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face-api
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face-api/dist/tfjs.esm.js

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/*
Face-API
homepage: <https://github.com/vladmandic/face-api>
author: <https://github.com/vladmandic>'
*/
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o=++this.pendingBackendInitId,s=n.then(i=>o<this.pendingBackendInitId?!1:(this.registry[t]=i,this.pendingBackendInit=null,!0)).catch(i=>(o<this.pendingBackendInitId||(this.pendingBackendInit=null,$i(`Initialization of backend ${t} failed`),$i(i.stack||i.message)),!1));return this.pendingBackendInit=s,{success:s,asyncInit:!0}}else return this.registry[t]=n,{success:!0,asyncInit:!1}}catch(n){return $i(`Initialization of backend ${t} failed`),$i(n.stack||n.message),{success:!1,asyncInit:!1}}}removeBackend(t){if(!(t in this.registryFactory))throw new Error(`${t} backend not found in registry`);this.backendName===t&&this.pendingBackendInit!=null&&this.pendingBackendInitId++,t in this.registry&&(this.disposeRegisteredKernels(t),this.registry[t].dispose(),delete this.registry[t]),delete this.registryFactory[t],this.backendName===t&&(this.pendingBackendInit=null,this.backendName=null,this.backendInstance=null)}getSortedBackends(){if(Object.keys(this.registryFactory).length===0)throw new Error("No backend found in registry.");return Object.keys(this.registryFactory).sort((t,e)=>this.registryFactory[e].priority-this.registryFactory[t].priority)}initializeBackendsAndReturnBest(){let t=this.getSortedBackends();for(let e=0;e<t.length;e++){let n=t[e],{success:o,asyncInit:s}=this.initializeBackend(n);if(s||o)return{name:n,asyncInit:s}}throw new Error("Could not initialize any backends, all backend initializations failed.")}moveData(t,e){let n=this.state.tensorInfo.get(e),o=n.backend,s=this.readSync(e),i=o.refCount(e);o.disposeData(e,!0),n.backend=t,t.move(e,s,n.shape,n.dtype,i),this.shouldCheckForMemLeaks()&&this.state.numDataMovesStack[this.state.numDataMovesStack.length-1]++}tidy(t,e){let n=null;if(e==null){if(typeof t!="function")throw new Error("Please provide a function to tidy()");e=t}else{if(typeof t!="string"&&!(t instanceof String))throw new Error("When calling with two arguments, the first argument to tidy() must be a string");if(typeof e!="function")throw new 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o=this.backend.numDataIds(),s=0;n.forEach(u=>{s+=u.dtype==="complex64"?3:1});let i=this.state.numDataMovesStack[this.state.numDataMovesStack.length-1],a=o-e-s-i;if(a>0)throw new Error(`Backend '${this.backendName}' has an internal memory leak (${a} data ids) after running '${t}'`)}runKernelFunc(t){let e,n=[],o=this.isTapeOn(),s=this.state.numBytes,i=this.state.numTensors;this.shouldCheckForMemLeaks()&&this.state.numDataMovesStack.push(0);let a;this.backendName==null&&this.backend;let u,l=Vv(t)?t.kernelName:this.state.activeScope!=null?this.state.activeScope.name:"";if(Vv(t)){let{kernelName:d,inputs:h,attrs:g}=t;this.backendName==null&&this.backend;let y=vf(d,this.backendName);A(y!=null,()=>`Cannot find registered kernel '${d}' for backend '${this.backendName}'`),a=()=>{let b=this.backend.numDataIds();u=y.kernelFunc({inputs:h,attrs:g,backend:this.backend});let w=Array.isArray(u)?u:[u];this.shouldCheckForMemLeaks()&&this.checkKernelForMemLeak(d,b,w);let v=w.map(I=>{if(I.rank!=null)return I;let{dataId:E,shape:D,dtype:$}=I;return this.makeTensorFromDataId(E,D,$)});if(o){let I=this.getTensorsForGradient(d,h,v);n=this.saveTensorsForBackwardMode(I)}return v}}else{let{forwardFunc:d}=t,h=g=>{!o||(n=g.map(y=>this.keep(this.clone(y))))};a=()=>{let g=this.backend.numDataIds();u=this.tidy(()=>d(this.backend,h));let y=Array.isArray(u)?u:[u];return this.shouldCheckForMemLeaks()&&this.checkKernelForMemLeak(l,g,y),y}}let{inputs:c,attrs:p}=t,m=Vv(t)?null:t.backwardsFunc,f;return this.scopedRun(()=>this.state.kernelDepth++,()=>this.state.kernelDepth--,()=>{!this.ENV.getBool("DEBUG")&&!this.state.profiling?e=a():(f=this.profiler.profileKernel(l,c,()=>a()),this.ENV.getBool("DEBUG")&&this.profiler.logKernelProfile(f),e=f.outputs)}),o&&this.addTapeNode(l,c,e,m,n,p),this.state.profiling&&this.state.activeProfile.kernels.push({name:l,bytesAdded:this.state.numBytes-s,totalBytesSnapshot:this.state.numBytes,tensorsAdded:this.state.numTensors-i,totalTensorsSnapshot:this.state.numTensors,inputShapes:Object.keys(c).map(d=>c[d]!=null?c[d].shape:null),outputShapes:e.map(d=>d.shape),kernelTimeMs:f.timeMs,extraInfo:f.extraInfo}),Array.isArray(u)?e:e[0]}saveTensorsForBackwardMode(t){return t.map(n=>this.keep(this.clone(n)))}getTensorsForGradient(t,e,n){let o=Tv(t);if(o!=null){let s=o.inputsToSave||[],i=o.outputsToSave||[],a;o.saveAllInputs?(A(Array.isArray(e),()=>"saveAllInputs is true, expected inputs to be an array."),a=Object.keys(e).map(l=>e[l])):a=s.map(l=>e[l]);let 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${l.rank}.`),c!=null&&A(c.rank===2||c.rank===1,()=>`Error in batchNorm2D: offset must be rank 2 or rank 1 but got rank ${c.rank}.`),mo(i,a,u,c,l,s)}var h0=N({batchNorm2d_:_H});function EH(r,t,e,n,o,s){let i=C(r,"x","batchNorm"),a=C(t,"mean","batchNorm"),u=C(e,"variance","batchNorm"),l;o!=null&&(l=C(o,"scale","batchNorm"));let c;return n!=null&&(c=C(n,"offset","batchNorm")),A(i.rank===3,()=>`Error in batchNorm3D: x must be rank 3 but got rank ${i.rank}.`),A(a.rank===3||a.rank===1,()=>`Error in batchNorm3D: mean must be rank 3 or rank 1 but got rank ${a.rank}.`),A(u.rank===3||u.rank===1,()=>`Error in batchNorm3D: variance must be rank 3 or rank 1 but got rank ${u.rank}.`),l!=null&&A(l.rank===3||l.rank===1,()=>`Error in batchNorm3D: scale must be rank 3 or rank 1 but got rank ${l.rank}.`),c!=null&&A(c.rank===3||c.rank===1,()=>`Error in batchNorm3D: offset must be rank 3 or rank 1 but got rank ${c.rank}.`),mo(i,a,u,c,l,s)}var g0=N({batchNorm3d_:EH});function AH(r,t,e,n,o,s){let i=C(r,"x","batchNorm"),a=C(t,"mean","batchNorm"),u=C(e,"variance","batchNorm"),l;o!=null&&(l=C(o,"scale","batchNorm"));let c;return n!=null&&(c=C(n,"offset","batchNorm")),A(i.rank===4,()=>`Error in batchNorm4D: x must be rank 4 but got rank ${i.rank}.`),A(a.rank===4||a.rank===1,()=>`Error in batchNorm4D: mean must be rank 4 or rank 1 but got rank ${a.rank}.`),A(u.rank===4||u.rank===1,()=>`Error in batchNorm4D: variance must be rank 4 or rank 1 but got rank ${u.rank}.`),l!=null&&A(l.rank===4||l.rank===1,()=>`Error in batchNorm4D: scale must be rank 4 or rank 1 but got rank ${l.rank}.`),c!=null&&A(c.rank===4||c.rank===1,()=>`Error in batchNorm4D: offset must be rank 4 or rank 1 but got rank ${c.rank}.`),mo(i,a,u,c,l,s)}var x0=N({batchNorm4d_:AH});function DH(r,t,e){let n=C(r,"x","bincount"),o=C(t,"weights","bincount");A(n.dtype==="int32",()=>`Error in bincount: input dtype must be int32, but got ${n.dtype}`),A(e>=0,()=>`size must be non-negative, but got ${e}.`),A(o.size===n.size||o.size===0,()=>`Error in bincount: weights must have the same size as input or0-length, but got input shape: ${n.shape}, weights shape: ${o.shape}.`);let s={x:n,weights:o},i={size:e};return _.runKernel(up,s,i)}var zf=N({bincount_:DH});function $H(r,t){let e=C(r,"s0","broadcastArgs","int32"),n=C(t,"s1","broadcastArgs","int32");if(e.rank!==1)throw new Error(`broadcastArgs(): first input must be a vector (rank=1). 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qs=N({depthwiseConv2d_:JH});function QH(r){let e={x:C(r,"x","diag")};return _.runKernel(yp,e)}var tq=N({diag_:QH});function eq(r,t,e,n,o=[1,1],s="NHWC"){let i=C(r,"x","dilation2d"),a=C(t,"filter","dilation2d");A(i.rank===3||i.rank===4,()=>`Error in dilation2d: input must be rank 3 or 4, but got rank ${i.rank}.`),A(a.rank===3,()=>`Error in dilation2d: filter must be rank 3, but got rank ${a.rank}.`),A(s==="NHWC",()=>`Error in dilation2d: Only NHWC is currently supported, but got dataFormat of ${s}`);let u=i,l=!1;i.rank===3&&(u=O(i,[1,i.shape[0],i.shape[1],i.shape[2]]),l=!0);let c={x:u,filter:a},p={strides:e,pad:n,dilations:o},m=_.runKernel(Sl,c,p);return l?O(m,[m.shape[1],m.shape[2],m.shape[3]]):m}var Wf=N({dilation2d_:eq});function rq(r,t){let e=C(r,"a","equal","string_or_numeric"),n=C(t,"b","equal","string_or_numeric");[e,n]=jt(e,n),Lt(e.shape,n.shape);let o={a:e,b:n};return _.runKernel(ia,o)}var Sr=N({equal_:rq});function nq(r,t,e){let n=C(t,"a","where"),o=C(e,"b","where"),s=C(r,"condition","where","bool"),i=Lt(Lt(s.shape,n.shape),o.shape),a=Ga(s,i),u=Ga(n,i),l=Ga(o,i),c={condition:a,t:u,e:l};return _.runKernel(Ii,c)}var Ne=N({where_:nq});function oq(r){let e={x:C(r,"x","zerosLike")};return _.runKernel(_i,e)}var St=N({zerosLike_:oq});function sq(r,t){let e=C(r,"a","div"),n=C(t,"b","div");[e,n]=jt(e,n);let o=ct(e,n),s=St(o),i=Sr(n,s);return Ne(i,s,o)}var Uf=N({divNoNan_:sq});function iq(r,t){let e=C(r,"t1","dot"),n=C(t,"t2","dot");A((e.rank===1||e.rank===2)&&(n.rank===1||n.rank===2),()=>`Error in dot: inputs must all be rank 1 or 2, but got ranks ${e.rank} and ${n.rank}.`);let o=e.rank===1?e.size:e.shape[1],s=n.rank===1?n.size:n.shape[0];if(A(o===s,()=>`Error in dot: inner dimensions of inputs must match, but got ${o} and ${s}.`),e.rank===1&&n.rank===1){let i=O(e,[1,-1]),a=O(n,[-1,1]),u=Mt(i,a);return O(u,[])}else if(e.rank===1&&n.rank===2){let i=O(e,[1,-1]),a=O(n,[n.shape[0],n.shape[1]]),u=Mt(i,a);return 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qf=N({expm1_:mq});function fq(r,t){let e=C(r,"x","tile","string_or_numeric");A(e.rank===t.length,()=>`Error in transpose: rank of input ${e.rank} must match length of reps ${t}.`);let n={x:e},o={reps:t};return _.runKernel(jn,n,o)}var kr=N({tile_:fq});function dq(r,t,e,n="float32"){t==null&&(t=r);let o=It([r,t],n),s=r<=t?r:t;for(let a=0;a<s;++a)o.set(1,a,a);let i=O(o.toTensor(),[r,t]);if(e==null)return i;if(e.length===1)return kr(mr(i,0),[e[0],1,1]);if(e.length===2)return kr(mr(mr(i,0),0),[e[0],e[1],1,1]);if(e.length===3)return kr(mr(mr(mr(i,0),0),0),[e[0],e[1],e[2],1,1]);throw new Error(`eye() currently supports only 1D and 2D batchShapes, but received ${e.length}D.`)}var Zp=N({eye_:dq});function js(r,t,e){let n={shape:r,value:t,dtype:e};return _.runKernel(kl,{},n)}function hq(r){let e={x:C(r,"x","floor","float32")};return _.runKernel(is,e)}var Xs=N({floor_:hq});function gq(r,t,e=0,n=0){let o=C(r,"x","gather"),s=C(t,"indices","gather","int32"),i={x:o,indices:s},a={axis:e,batchDims:n};return _.runKernel(yi,i,a)}var fo=N({gather_:gq});function xq(r,t){let e=C(r,"a","greater","string_or_numeric"),n=C(t,"b","greater","string_or_numeric");[e,n]=jt(e,n),Lt(e.shape,n.shape);let o={a:e,b:n};return _.runKernel(ca,o)}var Ge=N({greater_:xq});function yq(r,t){let e=C(r,"a","greaterEqual","string_or_numeric"),n=C(t,"b","greaterEqual","string_or_numeric");[e,n]=jt(e,n),Lt(e.shape,n.shape);let o={a:e,b:n};return _.runKernel(us,o)}var Sn=N({greaterEqual_:yq});function bq(r){let e={input:C(r,"input","imag")};return _.runKernel(Ip,e)}var zu=N({imag_:bq});function wq(r){let e={x:C(r,"x","isFinite")};return _.runKernel(pa,e)}var T0=N({isFinite_:wq});function vq(r){let e={x:C(r,"x","isInf")};return _.runKernel(ma,e)}var _0=N({isInf_:vq});function Cq(r){let e={x:C(r,"x","isNaN")};return _.runKernel(fa,e)}var Kf=N({isNaN_:Cq});function Iq(r,t=.2){let 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Error("getWeights() is not implemented for Adamax yet.")}async setWeights(t){throw new Error("setWeights() is not implemented for Adamax yet.")}getConfig(){return{learningRate:this.learningRate,beta1:this.beta1,beta2:this.beta2,epsilon:this.epsilon,decay:this.decay}}static fromConfig(t,e){return new t(e.learningRate,e.beta1,e.beta2,e.epsilon,e.decay)}};ac.className="Adamax";In(ac);var tl=class extends jr{constructor(t){super();this.learningRate=t,this.setLearningRate(t)}applyGradients(t){(Array.isArray(t)?t.map(n=>n.name):Object.keys(t)).forEach((n,o)=>{let s=Array.isArray(t)?t[o].tensor:t[n];if(s==null)return;let i=_.registeredVariables[n];B(()=>{let a=J(P(this.c,s),i);i.assign(a)})}),this.incrementIterations()}setLearningRate(t){this.learningRate=t,this.c!=null&&this.c.dispose(),this.c=Pe(pt(-t))}dispose(){this.c.dispose()}async getWeights(){return[await this.saveIterations()]}async setWeights(t){if(t=await this.extractIterations(t),t.length!==0)throw new Error("SGD optimizer does 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Provided ${e} not understood: ${JSON.stringify(r)}`)}function uy(r,t){return KX(r,t,"classWeight")}async function cy(r,t,e,n){if(t!=null||n!=null)throw new Error("Support sampleWeight is not implemented yet");if(e!=null){let o=B(()=>{if(r.shape.length===1)return Cn(r);if(r.shape.length===2){if(r.shape[1]>1)return Us(r,1);if(r.shape[1]===1)return O(r,[r.shape[0]]);throw new Error(`Encountered unexpected last-dimension size (${r.shape[1]}) during handling of class weights. The size is expected to be >= 1.`)}else throw new Error(`Unexpected rank of target (y) tensor (${r.rank}) during handling of class weights. The rank is expected to be 1 or 2.`)}),s=Array.from(await o.data());_t(o);let i=[];return s.forEach(a=>{if(e[a]==null)throw new Error(`classWeight must contain all classes in the training data. 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compiled before being used.");return this.model.evaluate(t,e,n)}async evaluateDataset(t,e){if(!this.built)throw new Xr("The model needs to be compiled before being used.");return this.model.evaluateDataset(t,e)}predict(t,e={}){return this.model==null&&this.build(),this.model.predict(t,e)}predictOnBatch(t){return this.model==null&&this.build(),this.model.predictOnBatch(t)}compile(t){this.build(),this.model.compile(t),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(t){this.model.optimizer=t}async fit(t,e,n={}){if(!this.built)throw new Xr("The model needs to be compiled before being used.");return this.model.fit(t,e,n)}async fitDataset(t,e){if(!this.built)throw new Xr("The model needs to be compiled before being used.");return this.model.fitDataset(t,e)}async trainOnBatch(t,e){return this.model.trainOnBatch(t,e)}static fromConfig(t,e,n={},o=!1){let s,i={};if(e instanceof Array){if(e[0].className==null||e[0].className==="Merge")throw new z("Legacy serialization format not supported yet.");s=e}else x.assert(e.layers!=null,()=>"When the config data for a Sequential model is not an Array, it must be an Object that contains the 'layers' field."),s=e.layers,delete e.layers,i=e;let a=new t(i);if(!(a instanceof ol))throw new Tt(`Sequential.fromConfig called on non-Sequential input: ${a}`);for(let u of s){let c=gn(u,void 0,o);o&&c.setFastWeightInitDuringBuild(!0),a.add(c)}return a}set stopTraining(t){if(this.model==null)throw new z("Cannot set the stopTraining property of a sequential model before it is compiled.");this.model.stopTraining=t}get stopTraining(){if(this.model==null)throw new z("Cannot get the stopTraining property of a sequential model before it is compiled.");return this.model.stopTraining}getConfig(){let t=[];for(let e of this.layers){let n={};n.className=e.getClassName(),n.config=e.getConfig(),t.push(n)}return{name:this.name,layers:t}}};ol.className="Sequential";et.registerClass(ol);function i8(r){return new Qn(r)}function a8(r){return new ol(r)}function l8(r,t){return t==null&&(t={}),SD(r,t)}function TC(r){return Qx(r)}function u8(r,t){_n.registerCallbackConstructor(r,t)}var xn=class extends et.Serializable{getConfig(){return{}}},EC=class extends xn{apply(t,e=1){return H2(t,e)}};EC.className="elu";et.registerClass(EC);var AC=class extends xn{apply(t){return ju(t)}};AC.className="selu";et.registerClass(AC);var DC=class extends xn{apply(t){return Tr(t)}};DC.className="relu";et.registerClass(DC);var $C=class extends xn{apply(t){return B(()=>Ys(6,Tr(t)))}};$C.className="relu6";et.registerClass($C);var RC=class extends xn{apply(t){return t}};RC.className="linear";et.registerClass(RC);var FC=class extends xn{apply(t){return 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t={};return t.className="linear",t.config={},_C(t)}if(typeof r=="string"){let t={};return t.className=r,t.config={},_C(t)}else return r instanceof xn?r:_C(r)}function GC(r){if(r!=null&&typeof r!="object")throw new Error(`Argument to L1L2 regularizer's constructor is expected to be an object, but received: ${r}`)}var WC=class extends et.Serializable{},yc=class extends WC{constructor(t){super();GC(t),this.l1=t==null||t.l1==null?.01:t.l1,this.l2=t==null||t.l2==null?.01:t.l2,this.hasL1=this.l1!==0,this.hasL2=this.l2!==0}apply(t){return B(()=>{let e=ye([1]);return this.hasL1&&(e=J(e,mt(P(this.l1,Se(t))))),this.hasL2&&(e=J(e,mt(P(this.l2,fc(t))))),O(e,[])})}getConfig(){return{l1:this.l1,l2:this.l2}}static fromConfig(t,e){return new t({l1:e.l1,l2:e.l2})}};yc.className="L1L2";et.registerClass(yc);function TD(r){return GC(r),new yc({l1:r!=null?r.l1:null,l2:0})}function _D(r){return GC(r),new yc({l2:r!=null?r.l2:null,l1:0})}var kD={l1l2:"L1L2"};function pe(r){return om(r)}function ND(r,t={}){return Mi(r,et.SerializationMap.getMap().classNameMap,t,"regularizer")}function ve(r){if(r==null)return null;if(typeof r=="string"){let e={className:r in kD?kD[r]:r,config:{}};return ND(e)}else return r instanceof WC?r:ND(r)}var Od=class extends Wt{constructor(t){super(t==null?{}:t);this.supportsMasking=!0,t!=null&&(this.maxValue=t.maxValue)}call(t,e){t=Pt(t);let n=Tr(t);return this.maxValue!=null&&(n=br(n,0,this.maxValue)),n}computeOutputShape(t){return t}getConfig(){let t={maxValue:this.maxValue},e=super.getConfig();return Object.assign(t,e),t}};Od.className="ReLU";et.registerClass(Od);var Pd=class extends Wt{constructor(t){super(t==null?{}:t);this.DEFAULT_ALPHA=.3,t==null&&(t={}),this.alpha=t.alpha==null?this.DEFAULT_ALPHA:t.alpha}call(t,e){let n=Pt(t);return Ua(n,this.alpha)}computeOutputShape(t){return t}getConfig(){let t={alpha:this.alpha},e=super.getConfig();return Object.assign(t,e),t}};Pd.className="LeakyReLU";et.registerClass(Pd);var Md=class extends Wt{constructor(t){super(t==null?{}:t);if(this.DEFAULT_ALPHA_INITIALIZER="zeros",t==null&&(t={}),this.supportsMasking=!0,this.alphaInitializer=de(t.alphaInitializer||this.DEFAULT_ALPHA_INITIALIZER),this.alphaRegularizer=ve(t.alphaRegularizer),this.alphaConstraint=Ue(t.alphaConstraint),t.sharedAxes==null)this.sharedAxes=null;else if(Array.isArray(t.sharedAxes))this.sharedAxes=t.sharedAxes;else if(typeof t.sharedAxes=="number")this.sharedAxes=[t.sharedAxes];else throw new z(`Expected sharedAxes to be a number or an array of numbers, but got ${t.sharedAxes}`)}build(t){t=Jt(t);let e=t.slice(1);if(this.sharedAxes!=null)for(let o of this.sharedAxes)e[o-1]=1;this.alpha=this.addWeight("alpha",e,"float32",this.alphaInitializer,this.alphaRegularizer,!0,this.alphaConstraint);let n={};if(this.sharedAxes!=null)for(let o=1;o<t.length;++o)n[o]=t[o];this.inputSpec=[new _e({ndim:t.length,axes:n})],this.built=!0}call(t,e){return t=Pt(t),Xa(t,this.alpha.read())}getConfig(){let t={alphaInitializer:Te(this.alphaInitializer),alphaRegularizer:pe(this.alphaRegularizer),alphaConstraint:We(this.alphaConstraint),sharedAxes:this.sharedAxes},e=super.getConfig();return Object.assign(t,e),t}};Md.className="PReLU";et.registerClass(Md);var Ld=class extends Wt{constructor(t){super(t==null?{}:t);if(this.DEFAULT_ALPHA=1,t==null&&(t={}),t.alpha!=null&&t.alpha!==this.DEFAULT_ALPHA)throw new Tt(`Non-default alpha value (${t.alpha}) is not supported by the ELU layer yet.`);this.alpha=t.alpha==null?this.DEFAULT_ALPHA:t.alpha}call(t,e){let n=Pt(t);return Ks(n)}computeOutputShape(t){return t}getConfig(){let t={alpha:this.alpha},e=super.getConfig();return Object.assign(t,e),t}};Ld.className="ELU";et.registerClass(Ld);var zd=class extends Wt{constructor(t){super(t==null?{}:t);this.DEFAULT_THETA=1,t==null&&(t={}),this.theta=t.theta==null?this.DEFAULT_THETA:t.theta}call(t,e){let n=Pt(t);return P(n,Z(Ge(n,this.theta),"float32"))}computeOutputShape(t){return t}getConfig(){let t={theta:this.theta},e=super.getConfig();return Object.assign(t,e),t}};zd.className="ThresholdedReLU";et.registerClass(zd);var Bd=class extends Wt{constructor(t){super(t==null?{}:t);this.DEFAULT_AXIS=1,t==null&&(t={}),this.softmax=new Fd().apply,this.axis=t.axis==null?this.DEFAULT_AXIS:t.axis}call(t,e){let n=Pt(t);return this.softmax(n,this.axis)}computeOutputShape(t){return t}getConfig(){let t={axis:this.axis},e=super.getConfig();return Object.assign(t,e),t}};Bd.className="Softmax";et.registerClass(Bd);function Xl(r,t,e){if(typeof r=="number")return vo(r,t);if(r.length!==t)throw new z(`The ${e} argument must be an integer or tuple of ${t} integers. 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z(`conv3dWithBias expects input to be of rank 4 or 5, but received ${r.rank}.`);if(t.rank!==4&&t.rank!==5)throw new z(`conv3dWithBias expects kernel to be of rank 4 or 5, but received ${r.rank}.`);let a=UC(r,s);if(o==="causal")throw new Tt("The support for CAUSAL padding mode in conv3dWithBias is not implemented yet.");return a=Vf(a,t,n,o==="same"?"same":"valid","NDHWC",i),e!=null&&(a=fn(a,e)),s==="channelsFirst"&&(a=Vt(a,[0,4,1,2,3])),a})}var Im=class extends Wt{constructor(t,e){super(e);if(this.bias=null,this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_BIAS_INITIALIZER="zeros",Im.verifyArgs(e),this.rank=t,Qe(this.rank,"rank"),this.rank!==1&&this.rank!==2&&this.rank!==3)throw new Tt(`Convolution layer for rank other than 1, 2, or 3 (${this.rank}) is not implemented yet.`);if(this.kernelSize=Xl(e.kernelSize,t,"kernelSize"),this.strides=Xl(e.strides==null?1:e.strides,t,"strides"),this.padding=e.padding==null?"valid":e.padding,mn(this.padding),this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,Me(this.dataFormat),this.activation=oi(e.activation),this.useBias=e.useBias==null?!0:e.useBias,this.biasInitializer=de(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.biasConstraint=Ue(e.biasConstraint),this.biasRegularizer=ve(e.biasRegularizer),this.activityRegularizer=ve(e.activityRegularizer),this.dilationRate=Xl(e.dilationRate==null?1:e.dilationRate,t,"dilationRate"),this.rank===1&&Array.isArray(this.dilationRate)&&this.dilationRate.length!==1)throw new z(`dilationRate must be a number or an array of a single number for 1D convolution, but received ${JSON.stringify(this.dilationRate)}`);if(this.rank===2){if(typeof this.dilationRate=="number")this.dilationRate=[this.dilationRate,this.dilationRate];else if(this.dilationRate.length!==2)throw new z(`dilationRate must be a number or array of two numbers for 2D convolution, but received ${JSON.stringify(this.dilationRate)}`)}else if(this.rank===3){if(typeof this.dilationRate=="number")this.dilationRate=[this.dilationRate,this.dilationRate,this.dilationRate];else if(this.dilationRate.length!==3)throw new z(`dilationRate must be a number or array of three numbers for 3D convolution, but received ${JSON.stringify(this.dilationRate)}`)}}static verifyArgs(t){if(Zn("kernelSize"in t,"required key 'kernelSize' not in config"),typeof t.kernelSize!="number"&&!Vx(t.kernelSize,"number",1,3))throw new z(`BaseConv expects config.kernelSize to be number or number[] with length 1, 2, or 3, but received ${JSON.stringify(t.kernelSize)}.`)}getConfig(){let t={kernelSize:this.kernelSize,strides:this.strides,padding:this.padding,dataFormat:this.dataFormat,dilationRate:this.dilationRate,activation:ni(this.activation),useBias:this.useBias,biasInitializer:Te(this.biasInitializer),biasRegularizer:pe(this.biasRegularizer),activityRegularizer:pe(this.activityRegularizer),biasConstraint:We(this.biasConstraint)},e=super.getConfig();return Object.assign(t,e),t}},bc=class extends Im{constructor(t,e){super(t,e);this.kernel=null,bc.verifyArgs(e),this.filters=e.filters,Qe(this.filters,"filters"),this.kernelInitializer=de(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.kernelConstraint=Ue(e.kernelConstraint),this.kernelRegularizer=ve(e.kernelRegularizer)}build(t){t=Jt(t);let e=this.dataFormat==="channelsFirst"?1:t.length-1;if(t[e]==null)throw new z(`The channel dimension of the input should be defined. 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Found `None`.");let n=t[e],o=this.kernelSize.concat([this.filters,n]);this.kernel=this.addWeight("kernel",o,"float32",this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[new _e({ndim:5,axes:{[e]:n}})],this.built=!0}call(t,e){return B(()=>{let n=Pt(t);if(n.shape.length!==5)throw new z(`Conv3DTranspose.call() expects input tensor to be rank-4, but received a tensor of rank-${n.shape.length}`);let o=n.shape,s=o[0],i,a,u;this.dataFormat==="channelsFirst"?(u=2,i=3,a=4):(u=1,i=2,a=3);let l=o[u],c=o[i],p=o[a],m=this.kernelSize[0],f=this.kernelSize[1],d=this.kernelSize[2],h=this.strides[0],g=this.strides[1],y=this.strides[2],b=si(l,h,m,this.padding),w=si(c,g,f,this.padding),v=si(p,y,d,this.padding),I=[s,b,w,v,this.filters];this.dataFormat!=="channelsLast"&&(n=Vt(n,[0,2,3,4,1]));let E=I0(n,this.kernel.read(),I,this.strides,this.padding);return this.dataFormat!=="channelsLast"&&(E=Vt(E,[0,4,1,2,3])),this.bias!==null&&(E=fn(E,this.bias.read(),this.dataFormat)),this.activation!==null&&(E=this.activation.apply(E)),E})}computeOutputShape(t){t=Jt(t);let e=t.slice(),n,o,s,i;this.dataFormat==="channelsFirst"?(n=1,o=2,s=3,i=4):(n=4,o=1,s=2,i=3);let a=this.kernelSize[0],u=this.kernelSize[1],l=this.kernelSize[2],c=this.strides[0],p=this.strides[1],m=this.strides[2];return e[n]=this.filters,e[o]=si(e[o],c,a,this.padding),e[s]=si(e[s],p,u,this.padding),e[i]=si(e[i],m,l,this.padding),e}getConfig(){let t=super.getConfig();return delete t.dilationRate,t}};Wd.className="Conv3DTranspose";et.registerClass(Wd);var HC=class extends bc{constructor(t,e){super(t,e);if(this.DEFAULT_DEPTHWISE_INITIALIZER="glorotUniform",this.DEFAULT_POINTWISE_INITIALIZER="glorotUniform",this.depthwiseKernel=null,this.pointwiseKernel=null,e.filters==null)throw new z("The `filters` configuration field is required by SeparableConv, but is unspecified.");if(e.kernelInitializer!=null||e.kernelRegularizer!=null||e.kernelConstraint!=null)throw new z("Fields kernelInitializer, kernelRegularizer and kernelConstraint are invalid for SeparableConv2D. Use depthwiseInitializer, depthwiseRegularizer, depthwiseConstraint, pointwiseInitializer, pointwiseRegularizer and pointwiseConstraint instead.");if(e.padding!=null&&e.padding!=="same"&&e.padding!=="valid")throw new z(`SeparableConv${this.rank}D supports only padding modes: 'same' and 'valid', but received ${JSON.stringify(e.padding)}`);this.depthMultiplier=e.depthMultiplier==null?1:e.depthMultiplier,this.depthwiseInitializer=de(e.depthwiseInitializer||this.DEFAULT_DEPTHWISE_INITIALIZER),this.depthwiseRegularizer=ve(e.depthwiseRegularizer),this.depthwiseConstraint=Ue(e.depthwiseConstraint),this.pointwiseInitializer=de(e.depthwiseInitializer||this.DEFAULT_POINTWISE_INITIALIZER),this.pointwiseRegularizer=ve(e.pointwiseRegularizer),this.pointwiseConstraint=Ue(e.pointwiseConstraint)}build(t){if(t=Jt(t),t.length<this.rank+2)throw new z(`Inputs to SeparableConv${this.rank}D should have rank ${this.rank+2}, but received input shape: ${JSON.stringify(t)}`);let e=this.dataFormat==="channelsFirst"?1:t.length-1;if(t[e]==null||t[e]<0)throw new z(`The channel dimension of the inputs should be defined, but found ${JSON.stringify(t[e])}`);let n=t[e],o=this.kernelSize.concat([n,this.depthMultiplier]),s=[];for(let a=0;a<this.rank;++a)s.push(1);s.push(n*this.depthMultiplier,this.filters);let i=!0;this.depthwiseKernel=this.addWeight("depthwise_kernel",o,"float32",this.depthwiseInitializer,this.depthwiseRegularizer,i,this.depthwiseConstraint),this.pointwiseKernel=this.addWeight("pointwise_kernel",s,"float32",this.pointwiseInitializer,this.pointwiseRegularizer,i,this.pointwiseConstraint),this.useBias?this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,i,this.biasConstraint):this.bias=null,this.inputSpec=[new _e({ndim:this.rank+2,axes:{[e]:n}})],this.built=!0}call(t,e){return B(()=>{t=Pt(t);let n;if(this.rank===1)throw new Tt("1D separable convolution is not implemented yet.");return this.rank===2&&(this.dataFormat==="channelsFirst"&&(t=Vt(t,[0,2,3,1])),n=ed(t,this.depthwiseKernel.read(),this.pointwiseKernel.read(),this.strides,this.padding,this.dilationRate,"NHWC")),this.useBias&&(n=fn(n,this.bias.read(),this.dataFormat)),this.activation!=null&&(n=this.activation.apply(n)),this.dataFormat==="channelsFirst"&&(n=Vt(n,[0,3,1,2])),n})}getConfig(){let t=super.getConfig();return delete t.rank,delete t.kernelInitializer,delete t.kernelRegularizer,delete t.kernelConstraint,t.depthwiseInitializer=Te(this.depthwiseInitializer),t.pointwiseInitializer=Te(this.pointwiseInitializer),t.depthwiseRegularizer=pe(this.depthwiseRegularizer),t.pointwiseRegularizer=pe(this.pointwiseRegularizer),t.depthwiseConstraint=We(this.depthwiseConstraint),t.pointwiseConstraint=We(this.pointwiseConstraint),t}};HC.className="SeparableConv";var Ud=class extends HC{constructor(t){super(2,t)}};Ud.className="SeparableConv2D";et.registerClass(Ud);var wc=class extends bc{constructor(t){super(1,t);wc.verifyArgs(t),this.inputSpec=[{ndim:3}]}getConfig(){let t=super.getConfig();return delete t.rank,delete t.dataFormat,t}static verifyArgs(t){if(typeof t.kernelSize!="number"&&!Vx(t.kernelSize,"number",1,1))throw new z(`Conv1D expects config.kernelSize to be number or number[] with length 1, but received ${JSON.stringify(t.kernelSize)}.`)}};wc.className="Conv1D";et.registerClass(wc);var Hd=class extends Wt{constructor(t){super(t);typeof t.cropping=="number"?this.cropping=[[t.cropping,t.cropping],[t.cropping,t.cropping]]:typeof t.cropping[0]=="number"?this.cropping=[[t.cropping[0],t.cropping[0]],[t.cropping[1],t.cropping[1]]]:this.cropping=t.cropping,this.dataFormat=t.dataFormat===void 0?"channelsLast":t.dataFormat,this.inputSpec=[{ndim:4}]}computeOutputShape(t){return this.dataFormat==="channelsFirst"?[t[0],t[1],t[2]-this.cropping[0][0]-this.cropping[0][1],t[3]-this.cropping[1][0]-this.cropping[1][1]]:[t[0],t[1]-this.cropping[0][0]-this.cropping[0][1],t[2]-this.cropping[1][0]-this.cropping[1][1],t[3]]}call(t,e){return B(()=>{if(t=Pt(t),this.dataFormat==="channelsLast"){let n=yd(t,this.cropping[0][0],t.shape[1]-this.cropping[0][0]-this.cropping[0][1],2);return yd(n,this.cropping[1][0],t.shape[2]-this.cropping[1][1]-this.cropping[1][0],3)}else{let n=yd(t,this.cropping[0][0],t.shape[2]-this.cropping[0][0]-this.cropping[0][1],3);return yd(n,this.cropping[1][0],t.shape[3]-this.cropping[1][1]-this.cropping[1][0],4)}})}getConfig(){let t={cropping:this.cropping,dataFormat:this.dataFormat},e=super.getConfig();return Object.assign(t,e),t}};Hd.className="Cropping2D";et.registerClass(Hd);var qd=class extends Wt{constructor(t){super(t);this.DEFAULT_SIZE=[2,2],this.inputSpec=[{ndim:4}],this.size=t.size==null?this.DEFAULT_SIZE:t.size,this.dataFormat=t.dataFormat==null?"channelsLast":t.dataFormat,Me(this.dataFormat),this.interpolation=t.interpolation==null?"nearest":t.interpolation,z2(this.interpolation)}computeOutputShape(t){if(this.dataFormat==="channelsFirst"){let e=t[2]==null?null:this.size[0]*t[2],n=t[3]==null?null:this.size[1]*t[3];return[t[0],t[1],e,n]}else{let e=t[1]==null?null:this.size[0]*t[1],n=t[2]==null?null:this.size[1]*t[2];return[t[0],e,n,t[3]]}}call(t,e){return B(()=>{let n=Pt(t),o=n.shape;if(this.dataFormat==="channelsFirst"){n=Vt(n,[0,2,3,1]);let s=this.size[0]*o[2],i=this.size[1]*o[3],a=this.interpolation==="nearest"?Nn.resizeNearestNeighbor(n,[s,i]):Nn.resizeBilinear(n,[s,i]);return Vt(a,[0,3,1,2])}else{let s=this.size[0]*o[1],i=this.size[1]*o[2];return this.interpolation==="nearest"?Nn.resizeNearestNeighbor(n,[s,i]):Nn.resizeBilinear(n,[s,i])}})}getConfig(){let t={size:this.size,dataFormat:this.dataFormat},e=super.getConfig();return Object.assign(t,e),t}};qd.className="UpSampling2D";et.registerClass(qd);function f8(r,t,e=[1,1],n="valid",o,s){return B(()=>{o==null&&(o=pn()),Me(o);let i=Vd(r,o);if(r.rank!==4)throw new z(`Input for depthwiseConv2d is required to be 4-D, but is instead ${r.rank}-D`);if(t.rank!==4)throw new z(`depthwiseKernel is required to be 4-D, but is instead ${t.rank}-D`);return i=qs(i,t,e,n==="same"?"same":"valid","NHWC",s),o==="channelsFirst"&&(i=Vt(i,[0,3,1,2])),i})}var Kd=class extends Im{constructor(t){super(2,t);this.depthwiseKernel=null,this.depthMultiplier=t.depthMultiplier==null?1:t.depthMultiplier,this.depthwiseInitializer=de(t.depthwiseInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.depthwiseConstraint=Ue(t.depthwiseConstraint),this.depthwiseRegularizer=ve(t.depthwiseRegularizer)}build(t){if(t=Jt(t),t.length<4)throw new z(`Inputs to DepthwiseConv2D should have rank 4. Received input shape: ${JSON.stringify(t)}.`);let e=this.dataFormat==="channelsFirst"?1:3;if(t[e]==null||t[e]<0)throw new z(`The channel dimension of the inputs to DepthwiseConv2D should be defined, but is not (${t[e]}).`);let n=t[e],o=[this.kernelSize[0],this.kernelSize[1],n,this.depthMultiplier];this.depthwiseKernel=this.addWeight("depthwise_kernel",o,null,this.depthwiseInitializer,this.depthwiseRegularizer,!0,this.depthwiseConstraint),this.useBias?this.bias=this.addWeight("bias",[n*this.depthMultiplier],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint):this.bias=null,this.built=!0}call(t,e){return B(()=>{t=Pt(t);let n=f8(t,this.depthwiseKernel.read(),this.strides,this.padding,this.dataFormat,null);return this.useBias&&(n=fn(n,this.bias.read(),this.dataFormat)),this.activation!=null&&(n=this.activation.apply(n)),n})}computeOutputShape(t){t=Jt(t);let e=this.dataFormat==="channelsFirst"?t[2]:t[1],n=this.dataFormat==="channelsFirst"?t[3]:t[2],o=this.dataFormat==="channelsFirst"?t[1]*this.depthMultiplier:t[3]*this.depthMultiplier,s=En(e,this.kernelSize[0],this.padding,this.strides[0]),i=En(n,this.kernelSize[1],this.padding,this.strides[1]);return this.dataFormat==="channelsFirst"?[t[0],o,s,i]:[t[0],s,i,o]}getConfig(){let t=super.getConfig();return t.depthMultiplier=this.depthMultiplier,t.depthwiseInitializer=Te(this.depthwiseInitializer),t.depthwiseRegularizer=pe(this.depthwiseRegularizer),t.depthwiseConstraint=We(this.depthwiseRegularizer),t}};Kd.className="DepthwiseConv2D";et.registerClass(Kd);function qC(r,t,e,n){if(Array.isArray(r)){if(t!=null||e!=null)throw new z("When inputs is an array, neither initialState or constants should be provided");n!=null&&(e=r.slice(r.length-n,r.length),r=r.slice(0,r.length-n)),r.length>1&&(t=r.slice(1,r.length)),r=r[0]}function o(s){return s==null||Array.isArray(s)?s:[s]}return t=o(t),e=o(e),{inputs:r,initialState:t,constants:e}}function KC(r,t,e,n=!1,o,s,i=!1,a=!1){return B(()=>{let u=t.shape.length;if(u<3)throw new z(`Input should be at least 3D, but is ${u}D.`);let l=[1,0].concat(Yr(2,u));if(t=Vt(t,l),s!=null)throw new Tt("The rnn() functoin of the deeplearn.js backend does not support constants yet.");i&&console.warn("Backend rnn(): the unroll = true option is not applicable to the imperative deeplearn.js backend."),o!=null&&(o=Z(Z(o,"bool"),"float32"),o.rank===u-1&&(o=mr(o,-1)),o=Vt(o,l)),n&&(t=or(t,0),o!=null&&(o=or(o,0)));let c=[],p,m=e,f=t.shape[0],d=vr(t),h;o!=null&&(h=vr(o));for(let y=0;y<f;++y){let b=d[y],w=B(()=>r(b,m));if(o==null)p=w[0],m=w[1];else{let v=B(()=>{let I=h[y],E=lt(fr(I),I),D=J(P(w[0],I),P(m[0],E)),$=m.map((R,M)=>J(P(w[1][M],I),P(R,E)));return{output:D,newStates:$}});p=v.output,m=v.newStates}a&&c.push(p)}let g;return a&&(g=Ye(c,1)),[p,g,m]})}var zn=class extends Wt{constructor(t){super(t);let e;if(t.cell==null)throw new z("cell property is missing for the constructor of RNN.");if(Array.isArray(t.cell)?e=new Nm({cells:t.cell}):e=t.cell,e.stateSize==null)throw new z("The RNN cell should have an attribute `stateSize` (tuple of integers, one integer per RNN state).");this.cell=e,this.returnSequences=t.returnSequences==null?!1:t.returnSequences,this.returnState=t.returnState==null?!1:t.returnState,this.goBackwards=t.goBackwards==null?!1:t.goBackwards,this._stateful=t.stateful==null?!1:t.stateful,this.unroll=t.unroll==null?!1:t.unroll,this.supportsMasking=!0,this.inputSpec=[new _e({ndim:3})],this.stateSpec=null,this.states_=null,this.numConstants=null,this.keptStates=[]}getStates(){if(this.states_==null){let t=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1;return Yr(0,t).map(e=>null)}else return this.states_}setStates(t){this.states_=t}computeOutputShape(t){Zx(t)&&(t=t[0]),t=t;let e=this.cell.stateSize;Array.isArray(e)||(e=[e]);let n=e[0],o;if(this.returnSequences?o=[t[0],t[1],n]:o=[t[0],n],this.returnState){let s=[];for(let i of e)s.push([t[0],i]);return[o].concat(s)}else return o}computeMask(t,e){return B(()=>{Array.isArray(e)&&(e=e[0]);let n=this.returnSequences?e:null;if(this.returnState){let o=this.states.map(s=>null);return[n].concat(o)}else return n})}get states(){if(this.states_==null){let t=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1,e=[];for(let n=0;n<t;++n)e.push(null);return e}else return this.states_}set states(t){this.states_=t}build(t){if(this.numConstants!=null)throw new Tt("Constants support is not implemented in RNN yet.");Zx(t)&&(t=t[0]),t=t;let n=this.stateful?t[0]:null,o=t.slice(2);this.inputSpec[0]=new _e({shape:[n,null,...o]});let s=[t[0]].concat(t.slice(2));this.cell.build(s);let i;if(Array.isArray(this.cell.stateSize)?i=this.cell.stateSize:i=[this.cell.stateSize],this.stateSpec!=null){if(!x.arraysEqual(this.stateSpec.map(a=>a.shape[a.shape.length-1]),i))throw new z(`An initialState was passed that is not compatible with cell.stateSize. Received stateSpec=${this.stateSpec}; However cell.stateSize is ${this.cell.stateSize}`)}else this.stateSpec=i.map(a=>new _e({shape:[null,a]}));this.stateful&&this.resetStates()}resetStates(t,e=!1){B(()=>{if(!this.stateful)throw new Ln("Cannot call resetStates() on an RNN Layer that is not stateful.");let n=this.inputSpec[0].shape[0];if(n==null)throw new z("If an RNN is stateful, it needs to know its batch size. Specify the batch size of your input tensors: \n- If using a Sequential model, specify the batch size by passing a `batchInputShape` option to your first layer.\n- If using the functional API, specify the batch size by passing a `batchShape` option to your Input layer.");if(this.states_==null)Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(o=>ye([n,o])):this.states_=[ye([n,this.cell.stateSize])];else if(t==null)_t(this.states_),this.keptStates!=null&&(_t(this.keptStates),this.keptStates=[]),Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(o=>ye([n,o])):this.states_[0]=ye([n,this.cell.stateSize]);else{if(Array.isArray(t)||(t=[t]),t.length!==this.states_.length)throw new z(`Layer ${this.name} expects ${this.states_.length} state(s), but it received ${t.length} state value(s). Input received: ${t}`);e===!0?this.keptStates.push(this.states_.slice()):_t(this.states_);for(let o=0;o<this.states_.length;++o){let s=t[o],i=Array.isArray(this.cell.stateSize)?this.cell.stateSize[o]:this.cell.stateSize,a=[n,i];if(!x.arraysEqual(s.shape,a))throw new z(`State ${o} is incompatible with layer ${this.name}: expected shape=${a}, received shape=${s.shape}`);this.states_[o]=s}}this.states_=this.states_.map(o=>Pe(o.clone()))})}apply(t,e){let n=e==null?null:e.initialState,o=e==null?null:e.constants;e==null&&(e={});let s=qC(t,n,o,this.numConstants);t=s.inputs,n=s.initialState,o=s.constants;let i=[],a=[];if(n!=null){e.initialState=n,i=i.concat(n),this.stateSpec=[];for(let l of n)this.stateSpec.push(new _e({shape:l.shape}));a=a.concat(this.stateSpec)}if(o!=null&&(e.constants=o,i=i.concat(o),this.numConstants=o.length),i[0]instanceof hn){let l=[t].concat(i),c=this.inputSpec.concat(a),p=this.inputSpec;this.inputSpec=c;let m=super.apply(l,e);return this.inputSpec=p,m}else return super.apply(t,e)}call(t,e){return B(()=>{let n=e==null?null:e.mask,o=e==null?null:e.training,s=e==null?null:e.initialState;t=Pt(t),s==null&&(this.stateful?s=this.states_:s=this.getInitialState(t));let i=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1;if(s.length!==i)throw new z(`RNN Layer has ${i} state(s) but was passed ${s.length} initial state(s).`);this.unroll&&console.warn("Ignoring unroll = true for RNN layer, due to imperative backend.");let a={training:o},l=KC((d,h)=>{let g=this.cell.call([d].concat(h),a);return[g[0],g.slice(1)]},t,s,this.goBackwards,n,null,this.unroll,this.returnSequences),c=l[0],p=l[1],m=l[2];this.stateful&&this.resetStates(m,o);let f=this.returnSequences?p:c;return this.returnState?[f].concat(m):f})}getInitialState(t){return B(()=>{let e=ye(t.shape);return e=mt(e,[1,2]),e=nl(e),Array.isArray(this.cell.stateSize)?this.cell.stateSize.map(n=>n>1?qx(e,[1,n]):e):this.cell.stateSize>1?[qx(e,[1,this.cell.stateSize])]:[e]})}get trainableWeights(){return this.trainable?this.cell.trainableWeights:[]}get nonTrainableWeights(){return this.trainable?this.cell.nonTrainableWeights:this.cell.weights}setFastWeightInitDuringBuild(t){super.setFastWeightInitDuringBuild(t),this.cell!=null&&this.cell.setFastWeightInitDuringBuild(t)}getConfig(){let t=super.getConfig(),e={returnSequences:this.returnSequences,returnState:this.returnState,goBackwards:this.goBackwards,stateful:this.stateful,unroll:this.unroll};this.numConstants!=null&&(e.numConstants=this.numConstants);let n=this.cell.getConfig();return this.getClassName()===zn.className&&(e.cell={className:this.cell.getClassName(),config:n}),Object.assign({},n,t,e)}static fromConfig(t,e,n={}){let o=e.cell,s=gn(o,n);return new t(Object.assign(e,{cell:s}))}};zn.className="RNN";et.registerClass(zn);var Jl=class extends Wt{},Sm=class extends Jl{constructor(t){super(t);this.DEFAULT_ACTIVATION="tanh",this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_RECURRENT_INITIALIZER="orthogonal",this.DEFAULT_BIAS_INITIALIZER="zeros",this.units=t.units,Qe(this.units,"units"),this.activation=oi(t.activation==null?this.DEFAULT_ACTIVATION:t.activation),this.useBias=t.useBias==null?!0:t.useBias,this.kernelInitializer=de(t.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=de(t.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=de(t.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelRegularizer=ve(t.kernelRegularizer),this.recurrentRegularizer=ve(t.recurrentRegularizer),this.biasRegularizer=ve(t.biasRegularizer),this.kernelConstraint=Ue(t.kernelConstraint),this.recurrentConstraint=Ue(t.recurrentConstraint),this.biasConstraint=Ue(t.biasConstraint),this.dropout=pc([1,ei([0,t.dropout==null?0:t.dropout])]),this.recurrentDropout=pc([1,ei([0,t.recurrentDropout==null?0:t.recurrentDropout])]),this.dropoutFunc=t.dropoutFunc,this.stateSize=this.units,this.dropoutMask=null,this.recurrentDropoutMask=null}build(t){t=Jt(t),this.kernel=this.addWeight("kernel",[t[t.length-1],this.units],null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.recurrentKernel=this.addWeight("recurrent_kernel",[this.units,this.units],null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint),this.useBias?this.bias=this.addWeight("bias",[this.units],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint):this.bias=null,this.built=!0}call(t,e){return B(()=>{if(t=t,t.length!==2)throw new z(`SimpleRNNCell expects 2 input Tensors, got ${t.length}.`);let n=t[1];t=t[0];let o=e.training==null?!1:e.training;0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=sl({ones:()=>fr(t),rate:this.dropout,training:o,dropoutFunc:this.dropoutFunc})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=sl({ones:()=>fr(n),rate:this.recurrentDropout,training:o,dropoutFunc:this.dropoutFunc}));let s,i=this.dropoutMask,a=this.recurrentDropoutMask;i!=null?s=ko(P(t,i),this.kernel.read()):s=ko(t,this.kernel.read()),this.bias!=null&&(s=fn(s,this.bias.read())),a!=null&&(n=P(n,a));let u=J(s,ko(n,this.recurrentKernel.read()));return this.activation!=null&&(u=this.activation.apply(u)),[u,u]})}getConfig(){let t=super.getConfig(),e={units:this.units,activation:ni(this.activation),useBias:this.useBias,kernelInitializer:Te(this.kernelInitializer),recurrentInitializer:Te(this.recurrentInitializer),biasInitializer:Te(this.biasInitializer),kernelRegularizer:pe(this.kernelRegularizer),recurrentRegularizer:pe(this.recurrentRegularizer),biasRegularizer:pe(this.biasRegularizer),activityRegularizer:pe(this.activityRegularizer),kernelConstraint:We(this.kernelConstraint),recurrentConstraint:We(this.recurrentConstraint),biasConstraint:We(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout};return Object.assign({},t,e)}};Sm.className="SimpleRNNCell";et.registerClass(Sm);var jd=class extends zn{constructor(t){t.cell=new Sm(t);super(t)}call(t,e){return B(()=>{this.cell.dropoutMask!=null&&(_t(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(_t(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=e==null?null:e.mask,o=e==null?null:e.training,s=e==null?null:e.initialState;return super.call(t,{mask:n,training:o,initialState:s})})}static fromConfig(t,e){return new t(e)}};jd.className="SimpleRNN";et.registerClass(jd);var km=class extends Jl{constructor(t){super(t);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",t.resetAfter)throw new z("GRUCell does not support reset_after parameter set to true.");this.units=t.units,Qe(this.units,"units"),this.activation=oi(t.activation===void 0?this.DEFAULT_ACTIVATION:t.activation),this.recurrentActivation=oi(t.recurrentActivation===void 0?this.DEFAULT_RECURRENT_ACTIVATION:t.recurrentActivation),this.useBias=t.useBias==null?!0:t.useBias,this.kernelInitializer=de(t.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=de(t.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=de(t.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelRegularizer=ve(t.kernelRegularizer),this.recurrentRegularizer=ve(t.recurrentRegularizer),this.biasRegularizer=ve(t.biasRegularizer),this.kernelConstraint=Ue(t.kernelConstraint),this.recurrentConstraint=Ue(t.recurrentConstraint),this.biasConstraint=Ue(t.biasConstraint),this.dropout=pc([1,ei([0,t.dropout==null?0:t.dropout])]),this.recurrentDropout=pc([1,ei([0,t.recurrentDropout==null?0:t.recurrentDropout])]),this.dropoutFunc=t.dropoutFunc,this.implementation=t.implementation,this.stateSize=this.units,this.dropoutMask=null,this.recurrentDropoutMask=null}build(t){t=Jt(t);let e=t[t.length-1];this.kernel=this.addWeight("kernel",[e,this.units*3],null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.recurrentKernel=this.addWeight("recurrent_kernel",[this.units,this.units*3],null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint),this.useBias?this.bias=this.addWeight("bias",[this.units*3],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint):this.bias=null,this.built=!0}call(t,e){return B(()=>{if(t=t,t.length!==2)throw new z(`GRUCell expects 2 input Tensors (inputs, h, c), got ${t.length}.`);let n=e.training==null?!1:e.training,o=t[1];t=t[0],0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=sl({ones:()=>fr(t),rate:this.dropout,training:n,count:3,dropoutFunc:this.dropoutFunc})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=sl({ones:()=>fr(o),rate:this.recurrentDropout,training:n,count:3,dropoutFunc:this.dropoutFunc}));let s=this.dropoutMask,i=this.recurrentDropoutMask,a,u,l;0<this.dropout&&this.dropout<1&&(t=P(t,s[0]));let c=ko(t,this.kernel.read());this.useBias&&(c=fn(c,this.bias.read())),0<this.recurrentDropout&&this.recurrentDropout<1&&(o=P(o,i[0]));let p=this.recurrentKernel.read(),[m,f]=lr(p,[2*this.units,this.units],p.rank-1),d=ko(o,m),[h,g,y]=lr(c,3,c.rank-1),[b,w]=lr(d,2,d.rank-1);a=this.recurrentActivation.apply(J(h,b)),u=this.recurrentActivation.apply(J(g,w));let v=ko(P(u,o),f);l=this.activation.apply(J(y,v));let I=J(P(a,o),P(J(1,Yt(a)),l));return[I,I]})}getConfig(){let t=super.getConfig(),e={units:this.units,activation:ni(this.activation),recurrentActivation:ni(this.recurrentActivation),useBias:this.useBias,kernelInitializer:Te(this.kernelInitializer),recurrentInitializer:Te(this.recurrentInitializer),biasInitializer:Te(this.biasInitializer),kernelRegularizer:pe(this.kernelRegularizer),recurrentRegularizer:pe(this.recurrentRegularizer),biasRegularizer:pe(this.biasRegularizer),activityRegularizer:pe(this.activityRegularizer),kernelConstraint:We(this.kernelConstraint),recurrentConstraint:We(this.recurrentConstraint),biasConstraint:We(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation,resetAfter:!1};return Object.assign({},t,e)}};km.className="GRUCell";et.registerClass(km);var Xd=class extends zn{constructor(t){t.implementation===0&&console.warn("`implementation=0` has been deprecated, and now defaults to `implementation=1`. Please update your layer call."),t.cell=new km(t);super(t)}call(t,e){return B(()=>{this.cell.dropoutMask!=null&&(_t(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(_t(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=e==null?null:e.mask,o=e==null?null:e.training,s=e==null?null:e.initialState;return super.call(t,{mask:n,training:o,initialState:s})})}static fromConfig(t,e){return e.implmentation===0&&(e.implementation=1),new t(e)}};Xd.className="GRU";et.registerClass(Xd);var Ql=class extends Jl{constructor(t){super(t);this.DEFAULT_ACTIVATION="tanh",this.DEFAULT_RECURRENT_ACTIVATION="hardSigmoid",this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_RECURRENT_INITIALIZER="orthogonal",this.DEFAULT_BIAS_INITIALIZER="zeros",this.units=t.units,Qe(this.units,"units"),this.activation=oi(t.activation===void 0?this.DEFAULT_ACTIVATION:t.activation),this.recurrentActivation=oi(t.recurrentActivation===void 0?this.DEFAULT_RECURRENT_ACTIVATION:t.recurrentActivation),this.useBias=t.useBias==null?!0:t.useBias,this.kernelInitializer=de(t.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=de(t.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=de(t.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.unitForgetBias=t.unitForgetBias,this.kernelRegularizer=ve(t.kernelRegularizer),this.recurrentRegularizer=ve(t.recurrentRegularizer),this.biasRegularizer=ve(t.biasRegularizer),this.kernelConstraint=Ue(t.kernelConstraint),this.recurrentConstraint=Ue(t.recurrentConstraint),this.biasConstraint=Ue(t.biasConstraint),this.dropout=pc([1,ei([0,t.dropout==null?0:t.dropout])]),this.recurrentDropout=pc([1,ei([0,t.recurrentDropout==null?0:t.recurrentDropout])]),this.dropoutFunc=t.dropoutFunc,this.implementation=t.implementation,this.stateSize=[this.units,this.units],this.dropoutMask=null,this.recurrentDropoutMask=null}build(t){var e;t=Jt(t);let n=t[t.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 o;if(this.useBias){if(this.unitForgetBias){let s=this.biasInitializer,i=this.units;o=new(e=class extends Tn{apply(u,l){let c=s.apply([i]),p=new dc().apply([i]),m=s.apply([i*2]);return dC(dC(c,p),m)}},e.className="CustomInit",e)}else o=this.biasInitializer;this.bias=this.addWeight("bias",[this.units*4],null,o,this.biasRegularizer,!0,this.biasConstraint)}else this.bias=null;this.built=!0}call(t,e){return B(()=>{let n=e.training==null?!1:e.training;if(t=t,t.length!==3)throw new z(`LSTMCell expects 3 input Tensors (inputs, h, c), got ${t.length}.`);let o=t[1],s=t[2];t=t[0],0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=sl({ones:()=>fr(t),rate:this.dropout,training:n,count:4,dropoutFunc:this.dropoutFunc})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=sl({ones:()=>fr(o),rate:this.recurrentDropout,training:n,count:4,dropoutFunc:this.dropoutFunc}));let i=this.dropoutMask,a=this.recurrentDropoutMask,u,l,c,p;0<this.dropout&&this.dropout<1&&(t=P(t,i[0]));let m=ko(t,this.kernel.read());0<this.recurrentDropout&&this.recurrentDropout<1&&(o=P(o,a[0])),m=J(m,ko(o,this.recurrentKernel.read())),this.useBias&&(m=fn(m,this.bias.read()));let[f,d,h,g]=lr(m,4,m.rank-1);u=this.recurrentActivation.apply(f),l=this.recurrentActivation.apply(d),c=J(P(l,s),P(u,this.activation.apply(h))),p=this.recurrentActivation.apply(g);let y=P(p,this.activation.apply(c));return[y,y,c]})}getConfig(){let t=super.getConfig(),e={units:this.units,activation:ni(this.activation),recurrentActivation:ni(this.recurrentActivation),useBias:this.useBias,kernelInitializer:Te(this.kernelInitializer),recurrentInitializer:Te(this.recurrentInitializer),biasInitializer:Te(this.biasInitializer),unitForgetBias:this.unitForgetBias,kernelRegularizer:pe(this.kernelRegularizer),recurrentRegularizer:pe(this.recurrentRegularizer),biasRegularizer:pe(this.biasRegularizer),activityRegularizer:pe(this.activityRegularizer),kernelConstraint:We(this.kernelConstraint),recurrentConstraint:We(this.recurrentConstraint),biasConstraint:We(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation};return Object.assign({},t,e)}};Ql.className="LSTMCell";et.registerClass(Ql);var Yd=class extends zn{constructor(t){t.implementation===0&&console.warn("`implementation=0` has been deprecated, and now defaults to `implementation=1`. Please update your layer call."),t.cell=new Ql(t);super(t)}call(t,e){return B(()=>{this.cell.dropoutMask!=null&&(_t(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(_t(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=e==null?null:e.mask,o=e==null?null:e.training,s=e==null?null:e.initialState;return super.call(t,{mask:n,training:o,initialState:s})})}static fromConfig(t,e){return e.implmentation===0&&(e.implementation=1),new t(e)}};Yd.className="LSTM";et.registerClass(Yd);var Nm=class extends Jl{constructor(t){super(t);this.cells=t.cells}get stateSize(){let t=[];for(let e of this.cells.slice().reverse())Array.isArray(e.stateSize)?t.push(...e.stateSize):t.push(e.stateSize);return t}call(t,e){return B(()=>{t=t;let n=t.slice(1),o=[];for(let a of this.cells.slice().reverse())Array.isArray(a.stateSize)?o.push(n.splice(0,a.stateSize.length)):o.push(n.splice(0,1));o.reverse();let s=[],i;for(let a=0;a<this.cells.length;++a){let u=this.cells[a];n=o[a],a===0?i=[t[0]].concat(n):i=[i[0]].concat(n),i=u.call(i,e),s.push(i.slice(1))}n=[];for(let a of s.slice().reverse())n.push(...a);return[i[0]].concat(n)})}build(t){Zx(t)&&(t=t[0]),t=t;let e;this.cells.forEach((n,o)=>{ti(`RNNCell_${o}`,()=>{n.build(t),Array.isArray(n.stateSize)?e=n.stateSize[0]:e=n.stateSize,t=[t[0],e]})}),this.built=!0}getConfig(){let t=super.getConfig(),e=s=>({className:s.getClassName(),config:s.getConfig()}),o={cells:this.cells.map(e)};return Object.assign({},t,o)}static fromConfig(t,e,n={}){let o=[];for(let s of e.cells)o.push(gn(s,n));return new t({cells:o})}get trainableWeights(){if(!this.trainable)return[];let t=[];for(let e of this.cells)t.push(...e.trainableWeights);return t}get nonTrainableWeights(){let t=[];for(let e of this.cells)t.push(...e.nonTrainableWeights);if(!this.trainable){let e=[];for(let n of this.cells)e.push(...n.trainableWeights);return e.concat(t)}return t}getWeights(){let t=[];for(let e of this.cells)t.push(...e.weights);return Nd(t)}setWeights(t){let e=[];for(let n of this.cells){let o=n.weights.length,s=t.splice(o);for(let i=0;i<n.weights.length;++i)e.push([n.weights[i],s[i]])}xm(e)}};Nm.className="StackedRNNCells";et.registerClass(Nm);function sl(r){let{ones:t,rate:e,training:n=!1,count:o=1,dropoutFunc:s}=r,i=()=>s!=null?s(t(),e):jx(t(),e),a=()=>Ul(i,t,n);return!o||o<=1?Pe(a().clone()):Array(o).fill(void 0).map(a).map(l=>Pe(l.clone()))}var d8=function(r,t){var e={};for(var n in r)Object.prototype.hasOwnProperty.call(r,n)&&t.indexOf(n)<0&&(e[n]=r[n]);if(r!=null&&typeof Object.getOwnPropertySymbols=="function")for(var o=0,n=Object.getOwnPropertySymbols(r);o<n.length;o++)t.indexOf(n[o])<0&&Object.prototype.propertyIsEnumerable.call(r,n[o])&&(e[n[o]]=r[n[o]]);return e};var jC=class extends zn{constructor(t){if(t.unroll)throw new Tt("Unrolling is not possible with convolutional RNNs.");if(Array.isArray(t.cell))throw new Tt("It is not possible at the moment to stack convolutional cells.");super(t);this.inputSpec=[new _e({ndim:5})]}call(t,e){return B(()=>{if(this.cell.dropoutMask!=null&&(_t(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(_t(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null),e&&e.constants)throw new z("ConvRNN2D cell does not support constants");let n=e==null?null:e.mask,o=e==null?null:e.training,s=e==null?null:e.initialState;return super.call(t,{mask:n,training:o,initialState:s})})}computeOutputShape(t){let e=this.computeSingleOutputShape(t);return this.returnSequences||(e=[e[0],...e.slice(2)]),this.returnState&&(e=[e,...Array(2).fill([t[0],...e.slice(-3)])]),e}getInitialState(t){return B(()=>{let{stateSize:e}=this.cell,n=t.shape,o=this.computeSingleOutputShape(n),s=[o[0],...o.slice(2)],i=ye(s);return Array.isArray(e)?Array(e.length).fill(i):[i]})}resetStates(t,e=!1){B(()=>{if(!this.stateful)throw new Ln("Cannot call resetStates() on an RNN Layer that is not stateful.");let n=this.inputSpec[0].shape,o=this.computeSingleOutputShape(n),s=[o[0],...o.slice(2)];if(n[0]==null)throw new z("If an RNN is stateful, it needs to know its batch size. Specify the batch size of your input tensors: \n- If using a Sequential model, specify the batch size by passing a `batchInputShape` option to your first layer.\n- If using the functional API, specify the batch size by passing a `batchShape` option to your Input layer.");if(this.getStates()==null)Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(()=>ye(s)):this.states_=[ye(s)];else if(t==null)_t(this.states_),this.keptStates!=null&&(_t(this.keptStates),this.keptStates=[]),Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(()=>ye(s)):this.states_[0]=ye(s);else{if(Array.isArray(t)||(t=[t]),t.length!==this.states_.length)throw new z(`Layer ${this.name} expects ${this.states_.length} state(s), but it received ${t.length} state value(s). Input received: ${t}`);e?this.keptStates.push(this.states_.slice()):_t(this.states_);for(let a=0;a<this.states_.length;++a){let u=t[a],l=s;if(!x.arraysEqual(u.shape,l))throw new z(`State ${a} is incompatible with layer ${this.name}: expected shape=${l}, received shape=${u.shape}`);this.states_[a]=u}}this.states_=this.states_.map(a=>Pe(a.clone()))})}computeSingleOutputShape(t){let{dataFormat:e,filters:n,kernelSize:o,padding:s,strides:i,dilationRate:a}=this.cell,u=e==="channelsFirst",l=t[u?3:2],c=t[u?4:3],p=En(l,o[0],s,i[0],a[0]),m=En(c,o[1],s,i[1],a[1]);return[...t.slice(0,2),...u?[n,p,m]:[p,m,n]]}};jC.className="ConvRNN2D";var Tm=class extends Ql{constructor(t){let{filters:e,kernelSize:n,strides:o,padding:s,dataFormat:i,dilationRate:a}=t;super(Object.assign({},t,{units:e}));this.filters=e,Qe(this.filters,"filters"),this.kernelSize=Xl(n,2,"kernelSize"),this.kernelSize.forEach(u=>Qe(u,"kernelSize")),this.strides=Xl(o||1,2,"strides"),this.strides.forEach(u=>Qe(u,"strides")),this.padding=s||"valid",mn(this.padding),this.dataFormat=i||"channelsLast",Me(this.dataFormat),this.dilationRate=Xl(a||1,2,"dilationRate"),this.dilationRate.forEach(u=>Qe(u,"dilationRate"))}build(t){var e;t=Jt(t);let n=this.dataFormat==="channelsFirst"?1:t.length-1;if(t[n]==null)throw new z(`The channel dimension of the input should be defined. Found ${t[n]}`);let o=t[n],s=4,i=this.kernelSize.concat([o,this.filters*s]);this.kernel=this.addWeight("kernel",i,null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint);let a=this.kernelSize.concat([this.filters,this.filters*s]);if(this.recurrentKernel=this.addWeight("recurrent_kernel",a,null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint),this.useBias){let u;if(this.unitForgetBias){let l=this.biasInitializer,c=this.filters;u=new(e=class extends Tn{apply(m,f){let d=l.apply([c]),h=ar([c]),g=l.apply([c*2]);return am([d,h,g])}},e.className="CustomInit",e)}else u=this.biasInitializer;this.bias=this.addWeight("bias",[this.filters*s],null,u,this.biasRegularizer,!0,this.biasConstraint)}this.built=!0}call(t,e){return B(()=>{if(t.length!==3)throw new z(`ConvLSTM2DCell expects 3 input Tensors (inputs, h, c), got ${t.length}.`);let n=e.training||!1,o=t[0],s=t[1],i=t[2],a=4;0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=sl({ones:()=>fr(o),rate:this.dropout,training:n,count:a,dropoutFunc:this.dropoutFunc}));let u=this.dropoutMask,l=(st,it,ft)=>!it||!it[ft]?st:P(it[ft],st),c=l(o,u,0),p=l(o,u,1),m=l(o,u,2),f=l(o,u,3);0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=sl({ones:()=>fr(s),rate:this.recurrentDropout,training:n,count:a,dropoutFunc:this.dropoutFunc}));let d=this.recurrentDropoutMask,h=l(s,d,0),g=l(s,d,1),y=l(s,d,2),b=l(s,d,3),w=3,[v,I,E,D]=lr(this.kernel.read(),a,w),[$,R,M,W]=this.useBias?lr(this.bias.read(),a):[null,null,null,null];c=this.inputConv(c,v,$,this.padding),p=this.inputConv(p,I,R,this.padding),m=this.inputConv(m,E,M,this.padding),f=this.inputConv(f,D,W,this.padding);let[U,q,K,j]=lr(this.recurrentKernel.read(),a,w);h=this.recurrentConv(h,U),g=this.recurrentConv(g,q),y=this.recurrentConv(y,K),b=this.recurrentConv(b,j);let Q=this.recurrentActivation.apply(J(c,h)),rt=this.recurrentActivation.apply(J(p,g)),X=J(P(rt,i),P(Q,this.activation.apply(J(m,y)))),nt=P(this.recurrentActivation.apply(J(f,b)),this.activation.apply(X));return[nt,nt,X]})}getConfig(){let t=super.getConfig(),{units:e}=t,n=d8(t,["units"]),o={filters:this.filters,kernelSize:this.kernelSize,padding:this.padding,dataFormat:this.dataFormat,dilationRate:this.dilationRate,strides:this.strides};return Object.assign({},n,o)}inputConv(t,e,n,o){let s=ln(t,e,this.strides,o||"valid",this.dataFormat==="channelsFirst"?"NCHW":"NHWC",this.dilationRate);return n?fn(s,n,this.dataFormat):s}recurrentConv(t,e){return ln(t,e,1,"same",this.dataFormat==="channelsFirst"?"NCHW":"NHWC")}};Tm.className="ConvLSTM2DCell";et.registerClass(Tm);var Zd=class extends jC{constructor(t){let e=new Tm(t);super(Object.assign({},t,{cell:e}))}static fromConfig(t,e){return new t(e)}};Zd.className="ConvLSTM2D";et.registerClass(Zd);var _m=class extends Wt{constructor(t){super(t);this.rate=Math.max(Math.min(t.rate,1),0),this.noiseShape=t.noiseShape,this.seed=t.seed,this.supportsMasking=!0}getNoiseShape(t){if(this.noiseShape==null)return this.noiseShape;let e=t.shape,n=[];for(let o=0;o<this.noiseShape.length;++o)n.push(this.noiseShape[o]==null?e[o]:this.noiseShape[o]);return n}call(t,e){return B(()=>{this.invokeCallHook(t,e);let n=Pt(t);if(0<this.rate&&this.rate<1){let o=e.training==null?!1:e.training,s=this.getNoiseShape(n);return Ul(()=>jx(n,this.rate,s,this.seed),()=>n,o)}return t})}getConfig(){let t={rate:this.rate,noiseShape:this.noiseShape,seed:this.seed},e=super.getConfig();return Object.assign(t,e),t}dispose(){return super.dispose()}};_m.className="Dropout";et.registerClass(_m);var Jd=class extends _m{constructor(t){super(t);this.inputSpec=[{ndim:3}]}getNoiseShape(t){let e=t.shape;return[e[0],1,e[2]]}};Jd.className="SpatialDropout1D";et.registerClass(Jd);var Qd=class extends Wt{constructor(t){super(t);if(this.activation=null,this.useBias=!0,this.kernel=null,this.bias=null,this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_BIAS_INITIALIZER="zeros",t.batchInputShape==null&&t.inputShape==null&&t.inputDim!=null){let e=null;t.batchSize!=null&&(e=t.batchSize),this.batchInputShape=[e,t.inputDim]}this.units=t.units,Qe(this.units,"units"),this.activation=oi(t.activation),t.useBias!=null&&(this.useBias=t.useBias),this.kernelInitializer=de(t.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.biasInitializer=de(t.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelConstraint=Ue(t.kernelConstraint),this.biasConstraint=Ue(t.biasConstraint),this.kernelRegularizer=ve(t.kernelRegularizer),this.biasRegularizer=ve(t.biasRegularizer),this.activityRegularizer=ve(t.activityRegularizer),this.supportsMasking=!0,this.inputSpec=[{minNDim:2}]}build(t){t=Jt(t);let e=t[t.length-1];this.kernel==null&&(this.kernel=this.addWeight("kernel",[e,this.units],null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.units],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint))),this.inputSpec=[{minNDim:2,axes:{[-1]:e}}],this.built=!0}computeOutputShape(t){t=Jt(t);let e=t.slice();return e[e.length-1]=this.units,e}call(t,e){return B(()=>{this.invokeCallHook(t,e);let n=Pt(t),o=Gx(this.activation.getClassName()),s;return o!=null?s=ko(n,this.kernel.read(),o,this.bias?this.bias.read():null):(s=ko(n,this.kernel.read()),this.bias!=null&&(s=fn(s,this.bias.read())),this.activation!=null&&(s=this.activation.apply(s))),s})}getConfig(){let t={units:this.units,activation:ni(this.activation),useBias:this.useBias,kernelInitializer:Te(this.kernelInitializer),biasInitializer:Te(this.biasInitializer),kernelRegularizer:pe(this.kernelRegularizer),biasRegularizer:pe(this.biasRegularizer),activityRegularizer:pe(this.activityRegularizer),kernelConstraint:We(this.kernelConstraint),biasConstraint:We(this.biasConstraint)},e=super.getConfig();return Object.assign(t,e),t}};Qd.className="Dense";et.registerClass(Qd);var th=class extends Wt{constructor(t){t=t||{};super(t);this.inputSpec=[{minNDim:3}],this.dataFormat=t.dataFormat}computeOutputShape(t){t=Jt(t);for(let e of t.slice(1))if(e==null)throw new z(`The shape of the input to "Flatten" is not fully defined (got ${t.slice(1)}). 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B(()=>(t=Pt(t),G2(t,this.n)))}getConfig(){let t={n:this.n},e=super.getConfig();return Object.assign(t,e),t}};rh.className="RepeatVector";et.registerClass(rh);var nh=class extends Wt{constructor(t){super(t);this.targetShape=t.targetShape;for(let e=0;e<this.targetShape.length;++e)this.isUnknown(this.targetShape[e])&&(this.targetShape[e]=null)}isUnknown(t){return t<0||t==null}fixUnknownDimension(t,e){let n="Total size of new array must be unchanged.",o=e.slice(),s=1,i=null;for(let u=0;u<o.length;++u){let l=o[u];if(this.isUnknown(l))if(i===null)i=u;else throw new z("Can only specifiy one unknown dimension.");else s*=l}let a=So(t);if(i!==null){if(s===0||a%s!==0)throw new z(n);o[i]=a/s}else if(a!==s)throw new z(n);return o}computeOutputShape(t){let e=!1;for(let n=0;n<t.length;++n)if(this.isUnknown(t[n])){e=!0;break}return e?t.slice(0,1).concat(this.targetShape):t.slice(0,1).concat(this.fixUnknownDimension(t.slice(1),this.targetShape))}call(t,e){return B(()=>{this.invokeCallHook(t,e);let n=Pt(t),o=n.shape,s=o.slice(0,1).concat(this.fixUnknownDimension(o.slice(1),this.targetShape));return O(n,s)})}getConfig(){let t={targetShape:this.targetShape},e=super.getConfig();return Object.assign(t,e),t}};nh.className="Reshape";et.registerClass(nh);var oh=class extends Wt{constructor(t){super(t);if(t.dims==null)throw new Error("Required configuration field `dims` is missing during Permute constructor call.");if(!Array.isArray(t.dims))throw new Error(`Permute constructor requires \`dims\` to be an Array, but received ${t.dims} instead.`);let e=Yr(1,t.dims.length+1);if(!x.arraysEqual(t.dims.slice().sort(),e))throw new Error("Invalid permutation `dims`: "+JSON.stringify(t.dims)+" `dims` must contain consecutive integers starting from 1.");this.dims=t.dims,this.dimsIncludingBatch=[0].concat(this.dims),this.inputSpec=[new _e({ndim:this.dims.length+1})]}computeOutputShape(t){t=Jt(t);let e=t.slice();return this.dims.forEach((n,o)=>{e[o+1]=t[n]}),e}call(t,e){return Vt(Pt(t),this.dimsIncludingBatch)}getConfig(){let t={dims:this.dims},e=super.getConfig();return Object.assign(t,e),t}};oh.className="Permute";et.registerClass(oh);var sh=class extends Wt{constructor(t){super(t==null?{}:t);this.supportsMasking=!0,t!=null?this.maskValue=t.maskValue==null?0:t.maskValue:this.maskValue=0}computeOutputShape(t){return t}getConfig(){let t=super.getConfig(),e={maskValue:this.maskValue};return Object.assign(e,t),e}computeMask(t,e){let n=Pt(t),o=-1;return Vl(xo(n,this.maskValue),o)}call(t,e){return B(()=>{this.invokeCallHook(t,e);let n=Pt(t),o=-1,s=!0,i=Vl(xo(n,this.maskValue),o,s);return P(n,Z(i,n.dtype))})}};sh.className="Masking";et.registerClass(sh);var ih=class extends Wt{constructor(t){super(t);if(this.embeddings=null,this.DEFAULT_EMBEDDINGS_INITIALIZER="randomUniform",t.batchInputShape==null&&t.inputShape==null){let e=null;t.batchSize!=null&&(e=t.batchSize),t.inputLength==null?this.batchInputShape=[e,null]:this.batchInputShape=[e].concat(we(t.inputLength))}this.inputDim=t.inputDim,Qe(this.inputDim,"inputDim"),this.outputDim=t.outputDim,Qe(this.outputDim,"outputDim"),this.embeddingsInitializer=de(t.embeddingsInitializer||this.DEFAULT_EMBEDDINGS_INITIALIZER),this.embeddingsRegularizer=ve(t.embeddingsRegularizer),this.activityRegularizer=ve(t.activityRegularizer),this.embeddingsConstraint=Ue(t.embeddingsConstraint),this.maskZero=t.maskZero,this.supportsMasking=t.maskZero,this.inputLength=t.inputLength}build(t){this.embeddings=this.addWeight("embeddings",[this.inputDim,this.outputDim],this.dtype,this.embeddingsInitializer,this.embeddingsRegularizer,!0,this.embeddingsConstraint),this.built=!0}warnOnIncompatibleInputShape(t){}computeMask(t,e){return B(()=>this.maskZero?(t=Pt(t),xo(t,St(t))):null)}computeOutputShape(t){if(t=Jt(t),this.inputLength==null)return[...t,this.outputDim];let e=we(this.inputLength);if(e.length!==t.length-1)throw new z(`"inputLength" is ${this.inputLength}, but received input shape has shape ${t}`);{let n=0;for(let o=0;o<e.length;++o){let s=e[o],i=t[o+1];if(s!=null&&i!=null&&s!==i)throw new z(`"inputLength" is ${this.inputLength}, but received input shape has shape ${t}`);s==null&&(e[n]=i),n++}}return[t[0],...e,this.outputDim]}call(t,e){return B(()=>{this.invokeCallHook(t,e);let n=Pt(t);n.dtype!=="int32"&&(n=mc(n,"int32"));let o=Kx(this.embeddings.read(),O(n,[n.size]));return O(o,Jt(this.computeOutputShape(n.shape)))})}getConfig(){let t={inputDim:this.inputDim,outputDim:this.outputDim,embeddingsInitializer:Te(this.embeddingsInitializer),embeddingsRegularizer:pe(this.embeddingsRegularizer),activityRegularizer:pe(this.activityRegularizer),embeddingsConstraint:We(this.embeddingsConstraint),maskZero:this.maskZero,inputLength:this.inputLength},e=super.getConfig();return Object.assign(t,e),t}};ih.className="Embedding";et.registerClass(ih);var tu=class extends Wt{constructor(t){super(t||{});this.supportsMasking=!0}mergeFunction(t){throw new Tt}computeElementwiseOpOutputShape(t,e){if(t==null||e==null)return null;if(t.length<e.length)return this.computeElementwiseOpOutputShape(e,t);if(e.length===0)return t;let n=t.slice(0,t.length-e.length);for(let o=0;o<e.length;++o){let s=t[t.length-e.length+o],i=e[o];if(s==null||i==null||s<0||i<0)n.push(null);else if(s===1)n.push(i);else if(i===1)n.push(s);else{if(s!==i)throw new z("Operands could not be broadcast together with shapes "+JSON.stringify(t)+" "+JSON.stringify(e));n.push(s)}}return n}build(t){if(Array.isArray(t)&&!Array.isArray(t[0])&&(t=[Jt(t)]),t=t,t.length<2)throw new z(`A merge layer should be called on an Array of at least 2 inputs. 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t={axis:this.axis},e=super.getConfig();return Object.assign(t,e),t}};fh.className="Concatenate";et.registerClass(fh);function ah(r,t){for(;r<0;)r+=t;return r}function h8(r,t,e){if(r.shape.length>3||t.shape.length>3)throw new Tt("batchDot is not implemented for tensors of 4D or higher rank yet");if(x.assert(r.shape.length>=2,()=>`batchDot requires the rank of x to be >= 2, but got ${r.shape.length}`),x.assert(r.shape.length>=2,()=>`batchDot requires the rank of y to be >= 2, but got ${t.shape.length}`),typeof e=="number"&&(e=[e,e]),r.dtype==="complex64"||t.dtype==="complex64")throw new Tt("batchDot is not implemented for complex64-type Tensors yet.");let n=r.shape.length,o=t.shape.length;e==null&&(e=[n-1,o-2]);let s=e;return B(()=>{let i;if(n>o){i=n-o;let u=[];for(let l=0;l<i;++l)u.push(1);t=O(t,t.shape.concat(u))}else if(o>n){i=o-n;let u=[];for(let l=0;l<i;++l)u.push(1);r=O(r,r.shape.concat(u))}else i=0;let a;if(r.shape.length===2&&t.shape.length===2)s[0]===s[1]?a=mt(P(r,t),s[0]):a=mt(P(Vt(r,[1,0]),t),s[1]);else{let u=s[0]!==r.shape.length-1,l=s[1]===t.shape.length-1;a=Mt(r,t,u,l)}if(i>0){let u;n>o?u=n+o-3:u=n-1;let l=[];for(let c=u;c<u+i;++c)l.push(c);a=zr(a,l)}return a.shape.length===1&&(a=mr(a,1)),a})}var dh=class extends tu{constructor(t){super(t);this.axes=t.axes,this.normalize=t.normalize==null?!1:t.normalize,this.supportsMasking=!0,this.reshapeRequired=!1}build(t){x.assert(Array.isArray(t)&&t.length===2&&Array.isArray(t[0])&&Array.isArray(t[1]),()=>"A `Dot` layer should be called on a list of exactly 2 inputs.");let e=t[0],n=t[1];if(e.length>3||n.length>3)throw new Tt("Dot layer does not support tensors of 4D or higher rank yet.");let o=this.interpretAxes(e,n);if(e[o[0]]!==n[o[1]])throw new z(`Dimension incompatibility: ${e[o[0]]} !== ${n[o[1]]}`)}mergeFunction(t){if(t.length!==2)throw new z(`A \`Dot\` layer must be called on exactly 2 inputs, but received ${t.length} input(s).`);let e=t[0],n=t[1],o;return Array.isArray(this.axes)?o=this.axes.map((s,i)=>ah(s,t[i].shape.length)):o=[ah(this.axes,e.shape.length),ah(this.axes,n.shape.length)],this.normalize&&(e=Td(e,o[0]),n=Td(n,o[1])),h8(e,n,o)}interpretAxes(t,e){let n;return Array.isArray(this.axes)?n=this.axes:n=[ah(this.axes,t.length),ah(this.axes,e.length)],n}computeOutputShape(t){x.assert(Array.isArray(t)&&t.length===2&&Array.isArray(t[0])&&Array.isArray(t[1]),()=>"A `Dot` layer should be called on a list of exactly 2 inputs.");let e=t[0].slice(),n=t[1].slice();if(e.length>3||n.length>3)throw new Tt("Dot layer does not support tensors of 4D or higher rank yet.");let o=this.interpretAxes(e,n);e.splice(o[0],1),n.splice(o[1],1),n.splice(0,1);let s=e.concat(n);return s.length===1&&s.push(1),s}computeMask(t,e){return null}getConfig(){let t={axes:this.axes,normalize:this.normalize},e=super.getConfig();return Object.assign(t,e),t}};dh.className="Dot";et.registerClass(dh);var hh=class extends Wt{constructor(t){super(t);this.supportsMasking=!0,this.stddev=t.stddev}computeOutputShape(t){return t}getConfig(){let t=super.getConfig(),e={stddev:this.stddev};return Object.assign(e,t),e}call(t,e){return B(()=>{this.invokeCallHook(t,e);let n=Pt(t);return Ul(()=>J(lm(n.shape,0,this.stddev),n),()=>n,e.training||!1)})}};hh.className="GaussianNoise";et.registerClass(hh);var gh=class extends Wt{constructor(t){super(t);this.supportsMasking=!0,this.rate=t.rate}computeOutputShape(t){return t}getConfig(){let t=super.getConfig(),e={rate:this.rate};return Object.assign(e,t),e}call(t,e){return B(()=>{this.invokeCallHook(t,e);let n=Pt(t);return this.rate>0&&this.rate<1?Ul(()=>{let s=Math.sqrt(this.rate/(1-this.rate));return P(n,lm(n.shape,1,s))},()=>n,e.training||!1):n})}};gh.className="GaussianDropout";et.registerClass(gh);var xh=class extends Wt{constructor(t){super(t);this.supportsMasking=!0,this.rate=t.rate,this.noiseShape=t.noiseShape}_getNoiseShape(t){return this.noiseShape||Pt(t).shape}computeOutputShape(t){return t}getConfig(){let t=super.getConfig(),e={rate:this.rate};return Object.assign(e,t),e}call(t,e){return B(()=>{if(this.rate<1&&this.rate>0){let n=this._getNoiseShape(t);return Ul(()=>{let s=Pt(t),i=1.6732632423543772,a=1.0507009873554805,u=-i*a,l=Sn(Zs(n),this.rate);l=mc(l,"float32");let c=((1-this.rate)*(1+this.rate*u**2))**-.5,p=-c*u*this.rate,m=J(P(s,l),P(J(l,-1),u));return J(P(m,c),p)},()=>Pt(t),e.training||!1)}return t})}};xh.className="AlphaDropout";et.registerClass(xh);function yh(r,t,e,n,o,s=.001){let i;if(r.rank===2)i=h0(r,t,e,n,o,s);else if(r.rank===3)i=g0(r,t,e,n,o,s);else if(r.rank===4)i=x0(r,t,e,n,o,s);else throw new Tt(`batchNormalization is not implemented for array of rank ${r.rank} yet`);return i}function g8(r,t,e,n,o=.001){return B(()=>{let s=Jp(r,n),i=s.mean,a=s.variance;return[yh(r,i,a,e,t,o),i,a]})}function x8(r,t,e,n,o=.001){return B(()=>{let s=Jp(r,n),i=s.mean,a=s.variance,u=[];for(let d of 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e=this.axis>=0?this.axis:this.axis+t.length,n=t[e];if(n==null)throw new z(`Axis ${e} of input tensor should have a defined dimension but the layer received an input with shape ${JSON.stringify(t)}.`);this.inputSpec=[new _e({ndim:t.length,axes:{[e]:n}})];let o=[n];this.scale&&(this.gamma=this.addWeight("gamma",o,null,this.gammaInitializer,this.gammaRegularizer,!0,this.gammaConstraint)),this.center&&(this.beta=this.addWeight("beta",o,null,this.betaInitializer,this.betaRegularizer,!0,this.betaConstraint)),this.movingMean=this.addWeight("moving_mean",o,null,this.movingMeanInitializer,null,!1),this.movingVariance=this.addWeight("moving_variance",o,null,this.movingVarianceInitializer,null,!1),this.built=!0}call(t,e){return B(()=>{let n=e.training==null?!1:e.training,o=Pt(t),s=o.shape,i=s.length,a=Yr(0,i),u=this.axis>=0?this.axis:this.axis+i;a.splice(u,1);let l=vo(1,i);l[u]=s[u];let c=a.slice();c.sort();let p=!x.arraysEqual(c,Yr(0,i).slice(0,i-1)),m=()=>{if(p){let 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t={axis:this.axis,momentum:this.momentum,epsilon:this.epsilon,center:this.center,scale:this.scale,betaInitializer:Te(this.betaInitializer),gammaInitializer:Te(this.gammaInitializer),movingMeanInitializer:Te(this.movingMeanInitializer),movingVarianceInitializer:Te(this.movingVarianceInitializer),betaRegularizer:pe(this.betaRegularizer),gammaRegularizer:pe(this.gammaRegularizer),betaConstraint:We(this.betaConstraint),gammaConstraint:We(this.gammaConstraint)},e=super.getConfig();return Object.assign(t,e),t}};bh.className="BatchNormalization";et.registerClass(bh);var wh=class extends Wt{constructor(t){t==null&&(t={});super(t);if(this.axis=t.axis==null?-1:t.axis,typeof this.axis=="number"){if(!Number.isInteger(this.axis))throw new Error(`Expected axis to be an integer, but received ${this.axis}`)}else if(Array.isArray(this.axis)){for(let e of this.axis)if(!Number.isInteger(e))throw new Error(`Expected axis to be an array of integers, but received ${JSON.stringify(this.axis)}`)}else throw new Error(`Expected axis to be an integer or an array of integers, but received ${JSON.stringify(this.axis)}`);this.epsilon=t.epsilon==null?.001:t.epsilon,this.center=t.center==null?!0:t.center,this.scale=t.scale==null?!0:t.scale,this.betaInitializer=de(t.betaInitializer||"zeros"),this.gammaInitializer=de(t.gammaInitializer||"ones"),this.betaRegularizer=ve(t.betaRegularizer),this.gammaRegularizer=ve(t.gammaRegularizer),this.supportsMasking=!0}build(t){t=Jt(t);let e=t.length;typeof this.axis=="number"&&(this.axis=[this.axis]);for(let s=0;s<this.axis.length;++s)this.axis[s]<0&&(this.axis[s]+=e);for(let s of this.axis)if(s<0||s>=e)throw new Error(`Invalid axis: ${s}`);if(this.axis.length!==Io(this.axis).length)throw new Error(`Found duplicate axes in: ${this.axis}`);let n=this.axis.map(s=>t[s]),o=!0;this.scale?this.gamma=this.addWeight("gamma",n,"float32",this.gammaInitializer,this.gammaRegularizer,o):this.gamma=null,this.center?this.beta=this.addWeight("beta",n,"float32",this.betaInitializer,this.betaRegularizer,o):this.beta=null,this.built=!0}call(t,e){let n=Pt(t),o=n.shape,s=o.length;return B(()=>{let{mean:a,variance:u}=Jp(n,this.axis,!0),l=vo(1,s);for(let h of this.axis)l[h]=o[h];let c=h=>h!=null&&h.shape.length!==s?O(h,l):h,p=c(this.gamma.read()),m=c(this.beta.read()),f=[],d=[];for(let h=0;h<s;++h)this.axis.indexOf(h)!==-1?(f.push(o[h]),d.push(1)):(f.push(1),d.push(o[h]));return a=kr(a,f),u=kr(u,f),p=kr(p,d),m=kr(m,d),yh(n,a,u,m,p,this.epsilon)})}getConfig(){let t={axis:this.axis,epsilon:this.epsilon,center:this.center,scale:this.scale,betaInitializer:Te(this.betaInitializer),gammaInitializer:Te(this.gammaInitializer),betaRegularizer:pe(this.betaRegularizer),gammaRegularizer:pe(this.gammaRegularizer)},e=super.getConfig();return Object.assign(t,e),t}};wh.className="LayerNormalization";et.registerClass(wh);function b8(r,t,e){return B(()=>{if(r.rank!==4)throw new z(`temporalPadding expects input tensor to be 4-D, but received a ${r.rank}-D tensor.`);if(t==null&&(t=[[1,1],[1,1]]),t.length!==2||t[0].length!==2||t[1].length!==2)throw new z("spatial2dPadding expects `padding` to be an Array of two Arrays, each of which is an Array of two integers.");if(e==null&&(e=pn()),e!=="channelsLast"&&e!=="channelsFirst")throw new z(`Unknown data format: ${e}. 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length-${t.padding[1].length} array.`);n=t.padding[1]}this.padding=[e,n]}this.inputSpec=[new _e({ndim:4})]}computeOutputShape(t){t=Jt(t);let e,n;return this.dataFormat==="channelsFirst"?(t[2]!=null&&t[2]>=0?e=t[2]+this.padding[0][0]+this.padding[0][1]:e=null,t[3]!=null&&t[3]>=0?n=t[3]+this.padding[1][0]+this.padding[1][1]:n=null,[t[0],t[1],e,n]):(t[1]!=null&&t[1]>=0?e=t[1]+this.padding[0][0]+this.padding[0][1]:e=null,t[2]!=null&&t[2]>=0?n=t[2]+this.padding[1][0]+this.padding[1][1]:n=null,[t[0],e,n,t[3]])}call(t,e){return B(()=>b8(Pt(t),this.padding,this.dataFormat))}getConfig(){let t={padding:this.padding,dataFormat:this.dataFormat},e=super.getConfig();return Object.assign(t,e),t}};vh.className="ZeroPadding2D";et.registerClass(vh);function dy(r,t,e,n,o,s){return B(()=>{Me(o),pC(s),mn(n),e==null&&(e=[1,1]),n==null&&(n="valid"),o==null&&(o=pn()),s==null&&(s="max"),r=Vd(r,o);let i,a=n==="same"?"same":"valid";return s==="max"?i=Ka(r,t,e,a):i=Ba(r,t,e,a),o==="channelsFirst"&&(i=Vt(i,[0,3,1,2])),i})}function AD(r,t,e,n,o,s){return B(()=>{Me(o),pC(s),mn(n),e==null&&(e=[1,1,1]),n==null&&(n="valid"),o==null&&(o=pn()),s==null&&(s="max"),r=UC(r,o);let i,a=n==="same"?"same":"valid";return s==="max"?i=Zf(r,t,e,a):i=Lf(r,t,e,a),o==="channelsFirst"&&(i=Vt(i,[0,4,1,2,3])),i})}var XC=class extends Wt{constructor(t){t.poolSize==null&&(t.poolSize=2);super(t);if(typeof t.poolSize=="number")this.poolSize=[t.poolSize];else if(Array.isArray(t.poolSize)&&t.poolSize.length===1&&typeof t.poolSize[0]=="number")this.poolSize=t.poolSize;else throw new z(`poolSize for 1D convolutional layer must be a number or an Array of a single number, but received ${JSON.stringify(t.poolSize)}`);if(Qe(this.poolSize,"poolSize"),t.strides==null)this.strides=this.poolSize;else if(typeof t.strides=="number")this.strides=[t.strides];else if(Array.isArray(t.strides)&&t.strides.length===1&&typeof t.strides[0]=="number")this.strides=t.strides;else throw new z(`strides for 1D convolutional layer must be a number or an Array of a single number, but received ${JSON.stringify(t.strides)}`);Qe(this.strides,"strides"),this.padding=t.padding==null?"valid":t.padding,mn(this.padding),this.inputSpec=[new _e({ndim:3})]}computeOutputShape(t){t=Jt(t);let e=En(t[1],this.poolSize[0],this.padding,this.strides[0]);return[t[0],e,t[2]]}call(t,e){return B(()=>{this.invokeCallHook(t,e),t=nl(Pt(t),2);let n=this.poolingFunction(Pt(t),[this.poolSize[0],1],[this.strides[0],1],this.padding,"channelsLast");return zr(n,[2])})}getConfig(){let t={poolSize:this.poolSize,padding:this.padding,strides:this.strides},e=super.getConfig();return Object.assign(t,e),t}},Ch=class extends XC{constructor(t){super(t)}poolingFunction(t,e,n,o,s){return Me(s),mn(o),dy(t,e,n,o,s,"max")}};Ch.className="MaxPooling1D";et.registerClass(Ch);var Ih=class extends XC{constructor(t){super(t)}poolingFunction(t,e,n,o,s){return Me(s),mn(o),dy(t,e,n,o,s,"avg")}};Ih.className="AveragePooling1D";et.registerClass(Ih);var YC=class extends Wt{constructor(t){t.poolSize==null&&(t.poolSize=[2,2]);super(t);if(this.poolSize=Array.isArray(t.poolSize)?t.poolSize:[t.poolSize,t.poolSize],t.strides==null)this.strides=this.poolSize;else if(Array.isArray(t.strides)){if(t.strides.length!==2)throw new z(`If the strides property of a 2D pooling layer is an Array, it is expected to have a length of 2, but received length ${t.strides.length}.`);this.strides=t.strides}else this.strides=[t.strides,t.strides];Qe(this.poolSize,"poolSize"),Qe(this.strides,"strides"),this.padding=t.padding==null?"valid":t.padding,this.dataFormat=t.dataFormat==null?"channelsLast":t.dataFormat,Me(this.dataFormat),mn(this.padding),this.inputSpec=[new _e({ndim:4})]}computeOutputShape(t){t=Jt(t);let e=this.dataFormat==="channelsFirst"?t[2]:t[1],n=this.dataFormat==="channelsFirst"?t[3]:t[2];return e=En(e,this.poolSize[0],this.padding,this.strides[0]),n=En(n,this.poolSize[1],this.padding,this.strides[1]),this.dataFormat==="channelsFirst"?[t[0],t[1],e,n]:[t[0],e,n,t[3]]}call(t,e){return B(()=>(this.invokeCallHook(t,e),this.poolingFunction(Pt(t),this.poolSize,this.strides,this.padding,this.dataFormat)))}getConfig(){let t={poolSize:this.poolSize,padding:this.padding,strides:this.strides,dataFormat:this.dataFormat},e=super.getConfig();return Object.assign(t,e),t}},Sh=class extends YC{constructor(t){super(t)}poolingFunction(t,e,n,o,s){return Me(s),mn(o),dy(t,e,n,o,s,"max")}};Sh.className="MaxPooling2D";et.registerClass(Sh);var kh=class extends YC{constructor(t){super(t)}poolingFunction(t,e,n,o,s){return Me(s),mn(o),dy(t,e,n,o,s,"avg")}};kh.className="AveragePooling2D";et.registerClass(kh);var ZC=class extends Wt{constructor(t){t.poolSize==null&&(t.poolSize=[2,2,2]);super(t);if(this.poolSize=Array.isArray(t.poolSize)?t.poolSize:[t.poolSize,t.poolSize,t.poolSize],t.strides==null)this.strides=this.poolSize;else if(Array.isArray(t.strides)){if(t.strides.length!==3)throw new z(`If the strides property of a 3D pooling layer is an Array, it is expected to have a length of 3, but received length ${t.strides.length}.`);this.strides=t.strides}else this.strides=[t.strides,t.strides,t.strides];Qe(this.poolSize,"poolSize"),Qe(this.strides,"strides"),this.padding=t.padding==null?"valid":t.padding,this.dataFormat=t.dataFormat==null?"channelsLast":t.dataFormat,Me(this.dataFormat),mn(this.padding),this.inputSpec=[new _e({ndim:5})]}computeOutputShape(t){t=Jt(t);let e=this.dataFormat==="channelsFirst"?t[2]:t[1],n=this.dataFormat==="channelsFirst"?t[3]:t[2],o=this.dataFormat==="channelsFirst"?t[4]:t[3];return e=En(e,this.poolSize[0],this.padding,this.strides[0]),n=En(n,this.poolSize[1],this.padding,this.strides[1]),o=En(o,this.poolSize[2],this.padding,this.strides[2]),this.dataFormat==="channelsFirst"?[t[0],t[1],e,n,o]:[t[0],e,n,o,t[4]]}call(t,e){return B(()=>(this.invokeCallHook(t,e),this.poolingFunction(Pt(t),this.poolSize,this.strides,this.padding,this.dataFormat)))}getConfig(){let t={poolSize:this.poolSize,padding:this.padding,strides:this.strides,dataFormat:this.dataFormat},e=super.getConfig();return Object.assign(t,e),t}},Nh=class extends ZC{constructor(t){super(t)}poolingFunction(t,e,n,o,s){return Me(s),mn(o),AD(t,e,n,o,s,"max")}};Nh.className="MaxPooling3D";et.registerClass(Nh);var Th=class extends ZC{constructor(t){super(t)}poolingFunction(t,e,n,o,s){return Me(s),mn(o),AD(t,e,n,o,s,"avg")}};Th.className="AveragePooling3D";et.registerClass(Th);var JC=class extends Wt{constructor(t){super(t);this.inputSpec=[new _e({ndim:3})]}computeOutputShape(t){return[t[0],t[2]]}call(t,e){throw new Tt}},_h=class extends JC{constructor(t){super(t||{})}call(t,e){return B(()=>{let n=Pt(t);return xe(n,1)})}};_h.className="GlobalAveragePooling1D";et.registerClass(_h);var Eh=class extends JC{constructor(t){super(t||{})}call(t,e){return B(()=>{let n=Pt(t);return $r(n,1)})}};Eh.className="GlobalMaxPooling1D";et.registerClass(Eh);var QC=class extends Wt{constructor(t){super(t);this.dataFormat=t.dataFormat==null?"channelsLast":t.dataFormat,Me(this.dataFormat),this.inputSpec=[new _e({ndim:4})]}computeOutputShape(t){return t=t,this.dataFormat==="channelsLast"?[t[0],t[3]]:[t[0],t[1]]}call(t,e){throw new Tt}getConfig(){let t={dataFormat:this.dataFormat},e=super.getConfig();return Object.assign(t,e),t}},Ah=class extends QC{call(t,e){return B(()=>{let n=Pt(t);return this.dataFormat==="channelsLast"?xe(n,[1,2]):xe(n,[2,3])})}};Ah.className="GlobalAveragePooling2D";et.registerClass(Ah);var Dh=class extends QC{call(t,e){return B(()=>{let n=Pt(t);return this.dataFormat==="channelsLast"?$r(n,[1,2]):$r(n,[2,3])})}};Dh.className="GlobalMaxPooling2D";et.registerClass(Dh);var tI=class extends Wt{constructor(t){super(t);this.layer=t.layer}build(t){this.built=!0}get trainable(){return this.layer!=null?this.layer.trainable:!1}set trainable(t){this.layer!=null&&(this.layer.trainable=t)}get trainableWeights(){return this.layer.trainableWeights}get nonTrainableWeights(){return this.layer.nonTrainableWeights}get updates(){return this.layer._updates}get losses(){return this.layer.losses}getWeights(){return this.layer.getWeights()}setWeights(t){this.layer.setWeights(t)}getConfig(){let t={layer:{className:this.layer.getClassName(),config:this.layer.getConfig()}},e=super.getConfig();return Object.assign(t,e),t}setFastWeightInitDuringBuild(t){super.setFastWeightInitDuringBuild(t),this.layer!=null&&this.layer.setFastWeightInitDuringBuild(t)}static fromConfig(t,e,n={}){let o=e.layer,s=gn(o,n);delete e.layer;let i={layer:s};return Object.assign(i,e),new t(i)}},$h=class extends tI{constructor(t){super(t);this.supportsMasking=!0}build(t){if(t=Jt(t),t.length<3)throw new z(`TimeDistributed layer expects an input shape >= 3D, but received input shape ${JSON.stringify(t)}`);this.inputSpec=[{shape:t}];let e=[t[0]].concat(t.slice(2));this.layer.built||(this.layer.build(e),this.layer.built=!0),super.build(t)}computeOutputShape(t){t=Jt(t);let e=[t[0]].concat(t.slice(2)),n=this.layer.computeOutputShape(e),o=t[1];return[n[0],o].concat(n.slice(1))}call(t,e){return B(()=>(t=Pt(t),KC((i,a)=>[Pt(this.layer.call(i,e)),[]],t,[],!1,null,null,!1,!0)[1]))}};$h.className="TimeDistributed";et.registerClass($h);function w8(r){Li(M2,"BidirectionalMergeMode",r)}var v8="concat",Rh=class extends tI{constructor(t){super(t);let e=t.layer.getConfig(),n={};n.className=t.layer.getClassName(),n.config=e,this.forwardLayer=gn(n),e.goBackwards=e.goBackwards!==!0;let 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m$=(r,t,e)=>{switch(r.op){case"SparseFillEmptyRows":{let{outputIndices:n,outputValues:o,emptyRowIndicator:s,reverseIndexMap:i}=cd.sparseFillEmptyRows(S("indices",r,t,e),S("values",r,t,e),S("denseShape",r,t,e),S("defaultValue",r,t,e));return[n,o,s,i]}case"SparseReshape":{let{outputIndices:n,outputShape:o}=cd.sparseReshape(S("inputIndices",r,t,e),S("inputShape",r,t,e),S("newShape",r,t,e));return[n,o]}case"SparseSegmentMean":return[cd.sparseSegmentMean(S("data",r,t,e),S("indices",r,t,e),S("segmentIds",r,t,e))];case"SparseSegmentSum":return[cd.sparseSegmentSum(S("data",r,t,e),S("indices",r,t,e),S("segmentIds",r,t,e))];default:throw TypeError(`Node type ${r.op} is not implemented`)}};var f$=(r,t,e)=>{switch(r.op){case"FFT":return[Ja(S("x",r,t,e))];case"IFFT":return[Fi(S("x",r,t,e))];case"RFFT":return[Qa(S("x",r,t,e))];case"IRFFT":return[Zu(S("x",r,t,e))];default:throw TypeError(`Node type ${r.op} is not implemented`)}};var d$=(r,t,e)=>{switch(r.op){case"StringNGrams":{let{nGrams:n,nGramsSplits:o}=Mx.stringNGrams(S("data",r,t,e),S("dataSplits",r,t,e),S("separator",r,t,e),S("nGramWidths",r,t,e),S("leftPad",r,t,e),S("rightPad",r,t,e),S("padWidth",r,t,e),S("preserveShortSequences",r,t,e));return[n,o]}case"StringSplit":{let{indices:n,values:o,shape:s}=Mx.stringSplit(S("input",r,t,e),S("delimiter",r,t,e),S("skipEmpty",r,t,e));return[n,o,s]}case"StringToHashBucketFast":return[Mx.stringToHashBucketFast(S("input",r,t,e),S("numBuckets",r,t,e))];default:throw TypeError(`Node type ${r.op} is not implemented`)}};var h$=(r,t,e)=>{switch(r.op){case"Cast":return[Z(S("x",r,t,e),S("dtype",r,t,e))];case"ExpandDims":{let n=S("axis",r,t,e);return[mr(S("x",r,t,e),n)]}case"Squeeze":{let n=S("axis",r,t,e);return[zr(S("x",r,t,e),n)]}case"Reshape":return[O(S("x",r,t,e),S("shape",r,t,e))];case"MirrorPad":return[Jf(S("x",r,t,e),S("padding",r,t,e),S("mode",r,t,e))];case"PadV2":case"Pad":return[qr(S("x",r,t,e),S("padding",r,t,e),S("constantValue",r,t,e))];case"SpaceToBatchND":{let n=S("blockShape",r,t,e),o=S("paddings",r,t,e);return[ja(S("x",r,t,e),n,o)]}case"BatchToSpaceND":{let n=S("blockShape",r,t,e),o=S("crops",r,t,e);return[Va(S("x",r,t,e),n,o)]}case"DepthToSpace":{let n=S("blockSize",r,t,e),o=S("dataFormat",r,t,e).toUpperCase();return[Gf(S("x",r,t,e),n,o)]}case"BroadcastTo":return[Ga(S("x",r,t,e),S("shape",r,t,e))];case"BroadcastArgs":return[y0(S("s0",r,t,e),S("s1",r,t,e))];default:throw TypeError(`Node type ${r.op} is not implemented`)}};function DI(r,t,e,n){let o=((s,i,a)=>{switch(s.category){case"arithmetic":return B(()=>HD(s,i,a));case"basic_math":return B(()=>qD(s,i,a));case"control":return JD(s,i,a);case"convolution":return B(()=>t$(s,i,a));case"creation":return B(()=>e$(s,i,a));case"dynamic":return r$(s,i,a);case"evaluation":return B(()=>n$(s,i,a));case"image":return B(()=>i$(s,i,a));case"graph":return B(()=>o$(s,i,a));case"logical":return B(()=>a$(s,i,a));case"matrices":return B(()=>l$(s,i,a));case"normalization":return B(()=>u$(s,i,a));case"reduction":return B(()=>c$(s,i,a));case"slice_join":return B(()=>p$(s,i,a));case"sparse":return B(()=>m$(s,i,a));case"spectral":return B(()=>f$(s,i,a));case"string":return B(()=>d$(s,i,a));case"transformation":return B(()=>h$(s,i,a));case"hash_table":return s$(s,i,a,n);case"custom":let u=gy(s.op);if(u&&u.customExecutor)return u.customExecutor(new TI(s,i,a));throw TypeError(`Custom op ${s.op} is not registered.`);default:throw TypeError(`Unknown op '${s.op}'. 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t?t.map(e=>e.id===0&&e.iterationId===0?"":`${e.frameName}-${e.iterationId}`).join("/"):""}enterFrame(t){this.contexts&&(this.lastId++,this.contexts=this.contexts.slice(),this.contexts.push(this.newFrame(this.lastId,t)),this._currentContextIds.unshift(this.contextIdforContexts(this.contexts)))}exitFrame(){if(this.contexts&&this.contexts.length>1)this.contexts=this.contexts.slice(),this.contexts.splice(-1),this.currentContextIds.shift();else throw new Error("Cannot exit frame, the context is empty")}nextIteration(){if(this.contexts&&this.contexts.length>0){this.contexts=this.contexts.slice(),this.lastId++;let t=Object.assign({},this.contexts[this.contexts.length-1]);t.iterationId+=1,t.id=this.lastId,this.contexts.splice(-1,1,t),this._currentContextIds.splice(0,1,this.contextIdforContexts(this.contexts))}else throw new Error("Cannot increase frame iteration, the context is empty")}getWeight(t){return this.weightMap[t]}addTensorArray(t){this.tensorArrayMap[t.id]=t}getTensorArray(t){return this.tensorArrayMap[t]}addTensorList(t){this.tensorListMap[t.id]=t}getTensorList(t){return this.tensorListMap[t]}dispose(t){for(let e in this.tensorArrayMap)this.tensorArrayMap[e].clearAndClose(t);for(let e in this.tensorListMap)this.tensorListMap[e].clearAndClose(t)}};function $I(r,t,e,n){let o=new Set,s=[],i=null,a=null,u=new Set,l=Object.keys(r).map(m=>yn(m)[0]),c=[];n!=null&&(c=n.map(m=>yn(m.name)[0]));let p=[...t];for(;p.length>0;){let m=p.pop();if((RI(m)||U7(m)||H7(m))&&i==null&&(i=m,a=i.children.map(f=>f.name).filter(f=>o.has(f))),o.add(m.name),e[m.name]==null&&l.indexOf(m.name)===-1&&c.indexOf(m.name)===-1){if(m.inputs.length===0){s.push(m.name);continue}m.inputs.forEach(f=>{u.has(f.name)||(u.add(f.name),p.push(f))})}}return{inputs:r,outputs:t,usedNodes:o,missingInputs:s,dynamicNode:i,syncInputs:a}}function g$(r,t,e){let{usedNodes:n,inputs:o}=e,s=[],i=Object.keys(o).map(c=>yn(c)[0]).map(c=>r.nodes[c]),a=r.initNodes;i.forEach(c=>{n.has(c.name)&&s.push(c)}),r.weights.forEach(c=>{n.has(c.name)&&s.push(c)}),a!=null&&a.forEach(c=>{n.has(c.name)&&s.push(c)});let u=new Set,l=[];for(;s.length>0;){let c=s.pop();u.add(c.name),t[c.name]||l.push(c),c.children.forEach(p=>{!u.has(p.name)&&n.has(p.name)&&p.inputs.every(m=>u.has(m.name))&&s.push(p)})}return l}var V7=["Switch","Merge","Enter","Exit","NextIteration","StatelessIf","StatelessWhile","if","While"],G7=["NonMaxSuppressionV2","NonMaxSuppressionV3","NonMaxSuppressionV5","Where"],W7=["HashTable","HashTableV2","LookupTableImport","LookupTableImportV2","LookupTableFind","LookupTableFindV2","LookupTableSize","LookupTableSizeV2"];function RI(r){return V7.indexOf(r.op)>=0}function U7(r){return G7.indexOf(r.op)>=0}function H7(r){return W7.indexOf(r.op)>=0}var Am=class{constructor(t,e){this.graph=t,this.parent=e,this.compiledMap=new Map,this._weightMap={},this.SEPERATOR=",",this._functions={},this._functionExecutorMap={},this.intermediateTensors={},this.keepTensorForDebug=!1,this._outputs=t.outputs,this._inputs=t.inputs,this._initNodes=t.initNodes,this._signature=t.signature,this._functions=t.functions,t.functions!=null&&Object.keys(t.functions).forEach(n=>{this._functionExecutorMap[n]=new Am(t.functions[n],this)})}get weightIds(){return this.parent?this.parent.weightIds:this._weightIds}get functionExecutorMap(){return this.parent?this.parent.functionExecutorMap:this._functionExecutorMap}get weightMap(){return this.parent?this.parent.weightMap:this._weightMap}set weightMap(t){let e=Object.keys(t).map(n=>t[n].map(o=>o.id));this._weightIds=[].concat(...e),this._weightMap=t}set resourceManager(t){this._resourceManager=t}get inputs(){return this._inputs.map(t=>({name:t.name,shape:t.attrParams.shape?t.attrParams.shape.value:void 0,dtype:t.attrParams.dtype?t.attrParams.dtype.value:void 0}))}get outputs(){return this._outputs.map(t=>({name:t.name,shape:t.attrParams.shape?t.attrParams.shape.value:void 0,dtype:t.attrParams.dtype?t.attrParams.dtype.value:void 0}))}get inputNodes(){return this._inputs.map(t=>t.signatureKey||t.name)}get outputNodes(){return this._outputs.map(t=>{let e=t.signatureKey||t.name;return t.defaultOutput?`${e}:${t.defaultOutput}`:e})}get functions(){return Object.keys(this._functions).reduce((t,e)=>(t[e]=this._functions[e].signature,t),{})}getCompilationKey(t,e){let n=t.map(s=>s.name).sort(),o=e.map(s=>s.name).sort();return n.join(this.SEPERATOR)+"--"+o.join(this.SEPERATOR)}compile(t,e){let n=$I(t,e,this.weightMap,this._initNodes),{missingInputs:o,dynamicNode:s,syncInputs:i}=n;if(s!=null)throw new Error(`This execution contains the node '${s.name}', which has the dynamic op '${s.op}'. 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Missing the following inputs: [${o}]`)}return g$(this.graph,this.weightMap,n)}execute(t,e){t=this.mapInputs(t);let n=Object.keys(t).sort();this.checkInputs(t),this.checkInputShapeAndType(t),e=this.mapOutputs(e),this.checkOutputs(e);let o=n.map(p=>this.graph.nodes[yn(p)[0]]),s=e.map(p=>yn(p)[0]),i=s.map(p=>this.graph.nodes[p]);this.resetIntermediateTensors(),i.length===0&&(i=this._outputs);let a=this.getCompilationKey(o,i),u=this.compiledMap.get(a);u==null&&(u=this.compile(t,i),this.compiledMap.set(a,u));let l={},c={};return B(()=>{let p=new Ay(this.weightMap,l,c,this.functionExecutorMap),m=Object.assign({},this.weightMap);Object.keys(t).forEach(h=>{let[g,y]=yn(h),b=[];b[y]=t[h],m[g]=b});let f=this.getFrozenTensorIds(m),d={};for(let h=0;h<u.length;h++){let g=u[h];if(!m[g.name]){let y=DI(g,m,p,this._resourceManager);if(x.isPromise(y))throw new Error(`The execution of the op '${g.op}' returned a promise. 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Consider providing the following inputs: [${c}]. ${w}`)}return d}processStack(t,e,n,o,s,i,a,u,l){let c=[];for(;e.length>0;){let p=e.pop();n.currentContext=p.contexts;let m="";if(p.node.op==="Enter"&&S("isConstant",p.node,o,n)&&([m]=To(p.node.name,n)),o[p.node.name]==null){let f=DI(p.node,o,n,this._resourceManager);m||([m]=To(p.node.name,n));let d=n.currentContext;x.isPromise(f)?c.push(f.then(h=>(o[m]=h,n.currentContext=d,this.checkTensorForDisposal(m,p.node,o,n,i,a,u),this.processChildNodes(p.node,e,n,o,s,l),h))):(o[m]=f,this.checkTensorForDisposal(m,p.node,o,n,i,a,u),this.processChildNodes(p.node,e,n,o,s,l))}else this.processChildNodes(p.node,e,n,o,s,l)}return c}processChildNodes(t,e,n,o,s,i){t.children.forEach(a=>{let[u]=To(a.name,n);s[u]||!i.has(a.name)||(a.op==="Merge"?a.inputNames.some(l=>!!Cr(l,o,n))&&(s[u]=!0,e.push({contexts:n.currentContext,node:a})):a.inputNames.every(l=>!!Cr(l,o,n))&&(s[u]=!0,e.push({contexts:n.currentContext,node:a})))})}dispose(){Object.keys(this.weightMap).forEach(t=>this.weightMap[t].forEach(e=>e.dispose()))}checkInputShapeAndType(t){Object.keys(t).forEach(e=>{let n=t[e],[o]=yn(e),s=this.graph.nodes[o];if(s.attrParams.shape&&s.attrParams.shape.value){let i=s.attrParams.shape.value,a=i.length===n.shape.length&&n.shape.every((u,l)=>i[l]===-1||i[l]===u);x.assert(a,()=>`The shape of dict['${s.name}'] provided in model.execute(dict) must be [${i}], but was [${n.shape}]`)}s.attrParams.dtype&&s.attrParams.dtype.value&&x.assert(n.dtype===s.attrParams.dtype.value,()=>`The dtype of dict['${s.name}'] provided in model.execute(dict) must be ${s.attrParams.dtype.value}, but was ${n.dtype}`)})}mapInputs(t){let e={};for(let n in t)if(this._signature!=null&&this._signature.inputs!=null&&this._signature.inputs[n]!=null){let o=this._signature.inputs[n];e[o.name]=t[n]}else e[n]=t[n];return e}checkInputs(t){let e=Object.keys(t).filter(n=>{let[o]=yn(n);return this.graph.nodes[o]==null});if(e.length>0)throw new Error(`The dict provided in model.execute(dict) has keys: [${e}] that are not part of graph`)}mapOutputs(t){return t.map(e=>this._signature!=null&&this._signature.outputs!=null&&this._signature.outputs[e]!=null?this._signature.outputs[e].name:e,{})}checkOutputs(t){t.forEach(e=>{let[n]=yn(e);if(!this.graph.nodes[n])throw new Error(`The output '${e}' is not found in the graph`)})}};var FI=class{constructor(t={},e={}){this.hashTableNameToHandle=t,this.hashTableMap=e}addHashTable(t,e){this.hashTableNameToHandle[t]=e.handle,this.hashTableMap[e.id]=e}getHashTableHandleByName(t){return this.hashTableNameToHandle[t]}getHashTableById(t){return this.hashTableMap[t]}dispose(){for(let t in this.hashTableMap)this.hashTableMap[t].clearAndClose(),delete this.hashTableMap[t];for(let t in this.hashTableNameToHandle)this.hashTableNameToHandle[t].dispose(),delete this.hashTableNameToHandle[t]}};var q7="?tfjs-format=file",K7="model.json",OI=class{constructor(t,e={}){this.modelUrl=t,this.loadOptions=e,this.version="n/a",e==null&&(this.loadOptions={}),this.resourceManager=new FI}get modelVersion(){return this.version}get inputNodes(){return this.executor.inputNodes}get outputNodes(){return this.executor.outputNodes}get inputs(){return this.executor.inputs}get outputs(){return this.executor.outputs}get weights(){return this.executor.weightMap}get metadata(){return this.artifacts.userDefinedMetadata}get modelSignature(){return this.signature}findIOHandler(){let t=this.modelUrl;if(t.load!=null)this.handler=t;else if(this.loadOptions.requestInit!=null)this.handler=Pr.browserHTTPRequest(t,this.loadOptions);else{let e=Pr.getLoadHandlers(t,this.loadOptions);if(e.length===0)e.push(Pr.browserHTTPRequest(t,this.loadOptions));else if(e.length>1)throw new Error(`Found more than one (${e.length}) load handlers for URL '${[t]}'`);this.handler=e[0]}}async load(){if(this.findIOHandler(),this.handler.load==null)throw new Error("Cannot proceed with model loading because the IOHandler provided does not have the `load` method implemented.");let t=await this.handler.load();return this.loadSync(t)}loadSync(t){this.artifacts=t;let e=this.artifacts.modelTopology,n;this.artifacts.userDefinedMetadata!=null&&this.artifacts.userDefinedMetadata.signature!=null?n=this.artifacts.userDefinedMetadata.signature:n=this.artifacts.signature,this.signature=n,this.version=`${e.versions.producer}.${e.versions.minConsumer}`;let o=Pr.decodeWeights(this.artifacts.weightData,this.artifacts.weightSpecs);if(this.executor=new Am(_y.Instance.transformGraph(e,this.signature)),this.executor.weightMap=this.convertTensorMapToTensorsMap(o),this.executor.resourceManager=this.resourceManager,t.modelInitializer!=null&&t.modelInitializer.node!=null){let s=_y.Instance.transformGraph(t.modelInitializer);this.initializer=new Am(s),this.initializer.weightMap=this.executor.weightMap,this.initializer.resourceManager=this.resourceManager,this.initializer.executeAsync({},[])}return!0}async save(t,e){if(typeof t=="string"){let n=Pr.getSaveHandlers(t);if(n.length===0)throw new Error(`Cannot find any save handlers for URL '${t}'`);if(n.length>1)throw new Error(`Found more than one (${n.length}) save handlers for URL '${t}'`);t=n[0]}if(t.save==null)throw new Error("GraphModel.save() cannot proceed because the IOHandler provided does not have the `save` attribute defined.");return t.save(this.artifacts)}predict(t,e){return this.execute(t,this.outputNodes)}normalizeInputs(t){if(!(t instanceof Bt)&&!Array.isArray(t))return 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`).map(o=>(o.endsWith("\r")&&(o=o.slice(0,-1)),o))}};var Fy='"',Lh=Symbol("out"),rR=Symbol("field"),Oy=Symbol("quote"),XI=Symbol("quoteafterquote"),nR=Symbol("quoteinquote"),zh=class extends Gi{constructor(t,e){super();this.input=t,this.hasHeader=!0,this.fullColumnNames=null,this.columnNamesValidated=!1,this.columnConfigs=null,this.configuredColumnsOnly=!1,this.delimiter=",",this.delimWhitespace=!1,this.base=new Mh(t),e||(e={}),this.hasHeader=e.hasHeader!==!1,this.fullColumnNames=e.columnNames,this.columnConfigs=e.columnConfigs,this.configuredColumnsOnly=e.configuredColumnsOnly,e.delimWhitespace?(x.assert(e.delimiter==null,()=>"Delimiter should not be provided when delimWhitespace is true."),this.delimWhitespace=!0,this.delimiter=" "):this.delimiter=e.delimiter?e.delimiter:","}async columnNames(){return this.columnNamesValidated||await this.setColumnNames(),this.configuredColumnsOnly?Object.keys(this.columnConfigs):this.fullColumnNames}async setColumnNames(){let t=await this.maybeReadHeaderLine();if(!this.fullColumnNames&&!t)throw new Error("Column names must be provided if there is no header line.");this.fullColumnNames&&t&&x.assert(t.length===this.fullColumnNames.length,()=>"The length of provided columnNames ("+this.fullColumnNames.length.toString()+") does not match the length of the header line read from file ("+t.length.toString()+")."),this.fullColumnNames||(this.fullColumnNames=t);let e=this.fullColumnNames.reduce((o,s)=>(o[s]=o[s]+1||1,o),{}),n=Object.keys(e).filter(o=>e[o]>1);if(x.assert(n.length===0,()=>"Duplicate column names found: "+n.toString()),this.columnConfigs){for(let o of Object.keys(this.columnConfigs))if(this.fullColumnNames.indexOf(o)===-1)throw new Error('The key "'+o+'" provided in columnConfigs does not match any of the column names ('+this.fullColumnNames.toString()+").")}this.columnNamesValidated=!0}async maybeReadHeaderLine(){if(this.hasHeader){let e=await(await this.base.iterator()).next();if(e.done)throw new Error("No data was found for CSV parsing.");let n=e.value;return this.parseRow(n,!1)}else return null}async iterator(){this.columnNamesValidated||await this.setColumnNames();let t=await this.base.iterator();return this.hasHeader&&(t=t.skip(1)),t.map(e=>this.makeDataElement(e))}makeDataElement(t){let e=this.parseRow(t),n={},o={};for(let s=0;s<this.fullColumnNames.length;s++){let i=this.fullColumnNames[s],a=this.columnConfigs?this.columnConfigs[i]:null;if(!(this.configuredColumnsOnly&&!a)){let u=e[s],l=null;if(u==="")if(a&&a.default!==void 0)l=a.default;else{if(a&&(a.required||a.isLabel))throw new Error(`Required column ${i} is empty in this line: ${t}`);l=void 0}else{let c=Number(u);if(isNaN(c))a&&a.dtype==="bool"?l=this.getBoolean(u):l=u;else if(!a||!a.dtype)l=c;else switch(a.dtype){case"float32":l=c;break;case"int32":l=Math.floor(c);break;case"bool":l=this.getBoolean(u);break;default:l=c}}a&&a.isLabel?o[i]=l:n[i]=l}}return Object.keys(o).length===0?n:{xs:n,ys:o}}getBoolean(t){return t==="1"||t.toLowerCase()==="true"?1:0}parseRow(t,e=!0){let n=[],o=0,s=t.length,i=Lh;for(let a=0;a<s;a++)switch(i){case Lh:switch(t.charAt(a)){case Fy:o=a+1,i=Oy;break;case this.delimiter:if(o=a+1,this.delimiter===" "&&this.delimWhitespace)break;n.push(""),i=Lh;break;default:i=rR,o=a;break}break;case rR:switch(t.charAt(a)){case this.delimiter:n.push(t.substring(o,a)),i=Lh,o=a+1;break;default:}break;case Oy:switch(t.charAt(a)){case Fy:i=XI;break;default:}break;case XI:switch(t.charAt(a)){case this.delimiter:n.push(t.substring(o,a-1)),i=Lh,o=a+1;break;case Fy:i=Oy;break;default:i=nR;break}break;case nR:switch(t.charAt(a)){case Fy:i=Oy;break;default:}break;default:}if(i===XI?n.push(t.substring(o,s-1)):n.push(t.substring(o)),e&&n.length!==this.fullColumnNames.length)throw new Error(`Invalid row in csv file. Should have ${this.fullColumnNames.length} elements in a row, but got ${n}`);return n}};var Bh=class extends sr{constructor(t){super();this.microphoneConfig=t,this.isClosed=!1,this.fftSize=t.fftSize||1024;let e=Math.log2(this.fftSize);if(this.fftSize<0||e<4||e>14||!Number.isInteger(e))throw new Error(`Invalid fftSize: it must be a power of 2 between 2 to 4 and 2 to 14, but got ${this.fftSize}`);if(this.numFrames=t.numFramesPerSpectrogram||43,this.sampleRateHz=t.sampleRateHz,this.columnTruncateLength=t.columnTruncateLength||this.fftSize,this.audioTrackConstraints=t.audioTrackConstraints,this.smoothingTimeConstant=t.smoothingTimeConstant||0,this.includeSpectrogram=t.includeSpectrogram!==!1,this.includeWaveform=t.includeWaveform===!0,!this.includeSpectrogram&&!this.includeWaveform)throw new Error("Both includeSpectrogram and includeWaveform are false. At least one type of data should be returned.")}summary(){return"microphone"}static async create(t={}){if(G().get("IS_NODE"))throw new Error("microphone API is only supported in browser environment.");let e=new Bh(t);return await e.start(),e}async start(){try{this.stream=await navigator.mediaDevices.getUserMedia({audio:this.audioTrackConstraints==null?!0:this.audioTrackConstraints,video:!1})}catch(n){throw new Error(`Error thrown while initializing video stream: ${n.message}`)}if(!this.stream)throw new Error("Could not obtain audio from microphone.");let t=window.AudioContext||window.webkitAudioContext;if(this.audioContext=new t,!this.sampleRateHz)this.sampleRateHz=this.audioContext.sampleRate;else if(this.audioContext.sampleRate!==this.sampleRateHz)throw new Error(`Mismatch in sampling rate: Expected: ${this.sampleRateHz}; Actual: ${this.audioContext.sampleRate}`);let e=this.audioContext.createMediaStreamSource(this.stream);this.analyser=this.audioContext.createAnalyser(),this.analyser.fftSize=this.fftSize*2,this.analyser.smoothingTimeConstant=this.smoothingTimeConstant,e.connect(this.analyser),this.freqData=new Float32Array(this.fftSize),this.timeData=new Float32Array(this.fftSize)}async next(){if(this.isClosed)return{value:null,done:!0};let t,e,n=await this.getAudioData();if(this.includeSpectrogram){let o=this.flattenQueue(n.freqDataQueue);t=this.getTensorFromAudioDataArray(o,[this.numFrames,this.columnTruncateLength,1])}if(this.includeWaveform){let o=this.flattenQueue(n.timeDataQueue);e=this.getTensorFromAudioDataArray(o,[this.numFrames*this.fftSize,1])}return{value:{spectrogram:t,waveform:e},done:!1}}async capture(){return(await this.next()).value}async getAudioData(){let t=[],e=[],n=0;return new Promise(o=>{let s=setInterval(()=>{this.includeSpectrogram&&(this.analyser.getFloatFrequencyData(this.freqData),this.freqData[0]===-1/0&&o({freqDataQueue:t,timeDataQueue:e}),t.push(this.freqData.slice(0,this.columnTruncateLength))),this.includeWaveform&&(this.analyser.getFloatTimeDomainData(this.timeData),e.push(this.timeData.slice())),++n===this.numFrames&&(clearInterval(s),o({freqDataQueue:t,timeDataQueue:e}))},this.fftSize/this.sampleRateHz*1e3)})}stop(){this.isClosed||(this.isClosed=!0,this.analyser.disconnect(),this.audioContext.close(),this.stream!=null&&this.stream.getTracks().length>0&&this.stream.getTracks()[0].stop())}toArray(){throw new Error("Can not convert infinite audio stream to array.")}getSampleRate(){return this.sampleRateHz}flattenQueue(t){let e=t[0].length,n=new Float32Array(t.length*e);return t.forEach((o,s)=>n.set(o,s*e)),n}getTensorFromAudioDataArray(t,e){let n=new Float32Array(x.sizeFromShape(e));return n.set(t,n.length-t.length),Ar(n,e)}};var Vh=class extends sr{constructor(t,e){super();if(this.webcamVideoElement=t,this.webcamConfig=e,this.isClosed=!0,this.resize=!1,this.needToResize())if(this.resize=!0,this.cropSize=[this.webcamConfig.resizeHeight,this.webcamConfig.resizeWidth],this.cropBoxInd=$e([0],"int32"),this.webcamConfig.centerCrop){let n=this.webcamConfig.resizeWidth*1/this.webcamVideoElement.width,o=this.webcamConfig.resizeHeight*1/this.webcamVideoElement.height,s=(1-n)/2,i=(1-o)/2,a=s+n,u=o+i;this.cropBox=Oi([i,s,u,a],[1,4])}else this.cropBox=Oi([0,0,1,1],[1,4])}summary(){return"webcam"}static async create(t,e={}){if(G().get("IS_NODE"))throw new Error("tf.data.webcam is only supported in browser environment.");if(!t){if(t=document.createElement("video"),!e.resizeWidth||!e.resizeHeight)throw new Error("Please provide webcam video element, or resizeWidth and resizeHeight to create a hidden video element.");t.width=e.resizeWidth,t.height=e.resizeHeight}let n=new Vh(t,e);return await n.start(),n}async start(){this.webcamConfig.facingMode&&x.assert(this.webcamConfig.facingMode==="user"||this.webcamConfig.facingMode==="environment",()=>`Invalid webcam facing mode: ${this.webcamConfig.facingMode}. Please provide 'user' or 'environment'`);try{this.stream=await navigator.mediaDevices.getUserMedia({video:{deviceId:this.webcamConfig.deviceId,facingMode:this.webcamConfig.facingMode?this.webcamConfig.facingMode:"user",width:this.webcamVideoElement.width,height:this.webcamVideoElement.height}})}catch(t){throw t.message=`Error thrown while initializing video stream: ${t.message}`,t}if(!this.stream)throw new Error("Could not obtain video from webcam.");try{this.webcamVideoElement.srcObject=this.stream}catch(t){console.log(t),this.webcamVideoElement.src=window.URL.createObjectURL(this.stream)}return this.webcamVideoElement.play(),this.isClosed=!1,new Promise(t=>{this.webcamVideoElement.onloadedmetadata=()=>{t()}})}async next(){if(this.isClosed)return{value:null,done:!0};let t;try{t=mx.fromPixels(this.webcamVideoElement)}catch(e){throw new Error(`Error thrown converting video to pixels: ${JSON.stringify(e)}`)}if(this.resize)try{return{value:this.cropAndResizeFrame(t),done:!1}}catch(e){throw new Error(`Error thrown cropping the video: ${e.message}`)}finally{t.dispose()}else return{value:t,done:!1}}needToResize(){return!!(this.webcamConfig.resizeWidth&&this.webcamConfig.resizeHeight&&(this.webcamVideoElement.width!==this.webcamConfig.resizeWidth||this.webcamVideoElement.height!==this.webcamConfig.resizeHeight))}cropAndResizeFrame(t){return B(()=>{let e=mr(Z(t,"float32"),0),n;n=Nn.cropAndResize(e,this.cropBox,this.cropBoxInd,this.cropSize,"bilinear");let o=n.shape;return O(n,o.slice(1))})}async capture(){return(await this.next()).value}stop(){this.stream.getTracks().forEach(e=>e.stop());try{this.webcamVideoElement.srcObject=null}catch(e){console.log(e),this.webcamVideoElement.src=null}this.isClosed=!0}toArray(){throw new Error("Can not convert infinite video stream to array.")}};var Gh=class{};var Py=class extends sr{split(t){return new oR(this,t)}},oR=class extends Py{constructor(t,e){super();this.upstream=t,this.impl=new sR(t,e)}summary(){return this.impl.summary()}async next(){return this.impl.next()}},sR=class extends $m{constructor(t,e){super();this.upstream=t,this.separator=e,this.carryover=""}summary(){return`${this.upstream.summary()} -> Split('${this.separator}')`}async pump(){let t=await this.upstream.next();if(t.done)return this.carryover===""?!1:(this.outputQueue.push(this.carryover),this.carryover="",!0);let e=t.value.split(this.separator);e[0]=this.carryover+e[0];for(let n of e.slice(0,-1))this.outputQueue.push(n);return this.carryover=e[e.length-1],!0}};var YI=class extends sr{decodeUTF8(){return new iR(this)}},iR=class extends Py{constructor(t){super();this.upstream=t,this.impl=new aR(t)}summary(){return this.impl.summary()}async next(){return this.impl.next()}},aR=class extends $m{constructor(t){super();if(this.upstream=t,G().get("IS_BROWSER"))this.decoder=new TextDecoder("utf-8");else{let{StringDecoder:e}=WI();this.decoder=new e("utf8")}}summary(){return`${this.upstream.summary()} -> Utf8`}async pump(){let t=await this.upstream.next(),e;if(t.done)return!1;e=t.value;let n;return G().get("IS_BROWSER")?n=this.decoder.decode(e,{stream:!0}):n=this.decoder.write(Buffer.from(e.buffer)),this.outputQueue.push(n),!0}};var Wh=class extends YI{constructor(t,e={}){super();this.file=t,this.options=e,x.assert(t instanceof Uint8Array||(G().get("IS_BROWSER")?t instanceof File||t instanceof Blob:!1),()=>"FileChunkIterator only supports File, Blob and Uint8Array right now."),this.offset=e.offset||0,this.chunkSize=e.chunkSize||1024*1024}summary(){return`FileChunks ${this.file}`}async next(){return this.offset>=(this.file instanceof Uint8Array?this.file.byteLength:this.file.size)?{value:null,done:!0}:{value:await new Promise((e,n)=>{let o=this.offset+this.chunkSize;if(this.file instanceof Uint8Array)e(new Uint8Array(this.file.slice(this.offset,o)));else{let s=new FileReader;s.onload=a=>{let u=s.result;if(u instanceof ArrayBuffer&&(u=new Uint8Array(u)),!(u instanceof Uint8Array))return n(new TypeError("FileReader returned unknown type."));e(u)},s.onabort=a=>n(new Error("Aborted")),s.onerror=a=>n(new Error(a.type));let i=this.file.slice(this.offset,o);s.readAsArrayBuffer(i)}this.offset=o}),done:!1}}};async function lR(r,t={},e){let n,o;typeof r=="string"?n=r:(n=r.url,o=sZ(r));let s=await(e||x.fetch)(n,o);if(s.ok){let i=new Uint8Array(await s.arrayBuffer());return new Wh(i,t)}else throw new Error(s.statusText)}var sZ=r=>({method:r.method,headers:r.headers,body:r.body,mode:r.mode,credentials:r.credentials,cache:r.cache,redirect:r.redirect,referrer:r.referrer,integrity:r.integrity});function My(r){return typeof r=="string"&&r.substr(0,7)==="file://"}var Uh=class extends Gh{constructor(t,e={}){super();this.input=t,this.options=e}async iterator(){if(My(this.input)&&G().get("IS_NODE")){let t=Ly();this.input=t.readFileSync(this.input.substr(7))}return new Wh(this.input,this.options)}};var Hh=class extends Gh{constructor(t,e={}){super();this.url=t,this.fileOptions=e}async iterator(){return My(this.url)?new Uh(this.url,this.fileOptions).iterator():lR(this.url,this.fileOptions)}};function uR(r,t={}){return new zh(new Hh(r),t)}function cR(r){let t=Ph(r);return An(async()=>t)}function pR(r){return An(async()=>{let t=await r();return Ph(()=>t.next())})}async function mR(r,t){return Vh.create(r,t)}async function fR(r){return Bh.create(r)}var ZI="3.14.0";function ot(r,t){Array.isArray(r)||(r=[r]),r.forEach(e=>{e!=null&&x.assert(e.dtype!=="complex64",()=>`${t} does not support complex64 tensors in the CPU backend.`)})}var iZ=Vr.whereImpl,Ic=class extends pi{constructor(){super();this.blockSize=48,this.firstUse=!0,this.data=new bl(this,po())}nextDataId(){return Ic.nextDataId++}write(t,e,n){this.firstUse&&(this.firstUse=!1,G().get("IS_NODE")&&k.warn(`
============================
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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c=k.computePool3DInfo(s.shape,i,a,1,u,l),p=c.strideDepth,m=c.strideHeight,f=c.strideWidth,d=c.filterDepth,h=c.filterHeight,g=c.filterWidth,y=c.dilationDepth,b=c.dilationHeight,w=c.dilationWidth,v=c.effectiveFilterDepth,I=c.effectiveFilterHeight,E=c.effectiveFilterWidth,D=v-1-c.padInfo.front,$=E-1-c.padInfo.left,R=I-1-c.padInfo.top,M=It(s.shape,"float32"),W=1/(d*h*g),U=e.bufferSync(o);for(let q=0;q<c.batchSize;++q)for(let K=0;K<c.inChannels;++K)for(let j=0;j<c.inDepth;++j)for(let Q=0;Q<c.inHeight;++Q)for(let rt=0;rt<c.inWidth;++rt){let X=j-D,nt=Q-R,st=rt-$,it=0;for(let ft=0;ft<v;ft+=y){let at=(X+ft)/p;if(!(at<0||at>=c.outDepth||Math.floor(at)!==at))for(let xt=0;xt<I;xt+=b){let dt=(nt+xt)/m;if(!(dt<0||dt>=c.outHeight||Math.floor(dt)!==dt))for(let bt=0;bt<E;bt+=w){let kt=(st+bt)/f;if(kt<0||kt>=c.outWidth||Math.floor(kt)!==kt)continue;it+=U.get(q,at,dt,kt,K)}}}M.set(it*W,q,j,Q,rt,K)}return e.makeTensorInfo(M.shape,M.dtype,M.values)}var xF={kernelName:lp,backendName:"cpu",kernelFunc:qZ};function KZ(r){let{inputs:t,backend:e,attrs:n}=r,{dy:o,input:s}=t,i=s;ot([o,s],"avgPoolGrad");let{filterSize:a,strides:u,pad:l}=n,c=k.computePool2DInfo(i.shape,a,u,1,l),p=c.strideHeight,m=c.strideWidth,f=c.filterHeight,d=c.filterWidth,h=c.dilationHeight,g=c.dilationWidth,y=c.effectiveFilterHeight,b=c.effectiveFilterWidth,w=b-1-c.padInfo.left,v=y-1-c.padInfo.top,I=It(i.shape,"float32"),E=1/(f*d),D=e.data.get(o.dataId).values,$=It(o.shape,"float32",D);for(let R=0;R<c.batchSize;++R)for(let M=0;M<c.inChannels;++M)for(let W=0;W<c.inHeight;++W)for(let U=0;U<c.inWidth;++U){let q=W-v,K=U-w,j=0;for(let Q=0;Q<y;Q+=h){let rt=(q+Q)/p;if(!(rt<0||rt>=c.outHeight||Math.floor(rt)!==rt))for(let X=0;X<b;X+=g){let nt=(K+X)/m;if(nt<0||nt>=c.outWidth||Math.floor(nt)!==nt)continue;j+=$.get(R,rt,nt,M)}}I.set(j*E,R,W,U,M)}return e.makeTensorInfo(I.shape,I.dtype,I.values)}var yF={kernelName:ap,backendName:"cpu",kernelFunc:KZ};function 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e.makeTensorInfo(o.shape,o.dtype,h)}var bF={kernelName:ls,backendName:"cpu",kernelFunc:jZ};function XZ(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{blockShape:s,crops:i}=n;ot([o],"batchToSpaceND");let a=s.reduce((y,b)=>y*b),u=k.getReshaped(o.shape,s,a),l=k.getPermuted(u.length,s.length),c=k.getReshapedPermuted(o.shape,s,a),p=k.getSliceBeginCoords(i,s.length),m=k.getSliceSize(c,i,s.length),f=ne({inputs:{x:o},backend:e,attrs:{shape:u}}),d=ir({inputs:{x:f},backend:e,attrs:{perm:l}}),h=ne({inputs:{x:d},backend:e,attrs:{shape:c}}),g=Do({inputs:{x:h},backend:e,attrs:{begin:p,size:m}});return e.disposeIntermediateTensorInfo(f),e.disposeIntermediateTensorInfo(d),e.disposeIntermediateTensorInfo(h),g}var wF={kernelName:hi,backendName:"cpu",kernelFunc:XZ};function YZ(r){let{inputs:t,backend:e,attrs:n}=r,{x:o,weights:s}=t,{size:i}=n,a=e.data.get(o.dataId).values,u=e.data.get(s.dataId).values,l=Om(a,u,s.dtype,s.shape,i);return e.makeTensorInfo([i],s.dtype,l)}var vF={kernelName:up,backendName:"cpu",kernelFunc:YZ};function ZZ(r){let{inputs:t,backend:e}=r,{s0:n,s1:o}=t,s=e.data.get(n.dataId).values,i=e.data.get(o.dataId).values,a=k.assertAndGetBroadcastShape(Array.from(s),Array.from(i));return e.makeTensorInfo([a.length],"int32",Int32Array.from(a))}var CF={kernelName:cp,backendName:"cpu",kernelFunc:ZZ};var JZ=Et(oo,(r,t)=>{let e=t;return r>e.clipValueMax?e.clipValueMax:r<e.clipValueMin?e.clipValueMin:r}),IF={kernelName:oo,backendName:"cpu",kernelFunc:JZ};var QZ=r=>{let{x:t}=r.inputs,e=r.backend,n=new Float32Array(x.sizeFromShape(t.shape)),o=e.data.get(t.dataId),s=o.complexTensorInfos.real,i=o.complexTensorInfos.imag,a=e.data.get(s.dataId).values,u=e.data.get(i.dataId).values;for(let l=0;l<a.length;l++){let c=a[l],p=u[l];n[l]=Math.hypot(c,p)}return e.makeOutput(n,t.shape,"float32")},SF={kernelName:Cl,backendName:"cpu",kernelFunc:QZ};function 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e.makeTensorInfo(b.shape,b.dtype,b.values)}var _F={kernelName:mp,backendName:"cpu",kernelFunc:t9};function e9(r){let{inputs:t,backend:e,attrs:n}=r,{dy:o,filter:s}=t,{inputShape:i,strides:a,pad:u,dataFormat:l,dimRoundingMode:c}=n;ot([o,s],"conv2dBackpropInput");let p=x.computeStrides(s.shape),m=x.computeStrides(o.shape),f=k.convertConv2DDataFormat(l),d=k.computeConv2DInfo(i,s.shape,a,1,u,c,!1,f),h=new me(d.inShape,"float32"),g=h.values,y=e.data.get(o.dataId).values,b=e.data.get(s.dataId).values,[w,v,I]=p,{batchSize:E,filterHeight:D,filterWidth:$,inChannels:R,inHeight:M,inWidth:W,outChannels:U,outHeight:q,outWidth:K,strideHeight:j,strideWidth:Q}=d;f=d.dataFormat;let rt=D-1-d.padInfo.top,X=$-1-d.padInfo.left,nt=f==="channelsLast",st=h.strides[0],it=nt?h.strides[1]:h.strides[2],ft=nt?h.strides[2]:1,at=nt?1:h.strides[1],xt=m[0],dt=nt?m[1]:m[2],bt=nt?m[2]:1,kt=nt?1:m[1];for(let At=0;At<E;++At)for(let $t=0;$t<R;++$t)for(let qt=0;qt<M;++qt){let Kt=qt-rt,ce=Math.max(0,Math.ceil(Kt/j)),Ot=Math.min(q,(D+Kt)/j);for(let Ee=0;Ee<W;++Ee){let Ie=Ee-X,ae=Math.max(0,Math.ceil(Ie/Q)),qe=Math.min(K,($+Ie)/Q),Re=0;for(let ze=ce;ze<Ot;++ze){let Po=ze*j-Kt;for(let Fr=ae;Fr<qe;++Fr){let Qr=Fr*Q-Ie,tn=xt*At+dt*ze+bt*Fr,Hr=w*(D-1-Po)+v*($-1-Qr)+I*$t;for(let eo=0;eo<U;++eo){let $n=y[tn+kt*eo],Mo=b[Hr+eo];Re+=$n*Mo}}}let Jr=st*At+it*qt+ft*Ee+at*$t;g[Jr]=Re}}return e.makeTensorInfo(h.shape,h.dtype,h.values)}var EF={kernelName:Jo,backendName:"cpu",kernelFunc:e9};function r9(r){let{inputs:t,backend:e,attrs:n}=r,{x:o,filter:s}=t,{strides:i,pad:a,dilations:u}=n;ot([o,s],"conv3d");let l=k.computeConv3DInfo(o.shape,s.shape,i,u,a),{filterDepth:c,filterHeight:p,filterWidth:m,dilationDepth:f,dilationHeight:d,dilationWidth:h,padInfo:g}=l,y=g.front,b=g.left,w=g.top,v=new me(l.outShape,o.dtype),I=e.data.get(o.dataId).values,E=e.data.get(s.dataId).values,D=v.values,$=x.computeStrides(o.shape),R=x.computeStrides(s.shape);for(let M=0;M<l.batchSize;++M){let W=M*$[0],U=M*v.strides[0];for(let q=0;q<l.outDepth;++q){let K=U+q*v.strides[1],j=q*l.strideDepth-y;for(let Q=0;Q<c;++Q){let rt=j+Q*f;if(rt<0||rt>=l.inDepth)continue;let X=Q*R[0],nt=W+rt*$[1];for(let st=0;st<l.outHeight;++st){let it=K+st*v.strides[2],ft=st*l.strideHeight-w;for(let at=0;at<p;++at){let xt=ft+at*d;if(xt<0||xt>=l.inHeight)continue;let dt=X+at*R[1],bt=nt+xt*$[2];for(let kt=0;kt<l.outWidth;++kt){let At=it+kt*l.outChannels,$t=kt*l.strideWidth-b;for(let qt=0;qt<m;++qt){let Kt=$t+qt*h;if(Kt<0||Kt>=l.inWidth)continue;let ce=dt+qt*R[2],Ot=bt+Kt*l.inChannels,Ee=ce;for(let Ie=0;Ie<l.inChannels;++Ie){let ae=I[Ot+Ie];for(let qe=0;qe<l.outChannels;++qe)D[At+qe]+=ae*E[Ee+qe];Ee+=l.outChannels}}}}}}}}return e.makeTensorInfo(v.shape,v.dtype,v.values)}var AF={kernelName:Il,backendName:"cpu",kernelFunc:r9};function n9(r){let{inputs:t,backend:e,attrs:n}=r,{x:o,dy:s}=t,{strides:i,pad:a,filterShape:u}=n;ot([o,s],"conv3dBackpropFilterV2");let l=x.computeStrides(o.shape),c=x.computeStrides(s.shape),p=k.computeConv3DInfo(o.shape,u,i,1,a),m=p.strideDepth,f=p.strideHeight,d=p.strideWidth,h=p.filterDepth,g=p.filterHeight,y=p.filterWidth,b=new me(p.filterShape,"float32"),w=b.values,[v,I,E,D]=b.strides,$=e.data.get(s.dataId).values,[R,M,W,U]=c,q=e.data.get(o.dataId).values,[K,j,Q,rt]=l,X=p.padInfo.front,nt=p.padInfo.left,st=p.padInfo.top;for(let it=0;it<h;++it){let ft=Math.max(0,Math.ceil((X-it)/m)),at=Math.min(p.outDepth,(p.inDepth+X-it)/m),xt=it*v;for(let dt=0;dt<g;++dt){let bt=Math.max(0,Math.ceil((st-dt)/f)),kt=Math.min(p.outHeight,(p.inHeight+st-dt)/f),At=dt*I+xt;for(let $t=0;$t<y;++$t){let qt=Math.max(0,Math.ceil((nt-$t)/d)),Kt=Math.min(p.outWidth,(p.inWidth+nt-$t)/d),ce=$t*E+At;for(let Ot=0;Ot<p.inChannels;++Ot){let Ee=Ot*D+ce;for(let Ie=0;Ie<p.outChannels;++Ie){let ae=0;for(let qe=0;qe<p.batchSize;++qe){let Re=qe*K,Jr=qe*R;for(let ze=ft;ze<at;++ze){let Fr=(it+ze*m-X)*j+Re,Qr=ze*M+Jr;for(let tn=bt;tn<kt;++tn){let eo=(dt+tn*f-st)*Q+Fr,$n=tn*W+Qr;for(let Mo=qt;Mo<Kt;++Mo){let hl=($t+Mo*d-nt)*rt+eo,uu=Mo*U+$n;ae+=q[hl+Ot]*$[uu+Ie]}}}}w[Ee+Ie]=ae}}}}}return e.makeTensorInfo(b.shape,b.dtype,b.values)}var DF={kernelName:fp,backendName:"cpu",kernelFunc:n9};function o9(r){let{inputs:t,backend:e,attrs:n}=r,{dy:o,filter:s}=t,{pad:i,strides:a,inputShape:u}=n;ot([o],"conv3dBackpropInputV2");let l=x.computeStrides(o.shape),c=x.computeStrides(s.shape),p=k.computeConv3DInfo(u,s.shape,a,1,i),m=new me(p.inShape,"float32"),f=m.values,[d,h,g,y]=m.strides,b=e.data.get(o.dataId).values,[w,v,I,E]=l,D=e.data.get(s.dataId).values,[$,R,M,W]=c,{batchSize:U,filterDepth:q,filterHeight:K,filterWidth:j,inChannels:Q,inDepth:rt,inHeight:X,inWidth:nt,outChannels:st,outDepth:it,outHeight:ft,outWidth:at,strideDepth:xt,strideHeight:dt,strideWidth:bt}=p,kt=q-1-p.padInfo.front,At=K-1-p.padInfo.top,$t=j-1-p.padInfo.left;for(let qt=0;qt<U;++qt)for(let Kt=0;Kt<Q;++Kt)for(let ce=0;ce<rt;++ce){let Ot=ce-kt,Ee=Math.max(0,Math.ceil(Ot/xt)),Ie=Math.min(it,(q+Ot)/xt);for(let ae=0;ae<X;++ae){let qe=ae-At,Re=Math.max(0,Math.ceil(qe/dt)),Jr=Math.min(ft,(K+qe)/dt);for(let ze=0;ze<nt;++ze){let Po=ze-$t,Fr=Math.max(0,Math.ceil(Po/bt)),Qr=Math.min(at,(j+Po)/bt),tn=0;for(let Hr=Ee;Hr<Ie;++Hr){let eo=Hr*xt-Ot;for(let $n=Re;$n<Jr;++$n){let Mo=$n*dt-qe;for(let ro=Fr;ro<Qr;++ro){let hl=ro*bt-Po,uu=w*qt+v*Hr+I*$n+E*ro,Gc=$*(q-1-eo)+R*(K-1-Mo)+M*(j-1-hl)+W*Kt;for(let hr=0;hr<st;++hr){let Wc=b[uu+hr],Uc=D[Gc+hr];tn+=Wc*Uc}}}}f[d*qt+h*ce+g*ae+y*ze+Kt]=tn}}}return e.makeTensorInfo(m.shape,m.dtype,m.values)}var $F={kernelName:dp,backendName:"cpu",kernelFunc:o9};var s9=Et(Qo,r=>Math.cos(r)),RF={kernelName:Qo,backendName:"cpu",kernelFunc:s9};var i9=Et(ts,r=>Math.cosh(r)),FF={kernelName:ts,backendName:"cpu",kernelFunc:i9};function a9(r){let{inputs:t,backend:e,attrs:n}=r,{image:o,boxes:s,boxInd:i}=t,{cropSize:a,method:u,extrapolationValue:l}=n,[c,p,m,f]=o.shape,d=s.shape[0],[h,g]=a,y=It([d,h,g,f],"float32"),b=e.data.get(s.dataId).values,w=e.data.get(i.dataId).values,v=e.data.get(o.dataId).values,I=x.computeStrides(o.shape),E=x.computeStrides(y.shape);for(let D=0;D<d;D++){let $=D*4,R=b[$],M=b[$+1],W=b[$+2],U=b[$+3],q=w[D];if(q>=c)continue;let K=h>1?(W-R)*(p-1)/(h-1):0,j=g>1?(U-M)*(m-1)/(g-1):0;for(let Q=0;Q<h;Q++){let rt=h>1?R*(p-1)+Q*K:.5*(R+W)*(p-1);if(rt<0||rt>p-1){for(let X=0;X<g;X++)for(let nt=0;nt<f;nt++){let st=nt+X*E[2]+Q*E[1]+D*E[0];y.values[st]=l}continue}if(u==="bilinear"){let X=Math.floor(rt),nt=Math.ceil(rt),st=rt-X;for(let it=0;it<g;it++){let ft=g>1?M*(m-1)+it*j:.5*(M+U)*(m-1);if(ft<0||ft>m-1){for(let bt=0;bt<f;bt++){let kt=bt+it*E[2]+Q*E[1]+D*E[0];y.values[kt]=l}continue}let at=Math.floor(ft),xt=Math.ceil(ft),dt=ft-at;for(let bt=0;bt<f;bt++){let kt=bt+at*I[2]+X*I[1]+q*I[0],At=v[kt];kt=bt+xt*I[2]+X*I[1]+q*I[0];let $t=v[kt];kt=bt+at*I[2]+nt*I[1]+q*I[0];let qt=v[kt];kt=bt+xt*I[2]+nt*I[1]+q*I[0];let Kt=v[kt],ce=At+($t-At)*dt,Ot=qt+(Kt-qt)*dt;kt=bt+it*E[2]+Q*E[1]+D*E[0],y.values[kt]=ce+(Ot-ce)*st}}}else for(let X=0;X<g;++X){let nt=g>1?M*(m-1)+X*j:.5*(M+U)*(m-1);if(nt<0||nt>m-1){for(let ft=0;ft<f;ft++){let at=ft+X*E[2]+Q*E[1]+D*E[0];y.values[at]=l}continue}let st=Math.round(nt),it=Math.round(rt);for(let ft=0;ft<f;ft++){let at=ft+st*I[2]+it*I[1]+q*I[0],xt=ft+X*E[2]+Q*E[1]+D*E[0];y.values[xt]=v[at]}}}}return e.makeTensorInfo(y.shape,y.dtype,y.values)}var OF={kernelName:na,backendName:"cpu",kernelFunc:a9};function l9(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{axis:s,exclusive:i,reverse:a}=n;ot(o,"cumsum");let u=k.getAxesPermutation([s],o.shape.length),l=o;u!=null&&(l=ir({inputs:{x:o},backend:e,attrs:{perm:u}}));let c=k.getInnerMostAxes(1,o.shape.length)[0];if(c!==l.shape.length-1)throw new Error(`backend.cumsum in CPU expects an 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e.makeTensorInfo(c.shape,s.dtype,c.values)}throw new Error(`Error in denseBincount: input must be at most rank 2, but got rank${o.shape.length}.`)}var MF={kernelName:hp,backendName:"cpu",kernelFunc:u9};function c9(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{blockSize:s,dataFormat:i}=n;x.assert(i==="NHWC",()=>`Only NHWC dataFormat supported on CPU for depthToSpace. 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BF={kernelName:gp,backendName:"cpu",kernelFunc:p9};function m9(r){let{inputs:t,backend:e,attrs:n}=r,{dy:o,filter:s}=t,{strides:i,dilations:a,pad:u,dimRoundingMode:l,inputShape:c}=n;ot([o,s],"depthwiseConv2DNativeBackpropInput");let p=x.computeStrides(o.shape),m=x.computeStrides(s.shape),f=k.computeConv2DInfo(c,s.shape,i,a,u,l,!0),d=new me(f.inShape,"float32"),h=d.values,[g,y,b]=d.strides,w=e.data.get(o.dataId).values,[v,I,E]=p,D=e.data.get(s.dataId).values,[$,R,M]=m,{batchSize:W,filterHeight:U,filterWidth:q,inChannels:K,inHeight:j,inWidth:Q,outChannels:rt,outHeight:X,outWidth:nt,strideHeight:st,strideWidth:it}=f,ft=U-1-f.padInfo.top,at=q-1-f.padInfo.left,xt=rt/K;for(let dt=0;dt<W;++dt)for(let bt=0;bt<K;++bt)for(let kt=0;kt<j;++kt){let At=kt-ft,$t=Math.max(0,Math.ceil(At/st)),qt=Math.min(X,(U+At)/st);for(let Kt=0;Kt<Q;++Kt){let ce=Kt-at,Ot=Math.max(0,Math.ceil(ce/it)),Ee=Math.min(nt,(q+ce)/it),Ie=0;for(let ae=$t;ae<qt;++ae){let qe=ae*st-At;for(let Re=Ot;Re<Ee;++Re){let 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n=r.shape,o=n[0],s=n[1],i=e.data.get(r.dataId),a=i.complexTensorInfos.real,u=i.complexTensorInfos.imag,l=[o,s],c=x.sizeFromShape(l),p=x.getTypedArrayFromDType("float32",c),m=x.getTypedArrayFromDType("float32",c);for(let g=0;g<o;g++){let y=Do({inputs:{x:a},backend:e,attrs:{begin:[g,0],size:[1,s]}}),b=Do({inputs:{x:u},backend:e,attrs:{begin:[g,0],size:[1,s]}}),w=Ir({inputs:{real:y,imag:b},backend:e}),{real:v,imag:I}=S9(w,t,e),E=k.mergeRealAndImagArrays(v,I);for(let D=0;D<s;D++){let $=k.getComplexWithIndex(E,D);p[g*s+D]=$.real,m[g*s+D]=$.imag}e.disposeIntermediateTensorInfo(y),e.disposeIntermediateTensorInfo(b),e.disposeIntermediateTensorInfo(w)}let f=e.makeTensorInfo(l,"float32",p),d=e.makeTensorInfo(l,"float32",m),h=Ir({inputs:{real:f,imag:d},backend:e});return e.disposeIntermediateTensorInfo(f),e.disposeIntermediateTensorInfo(d),h}function S9(r,t,e){let n=x.sizeFromShape(r.shape),o=e.data.get(r.dataId),s=e.data.get(o.complexTensorInfos.real.dataId).values,i=e.data.get(o.complexTensorInfos.imag.dataId).values;if(k9(n)){let a=ES(s,i,n,t,e),u=[r.shape[0],r.shape[1]];if(t){let l=e.makeTensorInfo(u,"float32",a.real),c=e.makeTensorInfo(u,"float32",a.imag),p=e.makeTensorInfo([],"float32",x.createScalarValue(n,"float32")),m=Wr({inputs:{x:p},backend:e}),f=Yh.kernelFunc({inputs:{a:l,b:p},backend:e}),d=Yh.kernelFunc({inputs:{a:c,b:m},backend:e}),h=e.data.get(f.dataId).values,g=e.data.get(d.dataId).values;return e.disposeIntermediateTensorInfo(l),e.disposeIntermediateTensorInfo(c),e.disposeIntermediateTensorInfo(p),e.disposeIntermediateTensorInfo(m),e.disposeIntermediateTensorInfo(f),e.disposeIntermediateTensorInfo(d),{real:h,imag:g}}return a}else{let a=k.mergeRealAndImagArrays(s,i),u=N9(a,n,t);return k.splitRealAndImagArrays(u)}}function k9(r){return(r&r-1)===0}function ES(r,t,e,n,o){if(e===1)return{real:r,imag:t};let 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n=1,o=1;r.texImage2D(r.TEXTURE_2D,0,t.internalFormatFloat,n,o,0,t.textureFormatFloat,t.textureTypeFloat,null);let s=r.createFramebuffer();r.bindFramebuffer(r.FRAMEBUFFER,s),r.framebufferTexture2D(r.FRAMEBUFFER,r.COLOR_ATTACHMENT0,r.TEXTURE_2D,e,0);let i=r.checkFramebufferStatus(r.FRAMEBUFFER)===r.FRAMEBUFFER_COMPLETE;return r.bindTexture(r.TEXTURE_2D,null),r.bindFramebuffer(r.FRAMEBUFFER,null),r.deleteTexture(e),r.deleteFramebuffer(s),i}function xQ(r,t){let e=eg(r,t),n=r.createTexture();r.bindTexture(r.TEXTURE_2D,n);let o=1,s=1;r.texImage2D(r.TEXTURE_2D,0,e.internalFormatHalfFloat,o,s,0,e.textureFormatFloat,e.textureTypeHalfFloat,null);let i=r.createFramebuffer();r.bindFramebuffer(r.FRAMEBUFFER,i),r.framebufferTexture2D(r.FRAMEBUFFER,r.COLOR_ATTACHMENT0,r.TEXTURE_2D,n,0);let a=r.checkFramebufferStatus(r.FRAMEBUFFER)===r.FRAMEBUFFER_COMPLETE;return r.bindTexture(r.TEXTURE_2D,null),r.bindFramebuffer(r.FRAMEBUFFER,null),r.deleteTexture(n),r.deleteFramebuffer(i),a}function rk(r){return r!==2?!1:Vn(r).fenceSync!=null}function ai(r,t){Array.isArray(r)||(r=[r]),r.forEach(e=>{e!=null&&x.assert(e.dtype!=="complex64",()=>`${t} does not support complex64 tensors in the WebGL backend.`)})}var Ft=G();Ft.registerFlag("HAS_WEBGL",()=>Ft.getNumber("WEBGL_VERSION")>0);Ft.registerFlag("WEBGL_VERSION",()=>cb(2)?2:cb(1)?1:0);Ft.registerFlag("WEBGL_CHECK_NUMERICAL_PROBLEMS",()=>!1);Ft.registerFlag("WEBGL_BUFFER_SUPPORTED",()=>Ft.get("WEBGL_VERSION")===2);Ft.registerFlag("WEBGL_CPU_FORWARD",()=>!0);Ft.registerFlag("WEBGL_FORCE_F16_TEXTURES",()=>!1);Ft.registerFlag("WEBGL_PACK",()=>Ft.getBool("HAS_WEBGL"));Ft.registerFlag("WEBGL_PACK_NORMALIZATION",()=>Ft.getBool("WEBGL_PACK"));Ft.registerFlag("WEBGL_PACK_CLIP",()=>Ft.getBool("WEBGL_PACK"));Ft.registerFlag("WEBGL_PACK_DEPTHWISECONV",()=>Ft.getBool("WEBGL_PACK"));Ft.registerFlag("WEBGL_PACK_BINARY_OPERATIONS",()=>Ft.getBool("WEBGL_PACK"));Ft.registerFlag("WEBGL_PACK_UNARY_OPERATIONS",()=>Ft.getBool("WEBGL_PACK"));Ft.registerFlag("WEBGL_PACK_ARRAY_OPERATIONS",()=>Ft.getBool("WEBGL_PACK"));Ft.registerFlag("WEBGL_PACK_IMAGE_OPERATIONS",()=>Ft.getBool("WEBGL_PACK"));Ft.registerFlag("WEBGL_PACK_REDUCE",()=>Ft.getBool("WEBGL_PACK"));Ft.registerFlag("WEBGL_LAZILY_UNPACK",()=>Ft.getBool("WEBGL_PACK"));Ft.registerFlag("WEBGL_CONV_IM2COL",()=>Ft.getBool("WEBGL_PACK"));Ft.registerFlag("WEBGL_MAX_TEXTURE_SIZE",()=>ZS(Ft.getNumber("WEBGL_VERSION")));Ft.registerFlag("WEBGL_MAX_TEXTURES_IN_SHADER",()=>JS(Ft.getNumber("WEBGL_VERSION")));Ft.registerFlag("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION",()=>{let r=Ft.getNumber("WEBGL_VERSION");return r===0?0:QS(r)});Ft.registerFlag("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE",()=>Ft.getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")>0&&!Ll.isMobile());Ft.registerFlag("WEBGL_RENDER_FLOAT32_CAPABLE",()=>tk(Ft.getNumber("WEBGL_VERSION")));Ft.registerFlag("WEBGL_RENDER_FLOAT32_ENABLED",()=>Ft.getBool("WEBGL_FORCE_F16_TEXTURES")?!1:Ft.getBool("WEBGL_RENDER_FLOAT32_CAPABLE"));Ft.registerFlag("WEBGL_DOWNLOAD_FLOAT_ENABLED",()=>ek(Ft.getNumber("WEBGL_VERSION")));Ft.registerFlag("WEBGL_FENCE_API_ENABLED",()=>rk(Ft.getNumber("WEBGL_VERSION")));Ft.registerFlag("WEBGL_SIZE_UPLOAD_UNIFORM",()=>Ft.getBool("WEBGL_RENDER_FLOAT32_ENABLED")?4:0);Ft.registerFlag("WEBGL_DELETE_TEXTURE_THRESHOLD",()=>-1,r=>{if(r<0&&r!==-1)throw new Error(`WEBGL_DELETE_TEXTURE_THRESHOLD must be -1 (indicating never delete) or at least 0, but got ${r}.`)});Ft.registerFlag("WEBGL_FLUSH_THRESHOLD",()=>Ll.isMobile()?1:-1,r=>{if(r<0&&r!==-1)throw new Error(`WEBGL_FLUSH_THRESHOLD must be -1 (indicating never manual flush) or at least 0, but got ${r}.`)});Ft.registerFlag("CPU_HANDOFF_SIZE_THRESHOLD",()=>128);Ft.registerFlag("WEBGL_USE_SHAPES_UNIFORMS",()=>!1);Ft.registerFlag("TOPK_LAST_DIM_CPU_HANDOFF_SIZE_THRESHOLD",()=>1e5);Ft.registerFlag("TOPK_K_CPU_HANDOFF_THRESHOLD",()=>128);function He(){let r,t,e,n,o,s,i,a,u,l;return G().getNumber("WEBGL_VERSION")===2?(r="#version 300 es",t="in",e="out",n="in",o="texture",s="outputColor",i="out vec4 outputColor;",a=`
bool isnan_custom(float val) {
uint floatToUint = floatBitsToUint(val);
return (floatToUint & 0x7fffffffu) > 0x7f800000u;
}
bvec4 isnan_custom(vec4 val) {
return bvec4(isnan_custom(val.x),
isnan_custom(val.y), isnan_custom(val.z), isnan_custom(val.w));
}
#define isnan(value) isnan_custom(value)
`,u="",l=`
#define round(value) newRound(value)
int newRound(float value) {
return int(floor(value + 0.5));
}
ivec4 newRound(vec4 value) {
return ivec4(floor(value + vec4(0.5)));
}
`):(r="",t="attribute",e="varying",n="varying",o="texture2D",s="gl_FragColor",i="",a=`
#define isnan(value) isnan_custom(value)
bool isnan_custom(float val) {
return (val > 0. || val < 1. || val == 0.) ? false : true;
}
bvec4 isnan_custom(vec4 val) {
return bvec4(isnan(val.x), isnan(val.y), isnan(val.z), isnan(val.w));
}
`,u=`
uniform float INFINITY;
bool isinf(float val) {
return abs(val) == INFINITY;
}
bvec4 isinf(vec4 val) {
return equal(abs(val), vec4(INFINITY));
}
`,l=`
int round(float value) {
return int(floor(value + 0.5));
}
ivec4 round(vec4 value) {
return ivec4(floor(value + vec4(0.5)));
}
`),{version:r,attribute:t,varyingVs:e,varyingFs:n,texture2D:o,output:s,defineOutput:i,defineSpecialNaN:a,defineSpecialInf:u,defineRound:l}}function li(r,t,e="index"){let n=x.computeStrides(t);return n.map((o,s)=>{let i=`int ${r[s]} = ${e} / ${o}`,a=s===n.length-1?`int ${r[s+1]} = ${e} - ${r[s]} * ${o}`:`index -= ${r[s]} * ${o}`;return`${i}; ${a};`}).join("")}function Ac(r,t,e="index"){let n=x.computeStrides(t);return n.map((o,s)=>{let i=`int ${r[s]} = ${e} / outShapeStrides[${s}]`,a=s===n.length-1?`int ${r[s+1]} = ${e} - ${r[s]} * outShapeStrides[${s}]`:`index -= ${r[s]} * outShapeStrides[${s}]`;return`${i}; ${a};`}).join("")}function yQ(r,t){let e=r.length,n=r.map(s=>`${t}[${s}]`),o=new Array(e-1);o[e-2]=n[e-1];for(let s=e-3;s>=0;--s)o[s]=`(${o[s+1]} * ${n[s+1]})`;return o}function AP(r,t,e="index"){let n=r.map((s,i)=>i),o=yQ(n,t);return o.map((s,i)=>{let a=`int ${r[i]} = ${e} / ${o[i]}`,u=i===o.length-1?`int ${r[i+1]} = ${e} - ${r[i]} * ${o[i]}`:`index -= ${r[i]} * ${o[i]}`;return`${a}; ${u};`}).join("")}function Um(r){let t=x.computeStrides(r).map(e=>e.toString());return`
int getFlatIndex(ivec3 coords) {
return coords.x * ${t[0]} + coords.y * ${t[1]} + coords.z;
}
`}function Hm(){return`
int getFlatIndex(ivec3 coords) {
return coords.x * outShapeStrides[0] + coords.y * outShapeStrides[1] + coords.z;
}
`}var pb=`
const float FLOAT_MAX = 1.70141184e38;
const float FLOAT_MIN = 1.17549435e-38;
lowp vec4 encode_float(highp float v) {
if (isnan(v)) {
return vec4(255, 255, 255, 255);
}
highp float av = abs(v);
if(av < FLOAT_MIN) {
return vec4(0.0, 0.0, 0.0, 0.0);
} else if(v > FLOAT_MAX) {
return vec4(0.0, 0.0, 128.0, 127.0) / 255.0;
} else if(v < -FLOAT_MAX) {
return vec4(0.0, 0.0, 128.0, 255.0) / 255.0;
}
highp vec4 c = vec4(0,0,0,0);
highp float e = floor(log2(av));
highp float m = exp2(fract(log2(av))) - 1.0;
c[2] = floor(128.0 * m);
m -= c[2] / 128.0;
c[1] = floor(32768.0 * m);
m -= c[1] / 32768.0;
c[0] = floor(8388608.0 * m);
highp float ebias = e + 127.0;
c[3] = floor(ebias / 2.0);
ebias -= c[3] * 2.0;
c[2] += floor(ebias) * 128.0;
c[3] += 128.0 * step(0.0, -v);
return c / 255.0;
}
`;var{getBroadcastDims:DP}=k;function $P(r,t,e){let n=[];if(r.forEach(f=>{let d=x.sizeFromShape(f.shapeInfo.logicalShape);if(f.shapeInfo.isUniform?n.push(`uniform float ${f.name}${d>1?`[${d}]`:""};`):(n.push(`uniform sampler2D ${f.name};`),n.push(`uniform int offset${f.name};`)),e.enableShapeUniforms){let{uniformShape:h}=mb(e.packedInputs,f.shapeInfo.logicalShape,f.shapeInfo.texShape);switch(h.length){case 1:n.push(`uniform int ${f.name}Shape;`);break;case 2:n.push(`uniform ivec2 ${f.name}Shape;`);break;case 3:n.push(`uniform ivec3 ${f.name}Shape;`);break;case 4:n.push(`uniform ivec4 ${f.name}Shape;`);break;default:break}n.push(`uniform ivec2 ${f.name}TexShape;`)}}),e.enableShapeUniforms){switch(t.logicalShape.length){case 1:n.push("uniform int outShape;");break;case 2:n.push("uniform ivec2 outShape;"),n.push("uniform int outShapeStrides;");break;case 3:n.push("uniform ivec3 outShape;"),n.push("uniform ivec2 outShapeStrides;");break;case 4:n.push("uniform ivec4 outShape;"),n.push("uniform ivec3 outShapeStrides;");break;default:break}n.push("uniform ivec2 outTexShape;")}e.customUniforms&&e.customUniforms.forEach(f=>{n.push(`uniform ${f.type} ${f.name}${f.arrayIndex?`[${f.arrayIndex}]`:""};`)});let o=n.join(`
`),s=r.map(f=>bQ(f,t,e.packedInputs,e.enableShapeUniforms)).join(`
`),i=t.texShape,a=He(),u=CQ(a),l,c,p=kQ(a);return t.isPacked?(l=wQ(t.logicalShape,i,e.enableShapeUniforms),c=SQ(a)):(l=vQ(t.logicalShape,i,e.enableShapeUniforms),c=IQ(a)),e.packedInputs&&(p+=EQ),[p,u,c,o,l,s,e.userCode].join(`
`)}function Km(r,t=!1){let e=r.shapeInfo.logicalShape;switch(e.length){case 0:return VQ(r,t);case 1:return WQ(r,t);case 2:return HQ(r,t);case 3:return KQ(r,t);case 4:return XQ(r,t);case 5:return YQ(r);case 6:return ZQ(r);default:throw new Error(`${e.length}-D input sampling is not yet supported`)}}function RP(r,t){switch(r.shapeInfo.logicalShape.length){case 0:return BQ(r);case 1:return GQ(r,t);case 2:return UQ(r,t);case 3:return qQ(r,t);default:return jQ(r,t)}}function bQ(r,t,e=!1,n){let o="";e?o+=RP(r,n):o+=Km(r,n);let s=r.shapeInfo.logicalShape,i=t.logicalShape;return s.length<=i.length&&(e?o+=JQ(r,t):o+=QQ(r,t)),o}function wQ(r,t,e){switch(r.length){case 0:return FP();case 1:return AQ(r,t,e);case 2:return LQ(r,t,e);case 3:return $Q(r,t,e);default:return FQ(r,t,e)}}function vQ(r,t,e){switch(r.length){case 0:return FP();case 1:return DQ(r,t,e);case 2:return zQ(r,t,e);case 3:return RQ(r,t,e);case 4:return OQ(r,t,e);case 5:return PQ(r,t);case 6:return MQ(r,t);default:throw new Error(`${r.length}-D output sampling is not yet supported`)}}function CQ(r){return`
float sampleTexture(sampler2D textureSampler, vec2 uv) {
return ${r.texture2D}(textureSampler, uv).r;
}
`}function IQ(r){return`
void setOutput(float val) {
${r.output} = vec4(val, 0, 0, 0);
}
`}function SQ(r){return`
void setOutput(vec4 val) {
${r.output} = val;
}
`}function kQ(r){return`${r.version}
precision highp float;
precision highp int;
precision highp sampler2D;
${r.varyingFs} vec2 resultUV;
${r.defineOutput}
const vec2 halfCR = vec2(0.5, 0.5);
struct ivec5
{
int x;
int y;
int z;
int w;
int u;
};
struct ivec6
{
int x;
int y;
int z;
int w;
int u;
int v;
};
uniform float NAN;
${r.defineSpecialNaN}
${r.defineSpecialInf}
${r.defineRound}
int imod(int x, int y) {
return x - y * (x / y);
}
int idiv(int a, int b, float sign) {
int res = a / b;
int mod = imod(a, b);
if (sign < 0. && mod != 0) {
res -= 1;
}
return res;
}
//Based on the work of Dave Hoskins
//https://www.shadertoy.com/view/4djSRW
#define HASHSCALE1 443.8975
float random(float seed){
vec2 p = resultUV * seed;
vec3 p3 = fract(vec3(p.xyx) * HASHSCALE1);
p3 += dot(p3, p3.yzx + 19.19);
return fract((p3.x + p3.y) * p3.z);
}
${NQ}
${TQ}
${_Q}
`}var NQ=`
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);
}
`,TQ=`
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);
}
`,_Q=`
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 FP(){return`
int getOutputCoords() {
return 0;
}
`}function AQ(r,t,e){let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)];return n[0]===1?e?`
int getOutputCoords() {
return 2 * int(resultUV.x * ceil(float(outTexShape[1]) / 2.0));
}
`:`
int getOutputCoords() {
return 2 * int(resultUV.x * ${n[1]}.0);
}
`:n[1]===1?e?`
int getOutputCoords() {
return 2 * int(resultUV.y * ceil(float(outTexShape[0]) / 2.0));
}
`:`
int getOutputCoords() {
return 2 * int(resultUV.y * ${n[0]}.0);
}
`:e?`
int getOutputCoords() {
ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(packedTexShape[0], packedTexShape[1]));
return 2 * (resTexRC.x * packedTexShape[1] + resTexRC.y);
}
`:`
int getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${n[0]}, ${n[1]}));
return 2 * (resTexRC.x * ${n[1]} + resTexRC.y);
}
`}function DQ(r,t,e){return t[0]===1?e?`
int getOutputCoords() {
return int(resultUV.x * float(outTexShape[1]));
}
`:`
int getOutputCoords() {
return int(resultUV.x * ${t[1]}.0);
}
`:t[1]===1?e?`
int getOutputCoords() {
return int(resultUV.y * float(outTexShape[0]));
}
`:`
int getOutputCoords() {
return int(resultUV.y * ${t[0]}.0);
}
`:e?`
int getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(outTexShape[0], outTexShape[1]));
return resTexRC.x * outTexShape[1] + resTexRC.y;
}
`:`
int getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${t[0]}, ${t[1]}));
return resTexRC.x * ${t[1]} + resTexRC.y;
}
`}function $Q(r,t,e){if(e)return`
ivec3 getOutputCoords() {
ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));
int texelsInLogicalRow = int(ceil(float(outShape[2]) / 2.0));
int texelsInBatch = texelsInLogicalRow * int(ceil(float(outShape[1]) / 2.0));
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(packedTexShape[0], packedTexShape[1]));
int index = resTexRC.x * packedTexShape[1] + resTexRC.y;
int b = index / texelsInBatch;
index -= b * texelsInBatch;
int r = 2 * (index / texelsInLogicalRow);
int c = imod(index, texelsInLogicalRow) * 2;
return ivec3(b, r, c);
}
`;let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)],o=Math.ceil(r[2]/2),s=o*Math.ceil(r[1]/2);return`
ivec3 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${n[0]}, ${n[1]}));
int index = resTexRC.x * ${n[1]} + resTexRC.y;
int b = index / ${s};
index -= b * ${s};
int r = 2 * (index / ${o});
int c = imod(index, ${o}) * 2;
return ivec3(b, r, c);
}
`}function RQ(r,t,e){if(e)return`
ivec3 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(outTexShape[0], outTexShape[1]));
int index = resTexRC.x * outTexShape[1] + resTexRC.y;
${Ac(["r","c","d"],r)}
return ivec3(r, c, d);
}
`;let n=li(["r","c","d"],r);return`
ivec3 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${t[0]}, ${t[1]}));
int index = resTexRC.x * ${t[1]} + resTexRC.y;
${n}
return ivec3(r, c, d);
}
`}function FQ(r,t,e){if(e)return`
ivec4 getOutputCoords() {
ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(packedTexShape[0], packedTexShape[1]));
int index = resTexRC.x * packedTexShape[1] + resTexRC.y;
int texelsInLogicalRow = int(ceil(float(outShape[3]) / 2.0));
int texelsInBatch = texelsInLogicalRow * int(ceil(float(outShape[2]) / 2.0));
int texelsInBatchN = texelsInBatch * outShape[1];
int b2 = index / texelsInBatchN;
index -= b2 * texelsInBatchN;
int b = index / texelsInBatch;
index -= b * texelsInBatch;
int r = 2 * (index / texelsInLogicalRow);
int c = imod(index, texelsInLogicalRow) * 2;
return ivec4(b2, b, r, c);
}
`;let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)],o=Math.ceil(r[r.length-1]/2),s=o*Math.ceil(r[r.length-2]/2),i=s,a="",u="b, r, c";for(let l=2;l<r.length-1;l++)i*=r[r.length-l-1],a=`
int b${l} = index / ${i};
index -= b${l} * ${i};
`+a,u=`b${l}, `+u;return`
ivec${r.length} getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${n[0]}, ${n[1]}));
int index = resTexRC.x * ${n[1]} + resTexRC.y;
${a}
int b = index / ${s};
index -= b * ${s};
int r = 2 * (index / ${o});
int c = imod(index, ${o}) * 2;
return ivec${r.length}(${u});
}
`}function OQ(r,t,e){if(e)return`
ivec4 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(outTexShape[0], outTexShape[1]));
int index = resTexRC.x * outTexShape[1] + resTexRC.y;
${Ac(["r","c","d","d2"],r)}
return ivec4(r, c, d, d2);
}
`;let n=li(["r","c","d","d2"],r);return`
ivec4 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${t[0]}, ${t[1]}));
int index = resTexRC.x * ${t[1]} + resTexRC.y;
${n}
return ivec4(r, c, d, d2);
}
`}function PQ(r,t){let e=li(["r","c","d","d2","d3"],r);return`
ivec5 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx * vec2(${t[0]},
${t[1]}));
int index = resTexRC.x * ${t[1]} + resTexRC.y;
${e}
ivec5 outShape = ivec5(r, c, d, d2, d3);
return outShape;
}
`}function MQ(r,t){let e=li(["r","c","d","d2","d3","d4"],r);return`
ivec6 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${t[0]}, ${t[1]}));
int index = resTexRC.x * ${t[1]} + resTexRC.y;
${e}
ivec6 result = ivec6(r, c, d, d2, d3, d4);
return result;
}
`}function LQ(r,t,e){let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)];if(x.arraysEqual(r,t))return e?`
ivec2 getOutputCoords() {
ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));
return 2 * ivec2(resultUV.yx * vec2(packedTexShape[0], packedTexShape[1]));
}
`:`
ivec2 getOutputCoords() {
return 2 * ivec2(resultUV.yx * vec2(${n[0]}, ${n[1]}));
}
`;let o=Math.ceil(r[1]/2);return e?`
ivec2 getOutputCoords() {
ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));
int texelsInLogicalRow = int(ceil(float(outShape[1]) / 2.0));
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(packedTexShape[0], packedTexShape[1]));
int index = resTexRC.x * packedTexShape[1] + resTexRC.y;
int r = 2 * (index / texelsInLogicalRow);
int c = imod(index, texelsInLogicalRow) * 2;
return ivec2(r, c);
}
`:`
ivec2 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${n[0]}, ${n[1]}));
int index = resTexRC.x * ${n[1]} + resTexRC.y;
int r = 2 * (index / ${o});
int c = imod(index, ${o}) * 2;
return ivec2(r, c);
}
`}function zQ(r,t,e){return x.arraysEqual(r,t)?e?`
ivec2 getOutputCoords() {
return ivec2(resultUV.yx * vec2(outTexShape[0], outTexShape[1]));
}
`:`
ivec2 getOutputCoords() {
return ivec2(resultUV.yx * vec2(${t[0]}, ${t[1]}));
}
`:r[1]===1?e?`
ivec2 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(outTexShape[0], outTexShape[1]));
int index = resTexRC.x * outTexShape[1] + resTexRC.y;
return ivec2(index, 0);
}
`:`
ivec2 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${t[0]}, ${t[1]}));
int index = resTexRC.x * ${t[1]} + resTexRC.y;
return ivec2(index, 0);
}
`:r[0]===1?e?`
ivec2 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(outTexShape[0], outTexShape[1]));
int index = resTexRC.x * outTexShape[1] + resTexRC.y;
return ivec2(0, index);
}
`:`
ivec2 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${t[0]}, ${t[1]}));
int index = resTexRC.x * ${t[1]} + resTexRC.y;
return ivec2(0, index);
}
`:e?`
ivec2 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(outTexShape[0], outTexShape[1]));
int index = resTexRC.x * outTexShape[1] + resTexRC.y;
int r = index / outShape[1];
int c = index - r * outShape[1];
return ivec2(r, c);
}
`:`
ivec2 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${t[0]}, ${t[1]}));
int index = resTexRC.x * ${t[1]} + resTexRC.y;
int r = index / ${r[1]};
int c = index - r * ${r[1]};
return ivec2(r, c);
}
`}function Dc(r){return`offset${r}`}function BQ(r){let t=r.name,e="get"+t.charAt(0).toUpperCase()+t.slice(1),n=He();return`
vec4 ${e}() {
return ${n.texture2D}(${t}, halfCR);
}
`}function VQ(r,t){let e=r.name,n="get"+e.charAt(0).toUpperCase()+e.slice(1);if(r.shapeInfo.isUniform)return`float ${n}() {return ${e};}`;let[o,s]=r.shapeInfo.texShape;if(o===1&&s===1)return`
float ${n}() {
return sampleTexture(${e}, halfCR);
}
`;let i=Dc(e);if(t)return`
float ${n}() {
vec2 uv = uvFromFlat(${e}TexShape[0], ${e}TexShape[1], ${i});
return sampleTexture(${e}, uv);
}
`;let[a,u]=r.shapeInfo.texShape;return`
float ${n}() {
vec2 uv = uvFromFlat(${a}, ${u}, ${i});
return sampleTexture(${e}, uv);
}
`}function GQ(r,t){let e=r.name,n="get"+e.charAt(0).toUpperCase()+e.slice(1),o=r.shapeInfo.texShape,s=He();if(t)return`
vec4 ${n}(int index) {
ivec2 packedTexShape = ivec2(ceil(float(${e}TexShape[0]) / 2.0), ceil(float(${e}TexShape[1]) / 2.0));
vec2 uv = packedUVfrom1D(
packedTexShape[0], packedTexShape[1], index);
return ${s.texture2D}(${e}, uv);
}
`;let i=[Math.ceil(o[0]/2),Math.ceil(o[1]/2)];return`
vec4 ${n}(int index) {
vec2 uv = packedUVfrom1D(
${i[0]}, ${i[1]}, index);
return ${s.texture2D}(${e}, uv);
}
`}function WQ(r,t){let e=r.name,n="get"+e.charAt(0).toUpperCase()+e.slice(1);if(r.shapeInfo.isUniform)return`
float ${n}(int index) {
${jm(r)}
}
`;let o=r.shapeInfo.texShape,s=o[0],i=o[1];if(i===1&&s===1)return`
float ${n}(int index) {
return sampleTexture(${e}, halfCR);
}
`;let a=Dc(e);return i===1?t?`
float ${n}(int index) {
vec2 uv = vec2(0.5, (float(index + ${a}) + 0.5) / float(${e}TexShape[0]));
return sampleTexture(${e}, uv);
}
`:`
float ${n}(int index) {
vec2 uv = vec2(0.5, (float(index + ${a}) + 0.5) / ${s}.0);
return sampleTexture(${e}, uv);
}
`:s===1?t?`
float ${n}(int index) {
vec2 uv = vec2((float(index + ${a}) + 0.5) / float(${e}TexShape[1]), 0.5);
return sampleTexture(${e}, uv);
}
`:`
float ${n}(int index) {
vec2 uv = vec2((float(index + ${a}) + 0.5) / ${i}.0, 0.5);
return sampleTexture(${e}, uv);
}
`:t?`
float ${n}(int index) {
vec2 uv = uvFromFlat(${e}TexShape[0], ${e}TexShape[1], index + ${a});
return sampleTexture(${e}, uv);
}
`:`
float ${n}(int index) {
vec2 uv = uvFromFlat(${s}, ${i}, index + ${a});
return sampleTexture(${e}, uv);
}
`}function UQ(r,t){let e=r.shapeInfo.logicalShape,n=r.name,o="get"+n.charAt(0).toUpperCase()+n.slice(1),s=r.shapeInfo.texShape,i=s[0],a=s[1],u=He();if(s!=null&&x.arraysEqual(e,s))return t?`
vec4 ${o}(int row, int col) {
vec2 uv = (vec2(col, row) + halfCR) / vec2(${n}TexShape[1], ${n}TexShape[0]);
return ${u.texture2D}(${n}, uv);
}
`:`
vec4 ${o}(int row, int col) {
vec2 uv = (vec2(col, row) + halfCR) / vec2(${a}.0, ${i}.0);
return ${u.texture2D}(${n}, uv);
}
`;if(t)return`
vec4 ${o}(int row, int col) {
ivec2 packedTexShape = ivec2(ceil(float(${n}TexShape[0]) / 2.0), ceil(float(${n}TexShape[1]) / 2.0));
int valuesPerRow = int(ceil(float(${n}Shape[1]) / 2.0));
vec2 uv = packedUVfrom2D(valuesPerRow, packedTexShape[0], packedTexShape[1], row, col);
return ${u.texture2D}(${n}, uv);
}
`;let l=[Math.ceil(s[0]/2),Math.ceil(s[1]/2)],c=Math.ceil(e[1]/2);return`
vec4 ${o}(int row, int col) {
vec2 uv = packedUVfrom2D(${c}, ${l[0]}, ${l[1]}, row, col);
return ${u.texture2D}(${n}, uv);
}
`}function HQ(r,t){let e=r.shapeInfo.logicalShape,n=r.name,o="get"+n.charAt(0).toUpperCase()+n.slice(1),s=r.shapeInfo.texShape;if(s!=null&&x.arraysEqual(e,s)){if(t)return`
float ${o}(int row, int col) {
vec2 uv = (vec2(col, row) + halfCR) / vec2(${n}TexShape[1], ${n}TexShape[0]);
return sampleTexture(${n}, uv);
}
`;let m=s[0],f=s[1];return`
float ${o}(int row, int col) {
vec2 uv = (vec2(col, row) + halfCR) / vec2(${f}.0, ${m}.0);
return sampleTexture(${n}, uv);
}
`}let{newShape:i,keptDims:a}=x.squeezeShape(e),u=i;if(u.length<e.length){let m=Xm(r,u),f=["row","col"];return`
${Km(m,t)}
float ${o}(int row, int col) {
return ${o}(${Ym(f,a)});
}
`}if(r.shapeInfo.isUniform)return`
float ${o}(int row, int col) {
int index = round(dot(vec2(row, col), vec2(${e[1]}, 1)));
${jm(r)}
}
`;let l=s[0],c=s[1],p=Dc(n);return c===1?t?`
float ${o}(int row, int col) {
float index = dot(vec3(row, col, ${p}), vec3(${n}Shape[1], 1, 1));
vec2 uv = vec2(0.5, (index + 0.5) / float(${n}TexShape[0]));
return sampleTexture(${n}, uv);
}
`:`
float ${o}(int row, int col) {
float index = dot(vec3(row, col, ${p}), vec3(${e[1]}, 1, 1));
vec2 uv = vec2(0.5, (index + 0.5) / ${l}.0);
return sampleTexture(${n}, uv);
}
`:l===1?t?`
float ${o}(int row, int col) {
float index = dot(vec3(row, col, ${p}), vec3(${n}Shape[1], 1, 1));
vec2 uv = vec2((index + 0.5) / float(${n}TexShape[1]), 0.5);
return sampleTexture(${n}, uv);
}
`:`
float ${o}(int row, int col) {
float index = dot(vec3(row, col, ${p}), vec3(${e[1]}, 1, 1));
vec2 uv = vec2((index + 0.5) / ${c}.0, 0.5);
return sampleTexture(${n}, uv);
}
`:t?`
float ${o}(int row, int col) {
// Explicitly use integer operations as dot() only works on floats.
int index = row * ${n}Shape[1] + col + ${p};
vec2 uv = uvFromFlat(${n}TexShape[0], ${n}TexShape[1], index);
return sampleTexture(${n}, uv);
}
`:`
float ${o}(int row, int col) {
// Explicitly use integer operations as dot() only works on floats.
int index = row * ${e[1]} + col + ${p};
vec2 uv = uvFromFlat(${l}, ${c}, index);
return sampleTexture(${n}, uv);
}
`}function qQ(r,t){let e=r.shapeInfo.logicalShape,n=r.name,o="get"+n.charAt(0).toUpperCase()+n.slice(1),s=r.shapeInfo.texShape,i=[Math.ceil(s[0]/2),Math.ceil(s[1]/2)];if(e[0]===1){let m=e.slice(1),f=[1,2],d=Xm(r,m),h=["b","row","col"];return`
${RP(d,t)}
vec4 ${o}(int b, int row, int col) {
return ${o}(${Ym(h,f)});
}
`}let a=He();if(t)return`
vec4 ${o}(int b, int row, int col) {
ivec2 packedTexShape = ivec2(ceil(float(${n}TexShape[0]) / 2.0), ceil(float(${n}TexShape[1]) / 2.0));
int valuesPerRow = int(ceil(float(${n}Shape[2]) / 2.0));
int texelsInBatch = valuesPerRow * int(ceil(float(${n}Shape[1]) / 2.0));
vec2 uv = packedUVfrom3D(
packedTexShape[0], packedTexShape[1], texelsInBatch, valuesPerRow, b, row, col);
return ${a.texture2D}(${n}, uv);
}
`;let u=i[0],l=i[1],c=Math.ceil(e[2]/2),p=c*Math.ceil(e[1]/2);return`
vec4 ${o}(int b, int row, int col) {
vec2 uv = packedUVfrom3D(
${u}, ${l}, ${p}, ${c}, b, row, col);
return ${a.texture2D}(${n}, uv);
}
`}function KQ(r,t){let e=r.shapeInfo.logicalShape,n=r.name,o="get"+n.charAt(0).toUpperCase()+n.slice(1),s=e[1]*e[2],i=e[2],{newShape:a,keptDims:u}=x.squeezeShape(e),l=a;if(l.length<e.length){let h=Xm(r,l),g=["row","col","depth"];return`
${Km(h,t)}
float ${o}(int row, int col, int depth) {
return ${o}(${Ym(g,u)});
}
`}if(r.shapeInfo.isUniform)return`
float ${o}(int row, int col, int depth) {
int index = round(dot(vec3(row, col, depth),
vec3(${s}, ${i}, 1)));
${jm(r)}
}
`;let c=r.shapeInfo.texShape,p=c[0],m=c[1],f=r.shapeInfo.flatOffset;if(m===s&&f==null)return t?`
float ${o}(int row, int col, int depth) {
int stride1 = ${n}Shape[2];
float texR = float(row);
float texC = dot(vec2(col, depth), vec2(stride1, 1));
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${n}TexShape[1], ${n}TexShape[0]);
return sampleTexture(${n}, uv);
}
`:`
float ${o}(int row, int col, int depth) {
float texR = float(row);
float texC = dot(vec2(col, depth), vec2(${i}, 1));
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${m}.0, ${p}.0);
return sampleTexture(${n}, uv);
}
`;if(m===i&&f==null)return t?`
float ${o}(int row, int col, int depth) {
float texR = dot(vec2(row, col), vec2(${n}Shape[1], 1));
float texC = float(depth);
vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${n}TexShape[1], ${n}TexShape[0]);
return sampleTexture(${n}, uv);
}
`:`
float ${o}(int row, int col, int depth) {
float texR = dot(vec2(row, col), vec2(${e[1]}, 1));
float texC = float(depth);
vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${m}.0, ${p}.0);
return sampleTexture(${n}, uv);
}
`;let d=Dc(n);return t?`
float ${o}(int row, int col, int depth) {
// Explicitly use integer operations as dot() only works on floats.
int stride0 = ${n}Shape[1] * ${n}Shape[2];
int stride1 = ${n}Shape[2];
int index = row * ${s} + col * ${i} + depth + ${d};
vec2 uv = uvFromFlat(${n}TexShape[0], ${n}TexShape[1], index);
return sampleTexture(${n}, uv);
}
`:`
float ${o}(int row, int col, int depth) {
// Explicitly use integer operations as dot() only works on floats.
int index = row * ${s} + col * ${i} + depth + ${d};
vec2 uv = uvFromFlat(${p}, ${m}, index);
return sampleTexture(${n}, uv);
}
`}function jQ(r,t){let e=r.name,n="get"+e.charAt(0).toUpperCase()+e.slice(1),o=He();if(t)return`
vec4 ${n}(int b2, int b, int row, int col) {
int valuesPerRow = int(ceil(float(${e}Shape[3]) / 2.0));
int texelsInBatch = valuesPerRow * int(ceil(float(${e}Shape[2]) / 2.0));
int index = b * texelsInBatch + (row / 2) * valuesPerRow + (col / 2);
texelsInBatch *= ${e}Shape[1];
index = b2 * texelsInBatch + index;
ivec2 packedTexShape = ivec2(ceil(float(${e}TexShape[0]) / 2.0), ceil(float(${e}TexShape[1]) / 2.0));
int texR = index / packedTexShape[1];
int texC = index - texR * packedTexShape[1];
vec2 uv = (vec2(texC, texR) + halfCR) / vec2(packedTexShape[1], packedTexShape[0]); return ${o.texture2D}(${e}, uv);
}
`;let s=r.shapeInfo.logicalShape,i=s.length,a=r.shapeInfo.texShape,u=[Math.ceil(a[0]/2),Math.ceil(a[1]/2)],l=u[0],c=u[1],p=Math.ceil(s[i-1]/2),m=p*Math.ceil(s[i-2]/2),f="int b, int row, int col",d=`b * ${m} + (row / 2) * ${p} + (col / 2)`;for(let h=2;h<i-1;h++)f=`int b${h}, `+f,m*=s[i-h-1],d=`b${h} * ${m} + `+d;return`
vec4 ${n}(${f}) {
int index = ${d};
int texR = index / ${c};
int texC = index - texR * ${c};
vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${c}, ${l});
return ${o.texture2D}(${e}, uv);
}
`}function XQ(r,t){let e=r.shapeInfo.logicalShape,n=r.name,o="get"+n.charAt(0).toUpperCase()+n.slice(1),s=e[3],i=e[2]*s,a=e[1]*i,{newShape:u,keptDims:l}=x.squeezeShape(e);if(u.length<e.length){let b=Xm(r,u),w=["row","col","depth","depth2"];return`
${Km(b,t)}
float ${o}(int row, int col, int depth, int depth2) {
return ${o}(${Ym(w,l)});
}
`}if(r.shapeInfo.isUniform)return`
float ${o}(int row, int col, int depth, int depth2) {
int index = round(dot(vec4(row, col, depth, depth2),
vec4(${a}, ${i}, ${s}, 1)));
${jm(r)}
}
`;let c=r.shapeInfo.flatOffset,p=r.shapeInfo.texShape,m=p[0],f=p[1],d=`int stride2 = ${n}Shape[3];`,h=`int stride1 = ${n}Shape[2] * stride2;`,g=`int stride0 = ${n}Shape[1] * stride1;`;if(f===a&&c==null)return t?`
float ${o}(int row, int col, int depth, int depth2) {
${d}
${h}
float texR = float(row);
float texC =
dot(vec3(col, depth, depth2),
vec3(stride1, stride2, 1));
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${n}TexShape[1], ${n}TexShape[0]);
return sampleTexture(${n}, uv);
}
`:`
float ${o}(int row, int col, int depth, int depth2) {
float texR = float(row);
float texC =
dot(vec3(col, depth, depth2),
vec3(${i}, ${s}, 1));
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${f}.0, ${m}.0);
return sampleTexture(${n}, uv);
}
`;if(f===s&&c==null)return t?`
float ${o}(int row, int col, int depth, int depth2) {
float texR = dot(vec3(row, col, depth),
vec3(${n}Shape[1] * ${n}Shape[2], ${n}Shape[2], 1));
float texC = float(depth2);
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${n}TexShape[1], ${n}TexShape[0]);
return sampleTexture(${n}, uv);
}
`:`
float ${o}(int row, int col, int depth, int depth2) {
float texR = dot(vec3(row, col, depth),
vec3(${e[1]*e[2]}, ${e[2]}, 1));
float texC = float(depth2);
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${f}.0, ${m}.0);
return sampleTexture(${n}, uv);
}
`;let y=Dc(n);return t?`
float ${o}(int row, int col, int depth, int depth2) {
// Explicitly use integer operations as dot() only works on floats.
${d}
${h}
${g}
int index = row * stride0 + col * stride1 +
depth * stride2 + depth2;
vec2 uv = uvFromFlat(${n}TexShape[0], ${n}TexShape[1], index + ${y});
return sampleTexture(${n}, uv);
}
`:`
float ${o}(int row, int col, int depth, int depth2) {
// Explicitly use integer operations as dot() only works on floats.
int index = row * ${a} + col * ${i} +
depth * ${s} + depth2;
vec2 uv = uvFromFlat(${m}, ${f}, index + ${y});
return sampleTexture(${n}, uv);
}
`}function YQ(r){let t=r.shapeInfo.logicalShape,e=r.name,n="get"+e.charAt(0).toUpperCase()+e.slice(1),o=t[4],s=t[3]*o,i=t[2]*s,a=t[1]*i,{newShape:u,keptDims:l}=x.squeezeShape(t);if(u.length<t.length){let h=Xm(r,u),g=["row","col","depth","depth2","depth3"];return`
${Km(h)}
float ${n}(int row, int col, int depth, int depth2, int depth3) {
return ${n}(${Ym(g,l)});
}
`}if(r.shapeInfo.isUniform)return`
float ${n}(int row, int col, int depth, int depth2, int depth3) {
float index = dot(
vec4(row, col, depth, depth2),
vec4(${a}, ${i}, ${s}, ${o})) +
depth3;
${jm(r)}
}
`;let c=r.shapeInfo.flatOffset,p=r.shapeInfo.texShape,m=p[0],f=p[1];if(f===a&&c==null)return`
float ${n}(int row, int col, int depth, int depth2, int depth3) {
int texR = row;
float texC = dot(vec4(col, depth, depth2, depth3),
vec4(${i}, ${s}, ${o}, 1));
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${f}.0, ${m}.0);
return sampleTexture(${e}, uv);
}
`;if(f===o&&c==null)return`
float ${n}(int row, int col, int depth, int depth2, int depth3) {
float texR = dot(
vec4(row, col, depth, depth2),
vec4(${t[1]*t[2]*t[3]},
${t[2]*t[3]}, ${t[3]}, 1));
int texC = depth3;
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${f}.0, ${m}.0);
return sampleTexture(${e}, uv);
}
`;let d=Dc(e);return`
float ${n}(int row, int col, int depth, int depth2, int depth3) {
// Explicitly use integer operations as dot() only works on floats.
int index = row * ${a} + col * ${i} + depth * ${s} +
depth2 * ${o} + depth3 + ${d};
vec2 uv = uvFromFlat(${m}, ${f}, index);
return sampleTexture(${e}, uv);
}
`}function ZQ(r){let t=r.shapeInfo.logicalShape,e=r.name,n="get"+e.charAt(0).toUpperCase()+e.slice(1),{newShape:o,keptDims:s}=x.squeezeShape(t);if(o.length<t.length){let g=Xm(r,o),y=["row","col","depth","depth2","depth3","depth4"];return`
${Km(g)}
float ${n}(int row, int col, int depth,
int depth2, int depth3, int depth4) {
return ${n}(${Ym(y,s)});
}
`}let i=t[5],a=t[4]*i,u=t[3]*a,l=t[2]*u,c=t[1]*l;if(r.shapeInfo.isUniform)return`
float ${n}(int row, int col, int depth,
int depth2, int depth3, int depth4) {
int index = round(dot(
vec4(row, col, depth, depth2),
vec4(${c}, ${l}, ${u}, ${a})) +
dot(
vec2(depth3, depth4),
vec2(${i}, 1)));
${jm(r)}
}
`;let p=r.shapeInfo.flatOffset,m=r.shapeInfo.texShape,f=m[0],d=m[1];if(d===c&&p==null)return`
float ${n}(int row, int col, int depth,
int depth2, int depth3, int depth4) {
int texR = row;
float texC = dot(vec4(col, depth, depth2, depth3),
vec4(${l}, ${u}, ${a}, ${i})) +
float(depth4);
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${d}.0, ${f}.0);
return sampleTexture(${e}, uv);
}
`;if(d===i&&p==null)return`
float ${n}(int row, int col, int depth,
int depth2, int depth3, int depth4) {
float texR = dot(vec4(row, col, depth, depth2),
vec4(${t[1]*t[2]*t[3]*t[4]},
${t[2]*t[3]*t[4]},
${t[3]*t[4]},
${t[4]})) + float(depth3);
int texC = depth4;
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${d}.0, ${f}.0);
return sampleTexture(${e}, uv);
}
`;let h=Dc(e);return`
float ${n}(int row, int col, int depth,
int depth2, int depth3, int depth4) {
// Explicitly use integer operations as dot() only works on floats.
int index = row * ${c} + col * ${l} + depth * ${u} +
depth2 * ${a} + depth3 * ${i} + depth4 + ${h};
vec2 uv = uvFromFlat(${f}, ${d}, index);
return sampleTexture(${e}, uv);
}
`}function jm(r){let t=r.name,e=x.sizeFromShape(r.shapeInfo.logicalShape);return e<2?`return ${t};`:`
for (int i = 0; i < ${e}; i++) {
if (i == index) {
return ${t}[i];
}
}
`}function JQ(r,t){let e=r.name,n=e.charAt(0).toUpperCase()+e.slice(1),o="get"+n+"AtOutCoords",s=r.shapeInfo.logicalShape.length,i=t.logicalShape.length,a=DP(r.shapeInfo.logicalShape,t.logicalShape),u=Ht(i),l=i-s,c,p=["x","y","z","w","u","v"];s===0?c="":i<2&&a.length>=1?c="coords = 0;":c=a.map(b=>`coords.${p[b+l]} = 0;`).join(`
`);let m="";i<2&&s>0?m="coords":m=r.shapeInfo.logicalShape.map((b,w)=>`coords.${p[w+l]}`).join(", ");let f="return outputValue;",h=x.sizeFromShape(r.shapeInfo.logicalShape)===1,y=x.sizeFromShape(t.logicalShape)===1;if(s===1&&!h&&!y)f=`
return vec4(outputValue.xy, outputValue.xy);
`;else if(h&&!y)i===1?f=`
return vec4(outputValue.x, outputValue.x, 0., 0.);
`:f=`
return vec4(outputValue.x);
`;else if(a.length){let b=s-2,w=s-1;a.indexOf(b)>-1&&a.indexOf(w)>-1?f="return vec4(outputValue.x);":a.indexOf(b)>-1?f="return vec4(outputValue.x, outputValue.y, outputValue.x, outputValue.y);":a.indexOf(w)>-1&&(f="return vec4(outputValue.xx, outputValue.zz);")}return`
vec4 ${o}() {
${u} coords = getOutputCoords();
${c}
vec4 outputValue = get${n}(${m});
${f}
}
`}function QQ(r,t){let e=r.name,n=e.charAt(0).toUpperCase()+e.slice(1),o="get"+n+"AtOutCoords",s=t.texShape,i=r.shapeInfo.texShape,a=r.shapeInfo.logicalShape.length,u=t.logicalShape.length;if(!r.shapeInfo.isUniform&&a===u&&r.shapeInfo.flatOffset==null&&x.arraysEqual(i,s))return`
float ${o}() {
return sampleTexture(${e}, resultUV);
}
`;let l=Ht(u),c=DP(r.shapeInfo.logicalShape,t.logicalShape),p=u-a,m,f=["x","y","z","w","u","v"];a===0?m="":u<2&&c.length>=1?m="coords = 0;":m=c.map(h=>`coords.${f[h+p]} = 0;`).join(`
`);let d="";return u<2&&a>0?d="coords":d=r.shapeInfo.logicalShape.map((h,g)=>`coords.${f[g+p]}`).join(", "),`
float ${o}() {
${l} coords = getOutputCoords();
${m}
return get${n}(${d});
}
`}function Ht(r){if(r<=1)return"int";if(r===2)return"ivec2";if(r===3)return"ivec3";if(r===4)return"ivec4";if(r===5)return"ivec5";if(r===6)return"ivec6";throw Error(`GPU for rank ${r} is not yet supported`)}function mb(r,t,e){let{newShape:n,keptDims:o}=x.squeezeShape(t),s=t.length,i=r&&s===3&&t[0]===1,a=i?t.slice(1):n,u=!r&&s>1&&!x.arraysEqual(t,e)&&n.length<s||i;return{useSqueezeShape:u,uniformShape:u?a:t,keptDims:o}}function Xm(r,t){let e=JSON.parse(JSON.stringify(r));return e.shapeInfo.logicalShape=t,e}function Ym(r,t){return t.map(e=>r[e]).join(", ")}function PP(r,t,e,n){let o=e.map((v,I)=>{let E={logicalShape:v.shape,texShape:v.isUniform?null:v.texData.texShape,isUniform:v.isUniform,isPacked:v.isUniform?!1:v.texData.isPacked,flatOffset:null};return v.texData!=null&&v.texData.slice!=null&&v.texData.slice.flatOffset>0&&(E.flatOffset=v.texData.slice.flatOffset),{name:t.variableNames[I],shapeInfo:E}}),s=o.map(v=>v.shapeInfo),i={logicalShape:n.shape,texShape:n.texData.texShape,isUniform:!1,isPacked:n.texData.isPacked,flatOffset:null},a=$P(o,i,t),u=zS(r.gl,a),l=r.createProgram(u),c=null,p=r.getUniformLocation(l,"NAN",!1);G().getNumber("WEBGL_VERSION")===1&&(c=r.getUniformLocation(l,"INFINITY",!1));let m=!1,f={},d={},h={};for(let v=0;v<t.variableNames.length;v++){let I=t.variableNames[v];f[I]=r.getUniformLocation(l,I,m),f[`offset${I}`]=r.getUniformLocation(l,`offset${I}`,m),t.enableShapeUniforms&&(d[`${I}Shape`]=r.getUniformLocation(l,`${I}Shape`,m),h[`${I}TexShape`]=r.getUniformLocation(l,`${I}TexShape`,m))}let g,y,b;t.enableShapeUniforms&&(g=r.getUniformLocation(l,"outShape",m),b=r.getUniformLocation(l,"outShapeStrides",m),y=r.getUniformLocation(l,"outTexShape",m));let w=[];return t.customUniforms&&t.customUniforms.forEach((v,I)=>{w[I]=r.getUniformLocation(l,v.name,m)}),{program:t,fragmentShader:u,source:a,webGLProgram:l,uniformLocations:f,customUniformLocations:w,inShapeInfos:s,outShapeInfo:i,infLoc:c,nanLoc:p,inShapesLocations:d,inTexShapesLocations:h,outShapeLocation:g,outShapeStridesLocation:b,outTexShapeLocation:y}}function OP(r,t){if(r.length!==t.length)throw Error(`Binary was compiled with ${r.length} inputs, but was executed with ${t.length} inputs`);r.forEach((e,n)=>{let o=e.logicalShape,s=t[n],i=s.shape;if(!x.arraysEqual(o,i))throw Error(`Binary was compiled with different shapes than the current args. Shapes ${o} and ${i} must match`);if(e.isUniform&&s.isUniform)return;let a=e.texShape,u=s.isUniform?null:s.texData.texShape;if(!x.arraysEqual(a,u))throw Error(`Binary was compiled with different texture shapes than the current args. Shape ${a} and ${u} must match`)})}function MP(r,t,e,n,o){t.program.enableShapeUniforms||(OP(t.inShapeInfos,e),OP([t.outShapeInfo],[n]));let s=n.texData.texture,i=n.texData.texShape;n.texData.isPacked?r.setOutputPackedMatrixTexture(s.texture,i[0],i[1]):r.setOutputMatrixTexture(s.texture,i[0],i[1]),r.setProgram(t.webGLProgram),G().getNumber("WEBGL_VERSION")===1&&t.infLoc!==null&&r.gl.uniform1f(t.infLoc,1/0),t.nanLoc!==null&&r.gl.uniform1f(t.nanLoc,NaN),e.forEach((u,l)=>{let c=t.program.variableNames[l],p=t.uniformLocations[c],m=t.uniformLocations[`offset${c}`],f=t.inShapesLocations[`${c}Shape`],d=t.inTexShapesLocations[`${c}TexShape`];if(f){let{uniformShape:h}=mb(t.program.packedInputs,u.shape,u.texData.texShape);switch(h.length){case 1:r.gl.uniform1iv(f,new Int32Array(h));break;case 2:r.gl.uniform2iv(f,new Int32Array(h));break;case 3:r.gl.uniform3iv(f,new Int32Array(h));break;case 4:r.gl.uniform4iv(f,new Int32Array(h));break;default:break}}if(d&&r.gl.uniform2i(d,u.texData.texShape[0],u.texData.texShape[1]),p!=null){if(u.isUniform){if(x.sizeFromShape(u.shape)<2)r.gl.uniform1f(p,u.uniformValues[0]);else{let h=u.uniformValues;h instanceof Float32Array||(h=new Float32Array(h)),r.gl.uniform1fv(p,h)}return}u.texData.slice!=null&&m!=null&&r.gl.uniform1i(m,u.texData.slice.flatOffset),r.setInputMatrixTexture(u.texData.texture.texture,p,l)}});let a=t.outShapeLocation;if(a)switch(n.shape.length){case 1:r.gl.uniform1iv(a,new Int32Array(n.shape));break;case 2:r.gl.uniform2iv(a,new Int32Array(n.shape));break;case 3:r.gl.uniform3iv(a,new Int32Array(n.shape));break;case 4:r.gl.uniform4iv(a,new Int32Array(n.shape));break;default:break}if(t.outShapeStridesLocation){let u=x.computeStrides(n.shape);switch(n.shape.length){case 2:r.gl.uniform1iv(t.outShapeStridesLocation,new Int32Array(u));break;case 3:r.gl.uniform2iv(t.outShapeStridesLocation,new Int32Array(u));break;case 4:r.gl.uniform3iv(t.outShapeStridesLocation,new Int32Array(u));break;default:break}}t.outTexShapeLocation&&r.gl.uniform2i(t.outTexShapeLocation,n.texData.texShape[0],n.texData.texShape[1]),t.program.customUniforms&&o&&t.program.customUniforms.forEach((u,l)=>{let c=t.customUniformLocations[l],p=o[l];if(u.type==="float")r.gl.uniform1fv(c,p);else if(u.type==="vec2")r.gl.uniform2fv(c,p);else if(u.type==="vec3")r.gl.uniform3fv(c,p);else if(u.type==="vec4")r.gl.uniform4fv(c,p);else if(u.type==="int")r.gl.uniform1iv(c,p);else if(u.type==="ivec2")r.gl.uniform2iv(c,p);else if(u.type==="ivec3")r.gl.uniform3iv(c,p);else if(u.type==="ivec4")r.gl.uniform4iv(c,p);else throw Error(`uniform type ${u.type} is not supported yet.`)}),r.executeProgram()}function LP(r,t,e){let n="";t.concat(e).forEach(i=>{let a=i.texData!=null&&i.texData.slice!=null&&i.texData.slice.flatOffset>0;if(r.enableShapeUniforms&&!i.isUniform){let u=i.texData.texShape,{useSqueezeShape:l,uniformShape:c,keptDims:p}=mb(r.packedInputs,i.shape,u),m="",f="",d="";if(c.length===1&&r.packedInputs){let I=[Math.ceil(u[0]/2),Math.ceil(u[1]/2)];m=`${I[0]>1}_${I[1]>1}`}else if(c.length===2&&!r.packedInputs)f=`${c[0]>1}_${c[1]>1}`;else if(c.length>2&&!r.packedInputs){let I=x.computeStrides(c);d=`${I[0]===u[1]}_${I[I.length-1]===u[1]}`}let h=i.shape.length,g=c.length===2&&x.arraysEqual(i.shape,u),y=x.sizeFromShape(i.shape)===1,b=k.getBroadcastDims(i.shape,e.shape),w=!r.packedInputs&&h===e.shape.length&&x.arraysEqual(u,e.texData.texShape),v=r.packedInputs||c.length>2?"":`${u[0]>1}_${u[1]>1}`;n+=`${h}_${w}_${l?p:""}_${c.length}_${y}_${b}_${g}_${m}_${f}_${d}_${v}_${a}`}else{let u=i.isUniform?"uniform":i.texData.texShape;n+=`${i.shape}_${u}_${a}`}});let o=r.userCode,s=r.constructor.name;return s+="_"+n+"_"+o+`${G().getNumber("WEBGL_VERSION")}`,s}function De(r){return G().getBool("WEBGL_USE_SHAPES_UNIFORMS")&&r<=4}var nk=class{constructor(t){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outPackingScheme=nu.DENSE,this.customUniforms=[{name:"texShape",type:"ivec2"}];let e=He();this.outputShape=t,this.enableShapeUniforms=De(this.outputShape.length),this.userCode=`
ivec3 outCoordsFromFlatIndex(int index) {
${this.enableShapeUniforms?Ac(["r","c","d"],t):li(["r","c","d"],t)}
return ivec3(r, c, d);
}
void main() {
ivec2 resTexRC = ivec2(resultUV.yx * vec2(texShape[0], texShape[1]));
int index = 4 * (resTexRC.x * texShape[1] + resTexRC.y);
vec4 result = vec4(0.);
for (int i=0; i<4; i++) {
int flatIndex = index + i;
ivec3 rc = outCoordsFromFlatIndex(flatIndex);
result[i] = getA(rc.x, rc.y, rc.z);
}
${e.output} = result;
}
`}};var ok=class{constructor(t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outPackingScheme=nu.DENSE,this.customUniforms=[{name:"texShape",type:"ivec2"}];let e=He();this.outputShape=t,this.enableShapeUniforms=De(this.outputShape.length),this.userCode=`
ivec3 outCoordsFromFlatIndex(int index) {
${this.enableShapeUniforms?Ac(["r","c","d"],t):li(["r","c","d"],t)}
return ivec3(r, c, d);
}
void main() {
ivec2 resTexRC = ivec2(resultUV.yx * vec2(texShape[0], texShape[1]));
int index = 4 * (resTexRC.x * texShape[1] + resTexRC.y);
vec4 result = vec4(0.);
for (int i=0; i<4; i++) {
int flatIndex = index + i;
ivec3 rc = outCoordsFromFlatIndex(flatIndex);
result[i] = getChannel(getA(rc.x, rc.y, rc.z), vec2(rc.y, rc.z));
}
${e.output} = result;
}
`}};var sk=class{constructor(t){this.variableNames=["A"],this.outTexUsage=Ur.DOWNLOAD;let e=He();this.outputShape=t,this.userCode=`
${pb}
void main() {
float x = getAAtOutCoords();
${e.output} = encode_float(x);
}
`}};var ik=class{constructor(t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outTexUsage=Ur.DOWNLOAD;let e=He();this.outputShape=t,this.userCode=`
${pb}
void main() {
ivec3 coords = getOutputCoords();
float x = getChannel(getAAtOutCoords(), vec2(coords.y, coords.z));
${e.output} = encode_float(x);
}
`}};var ak=class{constructor(t,e=!1){this.variableNames=["A"],this.customUniforms=[{name:"texShape",type:"ivec2"}];let n=He();this.outputShape=t,this.enableShapeUniforms=De(this.outputShape.length);let o="result";e&&(o="floor(result * 255. + 0.5)"),this.userCode=`
${this.enableShapeUniforms?Hm():Um(t)}
void main() {
ivec3 coords = getOutputCoords();
int flatIndex = getFlatIndex(coords);
int offset = imod(flatIndex, 4);
flatIndex = idiv(flatIndex, 4, 1.);
int r = flatIndex / texShape[1];
int c = imod(flatIndex, texShape[1]);
vec2 uv = (vec2(c, r) + halfCR) / vec2(texShape[1], texShape[0]);
vec4 values = ${n.texture2D}(A, uv);
float result;
if(offset == 0) {
result = values[0];
} else if(offset == 1) {
result = values[1];
} else if(offset == 2) {
result = values[2];
} else {
result = values[3];
}
${n.output} = vec4(${o}, 0., 0., 0.);
}
`}};var lk=class{constructor(t,e=!1){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.customUniforms=[{name:"texShape",type:"ivec2"}];let n=He();this.outputShape=t,this.enableShapeUniforms=De(this.outputShape.length);let o="",s="result";e&&(s="floor(result * 255. + 0.5)");for(let i=0;i<=1;i++)for(let a=0;a<=1;a++){let u=i*2+a;o+=`
localCoords = coords;
if(localCoords[2] + ${a} < ${this.enableShapeUniforms?"outShape[2]":`${t[2]}`}) {
localCoords[2] += ${a};
if (localCoords[1] + ${i} < ${this.enableShapeUniforms?"outShape[1]":`${t[1]}`}) {
localCoords[1] += ${i};
flatIndex = getFlatIndex(localCoords);
offset = imod(flatIndex, 4);
flatIndex = idiv(flatIndex, 4, 1.);
int r = flatIndex / texShape[1];
int c = imod(flatIndex, texShape[1]);
vec2 uv = (vec2(c, r) + halfCR) / vec2(texShape[1], texShape[0]);
values = ${n.texture2D}(A, uv);
if (offset == 0) {
result[${u}] = values[0];
} else if (offset == 1) {
result[${u}] = values[1];
} else if (offset == 2) {
result[${u}] = values[2];
} else {
result[${u}] = values[3];
}
}
}
`}this.userCode=`
${this.enableShapeUniforms?Hm():Um(t)}
void main() {
ivec3 coords = getOutputCoords();
vec4 result = vec4(0.);
int flatIndex, r, c, offset;
ivec3 localCoords;
vec2 uv;
vec4 values;
${o}
${n.output} = ${s};
}
`}};var kk={};Xt(kk,{bindVertexProgramAttributeStreams:()=>xk,createBufferFromOutputTexture:()=>wk,createFloat16MatrixTexture:()=>fk,createFloat16PackedMatrixTexture:()=>gk,createFloat32MatrixTexture:()=>mk,createIndexBuffer:()=>pk,createPackedMatrixTexture:()=>hk,createUnsignedBytesMatrixTexture:()=>dk,createVertexBuffer:()=>ck,createVertexShader:()=>uk,downloadByteEncodedFloatMatrixFromOutputTexture:()=>Ck,downloadFloat32MatrixFromBuffer:()=>vk,downloadMatrixFromPackedOutputTexture:()=>Sk,downloadPackedMatrixFromBuffer:()=>Ik,getInternalFormatForFloat16MatrixTexture:()=>db,getInternalFormatForFloat16PackedMatrixTexture:()=>xb,getInternalFormatForFloat32MatrixTexture:()=>fb,getInternalFormatForPackedMatrixTexture:()=>gb,getInternalFormatForUnsignedBytesMatrixTexture:()=>hb,uploadDenseMatrixToTexture:()=>yk,uploadPixelDataToTexture:()=>bk});function uk(r){let t=He(),e=`${t.version}
precision highp float;
${t.attribute} vec3 clipSpacePos;
${t.attribute} vec2 uv;
${t.varyingVs} vec2 resultUV;
void main() {
gl_Position = vec4(clipSpacePos, 1);
resultUV = uv;
}`;return LS(r,e)}function ck(r){let t=new Float32Array([-1,1,0,0,1,-1,-1,0,0,0,1,1,0,1,1,1,-1,0,1,0]);return GS(r,t)}function pk(r){let t=new Uint16Array([0,1,2,2,1,3]);return WS(r,t)}function sg(r,t,e,n,o,s){HS(t,e);let i=US(r),a=r.TEXTURE_2D;return vt(r,()=>r.bindTexture(a,i)),vt(r,()=>r.texParameteri(a,r.TEXTURE_WRAP_S,r.CLAMP_TO_EDGE)),vt(r,()=>r.texParameteri(a,r.TEXTURE_WRAP_T,r.CLAMP_TO_EDGE)),vt(r,()=>r.texParameteri(a,r.TEXTURE_MIN_FILTER,r.NEAREST)),vt(r,()=>r.texParameteri(a,r.TEXTURE_MAG_FILTER,r.NEAREST)),G().getNumber("WEBGL_VERSION")===1?vt(r,()=>r.texImage2D(a,0,n,t,e,0,o,s,null)):vt(r,()=>r.texStorage2D(a,1,n,t,e)),vt(r,()=>r.bindTexture(r.TEXTURE_2D,null)),{texture:i,texShape:[e,t]}}function fb(r){return r.internalFormatFloat}function mk(r,t,e,n){let[o,s]=Ec(t,e);return sg(r,o,s,fb(n),n.textureFormatFloat,r.FLOAT)}function db(r){return r.internalFormatHalfFloat}function fk(r,t,e,n){let[o,s]=Ec(t,e);return sg(r,o,s,db(n),n.textureFormatFloat,n.textureTypeHalfFloat)}function hb(r){return r.downloadTextureFormat}function dk(r,t,e,n){let[o,s]=Ec(t,e);return sg(r,o,s,hb(n),r.RGBA,r.UNSIGNED_BYTE)}function gb(r){return r.internalFormatPackedFloat}function hk(r,t,e,n){let[o,s]=Ui(t,e);return sg(r,o,s,gb(n),r.RGBA,r.FLOAT)}function xb(r){return r.internalFormatPackedHalfFloat}function gk(r,t,e,n){let[o,s]=Ui(t,e);return sg(r,o,s,xb(n),r.RGBA,n.textureTypeHalfFloat)}function xk(r,t,e){return vt(r,()=>r.bindBuffer(r.ARRAY_BUFFER,e)),lb(r,t,"clipSpacePos",e,3,20,0)&&lb(r,t,"uv",e,2,20,12)}function yk(r,t,e,n,o,s){vt(r,()=>r.bindTexture(r.TEXTURE_2D,t));let i,a,u;o instanceof Uint8Array?(i=new Uint8Array(e*n*4),a=r.UNSIGNED_BYTE,u=r.RGBA):(i=new Float32Array(e*n*4),a=r.FLOAT,u=s.internalFormatPackedFloat),i.set(o),G().getNumber("WEBGL_VERSION")===2?vt(r,()=>r.texSubImage2D(r.TEXTURE_2D,0,0,0,e,n,r.RGBA,a,i)):vt(r,()=>r.texImage2D(r.TEXTURE_2D,0,u,e,n,0,r.RGBA,a,i)),vt(r,()=>r.bindTexture(r.TEXTURE_2D,null))}function bk(r,t,e){vt(r,()=>r.bindTexture(r.TEXTURE_2D,t)),e.data instanceof Uint8Array?G().getNumber("WEBGL_VERSION")===2?vt(r,()=>r.texSubImage2D(r.TEXTURE_2D,0,0,0,e.width,e.height,r.RGBA,r.UNSIGNED_BYTE,e.data)):vt(r,()=>r.texImage2D(r.TEXTURE_2D,0,r.RGBA,e.width,e.height,0,r.RGBA,r.UNSIGNED_BYTE,e.data)):G().getNumber("WEBGL_VERSION")===2?vt(r,()=>r.texSubImage2D(r.TEXTURE_2D,0,0,0,r.RGBA,r.UNSIGNED_BYTE,e)):vt(r,()=>r.texImage2D(r.TEXTURE_2D,0,r.RGBA,r.RGBA,r.UNSIGNED_BYTE,e)),vt(r,()=>r.bindTexture(r.TEXTURE_2D,null))}function wk(r,t,e,n){let o=r.createBuffer();vt(r,()=>r.bindBuffer(r.PIXEL_PACK_BUFFER,o));let a=4*4*t*e;return vt(r,()=>r.bufferData(r.PIXEL_PACK_BUFFER,a,r.STREAM_READ)),vt(r,()=>r.readPixels(0,0,e,t,r.RGBA,r.FLOAT,0)),vt(r,()=>r.bindBuffer(r.PIXEL_PACK_BUFFER,null)),o}function vk(r,t,e){let n=r,o=new Float32Array(e);return n.bindBuffer(n.PIXEL_PACK_BUFFER,t),n.getBufferSubData(n.PIXEL_PACK_BUFFER,0,o),n.bindBuffer(n.PIXEL_PACK_BUFFER,null),o}function Ck(r,t,e,n){let[o,s]=Ec(t,e),i=4,a=new Uint8Array(SP(t*e,i));return vt(r,()=>r.readPixels(0,0,o,s,n.downloadTextureFormat,r.UNSIGNED_BYTE,a)),new Float32Array(a.buffer)}function Ik(r,t,e,n,o,s,i,a){let u=r,l=new Float32Array(kP(s,i));return u.bindBuffer(u.PIXEL_PACK_BUFFER,t),u.getBufferSubData(u.PIXEL_PACK_BUFFER,0,l),u.bindBuffer(u.PIXEL_PACK_BUFFER,null),l}function Sk(r,t,e){let n=new Float32Array(t*e*4);return vt(r,()=>r.readPixels(0,0,e,t,r.RGBA,r.FLOAT,n)),n}var Zm=class{constructor(t){this.outputTexture=null,this.program=null,this.disposed=!1,this.vertexAttrsAreBound=!1,this.itemsToPoll=[];let e=G().getNumber("WEBGL_VERSION");t!=null?(this.gl=t,FS(e,t)):this.gl=Vn(e);let n="WEBGL_color_buffer_float",o="EXT_color_buffer_half_float";if(G().getNumber("WEBGL_VERSION")===1){let s="OES_texture_float",i="OES_texture_half_float";if(this.textureFloatExtension=Vm(this.gl,s),Gn(this.gl,i))this.textureHalfFloatExtension=Vm(this.gl,i);else if(G().get("WEBGL_FORCE_F16_TEXTURES"))throw new Error("GL context does not support half float textures, yet the environment flag WEBGL_FORCE_F16_TEXTURES is set to true.");if(this.colorBufferFloatExtension=this.gl.getExtension(n),Gn(this.gl,o))this.colorBufferHalfFloatExtension=Vm(this.gl,o);else if(G().get("WEBGL_FORCE_F16_TEXTURES"))throw new Error("GL context does not support color renderable half floats, yet the environment flag WEBGL_FORCE_F16_TEXTURES is set to true.")}else if(n="EXT_color_buffer_float",Gn(this.gl,n))this.colorBufferFloatExtension=this.gl.getExtension(n);else if(Gn(this.gl,o))this.colorBufferHalfFloatExtension=this.gl.getExtension(o);else throw new Error("GL context does not support color renderable floats");this.vertexBuffer=ck(this.gl),this.indexBuffer=pk(this.gl),this.framebuffer=qS(this.gl),this.textureConfig=eg(this.gl,this.textureHalfFloatExtension)}get debug(){return G().getBool("DEBUG")}dispose(){if(this.disposed)return;this.program!=null&&console.warn("Disposing a GPGPUContext that still has a bound WebGLProgram. This is probably a resource leak, delete the program with GPGPUContext.deleteProgram before disposing."),this.outputTexture!=null&&console.warn("Disposing a GPGPUContext that still has a bound output matrix texture. This is probably a resource leak, delete the output matrix texture with GPGPUContext.deleteMatrixTexture before disposing.");let t=this.gl;vt(t,()=>t.finish()),vt(t,()=>t.bindFramebuffer(t.FRAMEBUFFER,null)),vt(t,()=>t.deleteFramebuffer(this.framebuffer)),vt(t,()=>t.bindBuffer(t.ARRAY_BUFFER,null)),vt(t,()=>t.bindBuffer(t.ELEMENT_ARRAY_BUFFER,null)),vt(t,()=>t.deleteBuffer(this.indexBuffer)),this.disposed=!0}createFloat32MatrixTexture(t,e){return this.throwIfDisposed(),mk(this.gl,t,e,this.textureConfig)}createFloat16MatrixTexture(t,e){return this.throwIfDisposed(),fk(this.gl,t,e,this.textureConfig)}createUnsignedBytesMatrixTexture(t,e){return this.throwIfDisposed(),dk(this.gl,t,e,this.textureConfig)}uploadPixelDataToTexture(t,e){this.throwIfDisposed(),bk(this.gl,t,e)}uploadDenseMatrixToTexture(t,e,n,o){this.throwIfDisposed(),yk(this.gl,t,e,n,o,this.textureConfig)}createFloat16PackedMatrixTexture(t,e){return this.throwIfDisposed(),gk(this.gl,t,e,this.textureConfig)}createPackedMatrixTexture(t,e){return this.throwIfDisposed(),hk(this.gl,t,e,this.textureConfig)}deleteMatrixTexture(t){this.throwIfDisposed(),this.outputTexture===t&&(ub(this.gl,this.framebuffer),this.outputTexture=null),vt(this.gl,()=>this.gl.deleteTexture(t))}downloadByteEncodedFloatMatrixFromOutputTexture(t,e,n){return this.downloadMatrixDriver(t,()=>Ck(this.gl,e,n,this.textureConfig))}downloadPackedMatrixFromBuffer(t,e,n,o,s,i){return Ik(this.gl,t,e,n,o,s,i,this.textureConfig)}downloadFloat32MatrixFromBuffer(t,e){return vk(this.gl,t,e)}createBufferFromTexture(t,e,n){this.bindTextureToFrameBuffer(t);let o=wk(this.gl,e,n,this.textureConfig);return this.unbindTextureToFrameBuffer(),o}createAndWaitForFence(){let t=this.createFence(this.gl);return this.pollFence(t)}createFence(t){let e,n;if(G().getBool("WEBGL_FENCE_API_ENABLED")){let o=t,s=o.fenceSync(o.SYNC_GPU_COMMANDS_COMPLETE,0);t.flush(),n=()=>{let i=o.clientWaitSync(s,0,0);return i===o.ALREADY_SIGNALED||i===o.CONDITION_SATISFIED},e=s}else G().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")>0?(e=this.beginQuery(),this.endQuery(),n=()=>this.isQueryAvailable(e,G().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))):n=()=>!0;return{query:e,isFencePassed:n}}downloadMatrixFromPackedTexture(t,e,n){return this.downloadMatrixDriver(t,()=>Sk(this.gl,e,n))}createProgram(t){this.throwIfDisposed();let e=this.gl;this.vertexShader==null&&(this.vertexShader=uk(e));let n=BS(e);return vt(e,()=>e.attachShader(n,this.vertexShader)),vt(e,()=>e.attachShader(n,t)),VS(e,n),this.debug&&rg(e,n),this.vertexAttrsAreBound||(this.setProgram(n),this.vertexAttrsAreBound=xk(e,this.program,this.vertexBuffer)),n}deleteProgram(t){this.throwIfDisposed(),t===this.program&&(this.program=null),t!=null&&vt(this.gl,()=>this.gl.deleteProgram(t))}setProgram(t){this.throwIfDisposed(),this.program=t,this.program!=null&&this.debug&&rg(this.gl,this.program),vt(this.gl,()=>this.gl.useProgram(t))}getUniformLocation(t,e,n=!0){return this.throwIfDisposed(),n?KS(this.gl,t,e):jS(this.gl,t,e)}getAttributeLocation(t,e){return this.throwIfDisposed(),vt(this.gl,()=>this.gl.getAttribLocation(t,e))}getUniformLocationNoThrow(t,e){return this.throwIfDisposed(),this.gl.getUniformLocation(t,e)}setInputMatrixTexture(t,e,n){this.throwIfDisposed(),this.throwIfNoProgram(),XS(this.gl,t,e,n)}setOutputMatrixTexture(t,e,n){this.setOutputMatrixTextureDriver(t,n,e)}setOutputPackedMatrixTexture(t,e,n){this.throwIfDisposed();let[o,s]=Ui(e,n);this.setOutputMatrixTextureDriver(t,o,s)}setOutputMatrixWriteRegion(t,e,n,o){this.setOutputMatrixWriteRegionDriver(n,t,o,e)}setOutputPackedMatrixWriteRegion(t,e,n,o){throw new Error("setOutputPackedMatrixWriteRegion not implemented.")}debugValidate(){this.program!=null&&rg(this.gl,this.program),Gm(this.gl)}executeProgram(){this.throwIfDisposed(),this.throwIfNoProgram();let t=this.gl;this.debug&&this.debugValidate(),vt(t,()=>t.drawElements(t.TRIANGLES,6,t.UNSIGNED_SHORT,0))}blockUntilAllProgramsCompleted(){this.throwIfDisposed(),vt(this.gl,()=>this.gl.finish())}getQueryTimerExtension(){return this.disjointQueryTimerExtension==null&&(this.disjointQueryTimerExtension=Vm(this.gl,G().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")===2?"EXT_disjoint_timer_query_webgl2":"EXT_disjoint_timer_query")),this.disjointQueryTimerExtension}getQueryTimerExtensionWebGL2(){return this.getQueryTimerExtension()}getQueryTimerExtensionWebGL1(){return this.getQueryTimerExtension()}beginQuery(){if(G().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")===2){let n=this.gl,o=this.getQueryTimerExtensionWebGL2(),s=n.createQuery();return n.beginQuery(o.TIME_ELAPSED_EXT,s),s}let t=this.getQueryTimerExtensionWebGL1(),e=t.createQueryEXT();return t.beginQueryEXT(t.TIME_ELAPSED_EXT,e),e}endQuery(){if(G().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")===2){let e=this.gl,n=this.getQueryTimerExtensionWebGL2();e.endQuery(n.TIME_ELAPSED_EXT);return}let t=this.getQueryTimerExtensionWebGL1();t.endQueryEXT(t.TIME_ELAPSED_EXT)}async waitForQueryAndGetTime(t){return await x.repeatedTry(()=>this.disposed||this.isQueryAvailable(t,G().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))),this.getQueryTime(t,G().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))}getQueryTime(t,e){if(e===0)return null;if(e===2){let n=this.gl;return n.getQueryParameter(t,n.QUERY_RESULT)/1e6}else{let n=this.getQueryTimerExtensionWebGL1();return n.getQueryObjectEXT(t,n.QUERY_RESULT_EXT)/1e6}}isQueryAvailable(t,e){if(e===0)return!0;if(e===2){let n=this.gl,o=this.getQueryTimerExtensionWebGL2(),s=n.getQueryParameter(t,n.QUERY_RESULT_AVAILABLE);return this.disjoint==null&&(this.disjoint=this.gl.getParameter(o.GPU_DISJOINT_EXT)),s&&!this.disjoint}else{let n=this.getQueryTimerExtensionWebGL1(),o=n.getQueryObjectEXT(t,n.QUERY_RESULT_AVAILABLE_EXT);return this.disjoint==null&&(this.disjoint=this.gl.getParameter(n.GPU_DISJOINT_EXT)),o&&!this.disjoint}}pollFence(t){return new Promise(e=>{this.addItemToPoll(()=>t.isFencePassed(),()=>e())})}pollItems(){let t=rtt(this.itemsToPoll.map(e=>e.isDoneFn));for(let e=0;e<=t;++e){let{resolveFn:n}=this.itemsToPoll[e];n()}this.itemsToPoll=this.itemsToPoll.slice(t+1)}addItemToPoll(t,e){this.itemsToPoll.push({isDoneFn:t,resolveFn:e}),!(this.itemsToPoll.length>1)&&x.repeatedTry(()=>(this.pollItems(),this.itemsToPoll.length===0))}bindTextureToFrameBuffer(t){this.throwIfDisposed(),ng(this.gl,t,this.framebuffer),this.debug&&Gm(this.gl)}unbindTextureToFrameBuffer(){this.outputTexture!=null?(ng(this.gl,this.outputTexture,this.framebuffer),this.debug&&Gm(this.gl)):ub(this.gl,this.framebuffer)}downloadMatrixDriver(t,e){this.bindTextureToFrameBuffer(t);let n=e();return this.unbindTextureToFrameBuffer(),n}setOutputMatrixTextureDriver(t,e,n){this.throwIfDisposed();let o=this.gl;ng(o,t,this.framebuffer),this.debug&&Gm(o),this.outputTexture=t,vt(o,()=>o.viewport(0,0,e,n)),vt(o,()=>o.scissor(0,0,e,n))}setOutputMatrixWriteRegionDriver(t,e,n,o){this.throwIfDisposed(),vt(this.gl,()=>this.gl.scissor(t,e,n,o))}throwIfDisposed(){if(this.disposed)throw new Error("Attempted to use disposed GPGPUContext.")}throwIfNoProgram(){if(this.program==null)throw new Error("No GPU program is currently set.")}};function rtt(r){let t=0;for(;t<r.length&&r[t]();++t);return t-1}var{addImpl:zP,bincountImpl:yb,bincountReduceImpl:BP,ceilImpl:VP,concatImpl:GP,equalImpl:WP,expImpl:UP,expm1Impl:HP,floorImpl:qP,gatherNdImpl:KP,gatherV2Impl:jP,greaterImpl:XP,greaterEqualImpl:YP,lessImpl:ZP,lessEqualImpl:JP,linSpaceImpl:QP,logImpl:tM,maxImpl:eM,maximumImpl:rM,minimumImpl:nM,multiplyImpl:oM,negImpl:sM,notEqualImpl:iM,prodImpl:aM,rangeImpl:lM,rsqrtImpl:uM,sigmoidImpl:cM,simpleAbsImpl:bb,sliceImpl:pM,sparseFillEmptyRowsImpl:mM,sparseReshapeImpl:fM,sparseSegmentReductionImpl:wb,sqrtImpl:dM,stridedSliceImpl:hM,stringNGramsImpl:gM,stringSplitImpl:xM,stringToHashBucketFastImpl:yM,subImpl:bM,tileImpl:wM,topKImpl:vM,transposeImpl:$c,uniqueImpl:CM}=Qy;function Nk(r,t){return["x","y","z","w","u","v"].slice(0,t).map(e=>`${r}.${e}`)}function tr(r,t){return t===1?[r]:Nk(r,t)}function IM(r,t){if(r===1)return"rc";let e="";for(let n=0;n<r;n++)e+=t[n],n<r-1&&(e+=",");return e}var Tk=class{constructor(t){if(this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outputShape=t,this.rank=t.length,this.enableShapeUniforms=De(this.outputShape.length),this.rank===0)this.userCode=`
void main() {
setOutput(vec4(getA(), 0., 0., 0.));
}
`;else{let e=tr("rc",this.rank),n=Ht(this.rank),o=this.getOutOfBoundsCondition(e),s=this.getSetup(e),i=this.getOutput(e);this.userCode=`
void main() {
${n} rc = getOutputCoords();
if(${o}) {
setOutput(vec4(0));
} else {
${s}
setOutput(vec4(${i}));
}
}
`}}getSourceCoordsArr(t){let e=[];for(let n=0;n<=1;n++)for(let o=0;o<=1;o++){let s=`${n===0?"r":"rp1"}, ${o===0?"c":"cp1"}`;for(let i=2;i<this.rank;i++)s=`${t[t.length-1-i]},`+s;e.push(s)}return e}getOutOfBoundsCondition(t){if(this.rank===1)return`rc > ${this.enableShapeUniforms?"outShape":this.outputShape[0]}`;let e="";for(let n=this.rank-2;n<this.rank;n++)e+=`${t[n]} >= ${this.enableShapeUniforms?`outShape[${n}]`:this.outputShape[n]}`,n<this.rank-1&&(e+="||");return e}getSetup(t){if(this.rank===1)return"";let e=t.slice(-2),n=this.enableShapeUniforms?`outShape[${this.rank} - 1]`:this.outputShape[this.rank-1],o=this.enableShapeUniforms?`outShape[${this.rank} - 2]`:this.outputShape[this.rank-2];return`
int r = ${e[0]};
int c = ${e[1]};
int rp1 = r + 1;
int cp1 = c + 1;
bool cEdge = cp1 >= ${n};
bool rEdge = rp1 >= ${o};
`}getOutput(t){let e=this.getSourceCoordsArr(t);return this.rank===1?`getA(rc), (rc + 1 >= ${this.enableShapeUniforms?"outShape":this.outputShape[0]} ? 0. : getA(rc + 1)), 0, 0`:`getA(${e[0]}),
cEdge ? 0. : getA(${e[1]}),
rEdge ? 0. : getA(${e[2]}),
rEdge || cEdge ? 0. : getA(${e[3]})`}};var ig=class{constructor(t,e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"inputShape",type:"ivec3"}],this.outputShape=t,this.enableShapeUniforms=De(this.outputShape.length);let n="";for(let o=0;o<4;o++){let s="thisRC = rc;";o%2===1&&(s+="thisRC.z += 1;"),o>1&&(s+="thisRC.y += 1;"),n+=`
${s}
${o>0?"if(thisRC.y < rows && thisRC.z < cols){":""}
int flatIndex = getFlatIndex(thisRC);
ivec3 inputRC = inputCoordsFromReshapedOutCoords(flatIndex);
vec2 inputRCInnerDims = vec2(float(inputRC.y),float(inputRC.z));
result[${o}] =
getChannel(getA(inputRC.x, inputRC.y, inputRC.z), inputRCInnerDims);
${o>0?"}":""}
`}this.userCode=`
${ntt(e,this.enableShapeUniforms)}
${this.enableShapeUniforms?Hm():Um(t)}
void main() {
ivec3 rc = getOutputCoords();
vec4 result = vec4(0.);
ivec3 thisRC;
int rows = ${this.enableShapeUniforms?"outShape[1]":t[1]};
int cols = ${this.enableShapeUniforms?"outShape[2]":t[2]};
${n}
setOutput(result);
}
`}};function ntt(r,t){return`
ivec3 inputCoordsFromReshapedOutCoords(int index) {
${t?AP(["r","c","d"],"inputShape"):li(["r","c","d"],r)}
return ivec3(r, c, d);
}
`}var _k=class{constructor(t){this.gpgpu=t,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0,this.freeTextures={},this.logEnabled=!1,this.usedTextures={}}acquireTexture(t,e,n){let o=kM(e,n),s=NM(t,o,n);s in this.freeTextures||(this.freeTextures[s]=[]),s in this.usedTextures||(this.usedTextures[s]=[]);let i=SM(t,o,this.gpgpu.gl,this.gpgpu.textureConfig,n);if(this.freeTextures[s].length>0){this.numFreeTextures--,this.numUsedTextures++,this._numBytesFree-=i,this.log();let u=this.freeTextures[s].shift();return this.usedTextures[s].push(u),u}let a;return o===Rr.PACKED_2X2_FLOAT32?a=this.gpgpu.createPackedMatrixTexture(t[0],t[1]):o===Rr.PACKED_2X2_FLOAT16?a=this.gpgpu.createFloat16PackedMatrixTexture(t[0],t[1]):o===Rr.UNPACKED_FLOAT32?a=this.gpgpu.createFloat32MatrixTexture(t[0],t[1]):o===Rr.UNPACKED_FLOAT16?a=this.gpgpu.createFloat16MatrixTexture(t[0],t[1]):o===Rr.PACKED_4X1_UNSIGNED_BYTE&&(a=this.gpgpu.createUnsignedBytesMatrixTexture(t[0],t[1])),this.usedTextures[s].push(a),this.numUsedTextures++,this._numBytesAllocated+=i,this.log(),a}releaseTexture(t,e,n,o){if(this.freeTextures==null)return;let s=kM(n,o),i=NM(e,s,o);i in this.freeTextures||(this.freeTextures[i]=[]);let a=SM(e,s,this.gpgpu.gl,this.gpgpu.textureConfig,o),u=G().get("WEBGL_DELETE_TEXTURE_THRESHOLD");u!==-1&&this._numBytesAllocated>u?(this.gpgpu.deleteMatrixTexture(t.texture),this._numBytesAllocated-=a):(this.freeTextures[i].push(t),this.numFreeTextures++,this._numBytesFree+=a),this.numUsedTextures--;let l=this.usedTextures[i],c=l.indexOf(t);if(c<0)throw new Error("Cannot release a texture that was never provided by this texture manager");l.splice(c,1),this.log()}log(){if(!this.logEnabled)return;let t=this.numFreeTextures+this.numUsedTextures;console.log("Free/Used",`${this.numFreeTextures} / ${this.numUsedTextures}`,`(${t})`);let e=this._numBytesFree/this._numBytesAllocated;console.log(`Bytes allocated: ${this._numBytesAllocated}`),console.log(`Bytes unused: ${this._numBytesFree} (${Math.round(100*e)}%)`)}get numBytesAllocated(){return this._numBytesAllocated}get numBytesFree(){return this._numBytesFree}getNumUsedTextures(){return this.numUsedTextures}getNumFreeTextures(){return this.numFreeTextures}dispose(){if(this.freeTextures!=null){for(let t in this.freeTextures)this.freeTextures[t].forEach(e=>{this.gpgpu.deleteMatrixTexture(e.texture)});for(let t in this.usedTextures)this.usedTextures[t].forEach(e=>{this.gpgpu.deleteMatrixTexture(e.texture)});this.freeTextures=null,this.usedTextures=null,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0}}};function ott(r,t){let e=r;if(t===e.R32F)return 4;if(t===e.R16F)return 2;if(t===e.RGBA32F)return 16;if(t===r.RGBA)return 16;if(t===e.RGBA16F)return 8;if(t===e.RGBA8)return 4;throw new Error(`Unknown internal format ${t}`)}function SM(r,t,e,n,o){let s=stt(t,n),i;if(o){let[u,l]=Ui(r[0],r[1]);i=u*l}else{let[u,l]=Ec(r[0],r[1]);i=u*l}let a=ott(e,s);return i*a}function stt(r,t){switch(r){case Rr.PACKED_2X2_FLOAT32:return gb(t);case Rr.PACKED_2X2_FLOAT16:return xb(t);case Rr.UNPACKED_FLOAT32:return fb(t);case Rr.UNPACKED_FLOAT16:return db(t);case Rr.PACKED_4X1_UNSIGNED_BYTE:return hb(t);default:throw new Error(`Unknown physical texture type ${r}`)}}function itt(r){return G().getBool("WEBGL_RENDER_FLOAT32_ENABLED")?r?Rr.PACKED_2X2_FLOAT32:Rr.UNPACKED_FLOAT32:r?Rr.PACKED_2X2_FLOAT16:Rr.UNPACKED_FLOAT16}function kM(r,t){if(r===Ur.UPLOAD)return Rr.PACKED_2X2_FLOAT32;if(r===Ur.RENDER||r==null)return itt(t);if(r===Ur.DOWNLOAD||r===Ur.PIXELS)return Rr.PACKED_4X1_UNSIGNED_BYTE;throw new Error(`Unknown logical texture type ${r}`)}function NM(r,t,e){return`${r[0]}_${r[1]}_${t}_${e}`}var wn=class{constructor(t,e){this.variableNames=["A"],this.outputShape=t,this.enableShapeUniforms=De(this.outputShape.length),this.userCode=`
float unaryOperation(float x) {
${e}
}
void main() {
float x = getAAtOutCoords();
float y = unaryOperation(x);
setOutput(y);
}
`}},dr="if (isnan(x)) return x;",TM="return x;",Ek="return abs(x);";var _M="return (x >= 0.0) ? x : (exp(x) - 1.0);",EM=dr+`
return (x < 0.0) ? 0.0 : x;
`,AM=dr+`
return (x < 0.0) ? 0.0 : min(6.0, x);
`,Rc="return x;",DM="return 1.0 / (1.0 + exp(-1.0 * x));";var RM="return x;",FM=`
vec4 result;
result.r = (x.r >= 0.0) ? x.r : (exp(x.r) - 1.0);
result.g = (x.g >= 0.0) ? x.g : (exp(x.g) - 1.0);
result.b = (x.b >= 0.0) ? x.b : (exp(x.b) - 1.0);
result.a = (x.a >= 0.0) ? x.a : (exp(x.a) - 1.0);
return result;
`,OM=`
vec4 result = x * vec4(greaterThanEqual(x, vec4(0.0)));
bvec4 isNaN = isnan(x);
result.r = isNaN.r ? x.r : result.r;
result.g = isNaN.g ? x.g : result.g;
result.b = isNaN.b ? x.b : result.b;
result.a = isNaN.a ? x.a : result.a;
return result;
`,PM=`
vec4 result = min(x, vec4(6.)) * vec4(greaterThanEqual(x, vec4(0.0)));
bvec4 isNaN = isnan(x);
result.r = isNaN.r ? x.r : result.r;
result.g = isNaN.g ? x.g : result.g;
result.b = isNaN.b ? x.b : result.b;
result.a = isNaN.a ? x.a : result.a;
return result;
`,MM="return 1.0 / (1.0 + exp(-1.0 * x));",$o=class{constructor(t,e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t,this.enableShapeUniforms=De(this.outputShape.length),this.userCode=`
vec4 unaryOperation(vec4 x) {
${e}
}
void main() {
vec4 x = getAAtOutCoords();
vec4 y = unaryOperation(x);
setOutput(y);
}
`}};var Ak=class{constructor(t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outputShape=t,this.enableShapeUniforms=De(this.outputShape.length);let e=t.length,n=tr("rc",e),o=Ht(e),s=IM(e,n),i=n.slice(-2),a=e<=1?"rc":`vec2(${i.join(",")})`;this.userCode=`
void main() {
${o} rc = getOutputCoords();
vec4 packedInput = getA(${s});
setOutput(getChannel(packedInput, ${a}));
}
`}};var ltt=Vr.whereImpl,utt=1e-7,ctt=1e-4,vb={};function ptt(r){return r in vb||(vb[r]={}),vb[r]}var mtt=G().getNumber("CPU_HANDOFF_SIZE_THRESHOLD"),ftt=600;function dtt(){return G().global.screen==null?1024:G().global.screen.height*G().global.screen.width*window.devicePixelRatio*ftt/1024/1024}var Fc=class extends pi{constructor(t){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,!G().getBool("HAS_WEBGL"))throw new Error("WebGL is not supported on this device");let e;if(t!=null){if(t instanceof Zm)e=t;else{let n=Vn(G().getNumber("WEBGL_VERSION"),t);e=new Zm(n)}this.binaryCache={},this.gpgpuCreatedLocally=!1}else{let n=Vn(G().getNumber("WEBGL_VERSION"));e=new Zm(n),this.binaryCache=ptt(G().getNumber("WEBGL_VERSION")),this.gpgpuCreatedLocally=!0}this.gpgpu=e,this.canvas=this.gpgpu.gl.canvas,this.textureManager=new _k(this.gpgpu),this.numMBBeforeWarning=dtt(),this.texData=new bl(this,po())}nextDataId(){return Fc.nextDataId++}numDataIds(){return this.texData.numDataIds()-this.pendingDeletes}write(t,e,n){if((G().getBool("WEBGL_CHECK_NUMERICAL_PROBLEMS")||G().getBool("DEBUG"))&&this.checkNumericalProblems(t),n==="complex64"&&t!=null)throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");let o={id:this.nextDataId()};return this.texData.set(o,{shape:e,dtype:n,values:t,usage:Ur.UPLOAD,refCount:1}),o}refCount(t){return this.texData.has(t)?this.texData.get(t).refCount:0}incRef(t){let e=this.texData.get(t);e.refCount++}decRef(t){if(this.texData.has(t)){let e=this.texData.get(t);e.refCount--}}move(t,e,n,o,s){if(G().getBool("DEBUG")&&this.checkNumericalProblems(e),o==="complex64")throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");this.texData.set(t,{shape:n,dtype:o,values:e,usage:Ur.UPLOAD,refCount:s})}disposeIntermediateTensorInfo(t){this.disposeData(t.dataId)}readSync(t){let e=this.texData.get(t),{values:n,dtype:o,complexTensorInfos:s,slice:i,shape:a,isPacked:u}=e;if(i!=null){let m;u?m=new $o(a,Rc):m=new wn(a,Rc);let f=this.runWebGLProgram(m,[{dataId:t,shape:a,dtype:o}],o),d=this.readSync(f.dataId);return this.disposeIntermediateTensorInfo(f),d}if(n!=null)return this.convertAndCacheOnCPU(t);if(o==="string")return n;let l=this.activeTimers!=null,c;l&&(c=x.now());let p;if(o==="complex64"){let m=this.readSync(s.real.dataId),f=this.readSync(s.imag.dataId);p=k.mergeRealAndImagArrays(m,f)}else p=this.getValuesFromTexture(t);return l&&(this.downloadWaitMs+=x.now()-c),this.convertAndCacheOnCPU(t,p)}async read(t){if(this.pendingRead.has(t)){let d=this.pendingRead.get(t);return new Promise(h=>d.push(h))}let e=this.texData.get(t),{values:n,shape:o,slice:s,dtype:i,complexTensorInfos:a,isPacked:u}=e;if(s!=null){let d;u?d=new $o(o,Rc):d=new wn(o,Rc);let h=this.runWebGLProgram(d,[{dataId:t,shape:o,dtype:i}],i),g=this.read(h.dataId);return this.disposeIntermediateTensorInfo(h),g}if(n!=null)return this.convertAndCacheOnCPU(t);if(G().getBool("DEBUG")&&!G().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")&&G().getNumber("WEBGL_VERSION")===2)throw new Error("tensor.data() with WEBGL_DOWNLOAD_FLOAT_ENABLED=false and WEBGL_VERSION=2 not yet supported.");let l=null,c;if(i!=="complex64"&&G().get("WEBGL_BUFFER_SUPPORTED")){c=this.decode(t);let d=this.texData.get(c.dataId);l=this.gpgpu.createBufferFromTexture(d.texture.texture,...tg(o))}this.pendingRead.set(t,[]),i!=="complex64"&&await this.gpgpu.createAndWaitForFence();let p;if(i==="complex64"){let d=await Promise.all([this.read(a.real.dataId),this.read(a.imag.dataId)]),h=d[0],g=d[1];p=k.mergeRealAndImagArrays(h,g)}else if(l==null)p=this.getValuesFromTexture(t);else{let d=x.sizeFromShape(o);p=this.gpgpu.downloadFloat32MatrixFromBuffer(l,d)}if(c!=null&&this.disposeIntermediateTensorInfo(c),l!=null){let d=this.gpgpu.gl;vt(d,()=>d.deleteBuffer(l))}let m=this.convertAndCacheOnCPU(t,p),f=this.pendingRead.get(t);return this.pendingRead.delete(t),f.forEach(d=>d(m)),this.pendingDisposal.has(t)&&(this.pendingDisposal.delete(t),this.disposeData(t)&&po().removeDataId(t,this),this.pendingDeletes--),m}readToGPU(t,e={}){let n=this.texData.get(t),{values:o,shape:s,slice:i,dtype:a,isPacked:u,texture:l}=n;if(a==="complex64")throw new Error("Does not support reading texture for complex64 dtype.");if(i!=null){let f;u?f=new $o(s,Rc):f=new wn(s,Rc);let d=this.runWebGLProgram(f,[{dataId:t,shape:s,dtype:a}],a),h=this.readToGPU(d,e);return this.disposeIntermediateTensorInfo(d),h}if(l==null)throw o!=null?new Error("Data is not on GPU but on CPU."):new Error("There is no data on GPU or CPU.");let c=this.decode(t,e.customTexShape),p=po().makeTensorFromDataId(c.dataId,c.shape,c.dtype),m=this.texData.get(c.dataId);return Object.assign({tensorRef:p},m.texture)}bufferSync(t){let e=this.readSync(t.dataId),n=e;if(t.dtype==="string")try{n=e.map(o=>x.decodeString(o))}catch(o){throw new Error("Failed to decode encoded string bytes into utf-8")}return It(t.shape,t.dtype,n)}checkNumericalProblems(t){if(t!=null)for(let e=0;e<t.length;e++){let n=t[e];if(!MS(n))throw G().getBool("WEBGL_RENDER_FLOAT32_CAPABLE")?Error(`The value ${n} cannot be represented with your current settings. Consider enabling float32 rendering: 'tf.env().set('WEBGL_RENDER_FLOAT32_ENABLED', true);'`):Error(`The value ${n} cannot be represented on this device.`)}}getValuesFromTexture(t){let{shape:e,dtype:n,isPacked:o}=this.texData.get(t),s=x.sizeFromShape(e);if(G().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")){let m=this.decode(t),f=this.texData.get(m.dataId),d=this.gpgpu.downloadMatrixFromPackedTexture(f.texture.texture,...tg(e)).subarray(0,s);return this.disposeIntermediateTensorInfo(m),d}let i=G().getBool("WEBGL_PACK")&&o===!0,a=i?og(e):e,u=i?new ik(a):new sk(a),l=this.runWebGLProgram(u,[{shape:a,dtype:n,dataId:t}],"float32"),c=this.texData.get(l.dataId),p=this.gpgpu.downloadByteEncodedFloatMatrixFromOutputTexture(c.texture.texture,c.texShape[0],c.texShape[1]).subarray(0,s);return this.disposeIntermediateTensorInfo(l),p}timerAvailable(){return G().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0}time(t){let e=this.activeTimers,n=[],o=!1;this.programTimersStack==null?(this.programTimersStack=n,o=!0):this.activeTimers.push(n),this.activeTimers=n,t();let s=x.flatten(this.activeTimers.map(u=>u.query)).filter(u=>u!=null),i=x.flatten(this.activeTimers.map(u=>u.name)).filter(u=>u!=null);this.activeTimers=e,o&&(this.programTimersStack=null);let a={uploadWaitMs:this.uploadWaitMs,downloadWaitMs:this.downloadWaitMs,kernelMs:null,wallMs:null};return(async()=>{if(G().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0){let u=await Promise.all(s);a.kernelMs=x.sum(u),a.getExtraProfileInfo=()=>u.map((l,c)=>({name:i[c],ms:l})).map(l=>`${l.name}: ${l.ms}`).join(", ")}else a.kernelMs={error:"WebGL query timers are not supported in this environment."};return this.uploadWaitMs=0,this.downloadWaitMs=0,a})()}memory(){return{unreliable:!1,numBytesInGPU:this.numBytesInGPU,numBytesInGPUAllocated:this.textureManager.numBytesAllocated,numBytesInGPUFree:this.textureManager.numBytesFree}}startTimer(){return G().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?this.gpgpu.beginQuery():{startMs:x.now(),endMs:null}}endTimer(t){return G().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?(this.gpgpu.endQuery(),t):(t.endMs=x.now(),t)}async getQueryTime(t){if(G().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0)return this.gpgpu.waitForQueryAndGetTime(t);let e=t;return e.endMs-e.startMs}disposeData(t,e=!1){if(this.pendingDisposal.has(t))return!1;if(!this.texData.has(t))return!0;if(e?this.texData.get(t).refCount=0:this.texData.get(t).refCount--,!e&&this.texData.get(t).refCount>0)return!1;if(this.pendingRead.has(t))return this.pendingDisposal.add(t),this.pendingDeletes++,!1;this.releaseGPUData(t);let{complexTensorInfos:n}=this.texData.get(t);return n!=null&&(this.disposeData(n.real.dataId,e),this.disposeData(n.imag.dataId,e)),this.texData.delete(t),!0}releaseGPUData(t){let{texture:e,dtype:n,texShape:o,usage:s,isPacked:i,slice:a}=this.texData.get(t),u=a&&a.origDataId||t,l=this.dataRefCount.get(u);l>1?this.dataRefCount.set(u,l-1):(this.dataRefCount.delete(u),e!=null&&(this.numBytesInGPU-=this.computeBytes(o,n),this.textureManager.releaseTexture(e,o,s,i)));let c=this.texData.get(t);c.texture=null,c.texShape=null,c.isPacked=!1,c.slice=null}getTexture(t){return this.uploadToGPU(t),this.texData.get(t).texture.texture}getDataInfo(t){return this.texData.get(t)}shouldExecuteOnCPU(t,e=mtt){return G().getBool("WEBGL_CPU_FORWARD")&&t.every(n=>this.texData.get(n.dataId).texture==null&&x.sizeFromShape(n.shape)<e)}getGPGPUContext(){return this.gpgpu}where(t){k.warn("tf.where() in webgl locks the UI thread. Call tf.whereAsync() instead");let e=t.dataSync();return ltt(t.shape,e)}packedUnaryOp(t,e,n){let o=new $o(t.shape,e),s=this.compileAndRun(o,[t],n);return po().makeTensorFromDataId(s.dataId,s.shape,s.dtype)}abs(t){if(this.shouldExecuteOnCPU([t])&&t.dtype!=="complex64"){let o=bb(this.texData.get(t.dataId).values);return this.makeOutput(t.shape,t.dtype,o)}if(G().getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(t,Ek,t.dtype);let e=new wn(t.shape,Ek),n=this.compileAndRun(e,[t]);return po().makeTensorFromDataId(n.dataId,n.shape,n.dtype)}makeTensorInfo(t,e,n){let o;if(e==="string"&&n!=null&&n.length>0&&x.isString(n[0])){let s=n.map(i=>x.encodeString(i));o=this.write(s,t,e)}else o=this.write(n,t,e);return this.texData.get(o).usage=null,{dataId:o,shape:t,dtype:e}}makeOutput(t,e,n){let{dataId:o}=this.makeTensorInfo(t,e,n);return po().makeTensorFromDataId(o,t,e,this)}unpackTensor(t){let e=new Ak(t.shape);return this.runWebGLProgram(e,[t],t.dtype)}packTensor(t){let e=new Tk(t.shape),n=!0;return this.runWebGLProgram(e,[t],t.dtype,null,n)}packedReshape(t,e){let n=[cl(t.shape),...pl(t.shape)],o={dtype:t.dtype,shape:n,dataId:t.dataId},s=[cl(e),...pl(e)],i=new ig(s,n),a=!0,u=[n],l=this.runWebGLProgram(i,[o],t.dtype,u,a);return{dataId:l.dataId,shape:e,dtype:l.dtype}}decode(t,e){let n=this.texData.get(t),{isPacked:o,shape:s,dtype:i}=n;if(e!=null){let m=x.sizeFromShape(s),f=e[0]*e[1]*4;x.assert(m<=f,()=>"customTexShape is too small. Row * Column * 4 should be equal or larger than the size of the tensor data.")}let a=og(s),u;o?u=new ok(a):u=new nk(a);let l=!0,c=[e!=null?e:tg(a)],p=this.runWebGLProgram(u,[{shape:a,dtype:i,dataId:t}],i,c,l,e);return{dtype:i,shape:s,dataId:p.dataId}}runWebGLProgram(t,e,n,o,s=!1,i){let a=this.makeTensorInfo(t.outputShape,n),u=this.texData.get(a.dataId);if(t.packedOutput&&(u.isPacked=!0),t.outPackingScheme===nu.DENSE){let y=i!=null?i:tg(t.outputShape);u.texShape=y.map(b=>b*2)}if(t.outTexUsage!=null&&(u.usage=t.outTexUsage),x.sizeFromShape(a.shape)===0)return u.values=x.getTypedArrayFromDType(a.dtype,0),a;let l=[],c=e.map(y=>{if(y.dtype==="complex64")throw new Error("GPGPUProgram does not support complex64 input. For complex64 dtypes, please separate the program into real and imaginary parts.");let b=this.texData.get(y.dataId);if(b.texture==null){if(!t.packedInputs&&x.sizeFromShape(y.shape)<=G().getNumber("WEBGL_SIZE_UPLOAD_UNIFORM"))return{shape:y.shape,texData:null,isUniform:!0,uniformValues:b.values};t.packedInputs&&(b.isPacked=!0,b.shape=y.shape)}if(this.uploadToGPU(y.dataId),!!b.isPacked!=!!t.packedInputs)y=b.isPacked?this.unpackTensor(y):this.packTensor(y),l.push(y),b=this.texData.get(y.dataId);else if(b.isPacked&&!ou(b.shape,y.shape)){let w=y,v=y.shape;y.shape=b.shape,y=this.packedReshape(y,v),l.push(y),b=this.texData.get(y.dataId),w.shape=v}return{shape:y.shape,texData:b,isUniform:!1}});this.uploadToGPU(a.dataId);let p={shape:a.shape,texData:u,isUniform:!1},m=LP(t,c,p),f=this.getAndSaveBinary(m,()=>PP(this.gpgpu,t,c,p)),d=this.activeTimers!=null,h;d&&(h=this.startTimer()),MP(this.gpgpu,f,c,p,o),l.forEach(y=>this.disposeIntermediateTensorInfo(y)),d&&(h=this.endTimer(h),this.activeTimers.push({name:t.constructor.name,query:this.getQueryTime(h)}));let g=G().get("WEBGL_FLUSH_THRESHOLD");if(g>0){let y=x.now();y-this.lastGlFlushTime>g&&(this.gpgpu.gl.flush(),this.lastGlFlushTime=y)}if(!G().getBool("WEBGL_LAZILY_UNPACK")&&u.isPacked&&s===!1){let y=this.unpackTensor(a);return this.disposeIntermediateTensorInfo(a),y}return a}compileAndRun(t,e,n,o,s=!1){return n=n||e[0].dtype,this.runWebGLProgram(t,e,n,o,s)}getAndSaveBinary(t,e){return t in this.binaryCache||(this.binaryCache[t]=e()),this.binaryCache[t]}getTextureManager(){return this.textureManager}dispose(){this.disposed||(G().getBool("IS_TEST")||Object.keys(this.binaryCache).forEach(e=>{this.gpgpu.deleteProgram(this.binaryCache[e].webGLProgram),delete this.binaryCache[e]}),this.textureManager.dispose(),this.canvas!=null&&typeof HTMLCanvasElement!="undefined"&&this.canvas instanceof HTMLCanvasElement?this.canvas.remove():this.canvas=null,this.gpgpuCreatedLocally&&(this.gpgpu.program=null,this.gpgpu.dispose()),this.disposed=!0)}floatPrecision(){return this.floatPrecisionValue==null&&(this.floatPrecisionValue=B(()=>{if(!G().get("WEBGL_RENDER_FLOAT32_ENABLED")){let t=G().getBool("DEBUG");G().set("DEBUG",!1);let e=this.abs(pt(1e-8)).dataSync()[0];if(G().set("DEBUG",t),e>0)return 32}return 16})),this.floatPrecisionValue}epsilon(){return this.floatPrecision()===32?utt:ctt}uploadToGPU(t){let e=this.texData.get(t),{shape:n,dtype:o,values:s,texture:i,usage:a,isPacked:u}=e;if(i!=null)return;let l=this.activeTimers!=null,c;l&&(c=x.now());let p=e.texShape;if(p==null&&(p=YS(n,u),e.texShape=p),s!=null){let m=og(n),f,d=p[1],h=p[0],g=s instanceof Uint8Array||s instanceof Uint8ClampedArray;(u||!g)&&([d,h]=Ui(p[0],p[1])),u?f=new lk(m,g):f=new ak(m,g);let y=g?[h,d]:p,b=this.makeTensorInfo(y,o),w=this.texData.get(b.dataId);g?w.usage=Ur.PIXELS:w.usage=Ur.UPLOAD,w.texShape=y,this.gpgpu.uploadDenseMatrixToTexture(this.getTexture(b.dataId),d,h,s);let v=[[h,d]],I=!0,E=this.runWebGLProgram(f,[b],o,v,I),D=this.texData.get(E.dataId);e.texture=D.texture,e.texShape=D.texShape,e.isPacked=D.isPacked,e.usage=D.usage,this.disposeIntermediateTensorInfo(b),this.texData.delete(E.dataId),e.values=null,l&&(this.uploadWaitMs+=x.now()-c)}else{let m=this.acquireTexture(p,a,o,u);e.texture=m}}convertAndCacheOnCPU(t,e){let n=this.texData.get(t),{dtype:o}=n;return this.releaseGPUData(t),e!=null&&(n.values=htt(e,o)),n.values}acquireTexture(t,e,n,o){if(this.numBytesInGPU+=this.computeBytes(t,n),!this.warnedAboutMemory&&this.numBytesInGPU>this.numMBBeforeWarning*1024*1024){let s=(this.numBytesInGPU/1024/1024).toFixed(2);this.warnedAboutMemory=!0,console.warn(`High memory usage in GPU: ${s} MB, most likely due to a memory leak`)}return this.textureManager.acquireTexture(t,e,o)}computeBytes(t,e){return t[0]*t[1]*x.bytesPerElement(e)}};Fc.nextDataId=0;function htt(r,t){if(t==="float32"||t==="complex64")return r;if(t==="int32"||t==="bool"){let e=t==="int32"?new Int32Array(r.length):new Uint8Array(r.length);for(let n=0;n<e.length;++n)e[n]=Math.round(r[n]);return e}else throw new Error(`Unknown dtype ${t}`)}var LM="3.14.0";function zM(){G().set("WEBGL_FORCE_F16_TEXTURES",!0)}Ll.isBrowser()&&jp("webgl",()=>new Fc,2);var bSe={forceHalfFloat:zM};var Cb=`
if (isnan(a)) return a;
if (isnan(b)) return b;
`;var Ro=class{constructor(t,e,n){this.variableNames=["A","B"],this.outputShape=k.assertAndGetBroadcastShape(e,n),this.enableShapeUniforms=De(this.outputShape.length),this.userCode=`
float binaryOperation(float a, float b) {
${t}
}
void main() {
float a = getAAtOutCoords();
float b = getBAtOutCoords();
setOutput(binaryOperation(a, b));
}
`}};var su=`
result.r = isNaN.r > 0. ? NAN : result.r;
result.g = isNaN.g > 0. ? NAN : result.g;
result.b = isNaN.b > 0. ? NAN : result.b;
result.a = isNaN.a > 0. ? NAN : result.a;
`;var ui=class{constructor(t,e,n,o=!1){this.variableNames=["A","B"],this.supportsBroadcasting=!0,this.packedInputs=!0,this.packedOutput=!0,this.outputShape=k.assertAndGetBroadcastShape(e,n);let s=this.outputShape.length;this.enableShapeUniforms=De(s);let i="";if(o)if(s===0||x.sizeFromShape(this.outputShape)===1)i=`
result.y = 0.;
result.z = 0.;
result.w = 0.;
`;else if(i=`
${Ht(s)} coords = getOutputCoords();
`,s===1)this.enableShapeUniforms?i+=`
result.y = (coords + 1) >= outShape ? 0. : result.y;
result.z = 0.;
result.w = 0.;
`:i+=`
result.y = (coords + 1) >= ${this.outputShape[0]} ? 0. : result.y;
result.z = 0.;
result.w = 0.;
`;else{let u=tr("coords",s);this.enableShapeUniforms?i+=`
bool nextRowOutOfBounds =
(${u[s-2]} + 1) >= outShape[${s} - 2];
bool nextColOutOfBounds =
(${u[s-1]} + 1) >= outShape[${s} - 1];
result.y = nextColOutOfBounds ? 0. : result.y;
result.z = nextRowOutOfBounds ? 0. : result.z;
result.w = nextColOutOfBounds || nextRowOutOfBounds ? 0. : result.w;
`:i+=`
bool nextRowOutOfBounds =
(${u[s-2]} + 1) >= ${this.outputShape[s-2]};
bool nextColOutOfBounds =
(${u[s-1]} + 1) >= ${this.outputShape[s-1]};
result.y = nextColOutOfBounds ? 0. : result.y;
result.z = nextRowOutOfBounds ? 0. : result.z;
result.w = nextColOutOfBounds || nextRowOutOfBounds ? 0. : result.w;
`}this.userCode=`
vec4 binaryOperation(vec4 a, vec4 b) {
${t}
}
void main() {
vec4 a = getAAtOutCoords();
vec4 b = getBAtOutCoords();
vec4 result = binaryOperation(a, b);
${i}
setOutput(result);
}
`}};function er(r){let{inputs:t,backend:e}=r,{x:n}=t;return e.incRef(n.dataId),{dataId:n.dataId,shape:n.shape,dtype:n.dtype}}var BM={kernelName:so,backendName:"webgl",kernelFunc:er};function Dn(r){let{inputs:t,backend:e}=r,{real:n,imag:o}=t,s=e.makeTensorInfo(n.shape,"complex64"),i=e.texData.get(s.dataId),a=er({inputs:{x:n},backend:e}),u=er({inputs:{x:o},backend:e});return i.complexTensorInfos={real:a,imag:u},s}var VM={kernelName:pp,backendName:"webgl",kernelFunc:Dn};var Dk="return (a < 0.) ? b * a : a;",$k=`
vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));
return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);
`;function gtt(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{alpha:s}=n,i=e.makeTensorInfo([],"float32",x.createScalarValue(s,"float32")),a=G().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new ui($k,o.shape,i.shape):new Ro(Dk,o.shape,i.shape),u=e.runWebGLProgram(a,[o,i],"float32");return e.disposeIntermediateTensorInfo(i),u}var GM={kernelName:cs,backendName:"webgl",kernelFunc:gtt};var Rk="return (a < 0.) ? b * a : a;",Fk=`
vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));
return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);
`;function xtt(r){let{inputs:t,backend:e}=r,{x:n,alpha:o}=t,s=G().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new ui(Fk,n.shape,o.shape):new Ro(Rk,n.shape,o.shape);return e.runWebGLProgram(s,[n,o],"float32")}var WM={kernelName:Is,backendName:"webgl",kernelFunc:xtt};var Fo="if (isnan(x)) return x;",UM=`
if (isnan(a)) return a;
if (isnan(b)) return b;
`,HM=`
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 Ct({opSnippet:r,packedOpSnippet:t,cpuKernelImpl:e,dtype:n}){return({inputs:o,backend:s})=>{let{x:i}=o,a=s,u=n||i.dtype;if(a.shouldExecuteOnCPU([i])&&e!=null){let p=a.texData.get(i.dataId),m=e(p.values,u);return a.makeTensorInfo(i.shape,u,m)}let l=G().getBool("WEBGL_PACK_UNARY_OPERATIONS")&&t!=null,c;return l?c=new $o(i.shape,t):c=new wn(i.shape,r),a.runWebGLProgram(c,[i],u)}}function le({opSnippet:r,packedOpSnippet:t,checkOutOfBounds:e=!1,supportsComplex:n=!1,cpuKernelImpl:o,dtype:s}){return({inputs:i,backend:a})=>{let{a:u,b:l}=i,c=a;if(n&&u.dtype==="complex64"){let d=c.texData.get(u.dataId),h=c.texData.get(l.dataId),[g,y]=[[d.complexTensorInfos.real,h.complexTensorInfos.real],[d.complexTensorInfos.imag,h.complexTensorInfos.imag]].map(w=>{let[v,I]=w,E={dataId:v.dataId,dtype:v.dtype,shape:u.shape},D={dataId:I.dataId,dtype:I.dtype,shape:l.shape},$=new Ro(r,u.shape,l.shape);return c.runWebGLProgram($,[E,D],yr(v.dtype,I.dtype))}),b=Dn({inputs:{real:g,imag:y},backend:c});return c.disposeIntermediateTensorInfo(g),c.disposeIntermediateTensorInfo(y),b}let p=s||yr(u.dtype,l.dtype);if((u.dtype==="string"||l.dtype==="string"||c.shouldExecuteOnCPU([u,l]))&&o!=null){let d=c.texData.get(u.dataId).values,h=c.texData.get(l.dataId).values,g=u.dtype==="string"?k.fromUint8ToStringArray(d):d,y=u.dtype==="string"?k.fromUint8ToStringArray(h):h,[b,w]=o(u.shape,l.shape,g,y,p),v=c.makeTensorInfo(w,p),I=c.texData.get(v.dataId);return I.values=b,v}let m=G().getBool("WEBGL_PACK_BINARY_OPERATIONS")&&t!=null,f;return m?f=new ui(t,u.shape,l.shape,e):f=new Ro(r,u.shape,l.shape),c.runWebGLProgram(f,[u,l],p)}}function iu(r,t=!1){if(r==="linear")return t?RM:TM;if(r==="relu")return t?OM:EM;if(r==="elu")return t?FM:_M;if(r==="relu6")return t?PM:AM;if(r==="prelu")return t?Fk:Rk;if(r==="leakyrelu")return t?$k:Dk;if(r==="sigmoid")return t?MM:DM;throw new Error(`Activation ${r} has not been implemented for the WebGL backend.`)}var ag=class{constructor(t,e,n,o=!1,s=!1,i=!1,a=null,u=!1,l=!1){this.variableNames=["matrixA","matrixB"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=n,this.enableShapeUniforms=De(this.outputShape.length);let c=o?t[1]:t[2],p=Math.ceil(c/2),m=o?"i * 2, rc.y":"rc.y, i * 2",f=s?"rc.z, i * 2":"i * 2, rc.z",d=o?["a.xxyy","a.zzww"]:["a.xxzz","a.yyww"],h=s?["b.xzxz","b.ywyw"]:["b.xyxy","b.zwzw"],g="",y="";a&&(u?g=`vec4 activation(vec4 a) {
vec4 b = getPreluActivationWeightsAtOutCoords();
${a}
}`:l?g=`vec4 activation(vec4 a) {
vec4 b = getLeakyreluAlphaAtOutCoords();
${a}
}`:g=`vec4 activation(vec4 x) {
${a}
}`,y="result = activation(result);");let b=i?"result += getBiasAtOutCoords();":"";i&&this.variableNames.push("bias"),u&&this.variableNames.push("preluActivationWeights"),l&&this.variableNames.push("leakyreluAlpha");let w="rc.x",v="rc.x";t[0]<e[0]?w=`int(min(float(rc.x), ${t[0]-1}.))`:e[0]<t[0]&&(v=`int(min(float(rc.x), ${e[0]-1}.))`),this.userCode=`
${g}
// Don't use uniform for sharedDimensionPacked for performance.
const float sharedDimension = ${p}.0;
vec4 dot2x2ARowBCol(ivec3 rc) {
vec4 result = vec4(0);
for (int i = 0; i < ${p}; i++) {
int batchA = ${w};
int batchB = ${v};
vec4 a = getMatrixA(batchA, ${m});
vec4 b = getMatrixB(batchB, ${f});
// These swizzled products need to be separately added.
// See: https://github.com/tensorflow/tfjs/issues/1735
result += (${d[0]} * ${h[0]});
result += (${d[1]} * ${h[1]});
}
return result;
}
void main() {
ivec3 rc = getOutputCoords();
vec4 result = dot2x2ARowBCol(rc);
${b}
${y}
setOutput(result);
}
`}};var Ok={REAL:"return areal * breal - aimag * bimag;",IMAG:"return areal * bimag + aimag * breal;"},Ib=class{constructor(t,e,n){this.variableNames=["AReal","AImag","BReal","BImag"],this.outputShape=k.assertAndGetBroadcastShape(e,n),this.userCode=`
float binaryOpComplex(
float areal, float aimag, float breal, float bimag) {
${t}
}
void main() {
float areal = getARealAtOutCoords();
float aimag = getAImagAtOutCoords();
float breal = getBRealAtOutCoords();
float bimag = getBImagAtOutCoords();
setOutput(binaryOpComplex(areal, aimag, breal, bimag));
}
`}};var qM="return a * b;";function lg(r){let{inputs:t,backend:e}=r,{a:n,b:o}=t,s=k.upcastType(n.dtype,o.dtype);if(n.dtype==="complex64"){let a=e.texData.get(n.dataId),u=e.texData.get(o.dataId),l=new Ib(Ok.REAL,n.shape,o.shape),c=new Ib(Ok.IMAG,n.shape,o.shape),p=[{dataId:a.complexTensorInfos.real.dataId,dtype:a.complexTensorInfos.real.dtype,shape:n.shape},{dataId:a.complexTensorInfos.imag.dataId,dtype:a.complexTensorInfos.imag.dtype,shape:n.shape},{dataId:u.complexTensorInfos.real.dataId,dtype:u.complexTensorInfos.real.dtype,shape:o.shape},{dataId:u.complexTensorInfos.imag.dataId,dtype:u.complexTensorInfos.imag.dtype,shape:o.shape}],m=e.runWebGLProgram(l,p,"float32"),f=e.runWebGLProgram(c,p,"float32"),d=Dn({inputs:{real:m,imag:f},backend:e});return e.disposeIntermediateTensorInfo(m),e.disposeIntermediateTensorInfo(f),d}if(e.shouldExecuteOnCPU([n,o])){let a=e.texData.get(n.dataId),u=e.texData.get(o.dataId),[l,c]=oM(n.shape,o.shape,a.values,u.values,s),p=e.makeTensorInfo(c,s),m=e.texData.get(p.dataId);return m.values=l,p}let i;return G().getBool("WEBGL_PACK_BINARY_OPERATIONS")?i=new ui(qM,n.shape,o.shape):i=new Ro(qM,n.shape,o.shape),e.runWebGLProgram(i,[n,o],s)}var KM={kernelName:bs,backendName:"webgl",kernelFunc:lg};function jM(r,t,e){let n=[cl(r.shape),...pl(r.shape)],o={dtype:r.dtype,shape:n,dataId:r.dataId},s=[cl(t),...pl(t)],i=new ig(s,n),a=!0,u=[n],l=e.runWebGLProgram(i,[o],r.dtype,u,a);return{dataId:l.dataId,shape:t,dtype:l.dtype}}function ut(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{shape:s}=n,i=e,a=x.sizeFromShape(o.shape),u=x.inferFromImplicitShape(s,a),l=x.sizeFromShape(u);x.assert(a===l,()=>`The new shape (${u}) has ${l} elements and the old shape (${o.shape}) has ${a} elements. The new shape and old shape must have the same number of elements.`);let c=i.texData.get(o.dataId);return c.isPacked&&!ou(o.shape,u)&&!(c.texture!==null&&ou(c.shape,u))?jM(o,u,i):(i.incRef(o.dataId),{dataId:o.dataId,shape:u,dtype:o.dtype})}var XM={kernelName:Ci,backendName:"webgl",kernelFunc:ut};var Sb=class{constructor(t,e){this.variableNames=["x"];let{windowSize:n,batchSize:o,inSize:s,outSize:i}=t;this.outputShape=[o,i];let a=Math.floor(n/4)*4,u=n%4,l="sumValue += dot(values, ones);";if(e!=null){let p=1/e;l=`sumValue += dot(values * ${x.isInt(p)?p.toPrecision(2):p}, ones);`}let c="";s%n>0&&(c=`
if (inIdx < 0 || inIdx >= ${s}) {
return 0.0;
}
`),this.userCode=`
const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);
float getValue(int batch, int inIdx) {
${c}
return getX(batch, inIdx);
}
void main() {
ivec2 coords = getOutputCoords();
int batch = coords[0];
int outIdx = coords[1];
int inOffset = outIdx * ${n};
float sumValue = 0.0;
for (int i = 0; i < ${a}; i += 4) {
int inIdx = inOffset + i;
vec4 values = vec4(
getValue(batch, inIdx),
getValue(batch, inIdx + 1),
getValue(batch, inIdx + 2),
getValue(batch, inIdx + 3)
);
${l}
}
int inIdx = inOffset + ${a};
if (${u===1}) {
vec4 values = vec4(getValue(batch, inIdx), 0.0, 0.0, 0.0);
${l}
} else if (${u===2}) {
vec4 values = vec4(
getValue(batch, inIdx),
getValue(batch, inIdx + 1), 0.0, 0.0);
${l}
} else if (${u===3}) {
vec4 values = vec4(
getValue(batch, inIdx),
getValue(batch, inIdx + 1),
getValue(batch, inIdx + 2), 0.0);
${l}
}
setOutput(sumValue);
}
`}};var Pk=class{constructor(t,e){this.variableNames=["x"];let{windowSize:n,batchSize:o,inSize:s,outSize:i}=t;this.outputShape=[o,i];let a="0.0",u="";e==="prod"?a="1.0":e==="min"?(a="1.0 / 1e-20",u="min"):e==="max"&&(a="-1.0 / 1e-20",u="max");let l=`${e}(${e}(${e}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;e==="sum"?l="sumValue":e==="prod"?l="prodValue":e==="all"?l="allValue":e==="any"&&(l="anyValue");let c=Math.floor(n/4)*4,p=n%4,m=`
if (${e==="sum"}) {
sumValue += dot(values, ones);
} else if (${e==="prod"}) {
vec2 tmp = vec2(values[0], values[1]) * vec2(values[2], values[3]);
prodValue *= tmp[0] * tmp[1];
} else {
minMaxValue = ${u}(values, minMaxValue);
if (${e==="min"} || ${e==="max"}) {
minMaxValue = ${u}(values, minMaxValue);
bvec4 isNaN = isnan(values);
if (isNaN.r || isNaN.g || isNaN.b || isNaN.a) {
minMaxValue = vec4(NAN);
}
}
}
`,f="vec4";e==="all"?(a="1.0",m=`
bool reducedAllValue = all(values);
float floatedReducedAllValue = float(reducedAllValue);
allValue = float(allValue >= 1.0 && floatedReducedAllValue >= 1.0);
`,f="bvec4"):e==="any"&&(a="0.0",m=`
bool reducedAnyValue = any(values);
float floatedReducedAnyValue = float(reducedAnyValue);
anyValue = float(anyValue >= 1.0 || floatedReducedAnyValue >= 1.0);
`,f="bvec4");let d="";s%n>0&&(d=`
if (inIdx < 0 || inIdx >= ${s}) {
return initializationValue;
}
`),this.userCode=`
const float initializationValue = ${a};
const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);
float getValue(int batch, int inIdx) {
${d}
return getX(batch, inIdx);
}
void main() {
ivec2 coords = getOutputCoords();
int batch = coords[0];
int outIdx = coords[1];
int inOffset = outIdx * ${n};
vec4 minMaxValue = vec4(${a});
float prodValue = 1.0;
float sumValue = 0.0;
float allValue = 1.0;
float anyValue = 0.0;
for (int i = 0; i < ${c}; i += 4) {
int inIdx = inOffset + i;
${f} values = ${f}(
getValue(batch, inIdx),
getValue(batch, inIdx + 1),
getValue(batch, inIdx + 2),
getValue(batch, inIdx + 3)
);
${m}
}
int inIdx = inOffset + ${c};
if (${p===1}) {
${f} values = ${f}(
getValue(batch, inIdx),
initializationValue,
initializationValue,
initializationValue
);
${m}
} else if (${p===2}) {
${f} values = ${f}(
getValue(batch, inIdx),
getValue(batch, inIdx + 1),
initializationValue,
initializationValue
);
${m}
} else if (${p===3}) {
${f} values = ${f}(
getValue(batch, inIdx),
getValue(batch, inIdx + 1),
getValue(batch, inIdx + 2),
initializationValue
);
${m}
}
setOutput(${l});
}
`}};function btt(r){let t=[];for(;t.length===0||t[t.length-1].outSize!==1;){let e=t.length?t[t.length-1].outSize:r[1],n=k.computeOptimalWindowSize(e);t.push({inSize:e,windowSize:n,outSize:Math.ceil(e/n)})}return t}function Wn(r,t,e,n){let o=btt(r.shape),s=r;for(let i=0;i<o.length;i++){let{inSize:a,windowSize:u,outSize:l}=o[i],c,p;e==="mean"?c=i===0?new Sb({windowSize:u,inSize:a,batchSize:r.shape[0],outSize:l},a):new Sb({windowSize:u,inSize:a,batchSize:r.shape[0],outSize:l}):c=new Pk({windowSize:u,inSize:a,batchSize:r.shape[0],outSize:l},e),p=s,s=n.runWebGLProgram(c,[s],t),p.dataId!==r.dataId&&n.disposeIntermediateTensorInfo(p)}return s}var Mk=class{constructor(t,e){this.variableNames=["A"];let n=new Array(t.length);for(let i=0;i<n.length;i++)n[i]=t[e[i]];this.outputShape=n,this.rank=n.length;let o=Ht(this.rank),s=wtt(e);this.userCode=`
void main() {
${o} resRC = getOutputCoords();
setOutput(getA(${s}));
}
`}};function wtt(r){let t=r.length;if(t>6)throw Error(`Transpose for rank ${t} is not yet supported`);let e=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u","resRC.v"],n=new Array(t);for(let o=0;o<r.length;o++)n[r[o]]=e[o];return n.join()}var Lk=class{constructor(t,e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0;let n=new Array(t.length);for(let c=0;c<n.length;c++)n[c]=t[e[c]];if(this.outputShape=n,this.rank=n.length,this.rank>6)throw Error(`Packed transpose for rank ${this.rank} is not yet supported.`);let o=Ht(this.rank),s=Nk("rc",this.rank),i=new Array(this.rank);for(let c=0;c<e.length;c++)i[e[c]]=s[c];let a=`vec2(${i.slice(-2).join()})`,u=`++${s[this.rank-1]} < ${n[this.rank-1]}`,l=`getChannel(getA(${i.join()}), ${a})`;this.userCode=`
void main() {
${o} rc = getOutputCoords();
vec4 result = vec4(0.);
result[0] = ${l};
if(${u}) {
result[1] = ${l};
}
--${s[this.rank-1]};
if(++${s[this.rank-2]} < ${n[this.rank-2]}) {
result[2] = ${l};
if(${u}) {
result[3] = ${l};
}
}
setOutput(result);
}
`}};function au(r,t,e){let n=G().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new Lk(r.shape,t):new Mk(r.shape,t);return e.runWebGLProgram(n,[r],r.dtype)}function YM(r,t,e,n){let o=t,s=r.shape.length,i=x.parseAxisParam(o,r.shape),a=i,u=k.getAxesPermutation(a,s),l=u!=null,c=r;l&&(c=au(r,u,n),a=k.getInnerMostAxes(a.length,s)),k.assertAxesAreInnerMostDims("sum",a,s);let[p,m]=k.computeOutAndReduceShapes(c.shape,a),f=p;e&&(f=k.expandShapeToKeepDim(p,i));let d=x.sizeFromShape(m),g=x.sizeFromShape(r.shape)/d,y=ut({inputs:{x:c},attrs:{shape:[g,d]},backend:n}),b=Tu(r.dtype),w=Wn(y,b,"sum",n),v=ut({inputs:{x:w},attrs:{shape:f},backend:n});return n.disposeIntermediateTensorInfo(y),n.disposeIntermediateTensorInfo(w),l&&n.disposeIntermediateTensorInfo(c),v}function Oc(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{axis:s,keepDims:i}=n;return YM(o,s,i,e)}var ZM={kernelName:Rs,backendName:"webgl",kernelFunc:Oc};function Le(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{perm:s}=n,i=e,a=o.shape.length,u=new Array(a);for(let c=0;c<u.length;c++)u[c]=o.shape[s[c]];let l;if(i.shouldExecuteOnCPU([o])){let p=i.texData.get(o.dataId).values,m=$c(p,o.shape,o.dtype,s,u);l=i.makeTensorInfo(u,o.dtype);let f=i.texData.get(l.dataId);f.values=m}else l=au(o,s,i);return l}var JM={kernelName:zs,backendName:"webgl",kernelFunc:Le};var zk=1e3;function Pc({a:r,b:t,transposeA:e,transposeB:n,backend:o,bias:s=null,preluActivationWeights:i=null,leakyreluAlpha:a=0,activation:u=null}){let l=r.shape.length,c=t.shape.length,p=e?r.shape[l-2]:r.shape[l-1],m=n?t.shape[c-1]:t.shape[c-2],f=e?r.shape[l-1]:r.shape[l-2],d=n?t.shape[c-2]:t.shape[c-1],h=r.shape.slice(0,-2),g=t.shape.slice(0,-2),y=x.sizeFromShape(h),b=x.sizeFromShape(g),v=Mr.assertAndGetBroadcastShape(r.shape.slice(0,-2),t.shape.slice(0,-2)).concat([f,d]);x.assert(p===m,()=>`Error in matMul: inner shapes (${p}) and (${m}) of Tensors with shapes ${r.shape} and ${t.shape} and transposeA=${e} and transposeB=${n} must match.`);let I=e?[y,p,f]:[y,f,p],E=n?[b,d,m]:[b,m,d],D=ut({inputs:{x:r},backend:o,attrs:{shape:I}}),$=ut({inputs:{x:t},backend:o,attrs:{shape:E}}),R=[D,$],M=Math.max(y,b),W=e?D.shape[1]:D.shape[2],U=s!=null,q=i!=null,K=u==="leakyrelu",j=u!=null?iu(u,!0):null,Q=U||q||K||j!=null,rt;if((f===1||d===1)&&W>zk&&Q===!1){let nt=D,st=$;e&&(nt=Le({inputs:{x:D},backend:o,attrs:{perm:[0,2,1]}}),R.push(nt)),n&&(st=Le({inputs:{x:$},backend:o,attrs:{perm:[0,2,1]}}),R.push(st));let it=d!==1,ft=d===1,at=nt;it&&(at=ut({inputs:{x:nt},backend:o,attrs:{shape:[M,W,1]}}),R.push(at));let xt=d===1?2:1,dt=st;ft&&(dt=ut({inputs:{x:st},backend:o,attrs:{shape:[M,1,W]}}),R.push(dt));let bt=lg({inputs:{a:at,b:dt},backend:o});rt=Oc({inputs:{x:bt},backend:o,attrs:{axis:xt,keepDims:!0}}),R.push(bt)}else{let nt=yr(r.dtype,t.dtype),st=new ag(I,E,[M,f,d],e,n,U,j,q,K),it=[D,$];if(s!=null&&it.push(s),q&&it.push(i),K){let ft=o.makeTensorInfo([],"float32",x.createScalarValue(a,"float32"));it.push(ft),R.push(ft)}rt=o.runWebGLProgram(st,it,nt)}let X=ut({inputs:{x:rt},backend:o,attrs:{shape:v}});R.push(rt);for(let nt of R)o.disposeIntermediateTensorInfo(nt);return X}function vtt(r){let{inputs:t,backend:e,attrs:n}=r,{a:o,b:s,bias:i,preluActivationWeights:a}=t,{transposeA:u,transposeB:l,activation:c,leakyreluAlpha:p}=n;return Pc({a:o,b:s,transposeA:u,transposeB:l,backend:e,bias:i,preluActivationWeights:a,leakyreluAlpha:p,activation:c})}var QM={kernelName:Ei,backendName:"webgl",kernelFunc:vtt};var tL="return abs(x);";function Ctt(r){let{inputs:t,backend:e}=r,{x:n}=t;if(e.shouldExecuteOnCPU([n])&&n.dtype!=="complex64"){let s=e.texData.get(n.dataId),i=bb(s.values);return e.makeTensorInfo(n.shape,n.dtype,i)}let o;return G().getBool("WEBGL_PACK_UNARY_OPERATIONS")?o=new $o(n.shape,tL):o=new wn(n.shape,tL),e.runWebGLProgram(o,[n],n.dtype)}var eL={kernelName:di,backendName:"webgl",kernelFunc:Ctt};var Itt=dr+`
if (abs(x) > 1.) {
return NAN;
}
return acos(x);
`,Stt=Ct({opSnippet:Itt}),rL={kernelName:ji,backendName:"webgl",kernelFunc:Stt};var ktt=dr+`
if (x < 1.0) return NAN;
return log(x + sqrt(x * x - 1.0));`,Ntt=Ct({opSnippet:ktt}),nL={kernelName:Xi,backendName:"webgl",kernelFunc:Ntt};var oL="return a + b;",Ttt=le({opSnippet:oL,packedOpSnippet:oL,supportsComplex:!0,cpuKernelImpl:zP}),sL={kernelName:Kn,backendName:"webgl",kernelFunc:Ttt};var Bk=class{constructor(t,e){this.outputShape=[],this.outputShape=t,this.variableNames=e.map((s,i)=>`T${i}`);let n=[];this.variableNames.forEach(s=>{n.push(`float v${s} = get${s}AtOutCoords();`)});let o=this.variableNames.map(s=>`v${s}`).join(" + ");this.userCode=`
void main() {
${n.join(`
`)}
float result = ${o};
setOutput(result);
}
`}};var Vk=class{constructor(t,e){this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t,this.variableNames=e.map((s,i)=>`T${i}`);let n=[];this.variableNames.forEach(s=>{n.push(`vec4 v${s} = get${s}AtOutCoords();`)});let o=this.variableNames.map(s=>`v${s}`).join(" + ");this.userCode=`
void main() {
${n.join(`
`)}
vec4 result = ${o};
setOutput(result);
}
`}};function kb(r){let{inputs:t,backend:e}=r,n=t;if(n.length===1)return er({inputs:{x:n[0]},backend:e});if(n.length>G().get("WEBGL_MAX_TEXTURES_IN_SHADER")){let u=Math.floor(n.length/2),l=kb({inputs:n.slice(0,u),backend:e}),c=kb({inputs:n.slice(u),backend:e});return kb({inputs:[l,c],backend:e})}let o=n.map(u=>u.dtype).reduce((u,l)=>yr(u,l)),s=n.map(u=>u.shape),a=G().getBool("WEBGL_PACK")?new Vk(n[0].shape,s):new Bk(n[0].shape,s);return e.runWebGLProgram(a,n,o)}var iL={kernelName:qo,backendName:"webgl",kernelFunc:kb};function _tt(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{axis:s,keepDims:i}=n,a=o.shape.length,u=x.parseAxisParam(s,o.shape),l=u,c=k.getAxesPermutation(l,a),p=o;c!=null&&(p=Le({inputs:{x:o},backend:e,attrs:{perm:c}}),l=k.getInnerMostAxes(l.length,a)),k.assertAxesAreInnerMostDims("all",l,a);let[m,f]=k.computeOutAndReduceShapes(p.shape,l),d=x.sizeFromShape(f),h=ut({inputs:{x:p},backend:e,attrs:{shape:[-1,d]}}),g=Wn(h,h.dtype,"all",e),y;if(i){let b=k.expandShapeToKeepDim(m,u);y=ut({inputs:{x:g},backend:e,attrs:{shape:b}})}else y=ut({inputs:{x:g},backend:e,attrs:{shape:m}});return e.disposeIntermediateTensorInfo(h),e.disposeIntermediateTensorInfo(g),c!=null&&e.disposeIntermediateTensorInfo(p),y}var aL={kernelName:Yi,backendName:"webgl",kernelFunc:_tt};function Ett(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{axis:s,keepDims:i}=n,a=o.shape.length,u=x.parseAxisParam(s,o.shape),l=u,c=k.getAxesPermutation(l,a),p=o;c!=null&&(p=Le({inputs:{x:o},backend:e,attrs:{perm:c}}),l=k.getInnerMostAxes(l.length,a)),k.assertAxesAreInnerMostDims("any",l,a);let[m,f]=k.computeOutAndReduceShapes(p.shape,l),d=x.sizeFromShape(f),h=ut({inputs:{x:p},backend:e,attrs:{shape:[-1,d]}}),g=Wn(h,h.dtype,"any",e),y;if(i){let b=k.expandShapeToKeepDim(m,u);y=ut({inputs:{x:g},backend:e,attrs:{shape:b}})}else y=ut({inputs:{x:g},backend:e,attrs:{shape:m}});return e.disposeIntermediateTensorInfo(h),e.disposeIntermediateTensorInfo(g),c!=null&&e.disposeIntermediateTensorInfo(p),y}var lL={kernelName:Zi,backendName:"webgl",kernelFunc:Ett};var Gk=class{constructor(t,e,n){this.variableNames=["A"];let{windowSize:o,batchSize:s,outSize:i}=t;n||this.variableNames.push("bestIndicesA"),this.outputShape=[s,i];let a=e==="max"?">":"<",u=n?"inOffset + i;":"round(getBestIndicesA(batch, inOffset + i));";this.userCode=`
void main() {
ivec2 coords = getOutputCoords();
int batch = coords[0];
int outIdx = coords[1];
int inOffset = outIdx * ${o};
int bestIndex = inOffset;
float bestValue = getA(batch, bestIndex);
for (int i = 0; i < ${o}; i++) {
int inIdx = ${u};
float candidate = getA(batch, inIdx);
if (candidate ${a} bestValue) {
bestValue = candidate;
bestIndex = inIdx;
}
}
setOutput(float(bestIndex));
}
`}};var Wk=class{constructor(t,e,n,o){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,x.assert(t.length>2,()=>`Packed arg${n.charAt(0).toUpperCase()+n.slice(1)} supports only inputs with rank above 2.`);let s=t[t.length-1],i=Math.ceil(s/e);this.outputShape=t.slice(0,-1),i>1&&this.outputShape.push(i),o||this.variableNames.push("bestIndicesA");let a=this.outputShape,u=a.length,l=Ht(u),c=tr("coords",u),p,m;if(i===1){m=u+1;let $=Ht(m);p=`
${$} sourceLocR = ${$}(${c.join()}, 0);
++${c[u-1]};
${$} sourceLocG = ${$}(${c.join()}, 0);
++${c[u-2]};
${$} sourceLocA = ${$}(${c.join()}, 0);
--${c[u-1]};
${$} sourceLocB = ${$}(${c.join()}, 0);
--${c[u-2]};`}else m=u,p=`
${l} sourceLocR = coords;
++${c[u-1]};
${l} sourceLocG = coords;
++${c[u-2]};
${l} sourceLocA = coords;
--${c[u-1]};
${l} sourceLocB = coords;
--${c[u-2]};`;let f=["x","y","z","w","u","v"].slice(0,m),d="."+f[m-1],h=f.map($=>"int "+$),g=tr("sourceLocR",m-1).concat("inIdx.r"),y=tr("sourceLocG",m-1).concat("inIdx.g"),b=tr("sourceLocB",m-1).concat("inIdx.b"),w=tr("sourceLocA",m-1).concat("inIdx.a"),v=n==="max"?"greaterThan":"lessThan",I=o?"":`
inIdx = round(vec4(getBestIndicesAChannel(${g.join()}),
getBestIndicesAChannel(${y.join()}),
getBestIndicesAChannel(${b.join()}),
getBestIndicesAChannel(${w.join()})));`,E=`vec4(
getAChannel(${g.join()}),
hasNextCol ? getAChannel(${y.join()}) : 0.,
hasNextRow ? getAChannel(${b.join()}) : 0.,
hasNextRow && hasNextCol ? getAChannel(${w.join()}) : 0.)`,D=o?"":`
float getBestIndicesAChannel(${h.join()}) {
return getChannel(getBestIndicesA(${f.join()}),
vec2(${f.slice(-2).join()}));
}`;this.userCode=`
float getAChannel(${h.join()}) {
return getChannel(getA(${f.join()}),
vec2(${f.slice(-2).join()}));
}
${D}
void main() {
${l} coords = getOutputCoords();
bool hasNextCol = ${c[u-1]} < ${a[u-1]-1};
bool hasNextRow = ${c[u-2]} < ${a[u-2]-1};
${p}
ivec4 srcIdx = ivec4(sourceLocR${d}, sourceLocG${d},
sourceLocB${d}, sourceLocA${d}) * ${e};
ivec4 inIdx = srcIdx;
vec4 bestIndex = vec4(inIdx);
vec4 bestValue = ${E};
for (int i = 0; i < ${e}; i++) {
inIdx = srcIdx;
${I}
vec4 candidate = ${E};
bvec4 nan = isnan(candidate);
bvec4 replace = bvec4(
vec4(${v}(candidate, bestValue)) * (vec4(1.0) - vec4(nan)));
bestValue = vec4(replace.x ? candidate.x : bestValue.x,
replace.y ? candidate.y : bestValue.y,
replace.z ? candidate.z : bestValue.z,
replace.w ? candidate.w : bestValue.w);
bestIndex = mix(bestIndex, vec4(inIdx), vec4(replace));
srcIdx++;
}
setOutput(bestIndex);
}
`}};function uL(r,t,e,n=null){let o=t.shape[0],s=t.shape[1];n!=null&&(o=n.shape[0],s=n.shape[1]);let i=k.computeOptimalWindowSize(s),a={windowSize:i,inSize:s,batchSize:o,outSize:Math.ceil(s/i)},u=new Gk(a,e,n==null),l=[t];n!=null&&l.push(n);let c=r.runWebGLProgram(u,l,"int32");if(c.shape[1]===1)return c;let p=uL(r,t,e,c);return r.disposeIntermediateTensorInfo(c),p}function cL(r,t,e,n=null){let o=n!=null?n.shape:t.shape,s=o[o.length-1],i=k.computeOptimalWindowSize(s),a=new Wk(o,i,e,n==null),u=n==null?[t]:[t,n],l=r.runWebGLProgram(a,u,"int32");if(l.shape.length===t.shape.length){let c=cL(r,t,e,l);return r.disposeIntermediateTensorInfo(l),c}return l}function Nb(r,t,e,n){let o=[e];if(k.assertAxesAreInnerMostDims("arg"+n.charAt(0).toUpperCase()+n.slice(1),o,t.shape.length),!G().getBool("WEBGL_PACK_REDUCE")||t.shape.length<=2){let s=[],i=r.texData.get(t.dataId),a=i!==null&&i.isPacked,u=t;a&&(u=r.unpackTensor(t),s.push(u));let[l,c]=k.computeOutAndReduceShapes(u.shape,o),p=x.sizeFromShape(c),m=ut({inputs:{x:u},backend:r,attrs:{shape:[-1,p]}});s.push(m);let f=uL(r,m,n);s.push(f);let d=ut({inputs:{x:f},backend:r,attrs:{shape:l}});return s.forEach(h=>r.disposeIntermediateTensorInfo(h)),d}return cL(r,t,n)}function Att(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{axis:s}=n,i=x.parseAxisParam(s,o.shape),a=k.getAxesPermutation(i,o.shape.length),u=o,l=[];a!=null&&(u=Le({inputs:{x:o},backend:e,attrs:{perm:a}}),l.push(u),i=k.getInnerMostAxes(i.length,u.shape.length)),k.assertAxesAreInnerMostDims("argMax",[i[0]],u.shape.length);let c=Nb(e,u,i[0],"max");return l.forEach(p=>e.disposeIntermediateTensorInfo(p)),c}var pL={kernelName:Ko,backendName:"webgl",kernelFunc:Att};function Dtt(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{axis:s}=n,i=x.parseAxisParam(s,o.shape),a=k.getAxesPermutation(i,o.shape.length),u=o,l=[];a!=null&&(u=Le({inputs:{x:o},backend:e,attrs:{perm:a}}),l.push(u),i=k.getInnerMostAxes(i.length,u.shape.length)),k.assertAxesAreInnerMostDims("argMin",[i[0]],u.shape.length);let c=Nb(e,u,i[0],"min");return l.forEach(p=>e.disposeIntermediateTensorInfo(p)),c}var mL={kernelName:wl,backendName:"webgl",kernelFunc:Dtt};var $tt=dr+`
if (abs(x) > 1.) {
return NAN;
}
return asin(x);
`,Rtt=Ct({opSnippet:$tt}),fL={kernelName:Ji,backendName:"webgl",kernelFunc:Rtt};var Ftt=dr+"return log(x + sqrt(x * x + 1.0));",Ott=Ct({opSnippet:Ftt}),dL={kernelName:Qi,backendName:"webgl",kernelFunc:Ott};var Ptt=dr+`
return atan(x);
`,Mtt=Ct({opSnippet:Ptt}),hL={kernelName:ta,backendName:"webgl",kernelFunc:Mtt};var Ltt=UM+`
return atan(a, b);
`,ztt=`
vec4 result = atan(a, b);
vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
`+HM+`
return result;
`,Btt=le({opSnippet:Ltt,packedOpSnippet:ztt}),gL={kernelName:ra,backendName:"webgl",kernelFunc:Btt};var Vtt=dr+`
if ((x < -1.0) || (x > 1.0)) return NAN;
return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,Gtt=Ct({opSnippet:Vtt}),xL={kernelName:ea,backendName:"webgl",kernelFunc:Gtt};var Hi=class{constructor(t,e,n,o=!1,s=!1){if(this.variableNames=["x"],e==="avg"&&n)throw new Error("Cannot compute positions for average pool.");let i=t.filterWidth,a=t.strideHeight,u=t.strideWidth,l=t.dilationHeight,c=t.dilationWidth,p=t.effectiveFilterHeight,m=t.effectiveFilterWidth,f=t.padInfo.top,d=t.padInfo.left;this.outputShape=t.outShape;let h=e==="avg",g=`((batch * ${t.inHeight} + xR) * ${t.inWidth} + xC) * ${t.inChannels} + d`,y=`(xR * ${t.inWidth} + xC) * ${t.inChannels} + d`,b="0.0";if(h||(b="-1.0 / 1e-20"),n){let $=">=";this.userCode=`
const ivec2 strides = ivec2(${a}, ${u});
const ivec2 pads = ivec2(${f}, ${d});
void main() {
ivec4 coords = getOutputCoords();
int batch = coords[0];
int d = coords[3];
ivec2 xRCCorner = coords.yz * strides - pads;
int xRCorner = xRCCorner.x;
int xCCorner = xRCCorner.y;
// max/min x(?, ?, d) to get y(yR, yC, d).
// ? = to be determined
float minMaxValue = 0.0;
float minMaxValueFound = 0.0;
int minMaxPosition = 0;
float avgValue = 0.0;
for (int wR = 0; wR < ${p};
wR += ${l}) {
int xR = xRCorner + wR;
if (xR < 0 || xR >= ${t.inHeight}) {
continue;
}
for (int wC = 0; wC < ${m};
wC += ${c}) {
int xC = xCCorner + wC;
if (xC < 0 || xC >= ${t.inWidth}) {
continue;
}
float value = getX(batch, xR, xC, d);
// If a min / max value has already been found, use it. If not,
// use the current value.
float currMinMaxValue = mix(
value, minMaxValue, minMaxValueFound);
if (value ${$} currMinMaxValue) {
minMaxValue = value;
minMaxValueFound = 1.0;
minMaxPosition = ${o?s?g:y:`wR * ${m} + wC`};
}
}
}
setOutput(float(minMaxPosition));
}
`;return}let w="max",v=`${e}(${e}(${e}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;e==="avg"&&(v="avgValue / count");let I=Math.floor(i/4)*4,E=i%4,D=`
if (${h}) {
avgValue += dot(values, ones);
} else {
minMaxValue = ${w}(values, minMaxValue);
}
`;this.userCode=`
const ivec2 strides = ivec2(${a}, ${u});
const ivec2 pads = ivec2(${f}, ${d});
const float initializationValue = ${b};
const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);
float count = 0.0;
float getValue(int batch, int xR, int xC, int d) {
if (xC < 0 || xC >= ${t.inWidth}) {
return initializationValue;
}
count += 1.0;
return getX(batch, xR, xC, d);
}
void main() {
ivec4 coords = getOutputCoords();
int batch = coords[0];
int d = coords[3];
ivec2 xRCCorner = coords.yz * strides - pads;
int xRCorner = xRCCorner.x;
int xCCorner = xRCCorner.y;
// max/min x(?, ?, d) to get y(yR, yC, d).
// ? = to be determined
vec4 minMaxValue = vec4(${b});
float avgValue = 0.0;
count = 0.0;
for (int wR = 0; wR < ${p};
wR += ${l}) {
int xR = xRCorner + wR;
if (xR < 0 || xR >= ${t.inHeight}) {
continue;
}
for (int wC = 0; wC < ${I}; wC += 4) {
int xC = xCCorner + wC * ${c};
vec4 values = vec4(
getValue(batch, xR, xC, d),
getValue(batch, xR, xC + ${c}, d),
getValue(batch, xR, xC + 2 * ${c}, d),
getValue(batch, xR, xC + 3 * ${c}, d)
);
${D}
}
int xC = xCCorner + ${I};
if (${E===1}) {
vec4 values = vec4(
getValue(batch, xR, xC, d),
initializationValue,
initializationValue,
initializationValue
);
${D}
} else if (${E===2}) {
vec4 values = vec4(
getValue(batch, xR, xC, d),
getValue(batch, xR, xC + ${c}, d),
initializationValue,
initializationValue
);
${D}
} else if (${E===3}) {
vec4 values = vec4(
getValue(batch, xR, xC, d),
getValue(batch, xR, xC + ${c}, d),
getValue(batch, xR, xC + 2 * ${c}, d),
initializationValue
);
${D}
}
}
setOutput(${v});
}
`}},Mc=class{constructor(t,e,n,o=!1,s=!1){if(this.variableNames=["x"],e==="avg"&&n)throw new Error("Cannot compute positions for average pool.");let i=t.filterWidth,a=t.strideDepth,u=t.strideHeight,l=t.strideWidth,c=t.dilationDepth,p=t.dilationHeight,m=t.dilationWidth,f=t.effectiveFilterDepth,d=t.effectiveFilterHeight,h=t.effectiveFilterWidth,g=t.padInfo.front,y=t.padInfo.top,b=t.padInfo.left;this.outputShape=t.outShape;let w=e==="avg",v="0.0";if(w||(v="-1.0 / 1e-20"),n){let M=">=";this.userCode=`
const ivec3 strides =
ivec3(${a}, ${u}, ${l});
const ivec3 pads = ivec3(${g}, ${y}, ${b});
void main() {
ivec5 coords = getOutputCoords();
int batch = coords.x;
int ch = coords.u;
ivec3 xCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;
int xDCorner = xCorner.x;
int xRCorner = xCorner.y;
int xCCorner = xCorner.z;
// max/min x(?, ?, ?, ch) to get y(yD, yR, yC, ch).
// ? = to be determined
float minMaxValue = 0.0;
float minMaxValueFound = 0.0;
int minMaxPosition = 0;
for (int wD = 0; wD < ${f};
wD += ${c}) {
int xD = xDCorner + wD;
if (xD < 0 || xD >= ${t.inDepth}) {
continue;
}
for (int wR = 0; wR < ${d};
wR += ${p}) {
int xR = xRCorner + wR;
if (xR < 0 || xR >= ${t.inHeight}) {
continue;
}
for (int wC = 0; wC < ${h};
wC += ${m}) {
int xC = xCCorner + wC;
if (xC < 0 || xC >= ${t.inWidth}) {
continue;
}
float value = getX(batch, xD, xR, xC, ch);
// If a min / max value has already been found, use it. If not,
// use the current value.
float currMinMaxValue = mix(
value, minMaxValue, minMaxValueFound);
if (value ${M} currMinMaxValue) {
minMaxValue = value;
minMaxValueFound = 1.0;
minMaxPosition = ${o?s?`(((batch * ${t.inDepth} + xD) * ${t.inHeight} + xR) * ${t.inWidth} + xC) * ${t.inChannels} + ch`:`((xD * ${t.inHeight} + xR) * ${t.inWidth} + xC) * ${t.inChannels} + ch`:`wD * ${d} * ${h} +
wR * ${h} + wC`};
}
}
}
}
setOutput(float(minMaxPosition));
}
`;return}let I="max",E=`${e}(${e}(${e}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;e==="avg"&&(E="avgValue / count");let D=Math.floor(i/4)*4,$=i%4,R=`
if (${w}) {
avgValue += dot(values, ones);
} else {
minMaxValue = ${I}(values, minMaxValue);
}
`;this.userCode=`
const ivec3 strides =
ivec3(${a}, ${u}, ${l});
const ivec3 pads = ivec3(${g}, ${y}, ${b});
const float initializationValue = ${v};
const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);
float count = 0.0;
float getValue(int batch, int xD, int xR, int xC, int ch) {
if (xC < 0 || xC >= ${t.inWidth}) {
return initializationValue;
}
count += 1.0;
return getX(batch, xD, xR, xC, ch);
}
void main() {
ivec5 coords = getOutputCoords();
int batch = coords.x;
int ch = coords.u;
ivec3 xCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;
int xDCorner = xCorner.x;
int xRCorner = xCorner.y;
int xCCorner = xCorner.z;
// max/min x(?, ?, ?, d) to get y(yD, yR, yC, ch).
// ? = to be determined
vec4 minMaxValue = vec4(${v});
float avgValue = 0.0;
count = 0.0;
for (int wD = 0; wD < ${f};
wD += ${c}) {
int xD = xDCorner + wD;
if (xD < 0 || xD >= ${t.inDepth}) {
continue;
}
for (int wR = 0; wR < ${d};
wR += ${p}) {
int xR = xRCorner + wR;
if (xR < 0 || xR >= ${t.inHeight}) {
continue;
}
for (int wC = 0; wC < ${D}; wC += 4) {
int xC = xCCorner + wC * ${m};
vec4 values = vec4(
getValue(batch, xD, xR, xC, ch),
getValue(batch, xD, xR, xC + ${m}, ch),
getValue(batch, xD, xR, xC + 2 * ${m}, ch),
getValue(batch, xD, xR, xC + 3 * ${m}, ch)
);
${R}
}
int xC = xCCorner + ${D};
if (${$===1}) {
vec4 values = vec4(
getValue(batch, xD, xR, xC, ch),
initializationValue,
initializationValue,
initializationValue
);
${R}
} else if (${$===2}) {
vec4 values = vec4(
getValue(batch, xD, xR, xC, ch),
getValue(batch, xD, xR, xC + ${m}, ch),
initializationValue,
initializationValue
);
${R}
} else if (${$===3}) {
vec4 values = vec4(
getValue(batch, xD, xR, xC, ch),
getValue(batch, xD, xR, xC + ${m}, ch),
getValue(batch, xD, xR, xC + 2 * ${m}, ch),
initializationValue
);
${R}
}
}
setOutput(${E});
}
}
`}};function Wtt(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t;ai(o,"avgPool");let{filterSize:s,strides:i,pad:a,dimRoundingMode:u}=n,l=1;x.assert(k.eitherStridesOrDilationsAreOne(i,l),()=>`Error in avgPool: Either strides or dilations must be 1. Got strides ${i} and dilations '${l}'`);let c=k.computePool2DInfo(o.shape,s,i,l,a,u);if(c.filterWidth===1&&c.filterHeight===1&&x.arraysEqual(c.inShape,c.outShape))return er({inputs:{x:o},backend:e});let p=new Hi(c,"avg",!1);return e.runWebGLProgram(p,[o],"float32")}var yL={kernelName:jo,backendName:"webgl",kernelFunc:Wtt};function Utt(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{filterSize:s,strides:i,pad:a,dimRoundingMode:u,dataFormat:l}=n,c=[1,1,1],p=k.computePool3DInfo(o.shape,s,i,c,a,u,l),m=new Mc(p,"avg",!1);return e.runWebGLProgram(m,[o],"float32")}var bL={kernelName:vl,backendName:"webgl",kernelFunc:Utt};var Uk=class{constructor(t){this.variableNames=["dy"],this.outputShape=t.inShape;let e=t.filterHeight,n=t.filterWidth,o=t.strideHeight,s=t.strideWidth,i=t.dilationHeight,a=t.dilationWidth,u=t.effectiveFilterHeight,l=t.effectiveFilterWidth,c=u-1-t.padInfo.top,p=l-1-t.padInfo.left,m=1/(e*n);this.userCode=`
const ivec2 pads = ivec2(${c}, ${p});
const float avgMultiplier = float(${m});
void main() {
ivec4 coords = getOutputCoords();
int b = coords[0];
int d = coords[3];
ivec2 dyRCCorner = coords.yz - pads;
int dyRCorner = dyRCCorner.x;
int dyCCorner = dyRCCorner.y;
// Convolve dy(?, ?, d) with pos mask(:, :, d) to get dx(xR, xC, d).
// ? = to be determined. : = across all values in that axis.
float dotProd = 0.0;
for (int wR = 0; wR < ${u};
wR += ${i}) {
float dyR = float(dyRCorner + wR) / ${o}.0;
if (dyR < 0.0 || dyR >= ${t.outHeight}.0 || fract(dyR) > 0.0) {
continue;
}
int idyR = int(dyR);
for (int wC = 0; wC < ${l};
wC+= ${a}) {
float dyC = float(dyCCorner + wC) / ${s}.0;
if (dyC < 0.0 || dyC >= ${t.outWidth}.0 ||
fract(dyC) > 0.0) {
continue;
}
int idyC = int(dyC);
float dyValue = getDy(b, idyR, idyC, d);
dotProd += dyValue * avgMultiplier;
}
}
setOutput(dotProd);
}
`}},Hk=class{constructor(t){this.variableNames=["dy"],this.outputShape=t.inShape;let e=t.filterDepth,n=t.filterHeight,o=t.filterWidth,s=t.strideDepth,i=t.strideHeight,a=t.strideWidth,u=t.dilationDepth,l=t.dilationHeight,c=t.dilationWidth,p=t.effectiveFilterDepth,m=t.effectiveFilterHeight,f=t.effectiveFilterWidth,d=p-1-t.padInfo.front,h=m-1-t.padInfo.top,g=f-1-t.padInfo.left,y=1/(e*n*o);this.userCode=`
const ivec3 pads = ivec3(${d}, ${h}, ${g});
const float avgMultiplier = float(${y});
void main() {
ivec5 coords = getOutputCoords();
int batch = coords.x;
int ch = coords.u;
ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads;
int dyDCorner = dyCorner.x;
int dyRCorner = dyCorner.y;
int dyCCorner = dyCorner.z;
// Convolve dy(?, ?, ?, d) with pos mask(:, :, :, ch) to get
// dx(xD, xR, xC, ch).
// ? = to be determined. : = across all values in that axis.
float dotProd = 0.0;
for (int wD = 0; wD < ${p};
wD += ${u}) {
float dyD = float(dyDCorner + wD) / ${s}.0;
if (dyD < 0.0 || dyD >= ${t.outDepth}.0 || fract(dyD) > 0.0) {
continue;
}
int idyD = int(dyD);
for (int wR = 0; wR < ${m};
wR += ${l}) {
float dyR = float(dyRCorner + wR) / ${i}.0;
if (dyR < 0.0 || dyR >= ${t.outHeight}.0 ||
fract(dyR) > 0.0) {
continue;
}
int idyR = int(dyR);
for (int wC = 0; wC < ${f};
wC += ${c}) {
float dyC = float(dyCCorner + wC) / ${a}.0;
if (dyC < 0.0 || dyC >= ${t.outWidth}.0 ||
fract(dyC) > 0.0) {
continue;
}
int idyC = int(dyC);
float dyValue = getDy(batch, idyD, idyR, idyC, ch);
dotProd += dyValue * avgMultiplier;
}
}
}
setOutput(dotProd);
}
`}};function Htt(r){let{inputs:t,backend:e,attrs:n}=r,{dy:o,input:s}=t,i=s,{filterSize:a,strides:u,pad:l,dimRoundingMode:c}=n,p=[1,1,1],m=k.computePool3DInfo(i.shape,a,u,p,l,c),f=new Hk(m);return e.runWebGLProgram(f,[o],i.dtype)}var wL={kernelName:lp,backendName:"webgl",kernelFunc:Htt};function qtt(r){let{inputs:t,backend:e,attrs:n}=r,{dy:o,input:s}=t,i=s;ai([o,s],"avgPoolGrad");let{filterSize:a,strides:u,pad:l}=n,c=k.computePool2DInfo(i.shape,a,u,1,l),p=new Uk(c);return e.runWebGLProgram(p,[o],i.dtype)}var vL={kernelName:ap,backendName:"webgl",kernelFunc:qtt};function Ktt(r){let{inputs:t,backend:e,attrs:n}=r,{a:o,b:s}=t,{transposeA:i,transposeB:a}=n;return Pc({a:o,b:s,transposeA:i,transposeB:a,backend:e})}var CL={kernelName:Xo,backendName:"webgl",kernelFunc:Ktt};var qk=class{constructor(t,e,n,o,s,i){this.outputShape=[],this.variableNames=["x","mean","variance"],k.assertAndGetBroadcastShape(t,e),k.assertAndGetBroadcastShape(t,n);let a="0.0";o!=null&&(k.assertAndGetBroadcastShape(t,o),this.variableNames.push("offset"),a="getOffsetAtOutCoords()");let u="1.0";s!=null&&(k.assertAndGetBroadcastShape(t,s),this.variableNames.push("scale"),u="getScaleAtOutCoords()"),this.outputShape=t,this.userCode=`
void main() {
float x = getXAtOutCoords();
float mean = getMeanAtOutCoords();
float variance = getVarianceAtOutCoords();
float offset = ${a};
float scale = ${u};
float inv = scale * inversesqrt(variance + float(${i}));
setOutput(dot(vec3(x, -mean, offset), vec3(inv, inv, 1)));
}
`}};var Kk=class{constructor(t,e,n,o,s,i){this.packedInputs=!0,this.packedOutput=!0,this.variableNames=["x","mean","variance"],k.assertAndGetBroadcastShape(t,e),k.assertAndGetBroadcastShape(t,n);let a="vec4(0.0)";o!=null&&(k.assertAndGetBroadcastShape(t,o),this.variableNames.push("offset"),a="getOffsetAtOutCoords()");let u="vec4(1.0)";s!=null&&(k.assertAndGetBroadcastShape(t,s),this.variableNames.push("scale"),u="getScaleAtOutCoords()"),this.outputShape=t,this.userCode=`
void main() {
vec4 offset = ${a};
vec4 scale = ${u};
vec4 x = getXAtOutCoords();
vec4 mean = getMeanAtOutCoords();
vec4 variance = getVarianceAtOutCoords();
vec4 inv = scale * inversesqrt(variance + vec4(${i}));
setOutput((x - mean) * inv + offset);
}
`}};var jtt=({inputs:r,backend:t,attrs:e})=>{let{x:n,mean:o,variance:s,offset:i,scale:a}=r;x.assert(o.shape.length===s.shape.length,()=>"Batch normalization gradient requires mean and variance to have equal ranks."),x.assert(i==null||o.shape.length===i.shape.length,()=>"Batch normalization gradient requires mean and offset to have equal ranks."),x.assert(a==null||o.shape.length===a.shape.length,()=>"Batch normalization gradient requires mean and scale to have equal ranks.");let{varianceEpsilon:u}=e;u==null&&(u=.001);let l=[n,o,s],c=null;i!=null&&(c=i.shape,l.push(i));let p=null;a!=null&&(p=a.shape,l.push(a));let m=G().getBool("WEBGL_PACK_NORMALIZATION")?new Kk(n.shape,o.shape,s.shape,c,p,u):new qk(n.shape,o.shape,s.shape,c,p,u);return t.runWebGLProgram(m,l,l[0].dtype)},IL={kernelName:ls,backendName:"webgl",kernelFunc:jtt};var Xk=class{constructor(t){this.variableNames=["source"],this.outputShape=t,this.rank=t.length;let e=Ht(this.rank);this.customUniforms=[{name:"start",arrayIndex:this.rank,type:"int"}];let n=Xtt(this.rank),o,s=t.map((i,a)=>`sourceLoc.${jk[a]} = start[${a}] + coords.${jk[a]};`);o=`
${e} sourceLoc;
${e} coords = getOutputCoords();
${s.join(`
`)}
`,this.userCode=`
void main() {
${o}
setOutput(getSource(${n}));
}
`}},jk=["x","y","z","w","u","v"];function Xtt(r){if(r===1)return"sourceLoc";if(r<=6)return jk.slice(0,r).map(t=>"sourceLoc."+t).join(",");throw Error(`Slicing for rank ${r} is not yet supported`)}var Yk=class{constructor(t){this.variableNames=["source"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t,this.rank=t.length,this.customUniforms=[{name:"start",arrayIndex:this.rank,type:"int"}];let e=Ht(this.rank),n=tr("coords",this.rank),o=tr("sourceLoc",this.rank),s=this.rank===1?"sourceLoc":`vec2(${o.slice(-2).join()})`,i=`getChannel(getSource(${o.join()}), ${s})`,a=`
result.x = ${i};
if (++${n[this.rank-1]} < ${t[this.rank-1]}) {
++${o[this.rank-1]};
result.y = ${i};
--${o[this.rank-1]};
}
`,u=this.rank===1?"":`
--${n[this.rank-1]};
if (++${n[this.rank-2]} < ${t[this.rank-2]}) {
++${o[this.rank-2]};
result.z = ${i};
if (++${n[this.rank-1]} < ${t[this.rank-1]}) {
++${o[this.rank-1]};
result.w = ${i};
}
}
`,l=this.rank<=4?`sourceLoc = coords +
${e}(${t.map((c,p)=>`start[${p}]`).join()});`:t.map((c,p)=>`${o[p]} = ${n[p]} + start[${p}];`).join(`
`);this.userCode=`
void main() {
${e} coords = getOutputCoords();
${e} sourceLoc;
${l}
vec4 result = vec4(0.);
${a}
${u}
setOutput(result);
}
`}};function Ytt(r,t,e,n){let o=n.texData.get(r.dataId),s=n.makeTensorInfo(e,r.dtype),i=n.texData.get(s.dataId);Object.assign(i,o),i.refCount=1,i.shape=e,i.dtype=r.dtype;let a=Ve.computeFlatOffset(t,x.computeStrides(r.shape));o.slice&&(a+=o.slice.flatOffset),i.slice={flatOffset:a,origDataId:o.slice&&o.slice.origDataId||r.dataId};let u=n.dataRefCount.get(i.slice.origDataId)||1;return n.dataRefCount.set(i.slice.origDataId,u+1),s}function ci(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{begin:s,size:i}=n,[a,u]=Ve.parseSliceParams(o,s,i);if(Ve.assertParamsValid(o,a,u),x.sizeFromShape(u)===0)return e.makeTensorInfo(u,o.dtype,[]);if(e.shouldExecuteOnCPU([o])||o.dtype==="string"){let p=e.texData.get(o.dataId),m=pM(p.values,a,u,o.shape,o.dtype);return e.makeTensorInfo(u,o.dtype,m)}let{isPacked:l}=e.texData.get(o.dataId),c=Ve.isSliceContinous(o.shape,a,u);if(l||!c){let p=G().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new Yk(u):new Xk(u),m=[a];return e.runWebGLProgram(p,[o],o.dtype,m)}return e.uploadToGPU(o.dataId),Ytt(o,a,u,e)}var SL={kernelName:Si,backendName:"webgl",kernelFunc:ci};var Ztt=r=>{let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{blockShape:s,crops:i}=n;x.assert(o.shape.length<=4,()=>"batchToSpaceND for rank > 4 with a WebGL backend not implemented yet");let a=s.reduce((b,w)=>b*w),u=k.getReshaped(o.shape,s,a),l=k.getPermuted(u.length,s.length),c=k.getReshapedPermuted(o.shape,s,a),p=k.getSliceBeginCoords(i,s.length),m=k.getSliceSize(c,i,s.length),f=[],d=ut({inputs:{x:o},backend:e,attrs:{shape:u}}),h=Le({inputs:{x:d},backend:e,attrs:{perm:l}}),g=ut({inputs:{x:h},backend:e,attrs:{shape:c}}),y=ci({inputs:{x:g},backend:e,attrs:{begin:p,size:m}});return f.push(d),f.push(h),f.push(g),f.forEach(b=>e.disposeIntermediateTensorInfo(b)),y},kL={kernelName:hi,backendName:"webgl",kernelFunc:Ztt};function Jtt(r){let{inputs:t,backend:e,attrs:n}=r,{x:o,weights:s}=t,{size:i}=n,a=e.readSync(o.dataId),u=e.readSync(s.dataId),l=yb(a,u,s.dtype,s.shape,i);return e.makeTensorInfo([i],s.dtype,l)}var NL={kernelName:up,backendName:"webgl",kernelFunc:Jtt};function Qtt(r){let{inputs:t,backend:e}=r,{s0:n,s1:o}=t,s=e.readSync(n.dataId),i=e.readSync(o.dataId),a=k.assertAndGetBroadcastShape(Array.from(s),Array.from(i));return e.makeTensorInfo([a.length],"int32",Int32Array.from(a))}var TL={kernelName:cp,backendName:"webgl",kernelFunc:Qtt};var tet="return float(a != b);",Zk=le({opSnippet:tet,cpuKernelImpl:iM,dtype:"bool"}),_L={kernelName:ba,backendName:"webgl",kernelFunc:Zk};function ml(r){let{inputs:t,backend:e}=r,{input:n}=t,o=e.texData.get(n.dataId);return er({inputs:{x:o.complexTensorInfos.real},backend:e})}var EL={kernelName:Ap,backendName:"webgl",kernelFunc:ml};var eet="return float(int(x));";function AL(r,t){let e=new wn(r.shape,eet),n=t.runWebGLProgram(e,[r],"int32");return{dataId:n.dataId,shape:n.shape,dtype:n.dtype}}function Jk(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{dtype:s}=n;if(s==="complex64"){if(o.dtype==="complex64")return er({inputs:{x:o},backend:e});let i=ye(o.shape),a=Jk({inputs:{x:o},backend:e,attrs:{dtype:"float32"}}),u=Dn({inputs:{real:a,imag:i},backend:e});return i.dispose(),e.disposeIntermediateTensorInfo(a),u}if(o.dtype==="complex64"){let i=ml({inputs:{input:o},backend:e}),a=Jk({inputs:{x:i},backend:e,attrs:{dtype:s}});return e.disposeIntermediateTensorInfo(i),a}if(!x.hasEncodingLoss(o.dtype,s)){let i=er({inputs:{x:o},backend:e});return{dataId:i.dataId,shape:i.shape,dtype:s}}if(s==="int32")return AL(o,e);if(s==="bool"){let i=e.makeTensorInfo([],"bool",x.getTypedArrayFromDType("bool",1)),u=Zk({inputs:{a:o,b:i},backend:e});return e.disposeIntermediateTensorInfo(i),u}throw new Error(`Error in Cast: failed to cast ${o.dtype} to ${s}`)}var DL={kernelName:no,backendName:"webgl",kernelFunc:Jk};var $L="return ceil(x);",ret=Ct({opSnippet:$L,packedOpSnippet:$L,cpuKernelImpl:VP}),RL={kernelName:Yo,backendName:"webgl",kernelFunc:ret};var Qk=class{constructor(t){this.variableNames=["A"],this.customUniforms=[{name:"minVal",type:"float"},{name:"maxVal",type:"float"}],this.outputShape=t,this.userCode=`
void main() {
float value = getAAtOutCoords();
if (isnan(value)) {
setOutput(value);
return;
}
setOutput(clamp(value, minVal, maxVal));
}
`}};var tN=class{constructor(t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"minVal",type:"float"},{name:"maxVal",type:"float"}],this.outputShape=t,this.userCode=`
void main() {
vec4 value = getAAtOutCoords();
if (any(isnan(value))) {
setOutput(value);
return;
}
setOutput(clamp(value, vec4(minVal), vec4(maxVal)));
}
`}};function net(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{clipValueMin:s,clipValueMax:i}=n,a;G().getBool("WEBGL_PACK_CLIP")?a=new tN(o.shape):a=new Qk(o.shape);let u=[[s],[i]];return e.runWebGLProgram(a,[o],o.dtype,u)}var FL={kernelName:oo,backendName:"webgl",kernelFunc:net};var eN=class{constructor(t){this.variableNames=["real","imag"],this.outputShape=t,this.userCode=`
void main() {
float re = abs(getRealAtOutCoords());
float im = abs(getImagAtOutCoords());
float mx = max(re, im);
// sadly the length function in glsl is not underflow-safe
// (at least not on Intel GPUs). So the safe solution is
// to ensure underflow-safety in all cases.
setOutput(
mx == 0.0 ? 0.0 : mx * length(vec2(1, min(re, im)/mx))
);
}
`}};function OL(r,t){return{dataId:t.dataId,dtype:t.dtype,shape:r.shape}}function oet(r){let{inputs:t,backend:e}=r,{x:n}=t,o=e.texData.get(n.dataId),s=new eN(n.shape),i=[OL(n,o.complexTensorInfos.real),OL(n,o.complexTensorInfos.imag)];return e.runWebGLProgram(s,i,i[0].dtype)}var PL={kernelName:Cl,backendName:"webgl",kernelFunc:oet};var rN=class{constructor(t){this.outputShape=[],this.outputShape=k.computeOutShape(t,1),this.variableNames=t.map((i,a)=>`T${a}`);let e=new Array(t.length-1);e[0]=t[0][1];for(let i=1;i<e.length;i++)e[i]=e[i-1]+t[i][1];let n=[`if (yC < ${e[0]}) setOutput(getT0(yR, yC));`];for(let i=1;i<e.length;i++){let a=e[i-1];n.push(`else if (yC < ${e[i]}) setOutput(getT${i}(yR, yC-${a}));`)}let o=e.length,s=e[e.length-1];n.push(`else setOutput(getT${o}(yR, yC-${s}));`),this.userCode=`
void main() {
ivec2 coords = getOutputCoords();
int yR = coords.x;
int yC = coords.y;
${n.join(`
`)}
}
`}};var nN=class{constructor(t,e){this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[],this.outputShape=k.computeOutShape(t,e);let n=this.outputShape,o=n.length,s=Ht(o),i=tr("coords",o),a=["x","y","z","w","u","v"].slice(0,o);this.variableNames=t.map((h,g)=>`T${g}`);let u=new Array(t.length-1);u[0]=t[0][e];for(let h=1;h<u.length;h++)u[h]=u[h-1]+t[h][e];let l=a[e],c=a.slice(-2),p=a.join(),m=`if (${l} < ${u[0]}) {
return getChannel(
getT0(${p}), vec2(${c.join()}));
}`;for(let h=1;h<u.length;h++){let g=u[h-1];m+=`
if (${l} < ${u[h]} && ${l} >= ${u[h-1]}) {
return getChannel(
getT${h}(${Tb(a,l,g)}),
vec2(${Tb(c,l,g)}));
}`}let f=u.length,d=u[u.length-1];m+=`
return getChannel(
getT${f}(${Tb(a,l,d)}),
vec2(${Tb(c,l,d)}));`,this.userCode=`
float getValue(${a.map(h=>"int "+h)}) {
${m}
}
void main() {
${s} coords = getOutputCoords();
vec4 result = vec4(getValue(${i}), 0., 0., 0.);
${i[o-1]} = ${i[o-1]} + 1;
if (${i[o-1]} < ${n[o-1]}) {
result.g = getValue(${i});
}
${i[o-2]} = ${i[o-2]} + 1;
if (${i[o-2]} < ${n[o-2]}) {
result.a = getValue(${i});
}
${i[o-1]} = ${i[o-1]} - 1;
if (${i[o-2]} < ${n[o-2]} &&
${i[o-1]} < ${n[o-1]}) {
result.b = getValue(${i});
}
setOutput(result);
}
`}};function Tb(r,t,e){let n=r.indexOf(t);return r.map((s,i)=>i===n?`${s} - ${e}`:s).join()}function Lc(r){let{inputs:t,backend:e}=r,{input:n}=t,o=e.texData.get(n.dataId);return er({inputs:{x:o.complexTensorInfos.imag},backend:e})}var ML={kernelName:Ip,backendName:"webgl",kernelFunc:Lc};function zc(r,t,e){let n=r[0].dtype;if(n==="complex64"){let c=r.map(h=>ml({inputs:{input:h},backend:e})),p=r.map(h=>Lc({inputs:{input:h},backend:e})),m=zc(c,t,e),f=zc(p,t,e),d=Dn({inputs:{real:m,imag:f},backend:e});return c.forEach(h=>e.disposeIntermediateTensorInfo(h)),p.forEach(h=>e.disposeIntermediateTensorInfo(h)),e.disposeIntermediateTensorInfo(m),e.disposeIntermediateTensorInfo(f),d}let o=e.shouldExecuteOnCPU(r);if(n==="string"&&(o=!0),o){let c=r.map(y=>{let b=x.sizeFromShape(y.shape.slice(t));return ut({inputs:{x:y},backend:e,attrs:{shape:[-1,b]}})}),p=c.map(y=>({vals:e.readSync(y.dataId),shape:y.shape})),m=k.computeOutShape(c.map(y=>y.shape),1),f=c[0].shape[0]===1,d=GP(p,m,n,f),h=k.computeOutShape(r.map(y=>y.shape),t),g=e.makeTensorInfo(h,n,d);return c.forEach(y=>e.disposeIntermediateTensorInfo(y)),g}if(r.length>G().getNumber("WEBGL_MAX_TEXTURES_IN_SHADER")){let c=Math.floor(r.length/2),p=zc(r.slice(0,c),t,e),m=zc(r.slice(c),t,e),f=zc([p,m],t,e);return e.disposeIntermediateTensorInfo(p),e.disposeIntermediateTensorInfo(m),f}if(G().getBool("WEBGL_PACK_ARRAY_OPERATIONS")&&r[0].shape.length>1){let c=new nN(r.map(p=>p.shape),t);return e.runWebGLProgram(c,r,n)}let{tensors2D:s,outShape:i}=set(r,t,e),a=new rN(s.map(c=>c.shape)),u=e.runWebGLProgram(a,s,n);s.forEach(c=>e.disposeIntermediateTensorInfo(c));let l=ut({inputs:{x:u},attrs:{shape:i},backend:e});return e.disposeIntermediateTensorInfo(u),l}function set(r,t,e){let n=k.computeOutShape(r.map(s=>s.shape),t);return{tensors2D:r.map(s=>ut({inputs:{x:s},attrs:{shape:[-1,x.sizeFromShape(s.shape.slice(t))]},backend:e})),outShape:n}}function oN(r){let{inputs:t,backend:e,attrs:n}=r,{axis:o}=n,s=x.parseAxisParam(o,t[0].shape)[0],i=k.computeOutShape(t.map(l=>l.shape),s);if(x.sizeFromShape(i)===0)return e.makeTensorInfo(i,t[0].dtype,[]);let a=t.filter(l=>x.sizeFromShape(l.shape)>0);if(a.length===1)return er({inputs:{x:a[0]},backend:e});let u=a.map(l=>l.shape);return k.assertParamsConsistent(u,s),zc(a,s,e)}var LL={kernelName:gi,backendName:"webgl",kernelFunc:oN};var ug=class{constructor(t,e=!1,n=null,o=!1,s=!1){this.variableNames=["x","W"],this.outputShape=t.outShape;let i=t.padInfo.top,a=t.padInfo.left,u=t.strideHeight,l=t.strideWidth,c=t.dilationHeight,p=t.dilationWidth,m=t.filterHeight,f=t.filterWidth,d=Math.floor(t.inChannels/4)*4,h=t.inChannels%4,g=t.dataFormat==="channelsLast",y=g?1:2,b=g?2:3,w=g?3:1,v="",I="";n&&(o?v=`float activation(float a) {
float b = getPreluActivationWeightsAtOutCoords();
${n}
}`:s?v=`float activation(float a) {
float b = getLeakyreluAlphaAtOutCoords();
${n}
}`:v=`
float activation(float x) {
${n}
}
`,I="result = activation(result);");let E=e?"result += getBiasAtOutCoords();":"";e&&this.variableNames.push("bias"),o&&this.variableNames.push("preluActivationWeights"),s&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
${v}
const ivec2 strides = ivec2(${u}, ${l});
const ivec2 pads = ivec2(${i}, ${a});
void main() {
ivec4 coords = getOutputCoords();
int batch = coords[0];
int d2 = coords[${w}];
ivec2 xRCCorner =
ivec2(coords[${y}], coords[${b}]) * strides - pads;
int xRCorner = xRCCorner.x;
int xCCorner = xRCCorner.y;
// Convolve x(?, ?, d1) with w(:, :, d1, d2) to get y(yR, yC, d2).
// ? = to be determined. : = across all values in that axis.
float dotProd = 0.0;
for (int wR = 0; wR < ${m}; wR++) {
int xR = xRCorner + wR * ${c};
if (xR < 0 || xR >= ${t.inHeight}) {
continue;
}
for (int wC = 0; wC < ${f}; wC++) {
int xC = xCCorner + wC * ${p};
if (xC < 0 || xC >= ${t.inWidth}) {
continue;
}
for (int d1 = 0; d1 < ${d}; d1 += 4) {
vec4 wValues = vec4(
getW(wR, wC, d1, d2),
getW(wR, wC, d1 + 1, d2),
getW(wR, wC, d1 + 2, d2),
getW(wR, wC, d1 + 3, d2)
);
if (${g}) {
vec4 xValues = vec4(
getX(batch, xR, xC, d1),
getX(batch, xR, xC, d1 + 1),
getX(batch, xR, xC, d1 + 2),
getX(batch, xR, xC, d1 + 3)
);
dotProd += dot(xValues, wValues);
} else {
vec4 xValues = vec4(
getX(batch, d1, xR, xC),
getX(batch, d1 + 1, xR, xC),
getX(batch, d1 + 2, xR, xC),
getX(batch, d1 + 3, xR, xC)
);
dotProd += dot(xValues, wValues);
}
}
if (${h===1}) {
if (${g}) {
dotProd +=
getX(batch, xR, xC, ${d}) *
getW(wR, wC, ${d}, d2);
} else {
dotProd +=
getX(batch, ${d}, xR, xC) *
getW(wR, wC, ${d}, d2);
}
} else if (${h===2}) {
vec2 wValues = vec2(
getW(wR, wC, ${d}, d2),
getW(wR, wC, ${d} + 1, d2)
);
if (${g}) {
vec2 xValues = vec2(
getX(batch, xR, xC, ${d}),
getX(batch, xR, xC, ${d} + 1)
);
dotProd += dot(xValues, wValues);
} else {
vec2 xValues = vec2(
getX(batch, ${d}, xR, xC),
getX(batch, ${d} + 1, xR, xC)
);
dotProd += dot(xValues, wValues);
}
} else if (${h===3}) {
vec3 wValues = vec3(
getW(wR, wC, ${d}, d2),
getW(wR, wC, ${d} + 1, d2),
getW(wR, wC, ${d} + 2, d2)
);
if (${g}) {
vec3 xValues = vec3(
getX(batch, xR, xC, ${d}),
getX(batch, xR, xC, ${d} + 1),
getX(batch, xR, xC, ${d} + 2)
);
dotProd += dot(xValues, wValues);
} else {
vec3 xValues = vec3(
getX(batch, ${d}, xR, xC),
getX(batch, ${d} + 1, xR, xC),
getX(batch, ${d} + 2, xR, xC)
);
dotProd += dot(xValues, wValues);
}
}
}
}
float result = dotProd;
${E}
${I}
setOutput(result);
}
`}},sN=class{constructor(t){this.variableNames=["x","W"],this.outputShape=t.outShape;let e=t.padInfo.front,n=t.padInfo.top,o=t.padInfo.left,s=t.strideDepth,i=t.strideHeight,a=t.strideWidth,u=t.dilationDepth,l=t.dilationHeight,c=t.dilationWidth,p=t.filterDepth,m=t.filterHeight,f=t.filterWidth,d=Math.floor(t.inChannels/4)*4,h=t.inChannels%4;this.userCode=`
const ivec3 strides = ivec3(${s}, ${i}, ${a});
const ivec3 pads = ivec3(${e}, ${n}, ${o});
void main() {
ivec5 coords = getOutputCoords();
int batch = coords.x;
int d2 = coords.u;
ivec3 xFRCCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;
int xFCorner = xFRCCorner.x;
int xRCorner = xFRCCorner.y;
int xCCorner = xFRCCorner.z;
// Convolve x(?, ?, ?, d1) with w(:, :, :, d1, d2) to get
// y(yF, yR, yC, d2). ? = to be determined. : = across all
// values in that axis.
float dotProd = 0.0;
for (int wF = 0; wF < ${p}; wF++) {
int xF = xFCorner + wF * ${u};
if (xF < 0 || xF >= ${t.inDepth}) {
continue;
}
for (int wR = 0; wR < ${m}; wR++) {
int xR = xRCorner + wR * ${l};
if (xR < 0 || xR >= ${t.inHeight}) {
continue;
}
for (int wC = 0; wC < ${f}; wC++) {
int xC = xCCorner + wC * ${c};
if (xC < 0 || xC >= ${t.inWidth}) {
continue;
}
for (int d1 = 0; d1 < ${d}; d1 += 4) {
vec4 xValues = vec4(
getX(batch, xF, xR, xC, d1),
getX(batch, xF, xR, xC, d1 + 1),
getX(batch, xF, xR, xC, d1 + 2),
getX(batch, xF, xR, xC, d1 + 3)
);
vec4 wValues = vec4(
getW(wF, wR, wC, d1, d2),
getW(wF, wR, wC, d1 + 1, d2),
getW(wF, wR, wC, d1 + 2, d2),
getW(wF, wR, wC, d1 + 3, d2)
);
dotProd += dot(xValues, wValues);
}
if (${h===1}) {
dotProd +=
getX(batch, xF, xR, xC, ${d}) *
getW(wF, wR, wC, ${d}, d2);
} else if (${h===2}) {
vec2 xValues = vec2(
getX(batch, xF, xR, xC, ${d}),
getX(batch, xF, xR, xC, ${d} + 1)
);
vec2 wValues = vec2(
getW(wF, wR, wC, ${d}, d2),
getW(wF, wR, wC, ${d} + 1, d2)
);
dotProd += dot(xValues, wValues);
} else if (${h===3}) {
vec3 xValues = vec3(
getX(batch, xF, xR, xC, ${d}),
getX(batch, xF, xR, xC, ${d} + 1),
getX(batch, xF, xR, xC, ${d} + 2)
);
vec3 wValues = vec3(
getW(wF, wR, wC, ${d}, d2),
getW(wF, wR, wC, ${d} + 1, d2),
getW(wF, wR, wC, ${d} + 2, d2)
);
dotProd += dot(xValues, wValues);
}
}
}
}
setOutput(dotProd);
}
`}};var iN=class{constructor(t,e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"inputShape",type:"ivec3"},{name:"pad",type:"ivec2"},{name:"stride",type:"ivec2"},{name:"dilation",type:"ivec2"},{name:"inChannels",type:"int"},{name:"itemsPerBlockRow",type:"int"},{name:"outWidth",type:"int"}],this.outputShape=t,this.enableShapeUniforms=De(this.outputShape.length);let{dataFormat:n}=e,o=He(),s=n==="channelsLast",i=s?0:1,a=s?1:2,u=this.enableShapeUniforms?"if(blockIndex < outShape[1] && pos < outShape[0]) {":`if(blockIndex < ${t[1]} && pos < ${t[0]}) {`,l="";for(let c=0;c<=1;c++)for(let p=0;p<=1;p++)l+=`
blockIndex = rc.y + ${p};
pos = rc.x + ${c};
${u}
offsetY = int(blockIndex / outWidth) * stride[0] - pad[0];
d0 = offsetY + dilation[0] * (pos / itemsPerBlockRow);
if(d0 < inputShape[${i}] && d0 >= 0) {
// Use custom imod instead mod. On Intel GPU, mod may generate
// unexpected value.
// https://github.com/tensorflow/tfjs/issues/5447
offsetX = imod(blockIndex, outWidth) * stride[1] - pad[1];
d1 = offsetX + dilation[1] * (imod(pos, itemsPerBlockRow) /
inChannels);
if(d1 < inputShape[${a}] && d1 >= 0) {
ch = imod(pos, inChannels);
if (${s}) {
innerDims = vec2(d1, ch);
result[${c*2+p}] = getChannel(
getA(d0, int(innerDims.x),
int(innerDims.y)), innerDims);
} else {
innerDims = vec2(d0, d1);
result[${c*2+p}] = 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;
${l}
${o.output} = result;
}
`}};function _b({x:r,filter:t,convInfo:e,backend:n,bias:o=null,preluActivationWeights:s=null,leakyreluAlpha:i=0,activation:a=null}){let u=r.shape,l=n.texData.get(r.dataId),c=e.inChannels,p=u[0]*u[1]*u[2],m=e.outChannels,f=e.dataFormat==="channelsLast",d=!1,h=!1,g,y=[];if(!((p===1||m===1)&&c>zk)&&l.isPacked&&f&&l.texture!=null&&u[2]%2!==0&&x.arraysEqual(l.shape.slice(-3),u.slice(-3))){let v=u[0]*u[1]*(u[2]+1),I={dataId:r.dataId,shape:[1,v,e.inChannels],dtype:r.dtype},E=l.shape;l.shape=l.shape.slice(),l.shape[l.shape.length-2]++,x.assert(ou(l.shape,I.shape),()=>`packed reshape ${l.shape} to ${I.shape} isn't free`);let D=ut({inputs:{x:t},backend:n,attrs:{shape:[1,e.inChannels,e.outChannels]}});y.push(D);let $=Pc({a:I,b:D,backend:n,transposeA:d,transposeB:h,bias:o,activation:a,preluActivationWeights:s,leakyreluAlpha:i}),R=n.texData.get($.dataId);x.assert(R.isPacked,()=>"batchMatMul result is expected to be packed"),l.shape=E,R.shape=e.outShape,g=er({inputs:{x:$},backend:n}),g.shape=e.outShape,y.push($)}else{let v=f?u[0]*u[1]*u[2]:u[0]*u[2]*u[3],I=ut({inputs:{x:r},backend:n,attrs:{shape:[1,v,e.inChannels]}}),E=ut({inputs:{x:t},backend:n,attrs:{shape:[1,e.inChannels,e.outChannels]}}),D=Pc({a:I,b:E,transposeA:d,transposeB:h,backend:n,bias:o,activation:a,preluActivationWeights:s,leakyreluAlpha:i});g=ut({inputs:{x:D},backend:n,attrs:{shape:e.outShape}}),y.push(I),y.push(E),y.push(D)}for(let v of y)n.disposeIntermediateTensorInfo(v);return g}function Eb({x:r,filter:t,convInfo:e,backend:n,bias:o=null,preluActivationWeights:s=null,leakyreluAlpha:i=0,activation:a=null}){let{filterWidth:u,filterHeight:l,inChannels:c,outWidth:p,outHeight:m,dataFormat:f}=e,d=f==="channelsLast",h=u*l*c,g=m*p,y=[h,g],b=!0,w=!1,v=[],I=ut({inputs:{x:r},backend:n,attrs:{shape:r.shape.slice(1)}}),E=ut({inputs:{x:t},backend:n,attrs:{shape:[1,h,x.sizeFromShape(t.shape)/h]}});v.push(I),v.push(E);let D=new iN(y,e),$=[I.shape,[e.padInfo.top,e.padInfo.left],[e.strideHeight,e.strideWidth],[e.dilationHeight,e.dilationWidth],[e.inChannels],[e.filterWidth*e.inChannels],[e.outWidth]],R=n.runWebGLProgram(D,[I],"float32",$),M=ut({inputs:{x:R},backend:n,attrs:{shape:[1,y[0],y[1]]}});v.push(R),v.push(M);let W=o!=null,U=s!=null,q=a==="leakyrelu",K=a?iu(a,!0):null,j=new ag(M.shape,E.shape,[1,g,e.outChannels],b,w,W,K,U,q),Q=[M,E];if(o&&Q.push(o),U&&Q.push(s),q){let st=n.makeTensorInfo([],"float32",x.createScalarValue(i,"float32"));Q.push(st),v.push(st)}let rt=n.runWebGLProgram(j,Q,"float32"),X=d?[1,m,p,e.outChannels]:[1,e.outChannels,m,p],nt=ut({inputs:{x:rt},backend:n,attrs:{shape:X}});v.push(rt);for(let st of v)n.disposeIntermediateTensorInfo(st);return nt}function iet(r){let{inputs:t,backend:e,attrs:n}=r,{x:o,filter:s}=t,{strides:i,pad:a,dataFormat:u,dilations:l,dimRoundingMode:c}=n,p=k.convertConv2DDataFormat(u),m=k.computeConv2DInfo(o.shape,s.shape,i,l,a,c,!1,p),f;if(m.filterHeight===1&&m.filterWidth===1&&m.dilationHeight===1&&m.dilationWidth===1&&m.strideHeight===1&&m.strideWidth===1&&(m.padInfo.type==="SAME"||m.padInfo.type==="VALID"))f=_b({x:o,filter:s,convInfo:m,backend:e});else if(G().getBool("WEBGL_CONV_IM2COL")&&o.shape[0]===1)f=Eb({x:o,filter:s,convInfo:m,backend:e});else{let h=new ug(m);f=e.runWebGLProgram(h,[o,s],"float32")}let d=ut({inputs:{x:f},backend:e,attrs:{shape:m.outShape}});return e.disposeIntermediateTensorInfo(f),d}var zL={kernelName:Zo,backendName:"webgl",kernelFunc:iet};var aN=class{constructor(t){this.variableNames=["x","dy"],this.outputShape=t.filterShape;let e=t.strideHeight,n=t.strideWidth,o=t.padInfo.top,s=t.padInfo.left,i=t.dataFormat==="channelsLast";this.userCode=`
void main() {
ivec4 coords = getOutputCoords();
int wR = coords.x;
int wC = coords.y;
int d1 = coords.z;
int d2 = coords.w;
// Convolve x(?, ?, d1) with dy(:, :, d2) to get dw(wR, wC, d1, d2).
// ? = to be determined. : = across all values in that axis.
float dotProd = 0.0;
for (int b = 0; b < ${t.batchSize}; b++) {
for (int yR = 0; yR < ${t.outHeight}; yR++) {
int xR = wR + yR * ${e} - ${o};
if (xR < 0 || xR >= ${t.inHeight}) {
continue;
}
for (int yC = 0; yC < ${t.outWidth}; yC++) {
int xC = wC + yC * ${n} - ${s};
if (xC < 0 || xC >= ${t.inWidth}) {
continue;
}
if (${i}) {
float dyValue = getDy(b, yR, yC, d2);
float xValue = getX(b, xR, xC, d1);
dotProd += (xValue * dyValue);
} else {
float dyValue = getDy(b, d2, yR, yC);
float xValue = getX(b, d1, xR, xC);
dotProd += (xValue * dyValue);
}
}
}
}
setOutput(dotProd);
}
`}},lN=class{constructor(t){this.variableNames=["dy","W"],this.outputShape=t.inShape;let e=t.filterHeight,n=t.filterWidth,o=t.strideHeight,s=t.strideWidth,i=t.dataFormat==="channelsLast",a=e-1-t.padInfo.top,u=n-1-t.padInfo.left,l=i?1:2,c=i?2:3,p=i?3:1;this.userCode=`
const ivec2 pads = ivec2(${a}, ${u});
void main() {
ivec4 coords = getOutputCoords();
int batch = coords[0];
int d1 = coords[${p}];
ivec2 dyCorner = ivec2(coords[${l}], coords[${c}]) - pads;
int dyRCorner = dyCorner.x;
int dyCCorner = dyCorner.y;
// Convolve dy(?, ?, d2) with w(:, :, d1, d2) to compute dx(xR, xC, d1).
// ? = to be determined. : = across all values in that axis.
float dotProd = 0.0;
for (int wR = 0; wR < ${e}; wR++) {
float dyR = float(dyRCorner + wR) / ${o}.0;
if (dyR < 0.0 || dyR >= ${t.outHeight}.0 || fract(dyR) > 0.0) {
continue;
}
int idyR = int(dyR);
int wRPerm = ${e} - 1 - wR;
for (int wC = 0; wC < ${n}; wC++) {
float dyC = float(dyCCorner + wC) / ${s}.0;
if (dyC < 0.0 || dyC >= ${t.outWidth}.0 ||
fract(dyC) > 0.0) {
continue;
}
int idyC = int(dyC);
int wCPerm = ${n} - 1 - wC;
for (int d2 = 0; d2 < ${t.outChannels}; d2++) {
if (${i}) {
float xValue = getDy(batch, idyR, idyC, d2);
float wValue = getW(wRPerm, wCPerm, d1, d2);
dotProd += xValue * wValue;
} else {
float xValue = getDy(batch, d2, idyR, idyC);
float wValue = getW(wRPerm, wCPerm, d1, d2);
dotProd += xValue * wValue;
}
}
}
}
setOutput(dotProd);
}
`}},uN=class{constructor(t){this.variableNames=["x","dy"],this.outputShape=t.filterShape;let e=t.strideDepth,n=t.strideHeight,o=t.strideWidth,s=t.padInfo.front,i=t.padInfo.top,a=t.padInfo.left;this.userCode=`
void main() {
ivec5 coords = getOutputCoords();
int wF = coords.x;
int wR = coords.y;
int wC = coords.z;
int d1 = coords.w;
int d2 = coords.u;
float dotProd = 0.0;
for (int b = 0; b < ${t.batchSize}; b++) {
for (int yF = 0; yF < ${t.outDepth}; yF++) {
int xF = wF + yF * ${e} - ${s};
if (xF < 0 || xF >= ${t.inDepth}) {
continue;
}
for (int yR = 0; yR < ${t.outHeight}; yR++) {
int xR = wR + yR * ${n} - ${i};
if (xR < 0 || xR >= ${t.inHeight}) {
continue;
}
for (int yC = 0; yC < ${t.outWidth}; yC++) {
int xC = wC + yC * ${o} - ${a};
if (xC < 0 || xC >= ${t.inWidth}) {
continue;
}
float dyValue = getDy(b, yF, yR, yC, d2);
float xValue = getX(b, xF, xR, xC, d1);
dotProd += (xValue * dyValue);
}
}
}
}
setOutput(dotProd);
}
`}},cN=class{constructor(t){this.variableNames=["dy","W"],this.outputShape=t.inShape;let e=t.filterDepth,n=t.filterHeight,o=t.filterWidth,s=t.strideDepth,i=t.strideHeight,a=t.strideWidth,u=e-1-t.padInfo.front,l=n-1-t.padInfo.top,c=o-1-t.padInfo.left;this.userCode=`
const ivec3 pads = ivec3(${u}, ${l}, ${c});
void main() {
ivec5 coords = getOutputCoords();
int batch = coords.x;
int d1 = coords.u;
ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads;
int dyFCorner = dyCorner.x;
int dyRCorner = dyCorner.y;
int dyCCorner = dyCorner.z;
float dotProd = 0.0;
for (int wF = 0; wF < ${e}; wF++) {
float dyF = float(dyFCorner + wF) / ${s}.0;
if (dyF < 0.0 || dyF >= ${t.outDepth}.0 || fract(dyF) > 0.0) {
continue;
}
int idyF = int(dyF);
int wFPerm = ${e} - 1 - wF;
for (int wR = 0; wR < ${n}; wR++) {
float dyR = float(dyRCorner + wR) / ${i}.0;
if (dyR < 0.0 || dyR >= ${t.outHeight}.0 ||
fract(dyR) > 0.0) {
continue;
}
int idyR = int(dyR);
int wRPerm = ${n} - 1 - wR;
for (int wC = 0; wC < ${o}; wC++) {
float dyC = float(dyCCorner + wC) / ${a}.0;
if (dyC < 0.0 || dyC >= ${t.outWidth}.0 ||
fract(dyC) > 0.0) {
continue;
}
int idyC = int(dyC);
int wCPerm = ${o} - 1 - wC;
for (int d2 = 0; d2 < ${t.outChannels}; d2++) {
float xValue = getDy(batch, idyF, idyR, idyC, d2);
float wValue = getW(wFPerm, wRPerm, wCPerm, d1, d2);
dotProd += xValue * wValue;
}
}
}
}
setOutput(dotProd);
}
`}};function aet(r){let{inputs:t,backend:e,attrs:n}=r,{x:o,dy:s}=t,{strides:i,pad:a,dataFormat:u,dimRoundingMode:l,filterShape:c}=n,p=k.convertConv2DDataFormat(u),m=k.computeConv2DInfo(o.shape,c,i,1,a,l,!1,p),f=new aN(m);return e.runWebGLProgram(f,[o,s],"float32")}var BL={kernelName:mp,backendName:"webgl",kernelFunc:aet};function uet(r){let{inputs:t,backend:e,attrs:n}=r,{dy:o,filter:s}=t,{inputShape:i,strides:a,pad:u,dataFormat:l,dimRoundingMode:c}=n,p=k.convertConv2DDataFormat(l),m=k.computeConv2DInfo(i,s.shape,a,1,u,c,!1,p),f=new lN(m);return e.runWebGLProgram(f,[o,s],"float32")}var VL={kernelName:Jo,backendName:"webgl",kernelFunc:uet};function cet(r){let{inputs:t,backend:e,attrs:n}=r,{x:o,filter:s}=t,{strides:i,pad:a,dilations:u}=n,l=k.computeConv3DInfo(o.shape,s.shape,i,u,a),c=new sN(l);return e.runWebGLProgram(c,[o,s],"float32")}var GL={kernelName:Il,backendName:"webgl",kernelFunc:cet};function pet(r){let{inputs:t,backend:e,attrs:n}=r,{x:o,dy:s}=t,{strides:i,pad:a,filterShape:u}=n,l=k.computeConv3DInfo(o.shape,u,i,1,a),c=new uN(l);return e.runWebGLProgram(c,[o,s],"float32")}var WL={kernelName:fp,backendName:"webgl",kernelFunc:pet};function met(r){let{inputs:t,backend:e,attrs:n}=r,{dy:o,filter:s}=t,{pad:i,strides:a,inputShape:u}=n,l=k.computeConv3DInfo(u,s.shape,a,1,i),c=new cN(l);return e.runWebGLProgram(c,[o,s],"float32")}var UL={kernelName:dp,backendName:"webgl",kernelFunc:met};var fet=Fo+`
return cos(x);
`,det=Ct({opSnippet:fet}),HL={kernelName:Qo,backendName:"webgl",kernelFunc:det};var het=`
float e2x = exp(-x);
return (e2x + 1.0 / e2x) / 2.0;
`,get=Ct({opSnippet:het}),qL={kernelName:ts,backendName:"webgl",kernelFunc:get};var pN=class{constructor(t,e,n,o,s){this.variableNames=["Image","Boxes","BoxInd"],this.outputShape=[];let[i,a,u,l]=t,[c]=e,[p,m]=n;this.outputShape=[c,p,m,l];let f=o==="bilinear"?1:0,[d,h]=[`${a-1}.0`,`${u-1}.0`],[g,y,b]=p>1?[`${(a-1)/(p-1)}`,"(y2-y1) * height_ratio",`y1*${d} + float(y)*(height_scale)`]:["0.0","0.0",`0.5 * (y1+y2) * ${d}`],[w,v,I]=m>1?[`${(u-1)/(m-1)}`,"(x2-x1) * width_ratio",`x1*${h} + float(x)*(width_scale)`]:["0.0","0.0",`0.5 * (x1+x2) * ${h}`];this.userCode=`
const float height_ratio = float(${g});
const float width_ratio = float(${w});
void main() {
ivec4 coords = getOutputCoords();
int b = coords[0];
int y = coords[1];
int x = coords[2];
int d = coords[3];
// get box vals
float y1 = getBoxes(b,0);
float x1 = getBoxes(b,1);
float y2 = getBoxes(b,2);
float x2 = getBoxes(b,3);
// get image in batch index
int bInd = round(getBoxInd(b));
if(bInd < 0 || bInd >= ${i}) {
return;
}
float height_scale = ${y};
float width_scale = ${v};
float in_y = ${b};
if( in_y < 0.0 || in_y > ${d} ) {
setOutput(float(${s}));
return;
}
float in_x = ${I};
if( in_x < 0.0 || in_x > ${h} ) {
setOutput(float(${s}));
return;
}
vec2 sourceFracIndexCR = vec2(in_x,in_y);
if(${f} == 1) {
// Compute the four integer indices.
ivec2 sourceFloorCR = ivec2(sourceFracIndexCR);
ivec2 sourceCeilCR = ivec2(ceil(sourceFracIndexCR));
float topLeft = getImage(b, sourceFloorCR.y, sourceFloorCR.x, d);
float bottomLeft = getImage(b, sourceCeilCR.y, sourceFloorCR.x, d);
float topRight = getImage(b, sourceFloorCR.y, sourceCeilCR.x, d);
float bottomRight = getImage(b, sourceCeilCR.y, sourceCeilCR.x, d);
vec2 fracCR = sourceFracIndexCR - vec2(sourceFloorCR);
float top = topLeft + (topRight - topLeft) * fracCR.x;
float bottom = bottomLeft + (bottomRight - bottomLeft) * fracCR.x;
float newValue = top + (bottom - top) * fracCR.y;
setOutput(newValue);
} else {
// Compute the coordinators of nearest neighbor point.
ivec2 sourceNearestCR = ivec2(floor(
sourceFracIndexCR + vec2(0.5,0.5)));
float newValue = getImage(b, sourceNearestCR.y, sourceNearestCR.x, d);
setOutput(newValue);
}
}
`}};var xet=r=>{let{inputs:t,backend:e,attrs:n}=r,{image:o,boxes:s,boxInd:i}=t,{cropSize:a,method:u,extrapolationValue:l}=n,c=new pN(o.shape,s.shape,a,u,l);return e.runWebGLProgram(c,[o,s,i],"float32")},KL={kernelName:na,backendName:"webgl",kernelFunc:xet};var Ab=class{constructor(t,e,n){this.variableNames=["x"],this.customUniforms=[{name:"index",type:"float"}],this.outputShape=t;let o=t.length,s=e?"0.0":`getX(${jL(o,"coords")})`,i=t[t.length-1],a="",u="";e?(a=n?`end != ${i-1}`:"end != 0",u=n?"end + 1":"end - 1"):(a=n?`end + pow2 < ${i}`:"end >= pow2",u=n?"end + pow2":"end - pow2"),this.userCode=`
void main() {
${Ht(o)} coords = getOutputCoords();
int end = ${XL(o,"coords")};
float val = ${s};
int pow2 = int(pow(2.0, index));
if (${a}) {
int idx = ${u};
${XL(o,"coords")} = idx;
val += getX(${jL(o,"coords")});
}
setOutput(val);
}
`}};function jL(r,t){if(r===1)return`${t}`;if(r===2)return`${t}.x, ${t}.y`;if(r===3)return`${t}.x, ${t}.y, ${t}.z`;if(r===4)return`${t}.x, ${t}.y, ${t}.z, ${t}.w`;throw Error(`Cumulative sum for rank ${r} is not yet supported`)}function XL(r,t){if(r===1)return`${t}`;if(r===2)return`${t}.y`;if(r===3)return`${t}.z`;if(r===4)return`${t}.w`;throw Error(`Cumulative sum for rank ${r} is not yet supported`)}function yet(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{axis:s,exclusive:i,reverse:a}=n,u=o.shape.length,l=k.getAxesPermutation([s],u),c=o;l!=null&&(c=Le({inputs:{x:o},backend:e,attrs:{perm:l}}));let p=k.getInnerMostAxes(1,u)[0];if(p!==u-1)throw new Error(`WebGL cumsum shader expects an inner-most axis=${o.shape.length-1} but got axis=${s}`);let m=c.shape[p],f=er({inputs:{x:c},backend:e});for(let d=0;d<=Math.ceil(Math.log2(m))-1;d++){let h=new Ab(c.shape,!1,a),g=[[d]],y=f;f=e.runWebGLProgram(h,[f],f.dtype,g),e.disposeIntermediateTensorInfo(y)}if(i){let d=new Ab(c.shape,i,a),h=f;f=e.runWebGLProgram(d,[f],f.dtype),e.disposeIntermediateTensorInfo(h)}if(l!=null){let d=k.getUndoAxesPermutation(l),h=Le({inputs:{x:f},backend:e,attrs:{perm:d}});return e.disposeIntermediateTensorInfo(f),e.disposeIntermediateTensorInfo(c),h}return f}var YL={kernelName:es,backendName:"webgl",kernelFunc:yet};function bet(r){let{inputs:t,backend:e,attrs:n}=r,{x:o,weights:s}=t,{size:i,binaryOutput:a}=n;if(o.shape.length===1){let u=e.readSync(o.dataId),l=e.readSync(s.dataId),c=yb(u,l,s.dtype,s.shape,i);return e.makeTensorInfo([i],s.dtype,c)}else if(o.shape.length===2){let u=e.bufferSync(o),l=e.bufferSync(s),c=BP(u,l,i,a);return e.makeTensorInfo(c.shape,s.dtype,c.values)}throw new Error(`Error in denseBincount: input must be at most rank 2, but got rank${o.shape.length}.`)}var ZL={kernelName:hp,backendName:"webgl",kernelFunc:bet};var mN=class{constructor(t,e,n){this.variableNames=["x"],this.outputShape=[],this.outputShape=t,this.blockSize=e,this.dataFormat=n,this.userCode=`
void main() {
ivec4 coords = getOutputCoords();
int b = coords[0];
int h = ${this.getHeightCoordString()};
int w = ${this.getWidthCoordString()};
int d = ${this.getDepthCoordString()};
int in_h = h / ${e};
int offset_h = imod(h, ${e});
int in_w = w / ${e};
int offset_w = imod(w, ${e});
int offset_d = (offset_h * ${e} + offset_w) *
${this.getOutputDepthSize()};
int in_d = d + offset_d;
float result = ${this.getInputSamplingString()};
setOutput(result);
}
`}getHeightCoordString(){return this.dataFormat==="NHWC"?"coords[1]":"coords[2]"}getWidthCoordString(){return this.dataFormat==="NHWC"?"coords[2]":"coords[3]"}getDepthCoordString(){return this.dataFormat==="NHWC"?"coords[3]":"coords[1]"}getOutputDepthSize(){return this.dataFormat==="NHWC"?this.outputShape[3]:this.outputShape[1]}getInputSamplingString(){return this.dataFormat==="NHWC"?"getX(b, in_h, in_w, in_d)":"getX(b, in_d, in_h, in_w)"}};function wet(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{blockSize:s,dataFormat:i}=n,a=o.shape[0],u=i==="NHWC"?o.shape[1]:o.shape[2],l=i==="NHWC"?o.shape[2]:o.shape[3],c=i==="NHWC"?o.shape[3]:o.shape[1],p=u*s,m=l*s,f=c/(s*s),d=i==="NHWC"?[a,p,m,f]:[a,f,p,m],h=new mN(d,s,i);return e.runWebGLProgram(h,[o],o.dtype)}var JL={kernelName:oa,backendName:"webgl",kernelFunc:wet};var cg=class{constructor(t,e=!1,n=null,o=!1,s=!1){this.variableNames=["x","W"],this.customUniforms=[{name:"pads",type:"ivec2"},{name:"strides",type:"ivec2"},{name:"dilations",type:"ivec2"},{name:"inDims",type:"ivec2"}],this.outputShape=t.outShape,this.enableShapeUniforms=De(this.outputShape.length);let i=t.filterHeight,a=t.filterWidth,u=t.outChannels/t.inChannels,l="",c="";n&&(o?l=`float activation(float a) {
float b = getPreluActivationWeightsAtOutCoords();
${n}
}`:s?l=`float activation(float a) {
float b = getLeakyreluAlphaAtOutCoords();
${n}
}`:l=`
float activation(float x) {
${n}
}
`,c="result = activation(result);");let p=e?"result += getBiasAtOutCoords();":"";e&&this.variableNames.push("bias"),o&&this.variableNames.push("preluActivationWeights"),s&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
${l}
void main() {
ivec4 coords = getOutputCoords();
int batch = coords.x;
ivec2 xRCCorner = coords.yz * strides - pads;
int d2 = coords.w;
int d1 = d2 / ${u};
int q = d2 - d1 * ${u};
int xRCorner = xRCCorner.x;
int xCCorner = xRCCorner.y;
// Convolve x(?, ?, d1) with w(:, :, d1, q) to get y(yR, yC, d2).
// ? = to be determined. : = across all values in that axis.
float dotProd = 0.0;
// TO DO(dsmilkov): Flatten the two for loops and vec4 the operations.
for (int wR = 0; wR < ${i}; wR++) {
int xR = xRCorner + wR * dilations[0];
if (xR < 0 || xR >= inDims[0]) {
continue;
}
for (int wC = 0; wC < ${a}; wC++) {
int xC = xCCorner + wC * dilations[1];
if (xC < 0 || xC >= inDims[1]) {
continue;
}
float xVal = getX(batch, xR, xC, d1);
float wVal = getW(wR, wC, d1, q);
dotProd += xVal * wVal;
}
}
float result = dotProd;
${p}
${c}
setOutput(result);
}
`}};var pg=class{constructor(t,e=!1,n=null,o=!1,s=!1){this.variableNames=["x","W"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"pads",type:"ivec2"},{name:"strides",type:"ivec2"},{name:"dilations",type:"ivec2"},{name:"inDims",type:"ivec2"}],this.outputShape=t.outShape,this.enableShapeUniforms=De(this.outputShape.length);let i=t.outChannels/t.inChannels,a=t.padInfo.left,u=t.strideWidth,l=t.dilationWidth,c=t.filterHeight,p=t.filterWidth,m=p,f=`
int xR; int xC; int xCOffset;
vec4 wTexel; vec4 previous; vec4 final;`;for(let y=0;y<p;y++)f+=`
vec4 xTexelC${y*2};
int xTexelC${y*2}Ready;
vec4 xTexelC${y*2+1};
int xTexelC${y*2+1}Ready;
vec4 xC${y};`;f+=`
for (int r = 0; r < ${c}; r++) {
`;for(let y=0;y<p;y++)f+=`
xTexelC${y*2} = vec4(0.0);
xTexelC${y*2}Ready = 0;
xTexelC${y*2+1} = vec4(0.0);
xTexelC${y*2+1}Ready = 0;
xC${y} = vec4(0.0);`;f+=`
xR = xRCorner + r * dilations[0];
if (xR >=0 && xR < inDims[0]) {
`;for(let y=0;y<(m+1)/2;y++){let b=y*2;if(f+=`
xC = xCCorner + ${b*l};
`,u===1){if(b<p&&(a%2===1?(f+=`
xCOffset = xC + 1;
if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${b}Ready == 0) {
xTexelC${b} = getX(batch, xR, xCOffset, d1);
// Need to manually clear unused channels in case
// we're reading from recycled texture.
if (xCOffset + 1 >= inDims[1]) {
xTexelC${b}.zw = vec2(0.0);
}
xTexelC${b}Ready = 1;
}
`,l===1&&b>0?f+=`
xC${b} = vec4(xTexelC${b-2}.zw, xTexelC${b}.xy);
`:f+=`
xCOffset = xC + 1 - 2;
if (xCOffset >= 0 && xCOffset < inDims[1]) {
previous = getX(batch, xR, xCOffset, d1);
// Need to manually clear unused channels in case
// we're reading from recycled texture.
if (xCOffset + 1 >= inDims[1]) {
previous.zw = vec2(0.0);
}
xC${b} = vec4(previous.zw, xTexelC${b}.xy);
} else {
xC${b} = vec4(0.0, 0.0, xTexelC${b}.xy);
}
`):f+=`
if (xC >= 0 && xC < inDims[1] && xTexelC${b}Ready == 0) {
xTexelC${b} = getX(batch, xR, xC, d1);
if (xC + 1 >= inDims[1]) {
xTexelC${b}.zw = vec2(0.0);
}
xTexelC${b}Ready = 1;
}
xC${b} = xTexelC${b};
`,b+1<p)){let w=a%2===0?x.nearestLargerEven(l):l;l%2===0&&a%2===1||l%2!==0&&a%2!==1?(f+=`
xCOffset = xC + imod(pads[1], 2) + ${w};
if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${b+1}Ready == 0) {
xTexelC${b+1} = getX(batch, xR, xCOffset, d1);
// Need to manually clear unused channels in case
// we're reading from recycled texture.
if (xCOffset + 1 >= inDims[1]) {
xTexelC${b+1}.zw = vec2(0.0);
}
xTexelC${b+1}Ready = 1;
}
`,l>1&&(f+=`
xCOffset -= 2;
if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${b}Ready == 0) {
xTexelC${b} = getX(batch, xR, xCOffset, d1);
xTexelC${b}Ready = 1;
}
`),f+=`
xC${b+1} = vec4(xTexelC${b}.zw, xTexelC${b+1}.xy);
`):w===1?f+=`
xC${b+1} = xTexelC${b};
`:f+=`
xCOffset = xC + ${w};
if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${b+1}Ready == 0) {
xTexelC${b+1} = getX(batch, xR, xCOffset, d1);
if (xCOffset + 1 >= inDims[1]) {
xTexelC${b+1}.zw = vec2(0.0);
}
xTexelC${b+1}Ready = 1;
}
xC${b+1} = xTexelC${b+1};
`}}else b<p&&(a%2===1?(f+=`
xCOffset = xC + 1 - strides[1];
if(xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${b}Ready == 0) {
xTexelC${b} = getX(batch, xR, xCOffset, d1);
// Need to manually clear unused channels in case
// we're reading from recycled texture.
if (xCOffset + 1 >= inDims[1]) {
xTexelC${b}.zw = vec2(0.0);
}
xTexelC${b}Ready = 1;
}
if(xC + 1 >= 0 && xC + 1 < inDims[1] && xTexelC${b+1}Ready == 0) {
xTexelC${b+1} = getX(batch, xR, xC + 1, d1);
// Need to manually clear unused channels in case
// we're reading from recycled texture.
if (xC + 2 >= inDims[1]) {
xTexelC${b+1}.zw = vec2(0.0);
}
xTexelC${b+1}Ready = 1;
}
xC${b} = vec4(xTexelC${b}.zw, xTexelC${b+1}.zw);
`,b+1<p&&(f+=`
final = vec4(0.0);
xCOffset = xC + 1 + strides[1];
if(xCOffset >= 0 && xCOffset < inDims[1]) {
final = getX(batch, xR, xCOffset, d1);
}
xC${b+1} = vec4(xTexelC${b+1}.xy, final.xy);
`)):(f+=`
if(xC >= 0 && xC < inDims[1] && xTexelC${b}Ready == 0) {
xTexelC${b} = getX(batch, xR, xC, d1);
if (xC + 1 >= inDims[1]) {
xTexelC${b}.zw = vec2(0.0);
}
xTexelC${b}Ready = 1;
}
xCOffset = xC + strides[1];
if(xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${b+1}Ready == 0) {
xTexelC${b+1} = getX(batch, xR, xCOffset, d1);
if (xCOffset + 1 >= inDims[1]) {
xTexelC${b+1}.zw = vec2(0.);
}
xTexelC${b+1}Ready = 1;
}
xC${b} = vec4(
xTexelC${b}.xy, xTexelC${b+1}.xy);
`,b+1<p&&(f+=`
xC${b+1} = vec4(xTexelC${b}.zw, xTexelC${b+1}.zw);
`)));b<p&&(f+=`
wTexel = getW(r, ${b}, d1, q);
dotProd += xC${b} * vec4(wTexel.xz, wTexel.xz);
`,b+1<p&&(f+=`
wTexel = getW(r, ${b+1}, d1, q);
dotProd += xC${b+1} * vec4(wTexel.xz, wTexel.xz);
`))}f+=`
}
`,f+=`
}
`;let d="",h="";n&&(o?d=`vec4 activation(vec4 a) {
vec4 b = getPreluActivationWeightsAtOutCoords();
${n}
}`:s?d=`vec4 activation(vec4 a) {
vec4 b = getLeakyreluAlphaAtOutCoords();
${n}
}`:d=`vec4 activation(vec4 x) {
${n}
}`,h="result = activation(result);");let g=e?"result += getBiasAtOutCoords();":"";e&&this.variableNames.push("bias"),o&&this.variableNames.push("preluActivationWeights"),s&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
${d}
void main() {
ivec4 coords = getOutputCoords();
int batch = coords.x;
ivec2 xRCCorner = coords.yz * strides - pads;
int d2 = coords.w;
int d1 = d2 / ${i};
int q = d2 - d1 * ${i};
int xRCorner = xRCCorner.x;
int xCCorner = xRCCorner.y;
//intialize dotProd with a small epsilon seems to reduce GPU accuracy loss.
vec4 dotProd = vec4(0.000000000000001);
${f}
vec4 result = dotProd - vec4(0.000000000000001);
${g}
${h}
setOutput(result);
}
`}};function vet(r){let{inputs:t,backend:e,attrs:n}=r,{x:o,filter:s}=t,{strides:i,pad:a,dilations:u,dimRoundingMode:l}=n,c=u;c==null&&(c=[1,1]),x.assert(k.eitherStridesOrDilationsAreOne(i,c),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${i} and dilations '${c}'`);let p=k.computeConv2DInfo(o.shape,s.shape,i,c,a,l,!0),m;G().getBool("WEBGL_PACK_DEPTHWISECONV")&&p.strideWidth<=2&&p.outChannels/p.inChannels===1?m=new pg(p):m=new cg(p);let f=[[p.padInfo.top,p.padInfo.left],[p.strideHeight,p.strideWidth],[p.dilationHeight,p.dilationWidth],[p.inHeight,p.inWidth]];return e.runWebGLProgram(m,[o,s],"float32",f)}var QL={kernelName:rs,backendName:"webgl",kernelFunc:vet};var fN=class{constructor(t){this.variableNames=["x","dy"],this.outputShape=t.filterShape;let e=t.strideHeight,n=t.strideWidth,o=t.padInfo.top,s=t.padInfo.left,i=t.outChannels/t.inChannels;this.userCode=`
void main() {
ivec4 coords = getOutputCoords();
int wR = coords.x;
int wC = coords.y;
int d1 = coords.z;
int dm = coords.w;
int d2 = d1 * ${i} + dm;
float dotProd = 0.0;
// TO DO: Vec4 over the batch size
for (int b = 0; b < ${t.batchSize}; b++) {
for (int yR = 0; yR < ${t.outHeight}; yR++) {
int xR = wR + yR * ${e} - ${o};
if (xR < 0 || xR >= ${t.inHeight}) {
continue;
}
for (int yC = 0; yC < ${t.outWidth}; yC++) {
int xC = wC + yC * ${n} - ${s};
if (xC < 0 || xC >= ${t.inWidth}) {
continue;
}
float dyValue = getDy(b, yR, yC, d2);
float xValue = getX(b, xR, xC, d1);
dotProd += (xValue * dyValue);
}
}
}
setOutput(dotProd);
}
`}},dN=class{constructor(t){this.variableNames=["dy","W"],this.outputShape=t.inShape;let e=t.filterHeight,n=t.filterWidth,o=t.strideHeight,s=t.strideWidth,i=e-1-t.padInfo.top,a=n-1-t.padInfo.left,u=t.outChannels/t.inChannels;this.userCode=`
const ivec2 pads = ivec2(${i}, ${a});
void main() {
ivec4 coords = getOutputCoords();
int batch = coords[0];
int d1 = coords[3];
ivec2 dyCorner = coords.yz - pads;
int dyRCorner = dyCorner.x;
int dyCCorner = dyCorner.y;
float dotProd = 0.0;
for (int wR = 0; wR < ${e}; wR++) {
float dyR = float(dyRCorner + wR) / ${o}.0;
if (dyR < 0.0 || dyR >= ${t.outHeight}.0 || fract(dyR) > 0.0) {
continue;
}
int idyR = int(dyR);
int wRPerm = ${e} - 1 - wR;
for (int wC = 0; wC < ${n}; wC++) {
float dyC = float(dyCCorner + wC) / ${s}.0;
if (dyC < 0.0 || dyC >= ${t.outWidth}.0 ||
fract(dyC) > 0.0) {
continue;
}
int idyC = int(dyC);
int wCPerm = ${n} - 1 - wC;
// TO DO: Vec4 over the channelMul
for (int dm = 0; dm < ${u}; dm++) {
int d2 = d1 * ${u} + dm;
float xValue = getDy(batch, idyR, idyC, d2);
float wValue = getW(wRPerm, wCPerm, d1, dm);
dotProd += xValue * wValue;
}
}
}
setOutput(dotProd);
}
`}};function Cet(r){let{inputs:t,backend:e,attrs:n}=r,{x:o,dy:s}=t,{strides:i,dilations:a,pad:u,dimRoundingMode:l,filterShape:c}=n,p=k.computeConv2DInfo(o.shape,c,i,a,u,l,!0),m=new fN(p);return e.runWebGLProgram(m,[o,s],"float32")}var tz={kernelName:gp,backendName:"webgl",kernelFunc:Cet};function Iet(r){let{inputs:t,backend:e,attrs:n}=r,{dy:o,filter:s}=t,{strides:i,dilations:a,pad:u,dimRoundingMode:l,inputShape:c}=n,p=k.computeConv2DInfo(c,s.shape,i,a,u,l,!0),m=new dN(p);return e.runWebGLProgram(m,[o,s],"float32")}var ez={kernelName:xp,backendName:"webgl",kernelFunc:Iet};var hN=class{constructor(t){this.variableNames=["X"],this.outputShape=[t,t],this.userCode=`
void main() {
ivec2 coords = getOutputCoords();
float val = coords[0] == coords[1] ? getX(coords[0]) : 0.0;
setOutput(val);
}
`}};function ket(r){let{inputs:t,backend:e}=r,{x:n}=t,o=[...n.shape,...n.shape],s=x.sizeFromShape(n.shape),i=ut({inputs:{x:n},backend:e,attrs:{shape:[s]}}),a=new hN(s),u=e.runWebGLProgram(a,[i],i.dtype),l=ut({inputs:{x:u},backend:e,attrs:{shape:o}});return e.disposeIntermediateTensorInfo(i),e.disposeIntermediateTensorInfo(u),l}var rz={kernelName:yp,backendName:"webgl",kernelFunc:ket};var gN=class{constructor(t){this.variableNames=["x","W"],this.outputShape=t.outShape;let{inHeight:e,inWidth:n,padInfo:o,strideHeight:s,strideWidth:i,filterHeight:a,filterWidth:u,dilationHeight:l,dilationWidth:c}=t,{top:p,left:m}=o;this.userCode=`
const ivec2 strides = ivec2(${s}, ${i});
const ivec2 pads = ivec2(${p}, ${m});
const float neg_infinity = -3.4e38;
void main() {
ivec4 coords = getOutputCoords();
int batch = coords.x;
int d1 = coords.w;
ivec2 outTopLeftCorner =
coords.yz * strides - pads;
int hBeg = outTopLeftCorner.x;
int wBeg = outTopLeftCorner.y;
float curVal = neg_infinity;
for (int h = 0; h < ${a}; h++) {
int hIn = hBeg + h * ${l};
if (hIn >= 0 && hIn < ${e}) {
for (int w = 0; w < ${u}; w++) {
int wIn = wBeg + w * ${c};
if (wIn >= 0 && wIn < ${n}) {
float xVal = getX(batch, hIn, wIn, d1);
float wVal = getW(h, w, d1);
float val = xVal + wVal;
if (val > curVal) {
curVal = val;
}
}
}
}
}
float result = curVal;
setOutput(result);
}
`}};function Net(r){let{inputs:t,backend:e,attrs:n}=r,{x:o,filter:s}=t,{strides:i,pad:a,dilations:u}=n,l=k.computeDilation2DInfo(o.shape,s.shape,i,a,"NHWC",u),c,p=new gN(l);c=e.runWebGLProgram(p,[o,s],"float32");let m=ut({inputs:{x:c},backend:e,attrs:{shape:l.outShape}});return e.disposeIntermediateTensorInfo(c),m}var nz={kernelName:Sl,backendName:"webgl",kernelFunc:Net};function Tet(r){let{inputs:t,backend:e,attrs:n}=r,{equation:o}=n,s=t,{allDims:i,summedDims:a,idDims:u}=k.decodeEinsumEquation(o,s.length);k.checkEinsumDimSizes(i.length,u,s);let{path:l,steps:c}=k.getEinsumComputePath(a,u),p=c.length,m=null,f=i.length,d=[];for(let h=0;h<p;++h){for(let g of c[h]){let{permutationIndices:y,expandDims:b}=k.getEinsumPermutation(f,u[g]),w;k.isIdentityPermutation(y)?w=s[g]:(w=Le({inputs:{x:s[g]},backend:e,attrs:{perm:y}}),d.push(w));let v=w.shape.slice();for(let I=0;I<b.length;++I)v.splice(b[I],0,1);x.arraysEqual(w.shape,v)||(w=ut({inputs:{x:w},backend:e,attrs:{shape:v}}),d.push(w)),m===null?m=w:(m=lg({inputs:{a:w,b:m},backend:e}),d.push(m))}h<p-1&&(l[h]>=0&&(m=Oc({inputs:{x:m},backend:e,attrs:{axis:l[h]-(i.length-f),keepDims:!1}}),d.push(m)),f--)}for(let h of d)h!==m&&e.disposeIntermediateTensorInfo(h);return m}var oz={kernelName:bp,backendName:"webgl",kernelFunc:Tet};var _et="return (x >= 0.0) ? x : (exp(x) - 1.0);",Eet=`
vec4 result;
result.r = (x.r >= 0.0) ? x.r : (exp(x.r) - 1.0);
result.g = (x.g >= 0.0) ? x.g : (exp(x.g) - 1.0);
result.b = (x.b >= 0.0) ? x.b : (exp(x.b) - 1.0);
result.a = (x.a >= 0.0) ? x.a : (exp(x.a) - 1.0);
return result;
`,Aet=Ct({opSnippet:_et,packedOpSnippet:Eet}),sz={kernelName:os,backendName:"webgl",kernelFunc:Aet};var Det="return (b >= 1.0) ? a : a * (b + 1.0);",$et=`
vec4 bGTEZero = vec4(greaterThanEqual(b, vec4(0.)));
return (bGTEZero * a) + ((vec4(1.0) - bGTEZero) * (a * (b + vec4(1.0))));
`,Ret=r=>{let{inputs:t,backend:e}=r,{dy:n,y:o}=t,s=G().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new ui($et,n.shape,o.shape):new Ro(Det,n.shape,o.shape);return e.runWebGLProgram(s,[n,o],n.dtype)},iz={kernelName:wp,backendName:"webgl",kernelFunc:Ret};var Fet=`
return vec4(equal(a, b));
`,Oet="return float(a == b);",Pet=le({opSnippet:Oet,packedOpSnippet:Fet,dtype:"bool",cpuKernelImpl:WP}),az={kernelName:ia,backendName:"webgl",kernelFunc:Pet};var Met=`
// Error function is calculated approximately with elementary function.
// See "Handbook of Mathematical Functions with Formulas,
// Graphs, and Mathematical Tables", Abramowitz and Stegun.
float p = ${k.ERF_P};
float a1 = ${k.ERF_A1};
float a2 = ${k.ERF_A2};
float a3 = ${k.ERF_A3};
float a4 = ${k.ERF_A4};
float a5 = ${k.ERF_A5};
float sign = sign(x);
x = abs(x);
float t = 1.0 / (1.0 + p * x);
return sign * (1.0 - (((((a5*t + a4)*t) + a3)*t + a2)*t + a1)*t*exp(-x*x));
`,Let=Ct({opSnippet:Met}),lz={kernelName:sa,backendName:"webgl",kernelFunc:Let};var zet=Fo+`
return exp(x);
`,Bet=`
vec4 result = exp(x);
bvec4 isNaN = isnan(x);
result.r = isNaN.r ? x.r : result.r;
result.g = isNaN.g ? x.g : result.g;
result.b = isNaN.b ? x.b : result.b;
result.a = isNaN.a ? x.a : result.a;
return result;
`,xN=Ct({opSnippet:zet,packedOpSnippet:Bet,cpuKernelImpl:UP,dtype:"float32"}),uz={kernelName:ss,backendName:"webgl",kernelFunc:xN};function Db(r){let{inputs:t,attrs:e,backend:n}=r,{dim:o}=e,{input:s}=t,i=s.shape.length,a=s.shape.slice(),u=o;return o<0&&(x.assert(-(i+1)<=o,()=>`Axis must be in the interval [${-(i+1)}, ${i}]`),u=i+o+1),a.splice(u,0,1),ut({inputs:{x:s},backend:n,attrs:{shape:a}})}var cz={kernelName:xi,backendName:"webgl",kernelFunc:Db};var pz="return exp(x) - 1.0;",Vet=Ct({opSnippet:pz,packedOpSnippet:pz,cpuKernelImpl:HP}),mz={kernelName:aa,backendName:"webgl",kernelFunc:Vet};var $b=class{constructor(t,e,n){this.variableNames=["real","imag"];let o=e[1];this.outputShape=e;let s=n?`2.0 * ${Math.PI}`:`-2.0 * ${Math.PI}`,i=n?`${o}.0`:"1.0",a;if(t==="real")a="return real * expR - imag * expI;";else if(t==="imag")a="return real * expI + imag * expR;";else throw new Error(`FFT component must be either "real" or "imag", got ${t}.`);this.userCode=`
const float exponentMultiplier = ${s};
float unaryOpComplex(float real, float expR, float imag, float expI) {
${a}
}
float mulMatDFT(int batch, int index) {
float indexRatio = float(index) / float(${o});
float exponentMultiplierTimesIndexRatio =
exponentMultiplier * indexRatio;
float result = 0.0;
for (int i = 0; i < ${o}; i++) {
// x = (-2|2 * PI / N) * index * i;
float x = exponentMultiplierTimesIndexRatio * float(i);
float expR = cos(x);
float expI = sin(x);
float real = getReal(batch, i);
float imag = getImag(batch, i);
result +=
unaryOpComplex(real, expR, imag, expI) / ${i};
}
return result;
}
void main() {
ivec2 coords = getOutputCoords();
setOutput(mulMatDFT(coords[0], coords[1]));
}
`}};function Rb(r,t,e){let n=e.texData.get(r.dataId),o=x.sizeFromShape(r.shape),s=r.shape[r.shape.length-1],i=o/s,a=ut({inputs:{x:r},backend:e,attrs:{shape:[i,s]}}),u=a.shape,l=new $b("real",u,t),c=new $b("imag",u,t),p=[{dataId:n.complexTensorInfos.real.dataId,dtype:n.complexTensorInfos.real.dtype,shape:u},{dataId:n.complexTensorInfos.imag.dataId,dtype:n.complexTensorInfos.imag.dtype,shape:u}],m=e.runWebGLProgram(l,p,"float32"),f=e.runWebGLProgram(c,p,"float32"),d=Dn({inputs:{real:m,imag:f},backend:e});e.disposeIntermediateTensorInfo(m),e.disposeIntermediateTensorInfo(f);let h=ut({inputs:{x:d},backend:e,attrs:{shape:r.shape}});return e.disposeIntermediateTensorInfo(a),e.disposeIntermediateTensorInfo(d),h}function Get(r){let{inputs:t,backend:e}=r,{input:n}=t;return Rb(n,!1,e)}var fz={kernelName:vp,backendName:"webgl",kernelFunc:Get};var yN=class{constructor(t,e){this.outputShape=[],this.customUniforms=[{name:"value",type:"float"}],this.variableNames=["x"],this.outputShape=t,this.userCode=`
void main() {
// Input can be obtained from uniform value.
setOutput(value);
}
`}};function fl(r){let{backend:t,attrs:e}=r,{shape:n,value:o}=e,{dtype:s}=e;if(s=s||x.inferDtype(o),s==="string"){let i=x.getArrayFromDType(s,x.sizeFromShape(n));return i.fill(o),t.makeTensorInfo(n,s,i)}else{let i=new yN(n,o),a=[[o]];return t.runWebGLProgram(i,[],s,a)}}var dz={kernelName:kl,backendName:"webgl",kernelFunc:fl};var bN=class{constructor(t){this.variableNames=["Image"],this.outputShape=[];let e=t[2];this.outputShape=t,this.userCode=`
void main() {
ivec4 coords = getOutputCoords();
int x = coords[2];
int coordX = ${e} - x - 1;
float outputValue;
if(coordX >= 0 && coordX < ${e}) {
outputValue = getImage(coords[0], coords[1], coordX, coords[3]);
} else {
outputValue = getImage(coords[0], coords[1], coords[2], coords[3]);
}
setOutput(outputValue);
}
`}};var hz={kernelName:la,backendName:"webgl",kernelFunc:({inputs:r,backend:t})=>{let{image:e}=r,n=t,o=new bN(e.shape);return n.runWebGLProgram(o,[e],e.dtype)}};var gz="return floor(x);",Wet=Ct({opSnippet:gz,packedOpSnippet:gz,cpuKernelImpl:qP}),xz={kernelName:is,backendName:"webgl",kernelFunc:Wet};var Uet=`
float s = sign(a) * sign(b);
int ia = round(a);
int ib = round(b);
if (ib != 0) {
// Windows (D3D) wants guaranteed non-zero int division at compile-time.
return float(idiv(ia, ib, s));
} else {
return NAN;
}
`,Het=`
ivec4 ia = round(a);
ivec4 ib = round(b);
bvec4 cond = notEqual(ib, ivec4(0));
ivec4 result = ivec4(0);
vec4 s = sign(a) * sign(b);
// Windows (D3D) wants guaranteed non-zero int division at compile-time.
if (cond[0]) {
result[0] = idiv(ia[0], ib[0], s[0]);
}
if (cond[1]) {
result[1] = idiv(ia[1], ib[1], s[1]);
}
if (cond[2]) {
result[2] = idiv(ia[2], ib[2], s[2]);
}
if (cond[3]) {
result[3] = idiv(ia[3], ib[3], s[3]);
}
return vec4(result);
`,qet=le({opSnippet:Uet,packedOpSnippet:Het,dtype:"int32"}),yz={kernelName:as,backendName:"webgl",kernelFunc:qet};var wN=class{constructor(t){this.variableNames=["A"];let e=He(),[n,o]=t;this.outputShape=t,this.userCode=`
void main() {
ivec3 coords = getOutputCoords();
int texR = coords[0];
int texC = coords[1];
int depth = coords[2];
vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${o}.0, ${n}.0);
vec4 values = ${e.texture2D}(A, uv);
float value;
if (depth == 0) {
value = values.r;
} else if (depth == 1) {
value = values.g;
} else if (depth == 2) {
value = values.b;
} else if (depth == 3) {
value = values.a;
}
setOutput(floor(value * 255.0 + 0.5));
}
`}};var vN=class{constructor(t){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0;let e=He(),[n,o]=t;this.outputShape=t,this.userCode=`
void main() {
ivec3 coords = getOutputCoords();
int texR = coords[0];
int texC = coords[1];
int depth = coords[2];
vec4 result = vec4(0.);
for(int row=0; row<=1; row++) {
for(int col=0; col<=1; col++) {
texC = coords[1] + row;
depth = coords[2] + col;
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${o}.0, ${n}.0);
vec4 values = ${e.texture2D}(A, uv);
float value;
if (depth == 0) {
value = values.r;
} else if (depth == 1) {
value = values.g;
} else if (depth == 2) {
value = values.b;
} else if (depth == 3) {
value = values.a;
}
result[row * 2 + col] = floor(value * 255.0 + 0.5);
}
}
${e.output} = result;
}
`}};var bz={kernelName:bf,backendName:"webgl",kernelFunc:Ket},Jm;function Ket(r){let{inputs:t,backend:e,attrs:n}=r,{pixels:o}=t,{numChannels:s}=n,i=typeof HTMLVideoElement!="undefined"&&o instanceof HTMLVideoElement,a=typeof HTMLImageElement!="undefined"&&o instanceof HTMLImageElement,[u,l]=i?[o.videoWidth,o.videoHeight]:[o.width,o.height],c=[l,u],p=[l,u,s];(a||i)&&(Jm==null&&(Jm=document.createElement("canvas").getContext("2d")),Jm.canvas.width=u,Jm.canvas.height=l,Jm.drawImage(o,0,0,u,l),o=Jm.canvas);let m=e.makeTensorInfo(c,"int32");e.texData.get(m.dataId).usage=Ur.PIXELS,e.gpgpu.uploadPixelDataToTexture(e.getTexture(m.dataId),o);let f=G().getBool("WEBGL_PACK")?new vN(p):new wN(p),d=e.runWebGLProgram(f,[m],"int32");return e.disposeData(m.dataId),d}function jet(r){let{inputs:t,backend:e,attrs:n}=r,{x:o,filter:s,bias:i,preluActivationWeights:a}=t,{strides:u,pad:l,dataFormat:c,dilations:p,dimRoundingMode:m,activation:f,leakyreluAlpha:d}=n,h=k.convertConv2DDataFormat(c),g=k.computeConv2DInfo(o.shape,s.shape,u,p,l,m,!1,h),y,b=[];if(g.filterHeight===1&&g.filterWidth===1&&g.dilationHeight===1&&g.dilationWidth===1&&g.strideHeight===1&&g.strideWidth===1&&(g.padInfo.type==="SAME"||g.padInfo.type==="VALID"))y=_b({x:o,filter:s,convInfo:g,backend:e,bias:i,activation:f,preluActivationWeights:a,leakyreluAlpha:d});else if(G().getBool("WEBGL_CONV_IM2COL")&&o.shape[0]===1)y=Eb({x:o,filter:s,convInfo:g,backend:e,bias:i,activation:f,preluActivationWeights:a,leakyreluAlpha:d});else{let v=i!=null,I=a!=null,E=f==="leakyrelu",D=f?iu(f,!1):null,$=new ug(g,v,D,I,E),R=[o,s];if(i&&R.push(i),a&&R.push(a),E){let M=e.makeTensorInfo([],"float32",x.createScalarValue(d,"float32"));R.push(M),b.push(M)}y=e.runWebGLProgram($,R,"float32")}let w=ut({inputs:{x:y},backend:e,attrs:{shape:g.outShape}});return b.push(y),b.forEach(v=>e.disposeIntermediateTensorInfo(v)),w}var wz={kernelName:Ai,backendName:"webgl",kernelFunc:jet};function Xet(r){let{inputs:t,backend:e,attrs:n}=r,{x:o,filter:s,bias:i,preluActivationWeights:a}=t,{strides:u,pad:l,dilations:c,dimRoundingMode:p,activation:m,leakyreluAlpha:f}=n,d=[],h=c;h==null&&(h=[1,1]),x.assert(k.eitherStridesOrDilationsAreOne(u,h),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${u} and dilations '${h}'`);let g=k.computeConv2DInfo(o.shape,s.shape,u,h,l,p,!0),y=G().getBool("WEBGL_PACK_DEPTHWISECONV")&&g.strideWidth<=2&&g.outChannels/g.inChannels===1,b=m?iu(m,y):null,w=[o,s],v=i!=null,I=a!=null,E=m==="leakyrelu";if(v&&w.push(i),I&&w.push(a),E){let M=e.makeTensorInfo([],"float32",x.createScalarValue(f,"float32"));w.push(M),d.push(M)}let D;y?D=new pg(g,v,b,I,E):D=new cg(g,v,b,I,E);let $=[[g.padInfo.top,g.padInfo.left],[g.strideHeight,g.strideWidth],[g.dilationHeight,g.dilationWidth],[g.inHeight,g.inWidth]],R=e.runWebGLProgram(D,w,"float32",$);return d.forEach(M=>e.disposeIntermediateTensorInfo(M)),R}var vz={kernelName:Di,backendName:"webgl",kernelFunc:Xet};var CN=class{constructor(t,e,n){this.sliceDim=t,this.strides=e,this.variableNames=["x","indices"],this.outputShape=n;let o=Ht(e.length),s=Ht(n.length),i=this.sliceDim>1?"strides[j]":"strides";this.userCode=`
${o} strides = ${o}(${this.strides});
void main() {
${s} coords = getOutputCoords();
int flattenIndex = 0;
for (int j = 0; j < ${this.sliceDim}; j++) {
int index = round(getIndices(coords[0], j));
flattenIndex += index * ${i};
}
setOutput(getX(flattenIndex, coords[1]));
}
`}};function Yet(r){let{inputs:t,backend:e}=r,{params:n,indices:o}=t,s=o.shape,i=s[s.length-1],a=x.sizeFromShape(n.shape),[u,l,c,p]=k.prepareAndValidate(n,o),m=ut({inputs:{x:o},backend:e,attrs:{shape:[l,i]}}),f=ut({inputs:{x:n},backend:e,attrs:{shape:[x.sizeFromShape(n.shape)/c,c]}});if(e.shouldExecuteOnCPU([n,o])||n.dtype==="string"){let y=e.readSync(o.dataId),b=e.bufferSync(n),w=KP(y,b,n.dtype,l,i,c,p,n.shape,a);return e.makeTensorInfo(u,n.dtype,w.values)}let d=new CN(i,p,[l,c]),h=e.runWebGLProgram(d,[f,m],f.dtype),g=ut({inputs:{x:h},backend:e,attrs:{shape:u}});return e.disposeIntermediateTensorInfo(m),e.disposeIntermediateTensorInfo(f),e.disposeIntermediateTensorInfo(h),g}var Cz={kernelName:ua,backendName:"webgl",kernelFunc:Yet};var IN=class{constructor(t,e){this.variableNames=["A","indices"],this.outputShape=e,this.rank=e.length;let n=Ht(this.rank),o=Zet(t,2);this.userCode=`
void main() {
${n} resRC = getOutputCoords();
int index = int(getIndices(resRC.x, resRC.z));
float inBounds = (index >= 0) && (index < ${t[2]}) ? 1.0 : 0.0;
setOutput(inBounds * getA(${o}));
}
`}};function Zet(r,t){let e=["resRC.x","resRC.y","resRC.z","resRC.w"],n=[];for(let o=0;o<r.length;o++)o===2?n.push("index"):n.push(`${e[o]}`);return n.join()}function SN(r){let{inputs:t,backend:e,attrs:n}=r,{x:o,indices:s}=t,{axis:i,batchDims:a}=n,u=x.parseAxisParam(i,o.shape)[0];if(G().get("DEBUG")){let b=e.readSync(s.dataId),w=o.shape[u];for(let v=0;v<b.length;++v){let I=b[v];x.assert(I<=w-1&&I>=0,()=>`GatherV2: the index value ${I} is not in [0, ${w-1}]`)}}let l=k.segment_util.collectGatherOpShapeInfo(o,s,u,a),c=x.sizeFromShape(s.shape),p=[],m=ut({inputs:{x:o},backend:e,attrs:{shape:[l.batchSize,l.outerSize,l.dimSize,l.sliceSize]}}),f=ut({inputs:{x:s},backend:e,attrs:{shape:[l.batchSize,c/l.batchSize]}});p.push(m),p.push(f);let d=[l.batchSize,l.outerSize,c/l.batchSize,l.sliceSize];if(e.shouldExecuteOnCPU([o,s])||o.dtype==="string"){let b=e.bufferSync(f),w=e.bufferSync(m),v=jP(w,b,d);return p.forEach(I=>e.disposeIntermediateTensorInfo(I)),e.makeTensorInfo(l.outputShape,v.dtype,v.values)}let h=new IN(m.shape,d),g=e.runWebGLProgram(h,[m,f],m.dtype);p.push(g);let y=ut({inputs:{x:g},backend:e,attrs:{shape:l.outputShape}});return p.forEach(b=>e.disposeIntermediateTensorInfo(b)),y}var Iz={kernelName:yi,backendName:"webgl",kernelFunc:SN};var Jet="return float(a > b);",Qet=`
return vec4(greaterThan(a, b));
`,trt=le({opSnippet:Jet,packedOpSnippet:Qet,cpuKernelImpl:XP,dtype:"bool"}),Sz={kernelName:ca,backendName:"webgl",kernelFunc:trt};var ert="return float(a >= b);",rrt=`
return vec4(greaterThanEqual(a, b));
`,nrt=le({opSnippet:ert,packedOpSnippet:rrt,dtype:"bool",cpuKernelImpl:YP}),kz={kernelName:us,backendName:"webgl",kernelFunc:nrt};function ort(r){let{inputs:t,backend:e}=r,{input:n}=t;return Rb(n,!0,e)}var Nz={kernelName:Cp,backendName:"webgl",kernelFunc:ort};var srt="return float(!isnan(x) && !isinf(x));",irt=Ct({opSnippet:srt,dtype:"bool"}),Tz={kernelName:pa,backendName:"webgl",kernelFunc:irt};var art="return float(isinf(x));",lrt=Ct({opSnippet:art,dtype:"bool"}),_z={kernelName:ma,backendName:"webgl",kernelFunc:lrt};var urt="return float(isnan(x));",crt=Ct({opSnippet:urt,dtype:"bool"}),Ez={kernelName:fa,backendName:"webgl",kernelFunc:crt};var prt="return float(a < b);",mrt=`
return vec4(lessThan(a, b));
`,frt=le({opSnippet:prt,packedOpSnippet:mrt,cpuKernelImpl:ZP,dtype:"bool"}),Az={kernelName:da,backendName:"webgl",kernelFunc:frt};var drt="return float(a <= b);",hrt=`
return vec4(lessThanEqual(a, b));
`,grt=le({opSnippet:drt,packedOpSnippet:hrt,cpuKernelImpl:JP,dtype:"bool"}),Dz={kernelName:ha,backendName:"webgl",kernelFunc:grt};function xrt(r){let{backend:t,attrs:e}=r,{start:n,stop:o,num:s}=e,i=QP(n,o,s);return t.makeTensorInfo([i.length],"float32",i)}var $z={kernelName:Sp,backendName:"webgl",kernelFunc:xrt};var yrt=Fo+`
return x < 0.0 ? 0./0. : log(x);
`,brt=`
vec4 result = log(x);
bvec4 isNaN = isnan(x);
result.r = isNaN.r ? x.r : (x.r < 0.0 ? 0./0. : result.r);
result.g = isNaN.g ? x.g : (x.g < 0.0 ? 0./0. : result.g);
result.b = isNaN.b ? x.b : (x.b < 0.0 ? 0./0. : result.b);
result.a = isNaN.a ? x.a : (x.a < 0.0 ? 0./0. : result.a);
return result;
`,wrt=Ct({opSnippet:yrt,packedOpSnippet:brt,cpuKernelImpl:tM}),Rz={kernelName:ps,backendName:"webgl",kernelFunc:wrt};var vrt=Fo+`
return log(1.0 + x);
`,Crt=Ct({opSnippet:vrt}),Fz={kernelName:ga,backendName:"webgl",kernelFunc:Crt};var Irt="return float(a >= 1.0 && b >= 1.0);",Srt=`
return vec4(
vec4(greaterThanEqual(a, vec4(1.0))) *
vec4(greaterThanEqual(b, vec4(1.0))));
`,krt=le({opSnippet:Irt,packedOpSnippet:Srt,dtype:"bool"}),Oz={kernelName:xa,backendName:"webgl",kernelFunc:krt};var Nrt="return float(!(x >= 1.0));",Trt=Ct({opSnippet:Nrt}),Pz={kernelName:bu,backendName:"webgl",kernelFunc:Trt};var _rt="return float(a >= 1.0 || b >= 1.0);",Ert=`
return min(
vec4(greaterThanEqual(a, vec4(1.0))) +
vec4(greaterThanEqual(b, vec4(1.0))),
vec4(1.0));
`,Art=le({opSnippet:_rt,packedOpSnippet:Ert,dtype:"bool"}),Mz={kernelName:wu,backendName:"webgl",kernelFunc:Art};var kN=class{constructor(t,e,n,o,s){this.variableNames=["x"],this.outputShape=[];let i=e,a=t[3]-1;this.outputShape=t;let u,l=`float(${n}) + float(${o}) * sum`;s===.5?u=`inversesqrt(${l})`:s===1?u=`1.0/(${l})`:u=`exp(log(${l}) * float(-${s}));`,this.userCode=`
void main() {
ivec4 coords = getOutputCoords();
int b = coords[0];
int r = coords[1];
int c = coords[2];
int d = coords[3];
float x = getX(b, r, c, d);
float sum = 0.0;
for (int j = -${i}; j <= ${i}; j++) {
int idx = d + j;
if (idx >= 0 && idx <= ${a}) {
float z = getX(b, r, c, idx);
sum += z * z;
}
}
float val = x * ${u};
setOutput(val);
}
`}};var NN=class{constructor(t,e,n,o,s){this.variableNames=["x"],this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0;let i=e,a=t[3]-1;this.outputShape=t;let u,l=`float(${n}) + float(${o}) * sum`;s===.5?u=`inversesqrt(${l})`:s===1?u=`1.0/(${l})`:u=`exp(log(${l}) * float(-${s}));`,this.userCode=`
void main() {
ivec4 coords = getOutputCoords();
int b = coords.x;
int r = coords.y;
int c = coords.z;
int d = coords.w;
bool hasNextCol = d < ${this.outputShape[3]};
bool hasNextRow = c < ${this.outputShape[2]};
vec4 sum = vec4(0.);
vec4 xFragAtOutputCoords = getX(b, r, c, d);
vec4 xAtOutputCoords = vec4(
getChannel(xFragAtOutputCoords, vec2(c, d)),
hasNextCol ?
getChannel(xFragAtOutputCoords, vec2(c, d + 1)) : 0.0,
hasNextRow ?
getChannel(xFragAtOutputCoords , vec2(c + 1, d)) : 0.0,
(hasNextRow && hasNextCol) ?
getChannel(xFragAtOutputCoords, vec2(c + 1, d + 1)) : 0.0
);
int firstChannel = d - ${i};
vec2 cache = vec2(0.);
if(firstChannel >= 0){
vec4 firstChannelFrag = getX(b, r, c, firstChannel);
cache.x = getChannel(firstChannelFrag, vec2(c, firstChannel));
if(hasNextRow){
cache.y = getChannel(firstChannelFrag, vec2(c + 1, firstChannel));
}
}
ivec2 depth = ivec2(d, d + 1);
for (int j = - ${i}; j <= ${i}; j++) {
ivec2 idx = depth + j;
bvec2 aboveLowerBound = greaterThanEqual(idx, ivec2(0));
bvec2 belowUpperBound = lessThanEqual(idx, ivec2(${a}));
bool depthInRange = aboveLowerBound.x && belowUpperBound.x;
bool depthPlusOneInRange = aboveLowerBound.y && belowUpperBound.y;
if(depthInRange || depthPlusOneInRange){
vec4 z = vec4(0.);
vec4 xFragAtCurrentDepth;
z.xz = cache.xy;
if(depthPlusOneInRange && hasNextCol){
xFragAtCurrentDepth = idx.y != d ?
getX(b, r, c, idx.y) : xFragAtOutputCoords;
z.y = getChannel(xFragAtCurrentDepth, vec2(c, idx.y));
if(hasNextRow){
z.w = getChannel(xFragAtCurrentDepth, vec2(c + 1, idx.y));
}
}
cache.xy = z.yw;
sum += z * z;
}
}
vec4 result = xAtOutputCoords * ${u};
setOutput(result);
}
`}};var Drt=r=>{let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{depthRadius:s,bias:i,alpha:a,beta:u}=n,l=G().getBool("WEBGL_PACK_NORMALIZATION")?new NN(o.shape,s,i,a,u):new kN(o.shape,s,i,a,u);return e.runWebGLProgram(l,[o],o.dtype)},Lz={kernelName:Nl,backendName:"webgl",kernelFunc:Drt};var TN=class{constructor(t,e,n,o,s){this.variableNames=["inputImage","outputImage","dy"],this.outputShape=[],this.outputShape=t,this.depth=t[3],this.depthRadius=e,this.bias=n,this.alpha=o,this.beta=s,this.userCode=`
void main() {
ivec4 coords = getOutputCoords();
int b = coords[0];
int r = coords[1];
int c = coords[2];
float result = 0.0;
for (int d = 0; d < ${this.depth}; ++d) {
int depthBegin = int(max(0.0, float(d - ${e})));
int depthEnd = int(min(float(${this.depth}),
float(d + ${e} + 1)));
const int MIN_DEPTH_BEGIN = 0;
const int MAX_DEPTH_END = ${this.depth};
float norm = 0.0;
for (int k = MIN_DEPTH_BEGIN; k < MAX_DEPTH_END; ++k) {
if (k < depthBegin){
continue;
}
else if (k >= depthBegin && k < depthEnd) {
norm += getInputImage(b, r, c, k) * getInputImage(b, r, c, k);
}
else {
break;
}
}
norm = float(${o}) * norm + float(${n});
for(int k = MIN_DEPTH_BEGIN; k < MAX_DEPTH_END; ++k){
if (k < depthBegin){
continue;
}
else if (k >= depthBegin && k < depthEnd){
float dyi = -2.0 * float(${o})
* float(${s})
* getInputImage(b ,r ,c, k) * getOutputImage(b, r, c, d)
/ norm;
if (k == d) {
dyi += pow(norm, -1.0 * ${s});
}
if (k == coords[3]) {
dyi *= getDy(b, r, c, d);
result += dyi;
}
}
else {
break;
}
}
}
setOutput(result);
}
`}};var $rt=r=>{let{inputs:t,backend:e,attrs:n}=r,{x:o,y:s,dy:i}=t,{depthRadius:a,bias:u,alpha:l,beta:c}=n,p=new TN(o.shape,a,u,l,c);return e.runWebGLProgram(p,[o,s,i],o.dtype)},zz={kernelName:kp,backendName:"webgl",kernelFunc:$rt};function Bz(r,t,e,n){let o=x.sizeFromShape(t),i=x.sizeFromShape(r.shape)/o,a=ut({inputs:{x:r},attrs:{shape:[i,o]},backend:n}),u=Wn(a,r.dtype,"max",n),l=ut({inputs:{x:u},attrs:{shape:e},backend:n});return n.disposeIntermediateTensorInfo(a),n.disposeIntermediateTensorInfo(u),l}function _N(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{reductionIndices:s,keepDims:i}=n,a=o.shape.length,u=x.parseAxisParam(s,o.shape),l=u,c=k.getAxesPermutation(l,a),p=c!=null,m=e.shouldExecuteOnCPU([o]),f=o;if(p){if(m){let w=e.texData.get(f.dataId).values,v=new Array(a);for(let D=0;D<v.length;D++)v[D]=o.shape[c[D]];let I=$c(w,o.shape,o.dtype,c,v);f=e.makeTensorInfo(v,o.dtype);let E=e.texData.get(f.dataId);E.values=I}else f=au(o,c,e);l=k.getInnerMostAxes(l.length,a)}k.assertAxesAreInnerMostDims("max",l,a);let[d,h]=k.computeOutAndReduceShapes(f.shape,l),g=d;i&&(g=k.expandShapeToKeepDim(d,u));let y;if(m){let w=e.texData.get(f.dataId).values,v=eM(w,x.sizeFromShape(h),g,o.dtype);y=e.makeTensorInfo(g,o.dtype);let I=e.texData.get(y.dataId);I.values=v}else y=Bz(f,h,g,e);return p&&e.disposeIntermediateTensorInfo(f),y}var Vz={kernelName:ms,backendName:"webgl",kernelFunc:_N};var Rrt=Cb+`
return max(a, b);
`,Frt=`
vec4 result = vec4(max(a, b));
vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
`+su+`
return result;
`,Ort=le({opSnippet:Rrt,packedOpSnippet:Frt,cpuKernelImpl:rM}),Gz={kernelName:fs,backendName:"webgl",kernelFunc:Ort};function Prt(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t;ai(o,"maxPool");let{filterSize:s,strides:i,pad:a,dimRoundingMode:u}=n,l=1;x.assert(k.eitherStridesOrDilationsAreOne(i,l),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${i} and dilations '${l}'`);let c=k.computePool2DInfo(o.shape,s,i,l,a,u);if(c.filterWidth===1&&c.filterHeight===1&&x.arraysEqual(c.inShape,c.outShape))return er({inputs:{x:o},backend:e});let p=new Hi(c,"max",!1);return e.runWebGLProgram(p,[o],o.dtype)}var Wz={kernelName:ds,backendName:"webgl",kernelFunc:Prt};function Mrt(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{filterSize:s,strides:i,pad:a,dataFormat:u,dimRoundingMode:l}=n,c=[1,1,1],p=k.computePool3DInfo(o.shape,s,i,c,a,l,u),m=new Mc(p,"max",!1);return e.runWebGLProgram(m,[o],o.dtype)}var Uz={kernelName:Tl,backendName:"webgl",kernelFunc:Mrt};var EN=class{constructor(t){this.variableNames=["dy","maxPos"],this.outputShape=t.inShape;let e=t.strideHeight,n=t.strideWidth,o=t.dilationHeight,s=t.effectiveFilterHeight,i=t.effectiveFilterWidth,a=s-1-t.padInfo.top,u=i-1-t.padInfo.left,l=s*i-1;this.userCode=`
const ivec2 pads = ivec2(${a}, ${u});
void main() {
ivec4 coords = getOutputCoords();
int b = coords[0];
int d = coords[3];
ivec2 dyRCCorner = coords.yz - pads;
int dyRCorner = dyRCCorner.x;
int dyCCorner = dyRCCorner.y;
// Convolve dy(?, ?, d) with pos mask(:, :, d) to get dx(xR, xC, d).
// ? = to be determined. : = across all values in that axis.
float dotProd = 0.0;
for (int wR = 0; wR < ${s};
wR += ${o}) {
float dyR = float(dyRCorner + wR) / ${e}.0;
if (dyR < 0.0 || dyR >= ${t.outHeight}.0 || fract(dyR) > 0.0) {
continue;
}
int idyR = int(dyR);
for (int wC = 0; wC < ${i}; wC++) {
float dyC = float(dyCCorner + wC) / ${n}.0;
if (dyC < 0.0 || dyC >= ${t.outWidth}.0 ||
fract(dyC) > 0.0) {
continue;
}
int idyC = int(dyC);
float dyValue = getDy(b, idyR, idyC, d);
int maxPosValue = ${l} - int(getMaxPos(b, idyR, idyC, d));
// Get the current value, check it against the value from the
// position matrix.
int curPosValue = wR * ${i} + wC;
float mask = float(maxPosValue == curPosValue ? 1.0 : 0.0);
dotProd += dyValue * mask;
}
}
setOutput(dotProd);
}
`}},AN=class{constructor(t){this.variableNames=["dy","maxPos"],this.outputShape=t.inShape;let e=t.strideDepth,n=t.strideHeight,o=t.strideWidth,s=t.dilationDepth,i=t.dilationHeight,a=t.dilationWidth,u=t.effectiveFilterDepth,l=t.effectiveFilterHeight,c=t.effectiveFilterWidth,p=u-1-t.padInfo.front,m=l-1-t.padInfo.top,f=c-1-t.padInfo.left,d=u*l*c-1;this.userCode=`
const ivec3 pads = ivec3(${p}, ${m}, ${f});
void main() {
ivec5 coords = getOutputCoords();
int batch = coords.x;
int ch = coords.u;
ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads;
int dyDCorner = dyCorner.x;
int dyRCorner = dyCorner.y;
int dyCCorner = dyCorner.z;
// Convolve dy(?, ?, ?, ch) with pos mask(:, :, :, d) to get
// dx(xD, xR, xC, ch).
// ? = to be determined. : = across all values in that axis.
float dotProd = 0.0;
for (int wD = 0; wD < ${u};
wD += ${s}) {
float dyD = float(dyDCorner + wD) / ${e}.0;
if (dyD < 0.0 || dyD >= ${t.outDepth}.0 || fract(dyD) > 0.0) {
continue;
}
int idyD = int(dyD);
for (int wR = 0; wR < ${l};
wR += ${i}) {
float dyR = float(dyRCorner + wR) / ${n}.0;
if (dyR < 0.0 || dyR >= ${t.outHeight}.0 ||
fract(dyR) > 0.0) {
continue;
}
int idyR = int(dyR);
for (int wC = 0; wC < ${c};
wC += ${a}) {
float dyC = float(dyCCorner + wC) / ${o}.0;
if (dyC < 0.0 || dyC >= ${t.outWidth}.0 ||
fract(dyC) > 0.0) {
continue;
}
int idyC = int(dyC);
float dyValue = getDy(batch, idyD, idyR, idyC, ch);
int maxPosValue = ${d} -
int(getMaxPos(batch, idyD, idyR, idyC, ch));
// Get the current value, check it against the value from the
// position matrix.
int curPosValue =
wD * ${l} * ${c} +
wR * ${c} + wC;
float mask = float(maxPosValue == curPosValue ? 1.0 : 0.0);
dotProd += dyValue * mask;
}
}
}
setOutput(dotProd);
}
`}};function Lrt(r){let{inputs:t,backend:e,attrs:n}=r,{dy:o,input:s}=t,i=s,{filterSize:a,strides:u,pad:l,dimRoundingMode:c}=n,p=[1,1,1],m=k.computePool3DInfo(i.shape,a,u,p,l,c),f=new Mc(m,"max",!0),d=e.runWebGLProgram(f,[i],i.dtype),h=new AN(m),g=e.runWebGLProgram(h,[o,d],i.dtype);return e.disposeIntermediateTensorInfo(d),g}var Hz={kernelName:Tp,backendName:"webgl",kernelFunc:Lrt};function zrt(r){let{inputs:t,backend:e,attrs:n}=r,{dy:o,input:s,output:i}=t,a=s;ai([s,i],"maxPoolGrad");let{filterSize:u,strides:l,pad:c,dimRoundingMode:p}=n,m=k.computePool2DInfo(a.shape,u,l,1,c,p),f=!0,d=new Hi(m,"max",f),h=e.runWebGLProgram(d,[a],a.dtype),g=new EN(m),y=e.runWebGLProgram(g,[o,h],a.dtype);return e.disposeIntermediateTensorInfo(h),y}var qz={kernelName:Np,backendName:"webgl",kernelFunc:zrt};function Kz(r,t,e,n){let o=new Hi(e,"max",!1),s=n.runWebGLProgram(o,[r],"float32");o=new Hi(e,"max",!0,!0,t);let i=n.runWebGLProgram(o,[r],"float32");return[s,i]}var jz={kernelName:_p,backendName:"webgl",kernelFunc:({inputs:r,attrs:t,backend:e})=>{let{x:n}=r,{filterSize:o,strides:s,pad:i,includeBatchInIndex:a}=t,u=e;x.assert(n.shape.length===4,()=>`Error in maxPool: input must be rank 4 but got rank ${n.shape.length}.`);let l=[1,1];x.assert(k.eitherStridesOrDilationsAreOne(s,l),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${s} and dilations '${l}'`);let c=k.computePool2DInfo(n.shape,o,s,l,i),[p,m]=Kz(n,a,c,u);return[p,m]}};function Xz(r,t,e,n){let o=x.sizeFromShape(t),i=x.sizeFromShape(r.shape)/o,a=ut({inputs:{x:r},attrs:{shape:[i,o]},backend:n}),u=Wn(a,"float32","mean",n),l=ut({inputs:{x:u},attrs:{shape:e},backend:n});return n.disposeIntermediateTensorInfo(a),n.disposeIntermediateTensorInfo(u),l}var Yz={kernelName:hs,backendName:"webgl",kernelFunc:({inputs:r,attrs:t,backend:e})=>{let{x:n}=r,{keepDims:o,axis:s}=t,i=e,a=n.shape.length,u=x.parseAxisParam(s,n.shape),l=u,c=k.getAxesPermutation(l,a),p=c!=null,m=i.shouldExecuteOnCPU([n]),f=[],d=n;if(p){if(m){let v=i.texData.get(d.dataId).values,I=new Array(a);for(let $=0;$<I.length;$++)I[$]=n.shape[c[$]];let E=$c(v,n.shape,n.dtype,c,I);d=i.makeTensorInfo(I,n.dtype);let D=i.texData.get(d.dataId);D.values=E}else d=au(n,c,i);f.push(d),l=k.getInnerMostAxes(l.length,a)}k.assertAxesAreInnerMostDims("sum",l,a);let[h,g]=k.computeOutAndReduceShapes(d.shape,l),y=h;o&&(y=k.expandShapeToKeepDim(h,u));let b=Xz(d,g,y,i);for(let w of f)i.disposeIntermediateTensorInfo(w);return b}};function Brt(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{axis:s,keepDims:i}=n,a=o.shape.length,u=x.parseAxisParam(s,o.shape),l=u,c=k.getAxesPermutation(l,a),p=o;c!=null&&(p=Le({inputs:{x:o},backend:e,attrs:{perm:c}}),l=k.getInnerMostAxes(l.length,o.shape.length)),k.assertAxesAreInnerMostDims("min",l,a);let[m,f]=k.computeOutAndReduceShapes(p.shape,l),d=x.sizeFromShape(f),h=ut({inputs:{x:p},backend:e,attrs:{shape:[-1,d]}}),g=Wn(h,h.dtype,"min",e),y;if(i){let b=k.expandShapeToKeepDim(m,u);y=ut({inputs:{x:g},backend:e,attrs:{shape:b}})}else y=ut({inputs:{x:g},backend:e,attrs:{shape:m}});return e.disposeIntermediateTensorInfo(h),e.disposeIntermediateTensorInfo(g),c!=null&&e.disposeIntermediateTensorInfo(p),y}var Zz={kernelName:gs,backendName:"webgl",kernelFunc:Brt};var Vrt=Cb+`
return min(a, b);
`,Grt=`
vec4 result = vec4(min(a, b));
vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
`+su+`
return result;
`,Wrt=le({opSnippet:Vrt,packedOpSnippet:Grt,cpuKernelImpl:nM}),Jz={kernelName:xs,backendName:"webgl",kernelFunc:Wrt};var DN=class{constructor(t,e,n){this.variableNames=["x"],this.outputShape=e.map((c,p)=>c[0]+t[p]+c[1]);let o=t.length,s=Ht(o),i=e.map(c=>c[0]).join(","),a=e.map((c,p)=>c[0]+t[p]).join(","),u=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,o),l=n==="reflect"?0:1;if(o===1){this.userCode=`
int start = ${i};
int end = ${a};
void main() {
int outC = getOutputCoords();
if (outC < start) {
outC = start * 2 - outC - ${l};
} else if(outC >= end) {
outC = (end - 1) * 2 - outC + ${l};
}
setOutput(getX(outC - start));
}
`;return}this.userCode=`
${s} start = ${s}(${i});
${s} end = ${s}(${a});
void main() {
${s} outC = getOutputCoords();
for (int i = 0; i < ${o}; i++) {
if (outC[i] < start[i]) {
outC[i] = start[i] * 2 - outC[i] - ${l};
} else if(outC[i] >= end[i]) {
outC[i] = (end[i] - 1) * 2 - outC[i] + ${l};
}
}
${s} coords = outC - start;
setOutput(getX(${u}));
}
`}};var $N=class{constructor(t,e,n){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e.map((d,h)=>d[0]+t[h]+d[1]);let o=t.length,s=Ht(o),i=e.map(d=>d[0]).join(","),a=e.map((d,h)=>d[0]+t[h]).join(","),u=tr("rc",o),l=tr("source",o),c=`${u[o-1]} < ${this.outputShape[o-1]}`,p=o===1?"source":`vec2(${l.slice(-2).join()})`,m=n==="reflect"?0:1,f="";if(o===1){let d=`
${s} source = rc;
if (source < start) {
source = start * 2 - source - ${m};
} else if (source >= end) {
source = (end - 1) * 2 - source + ${m};
}
source -= start;
`;f=`
${s} rc = outputLoc;
${d}
result[0] = getChannel(getX(${l.join()}), ${p});
${u[o-1]} += 1;
if(${c}) {
${d}
result[1] = getChannel(getX(${l.join()}), ${p});
}
`}else{let d=`
${s} source = rc;
${s} lt = ${s}(lessThan(source, start));
${s} gte = ${s}(greaterThanEqual(source, end));
${s} orig = 1 - (lt + gte);
source = orig * source +
lt * (start * 2 - source - ${m}) +
gte * ((end - 1) * 2 - source + ${m});
source -= start;
`;f=`
${s} rc = outputLoc;
${d}
result[0] = getChannel(getX(${l.join()}), ${p});
${u[o-1]} += 1;
if(${c}) {
${d}
result[1] = getChannel(getX(${l.join()}), ${p});
}
rc = outputLoc;
${u[o-2]} += 1;
if(${u[o-2]} < ${this.outputShape[o-2]}) {
${d}
result[2] = getChannel(getX(${l.join()}), ${p});
${u[o-1]} += 1;
if(${c}) {
${d}
result[3] = getChannel(getX(${l.join()}), ${p});
}
}
`}this.userCode=`
const ${s} start = ${s}(${i});
const ${s} end = ${s}(${a});
void main() {
${s} outputLoc = getOutputCoords();
vec4 result = vec4(0.);
${f}
setOutput(result);
}
`}};var Urt=({inputs:r,backend:t,attrs:e})=>{let{x:n}=r,{paddings:o,mode:s}=e,i=G().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new $N(n.shape,o,s):new DN(n.shape,o,s);return t.runWebGLProgram(i,[n],n.dtype)},Qz={kernelName:ys,backendName:"webgl",kernelFunc:Urt};var Hrt=`if (b == 0.0) return NAN;
return mod(a, b);`,qrt=`
vec4 result = mod(a, b);
vec4 isNaN = vec4(equal(b, vec4(0.0)));
`+su+`
return result;
`,Krt=le({opSnippet:Hrt,packedOpSnippet:qrt}),t3={kernelName:ya,backendName:"webgl",kernelFunc:Krt};var RN=class{constructor(t,e,n){this.variableNames=["probs"],this.customUniforms=[{name:"seed",type:"float"}],this.outputShape=[t,n],this.userCode=`
void main() {
ivec2 coords = getOutputCoords();
int batch = coords[0];
float r = random(seed);
float cdf = 0.0;
for (int i = 0; i < ${e-1}; i++) {
cdf += getProbs(batch, i);
if (r < cdf) {
setOutput(float(i));
return;
}
}
// If no other event happened, last event happened.
setOutput(float(${e-1}));
}
`}};var jrt=`
if (a == b) {
return 1.0;
};
return a / b;`,Xrt=`
// 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;
`,FN=le({opSnippet:jrt,packedOpSnippet:Xrt,checkOutOfBounds:!0}),e3={kernelName:ns,backendName:"webgl",kernelFunc:FN};var r3="return a - b;",ON=le({opSnippet:r3,packedOpSnippet:r3,supportsComplex:!0,cpuKernelImpl:bM}),n3={kernelName:Ps,backendName:"webgl",kernelFunc:ON};function PN(r){let{inputs:t,backend:e,attrs:n}=r,{logits:o}=t,{dim:s}=n,i=x.parseAxisParam([s],o.shape),a=_N({inputs:{x:o},backend:e,attrs:{reductionIndices:i,keepDims:!1}}),u=k.expandShapeToKeepDim(a.shape,i),l=ut({inputs:{x:a},backend:e,attrs:{shape:u}}),c=ON({inputs:{a:o,b:l},backend:e}),p=xN({inputs:{x:c},backend:e}),m=Oc({inputs:{x:p},backend:e,attrs:{axis:i,keepDims:!1}}),f=ut({inputs:{x:m},backend:e,attrs:{shape:u}}),d=FN({inputs:{a:p,b:f},backend:e});return e.disposeIntermediateTensorInfo(a),e.disposeIntermediateTensorInfo(l),e.disposeIntermediateTensorInfo(c),e.disposeIntermediateTensorInfo(p),e.disposeIntermediateTensorInfo(m),e.disposeIntermediateTensorInfo(f),d}var o3={kernelName:Fs,backendName:"webgl",kernelFunc:PN};function Yrt(r){let{inputs:t,backend:e,attrs:n}=r,{logits:o}=t,{numSamples:s,seed:i,normalized:a}=n,u=a?o:PN({inputs:{logits:o},backend:e,attrs:{dim:o.shape.length-1}}),l=u.shape[0],c=u.shape[1],p=new RN(l,c,s),m=[[i]],f=e.runWebGLProgram(p,[u],"int32",m);return a||e.disposeIntermediateTensorInfo(u),f}var s3={kernelName:Ep,backendName:"webgl",kernelFunc:Yrt};var Zrt=dr+`
return -x;
`,Jrt=`
vec4 result = -x;
bvec4 isNaN = isnan(x);
result.r = isNaN.r ? x.r : result.r;
result.g = isNaN.g ? x.g : result.g;
result.b = isNaN.b ? x.b : result.b;
result.a = isNaN.a ? x.a : result.a;
return result;
`;function Qrt(r){let{inputs:t,backend:e}=r,{x:n}=t;if(e.shouldExecuteOnCPU([n])){let s=e.texData.get(n.dataId),[i,a]=sM(s.values,n.shape,n.dtype);return e.makeTensorInfo(a,n.dtype,i)}let o;return G().getBool("WEBGL_PACK_UNARY_OPERATIONS")?o=new $o(n.shape,Jrt):o=new wn(n.shape,Zrt),e.runWebGLProgram(o,[n],n.dtype)}var i3={kernelName:bi,backendName:"webgl",kernelFunc:Qrt};var tnt=Vr.nonMaxSuppressionV3Impl;function ent(r){k.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:e,attrs:n}=r,{boxes:o,scores:s}=t,{maxOutputSize:i,iouThreshold:a,scoreThreshold:u}=n,l=e.readSync(o.dataId),c=e.readSync(s.dataId),{selectedIndices:p}=tnt(l,c,i,a,u);return e.makeTensorInfo([p.length],"int32",new Int32Array(p))}var a3={kernelName:wa,backendName:"webgl",kernelFunc:ent};var rnt=Vr.nonMaxSuppressionV4Impl;function nnt(r){k.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:e,attrs:n}=r,{boxes:o,scores:s}=t,{maxOutputSize:i,iouThreshold:a,scoreThreshold:u,padToMaxOutputSize:l}=n,c=e.readSync(o.dataId),p=e.readSync(s.dataId),{selectedIndices:m,validOutputs:f}=rnt(c,p,i,a,u,l);return[e.makeTensorInfo([m.length],"int32",new Int32Array(m)),e.makeTensorInfo([],"int32",new Int32Array([f]))]}var l3={kernelName:va,backendName:"webgl",kernelFunc:nnt};var ont=Vr.nonMaxSuppressionV5Impl;function snt(r){k.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:e,attrs:n}=r,{boxes:o,scores:s}=t,{maxOutputSize:i,iouThreshold:a,scoreThreshold:u,softNmsSigma:l}=n,c=e.readSync(o.dataId),p=e.readSync(s.dataId),m=i,f=a,d=u,h=l,{selectedIndices:g,selectedScores:y}=ont(c,p,m,f,d,h);return[e.makeTensorInfo([g.length],"int32",new Int32Array(g)),e.makeTensorInfo([y.length],"float32",new Float32Array(y))]}var u3={kernelName:Ca,backendName:"webgl",kernelFunc:snt};var MN=class{constructor(t,e,n,o){this.variableNames=["indices"],this.outputShape=[t,e],this.userCode=`
void main() {
ivec2 coords = getOutputCoords();
int index = round(getIndices(coords.x));
setOutput(mix(float(${o}), float(${n}),
float(index == coords.y)));
}
`}};var int=r=>{let{inputs:t,backend:e,attrs:n}=r,{indices:o}=t,{depth:s,onValue:i,offValue:a}=n,u=x.sizeFromShape(o.shape),l=new MN(u,s,i,a),c=ut({inputs:{x:o},backend:e,attrs:{shape:[u]}}),p=e.runWebGLProgram(l,[c],o.dtype);e.disposeIntermediateTensorInfo(c);let m=[...o.shape,s],f=ut({inputs:{x:p},backend:e,attrs:{shape:m}});return e.disposeIntermediateTensorInfo(p),f},c3={kernelName:ws,backendName:"webgl",kernelFunc:int};function mg(r){let{inputs:t,backend:e}=r,{x:n}=t;if(n.dtype==="complex64"){let o=ml({inputs:{input:n},backend:e}),s=mg({inputs:{x:o},backend:e}),i=Lc({inputs:{input:n},backend:e}),a=mg({inputs:{x:i},backend:e}),u=Dn({inputs:{real:s,imag:a},backend:e});return e.disposeIntermediateTensorInfo(o),e.disposeIntermediateTensorInfo(s),e.disposeIntermediateTensorInfo(i),e.disposeIntermediateTensorInfo(a),u}else return fl({attrs:{shape:n.shape,dtype:n.dtype,value:n.dtype==="string"?"":0},backend:e})}var p3={kernelName:_i,backendName:"webgl",kernelFunc:mg};function m3(r){let{inputs:t,backend:e}=r,{x:n}=t;if(n.dtype==="string")throw new Error("onesLike is not supported under string dtype");if(n.dtype==="complex64"){let o=ml({inputs:{input:n},backend:e}),s=m3({inputs:{x:o},backend:e}),i=Lc({inputs:{input:n},backend:e}),a=mg({inputs:{x:i},backend:e}),u=Dn({inputs:{real:s,imag:a},backend:e});return e.disposeIntermediateTensorInfo(o),e.disposeIntermediateTensorInfo(s),e.disposeIntermediateTensorInfo(i),e.disposeIntermediateTensorInfo(a),u}else return fl({attrs:{shape:n.shape,dtype:n.dtype,value:1},backend:e})}var f3={kernelName:wi,backendName:"webgl",kernelFunc:m3};function ant(r){let{inputs:t,backend:e,attrs:n}=r,{axis:o}=n;if(t.length===1)return Db({inputs:{input:t[0]},backend:e,attrs:{dim:o}});let s=t[0].shape,i=t[0].dtype;t.forEach(c=>{x.assertShapesMatch(s,c.shape,"All tensors passed to stack must have matching shapes"),x.assert(i===c.dtype,()=>"All tensors passed to stack must have matching dtypes")});let a=[],u=t.map(c=>{let p=Db({inputs:{input:c},backend:e,attrs:{dim:o}});return a.push(p),p}),l=oN({inputs:u,backend:e,attrs:{axis:o}});return a.forEach(c=>e.disposeIntermediateTensorInfo(c)),l}var d3={kernelName:vi,backendName:"webgl",kernelFunc:ant};var LN=class{constructor(t,e,n){this.variableNames=["x"],this.customUniforms=[{name:"value",type:"float"}],this.outputShape=e.map((l,c)=>l[0]+t[c]+l[1]);let o=t.length,s=Ht(o),i=e.map(l=>l[0]).join(","),a=e.map((l,c)=>l[0]+t[c]).join(","),u=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,o);if(o===1){this.userCode=`
int start = ${i};
int end = ${a};
void main() {
int outC = getOutputCoords();
if (outC < start || outC >= end) {
setOutput(value);
} else {
setOutput(getX(outC - start));
}
}
`;return}this.userCode=`
${s} start = ${s}(${i});
${s} end = ${s}(${a});
void main() {
${s} outC = getOutputCoords();
if (any(lessThan(outC, start)) || any(greaterThanEqual(outC, end))) {
setOutput(value);
} else {
${s} coords = outC - start;
setOutput(getX(${u}));
}
}
`}};var zN=class{constructor(t,e,n){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"value",type:"float"}],this.outputShape=e.map((h,g)=>h[0]+t[g]+h[1]);let o=t.length,s=Ht(o),i=e.map(h=>h[0]).join(","),a=e.map((h,g)=>h[0]+t[g]).join(","),u=tr("rc",o),l=tr("source",o),c=`${u[o-1]} < ${this.outputShape[o-1]}`,p=o===1?"source":`vec2(${l.slice(-2).join()})`,m=[`${s} rc = outputLoc;`,`${u[o-1]} += 1;
if(${c}) {
`,o===1?"":`}
rc = outputLoc;
${u[o-2]} += 1;
if(${u[o-2]} < ${this.outputShape[o-2]}) {`,o===1?"":` ${u[o-1]} += 1;
if(${c}) {`],f=o===1?"rc < start || rc >= end":"any(lessThan(rc, start)) || any(greaterThanEqual(rc, end))",d="";for(let h=0,g=o===1?2:4;h<g;h++)d+=`
${m[h]}
if (${f}) {
result[${h}] = float(value);
} else {
${s} source = rc - start;
result[${h}] = getChannel(getX(${l.join()}), ${p});
}
`;d+=o===1?"} ":"}}",this.userCode=`
const ${s} start = ${s}(${i});
const ${s} end = ${s}(${a});
void main() {
${s} outputLoc = getOutputCoords();
vec4 result = vec4(0.);
${d}
setOutput(result);
}
`}};var BN=r=>{let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{paddings:s,constantValue:i}=n;if(x.sizeFromShape(o.shape)===0){let l=s.map((c,p)=>c[0]+o.shape[p]+c[1]);return fl({backend:e,attrs:{shape:l,value:i,dtype:o.dtype}})}let a=G().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new zN(o.shape,s,i):new LN(o.shape,s,i),u=[[i]];return e.runWebGLProgram(a,[o],o.dtype,u)},h3={kernelName:vs,backendName:"webgl",kernelFunc:BN};var lnt=`
if(a < 0.0 && floor(b) < b){
return NAN;
}
if (b == 0.0) {
return 1.0;
}
return (round(mod(b, 2.0)) != 1) ?
pow(abs(a), b) : sign(a) * pow(abs(a), b);
`,unt=`
// isModRound1 has 1 for components with round(mod(b, 2.0)) == 1, 0 otherwise.
vec4 isModRound1 = vec4(equal(round(mod(b, 2.0)), ivec4(1)));
vec4 multiplier = sign(a) * isModRound1 + (vec4(1.0) - isModRound1);
vec4 result = multiplier * pow(abs(a), b);
// Ensure that a^0 = 1, including 0^0 = 1 as this correspond to TF and JS
bvec4 isExpZero = equal(b, vec4(0.0));
result.r = isExpZero.r ? 1.0 : result.r;
result.g = isExpZero.g ? 1.0 : result.g;
result.b = isExpZero.b ? 1.0 : result.b;
result.a = isExpZero.a ? 1.0 : result.a;
vec4 isNaN = vec4(lessThan(a, vec4(0.0))) * vec4(lessThan(floor(b), b));
`+su+`
return result;
`,cnt=le({opSnippet:lnt,packedOpSnippet:unt}),g3={kernelName:Cs,backendName:"webgl",kernelFunc:cnt};function pnt(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{axis:s,keepDims:i}=n,a=o.shape.length,u=[],l=x.parseAxisParam(s,o.shape),c=l,p=k.getAxesPermutation(c,a),m=o;p!=null&&(m=Le({inputs:{x:o},backend:e,attrs:{perm:p}}),c=k.getInnerMostAxes(c.length,a),u.push(m)),k.assertAxesAreInnerMostDims("prod",c,a);let f;if(e.shouldExecuteOnCPU([m])){let d=e.texData.get(m.dataId).values,{outVals:h,outShape:g,outDtype:y}=aM(m.shape,m.dtype,d,c);f=e.makeTensorInfo(g,y,h)}else{let[d,h]=k.computeOutAndReduceShapes(m.shape,c),g=x.sizeFromShape(h),y=ut({inputs:{x:m},backend:e,attrs:{shape:[-1,g]}}),b=Tu(o.dtype),w=Wn(y,b,"prod",e);f=ut({inputs:{x:w},backend:e,attrs:{shape:d}}),u.push(y),u.push(w)}if(i){u.push(f);let d=k.expandShapeToKeepDim(f.shape,l);f=ut({inputs:{x:f},backend:e,attrs:{shape:d}})}return u.forEach(d=>e.disposeIntermediateTensorInfo(d)),f}var x3={kernelName:Ia,backendName:"webgl",kernelFunc:pnt};var VN=r=>{let{backend:t,attrs:e}=r,{start:n,stop:o,step:s,dtype:i}=e,a=lM(n,o,s,i);return t.makeTensorInfo([a.length],i,a)},y3={kernelName:_l,backendName:"webgl",kernelFunc:VN};var mnt="return 1.0 / x;",fnt=Ct({opSnippet:mnt}),b3={kernelName:Sa,backendName:"webgl",kernelFunc:fnt};var dnt=dr+`
return (x < 0.0) ? 0.0 : x;
`,hnt=`
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;
`,gnt=Ct({opSnippet:dnt,packedOpSnippet:hnt}),w3={kernelName:Ss,backendName:"webgl",kernelFunc:gnt};var xnt=dr+`
return (x < 0.0) ? 0.0 : min(6.0, x);
`,ynt=`
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;
`,bnt=Ct({opSnippet:xnt,packedOpSnippet:ynt}),v3={kernelName:Ns,backendName:"webgl",kernelFunc:bnt};var GN=class{constructor(t,e,n,o,s){this.variableNames=["A"],this.outputShape=[];let[i,a,u,l]=t;this.outputShape=[i,e,n,l];let c=[o&&e>1?a-1:a,o&&n>1?u-1:u],p=[o&&e>1?e-1:e,o&&n>1?n-1:n],m;s?m="(vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC - vec2(0.5)":m="vec2(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
const vec2 effectiveInputOverOutputRatioRC = vec2(
${c[0]/p[0]},
${c[1]/p[1]});
const vec2 inputShapeRC = vec2(${a}.0, ${u}.0);
void main() {
ivec4 coords = getOutputCoords();
int b = coords[0];
int d = coords[3];
ivec2 yRC = coords.yz;
// Fractional source index.
vec2 sourceFracIndexRC = ${m};
// Compute the four integer indices.
ivec2 sourceFloorRC = ivec2(max(sourceFracIndexRC, vec2(0.0)));
ivec2 sourceCeilRC = ivec2(
min(inputShapeRC - 1.0, ceil(sourceFracIndexRC)));
float topLeft = getA(b, sourceFloorRC.x, sourceFloorRC.y, d);
float bottomLeft = getA(b, sourceCeilRC.x, sourceFloorRC.y, d);
float topRight = getA(b, sourceFloorRC.x, sourceCeilRC.y, d);
float bottomRight = getA(b, sourceCeilRC.x, sourceCeilRC.y, d);
vec2 fracRC = sourceFracIndexRC - vec2(sourceFloorRC);
float top = topLeft + (topRight - topLeft) * fracRC.y;
float bottom = bottomLeft + (bottomRight - bottomLeft) * fracRC.y;
float newValue = top + (bottom - top) * fracRC.x;
setOutput(newValue);
}
`}};var WN=class{constructor(t,e,n,o,s){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[];let[i,a,u,l]=t;this.outputShape=[i,e,n,l];let c=[o&&e>1?a-1:a,o&&n>1?u-1:u],p=[o&&e>1?e-1:e,o&&n>1?n-1:n],m;s?m="(vec3(yRC) + vec3(0.5)) * effectiveInputOverOutputRatioRC - vec3(0.5)":m="vec3(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
const vec3 effectiveInputOverOutputRatioRC = vec3(
${c[0]/p[0]},
${c[1]/p[1]},
${c[1]/p[1]});
const vec3 inputShapeRC = vec3(${a}.0, ${u}.0,
${u}.0);
float getAValue(int b, int r, int c, int d) {
return getChannel(getA(b, r, c, d), vec2(c, d));
}
void main() {
ivec4 coords = getOutputCoords();
int b = coords[0];
int d = coords[3];
// Calculate values for next column in yRC.z.
ivec3 yRC = coords.yzz + ivec3(0, 0, 1);
// Fractional source index.
vec3 sourceFracIndexRC = ${m};
// Compute the four integer indices.
ivec3 sourceFloorRC = ivec3(max(sourceFracIndexRC, vec3(0.0)));
ivec3 sourceCeilRC = ivec3(
min(inputShapeRC - 1.0, ceil(sourceFracIndexRC)));
// Should we calculate next column and row elements in 2x2 packed cell.
bool hasNextCol = d < ${l-1};
bool hasNextRow = coords.z < ${n-1};
// In parallel, construct four corners for all four components in
// packed 2x2 cell.
vec4 topLeft = vec4(
getAValue(b, sourceFloorRC.x, sourceFloorRC.y, d),
hasNextCol ? getAValue(b, sourceFloorRC.x, sourceFloorRC.y, d + 1)
: 0.0,
hasNextRow ? getAValue(b, sourceFloorRC.x, sourceFloorRC.z, d)
: 0.0,
(hasNextRow && hasNextCol) ?
getAValue(b, sourceFloorRC.x, sourceFloorRC.z, d + 1) : 0.0);
vec4 bottomLeft = vec4(
getAValue(b, sourceCeilRC.x, sourceFloorRC.y, d),
hasNextCol ? getAValue(b, sourceCeilRC.x, sourceFloorRC.y, d + 1)
: 0.0,
hasNextRow ? getAValue(b, sourceCeilRC.x, sourceFloorRC.z, d)
: 0.0,
(hasNextRow && hasNextCol) ?
getAValue(b, sourceCeilRC.x, sourceFloorRC.z, d + 1) : 0.0);
vec4 topRight = vec4(
getAValue(b, sourceFloorRC.x, sourceCeilRC.y, d),
hasNextCol ? getAValue(b, sourceFloorRC.x, sourceCeilRC.y, d + 1)
: 0.0,
hasNextRow ? getAValue(b, sourceFloorRC.x, sourceCeilRC.z, d)
: 0.0,
(hasNextRow && hasNextCol) ?
getAValue(b, sourceFloorRC.x, sourceCeilRC.z, d + 1) : 0.0);
vec4 bottomRight = vec4(
getAValue(b, sourceCeilRC.x, sourceCeilRC.y, d),
hasNextCol ? getAValue(b, sourceCeilRC.x, sourceCeilRC.y, d + 1)
: 0.0,
hasNextRow ? getAValue(b, sourceCeilRC.x, sourceCeilRC.z, d)
: 0.0,
(hasNextRow && hasNextCol) ?
getAValue(b, sourceCeilRC.x, sourceCeilRC.z, d + 1) : 0.0);
vec3 fracRC = sourceFracIndexRC - vec3(sourceFloorRC);
vec4 top = mix(topLeft, topRight, fracRC.yyzz);
vec4 bottom = mix(bottomLeft, bottomRight, fracRC.yyzz);
vec4 newValue = mix(top, bottom, fracRC.x);
setOutput(newValue);
}
`}};function wnt(r){let{inputs:t,backend:e,attrs:n}=r,{images:o}=t,{alignCorners:s,halfPixelCenters:i,size:a}=n,[u,l]=a,c=G().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new WN(o.shape,u,l,s,i):new GN(o.shape,u,l,s,i);return e.runWebGLProgram(c,[o],"float32")}var C3={kernelName:ks,backendName:"webgl",kernelFunc:wnt};var UN=class{constructor(t,e,n){this.variableNames=["dy"],this.outputShape=[],this.outputShape=e;let[,o,s]=e,[,i,a]=t,u=[n&&i>1?o-1:o,n&&a>1?s-1:s],l=[n&&i>1?i-1:i,n&&a>1?a-1:a],c=u[0]/l[0],p=u[1]/l[1],m=1/c,f=1/p,d=Math.ceil(m)*2+2,h=Math.ceil(f)*2+2;this.userCode=`
void main() {
ivec4 coords = getOutputCoords();
int b = coords[0];
int d = coords[3];
int r = coords[1];
int c = coords[2];
float accumulator = 0.0;
const float heightScale = float(${c});
const float widthScale = float(${p});
const float invHeightScale = float(${m});
const float invWidthScale = float(${f});
const int winHeight = int(${d});
const int winWidth = int(${h});
// Compute bounds for where in dy we will look
float startRLerp = floor(float(r) * invHeightScale);
int startDyR = int(startRLerp - float(winHeight / 2));
float startCLerp = floor(float(c) * invWidthScale);
int startDyC = int(startCLerp - float(winWidth / 2));
// Loop over dy
for (int dyROffset = 0; dyROffset < winHeight; dyROffset++) {
int dyR = dyROffset + startDyR;
// Guard against the window exceeding the bounds of dy
if (dyR < 0 || dyR >= ${i}) {
continue;
}
for (int dyCOffset = 0; dyCOffset < winWidth; dyCOffset++) {
int dyC = dyCOffset + startDyC;
// Guard against the window exceeding the bounds of dy
if (dyC < 0 || dyC >= ${a}) {
continue;
}
float dxR = float(dyR) * heightScale;
int topDxRIndex = int(floor(dxR));
int bottomDxRIndex = int(min(ceil(dxR), ${o-1}.0));
float dxRLerp = dxR - float(topDxRIndex);
float inverseDxRLerp = 1.0 - dxRLerp;
float dxC = float(dyC) * widthScale;
int leftDxCIndex = int(floor(dxC));
int rightDxCIndex = int(min(ceil(dxC), ${s-1}.0));
float dxCLerp = dxC - float(leftDxCIndex);
float inverseDxCLerp = 1.0 - dxCLerp;
if (r == topDxRIndex && c == leftDxCIndex) {
// topLeft
accumulator +=
getDy(b, dyR, dyC, d) * inverseDxRLerp * inverseDxCLerp;
}
if (r == topDxRIndex && c == rightDxCIndex) {
// topRight
accumulator += getDy(b, dyR, dyC, d) * inverseDxRLerp * dxCLerp;
}
if (r == bottomDxRIndex && c == leftDxCIndex) {
// bottomLeft
accumulator += getDy(b, dyR, dyC, d) * dxRLerp * inverseDxCLerp;
}
if (r == bottomDxRIndex && c == rightDxCIndex) {
// bottomRight
accumulator += getDy(b, dyR, dyC, d) * dxRLerp * dxCLerp;
}
}
}
// End loop over dy
setOutput(accumulator);
}
`}};function vnt(r){let{inputs:t,backend:e,attrs:n}=r,{images:o,dy:s}=t,{alignCorners:i}=n,a=new UN(s.shape,o.shape,i);return e.runWebGLProgram(a,[s],s.dtype)}var I3={kernelName:$p,backendName:"webgl",kernelFunc:vnt};var HN=class{constructor(t,e,n,o,s){this.variableNames=["A"],this.outputShape=[];let[i,a,u,l]=t;this.outputShape=[i,e,n,l];let c=[o&&e>1?a-1:a,o&&n>1?u-1:u],p=[o&&e>1?e-1:e,o&&n>1?n-1:n],m=o?"0.5":"0.0",f;s?f="max((vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC, vec2(0.0))":f="vec2(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
const vec2 effectiveInputOverOutputRatioRC = vec2(
${c[0]/p[0]},
${c[1]/p[1]});
const vec2 inputShapeRC = vec2(${a}.0, ${u}.0);
void main() {
ivec4 coords = getOutputCoords();
int b = coords[0];
int d = coords[3];
ivec2 yRC = coords.yz;
// Fractional source index.
vec2 sourceFracIndexRC = ${f};
// Compute the coordinators of nearest neighbor point.
ivec2 sourceNearestRC = ivec2(
min(inputShapeRC - 1.0, floor(sourceFracIndexRC + ${m})));
float newValue = getA(b, sourceNearestRC.x, sourceNearestRC.y, d);
setOutput(newValue);
}
`}};var qN=class{constructor(t,e,n,o,s){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[];let[i,a,u,l]=t;this.outputShape=[i,e,n,l];let c=[o&&e>1?a-1:a,o&&n>1?u-1:u],p=[o&&e>1?e-1:e,o&&n>1?n-1:n],m=o?"0.5":"0.0",f;s?f="max((vec3(yRC) + vec3(0.5)) * effectiveInputOverOutputRatioRC, vec3(0.0))":f="vec3(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
const vec3 effectiveInputOverOutputRatioRC = vec3(
${c[0]/p[0]},
${c[1]/p[1]},
${c[1]/p[1]});
const vec3 inputShapeRC = vec3(${a}.0, ${u}.0,
${u}.0);
float getAValue(int b, int r, int c, int d) {
return getChannel(getA(b, r, c, d), vec2(c, d));
}
void main() {
ivec4 coords = getOutputCoords();
int b = coords[0];
int d = coords[3];
// Calculate values for next column in yRC.z.
ivec3 yRC = coords.yzz + ivec3(0, 0, 1);
// Fractional source index.
vec3 sourceFracIndexRC = ${f};
// Compute the coordinators of nearest neighbor point.
ivec3 sourceNearestRC = ivec3(
min(inputShapeRC - 1.0, floor(sourceFracIndexRC + ${m})));
// Should we calculate next column and row elements in 2x2 packed cell.
bool hasNextCol = d < ${l-1};
bool hasNextRow = coords.z < ${n-1};
vec4 newValue = vec4(
getAValue(b, sourceNearestRC.x, sourceNearestRC.y, d),
hasNextCol ? getAValue(b, sourceNearestRC.x, sourceNearestRC.y, d + 1)
: 0.0,
hasNextRow ? getAValue(b, sourceNearestRC.x, sourceNearestRC.z, d)
: 0.0,
(hasNextRow && hasNextCol) ?
getAValue(b, sourceNearestRC.x, sourceNearestRC.z, d + 1) : 0.0);
setOutput(newValue);
}
`}};function Cnt(r){let{inputs:t,backend:e,attrs:n}=r,{images:o}=t,{alignCorners:s,halfPixelCenters:i,size:a}=n,[u,l]=a,c=G().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new qN(o.shape,u,l,s,i):new HN(o.shape,u,l,s,i);return e.runWebGLProgram(c,[o],o.dtype)}var S3={kernelName:El,backendName:"webgl",kernelFunc:Cnt};var KN=class{constructor(t,e,n){this.variableNames=["dy"],this.outputShape=[],this.outputShape=e;let[,o,s]=e,[,i,a]=t,u=[n&&i>1?o-1:o,n&&a>1?s-1:s],l=[n&&i>1?i-1:i,n&&a>1?a-1:a],c=u[0]/l[0],p=u[1]/l[1],m=1/c,f=1/p,d=Math.ceil(m)*2+2,h=Math.ceil(f)*2+2;this.userCode=`
void main() {
ivec4 coords = getOutputCoords();
int b = coords[0];
int d = coords[3];
int r = coords[1];
int c = coords[2];
float accumulator = 0.0;
const float heightScale = float(${c});
const float widthScale = float(${p});
const float invHeightScale = float(${m});
const float invWidthScale = float(${f});
const int winHeight = int(${d});
const int winWidth = int(${h});
// Compute bounds for where in dy we will look
float startRLerp = floor(float(r) * invHeightScale);
int startDyR = int(floor(startRLerp - float(winHeight / 2)));
float startCLerp = floor(float(c) * invWidthScale);
int startDyC = int(floor(startCLerp - float(winWidth / 2)));
// Loop over dy
for (int dyROffset = 0; dyROffset < winHeight; dyROffset++) {
int dyR = dyROffset + startDyR;
// Guard against the window exceeding the bounds of dy
if (dyR < 0 || dyR >= ${i}) {
continue;
}
for (int dyCOffset = 0; dyCOffset < winWidth; dyCOffset++) {
int dyC = dyCOffset + startDyC;
// Guard against the window exceeding the bounds of dy
if (dyC < 0 || dyC >= ${a}) {
continue;
}
float sourceFracRow =
float(${u[0]}) *
(float(dyR) / float(${l[0]}));
float sourceFracCol =
float(${u[1]}) *
(float(dyC) / float(${l[1]}));
int sourceNearestRow = int(min(
float(int(${o}) - 1),
${n} ? float(round(sourceFracRow)) :
float(floor(sourceFracRow))));
int sourceNearestCol = int(min(
float(int(${s}) - 1),
${n} ? float(round(sourceFracCol)) :
float(floor(sourceFracCol))));
if (r == sourceNearestRow && c == sourceNearestCol) {
accumulator += getDy(b, dyR, dyC, d);
}
}
}
// End loop over dy
setOutput(accumulator);
}
`}};function Int(r){let{inputs:t,backend:e,attrs:n}=r,{images:o,dy:s}=t,{alignCorners:i}=n,a=new KN(s.shape,o.shape,i);return e.runWebGLProgram(a,[s],s.dtype)}var k3={kernelName:Dp,backendName:"webgl",kernelFunc:Int};var jN=class{constructor(t,e){this.variableNames=["x"];let n=t.length;if(n>4)throw new Error(`WebGL backend: Reverse of rank-${n} tensor is not yet supported`);if(this.outputShape=t,n===1){this.userCode=`
void main() {
int coord = getOutputCoords();
setOutput(getX(${t[0]} - coord - 1));
}
`;return}let o=a=>e.indexOf(a)!==-1&&t[a]!==1?`${t[a]} - coords[${a}] - 1`:`coords[${a}]`,s=t.map((a,u)=>o(u)).join(","),i=Ht(n);this.userCode=`
void main() {
${i} coords = getOutputCoords();
setOutput(getX(${s}));
}
`}};var XN=class{constructor(t,e){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0;let n=t.length;if(n>4)throw new Error(`WebGL backend: Reverse of rank-${n} tensor is not yet supported`);this.outputShape=t;let o=tr("rc",n),s=`${o[n-1]} + 1 < ${this.outputShape[n-1]}`,i=`${o[n-2]} + 1 < ${this.outputShape[n-2]}`,a=Ht(n);n===1?this.userCode=`
void main(){
int rc = getOutputCoords();
vec4 result = vec4(0.);
result.r = getChannel(getX(${t[0]} - rc - 1),
${t[0]} - rc - 1);
if(${s}){
result.g = getChannel(getX(${t[0]} - (rc + 1) - 1),
${t[0]} - (rc + 1) - 1);
}
setOutput(result);
}
`:this.userCode=`
void main() {
${a} rc = getOutputCoords();
vec4 result = vec4(0.);
result.r = ${u(o.slice())};
if(${s}){
result.g = ${l(o.slice())};
}
if(${i}) {
result.b = ${c(o.slice())};
if(${s}) {
result.a = ${p(o.slice())};
}
}
setOutput(result);
}
`;function u(d){return m(d)}function l(d){return d[n-1]="("+d[n-1]+" + 1)",m(d)}function c(d){return d[n-2]="("+d[n-2]+" + 1)",m(d)}function p(d){return d[n-1]="("+d[n-1]+" + 1)",d[n-2]="("+d[n-2]+" + 1)",m(d)}function m(d){let h=t.map((b,w)=>f(w,d)),g=h.join(","),y=h.slice(-2).join(",");return`getChannel(getX(${g}), vec2(${y}))`}function f(d,h){return e.indexOf(d)!==-1&&t[d]!==1?`${t[d]} - ${h[d]} - 1`:`${h[d]}`}}};function Snt(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{dims:s}=n,i=o.shape.length,a=x.parseAxisParam(s,o.shape);if(i===0)return er({inputs:{x:o},backend:e});let u=G().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new XN(o.shape,a):new jN(o.shape,a);return e.runWebGLProgram(u,[o],o.dtype)}var N3={kernelName:Ts,backendName:"webgl",kernelFunc:Snt};var YN=class{constructor(t,e){this.variableNames=["Image"],this.outputShape=[],this.customUniforms=[{name:"params",type:"vec4"}];let n=t[1],o=t[2];this.outputShape=t;let s="";typeof e=="number"?s=`float outputValue = ${e.toFixed(2)};`:s=`
vec3 fill = vec3(${e.join(",")});
float outputValue = fill[coords[3]];`,this.userCode=`
void main() {
ivec4 coords = getOutputCoords();
int x = coords[2];
int y = coords[1];
float coordXFloat = (float(x) - params[0]) * params[3] -
(float(y) - params[1]) * params[2];
float coordYFloat = (float(x) - params[0]) * params[2] +
(float(y) - params[1]) * params[3];
int coordX = int(round(coordXFloat + params[0]));
int coordY = int(round(coordYFloat + params[1]));
${s}
if(coordX >= 0 && coordX < ${o} && coordY >= 0 && coordY < ${n}) {
outputValue = getImage(coords[0], coordY, coordX, coords[3]);
}
setOutput(outputValue);
}
`}};var T3={kernelName:Fa,backendName:"webgl",kernelFunc:({inputs:r,attrs:t,backend:e})=>{let{image:n}=r,{radians:o,fillValue:s,center:i}=t,a=e,u=new YN(n.shape,s),[l,c]=k.getImageCenter(i,n.shape[1],n.shape[2]),p=[[l,c,Math.sin(o),Math.cos(o)]];return a.runWebGLProgram(u,[n],n.dtype,p)}};var knt=`
// OpenGL ES does not support round function.
// The algorithm is based on banker's rounding.
float base = floor(x);
if ((x - base) < 0.5) {
return floor(x);
} else if ((x - base) > 0.5) {
return ceil(x);
} else {
if (mod(base, 2.0) == 0.0) {
return base;
} else {
return base + 1.0;
}
}
`,Nnt=Ct({opSnippet:knt}),_3={kernelName:_s,backendName:"webgl",kernelFunc:Nnt};var Tnt="return inversesqrt(x);",_nt=Ct({opSnippet:Tnt,cpuKernelImpl:uM}),E3={kernelName:Es,backendName:"webgl",kernelFunc:_nt};var fg=class{constructor(t,e,n,o,s,i,a=!0){this.variableNames=["updates","indices","defaultValue"],this.outputShape=i;let u=Ht(s.length),l=Ht(i.length),c="";n===1?c="i":n===2&&(c="i, j");let p=`getIndices(${c})`,m="";o===1?m="i":o===2&&(m="i, coords[1]");let f=`getUpdates(${m})`,d=e>1?"strides[j]":"strides";this.userCode=`
${u} strides = ${u}(${s});
void main() {
${l} coords = getOutputCoords();
float sum = 0.0;
bool found = false;
for (int i = 0; i < ${t}; i++) {
int flattenedIndex = 0;
for (int j = 0; j < ${e}; j++) {
int index = round(${p});
flattenedIndex += index * ${d};
}
if (flattenedIndex == coords[0]) {
sum += ${f};
found = true;
}
}
setOutput(mix(getDefaultValue(), sum, float(found)));
}
`}};function Ent(r){let{inputs:t,backend:e,attrs:n}=r,{indices:o,updates:s}=t,{shape:i}=n,{sliceRank:a,numUpdates:u,sliceSize:l,strides:c,outputSize:p}=k.calculateShapes(s,o,i),m=[p/l,l];if(p===0)return e.makeTensorInfo(i,o.dtype);let f=ut({inputs:{x:o},backend:e,attrs:{shape:[u,a]}}),d=ut({inputs:{x:s},backend:e,attrs:{shape:[u,l]}}),h=e.makeTensorInfo([],"float32",new Float32Array([0])),g=new fg(u,a,f.shape.length,d.shape.length,c,m),y=e.runWebGLProgram(g,[d,f,h],d.dtype),b=ut({inputs:{x:y},backend:e,attrs:{shape:i}});return e.disposeIntermediateTensorInfo(f),e.disposeIntermediateTensorInfo(d),e.disposeIntermediateTensorInfo(y),e.disposeIntermediateTensorInfo(h),b}var A3={kernelName:ka,backendName:"webgl",kernelFunc:Ent};var ZN=class{constructor(t,e,n){this.variableNames=["c","a","b"],this.outputShape=e;let o,s;if(n>4)throw Error(`Where for rank ${n} is not yet supported`);if(n===1)s="resRC",o="resRC";else{let a=["resRC.x","resRC.y","resRC.z","resRC.w"],u=[],l=[];for(let c=0;c<e.length;c++)l.push(`${a[c]}`),c<t&&u.push(`${a[c]}`);o=u.join(),s=l.join()}let i=Ht(n);this.userCode=`
void main() {
${i} resRC = getOutputCoords();
float cVal = getC(${o});
if (cVal >= 1.0) {
setOutput(getA(${s}));
} else {
setOutput(getB(${s}));
}
}
`}};function Ant(r){let{inputs:t,backend:e}=r,{condition:n,t:o,e:s}=t,i=new ZN(n.shape.length,o.shape,o.shape.length);return e.runWebGLProgram(i,[n,o,s],yr(o.dtype,s.dtype))}var D3={kernelName:Ii,backendName:"webgl",kernelFunc:Ant};var Dnt=`
// Stable and Attracting Fixed Point (0, 1) for Normalized Weights.
// see: https://arxiv.org/abs/1706.02515
float scaleAlpha = ${k.SELU_SCALEALPHA};
float scale = ${k.SELU_SCALE};
return (x >= 0.0) ? scale * x : scaleAlpha * (exp(x) - 1.0);
`,$nt=Ct({opSnippet:Dnt}),$3={kernelName:Na,backendName:"webgl",kernelFunc:$nt};var Rnt=Fo+`
return 1.0 / (1.0 + exp(-1.0 * x));
`,Fnt=`
vec4 result = 1.0 / (1.0 + exp(-1.0 * x));
bvec4 isNaN = isnan(x);
result.r = isNaN.r ? x.r : result.r;
result.g = isNaN.g ? x.g : result.g;
result.b = isNaN.b ? x.b : result.b;
result.a = isNaN.a ? x.a : result.a;
return result;
`,Ont=Ct({opSnippet:Rnt,packedOpSnippet:Fnt,cpuKernelImpl:cM}),R3={kernelName:Ds,backendName:"webgl",kernelFunc:Ont};var Pnt=`
if (isnan(x)) { return 0.0; }
return sign(x);
`,Mnt=Ct({opSnippet:Pnt}),F3={kernelName:_a,backendName:"webgl",kernelFunc:Mnt};var Lnt=Fo+`
return sin(x);
`,znt=Ct({opSnippet:Lnt}),O3={kernelName:As,backendName:"webgl",kernelFunc:znt};var Bnt=`
float e2x = exp(x);
return (e2x - 1.0 / e2x) / 2.0;
`,Vnt=Ct({opSnippet:Bnt}),P3={kernelName:Ta,backendName:"webgl",kernelFunc:Vnt};var Gnt=`
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;
`,Wnt=Ct({opSnippet:Gnt}),M3={kernelName:Ea,backendName:"webgl",kernelFunc:Wnt};var Unt=r=>{let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{blockShape:s,paddings:i}=n;x.assert(o.shape.length<=4,()=>"spaceToBatchND for rank > 4 with a WebGL backend not implemented yet");let a=s.reduce((y,b)=>y*b),u=[[0,0]];u.push(...i);for(let y=1+s.length;y<o.shape.length;++y)u.push([0,0]);let l=[],c=BN({inputs:{x:o},backend:e,attrs:{paddings:u,constantValue:0}}),p=k.getReshaped(c.shape,s,a,!1),m=k.getPermuted(p.length,s.length,!1),f=k.getReshapedPermuted(c.shape,s,a,!1),d=ut({inputs:{x:c},backend:e,attrs:{shape:p}}),h=Le({inputs:{x:d},backend:e,attrs:{perm:m}}),g=ut({inputs:{x:h},backend:e,attrs:{shape:f}});return l.push(c),l.push(d),l.push(h),l.forEach(y=>e.disposeIntermediateTensorInfo(y)),g},L3={kernelName:ki,backendName:"webgl",kernelFunc:Unt};function Hnt(r){let{inputs:t,backend:e}=r,{indices:n,values:o,denseShape:s,defaultValue:i}=t;if(s.shape.length!==1)throw new Error(`Dense shape must be a vector, saw:
${s.shape}`);if(n.shape.length!==2)throw new Error(`Indices must be a matrix, saw:
${n.shape}`);if(o.shape.length!==1)throw new Error(`Values must be a vector, saw:
${o.shape}`);if(i.shape.length!==0)throw new Error(`Default value must be a scalar, saw:
${i.shape}`);let a=e.readSync(n.dataId),u=e.readSync(o.dataId),l=e.readSync(s.dataId),c=e.readSync(i.dataId)[0],[p,m,f,d,h]=mM(a,n.shape,n.dtype,u,o.dtype,l,c);return[e.makeTensorInfo(m,n.dtype,p),e.makeTensorInfo([m[0]],o.dtype,f),e.makeTensorInfo([d.length],"bool",new Uint8Array(d.map(g=>Number(g)))),e.makeTensorInfo([h.length],n.dtype,new Int32Array(h))]}var z3={kernelName:Al,backendName:"webgl",kernelFunc:Hnt};function qnt(r){let{inputs:t,backend:e}=r,{inputIndices:n,inputShape:o,newShape:s}=t;if(n.shape.length!==2)throw new Error(`Input indices should be a matrix but received shape ${n.shape}`);if(o.shape.length!==1)throw new Error(`Input shape should be a vector but received shape ${o.shape}`);if(s.shape.length!==1)throw new Error(`Target shape should be a vector but received shape ${s.shape}`);let i=Array.from(e.readSync(o.dataId)),a=e.readSync(n.dataId),u=Array.from(e.readSync(s.dataId)),[l,c,p]=fM(a,n.shape,n.dtype,i,u);return[e.makeTensorInfo(c,n.dtype,l),e.makeTensorInfo([p.length],s.dtype,new Int32Array(p))]}var B3={kernelName:Aa,backendName:"webgl",kernelFunc:qnt};function Knt(r){let{inputs:t,backend:e}=r,{data:n,indices:o,segmentIds:s}=t;if(n.shape.length<1)throw new Error("Data should be at least 1 dimensional but received scalar");if(o.shape.length!==1)throw new Error(`Indices should be a vector but received shape
${o.shape}`);if(s.shape.length!==1)throw new Error(`Segment ids should be a vector but received shape
${s.shape}`);let i=e.readSync(n.dataId),a=e.readSync(o.dataId),u=e.readSync(s.dataId),[l,c]=wb(i,n.shape,n.dtype,a,u,!0);return e.makeTensorInfo(c,n.dtype,l)}var V3={kernelName:Dl,backendName:"webgl",kernelFunc:Knt};function jnt(r){let{inputs:t,backend:e}=r,{data:n,indices:o,segmentIds:s}=t;if(n.shape.length<1)throw new Error("Data should be at least 1 dimensional but received scalar");if(o.shape.length!==1)throw new Error(`Indices should be a vector but received shape
${o.shape}`);if(s.shape.length!==1)throw new Error(`Segment ids should be a vector but received shape
${s.shape}`);let i=e.readSync(n.dataId),a=e.readSync(o.dataId),u=e.readSync(s.dataId),[l,c]=wb(i,n.shape,n.dtype,a,u);return e.makeTensorInfo(c,n.dtype,l)}var G3={kernelName:$l,backendName:"webgl",kernelFunc:jnt};function Xnt(r){let{inputs:t,backend:e,attrs:n}=r,{sparseIndices:o,sparseValues:s,defaultValue:i}=t,{outputShape:a}=n,{sliceRank:u,numUpdates:l,strides:c,outputSize:p}=k.calculateShapes(s,o,a),m=!1,f=new fg(l,u,o.shape.length,s.shape.length,c,[p,1],m),d=e.runWebGLProgram(f,[s,o,i],s.dtype),h=ut({inputs:{x:d},backend:e,attrs:{shape:a}});return e.disposeIntermediateTensorInfo(d),h}var W3={kernelName:Rp,backendName:"webgl",kernelFunc:Xnt};function Ynt(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{numOrSizeSplits:s,axis:i}=n,a=x.parseAxisParam(i,o.shape)[0],u=k.prepareSplitSize(o,s,a),l=o.shape.length,c=new Array(l).fill(0),p=o.shape.slice();return u.map(m=>{let f=[...p];f[a]=m;let d=ci({inputs:{x:o},backend:e,attrs:{begin:c,size:f}});return c[a]+=m,d})}var U3={kernelName:Ni,backendName:"webgl",kernelFunc:Ynt};var H3="return sqrt(x);",Znt=Ct({opSnippet:H3,packedOpSnippet:H3,cpuKernelImpl:dM}),q3={kernelName:$s,backendName:"webgl",kernelFunc:Znt};var Jnt="return x * x;",Qnt=Ct({opSnippet:Jnt}),K3={kernelName:Rl,backendName:"webgl",kernelFunc:Qnt};var j3="return (a - b) * (a - b);",tot=le({opSnippet:j3,packedOpSnippet:j3}),X3={kernelName:Os,backendName:"webgl",kernelFunc:tot};function eot({inputs:r,attrs:t,backend:e}){let{x:n}=r,o=dr+`
return x > 0.0 ? 1.0 : float(${t.alpha});
`,s=new wn(n.shape,o);return e.runWebGLProgram(s,[n],n.dtype)}var Y3={kernelName:io,backendName:"webgl",kernelFunc:eot};var JN=class{constructor(t,e,n){this.variableNames=["x"],this.outputShape=n;let o=n.length,s=Ht(n.length),i=Ht(n.length),a="";if(o===1)a="coords * strides + begin";else{let u=0;a=n.map((l,c)=>(u++,n.length===1?`coords * strides[${c}] + begin[${c}]`:`coords[${u-1}] * strides[${c}] + begin[${c}]`)).join(",")}this.userCode=`
${s} begin = ${s}(${t});
${s} strides = ${s}(${e});
void main() {
${i} coords = getOutputCoords();
setOutput(getX(${a}));
}
`}};function rot(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{begin:s,end:i,strides:a,beginMask:u,endMask:l,ellipsisMask:c,newAxisMask:p,shrinkAxisMask:m}=n,{finalShapeSparse:f,finalShape:d,isIdentity:h,sliceDim0:g,isSimpleSlice:y,begin:b,end:w,strides:v}=Ve.sliceInfo(o.shape,s,i,a,u,l,c,p,m),I;if(h)I=ut({inputs:{x:o},backend:e,attrs:{shape:d}});else if(g||y){x.assert(o.shape.length>=1,()=>`Input must have rank at least 1, got: ${o.shape.length}`);let D=Ve.computeOutShape(b,w,v),$=ci({inputs:{x:o},backend:e,attrs:{begin:b,size:D}});I=ut({inputs:{x:$},backend:e,attrs:{shape:d}}),e.disposeIntermediateTensorInfo($)}else if(e.shouldExecuteOnCPU([o])){let $=e.readSync(o.dataId),R=It(o.shape,o.dtype,$),M=hM(f,R,v,b);I=e.makeTensorInfo(d,o.dtype,M.values)}else{let $=new JN(b,v,f);I=e.runWebGLProgram($,[o],o.dtype)}let E=ut({inputs:{x:I},backend:e,attrs:{shape:d}});return e.disposeIntermediateTensorInfo(I),E}var Z3={kernelName:Da,backendName:"webgl",kernelFunc:rot};function not(r){let{inputs:t,backend:e,attrs:n}=r,{separator:o,nGramWidths:s,leftPad:i,rightPad:a,padWidth:u,preserveShortSequences:l}=n,{data:c,dataSplits:p}=t,m=e.readSync(c.dataId),f=e.readSync(p.dataId),[d,h]=gM(m,f,o,s,i,a,u,l);return[e.makeTensorInfo([d.length],"string",d),e.makeTensorInfo(p.shape,"int32",h)]}var J3={kernelName:Fp,backendName:"webgl",kernelFunc:not};function oot(r){let{inputs:t,backend:e,attrs:n}=r,{skipEmpty:o}=n,{input:s,delimiter:i}=t;if(s.dtype!=="string")throw new Error("Input must be of datatype string");if(s.shape.length!==1)throw new Error(`Input must be a vector, got shape: ${s.shape}`);if(i.shape.length!==0)throw new Error(`Delimiter must be a scalar, got shape: ${i.shape}`);let a=e.readSync(s.dataId),u=e.readSync(i.dataId)[0],[l,c,p]=xM(a,u,o),m=c.length;return[e.makeTensorInfo([m,2],"int32",l),e.makeTensorInfo([m],"string",c),e.makeTensorInfo([2],"int32",new Int32Array(p))]}var Q3={kernelName:Op,backendName:"webgl",kernelFunc:oot};function sot(r){let{inputs:t,backend:e,attrs:n}=r,{numBuckets:o}=n,{input:s}=t;if(s.dtype!=="string")throw new Error("Input must be of datatype string");if(o<=0)throw new Error("Number of buckets must be at least 1");let i=e.readSync(s.dataId),a=yM(i,o);return e.makeTensorInfo(s.shape,"int32",a)}var tB={kernelName:Pp,backendName:"webgl",kernelFunc:sot};var iot="return tan(x);",aot=Ct({opSnippet:iot}),eB={kernelName:Ms,backendName:"webgl",kernelFunc:aot};var lot=`
float e2x = exp(-2.0 * abs(x));
return sign(x) * (1.0 - e2x) / (1.0 + e2x);
`,uot=Ct({opSnippet:lot}),rB={kernelName:Ls,backendName:"webgl",kernelFunc:uot};var QN=class{constructor(t,e){this.variableNames=["A"];let n=new Array(t.length);for(let i=0;i<n.length;i++)n[i]=t[i]*e[i];this.outputShape=n,this.rank=n.length;let o=Ht(this.rank),s=cot(t);this.userCode=`
void main() {
${o} resRC = getOutputCoords();
setOutput(getA(${s}));
}
`}};function cot(r){let t=r.length;if(t>5)throw Error(`Tile for rank ${t} is not yet supported`);if(t===1)return`imod(resRC, ${r[0]})`;let e=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u"],n=[];for(let o=0;o<r.length;o++)n.push(`imod(${e[o]}, ${r[o]})`);return n.join()}function tT(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{reps:s}=n;if(o.dtype==="string"||o.shape.length>5){let u=e.readSync(o.dataId),l=o.dtype==="string"?u.map(m=>x.decodeString(m)):u,c=It(o.shape,o.dtype,l),p=wM(c,s);return e.makeTensorInfo(p.shape,p.dtype,p.values)}let i=new QN(o.shape,s);return e.runWebGLProgram(i,[o],o.dtype)}var nB={kernelName:jn,backendName:"webgl",kernelFunc:tT};var eT=class{constructor(t){this.variableNames=["x","indices"],this.customUniforms=[{name:"n",type:"int"},{name:"firstPass",type:"int"},{name:"negativeInf",type:"float"},{name:"dir",type:"int"},{name:"inc",type:"int"}],this.outputShape=t,this.userCode=`
void main() {
ivec2 coords = getOutputCoords();
int batch = coords[0];
int elemIdx = coords[1];
// We compare elements pair-wise within a group of size 2 * inc.
// The comparing rule for each group alternates between ascending
// and descending. Within each group, we compare each pair at
// positions i and i+inc. To decide whether an element at position i
// is x0 or x1, we mod it by 2 * inc, if the result is smaller than
// inc, it is in the first half of the group, we denote it as x0,
// otherwise we denote it as x1.
// For example, as shown in the Bitonic top K paper referenced above,
// Figure5(a) shows that element[1] is in the
// second half of the group when group size is 2, but it is in the
// first half of the group when group size is 4.
bool isFirstInPair = imod(elemIdx, 2 * inc) < inc;
int i = isFirstInPair ? elemIdx : elemIdx - inc;
int i0 = firstPass == 1 ? i : int(getIndices(batch, i));
int i1 = firstPass == 1 ? i + inc : int(getIndices(batch, i + inc));
float x0 = i0 < n ? getX(batch, i0) : negativeInf;
float x1 = i1 < n ? getX(batch, i1) : negativeInf;
// Denotes which direction indices are in (ascending or descending).
bool reverse = imod(elemIdx, 2 * dir) >= dir;
bool isGreater = x0 > x1 || (x0 == x1 && i1 > i0);
if (reverse == isGreater) { // Elements in opposite order of direction
int iTemp = i0;
i0 = i1;
i1 = iTemp;
}
if (isFirstInPair) {
setOutput(float(i0));
} else {
setOutput(float(i1));
}
}
`}},rT=class{constructor(t){this.variableNames=["x","indices"],this.customUniforms=[{name:"n",type:"int"},{name:"firstPass",type:"int"},{name:"k",type:"int"}],this.outputShape=t,this.userCode=`
void main() {
// Takes max of indices (0, k), (1, k + 1), (2, k + 2) ...
ivec2 coords = getOutputCoords();
int batch = coords[0];
int elemIdx = coords[1];
// The output size is half of the previous size.
// If the previous sequence is | | | | _ _ _ _ | | | | _ _ _ _ (k=4),
// we only need to output the indices at positions |, the indices at
// positions _ can be thrown away, see Figure5(b) After Phase 2
// (Merge phase) in the Bitonic Top K paper referenced above.
// For example, the paper shows we only need to output the orange bars.
// The output sequence should look like this | | | | | | | |.
// Because the sequence is halved, to map the output index back
// to the previous sequence to find the corresponding value,
// we need to double the index. When we double the index,
// we basically interpolate a position, so 2i looks like
// | _ | _ | _ | _ | _ | _ | _. We move the | to the first k position
// of each 2k positions by - elemIdx % k. E.g. for output at
// index 4,5,6,7, we want to get the corresponding element at
// original index 8,9,10,11, for output at index 8,9,10,11,
// we want to get the corresponding element at original index
// 16,17,18,19, so on and so forth.
int i = elemIdx < k ? elemIdx : (elemIdx * 2 - imod(elemIdx, k));
int i0 = firstPass == 1 ? i : int(getIndices(batch, i));
int i1 = firstPass == 1 ? i + k : int(getIndices(batch, i + k));
float x0 = getX(batch, i0);
float x1 = i1 < n ? getX(batch, i1) : x0;
setOutput(x0 >= x1 ? float(i0) : float(i1));
}
`}};function Bc(r,t){t!==null&&r.disposeIntermediateTensorInfo(t)}function oB(r){let t=1;for(;t<r;)t*=2;return t}function pot(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{k:s,sorted:i}=n,a=G().getNumber("TOPK_LAST_DIM_CPU_HANDOFF_SIZE_THRESHOLD"),u=G().getNumber("TOPK_K_CPU_HANDOFF_THRESHOLD"),l=o.shape,c=l[l.length-1];if(e.shouldExecuteOnCPU([o])||c<a||s>u){let M=e.readSync(o.dataId),[W,U]=vM(M,l,o.dtype,s,i);return[e.makeTensorInfo(W.shape,W.dtype,W.values),e.makeTensorInfo(U.shape,U.dtype,U.values)]}if(s===0)return l[l.length-1]=0,[e.makeTensorInfo(l,o.dtype,[]),e.makeTensorInfo(l,"int32",[])];if(c===1)return[o,fl({attrs:{shape:l,dtype:"int32",value:0},backend:e})];let p=e.texData.get(o.dataId),m=p!==null&&p.isPacked,f=m?e.unpackTensor(o):o,h=x.sizeFromShape(l)/c,g=ut({inputs:{x:f},attrs:{shape:[h,c]},backend:e});m&&Bc(e,f);let y=oB(s),b=oB(c),w=null,v=()=>w===null?[g,g]:[g,w],I=(M,W,U)=>{let q=v(),K=new eT(U),Q=[[c],[w===null?1:0],[Number.NEGATIVE_INFINITY],[M],[W]],rt=w;w=e.runWebGLProgram(K,q,"int32",Q),Bc(e,rt)};for(let M=1;M<y;M*=2){let W=M*2;for(let U=M;U>=1;U/=2)I(W,U,[h,b])}for(let M=b;M>y;M/=2){let W=v(),U=new rT([h,M/2]),K=[[c],[w===null?1:0],[y]],j=w;w=e.runWebGLProgram(U,W,"int32",K),Bc(e,j);let Q=y/2,rt=Q*2;for(let X=Q;X>=1;X/=2)I(rt,X,w.shape)}let E=w;w=ci({inputs:{x:w},backend:e,attrs:{begin:0,size:[h,s]}}),Bc(e,E);let D=SN({inputs:{x:g,indices:w},backend:e,attrs:{axis:1,batchDims:1}});Bc(e,g);let $=l.slice(0,-1);$.push(s),E=w,w=ut({inputs:{x:w},attrs:{shape:$},backend:e}),Bc(e,E);let R=D;return D=ut({inputs:{x:D},attrs:{shape:$},backend:e}),Bc(e,R),[D,w]}var sB={kernelName:$a,backendName:"webgl",kernelFunc:pot};var nT=class{constructor(t,e,n,o,s,i){this.variableNames=["Image","Transforms"],this.outputShape=i;let a=n==="nearest"?1:2,u;switch(o){case"constant":u=1;break;case"reflect":u=2;break;case"wrap":u=3;break;case"nearest":u=4;break;default:u=1;break}this.userCode=`
float mapCoord(float outCoord, float len) {
float inCoord = outCoord;
if(${u} == 2) {
if (inCoord < 0.0) {
if (len <= 1.0) {
inCoord = 0.0;
} else {
float sz2 = 2.0 * len;
if (inCoord < sz2) {
inCoord = sz2 * float(int(float(-inCoord / sz2))) +
inCoord;
}
inCoord = inCoord < -len ? inCoord + sz2 : -inCoord - 1.0;
}
} else if (inCoord > len - 1.0) {
if (len <= 1.0) {
inCoord = 0.0;
} else {
float sz2 = 2.0 * len;
inCoord -= sz2 * float(int(float(inCoord / sz2)));
if (inCoord >= len) {
inCoord = sz2 - inCoord - 1.0;
}
}
}
return clamp(inCoord, 0.0, len - 1.0);
} else if (${u} == 3) {
if (inCoord < 0.0) {
if (len <= 1.0) {
inCoord = 0.0;
} else {
float sz = len - 1.0;
inCoord += len * (float(int(float(-inCoord / sz))) + 1.0);
}
} else if (inCoord > len - 1.0) {
if (len <= 1.0) {
inCoord = 0.0;
} else {
float sz = len - 1.0;
inCoord -= len * float(int(float(inCoord / sz)));
}
}
return clamp(inCoord, 0.0, len - 1.0);
} else if (${u} == 4) {
return clamp(outCoord, 0.0, len - 1.0);
} else {
return outCoord;
}
}
float readWithFillValue(int batch, int coordY, int coordX,
int channel) {
float outputValue;
if (0 <= coordY && coordY < ${t} && 0 <= coordX && coordX < ${e}) {
outputValue = getImage(batch, coordY, coordX, channel);
} else {
outputValue = float(${s});
}
return outputValue;
}
void main() {
ivec4 coords = getOutputCoords();
float outputValue;
int batch = coords[0];
int x = coords[2];
int y = coords[1];
int channel = coords[3];
float xf = float(x);
float yf = float(y);
float a1 = getTransforms(batch, 0);
float a2 = getTransforms(batch, 1);
float a3 = getTransforms(batch, 2);
float b1 = getTransforms(batch, 3);
float b2 = getTransforms(batch, 4);
float b3 = getTransforms(batch, 5);
float c1 = getTransforms(batch, 6);
float c2 = getTransforms(batch, 7);
float projection = c1 * xf + c2 * yf + 1.0;
if (projection == 0.0) {
outputValue = float(${s});
} else {
float inX = (a1 * xf + a2 * yf + a3) / projection;
float inY = (b1 * xf + b2 * yf + b3) / projection;
float mapX = mapCoord(inX, float(${e}));
float mapY = mapCoord(inY, float(${t}));
if (${a} == 1) {
int coordY = int(round(mapY));
int coordX = int(round(mapX));
outputValue = readWithFillValue(batch, coordY, coordX,
channel);
} else {
float yFloor = floor(mapY);
float xFloor = floor(mapX);
float yCeil = yFloor + 1.0;
float xCeil = xFloor + 1.0;
float valueYFloor = (xCeil - mapX) *
readWithFillValue(batch, int(yFloor), int(xFloor), channel) +
(mapX - xFloor) *
readWithFillValue(batch, int(yFloor), int(xCeil), channel);
float valueYCeil = (xCeil - mapX) *
readWithFillValue(batch, int(yCeil), int(xFloor), channel) +
(mapX - xFloor) *
readWithFillValue(batch, int(yCeil), int(xCeil), channel);
outputValue = (yCeil - mapY) * valueYFloor +
(mapY - yFloor) * valueYCeil;
}
}
setOutput(outputValue);
}
`}};function mot(r){let{inputs:t,backend:e,attrs:n}=r,{image:o,transforms:s}=t,{interpolation:i,fillMode:a,fillValue:u,outputShape:l}=n,[c,p,m,f]=o.shape,[d,h]=l!=null?l:[p,m],g=[c,d,h,f],y=new nT(p,m,i,a,u,g);return e.runWebGLProgram(y,[o,s],"float32")}var iB={kernelName:Ra,backendName:"webgl",kernelFunc:mot};function fot(r){let{inputs:t,attrs:e,backend:n}=r,{axis:o}=e,{x:s}=t;ai(s,"unique"),console.warn("WARNING: ","UI might be locked temporarily as data is being downloaded");let i=n.readSync(s.dataId),{outputValues:a,outputShape:u,indices:l}=CM(i,o,s.shape,s.dtype);return[n.makeTensorInfo(u,s.dtype,a),n.makeTensorInfo([l.length],"int32",l)]}var aB={kernelName:Mp,backendName:"webgl",kernelFunc:fot};function dot(r){let{inputs:t,backend:e,attrs:n}=r,{value:o}=t,{axis:s}=n;s<0&&(s+=o.shape.length);let i=o,a=i.shape.length,u=o.shape[s],l=new Array(a-1),c=0;for(let h=0;h<a;h++)h!==s&&(l[c++]=i.shape[h]);let p=[],m=new Array(a).fill(0),f=i.shape.slice();f[s]=1;let d=new Array(u);for(let h=0;h<d.length;h++){m[s]=h;let g=ci({inputs:{x:i},backend:e,attrs:{begin:m,size:f}}),y=ut({inputs:{x:g},backend:e,attrs:{shape:l}});d[h]=y,p.push(g)}return p.forEach(h=>e.disposeIntermediateTensorInfo(h)),d}var lB={kernelName:Ti,backendName:"webgl",kernelFunc:dot};var oT=class{constructor(t,e){this.variableNames=["x","segmentIds"];let n=t.windowSize,o=t.batchSize,s=t.inSize,i=t.numSegments,a=i*Math.ceil(s/n);this.outputShape=[o,a];let u="0.0",l="sumValue",c=Math.floor(n/4)*4,p=n%4,m=`
sumValue += dot(values, segFilter);
`,f="";s%n>0&&(f=`
if (inIdx < 0 || inIdx >= ${s}) {
return initializationValue;
}
`);let d="";s%n>0&&(d=`
if (inIdx < 0 || inIdx >= ${s}) {
return -1.0;
}
`),this.userCode=`
const float initializationValue = ${u};
float getValue(int batch, int inIdx) {
${f}
return getX(batch, inIdx);
}
float getSegmentIdAtIndex(int inIdx) {
${d}
return getSegmentIds(inIdx);
}
void main() {
ivec2 coords = getOutputCoords();
int batch = coords[0];
int outIdx = coords[1];
int inOffset = int(floor(float(outIdx) / float(
${i})) * float(${n}));
int currentSeg = int(mod(float(outIdx), float(${i})));
float sumValue = 0.0;
for (int i = 0; i < ${c}; i += 4) {
int inIdx = inOffset + i;
vec4 values = vec4(
getValue(batch, inIdx),
getValue(batch, inIdx + 1),
getValue(batch, inIdx + 2),
getValue(batch, inIdx + 3)
);
vec4 segFilter = vec4(
int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,
int(getSegmentIdAtIndex(inIdx + 1)) == currentSeg ? 1 : 0,
int(getSegmentIdAtIndex(inIdx + 2)) == currentSeg ? 1 : 0,
int(getSegmentIdAtIndex(inIdx + 3)) == currentSeg ? 1 : 0
);
${m}
}
int inIdx = inOffset + ${c};
if (${p===1}) {
vec4 values = vec4(
getValue(batch, inIdx),
initializationValue,
initializationValue,
initializationValue
);
int inIdxSeg = int(getSegmentIdAtIndex(inIdx));
vec4 segFilter = vec4(
int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,
0,
0,
0
);
${m}
} else if (${p===2}) {
vec4 values = vec4(
getValue(batch, inIdx),
getValue(batch, inIdx + 1),
initializationValue,
initializationValue
);
vec4 segFilter = vec4(
int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,
int(getSegmentIdAtIndex(inIdx + 1)) == currentSeg ? 1 : 0,
0,
0
);
${m}
} else if (${p===3}) {
vec4 values = vec4(
getValue(batch, inIdx),
getValue(batch, inIdx + 1),
getValue(batch, inIdx + 2),
initializationValue
);
vec4 segFilter = vec4(
int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,
int(getSegmentIdAtIndex(inIdx + 1)) == currentSeg ? 1 : 0,
int(getSegmentIdAtIndex(inIdx + 2)) == currentSeg ? 1 : 0,
0
);
${m}
}
setOutput(${l});
}
`}};function hot(r){let{inputs:t,backend:e,attrs:n}=r,{x:o,segmentIds:s}=t,{numSegments:i}=n,a=o.shape.length,u=[],l=0,c=k.getAxesPermutation([l],a),p=o;c!=null&&(p=Le({inputs:{x:o},backend:e,attrs:{perm:c}}),u.push(p),l=k.getInnerMostAxes(1,a)[0]);let m=k.segment_util.computeOutShape(p.shape,l,i),f=x.sizeFromShape([p.shape[l]]),d=ut({inputs:{x:p},backend:e,attrs:{shape:[-1,f]}});u.push(d);let h=Tu(o.dtype),g=(v,I,E,D,$)=>{let R=v.shape[0],M=v.shape[1],W=k.segment_util.segOpComputeOptimalWindowSize(M,$),U={windowSize:W,inSize:M,batchSize:R,numSegments:$},q=new oT(U,I),K=e.compileAndRun(q,[v,E],D);if(u.push(K),K.shape[1]===$)return K;let j=VN({backend:e,attrs:{start:0,stop:$,step:1,dtype:"float32"}}),Q=tT({inputs:{x:j},backend:e,attrs:{reps:[M/W]}});return u.push(j),u.push(Q),g(K,I,Q,D,$)},y=g(d,"unsortedSegmentSum",s,h,i),b=ut({inputs:{x:y},backend:e,attrs:{shape:m}}),w=b;if(c!=null){u.push(b);let v=k.getUndoAxesPermutation(c);w=Le({inputs:{x:w},backend:e,attrs:{perm:v}})}return u.forEach(v=>e.disposeIntermediateTensorInfo(v)),w}var uB={kernelName:Fl,backendName:"webgl",kernelFunc:hot};var got=[QM,eL,rL,nL,sL,iL,aL,lL,pL,mL,fL,dL,hL,gL,xL,yL,bL,wL,vL,CL,IL,kL,NL,TL,DL,RL,FL,VM,PL,LL,zL,BL,VL,GL,WL,UL,HL,qL,KL,YL,ZL,JL,QL,tz,ez,rz,nz,oz,sz,iz,az,lz,uz,cz,mz,fz,dz,hz,xz,yz,bz,wz,vz,Cz,Iz,Sz,kz,BM,Nz,ML,Tz,_z,Ez,GM,Az,Dz,$z,Rz,Fz,Oz,Pz,Mz,Lz,zz,Vz,Gz,Wz,Uz,Hz,qz,jz,Yz,Zz,Jz,Qz,t3,s3,KM,i3,a3,l3,u3,_L,c3,f3,d3,h3,g3,WM,x3,y3,EL,e3,b3,w3,v3,XM,C3,I3,S3,k3,N3,T3,_3,E3,A3,D3,$3,R3,F3,O3,P3,SL,o3,M3,L3,z3,B3,V3,G3,W3,U3,q3,K3,X3,Y3,Z3,J3,Q3,tB,n3,ZM,eB,rB,nB,sB,iB,JM,aB,lB,uB,p3];for(let r of got)vu(r);var Zt;(function(r){r[r.float32=0]="float32",r[r.int32=1]="int32",r[r.bool=2]="bool",r[r.string=3]="string",r[r.complex64=4]="complex64"})(Zt||(Zt={}));var lu;(function(r){r[r.linear=0]="linear",r[r.relu=1]="relu",r[r.relu6=2]="relu6",r[r.prelu=3]="prelu",r[r.leakyrelu=4]="leakyrelu",r[r.sigmoid=5]="sigmoid",r[r.elu=6]="elu"})(lu||(lu={}));var cB;function xot(r){cB=r.wasm.cwrap(Ei,null,["number","array","number","number","array","number","number","number","number","number","number","number","number"])}function yot(r){let{inputs:t,backend:e,attrs:n}=r,{a:o,b:s,bias:i,preluActivationWeights:a}=t;if(o.dtype!=="float32"||s.dtype!=="float32")throw new Error("_FusedMatMul for non non-float32 tensors not yet supported.");let{transposeA:u,transposeB:l,activation:c,leakyreluAlpha:p}=n,m=e.dataIdMap.get(o.dataId).id,f=e.dataIdMap.get(s.dataId).id,d=0;if(i!=null){let $=e.dataIdMap.get(i.dataId);if($.shape.length!==1)throw new Error(`_FusedMatMul only supports rank-1 bias but got rank ${$.shape.length}.`);d=$.id}let h=a==null?0:e.dataIdMap.get(a.dataId).id,g=lu[c];if(g==null)throw new Error(`${c} activation not yet supported for FusedConv2D in the wasm backend.`);let y=u?o.shape[2]:o.shape[1],b=l?s.shape[1]:s.shape[2],w=Mr.assertAndGetBroadcastShape(o.shape.slice(0,-2),s.shape.slice(0,-2)),v=e.makeOutput([...w,y,b],o.dtype),I=e.dataIdMap.get(v.dataId).id,E=new Uint8Array(new Int32Array(o.shape).buffer),D=new Uint8Array(new Int32Array(s.shape).buffer);return cB(m,E,o.shape.length,f,D,s.shape.length,u,l,g,d,h,p||0,I),v}var pB={kernelName:Ei,backendName:"wasm",setupFunc:xot,kernelFunc:yot};function ue(r,t){let e;function n(s){e=s.wasm.cwrap(r,null,["number","number","number"])}function o(s){let{backend:i,inputs:{x:a}}=s,u=i.dataIdMap.get(a.dataId).id,l=i.makeOutput(a.shape,t||a.dtype),c=i.dataIdMap.get(l.dataId).id;return x.sizeFromShape(l.shape)===0||e(u,Zt[a.dtype],c),l}return{kernelName:r,backendName:"wasm",setupFunc:n,kernelFunc:o}}var mB=ue(di);function Ce(r,t,e){let n;function o(i){n=i.wasm.cwrap(r,null,["number","array","number","number","array","number","number","number"])}function s(i){let{backend:a,inputs:u}=i,{a:l,b:c}=u,p=a.dataIdMap.get(l.dataId).id,m=a.dataIdMap.get(c.dataId).id,f=e!=null?e:l.dtype,d=k.assertAndGetBroadcastShape(l.shape,c.shape),h=a.makeOutput(d,f);if(x.sizeFromShape(d)===0)return h;let g=new Uint8Array(new Int32Array(l.shape).buffer),y=new Uint8Array(new Int32Array(c.shape).buffer),b=a.dataIdMap.get(h.dataId).id;return(()=>n(p,g,l.shape.length,m,y,c.shape.length,Zt[l.dtype],b))(),h}return{kernelName:r,backendName:"wasm",setupFunc:o,kernelFunc:s}}var bot=!0,fB=Ce(Kn,bot);var dB;function wot(r){dB=r.wasm.cwrap(qo,null,["array","number","number","number"])}function vot(r){let{inputs:t,backend:e}=r,n=e.makeOutput(t[0].shape,t[0].dtype);if(x.sizeFromShape(n.shape)===0)return n;let o=t.map(a=>e.dataIdMap.get(a.dataId).id),s=new Uint8Array(new Int32Array(o).buffer),i=e.dataIdMap.get(n.dataId).id;return dB(s,o.length,Zt[n.dtype],i),n}var hB={kernelName:qo,backendName:"wasm",setupFunc:wot,kernelFunc:vot};function Vc(r){let{inputs:{x:t},backend:e}=r,n=e.makeOutput(t.shape,t.dtype),o=e.typedArrayFromHeap(t);return e.typedArrayFromHeap(n).set(o),n}var gB={kernelName:so,backendName:"wasm",kernelFunc:Vc};var xB;function Cot(r){xB=r.wasm.cwrap(zs,null,["number","array","number","number","number","array","number"])}function qi(r){let{inputs:t,backend:e,attrs:n}=r,[o,s]=Sot(t.x.shape,n.perm),i=!0;for(let d=0;d<s.length;d++)s[d]!==d&&(i=!1);let a=Iot(t.x.shape,n.perm),u={dataId:t.x.dataId,shape:o,dtype:t.x.dtype};if(i){let d=Vc({inputs:t,backend:e});return d.shape=a,d}let l=e.makeOutput(a,u.dtype),c=e.dataIdMap.get(u.dataId).id,p=e.dataIdMap.get(l.dataId).id,m=new Uint8Array(new Int32Array(s).buffer),f=new Uint8Array(new Int32Array(u.shape).buffer);return xB(c,f,u.shape.length,Zt[u.dtype],p,m,s.length),l}function Iot(r,t){let e=new Array(r.length);for(let n=0;n<e.length;n++)e[n]=r[t[n]];return e}function Sot(r,t){let e=[],n=[];for(let o=0;o<r.length;++o)r[o]!==1&&e.push(r[o]),r[t[o]]!==1&&n.push(t[o]);for(let o=0;o<n.length;++o){let s=-1;for(let i=0;i<n.length;++i)n[i]>=o&&(s===-1||n[s]>n[i])&&(s=i);n[s]=o}return[e,n]}var yB={kernelName:zs,backendName:"wasm",kernelFunc:qi,setupFunc:Cot};function vn(r,t,e){let n=r.shape,o=r.shape.length,s=x.parseAxisParam(t,n),i=s,a=k.getAxesPermutation(i,o),u=null,l=!1;if(a!=null){let c=new Array(o);for(let f=0;f<c.length;f++)c[f]=n[a[f]];i=k.getInnerMostAxes(i.length,o),u=qi({inputs:{x:r},attrs:{perm:a},backend:e});let p=e.dataIdMap.get(r.dataId).id;e.dataIdMap.get(u.dataId).id!==p&&(l=!0)}return{transposed:u,originalAxes:s,axes:i,inputWasTransposed:l}}var bB;function kot(r){bB=r.wasm.cwrap(Yi,null,["number, number, number"])}function Not(r){let{backend:t,inputs:e,attrs:n}=r,{axis:o,keepDims:s}=n,{x:i}=e,u=t.dataIdMap.get(i.dataId).id,l=i,{transposed:c,axes:p,originalAxes:m,inputWasTransposed:f}=vn(i,o,t);if(f){let w=t.dataIdMap.get(c.dataId).id;l=c,u=w}let d=l.shape.length;k.assertAxesAreInnerMostDims("all",p,d);let[h,g]=k.computeOutAndReduceShapes(l.shape,p),y=x.sizeFromShape(g),b=t.makeOutput(h,i.dtype);if(x.sizeFromShape(l.shape)!==0){let w=t.dataIdMap.get(b.dataId).id;bB(u,y,w)}if(f&&t.disposeData(c.dataId),s){let w=k.expandShapeToKeepDim(b.shape,m);b.shape=w}return b}var wB={kernelName:Yi,backendName:"wasm",setupFunc:kot,kernelFunc:Not};var vB;function Tot(r){vB=r.wasm.cwrap(Zi,null,["number, number, number"])}function _ot(r){let{backend:t,inputs:e,attrs:n}=r,{axis:o,keepDims:s}=n,{x:i}=e,u=t.dataIdMap.get(i.dataId).id,l=i,{transposed:c,axes:p,originalAxes:m,inputWasTransposed:f}=vn(i,o,t);if(f){let w=t.dataIdMap.get(c.dataId).id;l=c,u=w}let d=l.shape.length;k.assertAxesAreInnerMostDims("any",p,d);let[h,g]=k.computeOutAndReduceShapes(l.shape,p),y=x.sizeFromShape(g),b=t.makeOutput(h,i.dtype);if(x.sizeFromShape(l.shape)!==0){let w=t.dataIdMap.get(b.dataId).id;vB(u,y,w)}if(f&&t.disposeData(c.dataId),s){let w=k.expandShapeToKeepDim(b.shape,m);b.shape=w}return b}var CB={kernelName:Zi,backendName:"wasm",setupFunc:Tot,kernelFunc:_ot};var IB;function Eot(r){IB=r.wasm.cwrap(Ko,null,["number","number","number","number","number"])}function Aot(r){let{backend:t,inputs:e,attrs:n}=r,{axis:o}=n,{x:s}=e,i=t.dataIdMap.get(s.dataId).id,a=i,u=s,{transposed:l,axes:c,inputWasTransposed:p}=vn(s,o,t);if(p){let y=t.dataIdMap.get(l.dataId).id;y!==i&&(u=l,a=y)}let m=u.shape.slice(0,-1),f=t.makeOutput(m,"int32"),d=t.dataIdMap.get(f.dataId).id,h=x.sizeFromShape(f.shape),g=u.shape[c[0]];return IB(a,Zt[u.dtype],h,g,d),p&&t.disposeData(l.dataId),f}var SB={kernelName:Ko,backendName:"wasm",kernelFunc:Aot,setupFunc:Eot};var kB;function Dot(r){kB=r.wasm.cwrap(jo,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function $ot(r){let{inputs:t,attrs:e,backend:n}=r,o=t.x,s=n.dataIdMap.get(o.dataId).id,{filterSize:i,strides:a,pad:u,dimRoundingMode:l}=e,c=k.computePool2DInfo(o.shape,i,a,1,u,l),p=c.filterHeight,m=c.filterWidth,f=c.padInfo.top,d=c.padInfo.right,h=c.padInfo.bottom,g=c.padInfo.left,y=c.strideHeight,b=c.strideWidth,w=c.inChannels;if(c.dataFormat!=="channelsLast")throw new Error(`wasm backend does not support dataFormat:'${c.dataFormat}'. 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t.dtype==="string"?p.stringBytes=u.slice(d,d+x.sizeFromShape(i)):o.typedArrayFromHeap(l).set(u.subarray(d,d+x.sizeFromShape(i))),l}if(t.dtype==="string"){let d=Tc(u,s,i,t.shape,t.dtype);return p.stringBytes=d,l}let m=o.typedArrayFromHeap(l),f=t.shape.length;if(f===2)Oot(u,c[0],m,s,i);else if(f===3)Pot(u,c[0],c[1],m,s,i);else if(f===4)Mot(u,c[0],c[1],c[2],m,s,i);else{let d=Tc(u,s,i,t.shape,t.dtype);m.set(d)}return l}function Oot(r,t,e,n,o){let s=0,i=n[0],a=n[1],u=i+o[0];for(let l=i;l<u;l++){let c=l*t+a;e.set(r.subarray(c,c+o[1]),s),s+=o[1]}}function Pot(r,t,e,n,o,s){let i=0,a=o[0],u=o[1],l=o[2],c=a+s[0],p=u+s[1];for(let m=a;m<c;m++)for(let f=u;f<p;f++){let d=m*t+f*e+l;n.set(r.subarray(d,d+s[2]),i),i+=s[2]}}function Mot(r,t,e,n,o,s,i){let a=0,u=s[0],l=s[1],c=s[2],p=u+i[0],m=l+i[1],f=c+i[2],d=s[3];for(let h=u;h<p;h++)for(let g=l;g<m;g++)for(let y=c;y<f;y++){let b=h*t+g*e+y*n+d;o.set(r.subarray(b,b+i[3]),a),a+=i[3]}}var AB={kernelName:Si,backendName:"wasm",kernelFunc:Oo};function Lot(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{blockShape:s,crops:i}=n,a=s.reduce((y,b)=>y*b),u=k.getReshaped(o.shape,s,a),l=k.getPermuted(u.length,s.length),c=k.getReshapedPermuted(o.shape,s,a),p=k.getSliceBeginCoords(i,s.length),m=k.getSliceSize(c,i,s.length),f=cr({inputs:{x:o},backend:e,attrs:{shape:u}}),d=qi({inputs:{x:f},backend:e,attrs:{perm:l}}),h=cr({inputs:{x:d},backend:e,attrs:{shape:c}}),g=Oo({inputs:{x:h},backend:e,attrs:{begin:p,size:m}});return e.disposeData(f.dataId),e.disposeData(d.dataId),e.disposeData(f.dataId),g}var DB={kernelName:hi,backendName:"wasm",kernelFunc:Lot};function dl(r){let{inputs:{x:t},attrs:{dtype:e},backend:n}=r,o=n.makeOutput(t.shape,e),s=n.typedArrayFromHeap(t);return n.typedArrayFromHeap(o).set(s),o}var $B={kernelName:no,backendName:"wasm",kernelFunc:dl};var RB=ue(Yo);var FB;function zot(r){FB=r.wasm.cwrap(oo,null,["number","number","number","number"])}function Bot(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{clipValueMin:s,clipValueMax:i}=n,a=e.dataIdMap.get(o.dataId).id,u=e.makeOutput(o.shape,o.dtype),l=e.dataIdMap.get(u.dataId).id;return FB(a,s,i,l),u}var OB={kernelName:oo,backendName:"wasm",setupFunc:zot,kernelFunc:Bot};function sT(r){let{inputs:t,backend:e}=r,n=x.parseAxisParam(r.attrs.axis,t[0].shape)[0],o=k.computeOutShape(t.map(f=>f.shape),n),s=t.filter(f=>x.sizeFromShape(f.shape)>0);if(s.length===1)return Vc({inputs:{x:s[0]},backend:e});let i=e.makeOutput(o,t[0].dtype);if(x.sizeFromShape(o)===0)return i;let a=s.map(f=>f.shape);if(k.assertParamsConsistent(a,n),s[0].dtype==="string"){let f=s.map(w=>{let v=x.sizeFromShape(w.shape.slice(n));return cr({inputs:{x:w},backend:e,attrs:{shape:[-1,v]}})}),d=f.map(w=>({vals:e.readSync(w.dataId),shape:w.shape}));o=k.computeOutShape(f.map(w=>w.shape),1);let h=f[0].shape[0]===1,g=Sc(d,o,t[0].dtype,h),y=k.computeOutShape(s.map(w=>w.shape),n);i.shape=y;let b=e.dataIdMap.get(i.dataId);return b.stringBytes=k.fromStringArrayToUint8(g),f.forEach(w=>e.disposeData(w.dataId)),i}let u=x.sizeFromShape(s[0].shape.slice(0,n)),l=0,c=s.map(f=>{let d=x.sizeFromShape(f.shape.slice(n));return l+=d,d}),p=s.map(f=>e.typedArrayFromHeap(f)),m=e.typedArrayFromHeap(i);for(let f=0;f<u;f++){let d=f*l;for(let h=0;h<p.length;h++){let g=c[h],y=f*g,b=p[h].subarray(y,y+g);m.set(b,d),d+=g}}return i}var PB={kernelName:gi,backendName:"wasm",kernelFunc:sT};var MB;function Vot(r){MB=r.wasm.cwrap(Zo,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function Got(r){let{inputs:t,attrs:e,backend:n}=r,{x:o,filter:s}=t,i=n.dataIdMap.get(o.dataId).id,a=n.dataIdMap.get(s.dataId).id,{strides:u,dilations:l,pad:c,dimRoundingMode:p,dataFormat:m}=e,f=k.convertConv2DDataFormat(m),d=k.computeConv2DInfo(o.shape,s.shape,u,l,c,p,!1,f),h=d.filterHeight,g=d.filterWidth,y=d.padInfo.top,b=d.padInfo.right,w=d.padInfo.bottom,v=d.padInfo.left,I=d.dilationHeight,E=d.dilationWidth,D=d.strideHeight,$=d.strideWidth,R=d.inChannels,M=d.outChannels,W=d.padInfo.type==="SAME"?1:0;if(d.dataFormat!=="channelsLast")throw new Error(`wasm backend Conv2D does not support dataFormat:'${d.dataFormat}'. Please use 'channelsLast'.`);let U=n.makeOutput(d.outShape,"float32"),q=n.dataIdMap.get(U.dataId).id;return MB(i,o.shape[0],o.shape[1],o.shape[2],a,h,g,y,b,w,v,W,I,E,D,$,R,M,q),U}var LB={kernelName:Zo,backendName:"wasm",setupFunc:Vot,kernelFunc:Got};var zB;function Wot(r){zB=r.wasm.cwrap(Jo,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 Uot(r){let{backend:t,inputs:e,attrs:n}=r,{dy:o,filter:s}=e,{strides:i,pad:a,dataFormat:u,dimRoundingMode:l,inputShape:c}=n,p=1,m=k.convertConv2DDataFormat(u),f=k.computeConv2DInfo(c,s.shape,i,p,a,l,!1,m),{batchSize:d,filterHeight:h,filterWidth:g,inChannels:y,inHeight:b,inWidth:w,outChannels:v,outHeight:I,outWidth:E,strideHeight:D,strideWidth:$}=f,R=h-1-f.padInfo.top,M=g-1-f.padInfo.left,W=f.dataFormat==="channelsLast",U=x.computeStrides(f.inShape),q=x.computeStrides(o.shape),[K,j,Q]=x.computeStrides(s.shape),rt=U[0],X=W?U[1]:U[2],nt=W?U[2]:1,st=W?1:U[1],it=q[0],ft=W?q[1]:q[2],at=W?q[2]:1,xt=W?1:q[1],dt=t.makeOutput(f.inShape,"float32"),bt=t.dataIdMap.get(dt.dataId).id,kt=t.dataIdMap.get(o.dataId).id,At=t.dataIdMap.get(s.dataId).id;return zB(kt,At,d,h,g,b,w,y,I,E,v,D,$,R,M,K,j,Q,rt,X,nt,st,it,ft,at,xt,bt),dt}var BB={kernelName:Jo,backendName:"wasm",setupFunc:Wot,kernelFunc:Uot};var VB=ue(Qo);var GB=ue(ts);var iT;(function(r){r[r.bilinear=0]="bilinear",r[r.nearest=1]="nearest"})(iT||(iT={}));var WB;function Hot(r){WB=r.wasm.cwrap(na,null,["number","number","number","number","array","number","number","number","number","number"])}function qot(r){let{backend:t,inputs:e,attrs:n}=r,{method:o,extrapolationValue:s,cropSize:i}=n,{image:a,boxes:u,boxInd:l}=e,c=u.shape[0],[p,m]=i,f=[c,p,m,a.shape[3]],d=t.dataIdMap.get(a.dataId),h;a.dtype!=="float32"&&(h=dl({backend:t,inputs:{x:a},attrs:{dtype:"float32"}}),d=t.dataIdMap.get(h.dataId));let g=d.id,y=t.dataIdMap.get(u.dataId).id,b=t.dataIdMap.get(l.dataId).id,w=t.makeOutput(f,"float32"),v=t.dataIdMap.get(w.dataId).id,I=new Uint8Array(new Int32Array(a.shape).buffer);return WB(g,y,b,c,I,p,m,iT[o],s,v),h!=null&&t.disposeData(h.dataId),w}var UB={kernelName:na,backendName:"wasm",setupFunc:Hot,kernelFunc:qot};var HB;function Kot(r){HB=r.wasm.cwrap(es,null,["number","number","number","number","number","number"])}function jot(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{axis:s,exclusive:i,reverse:a}=n,u=o.shape.length;x.assert(o.dtype==="float32"||o.dtype==="int32",()=>`cumsum does not support ${o.dtype} tensors in the WASM backend`);let l=k.getAxesPermutation([s],u),c=o;l!==null&&(c=qi({inputs:{x:o},attrs:{perm:l},backend:e}));let p=k.getInnerMostAxes(1,u)[0];k.assertAxesAreInnerMostDims("cumsum",[p],u);let m=e.makeOutput(c.shape,c.dtype),f=c.shape[p],d=e.dataIdMap.get(c.dataId).id,h=e.dataIdMap.get(m.dataId).id;HB(d,i?1:0,a?1:0,f,h,Zt[o.dtype]);let g=m;if(l!==null){let y=k.getUndoAxesPermutation(l);g=qi({inputs:{x:m},attrs:{perm:y},backend:e}),e.disposeData(c.dataId),e.disposeData(m.dataId)}return g}var qB={kernelName:es,backendName:"wasm",setupFunc:Kot,kernelFunc:jot};var KB;function Xot(r){KB=r.wasm.cwrap(oa,null,["number","number","number","array","number","array","array","number","number"])}function Yot(r){let{backend:t,inputs:e,attrs:n}=r,{x:o}=e,{blockSize:s,dataFormat:i}=n,a=o.shape[0],u=i==="NHWC"?o.shape[1]:o.shape[2],l=i==="NHWC"?o.shape[2]:o.shape[3],c=i==="NHWC"?o.shape[3]:o.shape[1],p=u*s,m=l*s,f=c/(s*s),d=i==="NHWC"?[a,p,m,f]:[a,f,p,m],h=t.makeOutput(d,"float32"),y=t.dataIdMap.get(o.dataId).id,b=new Uint8Array(new Int32Array(x.computeStrides(o.shape)).buffer),w=new Uint8Array(new Int32Array(d).buffer),v=new Uint8Array(new Int32Array(x.computeStrides(d)).buffer),I=t.dataIdMap.get(h.dataId).id;return KB(y,s,i==="NHWC"?1:0,b,o.shape.length-1,w,v,d.length,I),h}var jB={kernelName:oa,backendName:"wasm",setupFunc:Xot,kernelFunc:Yot};var XB;function Zot(r){XB=r.wasm.cwrap(rs,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function Jot(r){let{inputs:t,attrs:e,backend:n}=r,{x:o,filter:s}=t,i=n.dataIdMap.get(o.dataId).id,a=n.dataIdMap.get(s.dataId).id,{strides:u,dilations:l,pad:c,dimRoundingMode:p}=e,m=l==null?[1,1]:l,f=k.computeConv2DInfo(o.shape,s.shape,u,m,c,p,!0),d=f.filterHeight,h=f.filterWidth,g=f.padInfo.top,y=f.padInfo.right,b=f.padInfo.bottom,w=f.padInfo.left,v=f.dilationHeight,I=f.dilationWidth,E=f.strideHeight,D=f.strideWidth,$=f.inChannels,R=f.outChannels,M=f.padInfo.type==="SAME"?1:0;if(f.dataFormat!=="channelsLast")throw new Error(`wasm backend DepthwiseConv2dNative does not support dataFormat:'${f.dataFormat}'. 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lT;(function(r){r[r.reflect=0]="reflect",r[r.symmetric=1]="symmetric"})(lT||(lT={}));var FV;function Ast(r){FV=r.wasm.cwrap(ys,null,["number","array","number","number","array","array","number","number"])}function Dst(r){let{inputs:{x:t},backend:e,attrs:{paddings:n,mode:o}}=r,s=n.map((d,h)=>d[0]+t.shape[h]+d[1]),i=e.dataIdMap.get(t.dataId).id,a=e.makeOutput(s,t.dtype),u=e.dataIdMap.get(a.dataId).id,l=new Uint8Array(new Int32Array(t.shape).buffer),c=n.map(d=>d[0]),p=n.map(d=>d[1]),m=new Uint8Array(new Int32Array(c).buffer),f=new Uint8Array(new Int32Array(p).buffer);return FV(i,l,t.shape.length,Zt[t.dtype],m,f,lT[o],u),a}var OV={kernelName:ys,backendName:"wasm",kernelFunc:Dst,setupFunc:Ast};var $st=!0,PV=Ce(bs,$st);var MV=ue(bi);function Qm(r,t){let e=new Int32Array(r.wasm.HEAPU8.buffer,t,4),n=e[0],o=e[1],s=e[2],i=e[3];return r.wasm._free(t),{pSelectedIndices:n,selectedSize:o,pSelectedScores:s,pValidOutputs:i}}var LV;function 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tit(r){let{backend:t,inputs:e,attrs:n}=r,{images:o}=e,{alignCorners:s,halfPixelCenters:i,size:a}=n,[u,l]=a,[c,p,m,f]=o.shape,d=[c,u,l,f],h=t.dataIdMap.get(o.dataId),g;h.dtype!=="float32"&&(g=dl({backend:t,inputs:{x:o},attrs:{dtype:"float32"}}),h=t.dataIdMap.get(g.dataId));let y=h.id,b=t.makeOutput(d,"float32");if(x.sizeFromShape(o.shape)===0)return b;let w=t.dataIdMap.get(b.dataId).id;return sG(y,c,p,m,f,u,l,s?1:0,i?1:0,w),g!=null&&t.disposeData(g.dataId),b}var iG={kernelName:ks,backendName:"wasm",setupFunc:Qst,kernelFunc:tit};var aG;function eit(r){aG=r.wasm.cwrap(Ts,null,["number","array","number","array","number","number"])}function rit(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{dims:s}=n,i=x.parseAxisParam(s,o.shape);if(o.shape.length===0)return Vc({inputs:{x:o},backend:e});let a=e.makeOutput(o.shape,o.dtype),u=e.dataIdMap.get(o.dataId).id,l=e.dataIdMap.get(a.dataId).id,c=new Uint8Array(new Int32Array(i).buffer),p=new Uint8Array(new 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xG;function uit(r){xG=r.wasm.cwrap(Ds,null,["number","number"])}function cit(r){let{backend:t,inputs:{x:e}}=r,n=t.dataIdMap.get(e.dataId).id,o=t.makeOutput(e.shape,e.dtype),s=t.dataIdMap.get(o.dataId).id;return x.sizeFromShape(o.shape)===0||xG(n,s),o}var yG={kernelName:"Sigmoid",backendName:"wasm",setupFunc:uit,kernelFunc:cit};var bG=ue(As);var wG;function pit(r){wG=r.wasm.cwrap(Fs,null,["number","number","number","number"])}function mit(r){let{backend:t,inputs:{logits:e},attrs:{dim:n}}=r,o=t.dataIdMap.get(e.dataId).id,s=t.makeOutput(e.shape,e.dtype),i=t.dataIdMap.get(s.dataId).id,a=e.shape[n],u=x.sizeFromShape(e.shape)/a;return x.sizeFromShape(s.shape)===0||wG(o,i,a,u),s}var vG={kernelName:Fs,backendName:"wasm",setupFunc:pit,kernelFunc:mit};function fit(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{blockShape:s,paddings:i}=n,a=x.sizeFromShape(s),u=[[0,0]];u.push(...i);for(let E=1+s.length;E<o.shape.length;++E)u.push([0,0]);let l=Ob.kernelFunc({inputs:{x:o},backend:e,attrs:{paddings:u,constantValue:0}}),c=k.getReshaped(l.shape,s,a,!1),p=k.getPermuted(c.length,s.length,!1),m=k.getReshapedPermuted(l.shape,s,a,!1),h=cr({inputs:{x:l},backend:e,attrs:{shape:c}}),b=qi({inputs:{x:h},backend:e,attrs:{perm:p}}),I=cr({inputs:{x:b},backend:e,attrs:{shape:m}});return e.disposeData(l.dataId),e.disposeData(h.dataId),e.disposeData(b.dataId),I}var CG={kernelName:ki,backendName:"wasm",kernelFunc:fit};var IG;function dit(r){IG=r.wasm.cwrap("SparseFillEmptyRows","number",["number","number","number","number","number","number","number","number","number","number","number","number"])}function hit(r){let{backend:t,inputs:e}=r,{indices:n,values:o,denseShape:s,defaultValue:i}=e,a=n.shape[0],u=n.shape[1],l=t.readSync(s.dataId)[0],c=[a+l,u],p=t.dataIdMap.get(n.dataId).id,m=t.dataIdMap.get(o.dataId).id,f=t.dataIdMap.get(i.dataId).id,d=t.makeOutput(c,n.dtype),h=t.dataIdMap.get(d.dataId).id,g=t.makeOutput(c.slice(0,1),o.dtype),y=t.dataIdMap.get(g.dataId).id,b=t.makeOutput([l],"bool"),w=t.dataIdMap.get(b.dataId).id,v=t.makeOutput([a],n.dtype),I=t.dataIdMap.get(v.dataId).id,E=t.makeOutput([4],"int32"),D=t.dataIdMap.get(E.dataId).id,$=IG(p,m,Zt[o.dtype],a,l,u,f,h,y,w,I,D),R=t.readSync(E.dataId),M;switch(R[0]){case 1:{M=k.getSparseFillEmptyRowsIndicesDenseShapeMismatch(R[1]);break}case 2:{M=k.getSparseFillEmptyRowsNegativeIndexErrorMessage(R[1],R[2]);break}case 3:M=k.getSparseFillEmptyRowsOutOfRangeIndexErrorMessage(R[1],R[2],R[3]);break;default:M=""}if(t.disposeData(E.dataId),M)throw t.disposeData(d.dataId),t.disposeData(g.dataId),t.disposeData(b.dataId),t.disposeData(v.dataId),new 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w=Array.from(t.readSync(o.dataId)),v=Array.from(t.readSync(f.dataId));b=k.getSparseReshapeInputOutputMismatchErrorMessage(w,v);break}default:b=""}if(t.disposeData(h.dataId),b)throw t.disposeData(p.dataId),t.disposeData(f.dataId),new Error(b);return[p,f]}var NG={kernelName:Aa,backendName:"wasm",setupFunc:git,kernelFunc:xit};var TG;function Pb(r){TG=r.wasm.cwrap("SparseSegmentReduction",null,["number","number","number","number","number","number","number","number","number"])}function Mb(r,t){let{backend:e,inputs:n}=r,{data:o,indices:s,segmentIds:i}=n,a=s.shape[0],u=e.readSync(i.dataId,a-1,a)[0],c=a>0?u+1:0;if(c<0)throw new Error(k.getSparseSegmentReductionNegativeSegmentIdsErrorMessage());let p=o.shape.slice();p[0]=c;let m=e.dataIdMap.get(o.dataId).id,f=e.dataIdMap.get(s.dataId).id,d=e.dataIdMap.get(i.dataId).id,h=e.makeOutput(p,o.dtype),g=e.dataIdMap.get(h.dataId).id,y=e.makeOutput([4],"int32"),b=e.dataIdMap.get(y.dataId).id;TG(m,Zt[o.dtype],o.shape[0],f,d,g,b,t,0);let w=e.readSync(y.dataId),v;switch(w[0]){case 0:{v=k.getSparseSegmentReductionNegativeSegmentIdsErrorMessage();break}case 1:{v=k.getSparseSegmentReductionNonIncreasingSegmentIdsErrorMessage();break}case 2:v=k.getSparseSegmentReductionSegmentIdOutOfRangeErrorMessage(w[1],w[2]);break;case 3:v=k.getSparseSegmentReductionIndicesOutOfRangeErrorMessage(w[1],w[2],w[3]);break;default:v=""}if(e.disposeData(y.dataId),v)throw e.disposeData(h.dataId),new Error(v);return h}function yit(r){return Mb(r,!0)}var _G={kernelName:Dl,backendName:"wasm",setupFunc:Pb,kernelFunc:yit};function bit(r){return Mb(r,!1)}var EG={kernelName:$l,backendName:"wasm",setupFunc:Pb,kernelFunc:bit};function wit(r){let{inputs:t,attrs:e,backend:n}=r,{x:o}=t,{numOrSizeSplits:s,axis:i}=e,a=x.parseAxisParam(i,o.shape)[0],u=k.prepareSplitSize(o,s,a),l=new Array(o.shape.length).fill(0),c=o.shape.slice();return u.map(p=>{let m=[...c];m[a]=p;let f=Oo({inputs:{x:o},attrs:{begin:l,size:m},backend:n});return l[a]+=p,f})}var AG={kernelName:Ni,backendName:"wasm",kernelFunc:wit};var DG=ue($s);var $G=ue(Rl);var vit=!0,RG=Ce(Os,vit);var FG;function Cit(r){FG=r.wasm.cwrap(io,null,["number","number","number","number"])}function Iit(r){let{backend:t,inputs:e,attrs:n}=r,{alpha:o}=n,{x:s}=e,i=t.dataIdMap.get(s.dataId).id,a=t.makeOutput(s.shape,s.dtype),u=t.dataIdMap.get(a.dataId).id;return FG(i,o,Zt[s.dtype],u),a}var OG={kernelName:io,backendName:"wasm",setupFunc:Cit,kernelFunc:Iit};var PG;function Sit(r){PG=r.wasm.cwrap(Da,null,["number","array","number","array","array","array","array","array","number","number"])}function kit(r){let{backend:t,inputs:e,attrs:n}=r,{x:o}=e,{begin:s,end:i,strides:a,beginMask:u,endMask:l,ellipsisMask:c,newAxisMask:p,shrinkAxisMask:m}=n,{finalShapeSparse:f,finalShape:d,isIdentity:h,sliceDim0:g,isSimpleSlice:y,begin:b,end:w,strides:v}=Ve.sliceInfo(o.shape,s,i,a,u,l,c,p,m),I;if(h)I=cr({inputs:{x:o},backend:t,attrs:{shape:d}});else if(g||y){x.assert(o.shape.length>=1,()=>`Input must have 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as RealDiv,Sa as Reciprocal,Ze as Reduction,Ss as Relu,Ns as Relu6,Ci as Reshape,ks as ResizeBilinear,$p as ResizeBilinearGrad,El as ResizeNearestNeighbor,Dp as ResizeNearestNeighborGrad,Ts as Reverse,Fa as RotateWithOffset,_s as Round,Es as Rsqrt,tl as SGDOptimizer,ka as ScatterNd,Ii as Select,Na as Selu,ol as Sequential,Ds as Sigmoid,_a as Sign,As as Sin,Ta as Sinh,Si as Slice,Fs as Softmax,Ea as Softplus,ki as SpaceToBatchND,Al as SparseFillEmptyRows,Aa as SparseReshape,Dl as SparseSegmentMean,$l as SparseSegmentSum,Rp as SparseToDense,Ni as SplitV,$s as Sqrt,Rl as Square,Os as SquaredDifference,io as Step,Da as StridedSlice,Fp as StringNGrams,Op as StringSplit,Pp as StringToHashBucketFast,Ps as Sub,Rs as Sum,hn as SymbolicTensor,Ms as Tan,Ls as Tanh,Bt as Tensor,me as TensorBuffer,jn as Tile,$a as TopK,Ra as Transform,zs as Transpose,Mp as Unique,Ti as Unpack,Fl as UnsortedSegmentSum,Ml as Variable,_i as ZerosLike,Ei as _FusedMatMul,Se as abs,Af as acos,Df as acosh,J as add,p0 as addN,$u as all,Vl as any,Us as argMax,$f as argMin,Rf as asin,Ff as asinh,Of as atan,Pf as atan2,Mf as atanh,Ba as avgPool,Lf as avgPool3d,b_ as backend,k as backend_util,kH as basicLSTMCell,mo as batchNorm,h0 as batchNorm2d,g0 as batchNorm3d,x0 as batchNorm4d,Va as batchToSpaceND,zf as bincount,RTt as booleanMaskAsync,y0 as broadcastArgs,Ga as broadcastTo,Mr as broadcast_util,mx as browser,It as buffer,ZY as callbacks,Z as cast,Bf as ceil,br as clipByValue,Cn as clone,Mn as complex,se as concat,b0 as concat1d,w0 as concat2d,v0 as concat3d,C0 as concat4d,$2 as constraints,Ou as conv1d,ln as conv2d,Pu as conv2dTranspose,Vf as conv3d,I0 as conv3dTranspose,dat as copyRegisteredKernels,Wa as cos,Mu as cosh,Tx as cosineWindow,Lu as cumsum,un as customGrad,dR as data,S0 as denseBincount,c0 as deprecationWarn,Gf as depthToSpace,qs as depthwiseConv2d,e7 as deregisterOp,Ll as device_util,tq as diag,Wf as dilation2d,Mct as disableDeprecationWarnings,_t as dispose,Lct as disposeVariables,ct as div,Uf as divNoNan,k0 as dot,W_ as dropout,N0 as einsum,Ks as elu,Pct as enableDebugMode,Oct as enableProdMode,U_ as enclosingPowerOfTwo,po as engine,G as env,Sr as equal,Hf as erf,Xe as exp,mr as expandDims,qf as expm1,Zp as eye,Ja as fft,js as fill,Uct as findBackend,Hct as findBackendFactory,Xs as floor,Du as floorDiv,zM as forceHalfFloat,yo as fused,fo as gather,V_ as gatherND,fx as gather_util,Gct as getBackend,Tv as getGradient,vf as getKernel,tx as getKernelsForBackend,Uit as getThreadsCount,kk as gpgpu_util,Eq as grad,Aq as grads,Ge as greater,Sn as greaterEqual,Fi as ifft,zu as imag,Nn as image,P1t as inTopKAsync,J2 as initializers,TC as input,Pr as io,Zu as irfft,T0 as isFinite,_0 as isInf,Kf as isNaN,Pe as keep,Vr as kernel_impls,OD as layers,Ua as leakyRelu,Bu as less,kn as lessEqual,EE as linalg,E0 as linspace,j7 as loadGraphModel,l8 as loadLayersModel,jf as localResponseNormalization,wr as log,Ha as log1p,A0 as logSigmoid,Vu as logSoftmax,Yf as logSumExp,Nr as logicalAnd,qa as logicalNot,Gu as logicalOr,O0 as logicalXor,fFt as losses,Mt as matMul,t_ as math,$r as max,Ka as maxPool,Zf as maxPool3d,P0 as maxPoolWithArgmax,cn as maximum,xe as mean,Ef as memory,Jq as meshgrid,PD as metrics,Gl as min,Ys as minimum,Jf as mirrorPad,Qf as mod,i8 as model,MD as models,Jp as moments,n1t as movingAverage,P as mul,iK as multiRNNCell,M0 as multinomial,Yt as neg,J0 as nextFrame,rm as norm,xo as notEqual,Ws as oneHot,ar as ones,fr as onesLike,N as op,pK as outerProduct,qr as pad,dK as pad1d,gK as pad2d,yK as pad3d,wK as pad4d,L0 as pool,Kr as pow,Xa as prelu,t0 as print,Wu as prod,zct as profile,EK as rand,MK as randomGamma,Ix as randomNormal,Zs as randomUniform,Ya as range,Vct as ready,Wl as real,td as reciprocal,jp as registerBackend,u8 as registerCallbackConstructor,KT as registerGradient,vu as registerKernel,t7 as registerOp,LD as regularizers,Tr as relu,Hu as relu6,Wct as removeBackend,O as reshape,or as reverse,qK as reverse1d,jK as reverse2d,YK as reverse3d,JK as reverse4d,Qa as rfft,qu as round,Ku as rsqrt,pt as scalar,z_ as scatterND,_f as scatter_util,ju as selu,ed as separableConv2d,a8 as sequential,et as serialization,K4 as setBackend,qct as setPlatform,Wit as setThreadsCount,Vit as setWasmPath,Git as setWasmPaths,FS as setWebGLContext,X0 as setdiff1dAsync,Lr as sigmoid,rd as sign,BRt as signal,Xu as sin,Yu as sinh,Rt as slice,nd as slice1d,Sx as slice2d,od as slice3d,tm as slice4d,Ve as slice_util,Za as softmax,ho as softplus,ja as spaceToBatchND,cd as sparse,Nx as sparseToDense,ORt as spectral,lr as split,be as sqrt,Gt as square,Ju as squaredDifference,zr as squeeze,Ye as stack,Js as step,sd as stridedSlice,Mx as string,lt as sub,mt as sum,Tu as sumOutType,id as tan,Hs as tanh,Ar as tensor,$e as tensor1d,Oi as tensor2d,o0 as tensor3d,Sj as tensor4d,kj as tensor5d,Nj as tensor6d,co as tensor_util,x_ as test_util,B as tidy,kr as tile,Bct as time,ad as topk,cc as train,Vt as transpose,Qu as truncatedNormal,em as unique,fat as unregisterGradient,mat as unregisterKernel,ld as unsortedSegmentSum,vr as unstack,yr as upcastType,x as util,Dq as valueAndGrad,$q as valueAndGrads,Y0 as variable,bx as variableGrads,eat as version,x$ as version_converter,y_ as version_core,vm as version_layers,Hit as version_wasm,LM as version_webgl,bSe as webgl,Wm as webgl_util,Ne as where,ud as whereAsync,ye as zeros,St as zerosLike};
/**
* @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
* Copyright 2022 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 See the LICENSE file. */
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