human/dist/human.esm.js

  /*
  Human library
  homepage: <https://github.com/vladmandic/human>
  author: <https://github.com/vladmandic>'
  */

var __create=Object.create,__defProp=Object.defineProperty,__getProtoOf=Object.getPrototypeOf,__hasOwnProp=Object.prototype.hasOwnProperty,__getOwnPropNames=Object.getOwnPropertyNames,__getOwnPropDesc=Object.getOwnPropertyDescriptor;var __markAsModule=target=>__defProp(target,"__esModule",{value:!0});var __commonJS=(callback,module)=>()=>(module||(module={exports:{}},callback(module.exports,module)),module.exports),__export=(target,all4)=>{__markAsModule(target);for(var name in all4)__defProp(target,name,{get:all4[name],enumerable:!0})},__exportStar=(target,module,desc)=>{if(__markAsModule(target),module&&typeof module=="object"||typeof module=="function")for(let key of __getOwnPropNames(module))!__hasOwnProp.call(target,key)&&key!=="default"&&__defProp(target,key,{get:()=>module[key],enumerable:!(desc=__getOwnPropDesc(module,key))||desc.enumerable});return target},__toModule=module=>module&&module.__esModule?module:__exportStar(__defProp(module!=null?__create(__getProtoOf(module)):{},"default",{value:module,enumerable:!0}),module);var require_blazeface=__commonJS(exports=>{var NUM_LANDMARKS=6;function generateAnchors(inputSize){let spec={strides:[inputSize/16,inputSize/8],anchors:[2,6]},anchors=[];for(let i=0;i<spec.strides.length;i++){let stride=spec.strides[i],gridRows=Math.floor((inputSize+stride-1)/stride),gridCols=Math.floor((inputSize+stride-1)/stride),anchorsNum=spec.anchors[i];for(let gridY=0;gridY<gridRows;gridY++){let anchorY=stride*(gridY+.5);for(let gridX=0;gridX<gridCols;gridX++){let anchorX=stride*(gridX+.5);for(let n=0;n<anchorsNum;n++)anchors.push([anchorX,anchorY])}}}return anchors}var disposeBox=box=>{box.startEndTensor.dispose(),box.startPoint.dispose(),box.endPoint.dispose()},createBox=startEndTensor=>({startEndTensor,startPoint:slice(startEndTensor,[0,0],[-1,2]),endPoint:slice(startEndTensor,[0,2],[-1,2])}),scaleBox=(box,factors)=>{let starts=mul(box.startPoint,factors),ends=mul(box.endPoint,factors),newCoordinates=concat2d([starts,ends],1);return createBox(newCoordinates)};function decodeBounds(boxOutputs,anchors,inputSize){let boxStarts=slice(boxOutputs,[0,1],[-1,2]),centers=add2(boxStarts,anchors),boxSizes=slice(boxOutputs,[0,3],[-1,2]),boxSizesNormalized=div(boxSizes,inputSize),centersNormalized=div(centers,inputSize),halfBoxSize=div(boxSizesNormalized,2),starts=sub(centersNormalized,halfBoxSize),ends=add2(centersNormalized,halfBoxSize),startNormalized=mul(starts,inputSize),endNormalized=mul(ends,inputSize);return concat2d([startNormalized,endNormalized],1)}function scaleBoxFromPrediction(face3,scaleFactor){return tidy(()=>{let box=face3.box?face3.box:face3;return scaleBox(box,scaleFactor).startEndTensor.squeeze()})}var BlazeFaceModel=class{constructor(model2,config2){this.blazeFaceModel=model2,this.width=config2.face.detector.inputSize,this.height=config2.face.detector.inputSize,this.anchorsData=generateAnchors(config2.face.detector.inputSize),this.anchors=tensor2d(this.anchorsData),this.inputSize=tensor1d([this.width,this.height]),this.config=config2,this.scaleFaces=.8}async getBoundingBoxes(inputImage){if(!inputImage||inputImage.isDisposedInternal||inputImage.shape.length!==4||inputImage.shape[1]<1||inputImage.shape[2]<1)return null;let[detectedOutputs,boxes,scores]=tidy(()=>{let resizedImage=inputImage.resizeBilinear([this.width,this.height]),normalizedImage=sub(resizedImage.div(127.5),1),batchedPrediction=this.blazeFaceModel.predict(normalizedImage),prediction;if(Array.isArray(batchedPrediction)){let sorted=batchedPrediction.sort((a,b)=>a.size-b.size),concat384=concat([sorted[0],sorted[2]],2),concat512=concat([sorted[1],sorted[3]],2);prediction=concat([concat512,concat384],1).squeeze(0)}else prediction=batchedPrediction.squeeze();let decodedBounds=decodeBounds(prediction,this.anchors,this.inputSize),logits=slice(prediction,[0,0],[-1,1]),scoresOut=sigmoid(logits).squeeze();return[prediction,decodedBounds,scoresOut]}),boxIndicesTensor=await image.nonMaxSuppressionAsync(boxes,scores,this.config.face.detector.maxFaces,this.config.face.detector.iouThreshold,this.config.face.detector.scoreThresh
`),SHADER.FRAGMENT_IDENTITY=["precision highp float;","varying vec2 vUv;","uniform sampler2D texture;","void main(void) {","gl_FragColor = texture2D(texture, vUv);","}"].join(`
`);let _filter={};_filter.colorMatrix=function(matrix){let m=new Float32Array(matrix);m[4]/=255,m[9]/=255,m[14]/=255,m[19]/=255;let shader=m[18]===1&&m[3]===0&&m[8]===0&&m[13]===0&&m[15]===0&&m[16]===0&&m[17]===0&&m[19]===0?_filter.colorMatrix.SHADER.WITHOUT_ALPHA:_filter.colorMatrix.SHADER.WITH_ALPHA,program=_compileShader(shader);gl.uniform1fv(program.uniform.m,m),_draw()},_filter.colorMatrix.SHADER={},_filter.colorMatrix.SHADER.WITH_ALPHA=["precision highp float;","varying vec2 vUv;","uniform sampler2D texture;","uniform float m[20];","void main(void) {","vec4 c = texture2D(texture, vUv);","gl_FragColor.r = m[0] * c.r + m[1] * c.g + m[2] * c.b + m[3] * c.a + m[4];","gl_FragColor.g = m[5] * c.r + m[6] * c.g + m[7] * c.b + m[8] * c.a + m[9];","gl_FragColor.b = m[10] * c.r + m[11] * c.g + m[12] * c.b + m[13] * c.a + m[14];","gl_FragColor.a = m[15] * c.r + m[16] * c.g + m[17] * c.b + m[18] * c.a + m[19];","}"].join(`
`),_filter.colorMatrix.SHADER.WITHOUT_ALPHA=["precision highp float;","varying vec2 vUv;","uniform sampler2D texture;","uniform float m[20];","void main(void) {","vec4 c = texture2D(texture, vUv);","gl_FragColor.r = m[0] * c.r + m[1] * c.g + m[2] * c.b + m[4];","gl_FragColor.g = m[5] * c.r + m[6] * c.g + m[7] * c.b + m[9];","gl_FragColor.b = m[10] * c.r + m[11] * c.g + m[12] * c.b + m[14];","gl_FragColor.a = c.a;","}"].join(`
`),_filter.brightness=function(brightness){let b=(brightness||0)+1;_filter.colorMatrix([b,0,0,0,0,0,b,0,0,0,0,0,b,0,0,0,0,0,1,0])},_filter.saturation=function(amount){let x=(amount||0)*2/3+1,y=(x-1)*-.5;_filter.colorMatrix([x,y,y,0,0,y,x,y,0,0,y,y,x,0,0,0,0,0,1,0])},_filter.desaturate=function(){_filter.saturation(-1)},_filter.contrast=function(amount){let v=(amount||0)+1,o=-128*(v-1);_filter.colorMatrix([v,0,0,0,o,0,v,0,0,o,0,0,v,0,o,0,0,0,1,0])},_filter.negative=function(){_filter.contrast(-2)},_filter.hue=function(rotation){rotation=(rotation||0)/180*Math.PI;let cos4=Math.cos(rotation),sin4=Math.sin(rotation),lumR=.213,lumG=.715,lumB=.072;_filter.colorMatrix([lumR+cos4*(1-lumR)+sin4*-lumR,lumG+cos4*-lumG+sin4*-lumG,lumB+cos4*-lumB+sin4*(1-lumB),0,0,lumR+cos4*-lumR+sin4*.143,lumG+cos4*(1-lumG)+sin4*.14,lumB+cos4*-lumB+sin4*-.283,0,0,lumR+cos4*-lumR+sin4*-(1-lumR),lumG+cos4*-lumG+sin4*lumG,lumB+cos4*(1-lumB)+sin4*lumB,0,0,0,0,0,1,0])},_filter.desaturateLuminance=function(){_filter.colorMatrix([.2764723,.929708,.0938197,0,-37.1,.2764723,.929708,.0938197,0,-37.1,.2764723,.929708,.0938197,0,-37.1,0,0,0,1,0])},_filter.sepia=function(){_filter.colorMatrix([.393,.7689999,.18899999,0,0,.349,.6859999,.16799999,0,0,.272,.5339999,.13099999,0,0,0,0,0,1,0])},_filter.brownie=function(){_filter.colorMatrix([.5997023498159715,.34553243048391263,-.2708298674538042,0,47.43192855600873,-.037703249837783157,.8609577587992641,.15059552388459913,0,-36.96841498319127,.24113635128153335,-.07441037908422492,.44972182064877153,0,-7.562075277591283,0,0,0,1,0])},_filter.vintagePinhole=function(){_filter.colorMatrix([.6279345635605994,.3202183420819367,-.03965408211312453,0,9.651285835294123,.02578397704808868,.6441188644374771,.03259127616149294,0,7.462829176470591,.0466055556782719,-.0851232987247891,.5241648018700465,0,5.159190588235296,0,0,0,1,0])},_filter.kodachrome=function(){_filter.colorMatrix([1.1285582396593525,-.3967382283601348,-.03992559172921793,0,63.72958762196502,-.16404339962244616,1.0835251566291304,-.05498805115633132,0,24.732407896706203,-.16786010706155763,-.5603416277695248,1.6014850761964943,0,35.62982807460946,0,0,0,1,0])},_filter.technicolor=function(){_filter.colorMatrix([1.9125277891456083,-.8545344976951645,-.09155508482755585,0,11.793603434377337,-.3087833385928097,1.7658908555458428,-.10601743074722245,0,-70.35205161461398,-.231103377548616,-.7501899197440212,1.847597816108189,0,30.950940869491138,0,0,0,1,0])},_filter.polaroid=function(){_filter.colorMatrix([1.438,-.062,-.062,0,0,-.122,1.378,-.122,0,0,-.016,-.016,1.483,0,0,0,0,0,1,0])},_filter.shiftToBGR=function(){_filter.colorMatrix([0,0,1,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,1,0])},_filter.convolution=function(matrix){let m=new Float32Array(matrix),pixelSizeX=1/_width,pixelSizeY=1/_height,program=_compileShader(_filter.convolution.SHADER);gl.uniform1fv(program.uniform.m,m),gl.uniform2f(program.uniform.px,pixelSizeX,pixelSizeY),_draw()},_filter.convolution.SHADER=["precision highp float;","varying vec2 vUv;","uniform sampler2D texture;","uniform vec2 px;","uniform float m[9];","void main(void) {","vec4 c11 = texture2D(texture, vUv - px);","vec4 c12 = texture2D(texture, vec2(vUv.x, vUv.y - px.y));","vec4 c13 = texture2D(texture, vec2(vUv.x + px.x, vUv.y - px.y));","vec4 c21 = texture2D(texture, vec2(vUv.x - px.x, vUv.y) );","vec4 c22 = texture2D(texture, vUv);","vec4 c23 = texture2D(texture, vec2(vUv.x + px.x, vUv.y) );","vec4 c31 = texture2D(texture, vec2(vUv.x - px.x, vUv.y + px.y) );","vec4 c32 = texture2D(texture, vec2(vUv.x, vUv.y + px.y) );","vec4 c33 = texture2D(texture, vUv + px );","gl_FragColor = ","c11 * m[0] + c12 * m[1] + c22 * m[2] +","c21 * m[3] + c22 * m[4] + c23 * m[5] +","c31 * m[6] + c32 * m[7] + c33 * m[8];","gl_FragColor.a = c22.a;","}"].join(`
`),_filter.detectEdges=function(){_filter.convolution.call(this,[0,1,0,1,-4,1,0,1,0])},_filter.sobelX=function(){_filter.convolution.call(this,[-1,0,1,-2,0,2,-1,0,1])},_filter.sobelY=function(){_filter.convolution.call(this,[-1,-2,-1,0,0,0,1,2,1])},_filter.sharpen=function(amount){let a=amount||1;_filter.convolution.call(this,[0,-1*a,0,-1*a,1+4*a,-1*a,0,-1*a,0])},_filter.emboss=function(size){let s=size||1;_filter.convolution.call(this,[-2*s,-1*s,0,-1*s,1,1*s,0,1*s,2*s])},_filter.blur=function(size){let blurSizeX=size/7/_width,blurSizeY=size/7/_height,program=_compileShader(_filter.blur.SHADER);gl.uniform2f(program.uniform.px,0,blurSizeY),_draw(DRAW.INTERMEDIATE),gl.uniform2f(program.uniform.px,blurSizeX,0),_draw()},_filter.blur.SHADER=["precision highp float;","varying vec2 vUv;","uniform sampler2D texture;","uniform vec2 px;","void main(void) {","gl_FragColor = vec4(0.0);","gl_FragColor += texture2D(texture, vUv + vec2(-7.0*px.x, -7.0*px.y))*0.0044299121055113265;","gl_FragColor += texture2D(texture, vUv + vec2(-6.0*px.x, -6.0*px.y))*0.00895781211794;","gl_FragColor += texture2D(texture, vUv + vec2(-5.0*px.x, -5.0*px.y))*0.0215963866053;","gl_FragColor += texture2D(texture, vUv + vec2(-4.0*px.x, -4.0*px.y))*0.0443683338718;","gl_FragColor += texture2D(texture, vUv + vec2(-3.0*px.x, -3.0*px.y))*0.0776744219933;","gl_FragColor += texture2D(texture, vUv + vec2(-2.0*px.x, -2.0*px.y))*0.115876621105;","gl_FragColor += texture2D(texture, vUv + vec2(-1.0*px.x, -1.0*px.y))*0.147308056121;","gl_FragColor += texture2D(texture, vUv                             )*0.159576912161;","gl_FragColor += texture2D(texture, vUv + vec2( 1.0*px.x,  1.0*px.y))*0.147308056121;","gl_FragColor += texture2D(texture, vUv + vec2( 2.0*px.x,  2.0*px.y))*0.115876621105;","gl_FragColor += texture2D(texture, vUv + vec2( 3.0*px.x,  3.0*px.y))*0.0776744219933;","gl_FragColor += texture2D(texture, vUv + vec2( 4.0*px.x,  4.0*px.y))*0.0443683338718;","gl_FragColor += texture2D(texture, vUv + vec2( 5.0*px.x,  5.0*px.y))*0.0215963866053;","gl_FragColor += texture2D(texture, vUv + vec2( 6.0*px.x,  6.0*px.y))*0.00895781211794;","gl_FragColor += texture2D(texture, vUv + vec2( 7.0*px.x,  7.0*px.y))*0.0044299121055113265;","}"].join(`
`),_filter.pixelate=function(size){let blurSizeX=size/_width,blurSizeY=size/_height,program=_compileShader(_filter.pixelate.SHADER);gl.uniform2f(program.uniform.size,blurSizeX,blurSizeY),_draw()},_filter.pixelate.SHADER=["precision highp float;","varying vec2 vUv;","uniform vec2 size;","uniform sampler2D texture;","vec2 pixelate(vec2 coord, vec2 size) {","return floor( coord / size ) * size;","}","void main(void) {","gl_FragColor = vec4(0.0);","vec2 coord = pixelate(vUv, size);","gl_FragColor += texture2D(texture, coord);","}"].join(`
`)};exports.Canvas=WebGLImageFilter});var require_image=__commonJS(exports=>{var fxImage=__toModule(require_imagefx()),inCanvas=null,outCanvas=null;function process3(input2,config2){let tensor2;if(input2 instanceof Tensor)tensor2=clone(input2);else{let originalWidth=input2.naturalWidth||input2.videoWidth||input2.width||input2.shape&&input2.shape[1]>0,originalHeight=input2.naturalHeight||input2.videoHeight||input2.height||input2.shape&&input2.shape[2]>0,targetWidth=originalWidth,targetHeight=originalHeight;if(config2.filter.width>0?targetWidth=config2.filter.width:config2.filter.height>0&&(targetWidth=originalWidth*(config2.filter.height/originalHeight)),config2.filter.height>0?targetHeight=config2.filter.height:config2.filter.width>0&&(targetHeight=originalHeight*(config2.filter.width/originalWidth)),!targetWidth||!targetHeight)return log("Human: invalid input",input2),null;(!inCanvas||inCanvas.width!==targetWidth||inCanvas.height!==targetHeight)&&(inCanvas=typeof OffscreenCanvas!="undefined"?new OffscreenCanvas(targetWidth,targetHeight):document.createElement("canvas"),inCanvas.width!==targetWidth&&(inCanvas.width=targetWidth),inCanvas.height!==targetHeight&&(inCanvas.height=targetHeight));let ctx=inCanvas.getContext("2d");if(input2 instanceof ImageData?ctx.putImageData(input2,0,0):ctx.drawImage(input2,0,0,originalWidth,originalHeight,0,0,inCanvas.width,inCanvas.height),config2.filter.enabled){if((!this.fx||!outCanvas||inCanvas.width!==outCanvas.width||inCanvas.height!==outCanvas.height)&&(outCanvas=typeof OffscreenCanvas!="undefined"?new OffscreenCanvas(inCanvas.width,inCanvas.height):document.createElement("canvas"),outCanvas.width!==inCanvas.width&&(outCanvas.width=inCanvas.width),outCanvas.height!==inCanvas.height&&(outCanvas.height=inCanvas.height),this.fx=ENV.flags.IS_BROWSER?new fxImage.Canvas({canvas:outCanvas}):null),!this.fx)return inCanvas;this.fx.reset(),this.fx.addFilter("brightness",config2.filter.brightness),config2.filter.contrast!==0&&this.fx.addFilter("contrast",config2.filter.contrast),config2.filter.sharpness!==0&&this.fx.addFilter("sharpen",config2.filter.sharpness),config2.filter.blur!==0&&this.fx.addFilter("blur",config2.filter.blur),config2.filter.saturation!==0&&this.fx.addFilter("saturation",config2.filter.saturation),config2.filter.hue!==0&&this.fx.addFilter("hue",config2.filter.hue),config2.filter.negative&&this.fx.addFilter("negative"),config2.filter.sepia&&this.fx.addFilter("sepia"),config2.filter.vintage&&this.fx.addFilter("brownie"),config2.filter.sepia&&this.fx.addFilter("sepia"),config2.filter.kodachrome&&this.fx.addFilter("kodachrome"),config2.filter.technicolor&&this.fx.addFilter("technicolor"),config2.filter.polaroid&&this.fx.addFilter("polaroid"),config2.filter.pixelate!==0&&this.fx.addFilter("pixelate",config2.filter.pixelate),this.fx.apply(inCanvas)}else outCanvas=inCanvas;let pixels;if(outCanvas.data){let shape=[outCanvas.height,outCanvas.width,3];pixels=tensor3d(outCanvas.data,shape,"int32")}else if(config2.backend==="webgl"||outCanvas instanceof ImageData)pixels=browser_exports.fromPixels(outCanvas);else{let tempCanvas=typeof OffscreenCanvas!="undefined"?new OffscreenCanvas(targetWidth,targetHeight):document.createElement("canvas");tempCanvas.width=targetWidth,tempCanvas.height=targetHeight;let tempCtx=tempCanvas.getContext("2d");tempCtx==null||tempCtx.drawImage(outCanvas,0,0);let data2=tempCtx==null?void 0:tempCtx.getImageData(0,0,targetWidth,targetHeight);pixels=browser_exports.fromPixels(data2)}let casted=pixels.toFloat();tensor2=casted.expandDims(0),pixels.dispose(),casted.dispose()}return{tensor:tensor2,canvas:config2.filter.return?outCanvas:null}}exports.process=process3});function log(...msg){let dt=new Date,ts=`${dt.getHours().toString().padStart(2,"0")}:${dt.getMinutes().toString().padStart(2,"0")}:${dt.getSeconds().toString().padStart(2,"0")}.${dt.getMilliseconds().toString().padStart(3,"0")}`;msg&&console.log(ts,"Human:",...msg)}var tfjs_esm_exports={};__export(tfjs_esm_exports,{Abs:()=>Abs,Acos:()=>Acos,Acosh:()=>Acosh,AdadeltaOptimizer:()=>AdadeltaOptimizer,Adagra
`)),lines.join(`
`)}function computeMaxSizePerColumn(vals,shape,dtype,strides){let n=sizeFromShape(shape),numCols=strides[strides.length-1],padPerCol=new Array(numCols).fill(0),rank=shape.length,valuesOrTuples=dtype==="complex64"?createComplexTuples(vals):vals;if(rank>1)for(let row=0;row<n/numCols;row++){let offset=row*numCols;for(let j=0;j<numCols;j++)padPerCol[j]=Math.max(padPerCol[j],valToString(valuesOrTuples[offset+j],0,dtype).length)}return padPerCol}function valToString(val,pad3,dtype){let valStr;return Array.isArray(val)?valStr=`${parseFloat(val[0].toFixed(FORMAT_NUM_SIG_DIGITS))} + ${parseFloat(val[1].toFixed(FORMAT_NUM_SIG_DIGITS))}j`:isString(val)?valStr=`'${val}'`:dtype==="bool"?valStr=boolNumToString(val):valStr=parseFloat(val.toFixed(FORMAT_NUM_SIG_DIGITS)).toString(),rightPad(valStr,pad3)}function boolNumToString(v){return v===0?"false":"true"}function subTensorToString(vals,shape,dtype,strides,padPerCol,isLast=!0){let storagePerElement=dtype==="complex64"?2:1,size=shape[0],rank=shape.length;if(rank===0){if(dtype==="complex64"){let complexTuple=createComplexTuples(vals);return[valToString(complexTuple[0],0,dtype)]}return dtype==="bool"?[boolNumToString(vals[0])]:[vals[0].toString()]}if(rank===1){if(size>FORMAT_LIMIT_NUM_VALS){let firstValsSize=FORMAT_NUM_FIRST_LAST_VALS*storagePerElement,firstVals=Array.from(vals.slice(0,firstValsSize)),lastVals=Array.from(vals.slice((size-FORMAT_NUM_FIRST_LAST_VALS)*storagePerElement,size*storagePerElement));return dtype==="complex64"&&(firstVals=createComplexTuples(firstVals),lastVals=createComplexTuples(lastVals)),["["+firstVals.map((x,i)=>valToString(x,padPerCol[i],dtype)).join(", ")+", ..., "+lastVals.map((x,i)=>valToString(x,padPerCol[size-FORMAT_NUM_FIRST_LAST_VALS+i],dtype)).join(", ")+"]"]}let displayVals=dtype==="complex64"?createComplexTuples(vals):Array.from(vals);return["["+displayVals.map((x,i)=>valToString(x,padPerCol[i],dtype)).join(", ")+"]"]}let subshape=shape.slice(1),substrides=strides.slice(1),stride=strides[0]*storagePerElement,lines=[];if(size>FORMAT_LIMIT_NUM_VALS){for(let i=0;i<FORMAT_NUM_FIRST_LAST_VALS;i++){let start=i*stride,end=start+stride;lines.push(...subTensorToString(vals.slice(start,end),subshape,dtype,substrides,padPerCol,!1))}lines.push("...");for(let i=size-FORMAT_NUM_FIRST_LAST_VALS;i<size;i++){let start=i*stride,end=start+stride;lines.push(...subTensorToString(vals.slice(start,end),subshape,dtype,substrides,padPerCol,i===size-1))}}else for(let i=0;i<size;i++){let start=i*stride,end=start+stride;lines.push(...subTensorToString(vals.slice(start,end),subshape,dtype,substrides,padPerCol,i===size-1))}let sep=rank===2?",":"";lines[0]="["+lines[0]+sep;for(let i=1;i<lines.length-1;i++)lines[i]=" "+lines[i]+sep;let newLineSep=`,
`;for(let i=2;i<rank;i++)newLineSep+=`
`;return lines[lines.length-1]=" "+lines[lines.length-1]+"]"+(isLast?"":newLineSep),lines}function createComplexTuples(vals){let complexTuples=[];for(let i=0;i<vals.length;i+=2)complexTuples.push([vals[i],vals[i+1]]);return complexTuples}var TensorBuffer=class{constructor(shape,dtype,values){if(this.dtype=dtype,this.shape=shape.slice(),this.size=sizeFromShape(shape),values!=null){let n=values.length;assert(n===this.size,()=>`Length of values '${n}' does not match the size inferred by the shape '${this.size}'.`)}if(dtype==="complex64")throw new Error("complex64 dtype TensorBuffers are not supported. Please create a TensorBuffer for the real and imaginary parts separately and call tf.complex(real, imag).");this.values=values||getArrayFromDType(dtype,this.size),this.strides=computeStrides(shape)}set(value,...locs){locs.length===0&&(locs=[0]),assert(locs.length===this.rank,()=>`The number of provided coordinates (${locs.length}) must match the rank (${this.rank})`);let index=this.locToIndex(locs);this.values[index]=value}get(...locs){locs.length===0&&(locs=[0]);let i=0;for(let loc of locs){if(loc<0||loc>=this.shape[i]){let msg=`Requested out of range element at ${locs}.   Buffer shape=${this.shape}`;throw new Error(msg)}i++}let index=locs[locs.length-1];for(let i2=0;i2<locs.length-1;++i2)index+=this.strides[i2]*locs[i2];return this.values[index]}locToIndex(locs){if(this.rank===0)return 0;if(this.rank===1)return locs[0];let index=locs[locs.length-1];for(let i=0;i<locs.length-1;++i)index+=this.strides[i]*locs[i];return index}indexToLoc(index){if(this.rank===0)return[];if(this.rank===1)return[index];let locs=new Array(this.shape.length);for(let i=0;i<locs.length-1;++i)locs[i]=Math.floor(index/this.strides[i]),index-=locs[i]*this.strides[i];return locs[locs.length-1]=index,locs}get rank(){return this.shape.length}toTensor(){return trackerFn().makeTensor(this.values,this.shape,this.dtype)}},trackerFn=null,opHandler=null,deprecationWarningFn=null;function setTensorTracker(fn){trackerFn=fn}function setOpHandler(handler){opHandler=handler}function setDeprecationWarningFn(fn){deprecationWarningFn=fn}var Tensor=class{constructor(shape,dtype,dataId,id){this.kept=!1,this.isDisposedInternal=!1,this.shape=shape.slice(),this.dtype=dtype||"float32",this.size=sizeFromShape(shape),this.strides=computeStrides(shape),this.dataId=dataId,this.id=id,this.rankType=this.rank<5?this.rank.toString():"higher"}get rank(){return this.shape.length}async buffer(){let vals=await this.data();return opHandler.buffer(this.shape,this.dtype,vals)}bufferSync(){return opHandler.buffer(this.shape,this.dtype,this.dataSync())}async array(){let vals=await this.data();return toNestedArray(this.shape,vals)}arraySync(){return toNestedArray(this.shape,this.dataSync())}async data(){this.throwIfDisposed();let data2=trackerFn().read(this.dataId);if(this.dtype==="string"){let bytes=await data2;try{return bytes.map(b=>decodeString(b))}catch(_a){throw new Error("Failed to decode the string bytes into utf-8. To get the original bytes, call tensor.bytes().")}}return data2}dataSync(){this.throwIfDisposed();let data2=trackerFn().readSync(this.dataId);if(this.dtype==="string")try{return data2.map(b=>decodeString(b))}catch(_a){throw new Error("Failed to decode the string bytes into utf-8. To get the original bytes, call tensor.bytes().")}return data2}async bytes(){this.throwIfDisposed();let data2=await trackerFn().read(this.dataId);return this.dtype==="string"?data2:new Uint8Array(data2.buffer)}dispose(){this.isDisposed||(trackerFn().disposeTensor(this),this.isDisposedInternal=!0)}get isDisposed(){return this.isDisposedInternal}throwIfDisposed(){if(this.isDisposed)throw new Error("Tensor is disposed.")}print(verbose=!1){return opHandler.print(this,verbose)}clone(){return this.throwIfDisposed(),opHandler.clone(this)}toString(verbose=!1){let vals=this.dataSync();return tensorToString(vals,this.shape,this.dtype,verbose)}cast(dtype){return this.throwIfDisposed(),opHandler.cast(this,dtype)}variable(trainable=!0,name,dtype){return this.throwIfDisposed(),trackerFn().makeVariable(this,train
Manifest JSON has weights with names: ${allManifestWeightNames.join(", ")}.`)}let groupIndicesToFetch=groupIndicesToFetchMap.reduce((accumulator,shouldFetch,i)=>(shouldFetch&&accumulator.push(i),accumulator),[]),fetchUrls=[];groupIndicesToFetch.forEach(i=>{manifest[i].paths.forEach(filepath=>{let fetchUrl=filePathPrefix+(filePathPrefix.endsWith("/")?"":"/")+filepath;fetchUrls.push(fetchUrl)})});let buffers=await fetchWeightsFunction(fetchUrls),weightsTensorMap={},bufferIndexOffset=0;return groupIndicesToFetch.forEach(i=>{let numBuffers=manifest[i].paths.length,groupBytes=0;for(let i2=0;i2<numBuffers;i2++)groupBytes+=buffers[bufferIndexOffset+i2].byteLength;let groupBuffer=new ArrayBuffer(groupBytes),groupByteBuffer=new Uint8Array(groupBuffer),groupBufferOffset=0;for(let i2=0;i2<numBuffers;i2++){let buffer2=new Uint8Array(buffers[bufferIndexOffset+i2]);groupByteBuffer.set(buffer2,groupBufferOffset),groupBufferOffset+=buffer2.byteLength}groupWeightsToFetch[i].forEach(weightsEntry=>{let byteBuffer=groupBuffer.slice(weightsEntry.groupOffset,weightsEntry.groupOffset+weightsEntry.sizeBytes),nameToTensorMap=decodeWeights(byteBuffer,[weightsEntry.manifestEntry]);for(let name in nameToTensorMap)weightsTensorMap[name]=nameToTensorMap[name]}),bufferIndexOffset+=numBuffers}),weightsTensorMap}}var OCTET_STREAM_MIME_TYPE="application/octet-stream",JSON_TYPE="application/json",HTTPRequest=class{constructor(path,loadOptions){if(this.DEFAULT_METHOD="POST",loadOptions==null&&(loadOptions={}),this.weightPathPrefix=loadOptions.weightPathPrefix,this.onProgress=loadOptions.onProgress,this.weightUrlConverter=loadOptions.weightUrlConverter,loadOptions.fetchFunc!=null?(assert(typeof loadOptions.fetchFunc=="function",()=>"Must pass a function that matches the signature of `fetch` (see https://developer.mozilla.org/en-US/docs/Web/API/Fetch_API)"),this.fetch=loadOptions.fetchFunc):this.fetch=env().platform.fetch,assert(path!=null&&path.length>0,()=>"URL path for http must not be null, undefined or empty."),Array.isArray(path)&&assert(path.length===2,()=>`URL paths for http must have a length of 2, (actual length is ${path.length}).`),this.path=path,loadOptions.requestInit!=null&&loadOptions.requestInit.body!=null)throw new Error("requestInit is expected to have no pre-existing body, but has one.");this.requestInit=loadOptions.requestInit||{}}async save(modelArtifacts){if(modelArtifacts.modelTopology instanceof ArrayBuffer)throw new Error("BrowserHTTPRequest.save() does not support saving model topology in binary formats yet.");let init2=Object.assign({method:this.DEFAULT_METHOD},this.requestInit);init2.body=new FormData;let weightsManifest=[{paths:["./model.weights.bin"],weights:modelArtifacts.weightSpecs}],modelTopologyAndWeightManifest={modelTopology:modelArtifacts.modelTopology,format:modelArtifacts.format,generatedBy:modelArtifacts.generatedBy,convertedBy:modelArtifacts.convertedBy,weightsManifest};modelArtifacts.signature!=null&&(modelTopologyAndWeightManifest.signature=modelArtifacts.signature),modelArtifacts.userDefinedMetadata!=null&&(modelTopologyAndWeightManifest.userDefinedMetadata=modelArtifacts.userDefinedMetadata),modelArtifacts.modelInitializer!=null&&(modelTopologyAndWeightManifest.modelInitializer=modelArtifacts.modelInitializer),init2.body.append("model.json",new Blob([JSON.stringify(modelTopologyAndWeightManifest)],{type:JSON_TYPE}),"model.json"),modelArtifacts.weightData!=null&&init2.body.append("model.weights.bin",new Blob([modelArtifacts.weightData],{type:OCTET_STREAM_MIME_TYPE}),"model.weights.bin");let response=await this.fetch(this.path,init2);if(response.ok)return{modelArtifactsInfo:getModelArtifactsInfoForJSON(modelArtifacts),responses:[response]};throw new Error(`BrowserHTTPRequest.save() failed due to HTTP response status ${response.status}.`)}async load(){let modelConfigRequest=await this.fetch(this.path,this.requestInit);if(!modelConfigRequest.ok)throw new Error(`Request to ${this.path} failed with status code ${modelConfigRequest.status}. Please verify this URL points to the model JSON of the model to load.`);let mo
Actual:   ${actualFlat}.
Expected: ${expectedFlat}.`);for(let i=0;i<expectedFlat.length;++i){let a=actualFlat[i],e=expectedFlat[i];if(!predicate(a,e))throw new Error(`Arrays differ: actual[${i}] = ${a}, expected[${i}] = ${e}.
Actual:   ${actualFlat}.
Expected: ${expectedFlat}.`)}}function expectPromiseToFail(fn,done){fn().then(()=>done.fail(),()=>done())}function expectArraysEqual(actual,expected){let exp4=typeof expected=="string"||typeof expected=="number"||typeof expected=="boolean"?[expected]:expected;return isString(actual)||isString(actual[0])||isString(expected)||isString(expected[0])?expectArraysPredicate(actual,exp4,(a,b)=>a==b):expectArraysPredicate(actual,expected,(a,b)=>areClose(a,b,0))}function expectNumbersClose(a,e,epsilon3){if(epsilon3==null&&(epsilon3=testEpsilon()),!areClose(a,e,epsilon3))throw new Error(`Numbers differ: actual === ${a}, expected === ${e}`)}function areClose(a,e,epsilon3){return!isFinite(a)&&!isFinite(e)?!0:!(isNaN(a)||isNaN(e)||Math.abs(a-e)>epsilon3)}function expectValuesInRange(actual,low,high){for(let i=0;i<actual.length;i++)if(actual[i]<low||actual[i]>high)throw new Error(`Value out of range:${actual[i]} low: ${low}, high: ${high}`)}function expectArrayBuffersEqual(actual,expected){expect(new Float32Array(actual)).toEqual(new Float32Array(expected))}function encodeStrings(a){for(let i=0;i<a.length;i++){let val=a[i];Array.isArray(val)?encodeStrings(val):a[i]=encodeString(val)}return a}var version6="2.8.3";function enableProdMode(){env().set("PROD",!0)}function enableDebugMode(){env().set("DEBUG",!0)}function disableDeprecationWarnings(){env().set("DEPRECATION_WARNINGS_ENABLED",!1),console.warn("TensorFlow.js deprecation warnings have been disabled.")}function deprecationWarn(msg){env().getBool("DEPRECATION_WARNINGS_ENABLED")&&console.warn(msg+" You can disable deprecation warnings with tf.disableDeprecationWarnings().")}setDeprecationWarningFn(deprecationWarn);function disposeVariables(){ENGINE.disposeVariables()}function engine(){return ENGINE}function memory(){return ENGINE.memory()}function profile(f){return ENGINE.profile(f)}function tidy(nameOrFn,fn){return ENGINE.tidy(nameOrFn,fn)}function dispose(container){getTensorsInContainer(container).forEach(tensor2=>tensor2.dispose())}function keep(result){return ENGINE.keep(result)}function time(f){return ENGINE.time(f)}function setBackend(backendName){return ENGINE.setBackend(backendName)}function ready(){return ENGINE.ready()}function getBackend(){return ENGINE.backendName}function removeBackend(name){ENGINE.removeBackend(name)}function findBackend(name){return ENGINE.findBackend(name)}function findBackendFactory(name){return ENGINE.findBackendFactory(name)}function registerBackend(name,factory,priority=1){return ENGINE.registerBackend(name,factory,priority)}function backend(){return ENGINE.backend}function setPlatform(platformName,platform){env().setPlatform(platformName,platform)}function add_(a,b){let $a=convertToTensor(a,"a","add"),$b=convertToTensor(b,"b","add");[$a,$b]=makeTypesMatch($a,$b);let inputs={a:$a,b:$b};return ENGINE.runKernel(Add,inputs)}var add2=op({add_});function floorDiv_(a,b){let $a=convertToTensor(a,"a","floorDiv"),$b=convertToTensor(b,"b","floorDiv");[$a,$b]=makeTypesMatch($a,$b);let inputs={a:$a,b:$b};return ENGINE.runKernel(FloorDiv,inputs)}var floorDiv=op({floorDiv_});function div_(a,b){let $a=convertToTensor(a,"a","div"),$b=convertToTensor(b,"b","div");if([$a,$b]=makeTypesMatch($a,$b),$a.dtype==="int32"&&$b.dtype==="int32")return floorDiv($a,$b);let inputs={a:$a,b:$b},attrs={};return ENGINE.runKernel(RealDiv,inputs,attrs)}var div=op({div_});function mul_(a,b){let $a=convertToTensor(a,"a","mul"),$b=convertToTensor(b,"b","mul");[$a,$b]=makeTypesMatch($a,$b);let inputs={a:$a,b:$b};return ENGINE.runKernel(Multiply,inputs)}var mul=op({mul_});function abs_(x){let $x=convertToTensor(x,"x","abs");if($x.dtype==="complex64"){let inputs={x:$x};return ENGINE.runKernel(ComplexAbs,inputs)}else{let inputs={x:$x};return ENGINE.runKernel(Abs,inputs)}}var abs=op({abs_});function acos_(x){let inputs={x:convertToTensor(x,"x","acos")};return ENGINE.runKernel(Acos,inputs)}var acos=op({acos_});function acosh_(x){let inputs={x:convertToTensor(x,"x","acosh")};return ENGINE.runKernel(Acosh,inputs)}var acosh=op({acosh_});function addN_(tensors){assert(Array.isArray(tensors),()
          with dtype ${tensor2.dtype}. `)}),$tensors.length===1)return clone($tensors[0]);let inputs=$tensors,attr={axis};return ENGINE.runKernel(Concat,inputs,attr)}var concat=op({concat_});function sigmoid_(x){let inputs={x:convertToTensor(x,"x","sigmoid")};return ENGINE.runKernel(Sigmoid,inputs)}var sigmoid=op({sigmoid_});function slice_(x,begin,size){let $x=convertToTensor(x,"x","slice","string_or_numeric");if($x.rank===0)throw new Error("Slicing scalar is not possible");let inputs={x:$x},attrs={begin,size};return ENGINE.runKernel(Slice,inputs,attrs)}var slice=op({slice_});function tanh_(x){let inputs={x:convertToTensor(x,"x","tanh")};return ENGINE.runKernel(Tanh,inputs)}var tanh2=op({tanh_});function basicLSTMCell_(forgetBias,lstmKernel,lstmBias,data2,c,h){let $forgetBias=convertToTensor(forgetBias,"forgetBias","basicLSTMCell"),$lstmKernel=convertToTensor(lstmKernel,"lstmKernel","basicLSTMCell"),$lstmBias=convertToTensor(lstmBias,"lstmBias","basicLSTMCell"),$data=convertToTensor(data2,"data","basicLSTMCell"),$c=convertToTensor(c,"c","basicLSTMCell"),$h=convertToTensor(h,"h","basicLSTMCell"),combined=concat([$data,$h],1),weighted=matMul(combined,$lstmKernel),res=add2(weighted,$lstmBias),batchSize=res.shape[0],sliceCols=res.shape[1]/4,sliceSize=[batchSize,sliceCols],i=slice(res,[0,0],sliceSize),j=slice(res,[0,sliceCols],sliceSize),f=slice(res,[0,sliceCols*2],sliceSize),o=slice(res,[0,sliceCols*3],sliceSize),newC=add2(mul(sigmoid(i),tanh2(j)),mul($c,sigmoid(add2($forgetBias,f)))),newH=mul(tanh2(newC),sigmoid(o));return[newC,newH]}var basicLSTMCell=op({basicLSTMCell_});function batchToSpaceND_(x,blockShape,crops){let $x=convertToTensor(x,"x","batchToSpaceND"),prod5=blockShape.reduce((a,b)=>a*b);assert($x.rank>=1+blockShape.length,()=>`input rank is ${$x.rank} but should be > than blockShape.length ${blockShape.length}`),assert(crops.length===blockShape.length,()=>`crops.length is ${crops.length} but should be equal to blockShape.length  ${blockShape.length}`),assert($x.shape[0]%prod5==0,()=>`input tensor batch is ${$x.shape[0]} but is not divisible by the product of the elements of blockShape ${blockShape.join(" * ")} === ${prod5}`);let inputs={x:$x},attrs={blockShape,crops};return ENGINE.runKernel(BatchToSpaceND,inputs,attrs)}var batchToSpaceND=op({batchToSpaceND_});function xAs4D(x){let x4D;return x.rank===0||x.rank===1?x4D=reshape(x,[1,1,1,x.size]):x.rank===2?x4D=reshape(x,[1,1,x.shape[0],x.shape[1]]):x.rank===3?x4D=reshape(x,[1,x.shape[0],x.shape[1],x.shape[2]]):x4D=x,x4D}function batchNorm_(x,mean4,variance,offset,scale2,varianceEpsilon){varianceEpsilon==null&&(varianceEpsilon=.001);let $x=convertToTensor(x,"x","batchNorm"),$mean=convertToTensor(mean4,"mean","batchNorm"),$variance=convertToTensor(variance,"variance","batchNorm"),$scale;scale2!=null&&($scale=convertToTensor(scale2,"scale","batchNorm"));let $offset;offset!=null&&($offset=convertToTensor(offset,"offset","batchNorm")),assert($mean.rank===$variance.rank,()=>"Batch normalization gradient requires mean and variance to have equal ranks."),assert($offset==null||$mean.rank===$offset.rank,()=>"Batch normalization gradient requires mean and offset to have equal ranks."),assert($scale==null||$mean.rank===$scale.rank,()=>"Batch normalization gradient requires mean and scale to have equal ranks.");let inputs={x:xAs4D($x),scale:$scale,offset:$offset,mean:$mean,variance:$variance},attrs={varianceEpsilon},res=ENGINE.runKernel(FusedBatchNorm,inputs,attrs);return reshape(res,$x.shape)}var batchNorm=op({batchNorm_});function batchNorm2d_(x,mean4,variance,offset,scale2,varianceEpsilon){let $x=convertToTensor(x,"x","batchNorm"),$mean=convertToTensor(mean4,"mean","batchNorm"),$variance=convertToTensor(variance,"variance","batchNorm"),$scale;scale2!=null&&($scale=convertToTensor(scale2,"scale","batchNorm"));let $offset;return offset!=null&&($offset=convertToTensor(offset,"offset","batchNorm")),assert($x.rank===2,()=>`Error in batchNorm2D: x must be rank 2 but got rank ${$x.rank}.`),assert($mean.rank===2||$mean.rank===1,()=>`Error in batchNorm2D: mean must be rank 2 or ran
    ${inputHeight} and ${blockSize}  for depthToSpace with input shape
    ${$x.shape}`),assert(inputWidth*blockSize>=0,()=>`Negative dimension size caused by overflow when multiplying
    ${inputWidth} and ${blockSize} for depthToSpace with input shape
        ${$x.shape}`),assert(inputDepth%(blockSize*blockSize)==0,()=>`Dimension size must be evenly divisible by ${blockSize*blockSize} but is ${inputDepth} for depthToSpace with input shape ${$x.shape}`);let inputs={x:$x},attrs={blockSize,dataFormat};return ENGINE.runKernel(DepthToSpace,inputs,attrs)}var depthToSpace=op({depthToSpace_});function depthwiseConv2d_(x,filter,strides,pad3,dataFormat="NHWC",dilations=[1,1],dimRoundingMode){let $x=convertToTensor(x,"x","depthwiseConv2d"),$filter=convertToTensor(filter,"filter","depthwiseConv2d"),x4D=$x,reshapedTo4D=!1;$x.rank===3&&(reshapedTo4D=!0,x4D=reshape($x,[1,$x.shape[0],$x.shape[1],$x.shape[2]])),assert(x4D.rank===4,()=>`Error in depthwiseConv2d: input must be rank 4, but got rank ${x4D.rank}.`),assert($filter.rank===4,()=>`Error in depthwiseConv2d: filter must be rank 4, but got rank ${$filter.rank}.`),assert(x4D.shape[3]===$filter.shape[2],()=>`Error in depthwiseConv2d: number of input channels (${x4D.shape[3]}) must match the inChannels dimension in filter ${$filter.shape[2]}.`),dimRoundingMode!=null&&assert(isInt(pad3),()=>`Error in depthwiseConv2d: pad must be an integer when using, dimRoundingMode ${dimRoundingMode} but got pad ${pad3}.`);let inputs={x:x4D,filter:$filter},attrs={strides,pad:pad3,dataFormat,dilations,dimRoundingMode},res=ENGINE.runKernel(DepthwiseConv2dNative,inputs,attrs);return reshapedTo4D?reshape(res,[res.shape[1],res.shape[2],res.shape[3]]):res}var depthwiseConv2d=op({depthwiseConv2d_});function diag_(x){let inputs={x:convertToTensor(x,"x","diag")};return ENGINE.runKernel(Diag,inputs)}var diag=op({diag_});function dilation2d_(x,filter,strides,pad3,dilations=[1,1],dataFormat="NHWC"){let $x=convertToTensor(x,"x","dilation2d"),$filter=convertToTensor(filter,"filter","dilation2d");assert($x.rank===3||$x.rank===4,()=>`Error in dilation2d: input must be rank 3 or 4, but got rank ${$x.rank}.`),assert($filter.rank===3,()=>`Error in dilation2d: filter must be rank 3, but got rank ${$filter.rank}.`),assert(dataFormat==="NHWC",()=>`Error in dilation2d: Only NHWC is currently supported, but got dataFormat of ${dataFormat}`);let x4D=$x,reshapedTo4D=!1;$x.rank===3&&(x4D=reshape($x,[1,$x.shape[0],$x.shape[1],$x.shape[2]]),reshapedTo4D=!0);let inputs={x:x4D,filter:$filter},attrs={strides,pad:pad3,dilations},res=ENGINE.runKernel(Dilation2D,inputs,attrs);return reshapedTo4D?reshape(res,[res.shape[1],res.shape[2],res.shape[3]]):res}var dilation2d=op({dilation2d_});function getBroadcastDims(inShape,outShape){let inRank=inShape.length,dims=[];for(let i=0;i<inRank;i++){let dim=inRank-1-i,a=inShape[dim]||1;(outShape[outShape.length-1-i]||1)>1&&a===1&&dims.unshift(dim)}return dims}function getReductionAxes(inShape,outShape){let result=[];for(let i=0;i<outShape.length;i++){let inDim=inShape[inShape.length-i-1],outAxis=outShape.length-i-1,outDim=outShape[outAxis];(inDim==null||inDim===1&&outDim>1)&&result.unshift(outAxis)}return result}function assertAndGetBroadcastShape(shapeA,shapeB){let result=[],l=Math.max(shapeA.length,shapeB.length);for(let i=0;i<l;i++){let a=shapeA[shapeA.length-i-1];a==null&&(a=1);let b=shapeB[shapeB.length-i-1];if(b==null&&(b=1),a===1)result.unshift(b);else if(b===1)result.unshift(a);else if(a!==b){let errMsg=`Operands could not be broadcast together with shapes ${shapeA} and ${shapeB}.`;throw Error(errMsg)}else result.unshift(a)}return result}function equal_(a,b){let $a=convertToTensor(a,"a","equal"),$b=convertToTensor(b,"b","equal");[$a,$b]=makeTypesMatch($a,$b),assertAndGetBroadcastShape($a.shape,$b.shape);let inputs={a:$a,b:$b};return ENGINE.runKernel(Equal,inputs)}var equal=op({equal_});function where_(condition,a,b){let $a=convertToTensor(a,"a","where"),$b=convertToTensor(b,"b","where"),$condition=convertToTensor(condition,"condition","where","bool"),broadcastShape=assertAndGetBroadcastShape($a.shape,$b.shape),$broadcastedA=broadcastTo($a,broadcastShape),$broadcastedB=broadcastTo($b,broadcastShape);$condition.rank===1&&assert($condition.shape[0]===$a.shape[0],()=>"The first dimension of `a` must match the size of `condition`."),$conditi
               rank ${$x.rank}.`),assert(isInt(depthRadius),()=>`Error in localResponseNormalization: depthRadius must be an integer but got depthRadius ${depthRadius}.`);let x4D=$x,reshapedTo4D=!1;$x.rank===3&&(reshapedTo4D=!0,x4D=reshape($x,[1,$x.shape[0],$x.shape[1],$x.shape[2]]));let inputs={x:x4D},attrs={depthRadius,bias,alpha,beta},res=ENGINE.runKernel(LRN,inputs,attrs);return reshapedTo4D?reshape(res,[res.shape[1],res.shape[2],res.shape[3]]):res}var localResponseNormalization=op({localResponseNormalization_});function log_(x){let inputs={x:convertToTensor(x,"x","log")};return ENGINE.runKernel(Log,inputs)}var log2=op({log_});function log1p_(x){let inputs={x:convertToTensor(x,"x","log1p")};return ENGINE.runKernel(Log1p,inputs)}var log1p=op({log1p_});function grad(f){return assert(isFunction(f),()=>"The f passed in grad(f) must be a function"),(x,dy)=>{let $x=convertToTensor(x,"x","tf.grad","string_or_numeric"),$dy=dy!=null?convertToTensor(dy,"dy","tf.grad"):null;return ENGINE.tidy(()=>{let{value,grads:grads2}=ENGINE.gradients(()=>f($x),[$x],$dy);return $dy!=null&&assertShapesMatch(value.shape,$dy.shape,"The shape of dy passed in grad(f)(x, dy) must match the shape returned by f(x)"),checkGrads(grads2),grads2[0]})}}function grads(f){return assert(isFunction(f),()=>"The f passed in grads(f) must be a function"),(args,dy)=>{assert(Array.isArray(args),()=>"The args passed in grads(f)(args) must be an array of `Tensor`s or `TensorLike`s");let $args=convertToTensorArray(args,"args","tf.grads","string_or_numeric"),$dy=dy!=null?convertToTensor(dy,"dy","tf.grads"):null;return ENGINE.tidy(()=>{let{value,grads:grads2}=ENGINE.gradients(()=>f(...$args),$args,$dy);return $dy!=null&&assertShapesMatch(value.shape,$dy.shape,"The shape of dy passed in grads(f)([x1,...], dy) must match the shape returned by f([x1,...])"),checkGrads(grads2),grads2})}}function valueAndGrad(f){return assert(isFunction(f),()=>"The f passed in valueAndGrad(f) must be a function"),(x,dy)=>{assert(x instanceof Tensor,()=>"The x passed in valueAndGrad(f)(x) must be a tensor"),assert(dy==null||dy instanceof Tensor,()=>"The dy passed in valueAndGrad(f)(x, dy) must be a tensor");let{grads:grads2,value}=ENGINE.gradients(()=>f(x),[x],dy);return checkGrads(grads2),{grad:grads2[0],value}}}function valueAndGrads(f){return assert(isFunction(f),()=>"The f passed in valueAndGrads(f) must be a function"),(args,dy)=>{assert(Array.isArray(args)&&args.every(arg=>arg instanceof Tensor),()=>"The args passed in valueAndGrads(f)(args) must be array of tensors"),assert(dy==null||dy instanceof Tensor,()=>"The dy passed in valueAndGrads(f)(args, dy) must be a tensor");let res=ENGINE.gradients(()=>f(...args),args,dy);return dy!=null&&assertShapesMatch(res.value.shape,dy.shape,"The shape of dy passed in valueAndGrads(f)([x1,...], dy) must match the shape returned by f([x1,...])"),checkGrads(res.grads),res}}function variableGrads(f,varList){assert(isFunction(f),()=>"The f passed in variableGrads(f) must be a function"),assert(varList==null||Array.isArray(varList)&&varList.every(v=>v instanceof Variable),()=>"The varList passed in variableGrads(f, varList) must be an array of variables");let specifiedVarList=varList!=null;if(!specifiedVarList){varList=[];for(let varName in ENGINE.registeredVariables)varList.push(ENGINE.registeredVariables[varName])}let specifiedNonTrainable=specifiedVarList?varList.filter(variable2=>!variable2.trainable):null,originalVarCount=varList.length;varList=varList.filter(variable2=>variable2.trainable),assert(varList.length>0,()=>`variableGrads() expects at least one of the input variables to be trainable, but none of the ${originalVarCount} variables is trainable.`);let allowNoGradients=!0,{value,grads:grads2}=ENGINE.gradients(f,varList,null,allowNoGradients);assert(grads2.some(g=>g!=null),()=>"Cannot find a connection between any variable and the result of the loss function y=f(x). Please make sure the operations that use variables are inside the function f passed to minimize()."),assert(value.rank===0,()=>`The f passed in variableGrads(f) must return a sc
    the f you passed encloses all operations that lead from x to y.`)}function neg_(x){let inputs={x:convertToTensor(x,"x","neg")};return ENGINE.runKernel(Neg,inputs)}var neg=op({neg_});function softplus_(x){let inputs={x:convertToTensor(x,"x","softplus")};return ENGINE.runKernel(Softplus,inputs)}var softplus=op({softplus_});function logSigmoid_(x){let $x=convertToTensor(x,"x","logSigmoid");return customGrad(x2=>({value:neg(softplus(neg(x2))),gradFunc:dy=>mul(dy,sigmoid(neg(x2)))}))($x)}var logSigmoid=op({logSigmoid_});function max_(x,axis=null,keepDims=!1){let inputs={x:convertToTensor(x,"x","max")},attrs={reductionIndices:axis,keepDims};return ENGINE.runKernel(Max,inputs,attrs)}var max=op({max_});function sub_(a,b){let $a=convertToTensor(a,"a","sub"),$b=convertToTensor(b,"b","sub");[$a,$b]=makeTypesMatch($a,$b);let inputs={a:$a,b:$b};return ENGINE.runKernel(Sub,inputs)}var sub=op({sub_});function sum_(x,axis=null,keepDims=!1){let $x=convertToTensor(x,"x","sum");$x.dtype==="bool"&&($x=cast($x,"int32"));let inputs={x:$x},attrs={axis,keepDims};return ENGINE.runKernel(Sum,inputs,attrs)}var sum2=op({sum_});function logSoftmax_(logits,axis=-1){let $logits=convertToTensor(logits,"logits","logSoftmax");if(axis===-1&&(axis=$logits.rank-1),axis!==$logits.rank-1)throw Error(`Log Softmax along a non-last dimension is not yet supported. Logits was rank ${$logits.rank} and axis was ${axis}`);return customGrad((logits2,save)=>{let keepDims=!0,xMax=max(logits2,axis,!0),shifted=sub(logits2,xMax),value=sub(cast(shifted,"float32"),log2(sum2(exp(shifted),axis,keepDims)));return save([value]),{value,gradFunc:(dy,saved)=>{let[value2]=saved,keepDims2=!0,softmax6=exp(value2);return sub(dy,mul(sum2(dy,axis,keepDims2),softmax6))}}})($logits)}var logSoftmax=op({logSoftmax_});function axesAreInnerMostDims(axes,rank){for(let i=0;i<axes.length;++i)if(axes[axes.length-i-1]!==rank-1-i)return!1;return!0}function combineLocations(outputLoc,reduceLoc,axes){let rank=outputLoc.length+reduceLoc.length,loc=[],outIdx=0,reduceIdx=0;for(let dim=0;dim<rank;dim++)axes.indexOf(dim)===-1?loc.push(outputLoc[outIdx++]):loc.push(reduceLoc[reduceIdx++]);return loc}function computeOutAndReduceShapes(aShape,axes){let outShape=[],rank=aShape.length;for(let dim=0;dim<rank;dim++)axes.indexOf(dim)===-1&&outShape.push(aShape[dim]);let reduceShape=axes.map(dim=>aShape[dim]);return[outShape,reduceShape]}function expandShapeToKeepDim(shape,axes){let reduceSubShape=axes.map(x=>1);return combineLocations(shape,reduceSubShape,axes)}function assertAxesAreInnerMostDims(msg,axes,rank){assert(axesAreInnerMostDims(axes,rank),()=>`${msg} supports only inner-most axes for now. Got axes ${axes} and rank-${rank} input.`)}function getAxesPermutation(axes,rank){if(axesAreInnerMostDims(axes,rank))return null;let result=[];for(let i=0;i<rank;++i)axes.indexOf(i)===-1&&result.push(i);return axes.forEach(axis=>result.push(axis)),result}function getUndoAxesPermutation(axes){return axes.map((axis,i)=>[i,axis]).sort((a,b)=>a[1]-b[1]).map(x=>x[0])}function getInnerMostAxes(numAxes,rank){let res=[];for(let i=rank-numAxes;i<rank;++i)res.push(i);return res}function logSumExp_(x,axis=null,keepDims=!1){let $x=convertToTensor(x,"x","logSumExp"),axes=parseAxisParam(axis,$x.shape),xMax=max($x,axes,!0),a=sub($x,xMax),b=exp(a),c=sum2(b,axes),d=log2(c),res=add2(reshape(xMax,d.shape),d);if(keepDims){let newShape=expandShapeToKeepDim(res.shape,axes);return reshape(res,newShape)}return res}var logSumExp=op({logSumExp_});function logicalAnd_(a,b){let $a=convertToTensor(a,"a","logicalAnd","bool"),$b=convertToTensor(b,"b","logicalAnd","bool");assertAndGetBroadcastShape($a.shape,$b.shape);let inputs={a:$a,b:$b};return ENGINE.runKernel(LogicalAnd,inputs)}var logicalAnd=op({logicalAnd_});function logicalNot_(x){let inputs={x:convertToTensor(x,"x","logicalNot","bool")};return ENGINE.runKernel(LogicalNot,inputs)}var logicalNot=op({logicalNot_});function logicalOr_(a,b){let $a=convertToTensor(a,"a","logicalOr","bool"),$b=convertToTensor(b,"b","logicalOr","bool");assertAndGetBroadcastShape($a.shape,$b.shape);let inputs={a:
    ${xRank}).`);if(axis<batchDims)throw new Error(`batchDims (${batchDims}) must be less than or equal to axis (${axis}).`);for(let i=0;i<batchDims;++i)if(x.shape[i]!==indices.shape[i])throw new Error(`x.shape[${i}]: ${x.shape[i]} should be equal to indices.shape[${i}]: ${indices.shape[i]}.`);let dimSize=x.shape[axis],outputShape=[],batchSize=1,outerSize=1,sliceSize=1;for(let i=0;i<batchDims;++i)outputShape.push(x.shape[i]),batchSize*=x.shape[i];for(let i=batchDims;i<axis;i++)outputShape.push(x.shape[i]),outerSize*=x.shape[i];for(let i=batchDims;i<indicesRank;i++)outputShape.push(indices.shape[i]);for(let i=axis+1;i<xRank;i++)outputShape.push(x.shape[i]),sliceSize*=x.shape[i];return{batchSize,sliceSize,outerSize,dimSize,outputShape}}function castTensor(x,dtype,backend22){if(dtype==="complex64"){if(x.dtype==="complex64")return x.clone();let zerosTensor=zeros(x.shape),floatX=cast(x,"float32"),result=backend22.complex(floatX,zerosTensor);return zerosTensor.dispose(),floatX.dispose(),result}if(!hasEncodingLoss(x.dtype,dtype))return ENGINE.makeTensorFromDataId(x.dataId,x.shape,dtype);if(x.dtype==="complex64"){let real4=backend22.real(x),result=cast(real4,dtype);return real4.dispose(),result}if(dtype==="int32")return backend22.int(x);if(dtype==="bool"){let zero=scalar(0,x.dtype),result=backend22.notEqual(x,zero);return zero.dispose(),result}else throw new Error(`Error in Cast: failed to cast ${x.dtype} to ${dtype}`)}function reshapeTensor(x,shape){return ENGINE.makeTensorFromDataId(x.dataId,shape,x.dtype)}function fromUint8ToStringArray(vals){try{return vals.map(val=>decodeString(val))}catch(err){throw new Error(`Failed to decode encoded string bytes into utf-8, error: ${err}`)}}function fromStringArrayToUint8(strings){return strings.map(s=>encodeString(s))}var kernel_impls_exports={};__export2(kernel_impls_exports,{nonMaxSuppressionV3Impl:()=>nonMaxSuppressionV3Impl,nonMaxSuppressionV4Impl:()=>nonMaxSuppressionV4Impl,nonMaxSuppressionV5Impl:()=>nonMaxSuppressionV5Impl,whereImpl:()=>whereImpl});var absGradConfig={kernelName:Abs,inputsToSave:["x"],gradFunc:(dy,saved)=>{let[x]=saved;return{x:()=>mul(dy,step(cast(x,"float32"),-1))}}},acosGradConfig={kernelName:Acos,inputsToSave:["x"],gradFunc:(dy,saved)=>{let[x]=saved;return{x:()=>{let a=square(cast(x,"float32")),b=sqrt(sub(scalar(1),a));return neg(div(dy,b))}}}},acoshGradConfig={kernelName:Acosh,inputsToSave:["x"],gradFunc:(dy,saved)=>{let[x]=saved;return{x:()=>{let a=sqrt(sub(square(cast(x,"float32")),1));return div(dy,a)}}}},addGradConfig={kernelName:Add,inputsToSave:["a","b"],gradFunc:(dy,saved)=>{let[a,b]=saved,outShape=assertAndGetBroadcastShape(a.shape,b.shape);return{a:()=>{let res=dy,reduceAxes=getReductionAxes(a.shape,outShape);return reduceAxes.length>0&&(res=sum2(res,reduceAxes)),reshape(res,a.shape)},b:()=>{let res=dy,reduceAxes=getReductionAxes(b.shape,outShape);return reduceAxes.length>0&&(res=sum2(res,reduceAxes)),reshape(res,b.shape)}}}},addNGradConfig={kernelName:AddN,saveAllInputs:!0,gradFunc:(dy,saved)=>{let ders={};return saved.forEach((_,i)=>{ders[i]=()=>dy.clone()}),ders}},argMaxGradConfig={kernelName:ArgMax,inputsToSave:["x"],gradFunc:(dy,saved)=>{let[x]=saved;return{x:()=>zerosLike(x)}}},argMinGradConfig={kernelName:ArgMin,inputsToSave:["x"],gradFunc:(dy,saved)=>{let[x]=saved;return{x:()=>zerosLike(x)}}},asinGradConfig={kernelName:Asin,inputsToSave:["x"],gradFunc:(dy,saved)=>{let[x]=saved;return{x:()=>div(dy,sqrt(sub(scalar(1),square(cast(x,"float32")))))}}},asinhGradConfig={kernelName:Asinh,inputsToSave:["x"],gradFunc:(dy,saved)=>{let[x]=saved;return{x:()=>{let a=sqrt(add2(scalar(1),square(cast(x,"float32"))));return div(dy,a)}}}},atan2GradConfig={kernelName:Atan2,inputsToSave:["a","b"],gradFunc:(dy,saved)=>{let[a,b]=saved,outShape=assertAndGetBroadcastShape(a.shape,b.shape);return{a:()=>{let d=add2(square(a),square(b)),res=mul(dy,div(b,d)),reduceAxes=getReductionAxes(a.shape,outShape);return reduceAxes.length>0&&(res=sum2(res,reduceAxes)),reshape(res,a.shape)},b:()=>{let d=add2(square(a),square(b)),res=neg(mul(dy,div(a,d))),reduceAxes=getReductionAxes
============================
Hi there \u{1F44B}. Looks like you are running TensorFlow.js in Node.js. To speed things up dramatically, install our node backend, which binds to TensorFlow C++, by running npm i @tensorflow/tfjs-node, or npm i @tensorflow/tfjs-node-gpu if you have CUDA. Then call require('@tensorflow/tfjs-node'); (-gpu suffix for CUDA) at the start of your program. Visit https://github.com/tensorflow/tfjs-node for more details.
============================`));let dataId={};return this.data.set(dataId,{values,dtype,refCount:1}),dataId}makeTensorInfo(shape,dtype,values){let outId;if(dtype==="string"&&values!=null&&values.length>0&&util_exports.isString(values[0])){let encodedValues=values.map(d=>util_exports.encodeString(d));outId=this.write(encodedValues,shape,dtype)}else outId=this.write(values,shape,dtype);return{dataId:outId,shape,dtype}}incRef(dataId){let tensorData=this.data.get(dataId);tensorData.refCount++}decRef(dataId){if(this.data.has(dataId)){let tensorData=this.data.get(dataId);tensorData.refCount--}}move(dataId,values,shape,dtype){this.data.set(dataId,{values,dtype,refCount:1})}numDataIds(){return this.data.numDataIds()}async read(dataId){return this.readSync(dataId)}readSync(dataId){let{dtype,complexTensorInfos}=this.data.get(dataId);if(dtype==="complex64"){let realValues=this.readSync(complexTensorInfos.real.dataId),imagValues=this.readSync(complexTensorInfos.imag.dataId);return backend_util_exports.mergeRealAndImagArrays(realValues,imagValues)}return this.data.get(dataId).values}bufferSync(t){let data2=this.readSync(t.dataId),decodedData=data2;if(t.dtype==="string")try{decodedData=data2.map(d=>util_exports.decodeString(d))}catch(_a){throw new Error("Failed to decode encoded string bytes into utf-8")}return buffer(t.shape,t.dtype,decodedData)}makeOutput(values,shape,dtype){let dataId=this.write(values,shape,dtype);return engine().makeTensorFromDataId(dataId,shape,dtype,this)}disposeData(dataId){if(this.data.has(dataId)){let{complexTensorInfos}=this.data.get(dataId);complexTensorInfos!=null&&(this.disposeData(complexTensorInfos.real.dataId),this.disposeData(complexTensorInfos.imag.dataId)),this.data.delete(dataId)}}disposeIntermediateTensorInfo(tensorInfo){let dataId=tensorInfo.dataId;if(this.data.has(dataId)){let tensorData=this.data.get(dataId);tensorData.refCount--,tensorData.refCount<1&&this.disposeData(dataId)}}async time(f){let start=util_exports.now();return f(),{kernelMs:util_exports.now()-start}}memory(){return{unreliable:!0,reasons:["The reported memory is an upper bound. Due to automatic garbage collection, the true allocated memory may be less."]}}where(condition){assertNotComplex([condition],"where");let condVals=this.readSync(condition.dataId);return whereImpl2(condition.shape,condVals)}dispose(){}floatPrecision(){return 32}epsilon(){return super.epsilon()}},shared_exports={};__export2(shared_exports,{addImpl:()=>addImpl,bincountImpl:()=>bincountImpl,bincountReduceImpl:()=>bincountReduceImpl,ceilImpl:()=>ceilImpl,concatImpl:()=>concatImpl,expImpl:()=>expImpl,expm1Impl:()=>expm1Impl,floorImpl:()=>floorImpl,gatherV2Impl:()=>gatherV2Impl,greaterImpl:()=>greaterImpl,lessImpl:()=>lessImpl,linSpaceImpl:()=>linSpaceImpl,logImpl:()=>logImpl,maxImpl:()=>maxImpl,maximumImpl:()=>maximumImpl,minimumImpl:()=>minimumImpl,multiplyImpl:()=>multiplyImpl,negImpl:()=>negImpl,notEqualImpl:()=>notEqualImpl,prodImpl:()=>prodImpl,rangeImpl:()=>rangeImpl,rsqrtImpl:()=>rsqrtImpl,simpleAbsImpl:()=>simpleAbsImpl,sliceImpl:()=>sliceImpl,squaredDifferenceImpl:()=>squaredDifferenceImpl,stridedSliceImpl:()=>stridedSliceImpl,subImpl:()=>subImpl,tileImpl:()=>tileImpl,topKImpl:()=>topKImpl,transposeImpl:()=>transposeImpl,uniqueImpl:()=>uniqueImpl});function simpleAbsImpl(vals){let resultValues=new Float32Array(vals.length);for(let i=0;i<vals.length;++i)resultValues[i]=Math.abs(vals[i]);return resultValues}var abs2=args=>{let{x}=args.inputs,cpuBackend=args.backend;assertNotComplex(x,"abs");let resultValues=new Float32Array(util_exports.sizeFromShape(x.shape)),values=cpuBackend.data.get(x.dataId).values;return resultValues=simpleAbsImpl(values),cpuBackend.makeOutput(resultValues,x.shape,"float32")},absConfig={kernelName:Abs,backendName:"cpu",kernelFunc:abs2};function createSimpleBinaryKernelImpl(op2){return(aShape,bShape,aVals,bVals,dtype)=>{let newShape=backend_util_exports.assertAndGetBroadcastShape(aShape,bShape),resultRank=newShape.length,resultStrides=util_exports.computeStrides(newShape),resultSize=util_exports.sizeFromShape(newShape),result=util
`),pad3=shaderLines.length.toString().length+2,linesWithLineNumbers=shaderLines.map((line,lineNumber2)=>util_exports.rightPad((lineNumber2+1).toString(),pad3)+line),maxLineLength=0;for(let i=0;i<linesWithLineNumbers.length;i++)maxLineLength=Math.max(linesWithLineNumbers[i].length,maxLineLength);let beforeErrorLines=linesWithLineNumbers.slice(0,lineNumber-1),errorLine=linesWithLineNumbers.slice(lineNumber-1,lineNumber),afterErrorLines=linesWithLineNumbers.slice(lineNumber);console.log(beforeErrorLines.join(`
`)),console.log(shaderInfoLog.split(`
`)[0]),console.log(`%c ${util_exports.rightPad(errorLine[0],maxLineLength)}`,"border:1px solid red; background-color:#e3d2d2; color:#a61717"),console.log(afterErrorLines.join(`
`))}function createProgram(gl){return throwIfNull(gl,()=>gl.createProgram(),"Unable to create WebGLProgram.")}function linkProgram(gl,program){if(callAndCheck(gl,()=>gl.linkProgram(program)),gl.getProgramParameter(program,gl.LINK_STATUS)===!1)throw console.log(gl.getProgramInfoLog(program)),new Error("Failed to link vertex and fragment shaders.")}function validateProgram(gl,program){if(callAndCheck(gl,()=>gl.validateProgram(program)),gl.getProgramParameter(program,gl.VALIDATE_STATUS)===!1)throw console.log(gl.getProgramInfoLog(program)),new Error("Shader program validation failed.")}function createStaticVertexBuffer(gl,data2){let buffer2=throwIfNull(gl,()=>gl.createBuffer(),"Unable to create WebGLBuffer");return callAndCheck(gl,()=>gl.bindBuffer(gl.ARRAY_BUFFER,buffer2)),callAndCheck(gl,()=>gl.bufferData(gl.ARRAY_BUFFER,data2,gl.STATIC_DRAW)),buffer2}function createStaticIndexBuffer(gl,data2){let buffer2=throwIfNull(gl,()=>gl.createBuffer(),"Unable to create WebGLBuffer");return callAndCheck(gl,()=>gl.bindBuffer(gl.ELEMENT_ARRAY_BUFFER,buffer2)),callAndCheck(gl,()=>gl.bufferData(gl.ELEMENT_ARRAY_BUFFER,data2,gl.STATIC_DRAW)),buffer2}function getNumChannels(){return env().getNumber("WEBGL_VERSION")===2?1:4}function createTexture(gl){return throwIfNull(gl,()=>gl.createTexture(),"Unable to create WebGLTexture.")}function validateTextureSize(width,height){let maxTextureSize=env().getNumber("WEBGL_MAX_TEXTURE_SIZE");if(width<=0||height<=0){let requested=`[${width}x${height}]`;throw new Error("Requested texture size "+requested+" is invalid.")}if(width>maxTextureSize||height>maxTextureSize){let requested=`[${width}x${height}]`,max6=`[${maxTextureSize}x${maxTextureSize}]`;throw new Error("Requested texture size "+requested+" greater than WebGL maximum on this browser / GPU "+max6+".")}}function createFramebuffer(gl){return throwIfNull(gl,()=>gl.createFramebuffer(),"Unable to create WebGLFramebuffer.")}function bindVertexBufferToProgramAttribute(gl,program,attribute,buffer2,arrayEntriesPerItem,itemStrideInBytes,itemOffsetInBytes){let loc=gl.getAttribLocation(program,attribute);return loc===-1?!1:(callAndCheck(gl,()=>gl.bindBuffer(gl.ARRAY_BUFFER,buffer2)),callAndCheck(gl,()=>gl.vertexAttribPointer(loc,arrayEntriesPerItem,gl.FLOAT,!1,itemStrideInBytes,itemOffsetInBytes)),callAndCheck(gl,()=>gl.enableVertexAttribArray(loc)),!0)}function bindTextureUnit(gl,texture,textureUnit){validateTextureUnit(gl,textureUnit),callAndCheck(gl,()=>gl.activeTexture(gl.TEXTURE0+textureUnit)),callAndCheck(gl,()=>gl.bindTexture(gl.TEXTURE_2D,texture))}function unbindTextureUnit(gl,textureUnit){validateTextureUnit(gl,textureUnit),callAndCheck(gl,()=>gl.activeTexture(gl.TEXTURE0+textureUnit)),callAndCheck(gl,()=>gl.bindTexture(gl.TEXTURE_2D,null))}function getProgramUniformLocationOrThrow(gl,program,uniformName){return throwIfNull(gl,()=>gl.getUniformLocation(program,uniformName),'uniform "'+uniformName+'" not present in program.')}function getProgramUniformLocation(gl,program,uniformName){return gl.getUniformLocation(program,uniformName)}function bindTextureToProgramUniformSampler(gl,texture,uniformSamplerLocation,textureUnit){callAndCheck(gl,()=>bindTextureUnit(gl,texture,textureUnit)),callAndCheck(gl,()=>gl.uniform1i(uniformSamplerLocation,textureUnit))}function bindCanvasToFramebuffer(gl){callAndCheck(gl,()=>gl.bindFramebuffer(gl.FRAMEBUFFER,null)),callAndCheck(gl,()=>gl.viewport(0,0,gl.canvas.width,gl.canvas.height)),callAndCheck(gl,()=>gl.scissor(0,0,gl.canvas.width,gl.canvas.height))}function bindColorTextureToFramebuffer(gl,texture,framebuffer){callAndCheck(gl,()=>gl.bindFramebuffer(gl.FRAMEBUFFER,framebuffer)),callAndCheck(gl,()=>gl.framebufferTexture2D(gl.FRAMEBUFFER,gl.COLOR_ATTACHMENT0,gl.TEXTURE_2D,texture,0))}function unbindColorTextureFromFramebuffer(gl,framebuffer){callAndCheck(gl,()=>gl.bindFramebuffer(gl.FRAMEBUFFER,framebuffer)),callAndCheck(gl,()=>gl.framebufferTexture2D(gl.FRAMEBUFFER,gl.COLOR_ATTACHMENT0,gl.TEXTURE_2D,null,0))}function validateFramebuffer(gl){let status=gl.checkFramebufferStatus(gl.FRAMEBUFFER);if(status!==gl.FRAM
      bool isnan_custom(float val) {
        return (val > 0.0 || val < 0.0) ? false : val != 0.0;
      }

      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)
    `,defineSpecialInf="",defineRound=`
      #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)));
      }
    `):(version142="",attribute="attribute",varyingVs="varying",varyingFs="varying",texture2D="texture2D",output="gl_FragColor",defineOutput="",defineSpecialNaN=`
      #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));
      }
    `,defineSpecialInf=`
      uniform float INFINITY;

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

      ivec4 round(vec4 value) {
        return ivec4(floor(value + vec4(0.5)));
      }
    `),{version:version142,attribute,varyingVs,varyingFs,texture2D,output,defineOutput,defineSpecialNaN,defineSpecialInf,defineRound}}function getLogicalCoordinatesFromFlatIndex(coords2,shape,index="index"){let strides=util_exports.computeStrides(shape);return strides.map((stride,i)=>{let line1=`int ${coords2[i]} = ${index} / ${stride}`,line2=i===strides.length-1?`int ${coords2[i+1]} = ${index} - ${coords2[i]} * ${stride}`:`index -= ${coords2[i]} * ${stride}`;return`${line1}; ${line2};`}).join("")}function getFlatIndexFrom3D(shape){let strides=util_exports.computeStrides(shape).map(d=>d.toString());return`
  int getFlatIndex(ivec3 coords) {
    return coords.x * ${strides[0]} + coords.y * ${strides[1]} + coords.z;
  }
`}var ENCODE_FLOAT_SNIPPET=`
  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;
  }
`,DecodeMatrixProgram=class{constructor(outputShape){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outPackingScheme=PackingScheme.DENSE;let texShape=getDenseTexShape(outputShape),glsl=getGlslDifferences();this.outputShape=outputShape,this.userCode=`
      ivec3 outCoordsFromFlatIndex(int index) {
        ${getLogicalCoordinatesFromFlatIndex(["r","c","d"],outputShape)}
        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);
        }

        ${glsl.output} = result;
      }
    `}},DecodeMatrixPackedProgram=class{constructor(outputShape){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outPackingScheme=PackingScheme.DENSE;let texShape=getDenseTexShape(outputShape),glsl=getGlslDifferences();this.outputShape=outputShape,this.userCode=`
      ivec3 outCoordsFromFlatIndex(int index) {
        ${getLogicalCoordinatesFromFlatIndex(["r","c","d"],outputShape)}
        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));
        }

        ${glsl.output} = result;
      }
    `}},EncodeFloatProgram=class{constructor(outputShape){this.variableNames=["A"],this.outTexUsage=TextureUsage.DOWNLOAD;let glsl=getGlslDifferences();this.outputShape=outputShape,this.userCode=`
      ${ENCODE_FLOAT_SNIPPET}

      void main() {
        float x = getAAtOutCoords();
        ${glsl.output} = encode_float(x);
      }
    `}},EncodeFloatPackedProgram=class{constructor(outputShape){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outTexUsage=TextureUsage.DOWNLOAD;let glsl=getGlslDifferences();this.outputShape=outputShape,this.userCode=`
      ${ENCODE_FLOAT_SNIPPET}

      void main() {
        ivec3 coords = getOutputCoords();
        float x = getChannel(getAAtOutCoords(), vec2(coords.y, coords.z));
        ${glsl.output} = encode_float(x);
      }
    `}},EncodeMatrixProgram=class{constructor(outputShape,texShape,inputIsUnsignedByte=!1){this.variableNames=["A"];let glsl=getGlslDifferences(),[height,width]=texShape;this.outputShape=outputShape;let output="result";inputIsUnsignedByte&&(output="floor(result * 255. + 0.5)"),this.userCode=`
      ${getFlatIndexFrom3D(outputShape)}

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

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

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

        int r = flatIndex / ${width};
        int c = imod(flatIndex, ${width});
        vec2 uv = (vec2(c, r) + halfCR) / vec2(${width}.0, ${height}.0);
        vec4 values = ${glsl.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];
        }

        ${glsl.output} = vec4(${output}, 0., 0., 0.);
      }
    `}},EncodeMatrixPackedProgram=class{constructor(outputShape,texShape,inputIsUnsignedByte=!1){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0;let glsl=getGlslDifferences(),[height,width]=texShape;this.outputShape=outputShape;let mainLoop="",output="result";inputIsUnsignedByte&&(output="floor(result * 255. + 0.5)");for(let row=0;row<=1;row++)for(let col=0;col<=1;col++){let channel=row*2+col;mainLoop+=`
          localCoords = coords;
          if(localCoords[2] + ${col} < ${outputShape[2]}) {
            localCoords[2] += ${col};
            if(localCoords[1] + ${row} < ${outputShape[1]}) {
              localCoords[1] += ${row};

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

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

              r = flatIndex / ${width};
              c = imod(flatIndex, ${width});
              uv = (vec2(c, r) + halfCR) / vec2(${width}.0, ${height}.0);
              values = ${glsl.texture2D}(A, uv);

              if(offset == 0) {
                result[${channel}] = values[0];
              } else if(offset == 1) {
                result[${channel}] = values[1];
              } else if(offset == 2) {
                result[${channel}] = values[2];
              } else {
                result[${channel}] = values[3];
              }
            }
          }
        `}this.userCode=`
      ${getFlatIndexFrom3D(outputShape)}

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

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

        ${mainLoop}

        ${glsl.output} = ${output};
      }
    `}},gpgpu_util_exports={};__export2(gpgpu_util_exports,{bindVertexProgramAttributeStreams:()=>bindVertexProgramAttributeStreams,createBufferFromOutputTexture:()=>createBufferFromOutputTexture,createFloat16MatrixTexture:()=>createFloat16MatrixTexture,createFloat16PackedMatrixTexture:()=>createFloat16PackedMatrixTexture,createFloat32MatrixTexture:()=>createFloat32MatrixTexture,createIndexBuffer:()=>createIndexBuffer,createPackedMatrixTexture:()=>createPackedMatrixTexture,createUnsignedBytesMatrixTexture:()=>createUnsignedBytesMatrixTexture,createVertexBuffer:()=>createVertexBuffer,createVertexShader:()=>createVertexShader2,downloadByteEncodedFloatMatrixFromOutputTexture:()=>downloadByteEncodedFloatMatrixFromOutputTexture,downloadFloat32MatrixFromBuffer:()=>downloadFloat32MatrixFromBuffer,downloadMatrixFromPackedOutputTexture:()=>downloadMatrixFromPackedOutputTexture,downloadPackedMatrixFromBuffer:()=>downloadPackedMatrixFromBuffer,getInternalFormatForFloat16MatrixTexture:()=>getInternalFormatForFloat16MatrixTexture,getInternalFormatForFloat16PackedMatrixTexture:()=>getInternalFormatForFloat16PackedMatrixTexture,getInternalFormatForFloat32MatrixTexture:()=>getInternalFormatForFloat32MatrixTexture,getInternalFormatForPackedMatrixTexture:()=>getInternalFormatForPackedMatrixTexture,getInternalFormatForUnsignedBytesMatrixTexture:()=>getInternalFormatForUnsignedBytesMatrixTexture,uploadDenseMatrixToTexture:()=>uploadDenseMatrixToTexture,uploadPixelDataToTexture:()=>uploadPixelDataToTexture});function createVertexShader2(gl){let glsl=getGlslDifferences(),vertexShaderSource=`${glsl.version}
    precision highp float;
    ${glsl.attribute} vec3 clipSpacePos;
    ${glsl.attribute} vec2 uv;
    ${glsl.varyingVs} vec2 resultUV;

    void main() {
      gl_Position = vec4(clipSpacePos, 1);
      resultUV = uv;
    }`;return createVertexShader(gl,vertexShaderSource)}function createVertexBuffer(gl){let vertexArray=new Float32Array([-1,1,0,0,1,-1,-1,0,0,0,1,1,0,1,1,1,-1,0,1,0]);return createStaticVertexBuffer(gl,vertexArray)}function createIndexBuffer(gl){let triangleVertexIndices=new Uint16Array([0,1,2,2,1,3]);return createStaticIndexBuffer(gl,triangleVertexIndices)}function createAndConfigureTexture(gl,width,height,internalFormat,textureFormat,textureType){validateTextureSize(width,height);let texture=createTexture(gl),tex2d=gl.TEXTURE_2D;return callAndCheck(gl,()=>gl.bindTexture(tex2d,texture)),callAndCheck(gl,()=>gl.texParameteri(tex2d,gl.TEXTURE_WRAP_S,gl.CLAMP_TO_EDGE)),callAndCheck(gl,()=>gl.texParameteri(tex2d,gl.TEXTURE_WRAP_T,gl.CLAMP_TO_EDGE)),callAndCheck(gl,()=>gl.texParameteri(tex2d,gl.TEXTURE_MIN_FILTER,gl.NEAREST)),callAndCheck(gl,()=>gl.texParameteri(tex2d,gl.TEXTURE_MAG_FILTER,gl.NEAREST)),callAndCheck(gl,()=>gl.texImage2D(tex2d,0,internalFormat,width,height,0,textureFormat,textureType,null)),callAndCheck(gl,()=>gl.bindTexture(gl.TEXTURE_2D,null)),texture}function getInternalFormatForFloat32MatrixTexture(textureConfig){return textureConfig.internalFormatFloat}function createFloat32MatrixTexture(gl,rows,columns,textureConfig){let[width,height]=getUnpackedMatrixTextureShapeWidthHeight(rows,columns);return createAndConfigureTexture(gl,width,height,getInternalFormatForFloat32MatrixTexture(textureConfig),textureConfig.textureFormatFloat,gl.FLOAT)}function getInternalFormatForFloat16MatrixTexture(textureConfig){return textureConfig.internalFormatHalfFloat}function createFloat16MatrixTexture(gl,rows,columns,textureConfig){let[width,height]=getUnpackedMatrixTextureShapeWidthHeight(rows,columns);return createAndConfigureTexture(gl,width,height,getInternalFormatForFloat16MatrixTexture(textureConfig),textureConfig.textureFormatFloat,textureConfig.textureTypeHalfFloat)}function getInternalFormatForUnsignedBytesMatrixTexture(textureConfig){return textureConfig.downloadTextureFormat}function createUnsignedBytesMatrixTexture(gl,rows,columns,textureConfig){let[width,height]=getUnpackedMatrixTextureShapeWidthHeight(rows,columns);return createAndConfigureTexture(gl,width,height,getInternalFormatForUnsignedBytesMatrixTexture(textureConfig),gl.RGBA,gl.UNSIGNED_BYTE)}function getInternalFormatForPackedMatrixTexture(textureConfig){return textureConfig.internalFormatPackedFloat}function createPackedMatrixTexture(gl,rows,columns,textureConfig){let[width,height]=getPackedMatrixTextureShapeWidthHeight(rows,columns);return createAndConfigureTexture(gl,width,height,getInternalFormatForPackedMatrixTexture(textureConfig),gl.RGBA,gl.FLOAT)}function getInternalFormatForFloat16PackedMatrixTexture(textureConfig){return textureConfig.internalFormatPackedHalfFloat}function createFloat16PackedMatrixTexture(gl,rows,columns,textureConfig){let[width,height]=getPackedMatrixTextureShapeWidthHeight(rows,columns);return createAndConfigureTexture(gl,width,height,getInternalFormatForFloat16PackedMatrixTexture(textureConfig),gl.RGBA,textureConfig.textureTypeHalfFloat)}function bindVertexProgramAttributeStreams(gl,program,vertexBuffer){let posOffset=0,uvOffset=3*4,stride=3*4+2*4;return callAndCheck(gl,()=>gl.bindBuffer(gl.ARRAY_BUFFER,vertexBuffer)),bindVertexBufferToProgramAttribute(gl,program,"clipSpacePos",vertexBuffer,3,stride,posOffset)&&bindVertexBufferToProgramAttribute(gl,program,"uv",vertexBuffer,2,stride,uvOffset)}function uploadDenseMatrixToTexture(gl,texture,width,height,data2,textureConfig){callAndCheck(gl,()=>gl.bindTexture(gl.TEXTURE_2D,texture));let dataForUpload,texelDataType,internalFormat;data2 instanceof Uint8Array?(dataForUpload=new Uint8Array(width*height*4),texelDataType=gl.UNSIGNED_BYTE,internalFormat=gl.RGBA):(dataForUpload=new Float32Array(width*height*4),texelDataType=gl.FLOAT,internalFormat=textureConfig.internalFormatPackedFloat),dataForUpload.set(data2),callAndCheck(gl,()=>gl.texImage2D(gl.TEXTURE_2D,0,internalFormat,width,height,0,gl.RGBA,texelDataType,dataForUpload)),callAndCheck(gl,()=>gl.bindTexture(gl.TEXTURE_2D,null))}func
`),inputSamplingSnippet=inputsInfo.map(x=>getInputSamplingSnippet(x,outputShape,usesPackedTextures)).join(`
`),outTexShape=outputShape.texShape,glsl=getGlslDifferences(),floatTextureSampleSnippet=getFloatTextureSampleSnippet(glsl),outputSamplingSnippet,floatTextureSetOutputSnippet,shaderPrefix=getShaderPrefix(glsl);return outputShape.isPacked?(outputSamplingSnippet=getPackedOutputSamplingSnippet(outputShape.logicalShape,outTexShape),floatTextureSetOutputSnippet=getFloatTextureSetRGBASnippet(glsl)):(outputSamplingSnippet=getOutputSamplingSnippet(outputShape.logicalShape,outTexShape),floatTextureSetOutputSnippet=getFloatTextureSetRSnippet(glsl)),usesPackedTextures&&(shaderPrefix+=SHADER_PACKED_PREFIX),[shaderPrefix,floatTextureSampleSnippet,floatTextureSetOutputSnippet,inputPrefixSnippet,outputSamplingSnippet,inputSamplingSnippet,userCode].join(`
`)}function getSamplerFromInInfo(inInfo){let shape=inInfo.shapeInfo.logicalShape;switch(shape.length){case 0:return getSamplerScalar(inInfo);case 1:return getSampler1D(inInfo);case 2:return getSampler2D(inInfo);case 3:return getSampler3D(inInfo);case 4:return getSampler4D(inInfo);case 5:return getSampler5D(inInfo);case 6:return getSampler6D(inInfo);default:throw new Error(`${shape.length}-D input sampling is not yet supported`)}}function getPackedSamplerFromInInfo(inInfo){switch(inInfo.shapeInfo.logicalShape.length){case 0:return getPackedSamplerScalar(inInfo);case 1:return getPackedSampler1D(inInfo);case 2:return getPackedSampler2D(inInfo);case 3:return getPackedSampler3D(inInfo);default:return getPackedSamplerND(inInfo)}}function getInputSamplingSnippet(inInfo,outShapeInfo,usesPackedTextures=!1){let res="";usesPackedTextures?res+=getPackedSamplerFromInInfo(inInfo):res+=getSamplerFromInInfo(inInfo);let inShape=inInfo.shapeInfo.logicalShape,outShape=outShapeInfo.logicalShape;return inShape.length<=outShape.length&&(usesPackedTextures?res+=getPackedSamplerAtOutputCoords(inInfo,outShapeInfo):res+=getSamplerAtOutputCoords(inInfo,outShapeInfo)),res}function getPackedOutputSamplingSnippet(outShape,outTexShape){switch(outShape.length){case 0:return getOutputScalarCoords();case 1:return getOutputPacked1DCoords(outShape,outTexShape);case 2:return getOutputPacked2DCoords(outShape,outTexShape);case 3:return getOutputPacked3DCoords(outShape,outTexShape);default:return getOutputPackedNDCoords(outShape,outTexShape)}}function getOutputSamplingSnippet(outShape,outTexShape){switch(outShape.length){case 0:return getOutputScalarCoords();case 1:return getOutput1DCoords(outShape,outTexShape);case 2:return getOutput2DCoords(outShape,outTexShape);case 3:return getOutput3DCoords(outShape,outTexShape);case 4:return getOutput4DCoords(outShape,outTexShape);case 5:return getOutput5DCoords(outShape,outTexShape);case 6:return getOutput6DCoords(outShape,outTexShape);default:throw new Error(`${outShape.length}-D output sampling is not yet supported`)}}function getFloatTextureSampleSnippet(glsl){return`
    float sampleTexture(sampler2D textureSampler, vec2 uv) {
      return ${glsl.texture2D}(textureSampler, uv).r;
    }
  `}function getFloatTextureSetRSnippet(glsl){return`
    void setOutput(float val) {
      ${glsl.output} = vec4(val, 0, 0, 0);
    }
  `}function getFloatTextureSetRGBASnippet(glsl){return`
    void setOutput(vec4 val) {
      ${glsl.output} = val;
    }
  `}function getShaderPrefix(glsl){return`${glsl.version}
    precision highp float;
    precision highp int;
    precision highp sampler2D;
    ${glsl.varyingFs} vec2 resultUV;
    ${glsl.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;
    ${glsl.defineSpecialNaN}
    ${glsl.defineSpecialInf}
    ${glsl.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);
    }

    ${SAMPLE_1D_SNIPPET}
    ${SAMPLE_2D_SNIPPET}
    ${SAMPLE_3D_SNIPPET}
  `}var SAMPLE_1D_SNIPPET=`
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);
}
`,SAMPLE_2D_SNIPPET=`
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);
}
`,SAMPLE_3D_SNIPPET=`
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);
}
`,SHADER_PACKED_PREFIX=`
  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 getOutputScalarCoords(){return`
    int getOutputCoords() {
      return 0;
    }
  `}function getOutputPacked1DCoords(shape,texShape){let packedTexShape=[Math.ceil(texShape[0]/2),Math.ceil(texShape[1]/2)];return packedTexShape[0]===1?`
      int getOutputCoords() {
        return 2 * int(resultUV.x * ${packedTexShape[1]}.0);
      }
    `:packedTexShape[1]===1?`
      int getOutputCoords() {
        return 2 * int(resultUV.y * ${packedTexShape[0]}.0);
      }
    `:`
    int getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(${packedTexShape[0]}, ${packedTexShape[1]}));
      return 2 * (resTexRC.x * ${packedTexShape[1]} + resTexRC.y);
    }
  `}function getOutput1DCoords(shape,texShape){return texShape[0]===1?`
      int getOutputCoords() {
        return int(resultUV.x * ${texShape[1]}.0);
      }
    `:texShape[1]===1?`
      int getOutputCoords() {
        return int(resultUV.y * ${texShape[0]}.0);
      }
    `:`
    int getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(${texShape[0]}, ${texShape[1]}));
      return resTexRC.x * ${texShape[1]} + resTexRC.y;
    }
  `}function getOutputPacked3DCoords(shape,texShape){let packedTexShape=[Math.ceil(texShape[0]/2),Math.ceil(texShape[1]/2)],texelsInLogicalRow=Math.ceil(shape[2]/2),texelsInBatch=texelsInLogicalRow*Math.ceil(shape[1]/2);return`
    ivec3 getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(${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);
    }
  `}function getOutput3DCoords(shape,texShape){let coordsFromIndexSnippet=getLogicalCoordinatesFromFlatIndex(["r","c","d"],shape);return`
    ivec3 getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(${texShape[0]}, ${texShape[1]}));
      int index = resTexRC.x * ${texShape[1]} + resTexRC.y;
      ${coordsFromIndexSnippet}
      return ivec3(r, c, d);
    }
  `}function getOutputPackedNDCoords(shape,texShape){let packedTexShape=[Math.ceil(texShape[0]/2),Math.ceil(texShape[1]/2)],texelsInLogicalRow=Math.ceil(shape[shape.length-1]/2),texelsInBatch=texelsInLogicalRow*Math.ceil(shape[shape.length-2]/2),texelsInBatchN=texelsInBatch,batches="",coords2="b, r, c";for(let b=2;b<shape.length-1;b++)texelsInBatchN*=shape[shape.length-b-1],batches=`
      int b${b} = index / ${texelsInBatchN};
      index -= b${b} * ${texelsInBatchN};
    `+batches,coords2=`b${b}, `+coords2;return`
    ivec${shape.length} getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(${packedTexShape[0]}, ${packedTexShape[1]}));
      int index = resTexRC.x * ${packedTexShape[1]} + resTexRC.y;

      ${batches}

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

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

      return ivec${shape.length}(${coords2});
    }
  `}function getOutput4DCoords(shape,texShape){let coordsFromIndexSnippet=getLogicalCoordinatesFromFlatIndex(["r","c","d","d2"],shape);return`
    ivec4 getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
        vec2(${texShape[0]}, ${texShape[1]}));
      int index = resTexRC.x * ${texShape[1]} + resTexRC.y;
      ${coordsFromIndexSnippet}
      return ivec4(r, c, d, d2);
    }
  `}function getOutput5DCoords(shape,texShape){let coordsFromIndexSnippet=getLogicalCoordinatesFromFlatIndex(["r","c","d","d2","d3"],shape);return`
    ivec5 getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx * vec2(${texShape[0]},
                             ${texShape[1]}));

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

      ${coordsFromIndexSnippet}

      ivec5 outShape = ivec5(r, c, d, d2, d3);
      return outShape;
    }
  `}function getOutput6DCoords(shape,texShape){let coordsFromIndexSnippet=getLogicalCoordinatesFromFlatIndex(["r","c","d","d2","d3","d4"],shape);return`
    ivec6 getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
        vec2(${texShape[0]}, ${texShape[1]}));
      int index = resTexRC.x * ${texShape[1]} + resTexRC.y;

      ${coordsFromIndexSnippet}

      ivec6 result = ivec6(r, c, d, d2, d3, d4);
      return result;
    }
  `}function getOutputPacked2DCoords(shape,texShape){let packedTexShape=[Math.ceil(texShape[0]/2),Math.ceil(texShape[1]/2)];if(util_exports.arraysEqual(shape,texShape))return`
      ivec2 getOutputCoords() {
        return 2 * ivec2(resultUV.yx * vec2(${packedTexShape[0]}, ${packedTexShape[1]}));
      }
    `;let texelsInLogicalRow=Math.ceil(shape[1]/2);return`
    ivec2 getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(${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);
    }
  `}function getOutput2DCoords(shape,texShape){return util_exports.arraysEqual(shape,texShape)?`
      ivec2 getOutputCoords() {
        return ivec2(resultUV.yx * vec2(${texShape[0]}, ${texShape[1]}));
      }
    `:shape[1]===1?`
      ivec2 getOutputCoords() {
        ivec2 resTexRC = ivec2(resultUV.yx *
                               vec2(${texShape[0]}, ${texShape[1]}));
        int index = resTexRC.x * ${texShape[1]} + resTexRC.y;
        return ivec2(index, 0);
      }
    `:shape[0]===1?`
      ivec2 getOutputCoords() {
        ivec2 resTexRC = ivec2(resultUV.yx *
                               vec2(${texShape[0]}, ${texShape[1]}));
        int index = resTexRC.x * ${texShape[1]} + resTexRC.y;
        return ivec2(0, index);
      }
    `:`
    ivec2 getOutputCoords() {
      ivec2 resTexRC = ivec2(resultUV.yx *
                             vec2(${texShape[0]}, ${texShape[1]}));
      int index = resTexRC.x * ${texShape[1]} + resTexRC.y;
      int r = index / ${shape[1]};
      int c = index - r * ${shape[1]};
      return ivec2(r, c);
    }
  `}function getFlatOffsetUniformName(texName){return`offset${texName}`}function getPackedSamplerScalar(inputInfo){let texName=inputInfo.name,funcName="get"+texName.charAt(0).toUpperCase()+texName.slice(1),glsl=getGlslDifferences();return`
    vec4 ${funcName}() {
      return ${glsl.texture2D}(${texName}, halfCR);
    }
  `}function getSamplerScalar(inputInfo){let texName=inputInfo.name,funcName="get"+texName.charAt(0).toUpperCase()+texName.slice(1);if(inputInfo.shapeInfo.isUniform)return`float ${funcName}() {return ${texName};}`;let[texNumR,texNumC]=inputInfo.shapeInfo.texShape;if(texNumR===1&&texNumC===1)return`
      float ${funcName}() {
        return sampleTexture(${texName}, halfCR);
      }
    `;let[tNumR,tNumC]=inputInfo.shapeInfo.texShape,offset=getFlatOffsetUniformName(texName);return`
    float ${funcName}() {
      vec2 uv = uvFromFlat(${tNumR}, ${tNumC}, ${offset});
      return sampleTexture(${texName}, uv);
    }
  `}function getPackedSampler1D(inputInfo){let texName=inputInfo.name,funcName="get"+texName.charAt(0).toUpperCase()+texName.slice(1),texShape=inputInfo.shapeInfo.texShape,packedTexShape=[Math.ceil(texShape[0]/2),Math.ceil(texShape[1]/2)],glsl=getGlslDifferences();return`
    vec4 ${funcName}(int index) {
      vec2 uv = packedUVfrom1D(
        ${packedTexShape[0]}, ${packedTexShape[1]}, index);
      return ${glsl.texture2D}(${texName}, uv);
    }
  `}function getSampler1D(inputInfo){let texName=inputInfo.name,funcName="get"+texName.charAt(0).toUpperCase()+texName.slice(1);if(inputInfo.shapeInfo.isUniform)return`
      float ${funcName}(int index) {
        ${getUniformSampler(inputInfo)}
      }
    `;let texShape=inputInfo.shapeInfo.texShape,tNumR=texShape[0],tNumC=texShape[1];if(tNumC===1&&tNumR===1)return`
      float ${funcName}(int index) {
        return sampleTexture(${texName}, halfCR);
      }
    `;let offset=getFlatOffsetUniformName(texName);return tNumC===1?`
      float ${funcName}(int index) {
        vec2 uv = vec2(0.5, (float(index + ${offset}) + 0.5) / ${tNumR}.0);
        return sampleTexture(${texName}, uv);
      }
    `:tNumR===1?`
      float ${funcName}(int index) {
        vec2 uv = vec2((float(index + ${offset}) + 0.5) / ${tNumC}.0, 0.5);
        return sampleTexture(${texName}, uv);
      }
    `:`
    float ${funcName}(int index) {
      vec2 uv = uvFromFlat(${tNumR}, ${tNumC}, index + ${offset});
      return sampleTexture(${texName}, uv);
    }
  `}function getPackedSampler2D(inputInfo){let shape=inputInfo.shapeInfo.logicalShape,texName=inputInfo.name,funcName="get"+texName.charAt(0).toUpperCase()+texName.slice(1),texShape=inputInfo.shapeInfo.texShape,texNumR=texShape[0],texNumC=texShape[1],glsl=getGlslDifferences();if(texShape!=null&&util_exports.arraysEqual(shape,texShape))return`
      vec4 ${funcName}(int row, int col) {
        vec2 uv = (vec2(col, row) + halfCR) / vec2(${texNumC}.0, ${texNumR}.0);

        return ${glsl.texture2D}(${texName}, uv);
      }
    `;let packedTexShape=[Math.ceil(texShape[0]/2),Math.ceil(texShape[1]/2)],valuesPerRow=Math.ceil(shape[1]/2);return`
    vec4 ${funcName}(int row, int col) {
      vec2 uv = packedUVfrom2D(${valuesPerRow}, ${packedTexShape[0]}, ${packedTexShape[1]}, row, col);
      return ${glsl.texture2D}(${texName}, uv);
    }
  `}function getSampler2D(inputInfo){let shape=inputInfo.shapeInfo.logicalShape,texName=inputInfo.name,funcName="get"+texName.charAt(0).toUpperCase()+texName.slice(1),texShape=inputInfo.shapeInfo.texShape;if(texShape!=null&&util_exports.arraysEqual(shape,texShape)){let texNumR2=texShape[0],texNumC2=texShape[1];return`
    float ${funcName}(int row, int col) {
      vec2 uv = (vec2(col, row) + halfCR) / vec2(${texNumC2}.0, ${texNumR2}.0);
      return sampleTexture(${texName}, uv);
    }
  `}let{newShape,keptDims}=util_exports.squeezeShape(shape),squeezedShape=newShape;if(squeezedShape.length<shape.length){let newInputInfo=squeezeInputInfo(inputInfo,squeezedShape),params=["row","col"];return`
      ${getSamplerFromInInfo(newInputInfo)}
      float ${funcName}(int row, int col) {
        return ${funcName}(${getSqueezedParams(params,keptDims)});
      }
    `}if(inputInfo.shapeInfo.isUniform)return`
      float ${funcName}(int row, int col) {
        int index = round(dot(vec2(row, col), vec2(${shape[1]}, 1)));
        ${getUniformSampler(inputInfo)}
      }
    `;let texNumR=texShape[0],texNumC=texShape[1],offset=getFlatOffsetUniformName(texName);return texNumC===1?`
    float ${funcName}(int row, int col) {
      float index = dot(vec3(row, col, ${offset}), vec3(${shape[1]}, 1, 1));
      vec2 uv = vec2(0.5, (index + 0.5) / ${texNumR}.0);
      return sampleTexture(${texName}, uv);
    }
  `:texNumR===1?`
    float ${funcName}(int row, int col) {
      float index = dot(vec3(row, col, ${offset}), vec3(${shape[1]}, 1, 1));
      vec2 uv = vec2((index + 0.5) / ${texNumC}.0, 0.5);
      return sampleTexture(${texName}, uv);
    }
  `:`
  float ${funcName}(int row, int col) {
    // Explicitly use integer operations as dot() only works on floats.
    int index = row * ${shape[1]} + col + ${offset};
    vec2 uv = uvFromFlat(${texNumR}, ${texNumC}, index);
    return sampleTexture(${texName}, uv);
  }
`}function getPackedSampler3D(inputInfo){let shape=inputInfo.shapeInfo.logicalShape,texName=inputInfo.name,funcName="get"+texName.charAt(0).toUpperCase()+texName.slice(1),texShape=inputInfo.shapeInfo.texShape,packedTexShape=[Math.ceil(texShape[0]/2),Math.ceil(texShape[1]/2)];if(shape[0]===1){let squeezedShape=shape.slice(1),keptDims=[1,2],newInputInfo=squeezeInputInfo(inputInfo,squeezedShape),params=["b","row","col"];return`
        ${getPackedSamplerFromInInfo(newInputInfo)}
        vec4 ${funcName}(int b, int row, int col) {
          return ${funcName}(${getSqueezedParams(params,keptDims)});
        }
      `}let texNumR=packedTexShape[0],texNumC=packedTexShape[1],valuesPerRow=Math.ceil(shape[2]/2),texelsInBatch=valuesPerRow*Math.ceil(shape[1]/2),glsl=getGlslDifferences();return`
    vec4 ${funcName}(int b, int row, int col) {
      vec2 uv = packedUVfrom3D(
        ${texNumR}, ${texNumC}, ${texelsInBatch}, ${valuesPerRow}, b, row, col);
      return ${glsl.texture2D}(${texName}, uv);
    }
  `}function getSampler3D(inputInfo){let shape=inputInfo.shapeInfo.logicalShape,texName=inputInfo.name,funcName="get"+texName.charAt(0).toUpperCase()+texName.slice(1),stride0=shape[1]*shape[2],stride1=shape[2],{newShape,keptDims}=util_exports.squeezeShape(shape),squeezedShape=newShape;if(squeezedShape.length<shape.length){let newInputInfo=squeezeInputInfo(inputInfo,squeezedShape),params=["row","col","depth"];return`
        ${getSamplerFromInInfo(newInputInfo)}
        float ${funcName}(int row, int col, int depth) {
          return ${funcName}(${getSqueezedParams(params,keptDims)});
        }
      `}if(inputInfo.shapeInfo.isUniform)return`
      float ${funcName}(int row, int col, int depth) {
        int index = round(dot(vec3(row, col, depth),
                          vec3(${stride0}, ${stride1}, 1)));
        ${getUniformSampler(inputInfo)}
      }
    `;let texShape=inputInfo.shapeInfo.texShape,texNumR=texShape[0],texNumC=texShape[1],flatOffset=inputInfo.shapeInfo.flatOffset;if(texNumC===stride0&&flatOffset==null)return`
        float ${funcName}(int row, int col, int depth) {
          float texR = float(row);
          float texC = dot(vec2(col, depth), vec2(${stride1}, 1));
          vec2 uv = (vec2(texC, texR) + halfCR) /
                     vec2(${texNumC}.0, ${texNumR}.0);
          return sampleTexture(${texName}, uv);
        }
      `;if(texNumC===stride1&&flatOffset==null)return`
    float ${funcName}(int row, int col, int depth) {
      float texR = dot(vec2(row, col), vec2(${shape[1]}, 1));
      float texC = float(depth);
      vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${texNumC}.0, ${texNumR}.0);
      return sampleTexture(${texName}, uv);
    }
  `;let offset=getFlatOffsetUniformName(texName);return`
      float ${funcName}(int row, int col, int depth) {
        // Explicitly use integer operations as dot() only works on floats.
        int index = row * ${stride0} + col * ${stride1} + depth + ${offset};
        vec2 uv = uvFromFlat(${texNumR}, ${texNumC}, index);
        return sampleTexture(${texName}, uv);
      }
  `}function getPackedSamplerND(inputInfo){let shape=inputInfo.shapeInfo.logicalShape,rank=shape.length,texName=inputInfo.name,funcName="get"+texName.charAt(0).toUpperCase()+texName.slice(1),texShape=inputInfo.shapeInfo.texShape,packedTexShape=[Math.ceil(texShape[0]/2),Math.ceil(texShape[1]/2)],texNumR=packedTexShape[0],texNumC=packedTexShape[1],valuesPerRow=Math.ceil(shape[rank-1]/2),texelsInBatch=valuesPerRow*Math.ceil(shape[rank-2]/2),params="int b, int row, int col",index=`b * ${texelsInBatch} + (row / 2) * ${valuesPerRow} + (col / 2)`;for(let b=2;b<rank-1;b++)params=`int b${b}, `+params,texelsInBatch*=shape[rank-b-1],index=`b${b} * ${texelsInBatch} + `+index;let glsl=getGlslDifferences();return`
    vec4 ${funcName}(${params}) {
      int index = ${index};
      int texR = index / ${texNumC};
      int texC = index - texR * ${texNumC};
      vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${texNumC}, ${texNumR});
      return ${glsl.texture2D}(${texName}, uv);
    }
  `}function getSampler4D(inputInfo){let shape=inputInfo.shapeInfo.logicalShape,texName=inputInfo.name,funcName="get"+texName.charAt(0).toUpperCase()+texName.slice(1),stride2=shape[3],stride1=shape[2]*stride2,stride0=shape[1]*stride1,{newShape,keptDims}=util_exports.squeezeShape(shape);if(newShape.length<shape.length){let newInputInfo=squeezeInputInfo(inputInfo,newShape),params=["row","col","depth","depth2"];return`
      ${getSamplerFromInInfo(newInputInfo)}
      float ${funcName}(int row, int col, int depth, int depth2) {
        return ${funcName}(${getSqueezedParams(params,keptDims)});
      }
    `}if(inputInfo.shapeInfo.isUniform)return`
      float ${funcName}(int row, int col, int depth, int depth2) {
        int index = round(dot(vec4(row, col, depth, depth2),
                          vec4(${stride0}, ${stride1}, ${stride2}, 1)));
        ${getUniformSampler(inputInfo)}
      }
    `;let flatOffset=inputInfo.shapeInfo.flatOffset,texShape=inputInfo.shapeInfo.texShape,texNumR=texShape[0],texNumC=texShape[1];if(texNumC===stride0&&flatOffset==null)return`
      float ${funcName}(int row, int col, int depth, int depth2) {
        float texR = float(row);
        float texC =
            dot(vec3(col, depth, depth2),
                vec3(${stride1}, ${stride2}, 1));
        vec2 uv = (vec2(texC, texR) + halfCR) /
                   vec2(${texNumC}.0, ${texNumR}.0);
        return sampleTexture(${texName}, uv);
      }
    `;if(texNumC===stride2&&flatOffset==null)return`
      float ${funcName}(int row, int col, int depth, int depth2) {
        float texR = dot(vec3(row, col, depth),
                         vec3(${shape[1]*shape[2]}, ${shape[2]}, 1));
        float texC = float(depth2);
        vec2 uv = (vec2(texC, texR) + halfCR) /
                  vec2(${texNumC}.0, ${texNumR}.0);
        return sampleTexture(${texName}, uv);
      }
    `;let offset=getFlatOffsetUniformName(texName);return`
    float ${funcName}(int row, int col, int depth, int depth2) {
      // Explicitly use integer operations as dot() only works on floats.
      int index = row * ${stride0} + col * ${stride1} +
          depth * ${stride2} + depth2;
      vec2 uv = uvFromFlat(${texNumR}, ${texNumC}, index + ${offset});
      return sampleTexture(${texName}, uv);
    }
  `}function getSampler5D(inputInfo){let shape=inputInfo.shapeInfo.logicalShape,texName=inputInfo.name,funcName="get"+texName.charAt(0).toUpperCase()+texName.slice(1),stride3=shape[4],stride2=shape[3]*stride3,stride1=shape[2]*stride2,stride0=shape[1]*stride1,{newShape,keptDims}=util_exports.squeezeShape(shape);if(newShape.length<shape.length){let newInputInfo=squeezeInputInfo(inputInfo,newShape),params=["row","col","depth","depth2","depth3"];return`
      ${getSamplerFromInInfo(newInputInfo)}
      float ${funcName}(int row, int col, int depth, int depth2, int depth3) {
        return ${funcName}(${getSqueezedParams(params,keptDims)});
      }
    `}if(inputInfo.shapeInfo.isUniform)return`
      float ${funcName}(int row, int col, int depth, int depth2, int depth3) {
        float index = dot(
          vec4(row, col, depth, depth2),
          vec4(${stride0}, ${stride1}, ${stride2}, ${stride3})) +
          depth3;
        ${getUniformSampler(inputInfo)}
      }
    `;let flatOffset=inputInfo.shapeInfo.flatOffset,texShape=inputInfo.shapeInfo.texShape,texNumR=texShape[0],texNumC=texShape[1];if(texNumC===stride0&&flatOffset==null)return`
      float ${funcName}(int row, int col, int depth, int depth2, int depth3) {
        int texR = row;
        float texC = dot(vec4(col, depth, depth2, depth3),
                         vec4(${stride1}, ${stride2}, ${stride3}, 1));
        vec2 uv = (vec2(texC, texR) + halfCR) /
                   vec2(${texNumC}.0, ${texNumR}.0);
        return sampleTexture(${texName}, uv);
      }
    `;if(texNumC===stride3&&flatOffset==null)return`
      float ${funcName}(int row, int col, int depth, int depth2, int depth3) {
        float texR = dot(
          vec4(row, col, depth, depth2),
          vec4(${shape[1]*shape[2]*shape[3]},
               ${shape[2]*shape[3]}, ${shape[3]}, 1));
        int texC = depth3;
        vec2 uv = (vec2(texC, texR) + halfCR) /
                  vec2(${texNumC}.0, ${texNumR}.0);
        return sampleTexture(${texName}, uv);
      }
    `;let offset=getFlatOffsetUniformName(texName);return`
    float ${funcName}(int row, int col, int depth, int depth2, int depth3) {
      // Explicitly use integer operations as dot() only works on floats.
      int index = row * ${stride0} + col * ${stride1} + depth * ${stride2} +
          depth2 * ${stride3} + depth3 + ${offset};
      vec2 uv = uvFromFlat(${texNumR}, ${texNumC}, index);
      return sampleTexture(${texName}, uv);
    }
  `}function getSampler6D(inputInfo){let shape=inputInfo.shapeInfo.logicalShape,texName=inputInfo.name,funcName="get"+texName.charAt(0).toUpperCase()+texName.slice(1),{newShape,keptDims}=util_exports.squeezeShape(shape);if(newShape.length<shape.length){let newInputInfo=squeezeInputInfo(inputInfo,newShape),params=["row","col","depth","depth2","depth3","depth4"];return`
      ${getSamplerFromInInfo(newInputInfo)}
      float ${funcName}(int row, int col, int depth,
                    int depth2, int depth3, int depth4) {
        return ${funcName}(${getSqueezedParams(params,keptDims)});
      }
    `}let stride4=shape[5],stride3=shape[4]*stride4,stride2=shape[3]*stride3,stride1=shape[2]*stride2,stride0=shape[1]*stride1;if(inputInfo.shapeInfo.isUniform)return`
      float ${funcName}(int row, int col, int depth,
                  int depth2, int depth3, int depth4) {
        int index = round(dot(
          vec4(row, col, depth, depth2),
          vec4(${stride0}, ${stride1}, ${stride2}, ${stride3})) +
          dot(
            vec2(depth3, depth4),
            vec2(${stride4}, 1)));
        ${getUniformSampler(inputInfo)}
      }
    `;let flatOffset=inputInfo.shapeInfo.flatOffset,texShape=inputInfo.shapeInfo.texShape,texNumR=texShape[0],texNumC=texShape[1];if(texNumC===stride0&&flatOffset==null)return`
      float ${funcName}(int row, int col, int depth,
                    int depth2, int depth3, int depth4) {
        int texR = row;
        float texC = dot(vec4(col, depth, depth2, depth3),
          vec4(${stride1}, ${stride2}, ${stride3}, ${stride4})) +
               float(depth4);
        vec2 uv = (vec2(texC, texR) + halfCR) /
                   vec2(${texNumC}.0, ${texNumR}.0);
        return sampleTexture(${texName}, uv);
      }
    `;if(texNumC===stride4&&flatOffset==null)return`
      float ${funcName}(int row, int col, int depth,
                    int depth2, int depth3, int depth4) {
        float texR = dot(vec4(row, col, depth, depth2),
          vec4(${shape[1]*shape[2]*shape[3]*shape[4]},
               ${shape[2]*shape[3]*shape[4]},
               ${shape[3]*shape[4]},
               ${shape[4]})) + float(depth3);
        int texC = depth4;
        vec2 uv = (vec2(texC, texR) + halfCR) /
                  vec2(${texNumC}.0, ${texNumR}.0);
        return sampleTexture(${texName}, uv);
      }
    `;let offset=getFlatOffsetUniformName(texName);return`
    float ${funcName}(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 * ${stride0} + col * ${stride1} + depth * ${stride2} +
          depth2 * ${stride3} + depth3 * ${stride4} + depth4 + ${offset};
      vec2 uv = uvFromFlat(${texNumR}, ${texNumC}, index);
      return sampleTexture(${texName}, uv);
    }
  `}function getUniformSampler(inputInfo){let texName=inputInfo.name,inSize=util_exports.sizeFromShape(inputInfo.shapeInfo.logicalShape);return inSize<2?`return ${texName};`:`
    for (int i = 0; i < ${inSize}; i++) {
      if (i == index) {
        return ${texName}[i];
      }
    }
  `}function getPackedSamplerAtOutputCoords(inputInfo,outShapeInfo){let texName=inputInfo.name,texFuncSnippet=texName.charAt(0).toUpperCase()+texName.slice(1),funcName="get"+texFuncSnippet+"AtOutCoords",inRank=inputInfo.shapeInfo.logicalShape.length,outRank=outShapeInfo.logicalShape.length,broadcastDims=getBroadcastDims2(inputInfo.shapeInfo.logicalShape,outShapeInfo.logicalShape),type=getCoordsDataType(outRank),rankDiff=outRank-inRank,coordsSnippet,fields=["x","y","z","w","u","v"];inRank===0?coordsSnippet="":outRank<2&&broadcastDims.length>=1?coordsSnippet="coords = 0;":coordsSnippet=broadcastDims.map(d=>`coords.${fields[d+rankDiff]} = 0;`).join(`
`);let unpackedCoordsSnippet="";outRank<2&&inRank>0?unpackedCoordsSnippet="coords":unpackedCoordsSnippet=inputInfo.shapeInfo.logicalShape.map((s,i)=>`coords.${fields[i+rankDiff]}`).join(", ");let output="return outputValue;",isInputScalar=util_exports.sizeFromShape(inputInfo.shapeInfo.logicalShape)===1,isOutputScalar=util_exports.sizeFromShape(outShapeInfo.logicalShape)===1;if(inRank===1&&!isInputScalar&&!isOutputScalar)output=`
      return vec4(outputValue.xy, outputValue.xy);
    `;else if(isInputScalar&&!isOutputScalar)outRank===1?output=`
        return vec4(outputValue.x, outputValue.x, 0., 0.);
      `:output=`
        return vec4(outputValue.x);
      `;else if(broadcastDims.length){let rows=inRank-2,cols=inRank-1;broadcastDims.indexOf(rows)>-1&&broadcastDims.indexOf(cols)>-1?output="return vec4(outputValue.x);":broadcastDims.indexOf(rows)>-1?output="return vec4(outputValue.x, outputValue.y, outputValue.x, outputValue.y);":broadcastDims.indexOf(cols)>-1&&(output="return vec4(outputValue.xx, outputValue.zz);")}return`
    vec4 ${funcName}() {
      ${type} coords = getOutputCoords();
      ${coordsSnippet}
      vec4 outputValue = get${texFuncSnippet}(${unpackedCoordsSnippet});
      ${output}
    }
  `}function getSamplerAtOutputCoords(inputInfo,outShapeInfo){let texName=inputInfo.name,texFuncSnippet=texName.charAt(0).toUpperCase()+texName.slice(1),funcName="get"+texFuncSnippet+"AtOutCoords",outTexShape=outShapeInfo.texShape,inTexShape=inputInfo.shapeInfo.texShape,inRank=inputInfo.shapeInfo.logicalShape.length,outRank=outShapeInfo.logicalShape.length;if(!inputInfo.shapeInfo.isUniform&&inRank===outRank&&inputInfo.shapeInfo.flatOffset==null&&util_exports.arraysEqual(inTexShape,outTexShape))return`
      float ${funcName}() {
        return sampleTexture(${texName}, resultUV);
      }
    `;let type=getCoordsDataType(outRank),broadcastDims=getBroadcastDims2(inputInfo.shapeInfo.logicalShape,outShapeInfo.logicalShape),rankDiff=outRank-inRank,coordsSnippet,fields=["x","y","z","w","u","v"];inRank===0?coordsSnippet="":outRank<2&&broadcastDims.length>=1?coordsSnippet="coords = 0;":coordsSnippet=broadcastDims.map(d=>`coords.${fields[d+rankDiff]} = 0;`).join(`
`);let unpackedCoordsSnippet="";return outRank<2&&inRank>0?unpackedCoordsSnippet="coords":unpackedCoordsSnippet=inputInfo.shapeInfo.logicalShape.map((s,i)=>`coords.${fields[i+rankDiff]}`).join(", "),`
    float ${funcName}() {
      ${type} coords = getOutputCoords();
      ${coordsSnippet}
      return get${texFuncSnippet}(${unpackedCoordsSnippet});
    }
  `}function getCoordsDataType(rank){if(rank<=1)return"int";if(rank===2)return"ivec2";if(rank===3)return"ivec3";if(rank===4)return"ivec4";if(rank===5)return"ivec5";if(rank===6)return"ivec6";throw Error(`GPU for rank ${rank} is not yet supported`)}function squeezeInputInfo(inInfo,squeezedShape){let newInputInfo=JSON.parse(JSON.stringify(inInfo));return newInputInfo.shapeInfo.logicalShape=squeezedShape,newInputInfo}function getSqueezedParams(params,keptDims){return keptDims.map(d=>params[d]).join(", ")}function compileProgram(gpgpu,program,inputs,output){let userCode=program.userCode,inputInfos=inputs.map((input2,i)=>{let shapeInfo={logicalShape:input2.shape,texShape:input2.isUniform?null:input2.texData.texShape,isUniform:input2.isUniform,isPacked:input2.isUniform?!1:input2.texData.isPacked,flatOffset:null};return input2.texData!=null&&input2.texData.slice!=null&&input2.texData.slice.flatOffset>0&&(shapeInfo.flatOffset=input2.texData.slice.flatOffset),{name:program.variableNames[i],shapeInfo}}),inShapeInfos=inputInfos.map(x=>x.shapeInfo),outShapeInfo={logicalShape:output.shape,texShape:output.texData.texShape,isUniform:!1,isPacked:output.texData.isPacked,flatOffset:null},source=makeShader(inputInfos,outShapeInfo,userCode,program.packedInputs),webGLProgram=gpgpu.createProgram(source),infLoc=null,nanLoc=gpgpu.getUniformLocation(webGLProgram,"NAN",!1);env().getNumber("WEBGL_VERSION")===1&&(infLoc=gpgpu.getUniformLocation(webGLProgram,"INFINITY",!1));let uniformLocations={};for(let i=0;i<program.variableNames.length;i++){let varName=program.variableNames[i],shouldThrow=!1;uniformLocations[varName]=gpgpu.getUniformLocation(webGLProgram,varName,shouldThrow),uniformLocations[`offset${varName}`]=gpgpu.getUniformLocation(webGLProgram,`offset${varName}`,shouldThrow)}return{program,source,webGLProgram,uniformLocations,inShapeInfos,outShapeInfo,infLoc,nanLoc}}function validateBinaryAndProgram(shapeInfos,inputs){if(shapeInfos.length!==inputs.length)throw Error(`Binary was compiled with ${shapeInfos.length} inputs, but was executed with ${inputs.length} inputs`);shapeInfos.forEach((s,i)=>{let shapeA=s.logicalShape,input2=inputs[i],shapeB=input2.shape;if(!util_exports.arraysEqual(shapeA,shapeB))throw Error(`Binary was compiled with different shapes than the current args. Shapes ${shapeA} and ${shapeB} must match`);if(s.isUniform&&input2.isUniform)return;let texShapeA=s.texShape,texShapeB=input2.isUniform?null:input2.texData.texShape;if(!util_exports.arraysEqual(texShapeA,texShapeB))throw Error(`Binary was compiled with different texture shapes than the current args. Shape ${texShapeA} and ${texShapeB} must match`)})}function runProgram(gpgpu,binary,inputs,output,customSetup){validateBinaryAndProgram(binary.inShapeInfos,inputs),validateBinaryAndProgram([binary.outShapeInfo],[output]);let outTex=output.texData.texture,outTexShape=output.texData.texShape;output.texData.isPacked?gpgpu.setOutputPackedMatrixTexture(outTex,outTexShape[0],outTexShape[1]):gpgpu.setOutputMatrixTexture(outTex,outTexShape[0],outTexShape[1]),gpgpu.setProgram(binary.webGLProgram),env().getNumber("WEBGL_VERSION")===1&&binary.infLoc!==null&&gpgpu.gl.uniform1f(binary.infLoc,Infinity),binary.nanLoc!==null&&gpgpu.gl.uniform1f(binary.nanLoc,NaN),inputs.forEach((input2,i)=>{let varName=binary.program.variableNames[i],varLoc=binary.uniformLocations[varName],varOffsetLoc=binary.uniformLocations[`offset${varName}`];if(varLoc!=null){if(input2.isUniform){if(util_exports.sizeFromShape(input2.shape)<2)gpgpu.gl.uniform1f(varLoc,input2.uniformValues[0]);else{let vals=input2.uniformValues;vals instanceof Float32Array||(vals=new Float32Array(vals)),gpgpu.gl.uniform1fv(varLoc,vals)}return}input2.texData.slice!=null&&varOffsetLoc!=null&&gpgpu.gl.uniform1i(varOffsetLoc,input2.texData.slice.flatOffset),gpgpu.setInputMatrixTexture(input2.texData.texture,varLoc,i)}}),customSetup!=null&&customSetup(gpgpu,binary.webGLProgram),gpgpu.executeProgram()}function makeShaderKey(program,inputs,output){let keyInputs="";inputs.concat(output).forEach(x=>{let hasOffset=x.texData!=null&&x.texData.slice!=n
        void main() {
          setOutput(vec4(getA(), 0., 0., 0.));
        }
      `;else{let channels=getChannels("rc",rank),dtype=getCoordsDataType(rank),outOfBoundsCondition=getOutOfBoundsCondition(rank,outputShape,channels),setup41=getSetup(rank,outputShape[outputShape.length-1],outputShape[outputShape.length-2],channels),output=getOutput(outputShape,channels);this.userCode=`
        void main() {
          ${dtype} rc = getOutputCoords();

          if(${outOfBoundsCondition}) {
            setOutput(vec4(0));
          } else {
            ${setup41}

            setOutput(vec4(${output}));
          }
        }
      `}}};function getSourceCoordsArr(rank,dims){let coords2=[];for(let row=0;row<=1;row++)for(let col=0;col<=1;col++){let coord=`${row===0?"r":"rp1"}, ${col===0?"c":"cp1"}`;for(let d=2;d<rank;d++)coord=`${dims[dims.length-1-d]},`+coord;coords2.push(coord)}return coords2}function getOutOfBoundsCondition(rank,shape,dims){if(rank===1)return`rc > ${shape[0]}`;let cond="";for(let i=rank-2;i<rank;i++)cond+=`${dims[i]} >= ${shape[i]}`,i<rank-1&&(cond+="||");return cond}function getSetup(rank,cols,rows,dims){if(rank===1)return"";let innerDims=dims.slice(-2);return`
    int r = ${innerDims[0]};
    int c = ${innerDims[1]};
    int rp1 = r + 1;
    int cp1 = c + 1;

    bool cEdge = cp1 >= ${cols};
    bool rEdge = rp1 >= ${rows};
  `}function getOutput(shape,dims){let rank=shape.length,sourceCoords=getSourceCoordsArr(rank,dims);return rank===1?`getA(rc),
            rc + 1 >= ${shape[0]} ? 0. : getA(rc + 1),
            0, 0`:`getA(${sourceCoords[0]}),
          cEdge ? 0. : getA(${sourceCoords[1]}),
          rEdge ? 0. : getA(${sourceCoords[2]}),
          rEdge || cEdge ? 0. : getA(${sourceCoords[3]})`}var ReshapePackedProgram=class{constructor(outputShape,inputShape){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=outputShape;let mainLoop="";for(let i=0;i<4;i++){let thisRC="thisRC = rc;";i%2==1&&(thisRC+="thisRC.z += 1;"),i>1&&(thisRC+="thisRC.y += 1;"),mainLoop+=`
        ${thisRC}
        ${i>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[${i}] =
            getChannel(getA(inputRC.x, inputRC.y, inputRC.z), inputRCInnerDims);
        ${i>0?"}":""}
      `}this.userCode=`
      ${getReshapedInputCoords(inputShape)}
      ${getFlatIndexFrom3D(outputShape)}

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

        vec4 result = vec4(0.);

        ivec3 thisRC;
        int rows = ${outputShape[1]};
        int cols = ${outputShape[2]};

        ${mainLoop}

        setOutput(result);
      }
    `}};function getReshapedInputCoords(shape){return`
    ivec3 inputCoordsFromReshapedOutCoords(int index) {
      ${getLogicalCoordinatesFromFlatIndex(["r","c","d"],shape)}
      return ivec3(r, c, d);
    }
  `}var TextureManager=class{constructor(gpgpu){this.gpgpu=gpgpu,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0,this.freeTextures={},this.logEnabled=!1,this.usedTextures={}}acquireTexture(shapeRC,usage,isPacked){let physicalTexType=getPhysicalFromLogicalTextureType(usage,isPacked),shapeKey=getKeyFromTextureShape(shapeRC,physicalTexType,isPacked);shapeKey in this.freeTextures||(this.freeTextures[shapeKey]=[]),shapeKey in this.usedTextures||(this.usedTextures[shapeKey]=[]);let texBytes=computeBytes(shapeRC,physicalTexType,this.gpgpu.gl,this.gpgpu.textureConfig,isPacked);if(this.freeTextures[shapeKey].length>0){this.numFreeTextures--,this.numUsedTextures++,this._numBytesFree-=texBytes,this.log();let newTexture2=this.freeTextures[shapeKey].shift();return this.usedTextures[shapeKey].push(newTexture2),newTexture2}let newTexture;return physicalTexType===PhysicalTextureType.PACKED_2X2_FLOAT32?newTexture=this.gpgpu.createPackedMatrixTexture(shapeRC[0],shapeRC[1]):physicalTexType===PhysicalTextureType.PACKED_2X2_FLOAT16?newTexture=this.gpgpu.createFloat16PackedMatrixTexture(shapeRC[0],shapeRC[1]):physicalTexType===PhysicalTextureType.UNPACKED_FLOAT32?newTexture=this.gpgpu.createFloat32MatrixTexture(shapeRC[0],shapeRC[1]):physicalTexType===PhysicalTextureType.UNPACKED_FLOAT16?newTexture=this.gpgpu.createFloat16MatrixTexture(shapeRC[0],shapeRC[1]):physicalTexType===PhysicalTextureType.PACKED_4X1_UNSIGNED_BYTE&&(newTexture=this.gpgpu.createUnsignedBytesMatrixTexture(shapeRC[0],shapeRC[1])),this.usedTextures[shapeKey].push(newTexture),this.numUsedTextures++,this._numBytesAllocated+=texBytes,this.log(),newTexture}releaseTexture(texture,shape,logicalTexType,isPacked){if(this.freeTextures==null)return;let physicalTexType=getPhysicalFromLogicalTextureType(logicalTexType,isPacked),shapeKey=getKeyFromTextureShape(shape,physicalTexType,isPacked);shapeKey in this.freeTextures||(this.freeTextures[shapeKey]=[]);let texBytes=computeBytes(shape,physicalTexType,this.gpgpu.gl,this.gpgpu.textureConfig,isPacked),deleteTexThreshold=env().get("WEBGL_DELETE_TEXTURE_THRESHOLD");deleteTexThreshold!==-1&&this._numBytesAllocated>deleteTexThreshold?(this.gpgpu.deleteMatrixTexture(texture),this._numBytesAllocated-=texBytes):(this.freeTextures[shapeKey].push(texture),this.numFreeTextures++,this._numBytesFree+=texBytes),this.numUsedTextures--;let texList=this.usedTextures[shapeKey],texIndex=texList.indexOf(texture);if(texIndex<0)throw new Error("Cannot release a texture that was never provided by this texture manager");texList.splice(texIndex,1),this.log()}log(){if(!this.logEnabled)return;let total=this.numFreeTextures+this.numUsedTextures;console.log("Free/Used",`${this.numFreeTextures} / ${this.numUsedTextures}`,`(${total})`);let freeRatio=this._numBytesFree/this._numBytesAllocated;console.log(`Bytes allocated: ${this._numBytesAllocated}`),console.log(`Bytes unused: ${this._numBytesFree} (${Math.round(100*freeRatio)}%)`)}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 texShape in this.freeTextures)this.freeTextures[texShape].forEach(tex=>{this.gpgpu.deleteMatrixTexture(tex)});for(let texShape in this.usedTextures)this.usedTextures[texShape].forEach(tex=>{this.gpgpu.deleteMatrixTexture(tex)});this.freeTextures=null,this.usedTextures=null,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0}}};function numBytesForInternalFormat(gl,internalFormat){let glany=gl;if(internalFormat===glany.R32F)return 4;if(internalFormat===glany.R16F)return 2;if(internalFormat===glany.RGBA32F||internalFormat===gl.RGBA)return 16;if(internalFormat===glany.RGBA16F)return 8;throw new Error(`Unknown internal format ${internalFormat}`)}function computeBytes(shape,physicalTexType,gl,textureConfig,isPacked){let internalFormat=internalFormatForPhysicalTexType(physicalTexType,textureConfig),numElements;if(isPacked)
      float unaryOperation(float x) {
        ${opSnippet}
      }

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

        setOutput(y);
      }
    `}},CHECK_NAN_SNIPPET="if (isnan(x)) return x;",LINEAR="return x;",ABS="return abs(x);",ELU="return (x >= 0.0) ? x : (exp(x) - 1.0);",RELU=CHECK_NAN_SNIPPET+`
  return (x < 0.0) ? 0.0 : x;
`,RELU6=CHECK_NAN_SNIPPET+`
  return (x < 0.0) ? 0.0 : min(6.0, x);
`,CLONE="return x;",LINEAR2="return x;",ELU2=`
  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;
`,RELU2=`
  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;
`,RELU62=`
  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;
`,UnaryOpPackedProgram=class{constructor(aShape,opSnippet){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=aShape,this.userCode=`
      vec4 unaryOperation(vec4 x) {
        ${opSnippet}
      }

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

        setOutput(y);
      }
    `}},UnpackProgram=class{constructor(outputShape){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outputShape=outputShape;let rank=outputShape.length,channels=getChannels("rc",rank),dtype=getCoordsDataType(rank),sourceCoords=getSourceCoords(rank,channels),innerDims=channels.slice(-2),coords2=rank<=1?"rc":`vec2(${innerDims.join(",")})`;this.userCode=`
      void main() {
        ${dtype} rc = getOutputCoords();
        vec4 packedInput = getA(${sourceCoords});

        setOutput(getChannel(packedInput, ${coords2}));
      }
    `}},whereImpl3=kernel_impls_exports.whereImpl,EPSILON_FLOAT322=1e-7,EPSILON_FLOAT162=1e-4,binaryCaches={};function getBinaryCache(webGLVersion){return webGLVersion in binaryCaches||(binaryCaches[webGLVersion]={}),binaryCaches[webGLVersion]}var CPU_HANDOFF_SIZE_THRESHOLD=128,BEFORE_PAGING_CONSTANT=600;function numMBBeforeWarning(){return env().global.screen==null?1024:env().global.screen.height*env().global.screen.width*window.devicePixelRatio*BEFORE_PAGING_CONSTANT/1024/1024}var MathBackendWebGL=class extends KernelBackend{constructor(gpgpu){super();if(this.pendingRead=new WeakMap,this.pendingDisposal=new WeakSet,this.dataRefCount=new WeakMap,this.numBytesInGPU=0,this.uploadWaitMs=0,this.downloadWaitMs=0,this.warnedAboutMemory=!1,this.warnedAboutCPUBackend=!1,this.pendingDeletes=0,this.disposed=!1,!env().getBool("HAS_WEBGL"))throw new Error("WebGL is not supported on this device");if(gpgpu==null){let gl=getWebGLContext(env().getNumber("WEBGL_VERSION"));this.binaryCache=getBinaryCache(env().getNumber("WEBGL_VERSION")),this.gpgpu=new GPGPUContext(gl),this.canvas=gl.canvas,this.gpgpuCreatedLocally=!0}else this.gpgpu=gpgpu,this.binaryCache={},this.gpgpuCreatedLocally=!1,this.canvas=gpgpu.gl.canvas;this.textureManager=new TextureManager(this.gpgpu),this.numMBBeforeWarning=numMBBeforeWarning(),this.texData=new DataStorage(this,engine())}numDataIds(){return this.texData.numDataIds()+(this.cpuBackend?this.cpuBackend.numDataIds():0)-this.pendingDeletes}write(values,shape,dtype){if((env().getBool("WEBGL_CHECK_NUMERICAL_PROBLEMS")||env().getBool("DEBUG"))&&this.checkNumericalProblems(values),dtype==="complex64"&&values!=null)throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");let dataId={};return this.texData.set(dataId,{shape,dtype,values,usage:TextureUsage.UPLOAD,refCount:1,complexParentRefCount:0}),dataId}incRef(dataId){let texData=this.texData.get(dataId);texData.refCount++}decRef(dataId){if(this.texData.has(dataId)){let texData=this.texData.get(dataId);texData.refCount--}}move(dataId,values,shape,dtype){if(env().getBool("DEBUG")&&this.checkNumericalProblems(values),dtype==="complex64")throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");this.texData.set(dataId,{shape,dtype,values,usage:TextureUsage.UPLOAD,refCount:1,complexParentRefCount:0})}disposeIntermediateTensorInfo(tensorInfo){let dataId=tensorInfo.dataId;if(this.texData.has(dataId)){let textureData=this.texData.get(dataId);textureData.refCount--,textureData.refCount<1&&this.disposeData(dataId)}}readSync(dataId){let texData=this.texData.get(dataId),{values,dtype,complexTensorInfos,slice:slice5,shape,isPacked}=texData;if(slice5!=null){let program;isPacked?program=new UnaryOpPackedProgram(shape,CLONE):program=new UnaryOpProgram(shape,CLONE);let res=this.runWebGLProgram(program,[{dataId,shape,dtype}],dtype),data2=this.readSync(res.dataId);return this.disposeIntermediateTensorInfo(res),data2}if(values!=null)return this.convertAndCacheOnCPU(dataId);if(dtype==="string")return values;let shouldTimeProgram=this.activeTimers!=null,start;shouldTimeProgram&&(start=util_exports.now());let result;if(dtype==="complex64"){let realValues=this.readSync(complexTensorInfos.real.dataId),imagValues=this.readSync(complexTensorInfos.imag.dataId);result=backend_util_exports.mergeRealAndImagArrays(realValues,imagValues)}else result=this.getValuesFromTexture(dataId);return shouldTimeProgram&&(this.downloadWaitMs+=util_exports.now()-start),this.convertAndCacheOnCPU(dataId,result)}async read(dataId){if(this.pendingRead.has(dataId)){let subscribers2=this.pendingRead.get(dataId);return new Promise(resolve=>subscribers2.push(resolve))}let texData=this.texData.get(dataId),{values,shape,slice:slice5,dtype,complexTensorInfos,isPacked}=texData;if(slice5!=null){let program;isPacked?program=new UnaryOpPackedProgram(shape,CLONE):program=new UnaryOpProgram(shape,CLONE);let res=this.runWebGLProgram(program,[{dataId,shape,dtype}],dtype),data2=this.read(res.dataId);return this.disposeIntermediateTensorInfo(res),data2}if(values!=null)re
  if (isnan(a)) return a;
  if (isnan(b)) return b;
`,BinaryOpProgram=class{constructor(op2,aShape,bShape){this.variableNames=["A","B"],this.outputShape=backend_util_exports.assertAndGetBroadcastShape(aShape,bShape),this.userCode=`
      float binaryOperation(float a, float b) {
        ${op2}
      }

      void main() {
        float a = getAAtOutCoords();
        float b = getBAtOutCoords();
        setOutput(binaryOperation(a, b));
      }
    `}},CHECK_NAN_SNIPPET3=`
  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;
`,BinaryOpPackedProgram=class{constructor(op2,aShape,bShape,checkOutOfBounds=!1){this.variableNames=["A","B"],this.supportsBroadcasting=!0,this.packedInputs=!0,this.packedOutput=!0,this.outputShape=backend_util_exports.assertAndGetBroadcastShape(aShape,bShape);let rank=this.outputShape.length,checkOutOfBoundsString="";if(checkOutOfBounds)if(rank===0||util_exports.sizeFromShape(this.outputShape)===1)checkOutOfBoundsString=`
          result.y = 0.;
          result.z = 0.;
          result.w = 0.;
        `;else if(checkOutOfBoundsString=`
          ${getCoordsDataType(rank)} coords = getOutputCoords();
        `,rank===1)checkOutOfBoundsString+=`
            result.y = (coords + 1) >= ${this.outputShape[0]} ? 0. : result.y;
            result.z = 0.;
            result.w = 0.;
          `;else{let channels=getChannels("coords",rank);checkOutOfBoundsString+=`
            bool nextRowOutOfBounds =
              (${channels[rank-2]} + 1) >= ${this.outputShape[rank-2]};
            bool nextColOutOfBounds =
              (${channels[rank-1]} + 1) >= ${this.outputShape[rank-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) {
        ${op2}
      }

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

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

        setOutput(result);
      }
    `}};function identity2(args){let{inputs,backend:backend22}=args,{x}=inputs;return backend22.incRef(x.dataId),{dataId:x.dataId,shape:x.shape,dtype:x.dtype}}var identityConfig2={kernelName:Identity,backendName:"webgl",kernelFunc:identity2};function complex3(args){let{inputs,backend:backend22}=args,{real:real4,imag:imag4}=inputs,complexInfo=backend22.makeTensorInfo(real4.shape,"complex64"),complex4=backend22.texData.get(complexInfo.dataId),realTensorInfo=identity2({inputs:{x:real4},backend:backend22}),realData=backend22.texData.get(realTensorInfo.dataId);realData.complexParentRefCount++;let imagTensorInfo=identity2({inputs:{x:imag4},backend:backend22}),imagData=backend22.texData.get(imagTensorInfo.dataId);return imagData.complexParentRefCount++,complex4.complexTensorInfos={real:realTensorInfo,imag:imagTensorInfo},complexInfo}var complexConfig2={kernelName:Complex,backendName:"webgl",kernelFunc:complex3},LEAKYRELU="return (a < 0.) ? b * a : a;",LEAKYRELU_PACKED=`
  vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));
  return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);
`;function leakyRelu3(args){let{inputs,backend:backend22,attrs}=args,{x}=inputs,{alpha}=attrs,$alpha=backend22.makeTensorInfo([],"float32",util_exports.createScalarValue(alpha,"float32")),program=env().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new BinaryOpPackedProgram(LEAKYRELU_PACKED,x.shape,$alpha.shape):new BinaryOpProgram(LEAKYRELU,x.shape,$alpha.shape),result=backend22.runWebGLProgram(program,[x,$alpha],x.dtype);return backend22.disposeIntermediateTensorInfo($alpha),result}var leakyReluConfig2={kernelName:LeakyRelu,backendName:"webgl",kernelFunc:leakyRelu3},PRELU="return (a < 0.) ? b * a : a;",PRELU_PACKED=`
  vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));
  return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);
`;function prelu3(args){let{inputs,backend:backend22}=args,{x,alpha}=inputs,program=env().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new BinaryOpPackedProgram(PRELU_PACKED,x.shape,alpha.shape):new BinaryOpProgram(PRELU,x.shape,alpha.shape);return backend22.runWebGLProgram(program,[x,alpha],x.dtype)}var preluConfig2={kernelName:Prelu,backendName:"webgl",kernelFunc:prelu3},CHECK_NAN_SNIPPET_UNARY="if (isnan(x)) return x;",CHECK_NAN_SNIPPET_BINARY=`
  if (isnan(a)) return a;
  if (isnan(b)) return b;
`,CHECK_NAN_SNIPPET_BINARY_PACKED=`
  result.r = isNaN.r > 0. ? NAN : result.r;
  result.g = isNaN.g > 0. ? NAN : result.g;
  result.b = isNaN.b > 0. ? NAN : result.b;
  result.a = isNaN.a > 0. ? NAN : result.a;
`;function unaryKernelFunc2({opSnippet,packedOpSnippet,cpuKernelImpl,dtype}){return({inputs,backend:backend22})=>{let{x}=inputs,webglBackend=backend22,$dtype=dtype||x.dtype;if(webglBackend.shouldExecuteOnCPU([x])&&cpuKernelImpl!=null){let xData=webglBackend.texData.get(x.dataId),outValues=cpuKernelImpl(xData.values,$dtype);return webglBackend.makeTensorInfo(x.shape,$dtype,outValues)}let shouldUsePackedProgram=env().getBool("WEBGL_PACK_UNARY_OPERATIONS")&&packedOpSnippet!=null,program;return shouldUsePackedProgram?program=new UnaryOpPackedProgram(x.shape,packedOpSnippet):program=new UnaryOpProgram(x.shape,opSnippet),webglBackend.runWebGLProgram(program,[x],$dtype)}}function binaryKernelFunc2({opSnippet,packedOpSnippet,checkOutOfBounds=!1,supportsComplex=!1,cpuKernelImpl,dtype}){return({inputs,backend:backend22})=>{let{a,b}=inputs,webglBackend=backend22;if(supportsComplex&&a.dtype==="complex64"){let aData=webglBackend.texData.get(a.dataId),bData=webglBackend.texData.get(b.dataId),[real4,imag4]=[[aData.complexTensorInfos.real,bData.complexTensorInfos.real],[aData.complexTensorInfos.imag,bData.complexTensorInfos.imag]].map(complexParts=>{let[aPart,bPart]=complexParts,aHandle={dataId:aPart.dataId,dtype:aPart.dtype,shape:a.shape},bHandle={dataId:bPart.dataId,dtype:bPart.dtype,shape:b.shape},program2=new BinaryOpProgram(opSnippet,a.shape,b.shape);return webglBackend.runWebGLProgram(program2,[aHandle,bHandle],upcastType(aPart.dtype,bPart.dtype))}),complexOutput=complex3({inputs:{real:real4,imag:imag4},backend:webglBackend});return webglBackend.disposeIntermediateTensorInfo(real4),webglBackend.disposeIntermediateTensorInfo(imag4),complexOutput}let $dtype=dtype||upcastType(a.dtype,b.dtype);if(webglBackend.shouldExecuteOnCPU([a,b])&&cpuKernelImpl!=null){let aData=webglBackend.texData.get(a.dataId),bData=webglBackend.texData.get(b.dataId),[outValues,outShape]=cpuKernelImpl(a.shape,b.shape,aData.values,bData.values,$dtype),out=webglBackend.makeTensorInfo(outShape,$dtype),outData=webglBackend.texData.get(out.dataId);return outData.values=outValues,out}let shouldUsePackedProgram=env().getBool("WEBGL_PACK_BINARY_OPERATIONS")&&packedOpSnippet!=null,program;return shouldUsePackedProgram?program=new BinaryOpPackedProgram(packedOpSnippet,a.shape,b.shape,checkOutOfBounds):program=new BinaryOpProgram(opSnippet,a.shape,b.shape),webglBackend.runWebGLProgram(program,[a,b],$dtype)}}function mapActivationToShaderProgram(activation2,packed=!1){if(activation2==="linear")return packed?LINEAR2:LINEAR;if(activation2==="relu")return packed?RELU2:RELU;if(activation2==="elu")return packed?ELU2:ELU;if(activation2==="relu6")return packed?RELU62:RELU6;if(activation2==="prelu")return packed?PRELU_PACKED:PRELU;if(activation2==="leakyrelu")return packed?LEAKYRELU_PACKED:LEAKYRELU;throw new Error(`Activation ${activation2} has not been implemented for the WebGL backend.`)}var MatMulPackedProgram=class{constructor(aShape,bShape,outputShape,transposeA=!1,transposeB=!1,addBias=!1,activation2=null,hasPreluActivation=!1,hasLeakyreluActivation=!1){this.variableNames=["matrixA","matrixB"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=outputShape;let sharedDim=transposeA?aShape[1]:aShape[2],sharedDimensionPacked=Math.ceil(sharedDim/2),aSample=transposeA?"i * 2, rc.y":"rc.y, i * 2",bSample=transposeB?"rc.z, i * 2":"i * 2, rc.z",aSwizzle=transposeA?["a.xxyy","a.zzww"]:["a.xxzz","a.yyww"],bSwizzle=transposeB?["b.xzxz","b.ywyw"]:["b.xyxy","b.zwzw"],activationSnippet="",applyActivationSnippet="";activation2&&(hasPreluActivation?activationSnippet=`vec4 activation(vec4 a) {
          vec4 b = getPreluActivationWeightsAtOutCoords();
          ${activation2}
        }`:hasLeakyreluActivation?activationSnippet=`vec4 activation(vec4 a) {
          vec4 b = getLeakyreluAlphaAtOutCoords();
          ${activation2}
        }`:activationSnippet=`vec4 activation(vec4 x) {
          ${activation2}
        }`,applyActivationSnippet="result = activation(result);");let addBiasSnippet=addBias?"result += getBiasAtOutCoords();":"";addBias&&this.variableNames.push("bias"),hasPreluActivation&&this.variableNames.push("preluActivationWeights"),hasLeakyreluActivation&&this.variableNames.push("leakyreluAlpha");let batchASnippet="rc.x",batchBSnippet="rc.x";aShape[0]<bShape[0]?batchASnippet=`int(min(float(rc.x), ${aShape[0]-1}.))`:bShape[0]<aShape[0]&&(batchBSnippet=`int(min(float(rc.x), ${bShape[0]-1}.))`),this.userCode=`
      ${activationSnippet}

      const float sharedDimension = ${sharedDimensionPacked}.0;

      vec4 dot2x2ARowBCol(ivec3 rc) {
        vec4 result = vec4(0);
        for (int i = 0; i < ${sharedDimensionPacked}; i++) {
          int batchA = ${batchASnippet};
          int batchB = ${batchBSnippet};
          vec4 a = getMatrixA(batchA, ${aSample});
          vec4 b = getMatrixB(batchB, ${bSample});

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

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

        ${addBiasSnippet}

        ${applyActivationSnippet}

        setOutput(result);
      }
    `}},COMPLEX_MULTIPLY={REAL:"return areal * breal - aimag * bimag;",IMAG:"return areal * bimag + aimag * breal;"},BinaryOpComplexProgram=class{constructor(op2,aShape,bShape){this.variableNames=["AReal","AImag","BReal","BImag"],this.outputShape=backend_util_exports.assertAndGetBroadcastShape(aShape,bShape),this.userCode=`
      float binaryOpComplex(
          float areal, float aimag, float breal, float bimag) {
        ${op2}
      }

      void main() {
        float areal = getARealAtOutCoords();
        float aimag = getAImagAtOutCoords();
        float breal = getBRealAtOutCoords();
        float bimag = getBImagAtOutCoords();
        setOutput(binaryOpComplex(areal, aimag, breal, bimag));
      }
    `}},MUL="return a * b;";function multiply2(args){let{inputs,backend:backend22}=args,{a,b}=inputs,dtype=backend_util_exports.upcastType(a.dtype,b.dtype);if(a.dtype==="complex64"){let aData=backend22.texData.get(a.dataId),bData=backend22.texData.get(b.dataId),realProgram=new BinaryOpComplexProgram(COMPLEX_MULTIPLY.REAL,a.shape,b.shape),imagProgram=new BinaryOpComplexProgram(COMPLEX_MULTIPLY.IMAG,a.shape,b.shape),inputs2=[{dataId:aData.complexTensorInfos.real.dataId,dtype:aData.complexTensorInfos.real.dtype,shape:a.shape},{dataId:aData.complexTensorInfos.imag.dataId,dtype:aData.complexTensorInfos.imag.dtype,shape:a.shape},{dataId:bData.complexTensorInfos.real.dataId,dtype:bData.complexTensorInfos.real.dtype,shape:b.shape},{dataId:bData.complexTensorInfos.imag.dataId,dtype:bData.complexTensorInfos.imag.dtype,shape:b.shape}],realPart=backend22.runWebGLProgram(realProgram,inputs2,"float32"),imagPart=backend22.runWebGLProgram(imagProgram,inputs2,"float32"),complexOutput=complex3({inputs:{real:realPart,imag:imagPart},backend:backend22});return backend22.disposeIntermediateTensorInfo(realPart),backend22.disposeIntermediateTensorInfo(imagPart),complexOutput}if(backend22.shouldExecuteOnCPU([a,b])){let aData=backend22.texData.get(a.dataId),bData=backend22.texData.get(b.dataId),[outValues,outShape]=multiplyImplCPU(a.shape,b.shape,aData.values,bData.values,dtype),out=backend22.makeTensorInfo(outShape,dtype),outData=backend22.texData.get(out.dataId);return outData.values=outValues,out}let program;return env().getBool("WEBGL_PACK_BINARY_OPERATIONS")?program=new BinaryOpPackedProgram(MUL,a.shape,b.shape):program=new BinaryOpProgram(MUL,a.shape,b.shape),backend22.runWebGLProgram(program,[a,b],dtype)}var multiplyConfig2={kernelName:Multiply,backendName:"webgl",kernelFunc:multiply2};function packedReshape(input2,afterShape,backend22){let input3DShape=[getBatchDim(input2.shape),...getRowsCols(input2.shape)],input3D={dtype:input2.dtype,shape:input3DShape,dataId:input2.dataId},afterShapeAs3D=[getBatchDim(afterShape),...getRowsCols(afterShape)],program=new ReshapePackedProgram(afterShapeAs3D,input3DShape),preventEagerUnpackingOfOutput=!0,output=backend22.runWebGLProgram(program,[input3D],input2.dtype,null,preventEagerUnpackingOfOutput);return{dataId:output.dataId,shape:afterShape,dtype:output.dtype}}function reshape3(args){let{inputs,backend:backend22,attrs}=args,{x}=inputs,{shape}=attrs,webglBackend=backend22,xSize=util_exports.sizeFromShape(x.shape),$shape=util_exports.inferFromImplicitShape(shape,xSize),$xSize=util_exports.sizeFromShape($shape);util_exports.assert(xSize===$xSize,()=>`The new shape (${$shape}) has ${$xSize} elements and the old shape (${x.shape}) has ${xSize} elements. The new shape and old shape must have the same number of elements.`);let xTexData=webglBackend.texData.get(x.dataId);return xTexData.isPacked&&!isReshapeFree(x.shape,$shape)&&!(xTexData.texture!==null&&isReshapeFree(xTexData.shape,$shape))?packedReshape(x,$shape,webglBackend):(webglBackend.incRef(x.dataId),{dataId:x.dataId,shape:$shape,dtype:x.dtype})}var reshapeConfig2={kernelName:Reshape,backendName:"webgl",kernelFunc:reshape3},MeanProgram=class{constructor(reduceInfo,divisor){this.variableNames=["x"];let{windowSize,batchSize,inSize,outSize}=reduceInfo;this.outputShape=[batchSize,outSize];let windowSizeNearestVec4=Math.floor(windowSize/4)*4,windowSizeVec4Remainder=windowSize%4,updateSnippet="sumValue += dot(values, ones);";if(divisor!=null){let denominator=1/divisor;updateSnippet=`sumValue += dot(values * ${util_exports.isInt(denominator)?denominator.toPrecision(2):denominator}, ones);`}let checkOutOfBounds="";inSize%windowSize>0&&(checkOutOfBounds=`
        if (inIdx < 0 || inIdx >= ${inSize}) {
          return 0.0;
        }
      `),this.userCode=`
      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);

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

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

        float sumValue = 0.0;

        for (int i = 0; i < ${windowSizeNearestVec4}; i += 4) {
          int inIdx = inOffset + i;
          vec4 values = vec4(
            getValue(batch, inIdx),
            getValue(batch, inIdx + 1),
            getValue(batch, inIdx + 2),
            getValue(batch, inIdx + 3)
          );

          ${updateSnippet}
        }

        int inIdx = inOffset + ${windowSizeNearestVec4};
        if (${windowSizeVec4Remainder===1}) {
          vec4 values = vec4(getValue(batch, inIdx), 0.0, 0.0, 0.0);

          ${updateSnippet}
        } else if (${windowSizeVec4Remainder===2}) {
          vec4 values = vec4(
            getValue(batch, inIdx),
            getValue(batch, inIdx + 1), 0.0, 0.0);

          ${updateSnippet}
        } else if (${windowSizeVec4Remainder===3}) {
          vec4 values = vec4(
            getValue(batch, inIdx),
            getValue(batch, inIdx + 1),
            getValue(batch, inIdx + 2), 0.0);

          ${updateSnippet}
        }
        setOutput(sumValue);
      }
    `}},ReduceProgram=class{constructor(reduceInfo,reduceType){this.variableNames=["x"];let{windowSize,batchSize,inSize,outSize}=reduceInfo;this.outputShape=[batchSize,outSize];let initializationValue="0.0",compareOp="";reduceType==="prod"?initializationValue="1.0":reduceType==="min"?(initializationValue="1.0 / 1e-20",compareOp="min"):reduceType==="max"&&(initializationValue="-1.0 / 1e-20",compareOp="max");let returnValue=`${reduceType}(${reduceType}(${reduceType}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;reduceType==="sum"?returnValue="sumValue":reduceType==="prod"?returnValue="prodValue":reduceType==="all"?returnValue="allValue":reduceType==="any"&&(returnValue="anyValue");let windowSizeNearestVec4=Math.floor(windowSize/4)*4,windowSizeVec4Remainder=windowSize%4,updateSnippet=`
      if (${reduceType==="sum"}) {
        sumValue += dot(values, ones);
      } else if (${reduceType==="prod"}) {
        vec2 tmp = vec2(values[0], values[1]) * vec2(values[2], values[3]);
        prodValue *= tmp[0] * tmp[1];
      } else {
        minMaxValue = ${compareOp}(values, minMaxValue);
      }
    `,vecType="vec4";reduceType==="all"?(initializationValue="1.0",updateSnippet=`
        bool reducedAllValue = all(values);
        float floatedReducedAllValue = float(reducedAllValue);
        allValue = float(allValue >= 1.0 && floatedReducedAllValue >= 1.0);
      `,vecType="bvec4"):reduceType==="any"&&(initializationValue="0.0",updateSnippet=`
        bool reducedAnyValue = any(values);
        float floatedReducedAnyValue = float(reducedAnyValue);
        anyValue = float(anyValue >= 1.0 || floatedReducedAnyValue >= 1.0);
      `,vecType="bvec4");let checkOutOfBounds="";inSize%windowSize>0&&(checkOutOfBounds=`
        if (inIdx < 0 || inIdx >= ${inSize}) {
          return initializationValue;
        }
      `),this.userCode=`
      const float initializationValue = ${initializationValue};
      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);

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

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

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

        for (int i = 0; i < ${windowSizeNearestVec4}; i += 4) {
          int inIdx = inOffset + i;
          ${vecType} values = ${vecType}(
            getValue(batch, inIdx),
            getValue(batch, inIdx + 1),
            getValue(batch, inIdx + 2),
            getValue(batch, inIdx + 3)
          );

          ${updateSnippet}
        }

        int inIdx = inOffset + ${windowSizeNearestVec4};
        if (${windowSizeVec4Remainder===1}) {
          ${vecType} values = ${vecType}(
            getValue(batch, inIdx),
            initializationValue,
            initializationValue,
            initializationValue
          );

          ${updateSnippet}
        } else if (${windowSizeVec4Remainder===2}) {
          ${vecType} values = ${vecType}(
            getValue(batch, inIdx),
            getValue(batch, inIdx + 1),
            initializationValue,
            initializationValue
          );

          ${updateSnippet}
        } else if (${windowSizeVec4Remainder===3}) {
          ${vecType} values = ${vecType}(
            getValue(batch, inIdx),
            getValue(batch, inIdx + 1),
            getValue(batch, inIdx + 2),
            initializationValue
          );

          ${updateSnippet}
        }
        setOutput(${returnValue});
      }
    `}};function getReductionStages(inShape){let stages=[];for(;stages.length===0||stages[stages.length-1].outSize!==1;){let outSize=stages.length?stages[stages.length-1].outSize:inShape[1],windowSize=backend_util_exports.computeOptimalWindowSize(outSize);stages.push({inSize:outSize,windowSize,outSize:Math.ceil(outSize/windowSize)})}return stages}function reduce(x,dtype,reductionType,backend22){let reductionStages=getReductionStages(x.shape),result=x;for(let i=0;i<reductionStages.length;i++){let{inSize,windowSize,outSize}=reductionStages[i],program,previousResult;reductionType==="mean"?program=i===0?new MeanProgram({windowSize,inSize,batchSize:x.shape[0],outSize},inSize):new MeanProgram({windowSize,inSize,batchSize:x.shape[0],outSize}):program=new ReduceProgram({windowSize,inSize,batchSize:x.shape[0],outSize},reductionType),previousResult=result,result=backend22.runWebGLProgram(program,[result],dtype),previousResult.dataId!==x.dataId&&backend22.disposeIntermediateTensorInfo(previousResult)}return result}var TransposeProgram=class{constructor(aShape,newDim){this.variableNames=["A"];let outputShape=new Array(aShape.length);for(let i=0;i<outputShape.length;i++)outputShape[i]=aShape[newDim[i]];this.outputShape=outputShape,this.rank=outputShape.length;let dtype=getCoordsDataType(this.rank),switched=getSwitchedCoords(newDim);this.userCode=`
    void main() {
      ${dtype} resRC = getOutputCoords();
      setOutput(getA(${switched}));
    }
    `}};function getSwitchedCoords(newDim){let rank=newDim.length;if(rank>6)throw Error(`Transpose for rank ${rank} is not yet supported`);let originalOrder=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u","resRC.v"],switchedCoords=new Array(rank);for(let i=0;i<newDim.length;i++)switchedCoords[newDim[i]]=originalOrder[i];return switchedCoords.join()}var TransposePackedProgram=class{constructor(aShape,newDim){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0;let outputShape=new Array(aShape.length);for(let i=0;i<outputShape.length;i++)outputShape[i]=aShape[newDim[i]];if(this.outputShape=outputShape,this.rank=outputShape.length,this.rank>6)throw Error(`Packed transpose for rank ${this.rank} is not yet supported.`);let dtype=getCoordsDataType(this.rank),outputOrder=getVecChannels("rc",this.rank),switchedOrder=new Array(this.rank);for(let i=0;i<newDim.length;i++)switchedOrder[newDim[i]]=outputOrder[i];let innerDims=`vec2(${switchedOrder.slice(-2).join()})`,nextColumn=`++${outputOrder[this.rank-1]} < ${outputShape[this.rank-1]}`,getc=`getChannel(getA(${switchedOrder.join()}), ${innerDims})`;this.userCode=`
    void main() {
      ${dtype} rc = getOutputCoords();
      vec4 result = vec4(0.);
      result[0] = ${getc};
      if(${nextColumn}) {
        result[1] = ${getc};
      }
      --${outputOrder[this.rank-1]};
      if(++${outputOrder[this.rank-2]} < ${outputShape[this.rank-2]}) {
        result[2] = ${getc};
        if(${nextColumn}) {
          result[3] = ${getc};
        }
      }
      setOutput(result);
    }
    `}};function transposeImpl2(x,perm,backend22){let program=env().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new TransposePackedProgram(x.shape,perm):new TransposeProgram(x.shape,perm);return backend22.runWebGLProgram(program,[x],x.dtype)}function sumImpl(x,axis,keepDims,backend22){let reductionIndices=axis,xRank=x.shape.length,origAxes=util_exports.parseAxisParam(reductionIndices,x.shape),axes=origAxes,permutedAxes=backend_util_exports.getAxesPermutation(axes,xRank),sumInputIsTransposed=permutedAxes!=null,sumInput=x;sumInputIsTransposed&&(sumInput=transposeImpl2(x,permutedAxes,backend22),axes=backend_util_exports.getInnerMostAxes(axes.length,xRank)),backend_util_exports.assertAxesAreInnerMostDims("sum",axes,xRank);let[sumOutShape,reduceShape]=backend_util_exports.computeOutAndReduceShapes(sumInput.shape,axes),outShape=sumOutShape;keepDims&&(outShape=backend_util_exports.expandShapeToKeepDim(sumOutShape,origAxes));let inSize=util_exports.sizeFromShape(reduceShape),batchSize=util_exports.sizeFromShape(x.shape)/inSize,reshapedInput=reshape3({inputs:{x:sumInput},attrs:{shape:[batchSize,inSize]},backend:backend22}),outType=sumOutType(x.dtype),reduced=reduce(reshapedInput,outType,"sum",backend22),out=reshape3({inputs:{x:reduced},attrs:{shape:outShape},backend:backend22});return backend22.disposeIntermediateTensorInfo(reshapedInput),backend22.disposeIntermediateTensorInfo(reduced),sumInputIsTransposed&&backend22.disposeIntermediateTensorInfo(sumInput),out}function sum4(args){let{inputs,backend:backend22,attrs}=args,{x}=inputs,{axis,keepDims}=attrs;return sumImpl(x,axis,keepDims,backend22)}var sumConfig2={kernelName:Sum,backendName:"webgl",kernelFunc:sum4};function transpose3(args){let{inputs,backend:backend22,attrs}=args,{x}=inputs,{perm}=attrs,webglBackend=backend22,xRank=x.shape.length,newShape=new Array(xRank);for(let i=0;i<newShape.length;i++)newShape[i]=x.shape[perm[i]];let out;if(webglBackend.shouldExecuteOnCPU([x])){let values=webglBackend.texData.get(x.dataId).values,outValues=transposeImplCPU(values,x.shape,x.dtype,perm,newShape);out=webglBackend.makeTensorInfo(newShape,x.dtype);let outData=webglBackend.texData.get(out.dataId);outData.values=outValues}else out=transposeImpl2(x,perm,webglBackend);return out}var transposeConfig2={kernelName:Transpose,backendName:"webgl",kernelFunc:transpose3},MATMUL_SHARED_DIM_THRESHOLD=1e3;function batchMatMulImpl({a,b,transposeA,transposeB,backend:backend22,bias=null,preluActivationWeights=null,leakyreluAlpha=0,activation:activation2=null}){let aRank=a.shape.length,bRank=b.shape.length,innerShapeA=transposeA?a.shape[aRank-2]:a.shape[aRank-1],innerShapeB=transposeB?b.shape[bRank-1]:b.shape[bRank-2],outerShapeA=transposeA?a.shape[aRank-1]:a.shape[aRank-2],outerShapeB=transposeB?b.shape[bRank-2]:b.shape[bRank-1],outerDimsA=a.shape.slice(0,-2),outerDimsB=b.shape.slice(0,-2),batchDimA=util_exports.sizeFromShape(outerDimsA),batchDimB=util_exports.sizeFromShape(outerDimsB),batchDimsCompatible=batchDimA===batchDimB||batchDimA===1||batchDimB===1;util_exports.assert(aRank>=2&&bRank>=2&&batchDimsCompatible,()=>`Error in matMul: the input batch dimensions must either be the same or at least one input batch dimension must be 1. Got input batch dimensions of (${outerDimsA}) and (${outerDimsB}).`);let outShape=(batchDimA>batchDimB?a.shape.slice(0,-2):b.shape.slice(0,-2)).concat([outerShapeA,outerShapeB]);util_exports.assert(innerShapeA===innerShapeB,()=>`Error in matMul: inner shapes (${innerShapeA}) and (${innerShapeB}) of Tensors with shapes ${a.shape} and ${b.shape} and transposeA=${transposeA} and transposeB=${transposeB} must match.`);let a3dShape=transposeA?[batchDimA,innerShapeA,outerShapeA]:[batchDimA,outerShapeA,innerShapeA],b3dShape=transposeB?[batchDimB,outerShapeB,innerShapeB]:[batchDimB,innerShapeB,outerShapeB],a3d=reshape3({inputs:{x:a},backend:backend22,attrs:{shape:a3dShape}}),b3d=reshape3({inputs:{x:b},backend:backend22,attrs:{shape:b3dShape}}),intermediates=[a3d,b3d],batchDim=Math.max(batchDimA,batchDimB),sharedDim=transposeA?a3d.shape[1]:a3d.shape[2],hasBias=bias!=null,hasPreluActi
  if (abs(x) > 1.) {
    return NAN;
  }
  return acos(x);
`,acos3=unaryKernelFunc2({opSnippet:ACOS}),acosConfig2={kernelName:Acos,backendName:"webgl",kernelFunc:acos3},ACOSH=CHECK_NAN_SNIPPET+`
  if (x < 1.0) return NAN;
return log(x + sqrt(x * x - 1.0));`,acosh3=unaryKernelFunc2({opSnippet:ACOSH}),acoshConfig2={kernelName:Acosh,backendName:"webgl",kernelFunc:acosh3},ADD="return a + b;",addKernelFunc=binaryKernelFunc2({opSnippet:ADD,packedOpSnippet:ADD,supportsComplex:!0,cpuKernelImpl:addImplCPU}),addConfig2={kernelName:Add,backendName:"webgl",kernelFunc:addKernelFunc},AddNProgram=class{constructor(outputShape,shapes){this.outputShape=[],this.outputShape=outputShape,this.variableNames=shapes.map((_,i)=>`T${i}`);let snippets=[];this.variableNames.forEach(variable2=>{snippets.push(`float v${variable2} = get${variable2}AtOutCoords();`)});let operation=this.variableNames.map(variable2=>`v${variable2}`).join(" + ");this.userCode=`
      void main() {
        ${snippets.join(`
        `)}

        float result = ${operation};
        setOutput(result);
      }
    `}},AddNPackedProgram=class{constructor(outputShape,shapes){this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=outputShape,this.variableNames=shapes.map((_,i)=>`T${i}`);let snippets=[];this.variableNames.forEach(variable2=>{snippets.push(`vec4 v${variable2} = get${variable2}AtOutCoords();`)});let operation=this.variableNames.map(variable2=>`v${variable2}`).join(" + ");this.userCode=`
      void main() {
        ${snippets.join(`
        `)}

        vec4 result = ${operation};
        setOutput(result);
      }
    `}};function addN3(args){let{inputs,backend:backend22}=args,tensors=inputs;if(tensors.length===1)return identity2({inputs:{x:tensors[0]},backend:backend22});if(tensors.length>env().get("WEBGL_MAX_TEXTURES_IN_SHADER")){let midIndex=Math.floor(tensors.length/2),leftSide=addN3({inputs:tensors.slice(0,midIndex),backend:backend22}),rightSide=addN3({inputs:tensors.slice(midIndex),backend:backend22});return addN3({inputs:[leftSide,rightSide],backend:backend22})}let dtype=tensors.map(t=>t.dtype).reduce((d1,d2)=>upcastType(d1,d2)),shapes=tensors.map(t=>t.shape),program=env().getBool("WEBGL_PACK")?new AddNPackedProgram(tensors[0].shape,shapes):new AddNProgram(tensors[0].shape,shapes);return backend22.runWebGLProgram(program,tensors,dtype)}var addNConfig2={kernelName:AddN,backendName:"webgl",kernelFunc:addN3};function all3(args){let{inputs,backend:backend22,attrs}=args,{x}=inputs,{axis,keepDims}=attrs,xRank=x.shape.length,origAxes=util_exports.parseAxisParam(axis,x.shape),axes=origAxes,permutedAxes=backend_util_exports.getAxesPermutation(axes,xRank),permutedX=x;permutedAxes!=null&&(permutedX=transpose3({inputs:{x},backend:backend22,attrs:{perm:permutedAxes}}),axes=backend_util_exports.getInnerMostAxes(axes.length,xRank)),backend_util_exports.assertAxesAreInnerMostDims("all",axes,xRank);let[outShape,reduceShape]=backend_util_exports.computeOutAndReduceShapes(permutedX.shape,axes),inSize=util_exports.sizeFromShape(reduceShape),a2D=reshape3({inputs:{x:permutedX},backend:backend22,attrs:{shape:[-1,inSize]}}),reduced=reduce(a2D,a2D.dtype,"all",backend22),res;if(keepDims){let newShape=backend_util_exports.expandShapeToKeepDim(outShape,origAxes);res=reshape3({inputs:{x:reduced},backend:backend22,attrs:{shape:newShape}})}else res=reshape3({inputs:{x:reduced},backend:backend22,attrs:{shape:outShape}});return backend22.disposeIntermediateTensorInfo(a2D),backend22.disposeIntermediateTensorInfo(reduced),permutedAxes!=null&&backend22.disposeIntermediateTensorInfo(permutedX),res}var allConfig2={kernelName:All,backendName:"webgl",kernelFunc:all3};function any3(args){let{inputs,backend:backend22,attrs}=args,{x}=inputs,{axis,keepDims}=attrs,xRank=x.shape.length,origAxes=util_exports.parseAxisParam(axis,x.shape),axes=origAxes,permutedAxes=backend_util_exports.getAxesPermutation(axes,xRank),permutedX=x;permutedAxes!=null&&(permutedX=transpose3({inputs:{x},backend:backend22,attrs:{perm:permutedAxes}}),axes=backend_util_exports.getInnerMostAxes(axes.length,xRank)),backend_util_exports.assertAxesAreInnerMostDims("any",axes,xRank);let[outShape,reduceShape]=backend_util_exports.computeOutAndReduceShapes(permutedX.shape,axes),inSize=util_exports.sizeFromShape(reduceShape),a2D=reshape3({inputs:{x:permutedX},backend:backend22,attrs:{shape:[-1,inSize]}}),reduced=reduce(a2D,a2D.dtype,"any",backend22),res;if(keepDims){let newShape=backend_util_exports.expandShapeToKeepDim(outShape,origAxes);res=reshape3({inputs:{x:reduced},backend:backend22,attrs:{shape:newShape}})}else res=reshape3({inputs:{x:reduced},backend:backend22,attrs:{shape:outShape}});return backend22.disposeIntermediateTensorInfo(a2D),backend22.disposeIntermediateTensorInfo(reduced),permutedAxes!=null&&backend22.disposeIntermediateTensorInfo(permutedX),res}var anyConfig2={kernelName:Any,backendName:"webgl",kernelFunc:any3},ArgMinMaxProgram=class{constructor(reduceInfo,op2,firstPass){this.variableNames=["A"];let{windowSize,batchSize,outSize}=reduceInfo;firstPass||this.variableNames.push("bestIndicesA"),this.outputShape=[batchSize,outSize];let compOp=op2==="max"?">":"<",indexSnippet=firstPass?"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 * ${windowSize};

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

        for (int i = 0; i < ${windowSize}; i++) {
          int inIdx = ${indexSnippet};
          float candidate = getA(batch, inIdx);
          if (candidate ${compOp} bestValue) {
            bestValue = candidate;
            bestIndex = inIdx;
          }
        }
        setOutput(float(bestIndex));
      }
    `}},ArgMinMaxPackedProgram=class{constructor(shape,windowSize,op2,firstPass){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,util_exports.assert(shape.length>2,()=>`Packed arg${op2.charAt(0).toUpperCase()+op2.slice(1)} supports only inputs with rank above 2.`);let inSize=shape[shape.length-1],outSize=Math.ceil(inSize/windowSize);this.outputShape=shape.slice(0,-1),outSize>1&&this.outputShape.push(outSize),firstPass||this.variableNames.push("bestIndicesA");let outShape=this.outputShape,rank=outShape.length,dtype=getCoordsDataType(rank),coords2=getChannels("coords",rank),sourceLocSetup,sourceRank;if(outSize===1){sourceRank=rank+1;let sourceLocDType=getCoordsDataType(sourceRank);sourceLocSetup=`
        ${sourceLocDType} sourceLocR = ${sourceLocDType}(${coords2.join()}, 0);
        ++${coords2[rank-1]};
        ${sourceLocDType} sourceLocG = ${sourceLocDType}(${coords2.join()}, 0);
        ++${coords2[rank-2]};
        ${sourceLocDType} sourceLocA = ${sourceLocDType}(${coords2.join()}, 0);
        --${coords2[rank-1]};
        ${sourceLocDType} sourceLocB = ${sourceLocDType}(${coords2.join()}, 0);
        --${coords2[rank-2]};`}else sourceRank=rank,sourceLocSetup=`
        ${dtype} sourceLocR = coords;
        ++${coords2[rank-1]};
        ${dtype} sourceLocG = coords;
        ++${coords2[rank-2]};
        ${dtype} sourceLocA = coords;
        --${coords2[rank-1]};
        ${dtype} sourceLocB = coords;
        --${coords2[rank-2]};`;let channels=["x","y","z","w","u","v"].slice(0,sourceRank),inChannel="."+channels[sourceRank-1],intChannels=channels.map(x=>"int "+x),srcRCoords=getChannels("sourceLocR",sourceRank-1).concat("inIdx.r"),srcGCoords=getChannels("sourceLocG",sourceRank-1).concat("inIdx.g"),srcBCoords=getChannels("sourceLocB",sourceRank-1).concat("inIdx.b"),srcACoords=getChannels("sourceLocA",sourceRank-1).concat("inIdx.a"),compOp=op2==="max"?"greaterThan":"lessThan",fetchCandidateIdx=firstPass?"":`
          inIdx = round(vec4(getBestIndicesAChannel(${srcRCoords.join()}),
                             getBestIndicesAChannel(${srcGCoords.join()}),
                             getBestIndicesAChannel(${srcBCoords.join()}),
                             getBestIndicesAChannel(${srcACoords.join()})));`,fetchValue=`vec4(
            getAChannel(${srcRCoords.join()}),
            hasNextCol ? getAChannel(${srcGCoords.join()}) : 0.,
            hasNextRow ? getAChannel(${srcBCoords.join()}) : 0.,
            hasNextRow && hasNextCol ? getAChannel(${srcACoords.join()}) : 0.)`,getBestIndicesAChannelSnippet=firstPass?"":`
      float getBestIndicesAChannel(${intChannels.join()}) {
        return getChannel(getBestIndicesA(${channels.join()}),
                                          vec2(${channels.slice(-2).join()}));
      }`;this.userCode=`
      float getAChannel(${intChannels.join()}) {
        return getChannel(getA(${channels.join()}),
                               vec2(${channels.slice(-2).join()}));
      }
      ${getBestIndicesAChannelSnippet}
      void main() {
        ${dtype} coords = getOutputCoords();
        bool hasNextCol = ${coords2[rank-1]} < ${outShape[rank-1]-1};
        bool hasNextRow = ${coords2[rank-2]} < ${outShape[rank-2]-1};
        ${sourceLocSetup}
        ivec4 srcIdx = ivec4(sourceLocR${inChannel}, sourceLocG${inChannel},
          sourceLocB${inChannel}, sourceLocA${inChannel}) * ${windowSize};
        ivec4 inIdx = srcIdx;
        vec4 bestIndex = vec4(inIdx);
        vec4 bestValue = ${fetchValue};

        for (int i = 0; i < ${windowSize}; i++) {
          inIdx = srcIdx;
          ${fetchCandidateIdx}
          vec4 candidate = ${fetchValue};
          bvec4 nan = isnan(candidate);
          bvec4 replace = bvec4(
            vec4(${compOp}(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 argReduce(backend22,x,reduceType,bestIndicesA=null){let batchSize=x.shape[0],inSize=x.shape[1];bestIndicesA!=null&&(batchSize=bestIndicesA.shape[0],inSize=bestIndicesA.shape[1]);let windowSize=backend_util_exports.computeOptimalWindowSize(inSize),reduceInfo={windowSize,inSize,batchSize,outSize:Math.ceil(inSize/windowSize)},program=new ArgMinMaxProgram(reduceInfo,reduceType,bestIndicesA==null),inputs=[x];bestIndicesA!=null&&inputs.push(bestIndicesA);let output=backend22.runWebGLProgram(program,inputs,"int32");if(output.shape[1]===1)return output;let result=argReduce(backend22,x,reduceType,output);return backend22.disposeIntermediateTensorInfo(output),result}function argReducePacked(backend22,x,reduceType,bestIndicesA=null){let inShape=bestIndicesA!=null?bestIndicesA.shape:x.shape,inSize=inShape[inShape.length-1],windowSize=backend_util_exports.computeOptimalWindowSize(inSize),program=new ArgMinMaxPackedProgram(inShape,windowSize,reduceType,bestIndicesA==null),inputs=bestIndicesA==null?[x]:[x,bestIndicesA],output=backend22.runWebGLProgram(program,inputs,"int32");if(output.shape.length===x.shape.length){let result=argReducePacked(backend22,x,reduceType,output);return backend22.disposeIntermediateTensorInfo(output),result}return output}function argMinMaxReduce(backend22,x,axis,reduceType){let axes=[axis];if(backend_util_exports.assertAxesAreInnerMostDims("arg"+reduceType.charAt(0).toUpperCase()+reduceType.slice(1),axes,x.shape.length),!env().getBool("WEBGL_PACK_REDUCE")||x.shape.length<=2){let intermediateTensorInfos=[],[outShape,reduceShape]=backend_util_exports.computeOutAndReduceShapes(x.shape,axes),inSize=util_exports.sizeFromShape(reduceShape),a2D=reshape3({inputs:{x},backend:backend22,attrs:{shape:[-1,inSize]}});intermediateTensorInfos.push(a2D);let reduced=argReduce(backend22,a2D,reduceType);intermediateTensorInfos.push(reduced);let reshaped=reshape3({inputs:{x:reduced},backend:backend22,attrs:{shape:outShape}});return intermediateTensorInfos.forEach(t=>backend22.disposeIntermediateTensorInfo(t)),reshaped}return argReducePacked(backend22,x,reduceType)}function argMax3(args){let{inputs,backend:backend22,attrs}=args,{x}=inputs,{axis}=attrs,axes=util_exports.parseAxisParam(axis,x.shape),permutedAxes=backend_util_exports.getAxesPermutation(axes,x.shape.length),$x=x,intermediateTensorInfos=[];permutedAxes!=null&&($x=transpose3({inputs:{x},backend:backend22,attrs:{perm:permutedAxes}}),intermediateTensorInfos.push($x),axes=backend_util_exports.getInnerMostAxes(axes.length,$x.shape.length)),backend_util_exports.assertAxesAreInnerMostDims("argMax",[axes[0]],$x.shape.length);let out=argMinMaxReduce(backend22,$x,axes[0],"max");return intermediateTensorInfos.forEach(t=>backend22.disposeIntermediateTensorInfo(t)),out}var argMaxConfig2={kernelName:ArgMax,backendName:"webgl",kernelFunc:argMax3};function argMin3(args){let{inputs,backend:backend22,attrs}=args,{x}=inputs,{axis}=attrs,axes=util_exports.parseAxisParam(axis,x.shape),permutedAxes=backend_util_exports.getAxesPermutation(axes,x.shape.length),$x=x,intermediateTensorInfos=[];permutedAxes!=null&&($x=transpose3({inputs:{x},backend:backend22,attrs:{perm:permutedAxes}}),intermediateTensorInfos.push($x),axes=backend_util_exports.getInnerMostAxes(axes.length,$x.shape.length)),backend_util_exports.assertAxesAreInnerMostDims("argMin",[axes[0]],$x.shape.length);let out=argMinMaxReduce(backend22,$x,axes[0],"min");return intermediateTensorInfos.forEach(t=>backend22.disposeIntermediateTensorInfo(t)),out}var argMinConfig2={kernelName:ArgMin,backendName:"webgl",kernelFunc:argMin3},ASIN=CHECK_NAN_SNIPPET+`
  if (abs(x) > 1.) {
    return NAN;
  }
  return asin(x);
`,asin3=unaryKernelFunc2({opSnippet:ASIN}),asinConfig2={kernelName:Asin,backendName:"webgl",kernelFunc:asin3},ASINH=CHECK_NAN_SNIPPET+"return log(x + sqrt(x * x + 1.0));",asinh3=unaryKernelFunc2({opSnippet:ASINH}),asinhConfig2={kernelName:Asinh,backendName:"webgl",kernelFunc:asinh3},ATAN=CHECK_NAN_SNIPPET+`
  return atan(x);
`,atan4=unaryKernelFunc2({opSnippet:ATAN}),atanConfig2={kernelName:Atan,backendName:"webgl",kernelFunc:atan4},ATAN2=CHECK_NAN_SNIPPET_BINARY+`
  return atan(a, b);
`,ATAN2_PACKED=`
  vec4 result = atan(a, b);
  vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
  `+CHECK_NAN_SNIPPET_BINARY_PACKED+`
  return result;
`,atan23=binaryKernelFunc2({opSnippet:ATAN2,packedOpSnippet:ATAN2_PACKED}),atan2Config2={kernelName:Atan2,backendName:"webgl",kernelFunc:atan23},ATANH=CHECK_NAN_SNIPPET+`
  if ((x < -1.0) || (x > 1.0)) return NAN;
return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,atanh3=unaryKernelFunc2({opSnippet:ATANH}),atanhConfig2={kernelName:Atanh,backendName:"webgl",kernelFunc:atanh3},Pool2DProgram=class{constructor(convInfo,poolType,computePositions,flattenPositions=!1,includeBatchInIndex=!1){if(this.variableNames=["x"],poolType==="avg"&&computePositions)throw new Error("Cannot compute positions for average pool.");let filterWidth=convInfo.filterWidth,strideHeight=convInfo.strideHeight,strideWidth=convInfo.strideWidth,dilationHeight=convInfo.dilationHeight,dilationWidth=convInfo.dilationWidth,effectiveFilterHeight=convInfo.effectiveFilterHeight,effectiveFilterWidth=convInfo.effectiveFilterWidth,padTop=convInfo.padInfo.top,padLeft=convInfo.padInfo.left;this.outputShape=convInfo.outShape;let isAvgPool=poolType==="avg",batchFlattenPositionStr=`((batch  * ${convInfo.inHeight} + xR) * ${convInfo.inWidth} + xC) * ${convInfo.inChannels} + d`,flattenPositionStr=`(xR * ${convInfo.inWidth} + xC) * ${convInfo.inChannels} + d`,initializationValue="0.0";if(isAvgPool||(initializationValue="-1.0 / 1e-20"),computePositions){let compareOp2=">=";this.userCode=`
        const ivec2 strides = ivec2(${strideHeight}, ${strideWidth});
        const ivec2 pads = ivec2(${padTop}, ${padLeft});

        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 < ${effectiveFilterHeight};
              wR += ${dilationHeight}) {
            int xR = xRCorner + wR;

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

            for (int wC = 0; wC < ${effectiveFilterWidth};
                wC += ${dilationWidth}) {
              int xC = xCCorner + wC;

              if (xC < 0 || xC >= ${convInfo.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 ${compareOp2} currMinMaxValue) {
                minMaxValue = value;
                minMaxValueFound = 1.0;
                minMaxPosition = ${flattenPositions?includeBatchInIndex?batchFlattenPositionStr:flattenPositionStr:`wR * ${effectiveFilterWidth} + wC`};
              }
            }
          }
          setOutput(float(minMaxPosition));
        }
      `;return}let compareOp="max",returnValue=`${poolType}(${poolType}(${poolType}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;poolType==="avg"&&(returnValue="avgValue / count");let filterWidthNearestVec4=Math.floor(filterWidth/4)*4,filterWidthVec4Remainder=filterWidth%4,updateSnippet=`
      if (${isAvgPool}) {
        avgValue += dot(values, ones);
      } else {
        minMaxValue = ${compareOp}(values, minMaxValue);
      }
    `;this.userCode=`
      const ivec2 strides = ivec2(${strideHeight}, ${strideWidth});
      const ivec2 pads = ivec2(${padTop}, ${padLeft});
      const float initializationValue = ${initializationValue};
      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 >= ${convInfo.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(${initializationValue});
        float avgValue = 0.0;
        count = 0.0;

        for (int wR = 0; wR < ${effectiveFilterHeight};
            wR += ${dilationHeight}) {
          int xR = xRCorner + wR;

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

          for (int wC = 0; wC < ${filterWidthNearestVec4}; wC += 4) {
            int xC = xCCorner + wC * ${dilationWidth};

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

            ${updateSnippet}
          }

          int xC = xCCorner + ${filterWidthNearestVec4};
          if (${filterWidthVec4Remainder===1}) {
            vec4 values = vec4(
              getValue(batch, xR, xC, d),
              initializationValue,
              initializationValue,
              initializationValue
            );

            ${updateSnippet}
          } else if (${filterWidthVec4Remainder===2}) {
            vec4 values = vec4(
              getValue(batch, xR, xC, d),
              getValue(batch, xR, xC + ${dilationWidth}, d),
              initializationValue,
              initializationValue
            );

            ${updateSnippet}
          } else if (${filterWidthVec4Remainder===3}) {
            vec4 values = vec4(
              getValue(batch, xR, xC, d),
              getValue(batch, xR, xC + ${dilationWidth}, d),
              getValue(batch, xR, xC + 2 * ${dilationWidth}, d),
              initializationValue
            );

            ${updateSnippet}
          }
        }
        setOutput(${returnValue});
      }
    `}},Pool3DProgram=class{constructor(convInfo,poolType,computePositions,flattenPositions=!1,includeBatchInIndex=!1){if(this.variableNames=["x"],poolType==="avg"&&computePositions)throw new Error("Cannot compute positions for average pool.");let filterWidth=convInfo.filterWidth,strideDepth=convInfo.strideDepth,strideHeight=convInfo.strideHeight,strideWidth=convInfo.strideWidth,dilationDepth=convInfo.dilationDepth,dilationHeight=convInfo.dilationHeight,dilationWidth=convInfo.dilationWidth,effectiveFilterDepth=convInfo.effectiveFilterDepth,effectiveFilterHeight=convInfo.effectiveFilterHeight,effectiveFilterWidth=convInfo.effectiveFilterWidth,padFront=convInfo.padInfo.front,padTop=convInfo.padInfo.top,padLeft=convInfo.padInfo.left;this.outputShape=convInfo.outShape;let isAvgPool=poolType==="avg",initializationValue="0.0";if(isAvgPool||(initializationValue="-1.0 / 1e-20"),computePositions){let compareOp2=">=";this.userCode=`
        const ivec3 strides =
            ivec3(${strideDepth}, ${strideHeight}, ${strideWidth});
        const ivec3 pads = ivec3(${padFront}, ${padTop}, ${padLeft});

        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 < ${effectiveFilterDepth};
              wD += ${dilationDepth}) {
            int xD = xDCorner + wD;

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

            for (int wR = 0; wR < ${effectiveFilterHeight};
                wR += ${dilationHeight}) {
              int xR = xRCorner + wR;

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

              for (int wC = 0; wC < ${effectiveFilterWidth};
                  wC += ${dilationWidth}) {
                int xC = xCCorner + wC;

                if (xC < 0 || xC >= ${convInfo.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 ${compareOp2} currMinMaxValue) {
                  minMaxValue = value;
                  minMaxValueFound = 1.0;
                  minMaxPosition = ${flattenPositions?includeBatchInIndex?`(((batch * ${convInfo.inDepth} + xD) * ${convInfo.inHeight} + xR) * ${convInfo.inWidth} + xC) * ${convInfo.inChannels} + ch`:`((xD * ${convInfo.inHeight} + xR) * ${convInfo.inWidth} + xC) * ${convInfo.inChannels} + ch`:`wD * ${effectiveFilterHeight} * ${effectiveFilterWidth} +
                      wR * ${effectiveFilterWidth} + wC`};
                }
              }
            }
          }
          setOutput(float(minMaxPosition));
        }
      `;return}let compareOp="max",returnValue=`${poolType}(${poolType}(${poolType}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;poolType==="avg"&&(returnValue="avgValue / count");let filterWidthNearestVec4=Math.floor(filterWidth/4)*4,filterWidthVec4Remainder=filterWidth%4,updateSnippet=`
      if (${isAvgPool}) {
        avgValue += dot(values, ones);
      } else {
        minMaxValue = ${compareOp}(values, minMaxValue);
      }
    `;this.userCode=`
      const ivec3 strides =
        ivec3(${strideDepth}, ${strideHeight}, ${strideWidth});
      const ivec3 pads = ivec3(${padFront}, ${padTop}, ${padLeft});
      const float initializationValue = ${initializationValue};
      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 >= ${convInfo.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(${initializationValue});
        float avgValue = 0.0;
        count = 0.0;

        for (int wD = 0; wD < ${effectiveFilterDepth};
            wD += ${dilationDepth}) {
          int xD = xDCorner + wD;

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

          for (int wR = 0; wR < ${effectiveFilterHeight};
            wR += ${dilationHeight}) {
            int xR = xRCorner + wR;

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

            for (int wC = 0; wC < ${filterWidthNearestVec4}; wC += 4) {
              int xC = xCCorner + wC * ${dilationWidth};

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

              ${updateSnippet}
            }

            int xC = xCCorner + ${filterWidthNearestVec4};
            if (${filterWidthVec4Remainder===1}) {
              vec4 values = vec4(
                getValue(batch, xD, xR, xC, ch),
                initializationValue,
                initializationValue,
                initializationValue
              );

              ${updateSnippet}
            } else if (${filterWidthVec4Remainder===2}) {
              vec4 values = vec4(
                getValue(batch, xD, xR, xC, ch),
                getValue(batch, xD, xR, xC + ${dilationWidth}, ch),
                initializationValue,
                initializationValue
              );

              ${updateSnippet}
            } else if (${filterWidthVec4Remainder===3}) {
              vec4 values = vec4(
                getValue(batch, xD, xR, xC, ch),
                getValue(batch, xD, xR, xC + ${dilationWidth}, ch),
                getValue(batch, xD, xR, xC + 2 * ${dilationWidth}, ch),
                initializationValue
              );

              ${updateSnippet}
            }
          }
          setOutput(${returnValue});
        }
      }
    `}};function avgPool3(args){let{inputs,backend:backend22,attrs}=args,{x}=inputs;assertNotComplex2(x,"avgPool");let{filterSize,strides,pad:pad3,dimRoundingMode}=attrs,dilations=1;util_exports.assert(backend_util_exports.eitherStridesOrDilationsAreOne(strides,dilations),()=>`Error in avgPool: Either strides or dilations must be 1. Got strides ${strides} and dilations '${dilations}'`);let convInfo=backend_util_exports.computePool2DInfo(x.shape,filterSize,strides,dilations,pad3,dimRoundingMode);if(convInfo.filterWidth===1&&convInfo.filterHeight===1&&util_exports.arraysEqual(convInfo.inShape,convInfo.outShape))return identity2({inputs:{x},backend:backend22});let avgPoolProgram=new Pool2DProgram(convInfo,"avg",!1);return backend22.runWebGLProgram(avgPoolProgram,[x],"float32")}var avgPoolConfig2={kernelName:AvgPool,backendName:"webgl",kernelFunc:avgPool3};function avgPool3D2(args){let{inputs,backend:backend22,attrs}=args,{x}=inputs,{filterSize,strides,pad:pad3,dimRoundingMode,dataFormat}=attrs,dilations=[1,1,1],convInfo=backend_util_exports.computePool3DInfo(x.shape,filterSize,strides,dilations,pad3,dimRoundingMode,dataFormat),avgPoolProgram=new Pool3DProgram(convInfo,"avg",!1);return backend22.runWebGLProgram(avgPoolProgram,[x],"float32")}var avgPool3DConfig2={kernelName:AvgPool3D,backendName:"webgl",kernelFunc:avgPool3D2},AvgPool2DBackpropProgram=class{constructor(convInfo){this.variableNames=["dy"],this.outputShape=convInfo.inShape;let filterHeight=convInfo.filterHeight,filterWidth=convInfo.filterWidth,strideHeight=convInfo.strideHeight,strideWidth=convInfo.strideWidth,dilationHeight=convInfo.dilationHeight,dilationWidth=convInfo.dilationWidth,effectiveFilterHeight=convInfo.effectiveFilterHeight,effectiveFilterWidth=convInfo.effectiveFilterWidth,padTop=effectiveFilterHeight-1-convInfo.padInfo.top,padLeft=effectiveFilterWidth-1-convInfo.padInfo.left,avgMultiplier=1/(filterHeight*filterWidth);this.userCode=`
      const ivec2 pads = ivec2(${padTop}, ${padLeft});
      const float avgMultiplier = float(${avgMultiplier});

      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 < ${effectiveFilterHeight};
            wR += ${dilationHeight}) {
          float dyR = float(dyRCorner + wR) / ${strideHeight}.0;

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

          for (int wC = 0; wC < ${effectiveFilterWidth};
            wC+= ${dilationWidth}) {
            float dyC = float(dyCCorner + wC) / ${strideWidth}.0;

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

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

            dotProd += dyValue * avgMultiplier;
          }
        }
        setOutput(dotProd);
      }
    `}},AvgPool3DBackpropProgram=class{constructor(convInfo){this.variableNames=["dy"],this.outputShape=convInfo.inShape;let filterDepth=convInfo.filterDepth,filterHeight=convInfo.filterHeight,filterWidth=convInfo.filterWidth,strideDepth=convInfo.strideDepth,strideHeight=convInfo.strideHeight,strideWidth=convInfo.strideWidth,dilationDepth=convInfo.dilationDepth,dilationHeight=convInfo.dilationHeight,dilationWidth=convInfo.dilationWidth,effectiveFilterDepth=convInfo.effectiveFilterDepth,effectiveFilterHeight=convInfo.effectiveFilterHeight,effectiveFilterWidth=convInfo.effectiveFilterWidth,padFront=effectiveFilterDepth-1-convInfo.padInfo.front,padTop=effectiveFilterHeight-1-convInfo.padInfo.top,padLeft=effectiveFilterWidth-1-convInfo.padInfo.left,avgMultiplier=1/(filterDepth*filterHeight*filterWidth);this.userCode=`
      const ivec3 pads = ivec3(${padFront}, ${padTop}, ${padLeft});
      const float avgMultiplier = float(${avgMultiplier});

      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 < ${effectiveFilterDepth};
            wD += ${dilationDepth}) {
          float dyD = float(dyDCorner + wD) / ${strideDepth}.0;

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

          for (int wR = 0; wR < ${effectiveFilterHeight};
              wR += ${dilationHeight}) {
            float dyR = float(dyRCorner + wR) / ${strideHeight}.0;

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

            for (int wC = 0; wC < ${effectiveFilterWidth};
                wC += ${dilationWidth}) {
              float dyC = float(dyCCorner + wC) / ${strideWidth}.0;

              if (dyC < 0.0 || dyC >= ${convInfo.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 avgPool3DGrad2(args){let{inputs,backend:backend22,attrs}=args,{dy,input:input2}=inputs,x=input2,{filterSize,strides,pad:pad3,dimRoundingMode}=attrs,dilations=[1,1,1],convInfo=backend_util_exports.computePool3DInfo(x.shape,filterSize,strides,dilations,pad3,dimRoundingMode),avgPoolBackpropProgram=new AvgPool3DBackpropProgram(convInfo);return backend22.runWebGLProgram(avgPoolBackpropProgram,[dy],x.dtype)}var avgPoolGrad3DConfig={kernelName:AvgPool3DGrad,backendName:"webgl",kernelFunc:avgPool3DGrad2};function avgPoolGrad3(args){let{inputs,backend:backend22,attrs}=args,{dy,input:input2}=inputs,x=input2;assertNotComplex2([dy,input2],"avgPoolGrad");let{filterSize,strides,pad:pad3}=attrs,convInfo=backend_util_exports.computePool2DInfo(x.shape,filterSize,strides,1,pad3),avgPoolBackpropProgram=new AvgPool2DBackpropProgram(convInfo);return backend22.runWebGLProgram(avgPoolBackpropProgram,[dy],x.dtype)}var avgPoolGradConfig3={kernelName:AvgPoolGrad,backendName:"webgl",kernelFunc:avgPoolGrad3};function batchMatMul2(args){let{inputs,backend:backend22,attrs}=args,{a,b}=inputs,{transposeA,transposeB}=attrs;return batchMatMulImpl({a,b,transposeA,transposeB,backend:backend22})}var batchMatMulConfig2={kernelName:BatchMatMul,backendName:"webgl",kernelFunc:batchMatMul2},BatchNormProgram=class{constructor(xShape,meanShape,varianceShape,offsetShape,scaleShape,varianceEpsilon){this.outputShape=[],this.variableNames=["x","mean","variance"],backend_util_exports.assertAndGetBroadcastShape(xShape,meanShape),backend_util_exports.assertAndGetBroadcastShape(xShape,varianceShape);let offsetSnippet="0.0";offsetShape!=null&&(backend_util_exports.assertAndGetBroadcastShape(xShape,offsetShape),this.variableNames.push("offset"),offsetSnippet="getOffsetAtOutCoords()");let scaleSnippet="1.0";scaleShape!=null&&(backend_util_exports.assertAndGetBroadcastShape(xShape,scaleShape),this.variableNames.push("scale"),scaleSnippet="getScaleAtOutCoords()"),this.outputShape=xShape,this.userCode=`
      void main() {
        float x = getXAtOutCoords();
        float mean = getMeanAtOutCoords();
        float variance = getVarianceAtOutCoords();
        float offset = ${offsetSnippet};
        float scale = ${scaleSnippet};
        float inv = scale * inversesqrt(variance + float(${varianceEpsilon}));
        setOutput(dot(vec3(x, -mean, offset), vec3(inv, inv, 1)));
      }
    `}},BatchNormPackedProgram=class{constructor(xShape,meanShape,varianceShape,offsetShape,scaleShape,varianceEpsilon){this.packedInputs=!0,this.packedOutput=!0,this.variableNames=["x","mean","variance"],backend_util_exports.assertAndGetBroadcastShape(xShape,meanShape),backend_util_exports.assertAndGetBroadcastShape(xShape,varianceShape);let offsetSnippet="vec4(0.0)";offsetShape!=null&&(backend_util_exports.assertAndGetBroadcastShape(xShape,offsetShape),this.variableNames.push("offset"),offsetSnippet="getOffsetAtOutCoords()");let scaleSnippet="vec4(1.0)";scaleShape!=null&&(backend_util_exports.assertAndGetBroadcastShape(xShape,scaleShape),this.variableNames.push("scale"),scaleSnippet="getScaleAtOutCoords()"),this.outputShape=xShape,this.userCode=`
      void main() {
        vec4 offset = ${offsetSnippet};
        vec4 scale = ${scaleSnippet};

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

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

        setOutput((x - mean) * inv + offset);
      }
    `}},batchNorm3=({inputs,backend:backend22,attrs})=>{let{x,mean:mean4,variance,offset,scale:scale2}=inputs;util_exports.assert(mean4.shape.length===variance.shape.length,()=>"Batch normalization gradient requires mean and variance to have equal ranks."),util_exports.assert(offset==null||mean4.shape.length===offset.shape.length,()=>"Batch normalization gradient requires mean and offset to have equal ranks."),util_exports.assert(scale2==null||mean4.shape.length===scale2.shape.length,()=>"Batch normalization gradient requires mean and scale to have equal ranks.");let{varianceEpsilon}=attrs;varianceEpsilon==null&&(varianceEpsilon=.001);let finalInputs=[x,mean4,variance],offsetShape=null;offset!=null&&(offsetShape=offset.shape,finalInputs.push(offset));let scaleShape=null;scale2!=null&&(scaleShape=scale2.shape,finalInputs.push(scale2));let program=env().getBool("WEBGL_PACK_NORMALIZATION")?new BatchNormPackedProgram(x.shape,mean4.shape,variance.shape,offsetShape,scaleShape,varianceEpsilon):new BatchNormProgram(x.shape,mean4.shape,variance.shape,offsetShape,scaleShape,varianceEpsilon);return backend22.runWebGLProgram(program,finalInputs,finalInputs[0].dtype)},batchNormConfig2={kernelName:FusedBatchNorm,backendName:"webgl",kernelFunc:batchNorm3},SliceProgram=class{constructor(destSize){this.variableNames=["source"],this.outputShape=destSize,this.rank=destSize.length;let dtype=getCoordsDataType(this.rank),uniformPart=`uniform int start[${this.rank}];`,sourceCoords=getCoords(this.rank),body3,coordSum=destSize.map((_,i)=>`sourceLoc.${coords[i]} = start[${i}] + coords.${coords[i]};`);body3=`
        ${dtype} sourceLoc;
        ${dtype} coords = getOutputCoords();
        ${coordSum.join(`
`)}
      `,this.userCode=`
      ${uniformPart}
      void main() {
        ${body3}
        setOutput(getSource(${sourceCoords}));
      }
    `}getCustomSetupFunc(start){if(start.length!==this.rank)throw Error(`The rank (${this.rank}) of the program must match the length of start (${start.length})`);return(gpgpu,webGLProgram)=>{this.startLoc==null&&(this.startLoc=gpgpu.getUniformLocationNoThrow(webGLProgram,"start"),this.startLoc==null)||gpgpu.gl.uniform1iv(this.startLoc,start)}}},coords=["x","y","z","w","u","v"];function getCoords(rank){if(rank===1)return"sourceLoc";if(rank<=6)return coords.slice(0,rank).map(x=>"sourceLoc."+x).join(",");throw Error(`Slicing for rank ${rank} is not yet supported`)}var SlicePackedProgram=class{constructor(destSize){this.variableNames=["source"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=destSize,this.rank=destSize.length;let dtype=getCoordsDataType(this.rank),coords2=getChannels("coords",this.rank),sourceLoc=getChannels("sourceLoc",this.rank),innerDims=this.rank===1?"sourceLoc":`vec2(${sourceLoc.slice(-2).join()})`,getChannel=`getChannel(getSource(${sourceLoc.join()}), ${innerDims})`,upperRow=`
      result.x = ${getChannel};
      if (++${coords2[this.rank-1]} < ${destSize[this.rank-1]}) {
        ++${sourceLoc[this.rank-1]};
        result.y = ${getChannel};
        --${sourceLoc[this.rank-1]};
      }
    `,lowerRow=this.rank===1?"":`
      --${coords2[this.rank-1]};
      if (++${coords2[this.rank-2]} < ${destSize[this.rank-2]}) {
        ++${sourceLoc[this.rank-2]};
        result.z = ${getChannel};
        if (++${coords2[this.rank-1]} < ${destSize[this.rank-1]}) {
          ++${sourceLoc[this.rank-1]};
          result.w = ${getChannel};
        }
      }
    `,sourceLocSetup=this.rank<=4?`sourceLoc = coords +
            ${dtype}(${destSize.map((_,i)=>`start[${i}]`).join()});`:destSize.map((_,i)=>`${sourceLoc[i]} = ${coords2[i]} + start[${i}];`).join(`
`);this.userCode=`
      uniform int start[${this.rank}];
      void main() {
        ${dtype} coords = getOutputCoords();
        ${dtype} sourceLoc;
        ${sourceLocSetup}
        vec4 result = vec4(0.);
        ${upperRow}
        ${lowerRow}
        setOutput(result);
      }
    `}getCustomSetupFunc(start){if(start.length!==this.rank)throw Error(`The rank (${this.rank}) of the program must match the length of start (${start.length})`);return(gpgpu,webGLProgram)=>{this.startLoc==null&&(this.startLoc=gpgpu.getUniformLocationNoThrow(webGLProgram,"start"),this.startLoc==null)||gpgpu.gl.uniform1iv(this.startLoc,start)}}};function shallowSlice(x,begin,size,backend22){let xTexData=backend22.texData.get(x.dataId),t=backend22.makeTensorInfo(size,x.dtype),newTexData=backend22.texData.get(t.dataId);Object.assign(newTexData,xTexData),newTexData.shape=size,newTexData.dtype=x.dtype;let flatOffset=slice_util_exports.computeFlatOffset(begin,util_exports.computeStrides(x.shape));xTexData.slice&&(flatOffset+=xTexData.slice.flatOffset),newTexData.slice={flatOffset,origDataId:xTexData.slice&&xTexData.slice.origDataId||x.dataId};let refCount=backend22.dataRefCount.get(newTexData.slice.origDataId)||1;return backend22.dataRefCount.set(newTexData.slice.origDataId,refCount+1),t}function slice3(args){let{inputs,backend:backend22,attrs}=args,{x}=inputs,{begin,size}=attrs,[$begin,$size]=slice_util_exports.parseSliceParams(x,begin,size);if(slice_util_exports.assertParamsValid(x,$begin,$size),util_exports.sizeFromShape($size)===0)return backend22.makeTensorInfo($size,x.dtype,[]);if(backend22.shouldExecuteOnCPU([x])||x.dtype==="string"){let xTexData=backend22.texData.get(x.dataId),outValues=sliceImplCPU(xTexData.values,$begin,$size,x.shape,x.dtype);return backend22.makeTensorInfo($size,x.dtype,outValues)}let{isPacked}=backend22.texData.get(x.dataId),isContinous=slice_util_exports.isSliceContinous(x.shape,$begin,$size);if(isPacked||!isContinous){let program=env().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new SlicePackedProgram($size):new SliceProgram($size),customSetup=program.getCustomSetupFunc($begin);return backend22.runWebGLProgram(program,[x],x.dtype,customSetup)}return backend22.uploadToGPU(x.dataId),shallowSlice(x,$begin,$size,backend22)}var sliceConfig2={kernelName:Slice,backendName:"webgl",kernelFunc:slice3},batchToSpaceND3=args=>{let{inputs,backend:backend22,attrs}=args,{x}=inputs,{blockShape,crops}=attrs;util_exports.assert(x.shape.length<=4,()=>"batchToSpaceND for rank > 4 with a WebGL backend not implemented yet");let prod5=blockShape.reduce((a,b)=>a*b),reshaped=backend_util_exports.getReshaped(x.shape,blockShape,prod5),permuted=backend_util_exports.getPermuted(reshaped.length,blockShape.length),reshapedPermuted=backend_util_exports.getReshapedPermuted(x.shape,blockShape,prod5),sliceBeginCoords=backend_util_exports.getSliceBeginCoords(crops,blockShape.length),sliceSize=backend_util_exports.getSliceSize(reshapedPermuted,crops,blockShape.length),toDispose=[],reshapedIntermediate=reshape3({inputs:{x},backend:backend22,attrs:{shape:reshaped}}),transposedIntermediate=transpose3({inputs:{x:reshapedIntermediate},backend:backend22,attrs:{perm:permuted}}),reshapedIntermediate2=reshape3({inputs:{x:transposedIntermediate},backend:backend22,attrs:{shape:reshapedPermuted}}),sliced=slice3({inputs:{x:reshapedIntermediate2},backend:backend22,attrs:{begin:sliceBeginCoords,size:sliceSize}});return toDispose.push(reshapedIntermediate),toDispose.push(transposedIntermediate),toDispose.push(reshapedIntermediate2),toDispose.forEach(t=>backend22.disposeIntermediateTensorInfo(t)),sliced},batchToSpaceNDConfig2={kernelName:BatchToSpaceND,backendName:"webgl",kernelFunc:batchToSpaceND3};function bincount3(args){let{inputs,backend:backend22,attrs}=args,{x,weights}=inputs,{size}=attrs,xVals=backend22.readSync(x.dataId),weightsVals=backend22.readSync(weights.dataId),outVals=bincountImplCPU(xVals,weightsVals,weights.dtype,weights.shape,size);return backend22.makeTensorInfo([size],weights.dtype,outVals)}var bincountConfig2={kernelName:Bincount,backendName:"webgl",kernelFunc:bincount3},NOT_EQUAL="return float(a != b);",notEqual3=binaryKernelFunc2({opSnippet:NOT_EQUAL,dtype:"bool"}),notEqualConfig2={kernelName:NotEqual,backendName:"webgl",kernelFunc:notEqual3};function real3(args){let{inputs,backend:backend22}=args,{input:input2}=inputs,inputData=
      uniform float minVal;
      uniform float maxVal;

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

        setOutput(clamp(value, minVal, maxVal));
      }
    `}getCustomSetupFunc(min6,max6){return(gpgpu,webGLProgram)=>{this.minLoc==null&&(this.minLoc=gpgpu.getUniformLocationNoThrow(webGLProgram,"minVal"),this.maxLoc=gpgpu.getUniformLocationNoThrow(webGLProgram,"maxVal")),gpgpu.gl.uniform1f(this.minLoc,min6),gpgpu.gl.uniform1f(this.maxLoc,max6)}}},ClipPackedProgram=class{constructor(aShape){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=aShape,this.userCode=`
      uniform float minVal;
      uniform float maxVal;

      void main() {
        vec4 value = getAAtOutCoords();

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

        setOutput(clamp(value, vec4(minVal), vec4(maxVal)));
      }
    `}getCustomSetupFunc(min6,max6){return(gpgpu,webGLProgram)=>{this.minLoc==null&&(this.minLoc=gpgpu.getUniformLocationNoThrow(webGLProgram,"minVal"),this.maxLoc=gpgpu.getUniformLocationNoThrow(webGLProgram,"maxVal")),gpgpu.gl.uniform1f(this.minLoc,min6),gpgpu.gl.uniform1f(this.maxLoc,max6)}}};function clipByValue2(args){let{inputs,backend:backend22,attrs}=args,{x}=inputs,{clipValueMin,clipValueMax}=attrs,program;env().getBool("WEBGL_PACK_CLIP")?program=new ClipPackedProgram(x.shape):program=new ClipProgram(x.shape);let customSetup=program.getCustomSetupFunc(clipValueMin,clipValueMax);return backend22.runWebGLProgram(program,[x],x.dtype,customSetup)}var clipByValueConfig={kernelName:ClipByValue,backendName:"webgl",kernelFunc:clipByValue2},ComplexAbsProgram=class{constructor(shape){this.variableNames=["real","imag"],this.outputShape=shape,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 makeComplexComponentTensorInfo(complexTensor,complexPart){return{dataId:complexPart.dataId,dtype:complexPart.dtype,shape:complexTensor.shape}}function complexAbs2(args){let{inputs,backend:backend22}=args,{x}=inputs,xData=backend22.texData.get(x.dataId),program=new ComplexAbsProgram(x.shape),programInputs=[makeComplexComponentTensorInfo(x,xData.complexTensorInfos.real),makeComplexComponentTensorInfo(x,xData.complexTensorInfos.imag)];return backend22.runWebGLProgram(program,programInputs,programInputs[0].dtype)}var complexAbsConfig2={kernelName:ComplexAbs,backendName:"webgl",kernelFunc:complexAbs2},ConcatProgram=class{constructor(shapes){this.outputShape=[],this.outputShape=backend_util_exports.computeOutShape(shapes,1),this.variableNames=shapes.map((_,i)=>`T${i}`);let offsets=new Array(shapes.length-1);offsets[0]=shapes[0][1];for(let i=1;i<offsets.length;i++)offsets[i]=offsets[i-1]+shapes[i][1];let snippets=[`if (yC < ${offsets[0]}) setOutput(getT0(yR, yC));`];for(let i=1;i<offsets.length;i++){let shift=offsets[i-1];snippets.push(`else if (yC < ${offsets[i]}) setOutput(getT${i}(yR, yC-${shift}));`)}let lastIndex=offsets.length,lastShift=offsets[offsets.length-1];snippets.push(`else setOutput(getT${lastIndex}(yR, yC-${lastShift}));`),this.userCode=`
      void main() {
        ivec2 coords = getOutputCoords();
        int yR = coords.x;
        int yC = coords.y;

        ${snippets.join(`
        `)}
      }
    `}},ConcatPackedProgram=class{constructor(shapes,axis){this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[],this.outputShape=backend_util_exports.computeOutShape(shapes,axis);let shape=this.outputShape,rank=shape.length,dtype=getCoordsDataType(rank),coords2=getChannels("coords",rank),channels=["x","y","z","w","u","v"].slice(0,rank);this.variableNames=shapes.map((_,i)=>`T${i}`);let offsets=new Array(shapes.length-1);offsets[0]=shapes[0][axis];for(let i=1;i<offsets.length;i++)offsets[i]=offsets[i-1]+shapes[i][axis];let channel=channels[axis],lastChannels=channels.slice(-2),allChannels=channels.join(),getValueSnippet=`if (${channel} < ${offsets[0]}) {
        return getChannel(
            getT0(${allChannels}), vec2(${lastChannels.join()}));
        }`;for(let i=1;i<offsets.length;i++){let shift2=offsets[i-1];getValueSnippet+=`
        if (${channel} < ${offsets[i]}  && ${channel} >= ${offsets[i-1]}) {
          return getChannel(
            getT${i}(${shiftedChannels(channels,channel,shift2)}),
            vec2(${shiftedChannels(lastChannels,channel,shift2)}));
        }`}let lastIndex=offsets.length,shift=offsets[offsets.length-1];getValueSnippet+=`
        return getChannel(
          getT${lastIndex}(${shiftedChannels(channels,channel,shift)}),
          vec2(${shiftedChannels(lastChannels,channel,shift)}));`,this.userCode=`
      float getValue(${channels.map(x=>"int "+x)}) {
        ${getValueSnippet}
      }

      void main() {
        ${dtype} coords = getOutputCoords();
        vec4 result = vec4(getValue(${coords2}), 0., 0., 0.);

        ${coords2[rank-1]} = ${coords2[rank-1]} + 1;
        if (${coords2[rank-1]} < ${shape[rank-1]}) {
          result.g = getValue(${coords2});
        }

        ${coords2[rank-2]} = ${coords2[rank-2]} + 1;
        if (${coords2[rank-2]} < ${shape[rank-2]}) {
          result.a = getValue(${coords2});
        }

        ${coords2[rank-1]} = ${coords2[rank-1]} - 1;
        if (${coords2[rank-2]} < ${shape[rank-2]} &&
            ${coords2[rank-1]} < ${shape[rank-1]}) {
          result.b = getValue(${coords2});
        }
        setOutput(result);
      }
    `}};function shiftedChannels(channels,channel,shift){let channelIdx=channels.indexOf(channel);return channels.map((c,idx)=>idx===channelIdx?`${c} - ${shift}`:c).join()}function imag3(args){let{inputs,backend:backend22}=args,{input:input2}=inputs,inputData=backend22.texData.get(input2.dataId);return identity2({inputs:{x:inputData.complexTensorInfos.imag},backend:backend22})}var imagConfig2={kernelName:Imag,backendName:"webgl",kernelFunc:imag3};function concatImpl2(inputs,axis,backend22){let dtype=inputs[0].dtype;if(dtype==="complex64"){let reals=inputs.map(t=>real3({inputs:{input:t},backend:backend22})),imags=inputs.map(t=>imag3({inputs:{input:t},backend:backend22})),realConcated=concatImpl2(reals,axis,backend22),imagConcated=concatImpl2(imags,axis,backend22),result2=complex3({inputs:{real:realConcated,imag:imagConcated},backend:backend22});return reals.forEach(r=>backend22.disposeIntermediateTensorInfo(r)),imags.forEach(i=>backend22.disposeIntermediateTensorInfo(i)),backend22.disposeIntermediateTensorInfo(realConcated),backend22.disposeIntermediateTensorInfo(imagConcated),result2}if(dtype==="string"){let{tensors2D:tensors2D2,outShape:outShape2}=computeTensors2D(inputs,axis,backend22),inputsValShapes=tensors2D2.map(t=>({vals:backend22.readSync(t.dataId),shape:t.shape})),simplyConcat=tensors2D2[0].shape[0]===1,outVals=concatImplCPU(inputsValShapes,outShape2,dtype,simplyConcat),finalOutShape=backend_util_exports.computeOutShape(inputs.map(t=>t.shape),axis),outInfo=backend22.makeTensorInfo(finalOutShape,dtype,outVals);return tensors2D2.forEach(t=>backend22.disposeIntermediateTensorInfo(t)),outInfo}if(inputs.length>env().getNumber("WEBGL_MAX_TEXTURES_IN_SHADER")){let midIndex=Math.floor(inputs.length/2),leftSide=concatImpl2(inputs.slice(0,midIndex),axis,backend22),rightSide=concatImpl2(inputs.slice(midIndex),axis,backend22),result2=concatImpl2([leftSide,rightSide],axis,backend22);return backend22.disposeIntermediateTensorInfo(leftSide),backend22.disposeIntermediateTensorInfo(rightSide),result2}if(env().getBool("WEBGL_PACK_ARRAY_OPERATIONS")&&inputs[0].shape.length>1){let program2=new ConcatPackedProgram(inputs.map(t=>t.shape),axis);return backend22.runWebGLProgram(program2,inputs,dtype)}let{tensors2D,outShape}=computeTensors2D(inputs,axis,backend22),program=new ConcatProgram(tensors2D.map(t=>t.shape)),result=backend22.runWebGLProgram(program,tensors2D,dtype);tensors2D.forEach(r=>backend22.disposeIntermediateTensorInfo(r));let reshapedResult=reshape3({inputs:{x:result},attrs:{shape:outShape},backend:backend22});return backend22.disposeIntermediateTensorInfo(result),reshapedResult}function computeTensors2D(inputs,axis,backend22){let outShape=backend_util_exports.computeOutShape(inputs.map(t=>t.shape),axis);return{tensors2D:inputs.map(x=>reshape3({inputs:{x},attrs:{shape:[-1,util_exports.sizeFromShape(x.shape.slice(axis))]},backend:backend22})),outShape}}function concat3(args){let{inputs,backend:backend22,attrs}=args,{axis}=attrs,$axis=util_exports.parseAxisParam(axis,inputs[0].shape)[0],outShape=backend_util_exports.computeOutShape(inputs.map(t=>t.shape),$axis);if(util_exports.sizeFromShape(outShape)===0)return backend22.makeTensorInfo(outShape,inputs[0].dtype,[]);let $inputs=inputs.filter(t=>util_exports.sizeFromShape(t.shape)>0);if($inputs.length===1)return identity2({inputs:{x:$inputs[0]},backend:backend22});let shapes=$inputs.map(t=>t.shape);return backend_util_exports.assertParamsConsistent(shapes,$axis),concatImpl2($inputs,$axis,backend22)}var concatConfig2={kernelName:Concat,backendName:"webgl",kernelFunc:concat3},Conv2DProgram=class{constructor(convInfo,addBias=!1,activation2=null,hasPreluActivationWeights=!1,hasLeakyreluAlpha=!1){this.variableNames=["x","W"],this.outputShape=convInfo.outShape;let padTop=convInfo.padInfo.top,padLeft=convInfo.padInfo.left,strideHeight=convInfo.strideHeight,strideWidth=convInfo.strideWidth,dilationHeight=convInfo.dilationHeight,dilationWidth=convInfo.dilationWidth,filterHeight=convInfo.filterHeight,filterWidth=convInfo.filterWidth,inputDepthNearestVec4=Math.floor(convInfo.inChannels/
          float b = getPreluActivationWeightsAtOutCoords();
          ${activation2}
        }`:hasLeakyreluAlpha?activationSnippet=`float activation(float a) {
          float b = getLeakyreluAlphaAtOutCoords();
          ${activation2}
        }`:activationSnippet=`
          float activation(float x) {
            ${activation2}
          }
        `,applyActivationSnippet="result = activation(result);");let addBiasSnippet=addBias?"result += getBiasAtOutCoords();":"";addBias&&this.variableNames.push("bias"),hasPreluActivationWeights&&this.variableNames.push("preluActivationWeights"),hasLeakyreluAlpha&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
      ${activationSnippet}

      const ivec2 strides = ivec2(${strideHeight}, ${strideWidth});
      const ivec2 pads = ivec2(${padTop}, ${padLeft});

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

        ivec2 xRCCorner =
            ivec2(coords[${rowDim}], coords[${colDim}]) * 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 < ${filterHeight}; wR++) {
          int xR = xRCorner + wR * ${dilationHeight};

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

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

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

            for (int d1 = 0; d1 < ${inputDepthNearestVec4}; 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 (${isChannelsLast}) {
                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 (${inputDepthVec4Remainder===1}) {

              if (${isChannelsLast}) {
                dotProd +=
                    getX(batch, xR, xC, ${inputDepthNearestVec4}) *
                    getW(wR, wC, ${inputDepthNearestVec4}, d2);
              } else {
                dotProd +=
                    getX(batch, ${inputDepthNearestVec4}, xR, xC) *
                    getW(wR, wC, ${inputDepthNearestVec4}, d2);
              }

            } else if (${inputDepthVec4Remainder===2}) {
              vec2 wValues = vec2(
                getW(wR, wC, ${inputDepthNearestVec4}, d2),
                getW(wR, wC, ${inputDepthNearestVec4} + 1, d2)
              );

              if (${isChannelsLast}) {
                vec2 xValues = vec2(
                  getX(batch, xR, xC, ${inputDepthNearestVec4}),
                  getX(batch, xR, xC, ${inputDepthNearestVec4} + 1)
                );
                dotProd += dot(xValues, wValues);
              } else {
                vec2 xValues = vec2(
                  getX(batch, ${inputDepthNearestVec4}, xR, xC),
                  getX(batch, ${inputDepthNearestVec4} + 1, xR, xC)
                );
                dotProd += dot(xValues, wValues);
              }

            } else if (${inputDepthVec4Remainder===3}) {
              vec3 wValues = vec3(
                getW(wR, wC, ${inputDepthNearestVec4}, d2),
                getW(wR, wC, ${inputDepthNearestVec4} + 1, d2),
                getW(wR, wC, ${inputDepthNearestVec4} + 2, d2)
              );

              if (${isChannelsLast}) {
                vec3 xValues = vec3(
                  getX(batch, xR, xC, ${inputDepthNearestVec4}),
                  getX(batch, xR, xC, ${inputDepthNearestVec4} + 1),
                  getX(batch, xR, xC, ${inputDepthNearestVec4} + 2)
                );
                dotProd += dot(xValues, wValues);
              } else {
                vec3 xValues = vec3(
                  getX(batch, ${inputDepthNearestVec4}, xR, xC),
                  getX(batch, ${inputDepthNearestVec4} + 1, xR, xC),
                  getX(batch, ${inputDepthNearestVec4} + 2, xR, xC)
                );
                dotProd += dot(xValues, wValues);
              }

            }
          }
        }

        float result = dotProd;
        ${addBiasSnippet}
        ${applyActivationSnippet}
        setOutput(result);
      }
    `}},Conv3DProgram=class{constructor(convInfo){this.variableNames=["x","W"],this.outputShape=convInfo.outShape;let padFront=convInfo.padInfo.front,padTop=convInfo.padInfo.top,padLeft=convInfo.padInfo.left,strideDepth=convInfo.strideDepth,strideHeight=convInfo.strideHeight,strideWidth=convInfo.strideWidth,dilationDepth=convInfo.dilationDepth,dilationHeight=convInfo.dilationHeight,dilationWidth=convInfo.dilationWidth,filterDepth=convInfo.filterDepth,filterHeight=convInfo.filterHeight,filterWidth=convInfo.filterWidth,inputDepthNearestVec4=Math.floor(convInfo.inChannels/4)*4,inputDepthVec4Remainder=convInfo.inChannels%4;this.userCode=`
      const ivec3 strides = ivec3(${strideDepth}, ${strideHeight}, ${strideWidth});
      const ivec3 pads = ivec3(${padFront}, ${padTop}, ${padLeft});

      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 < ${filterDepth}; wF++) {
          int xF = xFCorner + wF * ${dilationDepth};

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

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

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

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

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

              for (int d1 = 0; d1 < ${inputDepthNearestVec4}; 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 (${inputDepthVec4Remainder===1}) {
                dotProd +=
                  getX(batch, xF, xR, xC, ${inputDepthNearestVec4}) *
                  getW(wF, wR, wC, ${inputDepthNearestVec4}, d2);
              } else if (${inputDepthVec4Remainder===2}) {
                vec2 xValues = vec2(
                  getX(batch, xF, xR, xC, ${inputDepthNearestVec4}),
                  getX(batch, xF, xR, xC, ${inputDepthNearestVec4} + 1)
                );
                vec2 wValues = vec2(
                  getW(wF, wR, wC, ${inputDepthNearestVec4}, d2),
                  getW(wF, wR, wC, ${inputDepthNearestVec4} + 1, d2)
                );
                dotProd += dot(xValues, wValues);
              } else if (${inputDepthVec4Remainder===3}) {
                vec3 xValues = vec3(
                  getX(batch, xF, xR, xC, ${inputDepthNearestVec4}),
                  getX(batch, xF, xR, xC, ${inputDepthNearestVec4} + 1),
                  getX(batch, xF, xR, xC, ${inputDepthNearestVec4} + 2)
                );
                vec3 wValues = vec3(
                  getW(wF, wR, wC, ${inputDepthNearestVec4}, d2),
                  getW(wF, wR, wC, ${inputDepthNearestVec4} + 1, d2),
                  getW(wF, wR, wC, ${inputDepthNearestVec4} + 2, d2)
                );
                dotProd += dot(xValues, wValues);
              }
            }
          }
        }
        setOutput(dotProd);
      }
    `}},Im2ColPackedProgram=class{constructor(outputShape,inputShape,convInfo){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=outputShape;let{filterWidth,inChannels,strideWidth,strideHeight,padInfo,outWidth,dilationWidth,dilationHeight,dataFormat}=convInfo,{left,top}=padInfo,itemsPerBlockRow=inChannels*filterWidth,glsl=getGlslDifferences(),isChannelsLast=dataFormat==="channelsLast",rowDim=isChannelsLast?0:1,colDim=isChannelsLast?1:2,unrolled="";for(let row=0;row<=1;row++)for(let col=0;col<=1;col++)unrolled+=`
          blockIndex = rc.y + ${col};
          pos = rc.x + ${row};

          if(blockIndex < ${outputShape[1]} && pos < ${outputShape[0]}) {
            offsetY = int(blockIndex / (${outWidth})) * ${strideHeight} - ${top};
            d0 = offsetY + ${dilationHeight} * (pos / ${itemsPerBlockRow});

            if(d0 < ${inputShape[rowDim]} && d0 >= 0) {

              offsetX = int(mod(float(blockIndex), ${outWidth}.) * ${strideWidth}. - ${left}.);
              d1 = offsetX + ${dilationWidth} * (int(mod(float(pos), ${itemsPerBlockRow}.) / ${inChannels}.));

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

                ch = int(mod(float(pos), ${inChannels}.));

                if (${isChannelsLast}) {
                  innerDims = vec2(d1, ch);
                  result[${row*2+col}] = getChannel(
                    getA(d0, int(innerDims.x),
                    int(innerDims.y)), innerDims);
                } else {
                  innerDims = vec2(d0, d1);
                  result[${row*2+col}] = 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;

        ${unrolled}

        ${glsl.output} = result;
      }
    `}};function conv2dByMatMul({x,filter,convInfo,backend:backend22,bias=null,preluActivationWeights=null,leakyreluAlpha=0,activation:activation2=null}){let xShape=x.shape,xTexData=backend22.texData.get(x.dataId),sharedMatMulDim=convInfo.inChannels,outerShapeX=xShape[0]*xShape[1]*xShape[2],outerShapeFilter=convInfo.outChannels,isChannelsLast=convInfo.dataFormat==="channelsLast",transposeA=!1,transposeB=!1,out,intermediates=[],batchMatMulWillBeUnpacked=(outerShapeX===1||outerShapeFilter===1)&&sharedMatMulDim>MATMUL_SHARED_DIM_THRESHOLD,reshapeWillBeExpensive=xShape[2]%2!=0&&!!xTexData.isPacked;if(batchMatMulWillBeUnpacked||!env().getBool("WEBGL_LAZILY_UNPACK")||!env().getBool("WEBGL_PACK_BINARY_OPERATIONS")||!reshapeWillBeExpensive){let targetShape=isChannelsLast?xShape[0]*xShape[1]*xShape[2]:xShape[0]*xShape[2]*xShape[3],xReshaped=reshape3({inputs:{x},backend:backend22,attrs:{shape:[1,targetShape,convInfo.inChannels]}}),filterReshaped=reshape3({inputs:{x:filter},backend:backend22,attrs:{shape:[1,convInfo.inChannels,convInfo.outChannels]}}),result=batchMatMulImpl({a:xReshaped,b:filterReshaped,transposeA,transposeB,backend:backend22,bias,activation:activation2,preluActivationWeights,leakyreluAlpha});out=reshape3({inputs:{x:result},backend:backend22,attrs:{shape:convInfo.outShape}}),intermediates.push(xReshaped),intermediates.push(filterReshaped),intermediates.push(result)}else{let targetShape=isChannelsLast?xShape[0]*xShape[1]*(xShape[2]+1):xShape[0]*xShape[2]*(xShape[3]+1),xReshaped={dataId:x.dataId,shape:[1,targetShape,convInfo.inChannels],dtype:x.dtype},originalXTexDataShape=xTexData.shape;xTexData.shape=xTexData.shape.slice(),xTexData.shape[xTexData.shape.length-2]++,util_exports.assert(isReshapeFree(xTexData.shape,xReshaped.shape),()=>`packed reshape ${xTexData.shape} to ${xReshaped.shape} isn't free`);let filterReshaped=reshape3({inputs:{x:filter},backend:backend22,attrs:{shape:[1,convInfo.inChannels,convInfo.outChannels]}});intermediates.push(filterReshaped);let pointwiseConv=batchMatMulImpl({a:xReshaped,b:filterReshaped,backend:backend22,transposeA,transposeB,bias,activation:activation2,preluActivationWeights,leakyreluAlpha}),pointwiseConvTexData=backend22.texData.get(pointwiseConv.dataId);util_exports.assert(pointwiseConvTexData.isPacked,()=>"batchMatMul result is expected to be packed"),xTexData.shape=originalXTexDataShape,pointwiseConvTexData.shape=convInfo.outShape,out=identity2({inputs:{x:pointwiseConv},backend:backend22}),out.shape=convInfo.outShape,intermediates.push(pointwiseConv)}for(let i of intermediates)backend22.disposeIntermediateTensorInfo(i);return out}function conv2dWithIm2Row({x,filter,convInfo,backend:backend22,bias=null,preluActivationWeights=null,leakyreluAlpha=0,activation:activation2=null}){let{filterWidth,filterHeight,inChannels,outWidth,outHeight,dataFormat}=convInfo,isChannelsLast=dataFormat==="channelsLast",sharedDim=filterWidth*filterHeight*inChannels,numCols=outHeight*outWidth,x2ColShape=[sharedDim,numCols],transposeA=!0,transposeB=!1,intermediates=[],xSqueezed=reshape3({inputs:{x},backend:backend22,attrs:{shape:x.shape.slice(1)}}),w2Row=reshape3({inputs:{x:filter},backend:backend22,attrs:{shape:[1,sharedDim,util_exports.sizeFromShape(filter.shape)/sharedDim]}});intermediates.push(xSqueezed),intermediates.push(w2Row);let im2ColProgram=new Im2ColPackedProgram(x2ColShape,xSqueezed.shape,convInfo),im2Col=backend22.runWebGLProgram(im2ColProgram,[xSqueezed],"float32"),im2ColReshaped=reshape3({inputs:{x:im2Col},backend:backend22,attrs:{shape:[1,x2ColShape[0],x2ColShape[1]]}});intermediates.push(im2Col),intermediates.push(im2ColReshaped);let hasBias=bias!=null,hasPreluActivationWeights=preluActivationWeights!=null,hasLeakyreluAlpha=activation2==="leakyrelu",fusedActivation=activation2?mapActivationToShaderProgram(activation2,!0):null,matmulProgram=new MatMulPackedProgram(im2ColReshaped.shape,w2Row.shape,[1,numCols,convInfo.outChannels],transposeA,transposeB,hasBias,fusedActivation,hasPreluActivationWeights,hasLeakyreluAlpha),inputs=[im2ColReshaped,w2Row];if(bias&&inputs.push(bias),hasPreluAc
      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 < ${convInfo.batchSize}; b++) {
          for (int yR = 0; yR < ${convInfo.outHeight}; yR++) {
            int xR = wR + yR * ${strideHeight} - ${padTop};

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

            for (int yC = 0; yC < ${convInfo.outWidth}; yC++) {
              int xC = wC + yC * ${strideWidth} - ${padLeft};

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

              if (${isChannelsLast}) {
                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);
      }
    `}},Conv2DDerInputProgram=class{constructor(convInfo){this.variableNames=["dy","W"],this.outputShape=convInfo.inShape;let filterHeight=convInfo.filterHeight,filterWidth=convInfo.filterWidth,strideHeight=convInfo.strideHeight,strideWidth=convInfo.strideWidth,isChannelsLast=convInfo.dataFormat==="channelsLast",padTop=filterHeight-1-convInfo.padInfo.top,padLeft=filterWidth-1-convInfo.padInfo.left,rowDim=isChannelsLast?1:2,colDim=isChannelsLast?2:3,channelDim=isChannelsLast?3:1;this.userCode=`
      const ivec2 pads = ivec2(${padTop}, ${padLeft});

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

        ivec2 dyCorner = ivec2(coords[${rowDim}], coords[${colDim}]) - 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 < ${filterHeight}; wR++) {
          float dyR = float(dyRCorner + wR) / ${strideHeight}.0;

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

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

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

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

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

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

              if (${isChannelsLast}) {
                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);
      }
    `}},Conv3DDerFilterProgram=class{constructor(convInfo){this.variableNames=["x","dy"],this.outputShape=convInfo.filterShape;let strideDepth=convInfo.strideDepth,strideHeight=convInfo.strideHeight,strideWidth=convInfo.strideWidth,padFront=convInfo.padInfo.front,padTop=convInfo.padInfo.top,padLeft=convInfo.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 < ${convInfo.batchSize}; b++) {
          for (int yF = 0; yF < ${convInfo.outDepth}; yF++) {
            int xF = wF + yF * ${strideDepth} - ${padFront};

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

            for (int yR = 0; yR < ${convInfo.outHeight}; yR++) {
              int xR = wR + yR * ${strideHeight} - ${padTop};

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

              for (int yC = 0; yC < ${convInfo.outWidth}; yC++) {
                int xC = wC + yC * ${strideWidth} - ${padLeft};

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

                float dyValue = getDy(b, yF, yR, yC, d2);
                float xValue = getX(b, xF, xR, xC, d1);
                dotProd += (xValue * dyValue);
              }
            }
          }
        }
        setOutput(dotProd);
      }
    `}},Conv3DDerInputProgram=class{constructor(convInfo){this.variableNames=["dy","W"],this.outputShape=convInfo.inShape;let filterDepth=convInfo.filterDepth,filterHeight=convInfo.filterHeight,filterWidth=convInfo.filterWidth,strideDepth=convInfo.strideDepth,strideHeight=convInfo.strideHeight,strideWidth=convInfo.strideWidth,padFront=filterDepth-1-convInfo.padInfo.front,padTop=filterHeight-1-convInfo.padInfo.top,padLeft=filterWidth-1-convInfo.padInfo.left;this.userCode=`
      const ivec3 pads = ivec3(${padFront}, ${padTop}, ${padLeft});

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

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

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

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

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

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

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

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

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

              for (int d2 = 0; d2 < ${convInfo.outChannels}; d2++) {
                float xValue = getDy(batch, idyF, idyR, idyC, d2);
                float wValue = getW(wFPerm, wRPerm, wCPerm, d1, d2);
                dotProd += xValue * wValue;
              }
            }
          }
        }
        setOutput(dotProd);
      }
    `}};function conv2DBackpropFilter3(args){let{inputs,backend:backend22,attrs}=args,{x,dy}=inputs,{strides,pad:pad3,dataFormat,dimRoundingMode,filterShape}=attrs,$dataFormat=backend_util_exports.convertConv2DDataFormat(dataFormat),convInfo=backend_util_exports.computeConv2DInfo(x.shape,filterShape,strides,1,pad3,dimRoundingMode,!1,$dataFormat),program=new Conv2DDerFilterProgram(convInfo);return backend22.runWebGLProgram(program,[x,dy],"float32")}var conv2DBackpropFilterConfig2={kernelName:Conv2DBackpropFilter,backendName:"webgl",kernelFunc:conv2DBackpropFilter3};function conv2DBackpropInput3(args){let{inputs,backend:backend22,attrs}=args,{dy,filter}=inputs,{inputShape,strides,pad:pad3,dataFormat,dimRoundingMode}=attrs,$dataFormat=backend_util_exports.convertConv2DDataFormat(dataFormat),convInfo=backend_util_exports.computeConv2DInfo(inputShape,filter.shape,strides,1,pad3,dimRoundingMode,!1,$dataFormat),program=new Conv2DDerInputProgram(convInfo);return backend22.runWebGLProgram(program,[dy,filter],"float32")}var conv2DBackpropInputConfig2={kernelName:Conv2DBackpropInput,backendName:"webgl",kernelFunc:conv2DBackpropInput3};function conv3D2(args){let{inputs,backend:backend22,attrs}=args,{x,filter}=inputs,{strides,pad:pad3,dilations}=attrs,convInfo=backend_util_exports.computeConv3DInfo(x.shape,filter.shape,strides,dilations,pad3),program=new Conv3DProgram(convInfo);return backend22.runWebGLProgram(program,[x,filter],"float32")}var conv3DConfig2={kernelName:Conv3D,backendName:"webgl",kernelFunc:conv3D2};function conv3DBackpropFilterV22(args){let{inputs,backend:backend22,attrs}=args,{x,dy}=inputs,{strides,pad:pad3,filterShape}=attrs,convInfo=backend_util_exports.computeConv3DInfo(x.shape,filterShape,strides,1,pad3),program=new Conv3DDerFilterProgram(convInfo);return backend22.runWebGLProgram(program,[x,dy],"float32")}var conv3DBackpropFilterV2Config2={kernelName:Conv3DBackpropFilterV2,backendName:"webgl",kernelFunc:conv3DBackpropFilterV22};function conv3DBackpropInput2(args){let{inputs,backend:backend22,attrs}=args,{dy,filter}=inputs,{pad:pad3,strides,inputShape}=attrs,convInfo=backend_util_exports.computeConv3DInfo(inputShape,filter.shape,strides,1,pad3),program=new Conv3DDerInputProgram(convInfo);return backend22.runWebGLProgram(program,[dy,filter],"float32")}var conv3DBackpropInputConfig={kernelName:Conv3DBackpropInputV2,backendName:"webgl",kernelFunc:conv3DBackpropInput2},COS=CHECK_NAN_SNIPPET_UNARY+`
  return cos(x);
`,cos3=unaryKernelFunc2({opSnippet:COS}),cosConfig2={kernelName:Cos,backendName:"webgl",kernelFunc:cos3},COSH=`
  float e2x = exp(-x);
  return (e2x + 1.0 / e2x) / 2.0;
`,cosh3=unaryKernelFunc2({opSnippet:COSH}),coshConfig2={kernelName:Cosh,backendName:"webgl",kernelFunc:cosh3},CropAndResizeProgram=class{constructor(imageShape,boxShape,cropSize,method,extrapolationValue){this.variableNames=["Image","Boxes","BoxInd"],this.outputShape=[];let[batch,imageHeight,imageWidth,depth]=imageShape,[numBoxes]=boxShape,[cropHeight,cropWidth]=cropSize;this.outputShape=[numBoxes,cropHeight,cropWidth,depth];let methodId=method==="bilinear"?1:0,[inputHeightFloat,inputWidthFloat]=[`${imageHeight-1}.0`,`${imageWidth-1}.0`],[heightRatio,heightScale,inY]=cropHeight>1?[`${(imageHeight-1)/(cropHeight-1)}`,"(y2-y1) * height_ratio",`y1*${inputHeightFloat} + float(y)*(height_scale)`]:["0.0","0.0",`0.5 * (y1+y2) * ${inputHeightFloat}`],[widthRatio,widthScale,inX]=cropWidth>1?[`${(imageWidth-1)/(cropWidth-1)}`,"(x2-x1) * width_ratio",`x1*${inputWidthFloat} + float(x)*(width_scale)`]:["0.0","0.0",`0.5 * (x1+x2) * ${inputWidthFloat}`];this.userCode=`
      const float height_ratio = float(${heightRatio});
      const float width_ratio = float(${widthRatio});
      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 >= ${batch}) {
          return;
        }

        float height_scale = ${heightScale};
        float width_scale = ${widthScale};

        float in_y = ${inY};
        if( in_y < 0.0 || in_y > ${inputHeightFloat} ) {
          setOutput(float(${extrapolationValue}));
          return;
        }
        float in_x = ${inX};
        if( in_x < 0.0 || in_x > ${inputWidthFloat} ) {
          setOutput(float(${extrapolationValue}));
          return;
        }

        vec2 sourceFracIndexCR = vec2(in_x,in_y);
        if(${methodId} == 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);
        }
      }
    `}},cropAndResize3=args=>{let{inputs,backend:backend22,attrs}=args,{image:image3,boxes,boxInd}=inputs,{cropSize,method,extrapolationValue}=attrs,program=new CropAndResizeProgram(image3.shape,boxes.shape,cropSize,method,extrapolationValue);return backend22.runWebGLProgram(program,[image3,boxes,boxInd],"float32")},cropAndResizeConfig2={kernelName:CropAndResize,backendName:"webgl",kernelFunc:cropAndResize3},CumSumProgram=class{constructor(shape,exclusive,reverse5){this.variableNames=["x"],this.outputShape=shape;let rank=shape.length,val=exclusive?"0.0":`getX(${getCoords2(rank,"coords")})`,length=shape[shape.length-1],condition="",idxString="";exclusive?(condition=reverse5?`end != ${length-1}`:"end != 0",idxString=reverse5?"end + 1":"end - 1"):(condition=reverse5?`end + pow2 < ${length}`:"end >= pow2",idxString=reverse5?"end + pow2":"end - pow2"),this.userCode=`
      uniform float index;
      void main() {
        ${getCoordsDataType(rank)} coords = getOutputCoords();
        int end = ${getFinalCoord(rank,"coords")};
        float val = ${val};
        int pow2 = int(pow(2.0, index));
        if (${condition}) {
          int idx = ${idxString};
          ${getFinalCoord(rank,"coords")} = idx;
          val += getX(${getCoords2(rank,"coords")});
        }
        setOutput(val);
      }
    `}getCustomSetupFunc(index){return(gpgpu,webGLProgram)=>{this.index==null&&(this.index=gpgpu.getUniformLocation(webGLProgram,"index")),gpgpu.gl.uniform1f(this.index,index)}}};function getCoords2(rank,name){if(rank===1)return`${name}`;if(rank===2)return`${name}.x, ${name}.y`;if(rank===3)return`${name}.x, ${name}.y, ${name}.z`;if(rank===4)return`${name}.x, ${name}.y, ${name}.z, ${name}.w`;throw Error(`Cumulative sum for rank ${rank} is not yet supported`)}function getFinalCoord(rank,name){if(rank===1)return`${name}`;if(rank===2)return`${name}.y`;if(rank===3)return`${name}.z`;if(rank===4)return`${name}.w`;throw Error(`Cumulative sum for rank ${rank} is not yet supported`)}function cumsum3(args){let{inputs,backend:backend22,attrs}=args,{x}=inputs,{axis,exclusive,reverse:reverse5}=attrs,xRank=x.shape.length,permutation=backend_util_exports.getAxesPermutation([axis],xRank),permutedX=x;permutation!=null&&(permutedX=transpose3({inputs:{x},backend:backend22,attrs:{perm:permutation}}));let permutedAxis=backend_util_exports.getInnerMostAxes(1,xRank)[0];if(permutedAxis!==xRank-1)throw new Error(`WebGL cumsum shader expects an inner-most axis=${x.shape.length-1} but got axis=${axis}`);let size=x.shape[permutedAxis],result=identity2({inputs:{x:permutedX},backend:backend22});for(let i=0;i<=Math.ceil(Math.log2(size))-1;i++){let program=new CumSumProgram(permutedX.shape,!1,reverse5),customSetup=program.getCustomSetupFunc(i),prevResult=result;result=backend22.runWebGLProgram(program,[result],result.dtype,customSetup),backend22.disposeIntermediateTensorInfo(prevResult)}if(exclusive){let program=new CumSumProgram(permutedX.shape,exclusive,reverse5),prevResult=result;result=backend22.runWebGLProgram(program,[result],result.dtype),backend22.disposeIntermediateTensorInfo(prevResult)}if(permutation!=null){let reversePermutation=backend_util_exports.getUndoAxesPermutation(permutation),reverseTransposedResult=transpose3({inputs:{x:result},backend:backend22,attrs:{perm:reversePermutation}});return backend22.disposeIntermediateTensorInfo(result),backend22.disposeIntermediateTensorInfo(permutedX),reverseTransposedResult}return result}var cumsumConfig2={kernelName:Cumsum,backendName:"webgl",kernelFunc:cumsum3};function denseBincount3(args){let{inputs,backend:backend22,attrs}=args,{x,weights}=inputs,{size,binaryOutput}=attrs;if(x.shape.length===1){let xVals=backend22.readSync(x.dataId),weightsVals=backend22.readSync(weights.dataId),outVals=bincountImplCPU(xVals,weightsVals,weights.dtype,weights.shape,size);return backend22.makeTensorInfo([size],weights.dtype,outVals)}else if(x.shape.length===2){let xBuf=backend22.bufferSync(x),weightsBuf=backend22.bufferSync(weights),outBuf=bincountReduceImplCPU(xBuf,weightsBuf,size,binaryOutput);return backend22.makeTensorInfo(outBuf.shape,weights.dtype,outBuf.values)}throw new Error(`Error in denseBincount: input must be at most rank 2, but got rank${x.shape.length}.`)}var denseBincountConfig2={kernelName:DenseBincount,backendName:"webgl",kernelFunc:denseBincount3},DepthToSpaceProgram=class{constructor(outputShape,blockSize,dataFormat){this.variableNames=["x"],this.outputShape=[],this.outputShape=outputShape,this.blockSize=blockSize,this.dataFormat=dataFormat,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 / ${blockSize};
      int offset_h = imod(h, ${blockSize});
      int in_w = w / ${blockSize};
      int offset_w = imod(w, ${blockSize});
      int offset_d = (offset_h * ${blockSize} + 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 depthToSpace3(args){let{inputs,backend:backend22,attrs}=args,{x}=inputs,{blockSize,dataFormat}=attrs;util_exports.assert(blockSize>1,()=>`blockSize should be > 1 for depthToSpace, but was: ${blockSize}`);let batchSize=x.shape[0],inputHeight=dataFormat==="NHWC"?x.shape[1]:x.shape[2],inputWidth=dataFormat==="NHWC"?x.shape[2]:x.shape[3],inputDepth=dataFormat==="NHWC"?x.shape[3]:x.shape[1],outputHeight=inputHeight*blockSize,outputWidth=inputWidth*blockSize,outputDepth=inputDepth/(blockSize*blockSize),outputShape=dataFormat==="NHWC"?[batchSize,outputHeight,outputWidth,outputDepth]:[batchSize,outputDepth,outputHeight,outputWidth],program=new DepthToSpaceProgram(outputShape,blockSize,dataFormat);return backend22.runWebGLProgram(program,[x],x.dtype)}var depthToSpaceConfig2={kernelName:DepthToSpace,backendName:"webgl",kernelFunc:depthToSpace3},DepthwiseConv2DProgram=class{constructor(convInfo,addBias=!1,activation2=null,hasPreluActivation=!1,hasLeakyReluAlpha=!1){this.variableNames=["x","W"],this.outputShape=convInfo.outShape;let xNumRows=convInfo.inHeight,xNumCols=convInfo.inWidth,padTop=convInfo.padInfo.top,padLeft=convInfo.padInfo.left,strideHeight=convInfo.strideHeight,strideWidth=convInfo.strideWidth,dilationHeight=convInfo.dilationHeight,dilationWidth=convInfo.dilationWidth,filterHeight=convInfo.filterHeight,filterWidth=convInfo.filterWidth,channelMul=convInfo.outChannels/convInfo.inChannels,activationSnippet="",applyActivationSnippet="";activation2&&(hasPreluActivation?activationSnippet=`float activation(float a) {
          float b = getPreluActivationWeightsAtOutCoords();
          ${activation2}
        }`:hasLeakyReluAlpha?activationSnippet=`float activation(float a) {
          float b = getLeakyreluAlphaAtOutCoords();
          ${activation2}
        }`:activationSnippet=`
          float activation(float x) {
            ${activation2}
          }
        `,applyActivationSnippet="result = activation(result);");let addBiasSnippet=addBias?"result += getBiasAtOutCoords();":"";addBias&&this.variableNames.push("bias"),hasPreluActivation&&this.variableNames.push("preluActivationWeights"),hasLeakyReluAlpha&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
      ${activationSnippet}

      const ivec2 strides = ivec2(${strideHeight}, ${strideWidth});
      const ivec2 pads = ivec2(${padTop}, ${padLeft});

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

        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 < ${filterHeight}; wR++) {
          int xR = xRCorner + wR * ${dilationHeight};

          if (xR < 0 || xR >= ${xNumRows}) {
            continue;
          }

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

            if (xC < 0 || xC >= ${xNumCols}) {
              continue;
            }

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

        float result = dotProd;
        ${addBiasSnippet}
        ${applyActivationSnippet}
        setOutput(result);
      }
    `}},DepthwiseConvPacked2DProgram=class{constructor(convInfo,addBias=!1,activation2=null,hasPreluActivation=!1,hasLeakyReluAlpha=!1){this.variableNames=["x","W"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=convInfo.outShape;let xNumRows=convInfo.inHeight,xNumCols=convInfo.inWidth,padTop=convInfo.padInfo.top,padLeft=convInfo.padInfo.left,strideHeight=convInfo.strideHeight,strideWidth=convInfo.strideWidth,dilationHeight=convInfo.dilationHeight,dilationWidth=convInfo.dilationWidth,filterHeight=convInfo.filterHeight,filterWidth=convInfo.filterWidth,texelsAcross=filterWidth,mainLoop="int xR; int xC; int xCOffset;";for(let r=0;r<filterHeight;r++)for(let c=0;c<filterWidth;c++)mainLoop+=`
          vec4 xTexelR${r}C${c*2} = vec4(0.);
          vec4 wR${r}C${c} = vec4(0.);
          vec4 xR${r}C${c} = vec4(0.);`;for(let r=0;r<filterHeight;r++)for(let texelC=0;texelC<texelsAcross;texelC++){let c=texelC*2;if(mainLoop+=`
          xR = xRCorner + ${r*dilationHeight};
          xC = xCCorner + ${c*dilationWidth};
        `,strideWidth===1){if(c<filterWidth&&(padLeft%2==1?mainLoop+=`
                xCOffset = xC + 1;
                if(xR >= 0 && xR < ${xNumRows} && xCOffset >= 0 && xCOffset < ${xNumCols}) {
                  xTexelR${r}C${c} = getX(batch, xR, xCOffset, d1);

                  // Need to manually clear unused channels in case
                  // we're reading from recycled texture.
                  if(xCOffset + 1 >= ${xNumCols}) {
                    xTexelR${r}C${c}.zw = vec2(0.);
                  }
                } else {
                  xTexelR${r}C${c} = vec4(0.);
                }

                xCOffset = xC + 1 - 2;
                if(xR >= 0 && xR < ${xNumRows} && xCOffset >= 0 && xCOffset < ${xNumCols}) {
                  vec4 previous = getX(batch, xR, xCOffset, d1);

                  // Need to manually clear unused channels in case
                  // we're reading from recycled texture.
                  if(xCOffset + 1 >= ${xNumCols}) {
                    previous.zw = vec2(0.);
                  }

                  xR${r}C${c} = vec4(previous.zw, xTexelR${r}C${c}.xy);
                } else {
                  xR${r}C${c} = vec4(0, 0, xTexelR${r}C${c}.xy);
                }
              `:mainLoop+=`
                if(xR >= 0 && xR < ${xNumRows} && xC >= 0 && xC < ${xNumCols}) {
                  xTexelR${r}C${c} = getX(batch, xR, xC, d1);
                } else {
                  xTexelR${r}C${c} = vec4(0.);
                }

                xR${r}C${c} = xTexelR${r}C${c};
              `,c+1<filterWidth)){let nextTexelOffset=padLeft%2==0?util_exports.nearestLargerEven(dilationWidth):dilationWidth;dilationWidth%2==0&&padLeft%2==1||dilationWidth%2!=0&&padLeft%2!=1?(mainLoop+=`
                  xCOffset = xC + ${padLeft%2} + ${nextTexelOffset};

                  if(xR >= 0 && xR < ${xNumRows} &&
                    xCOffset >= 0 && xCOffset < ${xNumCols}) {
                    xTexelR${r}C${c+2} = getX(batch, xR, xCOffset, d1);
                  }
                `,dilationWidth>1&&(mainLoop+=`
                    xCOffset -= 2;
                    if(xR >= 0 && xR < ${xNumRows} &&
                      xCOffset >= 0 && xCOffset < ${xNumCols}) {
                      xTexelR${r}C${c} = getX(batch, xR, xCOffset, d1);
                    } else {
                      xTexelR${r}C${c} = vec4(0.);
                    }
                  `),mainLoop+=`
                  xR${r}C${c+1} = vec4(
                    xTexelR${r}C${c}.zw, xTexelR${r}C${c+2}.xy);
                `):mainLoop+=`
                  xCOffset = xC + ${nextTexelOffset};

                  if(xR >= 0 && xR < ${xNumRows} &&
                    xCOffset >= 0 && xCOffset < ${xNumCols}) {
                    xTexelR${r}C${c+2} = getX(batch, xR, xCOffset, d1);
                  }

                  xR${r}C${c+1} = xTexelR${r}C${c+2};
                `}}else c<filterWidth&&(mainLoop+=`
              if(xR >= 0 && xR < ${xNumRows}) {
            `,padLeft%2==1?(mainLoop+=`
                xCOffset = xC + 1 - ${strideWidth};
                if(xCOffset >= 0 && xCOffset < ${xNumCols}) {
                  xTexelR${r}C${c} = getX(batch, xR, xCOffset, d1);
                } else {
                  xTexelR${r}C${c} = vec4(0.);
                }

                if(xC + 1 >= 0 && xC + 1 < ${xNumCols}) {
                  xTexelR${r}C${c+2} = getX(batch, xR, xC + 1, d1);
                } else {
                  xTexelR${r}C${c+2} = vec4(0.);
                }

                xR${r}C${c} = vec4(
                  xTexelR${r}C${c}.zw, xTexelR${r}C${c+2}.zw);
              `,c+1<filterWidth&&(mainLoop+=`
                  vec4 final = vec4(0.);
                  xCOffset = xC + 1 + ${strideWidth};
                  if(xCOffset >= 0 && xCOffset < ${xNumCols}) {
                    final = getX(batch, xR, xCOffset, d1);
                  }
                  xR${r}C${c+1} = vec4(xTexelR${r}C${c+2}.xy, final.xy);
                `)):(mainLoop+=`
                if(xC >= 0 && xC < ${xNumCols}) {
                  xTexelR${r}C${c} = getX(batch, xR, xC, d1);
                } else {
                  xTexelR${r}C${c} = vec4(0.);
                }

                xCOffset = xC + ${strideWidth};
                if(xCOffset >= 0 && xCOffset < ${xNumCols}) {
                  xTexelR${r}C${c+2} = getX(batch, xR, xCOffset, d1);
                } else {
                  xTexelR${r}C${c+2} = vec4(0.);
                }

                xR${r}C${c} = vec4(
                  xTexelR${r}C${c}.xy, xTexelR${r}C${c+2}.xy);
              `,c+1<filterWidth&&(mainLoop+=`
                  xR${r}C${c+1} = vec4(
                    xTexelR${r}C${c}.zw, xTexelR${r}C${c+2}.zw);
                `)),mainLoop+="}");c<filterWidth&&(mainLoop+=`
            vec4 wTexelR${r}C${c} = getW(${r}, ${c}, d1, q);
            wR${r}C${c} = vec4(wTexelR${r}C${c}.xz, wTexelR${r}C${c}.xz);
          `,c+1<filterWidth&&(mainLoop+=`
              vec4 wTexelR${r}C${c+1} = getW(${r}, ${c+1}, d1, q);
              wR${r}C${c+1} =
                vec4(wTexelR${r}C${c+1}.xz, wTexelR${r}C${c+1}.xz);`))}for(let r=0;r<filterHeight;r++)for(let c=0;c<filterWidth;c++)mainLoop+=`dotProd += xR${r}C${c} * wR${r}C${c};`;let activationSnippet="",applyActivationSnippet="";activation2&&(hasPreluActivation?activationSnippet=`vec4 activation(vec4 a) {
          vec4 b = getPreluActivationWeightsAtOutCoords();
          ${activation2}
        }`:hasLeakyReluAlpha?activationSnippet=`vec4 activation(vec4 a) {
          vec4 b = getLeakyreluAlphaAtOutCoords();
          ${activation2}
        }`:activationSnippet=`vec4 activation(vec4 x) {
          ${activation2}
        }`,applyActivationSnippet="result = activation(result);");let addBiasSnippet=addBias?"result += getBiasAtOutCoords();":"";addBias&&this.variableNames.push("bias"),hasPreluActivation&&this.variableNames.push("preluActivationWeights"),hasLeakyReluAlpha&&this.variableNames.push("leakyreluAlpha"),this.userCode=`
      ${activationSnippet}

      const ivec2 strides = ivec2(${strideHeight}, ${strideWidth});
      const ivec2 pads = ivec2(${padTop}, ${padLeft});

      void main() {

        ivec4 coords = getOutputCoords();
        int batch = coords.x;
        ivec2 xRCCorner = coords.yz * strides - pads;
        int d2 = coords.w;
        int d1 = d2;
        int q = 0;
        int xRCorner = xRCCorner.x;
        int xCCorner = xRCCorner.y;

        vec4 dotProd = vec4(0.);

        ${mainLoop}

        vec4 result = dotProd;
        ${addBiasSnippet}
        ${applyActivationSnippet}
        setOutput(result);
      }
    `}};function depthwiseConv2dNative2(args){let{inputs,backend:backend22,attrs}=args,{x,filter}=inputs,{strides,pad:pad3,dilations,dimRoundingMode}=attrs,$dilations=dilations;$dilations==null&&($dilations=[1,1]),util_exports.assert(backend_util_exports.eitherStridesOrDilationsAreOne(strides,$dilations),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${strides} and dilations '${$dilations}'`);let convInfo=backend_util_exports.computeConv2DInfo(x.shape,filter.shape,strides,$dilations,pad3,dimRoundingMode,!0),program;return env().getBool("WEBGL_PACK_DEPTHWISECONV")&&convInfo.strideWidth<=2&&convInfo.outChannels/convInfo.inChannels==1?program=new DepthwiseConvPacked2DProgram(convInfo):program=new DepthwiseConv2DProgram(convInfo),backend22.runWebGLProgram(program,[x,filter],"float32")}var depthwiseConv2dNativeConfig2={kernelName:DepthwiseConv2dNative,backendName:"webgl",kernelFunc:depthwiseConv2dNative2},DepthwiseConv2DDerFilterProgram=class{constructor(convInfo){this.variableNames=["x","dy"],this.outputShape=convInfo.filterShape;let strideHeight=convInfo.strideHeight,strideWidth=convInfo.strideWidth,padTop=convInfo.padInfo.top,padLeft=convInfo.padInfo.left,channelMul=convInfo.outChannels/convInfo.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 * ${channelMul} + dm;

        float dotProd = 0.0;

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

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

            for (int yC = 0; yC < ${convInfo.outWidth}; yC++) {
              int xC = wC + yC * ${strideWidth} - ${padLeft};

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

              float dyValue = getDy(b, yR, yC, d2);
              float xValue = getX(b, xR, xC, d1);
              dotProd += (xValue * dyValue);
            }
          }
        }
        setOutput(dotProd);
      }
    `}},DepthwiseConv2DDerInputProgram=class{constructor(convInfo){this.variableNames=["dy","W"],this.outputShape=convInfo.inShape;let filterHeight=convInfo.filterHeight,filterWidth=convInfo.filterWidth,strideHeight=convInfo.strideHeight,strideWidth=convInfo.strideWidth,padTop=filterHeight-1-convInfo.padInfo.top,padLeft=filterWidth-1-convInfo.padInfo.left,channelMul=convInfo.outChannels/convInfo.inChannels;this.userCode=`
      const ivec2 pads = ivec2(${padTop}, ${padLeft});

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

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

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

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

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

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

            // TO DO: Vec4 over the channelMul
            for (int dm = 0; dm < ${channelMul}; dm++) {
              int d2 = d1 * ${channelMul} + dm;
              float xValue = getDy(batch, idyR, idyC, d2);
              float wValue = getW(wRPerm, wCPerm, d1, dm);
              dotProd += xValue * wValue;
            }
          }
        }
        setOutput(dotProd);
      }
    `}};function depthwiseConv2dNativeBackpropFilter3(args){let{inputs,backend:backend22,attrs}=args,{x,dy}=inputs,{strides,dilations,pad:pad3,dimRoundingMode,filterShape}=attrs,convInfo=backend_util_exports.computeConv2DInfo(x.shape,filterShape,strides,dilations,pad3,dimRoundingMode,!0),program=new DepthwiseConv2DDerFilterProgram(convInfo);return backend22.runWebGLProgram(program,[x,dy],"float32")}var depthwiseConv2dNativeBackpropFilterConfig2={kernelName:DepthwiseConv2dNativeBackpropFilter,backendName:"webgl",kernelFunc:depthwiseConv2dNativeBackpropFilter3};function depthwiseConv2dNativeBackpropInput3(args){let{inputs,backend:backend22,attrs}=args,{dy,filter}=inputs,{strides,dilations,pad:pad3,dimRoundingMode,inputShape}=attrs,convInfo=backend_util_exports.computeConv2DInfo(inputShape,filter.shape,strides,dilations,pad3,dimRoundingMode,!0),program=new DepthwiseConv2DDerInputProgram(convInfo);return backend22.runWebGLProgram(program,[dy,filter],"float32")}var depthwiseConv2dNativeBackpropInputConfig2={kernelName:DepthwiseConv2dNativeBackpropInput,backendName:"webgl",kernelFunc:depthwiseConv2dNativeBackpropInput3},DiagProgram=class{constructor(size){this.variableNames=["X"],this.outputShape=[size,size],this.userCode=`
      void main() {
          ivec2 coords = getOutputCoords();
          float val = coords[0] == coords[1] ? getX(coords[0]) : 0.0;
          setOutput(val);
      }
    `}};function diag3(args){let{inputs,backend:backend22}=args,{x}=inputs,outShape=[...x.shape,...x.shape],xSize=util_exports.sizeFromShape(x.shape),flat=reshape3({inputs:{x},backend:backend22,attrs:{shape:[xSize]}}),program=new DiagProgram(xSize),res=backend22.runWebGLProgram(program,[flat],flat.dtype),out=reshape3({inputs:{x:res},backend:backend22,attrs:{shape:outShape}});return backend22.disposeIntermediateTensorInfo(flat),backend22.disposeIntermediateTensorInfo(res),out}var diagConfig2={kernelName:Diag,backendName:"webgl",kernelFunc:diag3},Dilation2DProgram=class{constructor(convInfo){this.variableNames=["x","W"],this.outputShape=convInfo.outShape;let{inHeight,inWidth,padInfo,strideHeight,strideWidth,filterHeight,filterWidth,dilationHeight,dilationWidth}=convInfo,{top:padTop,left:padLeft}=padInfo;this.userCode=`
      const ivec2 strides = ivec2(${strideHeight}, ${strideWidth});
      const ivec2 pads = ivec2(${padTop}, ${padLeft});
      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 < ${filterHeight}; h++) {
          int hIn = hBeg + h * ${dilationHeight};

          if (hIn >= 0 && hIn < ${inHeight}) {
            for (int w = 0; w < ${filterWidth}; w++) {
              int wIn = wBeg + w * ${dilationWidth};

              if (wIn >= 0 && wIn < ${inWidth}) {
                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 dilation2D(args){let{inputs,backend:backend22,attrs}=args,{x,filter}=inputs,{strides,pad:pad3,dilations}=attrs,convInfo=backend_util_exports.computeDilation2DInfo(x.shape,filter.shape,strides,pad3,"NHWC",dilations),out,program=new Dilation2DProgram(convInfo);out=backend22.runWebGLProgram(program,[x,filter],"float32");let outReshaped=reshape3({inputs:{x:out},backend:backend22,attrs:{shape:convInfo.outShape}});return backend22.disposeIntermediateTensorInfo(out),outReshaped}var dilation2DConfig={kernelName:Dilation2D,backendName:"webgl",kernelFunc:dilation2D},ELU3="return (x >= 0.0) ? x : (exp(x) - 1.0);",ELU_PACKED=`
  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;
`,elu3=unaryKernelFunc2({opSnippet:ELU3,packedOpSnippet:ELU_PACKED}),eluConfig2={kernelName:Elu,backendName:"webgl",kernelFunc:elu3},ELU_DER="return (b >= 1.0) ? a : a * (b + 1.0);",ELU_DER_PACKED=`
  vec4 bGTEZero = vec4(greaterThanEqual(b, vec4(0.)));
  return (bGTEZero * a) + ((vec4(1.0) - bGTEZero) * (a * (b + vec4(1.0))));
`,eluGrad2=args=>{let{inputs,backend:backend22}=args,{dy,y}=inputs,program=env().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new BinaryOpPackedProgram(ELU_DER_PACKED,dy.shape,y.shape):new BinaryOpProgram(ELU_DER,dy.shape,y.shape);return backend22.runWebGLProgram(program,[dy,y],dy.dtype)},eluGradConfig3={kernelName:EluGrad,backendName:"webgl",kernelFunc:eluGrad2},PACKED_EQUAL=`
  return vec4(equal(a, b));
`,EQUAL="return float(a == b);",equal3=binaryKernelFunc2({opSnippet:EQUAL,packedOpSnippet:PACKED_EQUAL,dtype:"bool"}),equalConfig2={kernelName:Equal,backendName:"webgl",kernelFunc:equal3},ERF=`
  // Error function is calculated approximately with elementary function.
  // See "Handbook of Mathematical Functions with Formulas,
  // Graphs, and Mathematical Tables", Abramowitz and Stegun.
  float p = ${backend_util_exports.ERF_P};
  float a1 = ${backend_util_exports.ERF_A1};
  float a2 = ${backend_util_exports.ERF_A2};
  float a3 = ${backend_util_exports.ERF_A3};
  float a4 = ${backend_util_exports.ERF_A4};
  float a5 = ${backend_util_exports.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));
`,erf3=unaryKernelFunc2({opSnippet:ERF}),erfConfig2={kernelName:Erf,backendName:"webgl",kernelFunc:erf3},EXP="return exp(x);",exp3=unaryKernelFunc2({opSnippet:EXP,packedOpSnippet:EXP,cpuKernelImpl:expImplCPU}),expConfig2={kernelName:Exp,backendName:"webgl",kernelFunc:exp3};function expandDims3(args){let{inputs,attrs,backend:backend22}=args,{dim}=attrs,{input:input2}=inputs,inputRank=input2.shape.length,newShape=input2.shape.slice(),$dim=dim;return dim<0&&(util_exports.assert(-(inputRank+1)<=dim,()=>`Axis must be in the interval [${-(inputRank+1)}, ${inputRank}]`),$dim=inputRank+dim+1),newShape.splice($dim,0,1),reshape3({inputs:{x:input2},backend:backend22,attrs:{shape:newShape}})}var expandDimsConfig2={kernelName:ExpandDims,backendName:"webgl",kernelFunc:expandDims3},EXPM1="return exp(x) - 1.0;",expm13=unaryKernelFunc2({opSnippet:EXPM1,packedOpSnippet:EXPM1,cpuKernelImpl:expm1ImplCPU}),expm1Config2={kernelName:Expm1,backendName:"webgl",kernelFunc:expm13},FFTProgram=class{constructor(component,inputShape,inverse){this.variableNames=["real","imag"];let innerDim=inputShape[1];this.outputShape=inputShape;let exponentMultiplierSnippet=inverse?`2.0 * ${Math.PI}`:`-2.0 * ${Math.PI}`,resultDenominator=inverse?`${innerDim}.0`:"1.0",opString;if(component==="real")opString="return real * expR - imag * expI;";else if(component==="imag")opString="return real * expI + imag * expR;";else throw new Error(`FFT component must be either "real" or "imag", got ${component}.`);this.userCode=`
      const float exponentMultiplier = ${exponentMultiplierSnippet};

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

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

        float result = 0.0;

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

        return result;
      }

      void main() {
        ivec2 coords = getOutputCoords();
        setOutput(mulMatDFT(coords[0], coords[1]));
      }
    `}};function fftImpl2(x,inverse,backend22){let xData=backend22.texData.get(x.dataId),inputSize=util_exports.sizeFromShape(x.shape),innerDimensionSize=x.shape[x.shape.length-1],batch=inputSize/innerDimensionSize,xShape=reshape3({inputs:{x},backend:backend22,attrs:{shape:[batch,innerDimensionSize]}}).shape,realProgram=new FFTProgram("real",xShape,inverse),imagProgram=new FFTProgram("imag",xShape,inverse),inputs=[{dataId:xData.complexTensorInfos.real.dataId,dtype:xData.complexTensorInfos.real.dtype,shape:xShape},{dataId:xData.complexTensorInfos.imag.dataId,dtype:xData.complexTensorInfos.imag.dtype,shape:xShape}],realPart=backend22.runWebGLProgram(realProgram,inputs,"float32"),imagPart=backend22.runWebGLProgram(imagProgram,inputs,"float32"),complexOutput=complex3({inputs:{real:realPart,imag:imagPart},backend:backend22});backend22.disposeIntermediateTensorInfo(realPart),backend22.disposeIntermediateTensorInfo(imagPart);let complexOutputReshaped=reshape3({inputs:{x:complexOutput},backend:backend22,attrs:{shape:x.shape}});return backend22.disposeIntermediateTensorInfo(complexOutputReshaped),complexOutputReshaped}function fft3(args){let{inputs,backend:backend22}=args,{input:input2}=inputs;return fftImpl2(input2,!1,backend22)}var fftConfig2={kernelName:FFT,backendName:"webgl",kernelFunc:fft3},FillProgram=class{constructor(shape,value){this.outputShape=[],this.variableNames=["x"],this.outputShape=shape,this.userCode=`
      uniform float value;
      void main() {
        // Input can be obtained from uniform value.
        setOutput(value);
      }
    `}getCustomSetupFunc(value){return(gpgpu,webGLProgram)=>{this.valueLoc==null&&(this.valueLoc=gpgpu.getUniformLocationNoThrow(webGLProgram,"value")),gpgpu.gl.uniform1f(this.valueLoc,value)}}};function fill3(args){let{backend:backend22,attrs}=args,{shape,value}=attrs,{dtype}=attrs;if(dtype=dtype||util_exports.inferDtype(value),dtype==="string"){let values=util_exports.getArrayFromDType(dtype,util_exports.sizeFromShape(shape));return values.fill(value),backend22.makeTensorInfo(shape,dtype,values)}else{let program=new FillProgram(shape,value),customSetup=program.getCustomSetupFunc(value);return backend22.runWebGLProgram(program,[],dtype,customSetup)}}var fillConfig2={kernelName:Fill,backendName:"webgl",kernelFunc:fill3},FlipLeftRightProgram=class{constructor(imageShape){this.variableNames=["Image"],this.outputShape=[];let imageWidth=imageShape[2];this.outputShape=imageShape,this.userCode=`
        void main() {
          ivec4 coords = getOutputCoords();
          int x = coords[2];

          int coordX = ${imageWidth} - x;
          float outputValue;
          if(coordX >= 0 && coordX < ${imageWidth}) {
            outputValue = getImage(coords[0], coords[1], coordX, coords[3]);
          } else {
            outputValue = getImage(coords[0], coords[1], coords[2], coords[3]);
          }
          setOutput(outputValue);
        }
    `}},flipLeftRightConfig2={kernelName:FlipLeftRight,backendName:"webgl",kernelFunc:({inputs,backend:backend22})=>{let{image:image3}=inputs,webglBackend=backend22,program=new FlipLeftRightProgram(image3.shape);return webglBackend.runWebGLProgram(program,[image3],image3.dtype)}},FLOOR="return floor(x);",floor3=unaryKernelFunc2({opSnippet:FLOOR,packedOpSnippet:FLOOR,cpuKernelImpl:floorImplCPU}),floorConfig2={kernelName:Floor,backendName:"webgl",kernelFunc:floor3},INT_DIV=`
  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;
  }
`,INT_DIV_PACKED=`
  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);
`,floorDiv3=binaryKernelFunc2({opSnippet:INT_DIV,packedOpSnippet:INT_DIV_PACKED,dtype:"int32"}),floorDivConfig2={kernelName:FloorDiv,backendName:"webgl",kernelFunc:floorDiv3},FromPixelsProgram=class{constructor(outputShape){this.variableNames=["A"];let glsl=getGlslDifferences(),[height,width]=outputShape;this.outputShape=outputShape,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(${width}.0, ${height}.0);

        vec4 values = ${glsl.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));
      }
    `}},FromPixelsPackedProgram=class{constructor(outputShape){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0;let glsl=getGlslDifferences(),[height,width]=outputShape;this.outputShape=outputShape,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(${width}.0, ${height}.0);
            vec4 values = ${glsl.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);
          }
        }

        ${glsl.output} = result;
      }
    `}},fromPixelsConfig={kernelName:FromPixels,backendName:"webgl",kernelFunc:fromPixels2},fromPixels2DContext2;function fromPixels2(args){let{inputs,backend:backend22,attrs}=args,{pixels}=inputs,{numChannels}=attrs,isVideo=typeof HTMLVideoElement!="undefined"&&pixels instanceof HTMLVideoElement,isImage=typeof HTMLImageElement!="undefined"&&pixels instanceof HTMLImageElement,isImageBitmap=typeof ImageBitmap!="undefined"&&pixels instanceof ImageBitmap,[width,height]=isVideo?[pixels.videoWidth,pixels.videoHeight]:[pixels.width,pixels.height],texShape=[height,width],outShape=[height,width,numChannels];(isImage||isVideo||isImageBitmap)&&(fromPixels2DContext2==null&&(fromPixels2DContext2=document.createElement("canvas").getContext("2d")),fromPixels2DContext2.canvas.width=width,fromPixels2DContext2.canvas.height=height,fromPixels2DContext2.drawImage(pixels,0,0,width,height),pixels=fromPixels2DContext2.canvas);let tempPixelHandle=backend22.makeTensorInfo(texShape,"int32");backend22.texData.get(tempPixelHandle.dataId).usage=TextureUsage.PIXELS,backend22.gpgpu.uploadPixelDataToTexture(backend22.getTexture(tempPixelHandle.dataId),pixels);let program=env().getBool("WEBGL_PACK")?new FromPixelsPackedProgram(outShape):new FromPixelsProgram(outShape),res=backend22.runWebGLProgram(program,[tempPixelHandle],"int32");return backend22.disposeData(tempPixelHandle.dataId),res}function fusedConv2d(args){let{inputs,backend:backend22,attrs}=args,{x,filter,bias,preluActivationWeights}=inputs,{strides,pad:pad3,dataFormat,dilations,dimRoundingMode,activation:activation2,leakyreluAlpha}=attrs,$dataFormat=backend_util_exports.convertConv2DDataFormat(dataFormat),convInfo=backend_util_exports.computeConv2DInfo(x.shape,filter.shape,strides,dilations,pad3,dimRoundingMode,!1,$dataFormat),out,intermediates=[];if(convInfo.filterHeight===1&&convInfo.filterWidth===1&&convInfo.dilationHeight===1&&convInfo.dilationWidth===1&&convInfo.strideHeight===1&&convInfo.strideWidth===1&&(convInfo.padInfo.type==="SAME"||convInfo.padInfo.type==="VALID"))out=conv2dByMatMul({x,filter,convInfo,backend:backend22,bias,activation:activation2,preluActivationWeights,leakyreluAlpha});else if(env().getBool("WEBGL_CONV_IM2COL")&&x.shape[0]===1)out=conv2dWithIm2Row({x,filter,convInfo,backend:backend22,bias,activation:activation2,preluActivationWeights,leakyreluAlpha});else{let hasBias=bias!=null,hasPreluActivationWeights=preluActivationWeights!=null,hasLeakyreluAlpha=activation2==="leakyrelu",fusedActivation=activation2?mapActivationToShaderProgram(activation2,!1):null,program=new Conv2DProgram(convInfo,hasBias,fusedActivation,hasPreluActivationWeights,hasLeakyreluAlpha),inputs2=[x,filter];if(bias&&inputs2.push(bias),preluActivationWeights&&inputs2.push(preluActivationWeights),hasLeakyreluAlpha){let $leakyreluAlpha=backend22.makeTensorInfo([],"float32",util_exports.createScalarValue(leakyreluAlpha,"float32"));inputs2.push($leakyreluAlpha),intermediates.push($leakyreluAlpha)}out=backend22.runWebGLProgram(program,inputs2,"float32")}let outReshaped=reshape3({inputs:{x:out},backend:backend22,attrs:{shape:convInfo.outShape}});return intermediates.push(out),intermediates.forEach(t=>backend22.disposeIntermediateTensorInfo(t)),outReshaped}var fusedConv2DConfig2={kernelName:FusedConv2D,backendName:"webgl",kernelFunc:fusedConv2d};function fusedDepthwiseConv2D2(args){let{inputs,backend:backend22,attrs}=args,{x,filter,bias,preluActivationWeights}=inputs,{strides,pad:pad3,dilations,dimRoundingMode,activation:activation2,leakyreluAlpha}=attrs,intermediates=[],$dilations=dilations;$dilations==null&&($dilations=[1,1]),util_exports.assert(backend_util_exports.eitherStridesOrDilationsAreOne(strides,$dilations),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${strides} and dilations '${$dilations}'`);let convInfo=backend_util_exports.computeConv2DInfo(x.shape,filter.shape,strides,$dilations,pad3,dimRoundingMode,!0),shouldPackDepthwiseConv=env().getBool("WEBGL_PACK_DEPTHWISECONV")&&convInfo.strideWidth<=2&&convInfo.outChannels/convInfo.inChannels==1,fusedActivation=ac
        ${stridesType} strides = ${stridesType}(${this.strides});
         void main() {
          ${dtype} coords = getOutputCoords();
          int flattenIndex = 0;
          for (int j = 0; j < ${this.sliceDim}; j++) {
            int index = round(getIndices(coords[0], j));
            flattenIndex += index * ${strideString};
          }
          setOutput(getX(flattenIndex, coords[1]));
        }
      `}};function gatherNd2(args){let{inputs,backend:backend22}=args,{params,indices}=inputs,indicesShape=indices.shape,sliceRank=indicesShape[indicesShape.length-1],[resultShape,numSlices,sliceSize,strides]=backend_util_exports.prepareAndValidate(params,indices),flattenIndices=reshape3({inputs:{x:indices},backend:backend22,attrs:{shape:[numSlices,sliceRank]}}),flattenX=reshape3({inputs:{x:params},backend:backend22,attrs:{shape:[util_exports.sizeFromShape(params.shape)/sliceSize,sliceSize]}}),program=new GatherNDProgram(sliceRank,strides,[numSlices,sliceSize]),res=backend22.runWebGLProgram(program,[flattenX,flattenIndices],flattenX.dtype),reshaped=reshape3({inputs:{x:res},backend:backend22,attrs:{shape:resultShape}});return backend22.disposeIntermediateTensorInfo(flattenIndices),backend22.disposeIntermediateTensorInfo(flattenX),backend22.disposeIntermediateTensorInfo(res),reshaped}var gatherNdConfig2={kernelName:GatherNd,backendName:"webgl",kernelFunc:gatherNd2},GatherProgram=class{constructor(aShape,outputShape){this.variableNames=["A","indices"],this.outputShape=outputShape,this.rank=outputShape.length;let dtype=getCoordsDataType(this.rank),sourceCoords=getSourceCoords2(aShape,2);this.userCode=`
      void main() {
        ${dtype} resRC = getOutputCoords();
        setOutput(getA(${sourceCoords}));
      }
    `}};function getSourceCoords2(aShape,axis){let currentCoords=["resRC.x","resRC.y","resRC.z","resRC.w"],sourceCoords=[];for(let i=0;i<aShape.length;i++)i===2?sourceCoords.push("int(getIndices(resRC.x, resRC.z))"):sourceCoords.push(`${currentCoords[i]}`);return sourceCoords.join()}function gatherV22(args){let{inputs,backend:backend22,attrs}=args,{x,indices}=inputs,{axis,batchDims}=attrs,parsedAxis=util_exports.parseAxisParam(axis,x.shape)[0],shapeInfo=backend_util_exports.segment_util.collectGatherOpShapeInfo(x,indices,parsedAxis,batchDims),indicesSize=util_exports.sizeFromShape(indices.shape),toDispose=[],flattenX=reshape3({inputs:{x},backend:backend22,attrs:{shape:[shapeInfo.batchSize,shapeInfo.outerSize,shapeInfo.dimSize,shapeInfo.sliceSize]}}),flattenIndex=reshape3({inputs:{x:indices},backend:backend22,attrs:{shape:[shapeInfo.batchSize,indicesSize/shapeInfo.batchSize]}});toDispose.push(flattenX),toDispose.push(flattenIndex);let flattenOutputShape=[shapeInfo.batchSize,shapeInfo.outerSize,indicesSize/shapeInfo.batchSize,shapeInfo.sliceSize];if(backend22.shouldExecuteOnCPU([x,indices])||x.dtype==="string"){let indicesBuf=backend22.bufferSync(flattenIndex),xBuf=backend22.bufferSync(flattenX),outBuf=gatherV2ImplCPU(xBuf,indicesBuf,flattenOutputShape);return toDispose.forEach(t=>backend22.disposeIntermediateTensorInfo(t)),backend22.makeTensorInfo(shapeInfo.outputShape,outBuf.dtype,outBuf.values)}let program=new GatherProgram(flattenX.shape,flattenOutputShape),res=backend22.runWebGLProgram(program,[flattenX,flattenIndex],flattenX.dtype);toDispose.push(res);let reshaped=reshape3({inputs:{x:res},backend:backend22,attrs:{shape:shapeInfo.outputShape}});return toDispose.forEach(t=>backend22.disposeIntermediateTensorInfo(t)),reshaped}var gatherV2Config2={kernelName:GatherV2,backendName:"webgl",kernelFunc:gatherV22},GREATER="return float(a > b);",GREATER_PACKED=`
  return vec4(greaterThan(a, b));
`,greater3=binaryKernelFunc2({opSnippet:GREATER,packedOpSnippet:GREATER_PACKED,cpuKernelImpl:greaterImplCPU,dtype:"bool"}),greaterConfig2={kernelName:Greater,backendName:"webgl",kernelFunc:greater3},GREATER_EQUAL="return float(a >= b);",GREATER_EQUAL_PACKED=`
  return vec4(greaterThanEqual(a, b));
`,greaterEqual3=binaryKernelFunc2({opSnippet:GREATER_EQUAL,packedOpSnippet:GREATER_EQUAL_PACKED,dtype:"bool"}),greaterEqualConfig2={kernelName:GreaterEqual,backendName:"webgl",kernelFunc:greaterEqual3};function ifft3(args){let{inputs,backend:backend22}=args,{input:input2}=inputs;return fftImpl2(input2,!0,backend22)}var ifftConfig2={kernelName:IFFT,backendName:"webgl",kernelFunc:ifft3},IS_FINITE="return float(!isnan(x) && !isinf(x));",isFinite4=unaryKernelFunc2({opSnippet:IS_FINITE,dtype:"bool"}),isFiniteConfig2={kernelName:IsFinite,backendName:"webgl",kernelFunc:isFinite4},IS_INF="return float(isinf(x));",isInf3=unaryKernelFunc2({opSnippet:IS_INF,dtype:"bool"}),isInfConfig2={kernelName:IsInf,backendName:"webgl",kernelFunc:isInf3},IS_NAN="return float(isnan(x));",isNaN4=unaryKernelFunc2({opSnippet:IS_NAN,dtype:"bool"}),isNaNConfig2={kernelName:IsNan,backendName:"webgl",kernelFunc:isNaN4},LESS="return float(a < b);",LESS_PACKED=`
  return vec4(lessThan(a, b));
`,less3=binaryKernelFunc2({opSnippet:LESS,packedOpSnippet:LESS_PACKED,cpuKernelImpl:lessImplCPU,dtype:"bool"}),lessConfig2={kernelName:Less,backendName:"webgl",kernelFunc:less3},LESS_EQUAL="return float(a <= b);",LESS_EQUAL_PACKED=`
  return vec4(lessThanEqual(a, b));
`,lessEqual3=binaryKernelFunc2({opSnippet:LESS_EQUAL,packedOpSnippet:LESS_EQUAL_PACKED,dtype:"bool"}),lessEqualConfig2={kernelName:LessEqual,backendName:"webgl",kernelFunc:lessEqual3};function linSpace2(args){let{backend:backend22,attrs}=args,{start,stop,num}=attrs,outVals=linSpaceImplCPU(start,stop,num);return backend22.makeTensorInfo([outVals.length],"float32",outVals)}var linSpaceConfig2={kernelName:LinSpace,backendName:"webgl",kernelFunc:linSpace2},LOG=`if (x < 0.0) return NAN;
  return log(x);`,LOG_PACKED=`
  vec4 result = log(x);
  vec4 isNaN = vec4(lessThan(x, vec4(0.0)));
  result.r = isNaN.r == 1.0 ? NAN : result.r;
  result.g = isNaN.g == 1.0 ? NAN : result.g;
  result.b = isNaN.b == 1.0 ? NAN : result.b;
  result.a = isNaN.a == 1.0 ? NAN : result.a;

  return result;
`,log4=unaryKernelFunc2({opSnippet:LOG,packedOpSnippet:LOG_PACKED,cpuKernelImpl:logImplCPU}),logConfig2={kernelName:Log,backendName:"webgl",kernelFunc:log4},LOG1P="return log(1.0 + x);",log1p3=unaryKernelFunc2({opSnippet:LOG1P}),log1pConfig2={kernelName:Log1p,backendName:"webgl",kernelFunc:log1p3},LOGICAL_AND="return float(a >= 1.0 && b >= 1.0);",LOGICAL_AND_PACKED=`
  return vec4(
    vec4(greaterThanEqual(a, vec4(1.0))) *
    vec4(greaterThanEqual(b, vec4(1.0))));
`,logicalAnd3=binaryKernelFunc2({opSnippet:LOGICAL_AND,packedOpSnippet:LOGICAL_AND_PACKED,dtype:"bool"}),logicalAndConfig2={kernelName:LogicalAnd,backendName:"webgl",kernelFunc:logicalAnd3},LOGICAL_NOT="return float(!(x >= 1.0));",logicalNot3=unaryKernelFunc2({opSnippet:LOGICAL_NOT}),logicalNotConfig2={kernelName:LogicalNot,backendName:"webgl",kernelFunc:logicalNot3},LOGICAL_OR="return float(a >= 1.0 || b >= 1.0);",LOGICAL_OR_PACKED=`
  return min(
    vec4(greaterThanEqual(a, vec4(1.0))) +
    vec4(greaterThanEqual(b, vec4(1.0))),
    vec4(1.0));
`,logicalOr3=binaryKernelFunc2({opSnippet:LOGICAL_OR,packedOpSnippet:LOGICAL_OR_PACKED,dtype:"bool"}),logicalOrConfig2={kernelName:LogicalOr,backendName:"webgl",kernelFunc:logicalOr3},LRNProgram=class{constructor(xShape,radius,bias,alpha,beta){this.variableNames=["x"],this.outputShape=[];let rad=radius,maxD=xShape[3]-1;this.outputShape=xShape;let powOperator,basis=`float(${bias}) + float(${alpha}) * sum`;beta===.5?powOperator=`inversesqrt(${basis})`:beta===1?powOperator=`1.0/(${basis})`:powOperator=`exp(log(${basis}) * float(-${beta}));`,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 = -${rad}; j <= ${rad}; j++) {
          int idx = d + j;
          if (idx >= 0 && idx <=  ${maxD}) {
            float z = getX(b, r, c, idx);
            sum += z * z;
          }
        }
        float val = x * ${powOperator};
        setOutput(val);
      }
    `}},LRNPackedProgram=class{constructor(xShape,radius,bias,alpha,beta){this.variableNames=["x"],this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0;let rad=radius,maxD=xShape[3]-1;this.outputShape=xShape;let powOperator,basis=`float(${bias}) + float(${alpha}) * sum`;beta===.5?powOperator=`inversesqrt(${basis})`:beta===1?powOperator=`1.0/(${basis})`:powOperator=`exp(log(${basis}) * float(-${beta}));`,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 - ${rad};
        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 = - ${rad}; j <= ${rad}; j++) {
          ivec2 idx = depth + j;
          bvec2 aboveLowerBound = greaterThanEqual(idx, ivec2(0));
          bvec2 belowUpperBound = lessThanEqual(idx, ivec2(${maxD}));

          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 * ${powOperator};
        setOutput(result);
      }
    `}},lrn=args=>{let{inputs,backend:backend22,attrs}=args,{x}=inputs,{depthRadius,bias,alpha,beta}=attrs,program=env().getBool("WEBGL_PACK_NORMALIZATION")?new LRNPackedProgram(x.shape,depthRadius,bias,alpha,beta):new LRNProgram(x.shape,depthRadius,bias,alpha,beta);return backend22.runWebGLProgram(program,[x],x.dtype)},LRNConfig={kernelName:LRN,backendName:"webgl",kernelFunc:lrn},LRNGradProgram=class{constructor(inputShape,depthRadius,bias,alpha,beta){this.variableNames=["inputImage","outputImage","dy"],this.outputShape=[],this.outputShape=inputShape,this.depth=inputShape[3],this.depthRadius=depthRadius,this.bias=bias,this.alpha=alpha,this.beta=beta,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 - ${depthRadius})));
          int depthEnd = int(min(float(${this.depth}),
              float(d + ${depthRadius} + 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(${alpha}) * norm + float(${bias});

          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(${alpha})
                * float(${beta})
                * getInputImage(b ,r ,c, k) * getOutputImage(b, r, c, d)
                / norm;
              if (k == d) {
                dyi += pow(norm, -1.0 * ${beta});
              }
              if (k == coords[3]) {
                dyi *= getDy(b, r, c, d);
                result += dyi;
              }
            }
            else {
              break;
            }
          }
      }
      setOutput(result);
      }
    `}},lrnGrad=args=>{let{inputs,backend:backend22,attrs}=args,{x,y,dy}=inputs,{depthRadius,bias,alpha,beta}=attrs,program=new LRNGradProgram(x.shape,depthRadius,bias,alpha,beta);return backend22.runWebGLProgram(program,[x,y,dy],x.dtype)},LRNGradConfig={kernelName:LRNGrad,backendName:"webgl",kernelFunc:lrnGrad};function maxImpl2(x,reduceShape,outShape,backend22){let inSize=util_exports.sizeFromShape(reduceShape),batchSize=util_exports.sizeFromShape(x.shape)/inSize,reshapedInput=reshape3({inputs:{x},attrs:{shape:[batchSize,inSize]},backend:backend22}),reduced=reduce(reshapedInput,x.dtype,"max",backend22),reshapedOutput=reshape3({inputs:{x:reduced},attrs:{shape:outShape},backend:backend22});return backend22.disposeIntermediateTensorInfo(reshapedInput),backend22.disposeIntermediateTensorInfo(reduced),reshapedOutput}function max3(args){let{inputs,backend:backend22,attrs}=args,{x}=inputs,{reductionIndices,keepDims}=attrs,xRank=x.shape.length,origAxes=util_exports.parseAxisParam(reductionIndices,x.shape),axes=origAxes,permutedAxes=backend_util_exports.getAxesPermutation(axes,xRank),maxInputIsTransposed=permutedAxes!=null,shouldExecuteOnCPU=backend22.shouldExecuteOnCPU([x]),maxInput=x;if(maxInputIsTransposed){if(shouldExecuteOnCPU){let values=backend22.texData.get(maxInput.dataId).values,newShape=new Array(xRank);for(let i=0;i<newShape.length;i++)newShape[i]=x.shape[permutedAxes[i]];let maxInputValues=transposeImplCPU(values,x.shape,x.dtype,permutedAxes,newShape);maxInput=backend22.makeTensorInfo(newShape,x.dtype);let maxInputData=backend22.texData.get(maxInput.dataId);maxInputData.values=maxInputValues}else maxInput=transposeImpl2(x,permutedAxes,backend22);axes=backend_util_exports.getInnerMostAxes(axes.length,xRank)}backend_util_exports.assertAxesAreInnerMostDims("max",axes,xRank);let[maxOutShape,reduceShape]=backend_util_exports.computeOutAndReduceShapes(maxInput.shape,axes),outShape=maxOutShape;keepDims&&(outShape=backend_util_exports.expandShapeToKeepDim(maxOutShape,origAxes));let out;if(shouldExecuteOnCPU){let values=backend22.texData.get(maxInput.dataId).values,outValues=maxImplCPU(values,util_exports.sizeFromShape(reduceShape),outShape,x.dtype);out=backend22.makeTensorInfo(outShape,x.dtype);let outData=backend22.texData.get(out.dataId);outData.values=outValues}else out=maxImpl2(maxInput,reduceShape,outShape,backend22);return maxInputIsTransposed&&backend22.disposeIntermediateTensorInfo(maxInput),out}var maxConfig2={kernelName:Max,backendName:"webgl",kernelFunc:max3},MAXIMUM=CHECK_NAN_SNIPPET2+`
  return max(a, b);
`,MAXIMUM_PACKED=`
  vec4 result = vec4(max(a, b));
  vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
  `+CHECK_NAN_SNIPPET3+`
  return result;
`,maximum3=binaryKernelFunc2({opSnippet:MAXIMUM,packedOpSnippet:MAXIMUM_PACKED,cpuKernelImpl:maximumImplCPU}),maximumConfig2={kernelName:Maximum,backendName:"webgl",kernelFunc:maximum3};function maxPool3(args){let{inputs,backend:backend22,attrs}=args,{x}=inputs;assertNotComplex2(x,"maxPool");let{filterSize,strides,pad:pad3,dimRoundingMode}=attrs,dilations=1;util_exports.assert(backend_util_exports.eitherStridesOrDilationsAreOne(strides,dilations),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${strides} and dilations '${dilations}'`);let convInfo=backend_util_exports.computePool2DInfo(x.shape,filterSize,strides,dilations,pad3,dimRoundingMode);if(convInfo.filterWidth===1&&convInfo.filterHeight===1&&util_exports.arraysEqual(convInfo.inShape,convInfo.outShape))return identity2({inputs:{x},backend:backend22});let maxPoolProgram=new Pool2DProgram(convInfo,"max",!1);return backend22.runWebGLProgram(maxPoolProgram,[x],x.dtype)}var maxPoolConfig2={kernelName:MaxPool,backendName:"webgl",kernelFunc:maxPool3};function maxPool3d2(args){let{inputs,backend:backend22,attrs}=args,{x}=inputs,{filterSize,strides,pad:pad3,dataFormat,dimRoundingMode}=attrs,dilations=[1,1,1],convInfo=backend_util_exports.computePool3DInfo(x.shape,filterSize,strides,dilations,pad3,dimRoundingMode,dataFormat),maxPoolProgram=new Pool3DProgram(convInfo,"max",!1);return backend22.runWebGLProgram(maxPoolProgram,[x],x.dtype)}var maxPool3DConfig2={kernelName:MaxPool3D,backendName:"webgl",kernelFunc:maxPool3d2},MaxPool2DBackpropProgram=class{constructor(convInfo){this.variableNames=["dy","maxPos"],this.outputShape=convInfo.inShape;let strideHeight=convInfo.strideHeight,strideWidth=convInfo.strideWidth,dilationHeight=convInfo.dilationHeight,effectiveFilterHeight=convInfo.effectiveFilterHeight,effectiveFilterWidth=convInfo.effectiveFilterWidth,padTop=effectiveFilterHeight-1-convInfo.padInfo.top,padLeft=effectiveFilterWidth-1-convInfo.padInfo.left,lastIndex=effectiveFilterHeight*effectiveFilterWidth-1;this.userCode=`
      const ivec2 pads = ivec2(${padTop}, ${padLeft});

      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 < ${effectiveFilterHeight};
          wR += ${dilationHeight}) {
          float dyR = float(dyRCorner + wR) / ${strideHeight}.0;

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

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

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

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

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

            dotProd += dyValue * mask;
          }
        }
        setOutput(dotProd);
      }
    `}},MaxPool3DBackpropProgram=class{constructor(convInfo){this.variableNames=["dy","maxPos"],this.outputShape=convInfo.inShape;let strideDepth=convInfo.strideDepth,strideHeight=convInfo.strideHeight,strideWidth=convInfo.strideWidth,dilationDepth=convInfo.dilationDepth,dilationHeight=convInfo.dilationHeight,dilationWidth=convInfo.dilationWidth,effectiveFilterDepth=convInfo.effectiveFilterDepth,effectiveFilterHeight=convInfo.effectiveFilterHeight,effectiveFilterWidth=convInfo.effectiveFilterWidth,padFront=effectiveFilterDepth-1-convInfo.padInfo.front,padTop=effectiveFilterHeight-1-convInfo.padInfo.top,padLeft=effectiveFilterWidth-1-convInfo.padInfo.left,lastIndex=effectiveFilterDepth*effectiveFilterHeight*effectiveFilterWidth-1;this.userCode=`
      const ivec3 pads = ivec3(${padFront}, ${padTop}, ${padLeft});

      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 < ${effectiveFilterDepth};
           wD += ${dilationDepth}) {
          float dyD = float(dyDCorner + wD) / ${strideDepth}.0;

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

          for (int wR = 0; wR < ${effectiveFilterHeight};
              wR += ${dilationHeight}) {
            float dyR = float(dyRCorner + wR) / ${strideHeight}.0;

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

            for (int wC = 0; wC < ${effectiveFilterWidth};
                wC += ${dilationWidth}) {
              float dyC = float(dyCCorner + wC) / ${strideWidth}.0;

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

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

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

              dotProd += dyValue * mask;
            }
          }
        }
        setOutput(dotProd);
      }
    `}};function maxPool3DGrad2(args){let{inputs,backend:backend22,attrs}=args,{dy,input:input2}=inputs,x=input2,{filterSize,strides,pad:pad3,dimRoundingMode}=attrs,dilations=[1,1,1],convInfo=backend_util_exports.computePool3DInfo(x.shape,filterSize,strides,dilations,pad3,dimRoundingMode),maxPool3dPositionsProgram=new Pool3DProgram(convInfo,"max",!0),maxPool3dPositions2=backend22.runWebGLProgram(maxPool3dPositionsProgram,[x],x.dtype),maxPoolBackpropProgram=new MaxPool3DBackpropProgram(convInfo),result=backend22.runWebGLProgram(maxPoolBackpropProgram,[dy,maxPool3dPositions2],x.dtype);return backend22.disposeIntermediateTensorInfo(maxPool3dPositions2),result}var maxPoolGrad3DConfig={kernelName:MaxPool3DGrad,backendName:"webgl",kernelFunc:maxPool3DGrad2};function maxPoolGrad3(args){let{inputs,backend:backend22,attrs}=args,{dy,input:input2,output}=inputs,x=input2;assertNotComplex2([input2,output],"maxPoolGrad");let{filterSize,strides,pad:pad3,dimRoundingMode}=attrs,convInfo=backend_util_exports.computePool2DInfo(x.shape,filterSize,strides,1,pad3,dimRoundingMode),getPositions=!0,maxPoolPositionsProgram=new Pool2DProgram(convInfo,"max",getPositions),maxPoolPositions2=backend22.runWebGLProgram(maxPoolPositionsProgram,[x],x.dtype),maxPoolBackPropProgram=new MaxPool2DBackpropProgram(convInfo),result=backend22.runWebGLProgram(maxPoolBackPropProgram,[dy,maxPoolPositions2],x.dtype);return backend22.disposeIntermediateTensorInfo(maxPoolPositions2),result}var maxPoolGradConfig3={kernelName:MaxPoolGrad,backendName:"webgl",kernelFunc:maxPoolGrad3};function maxPoolWithArgmaxImpl2(x,includeBatchInIndex,convInfo,backend22){let program=new Pool2DProgram(convInfo,"max",!1),poolOutput=backend22.runWebGLProgram(program,[x],"float32");program=new Pool2DProgram(convInfo,"max",!0,!0,includeBatchInIndex);let indexOutput=backend22.runWebGLProgram(program,[x],"float32");return[poolOutput,indexOutput]}var maxPoolWithArgmaxConfig2={kernelName:MaxPoolWithArgmax,backendName:"webgl",kernelFunc:({inputs,attrs,backend:backend22})=>{let{x}=inputs,{filterSize,strides,pad:pad3,includeBatchInIndex}=attrs,webglBackend=backend22;util_exports.assert(x.shape.length===4,()=>`Error in maxPool: input must be rank 4 but got rank ${x.shape.length}.`);let dilations=[1,1];util_exports.assert(backend_util_exports.eitherStridesOrDilationsAreOne(strides,dilations),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${strides} and dilations '${dilations}'`);let convInfo=backend_util_exports.computePool2DInfo(x.shape,filterSize,strides,dilations,pad3),[result,indexes]=maxPoolWithArgmaxImpl2(x,includeBatchInIndex,convInfo,webglBackend);return[result,indexes]}};function meanImpl(x,reduceShape,outShape,backend22){let inSize=util_exports.sizeFromShape(reduceShape),batchSize=util_exports.sizeFromShape(x.shape)/inSize,reshapedInput=reshape3({inputs:{x},attrs:{shape:[batchSize,inSize]},backend:backend22}),reduced=reduce(reshapedInput,"float32","mean",backend22),reshapedOutput=reshape3({inputs:{x:reduced},attrs:{shape:outShape},backend:backend22});return backend22.disposeIntermediateTensorInfo(reshapedInput),backend22.disposeIntermediateTensorInfo(reduced),reshapedOutput}var meanConfig2={kernelName:Mean,backendName:"webgl",kernelFunc:({inputs,attrs,backend:backend22})=>{let{x}=inputs,{keepDims,axis}=attrs,webglBackend=backend22,xRank=x.shape.length,origAxes=util_exports.parseAxisParam(axis,x.shape),axes=origAxes,permutedAxes=backend_util_exports.getAxesPermutation(axes,xRank),meanInputIsTransposed=permutedAxes!=null,shouldExecuteOnCPU=webglBackend.shouldExecuteOnCPU([x]),intermediates=[],meanInput=x;if(meanInputIsTransposed){if(shouldExecuteOnCPU){let values=webglBackend.texData.get(meanInput.dataId).values,newShape=new Array(xRank);for(let i=0;i<newShape.length;i++)newShape[i]=x.shape[permutedAxes[i]];let meanInputValues=transposeImplCPU(values,x.shape,x.dtype,permutedAxes,newShape);meanInput=webglBackend.makeTensorInfo(newShape,x.dtype);let meanInputData=webglBackend.texData.get(meanInput.dataId);meanInputData.values=meanInputValues}else meanInput=transposeIm
  return min(a, b);
`,MINIMUM_PACKED=`
  vec4 result = vec4(min(a, b));
  vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
  `+CHECK_NAN_SNIPPET3+`
  return result;
`,minimum3=binaryKernelFunc2({opSnippet:MINIMUM,packedOpSnippet:MINIMUM_PACKED,cpuKernelImpl:minimumImplCPU}),minimumConfig2={kernelName:Minimum,backendName:"webgl",kernelFunc:minimum3},MirrorPadProgram=class{constructor(xShape,paddings,mode){this.variableNames=["x"],this.outputShape=paddings.map((p2,i)=>p2[0]+xShape[i]+p2[1]);let rank=xShape.length,dtype=getCoordsDataType(rank),start=paddings.map(p2=>p2[0]).join(","),end=paddings.map((p2,i)=>p2[0]+xShape[i]).join(","),unpackedCoords=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,rank),offset=mode==="reflect"?0:1;if(rank===1){this.userCode=`
        int start = ${start};
        int end = ${end};

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

      void main() {
        ${dtype} outC = getOutputCoords();
        for (int i = 0; i < ${rank}; i++) {
          if (outC[i] < start[i]) {
            outC[i] = start[i] * 2 - outC[i] - ${offset};
          } else if(outC[i] >= end[i]) {
            outC[i] = (end[i] - 1) * 2 - outC[i] + ${offset};
          }
        }
        ${dtype} coords = outC - start;
        setOutput(getX(${unpackedCoords}));
      }
    `}},MirrorPadPackedProgram=class{constructor(xShape,paddings,mode){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=paddings.map((p2,i)=>p2[0]+xShape[i]+p2[1]);let rank=xShape.length,dtype=getCoordsDataType(rank),start=paddings.map(p2=>p2[0]).join(","),end=paddings.map((p2,i)=>p2[0]+xShape[i]).join(","),coords2=getChannels("rc",rank),source=getChannels("source",rank),cLimit=`${coords2[rank-1]} < ${this.outputShape[rank-1]}`,innerDims=rank===1?"source":`vec2(${source.slice(-2).join()})`,offset=mode==="reflect"?0:1,mainLoop="";if(rank===1){let padSetup=`
        ${dtype} source = rc;
        if (source < start) {
          source = start * 2 - source - ${offset};
        } else if (source >= end) {
          source = (end - 1) * 2 - source + ${offset};
        }
        source -= start;
      `;mainLoop=`
        ${dtype} rc = outputLoc;
        ${padSetup}
        result[0] = getChannel(getX(${source.join()}), ${innerDims});
        ${coords2[rank-1]} += 1;
        if(${cLimit}) {
          ${padSetup}
          result[1] = getChannel(getX(${source.join()}), ${innerDims});
        }
      `}else{let padSetup=`
        ${dtype} source = rc;
        ${dtype} lt = ${dtype}(lessThan(source, start));
        ${dtype} gte = ${dtype}(greaterThanEqual(source, end));
        ${dtype} orig = 1 - (lt + gte);
        source = orig * source +
                lt * (start * 2 - source - ${offset}) +
                gte * ((end - 1) * 2 - source + ${offset});
        source -= start;
      `;mainLoop=`
        ${dtype} rc = outputLoc;
        ${padSetup}
        result[0] = getChannel(getX(${source.join()}), ${innerDims});
        ${coords2[rank-1]} += 1;
        if(${cLimit}) {
          ${padSetup}
          result[1] = getChannel(getX(${source.join()}), ${innerDims});
        }
        rc = outputLoc;
        ${coords2[rank-2]} += 1;
        if(${coords2[rank-2]} < ${this.outputShape[rank-2]}) {
          ${padSetup}
          result[2] = getChannel(getX(${source.join()}), ${innerDims});
          ${coords2[rank-1]} += 1;
          if(${cLimit}) {
            ${padSetup}
            result[3] = getChannel(getX(${source.join()}), ${innerDims});
          }
        }
      `}this.userCode=`
      const ${dtype} start = ${dtype}(${start});
      const ${dtype} end = ${dtype}(${end});

      void main() {
        ${dtype} outputLoc = getOutputCoords();
        vec4 result = vec4(0.);
        ${mainLoop}
        setOutput(result);
      }
    `}},mirrorPadKernelFunc=({inputs,backend:backend22,attrs})=>{let{x}=inputs,{paddings,mode}=attrs,program=env().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new MirrorPadPackedProgram(x.shape,paddings,mode):new MirrorPadProgram(x.shape,paddings,mode);return backend22.runWebGLProgram(program,[x],x.dtype)},mirrorPadConfig2={kernelName:MirrorPad,backendName:"webgl",kernelFunc:mirrorPadKernelFunc},MOD=`if (b == 0.0) return NAN;
  return mod(a, b);`,MOD_PACKED=`
  vec4 result = mod(a, b);
  vec4 isNaN = vec4(equal(b, vec4(0.0)));
  `+CHECK_NAN_SNIPPET3+`
  return result;
`,mod3=binaryKernelFunc2({opSnippet:MOD,packedOpSnippet:MOD_PACKED}),modConfig2={kernelName:Mod,backendName:"webgl",kernelFunc:mod3},MultinomialProgram=class{constructor(batchSize,numOutcomes,numSamples){this.variableNames=["probs"],this.outputShape=[batchSize,numSamples],this.userCode=`
      uniform float seed;

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

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

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

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

        // If no other event happened, last event happened.
        setOutput(float(${numOutcomes-1}));
      }
    `}getCustomSetupFunc(seed){return(gpgpu,webGLProgram)=>{this.seedLoc==null&&(this.seedLoc=gpgpu.getUniformLocation(webGLProgram,"seed")),gpgpu.gl.uniform1f(this.seedLoc,seed)}}},DIV=`
if (a == b) {
  return 1.0;
};
return a / b;`,DIV_PACKED=`
  // 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;
`,realDiv=binaryKernelFunc2({opSnippet:DIV,packedOpSnippet:DIV_PACKED,checkOutOfBounds:!0}),realDivConfig2={kernelName:RealDiv,backendName:"webgl",kernelFunc:realDiv},SUB="return a - b;",sub3=binaryKernelFunc2({opSnippet:SUB,packedOpSnippet:SUB,supportsComplex:!0,cpuKernelImpl:subImplCPU}),subConfig2={kernelName:Sub,backendName:"webgl",kernelFunc:sub3};function softmax3(args){let{inputs,backend:backend22,attrs}=args,{logits}=inputs,{dim}=attrs,axes=util_exports.parseAxisParam([dim],logits.shape),maxLogit=max3({inputs:{x:logits},backend:backend22,attrs:{reductionIndices:axes,keepDims:!1}}),expandedShape=backend_util_exports.expandShapeToKeepDim(maxLogit.shape,axes),maxLogitsReshaped=reshape3({inputs:{x:maxLogit},backend:backend22,attrs:{shape:expandedShape}}),a=sub3({inputs:{a:logits,b:maxLogitsReshaped},backend:backend22}),b=exp3({inputs:{x:a},backend:backend22}),sumExp=sum4({inputs:{x:b},backend:backend22,attrs:{axis:axes,keepDims:!1}}),sumExpReshaped=reshape3({inputs:{x:sumExp},backend:backend22,attrs:{shape:expandedShape}}),res=realDiv({inputs:{a:b,b:sumExpReshaped},backend:backend22});return backend22.disposeIntermediateTensorInfo(maxLogit),backend22.disposeIntermediateTensorInfo(maxLogitsReshaped),backend22.disposeIntermediateTensorInfo(a),backend22.disposeIntermediateTensorInfo(b),backend22.disposeIntermediateTensorInfo(sumExp),backend22.disposeIntermediateTensorInfo(sumExpReshaped),res}var softmaxConfig2={kernelName:Softmax,backendName:"webgl",kernelFunc:softmax3};function multinomial3(args){let{inputs,backend:backend22,attrs}=args,{logits}=inputs,{numSamples,seed,normalized}=attrs,probs=normalized?logits:softmax3({inputs:{logits},backend:backend22,attrs:{dim:logits.shape.length-1}}),batchSize=probs.shape[0],numOutcomes=probs.shape[1],program=new MultinomialProgram(batchSize,numOutcomes,numSamples),customSetup=program.getCustomSetupFunc(seed),res=backend22.runWebGLProgram(program,[probs],"int32",customSetup);return normalized||backend22.disposeIntermediateTensorInfo(probs),res}var multinomialConfig2={kernelName:Multinomial,backendName:"webgl",kernelFunc:multinomial3},NEG="return -x;";function neg3(args){let{inputs,backend:backend22}=args,{x}=inputs;if(backend22.shouldExecuteOnCPU([x])){let xData=backend22.texData.get(x.dataId),[outValues,newShape]=negImplCPU(xData.values,x.shape,x.dtype);return backend22.makeTensorInfo(newShape,x.dtype,outValues)}let program;return env().getBool("WEBGL_PACK_UNARY_OPERATIONS")?program=new UnaryOpPackedProgram(x.shape,NEG):program=new UnaryOpProgram(x.shape,NEG),backend22.runWebGLProgram(program,[x],x.dtype)}var negConfig2={kernelName:Neg,backendName:"webgl",kernelFunc:neg3},nonMaxSuppressionV3Impl3=kernel_impls_exports.nonMaxSuppressionV3Impl;function nonMaxSuppressionV32(args){backend_util_exports.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs,backend:backend22,attrs}=args,{boxes,scores}=inputs,{maxOutputSize,iouThreshold,scoreThreshold}=attrs,boxesVals=backend22.readSync(boxes.dataId),scoresVals=backend22.readSync(scores.dataId),{selectedIndices}=nonMaxSuppressionV3Impl3(boxesVals,scoresVals,maxOutputSize,iouThreshold,scoreThreshold);return backend22.makeTensorInfo([selectedIndices.length],"int32",new Int32Array(selectedIndices))}var nonMaxSuppressionV3Config2={kernelName:NonMaxSuppressionV3,backendName:"webgl",kernelFunc:nonMaxSuppressionV32},nonMaxSuppressionV4Impl3=kernel_impls_exports.nonMaxSuppressionV4Impl;function nonMaxSuppressionV42(args){backend_util_exports.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs,backend:backend22,attrs}=args,{boxes,scores}=inputs,{maxOutputSize,iouThreshold,scoreThreshold,padToMaxOutputSize}=attrs,boxesVals=backend22.readSync(boxes.dataId),scoresVals=backend22.readSync(scores.dataId),{selectedIndices,validOutputs}=nonMaxSuppressionV4Impl3(boxesVals,scoresVals,maxOutputSize,iouThreshold,scoreThreshold,padToMaxOutputSize);return[backend22.makeTensorInfo([selectedIndices.length],"int32",new Int32Array(selectedIndices
      void main() {
        ivec2 coords = getOutputCoords();
        int index = round(getIndices(coords.x));
        setOutput(mix(float(${offValue}), float(${onValue}),
                      float(index == coords.y)));
      }
    `}},oneHot3=args=>{let{inputs,backend:backend22,attrs}=args,{indices}=inputs,{depth,onValue,offValue}=attrs,indicesSize=util_exports.sizeFromShape(indices.shape),program=new OneHotProgram(indicesSize,depth,onValue,offValue),reshaped=reshape3({inputs:{x:indices},backend:backend22,attrs:{shape:[indicesSize]}}),result=backend22.runWebGLProgram(program,[reshaped],indices.dtype);backend22.disposeIntermediateTensorInfo(reshaped);let outShape=[...indices.shape,depth],out=reshape3({inputs:{x:result},backend:backend22,attrs:{shape:outShape}});return backend22.disposeIntermediateTensorInfo(result),out},oneHotConfig2={kernelName:OneHot,backendName:"webgl",kernelFunc:oneHot3};function zerosLike3(args){let{inputs,backend:backend22}=args,{x}=inputs;if(x.dtype==="complex64"){let realPart=real3({inputs:{input:x},backend:backend22}),r=zerosLike3({inputs:{x:realPart},backend:backend22}),imagPart=imag3({inputs:{input:x},backend:backend22}),i=zerosLike3({inputs:{x:imagPart},backend:backend22}),result=complex3({inputs:{real:r,imag:i},backend:backend22});return backend22.disposeIntermediateTensorInfo(realPart),backend22.disposeIntermediateTensorInfo(r),backend22.disposeIntermediateTensorInfo(imagPart),backend22.disposeIntermediateTensorInfo(i),result}else return fill3({attrs:{shape:x.shape,dtype:x.dtype,value:x.dtype==="string"?"":0},backend:backend22})}var zerosLikeConfig2={kernelName:ZerosLike,backendName:"webgl",kernelFunc:zerosLike3};function onesLike3(args){let{inputs,backend:backend22}=args,{x}=inputs;if(x.dtype==="string")throw new Error("onesLike is not supported under string dtype");if(x.dtype==="complex64"){let realPart=real3({inputs:{input:x},backend:backend22}),r=onesLike3({inputs:{x:realPart},backend:backend22}),imagPart=imag3({inputs:{input:x},backend:backend22}),i=zerosLike3({inputs:{x:imagPart},backend:backend22}),result=complex3({inputs:{real:r,imag:i},backend:backend22});return backend22.disposeIntermediateTensorInfo(realPart),backend22.disposeIntermediateTensorInfo(r),backend22.disposeIntermediateTensorInfo(imagPart),backend22.disposeIntermediateTensorInfo(i),result}else return fill3({attrs:{shape:x.shape,dtype:x.dtype,value:1},backend:backend22})}var onesLikeConfig2={kernelName:OnesLike,backendName:"webgl",kernelFunc:onesLike3};function pack2(args){let{inputs,backend:backend22,attrs}=args,{axis}=attrs;if(inputs.length===1)return expandDims3({inputs:{input:inputs[0]},backend:backend22,attrs:{dim:axis}});let shape=inputs[0].shape,dtype=inputs[0].dtype;inputs.forEach(t=>{util_exports.assertShapesMatch(shape,t.shape,"All tensors passed to stack must have matching shapes"),util_exports.assert(dtype===t.dtype,()=>"All tensors passed to stack must have matching dtypes")});let intermediateTensorInfos=[],expandedTensors=inputs.map(t=>{let expandedT=expandDims3({inputs:{input:t},backend:backend22,attrs:{dim:axis}});return intermediateTensorInfos.push(expandedT),expandedT}),result=concat3({inputs:expandedTensors,backend:backend22,attrs:{axis}});return intermediateTensorInfos.forEach(t=>backend22.disposeIntermediateTensorInfo(t)),result}var packConfig2={kernelName:Pack,backendName:"webgl",kernelFunc:pack2},PadProgram=class{constructor(xShape,paddings,constantValue){this.variableNames=["x"],this.outputShape=paddings.map((p2,i)=>p2[0]+xShape[i]+p2[1]);let rank=xShape.length,type=getCoordsDataType(rank),start=paddings.map(p2=>p2[0]).join(","),end=paddings.map((p2,i)=>p2[0]+xShape[i]).join(","),unpackedCoords=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,rank);if(rank===1){this.userCode=`
        int start = ${start};
        int end = ${end};

        void main() {
          int outC = getOutputCoords();
          if (outC < start || outC >= end) {
            setOutput(float(${constantValue}));
          } else {
            setOutput(getX(outC - start));
          }
        }
      `;return}this.userCode=`
      ${type} start = ${type}(${start});
      ${type} end = ${type}(${end});

      void main() {
        ${type} outC = getOutputCoords();
        if (any(lessThan(outC, start)) || any(greaterThanEqual(outC, end))) {
          setOutput(float(${constantValue}));
        } else {
          ${type} coords = outC - start;
          setOutput(getX(${unpackedCoords}));
        }
      }
    `}},PadPackedProgram=class{constructor(xShape,paddings,constantValue){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=paddings.map((p2,i)=>p2[0]+xShape[i]+p2[1]);let rank=xShape.length,dtype=getCoordsDataType(rank),start=paddings.map(p2=>p2[0]).join(","),end=paddings.map((p2,i)=>p2[0]+xShape[i]).join(","),coords2=getChannels("rc",rank),source=getChannels("source",rank),cLimit=`${coords2[rank-1]} < ${this.outputShape[rank-1]}`,innerDims=rank===1?"source":`vec2(${source.slice(-2).join()})`,componentSetup=[`${dtype} rc = outputLoc;`,`${coords2[rank-1]} += 1;
       if(${cLimit}) {
      `,rank===1?"":`}
       rc = outputLoc;
       ${coords2[rank-2]} += 1;
       if(${coords2[rank-2]} < ${this.outputShape[rank-2]}) {`,rank===1?"":`  ${coords2[rank-1]} += 1;
         if(${cLimit}) {`],paddingArea=rank===1?"rc < start || rc >= end":"any(lessThan(rc, start)) || any(greaterThanEqual(rc, end))",mainLoop="";for(let i=0,j=rank===1?2:4;i<j;i++)mainLoop+=`
        ${componentSetup[i]}
        if (${paddingArea}) {
          result[${i}] = float(${constantValue});
        } else {
          ${dtype} source = rc - start;
          result[${i}] = getChannel(getX(${source.join()}), ${innerDims});
        }
      `;mainLoop+=rank===1?"} ":"}}",this.userCode=`
      const ${dtype} start = ${dtype}(${start});
      const ${dtype} end = ${dtype}(${end});

      void main() {
        ${dtype} outputLoc = getOutputCoords();
        vec4 result = vec4(0.);
        ${mainLoop}
        setOutput(result);
      }
    `}},padV22=args=>{let{inputs,backend:backend22,attrs}=args,{x}=inputs,{paddings,constantValue}=attrs,program=env().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new PadPackedProgram(x.shape,paddings,constantValue):new PadProgram(x.shape,paddings,constantValue);return backend22.runWebGLProgram(program,[x],x.dtype)},padV2Config2={kernelName:PadV2,backendName:"webgl",kernelFunc:padV22},POW=`
  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);
`,POW_PACKED=`
  // 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));
  `+CHECK_NAN_SNIPPET3+`
  return result;
`,pow3=binaryKernelFunc2({opSnippet:POW,packedOpSnippet:POW_PACKED}),powConfig2={kernelName:Pow,backendName:"webgl",kernelFunc:pow3};function prod3(args){let{inputs,backend:backend22,attrs}=args,{x}=inputs,{axis,keepDims}=attrs,xRank=x.shape.length,toDispose=[],origAxes=util_exports.parseAxisParam(axis,x.shape),axes=origAxes,permutedAxes=backend_util_exports.getAxesPermutation(axes,xRank),permutedX=x;permutedAxes!=null&&(permutedX=transpose3({inputs:{x},backend:backend22,attrs:{perm:permutedAxes}}),axes=backend_util_exports.getInnerMostAxes(axes.length,xRank),toDispose.push(permutedX)),backend_util_exports.assertAxesAreInnerMostDims("prod",axes,xRank);let res;if(backend22.shouldExecuteOnCPU([permutedX])){let xVals=backend22.texData.get(permutedX.dataId).values,{outVals,outShape,outDtype}=prodImplCPU(permutedX.shape,permutedX.dtype,xVals,axes);res=backend22.makeTensorInfo(outShape,outDtype,outVals)}else{let[outShape,reduceShape]=backend_util_exports.computeOutAndReduceShapes(permutedX.shape,axes),inSize=util_exports.sizeFromShape(reduceShape),a2D=reshape3({inputs:{x:permutedX},backend:backend22,attrs:{shape:[-1,inSize]}}),outputDType=sumOutType(x.dtype),reduced=reduce(a2D,outputDType,"prod",backend22);res=reshape3({inputs:{x:reduced},backend:backend22,attrs:{shape:outShape}}),toDispose.push(a2D),toDispose.push(reduced)}if(keepDims){toDispose.push(res);let newShape=backend_util_exports.expandShapeToKeepDim(res.shape,origAxes);res=reshape3({inputs:{x:res},backend:backend22,attrs:{shape:newShape}})}return toDispose.forEach(t=>backend22.disposeIntermediateTensorInfo(t)),res}var prodConfig2={kernelName:Prod,backendName:"webgl",kernelFunc:prod3},range3=args=>{let{backend:backend22,attrs}=args,{start,stop,step:step4,dtype}=attrs,values=rangeImplCPU(start,stop,step4,dtype);return backend22.makeTensorInfo([values.length],dtype,values)},rangeConfig2={kernelName:Range,backendName:"webgl",kernelFunc:range3},RECIPROCAL="return 1.0 / x;",reciprocal3=unaryKernelFunc2({opSnippet:RECIPROCAL}),reciprocalConfig2={kernelName:Reciprocal,backendName:"webgl",kernelFunc:reciprocal3},RELU3=CHECK_NAN_SNIPPET+`
  return (x < 0.0) ? 0.0 : x;
`,RELU_PACKED=`
  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;
`,relu3=unaryKernelFunc2({opSnippet:RELU3,packedOpSnippet:RELU_PACKED}),reluConfig2={kernelName:Relu,backendName:"webgl",kernelFunc:relu3},RELU63=CHECK_NAN_SNIPPET+`
  return (x < 0.0) ? 0.0 : min(6.0, x);
`,RELU6_PACKED=`
  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;
`,relu63=unaryKernelFunc2({opSnippet:RELU63,packedOpSnippet:RELU6_PACKED}),relu6Config2={kernelName:Relu6,backendName:"webgl",kernelFunc:relu63},ResizeBilinearProgram=class{constructor(inputShape,newHeight,newWidth,alignCorners,halfPixelCenters){this.variableNames=["A"],this.outputShape=[];let[batch,oldHeight,oldWidth,depth]=inputShape;this.outputShape=[batch,newHeight,newWidth,depth];let effectiveInSize=[alignCorners&&newHeight>1?oldHeight-1:oldHeight,alignCorners&&newWidth>1?oldWidth-1:oldWidth],effectiveOutSize=[alignCorners&&newHeight>1?newHeight-1:newHeight,alignCorners&&newWidth>1?newWidth-1:newWidth],sourceFracIndexRC;halfPixelCenters?sourceFracIndexRC="(vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC - vec2(0.5)":sourceFracIndexRC="vec2(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
      const vec2 effectiveInputOverOutputRatioRC = vec2(
          ${effectiveInSize[0]/effectiveOutSize[0]},
          ${effectiveInSize[1]/effectiveOutSize[1]});
      const vec2 inputShapeRC = vec2(${oldHeight}.0, ${oldWidth}.0);

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

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

        // 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);
      }
    `}},ResizeBilinearPackedProgram=class{constructor(inputShape,newHeight,newWidth,alignCorners,halfPixelCenters){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[];let[batch,oldHeight,oldWidth,depth]=inputShape;this.outputShape=[batch,newHeight,newWidth,depth];let effectiveInSize=[alignCorners&&newHeight>1?oldHeight-1:oldHeight,alignCorners&&newWidth>1?oldWidth-1:oldWidth],effectiveOutSize=[alignCorners&&newHeight>1?newHeight-1:newHeight,alignCorners&&newWidth>1?newWidth-1:newWidth],sourceFracIndexRC;halfPixelCenters?sourceFracIndexRC="(vec3(yRC) + vec3(0.5)) * effectiveInputOverOutputRatioRC - vec3(0.5)":sourceFracIndexRC="vec3(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
      const vec3 effectiveInputOverOutputRatioRC = vec3(
          ${effectiveInSize[0]/effectiveOutSize[0]},
          ${effectiveInSize[1]/effectiveOutSize[1]},
          ${effectiveInSize[1]/effectiveOutSize[1]});
      const vec3 inputShapeRC = vec3(${oldHeight}.0, ${oldWidth}.0,
                                     ${oldWidth}.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 = ${sourceFracIndexRC};

        // 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 < ${depth-1};
        bool hasNextRow = coords.z < ${newWidth-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 resizeBilinear3(args){let{inputs,backend:backend22,attrs}=args,{images}=inputs,{alignCorners,halfPixelCenters,size}=attrs,[newHeight,newWidth]=size,program=env().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new ResizeBilinearPackedProgram(images.shape,newHeight,newWidth,alignCorners,halfPixelCenters):new ResizeBilinearProgram(images.shape,newHeight,newWidth,alignCorners,halfPixelCenters);return backend22.runWebGLProgram(program,[images],"float32")}var resizeBilinearConfig2={kernelName:ResizeBilinear,backendName:"webgl",kernelFunc:resizeBilinear3},ResizeBilinearBackpropProgram=class{constructor(dyShape,inputShape,alignCorners){this.variableNames=["dy"],this.outputShape=[],this.outputShape=inputShape;let[,xHeight,xWidth]=inputShape,[,yHeight,yWidth]=dyShape,effectiveXSize=[alignCorners&&yHeight>1?xHeight-1:xHeight,alignCorners&&yWidth>1?xWidth-1:xWidth],effectiveYSize=[alignCorners&&yHeight>1?yHeight-1:yHeight,alignCorners&&yWidth>1?yWidth-1:yWidth],heightScale=effectiveXSize[0]/effectiveYSize[0],widthScale=effectiveXSize[1]/effectiveYSize[1],invHeightScale=1/heightScale,invWidthScale=1/widthScale,winHeight=Math.ceil(invHeightScale)*2+2,winWidth=Math.ceil(invWidthScale)*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(${heightScale});
        const float widthScale = float(${widthScale});

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

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

        // 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 >= ${yHeight}) {
            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 >= ${yWidth}) {
              continue;
            }

            float dxR = float(dyR) * heightScale;
            int topDxRIndex = int(floor(dxR));
            int bottomDxRIndex = int(min(ceil(dxR), ${xHeight-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), ${xWidth-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 resizeBilinearGrad2(args){let{inputs,backend:backend22,attrs}=args,{images,dy}=inputs,{alignCorners}=attrs,program=new ResizeBilinearBackpropProgram(dy.shape,images.shape,alignCorners);return backend22.runWebGLProgram(program,[dy],dy.dtype)}var resizeBilinearGradConfig3={kernelName:ResizeBilinearGrad,backendName:"webgl",kernelFunc:resizeBilinearGrad2},ResizeNearestNeighborProgram=class{constructor(inputShape,newHeight,newWidth,alignCorners,halfPixelCenters){this.variableNames=["A"],this.outputShape=[];let[batch,oldHeight,oldWidth,depth]=inputShape;this.outputShape=[batch,newHeight,newWidth,depth];let effectiveInSize=[alignCorners&&newHeight>1?oldHeight-1:oldHeight,alignCorners&&newWidth>1?oldWidth-1:oldWidth],effectiveOutSize=[alignCorners&&newHeight>1?newHeight-1:newHeight,alignCorners&&newWidth>1?newWidth-1:newWidth],roundBase=alignCorners?"0.5":"0.0",sourceFracIndexRC;halfPixelCenters?sourceFracIndexRC="max((vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC, vec2(0.0))":sourceFracIndexRC="vec2(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
      const vec2 effectiveInputOverOutputRatioRC = vec2(
          ${effectiveInSize[0]/effectiveOutSize[0]},
          ${effectiveInSize[1]/effectiveOutSize[1]});
      const vec2 inputShapeRC = vec2(${oldHeight}.0, ${oldWidth}.0);

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

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

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

        setOutput(newValue);
      }
    `}};function resizeNearestNeighbor3(args){let{inputs,backend:backend22,attrs}=args,{images}=inputs,{alignCorners,halfPixelCenters,size}=attrs,[newHeight,newWidth]=size,program=new ResizeNearestNeighborProgram(images.shape,newHeight,newWidth,alignCorners,halfPixelCenters);return backend22.runWebGLProgram(program,[images],images.dtype)}var resizeNearestNeighborConfig2={kernelName:ResizeNearestNeighbor,backendName:"webgl",kernelFunc:resizeNearestNeighbor3},ResizeNearestNeigborBackpropProgram=class{constructor(dyShape,inputShape,alignCorners){this.variableNames=["dy"],this.outputShape=[],this.outputShape=inputShape;let[,xHeight,xWidth]=inputShape,[,yHeight,yWidth]=dyShape,effectiveXSize=[alignCorners&&yHeight>1?xHeight-1:xHeight,alignCorners&&yWidth>1?xWidth-1:xWidth],effectiveYSize=[alignCorners&&yHeight>1?yHeight-1:yHeight,alignCorners&&yWidth>1?yWidth-1:yWidth],heightScale=effectiveXSize[0]/effectiveYSize[0],widthScale=effectiveXSize[1]/effectiveYSize[1],invHeightScale=1/heightScale,invWidthScale=1/widthScale,winHeight=Math.ceil(invHeightScale)*2+2,winWidth=Math.ceil(invWidthScale)*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(${heightScale});
        const float widthScale = float(${widthScale});

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

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

        // 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 >= ${yHeight}) {
            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 >= ${yWidth}) {
              continue;
            }

            float sourceFracRow =
              float(${effectiveXSize[0]}) *
                (float(dyR) / float(${effectiveYSize[0]}));

            float sourceFracCol =
                float(${effectiveXSize[1]}) *
                  (float(dyC) / float(${effectiveYSize[1]}));

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

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

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

        setOutput(accumulator);
      }
    `}};function resizeNearestNeighborGrad2(args){let{inputs,backend:backend22,attrs}=args,{images,dy}=inputs,{alignCorners}=attrs,program=new ResizeNearestNeigborBackpropProgram(dy.shape,images.shape,alignCorners);return backend22.runWebGLProgram(program,[dy],dy.dtype)}var resizeNearestNeighborGradConfig3={kernelName:ResizeNearestNeighborGrad,backendName:"webgl",kernelFunc:resizeNearestNeighborGrad2},ReverseProgram=class{constructor(xShape,axis){this.variableNames=["x"];let rank=xShape.length;if(rank>4)throw new Error(`WebGL backend: Reverse of rank-${rank} tensor is not yet supported`);if(this.outputShape=xShape,rank===1){this.userCode=`
        void main() {
          int coord = getOutputCoords();
          setOutput(getX(${xShape[0]} - coord - 1));
        }
      `;return}let getInCoord=i=>axis.indexOf(i)!==-1&&xShape[i]!==1?`${xShape[i]} - coords[${i}] - 1`:`coords[${i}]`,inCoords=xShape.map((_,i)=>getInCoord(i)).join(","),type=getCoordsDataType(rank);this.userCode=`
      void main() {
        ${type} coords = getOutputCoords();
        setOutput(getX(${inCoords}));
      }
    `}},ReversePackedProgram=class{constructor(xShape,axis){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0;let rank=xShape.length;if(rank>4)throw new Error(`WebGL backend: Reverse of rank-${rank} tensor is not yet supported`);this.outputShape=xShape;let channels=getChannels("rc",rank),nextColumn=`${channels[rank-1]} + 1 < ${this.outputShape[rank-1]}`,nextRow=`${channels[rank-2]} + 1 < ${this.outputShape[rank-2]}`,type=getCoordsDataType(rank);rank===1?this.userCode=`
        void main(){
          int rc = getOutputCoords();
          vec4 result = vec4(0.);
          result.r = getChannel(getX(${xShape[0]} - rc - 1),
            ${xShape[0]} - rc - 1);
          if(${nextColumn}){
              result.g = getChannel(getX(${xShape[0]} - (rc  + 1) - 1),
                ${xShape[0]} - (rc  + 1) - 1);
          }
          setOutput(result);
        }
      `:this.userCode=`
        void main() {
          ${type} rc = getOutputCoords();
          vec4 result = vec4(0.);
          result.r = ${getR(channels.slice())};
          if(${nextColumn}){
            result.g = ${getG(channels.slice())};
          }
          if(${nextRow}) {
            result.b = ${getB(channels.slice())};
            if(${nextColumn}) {
              result.a = ${getA(channels.slice())};
            }
          }
          setOutput(result);
        }
    `;function getR(channels2){return getChannel(channels2)}function getG(channels2){return channels2[rank-1]="("+channels2[rank-1]+" + 1)",getChannel(channels2)}function getB(channels2){return channels2[rank-2]="("+channels2[rank-2]+" + 1)",getChannel(channels2)}function getA(channels2){return channels2[rank-1]="("+channels2[rank-1]+" + 1)",channels2[rank-2]="("+channels2[rank-2]+" + 1)",getChannel(channels2)}function getChannel(channels2){let inCoordsArray=xShape.map((_,i)=>getInCoord(i,channels2)),inCoords=inCoordsArray.join(","),innerDims=inCoordsArray.slice(-2).join(",");return`getChannel(getX(${inCoords}), vec2(${innerDims}))`}function getInCoord(i,channels1){return axis.indexOf(i)!==-1&&xShape[i]!==1?`${xShape[i]} - ${channels1[i]} - 1`:`${channels1[i]}`}}};function reverse3(args){let{inputs,backend:backend22,attrs}=args,{x}=inputs,{dims}=attrs,xRank=x.shape.length,$dims=util_exports.parseAxisParam(dims,x.shape);if(xRank===0)return identity2({inputs:{x},backend:backend22});let program=env().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new ReversePackedProgram(x.shape,$dims):new ReverseProgram(x.shape,$dims);return backend22.runWebGLProgram(program,[x],x.dtype)}var reverseConfig2={kernelName:Reverse,backendName:"webgl",kernelFunc:reverse3},RotateProgram=class{constructor(imageShape,radians,fillValue,center){this.variableNames=["Image"],this.outputShape=[];let imageHeight=imageShape[1],imageWidth=imageShape[2],sinFactor=Math.sin(radians).toFixed(3),cosFactor=Math.cos(radians).toFixed(3);this.outputShape=imageShape;let[centerX,centerY]=backend_util_exports.getImageCenter(center,imageHeight,imageWidth),centerXString=centerX.toFixed(3),centerYString=centerY.toFixed(3),fillSnippet="";typeof fillValue=="number"?fillSnippet=`float outputValue = ${fillValue.toFixed(2)};`:fillSnippet=`
        vec3 fill = vec3(${fillValue.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) - ${centerXString}) * ${cosFactor} - (float(y) - ${centerYString}) * ${sinFactor};
          float coordYFloat = (float(x) - ${centerXString}) * ${sinFactor} + (float(y) - ${centerYString}) * ${cosFactor};
          int coordX = int(round(coordXFloat + ${centerXString}));
          int coordY = int(round(coordYFloat + ${centerYString}));
          ${fillSnippet}
          if(coordX >= 0 && coordX < ${imageWidth} && coordY >= 0 && coordY < ${imageHeight}) {
            outputValue = getImage(coords[0], coordY, coordX, coords[3]);
          }
          setOutput(outputValue);
        }
    `}},rotateWithOffsetConfig2={kernelName:RotateWithOffset,backendName:"webgl",kernelFunc:({inputs,attrs,backend:backend22})=>{let{image:image3}=inputs,{radians,fillValue,center}=attrs,webglBackend=backend22,program=new RotateProgram(image3.shape,radians,fillValue,center);return webglBackend.runWebGLProgram(program,[image3],image3.dtype)}},ROUND=`
  // OpenGL ES does not support round function.
  // The algorithm is based on banker's rounding.
  float base = floor(x);
  if ((x - base) < 0.5) {
    return floor(x);
  } else if ((x - base) > 0.5) {
    return ceil(x);
  } else {
    if (mod(base, 2.0) == 0.0) {
      return base;
    } else {
      return base + 1.0;
    }
  }
`,round4=unaryKernelFunc2({opSnippet:ROUND}),roundConfig2={kernelName:Round,backendName:"webgl",kernelFunc:round4},RSQRT="return inversesqrt(x);",rsqrt3=unaryKernelFunc2({opSnippet:RSQRT,cpuKernelImpl:rsqrtImplCPU}),rsqrtConfig2={kernelName:Rsqrt,backendName:"webgl",kernelFunc:rsqrt3},ScatterProgram=class{constructor(updateSize,sliceDim,indicesRank,updatesRank,strides,shape,summingDupeIndex=!0){this.variableNames=["updates","indices","defaultValue"],this.outputShape=shape;let stridesType=getCoordsDataType(strides.length),dtype=getCoordsDataType(shape.length),indicesString="";indicesRank===1?indicesString="i":indicesRank===2&&(indicesString="i, j");let indicesSnippet=`getIndices(${indicesString})`,updatesString="";updatesRank===1?updatesString="i":updatesRank===2&&(updatesString="i, coords[1]");let updatesSnippet=`getUpdates(${updatesString})`,strideString=sliceDim>1?"strides[j]":"strides";this.userCode=`
        ${stridesType} strides = ${stridesType}(${strides});

        void main() {
          ${dtype} coords = getOutputCoords();
          float sum = 0.0;
          bool found = false;
          for (int i = 0; i < ${updateSize}; i++) {
            int flattenedIndex = 0;
            for (int j = 0; j < ${sliceDim}; j++) {
              int index = round(${indicesSnippet});
              flattenedIndex += index * ${strideString};
            }
            if (flattenedIndex == coords[0]) {
              sum += ${updatesSnippet};
              found = true;
            }
          }
          setOutput(mix(getDefaultValue(), sum, float(found)));
        }
      `}};function scatterNd2(args){let{inputs,backend:backend22,attrs}=args,{indices,updates}=inputs,{shape}=attrs,{sliceRank,numUpdates,sliceSize,strides,outputSize}=backend_util_exports.calculateShapes(updates,indices,shape),flattenShape=[outputSize/sliceSize,sliceSize];if(outputSize===0)return backend22.makeTensorInfo(shape,indices.dtype);let flattenIndices=reshape3({inputs:{x:indices},backend:backend22,attrs:{shape:[numUpdates,sliceRank]}}),flattenX=reshape3({inputs:{x:updates},backend:backend22,attrs:{shape:[numUpdates,sliceSize]}}),defaultValue=backend22.makeTensorInfo([],"float32",new Float32Array([0])),program=new ScatterProgram(numUpdates,sliceRank,flattenIndices.shape.length,flattenX.shape.length,strides,flattenShape),res=backend22.runWebGLProgram(program,[flattenX,flattenIndices,defaultValue],flattenX.dtype),reshaped=reshape3({inputs:{x:res},backend:backend22,attrs:{shape}});return backend22.disposeIntermediateTensorInfo(flattenIndices),backend22.disposeIntermediateTensorInfo(flattenX),backend22.disposeIntermediateTensorInfo(res),backend22.disposeIntermediateTensorInfo(defaultValue),reshaped}var scatterNdConfig2={kernelName:ScatterNd,backendName:"webgl",kernelFunc:scatterNd2},SelectProgram=class{constructor(cRank,shape,rank){this.variableNames=["c","a","b"],this.outputShape=shape;let cCoords,abCoords;if(rank>4)throw Error(`Where for rank ${rank} is not yet supported`);if(rank===1)abCoords="resRC",cCoords="resRC";else{let currentCoords=["resRC.x","resRC.y","resRC.z","resRC.w"],cCoordVars=[],abCoordVars=[];for(let i=0;i<shape.length;i++)abCoordVars.push(`${currentCoords[i]}`),i<cRank&&cCoordVars.push(`${currentCoords[i]}`);cCoords=cCoordVars.join(),abCoords=abCoordVars.join()}let dtype=getCoordsDataType(rank);this.userCode=`
      void main() {
        ${dtype} resRC = getOutputCoords();
        float cVal = getC(${cCoords});
        if (cVal >= 1.0) {
          setOutput(getA(${abCoords}));
        } else {
          setOutput(getB(${abCoords}));
        }
      }
    `}};function select2(args){let{inputs,backend:backend22}=args,{condition,t,e}=inputs,program=new SelectProgram(condition.shape.length,t.shape,t.shape.length);return backend22.runWebGLProgram(program,[condition,t,e],upcastType(t.dtype,e.dtype))}var selectConfig2={kernelName:Select,backendName:"webgl",kernelFunc:select2},SELU=`
  // Stable and Attracting Fixed Point (0, 1) for Normalized Weights.
  // see: https://arxiv.org/abs/1706.02515
  float scaleAlpha = ${backend_util_exports.SELU_SCALEALPHA};
  float scale = ${backend_util_exports.SELU_SCALE};
  return (x >= 0.0) ? scale * x : scaleAlpha * (exp(x) - 1.0);
`,selu3=unaryKernelFunc2({opSnippet:SELU}),seluConfig2={kernelName:Selu,backendName:"webgl",kernelFunc:selu3},SIGMOID="return 1.0 / (1.0 + exp(-1.0 * x));",sigmoid3=unaryKernelFunc2({opSnippet:SIGMOID}),sigmoidConfig2={kernelName:Sigmoid,backendName:"webgl",kernelFunc:sigmoid3},SIGN=`
  if (isnan(x)) { return 0.0; }
  return sign(x);
`,sign3=unaryKernelFunc2({opSnippet:SIGN}),signConfig2={kernelName:Sign,backendName:"webgl",kernelFunc:sign3},SIN=CHECK_NAN_SNIPPET_UNARY+`
  return sin(x);
`,sin3=unaryKernelFunc2({opSnippet:SIN}),sinConfig2={kernelName:Sin,backendName:"webgl",kernelFunc:sin3},SINH=`
  float e2x = exp(x);
  return (e2x - 1.0 / e2x) / 2.0;
`,sinh3=unaryKernelFunc2({opSnippet:SINH}),sinhConfig2={kernelName:Sinh,backendName:"webgl",kernelFunc:sinh3},SOFTPLUS=`
  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;
`,softplus3=unaryKernelFunc2({opSnippet:SOFTPLUS}),softplusConfig2={kernelName:Softplus,backendName:"webgl",kernelFunc:softplus3},spaceToBatchND3=args=>{let{inputs,backend:backend22,attrs}=args,{x}=inputs,{blockShape,paddings}=attrs;util_exports.assert(x.shape.length<=4,()=>"spaceToBatchND for rank > 4 with a WebGL backend not implemented yet");let prod5=blockShape.reduce((a,b)=>a*b),completePaddings=[[0,0]];completePaddings.push(...paddings);for(let i=1+blockShape.length;i<x.shape.length;++i)completePaddings.push([0,0]);let toDispose=[],paddedX=padV22({inputs:{x},backend:backend22,attrs:{paddings:completePaddings,constantValue:0}}),reshapedPaddedShape=backend_util_exports.getReshaped(paddedX.shape,blockShape,prod5,!1),permutedReshapedPaddedPermutation=backend_util_exports.getPermuted(reshapedPaddedShape.length,blockShape.length,!1),flattenShape=backend_util_exports.getReshapedPermuted(paddedX.shape,blockShape,prod5,!1),reshapedPaddedX=reshape3({inputs:{x:paddedX},backend:backend22,attrs:{shape:reshapedPaddedShape}}),paddedXT=transpose3({inputs:{x:reshapedPaddedX},backend:backend22,attrs:{perm:permutedReshapedPaddedPermutation}}),result=reshape3({inputs:{x:paddedXT},backend:backend22,attrs:{shape:flattenShape}});return toDispose.push(paddedX),toDispose.push(reshapedPaddedX),toDispose.push(paddedXT),toDispose.forEach(t=>backend22.disposeIntermediateTensorInfo(t)),result},spaceToBatchNDConfig2={kernelName:SpaceToBatchND,backendName:"webgl",kernelFunc:spaceToBatchND3};function sparseToDense3(args){let{inputs,backend:backend22,attrs}=args,{sparseIndices,sparseValues,defaultValue}=inputs,{outputShape}=attrs,{sliceRank,numUpdates,strides,outputSize}=backend_util_exports.calculateShapes(sparseValues,sparseIndices,outputShape),sumDupeIndices=!1,program=new ScatterProgram(numUpdates,sliceRank,sparseIndices.shape.length,sparseValues.shape.length,strides,[outputSize,1],sumDupeIndices),res=backend22.runWebGLProgram(program,[sparseValues,sparseIndices,defaultValue],sparseValues.dtype),reshaped=reshape3({inputs:{x:res},backend:backend22,attrs:{shape:outputShape}});return backend22.disposeIntermediateTensorInfo(res),reshaped}var sparseToDenseConfig2={kernelName:SparseToDense,backendName:"webgl",kernelFunc:sparseToDense3};function splitV2(args){let{inputs,backend:backend22,attrs}=args,{x}=inputs,{numOrSizeSplits,axis}=attrs,$axis=util_exports.parseAxisParam(axis,x.shape)[0],splitSizes=backend_util_exports.prepareSplitSize(x,numOrSizeSplits,$axis),xRank=x.shape.length,begin=new Array(xRank).fill(0),size=x.shape.slice();return splitSizes.map(s=>{let sliceSize=[...size];sliceSize[$axis]=s;let sliceT=slice3({inputs:{x},backend:backend22,attrs:{begin,size:sliceSize}});return begin[$axis]+=s,sliceT})}var splitVConfig2={kernelName:SplitV,backendName:"webgl",kernelFunc:splitV2},SQRT="return sqrt(x);",sqrt3=unaryKernelFunc2({opSnippet:SQRT}),sqrtConfig2={kernelName:Sqrt,backendName:"webgl",kernelFunc:sqrt3},SQUARE="return x * x;",square2=unaryKernelFunc2({opSnippet:SQUARE}),squareConfig2={kernelName:Square,backendName:"webgl",kernelFunc:square2},SQUARED_DIFFERENCE="return (a - b) * (a - b);",squaredDifference3=binaryKernelFunc2({opSnippet:SQUARED_DIFFERENCE,packedOpSnippet:SQUARED_DIFFERENCE}),squaredDifferenceConfig2={kernelName:SquaredDifference,backendName:"webgl",kernelFunc:squaredDifference3};function step3({inputs,attrs,backend:backend22}){let{x}=inputs,opSnippet=CHECK_NAN_SNIPPET+`
    return x > 0.0 ? 1.0 : float(${attrs.alpha});
  `,program=new UnaryOpProgram(x.shape,opSnippet);return backend22.runWebGLProgram(program,[x],x.dtype)}var stepConfig2={kernelName:Step,backendName:"webgl",kernelFunc:step3},StridedSliceProgram=class{constructor(begin,strides,size){this.variableNames=["x"],this.outputShape=size;let rank=size.length,inputDtype=getCoordsDataType(size.length),dtype=getCoordsDataType(size.length),newCoords="";if(rank===1)newCoords="coords * strides + begin";else{let outputAxis=0;newCoords=size.map((_,i)=>(outputAxis++,size.length===1?`coords * strides[${i}] + begin[${i}]`:`coords[${outputAxis-1}] * strides[${i}] + begin[${i}]`)).join(",")}this.userCode=`
      ${inputDtype} begin = ${inputDtype}(${begin});
      ${inputDtype} strides = ${inputDtype}(${strides});

      void main() {
        ${dtype} coords = getOutputCoords();
        setOutput(getX(${newCoords}));
      }
    `}};function stridedSlice3(args){let{inputs,backend:backend22,attrs}=args,{x}=inputs,{begin,end,strides,beginMask,endMask,ellipsisMask,newAxisMask,shrinkAxisMask}=attrs,{nonStrided,$begin,$strides,size,newShape,outShape}=slice_util_exports.sliceInfo(x.shape,begin,end,strides,beginMask,endMask,ellipsisMask,newAxisMask,shrinkAxisMask),$x=reshape3({inputs:{x},backend:backend22,attrs:{shape:newShape}}),result;if(nonStrided){let sliced=slice3({inputs:{x:$x},backend:backend22,attrs:{begin:$begin,size}});result=reshape3({inputs:{x:sliced},backend:backend22,attrs:{shape:outShape}}),backend22.disposeIntermediateTensorInfo(sliced)}else if(outShape.some(axis=>axis===0))result=backend22.makeTensorInfo(outShape,x.dtype,[]);else if(backend22.shouldExecuteOnCPU([$x])){let values=backend22.texData.get($x.dataId).values,xBuf=buffer($x.shape,$x.dtype,values),resultValues=stridedSliceImplCPU(outShape,xBuf,$strides,$begin);result=backend22.makeTensorInfo(outShape,$x.dtype,resultValues.values)}else{let program=new StridedSliceProgram($begin,$strides,outShape);result=backend22.runWebGLProgram(program,[$x],$x.dtype)}let resultReshaped=reshape3({inputs:{x:result},backend:backend22,attrs:{shape:outShape}});return backend22.disposeIntermediateTensorInfo($x),backend22.disposeIntermediateTensorInfo(result),resultReshaped}var stridedSliceConfig2={kernelName:StridedSlice,backendName:"webgl",kernelFunc:stridedSlice3},TAN="return tan(x);",tan3=unaryKernelFunc2({opSnippet:TAN}),tanConfig2={kernelName:Tan,backendName:"webgl",kernelFunc:tan3},TANH=`
  float e2x = exp(-2.0 * abs(x));
  return sign(x) * (1.0 - e2x) / (1.0 + e2x);
`,tanh4=unaryKernelFunc2({opSnippet:TANH}),tanhConfig2={kernelName:Tanh,backendName:"webgl",kernelFunc:tanh4},TileProgram=class{constructor(aShape,reps){this.variableNames=["A"];let outputShape=new Array(aShape.length);for(let i=0;i<outputShape.length;i++)outputShape[i]=aShape[i]*reps[i];this.outputShape=outputShape,this.rank=outputShape.length;let dtype=getCoordsDataType(this.rank),sourceCoords=getSourceCoords3(aShape);this.userCode=`
      void main() {
        ${dtype} resRC = getOutputCoords();
        setOutput(getA(${sourceCoords}));
      }
    `}};function getSourceCoords3(aShape){let rank=aShape.length;if(rank>5)throw Error(`Tile for rank ${rank} is not yet supported`);if(rank===1)return`imod(resRC, ${aShape[0]})`;let currentCoords=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u"],sourceCoords=[];for(let i=0;i<aShape.length;i++)sourceCoords.push(`imod(${currentCoords[i]}, ${aShape[i]})`);return sourceCoords.join()}function tile3(params){let{inputs,backend:backend22,attrs}=params,{x}=inputs,{reps}=attrs;if(x.dtype==="string"){let decodedData=backend22.readSync(x.dataId).map(d=>util_exports.decodeString(d)),buf=buffer(x.shape,x.dtype,decodedData),outBuf=tileImplCPU(buf,reps);return backend22.makeTensorInfo(outBuf.shape,outBuf.dtype,outBuf.values)}let program=new TileProgram(x.shape,reps);return backend22.runWebGLProgram(program,[x],x.dtype)}var tileConfig2={kernelName:Tile,backendName:"webgl",kernelFunc:tile3};function topK2(args){let{inputs,backend:backend22,attrs}=args,{x}=inputs,{k,sorted}=attrs,xVals=backend22.readSync(x.dataId),[allTopKVals,allTopKIndices]=topKImplCPU(xVals,x.shape,x.dtype,k,sorted);return[backend22.makeTensorInfo(allTopKVals.shape,allTopKVals.dtype,allTopKVals.values),backend22.makeTensorInfo(allTopKIndices.shape,allTopKIndices.dtype,allTopKIndices.values)]}var topKConfig2={kernelName:TopK,backendName:"webgl",kernelFunc:topK2};function unique3(args){let{inputs,attrs,backend:backend22}=args,{axis}=attrs,{x}=inputs;assertNotComplex2(x,"unique"),console.warn("WARNING: ","UI might be locked temporarily as data is being downloaded");let values=backend22.readSync(x.dataId),{outputValues,outputShape,indices}=uniqueImplCPU(values,axis,x.shape,x.dtype);return[backend22.makeTensorInfo(outputShape,x.dtype,outputValues),backend22.makeTensorInfo([indices.length],"int32",indices)]}var uniqueConfig2={kernelName:Unique,backendName:"webgl",kernelFunc:unique3};function unpack2(args){let{inputs,backend:backend22,attrs}=args,{value}=inputs,{axis}=attrs;axis<0&&(axis+=value.shape.length);let x=value,xRank=x.shape.length,num=value.shape[axis],outShape=new Array(xRank-1),outIndex=0;for(let i=0;i<xRank;i++)i!==axis&&(outShape[outIndex++]=x.shape[i]);let toDispose=[],begin=new Array(xRank).fill(0),size=x.shape.slice();size[axis]=1;let res=new Array(num);for(let i=0;i<res.length;i++){begin[axis]=i;let sliced=slice3({inputs:{x},backend:backend22,attrs:{begin,size}}),reshaped=reshape3({inputs:{x:sliced},backend:backend22,attrs:{shape:outShape}});res[i]=reshaped,toDispose.push(sliced)}return toDispose.forEach(t=>backend22.disposeIntermediateTensorInfo(t)),res}var unpackConfig2={kernelName:Unpack,backendName:"webgl",kernelFunc:unpack2},SegmentOpProgram=class{constructor(segOpInfo,segOpType){this.variableNames=["x","segmentIds"];let windowSize=segOpInfo.windowSize,batchSize=segOpInfo.batchSize,inSize=segOpInfo.inSize,numSegments=segOpInfo.numSegments,outSize=numSegments*Math.ceil(inSize/windowSize);this.outputShape=[batchSize,outSize];let initializationValue="0.0",returnValue="sumValue",windowSizeNearestVec4=Math.floor(windowSize/4)*4,windowSizeVec4Remainder=windowSize%4,updateSnippet=`
        sumValue += dot(values, segFilter);
    `,checkValueOutOfBounds="";inSize%windowSize>0&&(checkValueOutOfBounds=`
        if (inIdx < 0 || inIdx >= ${inSize}) {
          return initializationValue;
        }
      `);let checkSegmentIdOutOfBounds="";inSize%windowSize>0&&(checkSegmentIdOutOfBounds=`
        if (inIdx < 0 || inIdx >= ${inSize}) {
          return -1.0;
        }
      `),this.userCode=`
      const float initializationValue = ${initializationValue};

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

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

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

        float sumValue = 0.0;

        for (int i = 0; i < ${windowSizeNearestVec4}; 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
          );

          ${updateSnippet}
        }

        int inIdx = inOffset + ${windowSizeNearestVec4};
        if (${windowSizeVec4Remainder===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
          );

          ${updateSnippet}
        } else if (${windowSizeVec4Remainder===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
          );

          ${updateSnippet}
        } else if (${windowSizeVec4Remainder===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
          );

          ${updateSnippet}
        }
        setOutput(${returnValue});
      }
    `}};function unsortedSegmentSum3(args){let{inputs,backend:backend22,attrs}=args,{x,segmentIds}=inputs,{numSegments}=attrs,xRank=x.shape.length,toDispose=[],axis=0,permutation=backend_util_exports.getAxesPermutation([axis],xRank),permutedX=x;permutation!=null&&(permutedX=transpose3({inputs:{x},backend:backend22,attrs:{perm:permutation}}),toDispose.push(permutedX),axis=backend_util_exports.getInnerMostAxes(1,xRank)[0]);let outShape=backend_util_exports.segment_util.computeOutShape(permutedX.shape,axis,numSegments),inSize=util_exports.sizeFromShape([permutedX.shape[axis]]),a2D=reshape3({inputs:{x:permutedX},backend:backend22,attrs:{shape:[-1,inSize]}});toDispose.push(a2D);let outputDType=sumOutType(x.dtype),segOpCompute=(x2,segOpType,segmentIds2,dtype,numSegments2)=>{let batchSize=x2.shape[0],inSize2=x2.shape[1],windowSize=backend_util_exports.segment_util.segOpComputeOptimalWindowSize(inSize2,numSegments2),segOpInfo={windowSize,inSize:inSize2,batchSize,numSegments:numSegments2},program=new SegmentOpProgram(segOpInfo,segOpType),output=backend22.compileAndRun(program,[x2,segmentIds2],dtype);if(toDispose.push(output),output.shape[1]===numSegments2)return output;let rangeInfo=range3({backend:backend22,attrs:{start:0,stop:numSegments2,step:1,dtype:"float32"}}),tileInfo=tile3({inputs:{x:rangeInfo},backend:backend22,attrs:{reps:[inSize2/windowSize]}});return toDispose.push(rangeInfo),toDispose.push(tileInfo),segOpCompute(output,segOpType,tileInfo,dtype,numSegments2)},segOpResult=segOpCompute(a2D,"unsortedSegmentSum",segmentIds,outputDType,numSegments),reshaped=reshape3({inputs:{x:segOpResult},backend:backend22,attrs:{shape:outShape}}),result=reshaped;if(permutation!=null){toDispose.push(reshaped);let perm=backend_util_exports.getUndoAxesPermutation(permutation);result=transpose3({inputs:{x:result},backend:backend22,attrs:{perm}})}return toDispose.forEach(t=>backend22.disposeIntermediateTensorInfo(t)),result}var unsortedSegmentSumConfig2={kernelName:UnsortedSegmentSum,backendName:"webgl",kernelFunc:unsortedSegmentSum3},kernelConfigs2=[LRNConfig,LRNGradConfig,_fusedMatMulConfig2,absConfig2,acosConfig2,acoshConfig2,addConfig2,addNConfig2,allConfig2,anyConfig2,argMaxConfig2,argMinConfig2,asinConfig2,asinhConfig2,atan2Config2,atanConfig2,atanhConfig2,avgPool3DConfig2,avgPoolConfig2,avgPoolGrad3DConfig,avgPoolGradConfig3,batchMatMulConfig2,batchNormConfig2,batchToSpaceNDConfig2,bincountConfig2,castConfig2,ceilConfig2,clipByValueConfig,complexAbsConfig2,complexConfig2,concatConfig2,conv2DBackpropFilterConfig2,conv2DBackpropInputConfig2,conv2DConfig2,conv3DBackpropFilterV2Config2,conv3DBackpropInputConfig,conv3DConfig2,cosConfig2,coshConfig2,cropAndResizeConfig2,cumsumConfig2,denseBincountConfig2,depthToSpaceConfig2,depthwiseConv2dNativeBackpropFilterConfig2,depthwiseConv2dNativeBackpropInputConfig2,depthwiseConv2dNativeConfig2,diagConfig2,dilation2DConfig,eluConfig2,eluGradConfig3,equalConfig2,erfConfig2,expConfig2,expandDimsConfig2,expm1Config2,fftConfig2,fillConfig2,flipLeftRightConfig2,floorConfig2,floorDivConfig2,fromPixelsConfig,fusedConv2DConfig2,fusedDepthwiseConv2DConfig2,gatherNdConfig2,gatherV2Config2,greaterConfig2,greaterEqualConfig2,identityConfig2,ifftConfig2,imagConfig2,isFiniteConfig2,isInfConfig2,isNaNConfig2,leakyReluConfig2,lessConfig2,lessEqualConfig2,linSpaceConfig2,log1pConfig2,logConfig2,logicalAndConfig2,logicalNotConfig2,logicalOrConfig2,maxConfig2,maxPool3DConfig2,maxPoolConfig2,maxPoolGrad3DConfig,maxPoolGradConfig3,maxPoolWithArgmaxConfig2,maximumConfig2,meanConfig2,minConfig2,minimumConfig2,mirrorPadConfig2,modConfig2,multinomialConfig2,multiplyConfig2,negConfig2,nonMaxSuppressionV3Config2,nonMaxSuppressionV4Config2,nonMaxSuppressionV5Config2,notEqualConfig2,oneHotConfig2,onesLikeConfig2,packConfig2,padV2Config2,powConfig2,preluConfig2,prodConfig2,rangeConfig2,realConfig2,realDivConfig2,reciprocalConfig2,relu6Config2,reluConfig2,reshapeConfig2,resizeBilinearConfig2,resizeBilinearGradConfig3,resizeNearestNeighborConfig2,resizeNearestNeighborGradConfig3,reverseConfig2,rotateWithOffsetConfig2,roundConfig2,
1. The ${printableModuleName} is defined in Python, in which case it needs to be ported to TensorFlow.js or your JavaScript code.
2. The custom ${printableModuleName} is defined in JavaScript, but is not registered properly with tf.serialization.registerClass().`);return fn}else{let config2=identifier;if(config2.className==null||config2.config==null)throw new ValueError(`${printableModuleName}: Improper config format: ${JSON.stringify(config2)}.
'className' and 'config' must set.`);let className=config2.className,cls,fromConfig;if(className in customObjects?[cls,fromConfig]=customObjects[className]:className in _GLOBAL_CUSTOM_OBJECTS?[cls,fromConfig]=_GLOBAL_CUSTOM_OBJECTS.className:className in moduleObjects&&([cls,fromConfig]=moduleObjects[className]),cls==null)throw new ValueError(`Unknown ${printableModuleName}: ${className}. This may be due to one of the following reasons:
1. The ${printableModuleName} is defined in Python, in which case it needs to be ported to TensorFlow.js or your JavaScript code.
2. The custom ${printableModuleName} is defined in JavaScript, but is not registered properly with tf.serialization.registerClass().`);if(fromConfig!=null){let customObjectsCombined={};for(let key of Object.keys(_GLOBAL_CUSTOM_OBJECTS))customObjectsCombined[key]=_GLOBAL_CUSTOM_OBJECTS[key];for(let key of Object.keys(customObjects))customObjectsCombined[key]=customObjects[key];let nestedConfig=config2.config;nestedConfig.customObjects=customObjectsCombined;let backupCustomObjects=Object.assign({},_GLOBAL_CUSTOM_OBJECTS);for(let key of Object.keys(customObjects))_GLOBAL_CUSTOM_OBJECTS[key]=customObjects[key];convertNDArrayScalarsInConfig(config2.config);let returnObj=fromConfig(cls,config2.config,customObjects,fastWeightInit);return _GLOBAL_CUSTOM_OBJECTS=Object.assign({},backupCustomObjects),returnObj}else{let backupCustomObjects=Object.assign({},_GLOBAL_CUSTOM_OBJECTS);for(let key of Object.keys(customObjects))_GLOBAL_CUSTOM_OBJECTS[key]=customObjects[key];let returnObj=new cls(config2.config);return _GLOBAL_CUSTOM_OBJECTS=Object.assign({},backupCustomObjects),returnObj}}}function numberCompare(a,b){return a<b?-1:a>b?1:0}function reverseNumberCompare(a,b){return-1*numberCompare(a,b)}function unique4(xs){if(xs==null)return xs;let out=[];for(let x of xs)out.indexOf(x)===-1&&out.push(x);return out}function isObjectEmpty(obj){if(obj==null)throw new ValueError(`Invalid value in obj: ${JSON.stringify(obj)}`);for(let key in obj)if(obj.hasOwnProperty(key))return!1;return!0}function checkStringTypeUnionValue(values,label,value){if(value!=null&&values.indexOf(value)<0)throw new ValueError(`${value} is not a valid ${label}.  Valid values are ${values} or null/undefined.`)}function checkArrayTypeAndLength(x,expectedType,minLength=0,maxLength=Infinity){return assert2(minLength>=0),assert2(maxLength>=minLength),Array.isArray(x)&&x.length>=minLength&&x.length<=maxLength&&x.every(e=>typeof e===expectedType)}function assertPositiveInteger(value,name){Array.isArray(value)?(util_exports.assert(value.length>0,()=>`${name} is unexpectedly an empty array.`),value.forEach((v,i)=>assertPositiveInteger(v,`element ${i+1} of ${name}`))):util_exports.assert(Number.isInteger(value)&&value>0,()=>`Expected ${name} to be a positive integer, but got ${formatAsFriendlyString(value)}.`)}function formatAsFriendlyString(value){return value===null?"null":Array.isArray(value)?"["+value.map(v=>formatAsFriendlyString(v)).join(",")+"]":typeof value=="string"?`"${value}"`:`${value}`}function debounce(f,waitMs){let lastTime=util_exports.now(),lastResult;return(...args)=>{let now22=util_exports.now();return now22-lastTime<waitMs||(lastTime=now22,lastResult=f(...args)),lastResult}}function mapActivationToFusedKernel(activationName){return activationName==="relu"?"relu":activationName==="linear"?"linear":activationName==="elu"?"elu":null}function calcL2Norms(w,axis){return tidy(()=>sqrt(sum2(mul(w,w),axis,!0)))}var Constraint=class extends serialization_exports.Serializable{getConfig(){return{}}},MaxNorm=class extends Constraint{constructor(args){super();this.defaultMaxValue=2,this.defaultAxis=0,this.maxValue=args.maxValue!=null?args.maxValue:this.defaultMaxValue,this.axis=args.axis!=null?args.axis:this.defaultAxis}apply(w){return tidy(()=>{let norms=calcL2Norms(w,this.axis),desired=clipByValue(norms,0,this.maxValue);return mul(w,div(desired,add2(epsilon2(),norms)))})}getConfig(){return{maxValue:this.maxValue,axis:this.axis}}};MaxNorm.className="MaxNorm";serialization_exports.registerClass(MaxNorm);var UnitNorm=class extends Constraint{constructor(args){super();this.defaultAxis=0,this.axis=args.axis!=null?args.axis:this.defaultAxis}apply(w){return tidy(()=>div(w,add2(epsilon2(),calcL2Norms(w,this.axis))))}getConfig(){return{axis:this.axis}}};UnitNorm.className="UnitNorm";serialization_exports.registerClass(UnitNorm);var NonNeg=class extends Constraint{apply(w){return relu(w)}};NonNeg.className="NonNeg";serialization_exports.registerClass(NonNeg);var MinMaxNorm=class extends Constraint{constructor(args){super();this.defaultMinValue=0,this.defaultMaxValue=1,this.defau
          because the value dtype is ${tensor2.dtype}, but TensorArray dtype is ${this.dtype}.`);if(this.size()===0&&(this.elementShape==null||this.elementShape.length===0)&&(this.elementShape=tensor2.shape),assertShapesMatchAllowUndefinedSize(this.elementShape,tensor2.shape,`TensorArray ${this.name}: Could not write to TensorArray index ${index}.`),t.read)throw new Error(`TensorArray ${this.name}: Could not write to TensorArray index ${index}, because it has already been read.`);if(t.written)throw new Error(`TensorArray ${this.name}: Could not write to TensorArray index ${index}, because it has already been written.`);t.tensor=tensor2,keep(tensor2),t.written=!0,this.tensors[index]=t}writeMany(indices,tensors){if(indices.length!==tensors.length)throw new Error(`TensorArray ${this.name}: could not write multiple tensors,because the index size: ${indices.length} is not the same as tensors size: ${tensors.length}.`);indices.forEach((i,index)=>this.write(i,tensors[index]))}gather(indices,dtype){if(!!dtype&&dtype!==this.dtype)throw new Error(`TensorArray dtype is ${this.dtype} but gather requested dtype ${dtype}`);if(indices)indices=indices.slice(0,this.size());else{indices=[];for(let i=0;i<this.size();i++)indices.push(i)}if(indices.length===0)return tensor([],[0].concat(this.elementShape));let tensors=this.readMany(indices);return assertShapesMatchAllowUndefinedSize(this.elementShape,tensors[0].shape,"TensorArray shape mismatch: "),stack(tensors,0)}concat(dtype){if(!!dtype&&dtype!==this.dtype)throw new Error(`TensorArray dtype is ${this.dtype} but concat requested dtype ${dtype}`);if(this.size()===0)return tensor([],[0].concat(this.elementShape));let indices=[];for(let i=0;i<this.size();i++)indices.push(i);let tensors=this.readMany(indices);return assertShapesMatchAllowUndefinedSize(this.elementShape,tensors[0].shape,`TensorArray shape mismatch: tensor array shape (${this.elementShape}) vs first tensor shape (${tensors[0].shape})`),concat(tensors,0)}scatter(indices,tensor2){if(tensor2.dtype!==this.dtype)throw new Error(`TensorArray dtype is ${this.dtype} but tensor has dtype ${tensor2.dtype}`);if(indices.length!==tensor2.shape[0])throw new Error(`Expected len(indices) == tensor.shape[0], but saw: ${indices.length} vs. ${tensor2.shape[0]}`);let maxIndex=Math.max(...indices);if(!this.dynamicSize&&maxIndex>=this.maxSize)throw new Error(`Max index must be < array size (${maxIndex}  vs. ${this.maxSize})`);this.writeMany(indices,unstack(tensor2,0))}split(length,tensor2){if(tensor2.dtype!==this.dtype)throw new Error(`TensorArray dtype is ${this.dtype} but tensor has dtype ${tensor2.dtype}`);let totalLength=0,cumulativeLengths=length.map(len=>(totalLength+=len,totalLength));if(totalLength!==tensor2.shape[0])throw new Error(`Expected sum of lengths to be equal to
          tensor.shape[0], but sum of lengths is
        ${totalLength}, and tensor's shape is: ${tensor2.shape}`);if(!this.dynamicSize&&length.length!==this.maxSize)throw new Error(`TensorArray's size is not equal to the size of lengths (${this.maxSize} vs. ${length.length}), and the TensorArray is not marked as dynamically resizeable`);let elementPerRow=totalLength===0?0:tensor2.size/totalLength,tensors=[];tidy(()=>{tensor2=reshape(tensor2,[1,totalLength,elementPerRow]);for(let i=0;i<length.length;++i){let previousLength=i===0?0:cumulativeLengths[i-1],indices2=[0,previousLength,0],sizes=[1,length[i],elementPerRow];tensors[i]=reshape(slice(tensor2,indices2,sizes),this.elementShape)}return tensors});let indices=[];for(let i=0;i<length.length;i++)indices[i]=i;this.writeMany(indices,tensors)}},TensorList=class{constructor(tensors,elementShape,elementDtype,maxNumElements=-1){this.tensors=tensors,this.elementShape=elementShape,this.elementDtype=elementDtype,tensors!=null&&tensors.forEach(tensor2=>{if(elementDtype!==tensor2.dtype)throw new Error(`Invalid data types; op elements ${elementDtype}, but list elements ${tensor2.dtype}`);assertShapesMatchAllowUndefinedSize(elementShape,tensor2.shape,"TensorList shape mismatch: "),keep(tensor2)}),this.idTensor=scalar(0),this.maxNumElements=maxNumElements,keep(this.idTensor)}get id(){return this.idTensor.id}copy(){return new TensorList([...this.tensors],this.elementShape,this.elementDtype)}clearAndClose(keepIds){this.tensors.forEach(tensor2=>{(keepIds==null||!keepIds.has(tensor2.id))&&tensor2.dispose()}),this.tensors.length=0,this.idTensor.dispose()}size(){return this.tensors.length}stack(elementShape,elementDtype,numElements=-1){if(elementDtype!==this.elementDtype)throw new Error(`Invalid data types; op elements ${elementDtype}, but list elements ${this.elementDtype}`);if(numElements!==-1&&this.tensors.length!==numElements)throw new Error(`Operation expected a list with ${numElements} elements but got a list with ${this.tensors.length} elements.`);return assertShapesMatchAllowUndefinedSize(elementShape,this.elementShape,"TensorList shape mismatch: "),tidy(()=>{let reshapedTensors=this.tensors.map(tensor2=>reshape(tensor2,elementShape));return stack(reshapedTensors,0)})}popBack(elementShape,elementDtype){if(elementDtype!==this.elementDtype)throw new Error(`Invalid data types; op elements ${elementDtype}, but list elements ${this.elementDtype}`);if(this.size()===0)throw new Error("Trying to pop from an empty list.");let tensor2=this.tensors.pop();return assertShapesMatchAllowUndefinedSize(tensor2.shape,elementShape,"TensorList shape mismatch: "),reshape(tensor2,elementShape)}pushBack(tensor2){if(tensor2.dtype!==this.elementDtype)throw new Error(`Invalid data types; op elements ${tensor2.dtype}, but list elements ${this.elementDtype}`);if(assertShapesMatchAllowUndefinedSize(tensor2.shape,this.elementShape,"TensorList shape mismatch: "),this.maxNumElements===this.size())throw new Error("Trying to push element into a full list.");keep(tensor2),this.tensors.push(tensor2)}resize(size){if(size<0)throw new Error(`TensorListResize expects size to be non-negative. Got: ${size}`);if(this.maxNumElements!==-1&&size>this.maxNumElements)throw new Error(`TensorListResize input size ${size} is greater maxNumElement ${this.maxNumElements}.`);this.tensors.length=size}getItem(elementIndex,elementShape,elementDtype){if(elementDtype!==this.elementDtype)throw new Error(`Invalid data types; op elements ${elementDtype}, but list elements ${this.elementDtype}`);if(elementIndex<0||elementIndex>this.tensors.length)throw new Error(`Trying to access element ${elementIndex} in a list with ${this.tensors.length} elements.`);if(this.tensors[elementIndex]==null)throw new Error(`element at index ${elementIndex} is null.`);return assertShapesMatchAllowUndefinedSize(this.tensors[elementIndex].shape,elementShape,"TensorList shape mismatch: "),this.tensors[elementIndex]}setItem(elementIndex,tensor2){if(tensor2.dtype!==this.elementDtype)throw new Error(`Invalid data types; op elements ${tensor2.dtype}, but list elements ${this.elementDtype}`);if(elementIndex<0||this.maxN
          tensor.shape[0], but sum of lengths is
        ${totalLength}, and tensor's shape is: ${tensor2.shape}`);let elementPerRow=totalLength===0?0:tensor2.size/totalLength,tensors=tidy(()=>{let tensors2=[];tensor2=reshape(tensor2,[1,totalLength,elementPerRow]);for(let i=0;i<length.length;++i){let previousLength=i===0?0:cumulativeLengths[i-1],indices=[0,previousLength,0],sizes=[1,length[i],elementPerRow];tensors2[i]=reshape(slice(tensor2,indices,sizes),elementShape)}return tensor2.dispose(),tensors2}),list=new TensorList([],elementShape,tensor2.dtype,length.length);for(let i=0;i<tensors.length;i++)list.setItem(i,tensors[i]);return list}var executeOp3=async(node,tensorMap,context)=>{switch(node.op){case"If":case"StatelessIf":{let thenFunc=getParamValue("thenBranch",node,tensorMap,context),elseFunc=getParamValue("elseBranch",node,tensorMap,context),cond=getParamValue("cond",node,tensorMap,context),args=getParamValue("args",node,tensorMap,context);return(await cond.data())[0]?context.functionMap[thenFunc].executeFunctionAsync(args,context.tensorArrayMap,context.tensorListMap):context.functionMap[elseFunc].executeFunctionAsync(args,context.tensorArrayMap,context.tensorListMap)}case"While":case"StatelessWhile":{let bodyFunc=getParamValue("body",node,tensorMap,context),condFunc=getParamValue("cond",node,tensorMap,context),args=getParamValue("args",node,tensorMap,context),condResult=await context.functionMap[condFunc].executeFunctionAsync(args,context.tensorArrayMap,context.tensorListMap),argIds=args.map(tensor2=>tensor2.id),condValue=await condResult[0].data();condResult.forEach(tensor2=>{!tensor2.kept&&argIds.indexOf(tensor2.id)===-1&&tensor2.dispose()});let result=args;for(;condValue[0];){let origResult=result;result=await context.functionMap[bodyFunc].executeFunctionAsync(result,context.tensorArrayMap,context.tensorListMap);let resultIds=result.map(tensor2=>tensor2.id);origResult.forEach(tensor2=>{!tensor2.kept&&argIds.indexOf(tensor2.id)===-1&&resultIds.indexOf(tensor2.id)===-1&&tensor2.dispose()});let condResult2=await context.functionMap[condFunc].executeFunctionAsync(result,context.tensorArrayMap,context.tensorListMap);condValue=await condResult2[0].data(),condResult2.forEach(tensor2=>{!tensor2.kept&&argIds.indexOf(tensor2.id)===-1&&resultIds.indexOf(tensor2.id)===-1&&tensor2.dispose()})}return result}case"LoopCond":{let pred=getParamValue("pred",node,tensorMap,context);return[cloneTensor(pred)]}case"Switch":{let pred=getParamValue("pred",node,tensorMap,context),data2=getParamValue("data",node,tensorMap,context);return data2.kept||(data2=cloneTensor(data2)),(await pred.data())[0]?[void 0,data2]:[data2,void 0]}case"Merge":{let inputName=node.inputNames.find(name=>getTensor(name,tensorMap,context)!==void 0);if(inputName){let data2=getTensor(inputName,tensorMap,context);return[cloneTensor(data2)]}return}case"Enter":{let frameId=getParamValue("frameName",node,tensorMap,context),data2=getParamValue("tensor",node,tensorMap,context);return context.enterFrame(frameId),[cloneTensor(data2)]}case"Exit":{let data2=getParamValue("tensor",node,tensorMap,context);return context.exitFrame(),[cloneTensor(data2)]}case"NextIteration":{let data2=getParamValue("tensor",node,tensorMap,context);return context.nextIteration(),[cloneTensor(data2)]}case"TensorArrayV3":{let size=getParamValue("size",node,tensorMap,context),dtype=getParamValue("dtype",node,tensorMap,context),elementShape=getParamValue("elementShape",node,tensorMap,context),dynamicSize=getParamValue("dynamicSize",node,tensorMap,context),clearAfterRead=getParamValue("clearAfterRead",node,tensorMap,context),identicalElementShapes=getParamValue("identicalElementShapes",node,tensorMap,context),name=getParamValue("name",node,tensorMap,context),tensorArray=new TensorArray(name,dtype,size,elementShape,identicalElementShapes,dynamicSize,clearAfterRead);return context.addTensorArray(tensorArray),[tensorArray.idTensor,scalar(1)]}case"TensorArrayWriteV3":{let id=getParamValue("tensorArrayId",node,tensorMap,context),index=getParamValue("index",node,tensorMap,context),writeTensor=getParamValue("tensor",node,tensorMap,context),writeTensorA
      ${batchSize}`);let size;return this.size===Infinity||this.size==null?size=this.size:smallLastBatch?size=Math.ceil(this.size/batchSize):size=Math.floor(this.size/batchSize),datasetFromIteratorFn(async()=>(await base2.iterator()).columnMajorBatch(batchSize,smallLastBatch,deepBatchConcat),size)}concatenate(dataset){let base2=this,size;return this.size===Infinity||dataset.size===Infinity?size=Infinity:this.size!=null&&dataset.size!=null?size=this.size+dataset.size:size=null,datasetFromIteratorFn(async()=>(await base2.iterator()).concatenate(await dataset.iterator()),size)}filter(predicate){let base2=this,size;return this.size===Infinity?size=Infinity:size=null,datasetFromIteratorFn(async()=>(await base2.iterator()).filter(x=>tidy(()=>predicate(x))),size)}async forEachAsync(f){return(await this.iterator()).forEachAsync(f)}map(transform){let base2=this;return datasetFromIteratorFn(async()=>(await base2.iterator()).map(x=>tidy(()=>transform(x))),this.size)}mapAsync(transform){let base2=this;return datasetFromIteratorFn(async()=>(await base2.iterator()).mapAsync(transform),this.size)}prefetch(bufferSize){if(bufferSize==null)throw new RangeError("`Dataset.prefetch()` requires bufferSize to be specified.");let base2=this;return datasetFromIteratorFn(async()=>(await base2.iterator()).prefetch(bufferSize),this.size)}repeat(count2){let base2=this,size;return this.size!=null&&count2>0?size=this.size*count2:count2===0?size=0:this.size!=null&&(count2===void 0||count2<0)?size=Infinity:size=null,datasetFromIteratorFn(async()=>{let iteratorIterator=iteratorFromFunction(async()=>({value:await base2.iterator(),done:!1}));return iteratorFromConcatenated(iteratorIterator.take(count2))},size)}skip(count2){let base2=this,size;return this.size!=null&&count2>=0&&this.size>=count2?size=this.size-count2:this.size!=null&&(this.size<count2||count2===void 0||count2<0)?size=0:size=null,datasetFromIteratorFn(async()=>(await base2.iterator()).skip(count2),size)}shuffle(bufferSize,seed,reshuffleEachIteration=!0){if(bufferSize==null||bufferSize<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 base2=this,random=seedrandom4.alea(seed||util_exports.now().toString());return datasetFromIteratorFn(async()=>{let seed2=random.int32();return reshuffleEachIteration&&(seed2+=random.int32()),(await base2.iterator()).shuffle(bufferSize,seed2.toString())},this.size)}take(count2){let base2=this,size;return this.size!=null&&this.size>count2?size=count2:this.size!=null&&this.size<=count2?size=this.size:size=null,datasetFromIteratorFn(async()=>(await base2.iterator()).take(count2),size)}async toArray(){if(this.size===Infinity)throw new Error("Can not convert infinite data stream to array.");return(await this.iterator()).toArray()}async toArrayForTest(){if(this.size===Infinity)throw new Error("Can not convert infinite data stream to array.");return(await this.iterator()).toArrayForTest()}};Dataset.MAX_BUFFER_SIZE=1e4;function datasetFromIteratorFn(iteratorFn,size=null){return new class extends Dataset{constructor(){super(...arguments);this.size=size}async iterator(){return iteratorFn()}}}function array(items){return datasetFromIteratorFn(async()=>iteratorFromItems(items),items.length)}function zip(datasets){if(!isIterable2(datasets))throw new Error("The argument to zip() must be an object or array.");let size;if(Array.isArray(datasets))for(let i=0;i<datasets.length;i++)size=size==null?datasets[i].size:Math.min(size,datasets[i].size);else if(datasets instanceof Object)for(let ds in datasets)size=size==null?datasets[ds].size:Math.min(size,datasets[ds].size);return datasetFromIteratorFn(async()=>{let streams=await deepMapAndAwaitAll(datasets,d=>{if(d instanceof Dataset)return{value:d.iterator(),recurse:!1};if(isIterable2(d))return{value:null,recurse:!0};throw new Error("Leav
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2Q==`;var version14="0.9.25";var now2=()=>typeof performance!="undefined"?performance.now():parseInt(Number(process.hrtime.bigint())/1e3/1e3);function mergeDeep(...objects){let isObject=obj=>obj&&typeof obj=="object";return objects.reduce((prev,obj)=>(Object.keys(obj||{}).forEach(key=>{let pVal=prev[key],oVal=obj[key];Array.isArray(pVal)&&Array.isArray(oVal)?prev[key]=pVal.concat(...oVal):isObject(pVal)&&isObject(oVal)?prev[key]=mergeDeep(pVal,oVal):prev[key]=oVal}),prev),{})}var Human=class{constructor(userConfig={}){this.tf=tfjs_esm_exports,this.version=version14,this.config=mergeDeep(config_default,userConfig),this.fx=null,this.state="idle",this.numTensors=0,this.analyzeMemoryLeaks=!1,this.checkSanity=!1,this.firstRun=!0,this.perf={},this.models={facemesh:null,posenet:null,handpose:null,iris:null,age:null,gender:null,emotion:null},this.facemesh=facemesh,this.age=age,this.gender=gender,this.emotion=emotion,this.body=posenet,this.hand=handpose}profile(){return this.config.profile?profile2.data:{}}analyze(...msg){if(!this.analyzeMemoryLeaks)return;let current=engine().state.numTensors,previous=this.numTensors;this.numTensors=current;let leaked=current-previous;leaked!==0&&log(...msg,leaked)}sanity(input2){if(!this.checkSanity)return null;if(!input2)return"input is not defined";if(ENV.flags.IS_NODE&&!(input2 instanceof Tensor))return"input must be a tensor";try{getBackend()}catch(e){return"backend not loaded"}return null}simmilarity(embedding1,embedding22){return this.config.face.embedding.enabled?embedding2.simmilarity(embedding1,embedding22):0}async load(userConfig){this.state="load";let timeStamp=now2();userConfig&&(this.config=mergeDeep(this.config,userConfig)),this.firstRun&&(log(`version: ${this.version} TensorFlow/JS version: ${version6}`),await this.checkBackend(!0),ENV.flags.IS_BROWSER&&(log("configuration:",this.config),log("tf flags:",ENV.flags))),this.config.async?[this.models.facemesh,this.models.age,this.models.gender,this.models.emotion,this.models.embedding,this.models.posenet,this.models.handpose]=await Promise.all([this.models.facemesh||(this.config.face.enabled?facemesh.load(this.config):null),this.models.age||(this.config.face.enabled&&this.config.face.age.enabled?age.load(this.config):null),this.models.gender||(this.config.face.enabled&&this.config.face.gender.enabled?gender.load(this.config):null),this.models.emotion||(this.config.face.enabled&&this.config.face.emotion.enabled?emotion.load(this.config):null),this.models.embedding||(this.config.face.enabled&&this.config.face.embedding.enabled?embedding2.load(this.config):null),this.models.posenet||(this.config.body.enabled?posenet.load(this.config):null),this.models.handpose||(this.config.hand.enabled?handpose.load(this.config):null)]):(this.config.face.enabled&&!this.models.facemesh&&(this.models.facemesh=await facemesh.load(this.config)),this.config.face.enabled&&this.config.face.age.enabled&&!this.models.age&&(this.models.age=await age.load(this.config)),this.config.face.enabled&&this.config.face.gender.enabled&&!this.models.gender&&(this.models.gender=await gender.load(this.config)),this.config.face.enabled&&this.config.face.emotion.enabled&&!this.models.emotion&&(this.models.emotion=await emotion.load(this.config)),this.config.face.enabled&&this.config.face.embedding.enabled&&!this.models.embedding&&(this.models.embedding=await embedding2.load(this.config)),this.config.body.enabled&&!this.models.posenet&&(this.models.posenet=await posenet.load(this.config)),this.config.hand.enabled&&!this.models.handpose&&(this.models.handpose=await handpose.load(this.config))),this.firstRun&&(log("tf engine state:",engine().state.numBytes,"bytes",engine().state.numTensors,"tensors"),this.firstRun=!1);let current=Math.trunc(now2()-timeStamp);current>(this.perf.load||0)&&(this.perf.load=current)}async checkBackend(force){if(this.config.backend&&this.config.backend!==""&&force||getBackend()!==this.config.backend){let timeStamp=now2();this.state="backend",log("setting backend:",this.config.backend),this.config.backend==="wasm"&&(log("settings wasm path:",this.confi
/**
 * @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 See the LICENSE file. */
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