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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,Li(`Initialization of backend ${t} failed`),Li(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 Li(`Initialization of backend ${t} failed`),Li(n.stack||n.message),{success:!1,asyncInit:!1}}}removeBackend(t){if(!(t in this.registryFactory))throw new Error(`${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 '${t}'`)}runKernelFunc(t){let e,n=[],o=this.isTapeOn(),s=this.state.numBytes,i=this.state.numTensors;this.shouldCheckForMemLeaks()&&this.state.numDataMovesStack.push(0);let a;this.backendName==null&&this.backend;let u,l=nI(t)?t.kernelName:this.state.activeScope!=null?this.state.activeScope.name:"";if(nI(t)){let{kernelName:d,inputs:h,attrs:g}=t;this.backendName==null&&this.backend;let y=jd(d,this.backendName);A(y!=null,()=>`Cannot find registered kernel '${d}' for backend '${this.backendName}'`),a=()=>{let b=this.backend.numDataIds();u=y.kernelFunc({inputs:h,attrs:g,backend:this.backend});let w=Array.isArray(u)?u:[u];this.shouldCheckForMemLeaks()&&this.checkKernelForMemLeak(d,b,w);let v=w.map(k=>{if(k.rank!=null)return k;let{dataId:E,shape:$,dtype:D}=k;return this.makeTensorFromDataId(E,$,D)});if(o){let k=this.getTensorsForGradient(d,h,v);n=this.saveTensorsForBackwardMode(k)}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=nI(t)?null:t.backwardsFunc,f;return 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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}.`),xo(i,a,u,c,l,s)}var FI=N({batchNorm4d_:UH});function HH(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 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Zs=N({depthwiseConv2d_:fq});function dq(r){let e={x:C(r,"x","diag")};return _.runKernel(Lp,e)}var hq=N({diag_:dq});function gq(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=M(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(Ol,c,p);return l?M(m,[m.shape[1],m.shape[2],m.shape[3]]):m}var bh=N({dilation2d_:gq});function xq(r,t){let e=C(r,"a","equal","string_or_numeric"),n=C(t,"b","equal","string_or_numeric");[e,n]=jt(e,n),Bt(e.shape,n.shape);let o={a:e,b:n};return _.runKernel(da,o)}var Sr=N({equal_:xq});function yq(r,t,e){let n=C(t,"a","where"),o=C(e,"b","where"),s=C(r,"condition","where","bool"),i=Bt(Bt(s.shape,n.shape),o.shape),a=ja(s,i),u=ja(n,i),l=ja(o,i),c={condition:a,t:u,e:l};return _.runKernel(Ei,c)}var _e=N({where_:yq});function bq(r){let e={x:C(r,"x","zerosLike")};return _.runKernel(Fi,e)}var St=N({zerosLike_:bq});function wq(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 _e(i,s,o)}var wh=N({divNoNan_:wq});function vq(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=M(e,[1,-1]),a=M(n,[-1,1]),u=zt(i,a);return M(u,[])}else if(e.rank===1&&n.rank===2){let i=M(e,[1,-1]),a=M(n,[n.shape[0],n.shape[1]]),u=zt(i,a);return 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Ch=N({expm1_:Tq});function _q(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(Yn,n,o)}var kr=N({tile_:_q});function Eq(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=M(o.toTensor(),[r,t]);if(e==null)return i;if(e.length===1)return kr(fr(i,0),[e[0],1,1]);if(e.length===2)return kr(fr(fr(i,0),0),[e[0],e[1],1,1]);if(e.length===3)return kr(fr(fr(fr(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 xm=N({eye_:Eq});function Qs(r,t,e){let n={shape:r,value:t,dtype:e};return _.runKernel(Ml,{},n)}function Aq(r){let e={x:C(r,"x","floor","float32")};return _.runKernel(ps,e)}var ti=N({floor_:Aq});function $q(r,t,e=0,n=0){let o=C(r,"x","gather"),s=C(t,"indices","gather","int32"),i={x:o,indices:s},a={axis:e,batchDims:n};return _.runKernel(Si,i,a)}var yo=N({gather_:$q});function Dq(r,t){let e=C(r,"a","greater","string_or_numeric"),n=C(t,"b","greater","string_or_numeric");[e,n]=jt(e,n),Bt(e.shape,n.shape);let o={a:e,b:n};return _.runKernel(ya,o)}var Ge=N({greater_:Dq});function Rq(r,t){let e=C(r,"a","greaterEqual","string_or_numeric"),n=C(t,"b","greaterEqual","string_or_numeric");[e,n]=jt(e,n),Bt(e.shape,n.shape);let o={a:e,b:n};return _.runKernel(ds,o)}var Tn=N({greaterEqual_:Rq});function Fq(r){let e={input:C(r,"input","imag")};return _.runKernel(Wp,e)}var ec=N({imag_:Fq});function Oq(r){let e={x:C(r,"x","isFinite")};return _.runKernel(ba,e)}var UI=N({isFinite_:Oq});function Mq(r){let e={x:C(r,"x","isInf")};return _.runKernel(wa,e)}var HI=N({isInf_:Mq});function Pq(r){let e={x:C(r,"x","isNaN")};return _.runKernel(va,e)}var Ih=N({isNaN_:Pq});function Lq(r,t=.2){let 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g=0;g<t.length;g++)t[g]>o&&l.push({score:t[g],boxIndex:g,suppressBeginIndex:0});l.sort(_E);let c=s>0?-.5/s:0,p=[],m=[];for(;p.length<e&&l.length>0;){let g=l.pop(),{score:y,boxIndex:b,suppressBeginIndex:w}=g;if(y<o)break;let v=!1;for(let k=p.length-1;k>=w;--k){let E=v6(r,b,p[k]);if(E>=n){v=!0;break}if(g.score=g.score*C6(n,c,E),g.score<=o)break}g.suppressBeginIndex=p.length,v||(g.score===y?(p.push(b),m.push(g.score)):g.score>o&&TE(l,g,_E))}let f=p.length,d=e-f;a&&d>0&&(p.push(...new Array(d).fill(0)),m.push(...new Array(d).fill(0)));let h={selectedIndices:p};return i&&(h.selectedScores=m),u&&(h.validOutputs=f),h}function v6(r,t,e){let n=r.subarray(t*4,t*4+4),o=r.subarray(e*4,e*4+4),s=Math.min(n[0],n[2]),i=Math.min(n[1],n[3]),a=Math.max(n[0],n[2]),u=Math.max(n[1],n[3]),l=Math.min(o[0],o[2]),c=Math.min(o[1],o[3]),p=Math.max(o[0],o[2]),m=Math.max(o[1],o[3]),f=(a-s)*(u-i),d=(p-l)*(m-c);if(f<=0||d<=0)return 0;let h=Math.max(s,l),g=Math.max(i,c),y=Math.min(a,p),b=Math.min(u,m),w=Math.max(y-h,0)*Math.max(b-g,0);return w/(f+d-w)}function C6(r,t,e){let n=Math.exp(t*e*e);return e<=r?n:0}function _E(r,t){return r.score-t.score||r.score===t.score&&t.boxIndex-r.boxIndex}async function I6(r,t,e,n=.5,o=Number.NEGATIVE_INFINITY){let s=C(r,"boxes","nonMaxSuppressionAsync"),i=C(t,"scores","nonMaxSuppressionAsync"),a=Io(s,i,e,n,o);e=a.maxOutputSize,n=a.iouThreshold,o=a.scoreThreshold;let u=await Promise.all([s.data(),i.data()]),l=u[0],c=u[1],{selectedIndices:p}=Zx(l,c,e,n,o);return s!==r&&s.dispose(),i!==t&&i.dispose(),Re(p,"int32")}var EE=I6;function S6(r,t,e,n=.5,o=Number.NEGATIVE_INFINITY,s=0){let i=C(r,"boxes","nonMaxSuppression"),a=C(t,"scores","nonMaxSuppression"),u=Io(i,a,e,n,o,s);e=u.maxOutputSize,n=u.iouThreshold,o=u.scoreThreshold,s=u.softNmsSigma;let l={boxes:i,scores:a},c={maxOutputSize:e,iouThreshold:n,scoreThreshold:o,softNmsSigma:s},p=_.runKernel(Aa,l,c);return{selectedIndices:p[0],selectedScores:p[1]}}var AE=N({nonMaxSuppressionWithScore_:S6});async function k6(r,t,e,n=.5,o=Number.NEGATIVE_INFINITY,s=0){let i=C(r,"boxes","nonMaxSuppressionAsync"),a=C(t,"scores","nonMaxSuppressionAsync"),u=Io(i,a,e,n,o,s);e=u.maxOutputSize,n=u.iouThreshold,o=u.scoreThreshold,s=u.softNmsSigma;let l=await Promise.all([i.data(),a.data()]),c=l[0],p=l[1],{selectedIndices:m,selectedScores:f}=Qx(c,p,e,n,o,s);return i!==r&&i.dispose(),a!==t&&a.dispose(),{selectedIndices:Re(m,"int32"),selectedScores:Re(f)}}var $E=k6;function N6(r,t,e,n=.5,o=Number.NEGATIVE_INFINITY,s=!1){let 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n=C(r,"losses","computeWeightedLoss"),o=null;t!=null&&(o=C(t,"weights","computeWeightedLoss"));let s=o==null?n:O(n,o);if(e===Qe.NONE)return s;if(e===Qe.SUM)return mt(s);if(e===Qe.MEAN){if(o==null)return xe(s);{let i=n.size/o.size,a=ct(mt(s),mt(o));return i>1?ct(a,pt(i)):a}}if(e===Qe.SUM_BY_NONZERO_WEIGHTS){if(o==null)return ct(mt(s),pt(n.size));{let i=O(o,lr(n.shape)),a=Z(mt(vo(i,pt(0))),"float32");return ct(mt(s),a)}}throw Error(`Unknown reduction: ${e}`)}var Br=N({computeWeightedLoss_:M6});function P6(r,t,e,n=Qe.SUM_BY_NONZERO_WEIGHTS){let o=C(r,"labels","absoluteDifference"),s=C(t,"predictions","absoluteDifference"),i=null;e!=null&&(i=C(e,"weights","absoluteDifference")),Me(o.shape,s.shape,"Error in absoluteDifference: ");let a=Ne(lt(o,s));return Br(a,i,n)}var BE=N({absoluteDifference_:P6});function L6(r,t,e,n,o=Qe.SUM_BY_NONZERO_WEIGHTS){let s=C(r,"labels","cosineDistance"),i=C(t,"predictions","cosineDistance"),a=null;n!=null&&(a=C(n,"weights","cosineDistance")),Me(s.shape,i.shape,"Error in cosineDistance: ");let u=pt(1),l=lt(u,mt(O(s,i),e,!0));return Br(l,a,o)}var VE=N({cosineDistance_:L6});function z6(r,t,e,n=Qe.SUM_BY_NONZERO_WEIGHTS){let o=C(r,"labels","hingeLoss"),s=C(t,"predictions","hingeLoss"),i=null;e!=null&&(i=C(e,"weights","hingeLoss")),Me(o.shape,s.shape,"Error in hingeLoss: ");let a=pt(1);o=lt(O(pt(2),o),a);let u=Tr(lt(a,O(o,s)));return Br(u,i,n)}var GE=N({hingeLoss_:z6});function B6(r,t,e,n=1,o=Qe.SUM_BY_NONZERO_WEIGHTS){let s=C(r,"labels","huberLoss"),i=C(t,"predictions","huberLoss"),a=null;e!=null&&(a=C(e,"weights","huberLoss")),Me(s.shape,i.shape,"Error in huberLoss: ");let u=pt(n),l=Ne(lt(i,s)),c=ei(l,u),p=lt(l,c),m=J(O(pt(.5),Ut(c)),O(u,p));return Br(m,a,o)}var WE=N({huberLoss_:B6});function V6(r,t,e,n=1e-7,o=Qe.SUM_BY_NONZERO_WEIGHTS){let s=C(r,"labels","logLoss"),i=C(t,"predictions","logLoss"),a=null;e!=null&&(a=C(e,"weights","logLoss")),Me(s.shape,i.shape,"Error in logLoss: ");let u=pt(1),l=pt(n),c=Zt(O(s,wr(J(i,l)))),p=O(lt(u,s),wr(J(lt(u,i),l))),m=lt(c,p);return Br(m,a,o)}var UE=N({logLoss_:V6});function G6(r,t,e,n=Qe.SUM_BY_NONZERO_WEIGHTS){let o=C(r,"labels","meanSquaredError"),s=C(t,"predictions","meanSquaredError"),i=null;e!=null&&(i=C(e,"weights","meanSquaredError")),Me(o.shape,s.shape,"Error in meanSquaredError: ");let a=hc(o,s);return Br(a,i,n)}var HE=N({meanSquaredError_:G6});function W6(r,t){let e=C(r,"labels","sigmoidCrossEntropyWithLogits"),n=C(t,"logits","sigmoidCrossEntropyWithLogits");Me(e.shape,n.shape,"Error in sigmoidCrossEntropyWithLogits: ");let o=Tr(n),s=O(n,e),i=Za(Ze(Zt(Ne(n))));return J(lt(o,s),i)}function U6(r,t,e,n=0,o=Qe.SUM_BY_NONZERO_WEIGHTS){let s=C(r,"multiClassLabels","sigmoidCrossEntropy"),i=C(t,"logits","sigmoidCrossEntropy"),a=null;if(e!=null&&(a=C(e,"weights","sigmoidCrossEntropy")),Me(s.shape,i.shape,"Error in sigmoidCrossEntropy: "),n>0){let l=pt(n),c=pt(1),p=pt(.5);s=J(O(s,lt(c,l)),O(p,l))}let u=W6(s,i);return Br(u,a,o)}var qE=N({sigmoidCrossEntropy_:U6});function H6(r,t,e=-1){if(e===-1&&(e=t.rank-1),e!==t.rank-1)throw Error(`Softmax cross entropy along a non-last dimension is not yet supported. 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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)}};ou.className="Adamax";Nn(ou);var Hi=class extends Vr{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(O(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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Its own _trainableWeights must remain an empty Array.");if(!this.trainable)return[];let t=[];for(let e of this.layers)t=t.concat(e.trainableWeights);return t}get nonTrainableWeights(){let t=[];for(let e of this.layers)t.push(...e.nonTrainableWeights);if(!this.trainable){let e=[];for(let n of this.layers)e.push(...n.trainableWeights);return e.concat(t)}return t}get weights(){return this.trainableWeights.concat(this.nonTrainableWeights)}loadWeights(t,e=!0){let n={},o=0;for(let i of this.layers)for(let a of i.weights){if(n[a.originalName]!=null)throw new z(`Duplicate weight name: ${a.originalName}`);n[a.originalName]=a,o++}let s=[];for(let i in t){let a=i;if(n[i]==null){let u=i.split("/");a=u.slice(0,-2).concat([u[u.length-1]]).join("/")}if(n[a]!=null)s.push([n[a],t[i]]);else if(e)throw new z(`Provided weight data has no target variable: ${i}`);delete n[a]}if(e){let i=[];for(let a in n)i.push(a);if(i.length>0)throw new z(`${i.length} of ${o} weights are not set: ${i}`)}Pm(s)}updatedConfig(){let t=this.getConfig(),e={};return e.className=this.getClassName(),e.config=t,e.kerasVersion=`tfjs-layers ${Hm}`,e.backend="TensorFlow.js",e}toJSON(t,e=!0){let n=$y(this.updatedConfig());return e?JSON.stringify(n):n}call(t,e){return B(()=>{t=we(t);let n=new Ao;for(let o=0;o<this.inputs.length;++o)n.add(this.inputs[o],t[o]);return $c(this.outputs,n,e)})}computeMask(t,e){return B(()=>{t=we(t);let n;return e==null?n=ko(null,t.length):n=we(e),this.runInternalGraph(t,n)[1]})}computeOutputShape(t){let e=Om(t);if(e.length!==this.inputLayers.length)throw new z(`Invalid inputShape argument ${t}: model has ${this.inputLayers.length} tensor inputs.`);let n={};for(let a=0;a<e.length;a++){let u=this.inputLayers[a],l=e[a],c=u.name+"_0_0";n[c]=l}let o=Object.keys(this.nodesByDepth).map(a=>parseInt(a,10)).sort(Wh);if(o.length>1)for(let a of o){let u=this.nodesByDepth[a];for(let l of u){let c=l.outboundLayer;if(this.inputLayers.map(h=>h.id).indexOf(c.id)!==-1)continue;let p=[];for(let h=0;h<l.inboundLayers.length;h++){let g=l.inboundLayers[h],y=l.nodeIndices[h],b=l.tensorIndices[h],w=`${g.name}_${y}_${b}`,v=n[w];p.push(v)}let m=c.computeOutputShape(_r(p)),f=Om(m),d=c.inboundNodes.indexOf(l);for(let h=0;h<f.length;h++){let g=`${c.name}_${d}_${h}`;n[g]=f[h]}}}let s=[],i=[];for(let a=0;a<this.outputLayers.length;a++){let u=this.outputLayers[a],l=this.outputLayersNodeIndices[a],c=this.outputLayersTensorIndices[a],p=`${u.name}_${l}_${c}`;i.push(p)}for(let a=0;a<i.length;a++){let u=i[a];Qn(u in n),s.push(n[u])}return _r(s)}runInternalGraph(t,e){e==null&&(e=ko(null,t.length));let n={};for(let u=0;u<this.inputs.length;++u){let l=this.inputs[u],c=t[u],p=e[u];n[l.id]=[c,p]}let o=Object.keys(this.nodesByDepth).map(u=>parseInt(u,10)).sort(Wh);for(let u of o){let l=this.nodesByDepth[u];for(let c of l){let p=c.outboundLayer,m=c.inputTensors,f=c.outputTensors,d=new Array;for(let h of m)h.id in n&&d.push(n[h.id]);if(d.length===m.length){let h={},g,y,b,w;if(c.callArgs!=null&&(h=c.callArgs),d.length===1){let[v,k]=d[0];h.mask==null&&(h.mask=k),b=we(p.call(v,h)),w=we(p.computeMask(v,k)),g=[v],y=[k]}else g=d.map(v=>v[0]),y=d.map(v=>v[1]),h.mask==null&&(h.mask=y),b=we(p.call(g,h)),w=we(p.computeMask(g,y));if(p.activityRegularizer)throw new Nt("LayersModel invocation with concrete Tensor value(s) in the presence of activity regularizer(s) is not supported yet.");for(let v=0;v<f.length;++v){let k=f[v],E=b[v],$=w[v];n[k.id]=[E,$]}}}}let s=[],i=[],a=[];for(let u of this.outputs){Qn(u.id in n,`Could not compute output ${u.name} : ${u.id}`);let[l,c]=n[u.id];a.push(l.shape),s.push(l),i.push(c)}return[s,i,a]}buildNodeConversionMap(t){let e={},n;for(let o of this.layers){n=o instanceof Bn?1:0;for(let s=0;s<o.inboundNodes.length;s++){let i=Bn.nodeKey(o,s);this.containerNodes.has(i)&&(e[i]=n,n+=1)}}return e}getLayer(t,e){if(e!=null){if(this.layers.length<=e)throw new z(`Was asked to retrieve layer at index ${e}, but model only has ${this.layers.length} layer(s).`);return this.layers[e]}else if(t==null)throw new z("Provide either a layer name or layer index");for(let n of this.layers)if(n.name===t)return n;throw new z(`No such layer: ${t}`)}calculateLosses(){return B(()=>{let t=[];for(let e of this.layers)for(let n=0;n<e.inboundNodes.length;++n){let o=Bn.nodeKey(e,n);this.containerNodes.has(o)&&t.push(...e.calculateLosses())}return t})}getConfig(){let t={name:this.name},e=this.buildNodeConversionMap(this.layers),n=[];for(let i of this.layers){let a=i.getClassName(),u=i.getConfig(),l=[];for(let p=0;p<i.inboundNodes.length;p++){let m=i.inboundNodes[p],f=Bn.nodeKey(i,p),d={};if(this.containerNodes.has(f)){if(m.callArgs)try{JSON.stringify(m.callArgs),d=m.callArgs}catch(h){console.warn(`Layer ${i.name} was passed non-serializable keyword arguments: ${m.callArgs}. 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t={theta:this.theta},e=super.getConfig();return Object.assign(t,e),t}};Jm.className="ThresholdedReLU";et.registerClass(Jm);var Qm=class extends Vt{constructor(t){super(t==null?{}:t),this.DEFAULT_AXIS=1,t==null&&(t={}),this.softmax=new Km().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}};Qm.className="Softmax";et.registerClass(Qm);function mu(r,t,e){if(typeof r=="number")return ko(r,t);if(r.length!==t)throw new z(`The ${e} argument must be an integer or tuple of ${t} integers. Received: ${r.length} elements.`);for(let n=0;n<t;++n){let o=r[n];if(!p$(o))throw new z(`The ${e} argument must be an integer or tuple of ${t} integers. Received: ${JSON.stringify(r)} including a non-integer number ${o}`)}return r}function An(r,t,e,n,o=1){if(r==null)return r;let s=t+(t-1)*(o-1),i;return e==="same"?i=r:i=r-s+1,Math.floor((i+n-1)/n)}function pi(r,t,e,n){if(r==null)return null;if(n==="valid")r=r*t+ai([e-t,0]);else if(n==="same")r=r*t;else throw new z(`Unsupport padding mode: ${n}.`);return r}function eg(r,t){return B(()=>(Le(t),t==="channelsFirst"?Mt(r,[0,2,3,1]):r))}function BS(r,t){return B(()=>(Le(t),t==="channelsFirst"?Mt(r,[0,2,3,4,1]):r))}function E8(r,t,e,n=1,o="valid",s,i=1){return B(()=>{if(s==null&&(s=gn()),Le(s),r.shape.length!==3)throw new z(`The input of a conv1dWithBias operation should be 3, but is ${r.shape.length} instead.`);if(t.shape.length!==3)throw new z(`The kernel for a conv1dWithBias operation should be 3, but is ${t.shape.length} instead`);if(e!=null&&e.shape.length!==1)throw new z(`The bias for a conv1dWithBias operation should be 1, but is ${t.shape.length} instead`);if(s==="channelsFirst"&&(r=Mt(r,[0,2,1])),o==="causal")throw new Nt("The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.");let a=Zu(r,t,n,o==="same"?"same":"valid","NWC",i);return e!=null&&(a=xn(a,e)),a})}function eD(r,t,e,n=[1,1],o="valid",s,i,a=null){return B(()=>{if(s==null&&(s=gn()),Le(s),r.rank!==3&&r.rank!==4)throw new z(`conv2dWithBiasActivation expects input to be of rank 3 or 4, but received ${r.rank}.`);if(t.rank!==3&&t.rank!==4)throw new z(`conv2dWithBiasActivation expects kernel to be of rank 3 or 4, but received ${r.rank}.`);let u=eg(r,s);if(o==="causal")throw new Nt("The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.");return u=Co.conv2d({x:u,filter:t,strides:n,pad:o==="same"?"same":"valid",dilations:i,dataFormat:"NHWC",bias:e,activation:a}),s==="channelsFirst"&&(u=Mt(u,[0,3,1,2])),u})}function A8(r,t,e,n=[1,1,1],o="valid",s,i){return B(()=>{if(s==null&&(s=gn()),Le(s),r.rank!==4&&r.rank!==5)throw new z(`conv3dWithBias expects input to be of rank 4 or 5, but received ${r.rank}.`);if(t.rank!==4&&t.rank!==5)throw new z(`conv3dWithBias expects kernel to be of rank 4 or 5, but received ${r.rank}.`);let a=BS(r,s);if(o==="causal")throw new Nt("The support for CAUSAL padding mode in conv3dWithBias is not implemented yet.");return a=xh(a,t,n,o==="same"?"same":"valid","NDHWC",i),e!=null&&(a=xn(a,e)),s==="channelsFirst"&&(a=Mt(a,[0,4,1,2,3])),a})}var Oc=class extends Vt{constructor(t,e){if(super(e),this.bias=null,this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_BIAS_INITIALIZER="zeros",Oc.verifyArgs(e),this.rank=t,er(this.rank,"rank"),this.rank!==1&&this.rank!==2&&this.rank!==3)throw new Nt(`Convolution layer for rank other than 1, 2, or 3 (${this.rank}) is not implemented yet.`);if(this.kernelSize=mu(e.kernelSize,t,"kernelSize"),this.strides=mu(e.strides==null?1:e.strides,t,"strides"),this.padding=e.padding==null?"valid":e.padding,hn(this.padding),this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,Le(this.dataFormat),this.activation=ci(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=Ce(e.biasRegularizer),this.activityRegularizer=Ce(e.activityRegularizer),this.dilationRate=mu(e.dilationRate==null?1:e.dilationRate,t,"dilationRate"),this.rank===1&&Array.isArray(this.dilationRate)&&this.dilationRate.length!==1)throw new z(`dilationRate must be a number or an array of a single number for 1D convolution, but received ${JSON.stringify(this.dilationRate)}`);if(this.rank===2){if(typeof this.dilationRate=="number")this.dilationRate=[this.dilationRate,this.dilationRate];else if(this.dilationRate.length!==2)throw new z(`dilationRate must be a number or array of two numbers for 2D convolution, but received ${JSON.stringify(this.dilationRate)}`)}else if(this.rank===3){if(typeof this.dilationRate=="number")this.dilationRate=[this.dilationRate,this.dilationRate,this.dilationRate];else if(this.dilationRate.length!==3)throw new z(`dilationRate must be a number or array of three numbers for 3D convolution, but received ${JSON.stringify(this.dilationRate)}`)}}static verifyArgs(t){if(Qn("kernelSize"in t,"required key 'kernelSize' not in config"),typeof t.kernelSize!="number"&&!iy(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:ui(this.activation),useBias:this.useBias,biasInitializer:Ee(this.biasInitializer),biasRegularizer:me(this.biasRegularizer),activityRegularizer:me(this.activityRegularizer),biasConstraint:We(this.biasConstraint)},e=super.getConfig();return Object.assign(t,e),t}},fu=class extends Oc{constructor(t,e){super(t,e),this.kernel=null,fu.verifyArgs(e),this.filters=e.filters,er(this.filters,"filters"),this.kernelInitializer=de(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.kernelConstraint=Ue(e.kernelConstraint),this.kernelRegularizer=Ce(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. Found ${t[e]}`);let n=t[e],o=this.kernelSize.concat([n,this.filters]);this.kernel=this.addWeight("kernel",o,null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[{ndim:this.rank+2,axes:{[e]:n}}],this.built=!0}call(t,e){return B(()=>{t=Pt(t);let n,o=this.bias==null?null:this.bias.read(),s=ay(this.activation.getClassName());if(s!=null&&this.rank===2)n=eD(t,this.kernel.read(),o,this.strides,this.padding,this.dataFormat,this.dilationRate,s);else{if(this.rank===1)n=E8(t,this.kernel.read(),o,this.strides[0],this.padding,this.dataFormat,this.dilationRate[0]);else if(this.rank===2)n=eD(t,this.kernel.read(),o,this.strides,this.padding,this.dataFormat,this.dilationRate);else if(this.rank===3)n=A8(t,this.kernel.read(),o,this.strides,this.padding,this.dataFormat,this.dilationRate);else throw new Nt("convolutions greater than 3D are not implemented yet.");this.activation!=null&&(n=this.activation.apply(n))}return n})}computeOutputShape(t){t=Jt(t);let e=[],n=this.dataFormat==="channelsLast"?t.slice(1,t.length-1):t.slice(2);for(let s=0;s<n.length;++s){let i=An(n[s],this.kernelSize[s],this.padding,this.strides[s],typeof this.dilationRate=="number"?this.dilationRate:this.dilationRate[s]);e.push(i)}let o=[t[0]];return this.dataFormat==="channelsLast"?(o=o.concat(e),o.push(this.filters)):(o.push(this.filters),o=o.concat(e)),o}getConfig(){let t={filters:this.filters,kernelInitializer:Ee(this.kernelInitializer),kernelRegularizer:me(this.kernelRegularizer),kernelConstraint:We(this.kernelConstraint)},e=super.getConfig();return Object.assign(t,e),t}static verifyArgs(t){if(!("filters"in t)||typeof t.filters!="number"||t.filters<1)throw new z(`Convolution layer expected config.filters to be a 'number' > 0 but got ${JSON.stringify(t.filters)}`)}},pl=class extends fu{constructor(t){super(2,t),pl.verifyArgs(t)}getConfig(){let t=super.getConfig();return delete t.rank,t}static verifyArgs(t){if(typeof t.kernelSize!="number"&&!iy(t.kernelSize,"number",1,2))throw new z(`Conv2D expects config.kernelSize to be number or number[] with length 1 or 2, but received ${JSON.stringify(t.kernelSize)}.`)}};pl.className="Conv2D";et.registerClass(pl);var ml=class extends fu{constructor(t){super(3,t),ml.verifyArgs(t)}getConfig(){let t=super.getConfig();return delete t.rank,t}static verifyArgs(t){if(typeof t.kernelSize!="number"&&!(Array.isArray(t.kernelSize)&&(t.kernelSize.length===1||t.kernelSize.length===3)))throw new z(`Conv3D expects config.kernelSize to be number or [number, number, number], but received ${JSON.stringify(t.kernelSize)}.`)}};ml.className="Conv3D";et.registerClass(ml);var tf=class extends pl{constructor(t){if(super(t),this.inputSpec=[new ve({ndim:4})],this.padding!=="same"&&this.padding!=="valid")throw new z(`Conv2DTranspose currently supports only padding modes 'same' and 'valid', but received padding mode ${this.padding}`)}build(t){if(t=Jt(t),t.length!==4)throw new z("Input should have rank 4; Received input shape: "+JSON.stringify(t));let e=this.dataFormat==="channelsFirst"?1:t.length-1;if(t[e]==null)throw new z("The channel dimension of the inputs should be defined. Found `None`.");let n=t[e],o=this.kernelSize.concat([this.filters,n]);this.kernel=this.addWeight("kernel",o,"float32",this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[new ve({ndim:4,axes:{[e]:n}})],this.built=!0}call(t,e){return B(()=>{let n=Pt(t);if(n.shape.length!==4)throw new z(`Conv2DTranspose.call() expects input tensor to be rank-4, but received a tensor of rank-${n.shape.length}`);let o=n.shape,s=o[0],i,a;this.dataFormat==="channelsFirst"?(i=2,a=3):(i=1,a=2);let u=o[i],l=o[a],c=this.kernelSize[0],p=this.kernelSize[1],m=this.strides[0],f=this.strides[1],d=pi(u,m,c,this.padding),h=pi(l,f,p,this.padding),g=[s,d,h,this.filters];this.dataFormat!=="channelsLast"&&(n=Mt(n,[0,2,3,1]));let y=Ju(n,this.kernel.read(),g,this.strides,this.padding);return this.dataFormat!=="channelsLast"&&(y=Mt(y,[0,3,1,2])),this.bias!=null&&(y=xn(y,this.bias.read(),this.dataFormat)),this.activation!=null&&(y=this.activation.apply(y)),y})}computeOutputShape(t){t=Jt(t);let e=t.slice(),n,o,s;this.dataFormat==="channelsFirst"?(n=1,o=2,s=3):(n=3,o=1,s=2);let i=this.kernelSize[0],a=this.kernelSize[1],u=this.strides[0],l=this.strides[1];return e[n]=this.filters,e[o]=pi(e[o],u,i,this.padding),e[s]=pi(e[s],l,a,this.padding),e}getConfig(){let t=super.getConfig();return delete t.dilationRate,t}};tf.className="Conv2DTranspose";et.registerClass(tf);var ef=class extends ml{constructor(t){if(super(t),this.inputSpec=[new ve({ndim:5})],this.padding!=="same"&&this.padding!=="valid")throw new z(`Conv3DTranspose currently supports only padding modes 'same' and 'valid', but received padding mode ${this.padding}`)}build(t){if(t=Jt(t),t.length!==5)throw new z("Input should have rank 5; Received input shape: "+JSON.stringify(t));let e=this.dataFormat==="channelsFirst"?1:t.length-1;if(t[e]==null)throw new z("The channel dimension of the inputs should be defined. Found `None`.");let n=t[e],o=this.kernelSize.concat([this.filters,n]);this.kernel=this.addWeight("kernel",o,"float32",this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[new ve({ndim:5,axes:{[e]:n}})],this.built=!0}call(t,e){return B(()=>{let n=Pt(t);if(n.shape.length!==5)throw new z(`Conv3DTranspose.call() expects input tensor to be rank-4, but received a tensor of rank-${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=pi(l,h,m,this.padding),w=pi(c,g,f,this.padding),v=pi(p,y,d,this.padding),k=[s,b,w,v,this.filters];this.dataFormat!=="channelsLast"&&(n=Mt(n,[0,2,3,4,1]));let E=BI(n,this.kernel.read(),k,this.strides,this.padding);return this.dataFormat!=="channelsLast"&&(E=Mt(E,[0,4,1,2,3])),this.bias!==null&&(E=xn(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]=pi(e[o],c,a,this.padding),e[s]=pi(e[s],p,u,this.padding),e[i]=pi(e[i],m,l,this.padding),e}getConfig(){let t=super.getConfig();return delete t.dilationRate,t}};ef.className="Conv3DTranspose";et.registerClass(ef);var Jy=class extends fu{constructor(t,e){if(super(t,e),this.DEFAULT_DEPTHWISE_INITIALIZER="glorotUniform",this.DEFAULT_POINTWISE_INITIALIZER="glorotUniform",this.depthwiseKernel=null,this.pointwiseKernel=null,e.filters==null)throw new z("The `filters` configuration field is required by SeparableConv, but is unspecified.");if(e.kernelInitializer!=null||e.kernelRegularizer!=null||e.kernelConstraint!=null)throw new z("Fields kernelInitializer, kernelRegularizer and kernelConstraint are invalid for SeparableConv2D. Use depthwiseInitializer, depthwiseRegularizer, depthwiseConstraint, pointwiseInitializer, pointwiseRegularizer and pointwiseConstraint instead.");if(e.padding!=null&&e.padding!=="same"&&e.padding!=="valid")throw new z(`SeparableConv${this.rank}D supports only padding modes: 'same' and 'valid', but received ${JSON.stringify(e.padding)}`);this.depthMultiplier=e.depthMultiplier==null?1:e.depthMultiplier,this.depthwiseInitializer=de(e.depthwiseInitializer||this.DEFAULT_DEPTHWISE_INITIALIZER),this.depthwiseRegularizer=Ce(e.depthwiseRegularizer),this.depthwiseConstraint=Ue(e.depthwiseConstraint),this.pointwiseInitializer=de(e.depthwiseInitializer||this.DEFAULT_POINTWISE_INITIALIZER),this.pointwiseRegularizer=Ce(e.pointwiseRegularizer),this.pointwiseConstraint=Ue(e.pointwiseConstraint)}build(t){if(t=Jt(t),t.length<this.rank+2)throw new z(`Inputs to SeparableConv${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 ${JSON.stringify(t[e])}`);let n=t[e],o=this.kernelSize.concat([n,this.depthMultiplier]),s=[];for(let a=0;a<this.rank;++a)s.push(1);s.push(n*this.depthMultiplier,this.filters);let i=!0;this.depthwiseKernel=this.addWeight("depthwise_kernel",o,"float32",this.depthwiseInitializer,this.depthwiseRegularizer,i,this.depthwiseConstraint),this.pointwiseKernel=this.addWeight("pointwise_kernel",s,"float32",this.pointwiseInitializer,this.pointwiseRegularizer,i,this.pointwiseConstraint),this.useBias?this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,i,this.biasConstraint):this.bias=null,this.inputSpec=[new ve({ndim:this.rank+2,axes:{[e]:n}})],this.built=!0}call(t,e){return B(()=>{t=Pt(t);let n;if(this.rank===1)throw new Nt("1D separable convolution is not implemented yet.");return this.rank===2&&(this.dataFormat==="channelsFirst"&&(t=Mt(t,[0,2,3,1])),n=$h(t,this.depthwiseKernel.read(),this.pointwiseKernel.read(),this.strides,this.padding,this.dilationRate,"NHWC")),this.useBias&&(n=xn(n,this.bias.read(),this.dataFormat)),this.activation!=null&&(n=this.activation.apply(n)),this.dataFormat==="channelsFirst"&&(n=Mt(n,[0,3,1,2])),n})}getConfig(){let t=super.getConfig();return delete t.rank,delete t.kernelInitializer,delete t.kernelRegularizer,delete t.kernelConstraint,t.depthwiseInitializer=Ee(this.depthwiseInitializer),t.pointwiseInitializer=Ee(this.pointwiseInitializer),t.depthwiseRegularizer=me(this.depthwiseRegularizer),t.pointwiseRegularizer=me(this.pointwiseRegularizer),t.depthwiseConstraint=We(this.depthwiseConstraint),t.pointwiseConstraint=We(this.pointwiseConstraint),t}};Jy.className="SeparableConv";var rf=class extends Jy{constructor(t){super(2,t)}};rf.className="SeparableConv2D";et.registerClass(rf);var du=class extends fu{constructor(t){super(1,t),du.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"&&!iy(t.kernelSize,"number",1,1))throw new z(`Conv1D expects config.kernelSize to be number or number[] with length 1, but received ${JSON.stringify(t.kernelSize)}.`)}};du.className="Conv1D";et.registerClass(du);var nf=class extends Vt{constructor(t){super(t),typeof t.cropping=="number"?this.cropping=[[t.cropping,t.cropping],[t.cropping,t.cropping]]:typeof t.cropping[0]=="number"?this.cropping=[[t.cropping[0],t.cropping[0]],[t.cropping[1],t.cropping[1]]]:this.cropping=t.cropping,this.dataFormat=t.dataFormat===void 0?"channelsLast":t.dataFormat,this.inputSpec=[{ndim:4}]}computeOutputShape(t){return this.dataFormat==="channelsFirst"?[t[0],t[1],t[2]-this.cropping[0][0]-this.cropping[0][1],t[3]-this.cropping[1][0]-this.cropping[1][1]]:[t[0],t[1]-this.cropping[0][0]-this.cropping[0][1],t[2]-this.cropping[1][0]-this.cropping[1][1],t[3]]}call(t,e){return B(()=>{if(t=Pt(t),this.dataFormat==="channelsLast"){let n=Hh(t,this.cropping[0][0],t.shape[1]-this.cropping[0][0]-this.cropping[0][1],2);return Hh(n,this.cropping[1][0],t.shape[2]-this.cropping[1][1]-this.cropping[1][0],3)}else{let n=Hh(t,this.cropping[0][0],t.shape[2]-this.cropping[0][0]-this.cropping[0][1],3);return Hh(n,this.cropping[1][0],t.shape[3]-this.cropping[1][1]-this.cropping[1][0],4)}})}getConfig(){let t={cropping:this.cropping,dataFormat:this.dataFormat},e=super.getConfig();return Object.assign(t,e),t}};nf.className="Cropping2D";et.registerClass(nf);var of=class extends Vt{constructor(t){super(t),this.DEFAULT_SIZE=[2,2],this.inputSpec=[{ndim:4}],this.size=t.size==null?this.DEFAULT_SIZE:t.size,this.dataFormat=t.dataFormat==null?"channelsLast":t.dataFormat,Le(this.dataFormat),this.interpolation=t.interpolation==null?"nearest":t.interpolation,u$(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=Mt(n,[0,2,3,1]);let s=this.size[0]*o[2],i=this.size[1]*o[3],a=this.interpolation==="nearest"?dn.resizeNearestNeighbor(n,[s,i]):dn.resizeBilinear(n,[s,i]);return Mt(a,[0,3,1,2])}else{let s=this.size[0]*o[1],i=this.size[1]*o[2];return this.interpolation==="nearest"?dn.resizeNearestNeighbor(n,[s,i]):dn.resizeBilinear(n,[s,i])}})}getConfig(){let t={size:this.size,dataFormat:this.dataFormat},e=super.getConfig();return Object.assign(t,e),t}};of.className="UpSampling2D";et.registerClass(of);function $8(r,t,e=[1,1],n="valid",o,s){return B(()=>{o==null&&(o=gn()),Le(o);let i=eg(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=Zs(i,t,e,n==="same"?"same":"valid","NHWC",s),o==="channelsFirst"&&(i=Mt(i,[0,3,1,2])),i})}var sf=class extends Oc{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=Ce(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=$8(t,this.depthwiseKernel.read(),this.strides,this.padding,this.dataFormat,null);return this.useBias&&(n=xn(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=An(e,this.kernelSize[0],this.padding,this.strides[0]),i=An(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=Ee(this.depthwiseInitializer),t.depthwiseRegularizer=me(this.depthwiseRegularizer),t.depthwiseConstraint=We(this.depthwiseRegularizer),t}};sf.className="DepthwiseConv2D";et.registerClass(sf);function VS(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 GS(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 ${u}D.`);let l=[1,0].concat(Jr(2,u));if(t=Mt(t,l),s!=null)throw new Nt("The rnn() functoin of the deeplearn.js backend does not support constants yet.");i&&console.warn("Backend rnn(): the unroll = true option is not applicable to the imperative deeplearn.js backend."),o!=null&&(o=Z(Z(o,"bool"),"float32"),o.rank===u-1&&(o=fr(o,-1)),o=Mt(o,l)),n&&(t=ir(t,0),o!=null&&(o=ir(o,0)));let c=[],p,m=e,f=t.shape[0],d=vr(t),h;o!=null&&(h=vr(o));for(let y=0;y<f;++y){let b=d[y],w=B(()=>r(b,m));if(o==null)p=w[0],m=w[1];else{let v=B(()=>{let k=h[y],E=lt(dr(k),k),$=J(O(w[0],k),O(m[0],E)),D=m.map((R,P)=>J(O(w[1][P],k),O(R,E)));return{output:$,newStates:D}});p=v.output,m=v.newStates}a&&c.push(p)}let g;return a&&(g=Je(c,1)),[p,g,m]})}var $n=class extends Vt{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 Lc({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 ve({ndim:3})],this.stateSpec=null,this.states_=null,this.numConstants=null,this.keptStates=[]}getStates(){if(this.states_==null){let t=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1;return Jr(0,t).map(e=>null)}else return this.states_}setStates(t){this.states_=t}computeOutputShape(t){gy(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 Nt("Constants support is not implemented in RNN yet.");gy(t)&&(t=t[0]),t=t;let n=this.stateful?t[0]:null,o=t.slice(2);this.inputSpec[0]=new ve({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 ve({shape:[null,a]}));this.stateful&&this.resetStates()}resetStates(t,e=!1){B(()=>{if(!this.stateful)throw new En("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=VS(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 ve({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 Qr){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 ${s.length} initial state(s).`);this.unroll&&console.warn("Ignoring unroll = true for RNN layer, due to imperative backend.");let a={training:o},l=GS((d,h)=>{let g=this.cell.call([d].concat(h),a);return[g[0],g.slice(1)]},t,s,this.goBackwards,n,null,this.unroll,this.returnSequences),c=l[0],p=l[1],m=l[2];this.stateful&&this.resetStates(m,o);let f=this.returnSequences?p:c;return this.returnState?[f].concat(m):f})}getInitialState(t){return B(()=>{let e=ye(t.shape);return e=mt(e,[1,2]),e=ll(e),Array.isArray(this.cell.stateSize)?this.cell.stateSize.map(n=>n>1?fy(e,[1,n]):e):this.cell.stateSize>1?[fy(e,[1,this.cell.stateSize])]:[e]})}get trainableWeights(){return this.trainable?this.cell.trainableWeights:[]}get nonTrainableWeights(){return this.trainable?this.cell.nonTrainableWeights:this.cell.weights}setFastWeightInitDuringBuild(t){super.setFastWeightInitDuringBuild(t),this.cell!=null&&this.cell.setFastWeightInitDuringBuild(t)}getConfig(){let t=super.getConfig(),e={returnSequences:this.returnSequences,returnState:this.returnState,goBackwards:this.goBackwards,stateful:this.stateful,unroll:this.unroll};this.numConstants!=null&&(e.numConstants=this.numConstants);let n=this.cell.getConfig();return this.getClassName()===$n.className&&(e.cell={className:this.cell.getClassName(),config:n}),Object.assign({},n,t,e)}static fromConfig(t,e,n={}){let o=e.cell,s=vn(o,n);return new t(Object.assign(e,{cell:s}))}};$n.className="RNN";et.registerClass($n);var fl=class extends Vt{},Mc=class extends fl{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,er(this.units,"units"),this.activation=ci(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=Ce(t.kernelRegularizer),this.recurrentRegularizer=Ce(t.recurrentRegularizer),this.biasRegularizer=Ce(t.biasRegularizer),this.kernelConstraint=Ue(t.kernelConstraint),this.recurrentConstraint=Ue(t.recurrentConstraint),this.biasConstraint=Ue(t.biasConstraint),this.dropout=Cc([1,ai([0,t.dropout==null?0:t.dropout])]),this.recurrentDropout=Cc([1,ai([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=hl({ones:()=>dr(t),rate:this.dropout,training:o,dropoutFunc:this.dropoutFunc})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=hl({ones:()=>dr(n),rate:this.recurrentDropout,training:o,dropoutFunc:this.dropoutFunc}));let s,i=this.dropoutMask,a=this.recurrentDropoutMask;i!=null?s=Eo(O(t,i),this.kernel.read()):s=Eo(t,this.kernel.read()),this.bias!=null&&(s=xn(s,this.bias.read())),a!=null&&(n=O(n,a));let u=J(s,Eo(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:ui(this.activation),useBias:this.useBias,kernelInitializer:Ee(this.kernelInitializer),recurrentInitializer:Ee(this.recurrentInitializer),biasInitializer:Ee(this.biasInitializer),kernelRegularizer:me(this.kernelRegularizer),recurrentRegularizer:me(this.recurrentRegularizer),biasRegularizer:me(this.biasRegularizer),activityRegularizer:me(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)}};Mc.className="SimpleRNNCell";et.registerClass(Mc);var af=class extends $n{constructor(t){t.cell=new Mc(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)}};af.className="SimpleRNN";et.registerClass(af);var Pc=class extends fl{constructor(t){if(super(t),this.DEFAULT_ACTIVATION="tanh",this.DEFAULT_RECURRENT_ACTIVATION="hardSigmoid",this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_RECURRENT_INITIALIZER="orthogonal",this.DEFAULT_BIAS_INITIALIZER="zeros",t.resetAfter)throw new z("GRUCell does not support reset_after parameter set to true.");this.units=t.units,er(this.units,"units"),this.activation=ci(t.activation===void 0?this.DEFAULT_ACTIVATION:t.activation),this.recurrentActivation=ci(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=Ce(t.kernelRegularizer),this.recurrentRegularizer=Ce(t.recurrentRegularizer),this.biasRegularizer=Ce(t.biasRegularizer),this.kernelConstraint=Ue(t.kernelConstraint),this.recurrentConstraint=Ue(t.recurrentConstraint),this.biasConstraint=Ue(t.biasConstraint),this.dropout=Cc([1,ai([0,t.dropout==null?0:t.dropout])]),this.recurrentDropout=Cc([1,ai([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=hl({ones:()=>dr(t),rate:this.dropout,training:n,count:3,dropoutFunc:this.dropoutFunc})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=hl({ones:()=>dr(o),rate:this.recurrentDropout,training:n,count:3,dropoutFunc:this.dropoutFunc}));let s=this.dropoutMask,i=this.recurrentDropoutMask,a,u,l;0<this.dropout&&this.dropout<1&&(t=O(t,s[0]));let c=Eo(t,this.kernel.read());this.useBias&&(c=xn(c,this.bias.read())),0<this.recurrentDropout&&this.recurrentDropout<1&&(o=O(o,i[0]));let p=this.recurrentKernel.read(),[m,f]=ur(p,[2*this.units,this.units],p.rank-1),d=Eo(o,m),[h,g,y]=ur(c,3,c.rank-1),[b,w]=ur(d,2,d.rank-1);a=this.recurrentActivation.apply(J(h,b)),u=this.recurrentActivation.apply(J(g,w));let v=Eo(O(u,o),f);l=this.activation.apply(J(y,v));let k=J(O(a,o),O(J(1,Zt(a)),l));return[k,k]})}getConfig(){let t=super.getConfig(),e={units:this.units,activation:ui(this.activation),recurrentActivation:ui(this.recurrentActivation),useBias:this.useBias,kernelInitializer:Ee(this.kernelInitializer),recurrentInitializer:Ee(this.recurrentInitializer),biasInitializer:Ee(this.biasInitializer),kernelRegularizer:me(this.kernelRegularizer),recurrentRegularizer:me(this.recurrentRegularizer),biasRegularizer:me(this.biasRegularizer),activityRegularizer:me(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)}};Pc.className="GRUCell";et.registerClass(Pc);var lf=class extends $n{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 Pc(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)}};lf.className="GRU";et.registerClass(lf);var dl=class extends fl{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,er(this.units,"units"),this.activation=ci(t.activation===void 0?this.DEFAULT_ACTIVATION:t.activation),this.recurrentActivation=ci(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=Ce(t.kernelRegularizer),this.recurrentRegularizer=Ce(t.recurrentRegularizer),this.biasRegularizer=Ce(t.biasRegularizer),this.kernelConstraint=Ue(t.kernelConstraint),this.recurrentConstraint=Ue(t.recurrentConstraint),this.biasConstraint=Ue(t.biasConstraint),this.dropout=Cc([1,ai([0,t.dropout==null?0:t.dropout])]),this.recurrentDropout=Cc([1,ai([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 bn{apply(u,l){let c=s.apply([i]),p=new uu().apply([i]),m=s.apply([i*2]);return TS(TS(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=hl({ones:()=>dr(t),rate:this.dropout,training:n,count:4,dropoutFunc:this.dropoutFunc})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=hl({ones:()=>dr(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=O(t,i[0]));let m=Eo(t,this.kernel.read());0<this.recurrentDropout&&this.recurrentDropout<1&&(o=O(o,a[0])),m=J(m,Eo(o,this.recurrentKernel.read())),this.useBias&&(m=xn(m,this.bias.read()));let[f,d,h,g]=ur(m,4,m.rank-1);u=this.recurrentActivation.apply(f),l=this.recurrentActivation.apply(d),c=J(O(l,s),O(u,this.activation.apply(h))),p=this.recurrentActivation.apply(g);let y=O(p,this.activation.apply(c));return[y,y,c]})}getConfig(){let t=super.getConfig(),e={units:this.units,activation:ui(this.activation),recurrentActivation:ui(this.recurrentActivation),useBias:this.useBias,kernelInitializer:Ee(this.kernelInitializer),recurrentInitializer:Ee(this.recurrentInitializer),biasInitializer:Ee(this.biasInitializer),unitForgetBias:this.unitForgetBias,kernelRegularizer:me(this.kernelRegularizer),recurrentRegularizer:me(this.recurrentRegularizer),biasRegularizer:me(this.biasRegularizer),activityRegularizer:me(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)}};dl.className="LSTMCell";et.registerClass(dl);var uf=class extends $n{constructor(t){t.implementation===0&&console.warn("`implementation=0` has been deprecated, and now defaults to `implementation=1`. Please update your layer call."),t.cell=new dl(t),super(t)}call(t,e){return B(()=>{this.cell.dropoutMask!=null&&(_t(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(_t(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=e==null?null:e.mask,o=e==null?null:e.training,s=e==null?null:e.initialState;return super.call(t,{mask:n,training:o,initialState:s})})}static fromConfig(t,e){return e.implmentation===0&&(e.implementation=1),new t(e)}};uf.className="LSTM";et.registerClass(uf);var Lc=class extends fl{constructor(t){super(t),this.cells=t.cells}get stateSize(){let t=[];for(let e of this.cells.slice().reverse())Array.isArray(e.stateSize)?t.push(...e.stateSize):t.push(e.stateSize);return t}call(t,e){return B(()=>{t=t;let n=t.slice(1),o=[];for(let a of this.cells.slice().reverse())Array.isArray(a.stateSize)?o.push(n.splice(0,a.stateSize.length)):o.push(n.splice(0,1));o.reverse();let s=[],i;for(let a=0;a<this.cells.length;++a){let u=this.cells[a];n=o[a],a===0?i=[t[0]].concat(n):i=[i[0]].concat(n),i=u.call(i,e),s.push(i.slice(1))}n=[];for(let a of s.slice().reverse())n.push(...a);return[i[0]].concat(n)})}build(t){gy(t)&&(t=t[0]),t=t;let e;this.cells.forEach((n,o)=>{ii(`RNNCell_${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(vn(s,n));return new t({cells:o})}get trainableWeights(){if(!this.trainable)return[];let t=[];for(let e of this.cells)t.push(...e.trainableWeights);return t}get nonTrainableWeights(){let t=[];for(let e of this.cells)t.push(...e.nonTrainableWeights);if(!this.trainable){let e=[];for(let n of this.cells)e.push(...n.trainableWeights);return e.concat(t)}return t}getWeights(){let t=[];for(let e of this.cells)t.push(...e.weights);return Kh(t)}setWeights(t){let e=[];for(let n of this.cells){let o=n.weights.length,s=t.splice(o);for(let i=0;i<n.weights.length;++i)e.push([n.weights[i],s[i]])}Pm(e)}};Lc.className="StackedRNNCells";et.registerClass(Lc);function hl(r){let{ones:t,rate:e,training:n=!1,count:o=1,dropoutFunc:s}=r,i=()=>s!=null?s(t(),e):hy(t(),e),a=()=>lu(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 Qy=class extends $n{constructor(t){if(t.unroll)throw new Nt("Unrolling is not possible with convolutional RNNs.");if(Array.isArray(t.cell))throw new Nt("It is not possible at the moment to stack convolutional cells.");super(t),this.inputSpec=[new ve({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 En("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=An(l,o[0],s,i[0],a[0]),m=An(c,o[1],s,i[1],a[1]);return[...t.slice(0,2),...u?[n,p,m]:[p,m,n]]}};Qy.className="ConvRNN2D";var zc=class extends dl{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,er(this.filters,"filters"),this.kernelSize=mu(n,2,"kernelSize"),this.kernelSize.forEach(u=>er(u,"kernelSize")),this.strides=mu(o||1,2,"strides"),this.strides.forEach(u=>er(u,"strides")),this.padding=s||"valid",hn(this.padding),this.dataFormat=i||"channelsLast",Le(this.dataFormat),this.dilationRate=mu(a||1,2,"dilationRate"),this.dilationRate.forEach(u=>er(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 bn{apply(m,f){let d=l.apply([c]),h=lr([c]),g=l.apply([c*2]);return Nm([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 ${t.length}.`);let n=e.training||!1,o=t[0],s=t[1],i=t[2],a=4;0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=hl({ones:()=>dr(o),rate:this.dropout,training:n,count:a,dropoutFunc:this.dropoutFunc}));let u=this.dropoutMask,l=(st,it,ft)=>!it||!it[ft]?st:O(it[ft],st),c=l(o,u,0),p=l(o,u,1),m=l(o,u,2),f=l(o,u,3);0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=hl({ones:()=>dr(s),rate:this.recurrentDropout,training:n,count:a,dropoutFunc:this.dropoutFunc}));let d=this.recurrentDropoutMask,h=l(s,d,0),g=l(s,d,1),y=l(s,d,2),b=l(s,d,3),w=3,[v,k,E,$]=ur(this.kernel.read(),a,w),[D,R,P,W]=this.useBias?ur(this.bias.read(),a):[null,null,null,null];c=this.inputConv(c,v,D,this.padding),p=this.inputConv(p,k,R,this.padding),m=this.inputConv(m,E,P,this.padding),f=this.inputConv(f,$,W,this.padding);let[U,q,K,j]=ur(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(O(rt,i),O(Q,this.activation.apply(J(m,y)))),ot=O(this.recurrentActivation.apply(J(f,b)),this.activation.apply(X));return[ot,ot,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=pn(t,e,this.strides,o||"valid",this.dataFormat==="channelsFirst"?"NCHW":"NHWC",this.dilationRate);return n?xn(s,n,this.dataFormat):s}recurrentConv(t,e){return pn(t,e,1,"same",this.dataFormat==="channelsFirst"?"NCHW":"NHWC")}};zc.className="ConvLSTM2DCell";et.registerClass(zc);var cf=class extends Qy{constructor(t){let e=new zc(t);super(Object.assign({},t,{cell:e}))}static fromConfig(t,e){return new t(e)}};cf.className="ConvLSTM2D";et.registerClass(cf);var Bc=class extends Vt{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 lu(()=>hy(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()}};Bc.className="Dropout";et.registerClass(Bc);var pf=class extends Bc{constructor(t){super(t),this.inputSpec=[{ndim:3}]}getNoiseShape(t){let e=t.shape;return[e[0],1,e[2]]}};pf.className="SpatialDropout1D";et.registerClass(pf);var mf=class extends Vt{constructor(t){if(super(t),this.activation=null,this.useBias=!0,this.kernel=null,this.bias=null,this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_BIAS_INITIALIZER="zeros",t.batchInputShape==null&&t.inputShape==null&&t.inputDim!=null){let e=null;t.batchSize!=null&&(e=t.batchSize),this.batchInputShape=[e,t.inputDim]}this.units=t.units,er(this.units,"units"),this.activation=ci(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=Ce(t.kernelRegularizer),this.biasRegularizer=Ce(t.biasRegularizer),this.activityRegularizer=Ce(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=ay(this.activation.getClassName()),s;return o!=null?s=Eo(n,this.kernel.read(),o,this.bias?this.bias.read():null):(s=Eo(n,this.kernel.read()),this.bias!=null&&(s=xn(s,this.bias.read())),this.activation!=null&&(s=this.activation.apply(s))),s})}getConfig(){let t={units:this.units,activation:ui(this.activation),useBias:this.useBias,kernelInitializer:Ee(this.kernelInitializer),biasInitializer:Ee(this.biasInitializer),kernelRegularizer:me(this.kernelRegularizer),biasRegularizer:me(this.biasRegularizer),activityRegularizer:me(this.activityRegularizer),kernelConstraint:We(this.kernelConstraint),biasConstraint:We(this.biasConstraint)},e=super.getConfig();return Object.assign(t,e),t}};mf.className="Dense";et.registerClass(mf);var ff=class extends Vt{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 ${t.slice(1)}). Make sure to pass a complete "input_shape" or "batch_input_shape" argument to the first layer in your model.`);return[t[0],_o(t,1)]}call(t,e){return B(()=>{this.invokeCallHook(t,e);let n=Pt(t);if(this.dataFormat==="channelsFirst"&&n.rank>1){let o=[0];for(let s=2;s<n.rank;++s)o.push(s);o.push(1),n=Mt(n,o)}return d$(n)})}getConfig(){let t={};this.dataFormat!=null&&(t.dataFormat=this.dataFormat);let e=super.getConfig();return Object.assign(t,e),t}};ff.className="Flatten";et.registerClass(ff);var df=class extends Vt{constructor(t){super(t),this.supportsMasking=!0,this.activation=ci(t.activation)}call(t,e){return B(()=>{this.invokeCallHook(t,e);let n=Pt(t);return this.activation.apply(n)})}getConfig(){let t={activation:ui(this.activation)},e=super.getConfig();return Object.assign(t,e),t}};df.className="Activation";et.registerClass(df);var hf=class extends Vt{constructor(t){super(t),this.n=t.n,this.inputSpec=[{ndim:2}]}computeOutputShape(t){return[t[0],this.n,t[1]]}call(t,e){return B(()=>(t=Pt(t),m$(t,this.n)))}getConfig(){let t={n:this.n},e=super.getConfig();return Object.assign(t,e),t}};hf.className="RepeatVector";et.registerClass(hf);var gf=class extends Vt{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=_o(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 M(n,s)})}getConfig(){let t={targetShape:this.targetShape},e=super.getConfig();return Object.assign(t,e),t}};gf.className="Reshape";et.registerClass(gf);var xf=class extends Vt{constructor(t){if(super(t),t.dims==null)throw new Error("Required configuration field `dims` is missing during Permute constructor call.");if(!Array.isArray(t.dims))throw new Error(`Permute constructor requires \`dims\` to be an Array, but received ${t.dims} instead.`);let e=Jr(1,t.dims.length+1);if(!x.arraysEqual(t.dims.slice().sort(),e))throw new Error("Invalid permutation `dims`: "+JSON.stringify(t.dims)+" `dims` must contain consecutive integers starting from 1.");this.dims=t.dims,this.dimsIncludingBatch=[0].concat(this.dims),this.inputSpec=[new ve({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 Mt(Pt(t),this.dimsIncludingBatch)}getConfig(){let t={dims:this.dims},e=super.getConfig();return Object.assign(t,e),t}};xf.className="Permute";et.registerClass(xf);var yf=class extends Vt{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 Zl(vo(n,this.maskValue),o)}call(t,e){return B(()=>{this.invokeCallHook(t,e);let n=Pt(t),o=-1,s=!0,i=Zl(vo(n,this.maskValue),o,s);return O(n,Z(i,n.dtype))})}};yf.className="Masking";et.registerClass(yf);var bf=class extends Vt{constructor(t){if(super(t),this.embeddings=null,this.DEFAULT_EMBEDDINGS_INITIALIZER="randomUniform",t.batchInputShape==null&&t.inputShape==null){let 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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=Ic(n,"int32"));let o=dy(this.embeddings.read(),M(n,[n.size]));return M(o,Jt(this.computeOutputShape(n.shape)))})}getConfig(){let t={inputDim:this.inputDim,outputDim:this.outputDim,embeddingsInitializer:Ee(this.embeddingsInitializer),embeddingsRegularizer:me(this.embeddingsRegularizer),activityRegularizer:me(this.activityRegularizer),embeddingsConstraint:We(this.embeddingsConstraint),maskZero:this.maskZero,inputLength:this.inputLength},e=super.getConfig();return Object.assign(t,e),t}};bf.className="Embedding";et.registerClass(bf);var gl=class extends Vt{constructor(t){super(t||{}),this.supportsMasking=!0}mergeFunction(t){throw new Nt}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}};kf.className="Concatenate";et.registerClass(kf);function rg(r,t){for(;r<0;)r+=t;return r}function R8(r,t,e){if(r.shape.length>3||t.shape.length>3)throw new Nt("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 Nt("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=M(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=M(r,r.shape.concat(u))}else i=0;let a;if(r.shape.length===2&&t.shape.length===2)s[0]===s[1]?a=mt(O(r,t),s[0]):a=mt(O(Mt(r,[1,0]),t),s[1]);else{let u=s[0]!==r.shape.length-1,l=s[1]===t.shape.length-1;a=zt(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=fr(a,1)),a})}var Nf=class extends gl{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 Nt("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)=>rg(s,t[i].shape.length)):o=[rg(this.axes,e.shape.length),rg(this.axes,n.shape.length)],this.normalize&&(e=jh(e,o[0]),n=jh(n,o[1])),R8(e,n,o)}interpretAxes(t,e){let n;return Array.isArray(this.axes)?n=this.axes:n=[rg(this.axes,t.length),rg(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 Nt("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}};Nf.className="Dot";et.registerClass(Nf);var Tf=class extends Vt{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 lu(()=>J(Tm(n.shape,0,this.stddev),n),()=>n,e.training||!1)})}};Tf.className="GaussianNoise";et.registerClass(Tf);var _f=class extends Vt{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?lu(()=>{let s=Math.sqrt(this.rate/(1-this.rate));return O(n,Tm(n.shape,1,s))},()=>n,e.training||!1):n})}};_f.className="GaussianDropout";et.registerClass(_f);var Ef=class extends Vt{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 lu(()=>{let s=Pt(t),i=1.6732632423543772,a=1.0507009873554805,u=-i*a,l=Tn(ri(n),this.rate);l=Ic(l,"float32");let c=((1-this.rate)*(1+this.rate*u**2))**-.5,p=-c*u*this.rate,m=J(O(s,l),O(J(l,-1),u));return J(O(m,c),p)},()=>Pt(t),e.training||!1)}return t})}};Ef.className="AlphaDropout";et.registerClass(Ef);function ng(r,t,e,n,o,s=.001){let i;if(r.rank===2)i=DI(r,t,e,n,o,s);else if(r.rank===3)i=RI(r,t,e,n,o,s);else if(r.rank===4)i=FI(r,t,e,n,o,s);else throw new Nt(`batchNormalization is not implemented for array of rank ${r.rank} yet`);return i}function F8(r,t,e,n,o=.001){return B(()=>{let s=ym(r,n),i=s.mean,a=s.variance;return[ng(r,i,a,e,t,o),i,a]})}function O8(r,t,e,n,o=.001){return B(()=>{let s=ym(r,n),i=s.mean,a=s.variance,u=[];for(let d of Jr(0,r.rank))n.indexOf(d)!==-1?u.push(1):u.push(r.shape[d]);let l=M(i,u),c=M(a,u),p=t==null?null:M(t,u),m=e==null?null:M(e,u);return[ng(r,l,c,m,p,o),i,a]})}function M8(r,t,e,n,o=.001){return x.arraysEqual(n.slice().sort(),Jr(0,r.rank-1))?F8(r,t,e,n,o):O8(r,t,e,n,o)}var Af=class extends Vt{constructor(t){t==null&&(t={}),super(t),this.supportsMasking=!0,this.axis=t.axis==null?-1:t.axis,this.momentum=t.momentum==null?.99:t.momentum,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.movingMeanInitializer=de(t.movingMeanInitializer||"zeros"),this.movingVarianceInitializer=de(t.movingVarianceInitializer||"ones"),this.betaConstraint=Ue(t.betaConstraint),this.gammaConstraint=Ue(t.gammaConstraint),this.betaRegularizer=Ce(t.betaRegularizer),this.gammaRegularizer=Ce(t.gammaRegularizer)}build(t){t=Jt(t);let 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 ${JSON.stringify(t)}.`);this.inputSpec=[new ve({ndim:t.length,axes:{[e]:n}})];let o=[n];this.scale&&(this.gamma=this.addWeight("gamma",o,null,this.gammaInitializer,this.gammaRegularizer,!0,this.gammaConstraint)),this.center&&(this.beta=this.addWeight("beta",o,null,this.betaInitializer,this.betaRegularizer,!0,this.betaConstraint)),this.movingMean=this.addWeight("moving_mean",o,null,this.movingMeanInitializer,null,!1),this.movingVariance=this.addWeight("moving_variance",o,null,this.movingVarianceInitializer,null,!1),this.built=!0}call(t,e){return B(()=>{let n=e.training==null?!1:e.training,o=Pt(t),s=o.shape,i=s.length,a=Jr(0,i),u=this.axis>=0?this.axis:this.axis+i;a.splice(u,1);let l=ko(1,i);l[u]=s[u];let c=a.slice();c.sort();let p=!x.arraysEqual(c,Jr(0,i).slice(0,i-1)),m=()=>{if(p){let b=M(this.movingMean.read(),l),w=M(this.movingVariance.read(),l),v=this.center?M(this.beta.read(),l):null,k=this.scale?M(this.gamma.read(),l):null;return ng(o,b,w,v,k,this.epsilon)}else return ng(o,this.movingMean.read(),this.movingVariance.read(),this.beta==null?null:this.beta.read(),this.gamma==null?null:this.gamma.read(),this.epsilon)};if(!n)return m();let[f,d,h]=M8(o,this.gamma.read(),this.beta.read(),a,this.epsilon),g=(b,w,v)=>{B(()=>{let k=1-v,E=b.read(),$=O(lt(E,w),k);b.write(lt(E,$))})};return(()=>{g(this.movingMean,d,this.momentum),g(this.movingVariance,h,this.momentum)})(),f})}getConfig(){let t={axis:this.axis,momentum:this.momentum,epsilon:this.epsilon,center:this.center,scale:this.scale,betaInitializer:Ee(this.betaInitializer),gammaInitializer:Ee(this.gammaInitializer),movingMeanInitializer:Ee(this.movingMeanInitializer),movingVarianceInitializer:Ee(this.movingVarianceInitializer),betaRegularizer:me(this.betaRegularizer),gammaRegularizer:me(this.gammaRegularizer),betaConstraint:We(this.betaConstraint),gammaConstraint:We(this.gammaConstraint)},e=super.getConfig();return Object.assign(t,e),t}};Af.className="BatchNormalization";et.registerClass(Af);var $f=class extends Vt{constructor(t){if(t==null&&(t={}),super(t),this.axis=t.axis==null?-1:t.axis,typeof this.axis=="number"){if(!Number.isInteger(this.axis))throw new Error(`Expected axis to be an integer, but received ${this.axis}`)}else if(Array.isArray(this.axis)){for(let e of this.axis)if(!Number.isInteger(e))throw new Error(`Expected axis to be an array of integers, but received ${JSON.stringify(this.axis)}`)}else throw new Error(`Expected axis to be an integer or an array of integers, but received ${JSON.stringify(this.axis)}`);this.epsilon=t.epsilon==null?.001:t.epsilon,this.center=t.center==null?!0:t.center,this.scale=t.scale==null?!0:t.scale,this.betaInitializer=de(t.betaInitializer||"zeros"),this.gammaInitializer=de(t.gammaInitializer||"ones"),this.betaRegularizer=Ce(t.betaRegularizer),this.gammaRegularizer=Ce(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!==To(this.axis).length)throw new Error(`Found duplicate axes in: ${this.axis}`);let n=this.axis.map(s=>t[s]),o=!0;this.scale?this.gamma=this.addWeight("gamma",n,"float32",this.gammaInitializer,this.gammaRegularizer,o):this.gamma=null,this.center?this.beta=this.addWeight("beta",n,"float32",this.betaInitializer,this.betaRegularizer,o):this.beta=null,this.built=!0}call(t,e){let n=Pt(t),o=n.shape,s=o.length;return B(()=>{let{mean:a,variance:u}=ym(n,this.axis,!0),l=ko(1,s);for(let h of this.axis)l[h]=o[h];let c=h=>h!=null&&h.shape.length!==s?M(h,l):h,p=c(this.gamma.read()),m=c(this.beta.read()),f=[],d=[];for(let h=0;h<s;++h)this.axis.indexOf(h)!==-1?(f.push(o[h]),d.push(1)):(f.push(1),d.push(o[h]));return a=kr(a,f),u=kr(u,f),p=kr(p,d),m=kr(m,d),ng(n,a,u,m,p,this.epsilon)})}getConfig(){let t={axis:this.axis,epsilon:this.epsilon,center:this.center,scale:this.scale,betaInitializer:Ee(this.betaInitializer),gammaInitializer:Ee(this.gammaInitializer),betaRegularizer:me(this.betaRegularizer),gammaRegularizer:me(this.gammaRegularizer)},e=super.getConfig();return Object.assign(t,e),t}};$f.className="LayerNormalization";et.registerClass($f);function P8(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=gn()),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 ve({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(()=>P8(Pt(t),this.padding,this.dataFormat))}getConfig(){let t={padding:this.padding,dataFormat:this.dataFormat},e=super.getConfig();return Object.assign(t,e),t}};Df.className="ZeroPadding2D";et.registerClass(Df);function sb(r,t,e,n,o,s){return B(()=>{Le(o),IS(s),hn(n),e==null&&(e=[1,1]),n==null&&(n="valid"),o==null&&(o=gn()),s==null&&(s="max"),r=eg(r,o);let i,a=n==="same"?"same":"valid";return s==="max"?i=Qa(r,t,e,a):i=qa(r,t,e,a),o==="channelsFirst"&&(i=Mt(i,[0,3,1,2])),i})}function rD(r,t,e,n,o,s){return B(()=>{Le(o),IS(s),hn(n),e==null&&(e=[1,1,1]),n==null&&(n="valid"),o==null&&(o=gn()),s==null&&(s="max"),r=BS(r,o);let i,a=n==="same"?"same":"valid";return s==="max"?i=Th(r,t,e,a):i=dh(r,t,e,a),o==="channelsFirst"&&(i=Mt(i,[0,4,1,2,3])),i})}var tb=class extends Vt{constructor(t){if(t.poolSize==null&&(t.poolSize=2),super(t),typeof t.poolSize=="number")this.poolSize=[t.poolSize];else if(Array.isArray(t.poolSize)&&t.poolSize.length===1&&typeof t.poolSize[0]=="number")this.poolSize=t.poolSize;else throw new z(`poolSize for 1D convolutional layer must be a number or an Array of a single number, but received ${JSON.stringify(t.poolSize)}`);if(er(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)}`);er(this.strides,"strides"),this.padding=t.padding==null?"valid":t.padding,hn(this.padding),this.inputSpec=[new ve({ndim:3})]}computeOutputShape(t){t=Jt(t);let e=An(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=ll(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}},Rf=class extends tb{constructor(t){super(t)}poolingFunction(t,e,n,o,s){return Le(s),hn(o),sb(t,e,n,o,s,"max")}};Rf.className="MaxPooling1D";et.registerClass(Rf);var Ff=class extends tb{constructor(t){super(t)}poolingFunction(t,e,n,o,s){return Le(s),hn(o),sb(t,e,n,o,s,"avg")}};Ff.className="AveragePooling1D";et.registerClass(Ff);var eb=class extends Vt{constructor(t){if(t.poolSize==null&&(t.poolSize=[2,2]),super(t),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];er(this.poolSize,"poolSize"),er(this.strides,"strides"),this.padding=t.padding==null?"valid":t.padding,this.dataFormat=t.dataFormat==null?"channelsLast":t.dataFormat,Le(this.dataFormat),hn(this.padding),this.inputSpec=[new ve({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=An(e,this.poolSize[0],this.padding,this.strides[0]),n=An(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}},Of=class extends eb{constructor(t){super(t)}poolingFunction(t,e,n,o,s){return Le(s),hn(o),sb(t,e,n,o,s,"max")}};Of.className="MaxPooling2D";et.registerClass(Of);var Mf=class extends eb{constructor(t){super(t)}poolingFunction(t,e,n,o,s){return Le(s),hn(o),sb(t,e,n,o,s,"avg")}};Mf.className="AveragePooling2D";et.registerClass(Mf);var rb=class extends Vt{constructor(t){if(t.poolSize==null&&(t.poolSize=[2,2,2]),super(t),this.poolSize=Array.isArray(t.poolSize)?t.poolSize:[t.poolSize,t.poolSize,t.poolSize],t.strides==null)this.strides=this.poolSize;else if(Array.isArray(t.strides)){if(t.strides.length!==3)throw new z(`If the strides property of a 3D pooling layer is an Array, it is expected to have a length of 3, but received length ${t.strides.length}.`);this.strides=t.strides}else this.strides=[t.strides,t.strides,t.strides];er(this.poolSize,"poolSize"),er(this.strides,"strides"),this.padding=t.padding==null?"valid":t.padding,this.dataFormat=t.dataFormat==null?"channelsLast":t.dataFormat,Le(this.dataFormat),hn(this.padding),this.inputSpec=[new ve({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=An(e,this.poolSize[0],this.padding,this.strides[0]),n=An(n,this.poolSize[1],this.padding,this.strides[1]),o=An(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}},Pf=class extends rb{constructor(t){super(t)}poolingFunction(t,e,n,o,s){return Le(s),hn(o),rD(t,e,n,o,s,"max")}};Pf.className="MaxPooling3D";et.registerClass(Pf);var Lf=class extends rb{constructor(t){super(t)}poolingFunction(t,e,n,o,s){return Le(s),hn(o),rD(t,e,n,o,s,"avg")}};Lf.className="AveragePooling3D";et.registerClass(Lf);var nb=class extends Vt{constructor(t){super(t),this.inputSpec=[new ve({ndim:3})]}computeOutputShape(t){return[t[0],t[2]]}call(t,e){throw new Nt}},zf=class extends nb{constructor(t){super(t||{})}call(t,e){return B(()=>{let n=Pt(t);return xe(n,1)})}};zf.className="GlobalAveragePooling1D";et.registerClass(zf);var Bf=class extends nb{constructor(t){super(t||{})}call(t,e){return B(()=>{let n=Pt(t);return Dr(n,1)})}};Bf.className="GlobalMaxPooling1D";et.registerClass(Bf);var ob=class extends Vt{constructor(t){super(t),this.dataFormat=t.dataFormat==null?"channelsLast":t.dataFormat,Le(this.dataFormat),this.inputSpec=[new ve({ndim:4})]}computeOutputShape(t){return t=t,this.dataFormat==="channelsLast"?[t[0],t[3]]:[t[0],t[1]]}call(t,e){throw new Nt}getConfig(){let t={dataFormat:this.dataFormat},e=super.getConfig();return Object.assign(t,e),t}},Vf=class extends ob{call(t,e){return B(()=>{let n=Pt(t);return this.dataFormat==="channelsLast"?xe(n,[1,2]):xe(n,[2,3])})}};Vf.className="GlobalAveragePooling2D";et.registerClass(Vf);var Gf=class extends ob{call(t,e){return B(()=>{let n=Pt(t);return this.dataFormat==="channelsLast"?Dr(n,[1,2]):Dr(n,[2,3])})}};Gf.className="GlobalMaxPooling2D";et.registerClass(Gf);var ib=class extends Vt{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=vn(o,n);delete e.layer;let i={layer:s};return Object.assign(i,e),new t(i)}},Wf=class extends ib{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 ${JSON.stringify(t)}`);this.inputSpec=[{shape:t}];let e=[t[0]].concat(t.slice(2));this.layer.built||(this.layer.build(e),this.layer.built=!0),super.build(t)}computeOutputShape(t){t=Jt(t);let e=[t[0]].concat(t.slice(2)),n=this.layer.computeOutputShape(e),o=t[1];return[n[0],o].concat(n.slice(1))}call(t,e){return B(()=>(t=Pt(t),GS((i,a)=>[Pt(this.layer.call(i,e)),[]],t,[],!1,null,null,!1,!0)[1]))}};Wf.className="TimeDistributed";et.registerClass(Wf);function L8(r){Ki(a$,"BidirectionalMergeMode",r)}var z8="concat",Uf=class extends ib{constructor(t){super(t);let e=t.layer.getConfig(),n={};n.className=t.layer.getClassName(),n.config=e,this.forwardLayer=vn(n),e.goBackwards=e.goBackwards!==!0;let o={};if(o.className=t.layer.getClassName(),o.config=e,this.backwardLayer=vn(o),this.forwardLayer.name="forward_"+this.forwardLayer.name,this.backwardLayer.name="backward_"+this.backwardLayer.name,this.mergeMode=t.mergeMode===void 0?z8:t.mergeMode,L8(this.mergeMode),t.weights)throw new Nt("weights support is not implemented for Bidirectional layer yet.");this._stateful=t.layer.stateful,this.returnSequences=t.layer.returnSequences,this.returnState=t.layer.returnState,this.supportsMasking=!0,this._trainable=!0,this.inputSpec=t.layer.inputSpec,this.numConstants=null}get trainable(){return this._trainable}set trainable(t){this._trainable=t,this.forwardLayer!=null&&(this.forwardLayer.trainable=t),this.backwardLayer!=null&&(this.backwardLayer.trainable=t)}getWeights(){return this.forwardLayer.getWeights().concat(this.backwardLayer.getWeights())}setWeights(t){let e=t.length,n=Math.floor(e/2);this.forwardLayer.setWeights(t.slice(0,n)),this.backwardLayer.setWeights(t.slice(n))}computeOutputShape(t){let e=this.forwardLayer.computeOutputShape(t);Array.isArray(e)&&Array.isArray(e[0])||(e=[e]),e=e;let n,o,s;return this.returnState&&(s=e.slice(1)),n=e[0],n=n,this.mergeMode==="concat"?(n[n.length-1]*=2,o=[n]):this.mergeMode==null?o=[n,n.slice()]:o=[n],this.returnState?this.mergeMode==null?o.concat(s).concat(s.slice()):[n].concat(s).concat(s.slice()):_r(o)}apply(t,e){let n=e==null?null:e.initialState,o=e==null?null:e.constants;e==null&&(e={});let s=VS(t,n,o,this.numConstants);if(t=s.inputs,n=s.initialState,o=s.constants,Array.isArray(t)&&(n=t.slice(1),t=t[0]),(n==null||n.length===0)&&o==null)return super.apply(t,e);let i=[],a=[];if(n!=null){let l=n.length;if(l%2>0)throw new z("When passing `initialState` to a Bidrectional RNN, the state should be an Array containing the states of the underlying RNNs.");e.initialState=n,i.push(...n);let c=n.map(p=>new ve({shape:p.shape}));this.forwardLayer.stateSpec=c.slice(0,l/2),this.backwardLayer.stateSpec=c.slice(l/2),a.push(...c)}if(o!=null)throw new Nt("Support for constants in Bidirectional layers is not implemented yet.");let u=i[0]instanceof Qr;for(let l of i)if(l instanceof Qr!==u)throw new z("The initial state of a Bidirectional layer cannot be specified as a mix of symbolic and non-symbolic tensors");if(u){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.initialState,o,s;if(n==null)o=this.forwardLayer.call(t,e),s=this.backwardLayer.call(t,e);else{let u=n.slice(0,n.length/2),l=n.slice(n.length/2);o=this.forwardLayer.call(t,Object.assign(e,{initialState:u})),s=this.backwardLayer.call(t,Object.assign(e,{initialState:l}))}let i;this.returnState&&(Array.isArray(o)&&(i=o.slice(1).concat(s.slice(1))),o=o[0],s=s[0]),this.returnSequences&&(s=ir(s,1));let 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n=I("tensorArrayId",r,t,e),o=I("tensor",r,t,e),s=I("lengths",r,t,e),i=e.getTensorArray(n.id);return i.split(s,o),[i.idTensor]}case"TensorArraySizeV3":{let n=I("tensorArrayId",r,t,e),o=e.getTensorArray(n.id);return[pt(o.size(),"int32")]}case"TensorArrayCloseV3":{let n=I("tensorArrayId",r,t,e),o=e.getTensorArray(n.id);return o.clearAndClose(),[o.idTensor]}case"TensorListSetItem":{let n=I("tensorListId",r,t,e),o=I("index",r,t,e),s=I("tensor",r,t,e),i=e.getTensorList(n.id);return i.setItem(o,s),[i.idTensor]}case"TensorListGetItem":{let n=I("tensorListId",r,t,e),o=I("index",r,t,e),s=I("elementShape",r,t,e),i=I("elementDType",r,t,e);return[e.getTensorList(n.id).getItem(o,s,i)]}case"TensorListScatterV2":case"TensorListScatter":{let n=I("indices",r,t,e),o=I("tensor",r,t,e),s=I("elementShape",r,t,e),i=I("numElements",r,t,e),a=CD(o,n,s,i);return e.addTensorList(a),[a.idTensor]}case"TensorListReserve":case"EmptyTensorList":{let 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n=I("strides",r,t,e),o=og(r,t,e),s=I("dataFormat",r,t,e).toUpperCase(),i=I("dilations",r,t,e);return[pn(I("x",r,t,e),I("filter",r,t,e),[n[1],n[2]],o,s,[i[1],i[2]])]}case"_FusedConv2D":{let{stride:n,pad:o,dataFormat:s,dilations:i,biasArg:a,preluArg:u,activationFunc:l,leakyreluAlpha:c}=kD(r,t,e);return[Co.conv2d({x:I("x",r,t,e),filter:I("filter",r,t,e),strides:[n[1],n[2]],pad:o,dataFormat:s,dilations:[i[1],i[2]],bias:a,activation:l,preluActivationWeights:u,leakyreluAlpha:c})]}case"FusedDepthwiseConv2dNative":{let{stride:n,pad:o,dataFormat:s,dilations:i,biasArg:a,preluArg:u,activationFunc:l,leakyreluAlpha:c}=kD(r,t,e);return[Co.depthwiseConv2d({x:I("x",r,t,e),filter:I("filter",r,t,e),strides:[n[1],n[2]],pad:o,dataFormat:s,dilations:[i[1],i[2]],bias:a,activation:l,preluActivationWeights:u,leakyreluAlpha:c})]}case"Conv2DBackpropInput":case"Conv2dTranspose":{let 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n=I("image",r,t,e),o=I("boxes",r,t,e),s=I("boxInd",r,t,e),i=I("cropSize",r,t,e),a=I("method",r,t,e),u=I("extrapolationValue",r,t,e);return[dn.cropAndResize(n,o,s,i,a,u)]}case"ImageProjectiveTransformV3":{let n=I("images",r,t,e),o=I("transforms",r,t,e),s=I("outputShape",r,t,e),i=I("fillValue",r,t,e),a=I("interpolation",r,t,e),u=I("fillMode",r,t,e);return[dn.transform(n,o,a.toLowerCase(),u.toLowerCase(),i,s)]}default:throw TypeError(`Node type ${r.op} is not implemented`)}};var RD=(r,t,e)=>{switch(r.op){case"Equal":return[Sr(I("a",r,t,e),I("b",r,t,e))];case"NotEqual":return[vo(I("a",r,t,e),I("b",r,t,e))];case"Greater":return[Ge(I("a",r,t,e),I("b",r,t,e))];case"GreaterEqual":return[Tn(I("a",r,t,e),I("b",r,t,e))];case"Less":return[rc(I("a",r,t,e),I("b",r,t,e))];case"LessEqual":return[_n(I("a",r,t,e),I("b",r,t,e))];case"LogicalAnd":return[Nr(I("a",r,t,e),I("b",r,t,e))];case"LogicalNot":return[Ja(I("a",r,t,e))];case"LogicalOr":return[oc(I("a",r,t,e),I("b",r,t,e))];case"Select":case"SelectV2":return[_e(I("condition",r,t,e),I("a",r,t,e),I("b",r,t,e))];default:throw TypeError(`Node type ${r.op} is not implemented`)}};var FD=(r,t,e)=>{switch(r.op){case"BatchMatMul":case"BatchMatMulV2":case"MatMul":return[zt(I("a",r,t,e),I("b",r,t,e),I("transposeA",r,t,e),I("transposeB",r,t,e))];case"Einsum":return[WI(I("equation",r,t,e),...I("tensors",r,t,e))];case"Transpose":return[Mt(I("x",r,t,e),I("perm",r,t,e))];case"_FusedMatMul":let[n,o]=I("fusedOps",r,t,e),s=n==="biasadd",i=o==="prelu",a=I("numArgs",r,t,e),u=I("leakyreluAlpha",r,t,e);if(s){if(i&&a!==2)throw new Error("Fused MatMul with BiasAdd and Prelu must have two extra arguments: bias and alpha.");if(!i&&a!==1)throw new Error("Fused MatMul with BiasAdd must have one extra argument: bias.")}let[l,c]=I("args",r,t,e);return[Co.matMul({a:I("a",r,t,e),b:I("b",r,t,e),transposeA:I("transposeA",r,t,e),transposeB:I("transposeB",r,t,e),bias:l,activation:o,preluActivationWeights:c,leakyreluAlpha:u})];default:throw TypeError(`Node type ${r.op} is not implemented`)}};var 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GD(r,t,e){let{usedNodes:n,inputs:o}=e,s=[],i=Object.keys(o).map(c=>Cn(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 sZ=["Switch","Merge","Enter","Exit","NextIteration","StatelessIf","StatelessWhile","if","While"],iZ=["NonMaxSuppressionV2","NonMaxSuppressionV3","NonMaxSuppressionV5","Where"],aZ=["HashTable","HashTableV2","LookupTableImport","LookupTableImportV2","LookupTableFind","LookupTableFindV2","LookupTableSize","LookupTableSizeV2"];function gk(r){return sZ.indexOf(r.op)>=0}function lZ(r){return iZ.indexOf(r.op)>=0}function uZ(r){return aZ.indexOf(r.op)>=0}var Vc=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 Vc(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}:${t.defaultOutput}`:e})}get functions(){return Object.keys(this._functions).reduce((t,e)=>(t[e]=this._functions[e].signature,t),{})}getCompilationKey(t,e){let n=t.map(s=>s.name).sort(),o=e.map(s=>s.name).sort();return n.join(this.SEPERATOR)+"--"+o.join(this.SEPERATOR)}compile(t,e){let n=hk(t,e,this.weightMap,this._initNodes),{missingInputs:o,dynamicNode:s,syncInputs:i}=n;if(s!=null)throw new Error(`This execution contains the node '${s.name}', which has the dynamic op '${s.op}'. 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Missing the following inputs: [${o}]`)}return GD(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[Cn(p)[0]]),s=e.map(p=>Cn(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 ig(this.weightMap,l,c,this.functionExecutorMap),m=Object.assign({},this.weightMap);Object.keys(t).forEach(h=>{let[g,y]=Cn(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=dk(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}]. ${w}`)}return d}processStack(t,e,n,o,s,i,a,u,l){let c=[];for(;e.length>0;){let p=e.pop();n.currentContext=p.contexts;let m="";if(p.node.op==="Enter"&&I("isConstant",p.node,o,n)&&([m]=Do(p.node.name,n)),o[p.node.name]==null){let f=dk(p.node,o,n,this._resourceManager);m||([m]=Do(p.node.name,n));let d=n.currentContext;x.isPromise(f)?c.push(f.then(h=>(o[m]=h,n.currentContext=d,this.checkTensorForDisposal(m,p.node,o,n,i,a,u),this.processChildNodes(p.node,e,n,o,s,l),h))):(o[m]=f,this.checkTensorForDisposal(m,p.node,o,n,i,a,u),this.processChildNodes(p.node,e,n,o,s,l))}else this.processChildNodes(p.node,e,n,o,s,l)}return c}processChildNodes(t,e,n,o,s,i){t.children.forEach(a=>{let[u]=Do(a.name,n);s[u]||!i.has(a.name)||(a.op==="Merge"?a.inputNames.some(l=>!!Cr(l,o,n))&&(s[u]=!0,e.push({contexts:n.currentContext,node:a})):a.inputNames.every(l=>!!Cr(l,o,n))&&(s[u]=!0,e.push({contexts:n.currentContext,node:a})))})}dispose(){Object.keys(this.weightMap).forEach(t=>this.weightMap[t].forEach(e=>e.dispose()))}checkInputShapeAndType(t){Object.keys(t).forEach(e=>{let n=t[e],[o]=Cn(e),s=this.graph.nodes[o];if(s.attrParams.shape&&s.attrParams.shape.value){let i=s.attrParams.shape.value,a=i.length===n.shape.length&&n.shape.every((u,l)=>i[l]===-1||i[l]===u);x.assert(a,()=>`The shape of dict['${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 ${n.dtype}`)})}mapInputs(t){let e={};for(let n 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e=Mr.getLoadHandlers(t,this.loadOptions);if(e.length===0)e.push(Mr.browserHTTPRequest(t,this.loadOptions));else if(e.length>1)throw new Error(`Found more than one (${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=Mr.decodeWeights(this.artifacts.weightData,this.artifacts.weightSpecs);if(this.executor=new 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t=this.items[this.trav];return this.trav++,{value:uR(t),done:!1}}},Tk=class extends rr{constructor(t){super(),this.nextFn=t}summary(){return"Function call"}async next(){try{return this.nextFn()}catch(t){throw t.message=`Error thrown while iterating through a dataset: ${t.message}`,t}}},_k=class extends rr{constructor(t){super(),this.upstream=t,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> Serial`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){return this.upstream.next()}},Ek=class extends rr{constructor(t,e){super(),this.upstream=t,this.maxCount=e,this.count=0,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> Skip`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){for(;this.count++<this.maxCount;){let t=await this.upstream.next();if(t.done)return t;_t(t.value)}return this.upstream.next()}},Ak=class extends rr{constructor(t,e){super(),this.upstream=t,this.maxCount=e,this.count=0}summary(){return`${this.upstream.summary()} -> Take`}async next(){return this.count++>=this.maxCount?{value:null,done:!0}:this.upstream.next()}},$k=class extends rr{constructor(t,e,n=!0){super(),this.upstream=t,this.batchSize=e,this.enableSmallLastBatch=n,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> RowMajorBatch`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){let t=[];for(;t.length<this.batchSize;){let e=await this.upstream.next();if(e.done)return this.enableSmallLastBatch&&t.length>0?{value:t,done:!1}:{value:null,done:!0};t.push(e.value)}return{value:t,done:!1}}},Dk=class extends rr{constructor(t,e){super(),this.upstream=t,this.predicate=e,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> Filter`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){for(;;){let t=await this.upstream.next();if(t.done||this.predicate(t.value))return t;_t(t.value)}}},Rk=class extends rr{constructor(t,e){super(),this.upstream=t,this.transform=e}summary(){return`${this.upstream.summary()} -> Map`}async next(){let t=await this.upstream.next();if(t.done)return{value:null,done:!0};let e=fo.getTensorsInContainer(t.value),n=this.transform(t.value),o=fo.getTensorsInContainer(n);for(let s of e)fo.isTensorInList(s,o)||s.dispose();return{value:n,done:!1}}},Fk=class extends rr{constructor(t,e){super(),this.upstream=t,this.handler=e,this.count=0,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> handleErrors`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){for(;;)try{return await this.upstream.next()}catch(t){if(!this.handler(t))return{value:null,done:!0}}}},$b=class extends rr{constructor(t,e){super(),this.upstream=t,this.transform=e}summary(){return`${this.upstream.summary()} -> AsyncMap`}async next(){let t=await this.upstream.next();if(t.done)return{value:null,done:!0};let e=fo.getTensorsInContainer(t.value),n=await this.transform(t.value),o=fo.getTensorsInContainer(n);for(let s of e)fo.isTensorInList(s,o)||s.dispose();return{value:n,done:!1}}},Uc=class extends rr{constructor(){super(),this.outputQueue=new Wc,this.lastRead=Promise.resolve({value:null,done:!1})}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){for(;this.outputQueue.length()===0;)if(!await this.pump())return{value:null,done:!0};return{value:this.outputQueue.shift(),done:!1}}},Ok=class extends Uc{constructor(t,e){super(),this.upstream=t,this.transform=e}summary(){return`${this.upstream.summary()} -> Flatmap`}async pump(){let t=await this.upstream.next();if(t.done)return!1;let e=fo.getTensorsInContainer(t.value),n=this.transform(t.value),o=fo.getTensorsInContainer(n);this.outputQueue.pushAll(n);for(let s of e)fo.isTensorInList(s,o)||s.dispose();return!0}},Db=class extends rr{constructor(t,e){super(),this.baseErrorHandler=e,this.lastRead=null,this.iterator=null,this.moreIterators=t}summary(){return"TODO: fill in upstream of chained summaries -> Chained"}async next(){return this.lastRead=this.readFromChain(this.lastRead),this.lastRead}async readFromChain(t){if(await t,this.iterator==null){let n=await this.moreIterators.next();if(n.done)return{value:null,done:!0};this.iterator=n.value,this.baseErrorHandler!=null&&(this.iterator=this.iterator.handleErrors(this.baseErrorHandler))}let e=await this.iterator.next();return e.done?(this.iterator=null,this.readFromChain(t)):e}},yl;(function(r){r[r.FAIL=0]="FAIL",r[r.SHORTEST=1]="SHORTEST",r[r.LONGEST=2]="LONGEST"})(yl||(yl={}));var Mk=class extends rr{constructor(t,e=yl.FAIL){super(),this.iterators=t,this.mismatchMode=e,this.count=0,this.currentPromise=null}summary(){return"{TODO: fill in upstream of zip summaries} -> Zip"}async nextState(t){await t;let e=0,n=0;function o(i){return i instanceof rr?{value:i.next().then(u=>(e++,u.done&&n++,u.value)),recurse:!1}:{value:null,recurse:!0}}let s=await Ab(this.iterators,o);if(e===n)return{value:null,done:!0};if(n>0)switch(this.mismatchMode){case yl.FAIL:throw new Error(`Zipped streams should have the same length. Mismatched at element ${this.count}.`);case yl.SHORTEST:return{value:null,done:!0};case yl.LONGEST:default:}return this.count++,{value:s,done:!1}}async next(){return this.currentPromise=this.nextState(this.currentPromise),this.currentPromise}},Rb=class extends rr{constructor(t,e){super(),this.upstream=t,this.bufferSize=e,this.buffer=new qf(e)}summary(){return`${this.upstream.summary()} -> Prefetch`}refill(){for(;!this.buffer.isFull();){let t=this.upstream.next();this.buffer.push(t)}}next(){return this.refill(),this.buffer.shift()}},Pk=class extends Rb{constructor(t,e,n){super(t,e),this.upstream=t,this.windowSize=e,this.upstreamExhausted=!1,this.random=cR.alea(n||x.now().toString()),this.lastRead=Promise.resolve({value:null,done:!1})}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}randomInt(t){return Math.floor(this.random()*t)}chooseIndex(){return this.randomInt(this.buffer.length())}async serialNext(){for(this.upstreamExhausted||this.refill();!this.buffer.isEmpty();){let t=this.chooseIndex(),e=await this.buffer.shuffleExcise(t);if(e.done)this.upstreamExhausted=!0;else return this.refill(),e}return{value:null,done:!0}}};var fi=class{constructor(){this.size=null}batch(t,e=!0){let n=this;x.assert(t>0,()=>`batchSize needs to be positive, but it is
${t}`);let o;return this.size===1/0||this.size==null?o=this.size:e?o=Math.ceil(this.size/t):o=Math.floor(this.size/t),Dn(async()=>(await n.iterator()).columnMajorBatch(t,e,vZ),o)}concatenate(t){let e=this,n;return this.size===1/0||t.size===1/0?n=1/0:this.size!=null&&t.size!=null?n=this.size+t.size:n=null,Dn(async()=>(await e.iterator()).concatenate(await t.iterator()),n)}filter(t){let e=this,n;return this.size===1/0?n=1/0:n=null,Dn(async()=>(await e.iterator()).filter(o=>B(()=>t(o))),n)}async forEachAsync(t){return(await this.iterator()).forEachAsync(t)}map(t){let e=this;return Dn(async()=>(await e.iterator()).map(n=>B(()=>t(n))),this.size)}mapAsync(t){let e=this;return Dn(async()=>(await e.iterator()).mapAsync(t),this.size)}prefetch(t){if(t==null)throw new RangeError("`Dataset.prefetch()` requires bufferSize to be specified.");let e=this;return Dn(async()=>(await e.iterator()).prefetch(t),this.size)}repeat(t){let e=this,n;return this.size!=null&&t>0?n=this.size*t:t===0?n=0:this.size!=null&&(t===void 0||t<0)?n=1/0:n=null,Dn(async()=>{let o=ag(async()=>({value:await e.iterator(),done:!1}));return pR(o.take(t))},n)}skip(t){let e=this,n;return this.size!=null&&t>=0&&this.size>=t?n=this.size-t:this.size!=null&&(this.size<t||t===void 0||t<0)?n=0:n=null,Dn(async()=>(await e.iterator()).skip(t),n)}shuffle(t,e,n=!0){if(t==null||t<0)throw this.size==null?new RangeError("`Dataset.shuffle()` requires bufferSize to be specified."):new RangeError(`\`Dataset.shuffle()\` requires bufferSize to be specified. If your data fits in main memory (for regular JS objects), and/or GPU memory (for \`tf.Tensor\`s), consider setting bufferSize to the dataset size (${this.size} elements)`);let o=this,s=fR.alea(e||x.now().toString());return Dn(async()=>{let i=s.int32();return n&&(i+=s.int32()),(await o.iterator()).shuffle(t,i.toString())},this.size)}take(t){let e=this,n;return this.size!=null&&this.size>t?n=t:this.size!=null&&this.size<=t?n=this.size:n=null,Dn(async()=>(await e.iterator()).take(t),n)}async toArray(){if(this.size===1/0)throw new Error("Can not convert infinite data stream to array.");return(await this.iterator()).toArray()}async toArrayForTest(){if(this.size===1/0)throw new Error("Can not convert infinite data stream to array.");return(await this.iterator()).toArrayForTest()}};fi.MAX_BUFFER_SIZE=1e4;function Dn(r,t=null){return new class extends fi{constructor(){super(...arguments),this.size=t}async iterator(){return r()}}}function dR(r){return Dn(async()=>Lk(r),r.length)}function hR(r){if(!hu(r))throw new Error("The argument to zip() must be an object or array.");let t;if(Array.isArray(r))for(let e=0;e<r.length;e++)t=t==null?r[e].size:Math.min(t,r[e].size);else if(r instanceof Object)for(let e in r)t=t==null?r[e].size:Math.min(t,r[e].size);return Dn(async()=>{let e=await Ab(r,n=>{if(n instanceof fi)return{value:n.iterator(),recurse:!1};if(hu(n))return{value:null,recurse:!0};throw new Error("Leaves of the structure passed to zip() must be Datasets, not primitives.")});return mR(e,yl.SHORTEST)},t)}function vZ(r){if(r===null)return null;let t=r[0];return lR(t)?{value:CZ(r),recurse:!1}:{value:null,recurse:!0}}function CZ(r){if(r.length===0)throw new Error("Can't make a batch of zero elements.");return r[0]instanceof Lt?Je(r):Ar(r)}var Kf=class extends fi{constructor(t){super(),this.input=t}async iterator(){return(await this.input.iterator()).decodeUTF8().split(`
`).map(o=>(o.endsWith("\r")&&(o=o.slice(0,-1)),o))}};var Fb='"',lg=Symbol("out"),gR=Symbol("field"),Ob=Symbol("quote"),zk=Symbol("quoteafterquote"),xR=Symbol("quoteinquote"),jf=class extends fi{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 Kf(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=lg;for(let a=0;a<s;a++)switch(i){case lg:switch(t.charAt(a)){case Fb:o=a+1,i=Ob;break;case this.delimiter:if(o=a+1,this.delimiter===" "&&this.delimWhitespace)break;n.push(""),i=lg;break;default:i=gR,o=a;break}break;case gR:switch(t.charAt(a)){case this.delimiter:n.push(t.substring(o,a)),i=lg,o=a+1;break;default:}break;case Ob:switch(t.charAt(a)){case Fb:i=zk;break;default:}break;case zk:switch(t.charAt(a)){case this.delimiter:n.push(t.substring(o,a-1)),i=lg,o=a+1;break;case Fb:i=Ob;break;default:i=xR;break}break;case xR:switch(t.charAt(a)){case Fb:i=Ob;break;default:}break;default:}if(i===zk?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 Xf=class extends rr{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(!V().get("IS_BROWSER"))throw new Error("microphone API is only supported in browser environment.");let e=new Xf(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 Yf=class extends rr{constructor(t,e){if(super(),this.webcamVideoElement=t,this.webcamConfig=e,this.isClosed=!0,this.resize=!1,this.needToResize())if(this.resize=!0,this.cropSize=[this.webcamConfig.resizeHeight,this.webcamConfig.resizeWidth],this.cropBoxInd=Re([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=Ui([i,s,u,a],[1,4])}else this.cropBox=Ui([0,0,1,1],[1,4])}summary(){return"webcam"}static async create(t,e={}){if(!V().get("IS_BROWSER"))throw new Error("tf.data.webcam is only supported in browser environment.");if(!t){if(t=document.createElement("video"),!e.resizeWidth||!e.resizeHeight)throw new Error("Please provide webcam video element, or resizeWidth and resizeHeight to create a hidden video element.");t.width=e.resizeWidth,t.height=e.resizeHeight}let n=new Yf(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: ${this.webcamConfig.facingMode}. 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============================
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v=i?[g,c,m]:[g,m,c],k=a?[y,f,p]:[y,p,f],E=ne({inputs:{x:o},backend:e,attrs:{shape:v}}),$=ne({inputs:{x:s},backend:e,attrs:{shape:k}}),D=i?E.shape[1]:E.shape[2],R=i?E.shape[2]:E.shape[1],P=a?$.shape[1]:$.shape[2],W=Math.max(g,y),U=e.data.get(E.dataId).values,q=e.data.get($.dataId).values,K=x.computeStrides(E.shape),j=x.computeStrides($.shape),[Q,rt,X]=i?[K[0],1,K[1]]:[K[0],K[1],1],[ot,st,it]=a?[1,j[1],j[0]]:[j[1],1,j[0]],ft=R*P,at=It([W,R,P],E.dtype),xt=at.values,dt=e.blockSize;for(let bt=0;bt<W;bt++)for(let kt=0;kt<R;kt+=dt)for(let At=0;At<P;At+=dt)for(let Dt=0;Dt<D;Dt+=dt){let qt=Math.min(kt+dt,R),Kt=Math.min(At+dt,P),ce=Math.min(Dt+dt,D);for(let Ot=kt;Ot<qt;Ot++)for(let $e=At;$e<Kt;$e++){let Se=0;for(let ae=Dt;ae<ce;ae++){let je=Math.min(bt,g-1)*Q,Fe=Math.min(bt,y-1)*it,rn=U[je+Ot*rt+ae*X],ze=q[ae*ot+$e*st+Fe];Se+=rn*ze}xt[bt*ft+(Ot*P+$e)]+=Se}}return e.disposeIntermediateTensorInfo(E),e.disposeIntermediateTensorInfo($),e.makeTensorInfo(w,at.dtype,at.values)}var uF={kernelName:ts,backendName:"cpu",kernelFunc:wN};function jZ(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,m,f,d,h=[];m=wN({inputs:{a:o,b:s},attrs:{transposeA:u,transposeB:l},backend:e}),i&&(f=bl({inputs:{a:m,b:i},backend:e}),h.push(m),m=f),c&&(d=id(e,m,c,a,p),h.push(m),m=d);for(let y of h)e.disposeIntermediateTensorInfo(y);return m}var cF={kernelName:Oi,backendName:"cpu",kernelFunc:jZ};var XZ=Et(ea,r=>Math.acos(r)),pF={kernelName:ea,backendName:"cpu",kernelFunc:XZ};var YZ=Et(ra,r=>Math.acosh(r)),mF={kernelName:ra,backendName:"cpu",kernelFunc:YZ};function ZZ(r){let{inputs:t,backend:e}=r,n=t;nt(t,"addN");let o=n.map(a=>e.data.get(a.dataId).values),s=It(n[0].shape,n[0].dtype),i=s.values;for(let a=0;a<n.length;a++){let u=o[a];for(let l=0;l<i.length;l++)i[l]+=u[l]}return e.makeTensorInfo(s.shape,s.dtype,s.values)}var fF={kernelName:Zo,backendName:"cpu",kernelFunc:ZZ};function 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ae=dt;ae<bt;ae+=p){let je=Se+ae*n[3],Fe=r[je+U];if(s==="max"&&Fe>At?At=Fe:s==="avg"&&(Dt+=Fe,qt++),isNaN(At))break}if(isNaN(At))break}if(isNaN(At))break}let Kt=kt+U;v[Kt]=s==="avg"?Dt/qt:At}}}}return w}function IF(r,t){let e=It(t.outShape,"int32"),n=t.strideDepth,o=t.strideHeight,s=t.strideWidth,i=t.dilationDepth,a=t.dilationHeight,u=t.dilationWidth,l=t.effectiveFilterDepth,c=t.effectiveFilterHeight,p=t.effectiveFilterWidth,m=t.padInfo.front,f=t.padInfo.top,d=t.padInfo.left;for(let h=0;h<t.batchSize;++h)for(let g=0;g<t.inChannels;++g)for(let y=0;y<t.outDepth;++y){let b=y*n-m,w=b;for(;w<0;)w+=i;let v=Math.min(t.inDepth,l+b);for(let k=0;k<t.outHeight;++k){let E=k*o-f,$=E;for(;$<0;)$+=a;let D=Math.min(t.inHeight,c+E);for(let R=0;R<t.outWidth;++R){let P=R*s-d,W=P;for(;W<0;)W+=u;let U=Math.min(t.inWidth,p+P),q=Number.NEGATIVE_INFINITY,K=-1;for(let j=w;j<v;j+=i){let Q=j-b;for(let rt=$;rt<D;rt+=a){let X=rt-E;for(let ot=W;ot<U;ot+=u){let st=ot-P,it=r.get(h,j,rt,ot,g);it>=q&&(q=it,K=Q*c*p+X*c+st)}}}e.set(K,h,y,k,R,g)}}}return e}function l9(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t;nt(o,"avgPool");let{filterSize:s,strides:i,pad:a,dimRoundingMode:u}=n,l=1;x.assert(S.eitherStridesOrDilationsAreOne(i,l),()=>`Error in avgPool: Either strides or dilations must be 1. 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c=S.computePool3DInfo(s.shape,i,a,1,u,l),p=c.strideDepth,m=c.strideHeight,f=c.strideWidth,d=c.filterDepth,h=c.filterHeight,g=c.filterWidth,y=c.dilationDepth,b=c.dilationHeight,w=c.dilationWidth,v=c.effectiveFilterDepth,k=c.effectiveFilterHeight,E=c.effectiveFilterWidth,$=v-1-c.padInfo.front,D=E-1-c.padInfo.left,R=k-1-c.padInfo.top,P=It(s.shape,"float32"),W=1/(d*h*g),U=e.bufferSync(o);for(let q=0;q<c.batchSize;++q)for(let K=0;K<c.inChannels;++K)for(let j=0;j<c.inDepth;++j)for(let Q=0;Q<c.inHeight;++Q)for(let rt=0;rt<c.inWidth;++rt){let X=j-$,ot=Q-R,st=rt-D,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<k;xt+=b){let dt=(ot+xt)/m;if(!(dt<0||dt>=c.outHeight||Math.floor(dt)!==dt))for(let bt=0;bt<E;bt+=w){let kt=(st+bt)/f;if(kt<0||kt>=c.outWidth||Math.floor(kt)!==kt)continue;it+=U.get(q,at,dt,kt,K)}}}P.set(it*W,q,j,Q,rt,K)}return e.makeTensorInfo(P.shape,P.dtype,P.values)}var NF={kernelName:_p,backendName:"cpu",kernelFunc:c9};function p9(r){let{inputs:t,backend:e,attrs:n}=r,{dy:o,input:s}=t,i=s;nt([o,s],"avgPoolGrad");let{filterSize:a,strides:u,pad:l}=n,c=S.computePool2DInfo(i.shape,a,u,1,l),p=c.strideHeight,m=c.strideWidth,f=c.filterHeight,d=c.filterWidth,h=c.dilationHeight,g=c.dilationWidth,y=c.effectiveFilterHeight,b=c.effectiveFilterWidth,w=b-1-c.padInfo.left,v=y-1-c.padInfo.top,k=It(i.shape,"float32"),E=1/(f*d),$=e.data.get(o.dataId).values,D=It(o.shape,"float32",$);for(let R=0;R<c.batchSize;++R)for(let P=0;P<c.inChannels;++P)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 ot=(K+X)/m;if(ot<0||ot>=c.outWidth||Math.floor(ot)!==ot)continue;j+=D.get(R,rt,ot,P)}}k.set(j*E,R,W,U,P)}return e.makeTensorInfo(k.shape,k.dtype,k.values)}var TF={kernelName:Tp,backendName:"cpu",kernelFunc:p9};function 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e.makeTensorInfo(o.shape,o.dtype,h)}var _F={kernelName:fs,backendName:"cpu",kernelFunc:m9};function f9(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{blockShape:s,crops:i}=n;nt([o],"batchToSpaceND");let a=s.reduce((y,b)=>y*b),u=S.getReshaped(o.shape,s,a),l=S.getPermuted(u.length,s.length),c=S.getReshapedPermuted(o.shape,s,a),p=S.getSliceBeginCoords(i,s.length),m=S.getSliceSize(c,i,s.length),f=ne({inputs:{x:o},backend:e,attrs:{shape:u}}),d=He({inputs:{x:f},backend:e,attrs:{perm:l}}),h=ne({inputs:{x:d},backend:e,attrs:{shape:c}}),g=Mo({inputs:{x:h},backend:e,attrs:{begin:p,size:m}});return e.disposeIntermediateTensorInfo(f),e.disposeIntermediateTensorInfo(d),e.disposeIntermediateTensorInfo(h),g}var EF={kernelName:vi,backendName:"cpu",kernelFunc:f9};function d9(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=nd(a,u,s.dtype,s.shape,i);return e.makeTensorInfo([i],s.dtype,l)}var 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Zi(r){let{inputs:t,backend:e}=r,{input:n}=t,o=e.data.get(n.dataId).complexTensorInfos.imag,s=e.data.get(o.dataId).values;return e.makeTensorInfo(o.shape,o.dtype,s)}var FF={kernelName:Wp,backendName:"cpu",kernelFunc:Zi};function xu(r){let{inputs:t,backend:e,attrs:n}=r,{axis:o}=n,s=x.parseAxisParam(o,t[0].shape)[0],i=S.computeOutShape(t.map(h=>h.shape),s);if(x.sizeFromShape(i)===0)return e.makeTensorInfo(i,t[0].dtype,[]);let a=t.filter(h=>x.sizeFromShape(h.shape)>0);if(a.length===1)return qr({inputs:{x:a[0]},backend:e});let u=a.map(h=>h.shape);if(S.assertParamsConsistent(u,s),a[0].dtype==="complex64"){let h=a.map(v=>Ro({inputs:{input:v},backend:e})),g=a.map(v=>Zi({inputs:{input:v},backend:e})),y=xu({inputs:h,backend:e,attrs:{axis:s}}),b=xu({inputs:g,backend:e,attrs:{axis:s}}),w=Ir({inputs:{real:y,imag:b},backend:e});return 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e.makeTensorInfo(b.shape,b.dtype,b.values)}var PF={kernelName:Dp,backendName:"cpu",kernelFunc:y9};function b9(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;nt([o,s],"conv2dBackpropInput");let p=x.computeStrides(s.shape),m=x.computeStrides(o.shape),f=S.convertConv2DDataFormat(l),d=S.computeConv2DInfo(i,s.shape,a,1,u,c,!1,f),h=new pe(d.inShape,"float32"),g=h.values,y=e.data.get(o.dataId).values,b=e.data.get(s.dataId).values,[w,v,k]=p,{batchSize:E,filterHeight:$,filterWidth:D,inChannels:R,inHeight:P,inWidth:W,outChannels:U,outHeight:q,outWidth:K,strideHeight:j,strideWidth:Q}=d;f=d.dataFormat;let rt=$-1-d.padInfo.top,X=D-1-d.padInfo.left,ot=f==="channelsLast",st=h.strides[0],it=ot?h.strides[1]:h.strides[2],ft=ot?h.strides[2]:1,at=ot?1:h.strides[1],xt=m[0],dt=ot?m[1]:m[2],bt=ot?m[2]:1,kt=ot?1:m[1];for(let At=0;At<E;++At)for(let Dt=0;Dt<R;++Dt)for(let qt=0;qt<P;++qt){let 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l=x.computeStrides(o.shape),c=x.computeStrides(s.shape),p=S.computeConv3DInfo(o.shape,u,i,1,a),m=p.strideDepth,f=p.strideHeight,d=p.strideWidth,h=p.filterDepth,g=p.filterHeight,y=p.filterWidth,b=new pe(p.filterShape,"float32"),w=b.values,[v,k,E,$]=b.strides,D=e.data.get(s.dataId).values,[R,P,W,U]=c,q=e.data.get(o.dataId).values,[K,j,Q,rt]=l,X=p.padInfo.front,ot=p.padInfo.left,st=p.padInfo.top;for(let it=0;it<h;++it){let ft=Math.max(0,Math.ceil((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*k+xt;for(let Dt=0;Dt<y;++Dt){let qt=Math.max(0,Math.ceil((ot-Dt)/d)),Kt=Math.min(p.outWidth,(p.inWidth+ot-Dt)/d),ce=Dt*E+At;for(let Ot=0;Ot<p.inChannels;++Ot){let $e=Ot*$+ce;for(let Se=0;Se<p.outChannels;++Se){let ae=0;for(let je=0;je<p.batchSize;++je){let Fe=je*K,rn=je*R;for(let ze=ft;ze<at;++ze){let Fr=(it+ze*m-X)*j+Fe,nn=ze*P+rn;for(let on=bt;on<kt;++on){let oo=(dt+on*f-st)*Q+Fr,Fn=on*W+nn;for(let Vo=qt;Vo<Kt;++Vo){let Tl=(Dt+Vo*d-ot)*rt+oo,Nu=Vo*U+Fn;ae+=q[Tl+Ot]*D[Nu+Se]}}}}w[$e+Se]=ae}}}}}return e.makeTensorInfo(b.shape,b.dtype,b.values)}var BF={kernelName:Rp,backendName:"cpu",kernelFunc:v9};function C9(r){let{inputs:t,backend:e,attrs:n}=r,{dy:o,filter:s}=t,{pad:i,strides:a,inputShape:u}=n;nt([o],"conv3dBackpropInputV2");let l=x.computeStrides(o.shape),c=x.computeStrides(s.shape),p=S.computeConv3DInfo(u,s.shape,a,1,i),m=new pe(p.inShape,"float32"),f=m.values,[d,h,g,y]=m.strides,b=e.data.get(o.dataId).values,[w,v,k,E]=l,$=e.data.get(s.dataId).values,[D,R,P,W]=c,{batchSize:U,filterDepth:q,filterHeight:K,filterWidth:j,inChannels:Q,inDepth:rt,inHeight:X,inWidth:ot,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,Dt=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,$e=Math.max(0,Math.ceil(Ot/xt)),Se=Math.min(it,(q+Ot)/xt);for(let ae=0;ae<X;++ae){let je=ae-At,Fe=Math.max(0,Math.ceil(je/dt)),rn=Math.min(ft,(K+je)/dt);for(let ze=0;ze<ot;++ze){let Bo=ze-Dt,Fr=Math.max(0,Math.ceil(Bo/bt)),nn=Math.min(at,(j+Bo)/bt),on=0;for(let jr=$e;jr<Se;++jr){let oo=jr*xt-Ot;for(let Fn=Fe;Fn<rn;++Fn){let Vo=Fn*dt-je;for(let so=Fr;so<nn;++so){let Tl=so*bt-Bo,Nu=w*qt+v*jr+k*Fn+E*so,lp=D*(q-1-oo)+R*(K-1-Vo)+P*(j-1-Tl)+W*Kt;for(let gr=0;gr<st;++gr){let up=b[Nu+gr],cp=$[lp+gr];on+=up*cp}}}}f[d*qt+h*ce+g*ae+y*ze+Kt]=on}}}return e.makeTensorInfo(m.shape,m.dtype,m.values)}var VF={kernelName:Fp,backendName:"cpu",kernelFunc:C9};var I9=Et(os,r=>Math.cos(r)),GF={kernelName:os,backendName:"cpu",kernelFunc:I9};var S9=Et(ss,r=>Math.cosh(r)),WF={kernelName:ss,backendName:"cpu",kernelFunc:S9};function k9(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,k=x.computeStrides(o.shape),E=x.computeStrides(y.shape);for(let $=0;$<d;$++){let D=$*4,R=b[D],P=b[D+1],W=b[D+2],U=b[D+3],q=w[$];if(q>=c)continue;let K=h>1?(W-R)*(p-1)/(h-1):0,j=g>1?(U-P)*(m-1)/(g-1):0;for(let Q=0;Q<h;Q++){let rt=h>1?R*(p-1)+Q*K:.5*(R+W)*(p-1);if(rt<0||rt>p-1){for(let X=0;X<g;X++)for(let ot=0;ot<f;ot++){let st=ot+X*E[2]+Q*E[1]+$*E[0];y.values[st]=l}continue}if(u==="bilinear"){let X=Math.floor(rt),ot=Math.ceil(rt),st=rt-X;for(let it=0;it<g;it++){let ft=g>1?P*(m-1)+it*j:.5*(P+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]+$*E[0];y.values[kt]=l}continue}let at=Math.floor(ft),xt=Math.ceil(ft),dt=ft-at;for(let bt=0;bt<f;bt++){let kt=bt+at*k[2]+X*k[1]+q*k[0],At=v[kt];kt=bt+xt*k[2]+X*k[1]+q*k[0];let Dt=v[kt];kt=bt+at*k[2]+ot*k[1]+q*k[0];let qt=v[kt];kt=bt+xt*k[2]+ot*k[1]+q*k[0];let Kt=v[kt],ce=At+(Dt-At)*dt,Ot=qt+(Kt-qt)*dt;kt=bt+it*E[2]+Q*E[1]+$*E[0],y.values[kt]=ce+(Ot-ce)*st}}}else for(let X=0;X<g;++X){let ot=g>1?P*(m-1)+X*j:.5*(P+U)*(m-1);if(ot<0||ot>m-1){for(let ft=0;ft<f;ft++){let at=ft+X*E[2]+Q*E[1]+$*E[0];y.values[at]=l}continue}let st=Math.round(ot),it=Math.round(rt);for(let ft=0;ft<f;ft++){let at=ft+st*k[2]+it*k[1]+q*k[0],xt=ft+X*E[2]+Q*E[1]+$*E[0];y.values[xt]=v[at]}}}}return e.makeTensorInfo(y.shape,y.dtype,y.values)}var UF={kernelName:pa,backendName:"cpu",kernelFunc:k9};function N9(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{axis:s,exclusive:i,reverse:a}=n;nt(o,"cumprod");let u=S.getAxesPermutation([s],o.shape.length),l=o;u!=null&&(l=He({inputs:{x:o},backend:e,attrs:{perm:u}}));let c=S.getInnerMostAxes(1,o.shape.length)[0];if(c!==l.shape.length-1)throw new Error(`backend.cumprod in CPU expects an inner-most axis=${l.shape.length-1} but got axis=${c}`);let p=ar(l.dtype,"int32"),m=x.makeOnesTypedArray(x.sizeFromShape(l.shape),p),f=e.data.get(l.dataId).values,d=l.shape[l.shape.length-1],h=a?(y,b)=>y+d-b-1:(y,b)=>y+b;for(let y=0;y<f.length;y+=d)for(let b=0;b<d;b++){let w=h(y,b);if(b===0)m[w]=i?1:f[w];else{let v=h(y,b-1);m[w]=i?f[v]*m[v]:f[w]*m[v]}}let g=e.makeTensorInfo(l.shape,p,m);if(u!=null){let y=S.getUndoAxesPermutation(u),b=He({inputs:{x:g},backend:e,attrs:{perm:y}});return e.disposeIntermediateTensorInfo(g),e.disposeIntermediateTensorInfo(l),b}return g}var HF={kernelName:ca,backendName:"cpu",kernelFunc:N9};function T9(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{axis:s,exclusive:i,reverse:a}=n;nt(o,"cumsum");let u=S.getAxesPermutation([s],o.shape.length),l=o;u!=null&&(l=He({inputs:{x:o},backend:e,attrs:{perm:u}}));let c=S.getInnerMostAxes(1,o.shape.length)[0];if(c!==l.shape.length-1)throw new Error(`backend.cumsum in CPU expects an inner-most axis=${l.shape.length-1} but got axis=${c}`);let p=ar(l.dtype,"int32"),m=x.makeZerosTypedArray(x.sizeFromShape(l.shape),p),f=e.data.get(l.dataId).values,d=l.shape[l.shape.length-1],h=a?(y,b)=>y+d-b-1:(y,b)=>y+b;for(let y=0;y<f.length;y+=d)for(let b=0;b<d;b++){let w=h(y,b);if(b===0)m[w]=i?0:f[w];else{let v=h(y,b-1);m[w]=i?f[v]+m[v]:f[w]+m[v]}}let g=e.makeTensorInfo(l.shape,p,m);if(u!=null){let y=S.getUndoAxesPermutation(u),b=He({inputs:{x:g},backend:e,attrs:{perm:y}});return e.disposeIntermediateTensorInfo(g),e.disposeIntermediateTensorInfo(l),b}return g}var qF={kernelName:is,backendName:"cpu",kernelFunc:T9};function _9(r){let{inputs:t,backend:e,attrs:n}=r,{x:o,weights:s}=t,{size:i,binaryOutput:a}=n;if(o.shape.length===1){let u=e.data.get(o.dataId).values,l=e.data.get(s.dataId).values,c=nd(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=zb(u,l,i,a);return e.makeTensorInfo(c.shape,s.dtype,c.values)}throw new Error(`Error in 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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=Mo({inputs:{x:a},backend:e,attrs:{begin:[g,0],size:[1,s]}}),b=Mo({inputs:{x:u},backend:e,attrs:{begin:[g,0],size:[1,s]}}),w=Ir({inputs:{real:y,imag:b},backend:e}),{real:v,imag:k}=W9(w,t,e),E=S.mergeRealAndImagArrays(v,k);for(let $=0;$<s;$++){let D=S.getComplexWithIndex(E,$);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 W9(r,t,e){let 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r.FRAMEBUFFER_INCOMPLETE_DIMENSIONS:return"FRAMEBUFFER_INCOMPLETE_DIMENSIONS";case r.FRAMEBUFFER_UNSUPPORTED:return"FRAMEBUFFER_UNSUPPORTED";default:return`unknown error ${t}`}}function vl(r,t,e){let n=vt(r,()=>t());if(n==null)throw new Error(e);return n}function zM(r,t){let e=r.MAX_COMBINED_TEXTURE_IMAGE_UNITS-1,n=t+r.TEXTURE0;if(n<r.TEXTURE0||n>e){let o=`[gl.TEXTURE0, gl.TEXTURE${e}]`;throw new Error(`textureUnit must be in ${o}.`)}}function Cl(r,t=2){return x.sizeFromShape(r.slice(0,r.length-t))}function Il(r){if(r.length===0)throw Error("Cannot get rows and columns of an empty shape array.");return[r.length>1?r[r.length-2]:1,r[r.length-1]]}function Cg(r){let t=[1,1,1];return r.length===0||r.length===1&&r[0]===1||(t=[Cl(r),...Il(r)]),t}function UN(r,t=!1){let e=V().getNumber("WEBGL_MAX_TEXTURE_SIZE");t&&(e=e*2,r=r.map((o,s)=>s>=r.length-2?x.nearestLargerEven(r[s]):r[s]),r.length===1&&(r=[2,r[0]])),r.length!==2&&(r=x.squeezeShape(r).newShape);let n=x.sizeFromShape(r);if(r.length<=1&&n<=e)return[1,n];if(r.length===2&&r[0]<=e&&r[1]<=e)return r;if(r.length===3&&r[0]*r[1]<=e&&r[2]<=e)return[r[0]*r[1],r[2]];if(r.length===3&&r[0]<=e&&r[1]*r[2]<=e)return[r[0],r[1]*r[2]];if(r.length===4&&r[0]*r[1]*r[2]<=e&&r[3]<=e)return[r[0]*r[1]*r[2],r[3]];if(r.length===4&&r[0]<=e&&r[1]*r[2]*r[3]<=e)return[r[0],r[1]*r[2]*r[3]];if(t){let o=Cl(r),s=2,i=2;return r.length&&([s,i]=Il(r)),n=o*(s/2)*(i/2),x.sizeToSquarishShape(n).map(a=>a*2)}return x.sizeToSquarishShape(n)}function sw(r){return r%2===0}function bu(r,t){if(r=r.slice(-2),t=t.slice(-2),x.arraysEqual(r,t)||!r.length||!t.length||r[0]===0||r[1]===0||t[0]===0||t[1]===0)return!0;if(r.length!==t.length){let e=r.slice(-1)[0],n=t.slice(-1)[0];if(e===n||sw(e)&&sw(n)&&(r[0]===1||t[0]===1))return!0}return r[1]===t[1]&&sw(r[0])&&sw(t[0])}var iw,aw;function HN(r){if(iw==null){let t=Wn(r);iw=t.getParameter(t.MAX_TEXTURE_SIZE)}return iw}function RQ(){iw=null}function FQ(){aw=null}function qN(r){if(aw==null){let t=Wn(r);aw=t.getParameter(t.MAX_TEXTURE_IMAGE_UNITS)}return Math.min(16,aw)}function KN(r){if(r===0)return 0;let t,e=Wn(r);return Un(e,"EXT_disjoint_timer_query_webgl2")&&r===2?t=2:Un(e,"EXT_disjoint_timer_query")?t=1:t=0,t}function Un(r,t){return r.getExtension(t)!=null}function pw(r){try{if(Wn(r)!=null)return!0}catch(t){return console.log("Error when getting WebGL context: ",t),!1}return!1}function jN(r){if(r===0)return!1;let t=Wn(r);if(r===1){if(!Un(t,"OES_texture_float"))return!1}else if(!Un(t,"EXT_color_buffer_float"))return!1;return AN(t)}function XN(r){if(r===0)return!1;let t=Wn(r);if(r===1){if(!Un(t,"OES_texture_float")||!Un(t,"WEBGL_color_buffer_float"))return!1}else{if(Un(t,"EXT_color_buffer_float"))return AN(t);let n="EXT_color_buffer_half_float";if(Un(t,n)){let o=t.getExtension(n);return OQ(t,o)}return!1}return AN(t)}function AN(r){let t=bg(r),e=r.createTexture();r.bindTexture(r.TEXTURE_2D,e);let 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 OQ(r,t){let e=bg(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 YN(r){return r!==2?!1:Wn(r).fenceSync!=null}function di(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=V();Ft.registerFlag("HAS_WEBGL",()=>Ft.getNumber("WEBGL_VERSION")>0);Ft.registerFlag("WEBGL_VERSION",()=>pw(2)?2:pw(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",()=>HN(Ft.getNumber("WEBGL_VERSION")));Ft.registerFlag("WEBGL_MAX_TEXTURES_IN_SHADER",()=>qN(Ft.getNumber("WEBGL_VERSION")));Ft.registerFlag("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION",()=>{let 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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 qe(){let r,t,e,n,o,s,i,a,u,l;return V().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 hi(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 Zc(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}; ${a};`}).join("")}function MQ(r,t){let e=r.length,n=r.map(s=>`${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 BM(r,t,e="index"){let n=r.map((s,i)=>i),o=MQ(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 md(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 fd(){return`
int getFlatIndex(ivec3 coords) {
return coords.x * outShapeStrides[0] + coords.y * outShapeStrides[1] + coords.z;
}
`}var mw=`
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:VM}=S;function GM(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}=fw(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?`[${f.arrayIndex}]`:""};`)});let o=n.join(`
`),s=r.map(f=>PQ(f,t,e.packedInputs,e.enableShapeUniforms)).join(`
`),i=t.texShape,a=qe(),u=BQ(a),l,c,p=WQ(a);return t.isPacked?(l=LQ(t.logicalShape,i,e.enableShapeUniforms),c=GQ(a)):(l=zQ(t.logicalShape,i,e.enableShapeUniforms),c=VQ(a)),e.packedInputs&&(p+=KQ),[p,u,c,o,l,s,e.userCode].join(`
`)}function hd(r,t=!1){let e=r.shapeInfo.logicalShape;switch(e.length){case 0:return stt(r,t);case 1:return att(r,t);case 2:return utt(r,t);case 3:return ptt(r,t);case 4:return ftt(r,t);case 5:return dtt(r);case 6:return htt(r);default:throw new Error(`${e.length}-D input sampling is not yet supported`)}}function WM(r,t){switch(r.shapeInfo.logicalShape.length){case 0:return ott(r);case 1:return itt(r,t);case 2:return ltt(r,t);case 3:return ctt(r,t);default:return mtt(r,t)}}function PQ(r,t,e=!1,n){let o="";e?o+=WM(r,n):o+=hd(r,n);let s=r.shapeInfo.logicalShape,i=t.logicalShape;return s.length<=i.length&&(e?o+=gtt(r,t):o+=xtt(r,t)),o}function LQ(r,t,e){switch(r.length){case 0:return UM();case 1:return jQ(r,t,e);case 2:return rtt(r,t,e);case 3:return YQ(r,t,e);default:return JQ(r,t,e)}}function zQ(r,t,e){switch(r.length){case 0:return UM();case 1:return XQ(r,t,e);case 2:return ntt(r,t,e);case 3:return ZQ(r,t,e);case 4:return QQ(r,t,e);case 5:return ttt(r,t);case 6:return ett(r,t);default:throw new Error(`${r.length}-D output sampling is not yet supported`)}}function BQ(r){return`
float sampleTexture(sampler2D textureSampler, vec2 uv) {
return ${r.texture2D}(textureSampler, uv).r;
}
`}function VQ(r){return`
void setOutput(float val) {
${r.output} = vec4(val, 0, 0, 0);
}
`}function GQ(r){return`
void setOutput(vec4 val) {
${r.output} = val;
}
`}function WQ(r){return`${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);
}
${UQ}
${HQ}
${qQ}
`}var UQ=`
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);
}
`,HQ=`
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);
}
`,qQ=`
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);
}
`,KQ=`
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 UM(){return`
int getOutputCoords() {
return 0;
}
`}function jQ(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 XQ(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 * ${t[1]} + resTexRC.y;
}
`}function YQ(r,t,e){if(e)return`
ivec3 getOutputCoords() {
ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));
int texelsInLogicalRow = int(ceil(float(outShape[2]) / 2.0));
int texelsInBatch = texelsInLogicalRow * int(ceil(float(outShape[1]) / 2.0));
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(packedTexShape[0], packedTexShape[1]));
int index = resTexRC.x * packedTexShape[1] + resTexRC.y;
int b = index / texelsInBatch;
index -= b * texelsInBatch;
int r = 2 * (index / texelsInLogicalRow);
int c = imod(index, texelsInLogicalRow) * 2;
return ivec3(b, r, c);
}
`;let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)],o=Math.ceil(r[2]/2),s=o*Math.ceil(r[1]/2);return`
ivec3 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${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 ZQ(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;
${Zc(["r","c","d"],r)}
return ivec3(r, c, d);
}
`;let n=hi(["r","c","d"],r);return`
ivec3 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${t[0]}, ${t[1]}));
int index = resTexRC.x * ${t[1]} + resTexRC.y;
${n}
return ivec3(r, c, d);
}
`}function JQ(r,t,e){if(e)return`
ivec4 getOutputCoords() {
ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(packedTexShape[0], packedTexShape[1]));
int index = resTexRC.x * packedTexShape[1] + resTexRC.y;
int texelsInLogicalRow = int(ceil(float(outShape[3]) / 2.0));
int texelsInBatch = texelsInLogicalRow * int(ceil(float(outShape[2]) / 2.0));
int texelsInBatchN = texelsInBatch * outShape[1];
int b2 = index / texelsInBatchN;
index -= b2 * texelsInBatchN;
int b = index / texelsInBatch;
index -= b * texelsInBatch;
int r = 2 * (index / texelsInLogicalRow);
int c = imod(index, texelsInLogicalRow) * 2;
return ivec4(b2, b, r, c);
}
`;let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)],o=Math.ceil(r[r.length-1]/2),s=o*Math.ceil(r[r.length-2]/2),i=s,a="",u="b, r, c";for(let l=2;l<r.length-1;l++)i*=r[r.length-l-1],a=`
int b${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 QQ(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;
${Zc(["r","c","d","d2"],r)}
return ivec4(r, c, d, d2);
}
`;let n=hi(["r","c","d","d2"],r);return`
ivec4 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${t[0]}, ${t[1]}));
int index = resTexRC.x * ${t[1]} + resTexRC.y;
${n}
return ivec4(r, c, d, d2);
}
`}function ttt(r,t){let e=hi(["r","c","d","d2","d3"],r);return`
ivec5 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx * vec2(${t[0]},
${t[1]}));
int index = resTexRC.x * ${t[1]} + resTexRC.y;
${e}
ivec5 outShape = ivec5(r, c, d, d2, d3);
return outShape;
}
`}function ett(r,t){let e=hi(["r","c","d","d2","d3","d4"],r);return`
ivec6 getOutputCoords() {
ivec2 resTexRC = ivec2(resultUV.yx *
vec2(${t[0]}, ${t[1]}));
int index = resTexRC.x * ${t[1]} + resTexRC.y;
${e}
ivec6 result = ivec6(r, c, d, d2, d3, d4);
return result;
}
`}function rtt(r,t,e){let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)];if(x.arraysEqual(r,t))return e?`
ivec2 getOutputCoords() {
ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));
return 2 * ivec2(resultUV.yx * vec2(packedTexShape[0], packedTexShape[1]));
}
`:`
ivec2 getOutputCoords() {
return 2 * ivec2(resultUV.yx * vec2(${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, ${o}) * 2;
return ivec2(r, c);
}
`}function ntt(r,t,e){return x.arraysEqual(r,t)?e?`
ivec2 getOutputCoords() {
return ivec2(resultUV.yx * vec2(outTexShape[0], outTexShape[1]));
}
`:`
ivec2 getOutputCoords() {
return ivec2(resultUV.yx * vec2(${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 * ${r[1]};
return ivec2(r, c);
}
`}function Jc(r){return`offset${r}`}function ott(r){let t=r.name,e="get"+t.charAt(0).toUpperCase()+t.slice(1),n=qe();return`
vec4 ${e}() {
return ${n.texture2D}(${t}, halfCR);
}
`}function stt(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=Jc(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 itt(r,t){let e=r.name,n="get"+e.charAt(0).toUpperCase()+e.slice(1),o=r.shapeInfo.texShape,s=qe();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 att(r,t){let e=r.name,n="get"+e.charAt(0).toUpperCase()+e.slice(1);if(r.shapeInfo.isUniform)return`
float ${n}(int index) {
${gd(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=Jc(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 ltt(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=qe();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 utt(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=xd(r,u),f=["row","col"];return`
${hd(m,t)}
float ${o}(int row, int col) {
return ${o}(${yd(f,a)});
}
`}if(r.shapeInfo.isUniform)return`
float ${o}(int row, int col) {
int index = round(dot(vec2(row, col), vec2(${e[1]}, 1)));
${gd(r)}
}
`;let l=s[0],c=s[1],p=Jc(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 ctt(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=xd(r,m),h=["b","row","col"];return`
${WM(d,t)}
vec4 ${o}(int b, int row, int col) {
return ${o}(${yd(h,f)});
}
`}let a=qe();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 ptt(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=xd(r,l),g=["row","col","depth"];return`
${hd(h,t)}
float ${o}(int row, int col, int depth) {
return ${o}(${yd(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)));
${gd(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=Jc(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 mtt(r,t){let e=r.name,n="get"+e.charAt(0).toUpperCase()+e.slice(1),o=qe();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 ftt(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=xd(r,u),w=["row","col","depth","depth2"];return`
${hd(b,t)}
float ${o}(int row, int col, int depth, int depth2) {
return ${o}(${yd(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)));
${gd(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=Jc(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 dtt(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=xd(r,u),g=["row","col","depth","depth2","depth3"];return`
${hd(h)}
float ${n}(int row, int col, int depth, int depth2, int depth3) {
return ${n}(${yd(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;
${gd(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=Jc(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 htt(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=xd(r,o),y=["row","col","depth","depth2","depth3","depth4"];return`
${hd(g)}
float ${n}(int row, int col, int depth,
int depth2, int depth3, int depth4) {
return ${n}(${yd(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)));
${gd(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=Jc(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 gd(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 ${t}[i];
}
}
`}function gtt(r,t){let e=r.name,n=e.charAt(0).toUpperCase()+e.slice(1),o="get"+n+"AtOutCoords",s=r.shapeInfo.logicalShape.length,i=t.logicalShape.length,a=VM(r.shapeInfo.logicalShape,t.logicalShape),u=Gt(i),l=i-s,c,p=["x","y","z","w","u","v"];s===0?c="":i<2&&a.length>=1?c="coords = 0;":c=a.map(b=>`coords.${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 xtt(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=Gt(u),c=VM(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 Gt(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 ${r} is not yet supported`)}function fw(r,t,e){let{newShape:n,keptDims:o}=x.squeezeShape(t),s=t.length,i=r&&s===3&&t[0]===1,a=i?t.slice(1):n,u=!r&&s>1&&!x.arraysEqual(t,e)&&n.length<s||i;return{useSqueezeShape:u,uniformShape:u?a:t,keptDims:o}}function xd(r,t){let e=JSON.parse(JSON.stringify(r));return e.shapeInfo.logicalShape=t,e}function yd(r,t){return t.map(e=>r[e]).join(", ")}function qM(r,t,e,n){let o=e.map((c,p)=>{let m={logicalShape:c.shape,texShape:c.isUniform?null:c.texData.texShape,isUniform:c.isUniform,isPacked:c.isUniform?!1:c.texData.isPacked,flatOffset:null};return c.texData!=null&&c.texData.slice!=null&&c.texData.slice.flatOffset>0&&(m.flatOffset=c.texData.slice.flatOffset),{name:t.variableNames[p],shapeInfo:m}}),s=o.map(c=>c.shapeInfo),i={logicalShape:n.shape,texShape:n.texData.texShape,isUniform:!1,isPacked:n.texData.isPacked,flatOffset:null},a=GM(o,i,t),u=RN(r.gl,a),l=r.createProgram(u);return V().get("ENGINE_COMPILE_ONLY")?{program:t,fragmentShader:u,source:a,webGLProgram:l,inShapeInfos:s,outShapeInfo:i,uniformLocations:null,customUniformLocations:null,infLoc:null,nanLoc:null,inShapesLocations:null,inTexShapesLocations:null,outShapeLocation:null,outShapeStridesLocation:null,outTexShapeLocation:null}:Object.assign({program:t,fragmentShader:u,source:a,webGLProgram:l,inShapeInfos:s,outShapeInfo:i},ZN(r,t,l))}function ZN(r,t,e){let n={},o={},s={},i=[],a,u,l,c=null,p=null;p=r.getUniformLocation(e,"NAN",!1),V().getNumber("WEBGL_VERSION")===1&&(c=r.getUniformLocation(e,"INFINITY",!1));let m=!1;for(let f=0;f<t.variableNames.length;f++){let d=t.variableNames[f];n[d]=r.getUniformLocation(e,d,m),n[`offset${d}`]=r.getUniformLocation(e,`offset${d}`,m),t.enableShapeUniforms&&(o[`${d}Shape`]=r.getUniformLocation(e,`${d}Shape`,m),s[`${d}TexShape`]=r.getUniformLocation(e,`${d}TexShape`,m))}return t.enableShapeUniforms&&(a=r.getUniformLocation(e,"outShape",m),l=r.getUniformLocation(e,"outShapeStrides",m),u=r.getUniformLocation(e,"outTexShape",m)),t.customUniforms&&t.customUniforms.forEach((f,d)=>{i[d]=r.getUniformLocation(e,f.name,m)}),{uniformLocations:n,customUniformLocations:i,infLoc:c,nanLoc:p,inShapesLocations:o,inTexShapesLocations:s,outShapeLocation:a,outShapeStridesLocation:l,outTexShapeLocation:u}}function HM(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 ${u} must match`)})}function KM(r,t,e,n,o){t.program.enableShapeUniforms||(HM(t.inShapeInfos,e),HM([t.outShapeInfo],[n]));let s=n.texData.texture,i=n.texData.texShape;n.texData.isPacked?r.setOutputPackedMatrixTexture(s.texture,i[0],i[1]):r.setOutputMatrixTexture(s.texture,i[0],i[1]),r.setProgram(t.webGLProgram),V().getNumber("WEBGL_VERSION")===1&&t.infLoc!==null&&r.gl.uniform1f(t.infLoc,1/0),t.nanLoc!==null&&r.gl.uniform1f(t.nanLoc,NaN),e.forEach((u,l)=>{let c=t.program.variableNames[l],p=t.uniformLocations[c],m=t.uniformLocations[`offset${c}`],f=t.inShapesLocations[`${c}Shape`],d=t.inTexShapesLocations[`${c}TexShape`];if(f){let{uniformShape:h}=fw(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 ${u.type} is not supported yet.`)}),r.executeProgram()}function jM(r,t,e){let n="";t.concat(e).forEach(i=>{let a=i.texData!=null&&i.texData.slice!=null&&i.texData.slice.flatOffset>0;if(r.enableShapeUniforms&&!i.isUniform){let u=i.texData.texShape,{useSqueezeShape:l,uniformShape:c,keptDims:p}=fw(r.packedInputs,i.shape,u),m="",f="",d="";if(c.length===1&&r.packedInputs){let k=[Math.ceil(u[0]/2),Math.ceil(u[1]/2)];m=`${k[0]>1}_${k[1]>1}`}else if(c.length===2&&!r.packedInputs)f=`${c[0]>1}_${c[1]>1}`;else if(c.length>2&&!r.packedInputs){let k=x.computeStrides(c);d=`${k[0]===u[1]}_${k[k.length-1]===u[1]}`}let h=i.shape.length,g=c.length===2&&x.arraysEqual(i.shape,u),y=x.sizeFromShape(i.shape)===1,b=S.getBroadcastDims(i.shape,e.shape),w=!r.packedInputs&&h===e.shape.length&&x.arraysEqual(u,e.texData.texShape),v=r.packedInputs||c.length>2?"":`${u[0]>1}_${u[1]>1}`;n+=`${h}_${w}_${l?p:""}_${c.length}_${y}_${b}_${g}_${m}_${f}_${d}_${v}_${a}`}else{let u=i.isUniform?"uniform":i.texData.texShape;n+=`${i.shape}_${u}_${a}`}});let o=r.userCode,s=r.constructor.name;return s+="_"+n+"_"+o+`${V().getNumber("WEBGL_VERSION")}`,s}function De(r){return V().getBool("WEBGL_USE_SHAPES_UNIFORMS")&&r<=4}var dw=class{constructor(t){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outPackingScheme=yu.DENSE,this.customUniforms=[{name:"texShape",type:"ivec2"}];let e=qe();this.outputShape=t,this.enableShapeUniforms=De(this.outputShape.length),this.userCode=`
ivec3 outCoordsFromFlatIndex(int index) {
${this.enableShapeUniforms?Zc(["r","c","d"],t):hi(["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 hw=class{constructor(t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outPackingScheme=yu.DENSE,this.customUniforms=[{name:"texShape",type:"ivec2"}];let e=qe();this.outputShape=t,this.enableShapeUniforms=De(this.outputShape.length),this.userCode=`
ivec3 outCoordsFromFlatIndex(int index) {
${this.enableShapeUniforms?Zc(["r","c","d"],t):hi(["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 gw=class{constructor(t){this.variableNames=["A"],this.outTexUsage=Kr.DOWNLOAD;let e=qe();this.outputShape=t,this.userCode=`
${mw}
void main() {
float x = getAAtOutCoords();
${e.output} = encode_float(x);
}
`}};var xw=class{constructor(t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outTexUsage=Kr.DOWNLOAD;let e=qe();this.outputShape=t,this.userCode=`
${mw}
void main() {
ivec3 coords = getOutputCoords();
float x = getChannel(getAAtOutCoords(), vec2(coords.y, coords.z));
${e.output} = encode_float(x);
}
`}};var yw=class{constructor(t,e=!1){this.variableNames=["A"],this.customUniforms=[{name:"texShape",type:"ivec2"}];let n=qe();this.outputShape=t,this.enableShapeUniforms=De(this.outputShape.length);let o="result";e&&(o="floor(result * 255. + 0.5)"),this.userCode=`
${this.enableShapeUniforms?fd():md(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 bw=class{constructor(t,e=!1){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.customUniforms=[{name:"texShape",type:"ivec2"}];let n=qe();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?fd():md(t)}
void main() {
ivec3 coords = getOutputCoords();
vec4 result = vec4(0.);
int flatIndex, r, c, offset;
ivec3 localCoords;
vec2 uv;
vec4 values;
${o}
${n.output} = ${s};
}
`}};var dT={};Yt(dT,{bindVertexProgramAttributeStreams:()=>iT,createBufferFromOutputTexture:()=>uT,createFloat16MatrixTexture:()=>rT,createFloat16PackedMatrixTexture:()=>sT,createFloat32MatrixTexture:()=>eT,createIndexBuffer:()=>tT,createPackedMatrixTexture:()=>oT,createUnsignedBytesMatrixTexture:()=>nT,createVertexBuffer:()=>QN,createVertexShader:()=>JN,downloadByteEncodedFloatMatrixFromOutputTexture:()=>pT,downloadFloat32MatrixFromBuffer:()=>cT,downloadMatrixFromPackedOutputTexture:()=>fT,downloadPackedMatrixFromBuffer:()=>mT,getInternalFormatForFloat16MatrixTexture:()=>vw,getInternalFormatForFloat16PackedMatrixTexture:()=>Sw,getInternalFormatForFloat32MatrixTexture:()=>ww,getInternalFormatForPackedMatrixTexture:()=>Iw,getInternalFormatForUnsignedBytesMatrixTexture:()=>Cw,uploadDenseMatrixToTexture:()=>aT,uploadPixelDataToTexture:()=>lT});function JN(r){let t=qe(),e=`${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 DN(r,e)}function QN(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 MN(r,t)}function tT(r){let t=new Uint16Array([0,1,2,2,1,3]);return PN(r,t)}function Ig(r,t,e,n,o,s){zN(t,e);let i=LN(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)),V().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 ww(r){return r.internalFormatFloat}function eT(r,t,e,n){let[o,s]=Yc(t,e);return Ig(r,o,s,ww(n),n.textureFormatFloat,r.FLOAT)}function vw(r){return r.internalFormatHalfFloat}function rT(r,t,e,n){let[o,s]=Yc(t,e);return Ig(r,o,s,vw(n),n.textureFormatFloat,n.textureTypeHalfFloat)}function Cw(r){return r.downloadTextureFormat}function nT(r,t,e,n){let[o,s]=Yc(t,e);return Ig(r,o,s,Cw(n),r.RGBA,r.UNSIGNED_BYTE)}function Iw(r){return r.internalFormatPackedFloat}function oT(r,t,e,n){let[o,s]=Ji(t,e);return Ig(r,o,s,Iw(n),r.RGBA,r.FLOAT)}function Sw(r){return r.internalFormatPackedHalfFloat}function sT(r,t,e,n){let[o,s]=Ji(t,e);return Ig(r,o,s,Sw(n),r.RGBA,n.textureTypeHalfFloat)}function iT(r,t,e){return vt(r,()=>r.bindBuffer(r.ARRAY_BUFFER,e)),uw(r,t,"clipSpacePos",e,3,20,0)&&uw(r,t,"uv",e,2,20,12)}function aT(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),V().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 lT(r,t,e){vt(r,()=>r.bindTexture(r.TEXTURE_2D,t)),e.data instanceof Uint8Array?V().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)):V().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 uT(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 cT(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 pT(r,t,e,n){let[o,s]=Yc(t,e),i=4,a=new Uint8Array(FM(t*e,i));return vt(r,()=>r.readPixels(0,0,o,s,n.downloadTextureFormat,r.UNSIGNED_BYTE,a)),new Float32Array(a.buffer)}function mT(r,t,e,n,o,s,i,a){let u=r,l=new Float32Array(OM(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 fT(r,t,e){let n=new Float32Array(t*e*4);return vt(r,()=>r.readPixels(0,0,e,t,r.RGBA,r.FLOAT,n)),n}var Qc=class{constructor(t){this.outputTexture=null,this.program=null,this.disposed=!1,this.vertexAttrsAreBound=!1,this.itemsToPoll=[];let e=V().getNumber("WEBGL_VERSION");t!=null?(this.gl=t,_N(e,t)):this.gl=Wn(e);let n="WEBGL_color_buffer_float",o="EXT_color_buffer_half_float";if(this.parallelCompilationExtension=this.gl.getExtension("KHR_parallel_shader_compile"),V().getNumber("WEBGL_VERSION")===1){let s="OES_texture_float",i="OES_texture_half_float";if(this.textureFloatExtension=ud(this.gl,s),Un(this.gl,i))this.textureHalfFloatExtension=ud(this.gl,i);else if(V().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),Un(this.gl,o))this.colorBufferHalfFloatExtension=ud(this.gl,o);else if(V().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",Un(this.gl,n))this.colorBufferFloatExtension=this.gl.getExtension(n);else if(Un(this.gl,o))this.colorBufferHalfFloatExtension=this.gl.getExtension(o);else throw new Error("GL context does not support color renderable floats");this.vertexBuffer=QN(this.gl),this.indexBuffer=tT(this.gl),this.framebuffer=BN(this.gl),this.textureConfig=bg(this.gl,this.textureHalfFloatExtension)}get debug(){return V().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(),eT(this.gl,t,e,this.textureConfig)}createFloat16MatrixTexture(t,e){return this.throwIfDisposed(),rT(this.gl,t,e,this.textureConfig)}createUnsignedBytesMatrixTexture(t,e){return this.throwIfDisposed(),nT(this.gl,t,e,this.textureConfig)}uploadPixelDataToTexture(t,e){this.throwIfDisposed(),lT(this.gl,t,e)}uploadDenseMatrixToTexture(t,e,n,o){this.throwIfDisposed(),aT(this.gl,t,e,n,o,this.textureConfig)}createFloat16PackedMatrixTexture(t,e){return this.throwIfDisposed(),sT(this.gl,t,e,this.textureConfig)}createPackedMatrixTexture(t,e){return this.throwIfDisposed(),oT(this.gl,t,e,this.textureConfig)}deleteMatrixTexture(t){this.throwIfDisposed(),this.outputTexture===t&&(cw(this.gl,this.framebuffer),this.outputTexture=null),vt(this.gl,()=>this.gl.deleteTexture(t))}downloadByteEncodedFloatMatrixFromOutputTexture(t,e,n){return this.downloadMatrixDriver(t,()=>pT(this.gl,e,n,this.textureConfig))}downloadPackedMatrixFromBuffer(t,e,n,o,s,i){return mT(this.gl,t,e,n,o,s,i,this.textureConfig)}downloadFloat32MatrixFromBuffer(t,e){return cT(this.gl,t,e)}createBufferFromTexture(t,e,n){this.bindTextureToFrameBuffer(t);let o=uT(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(V().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 V().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")>0?(e=this.beginQuery(),this.endQuery(),n=()=>this.isQueryAvailable(e,V().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))):n=()=>!0;return{query:e,isFencePassed:n}}downloadMatrixFromPackedTexture(t,e,n){return this.downloadMatrixDriver(t,()=>fT(this.gl,e,n))}createProgram(t){this.throwIfDisposed();let e=this.gl;this.vertexShader==null&&(this.vertexShader=JN(e));let n=FN(e);return vt(e,()=>e.attachShader(n,this.vertexShader)),vt(e,()=>e.attachShader(n,t)),ON(e,n),this.debug&&wg(e,n),this.vertexAttrsAreBound||(this.setProgram(n),this.vertexAttrsAreBound=iT(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&&wg(this.gl,this.program),vt(this.gl,()=>this.gl.useProgram(t))}getUniformLocation(t,e,n=!0){return this.throwIfDisposed(),n?VN(this.gl,t,e):GN(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(),WN(this.gl,t,e,n)}setOutputMatrixTexture(t,e,n){this.setOutputMatrixTextureDriver(t,n,e)}setOutputPackedMatrixTexture(t,e,n){this.throwIfDisposed();let[o,s]=Ji(e,n);this.setOutputMatrixTextureDriver(t,o,s)}setOutputMatrixWriteRegion(t,e,n,o){this.setOutputMatrixWriteRegionDriver(n,t,o,e)}setOutputPackedMatrixWriteRegion(t,e,n,o){throw new Error("setOutputPackedMatrixWriteRegion not implemented.")}debugValidate(){this.program!=null&&wg(this.gl,this.program),cd(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=ud(this.gl,V().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(V().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(V().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,V().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))),this.getQueryTime(t,V().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=wtt(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(),vg(this.gl,t,this.framebuffer),this.debug&&cd(this.gl)}unbindTextureToFrameBuffer(){this.outputTexture!=null?(vg(this.gl,this.outputTexture,this.framebuffer),this.debug&&cd(this.gl)):cw(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;vg(o,t,this.framebuffer),this.debug&&cd(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 wtt(r){let t=0;for(;t<r.length&&r[t]();++t);return t-1}var{addImpl:XM,bincountImpl:kw,bincountReduceImpl:YM,ceilImpl:ZM,concatImpl:JM,equalImpl:QM,expImpl:tP,expm1Impl:eP,floorImpl:rP,gatherNdImpl:nP,gatherV2Impl:oP,greaterImpl:sP,greaterEqualImpl:iP,lessImpl:aP,lessEqualImpl:lP,linSpaceImpl:uP,logImpl:cP,maxImpl:pP,maximumImpl:mP,minimumImpl:fP,multiplyImpl:dP,negImpl:hP,notEqualImpl:gP,prodImpl:xP,rangeImpl:yP,rsqrtImpl:bP,sigmoidImpl:wP,simpleAbsImpl:Nw,sliceImpl:vP,sparseFillEmptyRowsImpl:CP,sparseReshapeImpl:IP,sparseSegmentReductionImpl:Tw,sqrtImpl:SP,stridedSliceImpl:kP,stringNGramsImpl:NP,stringSplitImpl:TP,stringToHashBucketFastImpl:_P,subImpl:EP,tileImpl:AP,topKImpl:$P,transposeImpl:tp,uniqueImpl:DP}=Qb;function hT(r,t){return["x","y","z","w","u","v"].slice(0,t).map(e=>`${r}.${e}`)}function nr(r,t){return t===1?[r]:hT(r,t)}function RP(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 _w=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=nr("rc",this.rank),n=Gt(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 bd=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=`
${vtt(e,this.enableShapeUniforms)}
${this.enableShapeUniforms?fd():md(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 vtt(r,t){return`
ivec3 inputCoordsFromReshapedOutCoords(int index) {
${t?BM(["r","c","d"],"inputShape"):hi(["r","c","d"],r)}
return ivec3(r, c, d);
}
`}var Ew=class{constructor(t){this.gpgpu=t,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0,this.freeTextures={},this.logEnabled=!1,this.usedTextures={}}acquireTexture(t,e,n){let o=OP(e,n),s=MP(t,o,n);s in this.freeTextures||(this.freeTextures[s]=[]),s in this.usedTextures||(this.usedTextures[s]=[]);let i=FP(t,o,this.gpgpu.gl,this.gpgpu.textureConfig,n);if(this.freeTextures[s].length>0){this.numFreeTextures--,this.numUsedTextures++,this._numBytesFree-=i,this.log();let u=this.freeTextures[s].shift();return this.usedTextures[s].push(u),u}let a;return o===Rr.PACKED_2X2_FLOAT32?a=this.gpgpu.createPackedMatrixTexture(t[0],t[1]):o===Rr.PACKED_2X2_FLOAT16?a=this.gpgpu.createFloat16PackedMatrixTexture(t[0],t[1]):o===Rr.UNPACKED_FLOAT32?a=this.gpgpu.createFloat32MatrixTexture(t[0],t[1]):o===Rr.UNPACKED_FLOAT16?a=this.gpgpu.createFloat16MatrixTexture(t[0],t[1]):o===Rr.PACKED_4X1_UNSIGNED_BYTE&&(a=this.gpgpu.createUnsignedBytesMatrixTexture(t[0],t[1])),this.usedTextures[s].push(a),this.numUsedTextures++,this._numBytesAllocated+=i,this.log(),a}releaseTexture(t,e,n,o){if(this.freeTextures==null)return;let s=OP(n,o),i=MP(e,s,o);i in this.freeTextures||(this.freeTextures[i]=[]);let a=FP(e,s,this.gpgpu.gl,this.gpgpu.textureConfig,o),u=V().get("WEBGL_DELETE_TEXTURE_THRESHOLD");u!==-1&&this._numBytesAllocated>u?(this.gpgpu.deleteMatrixTexture(t.texture),this._numBytesAllocated-=a):(this.freeTextures[i].push(t),this.numFreeTextures++,this._numBytesFree+=a),this.numUsedTextures--;let l=this.usedTextures[i],c=l.indexOf(t);if(c<0)throw new Error("Cannot release a texture that was never provided by this texture manager");l.splice(c,1),this.log()}log(){if(!this.logEnabled)return;let t=this.numFreeTextures+this.numUsedTextures;console.log("Free/Used",`${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 Ctt(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 FP(r,t,e,n,o){let s=Itt(t,n),i;if(o){let[u,l]=Ji(r[0],r[1]);i=u*l}else{let[u,l]=Yc(r[0],r[1]);i=u*l}let a=Ctt(e,s);return i*a}function Itt(r,t){switch(r){case Rr.PACKED_2X2_FLOAT32:return Iw(t);case Rr.PACKED_2X2_FLOAT16:return Sw(t);case Rr.UNPACKED_FLOAT32:return ww(t);case Rr.UNPACKED_FLOAT16:return vw(t);case Rr.PACKED_4X1_UNSIGNED_BYTE:return Cw(t);default:throw new Error(`Unknown physical texture type ${r}`)}}function Stt(r){return V().getBool("WEBGL_RENDER_FLOAT32_ENABLED")?r?Rr.PACKED_2X2_FLOAT32:Rr.UNPACKED_FLOAT32:r?Rr.PACKED_2X2_FLOAT16:Rr.UNPACKED_FLOAT16}function OP(r,t){if(r===Kr.UPLOAD)return Rr.PACKED_2X2_FLOAT32;if(r===Kr.RENDER||r==null)return Stt(t);if(r===Kr.DOWNLOAD||r===Kr.PIXELS)return Rr.PACKED_4X1_UNSIGNED_BYTE;throw new Error(`Unknown logical texture type ${r}`)}function MP(r,t,e){return`${r[0]}_${r[1]}_${t}_${e}`}var en=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);
}
`}},hr="if (isnan(x)) return x;",PP="return x;",gT="return abs(x);";var LP="return (x >= 0.0) ? x : (exp(x) - 1.0);",zP=hr+`
return (x < 0.0) ? 0.0 : x;
`,BP=hr+`
return (x < 0.0) ? 0.0 : min(6.0, x);
`,ep="return x;",VP="return 1.0 / (1.0 + exp(-1.0 * x));";var WP="return x;",UP=`
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;
`,HP=`
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;
`,qP=`
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;
`,KP="return 1.0 / (1.0 + exp(-1.0 * x));",eo=class{constructor(t,e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t,this.enableShapeUniforms=De(this.outputShape.length),this.userCode=`
vec4 unaryOperation(vec4 x) {
${e}
}
void main() {
vec4 x = getAAtOutCoords();
vec4 y = unaryOperation(x);
setOutput(y);
}
`}};var Aw=class{constructor(t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outputShape=t,this.enableShapeUniforms=De(this.outputShape.length);let e=t.length,n=nr("rc",e),o=Gt(e),s=RP(e,n),i=n.slice(-2),a=e<=1?"rc":`vec2(${i.join(",")})`;this.userCode=`
void main() {
${o} rc = getOutputCoords();
vec4 packedInput = getA(${s});
setOutput(getChannel(packedInput, ${a}));
}
`}};var Ntt=Gr.whereImpl,Ttt=1e-7,_tt=1e-4,$w={};function Ett(r){return r in $w||($w[r]={}),$w[r]}var Att=V().getNumber("CPU_HANDOFF_SIZE_THRESHOLD"),$tt=600;function Dtt(){return V().global.screen==null?1024:V().global.screen.height*V().global.screen.width*window.devicePixelRatio*$tt/1024/1024}var wu=class extends jo{constructor(t){if(super(),this.pendingRead=new WeakMap,this.pendingDisposal=new WeakSet,this.dataRefCount=new WeakMap,this.numBytesInGPU=0,this.uploadWaitMs=0,this.downloadWaitMs=0,this.lastGlFlushTime=0,this.warnedAboutMemory=!1,this.pendingDeletes=0,this.disposed=!1,!V().getBool("HAS_WEBGL"))throw new Error("WebGL is not supported on this device");let e;if(t!=null){if(t instanceof Qc)e=t;else{let n=Wn(V().getNumber("WEBGL_VERSION"),t);e=new Qc(n)}this.binaryCache={},this.gpgpuCreatedLocally=!1}else{let n=Wn(V().getNumber("WEBGL_VERSION"));e=new Qc(n),this.binaryCache=Ett(V().getNumber("WEBGL_VERSION")),this.gpgpuCreatedLocally=!0}this.gpgpu=e,this.canvas=this.gpgpu.gl.canvas,this.textureManager=new Ew(this.gpgpu),this.numMBBeforeWarning=Dtt(),this.texData=new Qi(this,go())}nextDataId(){return wu.nextDataId++}numDataIds(){return this.texData.numDataIds()-this.pendingDeletes}write(t,e,n){if((V().getBool("WEBGL_CHECK_NUMERICAL_PROBLEMS")||V().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:Kr.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(V().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:Kr.UPLOAD,refCount:s})}disposeIntermediateTensorInfo(t){this.disposeData(t.dataId)}readSync(t){let e=this.texData.get(t),{values:n,dtype:o,complexTensorInfos:s,slice:i,shape:a,isPacked:u}=e;if(i!=null){let m;u?m=new eo(a,ep):m=new en(a,ep);let f=this.runWebGLProgram(m,[{dataId:t,shape:a,dtype:o}],o),d=this.readSync(f.dataId);return this.disposeIntermediateTensorInfo(f),d}if(n!=null)return this.convertAndCacheOnCPU(t);if(o==="string")return n;let l=this.activeTimers!=null,c;l&&(c=x.now());let p;if(o==="complex64"){let m=this.readSync(s.real.dataId),f=this.readSync(s.imag.dataId);p=S.mergeRealAndImagArrays(m,f)}else p=this.getValuesFromTexture(t);return l&&(this.downloadWaitMs+=x.now()-c),this.convertAndCacheOnCPU(t,p)}async read(t){if(this.pendingRead.has(t)){let d=this.pendingRead.get(t);return new Promise(h=>d.push(h))}let e=this.texData.get(t),{values:n,shape:o,slice:s,dtype:i,complexTensorInfos:a,isPacked:u}=e;if(s!=null){let d;u?d=new eo(o,ep):d=new en(o,ep);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(V().getBool("DEBUG")&&!V().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")&&V().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"&&V().get("WEBGL_BUFFER_SUPPORTED")){c=this.decode(t);let d=this.texData.get(c.dataId);l=this.gpgpu.createBufferFromTexture(d.texture.texture,...yg(o))}this.pendingRead.set(t,[]),i!=="complex64"&&await this.gpgpu.createAndWaitForFence();let p;if(i==="complex64"){let d=await Promise.all([this.read(a.real.dataId),this.read(a.imag.dataId)]),h=d[0],g=d[1];p=S.mergeRealAndImagArrays(h,g)}else if(l==null)p=this.getValuesFromTexture(t);else{let d=x.sizeFromShape(o);p=this.gpgpu.downloadFloat32MatrixFromBuffer(l,d)}if(c!=null&&this.disposeIntermediateTensorInfo(c),l!=null){let d=this.gpgpu.gl;vt(d,()=>d.deleteBuffer(l))}let m=this.convertAndCacheOnCPU(t,p),f=this.pendingRead.get(t);return this.pendingRead.delete(t),f.forEach(d=>d(m)),this.pendingDisposal.has(t)&&(this.pendingDisposal.delete(t),this.disposeData(t)&&go().removeDataId(t,this),this.pendingDeletes--),m}readToGPU(t,e={}){let n=this.texData.get(t),{values:o,shape:s,slice:i,dtype:a,isPacked:u,texture:l}=n;if(a==="complex64")throw new Error("Does not support reading texture for complex64 dtype.");if(i!=null){let f;u?f=new eo(s,ep):f=new en(s,ep);let d=this.runWebGLProgram(f,[{dataId:t,shape:s,dtype:a}],a),h=this.readToGPU(d,e);return this.disposeIntermediateTensorInfo(d),h}if(l==null)throw o!=null?new Error("Data is not on GPU but on CPU."):new Error("There is no data on GPU or CPU.");let c=this.decode(t,e.customTexShape),p=go().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(!$N(n))throw V().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 ${n} cannot be represented on this device.`)}}getValuesFromTexture(t){let{shape:e,dtype:n,isPacked:o}=this.texData.get(t),s=x.sizeFromShape(e);if(V().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")){let m=this.decode(t),f=this.texData.get(m.dataId),d=this.gpgpu.downloadMatrixFromPackedTexture(f.texture.texture,...yg(e)).subarray(0,s);return this.disposeIntermediateTensorInfo(m),d}let i=V().getBool("WEBGL_PACK")&&o===!0,a=i?Cg(e):e,u=i?new xw(a):new gw(a),l=this.runWebGLProgram(u,[{shape:a,dtype:n,dataId:t}],"float32"),c=this.texData.get(l.dataId),p=this.gpgpu.downloadByteEncodedFloatMatrixFromOutputTexture(c.texture.texture,c.texShape[0],c.texShape[1]).subarray(0,s);return this.disposeIntermediateTensorInfo(l),p}timerAvailable(){return V().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0}time(t){let e=this.activeTimers,n=[],o=!1;this.programTimersStack==null?(this.programTimersStack=n,o=!0):this.activeTimers.push(n),this.activeTimers=n,t();let s=x.flatten(this.activeTimers.map(u=>u.query)).filter(u=>u!=null),i=x.flatten(this.activeTimers.map(u=>u.name)).filter(u=>u!=null);this.activeTimers=e,o&&(this.programTimersStack=null);let a={uploadWaitMs:this.uploadWaitMs,downloadWaitMs:this.downloadWaitMs,kernelMs:null,wallMs:null};return(async()=>{if(V().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0){let u=await Promise.all(s);a.kernelMs=x.sum(u),a.getExtraProfileInfo=()=>u.map((l,c)=>({name:i[c],ms:l})).map(l=>`${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 V().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?this.gpgpu.beginQuery():{startMs:x.now(),endMs:null}}endTimer(t){return V().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?(this.gpgpu.endQuery(),t):(t.endMs=x.now(),t)}async getQueryTime(t){if(V().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=Att){return V().getBool("WEBGL_CPU_FORWARD")&&t.every(n=>this.texData.get(n.dataId).texture==null&&x.sizeFromShape(n.shape)<e)}getGPGPUContext(){return this.gpgpu}where(t){S.warn("tf.where() in webgl locks the UI thread. Call tf.whereAsync() instead");let e=t.dataSync();return Ntt(t.shape,e)}packedUnaryOp(t,e,n){let o=new eo(t.shape,e),s=this.compileAndRun(o,[t],n);return go().makeTensorFromDataId(s.dataId,s.shape,s.dtype)}abs(t){if(this.shouldExecuteOnCPU([t])&&t.dtype!=="complex64"){let o=Nw(this.texData.get(t.dataId).values);return this.makeOutput(t.shape,t.dtype,o)}if(V().getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(t,gT,t.dtype);let e=new en(t.shape,gT),n=this.compileAndRun(e,[t]);return go().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 go().makeTensorFromDataId(o,t,e,this)}unpackTensor(t){let e=new Aw(t.shape);return this.runWebGLProgram(e,[t],t.dtype)}packTensor(t){let e=new _w(t.shape),n=!0;return this.runWebGLProgram(e,[t],t.dtype,null,n)}packedReshape(t,e){let n=[Cl(t.shape),...Il(t.shape)],o={dtype:t.dtype,shape:n,dataId:t.dataId},s=[Cl(e),...Il(e)],i=new bd(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=Cg(s),u;o?u=new hw(a):u=new dw(a);let l=!0,c=[e!=null?e:yg(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===yu.DENSE){let y=i!=null?i:yg(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)<=V().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&&!bu(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=jM(t,c,p),f=this.getAndSaveBinary(m,()=>qM(this.gpgpu,t,c,p)),d=this.activeTimers!=null,h;d&&(h=this.startTimer()),V().get("ENGINE_COMPILE_ONLY")||KM(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=V().get("WEBGL_FLUSH_THRESHOLD");if(g>0){let y=x.now();y-this.lastGlFlushTime>g&&(this.gpgpu.gl.flush(),this.lastGlFlushTime=y)}if(!V().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||(V().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(!V().get("WEBGL_RENDER_FLOAT32_ENABLED")){let t=V().getBool("DEBUG");V().set("DEBUG",!1);let e=this.abs(pt(1e-8)).dataSync()[0];if(V().set("DEBUG",t),e>0)return 32}return 16})),this.floatPrecisionValue}epsilon(){return this.floatPrecision()===32?Ttt:_tt}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=UN(n,u),e.texShape=p),s!=null){let m=Cg(n),f,d=p[1],h=p[0],g=s instanceof Uint8Array||s instanceof Uint8ClampedArray;(u||!g)&&([d,h]=Ji(p[0],p[1])),u?f=new bw(m,g):f=new yw(m,g);let y=g?[h,d]:p,b=this.makeTensorInfo(y,o),w=this.texData.get(b.dataId);g?w.usage=Kr.PIXELS:w.usage=Kr.UPLOAD,w.texShape=y,this.gpgpu.uploadDenseMatrixToTexture(this.getTexture(b.dataId),d,h,s);let v=[[h,d]],k=!0,E=this.runWebGLProgram(f,[b],o,v,k),$=this.texData.get(E.dataId);e.texShape=$.texShape,e.isPacked=$.isPacked,e.usage=$.usage,V().get("ENGINE_COMPILE_ONLY")?this.disposeData(E.dataId):(e.texture=$.texture,e.values=null,this.texData.delete(E.dataId)),this.disposeIntermediateTensorInfo(b),l&&(this.uploadWaitMs+=x.now()-c)}else{let m=this.acquireTexture(p,a,o,u);e.texture=m}}convertAndCacheOnCPU(t,e){let n=this.texData.get(t),{dtype:o}=n;return this.releaseGPUData(t),e!=null&&(n.values=Rtt(e,o)),n.values}acquireTexture(t,e,n,o){if(this.numBytesInGPU+=this.computeBytes(t,n),!this.warnedAboutMemory&&this.numBytesInGPU>this.numMBBeforeWarning*1024*1024){let s=(this.numBytesInGPU/1024/1024).toFixed(2);this.warnedAboutMemory=!0,console.warn(`High memory usage in GPU: ${s} MB, most likely due to a memory leak`)}return this.textureManager.acquireTexture(t,e,o)}computeBytes(t,e){return t[0]*t[1]*x.bytesPerElement(e)}checkCompileCompletion(){for(let[,t]of Object.entries(this.binaryCache))this.checkCompletion_(t)}async checkCompileCompletionAsync(){let t=[];if(this.gpgpu.parallelCompilationExtension){for(let[,e]of Object.entries(this.binaryCache))t.push(this.checkCompletionAsync_(e));return Promise.all(t)}else{for(let[,e]of Object.entries(this.binaryCache)){let n=new Promise(o=>{try{this.checkCompletion_(e),o(!0)}catch(s){throw s}});t.push(n)}return Promise.all(t)}}async checkCompletionAsync_(t){return this.gpgpu.gl.getProgramParameter(t.webGLProgram,this.gpgpu.parallelCompilationExtension.COMPLETION_STATUS_KHR)?this.checkCompletion_(t):(await Vh(),this.checkCompletionAsync_(t))}checkCompletion_(t){if(this.gpgpu.gl.getProgramParameter(t.webGLProgram,this.gpgpu.gl.LINK_STATUS)===!1)throw console.log(this.gpgpu.gl.getProgramInfoLog(t.webGLProgram)),this.gpgpu.gl.getShaderParameter(t.fragmentShader,this.gpgpu.gl.COMPILE_STATUS)===!1?(lw(t.source,this.gpgpu.gl.getShaderInfoLog(t.fragmentShader)),new Error("Failed to compile fragment shader.")):new Error("Failed to link vertex and fragment shaders.");return!0}getUniformLocations(){for(let[,t]of Object.entries(this.binaryCache)){let{uniformLocations:e,customUniformLocations:n,infLoc:o,nanLoc:s,inShapesLocations:i,inTexShapesLocations:a,outShapeLocation:u,outShapeStridesLocation:l,outTexShapeLocation:c}=ZN(this.gpgpu,t.program,t.webGLProgram);t.uniformLocations=e,t.customUniformLocations=n,t.infLoc=o,t.nanLoc=s,t.inShapesLocations=i,t.inTexShapesLocations=a,t.outShapeLocation=u,t.outShapeStridesLocation=l,t.outTexShapeLocation=c}}};wu.nextDataId=0;function Rtt(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 jP="3.16.0";function XP(){V().set("WEBGL_FORCE_F16_TEXTURES",!0)}Xl.isBrowser()&&dm("webgl",()=>new wu,2);var gke={forceHalfFloat:XP};var Dw=`
if (isnan(a)) return a;
if (isnan(b)) return b;
`;var ro=class{constructor(t,e,n){this.variableNames=["A","B"],this.outputShape=S.assertAndGetBroadcastShape(e,n),this.enableShapeUniforms=De(this.outputShape.length),this.userCode=`
float binaryOperation(float a, float b) {
${t}
}
void main() {
float a = getAAtOutCoords();
float b = getBAtOutCoords();
setOutput(binaryOperation(a, b));
}
`}};var vu=`
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 Po=class{constructor(t,e,n,o=!1){this.variableNames=["A","B"],this.supportsBroadcasting=!0,this.packedInputs=!0,this.packedOutput=!0,this.outputShape=S.assertAndGetBroadcastShape(e,n);let s=this.outputShape.length;this.enableShapeUniforms=De(s);let i="";if(o)if(s===0||x.sizeFromShape(this.outputShape)===1)i=`
result.y = 0.;
result.z = 0.;
result.w = 0.;
`;else if(i=`
${Gt(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) >= ${this.outputShape[0]} ? 0. : result.y;
result.z = 0.;
result.w = 0.;
`;else{let u=nr("coords",s);this.enableShapeUniforms?i+=`
bool nextRowOutOfBounds =
(${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);
${i}
setOutput(result);
}
`}};function Ke(r){let{inputs:t,backend:e}=r,{x:n}=t;return e.incRef(n.dataId),{dataId:n.dataId,shape:n.shape,dtype:n.dtype}}var YP={kernelName:lo,backendName:"webgl",kernelFunc:Ke};function Rn(r){let{inputs:t,backend:e}=r,{real:n,imag:o}=t,s=e.makeTensorInfo(n.shape,"complex64"),i=e.texData.get(s.dataId),a=Ke({inputs:{x:n},backend:e}),u=Ke({inputs:{x:o},backend:e});return i.complexTensorInfos={real:a,imag:u},s}var ZP={kernelName:$p,backendName:"webgl",kernelFunc:Rn};var xT="return (a < 0.) ? b * a : a;",yT=`
vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));
return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);
`;function Ftt(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{alpha:s}=n,i=e.makeTensorInfo([],"float32",x.createScalarValue(s,"float32")),a=V().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new Po(yT,o.shape,i.shape):new ro(xT,o.shape,i.shape),u=e.runWebGLProgram(a,[o,i],"float32");return e.disposeIntermediateTensorInfo(i),u}var JP={kernelName:hs,backendName:"webgl",kernelFunc:Ftt};var bT="return (a < 0.) ? b * a : a;",wT=`
vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));
return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);
`;function Ott(r){let{inputs:t,backend:e}=r,{x:n,alpha:o}=t,s=V().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new Po(wT,n.shape,o.shape):new ro(bT,n.shape,o.shape);return e.runWebGLProgram(s,[n,o],"float32")}var QP={kernelName:_s,backendName:"webgl",kernelFunc:Ott};var Lo="if (isnan(x)) return x;",tL=`
if (isnan(a)) return a;
if (isnan(b)) return b;
`,eL=`
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=V().getBool("WEBGL_PACK_UNARY_OPERATIONS")&&t!=null,c;return l?c=new eo(i.shape,t):c=new en(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,k]=w,E={dataId:v.dataId,dtype:v.dtype,shape:u.shape},$={dataId:k.dataId,dtype:k.dtype,shape:l.shape},D=new ro(r,u.shape,l.shape);return c.runWebGLProgram(D,[E,$],ar(v.dtype,k.dtype))}),b=Rn({inputs:{real:g,imag:y},backend:c});return c.disposeIntermediateTensorInfo(g),c.disposeIntermediateTensorInfo(y),b}let p=s||ar(u.dtype,l.dtype);if((u.dtype==="string"||l.dtype==="string"||c.shouldExecuteOnCPU([u,l]))&&o!=null){let d=c.texData.get(u.dataId).values,h=c.texData.get(l.dataId).values,g=u.dtype==="string"?S.fromUint8ToStringArray(d):d,y=u.dtype==="string"?S.fromUint8ToStringArray(h):h,[b,w]=o(u.shape,l.shape,g,y,p),v=c.makeTensorInfo(w,p),k=c.texData.get(v.dataId);return k.values=b,v}let m=V().getBool("WEBGL_PACK_BINARY_OPERATIONS")&&t!=null,f;return m?f=new Po(t,u.shape,l.shape,e):f=new ro(r,u.shape,l.shape),c.runWebGLProgram(f,[u,l],p)}}function Cu(r,t=!1){if(r==="linear")return t?WP:PP;if(r==="relu")return t?HP:zP;if(r==="elu")return t?UP:LP;if(r==="relu6")return t?qP:BP;if(r==="prelu")return t?wT:bT;if(r==="leakyrelu")return t?yT:xT;if(r==="sigmoid")return t?KP:VP;throw new Error(`Activation ${r} has not been implemented for the WebGL backend.`)}var wd=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 vT={REAL:"return areal * breal - aimag * bimag;",IMAG:"return areal * bimag + aimag * breal;"},Sg=class{constructor(t,e,n){this.variableNames=["AReal","AImag","BReal","BImag"],this.outputShape=S.assertAndGetBroadcastShape(e,n),this.userCode=`
float binaryOpComplex(
float areal, float aimag, float breal, float bimag) {
${t}
}
void main() {
float areal = getARealAtOutCoords();
float aimag = getAImagAtOutCoords();
float breal = getBRealAtOutCoords();
float bimag = getBImagAtOutCoords();
setOutput(binaryOpComplex(areal, aimag, breal, bimag));
}
`}};var rL="return a * b;";function kg(r){let{inputs:t,backend:e}=r,{a:n,b:o}=t,s=S.upcastType(n.dtype,o.dtype);if(n.dtype==="complex64"){let a=e.texData.get(n.dataId),u=e.texData.get(o.dataId),l=new Sg(vT.REAL,n.shape,o.shape),c=new Sg(vT.IMAG,n.shape,o.shape),p=[{dataId:a.complexTensorInfos.real.dataId,dtype:a.complexTensorInfos.real.dtype,shape:n.shape},{dataId:a.complexTensorInfos.imag.dataId,dtype:a.complexTensorInfos.imag.dtype,shape:n.shape},{dataId:u.complexTensorInfos.real.dataId,dtype:u.complexTensorInfos.real.dtype,shape:o.shape},{dataId:u.complexTensorInfos.imag.dataId,dtype:u.complexTensorInfos.imag.dtype,shape:o.shape}],m=e.runWebGLProgram(l,p,"float32"),f=e.runWebGLProgram(c,p,"float32"),d=Rn({inputs:{real:m,imag:f},backend:e});return e.disposeIntermediateTensorInfo(m),e.disposeIntermediateTensorInfo(f),d}if(e.shouldExecuteOnCPU([n,o])){let a=e.texData.get(n.dataId),u=e.texData.get(o.dataId),[l,c]=dP(n.shape,o.shape,a.values,u.values,s),p=e.makeTensorInfo(c,s),m=e.texData.get(p.dataId);return m.values=l,p}let i;return V().getBool("WEBGL_PACK_BINARY_OPERATIONS")?i=new Po(rL,n.shape,o.shape):i=new ro(rL,n.shape,o.shape),e.runWebGLProgram(i,[n,o],s)}var nL={kernelName:Ss,backendName:"webgl",kernelFunc:kg};function oL(r,t,e){let n=[Cl(r.shape),...Il(r.shape)],o={dtype:r.dtype,shape:n,dataId:r.dataId},s=[Cl(t),...Il(t)],i=new bd(s,n),a=!0,u=[n],l=e.runWebGLProgram(i,[o],r.dtype,u,a);return{dataId:l.dataId,shape:t,dtype:l.dtype}}function ut(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{shape:s}=n,i=e,a=x.sizeFromShape(o.shape),u=x.inferFromImplicitShape(s,a),l=x.sizeFromShape(u);x.assert(a===l,()=>`The new shape (${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&&!bu(o.shape,u)&&!(c.texture!==null&&bu(c.shape,u))?oL(o,u,i):(i.incRef(o.dataId),{dataId:o.dataId,shape:u,dtype:o.dtype})}var sL={kernelName:_i,backendName:"webgl",kernelFunc:ut};var Ng=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);
${l}
}
setOutput(sumValue);
}
`}};var Rw=class{constructor(t,e){this.variableNames=["x"];let{windowSize:n,batchSize:o,inSize:s,outSize:i}=t;this.outputShape=[o,i];let a="0.0",u="";e==="prod"?a="1.0":e==="min"?(a="1.0 / 1e-20",u="min"):e==="max"&&(a="-1.0 / 1e-20",u="max");let l=`${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 Ptt(r){let t=[];for(;t.length===0||t[t.length-1].outSize!==1;){let e=t.length?t[t.length-1].outSize:r[1],n=S.computeOptimalWindowSize(e);t.push({inSize:e,windowSize:n,outSize:Math.ceil(e/n)})}return t}function Hn(r,t,e,n){let o=Ptt(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 Ng({windowSize:u,inSize:a,batchSize:r.shape[0],outSize:l},a):new Ng({windowSize:u,inSize:a,batchSize:r.shape[0],outSize:l}):c=new Rw({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 Fw=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=Gt(this.rank),s=Ltt(e);this.userCode=`
void main() {
${o} resRC = getOutputCoords();
setOutput(getA(${s}));
}
`}};function Ltt(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 Ow=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 ${this.rank} is not yet supported.`);let o=Gt(this.rank),s=hT("rc",this.rank),i=new Array(this.rank);for(let c=0;c<e.length;c++)i[e[c]]=s[c];let a=`vec2(${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] = ${l};
}
}
setOutput(result);
}
`}};function Iu(r,t,e){let n=V().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new Ow(r.shape,t):new Fw(r.shape,t);return e.runWebGLProgram(n,[r],r.dtype)}function iL(r,t,e,n){let o=t,s=r.shape.length,i=x.parseAxisParam(o,r.shape),a=i,u=S.getAxesPermutation(a,s),l=u!=null,c=r;l&&(c=Iu(r,u,n),a=S.getInnerMostAxes(a.length,s)),S.assertAxesAreInnerMostDims("sum",a,s);let[p,m]=S.computeOutAndReduceShapes(c.shape,a),f=p;e&&(f=S.expandShapeToKeepDim(p,i));let d=x.sizeFromShape(m),g=x.sizeFromShape(r.shape)/d,y=ut({inputs:{x:c},attrs:{shape:[g,d]},backend:n}),b=Uu(r.dtype),w=Hn(y,b,"sum",n),v=ut({inputs:{x:w},attrs:{shape:f},backend:n});return n.disposeIntermediateTensorInfo(y),n.disposeIntermediateTensorInfo(w),l&&n.disposeIntermediateTensorInfo(c),v}function rp(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{axis:s,keepDims:i}=n;return iL(o,s,i,e)}var aL={kernelName:zs,backendName:"webgl",kernelFunc:rp};function Ae(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{perm:s}=n,i=e,a=o.shape.length,u=new Array(a);for(let c=0;c<u.length;c++)u[c]=o.shape[s[c]];let l;if(i.shouldExecuteOnCPU([o])){let p=i.texData.get(o.dataId).values,m=tp(p,o.shape,o.dtype,s,u);l=i.makeTensorInfo(u,o.dtype);let f=i.texData.get(l.dataId);f.values=m}else l=Iu(o,s,i);return l}var lL={kernelName:Hs,backendName:"webgl",kernelFunc:Ae};var CT=1e3;function np({a:r,b:t,transposeA:e,transposeB:n,backend:o,bias:s=null,preluActivationWeights:i=null,leakyreluAlpha:a=0,activation:u=null}){let l=r.shape.length,c=t.shape.length,p=e?r.shape[l-2]:r.shape[l-1],m=n?t.shape[c-1]:t.shape[c-2],f=e?r.shape[l-1]:r.shape[l-2],d=n?t.shape[c-2]:t.shape[c-1],h=r.shape.slice(0,-2),g=t.shape.slice(0,-2),y=x.sizeFromShape(h),b=x.sizeFromShape(g),v=Pr.assertAndGetBroadcastShape(r.shape.slice(0,-2),t.shape.slice(0,-2)).concat([f,d]);x.assert(p===m,()=>`Error in matMul: inner shapes (${p}) and (${m}) of Tensors with shapes ${r.shape} and ${t.shape} and transposeA=${e} and transposeB=${n} must match.`);let k=e?[y,p,f]:[y,f,p],E=n?[b,d,m]:[b,m,d],$=ut({inputs:{x:r},backend:o,attrs:{shape:k}}),D=ut({inputs:{x:t},backend:o,attrs:{shape:E}}),R=[$,D],P=Math.max(y,b),W=e?$.shape[1]:$.shape[2],U=s!=null,q=i!=null,K=u==="leakyrelu",j=u!=null?Cu(u,!0):null,Q=U||q||K||j!=null,rt;if((f===1||d===1)&&W>CT&&Q===!1){let ot=$,st=D;e&&(ot=Ae({inputs:{x:$},backend:o,attrs:{perm:[0,2,1]}}),R.push(ot)),n&&(st=Ae({inputs:{x:D},backend:o,attrs:{perm:[0,2,1]}}),R.push(st));let it=d!==1,ft=d===1,at=ot;it&&(at=ut({inputs:{x:ot},backend:o,attrs:{shape:[P,W,1]}}),R.push(at));let xt=d===1?2:1,dt=st;ft&&(dt=ut({inputs:{x:st},backend:o,attrs:{shape:[P,1,W]}}),R.push(dt));let bt=kg({inputs:{a:at,b:dt},backend:o});rt=rp({inputs:{x:bt},backend:o,attrs:{axis:xt,keepDims:!0}}),R.push(bt)}else{let ot=ar(r.dtype,t.dtype),st=new wd(k,E,[P,f,d],e,n,U,j,q,K),it=[$,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,ot)}let X=ut({inputs:{x:rt},backend:o,attrs:{shape:v}});R.push(rt);for(let ot of R)o.disposeIntermediateTensorInfo(ot);return X}function ztt(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 np({a:o,b:s,transposeA:u,transposeB:l,backend:e,bias:i,preluActivationWeights:a,leakyreluAlpha:p,activation:c})}var uL={kernelName:Oi,backendName:"webgl",kernelFunc:ztt};var cL="return abs(x);";function Btt(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=Nw(s.values);return e.makeTensorInfo(n.shape,n.dtype,i)}let o;return V().getBool("WEBGL_PACK_UNARY_OPERATIONS")?o=new eo(n.shape,cL):o=new en(n.shape,cL),e.runWebGLProgram(o,[n],n.dtype)}var pL={kernelName:wi,backendName:"webgl",kernelFunc:Btt};var Vtt=hr+`
if (abs(x) > 1.) {
return NAN;
}
return acos(x);
`,Gtt=Ct({opSnippet:Vtt}),mL={kernelName:ea,backendName:"webgl",kernelFunc:Gtt};var Wtt=hr+`
if (x < 1.0) return NAN;
return log(x + sqrt(x * x - 1.0));`,Utt=Ct({opSnippet:Wtt}),fL={kernelName:ra,backendName:"webgl",kernelFunc:Utt};var dL="return a + b;",Htt=le({opSnippet:dL,packedOpSnippet:dL,supportsComplex:!0,cpuKernelImpl:XM}),hL={kernelName:Xn,backendName:"webgl",kernelFunc:Htt};var Mw=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 = ${o};
setOutput(result);
}
`}};var Pw=class{constructor(t,e){this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t,this.variableNames=e.map((s,i)=>`T${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 Lw(r){let{inputs:t,backend:e}=r,n=t;if(n.length===1)return Ke({inputs:{x:n[0]},backend:e});if(n.length>V().get("WEBGL_MAX_TEXTURES_IN_SHADER")){let u=Math.floor(n.length/2),l=Lw({inputs:n.slice(0,u),backend:e}),c=Lw({inputs:n.slice(u),backend:e});return Lw({inputs:[l,c],backend:e})}let o=n.map(u=>u.dtype).reduce((u,l)=>ar(u,l)),s=n.map(u=>u.shape),a=V().getBool("WEBGL_PACK")?new Pw(n[0].shape,s):new Mw(n[0].shape,s);return e.runWebGLProgram(a,n,o)}var gL={kernelName:Zo,backendName:"webgl",kernelFunc:Lw};function qtt(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{axis:s,keepDims:i}=n,a=o.shape.length,u=x.parseAxisParam(s,o.shape),l=u,c=S.getAxesPermutation(l,a),p=o;c!=null&&(p=Ae({inputs:{x:o},backend:e,attrs:{perm:c}}),l=S.getInnerMostAxes(l.length,a)),S.assertAxesAreInnerMostDims("all",l,a);let[m,f]=S.computeOutAndReduceShapes(p.shape,l),d=x.sizeFromShape(f),h=ut({inputs:{x:p},backend:e,attrs:{shape:[-1,d]}}),g=Hn(h,h.dtype,"all",e),y;if(i){let b=S.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 xL={kernelName:na,backendName:"webgl",kernelFunc:qtt};function Ktt(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{axis:s,keepDims:i}=n,a=o.shape.length,u=x.parseAxisParam(s,o.shape),l=u,c=S.getAxesPermutation(l,a),p=o;c!=null&&(p=Ae({inputs:{x:o},backend:e,attrs:{perm:c}}),l=S.getInnerMostAxes(l.length,a)),S.assertAxesAreInnerMostDims("any",l,a);let[m,f]=S.computeOutAndReduceShapes(p.shape,l),d=x.sizeFromShape(f),h=ut({inputs:{x:p},backend:e,attrs:{shape:[-1,d]}}),g=Hn(h,h.dtype,"any",e),y;if(i){let b=S.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 yL={kernelName:oa,backendName:"webgl",kernelFunc:Ktt};var zw=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 ${a} bestValue) {
bestValue = candidate;
bestIndex = inIdx;
}
}
setOutput(float(bestIndex));
}
`}};var Bw=class{constructor(t,e,n,o){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,x.assert(t.length>2,()=>`Packed arg${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=Gt(u),c=nr("coords",u),p,m;if(i===1){m=u+1;let D=Gt(m);p=`
${D} sourceLocR = ${D}(${c.join()}, 0);
++${c[u-1]};
${D} sourceLocG = ${D}(${c.join()}, 0);
++${c[u-2]};
${D} sourceLocA = ${D}(${c.join()}, 0);
--${c[u-1]};
${D} sourceLocB = ${D}(${c.join()}, 0);
--${c[u-2]};`}else m=u,p=`
${l} sourceLocR = coords;
++${c[u-1]};
${l} sourceLocG = coords;
++${c[u-2]};
${l} sourceLocA = coords;
--${c[u-1]};
${l} sourceLocB = coords;
--${c[u-2]};`;let f=["x","y","z","w","u","v"].slice(0,m),d="."+f[m-1],h=f.map(D=>"int "+D),g=nr("sourceLocR",m-1).concat("inIdx.r"),y=nr("sourceLocG",m-1).concat("inIdx.g"),b=nr("sourceLocB",m-1).concat("inIdx.b"),w=nr("sourceLocA",m-1).concat("inIdx.a"),v=n==="max"?"greaterThan":"lessThan",k=o?"":`
inIdx = round(vec4(getBestIndicesAChannel(${g.join()}),
getBestIndicesAChannel(${y.join()}),
getBestIndicesAChannel(${b.join()}),
getBestIndicesAChannel(${w.join()})));`,E=`vec4(
getAChannel(${g.join()}),
hasNextCol ? getAChannel(${y.join()}) : 0.,
hasNextRow ? getAChannel(${b.join()}) : 0.,
hasNextRow && hasNextCol ? getAChannel(${w.join()}) : 0.)`,$=o?"":`
float getBestIndicesAChannel(${h.join()}) {
return getChannel(getBestIndicesA(${f.join()}),
vec2(${f.slice(-2).join()}));
}`;this.userCode=`
float getAChannel(${h.join()}) {
return getChannel(getA(${f.join()}),
vec2(${f.slice(-2).join()}));
}
${$}
void main() {
${l} coords = getOutputCoords();
bool hasNextCol = ${c[u-1]} < ${a[u-1]-1};
bool hasNextRow = ${c[u-2]} < ${a[u-2]-1};
${p}
ivec4 srcIdx = ivec4(sourceLocR${d}, sourceLocG${d},
sourceLocB${d}, sourceLocA${d}) * ${e};
ivec4 inIdx = srcIdx;
vec4 bestIndex = vec4(inIdx);
vec4 bestValue = ${E};
for (int i = 0; i < ${e}; i++) {
inIdx = srcIdx;
${k}
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 bL(r,t,e,n=null){let o=t.shape[0],s=t.shape[1];n!=null&&(o=n.shape[0],s=n.shape[1]);let i=S.computeOptimalWindowSize(s),a={windowSize:i,inSize:s,batchSize:o,outSize:Math.ceil(s/i)},u=new zw(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=bL(r,t,e,c);return r.disposeIntermediateTensorInfo(c),p}function wL(r,t,e,n=null){let o=n!=null?n.shape:t.shape,s=o[o.length-1],i=S.computeOptimalWindowSize(s),a=new Bw(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=wL(r,t,e,l);return r.disposeIntermediateTensorInfo(l),c}return l}function Vw(r,t,e,n){let o=[e];if(S.assertAxesAreInnerMostDims("arg"+n.charAt(0).toUpperCase()+n.slice(1),o,t.shape.length),!V().getBool("WEBGL_PACK_REDUCE")||t.shape.length<=2){let s=[],i=r.texData.get(t.dataId),a=i!==null&&i.isPacked,u=t;a&&(u=r.unpackTensor(t),s.push(u));let[l,c]=S.computeOutAndReduceShapes(u.shape,o),p=x.sizeFromShape(c),m=ut({inputs:{x:u},backend:r,attrs:{shape:[-1,p]}});s.push(m);let f=bL(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 wL(r,t,n)}function jtt(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{axis:s}=n,i=x.parseAxisParam(s,o.shape),a=S.getAxesPermutation(i,o.shape.length),u=o,l=[];a!=null&&(u=Ae({inputs:{x:o},backend:e,attrs:{perm:a}}),l.push(u),i=S.getInnerMostAxes(i.length,u.shape.length)),S.assertAxesAreInnerMostDims("argMax",[i[0]],u.shape.length);let c=Vw(e,u,i[0],"max");return l.forEach(p=>e.disposeIntermediateTensorInfo(p)),c}var vL={kernelName:Jo,backendName:"webgl",kernelFunc:jtt};function Xtt(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{axis:s}=n,i=x.parseAxisParam(s,o.shape),a=S.getAxesPermutation(i,o.shape.length),u=o,l=[];a!=null&&(u=Ae({inputs:{x:o},backend:e,attrs:{perm:a}}),l.push(u),i=S.getInnerMostAxes(i.length,u.shape.length)),S.assertAxesAreInnerMostDims("argMin",[i[0]],u.shape.length);let c=Vw(e,u,i[0],"min");return l.forEach(p=>e.disposeIntermediateTensorInfo(p)),c}var CL={kernelName:$l,backendName:"webgl",kernelFunc:Xtt};var Ytt=hr+`
if (abs(x) > 1.) {
return NAN;
}
return asin(x);
`,Ztt=Ct({opSnippet:Ytt}),IL={kernelName:sa,backendName:"webgl",kernelFunc:Ztt};var Jtt=hr+"return log(x + sqrt(x * x + 1.0));",Qtt=Ct({opSnippet:Jtt}),SL={kernelName:ia,backendName:"webgl",kernelFunc:Qtt};var tet=hr+`
return atan(x);
`,eet=Ct({opSnippet:tet}),kL={kernelName:aa,backendName:"webgl",kernelFunc:eet};var ret=tL+`
return atan(a, b);
`,net=`
vec4 result = atan(a, b);
vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
`+eL+`
return result;
`,oet=le({opSnippet:ret,packedOpSnippet:net}),NL={kernelName:ua,backendName:"webgl",kernelFunc:oet};var set=hr+`
if ((x < -1.0) || (x > 1.0)) return NAN;
return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,iet=Ct({opSnippet:set}),TL={kernelName:la,backendName:"webgl",kernelFunc:iet};var gi=class{constructor(t,e,n,o=!1,s=!1){if(this.variableNames=["x"],e==="avg"&&n)throw new Error("Cannot compute positions for average pool.");let i=t.filterWidth,a=t.strideHeight,u=t.strideWidth,l=t.dilationHeight,c=t.dilationWidth,p=t.effectiveFilterHeight,m=t.effectiveFilterWidth,f=t.padInfo.top,d=t.padInfo.left;this.outputShape=t.outShape;let h=e==="avg",g=`((batch * ${t.inHeight} + xR) * ${t.inWidth} + xC) * ${t.inChannels} + d`,y=`(xR * ${t.inWidth} + xC) * ${t.inChannels} + d`,b="0.0";if(h||(b="-1.0 / 1e-20"),n){let D=">=";this.userCode=`
const ivec2 strides = ivec2(${a}, ${u});
const ivec2 pads = ivec2(${f}, ${d});
void main() {
ivec4 coords = getOutputCoords();
int batch = coords[0];
int d = coords[3];
ivec2 xRCCorner = coords.yz * strides - pads;
int xRCorner = xRCCorner.x;
int xCCorner = xRCCorner.y;
// max/min x(?, ?, d) to get y(yR, yC, d).
// ? = to be determined
float minMaxValue = 0.0;
float minMaxValueFound = 0.0;
int minMaxPosition = 0;
float avgValue = 0.0;
for (int wR = 0; wR < ${p};
wR += ${l}) {
int xR = xRCorner + wR;
if (xR < 0 || xR >= ${t.inHeight}) {
continue;
}
for (int wC = 0; wC < ${m};
wC += ${c}) {
int xC = xCCorner + wC;
if (xC < 0 || xC >= ${t.inWidth}) {
continue;
}
float value = getX(batch, xR, xC, d);
// If a min / max value has already been found, use it. If not,
// use the current value.
float currMinMaxValue = mix(
value, minMaxValue, minMaxValueFound);
if (value ${D} currMinMaxValue) {
minMaxValue = value;
minMaxValueFound = 1.0;
minMaxPosition = ${o?s?g:y:`wR * ${m} + wC`};
}
}
}
setOutput(float(minMaxPosition));
}
`;return}let w="max",v=`${e}(${e}(${e}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;e==="avg"&&(v="avgValue / count");let k=Math.floor(i/4)*4,E=i%4,$=`
if (${h}) {
avgValue += dot(values, ones);
} else {
minMaxValue = ${w}(values, minMaxValue);
}
`;this.userCode=`
const ivec2 strides = ivec2(${a}, ${u});
const ivec2 pads = ivec2(${f}, ${d});
const float initializationValue = ${b};
const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);
float count = 0.0;
float getValue(int batch, int xR, int xC, int d) {
if (xC < 0 || xC >= ${t.inWidth}) {
return initializationValue;
}
count += 1.0;
return getX(batch, xR, xC, d);
}
void main() {
ivec4 coords = getOutputCoords();
int batch = coords[0];
int d = coords[3];
ivec2 xRCCorner = coords.yz * strides - pads;
int xRCorner = xRCCorner.x;
int xCCorner = xRCCorner.y;
// max/min x(?, ?, d) to get y(yR, yC, d).
// ? = to be determined
vec4 minMaxValue = vec4(${b});
float avgValue = 0.0;
count = 0.0;
for (int wR = 0; wR < ${p};
wR += ${l}) {
int xR = xRCorner + wR;
if (xR < 0 || xR >= ${t.inHeight}) {
continue;
}
for (int wC = 0; wC < ${k}; wC += 4) {
int xC = xCCorner + wC * ${c};
vec4 values = vec4(
getValue(batch, xR, xC, d),
getValue(batch, xR, xC + ${c}, d),
getValue(batch, xR, xC + 2 * ${c}, d),
getValue(batch, xR, xC + 3 * ${c}, d)
);
${$}
}
int xC = xCCorner + ${k};
if (${E===1}) {
vec4 values = vec4(
getValue(batch, xR, xC, d),
initializationValue,
initializationValue,
initializationValue
);
${$}
} else if (${E===2}) {
vec4 values = vec4(
getValue(batch, xR, xC, d),
getValue(batch, xR, xC + ${c}, d),
initializationValue,
initializationValue
);
${$}
} else if (${E===3}) {
vec4 values = vec4(
getValue(batch, xR, xC, d),
getValue(batch, xR, xC + ${c}, d),
getValue(batch, xR, xC + 2 * ${c}, d),
initializationValue
);
${$}
}
}
setOutput(${v});
}
`}},Su=class{constructor(t,e,n,o=!1,s=!1){if(this.variableNames=["x"],e==="avg"&&n)throw new Error("Cannot compute positions for average pool.");let i=t.filterWidth,a=t.strideDepth,u=t.strideHeight,l=t.strideWidth,c=t.dilationDepth,p=t.dilationHeight,m=t.dilationWidth,f=t.effectiveFilterDepth,d=t.effectiveFilterHeight,h=t.effectiveFilterWidth,g=t.padInfo.front,y=t.padInfo.top,b=t.padInfo.left;this.outputShape=t.outShape;let w=e==="avg",v="0.0";if(w||(v="-1.0 / 1e-20"),n){let P=">=";this.userCode=`
const ivec3 strides =
ivec3(${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 ${P} 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 * ${h} + wC`};
}
}
}
}
setOutput(float(minMaxPosition));
}
`;return}let k="max",E=`${e}(${e}(${e}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;e==="avg"&&(E="avgValue / count");let $=Math.floor(i/4)*4,D=i%4,R=`
if (${w}) {
avgValue += dot(values, ones);
} else {
minMaxValue = ${k}(values, minMaxValue);
}
`;this.userCode=`
const ivec3 strides =
ivec3(${a}, ${u}, ${l});
const ivec3 pads = ivec3(${g}, ${y}, ${b});
const float initializationValue = ${v};
const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);
float count = 0.0;
float getValue(int batch, int xD, int xR, int xC, int ch) {
if (xC < 0 || xC >= ${t.inWidth}) {
return initializationValue;
}
count += 1.0;
return getX(batch, xD, xR, xC, ch);
}
void main() {
ivec5 coords = getOutputCoords();
int batch = coords.x;
int ch = coords.u;
ivec3 xCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;
int xDCorner = xCorner.x;
int xRCorner = xCorner.y;
int xCCorner = xCorner.z;
// max/min x(?, ?, ?, d) to get y(yD, yR, yC, ch).
// ? = to be determined
vec4 minMaxValue = vec4(${v});
float avgValue = 0.0;
count = 0.0;
for (int wD = 0; wD < ${f};
wD += ${c}) {
int xD = xDCorner + wD;
if (xD < 0 || xD >= ${t.inDepth}) {
continue;
}
for (int wR = 0; wR < ${d};
wR += ${p}) {
int xR = xRCorner + wR;
if (xR < 0 || xR >= ${t.inHeight}) {
continue;
}
for (int wC = 0; wC < ${$}; wC += 4) {
int xC = xCCorner + wC * ${m};
vec4 values = vec4(
getValue(batch, xD, xR, xC, ch),
getValue(batch, xD, xR, xC + ${m}, ch),
getValue(batch, xD, xR, xC + 2 * ${m}, ch),
getValue(batch, xD, xR, xC + 3 * ${m}, ch)
);
${R}
}
int xC = xCCorner + ${$};
if (${D===1}) {
vec4 values = vec4(
getValue(batch, xD, xR, xC, ch),
initializationValue,
initializationValue,
initializationValue
);
${R}
} else if (${D===2}) {
vec4 values = vec4(
getValue(batch, xD, xR, xC, ch),
getValue(batch, xD, xR, xC + ${m}, ch),
initializationValue,
initializationValue
);
${R}
} else if (${D===3}) {
vec4 values = vec4(
getValue(batch, xD, xR, xC, ch),
getValue(batch, xD, xR, xC + ${m}, ch),
getValue(batch, xD, xR, xC + 2 * ${m}, ch),
initializationValue
);
${R}
}
}
setOutput(${E});
}
}
`}};function aet(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t;di(o,"avgPool");let{filterSize:s,strides:i,pad:a,dimRoundingMode:u}=n,l=1;x.assert(S.eitherStridesOrDilationsAreOne(i,l),()=>`Error in avgPool: Either strides or dilations must be 1. Got strides ${i} and dilations '${l}'`);let c=S.computePool2DInfo(o.shape,s,i,l,a,u);if(c.filterWidth===1&&c.filterHeight===1&&x.arraysEqual(c.inShape,c.outShape))return Ke({inputs:{x:o},backend:e});let p=new gi(c,"avg",!1);return e.runWebGLProgram(p,[o],"float32")}var _L={kernelName:Qo,backendName:"webgl",kernelFunc:aet};function uet(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{filterSize:s,strides:i,pad:a,dimRoundingMode:u,dataFormat:l}=n,c=[1,1,1],p=S.computePool3DInfo(o.shape,s,i,c,a,u,l),m=new Su(p,"avg",!1);return e.runWebGLProgram(m,[o],"float32")}var EL={kernelName:Dl,backendName:"webgl",kernelFunc:uet};var Gw=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 >= ${t.outWidth}.0 ||
fract(dyC) > 0.0) {
continue;
}
int idyC = int(dyC);
float dyValue = getDy(b, idyR, idyC, d);
dotProd += dyValue * avgMultiplier;
}
}
setOutput(dotProd);
}
`}},Ww=class{constructor(t){this.variableNames=["dy"],this.outputShape=t.inShape;let e=t.filterDepth,n=t.filterHeight,o=t.filterWidth,s=t.strideDepth,i=t.strideHeight,a=t.strideWidth,u=t.dilationDepth,l=t.dilationHeight,c=t.dilationWidth,p=t.effectiveFilterDepth,m=t.effectiveFilterHeight,f=t.effectiveFilterWidth,d=p-1-t.padInfo.front,h=m-1-t.padInfo.top,g=f-1-t.padInfo.left,y=1/(e*n*o);this.userCode=`
const ivec3 pads = ivec3(${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 cet(r){let{inputs:t,backend:e,attrs:n}=r,{dy:o,input:s}=t,i=s,{filterSize:a,strides:u,pad:l,dimRoundingMode:c}=n,p=[1,1,1],m=S.computePool3DInfo(i.shape,a,u,p,l,c),f=new Ww(m);return e.runWebGLProgram(f,[o],i.dtype)}var AL={kernelName:_p,backendName:"webgl",kernelFunc:cet};function pet(r){let{inputs:t,backend:e,attrs:n}=r,{dy:o,input:s}=t,i=s;di([o,s],"avgPoolGrad");let{filterSize:a,strides:u,pad:l}=n,c=S.computePool2DInfo(i.shape,a,u,1,l),p=new Gw(c);return e.runWebGLProgram(p,[o],i.dtype)}var $L={kernelName:Tp,backendName:"webgl",kernelFunc:pet};function met(r){let{inputs:t,backend:e,attrs:n}=r,{a:o,b:s}=t,{transposeA:i,transposeB:a}=n;return np({a:o,b:s,transposeA:i,transposeB:a,backend:e})}var DL={kernelName:ts,backendName:"webgl",kernelFunc:met};var Uw=class{constructor(t,e,n,o,s,i){this.outputShape=[],this.variableNames=["x","mean","variance"],S.assertAndGetBroadcastShape(t,e),S.assertAndGetBroadcastShape(t,n);let a="0.0";o!=null&&(S.assertAndGetBroadcastShape(t,o),this.variableNames.push("offset"),a="getOffsetAtOutCoords()");let u="1.0";s!=null&&(S.assertAndGetBroadcastShape(t,s),this.variableNames.push("scale"),u="getScaleAtOutCoords()"),this.outputShape=t,this.userCode=`
void main() {
float x = getXAtOutCoords();
float mean = getMeanAtOutCoords();
float variance = getVarianceAtOutCoords();
float offset = ${a};
float scale = ${u};
float inv = scale * inversesqrt(variance + float(${i}));
setOutput(dot(vec3(x, -mean, offset), vec3(inv, inv, 1)));
}
`}};var Hw=class{constructor(t,e,n,o,s,i){this.packedInputs=!0,this.packedOutput=!0,this.variableNames=["x","mean","variance"],S.assertAndGetBroadcastShape(t,e),S.assertAndGetBroadcastShape(t,n);let a="vec4(0.0)";o!=null&&(S.assertAndGetBroadcastShape(t,o),this.variableNames.push("offset"),a="getOffsetAtOutCoords()");let u="vec4(1.0)";s!=null&&(S.assertAndGetBroadcastShape(t,s),this.variableNames.push("scale"),u="getScaleAtOutCoords()"),this.outputShape=t,this.userCode=`
void main() {
vec4 offset = ${a};
vec4 scale = ${u};
vec4 x = getXAtOutCoords();
vec4 mean = getMeanAtOutCoords();
vec4 variance = getVarianceAtOutCoords();
vec4 inv = scale * inversesqrt(variance + vec4(${i}));
setOutput((x - mean) * inv + offset);
}
`}};var fet=({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=V().getBool("WEBGL_PACK_NORMALIZATION")?new Hw(n.shape,o.shape,s.shape,c,p,u):new Uw(n.shape,o.shape,s.shape,c,p,u);return t.runWebGLProgram(m,l,l[0].dtype)},RL={kernelName:fs,backendName:"webgl",kernelFunc:fet};var qw=class{constructor(t){this.variableNames=["source"],this.outputShape=t,this.rank=t.length;let e=Gt(this.rank);this.customUniforms=[{name:"start",arrayIndex:this.rank,type:"int"}];let n=det(this.rank),o,s=t.map((i,a)=>`sourceLoc.${IT[a]} = start[${a}] + coords.${IT[a]};`);o=`
${e} sourceLoc;
${e} coords = getOutputCoords();
${s.join(`
`)}
`,this.userCode=`
void main() {
${o}
setOutput(getSource(${n}));
}
`}},IT=["x","y","z","w","u","v"];function det(r){if(r===1)return"sourceLoc";if(r<=6)return IT.slice(0,r).map(t=>"sourceLoc."+t).join(",");throw Error(`Slicing for rank ${r} is not yet supported`)}var Kw=class{constructor(t){this.variableNames=["source"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t,this.rank=t.length,this.customUniforms=[{name:"start",arrayIndex:this.rank,type:"int"}];let e=Gt(this.rank),n=nr("coords",this.rank),o=nr("sourceLoc",this.rank),s=this.rank===1?"sourceLoc":`vec2(${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 het(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 xi(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=vP(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=V().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new Kw(u):new qw(u),m=[a];return e.runWebGLProgram(p,[o],o.dtype,m)}return e.uploadToGPU(o.dataId),het(o,a,u,e)}var FL={kernelName:Ai,backendName:"webgl",kernelFunc:xi};var get=r=>{let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{blockShape:s,crops:i}=n;x.assert(o.shape.length<=4,()=>"batchToSpaceND for rank > 4 with a WebGL backend not implemented yet");let a=s.reduce((b,w)=>b*w),u=S.getReshaped(o.shape,s,a),l=S.getPermuted(u.length,s.length),c=S.getReshapedPermuted(o.shape,s,a),p=S.getSliceBeginCoords(i,s.length),m=S.getSliceSize(c,i,s.length),f=[],d=ut({inputs:{x:o},backend:e,attrs:{shape:u}}),h=Ae({inputs:{x:d},backend:e,attrs:{perm:l}}),g=ut({inputs:{x:h},backend:e,attrs:{shape:c}}),y=xi({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},OL={kernelName:vi,backendName:"webgl",kernelFunc:get};function xet(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=kw(a,u,s.dtype,s.shape,i);return e.makeTensorInfo([i],s.dtype,l)}var ML={kernelName:Ep,backendName:"webgl",kernelFunc:xet};function yet(r){let{inputs:t,backend:e}=r,{s0:n,s1:o}=t,s=e.readSync(n.dataId),i=e.readSync(o.dataId),a=S.assertAndGetBroadcastShape(Array.from(s),Array.from(i));return e.makeTensorInfo([a.length],"int32",Int32Array.from(a))}var PL={kernelName:Ap,backendName:"webgl",kernelFunc:yet};var bet="return float(a != b);",ST=le({opSnippet:bet,cpuKernelImpl:gP,dtype:"bool"}),LL={kernelName:Ta,backendName:"webgl",kernelFunc:ST};function Sl(r){let{inputs:t,backend:e}=r,{input:n}=t,o=e.texData.get(n.dataId);return Ke({inputs:{x:o.complexTensorInfos.real},backend:e})}var zL={kernelName:Yp,backendName:"webgl",kernelFunc:Sl};var wet="return float(int(x));";function BL(r,t){let e=new en(r.shape,wet),n=t.runWebGLProgram(e,[r],"int32");return{dataId:n.dataId,shape:n.shape,dtype:n.dtype}}function kT(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{dtype:s}=n;if(s==="complex64"){if(o.dtype==="complex64")return Ke({inputs:{x:o},backend:e});let i=ye(o.shape),a=kT({inputs:{x:o},backend:e,attrs:{dtype:"float32"}}),u=Rn({inputs:{real:a,imag:i},backend:e});return i.dispose(),e.disposeIntermediateTensorInfo(a),u}if(o.dtype==="complex64"){let i=Sl({inputs:{input:o},backend:e}),a=kT({inputs:{x:i},backend:e,attrs:{dtype:s}});return e.disposeIntermediateTensorInfo(i),a}if(!x.hasEncodingLoss(o.dtype,s)){let i=Ke({inputs:{x:o},backend:e});return{dataId:i.dataId,shape:i.shape,dtype:s}}if(s==="int32")return BL(o,e);if(s==="bool"){let i=e.makeTensorInfo([],"bool",x.getTypedArrayFromDType("bool",1)),u=ST({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 VL={kernelName:io,backendName:"webgl",kernelFunc:kT};var GL="return ceil(x);",vet=Ct({opSnippet:GL,packedOpSnippet:GL,cpuKernelImpl:ZM}),WL={kernelName:es,backendName:"webgl",kernelFunc:vet};var jw=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 Xw=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 Cet(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{clipValueMin:s,clipValueMax:i}=n,a;V().getBool("WEBGL_PACK_CLIP")?a=new Xw(o.shape):a=new jw(o.shape);let u=[[s],[i]];return e.runWebGLProgram(a,[o],o.dtype,u)}var UL={kernelName:ao,backendName:"webgl",kernelFunc:Cet};var Yw=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 HL(r,t){return{dataId:t.dataId,dtype:t.dtype,shape:r.shape}}function Iet(r){let{inputs:t,backend:e}=r,{x:n}=t,o=e.texData.get(n.dataId),s=new Yw(n.shape),i=[HL(n,o.complexTensorInfos.real),HL(n,o.complexTensorInfos.imag)];return e.runWebGLProgram(s,i,i[0].dtype)}var qL={kernelName:Rl,backendName:"webgl",kernelFunc:Iet};var Zw=class{constructor(t){this.outputShape=[],this.outputShape=S.computeOutShape(t,1),this.variableNames=t.map((i,a)=>`T${a}`);let e=new Array(t.length-1);e[0]=t[0][1];for(let i=1;i<e.length;i++)e[i]=e[i-1]+t[i][1];let n=[`if (yC < ${e[0]}) setOutput(getT0(yR, yC));`];for(let i=1;i<e.length;i++){let a=e[i-1];n.push(`else if (yC < ${e[i]}) setOutput(getT${i}(yR, yC-${a}));`)}let o=e.length,s=e[e.length-1];n.push(`else setOutput(getT${o}(yR, yC-${s}));`),this.userCode=`
void main() {
ivec2 coords = getOutputCoords();
int yR = coords.x;
int yC = coords.y;
${n.join(`
`)}
}
`}};var Qw=class{constructor(t,e){this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[],this.outputShape=S.computeOutShape(t,e);let n=this.outputShape,o=n.length,s=Gt(o),i=nr("coords",o),a=["x","y","z","w","u","v"].slice(0,o);this.variableNames=t.map((h,g)=>`T${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}(${Jw(a,l,g)}),
vec2(${Jw(c,l,g)}));
}`}let f=u.length,d=u[u.length-1];m+=`
return getChannel(
getT${f}(${Jw(a,l,d)}),
vec2(${Jw(c,l,d)}));`,this.userCode=`
float getValue(${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 Jw(r,t,e){let n=r.indexOf(t);return r.map((s,i)=>i===n?`${s} - ${e}`:s).join()}function op(r){let{inputs:t,backend:e}=r,{input:n}=t,o=e.texData.get(n.dataId);return Ke({inputs:{x:o.complexTensorInfos.imag},backend:e})}var KL={kernelName:Wp,backendName:"webgl",kernelFunc:op};function sp(r,t,e){let n=r[0].dtype;if(n==="complex64"){let c=r.map(h=>Sl({inputs:{input:h},backend:e})),p=r.map(h=>op({inputs:{input:h},backend:e})),m=sp(c,t,e),f=sp(p,t,e),d=Rn({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=S.computeOutShape(c.map(y=>y.shape),1),f=c[0].shape[0]===1,d=JM(p,m,n,f),h=S.computeOutShape(r.map(y=>y.shape),t),g=e.makeTensorInfo(h,n,d);return c.forEach(y=>e.disposeIntermediateTensorInfo(y)),g}if(r.length>V().getNumber("WEBGL_MAX_TEXTURES_IN_SHADER")){let c=Math.floor(r.length/2),p=sp(r.slice(0,c),t,e),m=sp(r.slice(c),t,e),f=sp([p,m],t,e);return e.disposeIntermediateTensorInfo(p),e.disposeIntermediateTensorInfo(m),f}if(V().getBool("WEBGL_PACK_ARRAY_OPERATIONS")&&r[0].shape.length>1){let c=new Qw(r.map(p=>p.shape),t);return e.runWebGLProgram(c,r,n)}let{tensors2D:s,outShape:i}=ket(r,t,e),a=new Zw(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 ket(r,t,e){let n=S.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 NT(r){let{inputs:t,backend:e,attrs:n}=r,{axis:o}=n,s=x.parseAxisParam(o,t[0].shape)[0],i=S.computeOutShape(t.map(l=>l.shape),s);if(x.sizeFromShape(i)===0)return e.makeTensorInfo(i,t[0].dtype,[]);let a=t.filter(l=>x.sizeFromShape(l.shape)>0);if(a.length===1)return Ke({inputs:{x:a[0]},backend:e});let u=a.map(l=>l.shape);return S.assertParamsConsistent(u,s),sp(a,s,e)}var jL={kernelName:Ci,backendName:"webgl",kernelFunc:NT};var vd=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="",k="";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}
}
`,k="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}
${k}
setOutput(result);
}
`}},tv=class{constructor(t){this.variableNames=["x","W"],this.outputShape=t.outShape;let e=t.padInfo.front,n=t.padInfo.top,o=t.padInfo.left,s=t.strideDepth,i=t.strideHeight,a=t.strideWidth,u=t.dilationDepth,l=t.dilationHeight,c=t.dilationWidth,p=t.filterDepth,m=t.filterHeight,f=t.filterWidth,d=Math.floor(t.inChannels/4)*4,h=t.inChannels%4;this.userCode=`
const ivec3 strides = ivec3(${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 ev=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=qe(),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 rv({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>CT)&&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),k={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(bu(l.shape,k.shape),()=>`packed reshape ${l.shape} to ${k.shape} isn't free`);let $=ut({inputs:{x:t},backend:n,attrs:{shape:[1,e.inChannels,e.outChannels]}});y.push($);let D=np({a:k,b:$,backend:n,transposeA:d,transposeB:h,bias:o,activation:a,preluActivationWeights:s,leakyreluAlpha:i}),R=n.texData.get(D.dataId);x.assert(R.isPacked,()=>"batchMatMul result is expected to be packed"),l.shape=E,R.shape=e.outShape,g=Ke({inputs:{x:D},backend:n}),g.shape=e.outShape,y.push(D)}else{let v=f?u[0]*u[1]*u[2]:u[0]*u[2]*u[3],k=ut({inputs:{x:r},backend:n,attrs:{shape:[1,v,e.inChannels]}}),E=ut({inputs:{x:t},backend:n,attrs:{shape:[1,e.inChannels,e.outChannels]}}),$=np({a:k,b:E,transposeA:d,transposeB:h,backend:n,bias:o,activation:a,preluActivationWeights:s,leakyreluAlpha:i});g=ut({inputs:{x:$},backend:n,attrs:{shape:e.outShape}}),y.push(k),y.push(E),y.push($)}for(let v of y)n.disposeIntermediateTensorInfo(v);return g}function nv({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=[],k=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(k),v.push(E);let $=new ev(y,e),D=[k.shape,[e.padInfo.top,e.padInfo.left],[e.strideHeight,e.strideWidth],[e.dilationHeight,e.dilationWidth],[e.inChannels],[e.filterWidth*e.inChannels],[e.outWidth]],R=n.runWebGLProgram($,[k],"float32",D),P=ut({inputs:{x:R},backend:n,attrs:{shape:[1,y[0],y[1]]}});v.push(R),v.push(P);let W=o!=null,U=s!=null,q=a==="leakyrelu",K=a?Cu(a,!0):null,j=new wd(P.shape,E.shape,[1,g,e.outChannels],b,w,W,K,U,q),Q=[P,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],ot=ut({inputs:{x:rt},backend:n,attrs:{shape:X}});v.push(rt);for(let st of v)n.disposeIntermediateTensorInfo(st);return ot}function Net(r){let{inputs:t,backend:e,attrs:n}=r,{x:o,filter:s}=t,{strides:i,pad:a,dataFormat:u,dilations:l,dimRoundingMode:c}=n,p=S.convertConv2DDataFormat(u),m=S.computeConv2DInfo(o.shape,s.shape,i,l,a,c,!1,p),f;if(m.filterHeight===1&&m.filterWidth===1&&m.dilationHeight===1&&m.dilationWidth===1&&m.strideHeight===1&&m.strideWidth===1&&(m.padInfo.type==="SAME"||m.padInfo.type==="VALID"))f=rv({x:o,filter:s,convInfo:m,backend:e});else if(V().getBool("WEBGL_CONV_IM2COL")&&o.shape[0]===1)f=nv({x:o,filter:s,convInfo:m,backend:e});else{let h=new vd(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 XL={kernelName:rs,backendName:"webgl",kernelFunc:Net};var ov=class{constructor(t){this.variableNames=["x","dy"],this.outputShape=t.filterShape;let e=t.strideHeight,n=t.strideWidth,o=t.padInfo.top,s=t.padInfo.left,i=t.dataFormat==="channelsLast";this.userCode=`
void main() {
ivec4 coords = getOutputCoords();
int wR = coords.x;
int wC = coords.y;
int d1 = coords.z;
int d2 = coords.w;
// Convolve x(?, ?, d1) with dy(:, :, d2) to get dw(wR, wC, d1, d2).
// ? = to be determined. : = across all values in that axis.
float dotProd = 0.0;
for (int b = 0; b < ${t.batchSize}; b++) {
for (int yR = 0; yR < ${t.outHeight}; yR++) {
int xR = wR + yR * ${e} - ${o};
if (xR < 0 || xR >= ${t.inHeight}) {
continue;
}
for (int yC = 0; yC < ${t.outWidth}; yC++) {
int xC = wC + yC * ${n} - ${s};
if (xC < 0 || xC >= ${t.inWidth}) {
continue;
}
if (${i}) {
float dyValue = getDy(b, yR, yC, d2);
float xValue = getX(b, xR, xC, d1);
dotProd += (xValue * dyValue);
} else {
float dyValue = getDy(b, d2, yR, yC);
float xValue = getX(b, d1, xR, xC);
dotProd += (xValue * dyValue);
}
}
}
}
setOutput(dotProd);
}
`}},sv=class{constructor(t){this.variableNames=["dy","W"],this.outputShape=t.inShape;let e=t.filterHeight,n=t.filterWidth,o=t.strideHeight,s=t.strideWidth,i=t.dataFormat==="channelsLast",a=e-1-t.padInfo.top,u=n-1-t.padInfo.left,l=i?1:2,c=i?2:3,p=i?3:1;this.userCode=`
const ivec2 pads = ivec2(${a}, ${u});
void main() {
ivec4 coords = getOutputCoords();
int batch = coords[0];
int d1 = coords[${p}];
ivec2 dyCorner = ivec2(coords[${l}], coords[${c}]) - pads;
int dyRCorner = dyCorner.x;
int dyCCorner = dyCorner.y;
// Convolve dy(?, ?, d2) with w(:, :, d1, d2) to compute dx(xR, xC, d1).
// ? = to be determined. : = across all values in that axis.
float dotProd = 0.0;
for (int wR = 0; wR < ${e}; wR++) {
float dyR = float(dyRCorner + wR) / ${o}.0;
if (dyR < 0.0 || dyR >= ${t.outHeight}.0 || fract(dyR) > 0.0) {
continue;
}
int idyR = int(dyR);
int wRPerm = ${e} - 1 - wR;
for (int wC = 0; wC < ${n}; wC++) {
float dyC = float(dyCCorner + wC) / ${s}.0;
if (dyC < 0.0 || dyC >= ${t.outWidth}.0 ||
fract(dyC) > 0.0) {
continue;
}
int idyC = int(dyC);
int wCPerm = ${n} - 1 - wC;
for (int d2 = 0; d2 < ${t.outChannels}; d2++) {
if (${i}) {
float xValue = getDy(batch, idyR, idyC, d2);
float wValue = getW(wRPerm, wCPerm, d1, d2);
dotProd += xValue * wValue;
} else {
float xValue = getDy(batch, d2, idyR, idyC);
float wValue = getW(wRPerm, wCPerm, d1, d2);
dotProd += xValue * wValue;
}
}
}
}
setOutput(dotProd);
}
`}},iv=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 >= ${t.inWidth}) {
continue;
}
float dyValue = getDy(b, yF, yR, yC, d2);
float xValue = getX(b, xF, xR, xC, d1);
dotProd += (xValue * dyValue);
}
}
}
}
setOutput(dotProd);
}
`}},av=class{constructor(t){this.variableNames=["dy","W"],this.outputShape=t.inShape;let e=t.filterDepth,n=t.filterHeight,o=t.filterWidth,s=t.strideDepth,i=t.strideHeight,a=t.strideWidth,u=e-1-t.padInfo.front,l=n-1-t.padInfo.top,c=o-1-t.padInfo.left;this.userCode=`
const ivec3 pads = ivec3(${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 Tet(r){let{inputs:t,backend:e,attrs:n}=r,{x:o,dy:s}=t,{strides:i,pad:a,dataFormat:u,dimRoundingMode:l,filterShape:c}=n,p=S.convertConv2DDataFormat(u),m=S.computeConv2DInfo(o.shape,c,i,1,a,l,!1,p),f=new ov(m);return e.runWebGLProgram(f,[o,s],"float32")}var YL={kernelName:Dp,backendName:"webgl",kernelFunc:Tet};function _et(r){let{inputs:t,backend:e,attrs:n}=r,{dy:o,filter:s}=t,{inputShape:i,strides:a,pad:u,dataFormat:l,dimRoundingMode:c}=n,p=S.convertConv2DDataFormat(l),m=S.computeConv2DInfo(i,s.shape,a,1,u,c,!1,p),f=new sv(m);return e.runWebGLProgram(f,[o,s],"float32")}var ZL={kernelName:ns,backendName:"webgl",kernelFunc:_et};function Eet(r){let{inputs:t,backend:e,attrs:n}=r,{x:o,filter:s}=t,{strides:i,pad:a,dilations:u}=n,l=S.computeConv3DInfo(o.shape,s.shape,i,u,a),c=new tv(l);return e.runWebGLProgram(c,[o,s],"float32")}var JL={kernelName:Fl,backendName:"webgl",kernelFunc:Eet};function Aet(r){let{inputs:t,backend:e,attrs:n}=r,{x:o,dy:s}=t,{strides:i,pad:a,filterShape:u}=n,l=S.computeConv3DInfo(o.shape,u,i,1,a),c=new iv(l);return e.runWebGLProgram(c,[o,s],"float32")}var QL={kernelName:Rp,backendName:"webgl",kernelFunc:Aet};function $et(r){let{inputs:t,backend:e,attrs:n}=r,{dy:o,filter:s}=t,{pad:i,strides:a,inputShape:u}=n,l=S.computeConv3DInfo(u,s.shape,a,1,i),c=new av(l);return e.runWebGLProgram(c,[o,s],"float32")}var t3={kernelName:Fp,backendName:"webgl",kernelFunc:$et};var Det=Lo+`
return cos(x);
`,Ret=Ct({opSnippet:Det}),e3={kernelName:os,backendName:"webgl",kernelFunc:Ret};var Fet=`
float e2x = exp(-x);
return (e2x + 1.0 / e2x) / 2.0;
`,Oet=Ct({opSnippet:Fet}),r3={kernelName:ss,backendName:"webgl",kernelFunc:Oet};var lv=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) * ${d}`],[w,v,k]=m>1?[`${(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 = ${k};
if( in_x < 0.0 || in_x > ${h} ) {
setOutput(float(${s}));
return;
}
vec2 sourceFracIndexCR = vec2(in_x,in_y);
if(${f} == 1) {
// Compute the four integer indices.
ivec2 sourceFloorCR = ivec2(sourceFracIndexCR);
ivec2 sourceCeilCR = ivec2(ceil(sourceFracIndexCR));
float topLeft = getImage(b, sourceFloorCR.y, sourceFloorCR.x, d);
float bottomLeft = getImage(b, sourceCeilCR.y, sourceFloorCR.x, d);
float topRight = getImage(b, sourceFloorCR.y, sourceCeilCR.x, d);
float bottomRight = getImage(b, sourceCeilCR.y, sourceCeilCR.x, d);
vec2 fracCR = sourceFracIndexCR - vec2(sourceFloorCR);
float top = topLeft + (topRight - topLeft) * fracCR.x;
float bottom = bottomLeft + (bottomRight - bottomLeft) * fracCR.x;
float newValue = top + (bottom - top) * fracCR.y;
setOutput(newValue);
} else {
// Compute the coordinators of nearest neighbor point.
ivec2 sourceNearestCR = ivec2(floor(
sourceFracIndexCR + vec2(0.5,0.5)));
float newValue = getImage(b, sourceNearestCR.y, sourceNearestCR.x, d);
setOutput(newValue);
}
}
`}};var Met=r=>{let{inputs:t,backend:e,attrs:n}=r,{image:o,boxes:s,boxInd:i}=t,{cropSize:a,method:u,extrapolationValue:l}=n,c=new lv(o.shape,s.shape,a,u,l);return e.runWebGLProgram(c,[o,s,i],"float32")},n3={kernelName:pa,backendName:"webgl",kernelFunc:Met};var Tg=class{constructor(t,e,n){this.variableNames=["x"],this.customUniforms=[{name:"index",type:"float"}],this.outputShape=t;let o=t.length,s=e?"1.0":`getX(${o3(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() {
${Gt(o)} coords = getOutputCoords();
int end = ${s3(o,"coords")};
float val = ${s};
int pow2 = int(pow(2.0, index));
if (${a}) {
int idx = ${u};
${s3(o,"coords")} = idx;
val *= getX(${o3(o,"coords")});
}
setOutput(val);
}
`}};function o3(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 product for rank ${r} is not yet supported`)}function s3(r,t){if(r===1)return`${t}`;if(r===2)return`${t}.y`;if(r===3)return`${t}.z`;if(r===4)return`${t}.w`;throw Error(`Cumulative product for rank ${r} is not yet supported`)}function Pet(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{axis:s,exclusive:i,reverse:a}=n,u=o.shape.length,l=S.getAxesPermutation([s],u),c=o;l!=null&&(c=Ae({inputs:{x:o},backend:e,attrs:{perm:l}}));let p=S.getInnerMostAxes(1,u)[0];if(p!==u-1)throw new Error(`WebGL cumprod shader expects an inner-most axis=${o.shape.length-1} but got axis=${s}`);let m=c.shape[p],f=Ke({inputs:{x:c},backend:e});for(let d=0;d<=Math.ceil(Math.log2(m))-1;d++){let h=new Tg(c.shape,!1,a),g=[[d]],y=f;f=e.runWebGLProgram(h,[f],f.dtype,g),e.disposeIntermediateTensorInfo(y)}if(i){let d=new Tg(c.shape,i,a),h=f;f=e.runWebGLProgram(d,[f],f.dtype),e.disposeIntermediateTensorInfo(h)}if(l!=null){let d=S.getUndoAxesPermutation(l),h=Ae({inputs:{x:f},backend:e,attrs:{perm:d}});return e.disposeIntermediateTensorInfo(f),e.disposeIntermediateTensorInfo(c),h}return f}var i3={kernelName:ca,backendName:"webgl",kernelFunc:Pet};var _g=class{constructor(t,e,n){this.variableNames=["x"],this.customUniforms=[{name:"index",type:"float"}],this.outputShape=t;let o=t.length,s=e?"0.0":`getX(${a3(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() {
${Gt(o)} coords = getOutputCoords();
int end = ${l3(o,"coords")};
float val = ${s};
int pow2 = int(pow(2.0, index));
if (${a}) {
int idx = ${u};
${l3(o,"coords")} = idx;
val += getX(${a3(o,"coords")});
}
setOutput(val);
}
`}};function a3(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 ${r} is not yet supported`)}function l3(r,t){if(r===1)return`${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 ${r} is not yet supported`)}function Let(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{axis:s,exclusive:i,reverse:a}=n,u=o.shape.length,l=S.getAxesPermutation([s],u),c=o;l!=null&&(c=Ae({inputs:{x:o},backend:e,attrs:{perm:l}}));let p=S.getInnerMostAxes(1,u)[0];if(p!==u-1)throw new Error(`WebGL cumsum shader expects an inner-most axis=${o.shape.length-1} but got axis=${s}`);let m=c.shape[p],f=Ke({inputs:{x:c},backend:e});for(let d=0;d<=Math.ceil(Math.log2(m))-1;d++){let h=new _g(c.shape,!1,a),g=[[d]],y=f;f=e.runWebGLProgram(h,[f],f.dtype,g),e.disposeIntermediateTensorInfo(y)}if(i){let d=new _g(c.shape,i,a),h=f;f=e.runWebGLProgram(d,[f],f.dtype),e.disposeIntermediateTensorInfo(h)}if(l!=null){let d=S.getUndoAxesPermutation(l),h=Ae({inputs:{x:f},backend:e,attrs:{perm:d}});return e.disposeIntermediateTensorInfo(f),e.disposeIntermediateTensorInfo(c),h}return f}var u3={kernelName:is,backendName:"webgl",kernelFunc:Let};function zet(r){let{inputs:t,backend:e,attrs:n}=r,{x:o,weights:s}=t,{size:i,binaryOutput:a}=n;if(o.shape.length===1){let u=e.readSync(o.dataId),l=e.readSync(s.dataId),c=kw(u,l,s.dtype,s.shape,i);return e.makeTensorInfo([i],s.dtype,c)}else if(o.shape.length===2){let u=e.bufferSync(o),l=e.bufferSync(s),c=YM(u,l,i,a);return e.makeTensorInfo(c.shape,s.dtype,c.values)}throw new Error(`Error in denseBincount: input must be at most rank 2, but got rank${o.shape.length}.`)}var c3={kernelName:Op,backendName:"webgl",kernelFunc:zet};var uv=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 Bet(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 uv(d,s,i);return e.runWebGLProgram(h,[o],o.dtype)}var p3={kernelName:ma,backendName:"webgl",kernelFunc:Bet};var Cd=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}
${c}
setOutput(result);
}
`}};var Id=class{constructor(t,e=!1,n=null,o=!1,s=!1){this.variableNames=["x","W"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"pads",type:"ivec2"},{name:"strides",type:"ivec2"},{name:"dilations",type:"ivec2"},{name:"inDims",type:"ivec2"}],this.outputShape=t.outShape,this.enableShapeUniforms=De(this.outputShape.length);let i=t.outChannels/t.inChannels,a=t.padInfo.left,u=t.strideWidth,l=t.dilationWidth,c=t.filterHeight,p=t.filterWidth,m=p,f=`
int xR; int xC; int xCOffset;
vec4 wTexel; vec4 previous; vec4 final;`;for(let y=0;y<p;y++)f+=`
vec4 xTexelC${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(S.eitherStridesOrDilationsAreOne(i,c),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${i} and dilations '${c}'`);let p=S.computeConv2DInfo(o.shape,s.shape,i,c,a,l,!0),m;V().getBool("WEBGL_PACK_DEPTHWISECONV")&&p.strideWidth<=2&&p.outChannels/p.inChannels===1?m=new Id(p):m=new Cd(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 m3={kernelName:as,backendName:"webgl",kernelFunc:Vet};var cv=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 >= ${t.inWidth}) {
continue;
}
float dyValue = getDy(b, yR, yC, d2);
float xValue = getX(b, xR, xC, d1);
dotProd += (xValue * dyValue);
}
}
}
setOutput(dotProd);
}
`}},pv=class{constructor(t){this.variableNames=["dy","W"],this.outputShape=t.inShape;let e=t.filterHeight,n=t.filterWidth,o=t.strideHeight,s=t.strideWidth,i=e-1-t.padInfo.top,a=n-1-t.padInfo.left,u=t.outChannels/t.inChannels;this.userCode=`
const ivec2 pads = ivec2(${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 * ${u} + dm;
float xValue = getDy(batch, idyR, idyC, d2);
float wValue = getW(wRPerm, wCPerm, d1, dm);
dotProd += xValue * wValue;
}
}
}
setOutput(dotProd);
}
`}};function Get(r){let{inputs:t,backend:e,attrs:n}=r,{x:o,dy:s}=t,{strides:i,dilations:a,pad:u,dimRoundingMode:l,filterShape:c}=n,p=S.computeConv2DInfo(o.shape,c,i,a,u,l,!0),m=new cv(p);return e.runWebGLProgram(m,[o,s],"float32")}var f3={kernelName:Mp,backendName:"webgl",kernelFunc:Get};function Wet(r){let{inputs:t,backend:e,attrs:n}=r,{dy:o,filter:s}=t,{strides:i,dilations:a,pad:u,dimRoundingMode:l,inputShape:c}=n,p=S.computeConv2DInfo(c,s.shape,i,a,u,l,!0),m=new pv(p);return e.runWebGLProgram(m,[o,s],"float32")}var d3={kernelName:Pp,backendName:"webgl",kernelFunc:Wet};var mv=class{constructor(t){this.variableNames=["X"],this.outputShape=[t,t],this.userCode=`
void main() {
ivec2 coords = getOutputCoords();
float val = coords[0] == coords[1] ? getX(coords[0]) : 0.0;
setOutput(val);
}
`}};function Uet(r){let{inputs:t,backend:e}=r,{x:n}=t,o=[...n.shape,...n.shape],s=x.sizeFromShape(n.shape),i=ut({inputs:{x:n},backend:e,attrs:{shape:[s]}}),a=new mv(s),u=e.runWebGLProgram(a,[i],i.dtype),l=ut({inputs:{x:u},backend:e,attrs:{shape:o}});return e.disposeIntermediateTensorInfo(i),e.disposeIntermediateTensorInfo(u),l}var h3={kernelName:Lp,backendName:"webgl",kernelFunc:Uet};var fv=class{constructor(t){this.variableNames=["x","W"],this.outputShape=t.outShape;let{inHeight:e,inWidth:n,padInfo:o,strideHeight:s,strideWidth:i,filterHeight:a,filterWidth:u,dilationHeight:l,dilationWidth:c}=t,{top:p,left:m}=o;this.userCode=`
const ivec2 strides = ivec2(${s}, ${i});
const ivec2 pads = ivec2(${p}, ${m});
const float neg_infinity = -3.4e38;
void main() {
ivec4 coords = getOutputCoords();
int batch = coords.x;
int d1 = coords.w;
ivec2 outTopLeftCorner =
coords.yz * strides - pads;
int hBeg = outTopLeftCorner.x;
int wBeg = outTopLeftCorner.y;
float curVal = neg_infinity;
for (int h = 0; h < ${a}; h++) {
int hIn = hBeg + h * ${l};
if (hIn >= 0 && hIn < ${e}) {
for (int w = 0; w < ${u}; w++) {
int wIn = wBeg + w * ${c};
if (wIn >= 0 && wIn < ${n}) {
float xVal = getX(batch, hIn, wIn, d1);
float wVal = getW(h, w, d1);
float val = xVal + wVal;
if (val > curVal) {
curVal = val;
}
}
}
}
}
float result = curVal;
setOutput(result);
}
`}};function Het(r){let{inputs:t,backend:e,attrs:n}=r,{x:o,filter:s}=t,{strides:i,pad:a,dilations:u}=n,l=S.computeDilation2DInfo(o.shape,s.shape,i,a,"NHWC",u),c,p=new fv(l);c=e.runWebGLProgram(p,[o,s],"float32");let m=ut({inputs:{x:c},backend:e,attrs:{shape:l.outShape}});return e.disposeIntermediateTensorInfo(c),m}var g3={kernelName:Ol,backendName:"webgl",kernelFunc:Het};function qet(r){let{inputs:t,backend:e,attrs:n}=r,{equation:o}=n,s=t,{allDims:i,summedDims:a,idDims:u}=S.decodeEinsumEquation(o,s.length);S.checkEinsumDimSizes(i.length,u,s);let{path:l,steps:c}=S.getEinsumComputePath(a,u),p=c.length,m=null,f=i.length,d=[];for(let h=0;h<p;++h){for(let g of c[h]){let{permutationIndices:y,expandDims:b}=S.getEinsumPermutation(f,u[g]),w;S.isIdentityPermutation(y)?w=s[g]:(w=Ae({inputs:{x:s[g]},backend:e,attrs:{perm:y}}),d.push(w));let v=w.shape.slice();for(let k=0;k<b.length;++k)v.splice(b[k],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=kg({inputs:{a:w,b:m},backend:e}),d.push(m))}h<p-1&&(l[h]>=0&&(m=rp({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 x3={kernelName:zp,backendName:"webgl",kernelFunc:qet};var Ket="return (x >= 0.0) ? x : (exp(x) - 1.0);",jet=`
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;
`,Xet=Ct({opSnippet:Ket,packedOpSnippet:jet}),y3={kernelName:us,backendName:"webgl",kernelFunc:Xet};var Yet="return (b >= 1.0) ? a : a * (b + 1.0);",Zet=`
vec4 bGTEZero = vec4(greaterThanEqual(b, vec4(0.)));
return (bGTEZero * a) + ((vec4(1.0) - bGTEZero) * (a * (b + vec4(1.0))));
`,Jet=r=>{let{inputs:t,backend:e}=r,{dy:n,y:o}=t,s=V().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new Po(Zet,n.shape,o.shape):new ro(Yet,n.shape,o.shape);return e.runWebGLProgram(s,[n,o],n.dtype)},b3={kernelName:Bp,backendName:"webgl",kernelFunc:Jet};var Qet=`
return vec4(equal(a, b));
`,trt="return float(a == b);",ert=le({opSnippet:trt,packedOpSnippet:Qet,dtype:"bool",cpuKernelImpl:QM}),w3={kernelName:da,backendName:"webgl",kernelFunc:ert};var rrt=`
// Error function is calculated approximately with elementary function.
// See "Handbook of Mathematical Functions with Formulas,
// Graphs, and Mathematical Tables", Abramowitz and Stegun.
float p = ${S.ERF_P};
float a1 = ${S.ERF_A1};
float a2 = ${S.ERF_A2};
float a3 = ${S.ERF_A3};
float a4 = ${S.ERF_A4};
float a5 = ${S.ERF_A5};
float sign = sign(x);
x = abs(x);
float t = 1.0 / (1.0 + p * x);
return sign * (1.0 - (((((a5*t + a4)*t) + a3)*t + a2)*t + a1)*t*exp(-x*x));
`,nrt=Ct({opSnippet:rrt}),v3={kernelName:fa,backendName:"webgl",kernelFunc:nrt};var ort=Lo+`
return exp(x);
`,srt=`
vec4 result = exp(x);
bvec4 isNaN = isnan(x);
result.r = isNaN.r ? x.r : result.r;
result.g = isNaN.g ? x.g : result.g;
result.b = isNaN.b ? x.b : result.b;
result.a = isNaN.a ? x.a : result.a;
return result;
`,TT=Ct({opSnippet:ort,packedOpSnippet:srt,cpuKernelImpl:tP,dtype:"float32"}),C3={kernelName:cs,backendName:"webgl",kernelFunc:TT};function dv(r){let{inputs:t,attrs:e,backend:n}=r,{dim:o}=e,{input:s}=t,i=s.shape.length,a=s.shape.slice(),u=o;return o<0&&(x.assert(-(i+1)<=o,()=>`Axis must be in the interval [${-(i+1)}, ${i}]`),u=i+o+1),a.splice(u,0,1),ut({inputs:{x:s},backend:n,attrs:{shape:a}})}var I3={kernelName:Ii,backendName:"webgl",kernelFunc:dv};var S3="return exp(x) - 1.0;",irt=Ct({opSnippet:S3,packedOpSnippet:S3,cpuKernelImpl:eP}),k3={kernelName:ha,backendName:"webgl",kernelFunc:irt};var Eg=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 hv(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 Eg("real",u,t),c=new Eg("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=Rn({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 art(r){let{inputs:t,backend:e}=r,{input:n}=t;return hv(n,!1,e)}var N3={kernelName:Vp,backendName:"webgl",kernelFunc:art};var gv=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 kl(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 gv(n,o),a=[[o]];return t.runWebGLProgram(i,[],s,a)}}var T3={kernelName:Ml,backendName:"webgl",kernelFunc:kl};var xv=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 _3={kernelName:ga,backendName:"webgl",kernelFunc:({inputs:r,backend:t})=>{let{image:e}=r,n=t,o=new xv(e.shape);return n.runWebGLProgram(o,[e],e.dtype)}};var E3="return floor(x);",lrt=Ct({opSnippet:E3,packedOpSnippet:E3,cpuKernelImpl:rP}),A3={kernelName:ps,backendName:"webgl",kernelFunc:lrt};var urt=`
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;
}
`,crt=`
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);
`,prt=le({opSnippet:urt,packedOpSnippet:crt,dtype:"int32"}),$3={kernelName:ms,backendName:"webgl",kernelFunc:prt};var yv=class{constructor(t){this.variableNames=["A"];let e=qe(),[n,o]=t;this.outputShape=t,this.userCode=`
void main() {
ivec3 coords = getOutputCoords();
int texR = coords[0];
int texC = coords[1];
int depth = coords[2];
vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${o}.0, ${n}.0);
vec4 values = ${e.texture2D}(A, uv);
float value;
if (depth == 0) {
value = values.r;
} else if (depth == 1) {
value = values.g;
} else if (depth == 2) {
value = values.b;
} else if (depth == 3) {
value = values.a;
}
setOutput(floor(value * 255.0 + 0.5));
}
`}};var bv=class{constructor(t){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0;let e=qe(),[n,o]=t;this.outputShape=t,this.userCode=`
void main() {
ivec3 coords = getOutputCoords();
int texR = coords[0];
int texC = coords[1];
int depth = coords[2];
vec4 result = vec4(0.);
for(int row=0; row<=1; row++) {
for(int col=0; col<=1; col++) {
texC = coords[1] + row;
depth = coords[2] + col;
vec2 uv = (vec2(texC, texR) + halfCR) /
vec2(${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);
}
}
${e.output} = result;
}
`}};var D3={kernelName:qd,backendName:"webgl",kernelFunc:mrt},Sd;function mrt(r){let{inputs:t,backend:e,attrs:n}=r,{pixels:o}=t,{numChannels:s}=n,i=typeof HTMLVideoElement!="undefined"&&o instanceof HTMLVideoElement,a=typeof HTMLImageElement!="undefined"&&o instanceof HTMLImageElement,[u,l]=i?[o.videoWidth,o.videoHeight]:[o.width,o.height],c=[l,u],p=[l,u,s];(a||i)&&(Sd==null&&(Sd=document.createElement("canvas").getContext("2d")),Sd.canvas.width=u,Sd.canvas.height=l,Sd.drawImage(o,0,0,u,l),o=Sd.canvas);let m=e.makeTensorInfo(c,"int32");e.texData.get(m.dataId).usage=Kr.PIXELS,e.gpgpu.uploadPixelDataToTexture(e.getTexture(m.dataId),o);let f=V().getBool("WEBGL_PACK")?new bv(p):new yv(p),d=e.runWebGLProgram(f,[m],"int32");return e.disposeData(m.dataId),d}function frt(r){let{inputs:t,backend:e,attrs:n}=r,{x:o,filter:s,bias:i,preluActivationWeights:a}=t,{strides:u,pad:l,dataFormat:c,dilations:p,dimRoundingMode:m,activation:f,leakyreluAlpha:d}=n,h=S.convertConv2DDataFormat(c),g=S.computeConv2DInfo(o.shape,s.shape,u,p,l,m,!1,h),y,b=[];if(g.filterHeight===1&&g.filterWidth===1&&g.dilationHeight===1&&g.dilationWidth===1&&g.strideHeight===1&&g.strideWidth===1&&(g.padInfo.type==="SAME"||g.padInfo.type==="VALID"))y=rv({x:o,filter:s,convInfo:g,backend:e,bias:i,activation:f,preluActivationWeights:a,leakyreluAlpha:d});else if(V().getBool("WEBGL_CONV_IM2COL")&&o.shape[0]===1)y=nv({x:o,filter:s,convInfo:g,backend:e,bias:i,activation:f,preluActivationWeights:a,leakyreluAlpha:d});else{let v=i!=null,k=a!=null,E=f==="leakyrelu",$=f?Cu(f,!1):null,D=new vd(g,v,$,k,E),R=[o,s];if(i&&R.push(i),a&&R.push(a),E){let P=e.makeTensorInfo([],"float32",x.createScalarValue(d,"float32"));R.push(P),b.push(P)}y=e.runWebGLProgram(D,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 R3={kernelName:Mi,backendName:"webgl",kernelFunc:frt};function drt(r){let{inputs:t,backend:e,attrs:n}=r,{x:o,filter:s,bias:i,preluActivationWeights:a}=t,{strides:u,pad:l,dilations:c,dimRoundingMode:p,activation:m,leakyreluAlpha:f}=n,d=[],h=c;h==null&&(h=[1,1]),x.assert(S.eitherStridesOrDilationsAreOne(u,h),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${u} and dilations '${h}'`);let g=S.computeConv2DInfo(o.shape,s.shape,u,h,l,p,!0),y=V().getBool("WEBGL_PACK_DEPTHWISECONV")&&g.strideWidth<=2&&g.outChannels/g.inChannels===1,b=m?Cu(m,y):null,w=[o,s],v=i!=null,k=a!=null,E=m==="leakyrelu";if(v&&w.push(i),k&&w.push(a),E){let P=e.makeTensorInfo([],"float32",x.createScalarValue(f,"float32"));w.push(P),d.push(P)}let $;y?$=new Id(g,v,b,k,E):$=new Cd(g,v,b,k,E);let D=[[g.padInfo.top,g.padInfo.left],[g.strideHeight,g.strideWidth],[g.dilationHeight,g.dilationWidth],[g.inHeight,g.inWidth]],R=e.runWebGLProgram($,w,"float32",D);return d.forEach(P=>e.disposeIntermediateTensorInfo(P)),R}var F3={kernelName:Pi,backendName:"webgl",kernelFunc:drt};var wv=class{constructor(t,e,n){this.sliceDim=t,this.strides=e,this.variableNames=["x","indices"],this.outputShape=n;let o=Gt(e.length),s=Gt(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 hrt(r){let{inputs:t,backend:e}=r,{params:n,indices:o}=t,s=o.shape,i=s[s.length-1],a=x.sizeFromShape(n.shape),[u,l,c,p]=S.prepareAndValidate(n,o),m=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=nP(y,b,n.dtype,l,i,c,p,n.shape,a);return e.makeTensorInfo(u,n.dtype,w.values)}let d=new wv(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 O3={kernelName:xa,backendName:"webgl",kernelFunc:hrt};var vv=class{constructor(t,e){this.variableNames=["A","indices"],this.outputShape=e,this.rank=e.length;let n=Gt(this.rank),o=grt(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 grt(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 _T(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(V().get("DEBUG")){let b=e.readSync(s.dataId),w=o.shape[u];for(let v=0;v<b.length;++v){let k=b[v];x.assert(k<=w-1&&k>=0,()=>`GatherV2: the index value ${k} is not in [0, ${w-1}]`)}}let l=S.segment_util.collectGatherOpShapeInfo(o,s,u,a),c=x.sizeFromShape(s.shape),p=[],m=ut({inputs:{x:o},backend:e,attrs:{shape:[l.batchSize,l.outerSize,l.dimSize,l.sliceSize]}}),f=ut({inputs:{x:s},backend:e,attrs:{shape:[l.batchSize,c/l.batchSize]}});p.push(m),p.push(f);let d=[l.batchSize,l.outerSize,c/l.batchSize,l.sliceSize];if(e.shouldExecuteOnCPU([o,s])||o.dtype==="string"){let b=e.bufferSync(f),w=e.bufferSync(m),v=oP(w,b,d);return p.forEach(k=>e.disposeIntermediateTensorInfo(k)),e.makeTensorInfo(l.outputShape,v.dtype,v.values)}let h=new vv(m.shape,d),g=e.runWebGLProgram(h,[m,f],m.dtype);p.push(g);let y=ut({inputs:{x:g},backend:e,attrs:{shape:l.outputShape}});return p.forEach(b=>e.disposeIntermediateTensorInfo(b)),y}var M3={kernelName:Si,backendName:"webgl",kernelFunc:_T};var xrt="return float(a > b);",yrt=`
return vec4(greaterThan(a, b));
`,brt=le({opSnippet:xrt,packedOpSnippet:yrt,cpuKernelImpl:sP,dtype:"bool"}),P3={kernelName:ya,backendName:"webgl",kernelFunc:brt};var wrt="return float(a >= b);",vrt=`
return vec4(greaterThanEqual(a, b));
`,Crt=le({opSnippet:wrt,packedOpSnippet:vrt,dtype:"bool",cpuKernelImpl:iP}),L3={kernelName:ds,backendName:"webgl",kernelFunc:Crt};function Irt(r){let{inputs:t,backend:e}=r,{input:n}=t;return hv(n,!0,e)}var z3={kernelName:Gp,backendName:"webgl",kernelFunc:Irt};var Srt="return float(!isnan(x) && !isinf(x));",krt=Ct({opSnippet:Srt,dtype:"bool"}),B3={kernelName:ba,backendName:"webgl",kernelFunc:krt};var Nrt="return float(isinf(x));",Trt=Ct({opSnippet:Nrt,dtype:"bool"}),V3={kernelName:wa,backendName:"webgl",kernelFunc:Trt};var _rt="return float(isnan(x));",Ert=Ct({opSnippet:_rt,dtype:"bool"}),G3={kernelName:va,backendName:"webgl",kernelFunc:Ert};var Art="return float(a < b);",$rt=`
return vec4(lessThan(a, b));
`,Drt=le({opSnippet:Art,packedOpSnippet:$rt,cpuKernelImpl:aP,dtype:"bool"}),W3={kernelName:Ca,backendName:"webgl",kernelFunc:Drt};var Rrt="return float(a <= b);",Frt=`
return vec4(lessThanEqual(a, b));
`,Ort=le({opSnippet:Rrt,packedOpSnippet:Frt,cpuKernelImpl:lP,dtype:"bool"}),U3={kernelName:Ia,backendName:"webgl",kernelFunc:Ort};function Mrt(r){let{backend:t,attrs:e}=r,{start:n,stop:o,num:s}=e,i=uP(n,o,s);return t.makeTensorInfo([i.length],"float32",i)}var H3={kernelName:Up,backendName:"webgl",kernelFunc:Mrt};var Prt=Lo+`
return x < 0.0 ? 0./0. : log(x);
`,Lrt=`
vec4 result = log(x);
bvec4 isNaN = isnan(x);
result.r = isNaN.r ? x.r : (x.r < 0.0 ? 0./0. : result.r);
result.g = isNaN.g ? x.g : (x.g < 0.0 ? 0./0. : result.g);
result.b = isNaN.b ? x.b : (x.b < 0.0 ? 0./0. : result.b);
result.a = isNaN.a ? x.a : (x.a < 0.0 ? 0./0. : result.a);
return result;
`,zrt=Ct({opSnippet:Prt,packedOpSnippet:Lrt,cpuKernelImpl:cP}),q3={kernelName:gs,backendName:"webgl",kernelFunc:zrt};var Brt=Lo+`
return log(1.0 + x);
`,Vrt=Ct({opSnippet:Brt}),K3={kernelName:Sa,backendName:"webgl",kernelFunc:Vrt};var Grt="return float(a >= 1.0 && b >= 1.0);",Wrt=`
return vec4(
vec4(greaterThanEqual(a, vec4(1.0))) *
vec4(greaterThanEqual(b, vec4(1.0))));
`,Urt=le({opSnippet:Grt,packedOpSnippet:Wrt,dtype:"bool"}),j3={kernelName:ka,backendName:"webgl",kernelFunc:Urt};var Hrt="return float(!(x >= 1.0));",qrt=Ct({opSnippet:Hrt}),X3={kernelName:Mu,backendName:"webgl",kernelFunc:qrt};var Krt="return float(a >= 1.0 || b >= 1.0);",jrt=`
return min(
vec4(greaterThanEqual(a, vec4(1.0))) +
vec4(greaterThanEqual(b, vec4(1.0))),
vec4(1.0));
`,Xrt=le({opSnippet:Krt,packedOpSnippet:jrt,dtype:"bool"}),Y3={kernelName:Pu,backendName:"webgl",kernelFunc:Xrt};var Cv=class{constructor(t,e,n,o,s){this.variableNames=["x"],this.outputShape=[];let i=e,a=t[3]-1;this.outputShape=t;let u,l=`float(${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 * ${u};
setOutput(val);
}
`}};var Iv=class{constructor(t,e,n,o,s){this.variableNames=["x"],this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0;let i=e,a=t[3]-1;this.outputShape=t;let u,l=`float(${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 Yrt=r=>{let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{depthRadius:s,bias:i,alpha:a,beta:u}=n,l=V().getBool("WEBGL_PACK_NORMALIZATION")?new Iv(o.shape,s,i,a,u):new Cv(o.shape,s,i,a,u);return e.runWebGLProgram(l,[o],o.dtype)},Z3={kernelName:Pl,backendName:"webgl",kernelFunc:Yrt};var Sv=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 Zrt=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 Sv(o.shape,a,u,l,c);return e.runWebGLProgram(p,[o,s,i],o.dtype)},J3={kernelName:Hp,backendName:"webgl",kernelFunc:Zrt};function Q3(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=Hn(a,r.dtype,"max",n),l=ut({inputs:{x:u},attrs:{shape:e},backend:n});return n.disposeIntermediateTensorInfo(a),n.disposeIntermediateTensorInfo(u),l}function ET(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{reductionIndices:s,keepDims:i}=n,a=o.shape.length,u=x.parseAxisParam(s,o.shape),l=u,c=S.getAxesPermutation(l,a),p=c!=null,m=e.shouldExecuteOnCPU([o]),f=o;if(p){if(m){let w=e.texData.get(f.dataId).values,v=new Array(a);for(let $=0;$<v.length;$++)v[$]=o.shape[c[$]];let k=tp(w,o.shape,o.dtype,c,v);f=e.makeTensorInfo(v,o.dtype);let E=e.texData.get(f.dataId);E.values=k}else f=Iu(o,c,e);l=S.getInnerMostAxes(l.length,a)}S.assertAxesAreInnerMostDims("max",l,a);let[d,h]=S.computeOutAndReduceShapes(f.shape,l),g=d;i&&(g=S.expandShapeToKeepDim(d,u));let y;if(m){let w=e.texData.get(f.dataId).values,v=pP(w,x.sizeFromShape(h),g,o.dtype);y=e.makeTensorInfo(g,o.dtype);let k=e.texData.get(y.dataId);k.values=v}else y=Q3(f,h,g,e);return p&&e.disposeIntermediateTensorInfo(f),y}var tz={kernelName:xs,backendName:"webgl",kernelFunc:ET};var Jrt=Dw+`
return max(a, b);
`,Qrt=`
vec4 result = vec4(max(a, b));
vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
`+vu+`
return result;
`,tnt=le({opSnippet:Jrt,packedOpSnippet:Qrt,cpuKernelImpl:mP}),ez={kernelName:ys,backendName:"webgl",kernelFunc:tnt};function ent(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t;di(o,"maxPool");let{filterSize:s,strides:i,pad:a,dimRoundingMode:u}=n,l=1;x.assert(S.eitherStridesOrDilationsAreOne(i,l),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${i} and dilations '${l}'`);let c=S.computePool2DInfo(o.shape,s,i,l,a,u);if(c.filterWidth===1&&c.filterHeight===1&&x.arraysEqual(c.inShape,c.outShape))return Ke({inputs:{x:o},backend:e});let p=new gi(c,"max",!1);return e.runWebGLProgram(p,[o],o.dtype)}var rz={kernelName:bs,backendName:"webgl",kernelFunc:ent};function rnt(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{filterSize:s,strides:i,pad:a,dataFormat:u,dimRoundingMode:l}=n,c=[1,1,1],p=S.computePool3DInfo(o.shape,s,i,c,a,l,u),m=new Su(p,"max",!1);return e.runWebGLProgram(m,[o],o.dtype)}var nz={kernelName:Ll,backendName:"webgl",kernelFunc:rnt};var kv=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 * ${i} + wC;
float mask = float(maxPosValue == curPosValue ? 1.0 : 0.0);
dotProd += dyValue * mask;
}
}
setOutput(dotProd);
}
`}},Nv=class{constructor(t){this.variableNames=["dy","maxPos"],this.outputShape=t.inShape;let e=t.strideDepth,n=t.strideHeight,o=t.strideWidth,s=t.dilationDepth,i=t.dilationHeight,a=t.dilationWidth,u=t.effectiveFilterDepth,l=t.effectiveFilterHeight,c=t.effectiveFilterWidth,p=u-1-t.padInfo.front,m=l-1-t.padInfo.top,f=c-1-t.padInfo.left,d=u*l*c-1;this.userCode=`
const ivec3 pads = ivec3(${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 nnt(r){let{inputs:t,backend:e,attrs:n}=r,{dy:o,input:s}=t,i=s,{filterSize:a,strides:u,pad:l,dimRoundingMode:c}=n,p=[1,1,1],m=S.computePool3DInfo(i.shape,a,u,p,l,c),f=new Su(m,"max",!0),d=e.runWebGLProgram(f,[i],i.dtype),h=new Nv(m),g=e.runWebGLProgram(h,[o,d],i.dtype);return e.disposeIntermediateTensorInfo(d),g}var oz={kernelName:Kp,backendName:"webgl",kernelFunc:nnt};function ont(r){let{inputs:t,backend:e,attrs:n}=r,{dy:o,input:s,output:i}=t,a=s;di([s,i],"maxPoolGrad");let{filterSize:u,strides:l,pad:c,dimRoundingMode:p}=n,m=S.computePool2DInfo(a.shape,u,l,1,c,p),f=!0,d=new gi(m,"max",f),h=e.runWebGLProgram(d,[a],a.dtype),g=new kv(m),y=e.runWebGLProgram(g,[o,h],a.dtype);return e.disposeIntermediateTensorInfo(h),y}var sz={kernelName:qp,backendName:"webgl",kernelFunc:ont};function iz(r,t,e,n){let o=new gi(e,"max",!1),s=n.runWebGLProgram(o,[r],"float32");o=new gi(e,"max",!0,!0,t);let i=n.runWebGLProgram(o,[r],"float32");return[s,i]}var az={kernelName:jp,backendName:"webgl",kernelFunc:({inputs:r,attrs:t,backend:e})=>{let{x:n}=r,{filterSize:o,strides:s,pad:i,includeBatchInIndex:a}=t,u=e;x.assert(n.shape.length===4,()=>`Error in maxPool: input must be rank 4 but got rank ${n.shape.length}.`);let l=[1,1];x.assert(S.eitherStridesOrDilationsAreOne(s,l),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${s} and dilations '${l}'`);let c=S.computePool2DInfo(n.shape,o,s,l,i),[p,m]=iz(n,a,c,u);return[p,m]}};function lz(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=Hn(a,"float32","mean",n),l=ut({inputs:{x:u},attrs:{shape:e},backend:n});return n.disposeIntermediateTensorInfo(a),n.disposeIntermediateTensorInfo(u),l}var uz={kernelName:ws,backendName:"webgl",kernelFunc:({inputs:r,attrs:t,backend:e})=>{let{x:n}=r,{keepDims:o,axis:s}=t,i=e,a=n.shape.length,u=x.parseAxisParam(s,n.shape),l=u,c=S.getAxesPermutation(l,a),p=c!=null,m=i.shouldExecuteOnCPU([n]),f=[],d=n;if(p){if(m){let v=i.texData.get(d.dataId).values,k=new Array(a);for(let D=0;D<k.length;D++)k[D]=n.shape[c[D]];let E=tp(v,n.shape,n.dtype,c,k);d=i.makeTensorInfo(k,n.dtype);let $=i.texData.get(d.dataId);$.values=E}else d=Iu(n,c,i);f.push(d),l=S.getInnerMostAxes(l.length,a)}S.assertAxesAreInnerMostDims("sum",l,a);let[h,g]=S.computeOutAndReduceShapes(d.shape,l),y=h;o&&(y=S.expandShapeToKeepDim(h,u));let b=lz(d,g,y,i);for(let w of f)i.disposeIntermediateTensorInfo(w);return b}};function snt(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{axis:s,keepDims:i}=n,a=o.shape.length,u=x.parseAxisParam(s,o.shape),l=u,c=S.getAxesPermutation(l,a),p=o;c!=null&&(p=Ae({inputs:{x:o},backend:e,attrs:{perm:c}}),l=S.getInnerMostAxes(l.length,o.shape.length)),S.assertAxesAreInnerMostDims("min",l,a);let[m,f]=S.computeOutAndReduceShapes(p.shape,l),d=x.sizeFromShape(f),h=ut({inputs:{x:p},backend:e,attrs:{shape:[-1,d]}}),g=Hn(h,h.dtype,"min",e),y;if(i){let b=S.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 cz={kernelName:vs,backendName:"webgl",kernelFunc:snt};var int=Dw+`
return min(a, b);
`,ant=`
vec4 result = vec4(min(a, b));
vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
`+vu+`
return result;
`,lnt=le({opSnippet:int,packedOpSnippet:ant,cpuKernelImpl:fP}),pz={kernelName:Cs,backendName:"webgl",kernelFunc:lnt};var Tv=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=Gt(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 _v=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=Gt(o),i=e.map(d=>d[0]).join(","),a=e.map((d,h)=>d[0]+t[h]).join(","),u=nr("rc",o),l=nr("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 unt=({inputs:r,backend:t,attrs:e})=>{let{x:n}=r,{paddings:o,mode:s}=e,i=V().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new _v(n.shape,o,s):new Tv(n.shape,o,s);return t.runWebGLProgram(i,[n],n.dtype)},mz={kernelName:Is,backendName:"webgl",kernelFunc:unt};var cnt=`if (b == 0.0) return NAN;
return mod(a, b);`,pnt=`
vec4 result = mod(a, b);
vec4 isNaN = vec4(equal(b, vec4(0.0)));
`+vu+`
return result;
`,mnt=le({opSnippet:cnt,packedOpSnippet:pnt}),fz={kernelName:Na,backendName:"webgl",kernelFunc:mnt};var Ev=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 fnt=`
if (a == b) {
return 1.0;
};
return a / b;`,dnt=`
// 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;
`,AT=le({opSnippet:fnt,packedOpSnippet:dnt,checkOutOfBounds:!0}),dz={kernelName:ls,backendName:"webgl",kernelFunc:AT};var hz="return a - b;",$T=le({opSnippet:hz,packedOpSnippet:hz,supportsComplex:!0,cpuKernelImpl:EP}),gz={kernelName:Gs,backendName:"webgl",kernelFunc:$T};function DT(r){let{inputs:t,backend:e,attrs:n}=r,{logits:o}=t,{dim:s}=n,i=x.parseAxisParam([s],o.shape),a=ET({inputs:{x:o},backend:e,attrs:{reductionIndices:i,keepDims:!1}}),u=S.expandShapeToKeepDim(a.shape,i),l=ut({inputs:{x:a},backend:e,attrs:{shape:u}}),c=$T({inputs:{a:o,b:l},backend:e}),p=TT({inputs:{x:c},backend:e}),m=rp({inputs:{x:p},backend:e,attrs:{axis:i,keepDims:!1}}),f=ut({inputs:{x:m},backend:e,attrs:{shape:u}}),d=AT({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 xz={kernelName:Bs,backendName:"webgl",kernelFunc:DT};function hnt(r){let{inputs:t,backend:e,attrs:n}=r,{logits:o}=t,{numSamples:s,seed:i,normalized:a}=n,u=a?o:DT({inputs:{logits:o},backend:e,attrs:{dim:o.shape.length-1}}),l=u.shape[0],c=u.shape[1],p=new Ev(l,c,s),m=[[i]],f=e.runWebGLProgram(p,[u],"int32",m);return a||e.disposeIntermediateTensorInfo(u),f}var yz={kernelName:Xp,backendName:"webgl",kernelFunc:hnt};var gnt=hr+`
return -x;
`,xnt=`
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 ynt(r){let{inputs:t,backend:e}=r,{x:n}=t;if(e.shouldExecuteOnCPU([n])){let s=e.texData.get(n.dataId),[i,a]=hP(s.values,n.shape,n.dtype);return e.makeTensorInfo(a,n.dtype,i)}let o;return V().getBool("WEBGL_PACK_UNARY_OPERATIONS")?o=new eo(n.shape,xnt):o=new en(n.shape,gnt),e.runWebGLProgram(o,[n],n.dtype)}var bz={kernelName:ki,backendName:"webgl",kernelFunc:ynt};var bnt=Gr.nonMaxSuppressionV3Impl;function wnt(r){S.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:e,attrs:n}=r,{boxes:o,scores:s}=t,{maxOutputSize:i,iouThreshold:a,scoreThreshold:u}=n,l=e.readSync(o.dataId),c=e.readSync(s.dataId),{selectedIndices:p}=bnt(l,c,i,a,u);return e.makeTensorInfo([p.length],"int32",new Int32Array(p))}var wz={kernelName:_a,backendName:"webgl",kernelFunc:wnt};var vnt=Gr.nonMaxSuppressionV4Impl;function Cnt(r){S.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:e,attrs:n}=r,{boxes:o,scores:s}=t,{maxOutputSize:i,iouThreshold:a,scoreThreshold:u,padToMaxOutputSize:l}=n,c=e.readSync(o.dataId),p=e.readSync(s.dataId),{selectedIndices:m,validOutputs:f}=vnt(c,p,i,a,u,l);return[e.makeTensorInfo([m.length],"int32",new Int32Array(m)),e.makeTensorInfo([],"int32",new Int32Array([f]))]}var vz={kernelName:Ea,backendName:"webgl",kernelFunc:Cnt};var Int=Gr.nonMaxSuppressionV5Impl;function Snt(r){S.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:e,attrs:n}=r,{boxes:o,scores:s}=t,{maxOutputSize:i,iouThreshold:a,scoreThreshold:u,softNmsSigma:l}=n,c=e.readSync(o.dataId),p=e.readSync(s.dataId),m=i,f=a,d=u,h=l,{selectedIndices:g,selectedScores:y}=Int(c,p,m,f,d,h);return[e.makeTensorInfo([g.length],"int32",new Int32Array(g)),e.makeTensorInfo([y.length],"float32",new Float32Array(y))]}var Cz={kernelName:Aa,backendName:"webgl",kernelFunc:Snt};var Av=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 knt=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 Av(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},Iz={kernelName:ks,backendName:"webgl",kernelFunc:knt};function Ag(r){let{inputs:t,backend:e}=r,{x:n}=t;if(n.dtype==="complex64"){let o=Sl({inputs:{input:n},backend:e}),s=Ag({inputs:{x:o},backend:e}),i=op({inputs:{input:n},backend:e}),a=Ag({inputs:{x:i},backend:e}),u=Rn({inputs:{real:s,imag:a},backend:e});return e.disposeIntermediateTensorInfo(o),e.disposeIntermediateTensorInfo(s),e.disposeIntermediateTensorInfo(i),e.disposeIntermediateTensorInfo(a),u}else return kl({attrs:{shape:n.shape,dtype:n.dtype,value:n.dtype==="string"?"":0},backend:e})}var Sz={kernelName:Fi,backendName:"webgl",kernelFunc:Ag};function kz(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=Sl({inputs:{input:n},backend:e}),s=kz({inputs:{x:o},backend:e}),i=op({inputs:{input:n},backend:e}),a=Ag({inputs:{x:i},backend:e}),u=Rn({inputs:{real:s,imag:a},backend:e});return e.disposeIntermediateTensorInfo(o),e.disposeIntermediateTensorInfo(s),e.disposeIntermediateTensorInfo(i),e.disposeIntermediateTensorInfo(a),u}else return kl({attrs:{shape:n.shape,dtype:n.dtype,value:1},backend:e})}var Nz={kernelName:Ni,backendName:"webgl",kernelFunc:kz};function Nnt(r){let{inputs:t,backend:e,attrs:n}=r,{axis:o}=n;if(t.length===1)return dv({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=dv({inputs:{input:c},backend:e,attrs:{dim:o}});return a.push(p),p}),l=NT({inputs:u,backend:e,attrs:{axis:o}});return a.forEach(c=>e.disposeIntermediateTensorInfo(c)),l}var Tz={kernelName:Ti,backendName:"webgl",kernelFunc:Nnt};var $v=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=Gt(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 Dv=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=Gt(o),i=e.map(h=>h[0]).join(","),a=e.map((h,g)=>h[0]+t[g]).join(","),u=nr("rc",o),l=nr("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 RT=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 kl({backend:e,attrs:{shape:l,value:i,dtype:o.dtype}})}let a=V().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new Dv(o.shape,s,i):new $v(o.shape,s,i),u=[[i]];return e.runWebGLProgram(a,[o],o.dtype,u)},_z={kernelName:Ns,backendName:"webgl",kernelFunc:RT};var Tnt=`
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);
`,_nt=`
// 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));
`+vu+`
return result;
`,Ent=le({opSnippet:Tnt,packedOpSnippet:_nt}),Ez={kernelName:Ts,backendName:"webgl",kernelFunc:Ent};function Ant(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{axis:s,keepDims:i}=n,a=o.shape.length,u=[],l=x.parseAxisParam(s,o.shape),c=l,p=S.getAxesPermutation(c,a),m=o;p!=null&&(m=Ae({inputs:{x:o},backend:e,attrs:{perm:p}}),c=S.getInnerMostAxes(c.length,a),u.push(m)),S.assertAxesAreInnerMostDims("prod",c,a);let f;if(e.shouldExecuteOnCPU([m])){let d=e.texData.get(m.dataId).values,{outVals:h,outShape:g,outDtype:y}=xP(m.shape,m.dtype,d,c);f=e.makeTensorInfo(g,y,h)}else{let[d,h]=S.computeOutAndReduceShapes(m.shape,c),g=x.sizeFromShape(h),y=ut({inputs:{x:m},backend:e,attrs:{shape:[-1,g]}}),b=Uu(o.dtype),w=Hn(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=S.expandShapeToKeepDim(f.shape,l);f=ut({inputs:{x:f},backend:e,attrs:{shape:d}})}return u.forEach(d=>e.disposeIntermediateTensorInfo(d)),f}var Az={kernelName:Es,backendName:"webgl",kernelFunc:Ant};var FT=r=>{let{backend:t,attrs:e}=r,{start:n,stop:o,step:s,dtype:i}=e,a=yP(n,o,s,i);return t.makeTensorInfo([a.length],i,a)},$z={kernelName:zl,backendName:"webgl",kernelFunc:FT};var $nt="return 1.0 / x;",Dnt=Ct({opSnippet:$nt}),Dz={kernelName:$a,backendName:"webgl",kernelFunc:Dnt};var Rnt=hr+`
return (x < 0.0) ? 0.0 : x;
`,Fnt=`
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;
`,Ont=Ct({opSnippet:Rnt,packedOpSnippet:Fnt}),Rz={kernelName:As,backendName:"webgl",kernelFunc:Ont};var Mnt=hr+`
return (x < 0.0) ? 0.0 : min(6.0, x);
`,Pnt=`
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;
`,Lnt=Ct({opSnippet:Mnt,packedOpSnippet:Pnt}),Fz={kernelName:Ds,backendName:"webgl",kernelFunc:Lnt};var Rv=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 Fv=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 < ${n-1};
// In parallel, construct four corners for all four components in
// packed 2x2 cell.
vec4 topLeft = vec4(
getAValue(b, sourceFloorRC.x, sourceFloorRC.y, d),
hasNextCol ? getAValue(b, sourceFloorRC.x, sourceFloorRC.y, d + 1)
: 0.0,
hasNextRow ? getAValue(b, sourceFloorRC.x, sourceFloorRC.z, d)
: 0.0,
(hasNextRow && hasNextCol) ?
getAValue(b, sourceFloorRC.x, sourceFloorRC.z, d + 1) : 0.0);
vec4 bottomLeft = vec4(
getAValue(b, sourceCeilRC.x, sourceFloorRC.y, d),
hasNextCol ? getAValue(b, sourceCeilRC.x, sourceFloorRC.y, d + 1)
: 0.0,
hasNextRow ? getAValue(b, sourceCeilRC.x, sourceFloorRC.z, d)
: 0.0,
(hasNextRow && hasNextCol) ?
getAValue(b, sourceCeilRC.x, sourceFloorRC.z, d + 1) : 0.0);
vec4 topRight = vec4(
getAValue(b, sourceFloorRC.x, sourceCeilRC.y, d),
hasNextCol ? getAValue(b, sourceFloorRC.x, sourceCeilRC.y, d + 1)
: 0.0,
hasNextRow ? getAValue(b, sourceFloorRC.x, sourceCeilRC.z, d)
: 0.0,
(hasNextRow && hasNextCol) ?
getAValue(b, sourceFloorRC.x, sourceCeilRC.z, d + 1) : 0.0);
vec4 bottomRight = vec4(
getAValue(b, sourceCeilRC.x, sourceCeilRC.y, d),
hasNextCol ? getAValue(b, sourceCeilRC.x, sourceCeilRC.y, d + 1)
: 0.0,
hasNextRow ? getAValue(b, sourceCeilRC.x, sourceCeilRC.z, d)
: 0.0,
(hasNextRow && hasNextCol) ?
getAValue(b, sourceCeilRC.x, sourceCeilRC.z, d + 1) : 0.0);
vec3 fracRC = sourceFracIndexRC - vec3(sourceFloorRC);
vec4 top = mix(topLeft, topRight, fracRC.yyzz);
vec4 bottom = mix(bottomLeft, bottomRight, fracRC.yyzz);
vec4 newValue = mix(top, bottom, fracRC.x);
setOutput(newValue);
}
`}};function znt(r){let{inputs:t,backend:e,attrs:n}=r,{images:o}=t,{alignCorners:s,halfPixelCenters:i,size:a}=n,[u,l]=a,c=V().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new Fv(o.shape,u,l,s,i):new Rv(o.shape,u,l,s,i);return e.runWebGLProgram(c,[o],"float32")}var Oz={kernelName:$s,backendName:"webgl",kernelFunc:znt};var Ov=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 Bnt(r){let{inputs:t,backend:e,attrs:n}=r,{images:o,dy:s}=t,{alignCorners:i}=n,a=new Ov(s.shape,o.shape,i);return e.runWebGLProgram(a,[s],s.dtype)}var Mz={kernelName:Jp,backendName:"webgl",kernelFunc:Bnt};var Mv=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 Pv=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 < ${n-1};
vec4 newValue = vec4(
getAValue(b, sourceNearestRC.x, sourceNearestRC.y, d),
hasNextCol ? getAValue(b, sourceNearestRC.x, sourceNearestRC.y, d + 1)
: 0.0,
hasNextRow ? getAValue(b, sourceNearestRC.x, sourceNearestRC.z, d)
: 0.0,
(hasNextRow && hasNextCol) ?
getAValue(b, sourceNearestRC.x, sourceNearestRC.z, d + 1) : 0.0);
setOutput(newValue);
}
`}};function Vnt(r){let{inputs:t,backend:e,attrs:n}=r,{images:o}=t,{alignCorners:s,halfPixelCenters:i,size:a}=n,[u,l]=a,c=V().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new Pv(o.shape,u,l,s,i):new Mv(o.shape,u,l,s,i);return e.runWebGLProgram(c,[o],o.dtype)}var Pz={kernelName:Bl,backendName:"webgl",kernelFunc:Vnt};var Lv=class{constructor(t,e,n){this.variableNames=["dy"],this.outputShape=[],this.outputShape=e;let[,o,s]=e,[,i,a]=t,u=[n&&i>1?o-1:o,n&&a>1?s-1:s],l=[n&&i>1?i-1:i,n&&a>1?a-1:a],c=u[0]/l[0],p=u[1]/l[1],m=1/c,f=1/p,d=Math.ceil(m)*2+2,h=Math.ceil(f)*2+2;this.userCode=`
void main() {
ivec4 coords = getOutputCoords();
int b = coords[0];
int d = coords[3];
int r = coords[1];
int c = coords[2];
float accumulator = 0.0;
const float heightScale = float(${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),
${n} ? float(round(sourceFracCol)) :
float(floor(sourceFracCol))));
if (r == sourceNearestRow && c == sourceNearestCol) {
accumulator += getDy(b, dyR, dyC, d);
}
}
}
// End loop over dy
setOutput(accumulator);
}
`}};function Gnt(r){let{inputs:t,backend:e,attrs:n}=r,{images:o,dy:s}=t,{alignCorners:i}=n,a=new Lv(s.shape,o.shape,i);return e.runWebGLProgram(a,[s],s.dtype)}var Lz={kernelName:Zp,backendName:"webgl",kernelFunc:Gnt};var zv=class{constructor(t,e){this.variableNames=["x"];let n=t.length;if(n>4)throw new Error(`WebGL backend: Reverse of rank-${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=Gt(n);this.userCode=`
void main() {
${i} coords = getOutputCoords();
setOutput(getX(${s}));
}
`}};var Bv=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-${n} tensor is not yet supported`);this.outputShape=t;let o=nr("rc",n),s=`${o[n-1]} + 1 < ${this.outputShape[n-1]}`,i=`${o[n-2]} + 1 < ${this.outputShape[n-2]}`,a=Gt(n);n===1?this.userCode=`
void main(){
int rc = getOutputCoords();
vec4 result = vec4(0.);
result.r = getChannel(getX(${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 Wnt(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 Ke({inputs:{x:o},backend:e});let u=V().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new Bv(o.shape,a):new zv(o.shape,a);return e.runWebGLProgram(u,[o],o.dtype)}var zz={kernelName:Rs,backendName:"webgl",kernelFunc:Wnt};var Vv=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 < ${n}) {
outputValue = getImage(coords[0], coordY, coordX, coords[3]);
}
setOutput(outputValue);
}
`}};var Bz={kernelName:Va,backendName:"webgl",kernelFunc:({inputs:r,attrs:t,backend:e})=>{let{image:n}=r,{radians:o,fillValue:s,center:i}=t,a=e,u=new Vv(n.shape,s),[l,c]=S.getImageCenter(i,n.shape[1],n.shape[2]),p=[[l,c,Math.sin(o),Math.cos(o)]];return a.runWebGLProgram(u,[n],n.dtype,p)}};var Unt=`
// OpenGL ES does not support round function.
// The algorithm is based on banker's rounding.
float base = floor(x);
if ((x - base) < 0.5) {
return floor(x);
} else if ((x - base) > 0.5) {
return ceil(x);
} else {
if (mod(base, 2.0) == 0.0) {
return base;
} else {
return base + 1.0;
}
}
`,Hnt=Ct({opSnippet:Unt}),Vz={kernelName:Fs,backendName:"webgl",kernelFunc:Hnt};var qnt="return inversesqrt(x);",Knt=Ct({opSnippet:qnt,cpuKernelImpl:bP}),Gz={kernelName:Os,backendName:"webgl",kernelFunc:Knt};var kd=class{constructor(t,e,n,o,s,i,a=!0){this.variableNames=["updates","indices","defaultValue"],this.outputShape=i;let u=Gt(s.length),l=Gt(i.length),c="";n===1?c="i":n===2&&(c="i, j");let p=`getIndices(${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 jnt(r){let{inputs:t,backend:e,attrs:n}=r,{indices:o,updates:s}=t,{shape:i}=n,{sliceRank:a,numUpdates:u,sliceSize:l,strides:c,outputSize:p}=S.calculateShapes(s,o,i),m=[p/l,l];if(p===0)return e.makeTensorInfo(i,o.dtype);let f=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 kd(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 Wz={kernelName:Da,backendName:"webgl",kernelFunc:jnt};var Gv=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=Gt(n);this.userCode=`
void main() {
${i} resRC = getOutputCoords();
float cVal = getC(${o});
if (cVal >= 1.0) {
setOutput(getA(${s}));
} else {
setOutput(getB(${s}));
}
}
`}};function Xnt(r){let{inputs:t,backend:e}=r,{condition:n,t:o,e:s}=t,i=new Gv(n.shape.length,o.shape,o.shape.length);return e.runWebGLProgram(i,[n,o,s],ar(o.dtype,s.dtype))}var Uz={kernelName:Ei,backendName:"webgl",kernelFunc:Xnt};var Ynt=`
// Stable and Attracting Fixed Point (0, 1) for Normalized Weights.
// see: https://arxiv.org/abs/1706.02515
float scaleAlpha = ${S.SELU_SCALEALPHA};
float scale = ${S.SELU_SCALE};
return (x >= 0.0) ? scale * x : scaleAlpha * (exp(x) - 1.0);
`,Znt=Ct({opSnippet:Ynt}),Hz={kernelName:Ra,backendName:"webgl",kernelFunc:Znt};var Jnt=Lo+`
return 1.0 / (1.0 + exp(-1.0 * x));
`,Qnt=`
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;
`,tot=Ct({opSnippet:Jnt,packedOpSnippet:Qnt,cpuKernelImpl:wP}),qz={kernelName:Ps,backendName:"webgl",kernelFunc:tot};var eot=`
if (isnan(x)) { return 0.0; }
return sign(x);
`,rot=Ct({opSnippet:eot}),Kz={kernelName:Oa,backendName:"webgl",kernelFunc:rot};var not=Lo+`
return sin(x);
`,oot=Ct({opSnippet:not}),jz={kernelName:Ms,backendName:"webgl",kernelFunc:oot};var sot=`
float e2x = exp(x);
return (e2x - 1.0 / e2x) / 2.0;
`,iot=Ct({opSnippet:sot}),Xz={kernelName:Fa,backendName:"webgl",kernelFunc:iot};var aot=`
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;
`,lot=Ct({opSnippet:aot}),Yz={kernelName:Ma,backendName:"webgl",kernelFunc:lot};var uot=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=RT({inputs:{x:o},backend:e,attrs:{paddings:u,constantValue:0}}),p=S.getReshaped(c.shape,s,a,!1),m=S.getPermuted(p.length,s.length,!1),f=S.getReshapedPermuted(c.shape,s,a,!1),d=ut({inputs:{x:c},backend:e,attrs:{shape:p}}),h=Ae({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},Zz={kernelName:$i,backendName:"webgl",kernelFunc:uot};function cot(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]=CP(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 Jz={kernelName:Vl,backendName:"webgl",kernelFunc:cot};function pot(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]=IP(a,n.shape,n.dtype,i,u);return[e.makeTensorInfo(c,n.dtype,l),e.makeTensorInfo([p.length],s.dtype,new Int32Array(p))]}var Qz={kernelName:Pa,backendName:"webgl",kernelFunc:pot};function mot(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]=Tw(i,n.shape,n.dtype,a,u,!0);return e.makeTensorInfo(c,n.dtype,l)}var tB={kernelName:Gl,backendName:"webgl",kernelFunc:mot};function fot(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
${s.shape}`);let i=e.readSync(n.dataId),a=e.readSync(o.dataId),u=e.readSync(s.dataId),[l,c]=Tw(i,n.shape,n.dtype,a,u);return e.makeTensorInfo(c,n.dtype,l)}var eB={kernelName:Wl,backendName:"webgl",kernelFunc:fot};function dot(r){let{inputs:t,backend:e,attrs:n}=r,{sparseIndices:o,sparseValues:s,defaultValue:i}=t,{outputShape:a}=n,{sliceRank:u,numUpdates:l,strides:c,outputSize:p}=S.calculateShapes(s,o,a),m=!1,f=new kd(l,u,o.shape.length,s.shape.length,c,[p,1],m),d=e.runWebGLProgram(f,[s,o,i],s.dtype),h=ut({inputs:{x:d},backend:e,attrs:{shape:a}});return e.disposeIntermediateTensorInfo(d),h}var rB={kernelName:Qp,backendName:"webgl",kernelFunc:dot};function hot(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{numOrSizeSplits:s,axis:i}=n,a=x.parseAxisParam(i,o.shape)[0],u=S.prepareSplitSize(o,s,a),l=o.shape.length,c=new Array(l).fill(0),p=o.shape.slice();return u.map(m=>{let f=[...p];f[a]=m;let d=xi({inputs:{x:o},backend:e,attrs:{begin:c,size:f}});return c[a]+=m,d})}var nB={kernelName:Di,backendName:"webgl",kernelFunc:hot};var oB="return sqrt(x);",got=Ct({opSnippet:oB,packedOpSnippet:oB,cpuKernelImpl:SP}),sB={kernelName:Ls,backendName:"webgl",kernelFunc:got};var xot="return x * x;",yot=Ct({opSnippet:xot}),iB={kernelName:Ul,backendName:"webgl",kernelFunc:yot};var aB="return (a - b) * (a - b);",bot=le({opSnippet:aB,packedOpSnippet:aB}),lB={kernelName:Vs,backendName:"webgl",kernelFunc:bot};function wot({inputs:r,attrs:t,backend:e}){let{x:n}=r,o=hr+`
return x > 0.0 ? 1.0 : float(${t.alpha});
`,s=new en(n.shape,o);return e.runWebGLProgram(s,[n],n.dtype)}var uB={kernelName:uo,backendName:"webgl",kernelFunc:wot};var Wv=class{constructor(t,e,n){this.variableNames=["x"],this.outputShape=n;let o=n.length,s=Gt(n.length),i=Gt(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 vot(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),k;if(h)k=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 $=Ve.computeOutShape(b,w,v),D=xi({inputs:{x:o},backend:e,attrs:{begin:b,size:$}});k=ut({inputs:{x:D},backend:e,attrs:{shape:d}}),e.disposeIntermediateTensorInfo(D)}else if(e.shouldExecuteOnCPU([o])){let D=e.readSync(o.dataId),R=It(o.shape,o.dtype,D),P=kP(f,R,v,b);k=e.makeTensorInfo(d,o.dtype,P.values)}else{let D=new Wv(b,v,f);k=e.runWebGLProgram(D,[o],o.dtype)}let E=ut({inputs:{x:k},backend:e,attrs:{shape:d}});return e.disposeIntermediateTensorInfo(k),E}var cB={kernelName:La,backendName:"webgl",kernelFunc:vot};function Cot(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]=NP(m,f,o,s,i,a,u,l);return[e.makeTensorInfo([d.length],"string",d),e.makeTensorInfo(p.shape,"int32",h)]}var pB={kernelName:tm,backendName:"webgl",kernelFunc:Cot};function Iot(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]=TP(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 mB={kernelName:em,backendName:"webgl",kernelFunc:Iot};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=_P(i,o);return e.makeTensorInfo(s.shape,"int32",a)}var fB={kernelName:rm,backendName:"webgl",kernelFunc:Sot};var kot="return tan(x);",Not=Ct({opSnippet:kot}),dB={kernelName:Ws,backendName:"webgl",kernelFunc:Not};var Tot=`
float e2x = exp(-2.0 * abs(x));
return sign(x) * (1.0 - e2x) / (1.0 + e2x);
`,_ot=Ct({opSnippet:Tot}),hB={kernelName:Us,backendName:"webgl",kernelFunc:_ot};var Uv=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=Gt(this.rank),s=Eot(t);this.userCode=`
void main() {
${o} resRC = getOutputCoords();
setOutput(getA(${s}));
}
`}};function Eot(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 OT(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=AP(c,s);return e.makeTensorInfo(p.shape,p.dtype,p.values)}let i=new Uv(o.shape,s);return e.runWebGLProgram(i,[o],o.dtype)}var gB={kernelName:Yn,backendName:"webgl",kernelFunc:OT};var Hv=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));
}
}
`}},qv=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 ip(r,t){t!==null&&r.disposeIntermediateTensorInfo(t)}function xB(r){let t=1;for(;t<r;)t*=2;return t}function Aot(r){let{inputs:t,backend:e,attrs:n}=r,{x:o}=t,{k:s,sorted:i}=n,a=V().getNumber("TOPK_LAST_DIM_CPU_HANDOFF_SIZE_THRESHOLD"),u=V().getNumber("TOPK_K_CPU_HANDOFF_THRESHOLD"),l=o.shape,c=l[l.length-1];if(e.shouldExecuteOnCPU([o])||c<a||s>u){let P=e.readSync(o.dataId),[W,U]=$P(P,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,kl({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&&ip(e,f);let y=xB(s),b=xB(c),w=null,v=()=>w===null?[g,g]:[g,w],k=(P,W,U)=>{let q=v(),K=new Hv(U),Q=[[c],[w===null?1:0],[Number.NEGATIVE_INFINITY],[P],[W]],rt=w;w=e.runWebGLProgram(K,q,"int32",Q),ip(e,rt)};for(let P=1;P<y;P*=2){let W=P*2;for(let U=P;U>=1;U/=2)k(W,U,[h,b])}for(let P=b;P>y;P/=2){let W=v(),U=new qv([h,P/2]),K=[[c],[w===null?1:0],[y]],j=w;w=e.runWebGLProgram(U,W,"int32",K),ip(e,j);let Q=y/2,rt=Q*2;for(let X=Q;X>=1;X/=2)k(rt,X,w.shape)}let E=w;w=xi({inputs:{x:w},backend:e,attrs:{begin:0,size:[h,s]}}),ip(e,E);let $=_T({inputs:{x:g,indices:w},backend:e,attrs:{axis:1,batchDims:1}});ip(e,g);let D=l.slice(0,-1);D.push(s),E=w,w=ut({inputs:{x:w},attrs:{shape:D},backend:e}),ip(e,E);let R=$;return $=ut({inputs:{x:$},attrs:{shape:D},backend:e}),ip(e,R),[$,w]}var yB={kernelName:za,backendName:"webgl",kernelFunc:Aot};var Kv=class{constructor(t,e,n,o,s,i){this.variableNames=["Image","Transforms"],this.outputShape=i;let a=n==="nearest"?1:2,u;switch(o){case"constant":u=1;break;case"reflect":u=2;break;case"wrap":u=3;break;case"nearest":u=4;break;default:u=1;break}this.userCode=`
float mapCoord(float outCoord, float len) {
float inCoord = outCoord;
if(${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 $ot(r){let{inputs:t,backend:e,attrs:n}=r,{image:o,transforms:s}=t,{interpolation:i,fillMode:a,fillValue:u,outputShape:l}=n,[c,p,m,f]=o.shape,[d,h]=l!=null?l:[p,m],g=[c,d,h,f],y=new Kv(p,m,i,a,u,g);return e.runWebGLProgram(y,[o,s],"float32")}var bB={kernelName:Ba,backendName:"webgl",kernelFunc:$ot};function Dot(r){let{inputs:t,attrs:e,backend:n}=r,{axis:o}=e,{x:s}=t;di(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}=DP(i,o,s.shape,s.dtype);return[n.makeTensorInfo(u,s.dtype,a),n.makeTensorInfo([l.length],"int32",l)]}var wB={kernelName:nm,backendName:"webgl",kernelFunc:Dot};function Rot(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=xi({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 vB={kernelName:Ri,backendName:"webgl",kernelFunc:Rot};var jv=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 Fot(r){let{inputs:t,backend:e,attrs:n}=r,{x:o,segmentIds:s}=t,{numSegments:i}=n,a=o.shape.length,u=[],l=0,c=S.getAxesPermutation([l],a),p=o;c!=null&&(p=Ae({inputs:{x:o},backend:e,attrs:{perm:c}}),u.push(p),l=S.getInnerMostAxes(1,a)[0]);let m=S.segment_util.computeOutShape(p.shape,l,i),f=x.sizeFromShape([p.shape[l]]),d=ut({inputs:{x:p},backend:e,attrs:{shape:[-1,f]}});u.push(d);let h=Uu(o.dtype),g=(v,k,E,$,D)=>{let R=v.shape[0],P=v.shape[1],W=S.segment_util.segOpComputeOptimalWindowSize(P,D),U={windowSize:W,inSize:P,batchSize:R,numSegments:D},q=new jv(U,k),K=e.compileAndRun(q,[v,E],$);if(u.push(K),K.shape[1]===D)return K;let j=FT({backend:e,attrs:{start:0,stop:D,step:1,dtype:"float32"}}),Q=OT({inputs:{x:j},backend:e,attrs:{reps:[P/W]}});return u.push(j),u.push(Q),g(K,k,Q,$,D)},y=g(d,"unsortedSegmentSum",s,h,i),b=ut({inputs:{x:y},backend:e,attrs:{shape:m}}),w=b;if(c!=null){u.push(b);let v=S.getUndoAxesPermutation(c);w=Ae({inputs:{x:w},backend:e,attrs:{perm:v}})}return u.forEach(v=>e.disposeIntermediateTensorInfo(v)),w}var CB={kernelName:Hl,backendName:"webgl",kernelFunc:Fot};var Oot=[uL,pL,mL,fL,hL,gL,xL,yL,vL,CL,IL,SL,kL,NL,TL,_L,EL,AL,$L,DL,RL,OL,ML,PL,VL,WL,UL,ZP,qL,jL,XL,YL,ZL,JL,QL,t3,e3,r3,n3,i3,u3,c3,p3,m3,f3,d3,h3,g3,x3,y3,b3,w3,v3,C3,I3,k3,N3,T3,_3,A3,$3,D3,R3,F3,O3,M3,P3,L3,YP,z3,KL,B3,V3,G3,JP,W3,U3,H3,q3,K3,j3,X3,Y3,Z3,J3,tz,ez,rz,nz,oz,sz,az,uz,cz,pz,mz,fz,yz,nL,bz,wz,vz,Cz,LL,Iz,Nz,Tz,_z,Ez,QP,Az,$z,zL,dz,Dz,Rz,Fz,sL,Oz,Mz,Pz,Lz,zz,Bz,Vz,Gz,Wz,Uz,Hz,qz,Kz,jz,Xz,FL,xz,Yz,Zz,Jz,Qz,tB,eB,rB,nB,sB,iB,lB,uB,cB,pB,mB,fB,gz,aL,dB,hB,gB,yB,bB,lL,wB,vB,CB,Sz];for(let r of Oot)Lu(r);var Xt;(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"})(Xt||(Xt={}));var ku;(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"})(ku||(ku={}));var IB;function Mot(r){IB=r.wasm.cwrap(Oi,null,["number","array","number","number","array","number","number","number","number","number","number","number","number"])}function Pot(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 D=e.dataIdMap.get(i.dataId);if(D.shape.length!==1)throw new Error(`_FusedMatMul only supports rank-1 bias but got rank ${D.shape.length}.`);d=D.id}let h=a==null?0:e.dataIdMap.get(a.dataId).id,g=ku[c];if(g==null)throw new Error(`${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=Pr.assertAndGetBroadcastShape(o.shape.slice(0,-2),s.shape.slice(0,-2)),v=e.makeOutput([...w,y,b],o.dtype),k=e.dataIdMap.get(v.dataId).id,E=new Uint8Array(new Int32Array(o.shape).buffer),$=new Uint8Array(new Int32Array(s.shape).buffer);return IB(m,E,o.shape.length,f,$,s.shape.length,u,l,g,d,h,p||0,k),v}var SB={kernelName:Oi,backendName:"wasm",setupFunc:Mot,kernelFunc:Pot};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,Xt[a.dtype],c),l}return{kernelName:r,backendName:"wasm",setupFunc:n,kernelFunc:o}}var kB=ue(wi);function Ie(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=S.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,Xt[l.dtype],b))(),h}return{kernelName:r,backendName:"wasm",setupFunc:o,kernelFunc:s}}var Lot=!0,NB=Ie(Xn,Lot);var TB;function zot(r){TB=r.wasm.cwrap(Zo,null,["array","number","number","number"])}function Bot(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 TB(s,o.length,Xt[n.dtype],i),n}var _B={kernelName:Zo,backendName:"wasm",setupFunc:zot,kernelFunc:Bot};function ap(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 EB={kernelName:lo,backendName:"wasm",kernelFunc:ap};var AB;function Vot(r){AB=r.wasm.cwrap(Hs,null,["number","array","number","number","number","array","number"])}function no(r){let{inputs:t,backend:e,attrs:n}=r,[o,s]=Wot(t.x.shape,n.perm),i=!0;for(let d=0;d<s.length;d++)s[d]!==d&&(i=!1);let a=Got(t.x.shape,n.perm),u={dataId:t.x.dataId,shape:o,dtype:t.x.dtype};if(i){let d=ap({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 AB(c,f,u.shape.length,Xt[u.dtype],p,m,s.length),l}function Got(r,t){let e=new Array(r.length);for(let n=0;n<e.length;n++)e[n]=r[t[n]];return e}function Wot(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 $B={kernelName:Hs,backendName:"wasm",kernelFunc:no,setupFunc:Vot};function Sn(r,t,e){let n=r.shape,o=r.shape.length,s=x.parseAxisParam(t,n),i=s,a=S.getAxesPermutation(i,o),u=null,l=!1;if(a!=null){let c=new Array(o);for(let f=0;f<c.length;f++)c[f]=n[a[f]];i=S.getInnerMostAxes(i.length,o),u=no({inputs:{x:r},attrs:{perm:a},backend:e});let p=e.dataIdMap.get(r.dataId).id;e.dataIdMap.get(u.dataId).id!==p&&(l=!0)}return{transposed:u,originalAxes:s,axes:i,inputWasTransposed:l}}var DB;function Uot(r){DB=r.wasm.cwrap(na,null,["number, number, number"])}function Hot(r){let{backend:t,inputs:e,attrs:n}=r,{axis:o,keepDims:s}=n,{x:i}=e,u=t.dataIdMap.get(i.dataId).id,l=i,{transposed:c,axes:p,originalAxes:m,inputWasTransposed:f}=Sn(i,o,t);if(f){let w=t.dataIdMap.get(c.dataId).id;l=c,u=w}let 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ast(r){let{inputs:t,attrs:e,backend:n}=r,{x:o,filter:s}=t,i=n.dataIdMap.get(o.dataId).id,a=n.dataIdMap.get(s.dataId).id,{strides:u,dilations:l,pad:c,dimRoundingMode:p,dataFormat:m}=e,f=S.convertConv2DDataFormat(m),d=S.computeConv2DInfo(o.shape,s.shape,u,l,c,p,!1,f),h=d.filterHeight,g=d.filterWidth,y=d.padInfo.top,b=d.padInfo.right,w=d.padInfo.bottom,v=d.padInfo.left,k=d.dilationHeight,E=d.dilationWidth,$=d.strideHeight,D=d.strideWidth,R=d.inChannels,P=d.outChannels,W=d.padInfo.type==="SAME"?1:0;if(d.dataFormat!=="channelsLast")throw new Error(`wasm backend Conv2D does not support dataFormat:'${d.dataFormat}'. 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ust(r){let{backend:t,inputs:e,attrs:n}=r,{dy:o,filter:s}=e,{strides:i,pad:a,dataFormat:u,dimRoundingMode:l,inputShape:c}=n,p=1,m=S.convertConv2DDataFormat(u),f=S.computeConv2DInfo(c,s.shape,i,p,a,l,!1,m),{batchSize:d,filterHeight:h,filterWidth:g,inChannels:y,inHeight:b,inWidth:w,outChannels:v,outHeight:k,outWidth:E,strideHeight:$,strideWidth:D}=f,R=h-1-f.padInfo.top,P=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],ot=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 JB(kt,At,d,h,g,b,w,y,k,E,v,$,D,R,P,K,j,Q,rt,X,ot,st,it,ft,at,xt,bt),dt}var QB={kernelName:ns,backendName:"wasm",setupFunc:lst,kernelFunc:ust};var tV=ue(os);var eV=ue(ss);var PT;(function(r){r[r.bilinear=0]="bilinear",r[r.nearest=1]="nearest"})(PT||(PT={}));var rV;function cst(r){rV=r.wasm.cwrap(pa,null,["number","number","number","number","array","number","number","number","number","number"])}function pst(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=Nl({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,k=new Uint8Array(new Int32Array(a.shape).buffer);return rV(g,y,b,c,k,p,m,PT[o],s,v),h!=null&&t.disposeData(h.dataId),w}var nV={kernelName:pa,backendName:"wasm",setupFunc:cst,kernelFunc:pst};var oV;function mst(r){oV=r.wasm.cwrap(ca,null,["number","number","number","number","number","number"])}function 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xst(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),k=t.dataIdMap.get(h.dataId).id;return lV(y,s,i==="NHWC"?1:0,b,o.shape.length-1,w,v,d.length,k),h}var uV={kernelName:ma,backendName:"wasm",setupFunc:gst,kernelFunc:xst};var cV;function yst(r){cV=r.wasm.cwrap(as,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function bst(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=S.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,k=f.dilationWidth,E=f.strideHeight,$=f.strideWidth,D=f.inChannels,R=f.outChannels,P=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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zT;(function(r){r[r.reflect=0]="reflect",r[r.symmetric=1]="symmetric"})(zT||(zT={}));var XV;function Zst(r){XV=r.wasm.cwrap(Is,null,["number","array","number","number","array","array","number","number"])}function Jst(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 XV(i,l,t.shape.length,Xt[t.dtype],m,f,zT[o],u),a}var YV={kernelName:Is,backendName:"wasm",kernelFunc:Jst,setupFunc:Zst};var Qst=!0,ZV=Ie(Ss,Qst);var JV=ue(ki);function Nd(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 QV;function tit(r){QV=r.wasm.cwrap(_a,"number",["number","number","number","number","number"])}function eit(r){let{backend:t,inputs:e,attrs:n}=r,{iouThreshold:o,maxOutputSize:s,scoreThreshold:i}=n,{boxes:a,scores:u}=e,l=t.dataIdMap.get(a.dataId).id,c=t.dataIdMap.get(u.dataId).id,p=QV(l,c,s,o,i),{pSelectedIndices:m,selectedSize:f,pSelectedScores:d,pValidOutputs:h}=Nd(t,p);return t.wasm._free(d),t.wasm._free(h),t.makeOutput([f],"int32",m)}var tG={kernelName:_a,backendName:"wasm",setupFunc:tit,kernelFunc:eit};var eG;function rit(r){eG=r.wasm.cwrap(Ea,"number",["number","number","number","number","number","bool"])}function nit(r){let{backend:t,inputs:e,attrs:n}=r,{iouThreshold:o,maxOutputSize:s,scoreThreshold:i,padToMaxOutputSize:a}=n,{boxes:u,scores:l}=e,c=t.dataIdMap.get(u.dataId).id,p=t.dataIdMap.get(l.dataId).id,m=eG(c,p,s,o,i,a),{pSelectedIndices:f,selectedSize:d,pSelectedScores:h,pValidOutputs:g}=Nd(t,m);t.wasm._free(h);let 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uG={kernelName:Ti,backendName:"wasm",kernelFunc:cit};var cG;function pit(r){cG=r.wasm.cwrap(Ns,null,["number","array","number","number","array","array","number","number"])}function mit(r){let{inputs:{x:t},backend:e,attrs:{paddings:n,constantValue:o}}=r,s=n.map((h,g)=>h[0]+t.shape[g]+h[1]);if(x.sizeFromShape(t.shape)===0)return LT({backend:e,attrs:{shape:s,value:o,dtype:t.dtype}});let i=e.dataIdMap.get(t.dataId).id,a=e.makeOutput(s,t.dtype),l=e.dataIdMap.get(a.dataId).id,c=new Uint8Array(new Int32Array(t.shape).buffer),p=n.map(h=>h[0]),m=n.map(h=>h[1]),f=new Uint8Array(new Int32Array(p).buffer),d=new Uint8Array(new Int32Array(m).buffer);return cG(i,c,t.shape.length,Xt[t.dtype],f,d,o,l),a}var Yv={kernelName:Ns,backendName:"wasm",kernelFunc:mit,setupFunc:pit};var fit=!1,pG=Ie(Ts,fit);var mG;function dit(r){mG=r.wasm.cwrap(_s,null,["number","number","number"])}function 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this.dataIdMap.get(t).memoryOffset}dispose(){this.wasm.tfjs.dispose(),"PThread"in this.wasm&&this.wasm.PThread.terminateAllThreads(),this.wasm=null}memory(){return{unreliable:!1}}makeOutput(t,e,n){let o;if(n==null)o=this.write(null,t,e);else{let s=this.dataIdNextNumber++;o={id:s},this.dataIdMap.set(o,{id:s,memoryOffset:n,shape:t,dtype:e,refCount:1});let i=x.sizeFromShape(t);this.wasm.tfjs.registerTensor(s,i,n)}return{dataId:o,shape:t,dtype:e}}typedArrayFromHeap({shape:t,dtype:e,dataId:n}){let o=this.wasm.HEAPU8.buffer,{memoryOffset:s}=this.dataIdMap.get(n),i=x.sizeFromShape(t);switch(e){case"float32":return new Float32Array(o,s,i);case"int32":return new Int32Array(o,s,i);case"bool":return new Uint8Array(o,s,i);default:throw new Error(`Unknown dtype ${e}`)}}};function sat(r){return(t,e)=>(x.fetch(r,{credentials:"same-origin"}).then(n=>{n.ok||t.env.a(`failed to load wasm binary file at 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Make sure you call `setWasmPath()` before you call `tf.setBackend()` or `tf.ready()`");e0=r,KT=t}function uat(r,t=!1){if(Fg)throw new Error("The WASM backend was already initialized. Make sure you call `setWasmPaths()` before you call `tf.setBackend()` or `tf.ready()`");if(typeof r=="string")Dg=r;else{Rg=r;let e=aat.filter(n=>Rg[n]==null);if(e.length>0)throw new Error(`There were no entries found for the following binaries: ${e.join(",")}. Please either call setWasmPaths with a map providing a path for each binary, or with a string indicating the directory where all the binaries can be found.`)}KT=t}var vW=-1,qT=-1;function cat(r){vW=r}function pat(){if(qT===-1)throw new Error("WASM backend not initialized.");return qT}var mat="3.16.0";var fat=2;dm("wasm",async()=>{let{wasm:r}=await wW();return new Og(r)},fat);var dat="3.16.0",hat="3.16.0",gat="3.16.0",xat="3.16.0",yat="3.16.0",bat="3.16.0",wat="3.16.0",vat="3.16.0",Cat={tfjs:dat,"tfjs-core":hat,"tfjs-data":gat,"tfjs-layers":xat,"tfjs-converter":yat,"tfjs-backend-cpu":bat,"tfjs-backend-webgl":wat,"tfjs-backend-wasm":vat};export{wi as Abs,ea as Acos,ra as Acosh,eu as AdadeltaOptimizer,ru as AdagradOptimizer,nu as AdamOptimizer,ou as AdamaxOptimizer,Xn as Add,Zo as AddN,na as All,oa as Any,Jo as ArgMax,$l as ArgMin,sa as Asin,ia as Asinh,aa as Atan,ua as Atan2,la as Atanh,Qo as AvgPool,Dl as AvgPool3D,_p as AvgPool3DGrad,Tp as AvgPoolGrad,Og as BackendWasm,ts as BatchMatMul,vi as BatchToSpaceND,Ep as Bincount,Ap as BroadcastArgs,v1 as BroadcastTo,lb as Callback,vy as CallbackList,io as Cast,es as Ceil,ao as ClipByValue,$p as Complex,Rl as ComplexAbs,Ci as Concat,rs as Conv2D,Dp as Conv2DBackpropFilter,ns as Conv2DBackpropInput,Fl as Conv3D,Rp as Conv3DBackpropFilterV2,Fp as Conv3DBackpropInputV2,os as Cos,ss as Cosh,pa as CropAndResize,ca as Cumprod,is as Cumsum,Iy as CustomCallback,Qi as DataStorage,Op as DenseBincount,ma as DepthToSpace,as as DepthwiseConv2dNative,Mp as DepthwiseConv2dNativeBackpropFilter,Pp as DepthwiseConv2dNativeBackpropInput,Lp as Diag,Ol as Dilation2D,Hd as Dilation2DBackpropFilter,Ud as Dilation2DBackpropInput,BC as ENV,ub as EarlyStopping,zp as Einsum,us as Elu,Bp as EluGrad,Gd as Environment,da as Equal,fa as Erf,cs as Exp,Ii as ExpandDims,ha as Expm1,Vp as FFT,Ml as Fill,ga as FlipLeftRight,ps as Floor,ms as FloorDiv,qd as FromPixels,fs as FusedBatchNorm,Mi as FusedConv2D,Pi as FusedDepthwiseConv2D,Qc as GPGPUContext,xa as GatherNd,Si as GatherV2,Tb as GraphModel,ya as Greater,ds as GreaterEqual,Cy as History,Gp as IFFT,lo as Identity,Wp as Imag,ve as InputSpec,ba as IsFinite,wa as IsInf,va as IsNan,jo as KernelBackend,Pl as LRN,Hp as LRNGrad,qh as LayerVariable,Vn as LayersModel,hs as LeakyRelu,Ca as Less,Ia as LessEqual,Up as LinSpace,gs as Log,Sa as Log1p,C1 as LogSoftmax,ka as LogicalAnd,Mu as LogicalNot,Pu as LogicalOr,wu as MathBackendWebGL,xs as Max,bs as MaxPool,Ll as MaxPool3D,Kp as MaxPool3DGrad,qp as MaxPoolGrad,jp as MaxPoolWithArgmax,ys as Maximum,ws as Mean,vs as Min,Cs as Minimum,Is as MirrorPad,Na as Mod,su as MomentumOptimizer,Xp as Multinomial,Ss as Multiply,ki as Neg,_a as NonMaxSuppressionV3,Ea as NonMaxSuppressionV4,Aa as NonMaxSuppressionV5,Ta as NotEqual,Y1 as OP_SCOPE_SUFFIX,ks as OneHot,Ni as OnesLike,Vr as Optimizer,oi as OptimizerConstructors,Ti as Pack,Ns as PadV2,_at as Pool,Ts as Pow,_s as Prelu,Es as Prod,iu as RMSPropOptimizer,$n as RNN,zl as Range,ZC as Rank,Yp as Real,ls as RealDiv,$a as Reciprocal,Qe as Reduction,As as Relu,Ds as Relu6,_i as Reshape,$s as ResizeBilinear,Jp as ResizeBilinearGrad,Bl as ResizeNearestNeighbor,Zp as ResizeNearestNeighborGrad,Rs as Reverse,Va as RotateWithOffset,Fs as Round,Os as Rsqrt,Hi as SGDOptimizer,Da as ScatterNd,Ei as Select,Ra as Selu,Yi as Sequential,Ps as Sigmoid,Oa as Sign,Ms as Sin,Fa as Sinh,Ai as Slice,Bs as Softmax,Ma as Softplus,$i as SpaceToBatchND,Vl as SparseFillEmptyRows,Pa as SparseReshape,Gl as SparseSegmentMean,Wl as SparseSegmentSum,Qp as SparseToDense,Di as SplitV,Ls as Sqrt,Ul as Square,Vs as SquaredDifference,uo as Step,La as StridedSlice,tm as StringNGrams,em as StringSplit,rm as StringToHashBucketFast,Gs as Sub,zs as Sum,Qr as SymbolicTensor,Ws as Tan,Us as Tanh,Lt as Tensor,pe as TensorBuffer,Yn as Tile,za as TopK,Ba as Transform,Hs as Transpose,nm as Unique,Ri as Unpack,Hl as UnsortedSegmentSum,Ga as Variable,Fi as ZerosLike,Oi as _FusedMatMul,Ne as abs,ih as acos,ah as acosh,J as add,_I as addN,ju as all,Zl as any,Xs as argMax,lh as argMin,uh as asin,ch as asinh,ph as atan,mh as atan2,fh as atanh,qa as avgPool,dh as avgPool3d,H_ as backend,S as backend_util,zH as basicLSTMCell,xo as batchNorm,DI as batchNorm2d,RI as batchNorm3d,FI as batchNorm4d,Ka as batchToSpaceND,hh as bincount,s1t as booleanMaskAsync,OI as broadcastArgs,ja as broadcastTo,Pr as broadcast_util,Ax as browser,It as buffer,h7 as callbacks,Z as cast,gh as ceil,br as clipByValue,kn as clone,zn as complex,se as concat,MI as concat1d,PI as concat2d,LI as concat3d,zI as concat4d,_$ as constraints,Zu as conv1d,pn as conv2d,Ju as conv2dTranspose,xh as conv3d,BI as conv3dTranspose,Oat as copyRegisteredKernels,Xa as cos,Qu as cosh,qx as cosineWindow,Jl as cumprod,tc as cumsum,mn as customGrad,SR as data,VI as denseBincount,TI as deprecationWarn,yh as depthToSpace,Zs as depthwiseConv2d,b7 as deregisterOp,Xl as device_util,hq as diag,bh as dilation2d,opt as disableDeprecationWarnings,_t as dispose,spt as disposeVariables,ct as div,wh as divNoNan,GI as dot,hE as dropout,WI as einsum,Js as elu,npt as enableDebugMode,rpt as enableProdMode,gE as enclosingPowerOfTwo,go as engine,V as env,Sr as equal,vh as erf,Ze as exp,fr as expandDims,Ch as expm1,xm as eye,ol as fft,Qs as fill,ppt as findBackend,mpt as findBackendFactory,ti as floor,Ku as floorDiv,XP as forceHalfFloat,Co as fused,yo as gather,fE as gatherND,$x as gather_util,upt as getBackend,WC as getGradient,jd as getKernel,gx as getKernelsForBackend,pat as getThreadsCount,dT as gpgpu_util,Uq as grad,Hq as grads,Ge as greater,Tn as greaterEqual,Wi as ifft,ec as imag,dn as image,l_t as inTopKAsync,E$ as initializers,PS as input,Mr as io,dc as irfft,UI as isFinite,HI as isInf,Ih as isNaN,Pe as keep,Gr as kernel_impls,aD as layers,Ya as leakyRelu,rc as less,_n as lessEqual,eA as linalg,qI as linspace,mZ as loadGraphModel,N8 as loadLayersModel,Sh as localResponseNormalization,wr as log,Za as log1p,KI as logSigmoid,nc as logSoftmax,Nh as logSumExp,Nr as logicalAnd,Ja as logicalNot,oc as logicalOr,JI as logicalXor,zFt as losses,zt as matMul,N_ as math,Dr as max,Qa as maxPool,Th as maxPool3d,QI as maxPoolWithArgmax,fn as maximum,xe as mean,sh as memory,fK as meshgrid,lD as metrics,Ql as min,ei as minimum,_h as mirrorPad,Eh as mod,S8 as model,uD as models,ym as moments,E1t as movingAverage,O as mul,vK as multiRNNCell,tS as multinomial,Zt as neg,Vh as nextFrame,vm as norm,vo as notEqual,js as oneHot,lr as ones,dr as onesLike,N as op,NK as outerProduct,Yr as pad,EK as pad1d,$K as pad2d,RK as pad3d,OK as pad4d,eS as pool,Zr as pow,el as prelu,hI as print,sc as prod,ipt as profile,UK as rand,JK as randomGamma,Gx as randomNormal,ri as randomUniform,rl as range,lpt as ready,tu as real,Ah as reciprocal,dm as registerBackend,T8 as registerCallbackConstructor,S1 as registerGradient,Lu as registerKernel,y7 as registerOp,cD as regularizers,Tr as relu,lc as relu6,cpt as removeBackend,M as reshape,ir as reverse,aj as reverse1d,uj as reverse2d,pj as reverse3d,fj as reverse4d,sl as rfft,uc as round,cc as rsqrt,pt as scalar,pE as scatterND,nh as scatter_util,pc as selu,$h as separableConv2d,k8 as sequential,et as serialization,aH as setBackend,fpt as setPlatform,cat as setThreadsCount,lat as setWasmPath,uat as setWasmPaths,_N as setWebGLContext,cS as setdiff1dAsync,Lr as sigmoid,Dh as sign,mFt as signal,mc as sin,fc as sinh,Rt as slice,Rh as slice1d,Wx as slice2d,Fh as slice3d,bm as slice4d,Ve as slice_util,nl as softmax,bo as softplus,tl as spaceToBatchND,Bh as sparse,Hx as sparseToDense,aFt as spectral,ur as split,be as sqrt,Ut as square,hc as squaredDifference,zr as squeeze,Je as stack,ni as step,Oh as stridedSlice,ry as string,lt as sub,mt as sum,Uu as sumOutType,Mh as tan,Ys as tanh,Ar as tensor,Re as tensor1d,Ui as tensor2d,vI as tensor3d,zj as tensor4d,Bj as tensor5d,Vj as tensor6d,fo as tensor_util,W_ as test_util,B as tidy,kr as tile,apt as time,Ph as topk,vc as train,Mt as transpose,gc as truncatedNormal,wm as unique,Fat as unregisterGradient,Rat as unregisterKernel,Lh as unsortedSegmentSum,vr as unstack,ar as upcastType,x as util,qq as valueAndGrad,Kq as valueAndGrads,pS as variable,Mx as variableGrads,Cat as version,WD as version_converter,U_ as version_core,Hm as version_layers,mat as version_wasm,jP as version_webgl,gke as webgl,pd as webgl_util,_e as where,zh 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 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 2022 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 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 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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