setOutputMatrixWriteRegionDriver(n,e,s,t)}setOutputPackedMatrixWriteRegion(e,t,n,s){throw new Error("setOutputPackedMatrixWriteRegion not implemented.")}debugValidate(){this.program!=null&&nf(this.gl,this.program),Vc(this.gl)}executeProgram(){this.throwIfDisposed(),this.throwIfNoProgram();let e=this.gl;this.debug&&this.debugValidate(),be(e,()=>e.drawElements(e.TRIANGLES,6,e.UNSIGNED_SHORT,0))}blockUntilAllProgramsCompleted(){this.throwIfDisposed(),be(this.gl,()=>this.gl.finish())}getQueryTimerExtension(){return this.disjointQueryTimerExtension==null&&(this.disjointQueryTimerExtension=Wc(this.gl,ee().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(ee().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")===2){let n=this.gl,s=this.getQueryTimerExtensionWebGL2(),r=n.createQuery();return n.beginQuery(s.TIME_ELAPSED_EXT,r),r}let e=this.getQueryTimerExtensionWebGL1(),t=e.createQueryEXT();return e.beginQueryEXT(e.TIME_ELAPSED_EXT,t),t}endQuery(){if(ee().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 I.repeatedTry(()=>this.disposed||this.isQueryAvailable(e,ee().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))),this.getQueryTime(e,ee().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))}getQueryTime(e,t){if(t===0)return null;if(t===2){let n=this.gl;return n.getQueryParameter(e,n.QUERY_RESULT)/1e6}else{let n=this.getQueryTimerExtensionWebGL1();return n.getQueryObjectEXT(e,n.QUERY_RESULT_EXT)/1e6}}isQueryAvailable(e,t){if(t===0)return!0;if(t===2){let n=this.gl,s=this.getQueryTimerExtensionWebGL2(),r=n.getQueryParameter(e,n.QUERY_RESULT_AVAILABLE);return this.disjoint==null&&(this.disjoint=this.gl.getParameter(s.GPU_DISJOINT_EXT)),r&&!this.disjoint}else{let n=this.getQueryTimerExtensionWebGL1(),s=n.getQueryObjectEXT(e,n.QUERY_RESULT_AVAILABLE_EXT);return this.disjoint==null&&(this.disjoint=this.gl.getParameter(n.GPU_DISJOINT_EXT)),s&&!this.disjoint}}pollFence(e){return new Promise(t=>{this.addItemToPoll(()=>e.isFencePassed(),()=>t())})}pollItems(){let e=Vj(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){this.itemsToPoll.push({isDoneFn:e,resolveFn:t}),!(this.itemsToPoll.length>1)&&I.repeatedTry(()=>(this.pollItems(),this.itemsToPoll.length===0))}bindTextureToFrameBuffer(e){this.throwIfDisposed(),sf(this.gl,e,this.framebuffer),this.debug&&Vc(this.gl)}unbindTextureToFrameBuffer(){this.outputTexture!=null?(sf(this.gl,this.outputTexture,this.framebuffer),this.debug&&Vc(this.gl)):A1(this.gl,this.framebuffer)}downloadMatrixDriver(e,t){this.bindTextureToFrameBuffer(e);let n=t();return this.unbindTextureToFrameBuffer(),n}setOutputMatrixTextureDriver(e,t,n){this.throwIfDisposed();let s=this.gl;sf(s,e,this.framebuffer),this.debug&&Vc(s),this.outputTexture=e,be(s,()=>s.viewport(0,0,t,n)),be(s,()=>s.scissor(0,0,t,n))}setOutputMatrixWriteRegionDriver(e,t,n,s){this.throwIfDisposed(),be(this.gl,()=>this.gl.scissor(e,t,n,s))}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 Vj(e){let t=0;for(;t<e.length&&e[t]();++t);return t-1}var{getBroadcastDims:g6}=$;function Uj(e,t,n){let s=[];if(e.forEach(p=>{let m=I.sizeFromShape(p.shapeInfo.logicalShape);if(p.shapeInfo.isUniform?s.push(`uniform float ${p.name}${m>1?`[${m}]`:""};`):(s.push(`uniform sampler2D ${p.name};`),s.push(`uniform int offset${p.name};`)),n.enableShapeUniforms){let{uniformShape:f}=S1(n.packedInputs,p.shapeInfo.logicalShape,p.shapeInfo.texShape);switch(f.length){case 1:s.push(`uniform int ${p.name}Shape;`);break;case 2:s.push(`uniform ivec2 ${p.name}Shape;`);break;case 3:s.push(`uniform ivec3 ${p.name}Shape;`);break;case 4:s.push(`uniform ivec4 ${p.name}Shape;`);break;default:break}s.push(`uniform ivec2 ${p.name}TexShape;`)}}),n.enableShapeUniforms){switch(t.logicalShape.length){case 1:s.push("uniform int outShape;");break;case 2:s.push("uniform ivec2 outShape;"),s.push("uniform int outShapeStrides;");break;case 3:s.push("uniform ivec3 outShape;"),s.push("uniform ivec2 outShapeStrides;");break;case 4:s.push("uniform ivec4 outShape;"),s.push("uniform ivec3 outShapeStrides;");break;default:break}s.push("uniform ivec2 outTexShape;")}n.customUniforms&&n.customUniforms.forEach(p=>{s.push(`uniform ${p.type} ${p.name}${p.arrayIndex?`[${p.arrayIndex}]`:""};`)});let r=s.join(`
`),a=e.map(p=>Hj(p,t,n.packedInputs,n.enableShapeUniforms)).join(`
`),o=t.texShape,i=bn(),l=qj(i),u,c,d=Zj(i);return t.isPacked?(u=Gj(t.logicalShape,o,n.enableShapeUniforms),c=Kj(i)):(u=jj(t.logicalShape,o,n.enableShapeUniforms),c=Xj(i)),n.packedInputs&&(d+=eq),[d,l,c,r,u,a,n.userCode].join(`
`)}function ql(e,t=!1){let n=e.shapeInfo.logicalShape;switch(n.length){case 0:return hq(e,t);case 1:return fq(e,t);case 2:return Aq(e,t);case 3:return yq(e,t);case 4:return bq(e,t);case 5:return vq(e);case 6:return wq(e);default:throw new Error(`${n.length}-D input sampling is not yet supported`)}}function y6(e,t){switch(e.shapeInfo.logicalShape.length){case 0:return dq(e);case 1:return pq(e,t);case 2:return mq(e,t);case 3:return gq(e,t);default:return xq(e,t)}}function Hj(e,t,n=!1,s){let r="";n?r+=y6(e,s):r+=ql(e,s);let a=e.shapeInfo.logicalShape,o=t.logicalShape;return a.length<=o.length&&(n?r+=kq(e,t):r+=Iq(e,t)),r}function Gj(e,t,n){switch(e.length){case 0:return x6();case 1:return tq(e,t,n);case 2:return uq(e,t,n);case 3:return sq(e,t,n);default:return aq(e,t,n)}}function jj(e,t,n){switch(e.length){case 0:return x6();case 1:return nq(e,t,n);case 2:return cq(e,t,n);case 3:return rq(e,t,n);case 4:return oq(e,t,n);case 5:return iq(e,t);case 6:return lq(e,t);default:throw new Error(`${e.length}-D output sampling is not yet supported`)}}function qj(e){return`
float sampleTexture(sampler2D textureSampler, vec2 uv) {
return ${e.texture2D}(textureSampler, uv).r;
}
`}function Xj(e){return`
void setOutput(float val) {
${e.output} = vec4(val, 0, 0, 0);
}
`}function Kj(e){return`
void setOutput(vec4 val) {
${e.output} = val;
}
`}function Zj(e){return`${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);
}
${Yj}
${Jj}
${Qj}
`}var Yj=`
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);
}
`,Jj=`
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);
}
`,Qj=`
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);
}
`,eq=`
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 x6(){return`
int getOutputCoords() {
return 0;
}
`}function tq(e,t,n){let s=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)];return s[0]===1?n?`
int getOutputCoords() {
return 2 * int(resultUV.x * ceil(float(outTexShape[1]) / 2.0));
}
`:`
int getOutputCoords() {
return 2 * int(resultUV.x * ${s[1]}.0);
}
`:s[1]===1?n?`
int getOutputCoords() {
return 2 * int(resultUV.y * ceil(float(outTexShape[0]) / 2.0));
}
`:`
int getOutputCoords() {
return 2 * int(resultUV.y * ${s[0]}.0);
}
`:n?`
int getOutputCoords() {
ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(packedTexShape[0], packedTexShape[1]));
return 2 * (resTexRC.x * packedTexShape[1] + resTexRC.y);
}
`:`
int getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${s[0]}, ${s[1]}));
return 2 * (resTexRC.x * ${s[1]} + resTexRC.y);
}
`}function nq(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 * ${t[1]} + resTexRC.y;
}
`}function sq(e,t,n){if(n)return`
ivec3 getOutputCoords() {
ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));
int texelsInLogicalRow = int(ceil(float(outShape[2]) / 2.0));
int texelsInBatch = texelsInLogicalRow * int(ceil(float(outShape[1]) / 2.0));
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(packedTexShape[0], packedTexShape[1]));
int index = resTexRC.x * packedTexShape[1] + resTexRC.y;
int b = index / texelsInBatch;
index -= b * texelsInBatch;
int r = 2 * (index / texelsInLogicalRow);
int c = imod(index, texelsInLogicalRow) * 2;
return ivec3(b, r, c);
}
`;let s=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)],r=Math.ceil(e[2]/2),a=r*Math.ceil(e[1]/2);return`
ivec3 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${s[0]}, ${s[1]}));
int index = resTexRC.x * ${s[1]} + resTexRC.y;
int b = index / ${a};
index -= b * ${a};
int r = 2 * (index / ${r});
int c = imod(index, ${r}) * 2;
return ivec3(b, r, c);
}
`}function rq(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;
${Jw(["r","c","d"],e)}
return ivec3(r, c, d);
}
`;let s=Uo(["r","c","d"],e);return`
ivec3 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${t[0]}, ${t[1]}));
int index = resTexRC.x * ${t[1]} + resTexRC.y;
${s}
return ivec3(r, c, d);
}
`}function aq(e,t,n){if(n)return`
ivec4 getOutputCoords() {
ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(packedTexShape[0], packedTexShape[1]));
int index = resTexRC.x * packedTexShape[1] + resTexRC.y;
int texelsInLogicalRow = int(ceil(float(outShape[3]) / 2.0));
int texelsInBatch = texelsInLogicalRow * int(ceil(float(outShape[2]) / 2.0));
int texelsInBatchN = texelsInBatch * outShape[1];
int b2 = index / texelsInBatchN;
index -= b2 * texelsInBatchN;
int b = index / texelsInBatch;
index -= b * texelsInBatch;
int r = 2 * (index / texelsInLogicalRow);
int c = imod(index, texelsInLogicalRow) * 2;
return ivec4(b2, b, r, c);
}
`;let s=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)],r=Math.ceil(e[e.length-1]/2),a=r*Math.ceil(e[e.length-2]/2),o=a,i="",l="b, r, c";for(let u=2;u<e.length-1;u++)o*=e[e.length-u-1],i=`
int b${u} = index / ${o};
index -= b${u} * ${o};
`+i,l=`b${u}, `+l;return`
ivec${e.length} getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${s[0]}, ${s[1]}));
int index = resTexRC.x * ${s[1]} + resTexRC.y;
${i}
int b = index / ${a};
index -= b * ${a};
int r = 2 * (index / ${r});
int c = imod(index, ${r}) * 2;
return ivec${e.length}(${l});
}
`}function oq(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;
${Jw(["r","c","d","d2"],e)}
return ivec4(r, c, d, d2);
}
`;let s=Uo(["r","c","d","d2"],e);return`
ivec4 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${t[0]}, ${t[1]}));
int index = resTexRC.x * ${t[1]} + resTexRC.y;
${s}
return ivec4(r, c, d, d2);
}
`}function iq(e,t){let n=Uo(["r","c","d","d2","d3"],e);return`
ivec5 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx * vec2(${t[0]},
${t[1]}));
int index = resTexRC.x * ${t[1]} + resTexRC.y;
${n}
ivec5 outShape = ivec5(r, c, d, d2, d3);
return outShape;
}
`}function lq(e,t){let n=Uo(["r","c","d","d2","d3","d4"],e);return`
ivec6 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${t[0]}, ${t[1]}));
int index = resTexRC.x * ${t[1]} + resTexRC.y;
${n}
ivec6 result = ivec6(r, c, d, d2, d3, d4);
return result;
}
`}function uq(e,t,n){let s=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)];if(I.arraysEqual(e,t))return n?`
ivec2 getOutputCoords() {
ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));
return 2 * ivec2(resultUV.yx * vec2(packedTexShape[0], packedTexShape[1]));
}
`:`
ivec2 getOutputCoords() {
return 2 * ivec2(resultUV.yx * vec2(${s[0]}, ${s[1]}));
}
`;let r=Math.ceil(e[1]/2);return n?`
ivec2 getOutputCoords() {
ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));
int texelsInLogicalRow = int(ceil(float(outShape[1]) / 2.0));
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(packedTexShape[0], packedTexShape[1]));
int index = resTexRC.x * packedTexShape[1] + resTexRC.y;
int r = 2 * (index / texelsInLogicalRow);
int c = imod(index, texelsInLogicalRow) * 2;
return ivec2(r, c);
}
`:`
ivec2 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${s[0]}, ${s[1]}));
int index = resTexRC.x * ${s[1]} + resTexRC.y;
int r = 2 * (index / ${r});
int c = imod(index, ${r}) * 2;
return ivec2(r, c);
}
`}function cq(e,t,n){return I.arraysEqual(e,t)?n?`
ivec2 getOutputCoords() {
return ivec2(resultUV.yx * vec2(outTexShape[0], outTexShape[1]));
}
`:`
ivec2 getOutputCoords() {
return ivec2(resultUV.yx * vec2(${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 * ${e[1]};
return ivec2(r, c);
}
`}function Ho(e){return`offset${e}`}function dq(e){let t=e.name,n="get"+t.charAt(0).toUpperCase()+t.slice(1),s=bn();return`
vec4 ${n}() {
return ${s.texture2D}(${t}, halfCR);
}
`}function hq(e,t){let n=e.name,s="get"+n.charAt(0).toUpperCase()+n.slice(1);if(e.shapeInfo.isUniform)return`float ${s}() {return ${n};}`;let[r,a]=e.shapeInfo.texShape;if(r===1&&a===1)return`
float ${s}() {
return sampleTexture(${n}, halfCR);
}
`;let o=Ho(n);if(t)return`
float ${s}() {
vec2 uv = uvFromFlat(${n}TexShape[0], ${n}TexShape[1], ${o});
return sampleTexture(${n}, uv);
}
`;let[i,l]=e.shapeInfo.texShape;return`
float ${s}() {
vec2 uv = uvFromFlat(${i}, ${l}, ${o});
return sampleTexture(${n}, uv);
}
`}function pq(e,t){let n=e.name,s="get"+n.charAt(0).toUpperCase()+n.slice(1),r=e.shapeInfo.texShape,a=bn();if(t)return`
vec4 ${s}(int index) {
ivec2 packedTexShape = ivec2(ceil(float(${n}TexShape[0]) / 2.0), ceil(float(${n}TexShape[1]) / 2.0));
vec2 uv = packedUVfrom1D(
packedTexShape[0], packedTexShape[1], index);
return ${a.texture2D}(${n}, uv);
}
`;let o=[Math.ceil(r[0]/2),Math.ceil(r[1]/2)];return`
vec4 ${s}(int index) {
vec2 uv = packedUVfrom1D(
${o[0]}, ${o[1]}, index);
return ${a.texture2D}(${n}, uv);
}
`}function fq(e,t){let n=e.name,s="get"+n.charAt(0).toUpperCase()+n.slice(1);if(e.shapeInfo.isUniform)return`
float ${s}(int index) {
${Xl(e)}
}
`;let r=e.shapeInfo.texShape,a=r[0],o=r[1];if(o===1&&a===1)return`
float ${s}(int index) {
return sampleTexture(${n}, halfCR);
}
`;let i=Ho(n);return o===1?t?`
float ${s}(int index) {
vec2 uv = vec2(0.5, (float(index + ${i}) + 0.5) / float(${n}TexShape[0]));
return sampleTexture(${n}, uv);
}
`:`
float ${s}(int index) {
vec2 uv = vec2(0.5, (float(index + ${i}) + 0.5) / ${a}.0);
return sampleTexture(${n}, uv);
}
`:a===1?t?`
float ${s}(int index) {
vec2 uv = vec2((float(index + ${i}) + 0.5) / float(${n}TexShape[1]), 0.5);
return sampleTexture(${n}, uv);
}
`:`
float ${s}(int index) {
vec2 uv = vec2((float(index + ${i}) + 0.5) / ${o}.0, 0.5);
return sampleTexture(${n}, uv);
}
`:t?`
float ${s}(int index) {
vec2 uv = uvFromFlat(${n}TexShape[0], ${n}TexShape[1], index + ${i});
return sampleTexture(${n}, uv);
}
`:`
float ${s}(int index) {
vec2 uv = uvFromFlat(${a}, ${o}, index + ${i});
return sampleTexture(${n}, uv);
}
`}function mq(e,t){let n=e.shapeInfo.logicalShape,s=e.name,r="get"+s.charAt(0).toUpperCase()+s.slice(1),a=e.shapeInfo.texShape,o=a[0],i=a[1],l=bn();if(a!=null&&I.arraysEqual(n,a))return t?`
vec4 ${r}(int row, int col) {
vec2 uv = (vec2(col, row) + halfCR) / vec2(${s}TexShape[1], ${s}TexShape[0]);
return ${l.texture2D}(${s}, uv);
}
`:`
vec4 ${r}(int row, int col) {
vec2 uv = (vec2(col, row) + halfCR) / vec2(${i}.0, ${o}.0);
return ${l.texture2D}(${s}, uv);
}
`;if(t)return`
vec4 ${r}(int row, int col) {
ivec2 packedTexShape = ivec2(ceil(float(${s}TexShape[0]) / 2.0), ceil(float(${s}TexShape[1]) / 2.0));
int valuesPerRow = int(ceil(float(${s}Shape[1]) / 2.0));
vec2 uv = packedUVfrom2D(valuesPerRow, packedTexShape[0], packedTexShape[1], row, col);
return ${l.texture2D}(${s}, uv);
}
`;let u=[Math.ceil(a[0]/2),Math.ceil(a[1]/2)],c=Math.ceil(n[1]/2);return`
vec4 ${r}(int row, int col) {
vec2 uv = packedUVfrom2D(${c}, ${u[0]}, ${u[1]}, row, col);
return ${l.texture2D}(${s}, uv);
}
`}function Aq(e,t){let n=e.shapeInfo.logicalShape,s=e.name,r="get"+s.charAt(0).toUpperCase()+s.slice(1),a=e.shapeInfo.texShape;if(a!=null&&I.arraysEqual(n,a)){if(t)return`
float ${r}(int row, int col) {
vec2 uv = (vec2(col, row) + halfCR) / vec2(${s}TexShape[1], ${s}TexShape[0]);
return sampleTexture(${s}, uv);
}
`;let h=a[0],p=a[1];return`
float ${r}(int row, int col) {
vec2 uv = (vec2(col, row) + halfCR) / vec2(${p}.0, ${h}.0);
return sampleTexture(${s}, uv);
}
`}let{newShape:o,keptDims:i}=I.squeezeShape(n),l=o;if(l.length<n.length){let h=Kl(e,l),p=["row","col"];return`
${ql(h,t)}
float ${r}(int row, int col) {
return ${r}(${Zl(p,i)});
}
`}if(e.shapeInfo.isUniform)return`
float ${r}(int row, int col) {
int index = round(dot(vec2(row, col), vec2(${n[1]}, 1)));
${Xl(e)}
}
`;let u=a[0],c=a[1],d=Ho(s);return c===1?t?`
float ${r}(int row, int col) {
float index = dot(vec3(row, col, ${d}), vec3(${s}Shape[1], 1, 1));
vec2 uv = vec2(0.5, (index + 0.5) / float(${s}TexShape[0]));
return sampleTexture(${s}, 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) / ${u}.0);
return sampleTexture(${s}, uv);
}
`:u===1?t?`
float ${r}(int row, int col) {
float index = dot(vec3(row, col, ${d}), vec3(${s}Shape[1], 1, 1));
vec2 uv = vec2((index + 0.5) / float(${s}TexShape[1]), 0.5);
return sampleTexture(${s}, 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) / ${c}.0, 0.5);
return sampleTexture(${s}, uv);
}
`:t?`
float ${r}(int row, int col) {
// Explicitly use integer operations as dot() only works on floats.
int index = row * ${s}Shape[1] + col + ${d};
vec2 uv = uvFromFlat(${s}TexShape[0], ${s}TexShape[1], index);
return sampleTexture(${s}, 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}, ${c}, index);
return sampleTexture(${s}, uv);
}
`}function gq(e,t){let n=e.shapeInfo.logicalShape,s=e.name,r="get"+s.charAt(0).toUpperCase()+s.slice(1),a=e.shapeInfo.texShape,o=[Math.ceil(a[0]/2),Math.ceil(a[1]/2)];if(n[0]===1){let h=n.slice(1),p=[1,2],m=Kl(e,h),f=["b","row","col"];return`
${y6(m,t)}
vec4 ${r}(int b, int row, int col) {
return ${r}(${Zl(f,p)});
}
`}let i=bn();if(t)return`
vec4 ${r}(int b, int row, int col) {
ivec2 packedTexShape = ivec2(ceil(float(${s}TexShape[0]) / 2.0), ceil(float(${s}TexShape[1]) / 2.0));
int valuesPerRow = int(ceil(float(${s}Shape[2]) / 2.0));
int texelsInBatch = valuesPerRow * int(ceil(float(${s}Shape[1]) / 2.0));
vec2 uv = packedUVfrom3D(
packedTexShape[0], packedTexShape[1], texelsInBatch, valuesPerRow, b, row, col);
return ${i.texture2D}(${s}, uv);
}
`;let l=o[0],u=o[1],c=Math.ceil(n[2]/2),d=c*Math.ceil(n[1]/2);return`
vec4 ${r}(int b, int row, int col) {
vec2 uv = packedUVfrom3D(
${l}, ${u}, ${d}, ${c}, b, row, col);
return ${i.texture2D}(${s}, uv);
}
`}function yq(e,t){let n=e.shapeInfo.logicalShape,s=e.name,r="get"+s.charAt(0).toUpperCase()+s.slice(1),a=n[1]*n[2],o=n[2],{newShape:i,keptDims:l}=I.squeezeShape(n),u=i;if(u.length<n.length){let f=Kl(e,u),A=["row","col","depth"];return`
${ql(f,t)}
float ${r}(int row, int col, int depth) {
return ${r}(${Zl(A,l)});
}
`}if(e.shapeInfo.isUniform)return`
float ${r}(int row, int col, int depth) {
int index = round(dot(vec3(row, col, depth),
vec3(${a}, ${o}, 1)));
${Xl(e)}
}
`;let c=e.shapeInfo.texShape,d=c[0],h=c[1],p=e.shapeInfo.flatOffset;if(h===a&&p==null)return t?`
float ${r}(int row, int col, int depth) {
int stride1 = ${s}Shape[2];
float texR = float(row);
float texC = dot(vec2(col, depth), vec2(stride1, 1));
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${s}TexShape[1], ${s}TexShape[0]);
return sampleTexture(${s}, uv);
}
`:`
float ${r}(int row, int col, int depth) {
float texR = float(row);
float texC = dot(vec2(col, depth), vec2(${o}, 1));
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${h}.0, ${d}.0);
return sampleTexture(${s}, uv);
}
`;if(h===o&&p==null)return t?`
float ${r}(int row, int col, int depth) {
float texR = dot(vec2(row, col), vec2(${s}Shape[1], 1));
float texC = float(depth);
vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${s}TexShape[1], ${s}TexShape[0]);
return sampleTexture(${s}, 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(${h}.0, ${d}.0);
return sampleTexture(${s}, uv);
}
`;let m=Ho(s);return t?`
float ${r}(int row, int col, int depth) {
// Explicitly use integer operations as dot() only works on floats.
int stride0 = ${s}Shape[1] * ${s}Shape[2];
int stride1 = ${s}Shape[2];
int index = row * ${a} + col * ${o} + depth + ${m};
vec2 uv = uvFromFlat(${s}TexShape[0], ${s}TexShape[1], index);
return sampleTexture(${s}, uv);
}
`:`
float ${r}(int row, int col, int depth) {
// Explicitly use integer operations as dot() only works on floats.
int index = row * ${a} + col * ${o} + depth + ${m};
vec2 uv = uvFromFlat(${d}, ${h}, index);
return sampleTexture(${s}, uv);
}
`}function xq(e,t){let n=e.name,s="get"+n.charAt(0).toUpperCase()+n.slice(1),r=bn();if(t)return`
vec4 ${s}(int b2, int b, int row, int col) {
int valuesPerRow = int(ceil(float(${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 a=e.shapeInfo.logicalShape,o=a.length,i=e.shapeInfo.texShape,l=[Math.ceil(i[0]/2),Math.ceil(i[1]/2)],u=l[0],c=l[1],d=Math.ceil(a[o-1]/2),h=d*Math.ceil(a[o-2]/2),p="int b, int row, int col",m=`b * ${h} + (row / 2) * ${d} + (col / 2)`;for(let f=2;f<o-1;f++)p=`int b${f}, `+p,h*=a[o-f-1],m=`b${f} * ${h} + `+m;return`
vec4 ${s}(${p}) {
int index = ${m};
int texR = index / ${c};
int texC = index - texR * ${c};
vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${c}, ${u});
return ${r.texture2D}(${n}, uv);
}
`}function bq(e,t){let n=e.shapeInfo.logicalShape,s=e.name,r="get"+s.charAt(0).toUpperCase()+s.slice(1),a=n[3],o=n[2]*a,i=n[1]*o,{newShape:l,keptDims:u}=I.squeezeShape(n);if(l.length<n.length){let y=Kl(e,l),x=["row","col","depth","depth2"];return`
${ql(y,t)}
float ${r}(int row, int col, int depth, int depth2) {
return ${r}(${Zl(x,u)});
}
`}if(e.shapeInfo.isUniform)return`
float ${r}(int row, int col, int depth, int depth2) {
int index = round(dot(vec4(row, col, depth, depth2),
vec4(${i}, ${o}, ${a}, 1)));
${Xl(e)}
}
`;let c=e.shapeInfo.flatOffset,d=e.shapeInfo.texShape,h=d[0],p=d[1],m=`int stride2 = ${s}Shape[3];`,f=`int stride1 = ${s}Shape[2] * stride2;`,A=`int stride0 = ${s}Shape[1] * stride1;`;if(p===i&&c==null)return t?`
float ${r}(int row, int col, int depth, int depth2) {
${m}
${f}
float texR = float(row);
float texC =
dot(vec3(col, depth, depth2),
vec3(stride1, stride2, 1));
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${s}TexShape[1], ${s}TexShape[0]);
return sampleTexture(${s}, uv);
}
`:`
float ${r}(int row, int col, int depth, int depth2) {
float texR = float(row);
float texC =
dot(vec3(col, depth, depth2),
vec3(${o}, ${a}, 1));
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${p}.0, ${h}.0);
return sampleTexture(${s}, uv);
}
`;if(p===a&&c==null)return t?`
float ${r}(int row, int col, int depth, int depth2) {
float texR = dot(vec3(row, col, depth),
vec3(${s}Shape[1] * ${s}Shape[2], ${s}Shape[2], 1));
float texC = float(depth2);
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${s}TexShape[1], ${s}TexShape[0]);
return sampleTexture(${s}, uv);
}
`:`
float ${r}(int row, int col, int depth, int depth2) {
float texR = dot(vec3(row, col, depth),
vec3(${n[1]*n[2]}, ${n[2]}, 1));
float texC = float(depth2);
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${p}.0, ${h}.0);
return sampleTexture(${s}, uv);
}
`;let g=Ho(s);return t?`
float ${r}(int row, int col, int depth, int depth2) {
// Explicitly use integer operations as dot() only works on floats.
${m}
${f}
${A}
int index = row * stride0 + col * stride1 +
depth * stride2 + depth2;
vec2 uv = uvFromFlat(${s}TexShape[0], ${s}TexShape[1], index + ${g});
return sampleTexture(${s}, uv);
}
`:`
float ${r}(int row, int col, int depth, int depth2) {
// Explicitly use integer operations as dot() only works on floats.
int index = row * ${i} + col * ${o} +
depth * ${a} + depth2;
vec2 uv = uvFromFlat(${h}, ${p}, index + ${g});
return sampleTexture(${s}, uv);
}
`}function vq(e){let t=e.shapeInfo.logicalShape,n=e.name,s="get"+n.charAt(0).toUpperCase()+n.slice(1),r=t[4],a=t[3]*r,o=t[2]*a,i=t[1]*o,{newShape:l,keptDims:u}=I.squeezeShape(t);if(l.length<t.length){let f=Kl(e,l),A=["row","col","depth","depth2","depth3"];return`
${ql(f)}
float ${s}(int row, int col, int depth, int depth2, int depth3) {
return ${s}(${Zl(A,u)});
}
`}if(e.shapeInfo.isUniform)return`
float ${s}(int row, int col, int depth, int depth2, int depth3) {
float index = dot(
vec4(row, col, depth, depth2),
vec4(${i}, ${o}, ${a}, ${r})) +
depth3;
${Xl(e)}
}
`;let c=e.shapeInfo.flatOffset,d=e.shapeInfo.texShape,h=d[0],p=d[1];if(p===i&&c==null)return`
float ${s}(int row, int col, int depth, int depth2, int depth3) {
int texR = row;
float texC = dot(vec4(col, depth, depth2, depth3),
vec4(${o}, ${a}, ${r}, 1));
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${p}.0, ${h}.0);
return sampleTexture(${n}, uv);
}
`;if(p===r&&c==null)return`
float ${s}(int row, int col, int depth, int depth2, int depth3) {
float texR = dot(
vec4(row, col, depth, depth2),
vec4(${t[1]*t[2]*t[3]},
${t[2]*t[3]}, ${t[3]}, 1));
int texC = depth3;
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${p}.0, ${h}.0);
return sampleTexture(${n}, uv);
}
`;let m=Ho(n);return`
float ${s}(int row, int col, int depth, int depth2, int depth3) {
// Explicitly use integer operations as dot() only works on floats.
int index = row * ${i} + col * ${o} + depth * ${a} +
depth2 * ${r} + depth3 + ${m};
vec2 uv = uvFromFlat(${h}, ${p}, index);
return sampleTexture(${n}, uv);
}
`}function wq(e){let t=e.shapeInfo.logicalShape,n=e.name,s="get"+n.charAt(0).toUpperCase()+n.slice(1),{newShape:r,keptDims:a}=I.squeezeShape(t);if(r.length<t.length){let A=Kl(e,r),g=["row","col","depth","depth2","depth3","depth4"];return`
${ql(A)}
float ${s}(int row, int col, int depth,
int depth2, int depth3, int depth4) {
return ${s}(${Zl(g,a)});
}
`}let o=t[5],i=t[4]*o,l=t[3]*i,u=t[2]*l,c=t[1]*u;if(e.shapeInfo.isUniform)return`
float ${s}(int row, int col, int depth,
int depth2, int depth3, int depth4) {
int index = round(dot(
vec4(row, col, depth, depth2),
vec4(${c}, ${u}, ${l}, ${i})) +
dot(
vec2(depth3, depth4),
vec2(${o}, 1)));
${Xl(e)}
}
`;let d=e.shapeInfo.flatOffset,h=e.shapeInfo.texShape,p=h[0],m=h[1];if(m===c&&d==null)return`
float ${s}(int row, int col, int depth,
int depth2, int depth3, int depth4) {
int texR = row;
float texC = dot(vec4(col, depth, depth2, depth3),
vec4(${u}, ${l}, ${i}, ${o})) +
float(depth4);
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${m}.0, ${p}.0);
return sampleTexture(${n}, uv);
}
`;if(m===o&&d==null)return`
float ${s}(int row, int col, int depth,
int depth2, int depth3, int depth4) {
float texR = dot(vec4(row, col, depth, depth2),
vec4(${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, ${p}.0);
return sampleTexture(${n}, uv);
}
`;let f=Ho(n);return`
float ${s}(int row, int col, int depth,
int depth2, int depth3, int depth4) {
// Explicitly use integer operations as dot() only works on floats.
int index = row * ${c} + col * ${u} + depth * ${l} +
depth2 * ${i} + depth3 * ${o} + depth4 + ${f};
vec2 uv = uvFromFlat(${p}, ${m}, index);
return sampleTexture(${n}, uv);
}
`}function Xl(e){let t=e.name,n=I.sizeFromShape(e.shapeInfo.logicalShape);return n<2?`return ${t};`:`
for (int i = 0; i < ${n}; i++) {
if (i == index) {
return ${t}[i];
}
}
`}function kq(e,t){let n=e.name,s=n.charAt(0).toUpperCase()+n.slice(1),r="get"+s+"AtOutCoords",a=e.shapeInfo.logicalShape.length,o=t.logicalShape.length,i=g6(e.shapeInfo.logicalShape,t.logicalShape),l=ut(o),u=o-a,c,d=["x","y","z","w","u","v"];a===0?c="":o<2&&i.length>=1?c="coords = 0;":c=i.map(y=>`coords.${d[y+u]} = 0;`).join(`
`);let h="";o<2&&a>0?h="coords":h=e.shapeInfo.logicalShape.map((y,x)=>`coords.${d[x+u]}`).join(", ");let p="return outputValue;",f=I.sizeFromShape(e.shapeInfo.logicalShape)===1,g=I.sizeFromShape(t.logicalShape)===1;if(a===1&&!f&&!g)p=`
return vec4(outputValue.xy, outputValue.xy);
`;else if(f&&!g)o===1?p=`
return vec4(outputValue.x, outputValue.x, 0., 0.);
`:p=`
return vec4(outputValue.x);
`;else if(i.length){let y=a-2,x=a-1;i.indexOf(y)>-1&&i.indexOf(x)>-1?p="return vec4(outputValue.x);":i.indexOf(y)>-1?p="return vec4(outputValue.x, outputValue.y, outputValue.x, outputValue.y);":i.indexOf(x)>-1&&(p="return vec4(outputValue.xx, outputValue.zz);")}return`
vec4 ${r}() {
${l} coords = getOutputCoords();
${c}
vec4 outputValue = get${s}(${h});
${p}
}
`}function Iq(e,t){let n=e.name,s=n.charAt(0).toUpperCase()+n.slice(1),r="get"+s+"AtOutCoords",a=t.texShape,o=e.shapeInfo.texShape,i=e.shapeInfo.logicalShape.length,l=t.logicalShape.length;if(!e.shapeInfo.isUniform&&i===l&&e.shapeInfo.flatOffset==null&&I.arraysEqual(o,a))return`
float ${r}() {
return sampleTexture(${n}, resultUV);
}
`;let u=ut(l),c=g6(e.shapeInfo.logicalShape,t.logicalShape),d=l-i,h,p=["x","y","z","w","u","v"];i===0?h="":l<2&&c.length>=1?h="coords = 0;":h=c.map(f=>`coords.${p[f+d]} = 0;`).join(`
`);let m="";return l<2&&i>0?m="coords":m=e.shapeInfo.logicalShape.map((f,A)=>`coords.${p[A+d]}`).join(", "),`
float ${r}() {
${u} coords = getOutputCoords();
${h}
return get${s}(${m});
}
`}function ut(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 ${e} is not yet supported`)}function S1(e,t,n){let{newShape:s}=I.squeezeShape(t),r=t.length,a=e&&r===3&&t[0]===1,o=a?t.slice(1):s,i=!e&&r>1&&!I.arraysEqual(t,n)&&s.length<r||a;return{useSqueezeShape:i,uniformShape:i?o:t}}function Kl(e,t){let n=JSON.parse(JSON.stringify(e));return n.shapeInfo.logicalShape=t,n}function Zl(e,t){return t.map(n=>e[n]).join(", ")}function Sq(e,t,n,s){let r=n.map((x,b)=>{let v={logicalShape:x.shape,texShape:x.isUniform?null:x.texData.texShape,isUniform:x.isUniform,isPacked:x.isUniform?!1:x.texData.isPacked,flatOffset:null};return x.texData!=null&&x.texData.slice!=null&&x.texData.slice.flatOffset>0&&(v.flatOffset=x.texData.slice.flatOffset),{name:t.variableNames[b],shapeInfo:v}}),a=r.map(x=>x.shapeInfo),o={logicalShape:s.shape,texShape:s.texData.texShape,isUniform:!1,isPacked:s.texData.isPacked,flatOffset:null},i=Uj(r,o,t),l=e.createProgram(i),u=null,c=e.getUniformLocation(l,"NAN",!1);ee().getNumber("WEBGL_VERSION")===1&&(u=e.getUniformLocation(l,"INFINITY",!1));let d=!1,h={},p={},m={};for(let x=0;x<t.variableNames.length;x++){let b=t.variableNames[x];h[b]=e.getUniformLocation(l,b,d),h[`offset${b}`]=e.getUniformLocation(l,`offset${b}`,d),t.enableShapeUniforms&&(p[`${b}Shape`]=e.getUniformLocation(l,`${b}Shape`,d),m[`${b}TexShape`]=e.getUniformLocation(l,`${b}TexShape`,d))}let f,A,g;t.enableShapeUniforms&&(f=e.getUniformLocation(l,"outShape",d),g=e.getUniformLocation(l,"outShapeStrides",d),A=e.getUniformLocation(l,"outTexShape",d));let y=[];return t.customUniforms&&t.customUniforms.forEach((x,b)=>{y[b]=e.getUniformLocation(l,x.name,d)}),{program:t,source:i,webGLProgram:l,uniformLocations:h,customUniformLocations:y,inShapeInfos:a,outShapeInfo:o,infLoc:u,nanLoc:c,inShapesLocations:p,inTexShapesLocations:m,outShapeLocation:f,outShapeStridesLocation:g,outTexShapeLocation:A}}function b6(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,s)=>{let r=n.logicalShape,a=t[s],o=a.shape;if(!I.arraysEqual(r,o))throw Error(`Binary was compiled with different shapes than the current args. Shapes ${r} and ${o} must match`);if(n.isUniform&&a.isUniform)return;let i=n.texShape,l=a.isUniform?null:a.texData.texShape;if(!I.arraysEqual(i,l))throw Error(`Binary was compiled with different texture shapes than the current args. Shape ${i} and ${l} must match`)})}function Cq(e,t,n,s,r){t.program.enableShapeUniforms||(b6(t.inShapeInfos,n),b6([t.outShapeInfo],[s]));let a=s.texData.texture,o=s.texData.texShape;s.texData.isPacked?e.setOutputPackedMatrixTexture(a,o[0],o[1]):e.setOutputMatrixTexture(a,o[0],o[1]),e.setProgram(t.webGLProgram),ee().getNumber("WEBGL_VERSION")===1&&t.infLoc!==null&&e.gl.uniform1f(t.infLoc,1/0),t.nanLoc!==null&&e.gl.uniform1f(t.nanLoc,NaN),n.forEach((l,u)=>{let c=t.program.variableNames[u],d=t.uniformLocations[c],h=t.uniformLocations[`offset${c}`],p=t.inShapesLocations[`${c}Shape`],m=t.inTexShapesLocations[`${c}TexShape`];if(p){let{uniformShape:f}=S1(t.program.packedInputs,l.shape,l.texData.texShape);switch(f.length){case 1:e.gl.uniform1iv(p,new Int32Array(f));break;case 2:e.gl.uniform2iv(p,new Int32Array(f));break;case 3:e.gl.uniform3iv(p,new Int32Array(f));break;case 4:e.gl.uniform4iv(p,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(I.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&&h!=null&&e.gl.uniform1i(h,l.texData.slice.flatOffset),e.setInputMatrixTexture(l.texData.texture,d,u)}});let i=t.outShapeLocation;if(i)switch(s.shape.length){case 1:e.gl.uniform1iv(i,new Int32Array(s.shape));break;case 2:e.gl.uniform2iv(i,new Int32Array(s.shape));break;case 3:e.gl.uniform3iv(i,new Int32Array(s.shape));break;case 4:e.gl.uniform4iv(i,new Int32Array(s.shape));break;default:break}if(t.outShapeStridesLocation){let l=I.computeStrides(s.shape);switch(s.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,s.texData.texShape[0],s.texData.texShape[1]),t.program.customUniforms&&r&&t.program.customUniforms.forEach((l,u)=>{let c=t.customUniformLocations[u],d=r[u];if(l.type==="float")e.gl.uniform1fv(c,d);else if(l.type==="vec2")e.gl.uniform2fv(c,d);else if(l.type==="vec3")e.gl.uniform3fv(c,d);else if(l.type==="vec4")e.gl.uniform4fv(c,d);else if(l.type==="int")e.gl.uniform1iv(c,d);else if(l.type==="ivec2")e.gl.uniform2iv(c,d);else if(l.type==="ivec3")e.gl.uniform3iv(c,d);else if(l.type==="ivec4")e.gl.uniform4iv(c,d);else throw Error(`uniform type ${l.type} is not supported yet.`)}),e.executeProgram()}function Tq(e,t,n){let s="";t.concat(n).forEach(o=>{let i=o.texData!=null&&o.texData.slice!=null&&o.texData.slice.flatOffset>0;if(e.enableShapeUniforms&&!o.isUniform){let l=o.texData.texShape,{useSqueezeShape:u,uniformShape:c}=S1(e.packedInputs,o.shape,l),d="",h="",p="";if(c.length===1&&e.packedInputs){let b=[Math.ceil(l[0]/2),Math.ceil(l[1]/2)];d=`${b[0]>1}_${b[1]>1}`}else if(c.length===2&&!e.packedInputs)h=`${c[0]>1}_${c[1]>1}`;else if(c.length>2&&!e.packedInputs){let b=I.computeStrides(c);p=`${b[0]===l[1]}_${b[b.length-1]===l[1]}`}let m=o.shape.length,f=m===2&&I.arraysEqual(o.shape,l),A=I.sizeFromShape(o.shape)===1,g=$.getBroadcastDims(o.shape,n.shape),y=!e.packedInputs&&m===n.shape.length&&I.arraysEqual(l,n.texData.texShape),x=e.packedInputs||m>2?"":`${l[0]>1}_${l[1]>1}`;s+=`${m}_${y}_${u}_${c.length}_${A}_${g}_${f}_${d}_${h}_${p}_${x}_${i}`}else{let l=o.isUniform?"uniform":o.texData.texShape;s+=`${o.shape}_${l}_${i}`}});let r=e.userCode,a=e.constructor.name;return a+="_"+s+"_"+r+`${ee().getNumber("WEBGL_VERSION")}`,a}function cf(e){return ee().getBool("WEBGL_USE_SHAPES_UNIFORMS")&&e<=4}var{addImpl:Nq,bincountImpl:v6,bincountReduceImpl:Eq,ceilImpl:Rq,concatImpl:_q,equalImpl:$q,expImpl:Fq,expm1Impl:Dq,floorImpl:Oq,gatherNdImpl:Pq,gatherV2Impl:Mq,greaterImpl:zq,greaterEqualImpl:Lq,lessImpl:Bq,lessEqualImpl:Wq,linSpaceImpl:Vq,logImpl:Uq,maxImpl:Hq,maximumImpl:Gq,minimumImpl:jq,multiplyImpl:qq,negImpl:Xq,notEqualImpl:Kq,prodImpl:Zq,rangeImpl:Yq,rsqrtImpl:Jq,simpleAbsImpl:w6,sliceImpl:Qq,sparseFillEmptyRowsImpl:eX,sparseReshapeImpl:tX,sparseSegmentReductionImpl:k6,stridedSliceImpl:nX,stringNGramsImpl:sX,stringSplitImpl:rX,stringToHashBucketFastImpl:aX,subImpl:oX,tileImpl:iX,topKImpl:lX,transposeImpl:C1,uniqueImpl:uX}=J2;function I6(e,t){return["x","y","z","w","u","v"].slice(0,t).map(n=>`${e}.${n}`)}function vn(e,t){return t===1?[e]:I6(e,t)}function cX(e,t){if(e===1)return"rc";let n="";for(let s=0;s<e;s++)n+=t[s],s<e-1&&(n+=",");return n}var dX=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outputShape=e;let t=e.length;if(t===0)this.userCode=`
void main() {
setOutput(vec4(getA(), 0., 0., 0.));
}
`;else{let n=vn("rc",t),s=ut(t),r=pX(t,e,n),a=fX(t,e[e.length-1],e[e.length-2],n),o=mX(e,n);this.userCode=`
void main() {
${s} rc = getOutputCoords();
if(${r}) {
setOutput(vec4(0));
} else {
${a}
setOutput(vec4(${o}));
}
}
`}}};function hX(e,t){let n=[];for(let s=0;s<=1;s++)for(let r=0;r<=1;r++){let a=`${s===0?"r":"rp1"}, ${r===0?"c":"cp1"}`;for(let o=2;o<e;o++)a=`${t[t.length-1-o]},`+a;n.push(a)}return n}function pX(e,t,n){if(e===1)return`rc > ${t[0]}`;let s="";for(let r=e-2;r<e;r++)s+=`${n[r]} >= ${t[r]}`,r<e-1&&(s+="||");return s}function fX(e,t,n,s){if(e===1)return"";let r=s.slice(-2);return`
int r = ${r[0]};
int c = ${r[1]};
int rp1 = r + 1;
int cp1 = c + 1;
bool cEdge = cp1 >= ${t};
bool rEdge = rp1 >= ${n};
`}function mX(e,t){let n=e.length,s=hX(n,t);return n===1?`getA(rc),
rc + 1 >= ${e[0]} ? 0. : getA(rc + 1),
0, 0`:`getA(${s[0]}),
cEdge ? 0. : getA(${s[1]}),
rEdge ? 0. : getA(${s[2]}),
rEdge || cEdge ? 0. : getA(${s[3]})`}var S6=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e;let n="";for(let s=0;s<4;s++){let r="thisRC = rc;";s%2==1&&(r+="thisRC.z += 1;"),s>1&&(r+="thisRC.y += 1;"),n+=`
${r}
${s>0?"if(thisRC.y < rows && thisRC.z < cols){":""}
int flatIndex = getFlatIndex(thisRC);
ivec3 inputRC = inputCoordsFromReshapedOutCoords(flatIndex);
vec2 inputRCInnerDims = vec2(float(inputRC.y),float(inputRC.z));
result[${s}] =
getChannel(getA(inputRC.x, inputRC.y, inputRC.z), inputRCInnerDims);
${s>0?"}":""}
`}this.userCode=`
${AX(t)}
${x1(e)}
void main() {
ivec3 rc = getOutputCoords();
vec4 result = vec4(0.);
ivec3 thisRC;
int rows = ${e[1]};
int cols = ${e[2]};
${n}
setOutput(result);
}
`}};function AX(e){return`
ivec3 inputCoordsFromReshapedOutCoords(int index) {
${Uo(["r","c","d"],e)}
return ivec3(r, c, d);
}
`}var gX=class{constructor(e){this.gpgpu=e,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0,this.freeTextures={},this.logEnabled=!1,this.usedTextures={}}acquireTexture(e,t,n){let s=T6(t,n),r=N6(e,s,n);r in this.freeTextures||(this.freeTextures[r]=[]),r in this.usedTextures||(this.usedTextures[r]=[]);let a=C6(e,s,this.gpgpu.gl,this.gpgpu.textureConfig,n);if(this.freeTextures[r].length>0){this.numFreeTextures--,this.numUsedTextures++,this._numBytesFree-=a,this.log();let i=this.freeTextures[r].shift();return this.usedTextures[r].push(i),i}let o;return s===sn.PACKED_2X2_FLOAT32?o=this.gpgpu.createPackedMatrixTexture(e[0],e[1]):s===sn.PACKED_2X2_FLOAT16?o=this.gpgpu.createFloat16PackedMatrixTexture(e[0],e[1]):s===sn.UNPACKED_FLOAT32?o=this.gpgpu.createFloat32MatrixTexture(e[0],e[1]):s===sn.UNPACKED_FLOAT16?o=this.gpgpu.createFloat16MatrixTexture(e[0],e[1]):s===sn.PACKED_4X1_UNSIGNED_BYTE&&(o=this.gpgpu.createUnsignedBytesMatrixTexture(e[0],e[1])),this.usedTextures[r].push(o),this.numUsedTextures++,this._numBytesAllocated+=a,this.log(),o}releaseTexture(e,t,n,s){if(this.freeTextures==null)return;let r=T6(n,s),a=N6(t,r,s);a in this.freeTextures||(this.freeTextures[a]=[]);let o=C6(t,r,this.gpgpu.gl,this.gpgpu.textureConfig,s),i=ee().get("WEBGL_DELETE_TEXTURE_THRESHOLD");i!==-1&&this._numBytesAllocated>i?(this.gpgpu.deleteMatrixTexture(e),this._numBytesAllocated-=o):(this.freeTextures[a].push(e),this.numFreeTextures++,this._numBytesFree+=o),this.numUsedTextures--;let l=this.usedTextures[a],u=l.indexOf(e);if(u<0)throw new Error("Cannot release a texture that was never provided by this texture manager");l.splice(u,1),this.log()}log(){if(!this.logEnabled)return;let e=this.numFreeTextures+this.numUsedTextures;console.log("Free/Used",`${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)});for(let e in this.usedTextures)this.usedTextures[e].forEach(t=>{this.gpgpu.deleteMatrixTexture(t)});this.freeTextures=null,this.usedTextures=null,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0}}};function yX(e,t){let n=e;if(t===n.R32F)return 4;if(t===n.R16F)return 2;if(t===n.RGBA32F)return 16;if(t===e.RGBA)return 16;if(t===n.RGBA16F)return 8;throw new Error(`Unknown internal format ${t}`)}function C6(e,t,n,s,r){let a=xX(t,s),o;if(r){let[l,u]=Gl(e[0],e[1]);o=l*u}else{let[l,u]=Lc(e[0],e[1]);o=l*u}let i=yX(n,a);return o*i}function xX(e,t){switch(e){case sn.PACKED_2X2_FLOAT32:return k1(t);case sn.PACKED_2X2_FLOAT16:return I1(t);case sn.UNPACKED_FLOAT32:return b1(t);case sn.UNPACKED_FLOAT16:return v1(t);case sn.PACKED_4X1_UNSIGNED_BYTE:return w1(t);default:throw new Error(`Unknown physical texture type ${e}`)}}function bX(e){return ee().getBool("WEBGL_RENDER_FLOAT32_ENABLED")?e?sn.PACKED_2X2_FLOAT32:sn.UNPACKED_FLOAT32:e?sn.PACKED_2X2_FLOAT16:sn.UNPACKED_FLOAT16}function T6(e,t){if(e===fs.UPLOAD)return sn.PACKED_2X2_FLOAT32;if(e===fs.RENDER||e==null)return bX(t);if(e===fs.DOWNLOAD||e===fs.PIXELS)return sn.PACKED_4X1_UNSIGNED_BYTE;throw new Error(`Unknown logical texture type ${e}`)}function N6(e,t,n){return`${e[0]}_${e[1]}_${t}_${n}`}var sa=class{constructor(e,t){this.variableNames=["A"],this.outputShape=e,this.enableShapeUniforms=cf(this.outputShape.length),this.userCode=`
float unaryOperation(float x) {
${t}
}
void main() {
float x = getAAtOutCoords();
float y = unaryOperation(x);
setOutput(y);
}
`}},Bs="if (isnan(x)) return x;",vX="return x;",E6="return abs(x);",wX="return (x >= 0.0) ? x : (exp(x) - 1.0);",kX=Bs+`
return (x < 0.0) ? 0.0 : x;
`,IX=Bs+`
return (x < 0.0) ? 0.0 : min(6.0, x);
`,df="return x;",SX="return 1.0 / (1.0 + exp(-1.0 * x));",CX="return x;",TX=`
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;
`,NX=`
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;
`,EX=`
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;
`,RX="return 1.0 / (1.0 + exp(-1.0 * x));",Yl=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.enableShapeUniforms=cf(this.outputShape.length),this.userCode=`
vec4 unaryOperation(vec4 x) {
${t}
}
void main() {
vec4 x = getAAtOutCoords();
vec4 y = unaryOperation(x);
setOutput(y);
}
`}},_X=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outputShape=e;let t=e.length,n=vn("rc",t),s=ut(t),r=cX(t,n),a=n.slice(-2),o=t<=1?"rc":`vec2(${a.join(",")})`;this.userCode=`
void main() {
${s} rc = getOutputCoords();
vec4 packedInput = getA(${r});
setOutput(getChannel(packedInput, ${o}));
}
`}},$X=Js.whereImpl,FX=1e-7,DX=1e-4,hf={};function OX(e){return e in hf||(hf[e]={}),hf[e]}var PX=ee().getNumber("CPU_HANDOFF_SIZE_THRESHOLD"),MX=600;function zX(){return ee().global.screen==null?1024:ee().global.screen.height*ee().global.screen.width*window.devicePixelRatio*MX/1024/1024}var Jl=class extends Su{constructor(e){super();if(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,!ee().getBool("HAS_WEBGL"))throw new Error("WebGL is not supported on this device");if(e==null){let t=ar(ee().getNumber("WEBGL_VERSION"));this.binaryCache=OX(ee().getNumber("WEBGL_VERSION")),this.gpgpu=new uf(t),this.canvas=t.canvas,this.gpgpuCreatedLocally=!0}else this.gpgpu=e,this.binaryCache={},this.gpgpuCreatedLocally=!1,this.canvas=e.gl.canvas;this.textureManager=new gX(this.gpgpu),this.numMBBeforeWarning=zX(),this.texData=new Fd(this,Ar())}nextDataId(){return Jl.nextDataId++}numDataIds(){return this.texData.numDataIds()-this.pendingDeletes}write(e,t,n){if((ee().getBool("WEBGL_CHECK_NUMERICAL_PROBLEMS")||ee().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 s={id:this.nextDataId()};return this.texData.set(s,{shape:t,dtype:n,values:e,usage:fs.UPLOAD,refCount:1}),s}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,s,r){if(ee().getBool("DEBUG")&&this.checkNumericalProblems(t),s==="complex64")throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");this.texData.set(e,{shape:n,dtype:s,values:t,usage:fs.UPLOAD,refCount:r})}disposeIntermediateTensorInfo(e){this.disposeData(e.dataId)}readSync(e){let t=this.texData.get(e),{values:n,dtype:s,complexTensorInfos:r,slice:a,shape:o,isPacked:i}=t;if(a!=null){let d;i?d=new Yl(o,df):d=new sa(o,df);let h=this.runWebGLProgram(d,[{dataId:e,shape:o,dtype:s}],s),p=this.readSync(h.dataId);return this.disposeIntermediateTensorInfo(h),p}if(n!=null)return this.convertAndCacheOnCPU(e);if(s==="string")return n;let l=this.activeTimers!=null,u;l&&(u=I.now());let c;if(s==="complex64"){let d=this.readSync(r.real.dataId),h=this.readSync(r.imag.dataId);c=$.mergeRealAndImagArrays(d,h)}else c=this.getValuesFromTexture(e);return l&&(this.downloadWaitMs+=I.now()-u),this.convertAndCacheOnCPU(e,c)}async read(e){if(this.pendingRead.has(e)){let p=this.pendingRead.get(e);return new Promise(m=>p.push(m))}let t=this.texData.get(e),{values:n,shape:s,slice:r,dtype:a,complexTensorInfos:o,isPacked:i}=t;if(r!=null){let p;i?p=new Yl(s,df):p=new sa(s,df);let m=this.runWebGLProgram(p,[{dataId:e,shape:s,dtype:a}],a),f=this.read(m.dataId);return this.disposeIntermediateTensorInfo(m),f}if(n!=null)return this.convertAndCacheOnCPU(e);if(!ee().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")&&ee().getNumber("WEBGL_VERSION")===2)throw new Error("tensor.data() with WEBGL_DOWNLOAD_FLOAT_ENABLED=false and WEBGL_VERSION=2 not yet supported.");let l=null,u;if(a!=="complex64"&&ee().get("WEBGL_BUFFER_SUPPORTED")){u=this.decode(e);let p=this.texData.get(u.dataId);l=this.gpgpu.createBufferFromTexture(p.texture,...Bc(s))}this.pendingRead.set(e,[]),a!=="complex64"&&await this.gpgpu.createAndWaitForFence();let c;if(a==="complex64"){let p=await Promise.all([this.read(o.real.dataId),this.read(o.imag.dataId)]),m=p[0],f=p[1];c=$.mergeRealAndImagArrays(m,f)}else if(l==null)c=this.getValuesFromTexture(e);else{let p=I.sizeFromShape(s);c=this.gpgpu.downloadFloat32MatrixFromBuffer(l,p)}if(u!=null&&this.disposeIntermediateTensorInfo(u),l!=null){let p=this.gpgpu.gl;be(p,()=>p.deleteBuffer(l))}let d=this.convertAndCacheOnCPU(e,c),h=this.pendingRead.get(e);return this.pendingRead.delete(e),h.forEach(p=>p(d)),this.pendingDisposal.has(e)&&(this.pendingDisposal.delete(e),this.disposeData(e)&&Ar().removeDataId(e,this),this.pendingDeletes--),d}bufferSync(e){let t=this.readSync(e.dataId),n=t;if(e.dtype==="string")try{n=t.map(s=>I.decodeString(s))}catch(s){throw new Error("Failed to decode encoded string bytes into utf-8")}return Be(e.shape,e.dtype,n)}checkNumericalProblems(e){if(e!=null)for(let t=0;t<e.length;t++){let n=e[t];if(!Nw(n))throw ee().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 ${n} cannot be represented on this device.`)}}getValuesFromTexture(e){let{shape:t,dtype:n,isPacked:s}=this.texData.get(e),r=I.sizeFromShape(t);if(ee().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")){let d=this.decode(e),h=this.texData.get(d.dataId),p=this.gpgpu.downloadMatrixFromPackedTexture(h.texture,...Bc(t)).subarray(0,r);return this.disposeIntermediateTensorInfo(d),p}let a=ee().getBool("WEBGL_PACK")&&s===!0,o=a?rf(t):t,i=a?new Lj(o):new zj(o),l=this.runWebGLProgram(i,[{shape:o,dtype:n,dataId:e}],"float32"),u=this.texData.get(l.dataId),c=this.gpgpu.downloadByteEncodedFloatMatrixFromOutputTexture(u.texture,u.texShape[0],u.texShape[1]).subarray(0,r);return this.disposeIntermediateTensorInfo(l),c}timerAvailable(){return ee().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0}async time(e){let t=this.activeTimers,n=[],s=!1;this.programTimersStack==null?(this.programTimersStack=n,s=!0):this.activeTimers.push(n),this.activeTimers=n,e();let r=I.flatten(this.activeTimers.map(i=>i.query)).filter(i=>i!=null),a=I.flatten(this.activeTimers.map(i=>i.name)).filter(i=>i!=null);this.activeTimers=t,s&&(this.programTimersStack=null);let o={uploadWaitMs:this.uploadWaitMs,downloadWaitMs:this.downloadWaitMs,kernelMs:null,wallMs:null};if(ee().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0){let i=await Promise.all(r);o.kernelMs=I.sum(i),o.getExtraProfileInfo=()=>i.map((l,u)=>({name:a[u],ms:l})).map(l=>`${l.name}: ${l.ms}`).join(", ")}else o.kernelMs={error:"WebGL query timers are not supported in this environment."};return this.uploadWaitMs=0,this.downloadWaitMs=0,o}memory(){return{unreliable:!1,numBytesInGPU:this.numBytesInGPU,numBytesInGPUAllocated:this.textureManager.numBytesAllocated,numBytesInGPUFree:this.textureManager.numBytesFree}}startTimer(){return ee().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?this.gpgpu.beginQuery():{startMs:I.now(),endMs:null}}endTimer(e){return ee().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?(this.gpgpu.endQuery(),e):(e.endMs=I.now(),e)}async getQueryTime(e){if(ee().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0)return this.gpgpu.waitForQueryAndGetTime(e);let t=e;return t.endMs-t.startMs}disposeData(e,t=!1){if(this.pendingDisposal.has(e))return!1;if(!this.texData.has(e))return!0;if(t?this.texData.get(e).refCount=0:this.texData.get(e).refCount--,!t&&this.texData.get(e).refCount>0)return!1;if(this.pendingRead.has(e))return this.pendingDisposal.add(e),this.pendingDeletes++,!1;this.releaseGPUData(e);let{complexTensorInfos:n}=this.texData.get(e);return n!=null&&(this.disposeData(n.real.dataId,t),this.disposeData(n.imag.dataId,t)),this.texData.delete(e),!0}releaseGPUData(e){let{texture:t,dtype:n,texShape:s,usage:r,isPacked:a,slice:o}=this.texData.get(e),i=o&&o.origDataId||e,l=this.dataRefCount.get(i);l>1?this.dataRefCount.set(i,l-1):(this.dataRefCount.delete(i),t!=null&&(this.numBytesInGPU-=this.computeBytes(s,n),this.textureManager.releaseTexture(t,s,r,a)));let u=this.texData.get(e);u.texture=null,u.texShape=null,u.isPacked=!1,u.slice=null}getTexture(e){return this.uploadToGPU(e),this.texData.get(e).texture}getDataInfo(e){return this.texData.get(e)}shouldExecuteOnCPU(e,t=PX){return ee().getBool("WEBGL_CPU_FORWARD")&&e.every(n=>this.texData.get(n.dataId).texture==null&&I.sizeFromShape(n.shape)<t)}getGPGPUContext(){return this.gpgpu}where(e){$.warn("tf.where() in webgl locks the UI thread. Call tf.whereAsync() instead");let t=e.dataSync();return $X(e.shape,t)}packedUnaryOp(e,t,n){let s=new Yl(e.shape,t),r=this.compileAndRun(s,[e],n);return Ar().makeTensorFromDataId(r.dataId,r.shape,r.dtype)}abs(e){if(this.shouldExecuteOnCPU([e])&&e.dtype!=="complex64"){let s=w6(this.texData.get(e.dataId).values);return this.makeOutput(e.shape,e.dtype,s)}if(ee().getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(e,E6,e.dtype);let t=new sa(e.shape,E6),n=this.compileAndRun(t,[e]);return Ar().makeTensorFromDataId(n.dataId,n.shape,n.dtype)}makeTensorInfo(e,t,n){let s;if(t==="string"&&n!=null&&n.length>0&&I.isString(n[0])){let r=n.map(a=>I.encodeString(a));s=this.write(r,e,t)}else s=this.write(n,e,t);return this.texData.get(s).usage=null,{dataId:s,shape:e,dtype:t}}makeOutput(e,t,n){let{dataId:s}=this.makeTensorInfo(e,t,n);return Ar().makeTensorFromDataId(s,e,t,this)}unpackTensor(e){let t=new _X(e.shape);return this.runWebGLProgram(t,[e],e.dtype)}packTensor(e){let t=new dX(e.shape),n=!0;return this.runWebGLProgram(t,[e],e.dtype,null,n)}packedReshape(e,t){let n=[Wo(e.shape),...Vo(e.shape)],s={dtype:e.dtype,shape:n,dataId:e.dataId},r=[Wo(t),...Vo(t)],a=new S6(r,n),o=!0,i=this.runWebGLProgram(a,[s],e.dtype,null,o);return{dataId:i.dataId,shape:t,dtype:i.dtype}}decode(e){let t=this.texData.get(e),{isPacked:n,shape:s,dtype:r}=t,a=rf(s),o;n?o=new Mj(a):o=new Pj(a);let i=!0,l=this.runWebGLProgram(o,[{shape:a,dtype:r,dataId:e}],r,null,i);return{dtype:r,shape:s,dataId:l.dataId}}runWebGLProgram(e,t,n,s,r=!1){let a=this.makeTensorInfo(e.outputShape,n),o=this.texData.get(a.dataId);if(e.packedOutput&&(o.isPacked=!0),e.outPackingScheme===zc.DENSE){let f=Bc(e.outputShape);o.texShape=f.map(A=>A*2)}if(e.outTexUsage!=null&&(o.usage=e.outTexUsage),I.sizeFromShape(a.shape)===0)return o.values=I.getTypedArrayFromDType(a.dtype,0),a;let i=[],l=t.map(f=>{if(f.dtype==="complex64")throw new Error("GPGPUProgram does not support complex64 input. For complex64 dtypes, please separate the program into real and imaginary parts.");let A=this.texData.get(f.dataId);if(A.texture==null){if(!e.packedInputs&&I.sizeFromShape(f.shape)<=ee().getNumber("WEBGL_SIZE_UPLOAD_UNIFORM"))return{shape:f.shape,texData:null,isUniform:!0,uniformValues:A.values};e.packedInputs&&(A.isPacked=!0,A.shape=f.shape)}else if(!!A.isPacked!=!!e.packedInputs)f=A.isPacked?this.unpackTensor(f):this.packTensor(f),i.push(f),A=this.texData.get(f.dataId);else if(A.isPacked&&!Uc(A.shape,f.shape)){let g=f,y=f.shape;f.shape=A.shape,f=this.packedReshape(f,y),i.push(f),A=this.texData.get(f.dataId),g.shape=y}return this.uploadToGPU(f.dataId),{shape:f.shape,texData:A,isUniform:!1}});this.uploadToGPU(a.dataId);let u={shape:a.shape,texData:o,isUniform:!1},c=Tq(e,l,u),d=this.getAndSaveBinary(c,()=>Sq(this.gpgpu,e,l,u)),h=this.activeTimers!=null,p;h&&(p=this.startTimer()),Cq(this.gpgpu,d,l,u,s),i.forEach(f=>this.disposeIntermediateTensorInfo(f)),h&&(p=this.endTimer(p),this.activeTimers.push({name:e.constructor.name,query:this.getQueryTime(p)}));let m=ee().get("WEBGL_FLUSH_THRESHOLD");if(m>0){let f=I.now();f-this.lastGlFlushTime>m&&(this.gpgpu.gl.flush(),this.lastGlFlushTime=f)}if(!ee().getBool("WEBGL_LAZILY_UNPACK")&&o.isPacked&&r===!1){let f=this.unpackTensor(a);return this.disposeIntermediateTensorInfo(a),f}return a}compileAndRun(e,t,n,s,r=!1){return n=n||t[0].dtype,this.runWebGLProgram(e,t,n,s,r)}getAndSaveBinary(e,t){return e in this.binaryCache||(this.binaryCache[e]=t()),this.binaryCache[e]}getTextureManager(){return this.textureManager}dispose(){this.disposed||(ee().getBool("IS_TEST")||Object.keys(this.binaryCache).forEach(t=>{this.gpgpu.deleteProgram(this.binaryCache[t].webGLProgram),delete this.binaryCache[t]}),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=H(()=>{if(!ee().get("WEBGL_RENDER_FLOAT32_ENABLED")){let e=ee().getBool("DEBUG");ee().set("DEBUG",!1);let t=this.abs(Ie(1e-8)).dataSync()[0];if(ee().set("DEBUG",e),t>0)return 32}return 16})),this.floatPrecisionValue}epsilon(){return this.floatPrecision()===32?FX:DX}uploadToGPU(e){let t=this.texData.get(e),{shape:n,dtype:s,values:r,texture:a,usage:o,isPacked:i}=t;if(a!=null)return;let l=this.activeTimers!=null,u;l&&(u=I.now());let c=t.texShape;if(c==null&&(c=Gw(n,i),t.texShape=c),r!=null){let d=rf(n),h,p=c[1],m=c[0],f=r instanceof Uint8Array;i?([p,m]=Gl(c[0],c[1]),h=new Wj(d,[m,p],f)):h=new Bj(d,[m,p],f);let A=this.makeTensorInfo([m,p],s);f?this.texData.get(A.dataId).usage=fs.PIXELS:this.texData.get(A.dataId).usage=fs.UPLOAD,this.gpgpu.uploadDenseMatrixToTexture(this.getTexture(A.dataId),p,m,r);let g=!0,y=this.runWebGLProgram(h,[A],s,null,g),x=this.texData.get(y.dataId);t.texture=x.texture,t.texShape=x.texShape,t.isPacked=x.isPacked,t.usage=x.usage,this.disposeIntermediateTensorInfo(A),this.texData.delete(y.dataId),t.values=null,l&&(this.uploadWaitMs+=I.now()-u)}else{let d=this.acquireTexture(c,o,s,i);t.texture=d}}convertAndCacheOnCPU(e,t){let n=this.texData.get(e),{dtype:s}=n;return this.releaseGPUData(e),t!=null&&(n.values=LX(t,s)),n.values}acquireTexture(e,t,n,s){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,s)}computeBytes(e,t){return e[0]*e[1]*I.bytesPerElement(t)}};Jl.nextDataId=0;function LX(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 s=0;s<n.length;++s)n[s]=Math.round(e[s]);return n}else throw new Error(`Unknown dtype ${t}`)}var BX="3.8.0";function R6(){ee().set("WEBGL_FORCE_F16_TEXTURES",!0)}Yu.isBrowser()&&bl("webgl",()=>new Jl,2);var WX={forceHalfFloat:R6},_6=`
if (isnan(a)) return a;
if (isnan(b)) return b;
`,Ql=class{constructor(e,t,n){this.variableNames=["A","B"],this.outputShape=$.assertAndGetBroadcastShape(t,n),this.enableShapeUniforms=cf(this.outputShape.length),this.userCode=`
float binaryOperation(float a, float b) {
${e}
}
void main() {
float a = getAAtOutCoords();
float b = getBAtOutCoords();
setOutput(binaryOperation(a, b));
}
`}},pf=`
result.r = isNaN.r > 0. ? NAN : result.r;
result.g = isNaN.g > 0. ? NAN : result.g;
result.b = isNaN.b > 0. ? NAN : result.b;
result.a = isNaN.a > 0. ? NAN : result.a;
`,Gc=class{constructor(e,t,n,s=!1){this.variableNames=["A","B"],this.supportsBroadcasting=!0,this.packedInputs=!0,this.packedOutput=!0,this.outputShape=$.assertAndGetBroadcastShape(t,n);let r=this.outputShape.length;this.enableShapeUniforms=cf(r);let a="";if(s)if(r===0||I.sizeFromShape(this.outputShape)===1)a=`
result.y = 0.;
result.z = 0.;
result.w = 0.;
`;else if(a=`
${ut(r)} coords = getOutputCoords();
`,r===1)this.enableShapeUniforms?a+=`
result.y = (coords + 1) >= outShape ? 0. : result.y;
result.z = 0.;
result.w = 0.;
`:a+=`
result.y = (coords + 1) >= ${this.outputShape[0]} ? 0. : result.y;
result.z = 0.;
result.w = 0.;
`;else{let i=vn("coords",r);this.enableShapeUniforms?a+=`
bool nextRowOutOfBounds =
(${i[r-2]} + 1) >= outShape[${r} - 2];
bool nextColOutOfBounds =
(${i[r-1]} + 1) >= outShape[${r} - 1];
result.y = nextColOutOfBounds ? 0. : result.y;
result.z = nextRowOutOfBounds ? 0. : result.z;
result.w = nextColOutOfBounds || nextRowOutOfBounds ? 0. : result.w;
`:a+=`
bool nextRowOutOfBounds =
(${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);
${a}
setOutput(result);
}
`}};function qn(e){let{inputs:t,backend:n}=e,{x:s}=t;return n.incRef(s.dataId),{dataId:s.dataId,shape:s.shape,dtype:s.dtype}}var VX={kernelName:Oa,backendName:"webgl",kernelFunc:qn};function ra(e){let{inputs:t,backend:n}=e,{real:s,imag:r}=t,a=n.makeTensorInfo(s.shape,"complex64"),o=n.texData.get(a.dataId),i=qn({inputs:{x:s},backend:n}),l=qn({inputs:{x:r},backend:n});return o.complexTensorInfos={real:i,imag:l},a}var UX={kernelName:Wd,backendName:"webgl",kernelFunc:ra},$6="return (a < 0.) ? b * a : a;",F6=`
vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));
return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);
`;function HX(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{alpha:a}=s,o=n.makeTensorInfo([],"float32",I.createScalarValue(a,"float32")),i=ee().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new Gc(F6,r.shape,o.shape):new Ql($6,r.shape,o.shape),l=n.runWebGLProgram(i,[r,o],r.dtype);return n.disposeIntermediateTensorInfo(o),l}var GX={kernelName:Pa,backendName:"webgl",kernelFunc:HX},D6="return (a < 0.) ? b * a : a;",O6=`
vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));
return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);
`;function jX(e){let{inputs:t,backend:n}=e,{x:s,alpha:r}=t,a=ee().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new Gc(O6,s.shape,r.shape):new Ql(D6,s.shape,r.shape);return n.runWebGLProgram(a,[s,r],s.dtype)}var qX={kernelName:Ka,backendName:"webgl",kernelFunc:jX},P6="if (isnan(x)) return x;",XX=`
if (isnan(a)) return a;
if (isnan(b)) return b;
`,KX=`
result.r = isNaN.r > 0. ? NAN : result.r;
result.g = isNaN.g > 0. ? NAN : result.g;
result.b = isNaN.b > 0. ? NAN : result.b;
result.a = isNaN.a > 0. ? NAN : result.a;
`;function Ze({opSnippet:e,packedOpSnippet:t,cpuKernelImpl:n,dtype:s}){return({inputs:r,backend:a})=>{let{x:o}=r,i=a,l=s||o.dtype;if(i.shouldExecuteOnCPU([o])&&n!=null){let d=i.texData.get(o.dataId),h=n(d.values,l);return i.makeTensorInfo(o.shape,l,h)}let u=ee().getBool("WEBGL_PACK_UNARY_OPERATIONS")&&t!=null,c;return u?c=new Yl(o.shape,t):c=new sa(o.shape,e),i.runWebGLProgram(c,[o],l)}}function rn({opSnippet:e,packedOpSnippet:t,checkOutOfBounds:n=!1,supportsComplex:s=!1,cpuKernelImpl:r,dtype:a}){return({inputs:o,backend:i})=>{let{a:l,b:u}=o,c=i;if(s&&l.dtype==="complex64"){let m=c.texData.get(l.dataId),f=c.texData.get(u.dataId),[A,g]=[[m.complexTensorInfos.real,f.complexTensorInfos.real],[m.complexTensorInfos.imag,f.complexTensorInfos.imag]].map(x=>{let[b,v]=x,k={dataId:b.dataId,dtype:b.dtype,shape:l.shape},w={dataId:v.dataId,dtype:v.dtype,shape:u.shape},C=new Ql(e,l.shape,u.shape);return c.runWebGLProgram(C,[k,w],bs(b.dtype,v.dtype))}),y=ra({inputs:{real:A,imag:g},backend:c});return c.disposeIntermediateTensorInfo(A),c.disposeIntermediateTensorInfo(g),y}let d=a||bs(l.dtype,u.dtype);if((l.dtype==="string"||u.dtype==="string"||c.shouldExecuteOnCPU([l,u]))&&r!=null){let m=c.texData.get(l.dataId).values,f=c.texData.get(u.dataId).values,A=l.dtype==="string"?$.fromUint8ToStringArray(m):m,g=l.dtype==="string"?$.fromUint8ToStringArray(f):f,[y,x]=r(l.shape,u.shape,A,g,d),b=c.makeTensorInfo(x,d),v=c.texData.get(b.dataId);return v.values=y,b}let h=ee().getBool("WEBGL_PACK_BINARY_OPERATIONS")&&t!=null,p;return h?p=new Gc(t,l.shape,u.shape,n):p=new Ql(e,l.shape,u.shape),c.runWebGLProgram(p,[l,u],d)}}function ff(e,t=!1){if(e==="linear")return t?CX:vX;if(e==="relu")return t?NX:kX;if(e==="elu")return t?TX:wX;if(e==="relu6")return t?EX:IX;if(e==="prelu")return t?O6:D6;if(e==="leakyrelu")return t?F6:$6;if(e==="sigmoid")return t?RX:SX;throw new Error(`Activation ${e} has not been implemented for the WebGL backend.`)}var M6=class{constructor(e,t,n,s=!1,r=!1,a=!1,o=null,i=!1,l=!1){this.variableNames=["matrixA","matrixB"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=n;let u=s?e[1]:e[2],c=Math.ceil(u/2),d=s?"i * 2, rc.y":"rc.y, i * 2",h=r?"rc.z, i * 2":"i * 2, rc.z",p=s?["a.xxyy","a.zzww"]:["a.xxzz","a.yyww"],m=r?["b.xzxz","b.ywyw"]:["b.xyxy","b.zwzw"],f="",A="";o&&(i?f=`vec4 activation(vec4 a) {
vec4 b = getPreluActivationWeightsAtOutCoords();
${o}
}`:l?f=`vec4 activation(vec4 a) {
vec4 b = getLeakyreluAlphaAtOutCoords();
${o}
}`:f=`vec4 activation(vec4 x) {
${o}
}`,A="result = activation(result);");let g=a?"result += getBiasAtOutCoords();":"";a&&this.variableNames.push("bias"),i&&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}
const float sharedDimension = ${c}.0;
vec4 dot2x2ARowBCol(ivec3 rc) {
vec4 result = vec4(0);
for (int i = 0; i < ${c}; i++) {
int batchA = ${y};
int batchB = ${x};
vec4 a = getMatrixA(batchA, ${d});
vec4 b = getMatrixB(batchB, ${h});
// These swizzled products need to be separately added.
// See: https://github.com/tensorflow/tfjs/issues/1735
result += (${p[0]} * ${m[0]});
result += (${p[1]} * ${m[1]});
}
return result;
}
void main() {
ivec3 rc = getOutputCoords();
vec4 result = dot2x2ARowBCol(rc);
${g}
${A}
setOutput(result);
}
`}},z6={REAL:"return areal * breal - aimag * bimag;",IMAG:"return areal * bimag + aimag * breal;"},L6=class{constructor(e,t,n){this.variableNames=["AReal","AImag","BReal","BImag"],this.outputShape=$.assertAndGetBroadcastShape(t,n),this.userCode=`
float binaryOpComplex(
float areal, float aimag, float breal, float bimag) {
${e}
}
void main() {
float areal = getARealAtOutCoords();
float aimag = getAImagAtOutCoords();
float breal = getBRealAtOutCoords();
float bimag = getBImagAtOutCoords();
setOutput(binaryOpComplex(areal, aimag, breal, bimag));
}
`}},B6="return a * b;";function T1(e){let{inputs:t,backend:n}=e,{a:s,b:r}=t,a=$.upcastType(s.dtype,r.dtype);if(s.dtype==="complex64"){let i=n.texData.get(s.dataId),l=n.texData.get(r.dataId),u=new L6(z6.REAL,s.shape,r.shape),c=new L6(z6.IMAG,s.shape,r.shape),d=[{dataId:i.complexTensorInfos.real.dataId,dtype:i.complexTensorInfos.real.dtype,shape:s.shape},{dataId:i.complexTensorInfos.imag.dataId,dtype:i.complexTensorInfos.imag.dtype,shape:s.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}],h=n.runWebGLProgram(u,d,"float32"),p=n.runWebGLProgram(c,d,"float32"),m=ra({inputs:{real:h,imag:p},backend:n});return n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(p),m}if(n.shouldExecuteOnCPU([s,r])){let i=n.texData.get(s.dataId),l=n.texData.get(r.dataId),[u,c]=qq(s.shape,r.shape,i.values,l.values,a),d=n.makeTensorInfo(c,a),h=n.texData.get(d.dataId);return h.values=u,d}let o;return ee().getBool("WEBGL_PACK_BINARY_OPERATIONS")?o=new Gc(B6,s.shape,r.shape):o=new Ql(B6,s.shape,r.shape),n.runWebGLProgram(o,[s,r],a)}var ZX={kernelName:Ga,backendName:"webgl",kernelFunc:T1};function YX(e,t,n){let s=[Wo(e.shape),...Vo(e.shape)],r={dtype:e.dtype,shape:s,dataId:e.dataId},a=[Wo(t),...Vo(t)],o=new S6(a,s),i=!0,l=n.runWebGLProgram(o,[r],e.dtype,null,i);return{dataId:l.dataId,shape:t,dtype:l.dtype}}function ye(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{shape:a}=s,o=n,i=I.sizeFromShape(r.shape),l=I.inferFromImplicitShape(a,i),u=I.sizeFromShape(l);I.assert(i===u,()=>`The new shape (${l}) has ${u} elements and the old shape (${r.shape}) has ${i} elements. The new shape and old shape must have the same number of elements.`);let c=o.texData.get(r.dataId);return c.isPacked&&!Uc(r.shape,l)&&!(c.texture!==null&&Uc(c.shape,l))?YX(r,l,o):(o.incRef(r.dataId),{dataId:r.dataId,shape:l,dtype:r.dtype})}var JX={kernelName:Yi,backendName:"webgl",kernelFunc:ye},W6=class{constructor(e,t){this.variableNames=["x"];let{windowSize:n,batchSize:s,inSize:r,outSize:a}=e;this.outputShape=[s,a];let o=Math.floor(n/4)*4,i=n%4,l="sumValue += dot(values, ones);";if(t!=null){let c=1/t;l=`sumValue += dot(values * ${I.isInt(c)?c.toPrecision(2):c}, 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 < ${o}; 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 + ${o};
if (${i===1}) {
vec4 values = vec4(getValue(batch, inIdx), 0.0, 0.0, 0.0);
${l}
} else if (${i===2}) {
vec4 values = vec4(
getValue(batch, inIdx),
getValue(batch, inIdx + 1), 0.0, 0.0);
${l}
} else if (${i===3}) {
vec4 values = vec4(
getValue(batch, inIdx),
getValue(batch, inIdx + 1),
getValue(batch, inIdx + 2), 0.0);
${l}
}
setOutput(sumValue);
}
`}},QX=class{constructor(e,t){this.variableNames=["x"];let{windowSize:n,batchSize:s,inSize:r,outSize:a}=e;this.outputShape=[s,a];let o="0.0",i="";t==="prod"?o="1.0":t==="min"?(o="1.0 / 1e-20",i="min"):t==="max"&&(o="-1.0 / 1e-20",i="max");let l=`${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,c=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 = ${i}(values, minMaxValue);
if (${t==="min"} || ${t==="max"}) {
minMaxValue = ${i}(values, minMaxValue);
bvec4 isNaN = isnan(values);
if (isNaN.r || isNaN.g || isNaN.b || isNaN.a) {
minMaxValue = vec4(NAN);
}
}
}
`,h="vec4";t==="all"?(o="1.0",d=`
bool reducedAllValue = all(values);
float floatedReducedAllValue = float(reducedAllValue);
allValue = float(allValue >= 1.0 && floatedReducedAllValue >= 1.0);
`,h="bvec4"):t==="any"&&(o="0.0",d=`
bool reducedAnyValue = any(values);
float floatedReducedAnyValue = float(reducedAnyValue);
anyValue = float(anyValue >= 1.0 || floatedReducedAnyValue >= 1.0);
`,h="bvec4");let p="";r%n>0&&(p=`
if (inIdx < 0 || inIdx >= ${r}) {
return initializationValue;
}
`),this.userCode=`
const float initializationValue = ${o};
const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);
float getValue(int batch, int inIdx) {
${p}
return getX(batch, inIdx);
}
void main() {
ivec2 coords = getOutputCoords();
int batch = coords[0];
int outIdx = coords[1];
int inOffset = outIdx * ${n};
vec4 minMaxValue = vec4(${o});
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;
${h} values = ${h}(
getValue(batch, inIdx),
getValue(batch, inIdx + 1),
getValue(batch, inIdx + 2),
getValue(batch, inIdx + 3)
);
${d}
}
int inIdx = inOffset + ${u};
if (${c===1}) {
${h} values = ${h}(
getValue(batch, inIdx),
initializationValue,
initializationValue,
initializationValue
);
${d}
} else if (${c===2}) {
${h} values = ${h}(
getValue(batch, inIdx),
getValue(batch, inIdx + 1),
initializationValue,
initializationValue
);
${d}
} else if (${c===3}) {
${h} values = ${h}(
getValue(batch, inIdx),
getValue(batch, inIdx + 1),
getValue(batch, inIdx + 2),
initializationValue
);
${d}
}
setOutput(${l});
}
`}};function eK(e){let t=[];for(;t.length===0||t[t.length-1].outSize!==1;){let n=t.length?t[t.length-1].outSize:e[1],s=$.computeOptimalWindowSize(n);t.push({inSize:n,windowSize:s,outSize:Math.ceil(n/s)})}return t}function Go(e,t,n,s){let r=eK(e.shape),a=e;for(let o=0;o<r.length;o++){let{inSize:i,windowSize:l,outSize:u}=r[o],c,d;n==="mean"?c=o===0?new W6({windowSize:l,inSize:i,batchSize:e.shape[0],outSize:u},i):new W6({windowSize:l,inSize:i,batchSize:e.shape[0],outSize:u}):c=new QX({windowSize:l,inSize:i,batchSize:e.shape[0],outSize:u},n),d=a,a=s.runWebGLProgram(c,[a],t),d.dataId!==e.dataId&&s.disposeIntermediateTensorInfo(d)}return a}var tK=class{constructor(e,t){this.variableNames=["A"];let n=new Array(e.length);for(let a=0;a<n.length;a++)n[a]=e[t[a]];this.outputShape=n,this.rank=n.length;let s=ut(this.rank),r=nK(t);this.userCode=`
void main() {
${s} resRC = getOutputCoords();
setOutput(getA(${r}));
}
`}};function nK(e){let t=e.length;if(t>6)throw Error(`Transpose for rank ${t} is not yet supported`);let n=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u","resRC.v"],s=new Array(t);for(let r=0;r<e.length;r++)s[e[r]]=n[r];return s.join()}var sK=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0;let n=new Array(e.length);for(let u=0;u<n.length;u++)n[u]=e[t[u]];if(this.outputShape=n,this.rank=n.length,this.rank>6)throw Error(`Packed transpose for rank ${this.rank} is not yet supported.`);let s=ut(this.rank),r=I6("rc",this.rank),a=new Array(this.rank);for(let u=0;u<t.length;u++)a[t[u]]=r[u];let o=`vec2(${a.slice(-2).join()})`,i=`++${r[this.rank-1]} < ${n[this.rank-1]}`,l=`getChannel(getA(${a.join()}), ${o})`;this.userCode=`
void main() {
${s} rc = getOutputCoords();
vec4 result = vec4(0.);
result[0] = ${l};
if(${i}) {
result[1] = ${l};
}
--${r[this.rank-1]};
if(++${r[this.rank-2]} < ${n[this.rank-2]}) {
result[2] = ${l};
if(${i}) {
result[3] = ${l};
}
}
setOutput(result);
}
`}};function mf(e,t,n){let s=ee().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new sK(e.shape,t):new tK(e.shape,t);return n.runWebGLProgram(s,[e],e.dtype)}function rK(e,t,n,s){let r=t,a=e.shape.length,o=I.parseAxisParam(r,e.shape),i=o,l=$.getAxesPermutation(i,a),u=l!=null,c=e;u&&(c=mf(e,l,s),i=$.getInnerMostAxes(i.length,a)),$.assertAxesAreInnerMostDims("sum",i,a);let[d,h]=$.computeOutAndReduceShapes(c.shape,i),p=d;n&&(p=$.expandShapeToKeepDim(d,o));let m=I.sizeFromShape(h),A=I.sizeFromShape(e.shape)/m,g=ye({inputs:{x:c},attrs:{shape:[A,m]},backend:s}),y=Ch(e.dtype),x=Go(g,y,"sum",s),b=ye({inputs:{x},attrs:{shape:p},backend:s});return s.disposeIntermediateTensorInfo(g),s.disposeIntermediateTensorInfo(x),u&&s.disposeIntermediateTensorInfo(c),b}function Af(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,keepDims:o}=s;return rK(r,a,o,n)}var aK={kernelName:ao,backendName:"webgl",kernelFunc:Af};function wn(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{perm:a}=s,o=n,i=r.shape.length,l=new Array(i);for(let c=0;c<l.length;c++)l[c]=r.shape[a[c]];let u;if(o.shouldExecuteOnCPU([r])){let d=o.texData.get(r.dataId).values,h=C1(d,r.shape,r.dtype,a,l);u=o.makeTensorInfo(l,r.dtype);let p=o.texData.get(u.dataId);p.values=h}else u=mf(r,a,o);return u}var oK={kernelName:ho,backendName:"webgl",kernelFunc:wn},V6=1e3;function gf({a:e,b:t,transposeA:n,transposeB:s,backend:r,bias:a=null,preluActivationWeights:o=null,leakyreluAlpha:i=0,activation:l=null}){let u=e.shape.length,c=t.shape.length,d=n?e.shape[u-2]:e.shape[u-1],h=s?t.shape[c-1]:t.shape[c-2],p=n?e.shape[u-1]:e.shape[u-2],m=s?t.shape[c-2]:t.shape[c-1],f=e.shape.slice(0,-2),A=t.shape.slice(0,-2),g=I.sizeFromShape(f),y=I.sizeFromShape(A),x=g===y||g===1||y===1;I.assert(u>=2&&c>=2&&x,()=>`Error in matMul: the input batch dimensions must either be the same or at least one input batch dimension must be 1. Got input batch dimensions of (${f}) and (${A}).`);let v=(g>y?e.shape.slice(0,-2):t.shape.slice(0,-2)).concat([p,m]);I.assert(d===h,()=>`Error in matMul: inner shapes (${d}) and (${h}) of Tensors with shapes ${e.shape} and ${t.shape} and transposeA=${n} and transposeB=${s} must match.`);let k=n?[g,d,p]:[g,p,d],w=s?[y,m,h]:[y,h,m],C=ye({inputs:{x:e},backend:r,attrs:{shape:k}}),E=ye({inputs:{x:t},backend:r,attrs:{shape:w}}),P=[C,E],R=Math.max(g,y),_=n?C.shape[1]:C.shape[2],T=a!=null,O=o!=null,W=l==="leakyrelu",j=l!=null?ff(l,!0):null,q=T||O||W||j!=null,X;if((p===1||m===1)&&_>V6&&q===!1){let ne=C,te=E;n&&(ne=wn({inputs:{x:C},backend:r,attrs:{perm:[0,2,1]}}),P.push(ne)),s&&(te=wn({inputs:{x:E},backend:r,attrs:{perm:[0,2,1]}}),P.push(te));let se=m!==1,J=m===1,ie=ne;se&&(ie=ye({inputs:{x:ne},backend:r,attrs:{shape:[R,_,1]}}),P.push(ie));let le=m===1?2:1,he=te;J&&(he=ye({inputs:{x:te},backend:r,attrs:{shape:[R,1,_]}}),P.push(he));let ge=T1({inputs:{a:ie,b:he},backend:r});X=Af({inputs:{x:ge},backend:r,attrs:{axis:le,keepDims:!0}}),P.push(ge)}else{let ne=bs(e.dtype,t.dtype),te=new M6(k,w,[R,p,m],n,s,T,j,O,W),se=[C,E];if(a!=null&&se.push(a),O&&se.push(o),W){let J=r.makeTensorInfo([],"float32",I.createScalarValue(i,"float32"));se.push(J),P.push(J)}X=r.runWebGLProgram(te,se,ne)}let Q=ye({inputs:{x:X},backend:r,attrs:{shape:v}});P.push(X);for(let ne of P)r.disposeIntermediateTensorInfo(ne);return Q}function iK(e){let{inputs:t,backend:n,attrs:s}=e,{a:r,b:a,bias:o,preluActivationWeights:i}=t,{transposeA:l,transposeB:u,activation:c,leakyreluAlpha:d}=s;return gf({a:r,b:a,transposeA:l,transposeB:u,backend:n,bias:o,preluActivationWeights:i,leakyreluAlpha:d,activation:c})}var lK={kernelName:po,backendName:"webgl",kernelFunc:iK},U6="return abs(x);";function uK(e){let{inputs:t,backend:n}=e,{x:s}=t;if(n.shouldExecuteOnCPU([s])&&s.dtype!=="complex64"){let a=n.texData.get(s.dataId),o=w6(a.values);return n.makeTensorInfo(s.shape,s.dtype,o)}let r;return ee().getBool("WEBGL_PACK_UNARY_OPERATIONS")?r=new Yl(s.shape,U6):r=new sa(s.shape,U6),n.runWebGLProgram(r,[s],s.dtype)}var cK={kernelName:di,backendName:"webgl",kernelFunc:uK},dK=Bs+`
if (abs(x) > 1.) {
return NAN;
}
return acos(x);
`,hK=Ze({opSnippet:dK}),pK={kernelName:hi,backendName:"webgl",kernelFunc:hK},fK=Bs+`
if (x < 1.0) return NAN;
return log(x + sqrt(x * x - 1.0));`,mK=Ze({opSnippet:fK}),AK={kernelName:pi,backendName:"webgl",kernelFunc:mK},H6="return a + b;",gK=rn({opSnippet:H6,packedOpSnippet:H6,supportsComplex:!0,cpuKernelImpl:Nq}),yK={kernelName:Dr,backendName:"webgl",kernelFunc:gK},xK=class{constructor(e,t){this.outputShape=[],this.outputShape=e,this.variableNames=t.map((r,a)=>`T${a}`);let n=[];this.variableNames.forEach(r=>{n.push(`float v${r} = get${r}AtOutCoords();`)});let s=this.variableNames.map(r=>`v${r}`).join(" + ");this.userCode=`
void main() {
${n.join(`
`)}
float result = ${s};
setOutput(result);
}
`}},bK=class{constructor(e,t){this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.variableNames=t.map((r,a)=>`T${a}`);let n=[];this.variableNames.forEach(r=>{n.push(`vec4 v${r} = get${r}AtOutCoords();`)});let s=this.variableNames.map(r=>`v${r}`).join(" + ");this.userCode=`
void main() {
${n.join(`
`)}
vec4 result = ${s};
setOutput(result);
}
`}};function yf(e){let{inputs:t,backend:n}=e,s=t;if(s.length===1)return qn({inputs:{x:s[0]},backend:n});if(s.length>ee().get("WEBGL_MAX_TEXTURES_IN_SHADER")){let l=Math.floor(s.length/2),u=yf({inputs:s.slice(0,l),backend:n}),c=yf({inputs:s.slice(l),backend:n});return yf({inputs:[u,c],backend:n})}let r=s.map(l=>l.dtype).reduce((l,u)=>bs(l,u)),a=s.map(l=>l.shape),i=ee().getBool("WEBGL_PACK")?new bK(s[0].shape,a):new xK(s[0].shape,a);return n.runWebGLProgram(i,s,r)}var vK={kernelName:ga,backendName:"webgl",kernelFunc:yf};function wK(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,keepDims:o}=s,i=r.shape.length,l=I.parseAxisParam(a,r.shape),u=l,c=$.getAxesPermutation(u,i),d=r;c!=null&&(d=wn({inputs:{x:r},backend:n,attrs:{perm:c}}),u=$.getInnerMostAxes(u.length,i)),$.assertAxesAreInnerMostDims("all",u,i);let[h,p]=$.computeOutAndReduceShapes(d.shape,u),m=I.sizeFromShape(p),f=ye({inputs:{x:d},backend:n,attrs:{shape:[-1,m]}}),A=Go(f,f.dtype,"all",n),g;if(o){let y=$.expandShapeToKeepDim(h,l);g=ye({inputs:{x:A},backend:n,attrs:{shape:y}})}else g=ye({inputs:{x:A},backend:n,attrs:{shape:h}});return n.disposeIntermediateTensorInfo(f),n.disposeIntermediateTensorInfo(A),c!=null&&n.disposeIntermediateTensorInfo(d),g}var kK={kernelName:fi,backendName:"webgl",kernelFunc:wK};function IK(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,keepDims:o}=s,i=r.shape.length,l=I.parseAxisParam(a,r.shape),u=l,c=$.getAxesPermutation(u,i),d=r;c!=null&&(d=wn({inputs:{x:r},backend:n,attrs:{perm:c}}),u=$.getInnerMostAxes(u.length,i)),$.assertAxesAreInnerMostDims("any",u,i);let[h,p]=$.computeOutAndReduceShapes(d.shape,u),m=I.sizeFromShape(p),f=ye({inputs:{x:d},backend:n,attrs:{shape:[-1,m]}}),A=Go(f,f.dtype,"any",n),g;if(o){let y=$.expandShapeToKeepDim(h,l);g=ye({inputs:{x:A},backend:n,attrs:{shape:y}})}else g=ye({inputs:{x:A},backend:n,attrs:{shape:h}});return n.disposeIntermediateTensorInfo(f),n.disposeIntermediateTensorInfo(A),c!=null&&n.disposeIntermediateTensorInfo(d),g}var SK={kernelName:mi,backendName:"webgl",kernelFunc:IK},CK=class{constructor(e,t,n){this.variableNames=["A"];let{windowSize:s,batchSize:r,outSize:a}=e;n||this.variableNames.push("bestIndicesA"),this.outputShape=[r,a];let o=t==="max"?">":"<",i=n?"inOffset + i;":"round(getBestIndicesA(batch, inOffset + i));";this.userCode=`
void main() {
ivec2 coords = getOutputCoords();
int batch = coords[0];
int outIdx = coords[1];
int inOffset = outIdx * ${s};
int bestIndex = inOffset;
float bestValue = getA(batch, bestIndex);
for (int i = 0; i < ${s}; i++) {
int inIdx = ${i};
float candidate = getA(batch, inIdx);
if (candidate ${o} bestValue) {
bestValue = candidate;
bestIndex = inIdx;
}
}
setOutput(float(bestIndex));
}
`}},TK=class{constructor(e,t,n,s){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,I.assert(e.length>2,()=>`Packed arg${n.charAt(0).toUpperCase()+n.slice(1)} supports only inputs with rank above 2.`);let r=e[e.length-1],a=Math.ceil(r/t);this.outputShape=e.slice(0,-1),a>1&&this.outputShape.push(a),s||this.variableNames.push("bestIndicesA");let o=this.outputShape,i=o.length,l=ut(i),u=vn("coords",i),c,d;if(a===1){d=i+1;let w=ut(d);c=`
${w} sourceLocR = ${w}(${u.join()}, 0);
++${u[i-1]};
${w} sourceLocG = ${w}(${u.join()}, 0);
++${u[i-2]};
${w} sourceLocA = ${w}(${u.join()}, 0);
--${u[i-1]};
${w} sourceLocB = ${w}(${u.join()}, 0);
--${u[i-2]};`}else d=i,c=`
${l} sourceLocR = coords;
++${u[i-1]};
${l} sourceLocG = coords;
++${u[i-2]};
${l} sourceLocA = coords;
--${u[i-1]};
${l} sourceLocB = coords;
--${u[i-2]};`;let h=["x","y","z","w","u","v"].slice(0,d),p="."+h[d-1],m=h.map(w=>"int "+w),f=vn("sourceLocR",d-1).concat("inIdx.r"),A=vn("sourceLocG",d-1).concat("inIdx.g"),g=vn("sourceLocB",d-1).concat("inIdx.b"),y=vn("sourceLocA",d-1).concat("inIdx.a"),x=n==="max"?"greaterThan":"lessThan",b=s?"":`
inIdx = round(vec4(getBestIndicesAChannel(${f.join()}),
getBestIndicesAChannel(${A.join()}),
getBestIndicesAChannel(${g.join()}),
getBestIndicesAChannel(${y.join()})));`,v=`vec4(
getAChannel(${f.join()}),
hasNextCol ? getAChannel(${A.join()}) : 0.,
hasNextRow ? getAChannel(${g.join()}) : 0.,
hasNextRow && hasNextCol ? getAChannel(${y.join()}) : 0.)`,k=s?"":`
float getBestIndicesAChannel(${m.join()}) {
return getChannel(getBestIndicesA(${h.join()}),
vec2(${h.slice(-2).join()}));
}`;this.userCode=`
float getAChannel(${m.join()}) {
return getChannel(getA(${h.join()}),
vec2(${h.slice(-2).join()}));
}
${k}
void main() {
${l} coords = getOutputCoords();
bool hasNextCol = ${u[i-1]} < ${o[i-1]-1};
bool hasNextRow = ${u[i-2]} < ${o[i-2]-1};
${c}
ivec4 srcIdx = ivec4(sourceLocR${p}, sourceLocG${p},
sourceLocB${p}, sourceLocA${p}) * ${t};
ivec4 inIdx = srcIdx;
vec4 bestIndex = vec4(inIdx);
vec4 bestValue = ${v};
for (int i = 0; i < ${t}; i++) {
inIdx = srcIdx;
${b}
vec4 candidate = ${v};
bvec4 nan = isnan(candidate);
bvec4 replace = bvec4(
vec4(${x}(candidate, bestValue)) * (vec4(1.0) - vec4(nan)));
bestValue = vec4(replace.x ? candidate.x : bestValue.x,
replace.y ? candidate.y : bestValue.y,
replace.z ? candidate.z : bestValue.z,
replace.w ? candidate.w : bestValue.w);
bestIndex = mix(bestIndex, vec4(inIdx), vec4(replace));
srcIdx++;
}
setOutput(bestIndex);
}
`}};function G6(e,t,n,s=null){let r=t.shape[0],a=t.shape[1];s!=null&&(r=s.shape[0],a=s.shape[1]);let o=$.computeOptimalWindowSize(a),i={windowSize:o,inSize:a,batchSize:r,outSize:Math.ceil(a/o)},l=new CK(i,n,s==null),u=[t];s!=null&&u.push(s);let c=e.runWebGLProgram(l,u,"int32");if(c.shape[1]===1)return c;let d=G6(e,t,n,c);return e.disposeIntermediateTensorInfo(c),d}function j6(e,t,n,s=null){let r=s!=null?s.shape:t.shape,a=r[r.length-1],o=$.computeOptimalWindowSize(a),i=new TK(r,o,n,s==null),l=s==null?[t]:[t,s],u=e.runWebGLProgram(i,l,"int32");if(u.shape.length===t.shape.length){let c=j6(e,t,n,u);return e.disposeIntermediateTensorInfo(u),c}return u}function q6(e,t,n,s){let r=[n];if($.assertAxesAreInnerMostDims("arg"+s.charAt(0).toUpperCase()+s.slice(1),r,t.shape.length),!ee().getBool("WEBGL_PACK_REDUCE")||t.shape.length<=2){let a=[],[o,i]=$.computeOutAndReduceShapes(t.shape,r),l=I.sizeFromShape(i),u=ye({inputs:{x:t},backend:e,attrs:{shape:[-1,l]}});a.push(u);let c=G6(e,u,s);a.push(c);let d=ye({inputs:{x:c},backend:e,attrs:{shape:o}});return a.forEach(h=>e.disposeIntermediateTensorInfo(h)),d}return j6(e,t,s)}function NK(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a}=s,o=I.parseAxisParam(a,r.shape),i=$.getAxesPermutation(o,r.shape.length),l=r,u=[];i!=null&&(l=wn({inputs:{x:r},backend:n,attrs:{perm:i}}),u.push(l),o=$.getInnerMostAxes(o.length,l.shape.length)),$.assertAxesAreInnerMostDims("argMax",[o[0]],l.shape.length);let c=q6(n,l,o[0],"max");return u.forEach(d=>n.disposeIntermediateTensorInfo(d)),c}var EK={kernelName:ya,backendName:"webgl",kernelFunc:NK};function RK(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a}=s,o=I.parseAxisParam(a,r.shape),i=$.getAxesPermutation(o,r.shape.length),l=r,u=[];i!=null&&(l=wn({inputs:{x:r},backend:n,attrs:{perm:i}}),u.push(l),o=$.getInnerMostAxes(o.length,l.shape.length)),$.assertAxesAreInnerMostDims("argMin",[o[0]],l.shape.length);let c=q6(n,l,o[0],"min");return u.forEach(d=>n.disposeIntermediateTensorInfo(d)),c}var _K={kernelName:Nu,backendName:"webgl",kernelFunc:RK},$K=Bs+`
if (abs(x) > 1.) {
return NAN;
}
return asin(x);
`,FK=Ze({opSnippet:$K}),DK={kernelName:Ai,backendName:"webgl",kernelFunc:FK},OK=Bs+"return log(x + sqrt(x * x + 1.0));",PK=Ze({opSnippet:OK}),MK={kernelName:gi,backendName:"webgl",kernelFunc:PK},zK=Bs+`
return atan(x);
`,LK=Ze({opSnippet:zK}),BK={kernelName:yi,backendName:"webgl",kernelFunc:LK},WK=XX+`
return atan(a, b);
`,VK=`
vec4 result = atan(a, b);
vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
`+KX+`
return result;
`,UK=rn({opSnippet:WK,packedOpSnippet:VK}),HK={kernelName:bi,backendName:"webgl",kernelFunc:UK},GK=Bs+`
if ((x < -1.0) || (x > 1.0)) return NAN;
return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,jK=Ze({opSnippet:GK}),qK={kernelName:xi,backendName:"webgl",kernelFunc:jK},jc=class{constructor(e,t,n,s=!1,r=!1){if(this.variableNames=["x"],t==="avg"&&n)throw new Error("Cannot compute positions for average pool.");let a=e.filterWidth,o=e.strideHeight,i=e.strideWidth,l=e.dilationHeight,u=e.dilationWidth,c=e.effectiveFilterHeight,d=e.effectiveFilterWidth,h=e.padInfo.top,p=e.padInfo.left;this.outputShape=e.outShape;let m=t==="avg",f=`((batch * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + d`,A=`(xR * ${e.inWidth} + xC) * ${e.inChannels} + d`,g="0.0";if(m||(g="-1.0 / 1e-20"),n){let w=">=";this.userCode=`
const ivec2 strides = ivec2(${o}, ${i});
const ivec2 pads = ivec2(${h}, ${p});
void main() {
ivec4 coords = getOutputCoords();
int batch = coords[0];
int d = coords[3];
ivec2 xRCCorner = coords.yz * strides - pads;
int xRCorner = xRCCorner.x;
int xCCorner = xRCCorner.y;
// max/min x(?, ?, d) to get y(yR, yC, d).
// ? = to be determined
float minMaxValue = 0.0;
float minMaxValueFound = 0.0;
int minMaxPosition = 0;
float avgValue = 0.0;
for (int wR = 0; wR < ${c};
wR += ${l}) {
int xR = xRCorner + wR;
if (xR < 0 || xR >= ${e.inHeight}) {
continue;
}
for (int wC = 0; wC < ${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 ${w} currMinMaxValue) {
minMaxValue = value;
minMaxValueFound = 1.0;
minMaxPosition = ${s?r?f:A:`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 b=Math.floor(a/4)*4,v=a%4,k=`
if (${m}) {
avgValue += dot(values, ones);
} else {
minMaxValue = ${y}(values, minMaxValue);
}
`;this.userCode=`
const ivec2 strides = ivec2(${o}, ${i});
const ivec2 pads = ivec2(${h}, ${p});
const float initializationValue = ${g};
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 >= ${e.inWidth}) {
return initializationValue;
}
count += 1.0;
return getX(batch, xR, xC, d);
}
void main() {
ivec4 coords = getOutputCoords();
int batch = coords[0];
int d = coords[3];
ivec2 xRCCorner = coords.yz * strides - pads;
int xRCorner = xRCCorner.x;
int xCCorner = xRCCorner.y;
// max/min x(?, ?, d) to get y(yR, yC, d).
// ? = to be determined
vec4 minMaxValue = vec4(${g});
float avgValue = 0.0;
count = 0.0;
for (int wR = 0; wR < ${c};
wR += ${l}) {
int xR = xRCorner + wR;
if (xR < 0 || xR >= ${e.inHeight}) {
continue;
}
for (int wC = 0; wC < ${b}; 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)
);
${k}
}
int xC = xCCorner + ${b};
if (${v===1}) {
vec4 values = vec4(
getValue(batch, xR, xC, d),
initializationValue,
initializationValue,
initializationValue
);
${k}
} else if (${v===2}) {
vec4 values = vec4(
getValue(batch, xR, xC, d),
getValue(batch, xR, xC + ${u}, d),
initializationValue,
initializationValue
);
${k}
} else if (${v===3}) {
vec4 values = vec4(
getValue(batch, xR, xC, d),
getValue(batch, xR, xC + ${u}, d),
getValue(batch, xR, xC + 2 * ${u}, d),
initializationValue
);
${k}
}
}
setOutput(${x});
}
`}},N1=class{constructor(e,t,n,s=!1,r=!1){if(this.variableNames=["x"],t==="avg"&&n)throw new Error("Cannot compute positions for average pool.");let a=e.filterWidth,o=e.strideDepth,i=e.strideHeight,l=e.strideWidth,u=e.dilationDepth,c=e.dilationHeight,d=e.dilationWidth,h=e.effectiveFilterDepth,p=e.effectiveFilterHeight,m=e.effectiveFilterWidth,f=e.padInfo.front,A=e.padInfo.top,g=e.padInfo.left;this.outputShape=e.outShape;let y=t==="avg",x="0.0";if(y||(x="-1.0 / 1e-20"),n){let E=">=";this.userCode=`
const ivec3 strides =
ivec3(${o}, ${i}, ${l});
const ivec3 pads = ivec3(${f}, ${A}, ${g});
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 < ${h};
wD += ${u}) {
int xD = xDCorner + wD;
if (xD < 0 || xD >= ${e.inDepth}) {
continue;
}
for (int wR = 0; wR < ${p};
wR += ${c}) {
int xR = xRCorner + wR;
if (xR < 0 || xR >= ${e.inHeight}) {
continue;
}
for (int wC = 0; wC < ${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 ${E} currMinMaxValue) {
minMaxValue = value;
minMaxValueFound = 1.0;
minMaxPosition = ${s?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 * ${p} * ${m} +
wR * ${m} + wC`};
}
}
}
}
setOutput(float(minMaxPosition));
}
`;return}let b="max",v=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;t==="avg"&&(v="avgValue / count");let k=Math.floor(a/4)*4,w=a%4,C=`
if (${y}) {
avgValue += dot(values, ones);
} else {
minMaxValue = ${b}(values, minMaxValue);
}
`;this.userCode=`
const ivec3 strides =
ivec3(${o}, ${i}, ${l});
const ivec3 pads = ivec3(${f}, ${A}, ${g});
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 < ${h};
wD += ${u}) {
int xD = xDCorner + wD;
if (xD < 0 || xD >= ${e.inDepth}) {
continue;
}
for (int wR = 0; wR < ${p};
wR += ${c}) {
int xR = xRCorner + wR;
if (xR < 0 || xR >= ${e.inHeight}) {
continue;
}
for (int wC = 0; wC < ${k}; 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)
);
${C}
}
int xC = xCCorner + ${k};
if (${w===1}) {
vec4 values = vec4(
getValue(batch, xD, xR, xC, ch),
initializationValue,
initializationValue,
initializationValue
);
${C}
} else if (${w===2}) {
vec4 values = vec4(
getValue(batch, xD, xR, xC, ch),
getValue(batch, xD, xR, xC + ${d}, ch),
initializationValue,
initializationValue
);
${C}
} else if (${w===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
);
${C}
}
}
setOutput(${v});
}
}
`}};function XK(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t;jl(r,"avgPool");let{filterSize:a,strides:o,pad:i,dimRoundingMode:l}=s,u=1;I.assert($.eitherStridesOrDilationsAreOne(o,u),()=>`Error in avgPool: Either strides or dilations must be 1. Got strides ${o} and dilations '${u}'`);let c=$.computePool2DInfo(r.shape,a,o,u,i,l);if(c.filterWidth===1&&c.filterHeight===1&&I.arraysEqual(c.inShape,c.outShape))return qn({inputs:{x:r},backend:n});let d=new jc(c,"avg",!1);return n.runWebGLProgram(d,[r],"float32")}var KK={kernelName:xa,backendName:"webgl",kernelFunc:XK};function ZK(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{filterSize:a,strides:o,pad:i,dimRoundingMode:l,dataFormat:u}=s,c=[1,1,1],d=$.computePool3DInfo(r.shape,a,o,c,i,l,u),h=new N1(d,"avg",!1);return n.runWebGLProgram(h,[r],"float32")}var YK={kernelName:Eu,backendName:"webgl",kernelFunc:ZK},JK=class{constructor(e){this.variableNames=["dy"],this.outputShape=e.inShape;let t=e.filterHeight,n=e.filterWidth,s=e.strideHeight,r=e.strideWidth,a=e.dilationHeight,o=e.dilationWidth,i=e.effectiveFilterHeight,l=e.effectiveFilterWidth,u=i-1-e.padInfo.top,c=l-1-e.padInfo.left,d=1/(t*n);this.userCode=`
const ivec2 pads = ivec2(${u}, ${c});
const float avgMultiplier = float(${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 < ${i};
wR += ${a}) {
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 < ${l};
wC+= ${o}) {
float dyC = float(dyCCorner + wC) / ${r}.0;
if (dyC < 0.0 || dyC >= ${e.outWidth}.0 ||
fract(dyC) > 0.0) {
continue;
}
int idyC = int(dyC);
float dyValue = getDy(b, idyR, idyC, d);
dotProd += dyValue * avgMultiplier;
}
}
setOutput(dotProd);
}
`}},QK=class{constructor(e){this.variableNames=["dy"],this.outputShape=e.inShape;let t=e.filterDepth,n=e.filterHeight,s=e.filterWidth,r=e.strideDepth,a=e.strideHeight,o=e.strideWidth,i=e.dilationDepth,l=e.dilationHeight,u=e.dilationWidth,c=e.effectiveFilterDepth,d=e.effectiveFilterHeight,h=e.effectiveFilterWidth,p=c-1-e.padInfo.front,m=d-1-e.padInfo.top,f=h-1-e.padInfo.left,A=1/(t*n*s);this.userCode=`
const ivec3 pads = ivec3(${p}, ${m}, ${f});
const float avgMultiplier = float(${A});
void main() {
ivec5 coords = getOutputCoords();
int batch = coords.x;
int ch = coords.u;
ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads;
int dyDCorner = dyCorner.x;
int dyRCorner = dyCorner.y;
int dyCCorner = dyCorner.z;
// Convolve dy(?, ?, ?, d) with pos mask(:, :, :, ch) to get
// dx(xD, xR, xC, ch).
// ? = to be determined. : = across all values in that axis.
float dotProd = 0.0;
for (int wD = 0; wD < ${c};
wD += ${i}) {
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) / ${a}.0;
if (dyR < 0.0 || dyR >= ${e.outHeight}.0 ||
fract(dyR) > 0.0) {
continue;
}
int idyR = int(dyR);
for (int wC = 0; wC < ${h};
wC += ${u}) {
float dyC = float(dyCCorner + wC) / ${o}.0;
if (dyC < 0.0 || dyC >= ${e.outWidth}.0 ||
fract(dyC) > 0.0) {
continue;
}
int idyC = int(dyC);
float dyValue = getDy(batch, idyD, idyR, idyC, ch);
dotProd += dyValue * avgMultiplier;
}
}
}
setOutput(dotProd);
}
`}};function eZ(e){let{inputs:t,backend:n,attrs:s}=e,{dy:r,input:a}=t,o=a,{filterSize:i,strides:l,pad:u,dimRoundingMode:c}=s,d=[1,1,1],h=$.computePool3DInfo(o.shape,i,l,d,u,c),p=new QK(h);return n.runWebGLProgram(p,[r],o.dtype)}var tZ={kernelName:Ld,backendName:"webgl",kernelFunc:eZ};function nZ(e){let{inputs:t,backend:n,attrs:s}=e,{dy:r,input:a}=t,o=a;jl([r,a],"avgPoolGrad");let{filterSize:i,strides:l,pad:u}=s,c=$.computePool2DInfo(o.shape,i,l,1,u),d=new JK(c);return n.runWebGLProgram(d,[r],o.dtype)}var sZ={kernelName:zd,backendName:"webgl",kernelFunc:nZ};function rZ(e){let{inputs:t,backend:n,attrs:s}=e,{a:r,b:a}=t,{transposeA:o,transposeB:i}=s;return gf({a:r,b:a,transposeA:o,transposeB:i,backend:n})}var aZ={kernelName:ba,backendName:"webgl",kernelFunc:rZ},oZ=class{constructor(e,t,n,s,r,a){this.outputShape=[],this.variableNames=["x","mean","variance"],$.assertAndGetBroadcastShape(e,t),$.assertAndGetBroadcastShape(e,n);let o="0.0";s!=null&&($.assertAndGetBroadcastShape(e,s),this.variableNames.push("offset"),o="getOffsetAtOutCoords()");let i="1.0";r!=null&&($.assertAndGetBroadcastShape(e,r),this.variableNames.push("scale"),i="getScaleAtOutCoords()"),this.outputShape=e,this.userCode=`
void main() {
float x = getXAtOutCoords();
float mean = getMeanAtOutCoords();
float variance = getVarianceAtOutCoords();
float offset = ${o};
float scale = ${i};
float inv = scale * inversesqrt(variance + float(${a}));
setOutput(dot(vec3(x, -mean, offset), vec3(inv, inv, 1)));
}
`}},iZ=class{constructor(e,t,n,s,r,a){this.packedInputs=!0,this.packedOutput=!0,this.variableNames=["x","mean","variance"],$.assertAndGetBroadcastShape(e,t),$.assertAndGetBroadcastShape(e,n);let o="vec4(0.0)";s!=null&&($.assertAndGetBroadcastShape(e,s),this.variableNames.push("offset"),o="getOffsetAtOutCoords()");let i="vec4(1.0)";r!=null&&($.assertAndGetBroadcastShape(e,r),this.variableNames.push("scale"),i="getScaleAtOutCoords()"),this.outputShape=e,this.userCode=`
void main() {
vec4 offset = ${o};
vec4 scale = ${i};
vec4 x = getXAtOutCoords();
vec4 mean = getMeanAtOutCoords();
vec4 variance = getVarianceAtOutCoords();
vec4 inv = scale * inversesqrt(variance + vec4(${a}));
setOutput((x - mean) * inv + offset);
}
`}},lZ=({inputs:e,backend:t,attrs:n})=>{let{x:s,mean:r,variance:a,offset:o,scale:i}=e;I.assert(r.shape.length===a.shape.length,()=>"Batch normalization gradient requires mean and variance to have equal ranks."),I.assert(o==null||r.shape.length===o.shape.length,()=>"Batch normalization gradient requires mean and offset to have equal ranks."),I.assert(i==null||r.shape.length===i.shape.length,()=>"Batch normalization gradient requires mean and scale to have equal ranks.");let{varianceEpsilon:l}=n;l==null&&(l=.001);let u=[s,r,a],c=null;o!=null&&(c=o.shape,u.push(o));let d=null;i!=null&&(d=i.shape,u.push(i));let h=ee().getBool("WEBGL_PACK_NORMALIZATION")?new iZ(s.shape,r.shape,a.shape,c,d,l):new oZ(s.shape,r.shape,a.shape,c,d,l);return t.runWebGLProgram(h,u,u[0].dtype)},uZ={kernelName:Fa,backendName:"webgl",kernelFunc:lZ},cZ=class{constructor(e){this.variableNames=["source"],this.outputShape=e,this.rank=e.length;let t=ut(this.rank);this.customUniforms=[{name:"start",arrayIndex:this.rank,type:"int"}];let n=dZ(this.rank),s,r=e.map((a,o)=>`sourceLoc.${E1[o]} = start[${o}] + coords.${E1[o]};`);s=`
${t} sourceLoc;
${t} coords = getOutputCoords();
${r.join(`
`)}
`,this.userCode=`
void main() {
${s}
setOutput(getSource(${n}));
}
`}},E1=["x","y","z","w","u","v"];function dZ(e){if(e===1)return"sourceLoc";if(e<=6)return E1.slice(0,e).map(t=>"sourceLoc."+t).join(",");throw Error(`Slicing for rank ${e} is not yet supported`)}var hZ=class{constructor(e){this.variableNames=["source"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.rank=e.length,this.customUniforms=[{name:"start",arrayIndex:this.rank,type:"int"}];let t=ut(this.rank),n=vn("coords",this.rank),s=vn("sourceLoc",this.rank),r=this.rank===1?"sourceLoc":`vec2(${s.slice(-2).join()})`,a=`getChannel(getSource(${s.join()}), ${r})`,o=`
result.x = ${a};
if (++${n[this.rank-1]} < ${e[this.rank-1]}) {
++${s[this.rank-1]};
result.y = ${a};
--${s[this.rank-1]};
}
`,i=this.rank===1?"":`
--${n[this.rank-1]};
if (++${n[this.rank-2]} < ${e[this.rank-2]}) {
++${s[this.rank-2]};
result.z = ${a};
if (++${n[this.rank-1]} < ${e[this.rank-1]}) {
++${s[this.rank-1]};
result.w = ${a};
}
}
`,l=this.rank<=4?`sourceLoc = coords +
${t}(${e.map((u,c)=>`start[${c}]`).join()});`:e.map((u,c)=>`${s[c]} = ${n[c]} + start[${c}];`).join(`
`);this.userCode=`
void main() {
${t} coords = getOutputCoords();
${t} sourceLoc;
${l}
vec4 result = vec4(0.);
${o}
${i}
setOutput(result);
}
`}};function pZ(e,t,n,s){let r=s.texData.get(e.dataId),a=s.makeTensorInfo(n,e.dtype),o=s.texData.get(a.dataId);Object.assign(o,r),o.refCount=1,o.shape=n,o.dtype=e.dtype;let i=An.computeFlatOffset(t,I.computeStrides(e.shape));r.slice&&(i+=r.slice.flatOffset),o.slice={flatOffset:i,origDataId:r.slice&&r.slice.origDataId||e.dataId};let l=s.dataRefCount.get(o.slice.origDataId)||1;return s.dataRefCount.set(o.slice.origDataId,l+1),a}function eu(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{begin:a,size:o}=s,[i,l]=An.parseSliceParams(r,a,o);if(An.assertParamsValid(r,i,l),I.sizeFromShape(l)===0)return n.makeTensorInfo(l,r.dtype,[]);if(n.shouldExecuteOnCPU([r])||r.dtype==="string"){let d=n.texData.get(r.dataId),h=Qq(d.values,i,l,r.shape,r.dtype);return n.makeTensorInfo(l,r.dtype,h)}let{isPacked:u}=n.texData.get(r.dataId),c=An.isSliceContinous(r.shape,i,l);if(u||!c){let d=ee().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new hZ(l):new cZ(l),h=[i];return n.runWebGLProgram(d,[r],r.dtype,h)}return n.uploadToGPU(r.dataId),pZ(r,i,l,n)}var fZ={kernelName:tl,backendName:"webgl",kernelFunc:eu},mZ=e=>{let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{blockShape:a,crops:o}=s;I.assert(r.shape.length<=4,()=>"batchToSpaceND for rank > 4 with a WebGL backend not implemented yet");let i=a.reduce((y,x)=>y*x),l=$.getReshaped(r.shape,a,i),u=$.getPermuted(l.length,a.length),c=$.getReshapedPermuted(r.shape,a,i),d=$.getSliceBeginCoords(o,a.length),h=$.getSliceSize(c,o,a.length),p=[],m=ye({inputs:{x:r},backend:n,attrs:{shape:l}}),f=wn({inputs:{x:m},backend:n,attrs:{perm:u}}),A=ye({inputs:{x:f},backend:n,attrs:{shape:c}}),g=eu({inputs:{x:A},backend:n,attrs:{begin:d,size:h}});return p.push(m),p.push(f),p.push(A),p.forEach(y=>n.disposeIntermediateTensorInfo(y)),g},AZ={kernelName:vi,backendName:"webgl",kernelFunc:mZ};function gZ(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,weights:a}=t,{size:o}=s,i=n.readSync(r.dataId),l=n.readSync(a.dataId),u=v6(i,l,a.dtype,a.shape,o);return n.makeTensorInfo([o],a.dtype,u)}var yZ={kernelName:Bd,backendName:"webgl",kernelFunc:gZ},xZ="return float(a != b);",X6=rn({opSnippet:xZ,cpuKernelImpl:Kq,dtype:"bool"}),bZ={kernelName:Ui,backendName:"webgl",kernelFunc:X6};function qc(e){let{inputs:t,backend:n}=e,{input:s}=t,r=n.texData.get(s.dataId);return qn({inputs:{x:r.complexTensorInfos.real},backend:n})}var vZ={kernelName:lh,backendName:"webgl",kernelFunc:qc},wZ="return float(int(x));";function kZ(e,t){let n=new sa(e.shape,wZ),s=t.runWebGLProgram(n,[e],"int32");return{dataId:s.dataId,shape:s.shape,dtype:s.dtype}}function R1(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{dtype:a}=s;if(a==="complex64"){if(r.dtype==="complex64")return qn({inputs:{x:r},backend:n});let o=Dt(r.shape),i=R1({inputs:{x:r},backend:n,attrs:{dtype:"float32"}}),l=ra({inputs:{real:i,imag:o},backend:n});return o.dispose(),n.disposeIntermediateTensorInfo(i),l}if(r.dtype==="complex64"){let o=qc({inputs:{input:r},backend:n}),i=R1({inputs:{x:o},backend:n,attrs:{dtype:a}});return n.disposeIntermediateTensorInfo(o),i}if(!I.hasEncodingLoss(r.dtype,a)){let o=qn({inputs:{x:r},backend:n});return{dataId:o.dataId,shape:o.shape,dtype:a}}if(a==="int32")return kZ(r,n);if(a==="bool"){let o=n.makeTensorInfo([],"bool",I.getTypedArrayFromDType("bool",1)),l=X6({inputs:{a:r,b:o},backend:n});return n.disposeIntermediateTensorInfo(o),l}throw new Error(`Error in Cast: failed to cast ${r.dtype} to ${a}`)}var IZ={kernelName:va,backendName:"webgl",kernelFunc:R1},K6="return ceil(x);",SZ=Ze({opSnippet:K6,packedOpSnippet:K6,cpuKernelImpl:Rq}),CZ={kernelName:wa,backendName:"webgl",kernelFunc:SZ},TZ=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));
}
`}},NZ=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 EZ(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{clipValueMin:a,clipValueMax:o}=s,i;ee().getBool("WEBGL_PACK_CLIP")?i=new NZ(r.shape):i=new TZ(r.shape);let l=[[a],[o]];return n.runWebGLProgram(i,[r],r.dtype,l)}var RZ={kernelName:Or,backendName:"webgl",kernelFunc:EZ},_Z=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 Z6(e,t){return{dataId:t.dataId,dtype:t.dtype,shape:e.shape}}function $Z(e){let{inputs:t,backend:n}=e,{x:s}=t,r=n.texData.get(s.dataId),a=new _Z(s.shape),o=[Z6(s,r.complexTensorInfos.real),Z6(s,r.complexTensorInfos.imag)];return n.runWebGLProgram(a,o,o[0].dtype)}var FZ={kernelName:Ru,backendName:"webgl",kernelFunc:$Z},DZ=class{constructor(e){this.outputShape=[],this.outputShape=$.computeOutShape(e,1),this.variableNames=e.map((a,o)=>`T${o}`);let t=new Array(e.length-1);t[0]=e[0][1];for(let a=1;a<t.length;a++)t[a]=t[a-1]+e[a][1];let n=[`if (yC < ${t[0]}) setOutput(getT0(yR, yC));`];for(let a=1;a<t.length;a++){let o=t[a-1];n.push(`else if (yC < ${t[a]}) setOutput(getT${a}(yR, yC-${o}));`)}let s=t.length,r=t[t.length-1];n.push(`else setOutput(getT${s}(yR, yC-${r}));`),this.userCode=`
void main() {
ivec2 coords = getOutputCoords();
int yR = coords.x;
int yC = coords.y;
${n.join(`
`)}
}
`}},OZ=class{constructor(e,t){this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[],this.outputShape=$.computeOutShape(e,t);let n=this.outputShape,s=n.length,r=ut(s),a=vn("coords",s),o=["x","y","z","w","u","v"].slice(0,s);this.variableNames=e.map((m,f)=>`T${f}`);let i=new Array(e.length-1);i[0]=e[0][t];for(let m=1;m<i.length;m++)i[m]=i[m-1]+e[m][t];let l=o[t],u=o.slice(-2),c=o.join(),d=`if (${l} < ${i[0]}) {
return getChannel(
getT0(${c}), vec2(${u.join()}));
}`;for(let m=1;m<i.length;m++){let f=i[m-1];d+=`
if (${l} < ${i[m]} && ${l} >= ${i[m-1]}) {
return getChannel(
getT${m}(${xf(o,l,f)}),
vec2(${xf(u,l,f)}));
}`}let h=i.length,p=i[i.length-1];d+=`
return getChannel(
getT${h}(${xf(o,l,p)}),
vec2(${xf(u,l,p)}));`,this.userCode=`
float getValue(${o.map(m=>"int "+m)}) {
${d}
}
void main() {
${r} coords = getOutputCoords();
vec4 result = vec4(getValue(${a}), 0., 0., 0.);
${a[s-1]} = ${a[s-1]} + 1;
if (${a[s-1]} < ${n[s-1]}) {
result.g = getValue(${a});
}
${a[s-2]} = ${a[s-2]} + 1;
if (${a[s-2]} < ${n[s-2]}) {
result.a = getValue(${a});
}
${a[s-1]} = ${a[s-1]} - 1;
if (${a[s-2]} < ${n[s-2]} &&
${a[s-1]} < ${n[s-1]}) {
result.b = getValue(${a});
}
setOutput(result);
}
`}};function xf(e,t,n){let s=e.indexOf(t);return e.map((a,o)=>o===s?`${a} - ${n}`:a).join()}function bf(e){let{inputs:t,backend:n}=e,{input:s}=t,r=n.texData.get(s.dataId);return qn({inputs:{x:r.complexTensorInfos.imag},backend:n})}var PZ={kernelName:th,backendName:"webgl",kernelFunc:bf};function tu(e,t,n){let s=e[0].dtype;if(s==="complex64"){let c=e.map(f=>qc({inputs:{input:f},backend:n})),d=e.map(f=>bf({inputs:{input:f},backend:n})),h=tu(c,t,n),p=tu(d,t,n),m=ra({inputs:{real:h,imag:p},backend:n});return c.forEach(f=>n.disposeIntermediateTensorInfo(f)),d.forEach(f=>n.disposeIntermediateTensorInfo(f)),n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(p),m}let r=n.shouldExecuteOnCPU(e);if(s==="string"&&(r=!0),r){let c=e.map(g=>{let y=I.sizeFromShape(g.shape.slice(t));return ye({inputs:{x:g},backend:n,attrs:{shape:[-1,y]}})}),d=c.map(g=>({vals:n.readSync(g.dataId),shape:g.shape})),h=$.computeOutShape(c.map(g=>g.shape),1),p=c[0].shape[0]===1,m=_q(d,h,s,p),f=$.computeOutShape(e.map(g=>g.shape),t),A=n.makeTensorInfo(f,s,m);return c.forEach(g=>n.disposeIntermediateTensorInfo(g)),A}if(e.length>ee().getNumber("WEBGL_MAX_TEXTURES_IN_SHADER")){let c=Math.floor(e.length/2),d=tu(e.slice(0,c),t,n),h=tu(e.slice(c),t,n),p=tu([d,h],t,n);return n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(h),p}if(ee().getBool("WEBGL_PACK_ARRAY_OPERATIONS")&&e[0].shape.length>1){let c=new OZ(e.map(d=>d.shape),t);return n.runWebGLProgram(c,e,s)}let{tensors2D:a,outShape:o}=MZ(e,t,n),i=new DZ(a.map(c=>c.shape)),l=n.runWebGLProgram(i,a,s);a.forEach(c=>n.disposeIntermediateTensorInfo(c));let u=ye({inputs:{x:l},attrs:{shape:o},backend:n});return n.disposeIntermediateTensorInfo(l),u}function MZ(e,t,n){let s=$.computeOutShape(e.map(a=>a.shape),t);return{tensors2D:e.map(a=>ye({inputs:{x:a},attrs:{shape:[-1,I.sizeFromShape(a.shape.slice(t))]},backend:n})),outShape:s}}function Y6(e){let{inputs:t,backend:n,attrs:s}=e,{axis:r}=s,a=I.parseAxisParam(r,t[0].shape)[0],o=$.computeOutShape(t.map(u=>u.shape),a);if(I.sizeFromShape(o)===0)return n.makeTensorInfo(o,t[0].dtype,[]);let i=t.filter(u=>I.sizeFromShape(u.shape)>0);if(i.length===1)return qn({inputs:{x:i[0]},backend:n});let l=i.map(u=>u.shape);return $.assertParamsConsistent(l,a),tu(i,a,n)}var zZ={kernelName:wi,backendName:"webgl",kernelFunc:Y6},J6=class{constructor(e,t=!1,n=null,s=!1,r=!1){this.variableNames=["x","W"],this.outputShape=e.outShape;let a=e.padInfo.top,o=e.padInfo.left,i=e.strideHeight,l=e.strideWidth,u=e.dilationHeight,c=e.dilationWidth,d=e.filterHeight,h=e.filterWidth,p=Math.floor(e.inChannels/4)*4,m=e.inChannels%4,f=e.dataFormat==="channelsLast",A=f?1:2,g=f?2:3,y=f?3:1,x="",b="";n&&(s?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}
}
`,b="result = activation(result);");let v=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),s&&this.variableNames.push("preluActivationWeights"),r&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
${x}
const ivec2 strides = ivec2(${i}, ${l});
const ivec2 pads = ivec2(${a}, ${o});
void main() {
ivec4 coords = getOutputCoords();
int batch = coords[0];
int d2 = coords[${y}];
ivec2 xRCCorner =
ivec2(coords[${A}], coords[${g}]) * 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 < ${h}; wC++) {
int xC = xCCorner + wC * ${c};
if (xC < 0 || xC >= ${e.inWidth}) {
continue;
}
for (int d1 = 0; d1 < ${p}; d1 += 4) {
vec4 wValues = vec4(
getW(wR, wC, d1, d2),
getW(wR, wC, d1 + 1, d2),
getW(wR, wC, d1 + 2, d2),
getW(wR, wC, d1 + 3, d2)
);
if (${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, ${p}) *
getW(wR, wC, ${p}, d2);
} else {
dotProd +=
getX(batch, ${p}, xR, xC) *
getW(wR, wC, ${p}, d2);
}
} else if (${m===2}) {
vec2 wValues = vec2(
getW(wR, wC, ${p}, d2),
getW(wR, wC, ${p} + 1, d2)
);
if (${f}) {
vec2 xValues = vec2(
getX(batch, xR, xC, ${p}),
getX(batch, xR, xC, ${p} + 1)
);
dotProd += dot(xValues, wValues);
} else {
vec2 xValues = vec2(
getX(batch, ${p}, xR, xC),
getX(batch, ${p} + 1, xR, xC)
);
dotProd += dot(xValues, wValues);
}
} else if (${m===3}) {
vec3 wValues = vec3(
getW(wR, wC, ${p}, d2),
getW(wR, wC, ${p} + 1, d2),
getW(wR, wC, ${p} + 2, d2)
);
if (${f}) {
vec3 xValues = vec3(
getX(batch, xR, xC, ${p}),
getX(batch, xR, xC, ${p} + 1),
getX(batch, xR, xC, ${p} + 2)
);
dotProd += dot(xValues, wValues);
} else {
vec3 xValues = vec3(
getX(batch, ${p}, xR, xC),
getX(batch, ${p} + 1, xR, xC),
getX(batch, ${p} + 2, xR, xC)
);
dotProd += dot(xValues, wValues);
}
}
}
}
float result = dotProd;
${v}
${b}
setOutput(result);
}
`}},LZ=class{constructor(e){this.variableNames=["x","W"],this.outputShape=e.outShape;let t=e.padInfo.front,n=e.padInfo.top,s=e.padInfo.left,r=e.strideDepth,a=e.strideHeight,o=e.strideWidth,i=e.dilationDepth,l=e.dilationHeight,u=e.dilationWidth,c=e.filterDepth,d=e.filterHeight,h=e.filterWidth,p=Math.floor(e.inChannels/4)*4,m=e.inChannels%4;this.userCode=`
const ivec3 strides = ivec3(${r}, ${a}, ${o});
const ivec3 pads = ivec3(${t}, ${n}, ${s});
void main() {
ivec5 coords = getOutputCoords();
int batch = coords.x;
int d2 = coords.u;
ivec3 xFRCCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;
int xFCorner = xFRCCorner.x;
int xRCorner = xFRCCorner.y;
int xCCorner = xFRCCorner.z;
// Convolve x(?, ?, ?, d1) with w(:, :, :, d1, d2) to get
// y(yF, yR, yC, d2). ? = to be determined. : = across all
// values in that axis.
float dotProd = 0.0;
for (int wF = 0; wF < ${c}; wF++) {
int xF = xFCorner + wF * ${i};
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 < ${h}; wC++) {
int xC = xCCorner + wC * ${u};
if (xC < 0 || xC >= ${e.inWidth}) {
continue;
}
for (int d1 = 0; d1 < ${p}; d1 += 4) {
vec4 xValues = vec4(
getX(batch, xF, xR, xC, d1),
getX(batch, xF, xR, xC, d1 + 1),
getX(batch, xF, xR, xC, d1 + 2),
getX(batch, xF, xR, xC, d1 + 3)
);
vec4 wValues = vec4(
getW(wF, wR, wC, d1, d2),
getW(wF, wR, wC, d1 + 1, d2),
getW(wF, wR, wC, d1 + 2, d2),
getW(wF, wR, wC, d1 + 3, d2)
);
dotProd += dot(xValues, wValues);
}
if (${m===1}) {
dotProd +=
getX(batch, xF, xR, xC, ${p}) *
getW(wF, wR, wC, ${p}, d2);
} else if (${m===2}) {
vec2 xValues = vec2(
getX(batch, xF, xR, xC, ${p}),
getX(batch, xF, xR, xC, ${p} + 1)
);
vec2 wValues = vec2(
getW(wF, wR, wC, ${p}, d2),
getW(wF, wR, wC, ${p} + 1, d2)
);
dotProd += dot(xValues, wValues);
} else if (${m===3}) {
vec3 xValues = vec3(
getX(batch, xF, xR, xC, ${p}),
getX(batch, xF, xR, xC, ${p} + 1),
getX(batch, xF, xR, xC, ${p} + 2)
);
vec3 wValues = vec3(
getW(wF, wR, wC, ${p}, d2),
getW(wF, wR, wC, ${p} + 1, d2),
getW(wF, wR, wC, ${p} + 2, d2)
);
dotProd += dot(xValues, wValues);
}
}
}
}
setOutput(dotProd);
}
`}},BZ=class{constructor(e,t,n){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e;let{filterWidth:s,inChannels:r,strideWidth:a,strideHeight:o,padInfo:i,outWidth:l,dilationWidth:u,dilationHeight:c,dataFormat:d}=n,{left:h,top:p}=i,m=r*s,f=bn(),A=d==="channelsLast",g=A?0:1,y=A?1:2,x="";for(let b=0;b<=1;b++)for(let v=0;v<=1;v++)x+=`
blockIndex = rc.y + ${v};
pos = rc.x + ${b};
if(blockIndex < ${e[1]} && pos < ${e[0]}) {
offsetY = int(blockIndex / (${l})) * ${o} - ${p};
d0 = offsetY + ${c} * (pos / ${m});
if(d0 < ${t[g]} && d0 >= 0) {
offsetX = int(mod(float(blockIndex), ${l}.) * ${a}. - ${h}.);
d1 = offsetX + ${u} * (int(mod(float(pos), ${m}.) / ${r}.));
if(d1 < ${t[y]} && d1 >= 0) {
ch = int(mod(float(pos), ${r}.));
if (${A}) {
innerDims = vec2(d1, ch);
result[${b*2+v}] = getChannel(
getA(d0, int(innerDims.x),
int(innerDims.y)), innerDims);
} else {
innerDims = vec2(d0, d1);
result[${b*2+v}] = getChannel(
getA(ch, int(innerDims.x),
int(innerDims.y)), innerDims);
}
}
}
}
`;this.userCode=`
void main() {
ivec2 rc = getOutputCoords();
vec4 result = vec4(0);
int blockIndex, pos, offsetY, d0, offsetX, d1, ch;
vec2 innerDims;
${x}
${f.output} = result;
}
`}};function Q6({x:e,filter:t,convInfo:n,backend:s,bias:r=null,preluActivationWeights:a=null,leakyreluAlpha:o=0,activation:i=null}){let l=e.shape,u=s.texData.get(e.dataId),c=n.inChannels,d=l[0]*l[1]*l[2],h=n.outChannels,p=n.dataFormat==="channelsLast",m=!1,f=!1,A,g=[],y=(d===1||h===1)&&c>V6,x=l[2]%2!=0&&!!u.isPacked;if(y||!ee().getBool("WEBGL_LAZILY_UNPACK")||!ee().getBool("WEBGL_PACK_BINARY_OPERATIONS")||!x){let b=p?l[0]*l[1]*l[2]:l[0]*l[2]*l[3],v=ye({inputs:{x:e},backend:s,attrs:{shape:[1,b,n.inChannels]}}),k=ye({inputs:{x:t},backend:s,attrs:{shape:[1,n.inChannels,n.outChannels]}}),w=gf({a:v,b:k,transposeA:m,transposeB:f,backend:s,bias:r,activation:i,preluActivationWeights:a,leakyreluAlpha:o});A=ye({inputs:{x:w},backend:s,attrs:{shape:n.outShape}}),g.push(v),g.push(k),g.push(w)}else{let b=p?l[0]*l[1]*(l[2]+1):l[0]*l[2]*(l[3]+1),v={dataId:e.dataId,shape:[1,b,n.inChannels],dtype:e.dtype},k=u.shape;u.shape=u.shape.slice(),u.shape[u.shape.length-2]++,I.assert(Uc(u.shape,v.shape),()=>`packed reshape ${u.shape} to ${v.shape} isn't free`);let w=ye({inputs:{x:t},backend:s,attrs:{shape:[1,n.inChannels,n.outChannels]}});g.push(w);let C=gf({a:v,b:w,backend:s,transposeA:m,transposeB:f,bias:r,activation:i,preluActivationWeights:a,leakyreluAlpha:o}),E=s.texData.get(C.dataId);I.assert(E.isPacked,()=>"batchMatMul result is expected to be packed"),u.shape=k,E.shape=n.outShape,A=qn({inputs:{x:C},backend:s}),A.shape=n.outShape,g.push(C)}for(let b of g)s.disposeIntermediateTensorInfo(b);return A}function e4({x:e,filter:t,convInfo:n,backend:s,bias:r=null,preluActivationWeights:a=null,leakyreluAlpha:o=0,activation:i=null}){let{filterWidth:l,filterHeight:u,inChannels:c,outWidth:d,outHeight:h,dataFormat:p}=n,m=p==="channelsLast",f=l*u*c,A=h*d,g=[f,A],y=!0,x=!1,b=[],v=ye({inputs:{x:e},backend:s,attrs:{shape:e.shape.slice(1)}}),k=ye({inputs:{x:t},backend:s,attrs:{shape:[1,f,I.sizeFromShape(t.shape)/f]}});b.push(v),b.push(k);let w=new BZ(g,v.shape,n),C=s.runWebGLProgram(w,[v],"float32"),E=ye({inputs:{x:C},backend:s,attrs:{shape:[1,g[0],g[1]]}});b.push(C),b.push(E);let P=r!=null,R=a!=null,_=i==="leakyrelu",T=i?ff(i,!0):null,O=new M6(E.shape,k.shape,[1,A,n.outChannels],y,x,P,T,R,_),W=[E,k];if(r&&W.push(r),R&&W.push(a),_){let Q=s.makeTensorInfo([],"float32",I.createScalarValue(o,"float32"));W.push(Q),b.push(Q)}let j=s.runWebGLProgram(O,W,"float32"),q=m?[1,h,d,n.outChannels]:[1,n.outChannels,h,d],X=ye({inputs:{x:j},backend:s,attrs:{shape:q}});b.push(j);for(let Q of b)s.disposeIntermediateTensorInfo(Q);return X}function WZ(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,filter:a}=t,{strides:o,pad:i,dataFormat:l,dilations:u,dimRoundingMode:c}=s,d=$.convertConv2DDataFormat(l),h=$.computeConv2DInfo(r.shape,a.shape,o,u,i,c,!1,d),p;if(h.filterHeight===1&&h.filterWidth===1&&h.dilationHeight===1&&h.dilationWidth===1&&h.strideHeight===1&&h.strideWidth===1&&(h.padInfo.type==="SAME"||h.padInfo.type==="VALID"))p=Q6({x:r,filter:a,convInfo:h,backend:n});else if(ee().getBool("WEBGL_CONV_IM2COL")&&r.shape[0]===1)p=e4({x:r,filter:a,convInfo:h,backend:n});else{let f=new J6(h);p=n.runWebGLProgram(f,[r,a],"float32")}let m=ye({inputs:{x:p},backend:n,attrs:{shape:h.outShape}});return n.disposeIntermediateTensorInfo(p),m}var VZ={kernelName:ka,backendName:"webgl",kernelFunc:WZ},UZ=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideHeight,n=e.strideWidth,s=e.padInfo.top,r=e.padInfo.left,a=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} - ${s};
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 >= ${e.inWidth}) {
continue;
}
if (${a}) {
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);
}
`}},HZ=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterHeight,n=e.filterWidth,s=e.strideHeight,r=e.strideWidth,a=e.dataFormat==="channelsLast",o=t-1-e.padInfo.top,i=n-1-e.padInfo.left,l=a?1:2,u=a?2:3,c=a?3:1;this.userCode=`
const ivec2 pads = ivec2(${o}, ${i});
void main() {
ivec4 coords = getOutputCoords();
int batch = coords[0];
int d1 = coords[${c}];
ivec2 dyCorner = ivec2(coords[${l}], coords[${u}]) - pads;
int dyRCorner = dyCorner.x;
int dyCCorner = dyCorner.y;
// Convolve dy(?, ?, d2) with w(:, :, d1, d2) to compute dx(xR, xC, d1).
// ? = to be determined. : = across all values in that axis.
float dotProd = 0.0;
for (int wR = 0; wR < ${t}; wR++) {
float dyR = float(dyRCorner + wR) / ${s}.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 < ${e.outChannels}; d2++) {
if (${a}) {
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);
}
`}},GZ=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideDepth,n=e.strideHeight,s=e.strideWidth,r=e.padInfo.front,a=e.padInfo.top,o=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} - ${a};
if (xR < 0 || xR >= ${e.inHeight}) {
continue;
}
for (int yC = 0; yC < ${e.outWidth}; yC++) {
int xC = wC + yC * ${s} - ${o};
if (xC < 0 || xC >= ${e.inWidth}) {
continue;
}
float dyValue = getDy(b, yF, yR, yC, d2);
float xValue = getX(b, xF, xR, xC, d1);
dotProd += (xValue * dyValue);
}
}
}
}
setOutput(dotProd);
}
`}},jZ=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterDepth,n=e.filterHeight,s=e.filterWidth,r=e.strideDepth,a=e.strideHeight,o=e.strideWidth,i=t-1-e.padInfo.front,l=n-1-e.padInfo.top,u=s-1-e.padInfo.left;this.userCode=`
const ivec3 pads = ivec3(${i}, ${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) / ${a}.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 < ${s}; wC++) {
float dyC = float(dyCCorner + wC) / ${o}.0;
if (dyC < 0.0 || dyC >= ${e.outWidth}.0 ||
fract(dyC) > 0.0) {
continue;
}
int idyC = int(dyC);
int wCPerm = ${s} - 1 - wC;
for (int d2 = 0; d2 < ${e.outChannels}; d2++) {
float xValue = getDy(batch, idyF, idyR, idyC, d2);
float wValue = getW(wFPerm, wRPerm, wCPerm, d1, d2);
dotProd += xValue * wValue;
}
}
}
}
setOutput(dotProd);
}
`}};function qZ(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,dy:a}=t,{strides:o,pad:i,dataFormat:l,dimRoundingMode:u,filterShape:c}=s,d=$.convertConv2DDataFormat(l),h=$.computeConv2DInfo(r.shape,c,o,1,i,u,!1,d),p=new UZ(h);return n.runWebGLProgram(p,[r,a],"float32")}var XZ={kernelName:Vd,backendName:"webgl",kernelFunc:qZ};function KZ(e){let{inputs:t,backend:n,attrs:s}=e,{dy:r,filter:a}=t,{inputShape:o,strides:i,pad:l,dataFormat:u,dimRoundingMode:c}=s,d=$.convertConv2DDataFormat(u),h=$.computeConv2DInfo(o,a.shape,i,1,l,c,!1,d),p=new HZ(h);return n.runWebGLProgram(p,[r,a],"float32")}var ZZ={kernelName:Ia,backendName:"webgl",kernelFunc:KZ};function YZ(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,filter:a}=t,{strides:o,pad:i,dilations:l}=s,u=$.computeConv3DInfo(r.shape,a.shape,o,l,i),c=new LZ(u);return n.runWebGLProgram(c,[r,a],"float32")}var JZ={kernelName:_u,backendName:"webgl",kernelFunc:YZ};function QZ(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,dy:a}=t,{strides:o,pad:i,filterShape:l}=s,u=$.computeConv3DInfo(r.shape,l,o,1,i),c=new GZ(u);return n.runWebGLProgram(c,[r,a],"float32")}var eY={kernelName:Ud,backendName:"webgl",kernelFunc:QZ};function tY(e){let{inputs:t,backend:n,attrs:s}=e,{dy:r,filter:a}=t,{pad:o,strides:i,inputShape:l}=s,u=$.computeConv3DInfo(l,a.shape,i,1,o),c=new jZ(u);return n.runWebGLProgram(c,[r,a],"float32")}var nY={kernelName:Hd,backendName:"webgl",kernelFunc:tY},sY=P6+`
return cos(x);
`,rY=Ze({opSnippet:sY}),aY={kernelName:Sa,backendName:"webgl",kernelFunc:rY},oY=`
float e2x = exp(-x);
return (e2x + 1.0 / e2x) / 2.0;
`,iY=Ze({opSnippet:oY}),lY={kernelName:Ca,backendName:"webgl",kernelFunc:iY},uY=class{constructor(e,t,n,s,r){this.variableNames=["Image","Boxes","BoxInd"],this.outputShape=[];let[a,o,i,l]=e,[u]=t,[c,d]=n;this.outputShape=[u,c,d,l];let h=s==="bilinear"?1:0,[p,m]=[`${o-1}.0`,`${i-1}.0`],[f,A,g]=c>1?[`${(o-1)/(c-1)}`,"(y2-y1) * height_ratio",`y1*${p} + float(y)*(height_scale)`]:["0.0","0.0",`0.5 * (y1+y2) * ${p}`],[y,x,b]=d>1?[`${(i-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 >= ${a}) {
return;
}
float height_scale = ${A};
float width_scale = ${x};
float in_y = ${g};
if( in_y < 0.0 || in_y > ${p} ) {
setOutput(float(${r}));
return;
}
float in_x = ${b};
if( in_x < 0.0 || in_x > ${m} ) {
setOutput(float(${r}));
return;
}
vec2 sourceFracIndexCR = vec2(in_x,in_y);
if(${h} == 1) {
// Compute the four integer indices.
ivec2 sourceFloorCR = ivec2(sourceFracIndexCR);
ivec2 sourceCeilCR = ivec2(ceil(sourceFracIndexCR));
float topLeft = getImage(b, sourceFloorCR.y, sourceFloorCR.x, d);
float bottomLeft = getImage(b, sourceCeilCR.y, sourceFloorCR.x, d);
float topRight = getImage(b, sourceFloorCR.y, sourceCeilCR.x, d);
float bottomRight = getImage(b, sourceCeilCR.y, sourceCeilCR.x, d);
vec2 fracCR = sourceFracIndexCR - vec2(sourceFloorCR);
float top = topLeft + (topRight - topLeft) * fracCR.x;
float bottom = bottomLeft + (bottomRight - bottomLeft) * fracCR.x;
float newValue = top + (bottom - top) * fracCR.y;
setOutput(newValue);
} else {
// Compute the coordinators of nearest neighbor point.
ivec2 sourceNearestCR = ivec2(floor(
sourceFracIndexCR + vec2(0.5,0.5)));
float newValue = getImage(b, sourceNearestCR.y, sourceNearestCR.x, d);
setOutput(newValue);
}
}
`}},cY=e=>{let{inputs:t,backend:n,attrs:s}=e,{image:r,boxes:a,boxInd:o}=t,{cropSize:i,method:l,extrapolationValue:u}=s,c=new uY(r.shape,a.shape,i,l,u);return n.runWebGLProgram(c,[r,a,o],"float32")},dY={kernelName:ki,backendName:"webgl",kernelFunc:cY},t4=class{constructor(e,t,n){this.variableNames=["x"],this.customUniforms=[{name:"index",type:"float"}],this.outputShape=e;let s=e.length,r=t?"0.0":`getX(${n4(s,"coords")})`,a=e[e.length-1],o="",i="";t?(o=n?`end != ${a-1}`:"end != 0",i=n?"end + 1":"end - 1"):(o=n?`end + pow2 < ${a}`:"end >= pow2",i=n?"end + pow2":"end - pow2"),this.userCode=`
void main() {
${ut(s)} coords = getOutputCoords();
int end = ${s4(s,"coords")};
float val = ${r};
int pow2 = int(pow(2.0, index));
if (${o}) {
int idx = ${i};
${s4(s,"coords")} = idx;
val += getX(${n4(s,"coords")});
}
setOutput(val);
}
`}};function n4(e,t){if(e===1)return`${t}`;if(e===2)return`${t}.x, ${t}.y`;if(e===3)return`${t}.x, ${t}.y, ${t}.z`;if(e===4)return`${t}.x, ${t}.y, ${t}.z, ${t}.w`;throw Error(`Cumulative sum for rank ${e} is not yet supported`)}function s4(e,t){if(e===1)return`${t}`;if(e===2)return`${t}.y`;if(e===3)return`${t}.z`;if(e===4)return`${t}.w`;throw Error(`Cumulative sum for rank ${e} is not yet supported`)}function hY(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,exclusive:o,reverse:i}=s,l=r.shape.length,u=$.getAxesPermutation([a],l),c=r;u!=null&&(c=wn({inputs:{x:r},backend:n,attrs:{perm:u}}));let d=$.getInnerMostAxes(1,l)[0];if(d!==l-1)throw new Error(`WebGL cumsum shader expects an inner-most axis=${r.shape.length-1} but got axis=${a}`);let h=c.shape[d],p=qn({inputs:{x:c},backend:n});for(let m=0;m<=Math.ceil(Math.log2(h))-1;m++){let f=new t4(c.shape,!1,i),A=[[m]],g=p;p=n.runWebGLProgram(f,[p],p.dtype,A),n.disposeIntermediateTensorInfo(g)}if(o){let m=new t4(c.shape,o,i),f=p;p=n.runWebGLProgram(m,[p],p.dtype),n.disposeIntermediateTensorInfo(f)}if(u!=null){let m=$.getUndoAxesPermutation(u),f=wn({inputs:{x:p},backend:n,attrs:{perm:m}});return n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(c),f}return p}var pY={kernelName:Ta,backendName:"webgl",kernelFunc:hY};function fY(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,weights:a}=t,{size:o,binaryOutput:i}=s;if(r.shape.length===1){let l=n.readSync(r.dataId),u=n.readSync(a.dataId),c=v6(l,u,a.dtype,a.shape,o);return n.makeTensorInfo([o],a.dtype,c)}else if(r.shape.length===2){let l=n.bufferSync(r),u=n.bufferSync(a),c=Eq(l,u,o,i);return n.makeTensorInfo(c.shape,a.dtype,c.values)}throw new Error(`Error in denseBincount: input must be at most rank 2, but got rank${r.shape.length}.`)}var mY={kernelName:Gd,backendName:"webgl",kernelFunc:fY},AY=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 gY(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{blockSize:a,dataFormat:o}=s;I.assert(a>1,()=>`blockSize should be > 1 for depthToSpace, but was: ${a}`);let i=r.shape[0],l=o==="NHWC"?r.shape[1]:r.shape[2],u=o==="NHWC"?r.shape[2]:r.shape[3],c=o==="NHWC"?r.shape[3]:r.shape[1],d=l*a,h=u*a,p=c/(a*a),m=o==="NHWC"?[i,d,h,p]:[i,p,d,h],f=new AY(m,a,o);return n.runWebGLProgram(f,[r],r.dtype)}var yY={kernelName:Ii,backendName:"webgl",kernelFunc:gY},r4=class{constructor(e,t=!1,n=null,s=!1,r=!1){this.variableNames=["x","W"],this.outputShape=e.outShape;let a=e.inHeight,o=e.inWidth,i=e.padInfo.top,l=e.padInfo.left,u=e.strideHeight,c=e.strideWidth,d=e.dilationHeight,h=e.dilationWidth,p=e.filterHeight,m=e.filterWidth,f=e.outChannels/e.inChannels,A="",g="";n&&(s?A=`float activation(float a) {
float b = getPreluActivationWeightsAtOutCoords();
${n}
}`:r?A=`float activation(float a) {
float b = getLeakyreluAlphaAtOutCoords();
${n}
}`:A=`
float activation(float x) {
${n}
}
`,g="result = activation(result);");let y=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),s&&this.variableNames.push("preluActivationWeights"),r&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
${A}
const ivec2 strides = ivec2(${u}, ${c});
const ivec2 pads = ivec2(${i}, ${l});
void main() {
ivec4 coords = getOutputCoords();
int batch = coords.x;
ivec2 xRCCorner = coords.yz * strides - pads;
int d2 = coords.w;
int d1 = d2 / ${f};
int q = d2 - d1 * ${f};
int xRCorner = xRCCorner.x;
int xCCorner = xRCCorner.y;
// Convolve x(?, ?, d1) with w(:, :, d1, q) to get y(yR, yC, d2).
// ? = to be determined. : = across all values in that axis.
float dotProd = 0.0;
// TO DO(dsmilkov): Flatten the two for loops and vec4 the operations.
for (int wR = 0; wR < ${p}; wR++) {
int xR = xRCorner + wR * ${d};
if (xR < 0 || xR >= ${a}) {
continue;
}
for (int wC = 0; wC < ${m}; wC++) {
int xC = xCCorner + wC * ${h};
if (xC < 0 || xC >= ${o}) {
continue;
}
float xVal = getX(batch, xR, xC, d1);
float wVal = getW(wR, wC, d1, q);
dotProd += xVal * wVal;
}
}
float result = dotProd;
${y}
${g}
setOutput(result);
}
`}},a4=class{constructor(e,t=!1,n=null,s=!1,r=!1){this.variableNames=["x","W"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e.outShape;let a=e.outChannels/e.inChannels,o=e.inHeight,i=e.inWidth,l=e.padInfo.top,u=e.padInfo.left,c=e.strideHeight,d=e.strideWidth,h=e.dilationHeight,p=e.dilationWidth,m=e.filterHeight,f=e.filterWidth,A=f,g=`
int xR; int xC; int xCOffset;
vec4 wTexel; vec4 previous; vec4 final;`;for(let v=0;v<f;v++)g+=`
vec4 xTexelC${v*2};
int xTexelC${v*2}Ready;
vec4 xTexelC${v*2+1};
int xTexelC${v*2+1}Ready;
vec4 xC${v};`;for(let v=0;v<m;v++){for(let k=0;k<f;k++)g+=`
xTexelC${k*2} = vec4(0.0);
xTexelC${k*2}Ready = 0;
xTexelC${k*2+1} = vec4(0.0);
xTexelC${k*2+1}Ready = 0;
xC${k} = vec4(0.0);`;g+=`
xR = xRCorner + ${v*h};
if (xR >=0 && xR < ${o}) {
`;for(let k=0;k<(A+1)/2;k++){let w=k*2,C=w*p;if(g+=`
xC = xCCorner + ${C};
`,d===1){if(w<f&&(u%2==1?(g+=`
xCOffset = xC + 1;
if (xCOffset >= 0 && xCOffset < ${i} && xTexelC${w}Ready == 0) {
xTexelC${w} = getX(batch, xR, xCOffset, d1);
// Need to manually clear unused channels in case
// we're reading from recycled texture.
if (xCOffset + 1 >= ${i}) {
xTexelC${w}.zw = vec2(0.0);
}
xTexelC${w}Ready = 1;
}
`,p===1&&C>0?g+=`
xC${w} = vec4(xTexelC${w-2}.zw, xTexelC${w}.xy);
`:g+=`
xCOffset = xC + 1 - 2;
if (xCOffset >= 0 && xCOffset < ${i}) {
previous = getX(batch, xR, xCOffset, d1);
// Need to manually clear unused channels in case
// we're reading from recycled texture.
if (xCOffset + 1 >= ${i}) {
previous.zw = vec2(0.0);
}
xC${w} = vec4(previous.zw, xTexelC${w}.xy);
} else {
xC${w} = vec4(0.0, 0.0, xTexelC${w}.xy);
}
`):g+=`
if (xC >= 0 && xC < ${i} && xTexelC${w}Ready == 0) {
xTexelC${w} = getX(batch, xR, xC, d1);
if (xC + 1 >= ${i}) {
xTexelC${w}.zw = vec2(0.0);
}
xTexelC${w}Ready = 1;
}
xC${w} = xTexelC${w};
`,C+1<f)){let E=u%2==0?I.nearestLargerEven(p):p;p%2==0&&u%2==1||p%2!=0&&u%2!=1?(g+=`
xCOffset = xC + ${u%2} + ${E};
if (xCOffset >= 0 && xCOffset < ${i} && xTexelC${w+1}Ready == 0) {
xTexelC${w+1} = getX(batch, xR, xCOffset, d1);
// Need to manually clear unused channels in case
// we're reading from recycled texture.
if (xCOffset + 1 >= ${i}) {
xTexelC${w+1}.zw = vec2(0.0);
}
xTexelC${w+1}Ready = 1;
}
`,p>1&&(g+=`
xCOffset -= 2;
if (xCOffset >= 0 && xCOffset < ${i} && xTexelC${w}Ready == 0) {
xTexelC${w} = getX(batch, xR, xCOffset, d1);
xTexelC${w}Ready = 1;
}
`),g+=`
xC${w+1} = vec4(xTexelC${w}.zw, xTexelC${w+1}.xy);
`):E===1?g+=`
xC${w+1} = xTexelC${w};
`:g+=`
xCOffset = xC + ${E};
if (xCOffset >= 0 && xCOffset < ${i} && xTexelC${w+1}Ready == 0) {
xTexelC${w+1} = getX(batch, xR, xCOffset, d1);
if (xCOffset + 1 >= ${i}) {
xTexelC${w+1}.zw = vec2(0.0);
}
xTexelC${w+1}Ready = 1;
}
xC${w+1} = xTexelC${w+1};
`}}else C<f&&(u%2==1?(g+=`
xCOffset = xC + 1 - ${d};
if(xCOffset >= 0 && xCOffset < ${i} && xTexelC${w}Ready == 0) {
xTexelC${w} = getX(batch, xR, xCOffset, d1);
// Need to manually clear unused channels in case
// we're reading from recycled texture.
if (xCOffset + 1 >= ${i}) {
xTexelC${w}.zw = vec2(0.0);
}
xTexelC${w}Ready = 1;
}
if(xC + 1 >= 0 && xC + 1 < ${i} && xTexelC${w+1}Ready == 0) {
xTexelC${w+1} = getX(batch, xR, xC + 1, d1);
// Need to manually clear unused channels in case
// we're reading from recycled texture.
if (xC + 2 >= ${i}) {
xTexelC${w+1}.zw = vec2(0.0);
}
xTexelC${w+1}Ready = 1;
}
xC${w} = vec4(xTexelC${w}.zw, xTexelC${w+1}.zw);
`,C+1<f&&(g+=`
final = vec4(0.0);
xCOffset = xC + 1 + ${d};
if(xCOffset >= 0 && xCOffset < ${i}) {
final = getX(batch, xR, xCOffset, d1);
}
xC${w+1} = vec4(xTexelC${w+1}.xy, final.xy);
`)):(g+=`
if(xC >= 0 && xC < ${i} && xTexelC${w}Ready == 0) {
xTexelC${w} = getX(batch, xR, xC, d1);
if (xC + 1 >= ${i}) {
xTexelC${w}.zw = vec2(0.0);
}
xTexelC${w}Ready = 1;
}
xCOffset = xC + ${d};
if(xCOffset >= 0 && xCOffset < ${i} && xTexelC${w+1}Ready == 0) {
xTexelC${w+1} = getX(batch, xR, xCOffset, d1);
if (xCOffset + 1 >= ${i}) {
xTexelC${w+1}.zw = vec2(0.);
}
xTexelC${w+1}Ready = 1;
}
xC${w} = vec4(
xTexelC${w}.xy, xTexelC${w+1}.xy);
`,C+1<f&&(g+=`
xC${w+1} = vec4(xTexelC${w}.zw, xTexelC${w+1}.zw);
`)));w<f&&(g+=`
wTexel = getW(${v}, ${C}, d1, q);
dotProd += xC${w} * vec4(wTexel.xz, wTexel.xz);
`,C+1<f&&(g+=`
wTexel = getW(${v}, ${C+1}, d1, q);
dotProd += xC${w+1} * vec4(wTexel.xz, wTexel.xz);
`))}g+=`
}
`}let y="",x="";n&&(s?y=`vec4 activation(vec4 a) {
vec4 b = getPreluActivationWeightsAtOutCoords();
${n}
}`:r?y=`vec4 activation(vec4 a) {
vec4 b = getLeakyreluAlphaAtOutCoords();
${n}
}`:y=`vec4 activation(vec4 x) {
${n}
}`,x="result = activation(result);");let b=t?"result += getBiasAtOutCoords();":"";t&&this.variableNames.push("bias"),s&&this.variableNames.push("preluActivationWeights"),r&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
${y}
const ivec2 strides = ivec2(${c}, ${d});
const ivec2 pads = ivec2(${l}, ${u});
void main() {
ivec4 coords = getOutputCoords();
int batch = coords.x;
ivec2 xRCCorner = coords.yz * strides - pads;
int d2 = coords.w;
int d1 = d2 / ${a};
int q = d2 - d1 * ${a};
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);
${g}
vec4 result = dotProd - vec4(0.000000000000001);
${b}
${x}
setOutput(result);
}
`}};function xY(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,filter:a}=t,{strides:o,pad:i,dilations:l,dimRoundingMode:u}=s,c=l;c==null&&(c=[1,1]),I.assert($.eitherStridesOrDilationsAreOne(o,c),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${o} and dilations '${c}'`);let d=$.computeConv2DInfo(r.shape,a.shape,o,c,i,u,!0),h;return ee().getBool("WEBGL_PACK_DEPTHWISECONV")&&d.strideWidth<=2&&d.outChannels/d.inChannels==1?h=new a4(d):h=new r4(d),n.runWebGLProgram(h,[r,a],"float32")}var bY={kernelName:Na,backendName:"webgl",kernelFunc:xY},vY=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideHeight,n=e.strideWidth,s=e.padInfo.top,r=e.padInfo.left,a=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 * ${a} + 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} - ${s};
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 >= ${e.inWidth}) {
continue;
}
float dyValue = getDy(b, yR, yC, d2);
float xValue = getX(b, xR, xC, d1);
dotProd += (xValue * dyValue);
}
}
}
setOutput(dotProd);
}
`}},wY=class{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterHeight,n=e.filterWidth,s=e.strideHeight,r=e.strideWidth,a=t-1-e.padInfo.top,o=n-1-e.padInfo.left,i=e.outChannels/e.inChannels;this.userCode=`
const ivec2 pads = ivec2(${a}, ${o});
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) / ${s}.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 < ${i}; dm++) {
int d2 = d1 * ${i} + dm;
float xValue = getDy(batch, idyR, idyC, d2);
float wValue = getW(wRPerm, wCPerm, d1, dm);
dotProd += xValue * wValue;
}
}
}
setOutput(dotProd);
}
`}};function kY(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,dy:a}=t,{strides:o,dilations:i,pad:l,dimRoundingMode:u,filterShape:c}=s,d=$.computeConv2DInfo(r.shape,c,o,i,l,u,!0),h=new vY(d);return n.runWebGLProgram(h,[r,a],"float32")}var IY={kernelName:jd,backendName:"webgl",kernelFunc:kY};function SY(e){let{inputs:t,backend:n,attrs:s}=e,{dy:r,filter:a}=t,{strides:o,dilations:i,pad:l,dimRoundingMode:u,inputShape:c}=s,d=$.computeConv2DInfo(c,a.shape,o,i,l,u,!0),h=new wY(d);return n.runWebGLProgram(h,[r,a],"float32")}var CY={kernelName:qd,backendName:"webgl",kernelFunc:SY},TY=class{constructor(e){this.variableNames=["X"],this.outputShape=[e,e],this.userCode=`
void main() {
ivec2 coords = getOutputCoords();
float val = coords[0] == coords[1] ? getX(coords[0]) : 0.0;
setOutput(val);
}
`}};function NY(e){let{inputs:t,backend:n}=e,{x:s}=t,r=[...s.shape,...s.shape],a=I.sizeFromShape(s.shape),o=ye({inputs:{x:s},backend:n,attrs:{shape:[a]}}),i=new TY(a),l=n.runWebGLProgram(i,[o],o.dtype),u=ye({inputs:{x:l},backend:n,attrs:{shape:r}});return n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(l),u}var EY={kernelName:Xd,backendName:"webgl",kernelFunc:NY},RY=class{constructor(e){this.variableNames=["x","W"],this.outputShape=e.outShape;let{inHeight:t,inWidth:n,padInfo:s,strideHeight:r,strideWidth:a,filterHeight:o,filterWidth:i,dilationHeight:l,dilationWidth:u}=e,{top:c,left:d}=s;this.userCode=`
const ivec2 strides = ivec2(${r}, ${a});
const ivec2 pads = ivec2(${c}, ${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 < ${o}; h++) {
int hIn = hBeg + h * ${l};
if (hIn >= 0 && hIn < ${t}) {
for (int w = 0; w < ${i}; w++) {
int wIn = wBeg + w * ${u};
if (wIn >= 0 && wIn < ${n}) {
float xVal = getX(batch, hIn, wIn, d1);
float wVal = getW(h, w, d1);
float val = xVal + wVal;
if (val > curVal) {
curVal = val;
}
}
}
}
}
float result = curVal;
setOutput(result);
}
`}};function _Y(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,filter:a}=t,{strides:o,pad:i,dilations:l}=s,u=$.computeDilation2DInfo(r.shape,a.shape,o,i,"NHWC",l),c,d=new RY(u);c=n.runWebGLProgram(d,[r,a],"float32");let h=ye({inputs:{x:c},backend:n,attrs:{shape:u.outShape}});return n.disposeIntermediateTensorInfo(c),h}var $Y={kernelName:$u,backendName:"webgl",kernelFunc:_Y};function FY(e){let{inputs:t,backend:n,attrs:s}=e,{equation:r}=s,a=t,{allDims:o,summedDims:i,idDims:l}=$.decodeEinsumEquation(r,a.length);$.checkEinsumDimSizes(o.length,l,a);let{path:u,steps:c}=$.getEinsumComputePath(i,l),d=c.length,h=null,p=o.length,m=[];for(let f=0;f<d;++f){for(let A of c[f]){let{permutationIndices:g,expandDims:y}=$.getEinsumPermutation(p,l[A]),x;$.isIdentityPermutation(g)?x=a[A]:(x=wn({inputs:{x:a[A]},backend:n,attrs:{perm:g}}),m.push(x));let b=x.shape.slice();for(let v=0;v<y.length;++v)b.splice(y[v],0,1);I.arraysEqual(x.shape,b)||(x=ye({inputs:{x},backend:n,attrs:{shape:b}}),m.push(x)),h===null?h=x:(h=T1({inputs:{a:x,b:h},backend:n}),m.push(h))}f<d-1&&(u[f]>=0&&(h=Af({inputs:{x:h},backend:n,attrs:{axis:u[f]-(o.length-p),keepDims:!1}}),m.push(h)),p--)}for(let f of m)f!==h&&n.disposeIntermediateTensorInfo(f);return h}var DY={kernelName:Yd,backendName:"webgl",kernelFunc:FY},OY="return (x >= 0.0) ? x : (exp(x) - 1.0);",PY=`
vec4 result;
result.r = (x.r >= 0.0) ? x.r : (exp(x.r) - 1.0);
result.g = (x.g >= 0.0) ? x.g : (exp(x.g) - 1.0);
result.b = (x.b >= 0.0) ? x.b : (exp(x.b) - 1.0);
result.a = (x.a >= 0.0) ? x.a : (exp(x.a) - 1.0);
return result;
`,MY=Ze({opSnippet:OY,packedOpSnippet:PY}),zY={kernelName:Si,backendName:"webgl",kernelFunc:MY},LY="return (b >= 1.0) ? a : a * (b + 1.0);",BY=`
vec4 bGTEZero = vec4(greaterThanEqual(b, vec4(0.)));
return (bGTEZero * a) + ((vec4(1.0) - bGTEZero) * (a * (b + vec4(1.0))));
`,WY=e=>{let{inputs:t,backend:n}=e,{dy:s,y:r}=t,a=ee().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new Gc(BY,s.shape,r.shape):new Ql(LY,s.shape,r.shape);return n.runWebGLProgram(a,[s,r],s.dtype)},VY={kernelName:Jd,backendName:"webgl",kernelFunc:WY},UY=`
return vec4(equal(a, b));
`,HY="return float(a == b);",GY=rn({opSnippet:HY,packedOpSnippet:UY,dtype:"bool",cpuKernelImpl:$q}),jY={kernelName:Ti,backendName:"webgl",kernelFunc:GY},qY=`
// Error function is calculated approximately with elementary function.
// See "Handbook of Mathematical Functions with Formulas,
// Graphs, and Mathematical Tables", Abramowitz and Stegun.
float p = ${$.ERF_P};
float a1 = ${$.ERF_A1};
float a2 = ${$.ERF_A2};
float a3 = ${$.ERF_A3};
float a4 = ${$.ERF_A4};
float a5 = ${$.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));
`,XY=Ze({opSnippet:qY}),KY={kernelName:Ci,backendName:"webgl",kernelFunc:XY},o4="return exp(x);",i4=Ze({opSnippet:o4,packedOpSnippet:o4,cpuKernelImpl:Fq}),ZY={kernelName:Ra,backendName:"webgl",kernelFunc:i4};function _1(e){let{inputs:t,attrs:n,backend:s}=e,{dim:r}=n,{input:a}=t,o=a.shape.length,i=a.shape.slice(),l=r;return r<0&&(I.assert(-(o+1)<=r,()=>`Axis must be in the interval [${-(o+1)}, ${o}]`),l=o+r+1),i.splice(l,0,1),ye({inputs:{x:a},backend:s,attrs:{shape:i}})}var YY={kernelName:Ni,backendName:"webgl",kernelFunc:_1},l4="return exp(x) - 1.0;",JY=Ze({opSnippet:l4,packedOpSnippet:l4,cpuKernelImpl:Dq}),QY={kernelName:Ei,backendName:"webgl",kernelFunc:JY},u4=class{constructor(e,t,n){this.variableNames=["real","imag"];let s=t[1];this.outputShape=t;let r=n?`2.0 * ${Math.PI}`:`-2.0 * ${Math.PI}`,a=n?`${s}.0`:"1.0",o;if(e==="real")o="return real * expR - imag * expI;";else if(e==="imag")o="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) {
${o}
}
float mulMatDFT(int batch, int index) {
float indexRatio = float(index) / float(${s});
float exponentMultiplierTimesIndexRatio =
exponentMultiplier * indexRatio;
float result = 0.0;
for (int i = 0; i < ${s}; 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) / ${a};
}
return result;
}
void main() {
ivec2 coords = getOutputCoords();
setOutput(mulMatDFT(coords[0], coords[1]));
}
`}};function c4(e,t,n){let s=n.texData.get(e.dataId),r=I.sizeFromShape(e.shape),a=e.shape[e.shape.length-1],o=r/a,i=ye({inputs:{x:e},backend:n,attrs:{shape:[o,a]}}),l=i.shape,u=new u4("real",l,t),c=new u4("imag",l,t),d=[{dataId:s.complexTensorInfos.real.dataId,dtype:s.complexTensorInfos.real.dtype,shape:l},{dataId:s.complexTensorInfos.imag.dataId,dtype:s.complexTensorInfos.imag.dtype,shape:l}],h=n.runWebGLProgram(u,d,"float32"),p=n.runWebGLProgram(c,d,"float32"),m=ra({inputs:{real:h,imag:p},backend:n});n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(p);let f=ye({inputs:{x:m},backend:n,attrs:{shape:e.shape}});return n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(m),f}function eJ(e){let{inputs:t,backend:n}=e,{input:s}=t;return c4(s,!1,n)}var tJ={kernelName:Qd,backendName:"webgl",kernelFunc:eJ},nJ=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 vf(e){let{backend:t,attrs:n}=e,{shape:s,value:r}=n,{dtype:a}=n;if(a=a||I.inferDtype(r),a==="string"){let o=I.getArrayFromDType(a,I.sizeFromShape(s));return o.fill(r),t.makeTensorInfo(s,a,o)}else{let o=new nJ(s,r),i=[[r]];return t.runWebGLProgram(o,[],a,i)}}var sJ={kernelName:Fu,backendName:"webgl",kernelFunc:vf},rJ=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 < ${t}) {
outputValue = getImage(coords[0], coords[1], coordX, coords[3]);
} else {
outputValue = getImage(coords[0], coords[1], coords[2], coords[3]);
}
setOutput(outputValue);
}
`}},aJ={kernelName:Ri,backendName:"webgl",kernelFunc:({inputs:e,backend:t})=>{let{image:n}=e,s=t,r=new rJ(n.shape);return s.runWebGLProgram(r,[n],n.dtype)}},d4="return floor(x);",oJ=Ze({opSnippet:d4,packedOpSnippet:d4,cpuKernelImpl:Oq}),iJ={kernelName:_a,backendName:"webgl",kernelFunc:oJ},lJ=`
float s = sign(a) * sign(b);
int ia = round(a);
int ib = round(b);
if (ib != 0) {
// Windows (D3D) wants guaranteed non-zero int division at compile-time.
return float(idiv(ia, ib, s));
} else {
return NAN;
}
`,uJ=`
ivec4 ia = round(a);
ivec4 ib = round(b);
bvec4 cond = notEqual(ib, ivec4(0));
ivec4 result = ivec4(0);
vec4 s = sign(a) * sign(b);
// Windows (D3D) wants guaranteed non-zero int division at compile-time.
if (cond[0]) {
result[0] = idiv(ia[0], ib[0], s[0]);
}
if (cond[1]) {
result[1] = idiv(ia[1], ib[1], s[1]);
}
if (cond[2]) {
result[2] = idiv(ia[2], ib[2], s[2]);
}
if (cond[3]) {
result[3] = idiv(ia[3], ib[3], s[3]);
}
return vec4(result);
`,cJ=rn({opSnippet:lJ,packedOpSnippet:uJ,dtype:"int32"}),dJ={kernelName:$a,backendName:"webgl",kernelFunc:cJ},hJ=class{constructor(e){this.variableNames=["A"];let t=bn(),[n,s]=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(${s}.0, ${n}.0);
vec4 values = ${t.texture2D}(A, uv);
float value;
if (depth == 0) {
value = values.r;
} else if (depth == 1) {
value = values.g;
} else if (depth == 2) {
value = values.b;
} else if (depth == 3) {
value = values.a;
}
setOutput(floor(value * 255.0 + 0.5));
}
`}},pJ=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0;let t=bn(),[n,s]=e;this.outputShape=e,this.userCode=`
void main() {
ivec3 coords = getOutputCoords();
int texR = coords[0];
int texC = coords[1];
int depth = coords[2];
vec4 result = vec4(0.);
for(int row=0; row<=1; row++) {
for(int col=0; col<=1; col++) {
texC = coords[1] + row;
depth = coords[2] + col;
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${s}.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);
}
}
${t.output} = result;
}
`}},fJ={kernelName:bh,backendName:"webgl",kernelFunc:mJ},nu;function mJ(e){let{inputs:t,backend:n,attrs:s}=e,{pixels:r}=t,{numChannels:a}=s,o=typeof HTMLVideoElement!="undefined"&&r instanceof HTMLVideoElement,i=typeof HTMLImageElement!="undefined"&&r instanceof HTMLImageElement,[l,u]=o?[r.videoWidth,r.videoHeight]:[r.width,r.height],c=[u,l],d=[u,l,a];(i||o)&&(nu==null&&(nu=document.createElement("canvas").getContext("2d")),nu.canvas.width=l,nu.canvas.height=u,nu.drawImage(r,0,0,l,u),r=nu.canvas);let h=n.makeTensorInfo(c,"int32");n.texData.get(h.dataId).usage=fs.PIXELS,n.gpgpu.uploadPixelDataToTexture(n.getTexture(h.dataId),r);let p=ee().getBool("WEBGL_PACK")?new pJ(d):new hJ(d),m=n.runWebGLProgram(p,[h],"int32");return n.disposeData(h.dataId),m}function AJ(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,filter:a,bias:o,preluActivationWeights:i}=t,{strides:l,pad:u,dataFormat:c,dilations:d,dimRoundingMode:h,activation:p,leakyreluAlpha:m}=s,f=$.convertConv2DDataFormat(c),A=$.computeConv2DInfo(r.shape,a.shape,l,d,u,h,!1,f),g,y=[];if(A.filterHeight===1&&A.filterWidth===1&&A.dilationHeight===1&&A.dilationWidth===1&&A.strideHeight===1&&A.strideWidth===1&&(A.padInfo.type==="SAME"||A.padInfo.type==="VALID"))g=Q6({x:r,filter:a,convInfo:A,backend:n,bias:o,activation:p,preluActivationWeights:i,leakyreluAlpha:m});else if(ee().getBool("WEBGL_CONV_IM2COL")&&r.shape[0]===1)g=e4({x:r,filter:a,convInfo:A,backend:n,bias:o,activation:p,preluActivationWeights:i,leakyreluAlpha:m});else{let b=o!=null,v=i!=null,k=p==="leakyrelu",w=p?ff(p,!1):null,C=new J6(A,b,w,v,k),E=[r,a];if(o&&E.push(o),i&&E.push(i),k){let P=n.makeTensorInfo([],"float32",I.createScalarValue(m,"float32"));E.push(P),y.push(P)}g=n.runWebGLProgram(C,E,"float32")}let x=ye({inputs:{x:g},backend:n,attrs:{shape:A.outShape}});return y.push(g),y.forEach(b=>n.disposeIntermediateTensorInfo(b)),x}var gJ={kernelName:fo,backendName:"webgl",kernelFunc:AJ};function yJ(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,filter:a,bias:o,preluActivationWeights:i}=t,{strides:l,pad:u,dilations:c,dimRoundingMode:d,activation:h,leakyreluAlpha:p}=s,m=[],f=c;f==null&&(f=[1,1]),I.assert($.eitherStridesOrDilationsAreOne(l,f),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${l} and dilations '${f}'`);let A=$.computeConv2DInfo(r.shape,a.shape,l,f,u,d,!0),g=ee().getBool("WEBGL_PACK_DEPTHWISECONV")&&A.strideWidth<=2&&A.outChannels/A.inChannels==1,y=h?ff(h,g):null,x=[r,a],b=o!=null,v=i!=null,k=h==="leakyrelu";if(b&&x.push(o),v&&x.push(i),k){let E=n.makeTensorInfo([],"float32",I.createScalarValue(p,"float32"));x.push(E),m.push(E)}let w;g?w=new a4(A,b,y,v,k):w=new r4(A,b,y,v,k);let C=n.runWebGLProgram(w,x,"float32");return m.forEach(E=>n.disposeIntermediateTensorInfo(E)),C}var xJ={kernelName:mo,backendName:"webgl",kernelFunc:yJ},bJ=class{constructor(e,t,n){this.sliceDim=e,this.strides=t,this.variableNames=["x","indices"],this.outputShape=n;let s=ut(t.length),r=ut(n.length),a=this.sliceDim>1?"strides[j]":"strides";this.userCode=`
${s} strides = ${s}(${this.strides});
void main() {
${r} coords = getOutputCoords();
int flattenIndex = 0;
for (int j = 0; j < ${this.sliceDim}; j++) {
int index = round(getIndices(coords[0], j));
flattenIndex += index * ${a};
}
setOutput(getX(flattenIndex, coords[1]));
}
`}};function vJ(e){let{inputs:t,backend:n}=e,{params:s,indices:r}=t,a=r.shape,o=a[a.length-1],i=I.sizeFromShape(s.shape),[l,u,c,d]=$.prepareAndValidate(s,r),h=ye({inputs:{x:r},backend:n,attrs:{shape:[u,o]}}),p=ye({inputs:{x:s},backend:n,attrs:{shape:[I.sizeFromShape(s.shape)/c,c]}});if(n.shouldExecuteOnCPU([s,r])||s.dtype==="string"){let g=n.readSync(r.dataId),y=n.bufferSync(s),x=Pq(g,y,s.dtype,u,o,c,d,s.shape,i);return n.makeTensorInfo(l,s.dtype,x.values)}let m=new bJ(o,d,[u,c]),f=n.runWebGLProgram(m,[p,h],p.dtype),A=ye({inputs:{x:f},backend:n,attrs:{shape:l}});return n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(f),A}var wJ={kernelName:$i,backendName:"webgl",kernelFunc:vJ},kJ=class{constructor(e,t){this.variableNames=["A","indices"],this.outputShape=t,this.rank=t.length;let n=ut(this.rank),s=IJ(e,2);this.userCode=`
void main() {
${n} resRC = getOutputCoords();
setOutput(getA(${s}));
}
`}};function IJ(e,t){let n=["resRC.x","resRC.y","resRC.z","resRC.w"],s=[];for(let r=0;r<e.length;r++)r===2?s.push("int(getIndices(resRC.x, resRC.z))"):s.push(`${n[r]}`);return s.join()}function h4(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,indices:a}=t,{axis:o,batchDims:i}=s,l=I.parseAxisParam(o,r.shape)[0],u=$.segment_util.collectGatherOpShapeInfo(r,a,l,i),c=I.sizeFromShape(a.shape),d=[],h=ye({inputs:{x:r},backend:n,attrs:{shape:[u.batchSize,u.outerSize,u.dimSize,u.sliceSize]}}),p=ye({inputs:{x:a},backend:n,attrs:{shape:[u.batchSize,c/u.batchSize]}});d.push(h),d.push(p);let m=[u.batchSize,u.outerSize,c/u.batchSize,u.sliceSize];if(n.shouldExecuteOnCPU([r,a])||r.dtype==="string"){let y=n.bufferSync(p),x=n.bufferSync(h),b=Mq(x,y,m);return d.forEach(v=>n.disposeIntermediateTensorInfo(v)),n.makeTensorInfo(u.outputShape,b.dtype,b.values)}let f=new kJ(h.shape,m),A=n.runWebGLProgram(f,[h,p],h.dtype);d.push(A);let g=ye({inputs:{x:A},backend:n,attrs:{shape:u.outputShape}});return d.forEach(y=>n.disposeIntermediateTensorInfo(y)),g}var SJ={kernelName:_i,backendName:"webgl",kernelFunc:h4},CJ="return float(a > b);",TJ=`
return vec4(greaterThan(a, b));
`,NJ=rn({opSnippet:CJ,packedOpSnippet:TJ,cpuKernelImpl:zq,dtype:"bool"}),EJ={kernelName:Fi,backendName:"webgl",kernelFunc:NJ},RJ="return float(a >= b);",_J=`
return vec4(greaterThanEqual(a, b));
`,$J=rn({opSnippet:RJ,packedOpSnippet:_J,dtype:"bool",cpuKernelImpl:Lq}),FJ={kernelName:Da,backendName:"webgl",kernelFunc:$J};function DJ(e){let{inputs:t,backend:n}=e,{input:s}=t;return c4(s,!0,n)}var OJ={kernelName:eh,backendName:"webgl",kernelFunc:DJ},PJ="return float(!isnan(x) && !isinf(x));",MJ=Ze({opSnippet:PJ,dtype:"bool"}),zJ={kernelName:Di,backendName:"webgl",kernelFunc:MJ},LJ="return float(isinf(x));",BJ=Ze({opSnippet:LJ,dtype:"bool"}),WJ={kernelName:Oi,backendName:"webgl",kernelFunc:BJ},VJ="return float(isnan(x));",UJ=Ze({opSnippet:VJ,dtype:"bool"}),HJ={kernelName:Pi,backendName:"webgl",kernelFunc:UJ},GJ="return float(a < b);",jJ=`
return vec4(lessThan(a, b));
`,qJ=rn({opSnippet:GJ,packedOpSnippet:jJ,cpuKernelImpl:Bq,dtype:"bool"}),XJ={kernelName:Mi,backendName:"webgl",kernelFunc:qJ},KJ="return float(a <= b);",ZJ=`
return vec4(lessThanEqual(a, b));
`,YJ=rn({opSnippet:KJ,packedOpSnippet:ZJ,cpuKernelImpl:Wq,dtype:"bool"}),JJ={kernelName:zi,backendName:"webgl",kernelFunc:YJ};function QJ(e){let{backend:t,attrs:n}=e,{start:s,stop:r,num:a}=n,o=Vq(s,r,a);return t.makeTensorInfo([o.length],"float32",o)}var eQ={kernelName:nh,backendName:"webgl",kernelFunc:QJ},tQ=`if (x < 0.0) return NAN;
return log(x);`,nQ=`
vec4 result = log(x);
vec4 isNaN = vec4(lessThan(x, vec4(0.0)));
result.r = isNaN.r == 1.0 ? NAN : result.r;
result.g = isNaN.g == 1.0 ? NAN : result.g;
result.b = isNaN.b == 1.0 ? NAN : result.b;
result.a = isNaN.a == 1.0 ? NAN : result.a;
return result;
`,sQ=Ze({opSnippet:tQ,packedOpSnippet:nQ,cpuKernelImpl:Uq}),rQ={kernelName:Ma,backendName:"webgl",kernelFunc:sQ},aQ="return log(1.0 + x);",oQ=Ze({opSnippet:aQ}),iQ={kernelName:Li,backendName:"webgl",kernelFunc:oQ},lQ="return float(a >= 1.0 && b >= 1.0);",uQ=`
return vec4(
vec4(greaterThanEqual(a, vec4(1.0))) *
vec4(greaterThanEqual(b, vec4(1.0))));
`,cQ=rn({opSnippet:lQ,packedOpSnippet:uQ,dtype:"bool"}),dQ={kernelName:Bi,backendName:"webgl",kernelFunc:cQ},hQ="return float(!(x >= 1.0));",pQ=Ze({opSnippet:hQ}),fQ={kernelName:Du,backendName:"webgl",kernelFunc:pQ},mQ="return float(a >= 1.0 || b >= 1.0);",AQ=`
return min(
vec4(greaterThanEqual(a, vec4(1.0))) +
vec4(greaterThanEqual(b, vec4(1.0))),
vec4(1.0));
`,gQ=rn({opSnippet:mQ,packedOpSnippet:AQ,dtype:"bool"}),yQ={kernelName:Ou,backendName:"webgl",kernelFunc:gQ},xQ=class{constructor(e,t,n,s,r){this.variableNames=["x"],this.outputShape=[];let a=t,o=e[3]-1;this.outputShape=e;let i,l=`float(${n}) + float(${s}) * sum`;r===.5?i=`inversesqrt(${l})`:r===1?i=`1.0/(${l})`:i=`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 = -${a}; j <= ${a}; j++) {
int idx = d + j;
if (idx >= 0 && idx <= ${o}) {
float z = getX(b, r, c, idx);
sum += z * z;
}
}
float val = x * ${i};
setOutput(val);
}
`}},bQ=class{constructor(e,t,n,s,r){this.variableNames=["x"],this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0;let a=t,o=e[3]-1;this.outputShape=e;let i,l=`float(${n}) + float(${s}) * sum`;r===.5?i=`inversesqrt(${l})`:r===1?i=`1.0/(${l})`:i=`exp(log(${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 - ${a};
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 = - ${a}; j <= ${a}; j++) {
ivec2 idx = depth + j;
bvec2 aboveLowerBound = greaterThanEqual(idx, ivec2(0));
bvec2 belowUpperBound = lessThanEqual(idx, ivec2(${o}));
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 * ${i};
setOutput(result);
}
`}},vQ=e=>{let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{depthRadius:a,bias:o,alpha:i,beta:l}=s,u=ee().getBool("WEBGL_PACK_NORMALIZATION")?new bQ(r.shape,a,o,i,l):new xQ(r.shape,a,o,i,l);return n.runWebGLProgram(u,[r],r.dtype)},wQ={kernelName:Pu,backendName:"webgl",kernelFunc:vQ},kQ=class{constructor(e,t,n,s,r){this.variableNames=["inputImage","outputImage","dy"],this.outputShape=[],this.outputShape=e,this.depth=e[3],this.depthRadius=t,this.bias=n,this.alpha=s,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 = ${this.depth};
float norm = 0.0;
for (int k = MIN_DEPTH_BEGIN; k < MAX_DEPTH_END; ++k) {
if (k < depthBegin){
continue;
}
else if (k >= depthBegin && k < depthEnd) {
norm += getInputImage(b, r, c, k) * getInputImage(b, r, c, k);
}
else {
break;
}
}
norm = float(${s}) * norm + float(${n});
for(int k = MIN_DEPTH_BEGIN; k < MAX_DEPTH_END; ++k){
if (k < depthBegin){
continue;
}
else if (k >= depthBegin && k < depthEnd){
float dyi = -2.0 * float(${s})
* float(${r})
* getInputImage(b ,r ,c, k) * getOutputImage(b, r, c, d)
/ norm;
if (k == d) {
dyi += pow(norm, -1.0 * ${r});
}
if (k == coords[3]) {
dyi *= getDy(b, r, c, d);
result += dyi;
}
}
else {
break;
}
}
}
setOutput(result);
}
`}},IQ=e=>{let{inputs:t,backend:n,attrs:s}=e,{x:r,y:a,dy:o}=t,{depthRadius:i,bias:l,alpha:u,beta:c}=s,d=new kQ(r.shape,i,l,u,c);return n.runWebGLProgram(d,[r,a,o],r.dtype)},SQ={kernelName:sh,backendName:"webgl",kernelFunc:IQ};function CQ(e,t,n,s){let r=I.sizeFromShape(t),o=I.sizeFromShape(e.shape)/r,i=ye({inputs:{x:e},attrs:{shape:[o,r]},backend:s}),l=Go(i,e.dtype,"max",s),u=ye({inputs:{x:l},attrs:{shape:n},backend:s});return s.disposeIntermediateTensorInfo(i),s.disposeIntermediateTensorInfo(l),u}function p4(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{reductionIndices:a,keepDims:o}=s,i=r.shape.length,l=I.parseAxisParam(a,r.shape),u=l,c=$.getAxesPermutation(u,i),d=c!=null,h=n.shouldExecuteOnCPU([r]),p=r;if(d){if(h){let x=n.texData.get(p.dataId).values,b=new Array(i);for(let w=0;w<b.length;w++)b[w]=r.shape[c[w]];let v=C1(x,r.shape,r.dtype,c,b);p=n.makeTensorInfo(b,r.dtype);let k=n.texData.get(p.dataId);k.values=v}else p=mf(r,c,n);u=$.getInnerMostAxes(u.length,i)}$.assertAxesAreInnerMostDims("max",u,i);let[m,f]=$.computeOutAndReduceShapes(p.shape,u),A=m;o&&(A=$.expandShapeToKeepDim(m,l));let g;if(h){let x=n.texData.get(p.dataId).values,b=Hq(x,I.sizeFromShape(f),A,r.dtype);g=n.makeTensorInfo(A,r.dtype);let v=n.texData.get(g.dataId);v.values=b}else g=CQ(p,f,A,n);return d&&n.disposeIntermediateTensorInfo(p),g}var TQ={kernelName:za,backendName:"webgl",kernelFunc:p4},NQ=_6+`
return max(a, b);
`,EQ=`
vec4 result = vec4(max(a, b));
vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
`+pf+`
return result;
`,RQ=rn({opSnippet:NQ,packedOpSnippet:EQ,cpuKernelImpl:Gq}),_Q={kernelName:La,backendName:"webgl",kernelFunc:RQ};function $Q(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t;jl(r,"maxPool");let{filterSize:a,strides:o,pad:i,dimRoundingMode:l}=s,u=1;I.assert($.eitherStridesOrDilationsAreOne(o,u),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${o} and dilations '${u}'`);let c=$.computePool2DInfo(r.shape,a,o,u,i,l);if(c.filterWidth===1&&c.filterHeight===1&&I.arraysEqual(c.inShape,c.outShape))return qn({inputs:{x:r},backend:n});let d=new jc(c,"max",!1);return n.runWebGLProgram(d,[r],r.dtype)}var FQ={kernelName:Ba,backendName:"webgl",kernelFunc:$Q};function DQ(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{filterSize:a,strides:o,pad:i,dataFormat:l,dimRoundingMode:u}=s,c=[1,1,1],d=$.computePool3DInfo(r.shape,a,o,c,i,u,l),h=new N1(d,"max",!1);return n.runWebGLProgram(h,[r],r.dtype)}var OQ={kernelName:Mu,backendName:"webgl",kernelFunc:DQ},PQ=class{constructor(e){this.variableNames=["dy","maxPos"],this.outputShape=e.inShape;let t=e.strideHeight,n=e.strideWidth,s=e.dilationHeight,r=e.effectiveFilterHeight,a=e.effectiveFilterWidth,o=r-1-e.padInfo.top,i=a-1-e.padInfo.left,l=r*a-1;this.userCode=`
const ivec2 pads = ivec2(${o}, ${i});
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 += ${s}) {
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 < ${a}; 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 * ${a} + wC;
float mask = float(maxPosValue == curPosValue ? 1.0 : 0.0);
dotProd += dyValue * mask;
}
}
setOutput(dotProd);
}
`}},MQ=class{constructor(e){this.variableNames=["dy","maxPos"],this.outputShape=e.inShape;let t=e.strideDepth,n=e.strideHeight,s=e.strideWidth,r=e.dilationDepth,a=e.dilationHeight,o=e.dilationWidth,i=e.effectiveFilterDepth,l=e.effectiveFilterHeight,u=e.effectiveFilterWidth,c=i-1-e.padInfo.front,d=l-1-e.padInfo.top,h=u-1-e.padInfo.left,p=i*l*u-1;this.userCode=`
const ivec3 pads = ivec3(${c}, ${d}, ${h});
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 < ${i};
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 += ${a}) {
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 += ${o}) {
float dyC = float(dyCCorner + wC) / ${s}.0;
if (dyC < 0.0 || dyC >= ${e.outWidth}.0 ||
fract(dyC) > 0.0) {
continue;
}
int idyC = int(dyC);
float dyValue = getDy(batch, idyD, idyR, idyC, ch);
int maxPosValue = ${p} -
int(getMaxPos(batch, idyD, idyR, idyC, ch));
// Get the current value, check it against the value from the
// position matrix.
int curPosValue =
wD * ${l} * ${u} +
wR * ${u} + wC;
float mask = float(maxPosValue == curPosValue ? 1.0 : 0.0);
dotProd += dyValue * mask;
}
}
}
setOutput(dotProd);
}
`}};function zQ(e){let{inputs:t,backend:n,attrs:s}=e,{dy:r,input:a}=t,o=a,{filterSize:i,strides:l,pad:u,dimRoundingMode:c}=s,d=[1,1,1],h=$.computePool3DInfo(o.shape,i,l,d,u,c),p=new N1(h,"max",!0),m=n.runWebGLProgram(p,[o],o.dtype),f=new MQ(h),A=n.runWebGLProgram(f,[r,m],o.dtype);return n.disposeIntermediateTensorInfo(m),A}var LQ={kernelName:ah,backendName:"webgl",kernelFunc:zQ};function BQ(e){let{inputs:t,backend:n,attrs:s}=e,{dy:r,input:a,output:o}=t,i=a;jl([a,o],"maxPoolGrad");let{filterSize:l,strides:u,pad:c,dimRoundingMode:d}=s,h=$.computePool2DInfo(i.shape,l,u,1,c,d),p=!0,m=new jc(h,"max",p),f=n.runWebGLProgram(m,[i],i.dtype),A=new PQ(h),g=n.runWebGLProgram(A,[r,f],i.dtype);return n.disposeIntermediateTensorInfo(f),g}var WQ={kernelName:rh,backendName:"webgl",kernelFunc:BQ};function VQ(e,t,n,s){let r=new jc(n,"max",!1),a=s.runWebGLProgram(r,[e],"float32");r=new jc(n,"max",!0,!0,t);let o=s.runWebGLProgram(r,[e],"float32");return[a,o]}var UQ={kernelName:oh,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{x:s}=e,{filterSize:r,strides:a,pad:o,includeBatchInIndex:i}=t,l=n;I.assert(s.shape.length===4,()=>`Error in maxPool: input must be rank 4 but got rank ${s.shape.length}.`);let u=[1,1];I.assert($.eitherStridesOrDilationsAreOne(a,u),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${a} and dilations '${u}'`);let c=$.computePool2DInfo(s.shape,r,a,u,o),[d,h]=VQ(s,i,c,l);return[d,h]}};function HQ(e,t,n,s){let r=I.sizeFromShape(t),o=I.sizeFromShape(e.shape)/r,i=ye({inputs:{x:e},attrs:{shape:[o,r]},backend:s}),l=Go(i,"float32","mean",s),u=ye({inputs:{x:l},attrs:{shape:n},backend:s});return s.disposeIntermediateTensorInfo(i),s.disposeIntermediateTensorInfo(l),u}var GQ={kernelName:Wa,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{x:s}=e,{keepDims:r,axis:a}=t,o=n,i=s.shape.length,l=I.parseAxisParam(a,s.shape),u=l,c=$.getAxesPermutation(u,i),d=c!=null,h=o.shouldExecuteOnCPU([s]),p=[],m=s;if(d){if(h){let b=o.texData.get(m.dataId).values,v=new Array(i);for(let C=0;C<v.length;C++)v[C]=s.shape[c[C]];let k=C1(b,s.shape,s.dtype,c,v);m=o.makeTensorInfo(v,s.dtype);let w=o.texData.get(m.dataId);w.values=k}else m=mf(s,c,o);p.push(m),u=$.getInnerMostAxes(u.length,i)}$.assertAxesAreInnerMostDims("sum",u,i);let[f,A]=$.computeOutAndReduceShapes(m.shape,u),g=f;r&&(g=$.expandShapeToKeepDim(f,l));let y=HQ(m,A,g,o);for(let x of p)o.disposeIntermediateTensorInfo(x);return y}};function jQ(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,keepDims:o}=s,i=r.shape.length,l=I.parseAxisParam(a,r.shape),u=l,c=$.getAxesPermutation(u,i),d=r;c!=null&&(d=wn({inputs:{x:r},backend:n,attrs:{perm:c}}),u=$.getInnerMostAxes(u.length,r.shape.length)),$.assertAxesAreInnerMostDims("min",u,i);let[h,p]=$.computeOutAndReduceShapes(d.shape,u),m=I.sizeFromShape(p),f=ye({inputs:{x:d},backend:n,attrs:{shape:[-1,m]}}),A=Go(f,f.dtype,"min",n),g;if(o){let y=$.expandShapeToKeepDim(h,l);g=ye({inputs:{x:A},backend:n,attrs:{shape:y}})}else g=ye({inputs:{x:A},backend:n,attrs:{shape:h}});return n.disposeIntermediateTensorInfo(f),n.disposeIntermediateTensorInfo(A),c!=null&&n.disposeIntermediateTensorInfo(d),g}var qQ={kernelName:Va,backendName:"webgl",kernelFunc:jQ},XQ=_6+`
return min(a, b);
`,KQ=`
vec4 result = vec4(min(a, b));
vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
`+pf+`
return result;
`,ZQ=rn({opSnippet:XQ,packedOpSnippet:KQ,cpuKernelImpl:jq}),YQ={kernelName:Ua,backendName:"webgl",kernelFunc:ZQ},JQ=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=t.map((u,c)=>u[0]+e[c]+u[1]);let s=e.length,r=ut(s),a=t.map(u=>u[0]).join(","),o=t.map((u,c)=>u[0]+e[c]).join(","),i=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,s),l=n==="reflect"?0:1;if(s===1){this.userCode=`
int start = ${a};
int end = ${o};
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 = ${r}(${a});
${r} end = ${r}(${o});
void main() {
${r} outC = getOutputCoords();
for (int i = 0; i < ${s}; 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};
}
}
${r} coords = outC - start;
setOutput(getX(${i}));
}
`}},QQ=class{constructor(e,t,n){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t.map((p,m)=>p[0]+e[m]+p[1]);let s=e.length,r=ut(s),a=t.map(p=>p[0]).join(","),o=t.map((p,m)=>p[0]+e[m]).join(","),i=vn("rc",s),l=vn("source",s),u=`${i[s-1]} < ${this.outputShape[s-1]}`,c=s===1?"source":`vec2(${l.slice(-2).join()})`,d=n==="reflect"?0:1,h="";if(s===1){let p=`
${r} source = rc;
if (source < start) {
source = start * 2 - source - ${d};
} else if (source >= end) {
source = (end - 1) * 2 - source + ${d};
}
source -= start;
`;h=`
${r} rc = outputLoc;
${p}
result[0] = getChannel(getX(${l.join()}), ${c});
${i[s-1]} += 1;
if(${u}) {
${p}
result[1] = getChannel(getX(${l.join()}), ${c});
}
`}else{let p=`
${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;
`;h=`
${r} rc = outputLoc;
${p}
result[0] = getChannel(getX(${l.join()}), ${c});
${i[s-1]} += 1;
if(${u}) {
${p}
result[1] = getChannel(getX(${l.join()}), ${c});
}
rc = outputLoc;
${i[s-2]} += 1;
if(${i[s-2]} < ${this.outputShape[s-2]}) {
${p}
result[2] = getChannel(getX(${l.join()}), ${c});
${i[s-1]} += 1;
if(${u}) {
${p}
result[3] = getChannel(getX(${l.join()}), ${c});
}
}
`}this.userCode=`
const ${r} start = ${r}(${a});
const ${r} end = ${r}(${o});
void main() {
${r} outputLoc = getOutputCoords();
vec4 result = vec4(0.);
${h}
setOutput(result);
}
`}},eee=({inputs:e,backend:t,attrs:n})=>{let{x:s}=e,{paddings:r,mode:a}=n,o=ee().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new QQ(s.shape,r,a):new JQ(s.shape,r,a);return t.runWebGLProgram(o,[s],s.dtype)},tee={kernelName:Ha,backendName:"webgl",kernelFunc:eee},nee=`if (b == 0.0) return NAN;
return mod(a, b);`,see=`
vec4 result = mod(a, b);
vec4 isNaN = vec4(equal(b, vec4(0.0)));
`+pf+`
return result;
`,ree=rn({opSnippet:nee,packedOpSnippet:see}),aee={kernelName:Wi,backendName:"webgl",kernelFunc:ree},oee=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}));
}
`}},iee=`
if (a == b) {
return 1.0;
};
return a / b;`,lee=`
// 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;
`,f4=rn({opSnippet:iee,packedOpSnippet:lee,checkOutOfBounds:!0}),uee={kernelName:Ea,backendName:"webgl",kernelFunc:f4},m4="return a - b;",A4=rn({opSnippet:m4,packedOpSnippet:m4,supportsComplex:!0,cpuKernelImpl:oX}),cee={kernelName:lo,backendName:"webgl",kernelFunc:A4};function g4(e){let{inputs:t,backend:n,attrs:s}=e,{logits:r}=t,{dim:a}=s,o=I.parseAxisParam([a],r.shape),i=p4({inputs:{x:r},backend:n,attrs:{reductionIndices:o,keepDims:!1}}),l=$.expandShapeToKeepDim(i.shape,o),u=ye({inputs:{x:i},backend:n,attrs:{shape:l}}),c=A4({inputs:{a:r,b:u},backend:n}),d=i4({inputs:{x:c},backend:n}),h=Af({inputs:{x:d},backend:n,attrs:{axis:o,keepDims:!1}}),p=ye({inputs:{x:h},backend:n,attrs:{shape:l}}),m=f4({inputs:{a:d,b:p},backend:n});return n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(u),n.disposeIntermediateTensorInfo(c),n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(p),m}var dee={kernelName:oo,backendName:"webgl",kernelFunc:g4};function hee(e){let{inputs:t,backend:n,attrs:s}=e,{logits:r}=t,{numSamples:a,seed:o,normalized:i}=s,l=i?r:g4({inputs:{logits:r},backend:n,attrs:{dim:r.shape.length-1}}),u=l.shape[0],c=l.shape[1],d=new oee(u,c,a),h=[[o]],p=n.runWebGLProgram(d,[l],"int32",h);return i||n.disposeIntermediateTensorInfo(l),p}var pee={kernelName:ih,backendName:"webgl",kernelFunc:hee},y4="return -x;";function fee(e){let{inputs:t,backend:n}=e,{x:s}=t;if(n.shouldExecuteOnCPU([s])){let a=n.texData.get(s.dataId),[o,i]=Xq(a.values,s.shape,s.dtype);return n.makeTensorInfo(i,s.dtype,o)}let r;return ee().getBool("WEBGL_PACK_UNARY_OPERATIONS")?r=new Yl(s.shape,y4):r=new sa(s.shape,y4),n.runWebGLProgram(r,[s],s.dtype)}var mee={kernelName:Vi,backendName:"webgl",kernelFunc:fee},Aee=Js.nonMaxSuppressionV3Impl;function gee(e){$.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:s}=e,{boxes:r,scores:a}=t,{maxOutputSize:o,iouThreshold:i,scoreThreshold:l}=s,u=n.readSync(r.dataId),c=n.readSync(a.dataId),{selectedIndices:d}=Aee(u,c,o,i,l);return n.makeTensorInfo([d.length],"int32",new Int32Array(d))}var yee={kernelName:Hi,backendName:"webgl",kernelFunc:gee},xee=Js.nonMaxSuppressionV4Impl;function bee(e){$.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:s}=e,{boxes:r,scores:a}=t,{maxOutputSize:o,iouThreshold:i,scoreThreshold:l,padToMaxOutputSize:u}=s,c=n.readSync(r.dataId),d=n.readSync(a.dataId),{selectedIndices:h,validOutputs:p}=xee(c,d,o,i,l,u);return[n.makeTensorInfo([h.length],"int32",new Int32Array(h)),n.makeTensorInfo([],"int32",new Int32Array([p]))]}var vee={kernelName:Gi,backendName:"webgl",kernelFunc:bee},wee=Js.nonMaxSuppressionV5Impl;function kee(e){$.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:s}=e,{boxes:r,scores:a}=t,{maxOutputSize:o,iouThreshold:i,scoreThreshold:l,softNmsSigma:u}=s,c=n.readSync(r.dataId),d=n.readSync(a.dataId),h=o,p=i,m=l,f=u,{selectedIndices:A,selectedScores:g}=wee(c,d,h,p,m,f);return[n.makeTensorInfo([A.length],"int32",new Int32Array(A)),n.makeTensorInfo([g.length],"float32",new Float32Array(g))]}var Iee={kernelName:ji,backendName:"webgl",kernelFunc:kee},See=class{constructor(e,t,n,s){this.variableNames=["indices"],this.outputShape=[e,t],this.userCode=`
void main() {
ivec2 coords = getOutputCoords();
int index = round(getIndices(coords.x));
setOutput(mix(float(${s}), float(${n}),
float(index == coords.y)));
}
`}},Cee=e=>{let{inputs:t,backend:n,attrs:s}=e,{indices:r}=t,{depth:a,onValue:o,offValue:i}=s,l=I.sizeFromShape(r.shape),u=new See(l,a,o,i),c=ye({inputs:{x:r},backend:n,attrs:{shape:[l]}}),d=n.runWebGLProgram(u,[c],r.dtype);n.disposeIntermediateTensorInfo(c);let h=[...r.shape,a],p=ye({inputs:{x:d},backend:n,attrs:{shape:h}});return n.disposeIntermediateTensorInfo(d),p},Tee={kernelName:ja,backendName:"webgl",kernelFunc:Cee};function wf(e){let{inputs:t,backend:n}=e,{x:s}=t;if(s.dtype==="complex64"){let r=qc({inputs:{input:s},backend:n}),a=wf({inputs:{x:r},backend:n}),o=bf({inputs:{input:s},backend:n}),i=wf({inputs:{x:o},backend:n}),l=ra({inputs:{real:a,imag:i},backend:n});return n.disposeIntermediateTensorInfo(r),n.disposeIntermediateTensorInfo(a),n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(i),l}else return vf({attrs:{shape:s.shape,dtype:s.dtype,value:s.dtype==="string"?"":0},backend:n})}var Nee={kernelName:dl,backendName:"webgl",kernelFunc:wf};function x4(e){let{inputs:t,backend:n}=e,{x:s}=t;if(s.dtype==="string")throw new Error("onesLike is not supported under string dtype");if(s.dtype==="complex64"){let r=qc({inputs:{input:s},backend:n}),a=x4({inputs:{x:r},backend:n}),o=bf({inputs:{input:s},backend:n}),i=wf({inputs:{x:o},backend:n}),l=ra({inputs:{real:a,imag:i},backend:n});return n.disposeIntermediateTensorInfo(r),n.disposeIntermediateTensorInfo(a),n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(i),l}else return vf({attrs:{shape:s.shape,dtype:s.dtype,value:1},backend:n})}var Eee={kernelName:qi,backendName:"webgl",kernelFunc:x4};function Ree(e){let{inputs:t,backend:n,attrs:s}=e,{axis:r}=s;if(t.length===1)return _1({inputs:{input:t[0]},backend:n,attrs:{dim:r}});let a=t[0].shape,o=t[0].dtype;t.forEach(c=>{I.assertShapesMatch(a,c.shape,"All tensors passed to stack must have matching shapes"),I.assert(o===c.dtype,()=>"All tensors passed to stack must have matching dtypes")});let i=[],l=t.map(c=>{let d=_1({inputs:{input:c},backend:n,attrs:{dim:r}});return i.push(d),d}),u=Y6({inputs:l,backend:n,attrs:{axis:r}});return i.forEach(c=>n.disposeIntermediateTensorInfo(c)),u}var _ee={kernelName:Xi,backendName:"webgl",kernelFunc:Ree},$ee=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 s=e.length,r=ut(s),a=t.map(l=>l[0]).join(","),o=t.map((l,u)=>l[0]+e[u]).join(","),i=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,s);if(s===1){this.userCode=`
int start = ${a};
int end = ${o};
void main() {
int outC = getOutputCoords();
if (outC < start || outC >= end) {
setOutput(value);
} else {
setOutput(getX(outC - start));
}
}
`;return}this.userCode=`
${r} start = ${r}(${a});
${r} end = ${r}(${o});
void main() {
${r} outC = getOutputCoords();
if (any(lessThan(outC, start)) || any(greaterThanEqual(outC, end))) {
setOutput(value);
} else {
${r} coords = outC - start;
setOutput(getX(${i}));
}
}
`}},Fee=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 s=e.length,r=ut(s),a=t.map(m=>m[0]).join(","),o=t.map((m,f)=>m[0]+e[f]).join(","),i=vn("rc",s),l=vn("source",s),u=`${i[s-1]} < ${this.outputShape[s-1]}`,c=s===1?"source":`vec2(${l.slice(-2).join()})`,d=[`${r} rc = outputLoc;`,`${i[s-1]} += 1;
if(${u}) {
`,s===1?"":`}
rc = outputLoc;
${i[s-2]} += 1;
if(${i[s-2]} < ${this.outputShape[s-2]}) {`,s===1?"":` ${i[s-1]} += 1;
if(${u}) {`],h=s===1?"rc < start || rc >= end":"any(lessThan(rc, start)) || any(greaterThanEqual(rc, end))",p="";for(let m=0,f=s===1?2:4;m<f;m++)p+=`
${d[m]}
if (${h}) {
result[${m}] = float(value);
} else {
${r} source = rc - start;
result[${m}] = getChannel(getX(${l.join()}), ${c});
}
`;p+=s===1?"} ":"}}",this.userCode=`
const ${r} start = ${r}(${a});
const ${r} end = ${r}(${o});
void main() {
${r} outputLoc = getOutputCoords();
vec4 result = vec4(0.);
${p}
setOutput(result);
}
`}},b4=e=>{let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{paddings:a,constantValue:o}=s,i=ee().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new Fee(r.shape,a,o):new $ee(r.shape,a,o),l=[[o]];return n.runWebGLProgram(i,[r],r.dtype,l)},Dee={kernelName:qa,backendName:"webgl",kernelFunc:b4},Oee=`
if(a < 0.0 && floor(b) < b){
return NAN;
}
if (b == 0.0) {
return 1.0;
}
return (round(mod(b, 2.0)) != 1) ?
pow(abs(a), b) : sign(a) * pow(abs(a), b);
`,Pee=`
// isModRound1 has 1 for components with round(mod(b, 2.0)) == 1, 0 otherwise.
vec4 isModRound1 = vec4(equal(round(mod(b, 2.0)), ivec4(1)));
vec4 multiplier = sign(a) * isModRound1 + (vec4(1.0) - isModRound1);
vec4 result = multiplier * pow(abs(a), b);
// Ensure that a^0 = 1, including 0^0 = 1 as this correspond to TF and JS
bvec4 isExpZero = equal(b, vec4(0.0));
result.r = isExpZero.r ? 1.0 : result.r;
result.g = isExpZero.g ? 1.0 : result.g;
result.b = isExpZero.b ? 1.0 : result.b;
result.a = isExpZero.a ? 1.0 : result.a;
vec4 isNaN = vec4(lessThan(a, vec4(0.0))) * vec4(lessThan(floor(b), b));
`+pf+`
return result;
`,Mee=rn({opSnippet:Oee,packedOpSnippet:Pee}),zee={kernelName:Xa,backendName:"webgl",kernelFunc:Mee};function Lee(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,keepDims:o}=s,i=r.shape.length,l=[],u=I.parseAxisParam(a,r.shape),c=u,d=$.getAxesPermutation(c,i),h=r;d!=null&&(h=wn({inputs:{x:r},backend:n,attrs:{perm:d}}),c=$.getInnerMostAxes(c.length,i),l.push(h)),$.assertAxesAreInnerMostDims("prod",c,i);let p;if(n.shouldExecuteOnCPU([h])){let m=n.texData.get(h.dataId).values,{outVals:f,outShape:A,outDtype:g}=Zq(h.shape,h.dtype,m,c);p=n.makeTensorInfo(A,g,f)}else{let[m,f]=$.computeOutAndReduceShapes(h.shape,c),A=I.sizeFromShape(f),g=ye({inputs:{x:h},backend:n,attrs:{shape:[-1,A]}}),y=Ch(r.dtype),x=Go(g,y,"prod",n);p=ye({inputs:{x},backend:n,attrs:{shape:m}}),l.push(g),l.push(x)}if(o){l.push(p);let m=$.expandShapeToKeepDim(p.shape,u);p=ye({inputs:{x:p},backend:n,attrs:{shape:m}})}return l.forEach(m=>n.disposeIntermediateTensorInfo(m)),p}var Bee={kernelName:Ki,backendName:"webgl",kernelFunc:Lee},v4=e=>{let{backend:t,attrs:n}=e,{start:s,stop:r,step:a,dtype:o}=n,i=Yq(s,r,a,o);return t.makeTensorInfo([i.length],o,i)},Wee={kernelName:zu,backendName:"webgl",kernelFunc:v4},Vee="return 1.0 / x;",Uee=Ze({opSnippet:Vee}),Hee={kernelName:Zi,backendName:"webgl",kernelFunc:Uee},Gee=Bs+`
return (x < 0.0) ? 0.0 : x;
`,jee=`
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;
`,qee=Ze({opSnippet:Gee,packedOpSnippet:jee}),Xee={kernelName:Za,backendName:"webgl",kernelFunc:qee},Kee=Bs+`
return (x < 0.0) ? 0.0 : min(6.0, x);
`,Zee=`
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;
`,Yee=Ze({opSnippet:Kee,packedOpSnippet:Zee}),Jee={kernelName:Ja,backendName:"webgl",kernelFunc:Yee},Qee=class{constructor(e,t,n,s,r){this.variableNames=["A"],this.outputShape=[];let[a,o,i,l]=e;this.outputShape=[a,t,n,l];let u=[s&&t>1?o-1:o,s&&n>1?i-1:i],c=[s&&t>1?t-1:t,s&&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]/c[0]},
${u[1]/c[1]});
const vec2 inputShapeRC = vec2(${o}.0, ${i}.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);
}
`}},ete=class{constructor(e,t,n,s,r){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[];let[a,o,i,l]=e;this.outputShape=[a,t,n,l];let u=[s&&t>1?o-1:o,s&&n>1?i-1:i],c=[s&&t>1?t-1:t,s&&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]/c[0]},
${u[1]/c[1]},
${u[1]/c[1]});
const vec3 inputShapeRC = vec3(${o}.0, ${i}.0,
${i}.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 tte(e){let{inputs:t,backend:n,attrs:s}=e,{images:r}=t,{alignCorners:a,halfPixelCenters:o,size:i}=s,[l,u]=i,c=ee().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new ete(r.shape,l,u,a,o):new Qee(r.shape,l,u,a,o);return n.runWebGLProgram(c,[r],"float32")}var nte={kernelName:Ya,backendName:"webgl",kernelFunc:tte},ste=class{constructor(e,t,n){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t;let[,s,r]=t,[,a,o]=e,i=[n&&a>1?s-1:s,n&&o>1?r-1:r],l=[n&&a>1?a-1:a,n&&o>1?o-1:o],u=i[0]/l[0],c=i[1]/l[1],d=1/u,h=1/c,p=Math.ceil(d)*2+2,m=Math.ceil(h)*2+2;this.userCode=`
void main() {
ivec4 coords = getOutputCoords();
int b = coords[0];
int d = coords[3];
int r = coords[1];
int c = coords[2];
float accumulator = 0.0;
const float heightScale = float(${u});
const float widthScale = float(${c});
const float invHeightScale = float(${d});
const float invWidthScale = float(${h});
const int winHeight = int(${p});
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 >= ${a}) {
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 >= ${o}) {
continue;
}
float dxR = float(dyR) * heightScale;
int topDxRIndex = int(floor(dxR));
int bottomDxRIndex = int(min(ceil(dxR), ${s-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 rte(e){let{inputs:t,backend:n,attrs:s}=e,{images:r,dy:a}=t,{alignCorners:o}=s,i=new ste(a.shape,r.shape,o);return n.runWebGLProgram(i,[a],a.dtype)}var ate={kernelName:ch,backendName:"webgl",kernelFunc:rte},ote=class{constructor(e,t,n,s,r){this.variableNames=["A"],this.outputShape=[];let[a,o,i,l]=e;this.outputShape=[a,t,n,l];let u=[s&&t>1?o-1:o,s&&n>1?i-1:i],c=[s&&t>1?t-1:t,s&&n>1?n-1:n],d=s?"0.5":"0.0",h;r?h="max((vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC, vec2(0.0))":h="vec2(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
const vec2 effectiveInputOverOutputRatioRC = vec2(
${u[0]/c[0]},
${u[1]/c[1]});
const vec2 inputShapeRC = vec2(${o}.0, ${i}.0);
void main() {
ivec4 coords = getOutputCoords();
int b = coords[0];
int d = coords[3];
ivec2 yRC = coords.yz;
// Fractional source index.
vec2 sourceFracIndexRC = ${h};
// Compute the 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);
}
`}},ite=class{constructor(e,t,n,s,r){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[];let[a,o,i,l]=e;this.outputShape=[a,t,n,l];let u=[s&&t>1?o-1:o,s&&n>1?i-1:i],c=[s&&t>1?t-1:t,s&&n>1?n-1:n],d=s?"0.5":"0.0",h;r?h="max((vec3(yRC) + vec3(0.5)) * effectiveInputOverOutputRatioRC, vec3(0.0))":h="vec3(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
const vec3 effectiveInputOverOutputRatioRC = vec3(
${u[0]/c[0]},
${u[1]/c[1]},
${u[1]/c[1]});
const vec3 inputShapeRC = vec3(${o}.0, ${i}.0,
${i}.0);
float getAValue(int b, int r, int c, int d) {
return getChannel(getA(b, r, c, d), vec2(c, d));
}
void main() {
ivec4 coords = getOutputCoords();
int b = coords[0];
int d = coords[3];
// Calculate values for next column in yRC.z.
ivec3 yRC = coords.yzz + ivec3(0, 0, 1);
// Fractional source index.
vec3 sourceFracIndexRC = ${h};
// Compute the 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 < ${n-1};
vec4 newValue = vec4(
getAValue(b, sourceNearestRC.x, sourceNearestRC.y, d),
hasNextCol ? getAValue(b, sourceNearestRC.x, sourceNearestRC.y, d + 1)
: 0.0,
hasNextRow ? getAValue(b, sourceNearestRC.x, sourceNearestRC.z, d)
: 0.0,
(hasNextRow && hasNextCol) ?
getAValue(b, sourceNearestRC.x, sourceNearestRC.z, d + 1) : 0.0);
setOutput(newValue);
}
`}};function lte(e){let{inputs:t,backend:n,attrs:s}=e,{images:r}=t,{alignCorners:a,halfPixelCenters:o,size:i}=s,[l,u]=i,c=ee().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new ite(r.shape,l,u,a,o):new ote(r.shape,l,u,a,o);return n.runWebGLProgram(c,[r],r.dtype)}var ute={kernelName:Lu,backendName:"webgl",kernelFunc:lte},cte=class{constructor(e,t,n){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t;let[,s,r]=t,[,a,o]=e,i=[n&&a>1?s-1:s,n&&o>1?r-1:r],l=[n&&a>1?a-1:a,n&&o>1?o-1:o],u=i[0]/l[0],c=i[1]/l[1],d=1/u,h=1/c,p=Math.ceil(d)*2+2,m=Math.ceil(h)*2+2;this.userCode=`
void main() {
ivec4 coords = getOutputCoords();
int b = coords[0];
int d = coords[3];
int r = coords[1];
int c = coords[2];
float accumulator = 0.0;
const float heightScale = float(${u});
const float widthScale = float(${c});
const float invHeightScale = float(${d});
const float invWidthScale = float(${h});
const int winHeight = int(${p});
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 >= ${a}) {
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 >= ${o}) {
continue;
}
float sourceFracRow =
float(${i[0]}) *
(float(dyR) / float(${l[0]}));
float sourceFracCol =
float(${i[1]}) *
(float(dyC) / float(${l[1]}));
int sourceNearestRow = int(min(
float(int(${s}) - 1),
${n} ? float(round(sourceFracRow)) :
float(floor(sourceFracRow))));
int sourceNearestCol = int(min(
float(int(${r}) - 1),
${n} ? float(round(sourceFracCol)) :
float(floor(sourceFracCol))));
if (r == sourceNearestRow && c == sourceNearestCol) {
accumulator += getDy(b, dyR, dyC, d);
}
}
}
// End loop over dy
setOutput(accumulator);
}
`}};function dte(e){let{inputs:t,backend:n,attrs:s}=e,{images:r,dy:a}=t,{alignCorners:o}=s,i=new cte(a.shape,r.shape,o);return n.runWebGLProgram(i,[a],a.dtype)}var hte={kernelName:uh,backendName:"webgl",kernelFunc:dte},pte=class{constructor(e,t){this.variableNames=["x"];let n=e.length;if(n>4)throw new Error(`WebGL backend: Reverse of rank-${n} tensor is not yet supported`);if(this.outputShape=e,n===1){this.userCode=`
void main() {
int coord = getOutputCoords();
setOutput(getX(${e[0]} - coord - 1));
}
`;return}let s=o=>t.indexOf(o)!==-1&&e[o]!==1?`${e[o]} - coords[${o}] - 1`:`coords[${o}]`,r=e.map((o,i)=>s(i)).join(","),a=ut(n);this.userCode=`
void main() {
${a} coords = getOutputCoords();
setOutput(getX(${r}));
}
`}},fte=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-${n} tensor is not yet supported`);this.outputShape=e;let s=vn("rc",n),r=`${s[n-1]} + 1 < ${this.outputShape[n-1]}`,a=`${s[n-2]} + 1 < ${this.outputShape[n-2]}`,o=ut(n);n===1?this.userCode=`
void main(){
int rc = getOutputCoords();
vec4 result = vec4(0.);
result.r = getChannel(getX(${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() {
${o} rc = getOutputCoords();
vec4 result = vec4(0.);
result.r = ${i(s.slice())};
if(${r}){
result.g = ${l(s.slice())};
}
if(${a}) {
result.b = ${u(s.slice())};
if(${r}) {
result.a = ${c(s.slice())};
}
}
setOutput(result);
}
`;function i(p){return d(p)}function l(p){return p[n-1]="("+p[n-1]+" + 1)",d(p)}function u(p){return p[n-2]="("+p[n-2]+" + 1)",d(p)}function c(p){return p[n-1]="("+p[n-1]+" + 1)",p[n-2]="("+p[n-2]+" + 1)",d(p)}function d(p){let m=e.map((g,y)=>h(y,p)),f=m.join(","),A=m.slice(-2).join(",");return`getChannel(getX(${f}), vec2(${A}))`}function h(p,m){return t.indexOf(p)!==-1&&e[p]!==1?`${e[p]} - ${m[p]} - 1`:`${m[p]}`}}};function mte(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{dims:a}=s,o=r.shape.length,i=I.parseAxisParam(a,r.shape);if(o===0)return qn({inputs:{x:r},backend:n});let l=ee().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new fte(r.shape,i):new pte(r.shape,i);return n.runWebGLProgram(l,[r],r.dtype)}var Ate={kernelName:Qa,backendName:"webgl",kernelFunc:mte},gte=class{constructor(e,t){this.variableNames=["Image"],this.outputShape=[],this.customUniforms=[{name:"params",type:"vec4"}];let n=e[1],s=e[2];this.outputShape=e;let r="";typeof t=="number"?r=`float outputValue = ${t.toFixed(2)};`:r=`
vec3 fill = vec3(${t.join(",")});
float outputValue = fill[coords[3]];`,this.userCode=`
void main() {
ivec4 coords = getOutputCoords();
int x = coords[2];
int y = coords[1];
float coordXFloat = (float(x) - params[0]) * params[3] -
(float(y) - params[1]) * params[2];
float coordYFloat = (float(x) - params[0]) * params[2] +
(float(y) - params[1]) * params[3];
int coordX = int(round(coordXFloat + params[0]));
int coordY = int(round(coordYFloat + params[1]));
${r}
if(coordX >= 0 && coordX < ${s} && coordY >= 0 && coordY < ${n}) {
outputValue = getImage(coords[0], coordY, coordX, coords[3]);
}
setOutput(outputValue);
}
`}},yte={kernelName:hl,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{image:s}=e,{radians:r,fillValue:a,center:o}=t,i=n,l=new gte(s.shape,a),[u,c]=$.getImageCenter(o,s.shape[1],s.shape[2]),d=[[u,c,Math.sin(r),Math.cos(r)]];return i.runWebGLProgram(l,[s],s.dtype,d)}},xte=`
// OpenGL ES does not support round function.
// The algorithm is based on banker's rounding.
float base = floor(x);
if ((x - base) < 0.5) {
return floor(x);
} else if ((x - base) > 0.5) {
return ceil(x);
} else {
if (mod(base, 2.0) == 0.0) {
return base;
} else {
return base + 1.0;
}
}
`,bte=Ze({opSnippet:xte}),vte={kernelName:eo,backendName:"webgl",kernelFunc:bte},wte="return inversesqrt(x);",kte=Ze({opSnippet:wte,cpuKernelImpl:Jq}),Ite={kernelName:to,backendName:"webgl",kernelFunc:kte},w4=class{constructor(e,t,n,s,r,a,o=!0){this.variableNames=["updates","indices","defaultValue"],this.outputShape=a;let i=ut(r.length),l=ut(a.length),u="";n===1?u="i":n===2&&(u="i, j");let c=`getIndices(${u})`,d="";s===1?d="i":s===2&&(d="i, coords[1]");let h=`getUpdates(${d})`,p=t>1?"strides[j]":"strides";this.userCode=`
${i} strides = ${i}(${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 < ${t}; j++) {
int index = round(${c});
flattenedIndex += index * ${p};
}
if (flattenedIndex == coords[0]) {
sum += ${h};
found = true;
}
}
setOutput(mix(getDefaultValue(), sum, float(found)));
}
`}};function Ste(e){let{inputs:t,backend:n,attrs:s}=e,{indices:r,updates:a}=t,{shape:o}=s,{sliceRank:i,numUpdates:l,sliceSize:u,strides:c,outputSize:d}=$.calculateShapes(a,r,o),h=[d/u,u];if(d===0)return n.makeTensorInfo(o,r.dtype);let p=ye({inputs:{x:r},backend:n,attrs:{shape:[l,i]}}),m=ye({inputs:{x:a},backend:n,attrs:{shape:[l,u]}}),f=n.makeTensorInfo([],"float32",new Float32Array([0])),A=new w4(l,i,p.shape.length,m.shape.length,c,h),g=n.runWebGLProgram(A,[m,p,f],m.dtype),y=ye({inputs:{x:g},backend:n,attrs:{shape:o}});return n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(g),n.disposeIntermediateTensorInfo(f),y}var Cte={kernelName:Ji,backendName:"webgl",kernelFunc:Ste},Tte=class{constructor(e,t,n){this.variableNames=["c","a","b"],this.outputShape=t;let s,r;if(n>4)throw Error(`Where for rank ${n} is not yet supported`);if(n===1)r="resRC",s="resRC";else{let o=["resRC.x","resRC.y","resRC.z","resRC.w"],i=[],l=[];for(let u=0;u<t.length;u++)l.push(`${o[u]}`),u<e&&i.push(`${o[u]}`);s=i.join(),r=l.join()}let a=ut(n);this.userCode=`
void main() {
${a} resRC = getOutputCoords();
float cVal = getC(${s});
if (cVal >= 1.0) {
setOutput(getA(${r}));
} else {
setOutput(getB(${r}));
}
}
`}};function Nte(e){let{inputs:t,backend:n}=e,{condition:s,t:r,e:a}=t,o=new Tte(s.shape.length,r.shape,r.shape.length);return n.runWebGLProgram(o,[s,r,a],bs(r.dtype,a.dtype))}var Ete={kernelName:Qi,backendName:"webgl",kernelFunc:Nte},Rte=`
// Stable and Attracting Fixed Point (0, 1) for Normalized Weights.
// see: https://arxiv.org/abs/1706.02515
float scaleAlpha = ${$.SELU_SCALEALPHA};
float scale = ${$.SELU_SCALE};
return (x >= 0.0) ? scale * x : scaleAlpha * (exp(x) - 1.0);
`,_te=Ze({opSnippet:Rte}),$te={kernelName:el,backendName:"webgl",kernelFunc:_te},Fte="return 1.0 / (1.0 + exp(-1.0 * x));",Dte=Ze({opSnippet:Fte}),Ote={kernelName:so,backendName:"webgl",kernelFunc:Dte},Pte=`
if (isnan(x)) { return 0.0; }
return sign(x);
`,Mte=Ze({opSnippet:Pte}),zte={kernelName:sl,backendName:"webgl",kernelFunc:Mte},Lte=P6+`
return sin(x);
`,Bte=Ze({opSnippet:Lte}),Wte={kernelName:no,backendName:"webgl",kernelFunc:Bte},Vte=`
float e2x = exp(x);
return (e2x - 1.0 / e2x) / 2.0;
`,Ute=Ze({opSnippet:Vte}),Hte={kernelName:nl,backendName:"webgl",kernelFunc:Ute},Gte=`
float epsilon = 1.1920928955078125e-7;
float threshold = log(epsilon) + 2.0;
bool too_large = x > -threshold;
bool too_small = x < threshold;
float result;
float exp_x = exp(x);
if (too_large){
result = x;
}
else if (too_small){
result = exp_x;
}
else{
result = log(exp_x + 1.0);
}
return result;
`,jte=Ze({opSnippet:Gte}),qte={kernelName:rl,backendName:"webgl",kernelFunc:jte},Xte=e=>{let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{blockShape:a,paddings:o}=s;I.assert(r.shape.length<=4,()=>"spaceToBatchND for rank > 4 with a WebGL backend not implemented yet");let i=a.reduce((g,y)=>g*y),l=[[0,0]];l.push(...o);for(let g=1+a.length;g<r.shape.length;++g)l.push([0,0]);let u=[],c=b4({inputs:{x:r},backend:n,attrs:{paddings:l,constantValue:0}}),d=$.getReshaped(c.shape,a,i,!1),h=$.getPermuted(d.length,a.length,!1),p=$.getReshapedPermuted(c.shape,a,i,!1),m=ye({inputs:{x:c},backend:n,attrs:{shape:d}}),f=wn({inputs:{x:m},backend:n,attrs:{perm:h}}),A=ye({inputs:{x:f},backend:n,attrs:{shape:p}});return u.push(c),u.push(m),u.push(f),u.forEach(g=>n.disposeIntermediateTensorInfo(g)),A},Kte={kernelName:al,backendName:"webgl",kernelFunc:Xte};function Zte(e){let{inputs:t,backend:n}=e,{indices:s,values:r,denseShape:a,defaultValue:o}=t;if(a.shape.length!==1)throw new Error(`Dense shape must be a vector, saw:
${a.shape}`);if(s.shape.length!==2)throw new Error(`Indices must be a matrix, saw:
${s.shape}`);if(r.shape.length!==1)throw new Error(`Values must be a vector, saw:
${r.shape}`);if(o.shape.length!==0)throw new Error(`Default value must be a scalar, saw:
${o.shape}`);let i=n.readSync(s.dataId),l=n.readSync(r.dataId),u=n.readSync(a.dataId),c=n.readSync(o.dataId)[0],[d,h,p,m,f]=eX(i,s.shape,s.dtype,l,r.dtype,u,c);return[n.makeTensorInfo(h,s.dtype,d),n.makeTensorInfo([h[0]],r.dtype,p),n.makeTensorInfo([m.length],"bool",new Uint8Array(m.map(A=>Number(A)))),n.makeTensorInfo([f.length],s.dtype,new Int32Array(f))]}var Yte={kernelName:dh,backendName:"webgl",kernelFunc:Zte};function Jte(e){let{inputs:t,backend:n}=e,{inputIndices:s,inputShape:r,newShape:a}=t;if(s.shape.length!==2)throw new Error(`Input indices should be a matrix but received shape ${s.shape}`);if(r.shape.length!==1)throw new Error(`Input shape should be a vector but received shape ${r.shape}`);if(a.shape.length!==1)throw new Error(`Target shape should be a vector but received shape ${a.shape}`);let o=Array.from(n.readSync(r.dataId)),i=n.readSync(s.dataId),l=Array.from(n.readSync(a.dataId)),[u,c,d]=tX(i,s.shape,s.dtype,o,l);return[n.makeTensorInfo(c,s.dtype,u),n.makeTensorInfo([d.length],a.dtype,new Int32Array(d))]}var Qte={kernelName:hh,backendName:"webgl",kernelFunc:Jte};function ene(e){let{inputs:t,backend:n}=e,{data:s,indices:r,segmentIds:a}=t;if(s.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(a.shape.length!==1)throw new Error(`Segment ids should be a vector but received shape
${a.shape}`);let o=n.readSync(s.dataId),i=n.readSync(r.dataId),l=n.readSync(a.dataId),[u,c]=k6(o,s.shape,s.dtype,i,l,!0);return n.makeTensorInfo(c,s.dtype,u)}var tne={kernelName:ph,backendName:"webgl",kernelFunc:ene};function nne(e){let{inputs:t,backend:n}=e,{data:s,indices:r,segmentIds:a}=t;if(s.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(a.shape.length!==1)throw new Error(`Segment ids should be a vector but received shape
${a.shape}`);let o=n.readSync(s.dataId),i=n.readSync(r.dataId),l=n.readSync(a.dataId),[u,c]=k6(o,s.shape,s.dtype,i,l);return n.makeTensorInfo(c,s.dtype,u)}var sne={kernelName:fh,backendName:"webgl",kernelFunc:nne};function rne(e){let{inputs:t,backend:n,attrs:s}=e,{sparseIndices:r,sparseValues:a,defaultValue:o}=t,{outputShape:i}=s,{sliceRank:l,numUpdates:u,strides:c,outputSize:d}=$.calculateShapes(a,r,i),h=!1,p=new w4(u,l,r.shape.length,a.shape.length,c,[d,1],h),m=n.runWebGLProgram(p,[a,r,o],a.dtype),f=ye({inputs:{x:m},backend:n,attrs:{shape:i}});return n.disposeIntermediateTensorInfo(m),f}var ane={kernelName:mh,backendName:"webgl",kernelFunc:rne};function one(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{numOrSizeSplits:a,axis:o}=s,i=I.parseAxisParam(o,r.shape)[0],l=$.prepareSplitSize(r,a,i),u=r.shape.length,c=new Array(u).fill(0),d=r.shape.slice();return l.map(h=>{let p=[...d];p[i]=h;let m=eu({inputs:{x:r},backend:n,attrs:{begin:c,size:p}});return c[i]+=h,m})}var ine={kernelName:ol,backendName:"webgl",kernelFunc:one},lne="return sqrt(x);",une=Ze({opSnippet:lne}),cne={kernelName:ro,backendName:"webgl",kernelFunc:une},dne="return x * x;",hne=Ze({opSnippet:dne}),pne={kernelName:Bu,backendName:"webgl",kernelFunc:hne},k4="return (a - b) * (a - b);",fne=rn({opSnippet:k4,packedOpSnippet:k4}),mne={kernelName:io,backendName:"webgl",kernelFunc:fne};function Ane({inputs:e,attrs:t,backend:n}){let{x:s}=e,r=Bs+`
return x > 0.0 ? 1.0 : float(${t.alpha});
`,a=new sa(s.shape,r);return n.runWebGLProgram(a,[s],s.dtype)}var gne={kernelName:Mr,backendName:"webgl",kernelFunc:Ane},yne=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=n;let s=n.length,r=ut(n.length),a=ut(n.length),o="";if(s===1)o="coords * strides + begin";else{let i=0;o=n.map((l,u)=>(i++,n.length===1?`coords * strides[${u}] + begin[${u}]`:`coords[${i-1}] * strides[${u}] + begin[${u}]`)).join(",")}this.userCode=`
${r} begin = ${r}(${e});
${r} strides = ${r}(${t});
void main() {
${a} coords = getOutputCoords();
setOutput(getX(${o}));
}
`}};function xne(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{begin:a,end:o,strides:i,beginMask:l,endMask:u,ellipsisMask:c,newAxisMask:d,shrinkAxisMask:h}=s,{nonStrided:p,$begin:m,$strides:f,size:A,newShape:g,outShape:y}=An.sliceInfo(r.shape,a,o,i,l,u,c,d,h),x=ye({inputs:{x:r},backend:n,attrs:{shape:g}}),b;if(p){let k=eu({inputs:{x},backend:n,attrs:{begin:m,size:A}});b=ye({inputs:{x:k},backend:n,attrs:{shape:y}}),n.disposeIntermediateTensorInfo(k)}else if(y.some(k=>k===0))b=n.makeTensorInfo(y,r.dtype,[]);else if(n.shouldExecuteOnCPU([x])){let C=n.texData.get(x.dataId).values,E=Be(x.shape,x.dtype,C),P=nX(y,E,f,m);b=n.makeTensorInfo(y,x.dtype,P.values)}else{let w=new yne(m,f,y);b=n.runWebGLProgram(w,[x],x.dtype)}let v=ye({inputs:{x:b},backend:n,attrs:{shape:y}});return n.disposeIntermediateTensorInfo(x),n.disposeIntermediateTensorInfo(b),v}var bne={kernelName:il,backendName:"webgl",kernelFunc:xne};function vne(e){let{inputs:t,backend:n,attrs:s}=e,{separator:r,nGramWidths:a,leftPad:o,rightPad:i,padWidth:l,preserveShortSequences:u}=s,{data:c,dataSplits:d}=t,h=n.readSync(c.dataId),p=n.readSync(d.dataId),[m,f]=sX(h,p,r,a,o,i,l,u);return[n.makeTensorInfo([m.length],"string",m),n.makeTensorInfo(d.shape,"int32",f)]}var wne={kernelName:Ah,backendName:"webgl",kernelFunc:vne};function kne(e){let{inputs:t,backend:n,attrs:s}=e,{skipEmpty:r}=s,{input:a,delimiter:o}=t;if(a.dtype!=="string")throw new Error("Input must be of datatype string");if(a.shape.length!==1)throw new Error(`Input must be a vector, got shape: ${a.shape}`);if(o.shape.length!==0)throw new Error(`Delimiter must be a scalar, got shape: ${o.shape}`);let i=n.readSync(a.dataId),l=n.readSync(o.dataId)[0],[u,c,d]=rX(i,l,r),h=c.length;return[n.makeTensorInfo([h,2],"int32",u),n.makeTensorInfo([h],"string",c),n.makeTensorInfo([2],"int32",new Int32Array(d))]}var Ine={kernelName:gh,backendName:"webgl",kernelFunc:kne};function Sne(e){let{inputs:t,backend:n,attrs:s}=e,{numBuckets:r}=s,{input:a}=t;if(a.dtype!=="string")throw new Error("Input must be of datatype string");if(r<=0)throw new Error("Number of buckets must be at least 1");let o=n.readSync(a.dataId),i=aX(o,r);return n.makeTensorInfo(a.shape,"int32",i)}var Cne={kernelName:yh,backendName:"webgl",kernelFunc:Sne},Tne="return tan(x);",Nne=Ze({opSnippet:Tne}),Ene={kernelName:uo,backendName:"webgl",kernelFunc:Nne},Rne=`
float e2x = exp(-2.0 * abs(x));
return sign(x) * (1.0 - e2x) / (1.0 + e2x);
`,_ne=Ze({opSnippet:Rne}),$ne={kernelName:co,backendName:"webgl",kernelFunc:_ne},Fne=class{constructor(e,t){this.variableNames=["A"];let n=new Array(e.length);for(let a=0;a<n.length;a++)n[a]=e[a]*t[a];this.outputShape=n,this.rank=n.length;let s=ut(this.rank),r=Dne(e);this.userCode=`
void main() {
${s} resRC = getOutputCoords();
setOutput(getA(${r}));
}
`}};function Dne(e){let t=e.length;if(t>5)throw Error(`Tile for rank ${t} is not yet supported`);if(t===1)return`imod(resRC, ${e[0]})`;let n=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u"],s=[];for(let r=0;r<e.length;r++)s.push(`imod(${n[r]}, ${e[r]})`);return s.join()}function I4(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{reps:a}=s;if(r.dtype==="string"||r.shape.length>5){let l=n.readSync(r.dataId),u=r.dtype==="string"?l.map(h=>I.decodeString(h)):l,c=Be(r.shape,r.dtype,u),d=iX(c,a);return n.makeTensorInfo(d.shape,d.dtype,d.values)}let o=new Fne(r.shape,a);return n.runWebGLProgram(o,[r],r.dtype)}var One={kernelName:Pr,backendName:"webgl",kernelFunc:I4},Pne=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));
}
}
`}},Mne=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 jo(e,t){t!==null&&e.disposeIntermediateTensorInfo(t)}function S4(e){let t=1;for(;t<e;)t*=2;return t}function zne(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{k:a,sorted:o}=s,i=ee().getNumber("TOPK_LAST_DIM_CPU_HANDOFF_SIZE_THRESHOLD"),l=ee().getNumber("TOPK_K_CPU_HANDOFF_THRESHOLD"),u=r.shape,c=u[u.length-1];if(n.shouldExecuteOnCPU([r])||c<i||a>l){let P=n.readSync(r.dataId),[R,_]=lX(P,u,r.dtype,a,o);return[n.makeTensorInfo(R.shape,R.dtype,R.values),n.makeTensorInfo(_.shape,_.dtype,_.values)]}if(a===0)return u[u.length-1]=0,[n.makeTensorInfo(u,r.dtype,[]),n.makeTensorInfo(u,"int32",[])];if(c===1)return[r,vf({attrs:{shape:u,dtype:"int32",value:0},backend:n})];let d=n.texData.get(r.dataId),h=d!==null&&d.isPacked,p=h?n.unpackTensor(r):r,f=I.sizeFromShape(u)/c,A=ye({inputs:{x:p},attrs:{shape:[f,c]},backend:n});h&&jo(n,p);let g=S4(a),y=S4(c),x=null,b=()=>x===null?[A,A]:[A,x],v=(P,R,_)=>{let T=b(),O=new Pne(_),j=[[c],[x===null?1:0],[Number.NEGATIVE_INFINITY],[P],[R]],q=x;x=n.runWebGLProgram(O,T,"int32",j),jo(n,q)};for(let P=1;P<g;P*=2){let R=P*2;for(let _=P;_>=1;_/=2)v(R,_,[f,y])}for(let P=y;P>g;P/=2){let R=b(),_=new Mne([f,P/2]),O=[[c],[x===null?1:0],[g]],W=x;x=n.runWebGLProgram(_,R,"int32",O),jo(n,W);let j=g/2,q=j*2;for(let X=j;X>=1;X/=2)v(q,X,x.shape)}let k=x;x=eu({inputs:{x},backend:n,attrs:{begin:0,size:[f,a]}}),jo(n,k);let w=h4({inputs:{x:A,indices:x},backend:n,attrs:{axis:1,batchDims:1}});jo(n,A);let C=u.slice(0,-1);C.push(a),k=x,x=ye({inputs:{x},attrs:{shape:C},backend:n}),jo(n,k);let E=w;return w=ye({inputs:{x:w},attrs:{shape:C},backend:n}),jo(n,E),[w,x]}var Lne={kernelName:ll,backendName:"webgl",kernelFunc:zne},Bne=class{constructor(e,t,n,s,r,a){this.variableNames=["Image","Transforms"],this.outputShape=a;let o=n==="nearest"?1:2,i;switch(s){case"constant":i=1;break;case"reflect":i=2;break;case"wrap":i=3;break;case"nearest":i=4;break;default:i=1;break}this.userCode=`
float mapCoord(float outCoord, float len) {
float inCoord = outCoord;
if(${i} == 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 (${i} == 3) {
if (inCoord < 0.0) {
if (len <= 1.0) {
inCoord = 0.0;
} else {
float sz = len - 1.0;
inCoord += len * (float(int(float(-inCoord / sz))) + 1.0);
}
} else if (inCoord > len - 1.0) {
if (len <= 1.0) {
inCoord = 0.0;
} else {
float sz = len - 1.0;
inCoord -= len * float(int(float(inCoord / sz)));
}
}
return clamp(inCoord, 0.0, len - 1.0);
} else if (${i} == 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(${e}));
if (${o} == 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 Wne(e){let{inputs:t,backend:n,attrs:s}=e,{image:r,transforms:a}=t,{interpolation:o,fillMode:i,fillValue:l,outputShape:u}=s,[c,d,h,p]=r.shape,[m,f]=u!=null?u:[d,h],A=[c,m,f,p],g=new Bne(d,h,o,i,l,A);return n.runWebGLProgram(g,[r,a],"float32")}var Vne={kernelName:ul,backendName:"webgl",kernelFunc:Wne};function Une(e){let{inputs:t,attrs:n,backend:s}=e,{axis:r}=n,{x:a}=t;jl(a,"unique"),console.warn("WARNING: ","UI might be locked temporarily as data is being downloaded");let o=s.readSync(a.dataId),{outputValues:i,outputShape:l,indices:u}=uX(o,r,a.shape,a.dtype);return[s.makeTensorInfo(l,a.dtype,i),s.makeTensorInfo([u.length],"int32",u)]}var Hne={kernelName:xh,backendName:"webgl",kernelFunc:Une};function Gne(e){let{inputs:t,backend:n,attrs:s}=e,{value:r}=t,{axis:a}=s;a<0&&(a+=r.shape.length);let o=r,i=o.shape.length,l=r.shape[a],u=new Array(i-1),c=0;for(let f=0;f<i;f++)f!==a&&(u[c++]=o.shape[f]);let d=[],h=new Array(i).fill(0),p=o.shape.slice();p[a]=1;let m=new Array(l);for(let f=0;f<m.length;f++){h[a]=f;let A=eu({inputs:{x:o},backend:n,attrs:{begin:h,size:p}}),g=ye({inputs:{x:A},backend:n,attrs:{shape:u}});m[f]=g,d.push(A)}return d.forEach(f=>n.disposeIntermediateTensorInfo(f)),m}var jne={kernelName:cl,backendName:"webgl",kernelFunc:Gne},qne=class{constructor(e,t){this.variableNames=["x","segmentIds"];let n=e.windowSize,s=e.batchSize,r=e.inSize,a=e.numSegments,o=a*Math.ceil(r/n);this.outputShape=[s,o];let i="0.0",l="sumValue",u=Math.floor(n/4)*4,c=n%4,d=`
sumValue += dot(values, segFilter);
`,h="";r%n>0&&(h=`
if (inIdx < 0 || inIdx >= ${r}) {
return initializationValue;
}
`);let p="";r%n>0&&(p=`
if (inIdx < 0 || inIdx >= ${r}) {
return -1.0;
}
`),this.userCode=`
const float initializationValue = ${i};
float getValue(int batch, int inIdx) {
${h}
return getX(batch, inIdx);
}
float getSegmentIdAtIndex(int inIdx) {
${p}
return getSegmentIds(inIdx);
}
void main() {
ivec2 coords = getOutputCoords();
int batch = coords[0];
int outIdx = coords[1];
int inOffset = int(floor(float(outIdx) / float(
${a})) * float(${n}));
int currentSeg = int(mod(float(outIdx), float(${a})));
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 + ${u};
if (${c===1}) {
vec4 values = vec4(
getValue(batch, inIdx),
initializationValue,
initializationValue,
initializationValue
);
int inIdxSeg = int(getSegmentIdAtIndex(inIdx));
vec4 segFilter = vec4(
int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,
0,
0,
0
);
${d}
} else if (${c===2}) {
vec4 values = vec4(
getValue(batch, inIdx),
getValue(batch, inIdx + 1),
initializationValue,
initializationValue
);
vec4 segFilter = vec4(
int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,
int(getSegmentIdAtIndex(inIdx + 1)) == currentSeg ? 1 : 0,
0,
0
);
${d}
} else if (${c===3}) {
vec4 values = vec4(
getValue(batch, inIdx),
getValue(batch, inIdx + 1),
getValue(batch, inIdx + 2),
initializationValue
);
vec4 segFilter = vec4(
int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,
int(getSegmentIdAtIndex(inIdx + 1)) == currentSeg ? 1 : 0,
int(getSegmentIdAtIndex(inIdx + 2)) == currentSeg ? 1 : 0,
0
);
${d}
}
setOutput(${l});
}
`}};function Xne(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,segmentIds:a}=t,{numSegments:o}=s,i=r.shape.length,l=[],u=0,c=$.getAxesPermutation([u],i),d=r;c!=null&&(d=wn({inputs:{x:r},backend:n,attrs:{perm:c}}),l.push(d),u=$.getInnerMostAxes(1,i)[0]);let h=$.segment_util.computeOutShape(d.shape,u,o),p=I.sizeFromShape([d.shape[u]]),m=ye({inputs:{x:d},backend:n,attrs:{shape:[-1,p]}});l.push(m);let f=Ch(r.dtype),A=(b,v,k,w,C)=>{let E=b.shape[0],P=b.shape[1],R=$.segment_util.segOpComputeOptimalWindowSize(P,C),_={windowSize:R,inSize:P,batchSize:E,numSegments:C},T=new qne(_,v),O=n.compileAndRun(T,[b,k],w);if(l.push(O),O.shape[1]===C)return O;let W=v4({backend:n,attrs:{start:0,stop:C,step:1,dtype:"float32"}}),j=I4({inputs:{x:W},backend:n,attrs:{reps:[P/R]}});return l.push(W),l.push(j),A(O,v,j,w,C)},g=A(m,"unsortedSegmentSum",a,f,o),y=ye({inputs:{x:g},backend:n,attrs:{shape:h}}),x=y;if(c!=null){l.push(y);let b=$.getUndoAxesPermutation(c);x=wn({inputs:{x},backend:n,attrs:{perm:b}})}return l.forEach(b=>n.disposeIntermediateTensorInfo(b)),x}var Kne={kernelName:Wu,backendName:"webgl",kernelFunc:Xne},Zne=[wQ,SQ,lK,cK,pK,AK,yK,vK,kK,SK,EK,_K,DK,MK,HK,BK,qK,YK,KK,tZ,sZ,aZ,uZ,AZ,yZ,IZ,CZ,RZ,FZ,UX,zZ,XZ,ZZ,VZ,eY,nY,JZ,aY,lY,dY,pY,mY,yY,IY,CY,bY,EY,$Y,DY,zY,VY,jY,KY,ZY,YY,QY,tJ,sJ,aJ,iJ,dJ,fJ,gJ,xJ,wJ,SJ,EJ,FJ,VX,OJ,PZ,zJ,WJ,HJ,GX,XJ,JJ,eQ,iQ,rQ,dQ,fQ,yQ,TQ,OQ,FQ,LQ,WQ,UQ,_Q,GQ,qQ,YQ,tee,aee,pee,ZX,mee,yee,vee,Iee,bZ,Tee,Eee,_ee,Dee,zee,qX,Bee,Wee,vZ,uee,Hee,Jee,Xee,JX,nte,ate,ute,hte,Ate,yte,vte,Ite,Cte,Ete,$te,Ote,zte,Wte,Hte,fZ,dee,qte,Kte,Yte,Qte,tne,sne,ane,ine,cne,pne,mne,gne,bne,wne,Ine,Cne,cee,aK,Ene,$ne,One,Lne,Vne,oK,Hne,jne,Kne,Nee];for(let e of Zne)Ao(e);var $n;(function(e){e[e.float32=0]="float32",e[e.int32=1]="int32",e[e.bool=2]="bool",e[e.string=3]="string",e[e.complex64=4]="complex64"})($n||($n={}));var Xc;(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"})(Xc||(Xc={}));var C4;function Yne(e){C4=e.wasm.cwrap(po,null,["number","array","number","number","array","number","number","number","number","number","number","number","number"])}function Jne(e){let{inputs:t,backend:n,attrs:s}=e,{a:r,b:a,bias:o,preluActivationWeights:i}=t;if(r.dtype!=="float32"||a.dtype!=="float32")throw new Error("_FusedMatMul for non non-float32 tensors not yet supported.");let{transposeA:l,transposeB:u,activation:c,leakyreluAlpha:d}=s,h=n.dataIdMap.get(r.dataId).id,p=n.dataIdMap.get(a.dataId).id,m=0;if(o!=null){let C=n.dataIdMap.get(o.dataId);if(C.shape.length!==1)throw new Error(`_FusedMatMul only supports rank-1 bias but got rank ${C.shape.length}.`);m=C.id}let f=i==null?0:n.dataIdMap.get(i.dataId).id,A=Xc[c];if(A==null)throw new Error(`${c} activation not yet supported for FusedConv2D in the wasm backend.`);let g=l?r.shape[2]:r.shape[1],y=u?a.shape[1]:a.shape[2],x=r.shape[0],b=n.makeOutput([x,g,y],r.dtype),v=n.dataIdMap.get(b.dataId).id,k=new Uint8Array(new Int32Array(r.shape).buffer),w=new Uint8Array(new Int32Array(a.shape).buffer);return C4(h,k,r.shape.length,p,w,a.shape.length,l,u,A,m,f,d||0,v),b}var Qne={kernelName:po,backendName:"wasm",setupFunc:Yne,kernelFunc:Jne};function un(e){let t;function n(r){t=r.wasm.cwrap(e,null,["number","number"])}function s(r){let{backend:a,inputs:{x:o}}=r,i=a.dataIdMap.get(o.dataId).id,l=a.makeOutput(o.shape,o.dtype),u=a.dataIdMap.get(l.dataId).id;return I.sizeFromShape(l.shape)===0||t(i,u),l}return{kernelName:e,backendName:"wasm",setupFunc:n,kernelFunc:s}}var ese=un(di);function kn(e,t,n){let s;function r(o){s=o.wasm.cwrap(e,null,["number","array","number","number","array","number","number","number"])}function a(o){let{backend:i,inputs:l}=o,{a:u,b:c}=l,d=i.dataIdMap.get(u.dataId).id,h=i.dataIdMap.get(c.dataId).id,p=n!=null?n:u.dtype,m=$.assertAndGetBroadcastShape(u.shape,c.shape),f=i.makeOutput(m,p);if(I.sizeFromShape(m)===0)return f;let A=new Uint8Array(new Int32Array(u.shape).buffer),g=new Uint8Array(new Int32Array(c.shape).buffer),y=i.dataIdMap.get(f.dataId).id,x=()=>s(d,A,u.shape.length,h,g,c.shape.length,$n[u.dtype],y);if(t&&u.dtype==="float32")return x(),f;let b=$.getBroadcastDims(u.shape,m),v=$.getBroadcastDims(c.shape,m),k=b.every((C,E)=>C===E),w=v.every((C,E)=>C===E);if(k&&w)return x(),f;throw new Error(`Broadcasting along outer dims is not yet supported for ${u.dtype} ${e}.`)}return{kernelName:e,backendName:"wasm",setupFunc:r,kernelFunc:a}}var tse=!0,nse=kn(Dr,tse),T4;function sse(e){T4=e.wasm.cwrap(ga,null,["array","number","number","number"])}function rse(e){let{inputs:t,backend:n}=e,s=n.makeOutput(t[0].shape,t[0].dtype);if(I.sizeFromShape(s.shape)===0)return s;let r=t.map(i=>n.dataIdMap.get(i.dataId).id),a=new Uint8Array(new Int32Array(r).buffer),o=n.dataIdMap.get(s.dataId).id;return T4(a,r.length,$n[s.dtype],o),s}var ase={kernelName:ga,backendName:"wasm",setupFunc:sse,kernelFunc:rse};function kf(e){let{inputs:{x:t},backend:n}=e,s=n.makeOutput(t.shape,t.dtype),r=n.typedArrayFromHeap(t);return n.typedArrayFromHeap(s).set(r),s}var ose={kernelName:Oa,backendName:"wasm",kernelFunc:kf},N4;function ise(e){N4=e.wasm.cwrap(ho,null,["number","array","number","number","number","array","number"])}function su(e){let{inputs:t,backend:n,attrs:s}=e,[r,a]=use(t.x.shape,s.perm),o=!0;for(let m=0;m<a.length;m++)a[m]!==m&&(o=!1);let i=lse(t.x.shape,s.perm),l={dataId:t.x.dataId,shape:r,dtype:t.x.dtype};if(o){let m=kf({inputs:t,backend:n});return m.shape=i,m}let u=n.makeOutput(i,l.dtype),c=n.dataIdMap.get(l.dataId).id,d=n.dataIdMap.get(u.dataId).id,h=new Uint8Array(new Int32Array(a).buffer),p=new Uint8Array(new Int32Array(l.shape).buffer);return N4(c,p,l.shape.length,$n[l.dtype],d,h,a.length),u}function lse(e,t){let n=new Array(e.length);for(let s=0;s<n.length;s++)n[s]=e[t[s]];return n}function use(e,t){let n=[],s=[];for(let r=0;r<e.length;++r)e[r]!==1&&n.push(e[r]),e[t[r]]!==1&&s.push(t[r]);for(let r=0;r<s.length;++r){let a=-1;for(let o=0;o<s.length;++o)s[o]>=r&&(a===-1||s[a]>s[o])&&(a=o);s[a]=r}return[n,s]}var cse={kernelName:ho,backendName:"wasm",kernelFunc:su,setupFunc:ise};function aa(e,t,n){let s=e.shape,r=e.shape.length,a=I.parseAxisParam(t,s),o=a,i=$.getAxesPermutation(o,r),l=null,u=!1;if(i!=null){let c=new Array(r);for(let p=0;p<c.length;p++)c[p]=s[i[p]];o=$.getInnerMostAxes(o.length,r),l=su({inputs:{x:e},attrs:{perm:i},backend:n});let d=n.dataIdMap.get(e.dataId).id;n.dataIdMap.get(l.dataId).id!==d&&(u=!0)}return{transposed:l,originalAxes:a,axes:o,inputWasTransposed:u}}var E4;function dse(e){E4=e.wasm.cwrap(fi,null,["number, number, number"])}function hse(e){let{backend:t,inputs:n,attrs:s}=e,{axis:r,keepDims:a}=s,{x:o}=n,l=t.dataIdMap.get(o.dataId).id,u=o,{transposed:c,axes:d,originalAxes:h,inputWasTransposed:p}=aa(o,r,t);if(p){let x=t.dataIdMap.get(c.dataId).id;u=c,l=x}let m=u.shape.length;$.assertAxesAreInnerMostDims("all",d,m);let[f,A]=$.computeOutAndReduceShapes(u.shape,d),g=I.sizeFromShape(A),y=t.makeOutput(f,o.dtype);if(I.sizeFromShape(u.shape)!==0){let x=t.dataIdMap.get(y.dataId).id;E4(l,g,x)}if(p&&t.disposeData(c.dataId),a){let x=$.expandShapeToKeepDim(y.shape,h);y.shape=x}return y}var pse={kernelName:fi,backendName:"wasm",setupFunc:dse,kernelFunc:hse},R4;function fse(e){R4=e.wasm.cwrap(mi,null,["number, number, number"])}function mse(e){let{backend:t,inputs:n,attrs:s}=e,{axis:r,keepDims:a}=s,{x:o}=n,l=t.dataIdMap.get(o.dataId).id,u=o,{transposed:c,axes:d,originalAxes:h,inputWasTransposed:p}=aa(o,r,t);if(p){let x=t.dataIdMap.get(c.dataId).id;u=c,l=x}let m=u.shape.length;$.assertAxesAreInnerMostDims("any",d,m);let[f,A]=$.computeOutAndReduceShapes(u.shape,d),g=I.sizeFromShape(A),y=t.makeOutput(f,o.dtype);if(I.sizeFromShape(u.shape)!==0){let x=t.dataIdMap.get(y.dataId).id;R4(l,g,x)}if(p&&t.disposeData(c.dataId),a){let x=$.expandShapeToKeepDim(y.shape,h);y.shape=x}return y}var Ase={kernelName:mi,backendName:"wasm",setupFunc:fse,kernelFunc:mse},_4;function gse(e){_4=e.wasm.cwrap(ya,null,["number","number","number","number","number"])}function yse(e){let{backend:t,inputs:n,attrs:s}=e,{axis:r}=s,{x:a}=n,o=t.dataIdMap.get(a.dataId).id,i=o,l=a,{transposed:u,axes:c,inputWasTransposed:d}=aa(a,r,t);if(d){let g=t.dataIdMap.get(u.dataId).id;g!==o&&(l=u,i=g)}let h=l.shape.slice(0,-1),p=t.makeOutput(h,"int32"),m=t.dataIdMap.get(p.dataId).id,f=I.sizeFromShape(p.shape),A=l.shape[c[0]];return _4(i,$n[l.dtype],f,A,m),d&&t.disposeData(u.dataId),p}var xse={kernelName:ya,backendName:"wasm",kernelFunc:yse,setupFunc:gse},$4;function bse(e){$4=e.wasm.cwrap(xa,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function vse(e){let{inputs:t,attrs:n,backend:s}=e,r=t.x,a=s.dataIdMap.get(r.dataId).id,{filterSize:o,strides:i,pad:l,dimRoundingMode:u}=n,c=$.computePool2DInfo(r.shape,o,i,1,l,u),d=c.filterHeight,h=c.filterWidth,p=c.padInfo.top,m=c.padInfo.right,f=c.padInfo.bottom,A=c.padInfo.left,g=c.strideHeight,y=c.strideWidth,x=c.inChannels;if(c.dataFormat!=="channelsLast")throw new Error(`wasm backend does not support dataFormat:'${c.dataFormat}'. Please use 'channelsLast'.`);if(c.dilationWidth!==1||c.dilationHeight!==1)throw new Error(`was backend only supports average pooling with dilation = [1, 1], got [${c.dilationHeight}, ${c.dilationWidth}].`);let b=s.makeOutput(c.outShape,"float32"),v=s.dataIdMap.get(b.dataId).id;return $4(a,r.shape[0],r.shape[1],r.shape[2],d,h,p,m,f,A,g,y,x,v),b}var wse={kernelName:xa,backendName:"wasm",setupFunc:bse,kernelFunc:vse};function Fn(e){let{inputs:t,attrs:n}=e,{x:s}=t,{shape:r}=n,a=I.sizeFromShape(s.shape),o=I.inferFromImplicitShape(r,a);return I.assert(a===I.sizeFromShape(o),()=>`new shape: ${o}, old shape: ${s.shape}. New shape and old shape must have the same number of elements.`),e.backend.incRef(s.dataId),{dataId:s.dataId,shape:o,dtype:s.dtype}}var kse={kernelName:Yi,backendName:"wasm",kernelFunc:Fn},F4;function Ise(e){F4=e.wasm.cwrap(ba,null,["number","array","number","number","array","number","number","number","number"])}function Sse(e){let{inputs:t,backend:n,attrs:s}=e,{a:r,b:a}=t,{transposeA:o,transposeB:i}=s;if(r.dtype!=="float32"||a.dtype!=="float32")throw new Error("BatchMatMul for non non-float32 tensors not yet supported.");let l=r.shape.length,u=a.shape.length,c=o?r.shape[l-2]:r.shape[l-1],d=i?a.shape[u-1]:a.shape[u-2],h=o?r.shape[l-1]:r.shape[l-2],p=i?a.shape[u-2]:a.shape[u-1],m=r.shape.slice(0,-2),f=a.shape.slice(0,-2),A=I.sizeFromShape(m),g=I.sizeFromShape(f),y=A===g||A===1||g===1;I.assert(l>=2&&u>=2&&y,()=>`Error in matMul: the input batch dimensions must either be the same or at least one input batch dimension must be 1. Got input batch dimensions of (${m}) and (${f}).`);let b=(A>g?r.shape.slice(0,-2):a.shape.slice(0,-2)).concat([h,p]);I.assert(c===d,()=>`Error in matMul: inner shapes (${c}) and (${d}) of Tensors with shapes ${r.shape} and ${a.shape} and transposeA=${o} and transposeB=${i} must match.`);let v=o?[A,c,h]:[A,h,c],k=i?[g,p,d]:[g,d,p],w=Fn({inputs:{x:r},backend:n,attrs:{shape:v}}),C=Fn({inputs:{x:a},backend:n,attrs:{shape:k}}),E=n.dataIdMap.get(w.dataId).id,P=n.dataIdMap.get(C.dataId).id,R=o?w.shape[2]:w.shape[1],_=i?C.shape[1]:C.shape[2],T=Math.max(A,g),O=n.makeOutput([T,R,_],w.dtype),W=n.dataIdMap.get(O.dataId).id,j=new Uint8Array(new Int32Array(w.shape).buffer),q=new Uint8Array(new Int32Array(C.shape).buffer);return F4(E,j,w.shape.length,P,q,C.shape.length,o,i,W),n.disposeData(w.dataId),n.disposeData(C.dataId),O.shape=b,O}var Cse={kernelName:ba,backendName:"wasm",setupFunc:Ise,kernelFunc:Sse};function Kc(e){let{inputs:{x:t},attrs:{begin:n,size:s},backend:r}=e,[a,o]=An.parseSliceParams(t,n,s),i=An.isSliceContinous(t.shape,a,o),l=r.readSync(t.dataId),u=r.makeOutput(o,t.dtype),c=I.computeStrides(t.shape),d=r.dataIdMap.get(u.dataId);if(i){let m=An.computeFlatOffset(a,c);return t.dtype==="string"?d.stringBytes=l.slice(m,m+I.sizeFromShape(o)):r.typedArrayFromHeap(u).set(l.subarray(m,m+I.sizeFromShape(o))),u}if(t.dtype==="string"){let m=Jp(l,a,o,t.shape,t.dtype);return d.stringBytes=m,u}let h=r.typedArrayFromHeap(u),p=t.shape.length;if(p===2)Tse(l,c[0],h,a,o);else if(p===3)Nse(l,c[0],c[1],h,a,o);else if(p===4)Ese(l,c[0],c[1],c[2],h,a,o);else{let m=Jp(l,a,o,t.shape,t.dtype);h.set(m)}return u}function Tse(e,t,n,s,r){let a=0,o=s[0],i=s[1],l=o+r[0];for(let u=o;u<l;u++){let c=u*t+i;n.set(e.subarray(c,c+r[1]),a),a+=r[1]}}function Nse(e,t,n,s,r,a){let o=0,i=r[0],l=r[1],u=r[2],c=i+a[0],d=l+a[1];for(let h=i;h<c;h++)for(let p=l;p<d;p++){let m=h*t+p*n+u;s.set(e.subarray(m,m+a[2]),o),o+=a[2]}}function Ese(e,t,n,s,r,a,o){let i=0,l=a[0],u=a[1],c=a[2],d=l+o[0],h=u+o[1],p=c+o[2],m=a[3];for(let f=l;f<d;f++)for(let A=u;A<h;A++)for(let g=c;g<p;g++){let y=f*t+A*n+g*s+m;r.set(e.subarray(y,y+o[3]),i),i+=o[3]}}var Rse={kernelName:tl,backendName:"wasm",kernelFunc:Kc};function _se(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{blockShape:a,crops:o}=s,i=a.reduce((g,y)=>g*y),l=$.getReshaped(r.shape,a,i),u=$.getPermuted(l.length,a.length),c=$.getReshapedPermuted(r.shape,a,i),d=$.getSliceBeginCoords(o,a.length),h=$.getSliceSize(c,o,a.length),p=Fn({inputs:{x:r},backend:n,attrs:{shape:l}}),m=su({inputs:{x:p},backend:n,attrs:{perm:u}}),f=Fn({inputs:{x:m},backend:n,attrs:{shape:c}}),A=Kc({inputs:{x:f},backend:n,attrs:{begin:d,size:h}});return n.disposeData(p.dataId),n.disposeData(m.dataId),n.disposeData(p.dataId),A}var $se={kernelName:vi,backendName:"wasm",kernelFunc:_se};function If(e){let{inputs:{x:t},attrs:{dtype:n},backend:s}=e,r=s.makeOutput(t.shape,n),a=s.typedArrayFromHeap(t);return s.typedArrayFromHeap(r).set(a),r}var Fse={kernelName:va,backendName:"wasm",kernelFunc:If},Dse=un(wa),D4;function Ose(e){D4=e.wasm.cwrap(Or,null,["number","number","number","number"])}function Pse(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{clipValueMin:a,clipValueMax:o}=s,i=n.dataIdMap.get(r.dataId).id,l=n.makeOutput(r.shape,r.dtype),u=n.dataIdMap.get(l.dataId).id;return D4(i,a,o,u),l}var Mse={kernelName:Or,backendName:"wasm",setupFunc:Ose,kernelFunc:Pse};function O4(e){let{inputs:t,backend:n}=e,s=I.parseAxisParam(e.attrs.axis,t[0].shape)[0],r=$.computeOutShape(t.map(p=>p.shape),s),a=t.filter(p=>I.sizeFromShape(p.shape)>0);if(a.length===1)return kf({inputs:{x:a[0]},backend:n});let o=n.makeOutput(r,t[0].dtype);if(I.sizeFromShape(r)===0)return o;let i=a.map(p=>p.shape);if($.assertParamsConsistent(i,s),a[0].dtype==="string"){let p=a.map(x=>{let b=I.sizeFromShape(x.shape.slice(s));return 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Bse(e){let{inputs:t,attrs:n,backend:s}=e,{x:r,filter:a}=t,o=s.dataIdMap.get(r.dataId).id,i=s.dataIdMap.get(a.dataId).id,{strides:l,dilations:u,pad:c,dimRoundingMode:d,dataFormat:h}=n,p=$.convertConv2DDataFormat(h),m=$.computeConv2DInfo(r.shape,a.shape,l,u,c,d,!1,p),f=m.filterHeight,A=m.filterWidth,g=m.padInfo.top,y=m.padInfo.right,x=m.padInfo.bottom,b=m.padInfo.left,v=m.dilationHeight,k=m.dilationWidth,w=m.strideHeight,C=m.strideWidth,E=m.inChannels,P=m.outChannels,R=m.padInfo.type==="SAME"?1:0;if(m.dataFormat!=="channelsLast")throw new Error(`wasm backend Conv2D does not support dataFormat:'${m.dataFormat}'. Please use 'channelsLast'.`);let _=s.makeOutput(m.outShape,"float32"),T=s.dataIdMap.get(_.dataId).id;return P4(o,r.shape[0],r.shape[1],r.shape[2],i,f,A,g,y,x,b,R,v,k,w,C,E,P,T),_}var Wse={kernelName:ka,backendName:"wasm",setupFunc:Lse,kernelFunc:Bse},M4;function Vse(e){M4=e.wasm.cwrap(Ia,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function Use(e){let{backend:t,inputs:n,attrs:s}=e,{dy:r,filter:a}=n,{strides:o,pad:i,dataFormat:l,dimRoundingMode:u,inputShape:c}=s,d=1,h=$.convertConv2DDataFormat(l),p=$.computeConv2DInfo(c,a.shape,o,d,i,u,!1,h),{batchSize:m,filterHeight:f,filterWidth:A,inChannels:g,inHeight:y,inWidth:x,outChannels:b,outHeight:v,outWidth:k,strideHeight:w,strideWidth:C}=p,E=f-1-p.padInfo.top,P=A-1-p.padInfo.left,R=p.dataFormat==="channelsLast",_=I.computeStrides(p.inShape),T=I.computeStrides(r.shape),[O,W,j]=I.computeStrides(a.shape),q=_[0],X=R?_[1]:_[2],Q=R?_[2]:1,ne=R?1:_[1],te=T[0],se=R?T[1]:T[2],J=R?T[2]:1,ie=R?1:T[1],le=t.makeOutput(p.inShape,"float32"),he=t.dataIdMap.get(le.dataId).id,ge=t.dataIdMap.get(r.dataId).id,Ce=t.dataIdMap.get(a.dataId).id;return M4(ge,Ce,m,f,A,y,x,g,v,k,b,w,C,E,P,O,W,j,q,X,Q,ne,te,se,J,ie,he),le}var Hse={kernelName:Ia,backendName:"wasm",setupFunc:Vse,kernelFunc:Use},Gse=un(Sa),jse=un(Ca),$1;(function(e){e[e.bilinear=0]="bilinear",e[e.nearest=1]="nearest"})($1||($1={}));var z4;function qse(e){z4=e.wasm.cwrap(ki,null,["number","number","number","number","array","number","number","number","number","number"])}function Xse(e){let{backend:t,inputs:n,attrs:s}=e,{method:r,extrapolationValue:a,cropSize:o}=s,{image:i,boxes:l,boxInd:u}=n,c=l.shape[0],[d,h]=o,p=[c,d,h,i.shape[3]],m=t.dataIdMap.get(i.dataId),f;i.dtype!=="float32"&&(f=If({backend:t,inputs:{x:i},attrs:{dtype:"float32"}}),m=t.dataIdMap.get(f.dataId));let A=m.id,g=t.dataIdMap.get(l.dataId).id,y=t.dataIdMap.get(u.dataId).id,x=t.makeOutput(p,"float32"),b=t.dataIdMap.get(x.dataId).id,v=new Uint8Array(new Int32Array(i.shape).buffer);return z4(A,g,y,c,v,d,h,$1[r],a,b),f!=null&&t.disposeData(f.dataId),x}var Kse={kernelName:ki,backendName:"wasm",setupFunc:qse,kernelFunc:Xse},L4;function Zse(e){L4=e.wasm.cwrap(Ta,null,["number","number","number","number","number","number"])}function Yse(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,exclusive:o,reverse:i}=s,l=r.shape.length;I.assert(r.dtype==="float32"||r.dtype==="int32",()=>`cumsum does not support ${r.dtype} tensors in the WASM backend`);let u=$.getAxesPermutation([a],l),c=r;u!==null&&(c=su({inputs:{x:r},attrs:{perm:u},backend:n}));let d=$.getInnerMostAxes(1,l)[0];$.assertAxesAreInnerMostDims("cumsum",[d],l);let h=n.makeOutput(c.shape,c.dtype),p=c.shape[d],m=n.dataIdMap.get(c.dataId).id,f=n.dataIdMap.get(h.dataId).id;L4(m,o?1:0,i?1:0,p,f,$n[r.dtype]);let A=h;if(u!==null){let g=$.getUndoAxesPermutation(u);A=su({inputs:{x:h},attrs:{perm:g},backend:n}),n.disposeData(c.dataId),n.disposeData(h.dataId)}return A}var Jse={kernelName:Ta,backendName:"wasm",setupFunc:Zse,kernelFunc:Yse},B4;function Qse(e){B4=e.wasm.cwrap(Ii,null,["number","number","number","array","number","array","array","number","number"])}function ere(e){let{backend:t,inputs:n,attrs:s}=e,{x:r}=n,{blockSize:a,dataFormat:o}=s;I.assert(a>1,()=>`blockSize should be > 1 for depthToSpace, but was: ${a}`);let i=r.shape[0],l=o==="NHWC"?r.shape[1]:r.shape[2],u=o==="NHWC"?r.shape[2]:r.shape[3],c=o==="NHWC"?r.shape[3]:r.shape[1],d=l*a,h=u*a,p=c/(a*a),m=o==="NHWC"?[i,d,h,p]:[i,p,d,h],f=t.makeOutput(m,"float32"),g=t.dataIdMap.get(r.dataId).id,y=new Uint8Array(new Int32Array(I.computeStrides(r.shape)).buffer),x=new Uint8Array(new Int32Array(m).buffer),b=new Uint8Array(new Int32Array(I.computeStrides(m)).buffer),v=t.dataIdMap.get(f.dataId).id;return B4(g,a,o==="NHWC"?1:0,y,r.shape.length-1,x,b,m.length,v),f}var tre={kernelName:Ii,backendName:"wasm",setupFunc:Qse,kernelFunc:ere},W4;function nre(e){W4=e.wasm.cwrap(Na,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function sre(e){let{inputs:t,attrs:n,backend:s}=e,{x:r,filter:a}=t,o=s.dataIdMap.get(r.dataId).id,i=s.dataIdMap.get(a.dataId).id,{strides:l,dilations:u,pad:c,dimRoundingMode:d}=n,h=u==null?[1,1]:u,p=$.computeConv2DInfo(r.shape,a.shape,l,h,c,d,!0),m=p.filterHeight,f=p.filterWidth,A=p.padInfo.top,g=p.padInfo.right,y=p.padInfo.bottom,x=p.padInfo.left,b=p.dilationHeight,v=p.dilationWidth,k=p.strideHeight,w=p.strideWidth,C=p.inChannels,E=p.outChannels,P=p.padInfo.type==="SAME"?1:0;if(p.dataFormat!=="channelsLast")throw new Error(`wasm backend DepthwiseConv2dNative does not support dataFormat:'${p.dataFormat}'. Please use 'channelsLast'.`);let R=s.makeOutput(p.outShape,"float32"),_=s.dataIdMap.get(R.dataId).id;return W4(o,r.shape[0],r.shape[1],r.shape[2],i,m,f,A,g,y,x,P,b,v,k,w,C,E,_),R}var rre={kernelName:Na,backendName:"wasm",setupFunc:nre,kernelFunc:sre},are=!1,ore=kn(Ti,are,"bool"),ire=un(Ra);function F1(e){let{inputs:t,attrs:n,backend:s}=e,{input:r}=t,{dim:a}=n,o=r.shape.length,i=r.shape.slice(),l=a;return a<0&&(I.assert(-(o+1)<=a,()=>`Axis must be in the interval [${-(o+1)}, ${o}]`),l=o+a+1),i.splice(l,0,1),Fn({inputs:{x:r},backend:s,attrs:{shape:i}})}var lre={kernelName:Ni,backendName:"wasm",kernelFunc:F1};function ure(e){let{attrs:{shape:t,value:n,dtype:s},backend:r}=e,a=r.makeOutput(t,s);return r.typedArrayFromHeap(a).fill(n),a}var cre={kernelName:Fu,backendName:"wasm",kernelFunc:ure},V4;function dre(e){V4=e.wasm.cwrap(Ri,null,["number","number","number","number","number","number"])}function hre(e){let{inputs:t,backend:n}=e,{image:s}=t,r=n.makeOutput(s.shape,s.dtype),a=n.dataIdMap.get(s.dataId).id,o=n.dataIdMap.get(r.dataId).id,[i,l,u,c]=s.shape;return V4(a,i,l,u,c,o),r}var pre={kernelName:Ri,backendName:"wasm",kernelFunc:hre,setupFunc:dre},fre=un(_a),mre=!1,Are=kn($a,mre),U4;function gre(e){U4=e.wasm.cwrap(Fa,null,["number","number","number","number","number","number","number"])}function yre(e){let{backend:t,inputs:n,attrs:s}=e,{varianceEpsilon:r}=s,{x:a,mean:o,variance:i,offset:l,scale:u}=n,c=t.dataIdMap.get(a.dataId).id,d=t.dataIdMap.get(o.dataId).id,h=t.dataIdMap.get(i.dataId).id,p=l!=null?t.dataIdMap.get(l.dataId).id:0,m=u!=null?t.dataIdMap.get(u.dataId).id:0,f=t.makeOutput(a.shape,a.dtype);if(I.sizeFromShape(a.shape)===0)return f;let A=t.dataIdMap.get(f.dataId).id;return U4(c,d,h,p,m,r,A),f}var xre={kernelName:Fa,backendName:"wasm",setupFunc:gre,kernelFunc:yre},H4;function bre(e){H4=e.wasm.cwrap(fo,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 vre(e){let{inputs:t,attrs:n,backend:s}=e,{x:r,filter:a,bias:o,preluActivationWeights:i}=t,{strides:l,pad:u,dilations:c,dataFormat:d,dimRoundingMode:h,activation:p,leakyreluAlpha:m}=n,f=$.computeConv2DInfo(r.shape,a.shape,l,c,u,h),A=Xc[p];if(A==null)throw new Error(`${p} activation not yet supported for FusedConv2D in the wasm backend.`);let g=s.dataIdMap.get(r.dataId).id,y=s.dataIdMap.get(a.dataId).id,x=f.outChannels,b=0;if(o!=null){let J=s.dataIdMap.get(o.dataId);if(J.shape.length!==1)throw new Error(`FusedConv2D only supports rank-1 bias but got rank ${J.shape.length}.`);if(J.shape[0]!==x)throw new Error(`FusedConv2D bias shape (${J.shape}) does not match the number of output channels (${x})`);b=J.id}let v=f.filterHeight,k=f.filterWidth,w=f.padInfo.top,C=f.padInfo.right,E=f.padInfo.bottom,P=f.padInfo.left,R=f.dilationHeight,_=f.dilationWidth,T=f.strideHeight,O=f.strideWidth,W=f.inChannels,j=f.padInfo.type==="SAME"?1:0,q=f.batchSize,X=f.inHeight,Q=f.inWidth;if(d!=="NHWC")throw new Error(`wasm backend FusedConv2D does not support dataFormat:'${d}'. 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fie=[127,234,132,58,172,150,149,148,152,377,378,379,397,288,361,454,356,70,63,105,66,107,336,296,334,293,300,168,6,195,4,98,97,2,326,327,33,160,158,133,153,144,362,385,387,263,373,380,57,40,37,0,267,270,287,321,314,17,84,91,78,81,13,311,308,402,14,178],mie=[33,133,362,263,1,62,308,159,145,386,374,6,102,331,2,13,14,70,105,107,336,334,300,54,10,284,50,280,234,454,58,288,152],Aie=[33,133,362,263,1,78,308],ile=fie.map(e=>td[e]),lle=mie.map(e=>td[e]),ule=Aie.map(e=>td[e]);var W1=or.leftEyeLower0,V1=or.rightEyeLower0,ou={leftBounds:[W1[0],W1[W1.length-1]],rightBounds:[V1[0],V1[V1.length-1]]},Rf={count:468,mouth:13,symmetryLine:[13,or.midwayBetweenEyes[0]]},Ok={leftEye:0,rightEye:1,nose:2,mouth:3,leftEar:4,rightEar:5,symmetryLine:[3,2]},iu={upperCenter:3,lowerCenter:4,index:71,numCoordinates:76};function _f(e,t,n,s){for(let r=0;r<B1.length;r++){let{key:a,indices:o}=B1[r],i=or[`${n}${a}`];if(!s||s.includes(a))for(let l=0;l<o.length;l++){let u=o[l];e[i[l]]=[t[u][0],t[u][1],(t[u][2]+e[i[l]][2])/2]}}}var U1=class{constructor(t,n,s){var r,a;this.storedBoxes=[],this.boundingBoxDetector=t,this.meshDetector=n,this.irisModel=s,this.boxSize=((r=t==null?void 0:t.model)==null?void 0:r.inputs[0].shape[2])||0,this.meshSize=(n==null?void 0:n.inputs[0].shape[2])||((a=t==null?void 0:t.model)==null?void 0:a.inputs[0].shape[2]),this.irisSize=(s==null?void 0:s.inputs[0].shape[1])||0,this.irisEnlarge=2.3,this.skipped=0,this.detectedFaces=0}transformRawCoords(t,n,s,r){let a=ed({startPoint:n.startPoint,endPoint:n.endPoint}),o=t.map(d=>[a[0]/this.meshSize*(d[0]-this.meshSize/2),a[1]/this.meshSize*(d[1]-this.meshSize/2),d[2]]),i=s!==0?Ef(s,[0,0]):Nf,l=s!==0?o.map(d=>[...Rk(d,i),d[2]]):o,u=s!==0?Ek(r):Nf,c=[...ru({startPoint:n.startPoint,endPoint:n.endPoint}),1];return l.map(d=>[Math.round(d[0]+oa(c,u[0])),Math.round(d[1]+oa(c,u[1])),Math.round(d[2])])}getLeftToRightEyeDepthDifference(t){let n=t[ou.leftBounds[0]][2],s=t[ou.rightBounds[0]][2];return n-s}getEyeBox(t,n,s,r,a=!1){let o=Tf(Cf(z1([t[s],t[r]]),this.irisEnlarge)),i=ed(o),l=Re.cropAndResize(n,[[o.startPoint[1]/this.meshSize,o.startPoint[0]/this.meshSize,o.endPoint[1]/this.meshSize,o.endPoint[0]/this.meshSize]],[0],[this.irisSize,this.irisSize]);return a&&ns.flags.IS_BROWSER&&(l=Re.flipLeftRight(l)),{box:o,boxSize:i,crop:l}}getEyeCoords(t,n,s,r=!1){let a=[];for(let o=0;o<iu.numCoordinates;o++){let i=t[o*3],l=t[o*3+1],u=t[o*3+2];a.push([(r?1-i/this.irisSize:i/this.irisSize)*s[0]+n.startPoint[0],l/this.irisSize*s[1]+n.startPoint[1],u])}return{rawCoords:a,iris:a.slice(iu.index)}}getAdjustedIrisCoords(t,n,s){let r=t[or[`${s}EyeUpper0`][iu.upperCenter]][2],a=t[or[`${s}EyeLower0`][iu.lowerCenter]][2],o=(r+a)/2;return n.map((i,l)=>{let u=o;return l===2?u=r:l===4&&(u=a),[i[0],i[1],u]})}async predict(t,n){let s=!1,r;if((this.skipped===0||this.skipped>n.face.detector.skipFrames||!n.face.mesh.enabled||!n.skipFrame)&&(r=await this.boundingBoxDetector.getBoundingBoxes(t,n),this.skipped=0),n.skipFrame&&this.skipped++,!n.skipFrame||r&&r.boxes&&(!n.face.mesh.enabled||r.boxes.length!==this.detectedFaces&&this.detectedFaces!==n.face.detector.maxDetected)){this.storedBoxes=[],this.detectedFaces=0;for(let o of r.boxes)this.storedBoxes.push({startPoint:o.box.startPoint.dataSync(),endPoint:o.box.endPoint.dataSync(),landmarks:o.landmarks.arraySync(),confidence:o.confidence});this.storedBoxes.length>0&&(s=!0)}if(s){if(!r||!r.boxes||r.boxes.length===0)return this.storedBoxes=[],this.detectedFaces=0,null;for(let o=0;o<this.storedBoxes.length;o++){let i=Sk({startPoint:this.storedBoxes[o].startPoint,endPoint:this.storedBoxes[o].endPoint},r.scaleFactor),l=Cf(i),u=Tf(l),c=this.storedBoxes[o].landmarks,d=this.storedBoxes[o].confidence;this.storedBoxes[o]={...u,confidence:d,landmarks:c}}}r&&r.boxes&&r.boxes.forEach(o=>{Z(o.box.startPoint),Z(o.box.endPoint),Z(o.landmarks)});let a=H(()=>this.storedBoxes.map((o,i)=>{let l,u=0,c;if(n.face.detector.rotation&&n.face.mesh.enabled&&ns.flags.IS_BROWSER){let[x,b]=o.landmarks.length>=Rf.count?Rf.symmetryLine:Ok.symmetryLine;u=L1(o.landmarks[x],o.landmarks[b]);let v=ru({startPoint:o.startPoint,endPoint:o.endPoint}),k=[v[0]/t.shape[2],v[1]/t.shape[1]],w=Re.rotateWithOffset(t,u,0,k);c=Ef(-u,v),n.face.mesh.enabled?l=ce(au({startPoint:o.startPoint,endPoint:o.endPoint},w,[this.meshSize,this.meshSize]),255):l=ce(au({startPoint:o.startPoint,endPoint:o.endPoint},w,[this.boxSize,this.boxSize]),255)}else{c=Nf;let x=t.clone();n.face.mesh.enabled?l=ce(au({startPoint:o.startPoint,endPoint:o.endPoint},x,[this.meshSize,this.meshSize]),255):l=ce(au({startPoint:o.startPoint,endPoint:o.endPoint},x,[this.boxSize,this.boxSize]),255)}if(!n.face.mesh.enabled)return{mesh:[],box:o,faceConfidence:null,boxConfidence:o.confidence,confidence:o.confidence,image:l};let[,d,h]=this.meshDetector.execute(l),p=d.dataSync()[0];if(p<n.face.detector.minConfidence)return this.storedBoxes[i].confidence=p,null;let f=U(h,[-1,3]).arraySync();if(n.face.iris.enabled){let{box:x,boxSize:b,crop:v}=this.getEyeBox(f,l,ou.leftBounds[0],ou.leftBounds[1],!0),{box:k,boxSize:w,crop:C}=this.getEyeBox(f,l,ou.rightBounds[0],ou.rightBounds[1]),P=this.irisModel.predict(dt([v,C])).dataSync(),R=P.slice(0,iu.numCoordinates*3),{rawCoords:_,iris:T}=this.getEyeCoords(R,x,b,!0),O=P.slice(iu.numCoordinates*3),{rawCoords:W,iris:j}=this.getEyeCoords(O,k,w),q=this.getLeftToRightEyeDepthDifference(f);Math.abs(q)<30?(_f(f,_,"left",null),_f(f,W,"right",null)):q<1?_f(f,_,"left",["EyeUpper0","EyeLower0"]):_f(f,W,"right",["EyeUpper0","EyeLower0"]);let X=this.getAdjustedIrisCoords(f,T,"left"),Q=this.getAdjustedIrisCoords(f,j,"right");f=f.concat(X).concat(Q)}let A=this.transformRawCoords(f,o,u,c),g=o.confidence;if(o=Cf(z1(A),1.5),o.confidence=g,n.face.detector.rotation&&n.face.mesh.enabled&&n.face.description.enabled&&ns.flags.IS_BROWSER){let[x,b]=o.landmarks.length>=Rf.count?Rf.symmetryLine:Ok.symmetryLine;u=L1(o.landmarks[x],o.landmarks[b]);let v=ru({startPoint:o.startPoint,endPoint:o.endPoint}),k=[v[0]/t.shape[2],v[1]/t.shape[1]],w=Re.rotateWithOffset(ue(t,"float32"),u,0,k);c=Ef(-u,v),l=ce(au({startPoint:o.startPoint,endPoint:o.endPoint},w,[this.meshSize,this.meshSize]),255)}let y={mesh:A,box:o,faceConfidence:p,boxConfidence:o.confidence,image:l};return this.storedBoxes[i]={...Tf(o),confidence:o.confidence,faceConfidence:p},y}));return n.face.mesh.enabled&&(this.storedBoxes=this.storedBoxes.filter(o=>o.confidence>n.face.detector.minConfidence)),this.detectedFaces=a.length,a}};var Rt=[null,null,null],H1;async function Pk(e,t){let n=await H1.predict(e,t),s=[],r=0;for(let a of n||[]){if(!a||a.isDisposedInternal)continue;let o=a.mesh.map(c=>[c[0]/(e.shape[2]||0),c[1]/(e.shape[1]||0),c[2]/H1.meshSize]),i={};if(a.mesh&&a.mesh.length>0)for(let c of Object.keys(or))i[c]=or[c].map(d=>a.mesh[d]);let l=a.box?[Math.trunc(Math.max(0,a.box.startPoint[0])),Math.trunc(Math.max(0,a.box.startPoint[1])),Math.trunc(Math.min(e.shape[2]||0,a.box.endPoint[0])-Math.max(0,a.box.startPoint[0])),Math.trunc(Math.min(e.shape[1]||0,a.box.endPoint[1])-Math.max(0,a.box.startPoint[1]))]:[0,0,0,0],u=a.box?[a.box.startPoint[0]/(e.shape[2]||0),a.box.startPoint[1]/(e.shape[1]||0),(a.box.endPoint[0]-a.box.startPoint[0])/(e.shape[2]||0),(a.box.endPoint[1]-a.box.startPoint[1])/(e.shape[1]||0)]:[0,0,0,0];s.push({id:r++,score:Math.round(100*a.faceConfidence||100*a.boxConfidence||0)/100,boxScore:Math.round(100*a.boxConfidence)/100,faceScore:Math.round(100*a.faceConfidence)/100,box:l,boxRaw:u,mesh:a.mesh,meshRaw:o,annotations:i,image:a.image,tensor:a.image}),a.coords&&Z(a.coords)}return s}async function G1(e){return!Rt[0]&&e.face.enabled||!Rt[1]&&e.face.mesh.enabled||!Rt[2]&&e.face.iris.enabled?(Rt=await Promise.all([!Rt[0]&&e.face.enabled?Dk(e):null,!Rt[1]&&e.face.mesh.enabled?ht(pt(e.modelBasePath,e.face.mesh.modelPath),{fromTFHub:e.face.mesh.modelPath.includes("tfhub.dev")}):null,!Rt[2]&&e.face.iris.enabled?ht(pt(e.modelBasePath,e.face.iris.modelPath),{fromTFHub:e.face.iris.modelPath.includes("tfhub.dev")}):null]),e.face.mesh.enabled&&(!Rt[1]||!Rt[1].modelUrl?de("load model failed:",e.face.mesh.modelPath):e.debug&&de("load model:",Rt[1].modelUrl)),e.face.iris.enabled&&(!Rt[2]||!Rt[2].modelUrl?de("load model failed:",e.face.iris.modelPath):e.debug&&de("load model:",Rt[2].modelUrl))):e.debug&&(Rt[0]&&de("cached model:",Rt[0].model.modelUrl),Rt[1]&&de("cached model:",Rt[1].modelUrl),Rt[2]&&de("cached model:",Rt[2].modelUrl)),H1=new U1(Rt[0],Rt[1],Rt[2]),Rt}var Mk=qo,zk=td;var Ws,$f=[],Lk=0,j1=Number.MAX_SAFE_INTEGER;async function q1(e){let t=pt(e.modelBasePath,e.face.description.modelPath);return Ws?e.debug&&de("cached model:",t):(Ws=await ht(t),Ws?e.debug&&de("load model:",t):de("load model failed:",e.face.description.modelPath)),Ws}function X1(e,t,n=2){if(!e||!t||(e==null?void 0:e.length)===0||(t==null?void 0:t.length)===0||(e==null?void 0:e.length)!==(t==null?void 0:t.length))return 0;let s=5*e.map((a,o)=>Math.abs(e[o]-t[o])**n).reduce((a,o)=>a+o,0)**(1/n);return Math.max(0,100-s)/100}function Bk(e,t,n=0){let s={similarity:0,name:"",source:"",embedding:[]};if(!e||!t||!Array.isArray(e)||!Array.isArray(t))return s;for(let r of t)if(r.embedding&&r.name){let a=X1(e,r.embedding);a>n&&a>s.similarity&&(s={...r,similarity:a})}return s}function K1(e){return H(()=>{let n=e.image||e.tensor||e;if(!(n instanceof Ue))return null;let s=[[.05,.15,.85,.85]];if(!Ws.inputs[0].shape)return null;let r=n.shape.length===3?Re.cropAndResize(Ft(n,0),s,[0],[Ws.inputs[0].shape[2],Ws.inputs[0].shape[1]]):Re.cropAndResize(n,s,[0],[Ws.inputs[0].shape[2],Ws.inputs[0].shape[1]]);return z(r,255)})}async function Z1(e,t,n,s){var r,a;return Ws?j1<t.face.description.skipFrames&&t.skipFrame&&Lk===s&&((r=$f[n])==null?void 0:r.age)&&((a=$f[n])==null?void 0:a.age)>0?(j1++,$f[n]):(j1=0,new Promise(async o=>{let i=K1(e),l,u={age:0,gender:"unknown",genderScore:0,descriptor:[]};t.face.description.enabled&&(l=await Ws.predict(i)),Z(i),l&&(H(()=>{let c=l.find(f=>f.shape[1]===1).dataSync(),d=Math.trunc(200*Math.abs(c[0]-.5))/100;d>t.face.description.minConfidence&&(u.gender=c[0]<=.5?"female":"male",u.genderScore=Math.min(.99,d));let h=Xs(l.find(f=>f.shape[1]===100),1).dataSync()[0],p=l.find(f=>f.shape[1]===100).dataSync();u.age=Math.round(p[h-1]>p[h+1]?10*h-100*p[h-1]:10*h+100*p[h+1])/10;let m=l.find(f=>f.shape[1]===1024);u.descriptor=[...m.dataSync()]}),l.forEach(c=>Z(c))),$f[n]=u,Lk=s,o(u)})):null}var gie=["angry","disgust","fear","happy","sad","surprise","neutral"],Vs,Ff=[],Wk=0,Y1=Number.MAX_SAFE_INTEGER,J1=[.2989,.587,.114];async function Q1(e){return Vs?e.debug&&de("cached model:",Vs.modelUrl):(Vs=await ht(pt(e.modelBasePath,e.face.emotion.modelPath)),!Vs||!Vs.modelUrl?de("load model failed:",e.face.emotion.modelPath):e.debug&&de("load model:",Vs.modelUrl)),Vs}async function ey(e,t,n,s){return Vs?Y1<t.face.emotion.skipFrames&&t.skipFrame&&Wk===s&&Ff[n]&&Ff[n].length>0?(Y1++,Ff[n]):(Y1=0,new Promise(async r=>{let a=Re.resizeBilinear(e,[Vs.inputs[0].shape[2],Vs.inputs[0].shape[1]],!1),[o,i,l]=nn(a,3,3);Z(a);let u=z(o,J1[0]),c=z(i,J1[1]),d=z(l,J1[2]);Z(o),Z(i),Z(l);let h=$h([u,c,d]);Z(u),Z(c),Z(d);let p=H(()=>z(Ae(h,.5),2));Z(h);let m=[];if(t.face.emotion.enabled){let f=await Vs.predict(p),A=f.dataSync();Z(f);for(let g=0;g<A.length;g++)A[g]>t.face.emotion.minConfidence&&m.push({score:Math.min(.99,Math.trunc(100*A[g])/100),emotion:gie[g]});m.sort((g,y)=>y.score-g.score)}Z(p),Ff[n]=m,Wk=s,r(m)})):null}var nd=["nose","leftEye","rightEye","leftEar","rightEar","leftShoulder","rightShoulder","leftElbow","rightElbow","leftWrist","rightWrist","leftHip","rightHip","leftKnee","rightKnee","leftAnkle","rightAnkle"],Vk=nd.length,sd=nd.reduce((e,t,n)=>(e[t]=n,e),{}),yie=[["leftHip","leftShoulder"],["leftElbow","leftShoulder"],["leftElbow","leftWrist"],["leftHip","leftKnee"],["leftKnee","leftAnkle"],["rightHip","rightShoulder"],["rightElbow","rightShoulder"],["rightElbow","rightWrist"],["rightHip","rightKnee"],["rightKnee","rightAnkle"],["leftShoulder","rightShoulder"],["leftHip","rightHip"]],xie=yie.map(([e,t])=>[sd[e],sd[t]]),Uk=[["nose","leftEye"],["leftEye","leftEar"],["nose","rightEye"],["rightEye","rightEar"],["nose","leftShoulder"],["leftShoulder","leftElbow"],["leftElbow","leftWrist"],["leftShoulder","leftHip"],["leftHip","leftKnee"],["leftKnee","leftAnkle"],["nose","rightShoulder"],["rightShoulder","rightElbow"],["rightElbow","rightWrist"],["rightShoulder","rightHip"],["rightHip","rightKnee"],["rightKnee","rightAnkle"]];function Hk(e){let t=e.reduce(({maxX:n,maxY:s,minX:r,minY:a},{position:{x:o,y:i}})=>({maxX:Math.max(n,o),maxY:Math.max(s,i),minX:Math.min(r,o),minY:Math.min(a,i)}),{maxX:Number.NEGATIVE_INFINITY,maxY:Number.NEGATIVE_INFINITY,minX:Number.POSITIVE_INFINITY,minY:Number.POSITIVE_INFINITY});return[t.minX,t.minY,t.maxX-t.minX,t.maxY-t.minY]}function Gk(e,[t,n],[s,r]){let a=t/s,o=n/r,i=(u,c)=>({id:c,score:u.score,boxRaw:[u.box[0]/r,u.box[1]/s,u.box[2]/r,u.box[3]/s],box:[Math.trunc(u.box[0]*o),Math.trunc(u.box[1]*a),Math.trunc(u.box[2]*o),Math.trunc(u.box[3]*a)],keypoints:u.keypoints.map(({score:d,part:h,position:p})=>({score:d,part:h,position:[Math.trunc(p.x*o),Math.trunc(p.y*a)],positionRaw:[p.x/s,p.y/s]}))});return e.map((u,c)=>i(u,c))}var ty=class{constructor(t,n){this.priorityQueue=new Array(t),this.numberOfElements=-1,this.getElementValue=n}enqueue(t){this.priorityQueue[++this.numberOfElements]=t,this.swim(this.numberOfElements)}dequeue(){let t=this.priorityQueue[0];return 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jk(e,t,n,s){let r=n-e,a=s-t;return r*r+a*a}function ay(e,t){return{x:e.x+t.x,y:e.y+t.y}}var Df=1,lu=16,bie=50**2;function qk(e,t,n,s,r,a,o=2){let i=g=>({y:a.get(g.y,g.x,e),x:a.get(g.y,g.x,a.shape[2]/2+e)}),l=(g,y,x)=>({y:ry(Math.round(g.y/lu),0,y-1),x:ry(Math.round(g.x/lu),0,x-1)}),[u,c]=s.shape,d=l(t.position,u,c),h=i(d),m=ay(t.position,h);for(let g=0;g<o;g++){let y=l(m,u,c),x=ny(y.y,y.x,n,r);m=ay({x:y.x*lu,y:y.y*lu},{x:x.x,y:x.y})}let f=l(m,u,c),A=s.get(f.y,f.x,n);return{position:m,part:nd[n],score:A}}function vie(e,t,n,s,r){let a=Uk.map(([h,p])=>[sd[h],sd[p]]),o=a.map(([,h])=>h),i=a.map(([h])=>h),l=t.shape[2],u=o.length,c=new Array(l),d=sy(e.part,lu,n);c[e.part.id]={score:e.score,part:nd[e.part.id],position:d};for(let h=u-1;h>=0;--h){let p=o[h],m=i[h];c[p]&&!c[m]&&(c[m]=qk(h,c[p],m,t,n,r))}for(let h=0;h<u;++h){let p=i[h],m=o[h];c[p]&&!c[m]&&(c[m]=qk(h,c[p],m,t,n,s))}return c}function wie(e,t,n,s,r){let[a,o]=r.shape,i=!0,l=Math.max(n-Df,0),u=Math.min(n+Df+1,a);for(let c=l;c<u;++c){let d=Math.max(s-Df,0),h=Math.min(s+Df+1,o);for(let p=d;p<h;++p)if(r.get(c,p,e)>t){i=!1;break}if(!i)break}return i}function kie(e,t){let[n,s,r]=t.shape,a=new ty(n*s*r,({score:o})=>o);for(let o=0;o<n;++o)for(let i=0;i<s;++i)for(let l=0;l<r;++l){let u=t.get(o,i,l);u<e||wie(l,u,o,i,t)&&a.enqueue({score:u,part:{heatmapY:o,heatmapX:i,id:l}})}return a}function Xk(e,{x:t,y:n},s){return e.some(({keypoints:r})=>{var o;let a=(o=r[s])==null?void 0:o.position;return a?jk(n,t,a.y,a.x)<=bie:!1})}function Iie(e,t){return t.reduce((s,{position:r,score:a},o)=>(Xk(e,r,o)||(s+=a),s),0)/t.length}function Kk(e,t,n,s,r,a){let o=[],i=kie(a,t);for(;o.length<r&&!i.empty();){let l=i.dequeue(),u=sy(l.part,lu,e);if(Xk(o,u,l.part.id))continue;let c=vie(l,t,e,n,s);c=c.filter(p=>p.score>a);let d=Iie(o,c),h=Hk(c);d>a&&o.push({keypoints:c,box:h,score:Math.round(100*d)/100})}return o}var 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d=[];for(let h of c)if(o[h]>=n.hand.minConfidence){let p=_e(l,[h,0],[1,-1]),m=_e(r,[h,5],[1,14]),f=H(()=>U(this.normalizeLandmarks(m,h),[-1,2]));Z(m),d.push({box:p,palmLandmarks:f,confidence:o[h]})}return Z(r),Z(l),d}async estimateHandBounds(t,n){let s=t.shape[1],r=t.shape[2],a=H(()=>Ae(ce(Re.resizeBilinear(t,[this.inputSize,this.inputSize]),127.5),1)),o=await this.getBoxes(a,n);Z(a);let i=[];if(!o||o.length===0)return i;for(let l of o){let u=l.box.dataSync(),c=u.slice(0,2),d=u.slice(2,4),h=l.palmLandmarks.arraySync();Z(l.box),Z(l.palmLandmarks),i.push(Yk({startPoint:c,endPoint:d,palmLandmarks:h,confidence:l.confidence},[r/this.inputSize,s/this.inputSize]))}return i}};function Cie(e){return e-2*Math.PI*Math.floor((e+Math.PI)/(2*Math.PI))}function Qk(e,t){let n=Math.PI/2-Math.atan2(-(t[1]-e[1]),t[0]-e[0]);return Cie(n)}var e8=(e,t)=>[[1,0,e],[0,1,t],[0,0,1]];function ia(e,t){let n=0;for(let s=0;s<e.length;s++)n+=e[s]*t[s];return n}function Tie(e,t){let n=[];for(let s=0;s<e.length;s++)n.push(e[s][t]);return n}function t8(e,t){let n=[],s=e.length;for(let r=0;r<s;r++){n.push([]);for(let a=0;a<s;a++)n[r].push(ia(e[r],Tie(t,a)))}return n}function uy(e,t){let n=Math.cos(e),s=Math.sin(e),r=[[n,-s,0],[s,n,0],[0,0,1]],a=e8(t[0],t[1]),o=t8(a,r),i=e8(-t[0],-t[1]);return t8(o,i)}function n8(e){let t=[[e[0][0],e[1][0]],[e[0][1],e[1][1]]],n=[e[0][2],e[1][2]],s=[-ia(t[0],n),-ia(t[1],n)];return[t[0].concat(s[0]),t[1].concat(s[1]),[0,0,1]]}function cy(e,t){return[ia(e,t[0]),ia(e,t[1])]}var Nie=5,s8=1.65,r8=[0,5,9,13,17,1,2],Eie=0,Rie=2,dy=class{constructor(t,n){var s;this.handDetector=t,this.handPoseModel=n,this.inputSize=(s=this.handPoseModel)==null?void 0:s.inputs[0].shape[2],this.storedBoxes=[],this.skipped=0,this.detectedHands=0}calculateLandmarksBoundingBox(t){let n=t.map(o=>o[0]),s=t.map(o=>o[1]),r=[Math.min(...n),Math.min(...s)],a=[Math.max(...n),Math.max(...s)];return{startPoint:r,endPoint:a}}getBoxForPalmLandmarks(t,n){let 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e.canvas&&await p.drawImage(e.canvas,0,0),p.globalCompositeOperation="darken",p.filter="blur(8px)",await p.drawImage(l,0,0),p.globalCompositeOperation="source-over",p.filter="none",e.canvas=h,d}async function d8(e,t,n){var a;if($y)return null;$y=!0,As||await Vf(n);let s=Xo(e,n),r=await Fy(s);if(Z(s.tensor),t&&r){let o=Xo(t,n),i=o.canvas;Z(o.tensor);let l=s.canvas,u=(a=l.getContext("2d"))==null?void 0:a.getImageData(0,0,l.width,l.height).data,c=typeof OffscreenCanvas!="undefined"?new OffscreenCanvas(l.width,l.height):document.createElement("canvas");c.width=l.width,c.height=l.height;let d=c.getContext("2d");d.globalCompositeOperation="copy",d.drawImage(i,0,0,c.width,c.height);let h=d.getImageData(0,0,c.width,c.height);for(let p=0;p<c.width*c.height;p++)h.data[4*p+0]=(255-r[4*p+0])/255*h.data[4*p+0]+r[4*p+0]/255*u[4*p+0],h.data[4*p+1]=(255-r[4*p+1])/255*h.data[4*p+1]+r[4*p+1]/255*u[4*p+1],h.data[4*p+2]=(255-r[4*p+2])/255*h.data[4*p+2]+r[4*p+2]/255*u[4*p+2],h.data[4*p+3]=(255-r[4*p+3])/255*h.data[4*p+3]+r[4*p+3]/255*u[4*p+3];d.putImageData(h,0,0),s.canvas=c}return $y=!1,s.canvas}async function h8(e){e.config.async?[e.models.face,e.models.emotion,e.models.handpose,e.models.posenet,e.models.blazepose,e.models.efficientpose,e.models.movenet,e.models.nanodet,e.models.centernet,e.models.faceres,e.models.segmentation]=await Promise.all([e.models.face||(e.config.face.enabled?G1(e.config):null),e.models.emotion||(e.config.face.enabled&&e.config.face.emotion.enabled?Q1(e.config):null),e.models.handpose||(e.config.hand.enabled?py(e.config):null),e.models.posenet||(e.config.body.enabled&&e.config.body.modelPath.includes("posenet")?iy(e.config):null),e.models.blazepose||(e.config.body.enabled&&e.config.body.modelPath.includes("blazepose")?zf(e.config):null),e.models.efficientpose||(e.config.body.enabled&&e.config.body.modelPath.includes("efficientpose")?u8(e.config):null),e.models.movenet||(e.config.body.enabled&&e.config.body.modelPath.includes("movenet")?wy(e.config):null),e.models.nanodet||(e.config.object.enabled&&e.config.object.modelPath.includes("nanodet")?Cy(e.config):null),e.models.centernet||(e.config.object.enabled&&e.config.object.modelPath.includes("centernet")?Ry(e.config):null),e.models.faceres||(e.config.face.enabled&&e.config.face.description.enabled?q1(e.config):null),e.models.segmentation||(e.config.segmentation.enabled?Vf(e.config):null)]):(e.config.face.enabled&&!e.models.face&&(e.models.face=await G1(e.config)),e.config.face.enabled&&e.config.face.emotion.enabled&&!e.models.emotion&&(e.models.emotion=await Q1(e.config)),e.config.hand.enabled&&!e.models.handpose&&(e.models.handpose=await py(e.config)),e.config.body.enabled&&!e.models.posenet&&e.config.body.modelPath.includes("posenet")&&(e.models.posenet=await iy(e.config)),e.config.body.enabled&&!e.models.blazepose&&e.config.body.modelPath.includes("blazepose")&&(e.models.blazepose=await zf(e.config)),e.config.body.enabled&&!e.models.efficientpose&&e.config.body.modelPath.includes("efficientpose")&&(e.models.efficientpose=await zf(e.config)),e.config.body.enabled&&!e.models.movenet&&e.config.body.modelPath.includes("movenet")&&(e.models.movenet=await wy(e.config)),e.config.object.enabled&&!e.models.nanodet&&e.config.object.modelPath.includes("nanodet")&&(e.models.nanodet=await Cy(e.config)),e.config.object.enabled&&!e.models.centernet&&e.config.object.modelPath.includes("centernet")&&(e.models.centernet=await Ry(e.config)),e.config.face.enabled&&e.config.face.description.enabled&&!e.models.faceres&&(e.models.faceres=await q1(e.config)),e.config.segmentation.enabled&&!e.models.segmentation&&(e.models.segmentation=await Vf(e.config)))}var Mie=e=>{let t=(d,h)=>Math.atan2(d[1]-h[1],d[0]-h[0]);if(!e.annotations.rightEyeIris||!e.annotations.leftEyeIris)return{bearing:0,strength:0};let n=[0,-.1],s=1,r=e.mesh[33][2]>e.mesh[263][2],a=r?e.mesh[473]:e.mesh[468],o=r?[(e.mesh[133][0]+e.mesh[33][0])/2,(e.mesh[133][1]+e.mesh[33][1])/2]:[(e.mesh[263][0]+e.mesh[362][0])/2,(e.mesh[263][1]+e.mesh[362][1])/2],i=r?[e.mesh[133][0]-e.mesh[33][0],e.mesh[23][1]-e.mesh[27][1]]:[e.mesh[263][0]-e.mesh[362][0],e.mesh[253][1]-e.mesh[257][1]],l=[(o[0]-a[0])/i[0]-n[0],s*(a[1]-o[1])/i[1]-n[1]],u=Math.sqrt(l[0]**2+l[1]**2);return u=Math.min(u,e.boxRaw[2]/2,e.boxRaw[3]/2),{bearing:(t([0,0],l)+Math.PI/2)%Math.PI,strength:u}},zie=(e,t)=>{let n=A=>{let g=Math.sqrt(A[0]*A[0]+A[1]*A[1]+A[2]*A[2]);return A[0]/=g,A[1]/=g,A[2]/=g,A},s=(A,g)=>{let y=A[0]-g[0],x=A[1]-g[1],b=A[2]-g[2];return[y,x,b]},r=(A,g)=>{let y=A[1]*g[2]-A[2]*g[1],x=A[2]*g[0]-A[0]*g[2],b=A[0]*g[1]-A[1]*g[0];return[y,x,b]},a=A=>{let[g,y,x,b,v,k,w,C,E]=A,P,R,_;return b<1?b>-1?(_=Math.asin(b),R=Math.atan2(-w,g),P=Math.atan2(-k,v)):(_=-Math.PI/2,R=-Math.atan2(C,E),P=0):(_=Math.PI/2,R=Math.atan2(C,E),P=0),{pitch:2*-P,yaw:2*-R,roll:2*-_}},o=A=>{let g=(x,b,v,k)=>Math.atan2(k-b,v-x);return{pitch:g(A[10][1],A[10][2],A[152][1],A[152][2]),yaw:g(A[33][0],A[33][2],A[263][0],A[263][2]),roll:g(A[33][0],A[33][1],A[263][0],A[263][1])}},i=e.meshRaw;if(!i||i.length<300)return{angle:{pitch:0,yaw:0,roll:0},matrix:[1,0,0,0,1,0,0,0,1],gaze:{bearing:0,strength:0}};let l=Math.max(e.boxRaw[2]*t[0],e.boxRaw[3]*t[1])/1.5,u=[i[10],i[152],i[234],i[454]].map(A=>[A[0]*t[0]/l,A[1]*t[1]/l,A[2]]),c=n(s(u[1],u[0])),d=n(s(u[3],u[2])),h=n(r(d,c));d=r(c,h);let p=[d[0],d[1],d[2],c[0],c[1],c[2],h[0],h[1],h[2]],m=a(p),f=i.length===478?Mie(e):{bearing:0,strength:0};return{angle:m,matrix:p,gaze:f}},Dy=async(e,t)=>{var d,h,p,m,f,A;let n,s,r,a,o,i,l,u=[];e.state="run:face",n=Ke();let c=await Pk(t,e.config);if(e.performance.face=Math.trunc(Ke()-n),!t.shape||t.shape.length!==4)return[];if(!c)return[];for(let g=0;g<c.length;g++){if(e.analyze("Get Face"),!c[g].image||c[g].image.isDisposedInternal){de("Face object is disposed:",c[g].image);continue}let y=zie(c[g],[t.shape[2],t.shape[1]]);e.analyze("Start Emotion:"),e.config.async?o=e.config.face.emotion.enabled?ey(c[g].image||on([]),e.config,g,c.length):{}:(e.state="run:emotion",n=Ke(),o=e.config.face.emotion.enabled?await ey(c[g].image||on([]),e.config,g,c.length):{},e.performance.emotion=Math.trunc(Ke()-n)),e.analyze("End Emotion:"),e.analyze("Start 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0:A.rightEyeIris)?Math.max(Math.abs(c[g].annotations.leftEyeIris[3][0]-c[g].annotations.leftEyeIris[1][0]),Math.abs(c[g].annotations.rightEyeIris[4][1]-c[g].annotations.rightEyeIris[2][1]))/t.shape[2]:0;u.push({...c[g],id:g,age:l.age,gender:l.gender,genderScore:l.genderScore,embedding:l.descriptor,emotion:o,iris:x!==0?Math.trunc(500/x/11.7)/100:0,rotation:y,tensor:e.config.face.detector.return?mt(c[g].image):null}),Z(c[g].image),c[g].image&&delete c[g].image,e.analyze("End Face")}return e.analyze("End FaceMesh:"),e.config.async&&(e.performance.face&&delete e.performance.face,e.performance.age&&delete e.performance.age,e.performance.gender&&delete e.performance.gender,e.performance.emotion&&delete e.performance.emotion),u};var p8=e=>{if(!e)return[];let t=[];for(let n=0;n<e.length;n++){let s=e[n].keypoints.find(l=>l.part==="leftWrist"),r=e[n].keypoints.find(l=>l.part==="rightWrist"),a=e[n].keypoints.find(l=>l.part==="nose");a&&s&&r&&s.position.y<a.position.y&&r.position.y<a.position.y?t.push({body:n,gesture:"i give up"}):a&&s&&s.position.y<a.position.y?t.push({body:n,gesture:"raise left hand"}):a&&r&&r.position.y<a.position.y&&t.push({body:n,gesture:"raise right hand"});let o=e[n].keypoints.find(l=>l.part==="leftShoulder"),i=e[n].keypoints.find(l=>l.part==="rightShoulder");o&&i&&t.push({body:n,gesture:`leaning ${o.position.y>i.position.y?"left":"right"}`})}return t},f8=e=>{if(!e)return[];let t=[];for(let n=0;n<e.length;n++)if(e[n].mesh&&e[n].mesh.length>0){let s=e[n].mesh[33][2]-e[n].mesh[263][2];Math.abs(s)<10?t.push({face:n,gesture:"facing center"}):t.push({face:n,gesture:`facing ${s<0?"left":"right"}`}),Math.abs(e[n].mesh[374][1]-e[n].mesh[386][1])/Math.abs(e[n].mesh[443][1]-e[n].mesh[450][1])<.2&&t.push({face:n,gesture:"blink left 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d=Math.abs(e[n].mesh[33][0]-e[n].annotations.rightEyeIris[0][0])/e[n].box[2],h=Math.abs(e[n].mesh[263][0]-e[n].annotations.leftEyeIris[0][0])/e[n].box[2];(h>.06||d>.06)&&(u=!1),h>.06&&t.push({iris:n,gesture:"looking right"}),d>.06&&t.push({iris:n,gesture:"looking left"});let p=Math.abs(e[n].mesh[145][1]-e[n].annotations.rightEyeIris[0][1])/e[n].box[3],m=Math.abs(e[n].mesh[374][1]-e[n].annotations.leftEyeIris[0][1])/e[n].box[3];(m<.01||p<.01||m>.022||p>.022)&&(u=!1),(m<.01||p<.01)&&t.push({iris:n,gesture:"looking down"}),(m>.022||p>.022)&&t.push({iris:n,gesture:"looking up"}),u&&t.push({iris:n,gesture:"looking center"})}return t},A8=e=>{if(!e)return[];let t=[];for(let n=0;n<e.length;n++){let s=[];for(let[r,a]of Object.entries(e[n].annotations))r!=="palmBase"&&Array.isArray(a)&&s.push({name:r.toLowerCase(),position:a[0]});if(s&&s.length>0){let r=s.reduce((o,i)=>o.position[2]<i.position[2]?o:i);t.push({hand:n,gesture:`${r.name} forward`});let 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r=(t[s][0]+t[s+1][0])/2,a=(t[s][1]+t[s+1][1])/2;e.quadraticCurveTo(t[s][0],t[s][1],r,a)}e.quadraticCurveTo(t[t.length-2][0],t[t.length-2][1],t[t.length-1][0],t[t.length-1][1]),e.stroke(),n.fillPolygons&&(e.closePath(),e.fill())}}async function g8(e,t,n){let s=pn(ca,n);if(!t||!e||!(e instanceof HTMLCanvasElement))return;let r=e.getContext("2d");if(!r)return;r.font=s.font,r.fillStyle=s.color;let a=1;for(let o=0;o<t.length;o++){let i=[],l=[];if([i,l]=Object.entries(t[o]),l.length>1&&l[1].length>0){let u=i[1]>0?`#${i[1]}`:"",c=`${i[0]} ${u}: ${l[1]}`;s.shadowColor&&s.shadowColor!==""&&(r.fillStyle=s.shadowColor,r.fillText(c,8,2+a*s.lineHeight)),r.fillStyle=s.labelColor,r.fillText(c,6,0+a*s.lineHeight),a+=1}}}async function y8(e,t,n){var a,o,i,l;let s=pn(ca,n);if(!t||!e||!(e instanceof HTMLCanvasElement))return;let r=e.getContext("2d");if(!!r)for(let u of t){r.font=s.font,r.strokeStyle=s.color,r.fillStyle=s.color,s.drawBoxes&&ad(r,u.box[0],u.box[1],u.box[2],u.box[3],s);let c=[];if(c.push(`face: ${Math.trunc(100*u.score)}%`),u.genderScore&&c.push(`${u.gender||""} ${Math.trunc(100*u.genderScore)}%`),u.age&&c.push(`age: ${u.age||""}`),u.iris&&c.push(`distance: ${u.iris}`),u.emotion&&u.emotion.length>0){let d=u.emotion.map(h=>`${Math.trunc(100*h.score)}% ${h.emotion}`);d.length>3&&(d.length=3),c.push(d.join(" "))}u.rotation&&u.rotation.angle&&u.rotation.gaze&&(u.rotation.angle.roll&&c.push(`roll: ${Uf(u.rotation.angle.roll)}\xB0 yaw:${Uf(u.rotation.angle.yaw)}\xB0 pitch:${Uf(u.rotation.angle.pitch)}\xB0`),u.rotation.gaze.bearing&&c.push(`gaze: ${Uf(u.rotation.gaze.bearing)}\xB0`)),c.length===0&&c.push("face"),r.fillStyle=s.color;for(let d=c.length-1;d>=0;d--){let h=Math.max(u.box[0],0),p=d*s.lineHeight+u.box[1];s.shadowColor&&s.shadowColor!==""&&(r.fillStyle=s.shadowColor,r.fillText(c[d],h+5,p+16)),r.fillStyle=s.labelColor,r.fillText(c[d],h+4,p+15)}if(r.lineWidth=1,u.mesh&&u.mesh.length>0){if(s.drawPoints)for(let d of u.mesh)Oy(r,d[0],d[1],d[2],s);if(s.drawPolygons){r.lineWidth=1;for(let d=0;d<qo.length/3;d++){let h=[qo[d*3+0],qo[d*3+1],qo[d*3+2]].map(p=>u.mesh[p]);Py(r,h,s)}if(u.annotations&&u.annotations.leftEyeIris){r.strokeStyle=s.useDepth?"rgba(255, 200, 255, 0.3)":s.color,r.beginPath();let d=Math.abs(u.annotations.leftEyeIris[3][0]-u.annotations.leftEyeIris[1][0])/2,h=Math.abs(u.annotations.leftEyeIris[4][1]-u.annotations.leftEyeIris[2][1])/2;r.ellipse(u.annotations.leftEyeIris[0][0],u.annotations.leftEyeIris[0][1],d,h,0,0,2*Math.PI),r.stroke(),s.fillPolygons&&(r.fillStyle=s.useDepth?"rgba(255, 255, 200, 0.3)":s.color,r.fill())}if(u.annotations&&u.annotations.rightEyeIris){r.strokeStyle=s.useDepth?"rgba(255, 200, 255, 0.3)":s.color,r.beginPath();let d=Math.abs(u.annotations.rightEyeIris[3][0]-u.annotations.rightEyeIris[1][0])/2,h=Math.abs(u.annotations.rightEyeIris[4][1]-u.annotations.rightEyeIris[2][1])/2;r.ellipse(u.annotations.rightEyeIris[0][0],u.annotations.rightEyeIris[0][1],d,h,0,0,2*Math.PI),r.stroke(),s.fillPolygons&&(r.fillStyle=s.useDepth?"rgba(255, 255, 200, 0.3)":s.color,r.fill())}if(s.drawGaze&&((o=(a=u.rotation)==null?void 0:a.gaze)==null?void 0:o.strength)&&((l=(i=u.rotation)==null?void 0:i.gaze)==null?void 0:l.bearing)&&u.annotations.leftEyeIris&&u.annotations.rightEyeIris&&u.annotations.leftEyeIris[0]&&u.annotations.rightEyeIris[0]){r.strokeStyle="pink",r.beginPath();let d=[u.annotations.leftEyeIris[0][0]+Math.sin(u.rotation.gaze.bearing)*u.rotation.gaze.strength*u.box[3],u.annotations.leftEyeIris[0][1]+Math.cos(u.rotation.gaze.bearing)*u.rotation.gaze.strength*u.box[2]];r.moveTo(u.annotations.leftEyeIris[0][0],u.annotations.leftEyeIris[0][1]),r.lineTo(d[0],d[1]);let h=[u.annotations.rightEyeIris[0][0]+Math.sin(u.rotation.gaze.bearing)*u.rotation.gaze.strength*u.box[3],u.annotations.rightEyeIris[0][1]+Math.cos(u.rotation.gaze.bearing)*u.rotation.gaze.strength*u.box[2]];r.moveTo(u.annotations.rightEyeIris[0][0],u.annotations.rightEyeIris[0][1]),r.lineTo(h[0],h[1]),r.stroke()}}}}}async function x8(e,t,n){var a;let s=pn(ca,n);if(!t||!e||!(e instanceof HTMLCanvasElement))return;let r=e.getContext("2d");if(!!r){r.lineJoin="round";for(let o=0;o<t.length;o++){if(r.strokeStyle=s.color,r.fillStyle=s.color,r.lineWidth=s.lineWidth,r.font=s.font,s.drawBoxes&&t[o].box&&((a=t[o].box)==null?void 0:a.length)===4&&(ad(r,t[o].box[0],t[o].box[1],t[o].box[2],t[o].box[3],s),s.drawLabels&&(s.shadowColor&&s.shadowColor!==""&&(r.fillStyle=s.shadowColor,r.fillText(`body ${100*t[o].score}%`,t[o].box[0]+3,1+t[o].box[1]+s.lineHeight,t[o].box[2])),r.fillStyle=s.labelColor,r.fillText(`body ${100*t[o].score}%`,t[o].box[0]+2,0+t[o].box[1]+s.lineHeight,t[o].box[2]))),s.drawPoints)for(let i=0;i<t[o].keypoints.length;i++)r.fillStyle=s.useDepth&&t[o].keypoints[i].position[2]?`rgba(${127.5+2*(t[o].keypoints[i].position[2]||0)}, ${127.5-2*(t[o].keypoints[i].position[2]||0)}, 255, 0.5)`:s.color,Oy(r,t[o].keypoints[i].position[0],t[o].keypoints[i].position[1],0,s);if(s.drawLabels&&(r.font=s.font,t[o].keypoints))for(let i of t[o].keypoints)r.fillStyle=s.useDepth&&i.position[2]?`rgba(${127.5+2*i.position[2]}, ${127.5-2*i.position[2]}, 255, 0.5)`:s.color,r.fillText(`${i.part} ${Math.trunc(100*i.score)}%`,i.position[0]+4,i.position[1]+4);if(s.drawPolygons&&t[o].keypoints){let i,l=[];l.length=0,i=t[o].keypoints.find(u=>u.part==="leftShoulder"),i&&l.push([i.position[0],i.position[1]]),i=t[o].keypoints.find(u=>u.part==="rightShoulder"),i&&l.push([i.position[0],i.position[1]]),od(r,l,s),l.length=0,i=t[o].keypoints.find(u=>u.part==="rightShoulder"),i&&l.push([i.position[0],i.position[1]]),i=t[o].keypoints.find(u=>u.part==="rightHip"),i&&l.push([i.position[0],i.position[1]]),i=t[o].keypoints.find(u=>u.part==="leftHip"),i&&l.push([i.position[0],i.position[1]]),i=t[o].keypoints.find(u=>u.part==="leftShoulder"),i&&l.push([i.position[0],i.position[1]]),l.length===4&&Py(r,l,s),l.length=0,i=t[o].keypoints.find(u=>u.part==="leftHip"),i&&l.push([i.position[0],i.position[1]]),i=t[o].keypoints.find(u=>u.part==="leftKnee"),i&&l.push([i.position[0],i.position[1]]),i=t[o].keypoints.find(u=>u.part==="leftAnkle"),i&&l.push([i.position[0],i.position[1]]),i=t[o].keypoints.find(u=>u.part==="leftHeel"),i&&l.push([i.position[0],i.position[1]]),i=t[o].keypoints.find(u=>u.part==="leftFoot"),i&&l.push([i.position[0],i.position[1]]),od(r,l,s),l.length=0,i=t[o].keypoints.find(u=>u.part==="rightHip"),i&&l.push([i.position[0],i.position[1]]),i=t[o].keypoints.find(u=>u.part==="rightKnee"),i&&l.push([i.position[0],i.position[1]]),i=t[o].keypoints.find(u=>u.part==="rightAnkle"),i&&l.push([i.position[0],i.position[1]]),i=t[o].keypoints.find(u=>u.part==="rightHeel"),i&&l.push([i.position[0],i.position[1]]),i=t[o].keypoints.find(u=>u.part==="rightFoot"),i&&l.push([i.position[0],i.position[1]]),od(r,l,s),l.length=0,i=t[o].keypoints.find(u=>u.part==="leftShoulder"),i&&l.push([i.position[0],i.position[1]]),i=t[o].keypoints.find(u=>u.part==="leftElbow"),i&&l.push([i.position[0],i.position[1]]),i=t[o].keypoints.find(u=>u.part==="leftWrist"),i&&l.push([i.position[0],i.position[1]]),i=t[o].keypoints.find(u=>u.part==="leftPalm"),i&&l.push([i.position[0],i.position[1]]),od(r,l,s),l.length=0,i=t[o].keypoints.find(u=>u.part==="rightShoulder"),i&&l.push([i.position[0],i.position[1]]),i=t[o].keypoints.find(u=>u.part==="rightElbow"),i&&l.push([i.position[0],i.position[1]]),i=t[o].keypoints.find(u=>u.part==="rightWrist"),i&&l.push([i.position[0],i.position[1]]),i=t[o].keypoints.find(u=>u.part==="rightPalm"),i&&l.push([i.position[0],i.position[1]]),od(r,l,s)}}}}async function b8(e,t,n){let s=pn(ca,n);if(!t||!e||!(e instanceof HTMLCanvasElement))return;let r=e.getContext("2d");if(!!r){r.lineJoin="round",r.font=s.font;for(let a of t){if(s.drawBoxes&&(r.strokeStyle=s.color,r.fillStyle=s.color,ad(r,a.box[0],a.box[1],a.box[2],a.box[3],s),s.drawLabels&&(s.shadowColor&&s.shadowColor!==""&&(r.fillStyle=s.shadowColor,r.fillText("hand",a.box[0]+3,1+a.box[1]+s.lineHeight,a.box[2])),r.fillStyle=s.labelColor,r.fillText("hand",a.box[0]+2,0+a.box[1]+s.lineHeight,a.box[2])),r.stroke()),s.drawPoints&&a.keypoints&&a.keypoints.length>0)for(let o of a.keypoints)r.fillStyle=s.useDepth?`rgba(${127.5+2*o[2]}, ${127.5-2*o[2]}, 255, 0.5)`:s.color,Oy(r,o[0],o[1],0,s);if(s.drawLabels){let o=(i,l)=>{r.fillStyle=s.useDepth?`rgba(${127.5+2*i[i.length-1][2]}, ${127.5-2*i[i.length-1][2]}, 255, 0.5)`:s.color,r.fillText(l,i[i.length-1][0]+4,i[i.length-1][1]+4)};r.font=s.font,o(a.annotations.indexFinger,"index"),o(a.annotations.middleFinger,"middle"),o(a.annotations.ringFinger,"ring"),o(a.annotations.pinky,"pinky"),o(a.annotations.thumb,"thumb"),o(a.annotations.palmBase,"palm")}if(s.drawPolygons){let o=i=>{if(!!i)for(let l=0;l<i.length;l++)r.beginPath(),r.strokeStyle=s.useDepth?`rgba(${127.5+2*i[l][2]}, ${127.5-2*i[l][2]}, 255, 0.5)`:s.color,r.moveTo(i[l>0?l-1:0][0],i[l>0?l-1:0][1]),r.lineTo(i[l][0],i[l][1]),r.stroke()};r.lineWidth=s.lineWidth,o(a.annotations.indexFinger),o(a.annotations.middleFinger),o(a.annotations.ringFinger),o(a.annotations.pinky),o(a.annotations.thumb)}}}}async function v8(e,t,n){let s=pn(ca,n);if(!t||!e||!(e instanceof HTMLCanvasElement))return;let r=e.getContext("2d");if(!!r){r.lineJoin="round",r.font=s.font;for(let a of t)if(s.drawBoxes){if(r.strokeStyle=s.color,r.fillStyle=s.color,ad(r,a.box[0],a.box[1],a.box[2],a.box[3],s),s.drawLabels){let o=`${a.label} ${Math.round(100*a.score)}%`;s.shadowColor&&s.shadowColor!==""&&(r.fillStyle=s.shadowColor,r.fillText(o,a.box[0]+3,1+a.box[1]+s.lineHeight,a.box[2])),r.fillStyle=s.labelColor,r.fillText(o,a.box[0]+2,0+a.box[1]+s.lineHeight,a.box[2])}r.stroke()}}}async function Lie(e,t,n){let s=pn(ca,n);if(!t||!e||!(e instanceof HTMLCanvasElement))return;let r=e.getContext("2d");if(!!r){r.lineJoin="round",r.font=s.font;for(let a=0;a<t.length;a++)if(s.drawBoxes){if(r.strokeStyle=s.color,r.fillStyle=s.color,ad(r,t[a].box[0],t[a].box[1],t[a].box[2],t[a].box[3],s),s.drawLabels){let o=`person #${a}`;s.shadowColor&&s.shadowColor!==""&&(r.fillStyle=s.shadowColor,r.fillText(o,t[a].box[0]+3,1+t[a].box[1]+s.lineHeight,t[a].box[2])),r.fillStyle=s.labelColor,r.fillText(o,t[a].box[0]+2,0+t[a].box[1]+s.lineHeight,t[a].box[2])}r.stroke()}}}async function Bie(e,t){if(!e||!t||!(e instanceof HTMLCanvasElement)||!(t instanceof HTMLCanvasElement))return;let n=e.getContext("2d");n==null||n.drawImage(e,0,0)}async function Wie(e,t,n){let s=Ke(),r=pn(ca,n);!t||!e||e instanceof HTMLCanvasElement&&(y8(e,t.face,r),x8(e,t.body,r),b8(e,t.hand,r),v8(e,t.object,r),g8(e,t.gesture,r),t.performance.draw=Math.trunc(Ke()-s))}function w8(e,t,n,s,r){var i,l,u,c,d,h,p,m,f,A,g,y,x,b,v,k;let a=0,o=[];for(let w of e){let C={id:a++,face:w,body:null,hands:{left:null,right:null},gestures:[],box:[0,0,0,0]};for(let O of t)w.box[0]>O.box[0]&&w.box[0]<O.box[0]+O.box[2]&&w.box[1]+w.box[3]>O.box[1]&&w.box[1]+w.box[3]<O.box[1]+O.box[3]&&(C.body=O);if(C.body)for(let O of n)O.box[0]+O.box[2]>C.body.box[0]&&O.box[0]+O.box[2]<C.body.box[0]+C.body.box[2]&&O.box[1]+O.box[3]>C.body.box[1]&&O.box[1]+O.box[3]<C.body.box[1]+C.body.box[3]&&C.hands&&(C.hands.left=O),O.box[0]<C.body.box[0]+C.body.box[2]&&O.box[0]>C.body.box[0]&&O.box[1]+O.box[3]>C.body.box[1]&&O.box[1]+O.box[3]<C.body.box[1]+C.body.box[3]&&C.hands&&(C.hands.right=O);for(let O of s)O.face!==void 0&&O.face===w.id?(i=C.gestures)==null||i.push(O):O.iris!==void 0&&O.iris===w.id?(l=C.gestures)==null||l.push(O):O.body!==void 0&&O.body===((u=C.body)==null?void 0:u.id)?(c=C.gestures)==null||c.push(O):O.hand!==void 0&&O.hand===((h=(d=C.hands)==null?void 0:d.left)==null?void 0:h.id)?(p=C.gestures)==null||p.push(O):O.hand!==void 0&&O.hand===((f=(m=C.hands)==null?void 0:m.right)==null?void 0:f.id)&&((A=C.gestures)==null||A.push(O));let E=[],P=[],R=O=>{O&&O.length===4&&(E.push(O[0],O[0]+O[2]),P.push(O[1],O[1]+O[3]))};R((g=C.face)==null?void 0:g.box),R((y=C.body)==null?void 0:y.box),R((b=(x=C.hands)==null?void 0:x.left)==null?void 0:b.box),R((k=(v=C.hands)==null?void 0:v.right)==null?void 0:k.box);let _=Math.min(...E),T=Math.min(...P);C.box=[_,T,Math.max(...E)-_,Math.max(...P)-T],r&&r.length===4&&(C.boxRaw=[C.box[0]/r[2],C.box[1]/r[1],C.box[2]/r[2],C.box[3]/r[1]]),o.push(C)}return o}var Fe={face:[],body:[],hand:[],gesture:[],object:[],persons:[],performance:{},timestamp:0};function k8(e){var s,r,a,o,i,l,u,c,d,h,p,m,f,A,g,y,x,b,v,k,w;let t=Date.now()-e.timestamp,n=t<1e3?8-Math.log(t):1;if(Fe.canvas=e.canvas,!Fe.body||e.body.length!==Fe.body.length)Fe.body=JSON.parse(JSON.stringify(e.body));else for(let C=0;C<e.body.length;C++){let E=e.body[C].box.map((_,T)=>((n-1)*Fe.body[C].box[T]+_)/n),P=e.body[C].boxRaw.map((_,T)=>((n-1)*Fe.body[C].boxRaw[T]+_)/n),R=e.body[C].keypoints.map((_,T)=>({score:_.score,part:_.part,position:[Fe.body[C].keypoints[T]?((n-1)*Fe.body[C].keypoints[T].position[0]+_.position[0])/n:_.position[0],Fe.body[C].keypoints[T]?((n-1)*Fe.body[C].keypoints[T].position[1]+_.position[1])/n:_.position[1]],positionRaw:[Fe.body[C].keypoints[T]?((n-1)*Fe.body[C].keypoints[T].positionRaw[0]+_.positionRaw[0])/n:_.position[0],Fe.body[C].keypoints[T]?((n-1)*Fe.body[C].keypoints[T].positionRaw[1]+_.positionRaw[1])/n:_.position[1]]}));Fe.body[C]={...e.body[C],box:E,boxRaw:P,keypoints:R}}if(!Fe.hand||e.hand.length!==Fe.hand.length)Fe.hand=JSON.parse(JSON.stringify(e.hand));else for(let C=0;C<e.hand.length;C++){let E=e.hand[C].box.map((O,W)=>((n-1)*Fe.hand[C].box[W]+O)/n),P=e.hand[C].boxRaw.map((O,W)=>((n-1)*Fe.hand[C].boxRaw[W]+O)/n),R=e.hand[C].keypoints.map((O,W)=>O.map((j,q)=>((n-1)*Fe.hand[C].keypoints[W][q]+j)/n)),_=Object.keys(e.hand[C].annotations),T={};for(let O of _)T[O]=e.hand[C].annotations[O].map((W,j)=>W.map((q,X)=>((n-1)*Fe.hand[C].annotations[O][j][X]+q)/n));Fe.hand[C]={...e.hand[C],box:E,boxRaw:P,keypoints:R,annotations:T}}if(!Fe.face||e.face.length!==Fe.face.length)Fe.face=JSON.parse(JSON.stringify(e.face));else for(let C=0;C<e.face.length;C++){let E=e.face[C].box.map((_,T)=>((n-1)*Fe.face[C].box[T]+_)/n),P=e.face[C].boxRaw.map((_,T)=>((n-1)*Fe.face[C].boxRaw[T]+_)/n),R={matrix:[0,0,0,0,0,0,0,0,0],angle:{roll:0,yaw:0,pitch:0},gaze:{bearing:0,strength:0}};R.matrix=(s=e.face[C].rotation)==null?void 0:s.matrix,R.angle={roll:((n-1)*(((a=(r=Fe.face[C].rotation)==null?void 0:r.angle)==null?void 0:a.roll)||0)+(((i=(o=e.face[C].rotation)==null?void 0:o.angle)==null?void 0:i.roll)||0))/n,yaw:((n-1)*(((u=(l=Fe.face[C].rotation)==null?void 0:l.angle)==null?void 0:u.yaw)||0)+(((d=(c=e.face[C].rotation)==null?void 0:c.angle)==null?void 0:d.yaw)||0))/n,pitch:((n-1)*(((p=(h=Fe.face[C].rotation)==null?void 0:h.angle)==null?void 0:p.pitch)||0)+(((f=(m=e.face[C].rotation)==null?void 0:m.angle)==null?void 0:f.pitch)||0))/n},R.gaze={bearing:((n-1)*(((g=(A=Fe.face[C].rotation)==null?void 0:A.gaze)==null?void 0:g.bearing)||0)+(((x=(y=e.face[C].rotation)==null?void 0:y.gaze)==null?void 0:x.bearing)||0))/n,strength:((n-1)*(((v=(b=Fe.face[C].rotation)==null?void 0:b.gaze)==null?void 0:v.strength)||0)+(((w=(k=e.face[C].rotation)==null?void 0:k.gaze)==null?void 0:w.strength)||0))/n},Fe.face[C]={...e.face[C],rotation:R,box:E,boxRaw:P}}if(!Fe.object||e.object.length!==Fe.object.length)Fe.object=JSON.parse(JSON.stringify(e.object));else for(let C=0;C<e.object.length;C++){let E=e.object[C].box.map((R,_)=>((n-1)*Fe.object[C].box[_]+R)/n),P=e.object[C].boxRaw.map((R,_)=>((n-1)*Fe.object[C].boxRaw[_]+R)/n);Fe.object[C]={...e.object[C],box:E,boxRaw:P}}if(e.persons){let C=e.persons;if(!Fe.persons||C.length!==Fe.persons.length)Fe.persons=JSON.parse(JSON.stringify(C));else for(let E=0;E<C.length;E++)Fe.persons[E].box=C[E].box.map((P,R)=>((n-1)*Fe.persons[E].box[R]+P)/n)}return e.gesture&&(Fe.gesture=e.gesture),e.performance&&(Fe.performance=e.performance),Fe}var Hf=`
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ky(l.tensor,this.config):[]),a=Math.trunc(Ke()-r),a>0&&(this.performance.body=a)),this.analyze("End Body:"),this.analyze("Start Hand:"),this.config.async?(d=this.config.hand.enabled?hy(l.tensor,this.config):[],this.performance.hand&&delete this.performance.hand):(this.state="run:hand",r=Ke(),d=this.config.hand.enabled?await hy(l.tensor,this.config):[],a=Math.trunc(Ke()-r),a>0&&(this.performance.hand=a)),this.analyze("End Hand:"),this.analyze("Start Object:"),this.config.async?(this.config.object.modelPath.includes("nanodet")?h=this.config.object.enabled?Ty(l.tensor,this.config):[]:this.config.object.modelPath.includes("centernet")&&(h=this.config.object.enabled?_y(l.tensor,this.config):[]),this.performance.object&&delete this.performance.object):(this.state="run:object",r=Ke(),this.config.object.modelPath.includes("nanodet")?h=this.config.object.enabled?await Ty(l.tensor,this.config):[]:this.config.object.modelPath.includes("centernet")&&(h=this.config.object.enabled?await _y(l.tensor,this.config):[]),a=Math.trunc(Ke()-r),a>0&&(this.performance.object=a)),this.analyze("End Object:"),this.config.async&&([u,c,d,h]=await Promise.all([u,c,d,h]));let p=[];this.config.gesture.enabled&&(r=Ke(),p=[...f8(u),...p8(c),...A8(d),...m8(u)],this.config.async?this.performance.gesture&&delete this.performance.gesture:this.performance.gesture=Math.trunc(Ke()-r)),this.performance.total=Math.trunc(Ke()-i),this.state="idle",this.result={face:u,body:c,hand:d,gesture:p,object:h,performance:this.performance,canvas:l.canvas,timestamp:Date.now(),get persons(){var m;return w8(u,c,d,p,(m=l==null?void 0:l.tensor)==null?void 0:m.shape)}},Z(l.tensor),s(this.result)})}async warmup(t){let n=Ke();if(t&&(this.config=pn(this.config,t)),!this.config.warmup||this.config.warmup==="none")return{error:"null"};let s;typeof createImageBitmap=="function"?s=await hn(this,Xf).call(this):typeof Image!="undefined"?s=await hn(this,Kf).call(this):s=await hn(this,Zf).call(this);let r=Ke();return this.config.debug&&de("Warmup",this.config.warmup,Math.round(r-n),"ms",s),s}};du=new WeakMap,id=new WeakMap,ld=new WeakMap,Ko=new WeakMap,Zo=new WeakMap,hu=new WeakMap,jf=new WeakMap,ud=new WeakMap,qf=new WeakMap,Xf=new WeakMap,Kf=new WeakMap,Zf=new WeakMap;export{Uie as Human,Uie as default};
/**
* @license
* Copyright 2017 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
/**
* @license
* Copyright 2018 Google LLC
*
* Use of this source code is governed by an MIT-style
* license that can be found in the LICENSE file or at
* https://opensource.org/licenses/MIT.
* =============================================================================
*/
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*
* =============================================================================
*/
/**
* @license
* Copyright 2018 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
/**
* @license
* Copyright 2019 Google LLC
*
* Use of this source code is governed by an MIT-style
* license that can be found in the LICENSE file or at
* https://opensource.org/licenses/MIT.
* =============================================================================
*/
/**
* @license
* Copyright 2019 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*
* =============================================================================
*/
/**
* @license
* Copyright 2019 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
/**
* @license
* Copyright 2020 Google Inc. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
/**
* @license
* Copyright 2020 Google LLC
*
* Use of this source code is governed by an MIT-style
* license that can be found in the LICENSE file or at
* https://opensource.org/licenses/MIT.
* =============================================================================
*/
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the License);
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an AS IS BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
/**
* @license
* Copyright 2021 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
/**
* @license
* Copyright 2021 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* https://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
/** @license See the LICENSE file. */
//# sourceMappingURL=human.esm.js.map
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