/*!
 * artplayer-plugin-danmuku-mask.js v1.0.0
 * Github: https://github.com/zhw2590582/ArtPlayer
 * (c) 2017-2025 Harvey Zack
 * Released under the MIT License.
 */
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s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"default",()=>l);var a=e("@tensorflow-models/body-segmentation"),o=e("@tensorflow/tfjs-core");function l(e={}){return t=>{let{template:{$video:r,$danmuku:n}}=t,s=null,l=null,i=null,p=null,u=!1,c={solutionPath:e.solutionPath||"https://cdn.jsdelivr.net/npm/@mediapipe/selfie_segmentation",modelSelection:e.modelSelection||1,smoothSegmentation:void 0===e.smoothSegmentation||e.smoothSegmentation,minDetectionConfidence:e.minDetectionConfidence||.5,minTrackingConfidence:e.minTrackingConfidence||.5,selfieMode:e.selfieMode||!1,drawContour:e.drawContour||!1,foregroundThreshold:e.foregroundThreshold||.5,opacity:e.opacity||1,maskBlurAmount:e.maskBlurAmount||3};async function d(){try{await o.setBackend("webgl")}catch(e){console.warn("WebGL backend not available, falling back to CPU",e.message),await o.setBackend("cpu")}}async function f(){await d();let 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t=this.baseModel.predict(e);return{segmentLogits:t.segmentation,longOffsets:t.longOffsets,heatmapScores:t.heatmapScores,offsets:t.offsets,displacementFwd:t.displacementFwd,displacementBwd:t.displacementBwd,partHeatmaps:t.partHeatmaps}},e.prototype.segmentPersonActivation=function(e,t,r){var n=this;void 0===r&&(r=.5);var s=Z(e),a=s[0],l=s[1],i=ee(t,this.baseModel.outputStride,[a,l]),p=er(e,i),u=p.resized,c=p.padding,d=(0,o.tidy)(function(){var e=n.predictForPersonSegmentation(u),t=e.segmentLogits,s=e.heatmapScores,i=e.offsets,p=e.displacementFwd,d=e.displacementBwd,f=u.shape,m=et(t,[a,l],[f[0],f[1]],[[c.top,c.bottom],[c.left,c.right]],!0);return{segmentation:_((0,o.squeeze)(m),r),heatmapScores:s,offsets:i,displacementFwd:p,displacementBwd:d}}),f=d.segmentation,m=d.heatmapScores,h=d.offsets,g=d.displacementFwd,x=d.displacementBwd;return u.dispose(),{segmentation:f,heatmapScores:m,offsets:h,displacementFwd:g,displacementBwd:x,padding:c,internalResolutionHeightAndWidth:i}},e.prototype.segmentPerson=function(e,t){return void 0===t&&(t=eu),d(this,void 0,void 0,function(){var r,n,s,a,o,l,i,p,u,d,m,h,g,x,y,v;return f(this,function(f){switch(f.label){case 0:return ed(t=c(c({},eu),t)),n=(r=this.segmentPersonActivation(e,t.internalResolution,t.segmentationThreshold)).segmentation,s=r.heatmapScores,a=r.offsets,o=r.displacementFwd,l=r.displacementBwd,i=r.padding,p=r.internalResolutionHeightAndWidth,d=(u=n.shape)[0],m=u[1],[4,n.data()];case 1:return h=f.sent(),n.dispose(),[4,en([s,a,o,l])];case 2:return x=(g=f.sent())[0],y=g[1],v=es(v=U(x,y,g[2],g[3],this.baseModel.outputStride,t.maxDetections,t.scoreThreshold,t.nmsRadius),[d,m],p,i,!1),s.dispose(),a.dispose(),o.dispose(),l.dispose(),[2,{height:d,width:m,data:h,allPoses:v}]}})})},e.prototype.segmentMultiPerson=function(e,t){return void 0===t&&(t=ec),d(this,void 0,void 0,function(){var r,n,s,a,l,i,p,u,m,h,g,x,y,v,b,k,I,j,w,T=this;return f(this,function(S){switch(S.label){case 0:return ef(t=c(c({},ec),t)),n=(r=Z(e))[0],s=r[1],i=(l=er(e,a=ee(t.internalResolution,this.baseModel.outputStride,[n,s]))).resized,p=l.padding,m=(u=(0,o.tidy)(function(){var e=T.predictForMultiPersonInstanceSegmentationAndPart(i),r=e.segmentLogits,l=e.longOffsets,u=e.heatmapScores,c=e.offsets,d=e.displacementFwd,f=e.displacementBwd,m=et(r,[n,s],a,[[p.top,p.bottom],[p.left,p.right]],!0);return{segmentation:_((0,o.squeeze)(m),t.segmentationThreshold),longOffsets:l,heatmapScoresRaw:u,offsetsRaw:c,displacementFwdRaw:d,displacementBwdRaw:f}})).segmentation,h=u.longOffsets,g=u.heatmapScoresRaw,x=u.offsetsRaw,y=u.displacementFwdRaw,v=u.displacementBwdRaw,[4,en([g,x,y,v])];case 1:return k=(b=S.sent())[0],I=b[1],j=es(j=U(k,I,b[2],b[3],this.baseModel.outputStride,t.maxDetections,t.scoreThreshold,t.nmsRadius),[n,s],a,p,!1),[4,function(e,t,r,n,s,a,l,i,p,u,c,m){var h=l[0],g=l[1];return void 0===p&&(p=.2),void 0===u&&(u=8),void 0===c&&(c=.3),void 0===m&&(m=10),d(this,void 0,void 0,function(){var l,d,x,y,v;return f(this,function(f){switch(f.label){case 0:return l=r.filter(function(e){return e.score>=p}),$()?[4,Promise.all((x=(0,o.tidy)(function(){var r=P(e,t,l,n,s,a,[h,g],i,u,c,m),p=(0,o.engine)().makeTensorFromDataId(r.dataId,r.shape,r.dtype);return l.map(function(e,t){return(0,o.tidy)(function(){return(0,o.cast)((0,o.equal)(p,(0,o.scalar)(t)),"int32")})})})).map(function(e){return e.data()}))]:[3,2];case 1:return d=f.sent(),x.forEach(function(e){return e.dispose()}),[3,5];case 2:return[4,e.data()];case 3:return y=f.sent(),[4,t.data()];case 4:v=f.sent(),d=function(e,t,r,n,s,a,o,l,i,p){var u=o[0],c=o[1];void 0===p&&(p=5);for(var d=r.map(function(e){return new Uint8Array(n*s).fill(0)}),f=l.top,m=l.left,h=C([n,s],[u,c],l),g=h[0],x=h[1],y=R([u,c],a)[0],v=0;v<n;v+=1)for(var b=0;b<s;b+=1){var k=v*s+b;if(1===e[k]){var _=A({x:b,y:v},t,r,p,[f,m],[g,x],y,[n,s],a,i);_>=0&&(d[_][k]=1)}}return d}(y,v,l,n,s,a,[h,g],i,u),f.label=5;case 5:return[2,d.map(function(e,t){return{data:e,pose:l[t],width:s,height:n}})]}})})}(m,h,j,n,s,this.baseModel.outputStride,a,p,t.scoreThreshold,t.refineSteps,t.minKeypointScore,t.maxDetections)];case 2:return w=S.sent(),i.dispose(),m.dispose(),h.dispose(),g.dispose(),x.dispose(),y.dispose(),v.dispose(),[2,w]}})})},e.prototype.segmentPersonPartsActivation=function(e,t,r){var n=this;void 0===r&&(r=.5);var s=Z(e),a=s[0],l=s[1],i=ee(t,this.baseModel.outputStride,[a,l]),p=er(e,i),u=p.resized,c=p.padding,d=(0,o.tidy)(function(){var e,t,s,i,p,d=n.predictForPersonSegmentationAndPart(u),f=d.segmentLogits,m=d.partHeatmapLogits,h=d.heatmapScores,g=d.offsets,x=d.displacementFwd,y=d.displacementBwd,v=u.shape,b=v[0],I=v[1],j=et(f,[a,l],[b,I],[[c.top,c.bottom],[c.left,c.right]],!0),w=et(m,[a,l],[b,I],[[c.top,c.bottom],[c.left,c.right]],!0);return{partSegmentation:(e=_((0,o.squeeze)(j),r),s=(t=w.shape)[0],i=t[1],p=t[2],(0,o.tidy)(function(){var t=k(w),r=(0,o.expandDims)((0,o.range)(0,p,1,"int32"),1),n=(0,o.cast)((0,o.matMul)(t,r),"int32"),a=(0,o.reshape)(n,[s,i]),l=(0,o.add)(a,(0,o.scalar)(1,"int32"));return(0,o.sub)((0,o.mul)(l,e),(0,o.scalar)(1,"int32"))})),heatmapScores:h,offsets:g,displacementFwd:x,displacementBwd:y}}),f=d.partSegmentation,m=d.heatmapScores,h=d.offsets,g=d.displacementFwd,x=d.displacementBwd;return u.dispose(),{partSegmentation:f,heatmapScores:m,offsets:h,displacementFwd:g,displacementBwd:x,padding:c,internalResolutionHeightAndWidth:i}},e.prototype.segmentPersonParts=function(e,t){return void 0===t&&(t=eu),d(this,void 0,void 0,function(){var r,n,s,a,o,l,i,p,u,d,m,h,g,x,y,v;return f(this,function(f){switch(f.label){case 0:return ed(t=c(c({},eu),t)),n=(r=this.segmentPersonPartsActivation(e,t.internalResolution,t.segmentationThreshold)).partSegmentation,s=r.heatmapScores,a=r.offsets,o=r.displacementFwd,l=r.displacementBwd,i=r.padding,p=r.internalResolutionHeightAndWidth,d=(u=n.shape)[0],m=u[1],[4,n.data()];case 1:return h=f.sent(),n.dispose(),[4,en([s,a,o,l])];case 2:return x=(g=f.sent())[0],y=g[1],v=es(v=U(x,y,g[2],g[3],this.baseModel.outputStride,t.maxDetections,t.scoreThreshold,t.nmsRadius),[d,m],p,i,!1),s.dispose(),a.dispose(),o.dispose(),l.dispose(),[2,{height:d,width:m,data:h,allPoses:v}]}})})},e.prototype.segmentMultiPersonParts=function(e,t){return void 0===t&&(t=ec),d(this,void 0,void 0,function(){var r,n,s,a,l,i,p,u,m,h,g,x,y,v,b,I,j,w,T,S,N=this;return f(this,function(E){switch(E.label){case 0:return ef(t=c(c({},ec),t)),n=(r=Z(e))[0],s=r[1],i=(l=er(e,a=ee(t.internalResolution,this.baseModel.outputStride,[n,s]))).resized,p=l.padding,m=(u=(0,o.tidy)(function(){var e,r,l,u,c=N.predictForMultiPersonInstanceSegmentationAndPart(i),d=c.segmentLogits,f=c.longOffsets,m=c.heatmapScores,h=c.offsets,g=c.displacementFwd,x=c.displacementBwd,y=c.partHeatmaps,v=et(d,[n,s],a,[[p.top,p.bottom],[p.left,p.right]],!0),b=et(y,[n,s],a,[[p.top,p.bottom],[p.left,p.right]],!0);return{segmentation:_((0,o.squeeze)(v),t.segmentationThreshold),longOffsets:f,heatmapScoresRaw:m,offsetsRaw:h,displacementFwdRaw:g,displacementBwdRaw:x,partSegmentation:(r=(e=b.shape)[0],l=e[1],u=e[2],(0,o.tidy)(function(){var e=k(b),t=(0,o.expandDims)((0,o.range)(0,u,1,"int32"),1),n=(0,o.cast)((0,o.matMul)(e,t),"int32");return(0,o.reshape)(n,[r,l])}))}})).segmentation,h=u.longOffsets,g=u.heatmapScoresRaw,x=u.offsetsRaw,y=u.displacementFwdRaw,v=u.displacementBwdRaw,b=u.partSegmentation,[4,en([g,x,y,v])];case 1:return j=(I=E.sent())[0],w=I[1],T=es(T=U(j,w,I[2],I[3],this.baseModel.outputStride,t.maxDetections,t.scoreThreshold,t.nmsRadius),[n,s],a,p,!1),[4,function(e,t,r,n,s,a,l,i,p,u,c,m,h){var g=i[0],x=i[1];return void 0===u&&(u=.2),void 0===c&&(c=8),void 0===m&&(m=.3),void 0===h&&(h=10),d(this,void 0,void 0,function(){var i,d,y,v,b,k;return f(this,function(f){switch(f.label){case 0:return i=n.filter(function(e){return e.score>=u}),$()?[4,Promise.all((y=(0,o.tidy)(function(){var n=P(e,t,i,s,a,l,[g,x],p,c,m,h),u=(0,o.engine)().makeTensorFromDataId(n.dataId,n.shape,n.dtype);return i.map(function(e,t){return(0,o.tidy)(function(){return(0,o.sub)((0,o.mul)((0,o.cast)((0,o.equal)(u,(0,o.scalar)(t)),"int32"),(0,o.add)(r,1)),1)})})})).map(function(e){return e.data()}))]:[3,2];case 1:return d=f.sent(),y.forEach(function(e){return e.dispose()}),[3,6];case 2:return[4,e.data()];case 3:return v=f.sent(),[4,t.data()];case 4:return b=f.sent(),[4,r.data()];case 5:k=f.sent(),d=function(e,t,r,n,s,a,o,l,i,p,u){var c=l[0],d=l[1];void 0===u&&(u=5);for(var f=n.map(function(e){return new Int32Array(s*a).fill(-1)}),m=i.top,h=i.left,g=C([s,a],[c,d],i),x=g[0],y=g[1],v=R([c,d],o)[0],b=0;b<s;b+=1)for(var k=0;k<a;k+=1){var _=b*a+k;if(1===e[_]){var I=A({x:k,y:b},t,n,u,[m,h],[x,y],v,[s,a],o,p);I>=0&&(f[I][_]=r[_])}}return f}(v,b,k,i,s,a,l,[g,x],p,c),f.label=6;case 6:return[2,d.map(function(e,t){return{pose:i[t],data:e,height:s,width:a}})]}})})}(m,h,b,T,n,s,this.baseModel.outputStride,a,p,t.scoreThreshold,t.refineSteps,t.minKeypointScore,t.maxDetections)];case 2:return S=E.sent(),i.dispose(),m.dispose(),h.dispose(),g.dispose(),x.dispose(),y.dispose(),v.dispose(),b.dispose(),[2,S]}})})},e.prototype.dispose=function(){this.baseModel.dispose()},e}(),eh=["left_face","right_face","left_upper_arm_front","left_upper_arm_back","right_upper_arm_front","right_upper_arm_back","left_lower_arm_front","left_lower_arm_back","right_lower_arm_front","right_lower_arm_back","left_hand","right_hand","torso_front","torso_back","left_upper_leg_front","left_upper_leg_back","right_upper_leg_front","right_upper_leg_back","left_lower_leg_front","left_lower_leg_back","right_lower_leg_front","right_lower_leg_back","left_feet","right_feet"],eg=function(){function e(e){this.mask=e}return e.prototype.toCanvasImageSource=function(){return d(this,void 0,void 0,function(){return f(this,function(e){return[2,h(this.mask)]})})},e.prototype.toImageData=function(){return d(this,void 0,void 0,function(){return f(this,function(e){return[2,this.mask]})})},e.prototype.toTensor=function(){return d(this,void 0,void 0,function(){return f(this,function(e){return[2,x(this.mask)]})})},e.prototype.getUnderlyingType=function(){return"imagedata"},e}();function ex(e){if(y(e),255!==e)throw Error("Foreground id must be 255 but got "+e);return"person"}function ey(e){if(y(e),e>=eh.length)throw Error("Invalid body part value "+e);return eh[e]}var ev=function(){function e(e){this.bodyPixModel=e}return e.prototype.segmentPeople=function(e,t){return d(this,void 0,void 0,function(){var r,n,s,a;return f(this,function(o){switch(o.label){case 0:return e instanceof ImageBitmap&&((r=document.createElement("canvas")).getContext("2d").drawImage(e,0,0),e=r),t.segmentBodyParts?t.multiSegmentation?[4,this.bodyPixModel.segmentMultiPersonParts(e,t)]:[3,2]:[3,5];case 1:return s=o.sent(),[3,4];case 2:return[4,this.bodyPixModel.segmentPersonParts(e,t)];case 3:s=[o.sent()],o.label=4;case 4:return n=s.map(function(e){var t=e.data,r=e.width,n=e.height,s=new Uint8ClampedArray(r*n*4).fill(0);return t.forEach(function(e,t){-1===e?(s[4*t]=eh.length,s[4*t+3]=0):(s[4*t]=e,s[4*t+3]=255)}),{maskValueToLabel:ey,mask:new eg(new ImageData(s,r,n))}}),[3,10];case 5:return t.multiSegmentation?[4,this.bodyPixModel.segmentMultiPerson(e,t)]:[3,7];case 6:return a=o.sent(),[3,9];case 7:return[4,this.bodyPixModel.segmentPerson(e,t)];case 8:a=[o.sent()],o.label=9;case 9:n=a.map(function(e){var t=e.data,r=e.width,n=e.height,s=new Uint8ClampedArray(r*n*4).fill(0);return t.forEach(function(e,t){0===e?(s[4*t]=0,s[4*t+3]=0):(s[4*t]=255,s[4*t+3]=255)}),{maskValueToLabel:ex,mask:new eg(new ImageData(s,r,n))}}),o.label=10;case 10:return[2,n]}})})},e.prototype.dispose=function(){this.bodyPixModel.dispose()},e.prototype.reset=function(){},e}(),eb={runtime:"mediapipe",modelType:"general"},ek=function(){function e(e){this.mask=e}return e.prototype.toCanvasImageSource=function(){return d(this,void 0,void 0,function(){return f(this,function(e){return[2,this.mask]})})},e.prototype.toImageData=function(){return d(this,void 0,void 0,function(){return f(this,function(e){return[2,g(this.mask)]})})},e.prototype.toTensor=function(){return d(this,void 0,void 0,function(){return f(this,function(e){return[2,x(this.mask)]})})},e.prototype.getUnderlyingType=function(){return"canvasimagesource"},e}();function e_(e){return y(e),"person"}var eI=function(){function e(e){var t,r,n=this;this.selfieMode=!1,t=+(this.selfieSegmentationSolution=new(0,i.SelfieSegmentation)({locateFile:null!=(r=e.locateFile)?r:function(t,r){return e.solutionPath?e.solutionPath.replace(/\/+$/,"")+"/"+t:r+"/"+t}}),"landscape"===e.modelType),this.selfieSegmentationSolution.setOptions({modelSelection:t,selfieMode:this.selfieMode}),this.selfieSegmentationSolution.onResults(function(e){n.segmentation=[{maskValueToLabel:e_,mask:new ek(e.segmentationMask)}]})}return e.prototype.segmentPeople=function(e,t){return d(this,void 0,void 0,function(){var r,n;return f(this,function(s){switch(s.label){case 0:return t&&t.flipHorizontal&&t.flipHorizontal!==this.selfieMode&&(this.selfieMode=t.flipHorizontal,this.selfieSegmentationSolution.setOptions({selfieMode:this.selfieMode})),e instanceof o.Tensor?(n=ImageData.bind,[4,o.browser.toPixels(e)]):[3,2];case 1:return r=new(n.apply(ImageData,[void 0,s.sent(),e.shape[1],e.shape[0]])),[3,3];case 2:r=e,s.label=3;case 3:return e=r,[4,this.selfieSegmentationSolution.send({image:e})];case 4:return s.sent(),[2,this.segmentation]}})})},e.prototype.dispose=function(){this.selfieSegmentationSolution.close()},e.prototype.reset=function(){this.selfieSegmentationSolution.reset(),this.segmentation=null,this.selfieMode=!1},e.prototype.initialize=function(){return this.selfieSegmentationSolution.initialize()},e}();function ej(e){return e instanceof o.Tensor?{height:e.shape[0],width:e.shape[1]}:{height:e.height,width:e.width}}function ew(e,t){o.util.assert(0!==e.width,function(){return t+" width cannot be 0."}),o.util.assert(0!==e.height,function(){return t+" height cannot be 0."})}var eT={runtime:"tfjs",modelType:"general",modelUrl:"https://tfhub.dev/mediapipe/tfjs-model/selfie_segmentation/general/1"},eS={flipHorizontal:!1},eC={outputTensorSize:{width:256,height:256},keepAspectRatio:!1,borderMode:"zero",outputTensorFloatRange:[0,1]},eN={outputTensorSize:{width:256,height:144},keepAspectRatio:!1,borderMode:"zero",outputTensorFloatRange:[0,1]},eE={activation:"none"},eF=function(){function e(e){this.mask=e}return e.prototype.toCanvasImageSource=function(){return d(this,void 0,void 0,function(){return f(this,function(e){return[2,h(this.mask)]})})},e.prototype.toImageData=function(){return d(this,void 0,void 0,function(){return f(this,function(e){return[2,g(this.mask)]})})},e.prototype.toTensor=function(){return d(this,void 0,void 0,function(){return f(this,function(e){return[2,this.mask]})})},e.prototype.getUnderlyingType=function(){return"tensor"},e}();function eA(e){return y(e),"person"}var eR,eP=function(){function e(e,t){this.modelType=e,this.model=t}return e.prototype.segmentPeople=function(e,t){return d(this,void 0,void 0,function(){var r=this;return f(this,function(n){return t=function(e){if(null==e)return c({},eS);var t=c({},e);return null==t.flipHorizontal&&(t.flipHorizontal=eS.flipHorizontal),t}(t),null==e?(this.reset(),[2,[]]):[2,[{maskValueToLabel:eA,mask:new eF((0,o.tidy)(function(){var t,n,s,a,l,i,p,u,c,d,f,m,h,g,x,y,v,b,k,_,I,j,w=(x=(t="general"===r.modelType?eC:eN).outputTensorSize,y=t.keepAspectRatio,v=t.borderMode,b=t.outputTensorFloatRange,I=function(e,t,r){if(void 0===r&&(r=!1),!r)return{top:0,left:0,right:0,bottom:0};var n=t.height,s=t.width;ew(t,"targetSize"),ew(e,"roi");var a,o,l=n/s,i=e.height/e.width,p=0,u=0;return l>i?(a=e.width,o=e.width*l,u=(1-i/l)/2):(a=e.height/l,o=e.height,p=(1-l/i)/2),e.width=a,e.height=o,{top:u,left:p,right:p,bottom:u}}((n=k=ej(e),_={xCenter:.5*n.width,yCenter:.5*n.height,width:n.width,height:n.height,rotation:0}),x,y),s=k.width,a=k.height,l=_.width,i=_.height,p=1,u=Math.cos(_.rotation),c=Math.sin(_.rotation),d=_.xCenter,f=_.yCenter,m=1/s,h=1/a,(g=Array(16))[0]=l*u*p*m,g[1]=-i*c*m,g[2]=0,g[3]=(-.5*l*u*p+.5*i*c+d)*m,g[4]=l*c*p*h,g[5]=i*u*h,g[6]=0,g[7]=(-.5*i*u-.5*l*c*p+f)*h,g[8]=0,g[9]=0,g[10]=l*m,g[11]=0,g[12]=0,g[13]=0,g[14]=0,g[15]=1,j=function(e){if(16!==e.length)throw Error("Array length must be 16 but got "+e.length);return[[e[0],e[1],e[2],e[3]],[e[4],e[5],e[6],e[7]],[e[8],e[9],e[10],e[11]],[e[12],e[13],e[14],e[15]]]}(g),{imageTensor:(0,o.tidy)(function(){var t,r=e instanceof o.Tensor?e:o.browser.fromPixels(e),n=(0,o.tensor2d)((ew(x,"inputResolution"),[1/x.width*j[0][0]*k.width,1/x.height*j[0][1]*k.width,j[0][3]*k.width,1/x.width*j[1][0]*k.height,1/x.height*j[1][1]*k.height,j[1][3]*k.height,0,0]),[1,8]),s=o.image.transform((0,o.expandDims)((0,o.cast)(r,"float32")),n,"bilinear","zero"===v?"constant":"nearest",0,[x.height,x.width]);return null!=b?(t=function(e,t,r,n){!1;var s=(n-r)/255;return{scale:s,offset:r-0*s}}(0,0,b[0],b[1]),(0,o.tidy)(function(){return(0,o.add)((0,o.mul)(s,t.scale),t.offset)})):s}),padding:I,transformationMatrix:j}).imageTensor,T=(0,o.slice)(r.model.predict(w),[0,0,0,1],-1),S=ej(e),C=(0,o.tidy)(function(){var e=(0,o.squeeze)(T,[0]),t=e.shape[2];if(1===t){var r=e;switch(eE.activation){case"none":break;case"sigmoid":r=(0,o.sigmoid)(r);break;case"softmax":throw Error("Softmax activation requires two channels.");default:throw Error("Activation not supported ("+eE.activation+")")}var n=S?o.image.resizeBilinear(r,[S.height,S.width]):r;return(0,o.squeeze)(n,[2])}throw Error("Unsupported number of tensor channels "+t)}),N=(0,o.expandDims)(C,2),E=(0,o.pad)(N,[[0,0],[0,0],[0,1]]);return(0,o.mirrorPad)(E,[[0,0],[0,0],[0,2]],"symmetric")}))}]]})})},e.prototype.dispose=function(){this.model.dispose()},e.prototype.reset=function(){},e}();function e$(e,t){return d(this,void 0,void 0,function(){var r,n;return f(this,function(s){switch(e){case eR.MediaPipeSelfieSegmentation:if(r=void 0,null!=(n=t)){if("tfjs"===n.runtime)return[2,function(e){return d(this,void 0,void 0,function(){var t,r,n;return f(this,function(s){switch(s.label){case 0:return r="string"==typeof(t=function(e){if(null==e)return c({},eT);var t=c({},e);if(t.runtime="tfjs",null==t.modelType&&(t.modelType=eT.modelType),"general"!==t.modelType&&"landscape"!==t.modelType)throw Error("Model type must be one of general or landscape, but got "+t.modelType);return null==t.modelUrl&&("general"===t.modelType?t.modelUrl="https://tfhub.dev/mediapipe/tfjs-model/selfie_segmentation/general/1":t.modelUrl="https://tfhub.dev/mediapipe/tfjs-model/selfie_segmentation/landscape/1"),t}(e)).modelUrl&&t.modelUrl.indexOf("https://tfhub.dev")>-1,[4,(0,l.loadGraphModel)(t.modelUrl,{fromTFHub:r})];case 1:return n=s.sent(),[2,new eP(t.modelType,n)]}})})}(n)];if("mediapipe"===n.runtime)return[2,function(e){return d(this,void 0,void 0,function(){var t;return f(this,function(r){switch(r.label){case 0:return[4,(t=new eI(function(e){if(null==e)return c({},eb);var t=c({},e);return t.runtime="mediapipe",null==t.modelType&&(t.modelType=eb.modelType),t}(e))).initialize()];case 1:return r.sent(),[2,t]}})})}(n)];r=n.runtime}throw Error("Expect modelConfig.runtime to be either 'tfjs' or 'mediapipe', but got "+r);case eR.BodyPix:return[2,function(e){return d(this,void 0,void 0,function(){return f(this,function(t){return[2,(function(e){return void 0===e&&(e=ea),d(this,void 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Should be one of "+eo);if(null==e.outputStride&&(e.outputStride=16),0>el[e.architecture].indexOf(e.outputStride))throw Error("Invalid outputStride "+e.outputStride+". Should be one of "+el[e.architecture]+" for architecture "+e.architecture+".");if(null==e.multiplier&&(e.multiplier=1),0>ei[e.architecture].indexOf(e.multiplier))throw Error("Invalid multiplier "+e.multiplier+". Should be one of "+ei[e.architecture]+" for architecture "+e.architecture+".");if(null==e.quantBytes&&(e.quantBytes=4),0>ep.indexOf(e.quantBytes))throw Error("Invalid quantBytes "+e.quantBytes+". Should be one of "+ep+" for architecture "+e.architecture+".");return e}(e)).architecture?[2,function(e){return d(this,void 0,void 0,function(){var t,r,n;return f(this,function(s){switch(s.label){case 0:var a;if(t=e.outputStride,r=e.quantBytes,null==o)throw Error("Cannot find TensorFlow.js. If you are using a<script>tag, please also include @tensorflow/tfjs on the page before using this\n model.");return a="model-stride"+t+".json",n=4===r?K+"float/"+a:K+"quant"+r+"/"+a,[4,(0,l.loadGraphModel)(e.modelUrl||n)];case 1:return[2,new em(new H(s.sent(),t))]}})})}(e)]:"MobileNetV1"===e.architecture?[2,function(e){return d(this,void 0,void 0,function(){var t,r,n,s;return f(this,function(a){switch(a.label){case 0:var i,p;if(t=e.outputStride,r=e.quantBytes,n=e.multiplier,null==o)throw Error("Cannot find TensorFlow.js. If you are using a<script>tag, please also include @tensorflow/tfjs on the page before using this\n model.");return i={1:"100",.75:"075",.5:"050"},p="model-stride"+t+".json",s=4===r?X+"float/"+i[n]+"/"+p:X+"quant"+r+"/"+i[n]+"/"+p,[4,(0,l.loadGraphModel)(e.modelUrl||s)];case 1:return[2,new em(new j(a.sent(),t))]}})})}(e)]:[2,null]})})})(e).then(function(e){return new ev(e)})]})})}(n=t)];default:throw Error(e+" is not a supported model name.")}})})}(s=eR||(eR={})).BodyPix="BodyPix",s.MediaPipeSelfieSegmentation="MediaPipeSelfieSegmentation";var eO="blurred",eD="blurred-mask",eM="mask",eB={};function eG(e,t,r,n){var s=e.width,a=e.height,o=t.width,l=t.height;if(s!==o||a!==l)throw Error("error: dimensions must match. "+r+" has dimensions "+s+"x"+a+", "+n+" has dimensions "+o+"x"+l)}function eV(e){if("undefined"!=typeof HTMLCanvasElement&&e instanceof HTMLCanvasElement||"undefined"!=typeof OffscreenCanvas&&e instanceof OffscreenCanvas||"undefined"!=typeof HTMLImageElement&&e instanceof HTMLImageElement){if("offsetHeight"in e&&0!==e.offsetHeight&&"offsetWidth"in e&&0!==e.offsetWidth)return[e.offsetHeight,e.offsetWidth];if(null!=e.height&&null!=e.width)return[e.height,e.width];throw Error("HTMLImageElement must have height and width attributes set.")}if("undefined"!=typeof ImageData&&e instanceof ImageData)return[e.height,e.width];if("undefined"!=typeof HTMLVideoElement&&e instanceof HTMLVideoElement)return e.hasAttribute("height")&&e.hasAttribute("width")?[e.height,e.width]:[e.videoHeight,e.videoWidth];if(e instanceof o.Tensor)return[e.shape[0],e.shape[1]];throw Error("error: Unknown input type: "+e+".")}function eL(e){return eB[e]||(eB[e]=function(){if("undefined"!=typeof document)return document.createElement("canvas");if("undefined"!=typeof OffscreenCanvas)return new OffscreenCanvas(0,0);throw Error("Cannot create a canvas in this context")}()),eB[e]}function ez(e,t){var r=eL(t);return r.width=e.width,r.height=e.height,r.getContext("2d").putImageData(e,0,0),r}function eU(e,t,r,n,s,a){return d(this,void 0,void 0,function(){var l,i,p;return f(this,function(u){switch(u.label){case 0:return t instanceof o.Tensor?[4,o.browser.toPixels(t)]:[3,2];case 1:l=u.sent(),p=(i=eV(t))[0],t=new ImageData(l,i[1],p),u.label=2;case 2:return t instanceof ImageData&&(t=ez(t,"draw-image")),null==s||null==a?e.drawImage(t,r,n):e.drawImage(t,r,n,s,a),[2]}})})}function eW(e){var t=e.getContext("2d");t.scale(-1,1),t.translate(-e.width,0)}function eq(e,t,r){return d(this,void 0,void 0,function(){return f(this,function(n){switch(n.label){case 0:return e.globalCompositeOperation=r,[4,eU(e,t,0,0)];case 1:return n.sent(),[2]}})})}function eH(e,t,r){return d(this,void 0,void 0,function(){var n;return 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u<=r?(n.globalAlpha=o*Math.exp(-(u*u+p*p)/(2*a*a))/s*r,[4,eU(n,t,u,p)]):[3,5];case 3:c.sent(),c.label=4;case 4:return u+=l,[3,2];case 5:return p+=l,[3,1];case 6:return n.globalAlpha=1,[2]}})})}(r,e,t)]:[3,2];case 1:return l.sent(),[3,4];case 2:return o.filter="blur("+t+"px)",[4,eU(o,e,0,0,a,s)];case 3:l.sent(),l.label=4;case 4:return o.restore(),[2]}})})}(e,t,n)];case 3:s.sent(),s.label=4;case 4:return[2,n]}})})}function eK(e,t,r,n,s,a){return void 0===t&&(t={r:0,g:0,b:0,a:0}),void 0===r&&(r={r:0,g:0,b:0,a:255}),void 0===n&&(n=!1),void 0===s&&(s=.5),void 0===a&&(a=Array.from(Array(256).keys())),d(this,void 0,void 0,function(){var o,l,i,p,u,c,d,m,h,g,x,y,v,b;return f(this,function(f){switch(f.label){case 0:return 0===(o=Array.isArray(e)?e:[e]).length?[2,null]:[4,Promise.all(o.map(function(e){return e.mask.toImageData()}))];case 1:for(c=new Uint8ClampedArray((p=(i=(l=f.sent())[0]).width)*(u=i.height)*4),d=Math.round(255*s),m=Array(256).fill(!1),a.forEach(function(e){return 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e.mask.toImageData()}))];case 1:for(p=new Uint8ClampedArray((l=(o=(a=f.sent())[0]).width)*(i=o.height)*4),u=Math.round(255*n),c=0;c<i*l;++c)for(p[(d=4*c)+0]=r.r,p[d+1]=r.g,p[d+2]=r.b,p[d+3]=r.a,m=0,h=a;m<h.length;m++)(g=h[m]).data[d+3]>=u&&(x=t(g.data[d]),p[d+0]=x.r,p[d+1]=x.g,p[d+2]=x.b,p[d+3]=x.a);return[2,new ImageData(p,l,i)]}})})}function eZ(e,t,r,n,s,a){return void 0===n&&(n=.7),void 0===s&&(s=0),void 0===a&&(a=!1),d(this,void 0,void 0,function(){var o,l,i,p,u;return f(this,function(c){switch(c.label){case 0:return l=(o=eV(t))[0],e.width=i=o[1],e.height=l,(p=e.getContext("2d")).save(),a&&eW(e),[4,eU(p,t,0,0)];case 1:return c.sent(),p.globalAlpha=n,r?(eG({width:i,height:l},r,"image","mask"),[4,eH(ez(r,eM),s,eD)]):[3,3];case 2:u=c.sent(),p.drawImage(u,0,0,i,l),c.label=3;case 3:return p.restore(),[2]}})})}function eY(e,t,r,n,s,a,o){return void 0===n&&(n=.7),void 0===s&&(s=0),void 0===a&&(a=!1),void 0===o&&(o=10),d(this,void 0,void 0,function(){var l,i,p,u,c,d,m;return f(this,function(f){switch(f.label){case 0:return i=(l=eV(t))[0],eG({width:l[1],height:i},r,"image","mask"),[4,eH(ez(r,eM),s,eD)];case 1:for(e.width=(p=f.sent()).width,e.height=p.height,(u=e.getContext("2d")).save(),a&&eW(e),d=(c=eL("lowres-part-mask")).getContext("2d"),c.width=p.width*(1/o),c.height=p.height*(1/o),d.drawImage(p,0,0,p.width,p.height,0,0,c.width,c.height),u.imageSmoothingEnabled=!1,u.drawImage(c,0,0,c.width,c.height,0,0,e.width,e.height),m=0;m<c.width;m++)u.beginPath(),u.strokeStyle="#ffffff",u.moveTo(o*m,0),u.lineTo(o*m,e.height),u.stroke();for(m=0;m<c.height;m++)u.beginPath(),u.strokeStyle="#ffffff",u.moveTo(0,o*m),u.lineTo(e.width,o*m),u.stroke();return u.globalAlpha=1-n,[4,eU(u,t,0,0,p.width,p.height)];case 2:return f.sent(),u.restore(),[2]}})})}function eQ(e,t,r,n,s,a,o){return void 0===n&&(n=.5),void 0===s&&(s=3),void 0===a&&(a=3),void 0===o&&(o=!1),d(this,void 0,void 0,function(){var l,i,p,u,c,m;return f(this,function(h){switch(h.label){case 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s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"Engine",()=>y),s.export(r,"getOrMakeEngine",()=>v),s.export(r,"ENGINE",()=>b),s.export(r,"add",()=>k);var a=e("./backends/backend"),o=e("./environment"),l=e("./global_util"),i=e("./kernel_names"),p=e("./kernel_registry"),u=e("./log"),c=e("./profiler"),d=e("./tape"),f=e("./tensor"),m=e("./tensor_util"),h=e("./util");function g(e){return null!=e.kernelName}class x{constructor(){this.registeredVariables={},this.nextTapeNodeId=0,this.numBytes=0,this.numTensors=0,this.numStringTensors=0,this.numDataBuffers=0,this.gradientDepth=0,this.kernelDepth=0,this.scopeStack=[],this.numDataMovesStack=[],this.nextScopeId=0,this.tensorInfo=new WeakMap,this.profiling=!1,this.activeProfile={newBytes:0,newTensors:0,peakBytes:0,kernels:[],result:null,get kernelNames(){return Array.from(new Set(this.kernels.map(e=>e.name)))}}}dispose(){for(let e in this.registeredVariables)this.registeredVariables[e].dispose()}}class 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this.registry[e]=r,{success:!0,asyncInit:!1};{let t=++this.pendingBackendInitId,n=r.then(r=>!(t<this.pendingBackendInitId)&&(this.registry[e]=r,this.pendingBackendInit=null,!0)).catch(r=>!(t<this.pendingBackendInitId)&&(this.pendingBackendInit=null,u.warn(`Initialization of backend ${e} failed`),u.warn(r.stack||r.message),!1));return this.pendingBackendInit=n,{success:n,asyncInit:!0}}}catch(t){return u.warn(`Initialization of backend ${e} failed`),u.warn(t.stack||t.message),{success:!1,asyncInit:!1}}}removeBackend(e){if(!(e in this.registryFactory))throw Error(`${e} backend not found in registry`);this.backendName===e&&null!=this.pendingBackendInit&&this.pendingBackendInitId++,e in this.registry&&(this.disposeRegisteredKernels(e),this.registry[e].dispose(),delete this.registry[e]),delete this.registryFactory[e],this.backendName===e&&(this.pendingBackendInit=null,this.backendName=null,this.backendInstance=null)}getSortedBackends(){if(0===Object.keys(this.registryFactory).length)throw Error("No backend found in registry.");return Object.keys(this.registryFactory).sort((e,t)=>this.registryFactory[t].priority-this.registryFactory[e].priority)}initializeBackendsAndReturnBest(){let e=this.getSortedBackends();for(let t=0;t<e.length;t++){let r=e[t],{success:n,asyncInit:s}=this.initializeBackend(r);if(s||n)return{name:r,asyncInit:s}}throw Error("Could not initialize any backends, all backend initializations failed.")}moveData(e,t){let r=this.state.tensorInfo.get(t),n=r.backend,s=this.readSync(t),a=n.refCount(t);n.disposeData(t,!0),r.backend=e,e.move(t,s,r.shape,r.dtype,a),this.shouldCheckForMemLeaks()&&this.state.numDataMovesStack[this.state.numDataMovesStack.length-1]++}tidy(e,t){let r,n=null;if(null==t){if("function"!=typeof e)throw Error("Please provide a function to tidy()");t=e}else{if("string"!=typeof e&&!(e instanceof String))throw Error("When calling with two arguments, the first argument to tidy() must be a string");if("function"!=typeof t)throw Error("When 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a=this.state.numDataMovesStack[this.state.numDataMovesStack.length-1],o=n-t-s-a;if(o>0)throw Error(`Backend '${this.backendName}' has an internal memory leak (${o} data ids) after running '${e}'`)}runKernelFunc(e){let t,r,n,s,a=[],o=this.isTapeOn(),l=this.state.numBytes,i=this.state.numTensors;this.shouldCheckForMemLeaks()&&this.state.numDataMovesStack.push(0),null==this.backendName&&this.backend;let u=g(e)?e.kernelName:null!=this.state.activeScope?this.state.activeScope.name:"";if(g(e)){let{kernelName:t,inputs:s,attrs:l}=e;null==this.backendName&&this.backend;let i=(0,p.getKernel)(t,this.backendName);h.assert(null!=i,()=>`Cannot find registered kernel '${t}' for backend '${this.backendName}'`),r=()=>{let e=this.backend.numDataIds(),r=Array.isArray(n=i.kernelFunc({inputs:s,attrs:l,backend:this.backend}))?n:[n];this.shouldCheckForMemLeaks()&&this.checkKernelForMemLeak(t,e,r);let p=r.map(e=>null!=e.rank?e:this.makeTensorFromTensorInfo(e));if(o){let e=this.getTensorsForGradient(t,s,p);a=this.saveTensorsForBackwardMode(e)}return p}}else{let{forwardFunc:t}=e,s=e=>{o&&(a=e.map(e=>this.keep(this.clone(e))))};r=()=>{let e=this.backend.numDataIds(),r=Array.isArray(n=this.tidy(()=>t(this.backend,s)))?n:[n];return this.shouldCheckForMemLeaks()&&this.checkKernelForMemLeak(u,e,r),r}}let{inputs:c,attrs:d}=e,f=g(e)?null:e.backwardsFunc;return this.scopedRun(()=>this.state.kernelDepth++,()=>this.state.kernelDepth--,()=>{this.ENV.getBool("DEBUG")||this.state.profiling?(s=this.profiler.profileKernel(u,c,()=>r()),this.ENV.getBool("DEBUG")&&this.profiler.logKernelProfile(s),t=s.outputs):t=r()}),o&&this.addTapeNode(u,c,t,f,a,d),this.state.profiling&&this.state.activeProfile.kernels.push({name:u,bytesAdded:this.state.numBytes-l,totalBytesSnapshot:this.state.numBytes,tensorsAdded:this.state.numTensors-i,totalTensorsSnapshot:this.state.numTensors,inputShapes:Object.keys(c).map(e=>null!=c[e]?c[e].shape:null),outputShapes:t.map(e=>e.shape),kernelTimeMs:s.timeMs,extraInfo:s.extraInfo}),Array.isArray(n)?t:t[0]}saveTensorsForBackwardMode(e){return e.map(e=>this.keep(this.clone(e)))}getTensorsForGradient(e,t,r){let n=(0,p.getGradient)(e);if(null!=n){let e,s=n.inputsToSave||[],a=n.outputsToSave||[];n.saveAllInputs?(h.assert(Array.isArray(t),()=>"saveAllInputs is true, expected inputs to be an 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a=e("../engine"),o=e("../globals"),l=e("../ops/add"),i=e("../ops/mul"),p=e("../ops/scalar"),u=e("../ops/zeros_like"),c=e("./sgd_optimizer");class d extends c.SGDOptimizer{static get className(){return"Momentum"}constructor(e,t,r=!1){super(e),this.learningRate=e,this.momentum=t,this.useNesterov=r,this.accumulations=[],this.m=(0,p.scalar)(this.momentum)}applyGradients(e){(Array.isArray(e)?e.map(e=>e.name):Object.keys(e)).forEach((t,r)=>{let n=a.ENGINE.registeredVariables[t];null==this.accumulations[r]&&(this.accumulations[r]={originalName:`${t}/momentum`,variable:(0,o.tidy)(()=>(0,u.zerosLike)(n).variable(!1))});let s=this.accumulations[r].variable,p=Array.isArray(e)?e[r].tensor:e[t];null!=p&&(0,o.tidy)(()=>{let 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e(t.learningRate,t.momentum,t.useNesterov)}}},{"../engine":"5aImO","../globals":"1ONwU","../ops/add":"6AYbH","../ops/mul":"6u9Cs","../ops/scalar":"fhZsH","../ops/zeros_like":"gLLzC","./sgd_optimizer":"jvslj","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],jvslj:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"SGDOptimizer",()=>c);var a=e("../engine"),o=e("../globals"),l=e("../ops/add"),i=e("../ops/mul"),p=e("../ops/scalar"),u=e("./optimizer");class c extends u.Optimizer{static get className(){return"SGD"}constructor(e){super(),this.learningRate=e,this.setLearningRate(e)}applyGradients(e){(Array.isArray(e)?e.map(e=>e.name):Object.keys(e)).forEach((t,r)=>{let n=Array.isArray(e)?e[r].tensor:e[t];if(null==n)return;let s=a.ENGINE.registeredVariables[t];(0,o.tidy)(()=>{let 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e=[...this.accumulatedMeanSquares,...this.accumulatedMoments];return this.centered&&e.push(...this.accumulatedMeanGrads),[await this.saveIterations()].concat(e.map(e=>({name:e.originalName,tensor:e.variable})))}async setWeights(e){e=await this.extractIterations(e);let t=this.centered?e.length/3:e.length/2;this.accumulatedMeanSquares=e.slice(0,t).map(e=>({originalName:e.name,variable:e.tensor.variable(!1)})),this.accumulatedMoments=e.slice(t,2*t).map(e=>({originalName:e.name,variable:e.tensor.variable(!1)})),this.centered&&(this.accumulatedMeanGrads=e.slice(2*t,3*t).map(e=>({originalName:e.name,variable:e.tensor.variable(!1)})))}getConfig(){return{learningRate:this.learningRate,decay:this.decay,momentum:this.momentum,epsilon:this.epsilon,centered:this.centered}}static fromConfig(e,t){return new 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null!=s&&(p=(0,a.convertToTensor)(s,"scale","batchNorm")),null!=n&&(u=(0,a.convertToTensor)(n,"offset","batchNorm")),o.assert(4===c.rank,()=>`Error in batchNorm4D: x must be rank 4 but got rank ${c.rank}.`),o.assert(4===d.rank||1===d.rank,()=>`Error in batchNorm4D: mean must be rank 4 or rank 1 but got rank ${d.rank}.`),o.assert(4===f.rank||1===f.rank,()=>`Error in batchNorm4D: variance must be rank 4 or rank 1 but got rank ${f.rank}.`),null!=p&&o.assert(4===p.rank||1===p.rank,()=>`Error in batchNorm4D: scale must be rank 4 or rank 1 but got rank ${p.rank}.`),null!=u&&o.assert(4===u.rank||1===u.rank,()=>`Error in batchNorm4D: offset must be rank 4 or rank 1 but got rank ${u.rank}.`),(0,l.batchNorm)(c,d,f,u,p,i)}})},{"../tensor_util_env":"feaHs","../util":"98aA6","./batchnorm":"8P8kQ","./operation":"2qT2c","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],gV0pt:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"bincount",()=>p);var a=e("../engine"),o=e("../kernel_names"),l=e("../tensor_util_env"),i=e("../util");let p=(0,e("./operation").op)({bincount_:function(e,t,r){let n=(0,l.convertToTensor)(e,"x","bincount"),s=(0,l.convertToTensor)(t,"weights","bincount");return i.assert("int32"===n.dtype,()=>`Error in bincount: input dtype must be int32, but got ${n.dtype}`),i.assert(r>=0,()=>`size must be non-negative, but got ${r}.`),i.assert(s.size===n.size||0===s.size,()=>`Error in bincount: weights must have the same size as input or0-length, but got input shape: ${n.shape}, weights shape: ${s.shape}.`),a.ENGINE.runKernel(o.Bincount,{x:n,weights:s},{size:r})}})},{"../engine":"5aImO","../kernel_names":"bvyjS","../tensor_util_env":"feaHs","../util":"98aA6","./operation":"2qT2c","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],hQztO:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"bitwiseAnd",()=>p);var a=e("../engine"),o=e("../kernel_names"),l=e("../tensor_util_env"),i=e("../util_base");let p=(0,e("./operation").op)({bitwiseAnd_:function(e,t){let r=(0,l.convertToTensor)(e,"x","bitwiseAnd"),n=(0,l.convertToTensor)(t,"y","bitwiseAnd");if(!(0,i.arraysEqual)(r.shape,n.shape))throw Error(`BitwiseAnd: Tensors must have the same shape. x: ${r.shape}, y: ${n.shape}`);if("int32"!==r.dtype||"int32"!==n.dtype)throw Error(`BitwiseAnd: Only supports 'int32' values in tensor, found type of x: ${r.dtype} and type of y: ${n.dtype}`);return a.ENGINE.runKernel(o.BitwiseAnd,{a:r,b:n})}})},{"../engine":"5aImO","../kernel_names":"bvyjS","../tensor_util_env":"feaHs","../util_base":"F0lVc","./operation":"2qT2c","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],kesHt:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"broadcastArgs",()=>i);var a=e("../engine"),o=e("../kernel_names"),l=e("../tensor_util_env");let i=(0,e("./operation").op)({broadcastArgs_:function(e,t){let r=(0,l.convertToTensor)(e,"s0","broadcastArgs","int32"),n=(0,l.convertToTensor)(t,"s1","broadcastArgs","int32");if(1!==r.rank)throw Error(`broadcastArgs(): first input must be a vector (rank=1). Has rank ${r.rank}`);if(1!==n.rank)throw Error(`broadcastArgs(): second input must be a vector (rank=1). Has rank ${n.rank}`);return a.ENGINE.runKernel(o.BroadcastArgs,{s0:r,s1:n})}})},{"../engine":"5aImO","../kernel_names":"bvyjS","../tensor_util_env":"feaHs","./operation":"2qT2c","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],"3ybay":[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"broadcastTo",()=>d);var a=e("../engine"),o=e("../kernel_names"),l=e("../tensor_util_env"),i=e("../util_base"),p=e("./clone"),u=e("./operation"),c=e("./reshape");let d=(0,u.op)({broadcastTo_:function(e,t){let r=(0,l.convertToTensor)(e,"broadcastTo","x"),n=r.shape;if((0,i.assertNonNegativeIntegerDimensions)(t),t.length<r.rank)throw Error(`broadcastTo(): shape.length=${t.length} < input.rank=${r.rank}.`);if(t.length>r.rank){let e=r.shape.slice();for(;e.length<t.length;)e.unshift(1);r=(0,c.reshape)(r,e)}let s=r.shape,u=Array.from(t);for(let e=t.length-1;e>=0;e--)if(s[e]===t[e])u[e]=1;else if(1!==r.shape[e])throw Error(`broadcastTo(): [${n}] cannot be broadcast to [${t}].`);if(0===u.map((e,t)=>e>1?t:-1).filter(e=>e>=0).length)return(0,p.clone)(r);let d={x:r};return a.ENGINE.runKernel(o.Tile,d,{reps:u})}})},{"../engine":"5aImO","../kernel_names":"bvyjS","../tensor_util_env":"feaHs","../util_base":"F0lVc","./clone":"jyVCU","./operation":"2qT2c","./reshape":"i9E3v","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],"9mzTI":[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"ceil",()=>i);var a=e("../engine"),o=e("../kernel_names"),l=e("../tensor_util_env");let i=(0,e("./operation").op)({ceil_:function(e){let t=(0,l.convertToTensor)(e,"x","ceil","float32");return a.ENGINE.runKernel(o.Ceil,{x:t})}})},{"../engine":"5aImO","../kernel_names":"bvyjS","../tensor_util_env":"feaHs","./operation":"2qT2c","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],c5XEh:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"clipByValue",()=>u);var a=e("../engine"),o=e("../kernel_names"),l=e("../tensor_util_env"),i=e("../util"),p=e("./fill");let u=(0,e("./operation").op)({clipByValue_:function(e,t,r){let n=(0,l.convertToTensor)(e,"x","clipByValue");return(i.assert(t<=r,()=>`Error in clip: min (${t}) must be less than or equal to max (${r}).`),t===r)?(0,p.fill)(n.shape,t,n.dtype):a.ENGINE.runKernel(o.ClipByValue,{x:n},{clipValueMin:t,clipValueMax:r})}})},{"../engine":"5aImO","../kernel_names":"bvyjS","../tensor_util_env":"feaHs","../util":"98aA6","./fill":"5rPaY","./operation":"2qT2c","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],"6Sscv":[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"concat1d",()=>o);var a=e("./concat");let o=(0,e("./operation").op)({concat1d_:function(e){return(0,a.concat)(e,0)}})},{"./concat":"fUcw1","./operation":"2qT2c","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],gyHEd:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"concat2d",()=>o);var a=e("./concat");let o=(0,e("./operation").op)({concat2d_:function(e,t){return(0,a.concat)(e,t)}})},{"./concat":"fUcw1","./operation":"2qT2c","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],bsQ4C:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"concat3d",()=>o);var a=e("./concat");let o=(0,e("./operation").op)({concat3d_:function(e,t){return(0,a.concat)(e,t)}})},{"./concat":"fUcw1","./operation":"2qT2c","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],"2hiy1":[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"concat4d",()=>o);var a=e("./concat");let o=(0,e("./operation").op)({concat4d_:function(e,t){return(0,a.concat)(e,t)}})},{"./concat":"fUcw1","./operation":"2qT2c","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],ldpLm:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"conv1d",()=>c);var a=e("../tensor_util_env"),o=e("../util"),l=e("./conv2d"),i=e("./conv_util"),p=e("./operation"),u=e("./reshape");let c=(0,p.op)({conv1d_:function(e,t,r,n,s="NWC",p=1,c){let d=(0,a.convertToTensor)(e,"x","conv1d"),f=(0,a.convertToTensor)(t,"filter","conv1d"),m=d,h=!1;2===d.rank&&(h=!0,m=(0,u.reshape)(d,[1,d.shape[0],d.shape[1]])),o.assert(3===m.rank,()=>`Error in conv1d: input must be rank 3, but got rank ${m.rank}.`),o.assert(3===f.rank,()=>`Error in conv1d: filter must be rank 3, but got rank ${f.rank}.`),i.checkPadOnDimRoundingMode("conv1d",n,c),o.assert(m.shape[2]===f.shape[1],()=>`Error in conv1d: depth of input (${m.shape[2]}) must match input depth for filter ${f.shape[1]}.`),o.assert(i.eitherStridesOrDilationsAreOne(r,p),()=>`Error in conv1D: Either stride or dilation must be 1. 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Got strides ${r} and dilations '${u}'`),i.assert(p.stridesOrDilationsArePositive(u),()=>"Error in conv2D: Dilated rates should be larger than 0."),i.assert(p.stridesOrDilationsArePositive(r),()=>"Error in conv2D: Strides should be larger than 0.");let y={x:h,filter:m},v=a.ENGINE.runKernel(o.Conv2D,y,{strides:r,pad:n,dataFormat:s,dilations:u,dimRoundingMode:d});return g?(0,c.reshape)(v,[v.shape[1],v.shape[2],v.shape[3]]):v}})},{"../engine":"5aImO","../kernel_names":"bvyjS","../tensor_util_env":"feaHs","../util":"98aA6","./conv_util":"ckBsO","./operation":"2qT2c","./reshape":"i9E3v","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],"3bwnS":[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"conv2dTranspose",()=>l);var a=e("../tensor_util_env"),o=e("./conv2d_backprop_input");let l=(0,e("./operation").op)({conv2dTranspose_:function(e,t,r,n,s,l){let i=(0,a.convertToTensor)(e,"x","conv2dTranspose"),p=(0,a.convertToTensor)(t,"filter","conv2dTranspose");return(0,o.conv2DBackpropInput)(r,i,p,n,s,"NHWC",l)}})},{"../tensor_util_env":"feaHs","./conv2d_backprop_input":"jycaD","./operation":"2qT2c","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],jycaD:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"conv2DBackpropInput",()=>c);var a=e("../engine"),o=e("../kernel_names"),l=e("../util"),i=e("./conv_util"),p=e("./operation"),u=e("./reshape");let c=(0,p.op)({conv2DBackpropInput_:function(e,t,r,n,s,p="NHWC",c){l.assert(e.length===t.rank,()=>`Length of inShape (${e.length}) and rank of dy (${t.rank}) must match`);let d=e,f=t,m=!1;3===t.rank&&(m=!0,f=(0,u.reshape)(t,[1,t.shape[0],t.shape[1],t.shape[2]]),d=[1,e[0],e[1],e[2]]),l.assert(4===d.length,()=>`Error in conv2dDerInput: inShape must be length 4, but got length ${d.length}.`),l.assert(4===f.rank,()=>`Error in conv2dDerInput: dy must be rank 4, but got rank ${f.rank}`),l.assert(4===r.rank,()=>`Error in conv2dDerInput: filter must be rank 4, but got rank ${r.rank}`);let h="NHWC"===p?d[3]:d[1],g="NHWC"===p?f.shape[3]:f.shape[1];l.assert(h===r.shape[2],()=>`Error in conv2dDerInput: depth of input (${h}) must match input depth for filter ${r.shape[2]}.`),l.assert(g===r.shape[3],()=>`Error in conv2dDerInput: depth of output (${g}) must match output depth for filter ${r.shape[3]}.`),i.checkPadOnDimRoundingMode("conv2dDerInput",s,c);let x={dy:f,filter:r},y={strides:n,pad:s,dataFormat:p,dimRoundingMode:c,inputShape:d},v=a.ENGINE.runKernel(o.Conv2DBackpropInput,x,y);return m?(0,u.reshape)(v,[v.shape[1],v.shape[2],v.shape[3]]):v}})},{"../engine":"5aImO","../kernel_names":"bvyjS","../util":"98aA6","./conv_util":"ckBsO","./operation":"2qT2c","./reshape":"i9E3v","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],"74gae":[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"conv3d",()=>d);var a=e("../engine"),o=e("../kernel_names"),l=e("../tensor_util_env"),i=e("../util"),p=e("./conv_util"),u=e("./operation"),c=e("./reshape");let d=(0,u.op)({conv3d_:function(e,t,r,n,s="NDHWC",u=[1,1,1]){let d=(0,l.convertToTensor)(e,"x","conv3d"),f=(0,l.convertToTensor)(t,"filter","conv3d"),m=d,h=!1;4===d.rank&&(h=!0,m=(0,c.reshape)(d,[1,d.shape[0],d.shape[1],d.shape[2],d.shape[3]])),i.assert(5===m.rank,()=>`Error in conv3d: input must be rank 5, but got rank ${m.rank}.`),i.assert(5===f.rank,()=>`Error in conv3d: filter must be rank 5, but got rank ${f.rank}.`),i.assert(m.shape[4]===f.shape[3],()=>`Error in conv3d: depth of input (${m.shape[4]}) must match input depth for filter ${f.shape[3]}.`),i.assert((0,p.eitherStridesOrDilationsAreOne)(r,u),()=>`Error in conv3D: Either strides or dilations must be 1. Got strides ${r} and dilations '${u}'`),i.assert("NDHWC"===s,()=>`Error in conv3d: got dataFormat of ${s} but only NDHWC is currently supported.`),i.assert((0,p.stridesOrDilationsArePositive)(u),()=>"Error in conv3D: Dilated rates should be larger than 0."),i.assert((0,p.stridesOrDilationsArePositive)(r),()=>"Error in conv3D: Strides should be larger than 0.");let g={x:m,filter:f},x=a.ENGINE.runKernel(o.Conv3D,g,{strides:r,pad:n,dataFormat:s,dilations:u});return h?(0,c.reshape)(x,[x.shape[1],x.shape[2],x.shape[3],x.shape[4]]):x}})},{"../engine":"5aImO","../kernel_names":"bvyjS","../tensor_util_env":"feaHs","../util":"98aA6","./conv_util":"ckBsO","./operation":"2qT2c","./reshape":"i9E3v","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],lwUQU:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"conv3dTranspose",()=>l);var a=e("../tensor_util_env"),o=e("./conv3d_backprop_input");let 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S=(0,p.convertToTensor)(e,"x","conv2d","float32"),C=(0,p.convertToTensor)(t,"filter","conv2d","float32"),N=S,E=!1;3===S.rank&&(E=!0,N=(0,v.reshape)(S,[1,S.shape[0],S.shape[1],S.shape[2]])),u.assert(4===N.rank,()=>`Error in fused conv2d: input must be rank 4, but got rank ${N.rank}.`),u.assert(4===C.rank,()=>`Error in fused conv2d: filter must be rank 4, but got rank ${C.rank}.`),g.checkPadOnDimRoundingMode("fused conv2d",n,b);let F="NHWC"===s?N.shape[3]:N.shape[1];u.assert(C.shape[2]===F,()=>`Error in conv2d: depth of input (${F}) must match input depth for filter ${C.shape[2]}.`),u.assert(g.eitherStridesOrDilationsAreOne(r,y),()=>`Error in conv2D: Either strides or dilations must be 1. 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f=t;3===f.rank&&(f=(0,u.reshape)(t,[1,t.shape[0],t.shape[1],t.shape[2]])),l.assert(4===d.rank,()=>`Error in conv2dDerFilter: input must be rank 4, but got shape ${d.shape}.`),l.assert(4===f.rank,()=>`Error in conv2dDerFilter: dy must be rank 4, but got shape ${f.shape}.`),l.assert(4===r.length,()=>`Error in conv2dDerFilter: filterShape must be length 4, but got ${r}.`);let m="NHWC"===p?d.shape[3]:d.shape[1],h="NHWC"===p?f.shape[3]:f.shape[1];l.assert(m===r[2],()=>`Error in conv2dDerFilter: depth of input ${m}) must match input depth in filter (${r[2]}.`),l.assert(h===r[3],()=>`Error in conv2dDerFilter: depth of dy (${h}) must match output depth for filter (${r[3]}).`),i.checkPadOnDimRoundingMode("conv2dDerFilter",s,c);let g={x:d,dy:f};return a.ENGINE.runKernel(o.Conv2DBackpropFilter,g,{strides:n,pad:s,dataFormat:p,dimRoundingMode:c,filterShape:r})}})},{"../engine":"5aImO","../kernel_names":"bvyjS","../util":"98aA6","./conv_util":"ckBsO","./operation":"2qT2c","./reshape":"i9E3v","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],cl7EF:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"getFusedDyActivation",()=>g),s.export(r,"getFusedBiasGradient",()=>x),s.export(r,"applyActivation",()=>y),s.export(r,"shouldFuse",()=>v);var a=e("./broadcast_util"),o=e("./elu"),l=e("./leaky_relu"),i=e("./mul"),p=e("./prelu"),u=e("./relu"),c=e("./relu6"),d=e("./reshape"),f=e("./sigmoid"),m=e("./step"),h=e("./sum");function g(e,t,r){if(null==r||"linear"===r)return e;if("relu"===r)return(0,i.mul)(e,(0,m.step)(t));throw Error(`Cannot compute gradient for fused activation ${r}.`)}function x(e,t){let r=t,n=a.getReductionAxes(e.shape,t.shape);return n.length>0&&(r=(0,h.sum)(r,n)),(0,d.reshape)(r,e.shape)}function y(e,t,r,n){if("linear"===t)return e;if("relu"===t)return(0,u.relu)(e);if("elu"===t)return(0,o.elu)(e);if("relu6"===t)return(0,c.relu6)(e);if("prelu"===t)return(0,p.prelu)(e,r);else if("leakyrelu"===t)return(0,l.leakyRelu)(e,n);else if("sigmoid"===t)return(0,f.sigmoid)(e);throw Error(`Unknown fused activation ${t}.`)}let v=(e,t)=>!(e>0)||"linear"===t},{"./broadcast_util":"eciNq","./elu":"ezxha","./leaky_relu":"6T6LU","./mul":"6u9Cs","./prelu":"ez5fa","./relu":"7eL1z","./relu6":"9s4es","./reshape":"i9E3v","./sigmoid":"hx1GK","./step":"60OEJ","./sum":"jrqRB","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],"7YX01":[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"depthwiseConv2d",()=>b);var 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S=(0,p.convertToTensor)(e,"x","depthwiseConv2d","float32"),C=(0,p.convertToTensor)(t,"filter","depthwiseConv2d","float32"),N=S,E=!1;3===S.rank&&(E=!0,N=(0,v.reshape)(S,[1,S.shape[0],S.shape[1],S.shape[2]])),u.assert(4===N.rank,()=>`Error in fused depthwiseConv2d: input must be rank 4, but got rank ${N.rank}.`),u.assert(4===C.rank,()=>`Error in fused depthwiseConv2d: filter must be rank 4, but got rank ${C.rank}.`),u.assert(N.shape[3]===C.shape[2],()=>`Error in fused depthwiseConv2d: number of input channels (${N.shape[3]}) must match the inChannels dimension in filter ${C.shape[2]}.`),null==y&&(y=[1,1]),u.assert(f.eitherStridesOrDilationsAreOne(r,y),()=>`Error in fused depthwiseConv2d: Either strides or dilations must be 1. 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s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"json",()=>a);let a=[{tfOpName:"FFT",category:"spectral",inputs:[{start:0,name:"x",type:"tensor"}]},{tfOpName:"IFFT",category:"spectral",inputs:[{start:0,name:"x",type:"tensor"}]},{tfOpName:"RFFT",category:"spectral",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"fft_length",type:"number",notSupported:!0}]},{tfOpName:"IRFFT",category:"spectral",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"fft_length",type:"number",notSupported:!0}]}]},{"@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],"6z66K":[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"json",()=>a);let a=[{tfOpName:"StaticRegexReplace",category:"string",inputs:[{start:0,name:"input",type:"tensor"}],attrs:[{tfName:"pattern",name:"pattern",type:"string"},{tfName:"rewrite",name:"rewrite",type:"string"},{tfName:"replace_global",name:"replaceGlobal",type:"bool"}]},{tfOpName:"StringNGrams",category:"string",inputs:[{start:0,name:"data",type:"tensor"},{start:1,name:"dataSplits",type:"tensor"}],attrs:[{tfName:"separator",name:"separator",type:"string"},{tfName:"ngram_widths",name:"nGramWidths",type:"number[]"},{tfName:"left_pad",name:"leftPad",type:"string"},{tfName:"right_pad",name:"rightPad",type:"string"},{tfName:"pad_width",name:"padWidth",type:"number"},{tfName:"preserve_short_sequences",name:"preserveShortSequences",type:"bool"}],outputs:["ngrams","ngrams_splits"]},{tfOpName:"StringSplit",category:"string",inputs:[{start:0,name:"input",type:"tensor"},{start:1,name:"delimiter",type:"tensor"}],attrs:[{tfName:"skip_empty",name:"skipEmpty",type:"bool"}],outputs:["indices","values","shape"]},{tfOpName:"StringToHashBucketFast",category:"string",inputs:[{start:0,name:"input",type:"tensor"}],attrs:[{tfName:"num_buckets",name:"numBuckets",type:"number"}]}]},{"@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],"72RQ6":[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"json",()=>a);let a=[{tfOpName:"Cast",category:"transformation",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"SrcT",name:"sdtype",type:"dtype",notSupported:!0},{tfName:"DstT",name:"dtype",type:"dtype"}]},{tfOpName:"ExpandDims",category:"transformation",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"axis",type:"number"}]},{tfOpName:"MirrorPad",category:"transformation",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"padding",type:"number[]"}],attrs:[{tfName:"mode",name:"mode",type:"string"}]},{tfOpName:"Pad",category:"transformation",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"padding",type:"number[]"}],attrs:[{tfName:"constant_value",name:"constantValue",type:"number",defaultValue:0}]},{tfOpName:"PadV2",category:"transformation",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"padding",type:"number[]"},{start:2,name:"constantValue",type:"number",defaultValue:0}]},{tfOpName:"Reshape",category:"transformation",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"shape",type:"number[]"}]},{tfOpName:"EnsureShape",category:"transformation",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"shape",type:"number[]"}]},{tfOpName:"Squeeze",category:"transformation",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"axis",tfDeprecatedName:"squeeze_dims",name:"axis",type:"number[]"}]},{tfOpName:"SpaceToBatchND",category:"transformation",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"blockShape",type:"number[]"},{start:2,name:"paddings",type:"number[]"}]},{tfOpName:"BatchToSpaceND",category:"transformation",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"blockShape",type:"number[]"},{start:2,name:"crops",type:"number[]"}]},{tfOpName:"DepthToSpace",category:"transformation",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"block_size",name:"blockSize",type:"number"},{tfName:"data_format",name:"dataFormat",type:"string"}]},{tfOpName:"BroadcastTo",category:"transformation",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"shape",type:"number[]"}],attrs:[]},{tfOpName:"BroadcastArgs",category:"transformation",inputs:[{start:0,name:"s0",type:"tensor"},{start:1,name:"s1",type:"tensor"}],attrs:[]}]},{"@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],"2xoeY":[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"GraphExecutor",()=>u);var a=e("@tensorflow/tfjs-core"),o=e("../operations/executors/utils"),l=e("../operations/operation_executor"),i=e("./execution_context"),p=e("./model_analysis");class u{get weightIds(){return this.parent?this.parent.weightIds:this._weightIds}get functionExecutorMap(){return this.parent?this.parent.functionExecutorMap:this._functionExecutorMap}get weightMap(){return this.parent?this.parent.weightMap:this._weightMap}set weightMap(e){let t=Object.keys(e).map(t=>e[t].map(e=>e.id));this._weightIds=[].concat(...t),this._weightMap=e}set resourceManager(e){this._resourceManager=e}get inputs(){return this._inputs.map(e=>({name:e.name,shape:e.attrParams.shape?e.attrParams.shape.value:void 0,dtype:e.attrParams.dtype?e.attrParams.dtype.value:void 0}))}get outputs(){return this._outputs.map(e=>({name:e.name,shape:e.attrParams.shape?e.attrParams.shape.value:void 0,dtype:e.attrParams.dtype?e.attrParams.dtype.value:void 0}))}get inputNodes(){return this._inputs.map(e=>e.signatureKey||e.name)}get outputNodes(){return this._outputs.map(e=>{let t=e.signatureKey||e.name;return e.defaultOutput?`${t}:${e.defaultOutput}`:t})}get functions(){return Object.keys(this._functions).reduce((e,t)=>(e[t]=this._functions[t].signature,e),{})}constructor(e,t){this.graph=e,this.parent=t,this.compiledMap=new Map,this.parseNodeNameCache=new Map,this._weightMap={},this.SEPARATOR=",",this._functions={},this._functionExecutorMap={},this.keepIntermediateTensors=!1,this._outputs=e.outputs,this._inputs=e.inputs,this._initNodes=e.initNodes,this._signature=e.signature,this._functions=e.functions,null!=e.functions&&Object.keys(e.functions).forEach(t=>{this._functionExecutorMap[t]=new u(e.functions[t],this)})}getCompilationKey(e,t){let r=e.map(e=>e.name).sort(),n=t.map(e=>e.name).sort();return r.join(this.SEPARATOR)+"--"+n.join(this.SEPARATOR)}compile(e,t){let r=(0,p.getExecutionSubgraph)(e,t,this.weightMap,this._initNodes),{missingInputs:n,dynamicNode:s,syncInputs:a}=r;if(null!=s)throw Error(`This execution contains the node '${s.name}', which has the dynamic op '${s.op}'. Please use model.executeAsync() instead. Alternatively, to avoid the dynamic ops, specify the inputs [${a}]`);if(n.length>0){let r=t.map(e=>e.name),s=Object.keys(e);throw Error(`Cannot compute the outputs [${r}] from the provided inputs [${s}]. Missing the following inputs: [${n}]`)}let o=(0,p.getNodesInTopologicalOrder)(this.graph,r),l=(0,p.getNodeLiveUntilMap)(o);return{orderedNodes:o,nodeLiveUntilMap:l}}cloneAndKeepTensor(e){if(null==e)return null;let t=e.clone();return(0,a.keep)(t),t}cloneTensorList(e){return e?e.map(e=>this.cloneAndKeepTensor(e)):null}cloneTensorMap(e){return Object.fromEntries(Object.entries(e).map(([e,t])=>[e,this.cloneTensorList(t)]))}execute(e,t){this.disposeIntermediateTensors();let r=Object.keys(e=this.mapInputs(e)).sort();this.checkInputs(e),this.checkInputShapeAndType(e),t=this.mapOutputs(t),this.checkOutputs(t);let n=r.map(e=>this.graph.nodes[(0,o.parseNodeName)(e)[0]]),s=t.map(e=>(0,o.parseNodeName)(e)[0]),p=new Set(s),u=s.map(e=>this.graph.nodes[e]);0===u.length&&(u=this._outputs);let c=this.getCompilationKey(n,u),d=this.compiledMap.get(c);null==d&&(d=this.compile(e,u),this.compiledMap.set(c,d));try{this.keepIntermediateTensors=(0,a.env)().getBool("KEEP_INTERMEDIATE_TENSORS")}catch(e){this.keepIntermediateTensors=!1,console.warn(e.message)}let f={},m={};return(0,a.tidy)(()=>{let r=new(0,i.ExecutionContext)(this.weightMap,f,m,this.functionExecutorMap,this.parseNodeNameCache),n=Object.assign({},this.weightMap);this.keepIntermediateTensors&&(this.clonedTensorsMap=this.cloneTensorMap(this.weightMap)),Object.keys(e).forEach(t=>{let[s,a]=(0,o.parseNodeName)(t,r),l=[];l[a]=e[t],n[s]=l,this.keepIntermediateTensors&&(this.clonedTensorsMap[s]=this.cloneTensorList(l))});let s=this.getFrozenTensorIds(n),{orderedNodes:u,nodeLiveUntilMap:c}=d;for(let e of u){if(n[e.name])continue;let t=(0,l.executeOp)(e,n,r,this._resourceManager);if(a.util.isPromise(t))throw Error(`The execution of the op '${e.op}' returned a promise. Please use model.executeAsync() instead.`);n[e.name]=t,this.keepIntermediateTensors&&(this.clonedTensorsMap[e.name]=this.cloneTensorList(t)),this.checkTensorForDisposalWithNodeLiveUntilInfo(e,n,r,s,p,c.get(e.name))}return null==this.parent&&r.dispose(s),t.map(e=>(0,o.getTensor)(e,n,r))})}getFrozenTensorIds(e){return new Set([].concat.apply([],Object.keys(e).map(t=>e[t]).map(e=>e.map(e=>e.id))))}checkTensorForDisposal(e,t,r,n,s,a,l){if(!((0,p.isControlFlow)(t)||a.has(e))){for(let n of r[e])null!=n&&(l[n.id]=(l[n.id]||0)+t.children.length);for(let e of t.inputs){if((0,p.isControlFlow)(e))continue;let t=(0,o.getTensorsForCurrentContext)(e.name,r,n);if(null!=t)for(let e of t){if(!e||e.kept||s.has(e.id))continue;let t=l[e.id];1===t?(e.dispose(),delete l[e.id]):null!=t&&l[e.id]--}}}}checkTensorForDisposalWithNodeLiveUntilInfo(e,t,r,n,s,a){if(!(0,p.isControlFlow)(e)&&null!=a){for(let e of a)if(!((0,p.isControlFlow)(e)||s.has(e.name)))for(let s of(0,o.getTensorsForCurrentContext)(e.name,t,r))!s||s.kept||n.has(s.id)||s.dispose()}}async executeAsync(e,t){return this._executeAsync(e,t)}disposeIntermediateTensors(){this.clonedTensorsMap&&(Object.values(this.clonedTensorsMap).forEach(e=>{for(let t of e)t&&!t.isDisposed&&t.dispose()}),this.clonedTensorsMap=null)}getIntermediateTensors(){return this.clonedTensorsMap}async _executeAsync(e,t,r=!1,n={},s={}){this.disposeIntermediateTensors(),r||(e=this.mapInputs(e),this.checkInputs(e),this.checkInputShapeAndType(e),t=this.mapOutputs(t),this.checkOutputs(t));try{this.keepIntermediateTensors=(0,a.env)().getBool("KEEP_INTERMEDIATE_TENSORS")}catch(e){this.keepIntermediateTensors=!1,console.warn(e.message)}let l=new(0,i.ExecutionContext)(this.weightMap,n,s,this.functionExecutorMap,this.parseNodeNameCache);this.keepIntermediateTensors&&(this.clonedTensorsMap=this.cloneTensorMap(this.weightMap));let p=await this.executeWithControlFlow(e,l,t,r),u=t.map(e=>(0,o.getTensor)(e,p,l)),c=new Set([...u.map(e=>e.id),...Object.keys(e).map(t=>e[t].id),...this.weightIds]);return Object.values(p).forEach(e=>{e.forEach(e=>{!e||e.isDisposed||c.has(e.id)||e.dispose()})}),null==this.parent&&l.dispose(c),u}async executeFunctionAsync(e,t,r){let n=e.reduce((e,t,r)=>(e[this.inputs[r].name]=t,e),{});return this._executeAsync(n,this.outputNodes,!0,t,r)}async executeWithControlFlow(e,t,r,n){let s=Object.keys(e),a=s.map(e=>this.graph.nodes[(0,o.parseNodeName)(e)[0]]),l=r.map(e=>(0,o.parseNodeName)(e)[0]),i=new Set(l),u=l.map(e=>this.graph.nodes[e]);0===u.length&&(u=this._outputs);let{usedNodes:c,missingInputs:d,dynamicNode:f,syncInputs:m}=(0,p.getExecutionSubgraph)(e,u,this.weightMap,this._initNodes),h=[...a,...this.graph.weights,...this._initNodes||[]].map(e=>({node:e,contexts:t.currentContext})),g=Object.assign({},this.weightMap);Object.keys(e).forEach(t=>{let[r,n]=(0,o.parseNodeName)(t),s=[];s[n]=e[t],g[r]=s});let x={},y=this.getFrozenTensorIds(g),v={};for(;h.length>0;){let e=this.processStack(a,h,t,g,v,y,i,x,c);await Promise.all(e)}null!=f||n||console.warn("This model execution did not contain any nodes with control flow or dynamic output shapes. You can use model.execute() instead.");let b=u.filter(e=>!(0,p.isControlFlow)(e)&&!(0,o.getTensor)(e.name,g,t)).map(e=>e.name);if(b.length>0){let e="";throw null!=f&&(e=`Alternatively, to avoid the dynamic ops, use model.execute() and specify the inputs [${m}]`),Error(`Cannot compute the outputs [${b}] from the provided inputs [${s}]. Consider providing the following inputs: [${d}]. ${e}`)}return g}processStack(e,t,r,n,s,i,p,u,c){let d=[];for(;t.length>0;){let e=t.pop();r.currentContext=e.contexts;let f="";if("Enter"===e.node.op&&(0,o.getParamValue)("isConstant",e.node,n,r)&&([f]=(0,o.getNodeNameAndIndex)(e.node.name,r)),null==n[e.node.name]){let m=(0,l.executeOp)(e.node,n,r,this._resourceManager);f||([f]=(0,o.getNodeNameAndIndex)(e.node.name,r));let h=r.currentContext;a.util.isPromise(m)?d.push(m.then(a=>(n[f]=a,this.keepIntermediateTensors&&(this.clonedTensorsMap[f]=this.cloneTensorList(a)),r.currentContext=h,this.checkTensorForDisposal(f,e.node,n,r,i,p,u),this.processChildNodes(e.node,t,r,n,s,c),a))):(n[f]=m,this.keepIntermediateTensors&&(this.clonedTensorsMap[f]=this.cloneTensorList(m)),this.checkTensorForDisposal(f,e.node,n,r,i,p,u),this.processChildNodes(e.node,t,r,n,s,c))}else this.processChildNodes(e.node,t,r,n,s,c)}return d}processChildNodes(e,t,r,n,s,a){e.children.forEach(e=>{let[l]=(0,o.getNodeNameAndIndex)(e.name,r);!s[l]&&a.has(e.name)&&("Merge"===e.op?e.inputNames.some(e=>!!(0,o.getTensor)(e,n,r))&&(s[l]=!0,t.push({contexts:r.currentContext,node:e})):e.inputNames.every(e=>!!(0,o.getTensor)(e,n,r))&&(s[l]=!0,t.push({contexts:r.currentContext,node:e})))})}dispose(){Object.keys(this.weightMap).forEach(e=>this.weightMap[e].forEach(e=>e.dispose()))}checkInputShapeAndType(e){Object.keys(e).forEach(t=>{let r=e[t],[n]=(0,o.parseNodeName)(t),s=this.graph.nodes[n];if(s.attrParams.shape&&s.attrParams.shape.value){let e=s.attrParams.shape.value,t=e.length===r.shape.length&&r.shape.every((t,r)=>-1===e[r]||e[r]===t);a.util.assert(t,()=>`The shape of dict['${s.name}'] provided in model.execute(dict) must be [${e}], but was [${r.shape}]`)}s.attrParams.dtype&&s.attrParams.dtype.value&&a.util.assert(r.dtype===s.attrParams.dtype.value,()=>`The dtype of dict['${s.name}'] provided in model.execute(dict) must be ${s.attrParams.dtype.value}, but was ${r.dtype}`)})}mapInputs(e){var t,r;let n={};for(let s in e){let a=null==(r=null==(t=this._signature)?void 0:t.inputs)?void 0:r[s];null!=a?n[a.name]=e[s]:n[s]=e[s]}return n}checkInputs(e){let t=Object.keys(e).filter(e=>{let[t]=(0,o.parseNodeName)(e);return null==this.graph.nodes[t]});if(t.length>0)throw Error(`The dict provided in model.execute(dict) has keys: [${t}] that are not part of graph`)}mapOutputs(e){return e.map(e=>{var t,r;let n=null==(r=null==(t=this._signature)?void 0:t.outputs)?void 0:r[e];return null!=n?n.name:e},{})}checkOutputs(e){e.forEach(e=>{let[t]=(0,o.parseNodeName)(e);if(!this.graph.nodes[t])throw Error(`The output '${e}' is not found in the graph`)})}}},{"@tensorflow/tfjs-core":"2Gtps","../operations/executors/utils":"7JaBk","../operations/operation_executor":"jRbJE","./execution_context":"kjrPn","./model_analysis":"6RNWa","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],jRbJE:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"executeOp",()=>C);var a=e("@tensorflow/tfjs-core"),o=e("./custom_op/node_value_impl"),l=e("./custom_op/register"),i=e("./executors/arithmetic_executor"),p=e("./executors/basic_math_executor"),u=e("./executors/control_executor"),c=e("./executors/convolution_executor"),d=e("./executors/creation_executor"),f=e("./executors/dynamic_executor"),m=e("./executors/evaluation_executor"),h=e("./executors/graph_executor"),g=e("./executors/hash_table_executor"),x=e("./executors/image_executor"),y=e("./executors/logical_executor"),v=e("./executors/matrices_executor"),b=e("./executors/normalization_executor"),k=e("./executors/ragged_executor"),_=e("./executors/reduction_executor"),I=e("./executors/slice_join_executor"),j=e("./executors/sparse_executor"),w=e("./executors/spectral_executor"),T=e("./executors/string_executor"),S=e("./executors/transformation_executor");function C(e,t,r,n,s=a.tidy){let N=((e,t,r)=>{switch(e.category){case"arithmetic":return s(()=>i.executeOp(e,t,r));case"basic_math":return s(()=>p.executeOp(e,t,r));case"control":return u.executeOp(e,t,r);case"convolution":return s(()=>c.executeOp(e,t,r));case"creation":return s(()=>d.executeOp(e,t,r));case"dynamic":return f.executeOp(e,t,r);case"evaluation":return s(()=>m.executeOp(e,t,r));case"image":return s(()=>x.executeOp(e,t,r));case"graph":return s(()=>h.executeOp(e,t,r));case"logical":return s(()=>y.executeOp(e,t,r));case"matrices":return s(()=>v.executeOp(e,t,r));case"normalization":return s(()=>b.executeOp(e,t,r));case"ragged":return s(()=>k.executeOp(e,t,r));case"reduction":return s(()=>_.executeOp(e,t,r));case"slice_join":return s(()=>I.executeOp(e,t,r));case"sparse":return s(()=>j.executeOp(e,t,r));case"spectral":return s(()=>w.executeOp(e,t,r));case"string":return s(()=>T.executeOp(e,t,r));case"transformation":return s(()=>S.executeOp(e,t,r));case"hash_table":return g.executeOp(e,t,r,n);case"custom":let a=(0,l.getRegisteredOp)(e.op);if(a&&a.customExecutor)return a.customExecutor(new(0,o.NodeValueImpl)(e,t,r));throw TypeError(`Custom op ${e.op} is not registered.`);default:throw TypeError(`Unknown op '${e.op}'. File an issue at https://github.com/tensorflow/tfjs/issues so we can add it, or register a custom execution with tf.registerOp()`)}})(e,t,r);return a.util.isPromise(N)?N.then(e=>[].concat(e)):[].concat(N)}},{"@tensorflow/tfjs-core":"2Gtps","./custom_op/node_value_impl":"gsVt0","./custom_op/register":"j5u17","./executors/arithmetic_executor":"8j2Lq","./executors/basic_math_executor":"ibHoa","./executors/control_executor":"dUvmj","./executors/convolution_executor":"ebCt3","./executors/creation_executor":"jGuVv","./executors/dynamic_executor":"6MrZY","./executors/evaluation_executor":"aCa2f","./executors/graph_executor":"aTTe4","./executors/hash_table_executor":"bgWBQ","./executors/image_executor":"4PO7O","./executors/logical_executor":"1Av7N","./executors/matrices_executor":"iyJvB","./executors/normalization_executor":"3LyHZ","./executors/ragged_executor":"ig29V","./executors/reduction_executor":"ayS3S","./executors/slice_join_executor":"exLUI","./executors/sparse_executor":"4cqnd","./executors/spectral_executor":"ldBfB","./executors/string_executor":"dinGK","./executors/transformation_executor":"7MPCS","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],gsVt0:[function(e,t,r,n){var 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Consider enabling float32 rendering: 'tf.env().set('WEBGL_RENDER_FLOAT32_ENABLED', true);'`);throw Error(`The value ${r} cannot be represented on this device.`)}}}getValuesFromTexture(e){let{shape:t,dtype:r,isPacked:n}=this.texData.get(e),s=a.util.sizeFromShape(t);if((0,a.env)().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")){let r=this.decode(e),n=this.texData.get(r.dataId),a=this.gpgpu.downloadMatrixFromPackedTexture(n.texture.texture,...y.getDenseTexShape(t)).subarray(0,s);return this.disposeIntermediateTensorInfo(r),a}let o=(0,a.env)().getBool("WEBGL_PACK")&&!0===n,l=o?I.getShapeAs3D(t):t,i=o?new(0,u.EncodeFloatPackedProgram)(l):new(0,p.EncodeFloatProgram)(l),c=this.runWebGLProgram(i,[{shape:l,dtype:r,dataId:e}],"float32"),d=this.texData.get(c.dataId),f=this.gpgpu.downloadByteEncodedFloatMatrixFromOutputTexture(d.texture.texture,d.texShape[0],d.texShape[1]).subarray(0,s);return this.disposeIntermediateTensorInfo(c),f}timerAvailable(){return(0,a.env)().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0}time(e){let t=this.activeTimers,r=[],n=!1;null==this.programTimersStack?(this.programTimersStack=r,n=!0):this.activeTimers.push(r),this.activeTimers=r,e();let s=a.util.flatten(this.activeTimers.map(e=>e.query)).filter(e=>null!=e),o=a.util.flatten(this.activeTimers.map(e=>e.name)).filter(e=>null!=e);this.activeTimers=t,n&&(this.programTimersStack=null);let l={uploadWaitMs:this.uploadWaitMs,downloadWaitMs:this.downloadWaitMs,kernelMs:null,wallMs:null};return(async()=>{if((0,a.env)().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0){let e=await Promise.all(s);l.kernelMs=a.util.sum(e),l.getExtraProfileInfo=()=>e.map((e,t)=>({name:o[t],ms:e})).map(e=>`${e.name}: ${e.ms}`).join(", ")}else l.kernelMs={error:"WebGL query timers are not supported in this environment."};return this.uploadWaitMs=0,this.downloadWaitMs=0,l})()}memory(){return{unreliable:!1,numBytesInGPU:this.numBytesInGPU,numBytesInGPUAllocated:this.textureManager.numBytesAllocated,numBytesInGPUFree:this.textureManager.numBytesFree}}startTimer(){return(0,a.env)().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?this.gpgpu.beginQuery():{startMs:a.util.now(),endMs:null}}endTimer(e){return(0,a.env)().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?this.gpgpu.endQuery():e.endMs=a.util.now(),e}async getQueryTime(e){return(0,a.env)().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?this.gpgpu.waitForQueryAndGetTime(e):e.endMs-e.startMs}disposeData(e,t=!1){if(this.pendingDisposal.has(e))return!1;if(!this.texData.has(e))return!0;if(t?this.texData.get(e).refCount=0:this.texData.get(e).refCount--,!t&&this.texData.get(e).refCount>0)return!1;if(this.pendingRead.has(e))return this.pendingDisposal.add(e),this.pendingDeletes++,!1;this.releaseGPUData(e);let{complexTensorInfos:r}=this.texData.get(e);return null!=r&&(this.disposeData(r.real.dataId,t),this.disposeData(r.imag.dataId,t)),this.texData.delete(e),!0}releaseGPUData(e){let{texture:t,dtype:r,texShape:n,usage:s,isPacked:a,slice:o}=this.texData.get(e),l=o&&o.origDataId||e,i=this.dataRefCount.get(l);i>1?this.dataRefCount.set(l,i-1):(this.dataRefCount.delete(l),null!=t&&(this.numBytesInGPU-=this.computeBytes(n,r),this.textureManager.releaseTexture(t,n,s,a)));let p=this.texData.get(e);p.texture=null,p.texShape=null,p.isPacked=!1,p.slice=null}getTexture(e){return this.uploadToGPU(e),this.texData.get(e).texture.texture}getDataInfo(e){return this.texData.get(e)}shouldExecuteOnCPU(e,t=N){return(0,a.env)().getBool("WEBGL_CPU_FORWARD")&&e.every(e=>null==this.texData.get(e.dataId).texture&&a.util.sizeFromShape(e.shape)<t)}getGPGPUContext(){return this.gpgpu}where(e){a.backend_util.warn("tf.where() in webgl locks the UI thread. 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d={shape:i.shape,texData:p,isUniform:!1},f=m.makeShaderKey(e,c,d),h=this.getAndSaveBinary(f,()=>m.compileProgram(this.gpgpu,e,c,d)),g=null!=this.activeTimers;g&&(l=this.startTimer()),(0,a.env)().get("ENGINE_COMPILE_ONLY")||m.runProgram(this.gpgpu,h,c,d,n),u.forEach(e=>this.disposeIntermediateTensorInfo(e)),g&&(l=this.endTimer(l),this.activeTimers.push({name:e.constructor.name,query:this.getQueryTime(l)}));let x=(0,a.env)().getNumber("WEBGL_FLUSH_THRESHOLD");if(x>0){let e=a.util.now();e-this.lastGlFlushTime>x&&(this.gpgpu.gl.flush(),this.lastGlFlushTime=e)}if(!(0,a.env)().getBool("WEBGL_LAZILY_UNPACK")&&p.isPacked&&!1===s){let e=this.unpackTensor(i);return this.disposeIntermediateTensorInfo(i),e}return i}compileAndRun(e,t,r,n,s=!1){return r=r||t[0].dtype,this.runWebGLProgram(e,t,r,n,s)}getAndSaveBinary(e,t){return e in this.binaryCache||(this.binaryCache[e]=t()),this.binaryCache[e]}getTextureManager(){return this.textureManager}dispose(){this.disposed||((0,a.env)().getBool("IS_TEST")||Object.keys(this.binaryCache).forEach(e=>{this.gpgpu.deleteProgram(this.binaryCache[e].webGLProgram),delete this.binaryCache[e]}),this.textureManager.dispose(),null!=this.canvas&&"undefined"!=typeof HTMLCanvasElement&&this.canvas instanceof HTMLCanvasElement?this.canvas.remove():this.canvas=null,this.gpgpuCreatedLocally&&(this.gpgpu.program=null,this.gpgpu.dispose()),this.disposed=!0)}floatPrecision(){return null==this.floatPrecisionValue&&(this.floatPrecisionValue=(0,a.tidy)(()=>{if(!(0,a.env)().get("WEBGL_RENDER_FLOAT32_ENABLED")){let e=(0,a.env)().getBool("DEBUG");(0,a.env)().set("DEBUG",!1);let t=this.abs((0,a.scalar)(1e-8)).dataSync()[0];if((0,a.env)().set("DEBUG",e),t>0)return 32}return 16})),this.floatPrecisionValue}epsilon(){return 32===this.floatPrecision()?w:T}uploadToGPU(e){let t,r=this.texData.get(e),{shape:n,dtype:s,values:o,texture:l,usage:i,isPacked:p}=r;if(null!=l)return;let 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1:j.push(`uniform int ${e.name}Shape;`);break;case 2:j.push(`uniform ivec2 ${e.name}Shape;`);break;case 3:j.push(`uniform ivec3 ${e.name}Shape;`);break;case 4:j.push(`uniform ivec4 ${e.name}Shape;`)}j.push(`uniform ivec2 ${e.name}TexShape;`)}}),r.enableShapeUniforms){switch(t.logicalShape.length){case 1:j.push("uniform int outShape;");break;case 2:j.push("uniform ivec2 outShape;"),j.push("uniform int outShapeStrides;");break;case 3:j.push("uniform ivec3 outShape;"),j.push("uniform ivec2 outShapeStrides;");break;case 4:j.push("uniform ivec4 outShape;"),j.push("uniform ivec3 outShapeStrides;")}j.push("uniform ivec2 outTexShape;")}r.customUniforms&&r.customUniforms.forEach(e=>{j.push(`uniform ${e.type} ${e.name}${e.arrayIndex?`[${e.arrayIndex}]`:""};`)});let w=j.join("\n"),T=e.map(e=>(function(e,t,r=!1,n){let s="";r?s+=function e(t,r){switch(t.shapeInfo.logicalShape.length){case 0:let n,s,l;return s="get"+(n=t.name).charAt(0).toUpperCase()+n.slice(1),l=(0,o.getGlslDifferences)(),` vec4 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col) { vec2 uv = (vec2(col, row) + halfCR) / vec2(${p}.0, ${i}.0); return ${u.texture2D}(${n}, uv); } `;if(t)return` vec4 ${s}(int row, int col) { ivec2 packedTexShape = ivec2(ceil(float(${n}TexShape[0]) / 2.0), ceil(float(${n}TexShape[1]) / 2.0)); int valuesPerRow = int(ceil(float(${n}Shape[1]) / 2.0)); vec2 uv = packedUVfrom2D(valuesPerRow, packedTexShape[0], packedTexShape[1], row, col); return ${u.texture2D}(${n}, uv); } `;let c=[Math.ceil(l[0]/2),Math.ceil(l[1]/2)],d=Math.ceil(r[1]/2);return` vec4 ${s}(int row, int col) { vec2 uv = packedUVfrom2D(${d}, ${c[0]}, ${c[1]}, row, col); return ${u.texture2D}(${n}, uv); } `}(t,r);case 3:return function(t,r){let n=t.shapeInfo.logicalShape,s=t.name,a="get"+s.charAt(0).toUpperCase()+s.slice(1),l=t.shapeInfo.texShape,i=[Math.ceil(l[0]/2),Math.ceil(l[1]/2)];if(1===n[0]){let s=v(t,n.slice(1));return` ${e(s,r)} vec4 ${a}(int b, int row, int col) { return ${a}(${b(["b","row","col"],[1,2])}); } `}let p=(0,o.getGlslDifferences)();if(r)return` vec4 ${a}(int b, int row, int col) { ivec2 packedTexShape = ivec2(ceil(float(${s}TexShape[0]) / 2.0), ceil(float(${s}TexShape[1]) / 2.0)); int valuesPerRow = int(ceil(float(${s}Shape[2]) / 2.0)); int texelsInBatch = valuesPerRow * int(ceil(float(${s}Shape[1]) / 2.0)); vec2 uv = packedUVfrom3D( packedTexShape[0], packedTexShape[1], texelsInBatch, valuesPerRow, b, row, col); return ${p.texture2D}(${s}, uv); } `;let u=i[0],c=i[1],d=Math.ceil(n[2]/2),f=d*Math.ceil(n[1]/2);return` vec4 ${a}(int b, int row, int col) { vec2 uv = packedUVfrom3D( ${u}, ${c}, ${f}, ${d}, b, row, col); return ${p.texture2D}(${s}, uv); } `}(t,r);default:return function(e,t){let r=e.name,n="get"+r.charAt(0).toUpperCase()+r.slice(1),s=(0,o.getGlslDifferences)();if(t)return` vec4 ${n}(int b2, int b, int row, int col) { int valuesPerRow = int(ceil(float(${r}Shape[3]) / 2.0)); int texelsInBatch = valuesPerRow * int(ceil(float(${r}Shape[2]) / 2.0)); int index = b * texelsInBatch + (row / 2) * valuesPerRow + (col / 2); texelsInBatch *= ${r}Shape[1]; index = b2 * texelsInBatch + index; ivec2 packedTexShape = ivec2(ceil(float(${r}TexShape[0]) / 2.0), ceil(float(${r}TexShape[1]) / 2.0)); int texR = index / packedTexShape[1]; int texC = index - texR * packedTexShape[1]; vec2 uv = (vec2(texC, texR) + halfCR) / vec2(packedTexShape[1], packedTexShape[0]); return ${s.texture2D}(${r}, uv); } `;let a=e.shapeInfo.logicalShape,l=a.length,i=e.shapeInfo.texShape,p=[Math.ceil(i[0]/2),Math.ceil(i[1]/2)],u=p[0],c=p[1],d=Math.ceil(a[l-1]/2),f=d*Math.ceil(a[l-2]/2),m="int b, int row, int col",h=`b * ${f} + (row / 2) * ${d} + (col / 2)`;for(let e=2;e<l-1;e++)m=`int b${e}, `+m,f*=a[l-e-1],h=`b${e} * ${f} + `+h;return` vec4 ${n}(${m}) { int index = ${h}; int texR = index / ${c}; int texC = index - texR * ${c}; vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${c}, ${u}); return ${s.texture2D}(${r}, uv); } `}(t,r)}}(e,n):s+=function e(t,r=!1){let n=t.shapeInfo.logicalShape;switch(n.length){case 0:return function(e,t){let r=e.name,n="get"+r.charAt(0).toUpperCase()+r.slice(1);if(e.shapeInfo.isUniform)return`float ${n}() {return ${r};}`;let[s,a]=e.shapeInfo.texShape;if(1===s&&1===a)return` float ${n}() { return sampleTexture(${r}, halfCR); } `;let o=h(r);if(t)return` float ${n}() { vec2 uv = uvFromFlat(${r}TexShape[0], ${r}TexShape[1], ${o}); return sampleTexture(${r}, uv); } `;let[l,i]=e.shapeInfo.texShape;return` float ${n}() { vec2 uv = uvFromFlat(${l}, ${i}, ${o}); return sampleTexture(${r}, uv); } `}(t,r);case 1:return function(e,t){let r=e.name,n="get"+r.charAt(0).toUpperCase()+r.slice(1);if(e.shapeInfo.isUniform)return` float ${n}(int index) { ${g(e)} } `;let s=e.shapeInfo.texShape,a=s[0],o=s[1];if(1===o&&1===a)return` float ${n}(int index) { return sampleTexture(${r}, halfCR); } `;let l=h(r);return 1===o?t?` float ${n}(int index) { vec2 uv = vec2(0.5, (float(index + ${l}) + 0.5) / float(${r}TexShape[0])); return sampleTexture(${r}, uv); } `:` float ${n}(int index) { vec2 uv = vec2(0.5, (float(index + ${l}) + 0.5) / ${a}.0); return sampleTexture(${r}, uv); } `:1===a?t?` float ${n}(int index) { vec2 uv = vec2((float(index + ${l}) + 0.5) / float(${r}TexShape[1]), 0.5); return sampleTexture(${r}, uv); } `:` float ${n}(int index) { vec2 uv = vec2((float(index + ${l}) + 0.5) / ${o}.0, 0.5); return sampleTexture(${r}, uv); } `:t?` float ${n}(int index) { vec2 uv = uvFromFlat(${r}TexShape[0], ${r}TexShape[1], index + ${l}); return sampleTexture(${r}, uv); } `:` float ${n}(int index) { vec2 uv = uvFromFlat(${a}, ${o}, index + ${l}); return sampleTexture(${r}, uv); } `}(t,r);case 2:return function(t,r){let n=t.shapeInfo.logicalShape,s=t.name,o="get"+s.charAt(0).toUpperCase()+s.slice(1),l=t.shapeInfo.texShape;if(null!=l&&a.util.arraysEqual(n,l)){if(r)return` float ${o}(int row, int col) { vec2 uv = (vec2(col, row) + halfCR) / vec2(${s}TexShape[1], ${s}TexShape[0]); return sampleTexture(${s}, uv); } `;let e=l[0],t=l[1];return` float ${o}(int row, int col) { vec2 uv = (vec2(col, row) + halfCR) / vec2(${t}.0, ${e}.0); return sampleTexture(${s}, uv); } `}let{newShape:i,keptDims:p}=a.util.squeezeShape(n);if(i.length<n.length){let n=v(t,i);return` ${e(n,r)} float ${o}(int row, int col) { return ${o}(${b(["row","col"],p)}); } `}if(t.shapeInfo.isUniform)return` float ${o}(int row, int col) { int index = round(dot(vec2(row, col), vec2(${n[1]}, 1))); ${g(t)} } `;let u=l[0],c=l[1],d=h(s);return 1===c?r?` float ${o}(int row, int col) { float index = dot(vec3(row, col, ${d}), vec3(${s}Shape[1], 1, 1)); vec2 uv = vec2(0.5, (index + 0.5) / float(${s}TexShape[0])); return sampleTexture(${s}, uv); } `:` float ${o}(int row, int col) { float index = dot(vec3(row, col, ${d}), vec3(${n[1]}, 1, 1)); vec2 uv = vec2(0.5, (index + 0.5) / ${u}.0); return sampleTexture(${s}, uv); } `:1===u?r?` float ${o}(int row, int col) { float index = dot(vec3(row, col, ${d}), vec3(${s}Shape[1], 1, 1)); vec2 uv = vec2((index + 0.5) / float(${s}TexShape[1]), 0.5); return sampleTexture(${s}, uv); } `:` float ${o}(int row, int col) { float index = dot(vec3(row, col, ${d}), vec3(${n[1]}, 1, 1)); vec2 uv = vec2((index + 0.5) / ${c}.0, 0.5); return sampleTexture(${s}, uv); } `:r?` float ${o}(int row, int col) { // Explicitly use integer operations as dot() only works on floats. int index = row * ${s}Shape[1] + col + ${d}; vec2 uv = uvFromFlat(${s}TexShape[0], ${s}TexShape[1], index); return sampleTexture(${s}, uv); } `:` float ${o}(int row, int col) { // Explicitly use integer operations as dot() only works on floats. int index = row * ${n[1]} + col + ${d}; vec2 uv = uvFromFlat(${u}, ${c}, index); return sampleTexture(${s}, uv); } `}(t,r);case 3:return function(t,r){let n=t.shapeInfo.logicalShape,s=t.name,o="get"+s.charAt(0).toUpperCase()+s.slice(1),l=n[1]*n[2],i=n[2],{newShape:p,keptDims:u}=a.util.squeezeShape(n);if(p.length<n.length){let n=v(t,p);return` ${e(n,r)} float ${o}(int row, int col, int depth) { return ${o}(${b(["row","col","depth"],u)}); } `}if(t.shapeInfo.isUniform)return` float ${o}(int row, int col, int depth) { int index = round(dot(vec3(row, col, depth), vec3(${l}, ${i}, 1))); ${g(t)} } `;let c=t.shapeInfo.texShape,d=c[0],f=c[1],m=t.shapeInfo.flatOffset;if(f===l&&null==m)return r?` float ${o}(int row, int col, int depth) { int stride1 = ${s}Shape[2]; float texR = float(row); float texC = dot(vec2(col, depth), vec2(stride1, 1)); vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${s}TexShape[1], ${s}TexShape[0]); return sampleTexture(${s}, uv); } `:` float ${o}(int row, int col, int depth) { float texR = float(row); float texC = dot(vec2(col, depth), vec2(${i}, 1)); vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${f}.0, ${d}.0); return sampleTexture(${s}, uv); } `;if(f===i&&null==m)return r?` float ${o}(int row, int col, int depth) { float texR = dot(vec2(row, col), vec2(${s}Shape[1], 1)); float texC = float(depth); vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${s}TexShape[1], ${s}TexShape[0]); return sampleTexture(${s}, uv); } `:` float ${o}(int row, int col, int depth) { float texR = dot(vec2(row, col), vec2(${n[1]}, 1)); float texC = float(depth); vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${f}.0, ${d}.0); return sampleTexture(${s}, uv); } `;let x=h(s);return r?` float ${o}(int row, int col, int depth) { // Explicitly use integer operations as dot() only works on floats. int stride0 = ${s}Shape[1] * ${s}Shape[2]; int stride1 = ${s}Shape[2]; int index = row * stride0 + col * stride1 + depth + ${x}; vec2 uv = uvFromFlat(${s}TexShape[0], ${s}TexShape[1], index); return sampleTexture(${s}, uv); } `:` float ${o}(int row, int col, int depth) { // Explicitly use integer operations as dot() only works on floats. int index = row * ${l} + col * ${i} + depth + ${x}; vec2 uv = uvFromFlat(${d}, ${f}, index); return sampleTexture(${s}, uv); } `}(t,r);case 4:return function(t,r){let n=t.shapeInfo.logicalShape,s=t.name,o="get"+s.charAt(0).toUpperCase()+s.slice(1),l=n[3],i=n[2]*l,p=n[1]*i,{newShape:u,keptDims:c}=a.util.squeezeShape(n);if(u.length<n.length){let n=v(t,u);return` ${e(n,r)} float ${o}(int row, int col, int depth, int depth2) { return ${o}(${b(["row","col","depth","depth2"],c)}); } `}if(t.shapeInfo.isUniform)return` float ${o}(int row, int col, int depth, int depth2) { int index = round(dot(vec4(row, col, depth, depth2), vec4(${p}, ${i}, ${l}, 1))); ${g(t)} } `;let d=t.shapeInfo.flatOffset,f=t.shapeInfo.texShape,m=f[0],x=f[1],y=`int stride2 = ${s}Shape[3];`,k=`int stride1 = ${s}Shape[2] * stride2;`,_=`int stride0 = ${s}Shape[1] * stride1;`;if(x===p&&null==d)return r?` float ${o}(int row, int col, int depth, int depth2) { ${y} ${k} float texR = float(row); float texC = dot(vec3(col, depth, depth2), vec3(stride1, stride2, 1)); vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${s}TexShape[1], ${s}TexShape[0]); return sampleTexture(${s}, uv); } `:` float ${o}(int row, int col, int depth, int depth2) { float texR = float(row); float texC = dot(vec3(col, depth, depth2), vec3(${i}, ${l}, 1)); vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${x}.0, ${m}.0); return sampleTexture(${s}, uv); } `;if(x===l&&null==d)return r?` float ${o}(int row, int col, int depth, int depth2) { float texR = dot(vec3(row, col, depth), vec3(${s}Shape[1] * ${s}Shape[2], ${s}Shape[2], 1)); float texC = float(depth2); vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${s}TexShape[1], ${s}TexShape[0]); return sampleTexture(${s}, uv); } `:` float ${o}(int row, int col, int depth, int depth2) { float texR = dot(vec3(row, col, depth), vec3(${n[1]*n[2]}, ${n[2]}, 1)); float texC = float(depth2); vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${x}.0, ${m}.0); return sampleTexture(${s}, uv); } `;let I=h(s);return r?` float ${o}(int row, int col, int depth, int depth2) { // Explicitly use integer operations as dot() only works on floats. ${y} ${k} ${_} int index = row * stride0 + col * stride1 + depth * stride2 + depth2; vec2 uv = uvFromFlat(${s}TexShape[0], ${s}TexShape[1], index + ${I}); return sampleTexture(${s}, uv); } `:` float ${o}(int row, int col, int depth, int depth2) { // Explicitly use integer operations as dot() only works on floats. int index = row * ${p} + col * ${i} + depth * ${l} + depth2; vec2 uv = uvFromFlat(${m}, ${x}, index + ${I}); return sampleTexture(${s}, uv); } `}(t,r);case 5:return function(t){let r=t.shapeInfo.logicalShape,n=t.name,s="get"+n.charAt(0).toUpperCase()+n.slice(1),o=r[4],l=r[3]*o,i=r[2]*l,p=r[1]*i,{newShape:u,keptDims:c}=a.util.squeezeShape(r);if(u.length<r.length){let r=v(t,u);return` ${e(r)} float ${s}(int row, int col, int depth, int depth2, int depth3) { return ${s}(${b(["row","col","depth","depth2","depth3"],c)}); } `}if(t.shapeInfo.isUniform)return` float ${s}(int row, int col, int depth, int depth2, int depth3) { float index = dot( vec4(row, col, depth, depth2), vec4(${p}, ${i}, ${l}, ${o})) + depth3; ${g(t)} } `;let d=t.shapeInfo.flatOffset,f=t.shapeInfo.texShape,m=f[0],x=f[1];if(x===p&&null==d)return` float ${s}(int row, int col, int depth, int depth2, int depth3) { int texR = row; float texC = dot(vec4(col, depth, depth2, depth3), vec4(${i}, ${l}, ${o}, 1)); vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${x}.0, ${m}.0); return sampleTexture(${n}, uv); } `;if(x===o&&null==d)return` float ${s}(int row, int col, int depth, int depth2, int depth3) { float texR = dot( vec4(row, col, depth, depth2), vec4(${r[1]*r[2]*r[3]}, ${r[2]*r[3]}, ${r[3]}, 1)); int texC = depth3; vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${x}.0, ${m}.0); return sampleTexture(${n}, uv); } `;let y=h(n);return` float ${s}(int row, int col, int depth, int depth2, int depth3) { // Explicitly use integer operations as dot() only works on floats. int index = row * ${p} + col * ${i} + depth * ${l} + depth2 * ${o} + depth3 + ${y}; vec2 uv = uvFromFlat(${m}, ${x}, index); return sampleTexture(${n}, uv); } `}(t);case 6:return function(t){let r=t.shapeInfo.logicalShape,n=t.name,s="get"+n.charAt(0).toUpperCase()+n.slice(1),{newShape:o,keptDims:l}=a.util.squeezeShape(r);if(o.length<r.length){let r=v(t,o);return` ${e(r)} float ${s}(int row, int col, int depth, int depth2, int depth3, int depth4) { return ${s}(${b(["row","col","depth","depth2","depth3","depth4"],l)}); } `}let i=r[5],p=r[4]*i,u=r[3]*p,c=r[2]*u,d=r[1]*c;if(t.shapeInfo.isUniform)return` float ${s}(int row, int col, int depth, int depth2, int depth3, int depth4) { int index = round(dot( vec4(row, col, depth, depth2), vec4(${d}, ${c}, ${u}, ${p})) + dot( vec2(depth3, depth4), vec2(${i}, 1))); ${g(t)} } `;let f=t.shapeInfo.flatOffset,m=t.shapeInfo.texShape,x=m[0],y=m[1];if(y===d&&null==f)return` float ${s}(int row, int col, int depth, int depth2, int depth3, int depth4) { int texR = row; float texC = dot(vec4(col, depth, depth2, depth3), vec4(${c}, ${u}, ${p}, ${i})) + float(depth4); vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${y}.0, ${x}.0); return sampleTexture(${n}, uv); } `;if(y===i&&null==f)return` float ${s}(int row, int col, int depth, int depth2, int depth3, int depth4) { float texR = dot(vec4(row, col, depth, depth2), vec4(${r[1]*r[2]*r[3]*r[4]}, ${r[2]*r[3]*r[4]}, ${r[3]*r[4]}, ${r[4]})) + float(depth3); int texC = depth4; vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${y}.0, ${x}.0); return sampleTexture(${n}, uv); } `;let k=h(n);return` float ${s}(int row, int col, int depth, int depth2, int depth3, int depth4) { // Explicitly use integer operations as dot() only works on floats. int index = row * ${d} + col * ${c} + depth * ${u} + depth2 * ${p} + depth3 * ${i} + depth4 + ${k}; vec2 uv = uvFromFlat(${x}, ${y}, index); return sampleTexture(${n}, uv); } `}(t);default:throw Error(`${n.length}-D input sampling is not yet supported`)}}(e,n);let l=e.shapeInfo.logicalShape,p=t.logicalShape;return l.length<=p.length&&(r?s+=function(e,t){let r,n=e.name,s=n.charAt(0).toUpperCase()+n.slice(1),o=e.shapeInfo.logicalShape.length,l=t.logicalShape.length,p=i(e.shapeInfo.logicalShape,t.logicalShape),u=x(l),c=l-o,d=["x","y","z","w","u","v"];r=0===o?"":l<2&&p.length>=1?"coords = 0;":p.map(e=>`coords.${d[e+c]} = 0;`).join("\n");let f="";f=l<2&&o>0?"coords":e.shapeInfo.logicalShape.map((e,t)=>`coords.${d[t+c]}`).join(", ");let m="return outputValue;",h=1===a.util.sizeFromShape(e.shapeInfo.logicalShape),g=1===a.util.sizeFromShape(t.logicalShape);if(1!==o||h||g){if(h&&!g)m=1===l?` return vec4(outputValue.x, outputValue.x, 0., 0.); `:` return vec4(outputValue.x); `;else if(p.length){let e=o-2,t=o-1;p.indexOf(e)>-1&&p.indexOf(t)>-1?m="return vec4(outputValue.x);":p.indexOf(e)>-1?m="return vec4(outputValue.x, outputValue.y, outputValue.x, outputValue.y);":p.indexOf(t)>-1&&(m="return vec4(outputValue.xx, outputValue.zz);")}}else m=` return vec4(outputValue.xy, outputValue.xy); `;return` vec4 ${"get"+s+"AtOutCoords"}() { ${u} coords = getOutputCoords(); ${r} vec4 outputValue = get${s}(${f}); ${m} } `}(e,t):s+=function(e,t){let r,n=e.name,s=n.charAt(0).toUpperCase()+n.slice(1),o="get"+s+"AtOutCoords",l=t.texShape,p=e.shapeInfo.texShape,u=e.shapeInfo.logicalShape.length,c=t.logicalShape.length;if(!e.shapeInfo.isUniform&&u===c&&null==e.shapeInfo.flatOffset&&a.util.arraysEqual(p,l))return` float ${o}() { return sampleTexture(${n}, resultUV); } `;let d=x(c),f=i(e.shapeInfo.logicalShape,t.logicalShape),m=c-u,h=["x","y","z","w","u","v"];r=0===u?"":c<2&&f.length>=1?"coords = 0;":f.map(e=>`coords.${h[e+m]} = 0;`).join("\n");let g="";return g=c<2&&u>0?"coords":e.shapeInfo.logicalShape.map((e,t)=>`coords.${h[t+m]}`).join(", "),` float ${o}() { ${d} coords = getOutputCoords(); ${r} return get${s}(${g}); } `}(e,t)),s})(e,t,r.packedInputs,r.enableShapeUniforms)).join("\n"),S=t.texShape,C=(0,o.getGlslDifferences)(),N=(n=C,` float sampleTexture(sampler2D textureSampler, vec2 uv) { return ${n.texture2D}(textureSampler, uv).r; } 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int getOutputCoords() { return 2 * int(resultUV.x * ceil(float(outTexShape[1]) / 2.0)); } `:` int getOutputCoords() { return 2 * int(resultUV.x * ${o[1]}.0); } `:1===o[1]?s?` int getOutputCoords() { return 2 * int(resultUV.y * ceil(float(outTexShape[0]) / 2.0)); } `:` int getOutputCoords() { return 2 * int(resultUV.y * ${o[0]}.0); } `:s?` int getOutputCoords() { ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0)); ivec2 resTexRC = ivec2(resultUV.yx * vec2(packedTexShape[0], packedTexShape[1])); return 2 * (resTexRC.x * packedTexShape[1] + resTexRC.y); } `:` int getOutputCoords() { ivec2 resTexRC = ivec2(resultUV.yx * vec2(${o[0]}, ${o[1]})); return 2 * (resTexRC.x * ${o[1]} + resTexRC.y); } `;case 2:var l=e,i=t,p=r;let u=[Math.ceil(i[0]/2),Math.ceil(i[1]/2)];if(a.util.arraysEqual(l,i))return p?` ivec2 getOutputCoords() { ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0)); return 2 * 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getOutputCoords() { return ivec2(resultUV.yx * vec2(outTexShape[0], outTexShape[1])); } `:` ivec2 getOutputCoords() { return ivec2(resultUV.yx * vec2(${i[0]}, ${i[1]})); } `:1===o[1]?p?` ivec2 getOutputCoords() { ivec2 resTexRC = ivec2(resultUV.yx * vec2(outTexShape[0], outTexShape[1])); int index = resTexRC.x * outTexShape[1] + resTexRC.y; return ivec2(index, 0); } `:` ivec2 getOutputCoords() { ivec2 resTexRC = ivec2(resultUV.yx * vec2(${i[0]}, ${i[1]})); int index = resTexRC.x * ${i[1]} + resTexRC.y; return ivec2(index, 0); } `:1===o[0]?p?` ivec2 getOutputCoords() { ivec2 resTexRC = ivec2(resultUV.yx * vec2(outTexShape[0], outTexShape[1])); int index = resTexRC.x * outTexShape[1] + resTexRC.y; return ivec2(0, index); } `:` ivec2 getOutputCoords() { ivec2 resTexRC = ivec2(resultUV.yx * vec2(${i[0]}, ${i[1]})); int index = resTexRC.x * ${i[1]} + resTexRC.y; return ivec2(0, index); } `:p?` ivec2 getOutputCoords() { ivec2 resTexRC = ivec2(resultUV.yx * vec2(outTexShape[0], 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} `}function d(){return` int getFlatIndex(ivec3 coords) { return coords.x * outShapeStrides[0] + coords.y * outShapeStrides[1] + coords.z; } `}let f=` 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; } `},{"@tensorflow/tfjs-core":"2Gtps","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],hlqVO:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"DecodeMatrixPackedProgram",()=>p);var a=e("./glsl_version"),o=e("./gpgpu_math"),l=e("./shader_compiler_util"),i=e("./tex_util");class p{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outPackingScheme=i.PackingScheme.DENSE,this.customUniforms=[{name:"texShape",type:"ivec2"}];const t=(0,a.getGlslDifferences)();this.outputShape=e,this.enableShapeUniforms=(0,o.useShapeUniforms)(this.outputShape.length),this.userCode=` ivec3 outCoordsFromFlatIndex(int index) { ${this.enableShapeUniforms?l.getOutputLogicalCoordinatesFromFlatIndexByUniform(["r","c","d"],e):l.getLogicalCoordinatesFromFlatIndex(["r","c","d"],e)} return ivec3(r, c, d); 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if(localCoords[2] + ${s} < ${this.enableShapeUniforms?"outShape[2]":`${e[2]}`}) { localCoords[2] += ${s}; if (localCoords[1] + ${t} < ${this.enableShapeUniforms?"outShape[1]":`${e[1]}`}) { localCoords[1] += ${t}; flatIndex = getFlatIndex(localCoords); offset = imod(flatIndex, 4); flatIndex = idiv(flatIndex, 4, 1.); int r = flatIndex / texShape[1]; int c = imod(flatIndex, texShape[1]); vec2 uv = (vec2(c, r) + halfCR) / vec2(texShape[1], texShape[0]); values = ${r.texture2D}(A, uv); if (offset == 0) { result[${a}] = values[0]; } else if (offset == 1) { result[${a}] = values[1]; } else if (offset == 2) { result[${a}] = values[2]; } else { result[${a}] = values[3]; } } } `}this.userCode=` ${this.enableShapeUniforms?l.getFlatIndexFrom3DOutput():l.getFlatIndexFrom3D(e)} void main() { ivec3 coords = getOutputCoords(); vec4 result = vec4(0.); int flatIndex, r, c, offset; ivec3 localCoords; vec2 uv; vec4 values; ${n} ${r.output} = ${s}; } `}}},{"./glsl_version":"dyQn5","./gpgpu_math":"6rFox","./shader_compiler_util":"7L8PC","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],eJgSB:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"GPGPUContext",()=>u),s.export(r,"linearSearchLastTrue",()=>c);var a=e("@tensorflow/tfjs-core"),o=e("./canvas_util"),l=e("./gpgpu_util"),i=e("./tex_util"),p=e("./webgl_util");class u{constructor(e){this.outputTexture=null,this.program=null,this.disposed=!1,this.itemsToPoll=[];const t=(0,a.env)().getNumber("WEBGL_VERSION");if(null!=e?(this.gl=e,(0,o.setWebGLContext)(t,e)):this.gl=(0,o.getWebGLContext)(t),e=this.gl,2===(0,a.env)().getNumber("WEBGL_VERSION")){const t=e;this.createVertexArray=()=>p.callAndCheck(t,()=>t.createVertexArray()),this.bindVertexArray=e=>p.callAndCheck(t,()=>t.bindVertexArray(e)),this.deleteVertexArray=e=>p.callAndCheck(t,()=>t.deleteVertexArray(e)),this.getVertexArray=()=>p.callAndCheck(t,()=>t.getParameter(t.VERTEX_ARRAY_BINDING))}else if(null!=e){const t=e.getExtension("OES_vertex_array_object");if(null==t)throw Error("All WebGL1 implementations are expected to offer OES_vertex_array_object.");this.createVertexArray=()=>p.callAndCheck(e,()=>t.createVertexArrayOES()),this.bindVertexArray=r=>p.callAndCheck(e,()=>t.bindVertexArrayOES(r)),this.deleteVertexArray=r=>p.callAndCheck(e,()=>t.deleteVertexArrayOES(r)),this.getVertexArray=()=>p.callAndCheck(e,()=>e.getParameter(t.VERTEX_ARRAY_BINDING_OES))}let r="WEBGL_color_buffer_float";const n="EXT_color_buffer_half_float";if(this.parallelCompilationExtension=this.gl.getExtension("KHR_parallel_shader_compile"),1===(0,a.env)().getNumber("WEBGL_VERSION")){const e="OES_texture_half_float";if(this.textureFloatExtension=p.getExtensionOrThrow(this.gl,"OES_texture_float"),p.hasExtension(this.gl,e))this.textureHalfFloatExtension=p.getExtensionOrThrow(this.gl,e);else if((0,a.env)().get("WEBGL_FORCE_F16_TEXTURES"))throw Error("GL context does not support half float textures, yet the environment flag WEBGL_FORCE_F16_TEXTURES is set to true.");if(this.colorBufferFloatExtension=this.gl.getExtension(r),p.hasExtension(this.gl,n))this.colorBufferHalfFloatExtension=p.getExtensionOrThrow(this.gl,n);else if((0,a.env)().get("WEBGL_FORCE_F16_TEXTURES"))throw Error("GL context does not support color renderable half floats, yet the environment flag WEBGL_FORCE_F16_TEXTURES is set to true.")}else if(r="EXT_color_buffer_float",p.hasExtension(this.gl,r))this.colorBufferFloatExtension=this.gl.getExtension(r);else if(p.hasExtension(this.gl,n))this.colorBufferHalfFloatExtension=this.gl.getExtension(n);else throw Error("GL context does not support color renderable floats");this.vertexBuffer=l.createVertexBuffer(this.gl),this.indexBuffer=l.createIndexBuffer(this.gl),this.framebuffer=p.createFramebuffer(this.gl),this.textureConfig=i.getTextureConfig(this.gl,this.textureHalfFloatExtension)}get debug(){return(0,a.env)().getBool("DEBUG")}dispose(){if(this.disposed)return;null!=this.program&&console.warn("Disposing a GPGPUContext that still has a bound WebGLProgram. This is probably a resource leak, delete the program with GPGPUContext.deleteProgram before disposing."),null!=this.outputTexture&&console.warn("Disposing a GPGPUContext that still has a bound output matrix texture. This is probably a resource leak, delete the output matrix texture with GPGPUContext.deleteMatrixTexture before disposing.");let e=this.gl;p.callAndCheck(e,()=>e.finish()),p.callAndCheck(e,()=>e.bindFramebuffer(e.FRAMEBUFFER,null)),p.callAndCheck(e,()=>e.deleteFramebuffer(this.framebuffer)),p.callAndCheck(e,()=>e.bindBuffer(e.ARRAY_BUFFER,null)),p.callAndCheck(e,()=>e.bindBuffer(e.ELEMENT_ARRAY_BUFFER,null)),p.callAndCheck(e,()=>e.deleteBuffer(this.indexBuffer)),this.disposed=!0}createFloat32MatrixTexture(e,t){return this.throwIfDisposed(),l.createFloat32MatrixTexture(this.gl,e,t,this.textureConfig)}createFloat16MatrixTexture(e,t){return this.throwIfDisposed(),l.createFloat16MatrixTexture(this.gl,e,t,this.textureConfig)}createUnsignedBytesMatrixTexture(e,t){return this.throwIfDisposed(),l.createUnsignedBytesMatrixTexture(this.gl,e,t,this.textureConfig)}uploadPixelDataToTexture(e,t){this.throwIfDisposed(),l.uploadPixelDataToTexture(this.gl,e,t)}uploadDenseMatrixToTexture(e,t,r,n){this.throwIfDisposed(),l.uploadDenseMatrixToTexture(this.gl,e,t,r,n,this.textureConfig)}createFloat16PackedMatrixTexture(e,t){return this.throwIfDisposed(),l.createFloat16PackedMatrixTexture(this.gl,e,t,this.textureConfig)}createPackedMatrixTexture(e,t){return this.throwIfDisposed(),l.createPackedMatrixTexture(this.gl,e,t,this.textureConfig)}deleteMatrixTexture(e){this.throwIfDisposed(),this.outputTexture===e&&(p.unbindColorTextureFromFramebuffer(this.gl,this.framebuffer),this.outputTexture=null),p.callAndCheck(this.gl,()=>this.gl.deleteTexture(e))}downloadByteEncodedFloatMatrixFromOutputTexture(e,t,r){return this.downloadMatrixDriver(e,()=>l.downloadByteEncodedFloatMatrixFromOutputTexture(this.gl,t,r,this.textureConfig))}downloadPackedMatrixFromBuffer(e,t,r,n,s,a){return l.downloadPackedMatrixFromBuffer(this.gl,e,t,r,n,s,a,this.textureConfig)}downloadFloat32MatrixFromBuffer(e,t){return l.downloadFloat32MatrixFromBuffer(this.gl,e,t)}createBufferFromTexture(e,t,r){this.bindTextureToFrameBuffer(e);let n=l.createBufferFromOutputTexture(this.gl,t,r,this.textureConfig);return this.unbindTextureToFrameBuffer(),n}createAndWaitForFence(){let e=this.createFence(this.gl);return this.pollFence(e)}createFence(e){let t,r;if((0,a.env)().getBool("WEBGL_FENCE_API_ENABLED")){let n=e.fenceSync(e.SYNC_GPU_COMMANDS_COMPLETE,0);e.flush(),r=()=>{let t=e.clientWaitSync(n,0,0);return t===e.ALREADY_SIGNALED||t===e.CONDITION_SATISFIED},t=n}else(0,a.env)().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")>0?(t=this.beginQuery(),this.endQuery(),r=()=>this.isQueryAvailable(t,(0,a.env)().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))):r=()=>!0;return{query:t,isFencePassed:r}}downloadMatrixFromPackedTexture(e,t,r){return this.downloadMatrixDriver(e,()=>l.downloadMatrixFromPackedOutputTexture(this.gl,t,r))}createProgram(e){this.throwIfDisposed();let t=this.gl;null==this.vertexShader&&(this.vertexShader=l.createVertexShader(t));let r=p.createProgram(t);p.callAndCheck(t,()=>t.attachShader(r,this.vertexShader)),p.callAndCheck(t,()=>t.attachShader(r,e)),p.linkProgram(t,r);let n=Object.assign(r,{vao:this.createVertexArray()});return this.debug&&p.validateProgram(t,n),n}buildVao(e){this.setProgram(e),this.bindVertexArray(e.vao);let t=this.gl;p.callAndCheck(t,()=>t.bindBuffer(t.ELEMENT_ARRAY_BUFFER,this.indexBuffer)),l.bindVertexProgramAttributeStreams(t,e,this.vertexBuffer)}deleteProgram(e){this.throwIfDisposed(),e===this.program&&(this.program=null),null!=e&&(p.callAndCheck(this.gl,()=>this.gl.deleteProgram(e)),this.deleteVertexArray(e.vao))}setProgram(e){this.throwIfDisposed(),this.program=e,null!=this.program&&this.debug&&p.validateProgram(this.gl,this.program),p.callAndCheck(this.gl,()=>this.gl.useProgram(e))}getUniformLocation(e,t,r=!0){return(this.throwIfDisposed(),r)?p.getProgramUniformLocationOrThrow(this.gl,e,t):p.getProgramUniformLocation(this.gl,e,t)}getAttributeLocation(e,t){return this.throwIfDisposed(),p.callAndCheck(this.gl,()=>this.gl.getAttribLocation(e,t))}getUniformLocationNoThrow(e,t){return this.throwIfDisposed(),this.gl.getUniformLocation(e,t)}setInputMatrixTexture(e,t,r){this.throwIfDisposed(),this.throwIfNoProgram(),p.bindTextureToProgramUniformSampler(this.gl,e,t,r)}setOutputMatrixTexture(e,t,r){this.setOutputMatrixTextureDriver(e,r,t)}setOutputPackedMatrixTexture(e,t,r){this.throwIfDisposed();let[n,s]=i.getPackedMatrixTextureShapeWidthHeight(t,r);this.setOutputMatrixTextureDriver(e,n,s)}setOutputMatrixWriteRegion(e,t,r,n){this.setOutputMatrixWriteRegionDriver(r,e,n,t)}setOutputPackedMatrixWriteRegion(e,t,r,n){throw Error("setOutputPackedMatrixWriteRegion not implemented.")}debugValidate(){null!=this.program&&p.validateProgram(this.gl,this.program),p.validateFramebuffer(this.gl)}executeProgram(){this.throwIfDisposed(),this.throwIfNoProgram();let e=this.gl;this.debug&&(console.assert(this.getVertexArray()===this.program.vao,"VAO changed between setProgram and executeProgram!"),this.debugValidate()),p.callAndCheck(e,()=>e.drawElements(e.TRIANGLES,6,e.UNSIGNED_SHORT,0))}blockUntilAllProgramsCompleted(){this.throwIfDisposed(),p.callAndCheck(this.gl,()=>this.gl.finish())}getQueryTimerExtension(){return null==this.disjointQueryTimerExtension&&(this.disjointQueryTimerExtension=p.getExtensionOrThrow(this.gl,2===(0,a.env)().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")?"EXT_disjoint_timer_query_webgl2":"EXT_disjoint_timer_query")),this.disjointQueryTimerExtension}getQueryTimerExtensionWebGL2(){return this.getQueryTimerExtension()}getQueryTimerExtensionWebGL1(){return this.getQueryTimerExtension()}beginQuery(){if(2===(0,a.env)().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")){let e=this.gl,t=this.getQueryTimerExtensionWebGL2(),r=e.createQuery();return e.beginQuery(t.TIME_ELAPSED_EXT,r),r}let e=this.getQueryTimerExtensionWebGL1(),t=e.createQueryEXT();return e.beginQueryEXT(e.TIME_ELAPSED_EXT,t),t}endQuery(){if(2===(0,a.env)().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")){let e=this.gl,t=this.getQueryTimerExtensionWebGL2();e.endQuery(t.TIME_ELAPSED_EXT);return}let e=this.getQueryTimerExtensionWebGL1();e.endQueryEXT(e.TIME_ELAPSED_EXT)}async waitForQueryAndGetTime(e){return await a.util.repeatedTry(()=>this.disposed||this.isQueryAvailable(e,(0,a.env)().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))),this.getQueryTime(e,(0,a.env)().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))}getQueryTime(e,t){if(0===t)return null;if(2===t){let t=this.gl;return t.getQueryParameter(e,t.QUERY_RESULT)/1e6}{let t=this.getQueryTimerExtensionWebGL1();return t.getQueryObjectEXT(e,t.QUERY_RESULT_EXT)/1e6}}isQueryAvailable(e,t){if(0===t)return!0;if(2===t){let t=this.gl,r=this.getQueryTimerExtensionWebGL2(),n=t.getQueryParameter(e,t.QUERY_RESULT_AVAILABLE);return null==this.disjoint&&(this.disjoint=this.gl.getParameter(r.GPU_DISJOINT_EXT)),n&&!this.disjoint}{let t=this.getQueryTimerExtensionWebGL1(),r=t.getQueryObjectEXT(e,t.QUERY_RESULT_AVAILABLE_EXT);return null==this.disjoint&&(this.disjoint=this.gl.getParameter(t.GPU_DISJOINT_EXT)),r&&!this.disjoint}}pollFence(e){return new Promise(t=>{this.addItemToPoll(()=>e.isFencePassed(),()=>t())})}pollItems(){let e=c(this.itemsToPoll.map(e=>e.isDoneFn));for(let t=0;t<=e;++t){let{resolveFn:e}=this.itemsToPoll[t];e()}this.itemsToPoll=this.itemsToPoll.slice(e+1)}addItemToPoll(e,t){let r;this.itemsToPoll.push({isDoneFn:e,resolveFn:t}),this.itemsToPoll.length>1||("setTimeoutCustom"in(0,a.env)().platform&&(r=(0,a.env)().platform.setTimeoutCustom.bind((0,a.env)().platform)),a.util.repeatedTry(()=>(this.pollItems(),0===this.itemsToPoll.length),()=>0,null,r))}bindTextureToFrameBuffer(e){this.throwIfDisposed(),p.bindColorTextureToFramebuffer(this.gl,e,this.framebuffer),this.debug&&p.validateFramebuffer(this.gl)}unbindTextureToFrameBuffer(){null!=this.outputTexture?(p.bindColorTextureToFramebuffer(this.gl,this.outputTexture,this.framebuffer),this.debug&&p.validateFramebuffer(this.gl)):p.unbindColorTextureFromFramebuffer(this.gl,this.framebuffer)}downloadMatrixDriver(e,t){this.bindTextureToFrameBuffer(e);let r=t();return this.unbindTextureToFrameBuffer(),r}setOutputMatrixTextureDriver(e,t,r){this.throwIfDisposed();let n=this.gl;p.bindColorTextureToFramebuffer(n,e,this.framebuffer),this.debug&&p.validateFramebuffer(n),this.outputTexture=e,p.callAndCheck(n,()=>n.viewport(0,0,t,r)),p.callAndCheck(n,()=>n.scissor(0,0,t,r))}setOutputMatrixWriteRegionDriver(e,t,r,n){this.throwIfDisposed(),p.callAndCheck(this.gl,()=>this.gl.scissor(e,t,r,n))}throwIfDisposed(){if(this.disposed)throw Error("Attempted to use disposed GPGPUContext.")}throwIfNoProgram(){if(null==this.program)throw Error("No GPU program is currently set.")}}function c(e){let t=0;for(;t<e.length&&e[t]();++t);return t-1}},{"@tensorflow/tfjs-core":"2Gtps","./canvas_util":"hTzxU","./gpgpu_util":"lhqGJ","./tex_util":"etxDi","./webgl_util":"kBGlX","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],lhqGJ:[function(e,t,r,n){var 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ls/FlipLeftRight":"iloIr","./kernels/Floor":"68gWA","./kernels/FloorDiv":"dW3ZT","./kernels/FromPixels":"eouhM","./kernels/FusedConv2D":"4057Z","./kernels/FusedDepthwiseConv2D":"5c3VQ","./kernels/GatherNd":"9L1cm","./kernels/GatherV2":"l9Cv5","./kernels/Greater":"2onfy","./kernels/GreaterEqual":"j3rRR","./kernels/Identity":"97wVJ","./kernels/IFFT":"1XpIh","./kernels/Imag":"3QJSY","./kernels/IsFinite":"2G76h","./kernels/IsInf":"e9CB0","./kernels/IsNaN":"dGj2A","./kernels/LeakyRelu":"7xwOe","./kernels/Less":"aRr8q","./kernels/LessEqual":"khsCA","./kernels/LinSpace":"gzgJQ","./kernels/Log":"5Afxb","./kernels/Log1p":"ihKi1","./kernels/LogicalAnd":"g7wT3","./kernels/LogicalNot":"3Jb1X","./kernels/LogicalOr":"9pxKx","./kernels/LRN":"gm5j4","./kernels/LRNGrad":"lcb03","./kernels/Max":"afHh0","./kernels/Maximum":"94OQw","./kernels/MaxPool":"3XdiF","./kernels/MaxPool3D":"2yDQt","./kernels/MaxPool3DGrad":"5foYE","./kernels/MaxPoolGrad":"fOmt4","./kernels/MaxPoolWithArgmax":"1bzUD","./kernels/Mean":"76W3Z","./kernels/Min":"1XKVy","./kernels/Minimum":"jZlPa","./kernels/MirrorPad":"akMJ7","./kernels/Mod":"gnARU","./kernels/Multinomial":"bTfCp","./kernels/Multiply":"gGANs","./kernels/Neg":"7nm6C","./kernels/NonMaxSuppressionV3":"4Tndn","./kernels/NonMaxSuppressionV4":"h8she","./kernels/NonMaxSuppressionV5":"jjRNa","./kernels/NotEqual":"cIcHR","./kernels/OneHot":"3okp7","./kernels/OnesLike":"iSWOT","./kernels/Pack":"7VW16","./kernels/PadV2":"5SaGA","./kernels/Pow":"hTipi","./kernels/Prelu":"8Anjo","./kernels/Prod":"i8gle","./kernels/RaggedGather":"9WlaC","./kernels/RaggedRange":"6frqk","./kernels/RaggedTensorToTensor":"9QHo7","./kernels/Range":"h4DwD","./kernels/Real":"cAQO8","./kernels/RealDiv":"2I75W","./kernels/Reciprocal":"cW4of","./kernels/Relu":"fD5Nl","./kernels/Relu6":"fJ8FQ","./kernels/Reshape":"aOEE6","./kernels/ResizeBilinear":"50UZz","./kernels/ResizeBilinearGrad":"9CnrH","./kernels/ResizeNearestNeighbor":"g9ks1","./kernels/ResizeNearestNeighborGrad":"bi2fw","./kernels/Reverse":"ltUYd","./kernels/RotateWithOffset":"ct6xT","./kernels/Round":"guuD3","./kernels/Rsqrt":"cEMqB","./kernels/ScatterNd":"71HHv","./kernels/SearchSorted":"2HCMo","./kernels/Select":"bAD9b","./kernels/Selu":"lQKcR","./kernels/Sigmoid":"j9jdu","./kernels/Sign":"hXrTd","./kernels/Sin":"ik6fv","./kernels/Sinh":"icMAI","./kernels/Slice":"io5JZ","./kernels/Softmax":"gCAqF","./kernels/Softplus":"3vYWS","./kernels/SpaceToBatchND":"hahtJ","./kernels/SparseFillEmptyRows":"lzibC","./kernels/SparseReshape":"20NEG","./kernels/SparseSegmentMean":"hvZiZ","./kernels/SparseSegmentSum":"kvTUn","./kernels/SparseToDense":"8zzlj","./kernels/SplitV":"bpzye","./kernels/Sqrt":"8daDR","./kernels/Square":"2Dt4D","./kernels/SquaredDifference":"2n3Wa","./kernels/StaticRegexReplace":"dPF4m","./kernels/Step":"jXf2G","./kernels/StridedSlice":"8zt5O","./kernels/StringNGrams":"7gc6P","./kernels/StringSplit":"cqC5i","./kernels/StringToHashBucketFast":"dp2Po","./kernels/Sub":"bBcnF","./kernels/Sum":"M2cwD","./kernels/Tan":"jW0aV","./kernels/Tanh":"j5B1H","./kernels/TensorScatterUpdate":"lpK3g","./kernels/Tile":"2BktY","./kernels/TopK":"ctM3S","./kernels/Transform":"2YDLy","./kernels/Transpose":"lqCy7","./kernels/Unique":"hBsG3","./kernels/Unpack":"eP6TK","./kernels/UnsortedSegmentSum":"1Qhxo","./kernels/ZerosLike":"eoHmb"}],"9ilMK":[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"_fusedMatMul",()=>l),s.export(r,"_fusedMatMulConfig",()=>i);var a=e("@tensorflow/tfjs-core"),o=e("./BatchMatMul_impl");function l(e){let{inputs:t,backend:r,attrs:n}=e,{a:s,b:a,bias:l,preluActivationWeights:i}=t,{transposeA:p,transposeB:u,activation:c,leakyreluAlpha:d}=n;return(0,o.batchMatMulImpl)({a:s,b:a,transposeA:p,transposeB:u,backend:r,bias:l,preluActivationWeights:i,leakyreluAlpha:d,activation:c})}let i={kernelName:a._FusedMatMul,backendName:"webgl",kernelFunc:l}},{"@tensorflow/tfjs-core":"2Gtps","./BatchMatMul_impl":"aJhdh","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],aJhdh:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"MATMUL_SHARED_DIM_THRESHOLD",()=>d),s.export(r,"batchMatMulImpl",()=>f);var a=e("@tensorflow/tfjs-core"),o=e("../kernel_utils/kernel_funcs_utils"),l=e("../mulmat_packed_gpu"),i=e("./Multiply"),p=e("./Reshape"),u=e("./Sum"),c=e("./Transpose");let d=1e3;function f({a:e,b:t,transposeA:r,transposeB:n,backend:s,bias:f=null,preluActivationWeights:m=null,leakyreluAlpha:h=0,activation:g=null}){let x,y=e.shape.length,v=t.shape.length,b=r?e.shape[y-2]:e.shape[y-1],k=n?t.shape[v-1]:t.shape[v-2],_=r?e.shape[y-1]:e.shape[y-2],I=n?t.shape[v-2]:t.shape[v-1],j=e.shape.slice(0,-2),w=t.shape.slice(0,-2),T=a.util.sizeFromShape(j),S=a.util.sizeFromShape(w),C=a.broadcast_util.assertAndGetBroadcastShape(e.shape.slice(0,-2),t.shape.slice(0,-2)).concat([_,I]);a.util.assert(b===k,()=>`Error in matMul: inner shapes (${b}) and (${k}) of Tensors with shapes ${e.shape} and ${t.shape} and transposeA=${r} and transposeB=${n} must match.`);let 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p={kernelName:a.ArgMax,backendName:"webgl",kernelFunc:i}},{"@tensorflow/tfjs-core":"2Gtps","../kernel_utils/arg_min_max":"7vOin","./Transpose":"lqCy7","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],"7vOin":[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"argMinMaxReduce",()=>p);var a=e("@tensorflow/tfjs-core"),o=e("../argminmax_gpu"),l=e("../argminmax_packed_gpu"),i=e("../kernels/Reshape");function p(e,t,r,n){let s=[r];if(a.backend_util.assertAxesAreInnerMostDims("arg"+n.charAt(0).toUpperCase()+n.slice(1),s,t.shape.length),!(0,a.env)().getBool("WEBGL_PACK_REDUCE")||t.shape.length<=2){let r=[],l=e.texData.get(t.dataId),p=null!==l&&l.isPacked,u=t;p&&r.push(u=e.unpackTensor(t));let[c,d]=a.backend_util.computeOutAndReduceShapes(u.shape,s),f=a.util.sizeFromShape(d),m=(0,i.reshape)({inputs:{x:u},backend:e,attrs:{shape:[-1,f]}});r.push(m);let h=function e(t,r,n,s=null){let l=r.shape[0],i=r.shape[1];null!=s&&(l=s.shape[0],i=s.shape[1]);let p=a.backend_util.computeOptimalWindowSize(i),u={windowSize:p,inSize:i,batchSize:l,outSize:Math.ceil(i/p)},c=new(0,o.ArgMinMaxProgram)(u,n,null==s),d=[r];null!=s&&d.push(s);let f=t.runWebGLProgram(c,d,"int32");if(1===f.shape[1])return f;let m=e(t,r,n,f);return t.disposeIntermediateTensorInfo(f),m}(e,m,n);r.push(h);let g=(0,i.reshape)({inputs:{x:h},backend:e,attrs:{shape:c}});return r.forEach(t=>e.disposeIntermediateTensorInfo(t)),g}return function e(t,r,n,s=null){let o=null!=s?s.shape:r.shape,i=o[o.length-1],p=a.backend_util.computeOptimalWindowSize(i),u=new(0,l.ArgMinMaxPackedProgram)(o,p,n,null==s),c=null==s?[r]:[r,s],d=t.runWebGLProgram(u,c,"int32");if(d.shape.length===r.shape.length){let s=e(t,r,n,d);return t.disposeIntermediateTensorInfo(d),s}return d}(e,t,n)}},{"@tensorflow/tfjs-core":"2Gtps","../argminmax_gpu":"2ugSk","../argminmax_packed_gpu":"hKRFn","../kernels/Reshape":"aOEE6","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],"2ugSk":[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"ArgMinMaxProgram",()=>a);class a{constructor(e,t,r){this.variableNames=["A"];const{windowSize:n,batchSize:s,outSize:a}=e;r||this.variableNames.push("bestIndicesA"),this.outputShape=[s,a],this.userCode=` void main() { ivec2 coords = getOutputCoords(); int batch = coords[0]; int outIdx = coords[1]; int inOffset = outIdx * ${n}; int bestIndex = inOffset; float bestValue = getA(batch, bestIndex); for (int i = 0; i< ${n}; i++) { int inIdx = ${r?"inOffset + i;":"round(getBestIndicesA(batch, inOffset + i));"}; float candidate = getA(batch, inIdx); if (candidate ${"max"===t?">":"<"} bestValue) { bestValue = candidate; bestIndex = inIdx; } } setOutput(float(bestIndex)); } `}}},{"@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],hKRFn:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"ArgMinMaxPackedProgram",()=>i);var a=e("@tensorflow/tfjs-core"),o=e("./packing_util"),l=e("./shader_compiler");class i{constructor(e,t,r,n){let s,i;this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,a.util.assert(e.length>2,()=>`Packed arg${r.charAt(0).toUpperCase()+r.slice(1)} supports only inputs with rank above 2.`);const p=Math.ceil(e[e.length-1]/t);this.outputShape=e.slice(0,-1),p>1&&this.outputShape.push(p),n||this.variableNames.push("bestIndicesA");const u=this.outputShape,c=u.length,d=(0,l.getCoordsDataType)(c),f=(0,o.getChannels)("coords",c);if(1===p){i=c+1;const e=(0,l.getCoordsDataType)(i);s=` ${e} sourceLocR = ${e}(${f.join()}, 0); ++${f[c-1]}; ${e} sourceLocG = ${e}(${f.join()}, 0); ++${f[c-2]}; ${e} sourceLocA = ${e}(${f.join()}, 0); --${f[c-1]}; ${e} sourceLocB = ${e}(${f.join()}, 0); --${f[c-2]};`}else i=c,s=` ${d} sourceLocR = coords; ++${f[c-1]}; ${d} sourceLocG = coords; ++${f[c-2]}; ${d} sourceLocA = coords; --${f[c-1]}; ${d} sourceLocB = coords; --${f[c-2]};`;const m=["x","y","z","w","u","v"].slice(0,i),h="."+m[i-1],g=m.map(e=>"int "+e),x=(0,o.getChannels)("sourceLocR",i-1).concat("inIdx.r"),y=(0,o.getChannels)("sourceLocG",i-1).concat("inIdx.g"),v=(0,o.getChannels)("sourceLocB",i-1).concat("inIdx.b"),b=(0,o.getChannels)("sourceLocA",i-1).concat("inIdx.a"),k="max"===r?"greaterThan":"lessThan",_=n?"":` inIdx = round(vec4(getBestIndicesAChannel(${x.join()}), getBestIndicesAChannel(${y.join()}), getBestIndicesAChannel(${v.join()}), getBestIndicesAChannel(${b.join()})));`,I=`vec4( getAChannel(${x.join()}), hasNextCol ? getAChannel(${y.join()}) : 0., hasNextRow ? getAChannel(${v.join()}) : 0., hasNextRow && hasNextCol ? getAChannel(${b.join()}) : 0.)`,j=n?"":` float getBestIndicesAChannel(${g.join()}) { return getChannel(getBestIndicesA(${m.join()}), vec2(${m.slice(-2).join()})); }`;this.userCode=` float getAChannel(${g.join()}) { return getChannel(getA(${m.join()}), vec2(${m.slice(-2).join()})); } ${j} void main() { ${d} coords = getOutputCoords(); bool hasNextCol = ${f[c-1]}< ${u[c-1]-1}; bool hasNextRow = ${f[c-2]} < ${u[c-2]-1}; ${s} ivec4 srcIdx = ivec4(sourceLocR${h}, sourceLocG${h}, sourceLocB${h}, sourceLocA${h}) * ${t}; ivec4 inIdx = srcIdx; vec4 bestIndex = vec4(inIdx); vec4 bestValue = ${I}; for (int i = 0; i < ${t}; i++) { inIdx = srcIdx; ${_} vec4 candidate = ${I}; bvec4 nan = isnan(candidate); bvec4 replace = bvec4( vec4(${k}(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); } `}}},{"@tensorflow/tfjs-core":"2Gtps","./packing_util":"esmZC","./shader_compiler":"gZjZZ","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],"25IeA":[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"argMin",()=>i),s.export(r,"argMinConfig",()=>p);var a=e("@tensorflow/tfjs-core"),o=e("../kernel_utils/arg_min_max"),l=e("./Transpose");function i(e){let{inputs:t,backend:r,attrs:n}=e,{x:s}=t,{axis:i}=n,p=a.util.parseAxisParam(i,s.shape),u=a.backend_util.getAxesPermutation(p,s.shape.length),c=s,d=[];null!=u&&(d.push(c=(0,l.transpose)({inputs:{x:s},backend:r,attrs:{perm:u}})),p=a.backend_util.getInnerMostAxes(p.length,c.shape.length)),a.backend_util.assertAxesAreInnerMostDims("argMin",[p[0]],c.shape.length);let f=(0,o.argMinMaxReduce)(r,c,p[0],"min");return d.forEach(e=>r.disposeIntermediateTensorInfo(e)),f}let p={kernelName:a.ArgMin,backendName:"webgl",kernelFunc:i}},{"@tensorflow/tfjs-core":"2Gtps","../kernel_utils/arg_min_max":"7vOin","./Transpose":"lqCy7","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],gFt6t:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"asin",()=>i),s.export(r,"asinConfig",()=>p);var a=e("@tensorflow/tfjs-core"),o=e("../kernel_utils/kernel_funcs_utils");let l=e("../unaryop_gpu").CHECK_NAN_SNIPPET+` if (abs(x) > 1.) { return NAN; } return asin(x); `,i=(0,o.unaryKernelFunc)({opSnippet:l}),p={kernelName:a.Asin,backendName:"webgl",kernelFunc:i}},{"@tensorflow/tfjs-core":"2Gtps","../kernel_utils/kernel_funcs_utils":"5oexO","../unaryop_gpu":"byMKQ","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],"9i4m0":[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"asinh",()=>i),s.export(r,"asinhConfig",()=>p);var a=e("@tensorflow/tfjs-core"),o=e("../kernel_utils/kernel_funcs_utils");let l=e("../unaryop_gpu").CHECK_NAN_SNIPPET+"return log(x + sqrt(x * x + 1.0));",i=(0,o.unaryKernelFunc)({opSnippet:l}),p={kernelName:a.Asinh,backendName:"webgl",kernelFunc:i}},{"@tensorflow/tfjs-core":"2Gtps","../kernel_utils/kernel_funcs_utils":"5oexO","../unaryop_gpu":"byMKQ","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],lwVdA:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"atan",()=>i),s.export(r,"atanConfig",()=>p);var a=e("@tensorflow/tfjs-core"),o=e("../kernel_utils/kernel_funcs_utils");let l=e("../unaryop_gpu").CHECK_NAN_SNIPPET+` return atan(x); `,i=(0,o.unaryKernelFunc)({opSnippet:l}),p={kernelName:a.Atan,backendName:"webgl",kernelFunc:i}},{"@tensorflow/tfjs-core":"2Gtps","../kernel_utils/kernel_funcs_utils":"5oexO","../unaryop_gpu":"byMKQ","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],jZL8H:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"atan2",()=>c),s.export(r,"atan2Config",()=>d);var a=e("@tensorflow/tfjs-core"),o=e("../binaryop_gpu"),l=e("../binaryop_packed_gpu"),i=e("../kernel_utils/kernel_funcs_utils");let p=o.CHECK_NAN_SNIPPET+` return atan(a, b); `,u=` vec4 result = atan(a, b); bvec4 isNaNA = isnan(a); bvec4 isNaNB = isnan(b); bvec4 isNaN = bvec4(isNaNA.x || isNaNB.x, isNaNA.y || isNaNB.y, isNaNA.z || isNaNB.z, isNaNA.w || isNaNB.w); `+l.CHECK_NAN_SNIPPET_PACKED+` return result; `,c=(0,i.binaryKernelFunc)({opSnippet:p,packedOpSnippet:u}),d={kernelName:a.Atan2,backendName:"webgl",kernelFunc:c}},{"@tensorflow/tfjs-core":"2Gtps","../binaryop_gpu":"mK7ON","../binaryop_packed_gpu":"hyPKl","../kernel_utils/kernel_funcs_utils":"5oexO","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],l31E2:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"atanh",()=>i),s.export(r,"atanhConfig",()=>p);var a=e("@tensorflow/tfjs-core"),o=e("../kernel_utils/kernel_funcs_utils");let l=e("../unaryop_gpu").CHECK_NAN_SNIPPET+` if ((x< -1.0) || (x >1.0)) return NAN; return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,i=(0,o.unaryKernelFunc)({opSnippet:l}),p={kernelName:a.Atanh,backendName:"webgl",kernelFunc:i}},{"@tensorflow/tfjs-core":"2Gtps","../kernel_utils/kernel_funcs_utils":"5oexO","../unaryop_gpu":"byMKQ","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],"9LL2q":[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"avgPool",()=>p),s.export(r,"avgPoolConfig",()=>u);var a=e("@tensorflow/tfjs-core"),o=e("../pool_gpu"),l=e("../webgl_util"),i=e("./Identity");function p(e){let{inputs:t,backend:r,attrs:n}=e,{x:s}=t;(0,l.assertNotComplex)(s,"avgPool");let{filterSize:p,strides:u,pad:c,dimRoundingMode:d}=n;a.util.assert(a.backend_util.eitherStridesOrDilationsAreOne(u,1),()=>`Error in avgPool: Either strides or dilations must be 1. Got strides ${u} and dilations '1'`);let f=a.backend_util.computePool2DInfo(s.shape,p,u,1,c,d);if(1===f.filterWidth&&1===f.filterHeight&&a.util.arraysEqual(f.inShape,f.outShape))return(0,i.identity)({inputs:{x:s},backend:r});let m=new(0,o.Pool2DProgram)(f,"avg",!1);return r.runWebGLProgram(m,[s],"float32")}let u={kernelName:a.AvgPool,backendName:"webgl",kernelFunc:p}},{"@tensorflow/tfjs-core":"2Gtps","../pool_gpu":"1JUNb","../webgl_util":"kBGlX","./Identity":"97wVJ","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],"1JUNb":[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"Pool2DProgram",()=>a),s.export(r,"Pool3DProgram",()=>o);class a{constructor(e,t,r,n=!1,s=!1){if(this.variableNames=["x"],"avg"===t&&r)throw Error("Cannot compute positions for average pool.");const a=e.filterWidth,o=e.strideHeight,l=e.strideWidth,i=e.dilationHeight,p=e.dilationWidth,u=e.effectiveFilterHeight,c=e.effectiveFilterWidth,d=e.padInfo.top,f=e.padInfo.left;this.outputShape=e.outShape;const m="avg"===t,h=`((batch * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + d`,g=`(xR * ${e.inWidth} + xC) * ${e.inChannels} + d`;let x="0.0";if(m||(x="-1.0 / 1e-20"),r){this.userCode=` const ivec2 strides = ivec2(${o}, ${l}); const ivec2 pads = ivec2(${d}, ${f}); 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< ${u}; wR += ${i}) { int xR = xRCorner + wR; if (xR < 0 || xR >= ${e.inHeight}) { continue; } for (int wC = 0; wC< ${c}; wC += ${p}) { int xC = xCCorner + wC; if (xC < 0 || xC >= ${e.inWidth}) { continue; } float value = getX(batch, xR, xC, d); // If a min / max value has already been found, use it. If not, // use the current value. float currMinMaxValue = mix( value, minMaxValue, minMaxValueFound); if (value >= currMinMaxValue) { minMaxValue = value; minMaxValueFound = 1.0; minMaxPosition = ${n?s?h:g:`wR * ${c} + wC`}; } } } setOutput(float(minMaxPosition)); } `;return}let y=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;"avg"===t&&(y="avgValue / max(count, 1.0)");const v=4*Math.floor(a/4),b=a%4,k=` if (${m}) { avgValue += dot(values, ones); } else { minMaxValue = max(values, minMaxValue); } `;this.userCode=` const ivec2 strides = ivec2(${o}, ${l}); const ivec2 pads = ivec2(${d}, ${f}); const float initializationValue = ${x}; const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0); float count = 0.0; float getValue(int batch, int xR, int xC, int d) { if (xC< 0 || xC >= ${e.inWidth}) { return initializationValue; } count += 1.0; return getX(batch, xR, xC, d); } void main() { ivec4 coords = getOutputCoords(); int batch = coords[0]; int d = coords[3]; ivec2 xRCCorner = coords.yz * strides - pads; int xRCorner = xRCCorner.x; int xCCorner = xRCCorner.y; // max/min x(?, ?, d) to get y(yR, yC, d). // ? = to be determined vec4 minMaxValue = vec4(${x}); float avgValue = 0.0; count = 0.0; for (int wR = 0; wR< ${u}; wR += ${i}) { int xR = xRCorner + wR; if (xR < 0 || xR >= ${e.inHeight}) { continue; } for (int wC = 0; wC< ${v}; wC += 4) { int xC = xCCorner + wC * ${p}; vec4 values = vec4( getValue(batch, xR, xC, d), getValue(batch, xR, xC + ${p}, d), getValue(batch, xR, xC + 2 * ${p}, d), getValue(batch, xR, xC + 3 * ${p}, d) ); ${k} } int xC = xCCorner + ${v}; if (${1===b}) { vec4 values = vec4( getValue(batch, xR, xC, d), initializationValue, initializationValue, initializationValue ); ${k} } else if (${2===b}) { vec4 values = vec4( getValue(batch, xR, xC, d), getValue(batch, xR, xC + ${p}, d), initializationValue, initializationValue ); ${k} } else if (${3===b}) { vec4 values = vec4( getValue(batch, xR, xC, d), getValue(batch, xR, xC + ${p}, d), getValue(batch, xR, xC + 2 * ${p}, d), initializationValue ); ${k} } } setOutput(${y}); } `}}class o{constructor(e,t,r,n=!1,s=!1){if(this.variableNames=["x"],"avg"===t&&r)throw Error("Cannot compute positions for average pool.");const a=e.filterWidth,o=e.strideDepth,l=e.strideHeight,i=e.strideWidth,p=e.dilationDepth,u=e.dilationHeight,c=e.dilationWidth,d=e.effectiveFilterDepth,f=e.effectiveFilterHeight,m=e.effectiveFilterWidth,h=e.padInfo.front,g=e.padInfo.top,x=e.padInfo.left;this.outputShape=e.outShape;const y="avg"===t;let v="0.0";if(y||(v="-1.0 / 1e-20"),r){this.userCode=` const ivec3 strides = ivec3(${o}, ${l}, ${i}); const ivec3 pads = ivec3(${h}, ${g}, ${x}); 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 < ${d}; wD += ${p}) { int xD = xDCorner + wD; if (xD < 0 || xD >= ${e.inDepth}) { continue; } for (int wR = 0; wR< ${f}; wR += ${u}) { int xR = xRCorner + wR; if (xR < 0 || xR >= ${e.inHeight}) { continue; } for (int wC = 0; wC< ${m}; wC += ${c}) { int xC = xCCorner + wC; if (xC < 0 || xC >= ${e.inWidth}) { continue; } float value = getX(batch, xD, xR, xC, ch); // If a min / max value has already been found, use it. If not, // use the current value. float currMinMaxValue = mix( value, minMaxValue, minMaxValueFound); if (value >= currMinMaxValue) { minMaxValue = value; minMaxValueFound = 1.0; minMaxPosition = ${n?s?`(((batch * ${e.inDepth} + xD) * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + ch`:`((xD * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + ch`:`wD * ${f} * ${m} + wR * ${m} + wC`}; } } } } setOutput(float(minMaxPosition)); } `;return}let b=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;"avg"===t&&(b="avgValue / max(count, 1.0)");const k=4*Math.floor(a/4),_=a%4,I=` if (${y}) { avgValue += dot(values, ones); } else { minMaxValue = max(values, minMaxValue); } `;this.userCode=` const ivec3 strides = ivec3(${o}, ${l}, ${i}); const ivec3 pads = ivec3(${h}, ${g}, ${x}); const float initializationValue = ${v}; const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0); float count = 0.0; float getValue(int batch, int xD, int xR, int xC, int ch) { if (xC< 0 || xC >= ${e.inWidth}) { return initializationValue; } count += 1.0; return getX(batch, xD, xR, xC, ch); } void main() { ivec5 coords = getOutputCoords(); int batch = coords.x; int ch = coords.u; ivec3 xCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads; int xDCorner = xCorner.x; int xRCorner = xCorner.y; int xCCorner = xCorner.z; // max/min x(?, ?, ?, d) to get y(yD, yR, yC, ch). // ? = to be determined vec4 minMaxValue = vec4(${v}); float avgValue = 0.0; count = 0.0; for (int wD = 0; wD< ${d}; wD += ${p}) { int xD = xDCorner + wD; if (xD < 0 || xD >= ${e.inDepth}) { continue; } for (int wR = 0; wR< ${f}; wR += ${u}) { int xR = xRCorner + wR; if (xR < 0 || xR >= ${e.inHeight}) { continue; } for (int wC = 0; wC< ${k}; wC += 4) { int xC = xCCorner + wC * ${c}; vec4 values = vec4( getValue(batch, xD, xR, xC, ch), getValue(batch, xD, xR, xC + ${c}, ch), getValue(batch, xD, xR, xC + 2 * ${c}, ch), getValue(batch, xD, xR, xC + 3 * ${c}, ch) ); ${I} } int xC = xCCorner + ${k}; if (${1===_}) { vec4 values = vec4( getValue(batch, xD, xR, xC, ch), initializationValue, initializationValue, initializationValue ); ${I} } else if (${2===_}) { vec4 values = vec4( getValue(batch, xD, xR, xC, ch), getValue(batch, xD, xR, xC + ${c}, ch), initializationValue, initializationValue ); ${I} } else if (${3===_}) { vec4 values = vec4( getValue(batch, xD, xR, xC, ch), getValue(batch, xD, xR, xC + ${c}, ch), getValue(batch, xD, xR, xC + 2 * ${c}, ch), initializationValue ); ${I} } } } setOutput(${b}); } `}}},{"@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],"6DbtT":[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"avgPool3D",()=>l),s.export(r,"avgPool3DConfig",()=>i);var a=e("@tensorflow/tfjs-core"),o=e("../pool_gpu");function l(e){let{inputs:t,backend:r,attrs:n}=e,{x:s}=t,{filterSize:l,strides:i,pad:p,dimRoundingMode:u,dataFormat:c}=n,d=a.backend_util.computePool3DInfo(s.shape,l,i,[1,1,1],p,u,c),f=new(0,o.Pool3DProgram)(d,"avg",!1);return r.runWebGLProgram(f,[s],"float32")}let i={kernelName:a.AvgPool3D,backendName:"webgl",kernelFunc:l}},{"@tensorflow/tfjs-core":"2Gtps","../pool_gpu":"1JUNb","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],"8K7Pz":[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"avgPool3DGrad",()=>l),s.export(r,"avgPool3DGradConfig",()=>i);var a=e("@tensorflow/tfjs-core"),o=e("../avg_pool_backprop_gpu");function l(e){let{inputs:t,backend:r,attrs:n}=e,{dy:s,input:l}=t,{filterSize:i,strides:p,pad:u,dimRoundingMode:c}=n,d=a.backend_util.computePool3DInfo(l.shape,i,p,[1,1,1],u,c),f=new(0,o.AvgPool3DBackpropProgram)(d);return r.runWebGLProgram(f,[s],l.dtype)}let i={kernelName:a.AvgPool3DGrad,backendName:"webgl",kernelFunc:l}},{"@tensorflow/tfjs-core":"2Gtps","../avg_pool_backprop_gpu":"6tXZr","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],"6tXZr":[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"AvgPool2DBackpropProgram",()=>a),s.export(r,"AvgPool3DBackpropProgram",()=>o);class a{constructor(e){this.variableNames=["dy"],this.outputShape=e.inShape;const t=e.filterHeight,r=e.filterWidth,n=e.strideHeight,s=e.strideWidth,a=e.dilationHeight,o=e.dilationWidth,l=e.effectiveFilterHeight,i=e.effectiveFilterWidth,p=l-1-e.padInfo.top,u=i-1-e.padInfo.left;this.userCode=` const ivec2 pads = ivec2(${p}, ${u}); const float avgMultiplier = float(${1/(t*r)}); 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< ${l}; wR += ${a}) { float dyR = float(dyRCorner + wR) / ${n}.0; if (dyR < 0.0 || dyR >= ${e.outHeight}.0 || fract(dyR) > 0.0) { continue; } int idyR = int(dyR); for (int wC = 0; wC< ${i}; wC+= ${o}) { float dyC = float(dyCCorner + wC) / ${s}.0; if (dyC < 0.0 || dyC >= ${e.outWidth}.0 || fract(dyC) > 0.0) { continue; } int idyC = int(dyC); float dyValue = getDy(b, idyR, idyC, d); dotProd += dyValue * avgMultiplier; } } setOutput(dotProd); } `}}class o{constructor(e){this.variableNames=["dy"],this.outputShape=e.inShape;const t=e.filterDepth,r=e.filterHeight,n=e.filterWidth,s=e.strideDepth,a=e.strideHeight,o=e.strideWidth,l=e.dilationDepth,i=e.dilationHeight,p=e.dilationWidth,u=e.effectiveFilterDepth,c=e.effectiveFilterHeight,d=e.effectiveFilterWidth,f=u-1-e.padInfo.front,m=c-1-e.padInfo.top,h=d-1-e.padInfo.left;this.userCode=` const ivec3 pads = ivec3(${f}, ${m}, ${h}); const float avgMultiplier = float(${1/(t*r*n)}); 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< ${u}; wD += ${l}) { float dyD = float(dyDCorner + wD) / ${s}.0; if (dyD < 0.0 || dyD >= ${e.outDepth}.0 || fract(dyD) > 0.0) { continue; } int idyD = int(dyD); for (int wR = 0; wR< ${c}; wR += ${i}) { float dyR = float(dyRCorner + wR) / ${a}.0; if (dyR < 0.0 || dyR >= ${e.outHeight}.0 || fract(dyR) > 0.0) { continue; } int idyR = int(dyR); for (int wC = 0; wC< ${d}; wC += ${p}) { float dyC = float(dyCCorner + wC) / ${o}.0; if (dyC < 0.0 || dyC >= ${e.outWidth}.0 || fract(dyC) > 0.0) { continue; } int idyC = int(dyC); float dyValue = getDy(batch, idyD, idyR, idyC, ch); dotProd += dyValue * avgMultiplier; } } } setOutput(dotProd); } `}}},{"@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],"7Cxxo":[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"avgPoolGrad",()=>i),s.export(r,"avgPoolGradConfig",()=>p);var a=e("@tensorflow/tfjs-core"),o=e("../avg_pool_backprop_gpu"),l=e("../webgl_util");function i(e){let{inputs:t,backend:r,attrs:n}=e,{dy:s,input:i}=t;(0,l.assertNotComplex)([s,i],"avgPoolGrad");let{filterSize:p,strides:u,pad:c}=n,d=a.backend_util.computePool2DInfo(i.shape,p,u,1,c),f=new(0,o.AvgPool2DBackpropProgram)(d);return r.runWebGLProgram(f,[s],i.dtype)}let p={kernelName:a.AvgPoolGrad,backendName:"webgl",kernelFunc:i}},{"@tensorflow/tfjs-core":"2Gtps","../avg_pool_backprop_gpu":"6tXZr","../webgl_util":"kBGlX","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],bj0b9:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"batchMatMul",()=>l),s.export(r,"batchMatMulConfig",()=>i);var a=e("@tensorflow/tfjs-core"),o=e("./BatchMatMul_impl");function l(e){let{inputs:t,backend:r,attrs:n}=e,{a:s,b:a}=t,{transposeA:l,transposeB:i}=n;return(0,o.batchMatMulImpl)({a:s,b:a,transposeA:l,transposeB:i,backend:r})}let i={kernelName:a.BatchMatMul,backendName:"webgl",kernelFunc:l}},{"@tensorflow/tfjs-core":"2Gtps","./BatchMatMul_impl":"aJhdh","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],cHAjg:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"batchNorm",()=>i),s.export(r,"batchNormConfig",()=>p);var a=e("@tensorflow/tfjs-core"),o=e("../batchnorm_gpu"),l=e("../batchnorm_packed_gpu");let i=({inputs:e,backend:t,attrs:r})=>{let{x:n,mean:s,variance:i,offset:p,scale:u}=e;a.util.assert(s.shape.length===i.shape.length,()=>"Batch normalization gradient requires mean and variance to have equal ranks."),a.util.assert(null==p||s.shape.length===p.shape.length,()=>"Batch normalization gradient requires mean and offset to have equal ranks."),a.util.assert(null==u||s.shape.length===u.shape.length,()=>"Batch normalization gradient requires mean and scale to have equal ranks.");let{varianceEpsilon:c}=r;null==c&&(c=.001);let d=[n,s,i],f=null;null!=p&&(f=p.shape,d.push(p));let m=null;null!=u&&(m=u.shape,d.push(u));let h=(0,a.env)().getBool("WEBGL_PACK_NORMALIZATION")?new(0,l.BatchNormPackedProgram)(n.shape,s.shape,i.shape,f,m,c):new(0,o.BatchNormProgram)(n.shape,s.shape,i.shape,f,m,c);return t.runWebGLProgram(h,d,d[0].dtype)},p={kernelName:a.FusedBatchNorm,backendName:"webgl",kernelFunc:i}},{"@tensorflow/tfjs-core":"2Gtps","../batchnorm_gpu":"9mMT7","../batchnorm_packed_gpu":"aPc6x","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],"9mMT7":[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"BatchNormProgram",()=>o);var a=e("@tensorflow/tfjs-core");class o{constructor(e,t,r,n,s,o){this.outputShape=[],this.variableNames=["x","mean","variance"],a.backend_util.assertAndGetBroadcastShape(e,t),a.backend_util.assertAndGetBroadcastShape(e,r);let l="0.0";null!=n&&(a.backend_util.assertAndGetBroadcastShape(e,n),this.variableNames.push("offset"),l="getOffsetAtOutCoords()");let i="1.0";null!=s&&(a.backend_util.assertAndGetBroadcastShape(e,s),this.variableNames.push("scale"),i="getScaleAtOutCoords()"),this.outputShape=e,this.userCode=` void main() { float x = getXAtOutCoords(); float mean = getMeanAtOutCoords(); float variance = getVarianceAtOutCoords(); float offset = ${l}; float scale = ${i}; float inv = scale * inversesqrt(variance + float(${o})); setOutput(dot(vec3(x, -mean, offset), vec3(inv, inv, 1))); } `}}},{"@tensorflow/tfjs-core":"2Gtps","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],aPc6x:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"BatchNormPackedProgram",()=>o);var a=e("@tensorflow/tfjs-core");class o{constructor(e,t,r,n,s,o){this.packedInputs=!0,this.packedOutput=!0,this.variableNames=["x","mean","variance"],a.backend_util.assertAndGetBroadcastShape(e,t),a.backend_util.assertAndGetBroadcastShape(e,r);let l="vec4(0.0)";null!=n&&(a.backend_util.assertAndGetBroadcastShape(e,n),this.variableNames.push("offset"),l="getOffsetAtOutCoords()");let i="vec4(1.0)";null!=s&&(a.backend_util.assertAndGetBroadcastShape(e,s),this.variableNames.push("scale"),i="getScaleAtOutCoords()"),this.outputShape=e,this.userCode=` void main() { vec4 offset = ${l}; vec4 scale = ${i}; vec4 x = getXAtOutCoords(); vec4 mean = getMeanAtOutCoords(); vec4 variance = getVarianceAtOutCoords(); vec4 inv = scale * inversesqrt(variance + vec4(${o})); setOutput((x - mean) * inv + offset); } `}}},{"@tensorflow/tfjs-core":"2Gtps","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],l4Nfx:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"batchToSpaceND",()=>p),s.export(r,"batchToSpaceNDConfig",()=>u);var a=e("@tensorflow/tfjs-core"),o=e("./Reshape"),l=e("./Slice"),i=e("./Transpose");let p=e=>{let{inputs:t,backend:r,attrs:n}=e,{x:s}=t,{blockShape:p,crops:u}=n;a.util.assert(s.shape.length<=4,()=>"batchToSpaceND for rank > 4 with a WebGL backend not implemented yet");let c=p.reduce((e,t)=>e*t),d=a.backend_util.getReshaped(s.shape,p,c),f=a.backend_util.getPermuted(d.length,p.length),m=a.backend_util.getReshapedPermuted(s.shape,p,c),h=a.backend_util.getSliceBeginCoords(u,p.length),g=a.backend_util.getSliceSize(m,u,p.length),x=[],y=(0,o.reshape)({inputs:{x:s},backend:r,attrs:{shape:d}}),v=(0,i.transpose)({inputs:{x:y},backend:r,attrs:{perm:f}}),b=(0,o.reshape)({inputs:{x:v},backend:r,attrs:{shape:m}}),k=(0,l.slice)({inputs:{x:b},backend:r,attrs:{begin:h,size:g}});return x.push(y),x.push(v),x.push(b),x.forEach(e=>r.disposeIntermediateTensorInfo(e)),k},u={kernelName:a.BatchToSpaceND,backendName:"webgl",kernelFunc:p}},{"@tensorflow/tfjs-core":"2Gtps","./Reshape":"aOEE6","./Slice":"io5JZ","./Transpose":"lqCy7","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],io5JZ:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"slice",()=>p),s.export(r,"sliceConfig",()=>u);var a=e("@tensorflow/tfjs-core"),o=e("../kernel_utils/shared"),l=e("../slice_gpu"),i=e("../slice_packed_gpu");function p(e){let t,r,n,s,p,{inputs:u,backend:c,attrs:d}=e,{x:f}=u,{begin:m,size:h}=d,[g,x]=a.slice_util.parseSliceParams(f,m,h);if(a.slice_util.assertParamsValid(f,g,x),0===a.util.sizeFromShape(x))return c.makeTensorInfo(x,f.dtype,[]);if(c.shouldExecuteOnCPU([f])||"string"===f.dtype){let e=c.texData.get(f.dataId),t=(0,o.sliceImplCPU)(e.values,g,x,f.shape,f.dtype);return c.makeTensorInfo(x,f.dtype,t)}let{isPacked:y}=c.texData.get(f.dataId),v=a.slice_util.isSliceContinous(f.shape,g,x);if(y||!v){let e=(0,a.env)().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new(0,i.SlicePackedProgram)(x):new(0,l.SliceProgram)(x),t=[g];return c.runWebGLProgram(e,[f],f.dtype,t)}return c.uploadToGPU(f.dataId),t=c.texData.get(f.dataId),r=c.makeTensorInfo(x,f.dtype),Object.assign(n=c.texData.get(r.dataId),t),n.refCount=1,n.shape=x,n.dtype=f.dtype,s=a.slice_util.computeFlatOffset(g,a.util.computeStrides(f.shape)),t.slice&&(s+=t.slice.flatOffset),n.slice={flatOffset:s,origDataId:t.slice&&t.slice.origDataId||f.dataId},p=c.dataRefCount.get(n.slice.origDataId)||1,c.dataRefCount.set(n.slice.origDataId,p+1),r}let u={kernelName:a.Slice,backendName:"webgl",kernelFunc:p}},{"@tensorflow/tfjs-core":"2Gtps","../kernel_utils/shared":"6ruDg","../slice_gpu":"dToAv","../slice_packed_gpu":"gVf8Y","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],dToAv:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"SliceProgram",()=>o);var a=e("./shader_compiler");class o{constructor(e){let t;this.variableNames=["source"],this.outputShape=e,this.rank=e.length;const r=(0,a.getCoordsDataType)(this.rank);this.customUniforms=[{name:"start",arrayIndex:this.rank,type:"int"}];const n=function(e){if(1===e)return"sourceLoc";if(e<=6)return l.slice(0,e).map(e=>"sourceLoc."+e).join(",");throw Error(`Slicing for rank ${e} is not yet supported`)}(this.rank),s=e.map((e,t)=>`sourceLoc.${l[t]} = start[${t}] + coords.${l[t]};`);t=` ${r} sourceLoc; ${r} coords = getOutputCoords(); ${s.join("\n")} `,this.userCode=` void main() { ${t} setOutput(getSource(${n})); } `}}let l=["x","y","z","w","u","v"]},{"./shader_compiler":"gZjZZ","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],gVf8Y:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"SlicePackedProgram",()=>l);var a=e("./packing_util"),o=e("./shader_compiler");class 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i={kernelName:a.Real,backendName:"webgl",kernelFunc:l}},{"@tensorflow/tfjs-core":"2Gtps","./Identity":"97wVJ","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],kR5Ci:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"int",()=>o);var a=e("../unaryop_gpu");function o(e,t){let r=new(0,a.UnaryOpProgram)(e.shape,"return float(int(x));"),n=t.runWebGLProgram(r,[e],"int32");return{dataId:n.dataId,shape:n.shape,dtype:n.dtype}}},{"../unaryop_gpu":"byMKQ","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],"4LFu4":[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"ceil",()=>p),s.export(r,"ceilConfig",()=>u);var a=e("@tensorflow/tfjs-core"),o=e("../kernel_utils/kernel_funcs_utils"),l=e("../kernel_utils/shared");let i="return 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p={kernelName:a.ClipByValue,backendName:"webgl",kernelFunc:i}},{"@tensorflow/tfjs-core":"2Gtps","../clip_gpu":"bxmyW","../clip_packed_gpu":"alj4p","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],bxmyW:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"ClipProgram",()=>a);class a{constructor(e){this.variableNames=["A"],this.customUniforms=[{name:"minVal",type:"float"},{name:"maxVal",type:"float"}],this.outputShape=e,this.userCode=` void main() { float value = getAAtOutCoords(); if (isnan(value)) { setOutput(value); return; } setOutput(clamp(value, minVal, maxVal)); } `}}},{"@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],alj4p:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"ClipPackedProgram",()=>a);class a{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"minVal",type:"float"},{name:"maxVal",type:"float"}],this.outputShape=e,this.userCode=` void main() { vec4 value = getAAtOutCoords(); if (any(isnan(value))) { setOutput(value); return; } setOutput(clamp(value, vec4(minVal), vec4(maxVal))); } `}}},{"@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],dlNrQ:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"complexAbs",()=>i),s.export(r,"complexAbsConfig",()=>p);var a=e("@tensorflow/tfjs-core"),o=e("../complex_abs_gpu");function l(e,t){return{dataId:t.dataId,dtype:t.dtype,shape:e.shape}}function i(e){let{inputs:t,backend:r}=e,{x:n}=t,s=r.texData.get(n.dataId),a=new(0,o.ComplexAbsProgram)(n.shape),i=[l(n,s.complexTensorInfos.real),l(n,s.complexTensorInfos.imag)];return r.runWebGLProgram(a,i,i[0].dtype)}let p={kernelName:a.ComplexAbs,backendName:"webgl",kernelFunc:i}},{"@tensorflow/tfjs-core":"2Gtps","../complex_abs_gpu":"bmI9C","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],bmI9C:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"ComplexAbsProgram",()=>a);class a{constructor(e){this.variableNames=["real","imag"],this.outputShape=e,this.userCode=` void main() { float re = abs(getRealAtOutCoords()); float im = abs(getImagAtOutCoords()); float mx = max(re, im); // sadly the length function in glsl is not underflow-safe // (at least not on Intel GPUs). 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e=1;e<t.length;e++){const n=t[e-1];r.push(`else if (yC < ${t[e]}) setOutput(getT${e}(yR, yC-${n}));`)}const n=t.length,s=t[t.length-1];r.push(`else setOutput(getT${n}(yR, yC-${s}));`),this.userCode=` void main() { ivec2 coords = getOutputCoords(); int yR = coords.x; int yC = coords.y; ${r.join("\n ")} } `}}},{"@tensorflow/tfjs-core":"2Gtps","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],ih26f:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"ConcatPackedProgram",()=>i);var a=e("@tensorflow/tfjs-core"),o=e("./packing_util"),l=e("./shader_compiler");class i{constructor(e,t){this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[],this.outputShape=a.backend_util.computeOutShape(e,t);const r=this.outputShape,n=r.length,s=(0,l.getCoordsDataType)(n),i=(0,o.getChannels)("coords",n),u=["x","y","z","w","u","v"].slice(0,n);this.variableNames=e.map((e,t)=>`T${t}`);const c=Array(e.length-1);c[0]=e[0][t];for(let r=1;r<c.length;r++)c[r]=c[r-1]+e[r][t];const d=u[t],f=u.slice(-2),m=u.join();let h=`if (${d} < ${c[0]}) { return getChannel( getT0(${m}), vec2(${f.join()})); }`;for(let e=1;e<c.length;e++){const t=c[e-1];h+=` if (${d} < ${c[e]} && ${d} >= ${c[e-1]}) { return getChannel( getT${e}(${p(u,d,t)}), vec2(${p(f,d,t)})); }`}const g=c.length,x=c[c.length-1];h+=` return getChannel( getT${g}(${p(u,d,x)}), vec2(${p(f,d,x)}));`,this.userCode=` float getValue(${u.map(e=>"int "+e)}) { ${h} } void main() { ${s} coords = getOutputCoords(); vec4 result = vec4(getValue(${i}), 0., 0., 0.); ${i[n-1]} = ${i[n-1]} + 1; if (${i[n-1]}< ${r[n-1]}) { result.g = getValue(${i}); } ${i[n-2]} = ${i[n-2]} + 1; if (${i[n-2]} < ${r[n-2]}) { result.a = getValue(${i}); } ${i[n-1]} = ${i[n-1]} - 1; if (${i[n-2]} < ${r[n-2]} && ${i[n-1]} < ${r[n-1]}) { result.b = getValue(${i}); } setOutput(result); } `}}function p(e,t,r){let n=e.indexOf(t);return e.map((e,t)=>t===n?`${e} - ${r}`:e).join()}},{"@tensorflow/tfjs-core":"2Gtps","./packing_util":"esmZC","./shader_compiler":"gZjZZ","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],"3QJSY":[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"imag",()=>l),s.export(r,"imagConfig",()=>i);var a=e("@tensorflow/tfjs-core"),o=e("./Identity");function l(e){let{inputs:t,backend:r}=e,{input:n}=t,s=r.texData.get(n.dataId);return(0,o.identity)({inputs:{x:s.complexTensorInfos.imag},backend:r})}let i={kernelName:a.Imag,backendName:"webgl",kernelFunc:l}},{"@tensorflow/tfjs-core":"2Gtps","./Identity":"97wVJ","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],iKaWV:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"conv2d",()=>u),s.export(r,"conv2DConfig",()=>c);var a=e("@tensorflow/tfjs-core"),o=e("../conv_gpu"),l=e("../conv_packed_gpu"),i=e("./Conv2D_impl"),p=e("./Reshape");function u(e){let t,{inputs:r,backend:n,attrs:s}=e,{x:u,filter:c}=r,{strides:d,pad:f,dataFormat:m,dilations:h,dimRoundingMode:g}=s,x=a.backend_util.convertConv2DDataFormat(m),y=a.backend_util.computeConv2DInfo(u.shape,c.shape,d,h,f,g,!1,x);if(1===y.filterHeight&&1===y.filterWidth&&1===y.dilationHeight&&1===y.dilationWidth&&1===y.strideHeight&&1===y.strideWidth&&("SAME"===y.padInfo.type||"VALID"===y.padInfo.type))t=(0,i.conv2dByMatMul)({x:u,filter:c,convInfo:y,backend:n});else if(y.strideWidth<=2&&"channelsLast"===x&&(0,a.env)().getBool("WEBGL_EXP_CONV")){let e=new(0,l.Conv2DPackedProgram)(y),r=[[y.padInfo.top,y.padInfo.left],[y.strideHeight,y.strideWidth],[y.dilationHeight,y.dilationWidth],[y.inHeight,y.inWidth]];t=n.runWebGLProgram(e,[u,c],"float32",r)}else if((0,a.env)().getBool("WEBGL_CONV_IM2COL"))t=(0,i.conv2dWithIm2Row)({x:u,filter:c,convInfo:y,backend:n});else{let e=new(0,o.Conv2DProgram)(y);t=n.runWebGLProgram(e,[u,c],"float32")}let v=(0,p.reshape)({inputs:{x:t},backend:n,attrs:{shape:y.outShape}});return n.disposeIntermediateTensorInfo(t),v}let c={kernelName:a.Conv2D,backendName:"webgl",kernelFunc:u}},{"@tensorflow/tfjs-core":"2Gtps","../conv_gpu":"9rKCB","../conv_packed_gpu":"kQJUn","./Conv2D_impl":"bLHqw","./Reshape":"aOEE6","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],"9rKCB":[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"Conv2DProgram",()=>a),s.export(r,"Conv3DProgram",()=>o);class a{constructor(e,t=!1,r=null,n=!1,s=!1){this.variableNames=["x","W"],this.outputShape=e.outShape;const a=e.padInfo.top,o=e.padInfo.left,l=e.strideHeight,i=e.strideWidth,p=e.dilationHeight,u=e.dilationWidth,c=e.filterHeight,d=e.filterWidth,f=4*Math.floor(e.inChannels/4),m=e.inChannels%4,h="channelsLast"===e.dataFormat;let g="",x="";r&&(g=n?`float activation(float a) { float b = getPreluActivationWeightsAtOutCoords(); ${r} }`:s?`float activation(float a) { float b = getLeakyreluAlphaAtOutCoords(); ${r} }`:` float activation(float x) { ${r} } `,x="result = activation(result);"),t&&this.variableNames.push("bias"),n&&this.variableNames.push("preluActivationWeights"),s&&this.variableNames.push("leakyreluAlpha"),this.userCode=` ${g} const ivec2 strides = ivec2(${l}, ${i}); const ivec2 pads = ivec2(${a}, ${o}); void main() { ivec4 coords = getOutputCoords(); int batch = coords[0]; int d2 = coords[${h?3:1}]; ivec2 xRCCorner = ivec2(coords[${h?1:2}], coords[${h?2:3}]) * 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< ${c}; wR++) { int xR = xRCorner + wR * ${p}; if (xR < 0 || xR >= ${e.inHeight}) { continue; } for (int wC = 0; wC< ${d}; wC++) { int xC = xCCorner + wC * ${u}; if (xC < 0 || xC >= ${e.inWidth}) { continue; } for (int d1 = 0; d1< ${f}; d1 += 4) { vec4 wValues = vec4( getW(wR, wC, d1, d2), getW(wR, wC, d1 + 1, d2), getW(wR, wC, d1 + 2, d2), getW(wR, wC, d1 + 3, d2) ); if (${h}) { 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 (${1===m}) { if (${h}) { dotProd += getX(batch, xR, xC, ${f}) * getW(wR, wC, ${f}, d2); } else { dotProd += getX(batch, ${f}, xR, xC) * getW(wR, wC, ${f}, d2); } } else if (${2===m}) { vec2 wValues = vec2( getW(wR, wC, ${f}, d2), getW(wR, wC, ${f} + 1, d2) ); if (${h}) { vec2 xValues = vec2( getX(batch, xR, xC, ${f}), getX(batch, xR, xC, ${f} + 1) ); dotProd += dot(xValues, wValues); } else { vec2 xValues = vec2( getX(batch, ${f}, xR, xC), getX(batch, ${f} + 1, xR, xC) ); dotProd += dot(xValues, wValues); } } else if (${3===m}) { vec3 wValues = vec3( getW(wR, wC, ${f}, d2), getW(wR, wC, ${f} + 1, d2), getW(wR, wC, ${f} + 2, d2) ); if (${h}) { vec3 xValues = vec3( getX(batch, xR, xC, ${f}), getX(batch, xR, xC, ${f} + 1), getX(batch, xR, xC, ${f} + 2) ); dotProd += dot(xValues, wValues); } else { vec3 xValues = vec3( getX(batch, ${f}, xR, xC), getX(batch, ${f} + 1, xR, xC), getX(batch, ${f} + 2, xR, xC) ); dotProd += dot(xValues, wValues); } } } } float result = dotProd; ${t?"result += getBiasAtOutCoords();":""} ${x} setOutput(result); } `}}class o{constructor(e){this.variableNames=["x","W"],this.outputShape=e.outShape;const t=e.padInfo.front,r=e.padInfo.top,n=e.padInfo.left,s=e.strideDepth,a=e.strideHeight,o=e.strideWidth,l=e.dilationDepth,i=e.dilationHeight,p=e.dilationWidth,u=e.filterDepth,c=e.filterHeight,d=e.filterWidth,f=4*Math.floor(e.inChannels/4),m=e.inChannels%4;this.userCode=` const ivec3 strides = ivec3(${s}, ${a}, ${o}); const ivec3 pads = ivec3(${t}, ${r}, ${n}); 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 < ${u}; wF++) { int xF = xFCorner + wF * ${l}; if (xF < 0 || xF >= ${e.inDepth}) { continue; } for (int wR = 0; wR< ${c}; wR++) { int xR = xRCorner + wR * ${i}; if (xR < 0 || xR >= ${e.inHeight}) { continue; } for (int wC = 0; wC< ${d}; wC++) { int xC = xCCorner + wC * ${p}; if (xC < 0 || xC >= ${e.inWidth}) { continue; } for (int d1 = 0; d1< ${f}; d1 += 4) { vec4 xValues = vec4( getX(batch, xF, xR, xC, d1), getX(batch, xF, xR, xC, d1 + 1), getX(batch, xF, xR, xC, d1 + 2), getX(batch, xF, xR, xC, d1 + 3) ); vec4 wValues = vec4( getW(wF, wR, wC, d1, d2), getW(wF, wR, wC, d1 + 1, d2), getW(wF, wR, wC, d1 + 2, d2), getW(wF, wR, wC, d1 + 3, d2) ); dotProd += dot(xValues, wValues); } if (${1===m}) { dotProd += getX(batch, xF, xR, xC, ${f}) * getW(wF, wR, wC, ${f}, d2); } else if (${2===m}) { vec2 xValues = vec2( getX(batch, xF, xR, xC, ${f}), getX(batch, xF, xR, xC, ${f} + 1) ); vec2 wValues = vec2( getW(wF, wR, wC, ${f}, d2), getW(wF, wR, wC, ${f} + 1, d2) ); dotProd += dot(xValues, wValues); } else if (${3===m}) { vec3 xValues = vec3( getX(batch, xF, xR, xC, ${f}), getX(batch, xF, xR, xC, ${f} + 1), getX(batch, xF, xR, xC, ${f} + 2) ); vec3 wValues = vec3( getW(wF, wR, wC, ${f}, d2), getW(wF, wR, wC, ${f} + 1, d2), getW(wF, wR, wC, ${f} + 2, d2) ); dotProd += dot(xValues, wValues); } } } } setOutput(dotProd); } `}}},{"@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],kQJUn:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"Conv2DPackedProgram",()=>l);var a=e("@tensorflow/tfjs-core"),o=e("./gpgpu_math");class l{constructor(e,t=!1,r=null,n=!1,s=!1){this.variableNames=["x","W"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"pads",type:"ivec2"},{name:"strides",type:"ivec2"},{name:"dilations",type:"ivec2"},{name:"inDims",type:"ivec2"}],this.outputShape=e.outShape,this.enableShapeUniforms=(0,o.useShapeUniforms)(this.outputShape.length);const l=e.padInfo.left,i=e.strideWidth,p=e.dilationWidth,u=e.filterHeight,c=e.filterWidth;let d=` int xR; int xC; int xCOffset; vec4 wTexel; vec4 previous; vec4 final;`;for(let e=0;e<c;e++)d+=` vec4 xTexelC${2*e}; int xTexelC${2*e}Ready; vec4 xTexelC${2*e+1}; int xTexelC${2*e+1}Ready; vec4 xC${e};`;d+=` for (int r = 0; r < ${u}; r++) { for (int d1 = 0; d1 < ${e.inChannels}; d1 += 2) { `;for(let e=0;e<c;e++)d+=` xTexelC${2*e} = vec4(0.0); xTexelC${2*e}Ready = 0; xTexelC${2*e+1} = vec4(0.0); xTexelC${2*e+1}Ready = 0; xC${e} = vec4(0.0);`;d+=` xR = xRCorner + r * dilations[0]; if (xR >=0 && xR< inDims[0]) { `;for(let t=0;t<(c+1)/2;t++){const r=2*t;if(d+=` xC = xCCorner + ${r*p}; `,1===i){if(r<c&&(l%2==1?(d+=` xCOffset = xC + 1; if (xCOffset >= 0 && xCOffset< inDims[1] && xTexelC${r}Ready == 0) { xTexelC${r} = getX(batch, xR, xCOffset, d1); // Need to manually clear unused channels in case // we're reading from recycled texture. if (xCOffset + 1 >= inDims[1]) { xTexelC${r}.zw = vec2(0.0); } xTexelC${r}Ready = 1; } `,1===p&&r>0?d+=` xC${r} = vec4(xTexelC${r-2}.zw, xTexelC${r}.xy); `:d+=` xCOffset = xC + 1 - 2; if (xCOffset >= 0 && xCOffset< inDims[1]) { previous = getX(batch, xR, xCOffset, d1); // Need to manually clear unused channels in case // we're reading from recycled texture. if (xCOffset + 1 >= inDims[1]) { previous.zw = vec2(0.0); } xC${r} = vec4(previous.zw, xTexelC${r}.xy); } else { xC${r} = vec4(0.0, 0.0, xTexelC${r}.xy); } `):d+=` if (xC >= 0 && xC< inDims[1] && xTexelC${r}Ready == 0) { xTexelC${r} = getX(batch, xR, xC, d1); if (xC + 1 >= inDims[1]) { xTexelC${r}.zw = vec2(0.0); } xTexelC${r}Ready = 1; } xC${r} = xTexelC${r}; `,r+1<c)){const e=l%2==0?a.util.nearestLargerEven(p):p;p%2==0&&l%2==1||p%2!=0&&l%2!=1?(d+=` xCOffset = xC + imod(pads[1], 2) + ${e}; if (xCOffset >= 0 && xCOffset< inDims[1] && xTexelC${r+1}Ready == 0) { xTexelC${r+1} = getX(batch, xR, xCOffset, d1); // Need to manually clear unused channels in case // we're reading from recycled texture. if (xCOffset + 1 >= inDims[1]) { xTexelC${r+1}.zw = vec2(0.0); } xTexelC${r+1}Ready = 1; } `,p>1?d+=` xCOffset -= 2; if (xCOffset >= 0 && xCOffset< inDims[1]) { previous = getX(batch, xR, xCOffset, d1); xC${r+1} = vec4(previous.zw, xTexelC${r+1}.xy); } else { xC${r+1} = vec4(0.0, 0.0, xTexelC${r+1}.xy); } `:d+=` xC${r+1} = vec4(xTexelC${r}.zw, xTexelC${r+1}.xy); `):1===e?d+=` xC${r+1} = xTexelC${r}; `:d+=` xCOffset = xC + ${e}; if (xCOffset >= 0 && xCOffset< inDims[1] && xTexelC${r+1}Ready == 0) { xTexelC${r+1} = getX(batch, xR, xCOffset, d1); if (xCOffset + 1 >= inDims[1]) { xTexelC${r+1}.zw = vec2(0.0); } xTexelC${r+1}Ready = 1; } xC${r+1} = xTexelC${r+1}; `}}else r<c&&(l%2==1?(d+=` xCOffset = xC + 1 - strides[1]; if(xCOffset >= 0 && xCOffset< inDims[1] && xTexelC${r}Ready == 0) { xTexelC${r} = getX(batch, xR, xCOffset, d1); // Need to manually clear unused channels in case // we're reading from recycled texture. if (xCOffset + 1 >= inDims[1]) { xTexelC${r}.zw = vec2(0.0); } xTexelC${r}Ready = 1; } if(xC + 1 >= 0 && xC + 1< inDims[1] && xTexelC${r+1}Ready == 0) { xTexelC${r+1} = getX(batch, xR, xC + 1, d1); // Need to manually clear unused channels in case // we're reading from recycled texture. if (xC + 2 >= inDims[1]) { xTexelC${r+1}.zw = vec2(0.0); } xTexelC${r+1}Ready = 1; } xC${r} = vec4(xTexelC${r}.zw, xTexelC${r+1}.zw); `,r+1<c&&(d+=` final = vec4(0.0); xCOffset = xC + 1 + strides[1]; if(xCOffset >= 0 && xCOffset< inDims[1]) { final = getX(batch, xR, xCOffset, d1); } xC${r+1} = vec4(xTexelC${r+1}.xy, final.xy); `)):(d+=` if(xC >= 0 && xC< inDims[1] && xTexelC${r}Ready == 0) { xTexelC${r} = getX(batch, xR, xC, d1); if (xC + 1 >= inDims[1]) { xTexelC${r}.zw = vec2(0.0); } xTexelC${r}Ready = 1; } xCOffset = xC + strides[1]; if(xCOffset >= 0 && xCOffset< inDims[1] && xTexelC${r+1}Ready == 0) { xTexelC${r+1} = getX(batch, xR, xCOffset, d1); if (xCOffset + 1 >= inDims[1]) { xTexelC${r+1}.zw = vec2(0.); } xTexelC${r+1}Ready = 1; } xC${r} = vec4( xTexelC${r}.xy, xTexelC${r+1}.xy); `,r+1<c&&(d+=` xC${r+1} = vec4(xTexelC${r}.zw, xTexelC${r+1}.zw); `)));r<c&&(d+=` wTexel = getW(r, ${r}, d1, d2); dotProd += xC${r}.xxzz * vec4(wTexel.xy, wTexel.xy); if(d1 + 1 < ${e.inChannels}) { dotProd += xC${r}.yyww * vec4(wTexel.zw, wTexel.zw); } `,r+1<c&&(d+=` wTexel = getW(r, ${r+1}, d1, d2); dotProd += xC${r+1}.xxzz * vec4(wTexel.xy, wTexel.xy); if(d1 + 1 < ${e.inChannels}) { dotProd += xC${r+1}.yyww * vec4(wTexel.zw, wTexel.zw); } `))}d+=` } } } `;let f="",m="";r&&(f=n?`vec4 activation(vec4 a) { vec4 b = getPreluActivationWeightsAtOutCoords(); ${r} }`:s?`vec4 activation(vec4 a) { vec4 b = getLeakyreluAlphaAtOutCoords(); ${r} }`:`vec4 activation(vec4 x) { ${r} }`,m="result = activation(result);"),t&&this.variableNames.push("bias"),n&&this.variableNames.push("preluActivationWeights"),s&&this.variableNames.push("leakyreluAlpha"),this.userCode=` ${f} void main() { ivec4 coords = getOutputCoords(); int batch = coords.x; ivec2 xRCCorner = coords.yz * strides - pads; int d2 = coords.w; int xRCorner = xRCCorner.x; int xCCorner = xRCCorner.y; //intialize dotProd with a small epsilon seems to reduce GPU accuracy loss. vec4 dotProd = vec4(0.000000000000001); ${d} vec4 result = dotProd - vec4(0.000000000000001); ${t?"result += getBiasAtOutCoords();":""} ${m} setOutput(result); } `}}},{"@tensorflow/tfjs-core":"2Gtps","./gpgpu_math":"6rFox","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],bLHqw:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"conv2dByMatMul",()=>m),s.export(r,"conv2dWithIm2Row",()=>h);var a=e("@tensorflow/tfjs-core"),o=e("../im2col_packed_gpu"),l=e("../kernel_utils/kernel_funcs_utils"),i=e("../mulmat_packed_gpu"),p=e("../webgl_util"),u=e("./BatchMatMul_impl"),c=e("./Identity"),d=e("./Reshape");function f(e,t){let r=e.length;return r>=3?t?[...e.slice(0,-3),e[r-3]*e[r-2],e[r-1]]:[...e.slice(0,-3),e[r-3],e[r-2]*e[r-1]]:!t&&1===r&&e[0]>1?[e[0],1]:null}function m({x:e,filter:t,convInfo:r,backend:n,bias:s=null,preluActivationWeights:o=null,leakyreluAlpha:l=0,activation:i=null}){let m,h=e.shape,g=n.texData.get(e.dataId),x=r.inChannels,y=h[0]*h[1]*h[2],v=r.outChannels,b="channelsLast"===r.dataFormat,k=[];if(null!=o){let e=f(o.shape,b);null!=e&&(o=(0,d.reshape)({inputs:{x:o},backend:n,attrs:{shape:e}}),k.push(o))}if(null!=s){let e=f(s.shape,b);null!=e&&(s=(0,d.reshape)({inputs:{x:s},backend:n,attrs:{shape:e}}),k.push(s))}if(!((1===y||1===v)&&x>u.MATMUL_SHARED_DIM_THRESHOLD)&&g.isPacked&&b&&null!=g.texture&&h[2]%2!=0&&a.util.arraysEqual(g.shape.slice(-3),h.slice(-3))){let f=h[0]*h[1]*(h[2]+1),x={dataId:e.dataId,shape:[1,f,r.inChannels],dtype:e.dtype},y=g.shape;g.shape=g.shape.slice(),g.shape[g.shape.length-2]++,a.util.assert(p.isReshapeFree(g.shape,x.shape),()=>`packed reshape ${g.shape} to ${x.shape} isn't free`);let v=(0,d.reshape)({inputs:{x:t},backend:n,attrs:{shape:[1,r.inChannels,r.outChannels]}});k.push(v);let b=(0,u.batchMatMulImpl)({a:x,b:v,backend:n,transposeA:!1,transposeB:!1,bias:s,activation:i,preluActivationWeights:o,leakyreluAlpha:l}),_=n.texData.get(b.dataId);a.util.assert(_.isPacked,()=>"batchMatMul result is expected to be packed"),g.shape=y,_.shape=r.outShape,(m=(0,c.identity)({inputs:{x:b},backend:n})).shape=r.outShape,k.push(b)}else{let a=r.outHeight*r.outWidth,p=(0,d.reshape)({inputs:{x:e},backend:n,attrs:{shape:b?[r.batchSize,a,r.inChannels]:[r.batchSize,r.inChannels,a]}}),c=(0,d.reshape)({inputs:{x:t},backend:n,attrs:{shape:[1,r.inChannels,r.outChannels]}}),f=(0,u.batchMatMulImpl)({a:b?p:c,b:b?c:p,transposeA:!b,transposeB:!1,backend:n,bias:s,activation:i,preluActivationWeights:o,leakyreluAlpha:l});m=(0,d.reshape)({inputs:{x:f},backend:n,attrs:{shape:r.outShape}}),k.push(p),k.push(c),k.push(f)}for(let e of k)n.disposeIntermediateTensorInfo(e);return m}function h({x:e,filter:t,convInfo:r,backend:n,bias:s=null,preluActivationWeights:p=null,leakyreluAlpha:u=0,activation:c=null}){let{filterWidth:m,filterHeight:h,inChannels:g,outWidth:x,outHeight:y,dataFormat:v}=r,b="channelsLast"===v,k=m*h*g,_=y*x,I=[r.batchSize,k,_],j=[];if(null!=p){let e=f(p.shape,b);null!=e&&(p=(0,d.reshape)({inputs:{x:p},backend:n,attrs:{shape:e}}),j.push(p))}if(null!=s){let e=f(s.shape,b);null!=e&&(s=(0,d.reshape)({inputs:{x:s},backend:n,attrs:{shape:e}}),j.push(s))}let w=(0,d.reshape)({inputs:{x:t},backend:n,attrs:{shape:[1,k,a.util.sizeFromShape(t.shape)/k]}});j.push(w);let T=new(0,o.Im2ColPackedProgram)(I,r),S=[e.shape,[r.padInfo.top,r.padInfo.left],[r.strideHeight,r.strideWidth],[r.dilationHeight,r.dilationWidth],[r.inChannels],[r.filterWidth*r.inChannels],[r.outWidth]],C=n.runWebGLProgram(T,[e],"float32",S),N=(0,d.reshape)({inputs:{x:C},backend:n,attrs:{shape:I}});j.push(C),j.push(N);let E=null!=s,F=null!=p,A="leakyrelu"===c,R=c?(0,l.mapActivationToShaderProgram)(c,!0):null,P=new(0,i.MatMulPackedProgram)(b?N.shape:w.shape,b?w.shape:N.shape,b?[r.batchSize,_,r.outChannels]:[r.batchSize,r.outChannels,_],!0,!1,E,R,F,A),$=b?[N,w]:[w,N];if(s&&$.push(s),F&&$.push(p),A){let e=n.makeTensorInfo([],"float32",a.util.createScalarValue(u,"float32"));$.push(e),j.push(e)}let O=n.runWebGLProgram(P,$,"float32"),D=(0,d.reshape)({inputs:{x:O},backend:n,attrs:{shape:r.outShape}});for(let e of(j.push(O),j))n.disposeIntermediateTensorInfo(e);return D}},{"@tensorflow/tfjs-core":"2Gtps","../im2col_packed_gpu":"s8JGb","../kernel_utils/kernel_funcs_utils":"5oexO","../mulmat_packed_gpu":"eloy9","../webgl_util":"kBGlX","./BatchMatMul_impl":"aJhdh","./Identity":"97wVJ","./Reshape":"aOEE6","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],s8JGb:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"Im2ColPackedProgram",()=>l);var a=e("./glsl_version"),o=e("./gpgpu_math");class l{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"inputShape",type:"ivec4"},{name:"pad",type:"ivec2"},{name:"stride",type:"ivec2"},{name:"dilation",type:"ivec2"},{name:"inChannels",type:"int"},{name:"itemsPerBlockRow",type:"int"},{name:"outWidth",type:"int"}],this.outputShape=e,this.enableShapeUniforms=(0,o.useShapeUniforms)(this.outputShape.length);const{dataFormat:r}=t,n=(0,a.getGlslDifferences)(),s="channelsLast"===r,l=s?1:2,i=s?2:3,p=this.enableShapeUniforms?"if(blockIndex< outShape[2] && pos < outShape[1]) {":`if(blockIndex < ${e[2]} && pos < ${e[1]}) {`;let u="";for(let e=0;e<=1;e++)for(let t=0;t<=1;t++)u+=` blockIndex = rc.z + ${t}; pos = rc.y + ${e}; ${p} offsetY = int(blockIndex / outWidth) * stride[0] - pad[0]; d0 = offsetY + dilation[0] * (pos / itemsPerBlockRow); if(d0 < inputShape[${l}] && d0 >= 0) { // Use custom imod instead mod. On Intel GPU, mod may generate // unexpected value. // https://github.com/tensorflow/tfjs/issues/5447 offsetX = imod(blockIndex, outWidth) * stride[1] - pad[1]; d1 = offsetX + dilation[1] * (imod(pos, itemsPerBlockRow) / inChannels); if(d1< inputShape[${i}] && d1 >= 0) { ch = imod(pos, inChannels); if (${s}) { innerDims = vec2(d1, ch); result[${2*e+t}] = getChannel( getA(rc.x, d0, int(innerDims.x), int(innerDims.y)), innerDims); } else { innerDims = vec2(d0, d1); result[${2*e+t}] = getChannel( getA(rc.x, ch, int(innerDims.x), int(innerDims.y)), innerDims); } } } } `;this.userCode=` void main() { ivec3 rc = getOutputCoords(); vec4 result = vec4(0); int blockIndex, pos, offsetY, d0, offsetX, d1, ch; vec2 innerDims; ${u} ${n.output} = result; } `}}},{"./glsl_version":"dyQn5","./gpgpu_math":"6rFox","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],"8KDHf":[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"conv2DBackpropFilter",()=>l),s.export(r,"conv2DBackpropFilterConfig",()=>i);var a=e("@tensorflow/tfjs-core"),o=e("../conv_backprop_gpu");function l(e){let{inputs:t,backend:r,attrs:n}=e,{x:s,dy:l}=t,{strides:i,pad:p,dataFormat:u,dimRoundingMode:c,filterShape:d}=n,f=a.backend_util.convertConv2DDataFormat(u),m=a.backend_util.computeConv2DInfo(s.shape,d,i,1,p,c,!1,f),h=new(0,o.Conv2DDerFilterProgram)(m);return r.runWebGLProgram(h,[s,l],"float32")}let i={kernelName:a.Conv2DBackpropFilter,backendName:"webgl",kernelFunc:l}},{"@tensorflow/tfjs-core":"2Gtps","../conv_backprop_gpu":"e8lti","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],e8lti:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"Conv2DDerFilterProgram",()=>a),s.export(r,"Conv2DDerInputProgram",()=>o),s.export(r,"Conv3DDerFilterProgram",()=>l),s.export(r,"Conv3DDerInputProgram",()=>i);class a{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;const t=e.strideHeight,r=e.strideWidth,n=e.padInfo.top,s=e.padInfo.left,a="channelsLast"===e.dataFormat;this.userCode=` void main() { ivec4 coords = getOutputCoords(); int wR = coords.x; int wC = coords.y; int d1 = coords.z; int d2 = coords.w; // Convolve x(?, ?, d1) with dy(:, :, d2) to get dw(wR, wC, d1, d2). // ? = to be determined. : = across all values in that axis. float dotProd = 0.0; for (int b = 0; b< ${e.batchSize}; b++) { for (int yR = 0; yR < ${e.outHeight}; yR++) { int xR = wR + yR * ${t} - ${n}; if (xR < 0 || xR >= ${e.inHeight}) { continue; } for (int yC = 0; yC< ${e.outWidth}; yC++) { int xC = wC + yC * ${r} - ${s}; if (xC < 0 || xC >= ${e.inWidth}) { continue; } ${a?`float dyValue = getDy(b, yR, yC, d2); float xValue = getX(b, xR, xC, d1); dotProd += (xValue * dyValue);`:`float dyValue = getDy(b, d2, yR, yC); float xValue = getX(b, d1, xR, xC); dotProd += (xValue * dyValue);`} } } } setOutput(dotProd); } `}}class o{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;const t=e.filterHeight,r=e.filterWidth,n=e.strideHeight,s=e.strideWidth,a="channelsLast"===e.dataFormat,o=t-1-e.padInfo.top,l=r-1-e.padInfo.left;this.userCode=` const ivec2 pads = ivec2(${o}, ${l}); void main() { ivec4 coords = getOutputCoords(); int batch = coords[0]; int d1 = coords[${a?3:1}]; ivec2 dyCorner = ivec2(coords[${a?1:2}], coords[${a?2:3}]) - pads; int dyRCorner = dyCorner.x; int dyCCorner = dyCorner.y; // Convolve dy(?, ?, d2) with w(:, :, d1, d2) to compute dx(xR, xC, d1). // ? = to be determined. : = across all values in that axis. float dotProd = 0.0; for (int wR = 0; wR< ${t}; wR++) { float dyR = float(dyRCorner + wR) / ${n}.0; if (dyR < 0.0 || dyR >= ${e.outHeight}.0 || fract(dyR) > 0.0) { continue; } int idyR = int(dyR); int wRPerm = ${t} - 1 - wR; for (int wC = 0; wC< ${r}; wC++) { float dyC = float(dyCCorner + wC) / ${s}.0; if (dyC < 0.0 || dyC >= ${e.outWidth}.0 || fract(dyC) > 0.0) { continue; } int idyC = int(dyC); int wCPerm = ${r} - 1 - wC; for (int d2 = 0; d2< ${e.outChannels}; d2++) { if (${a}) { float xValue = getDy(batch, idyR, idyC, d2); float wValue = getW(wRPerm, wCPerm, d1, d2); dotProd += xValue * wValue; } else { float xValue = getDy(batch, d2, idyR, idyC); float wValue = getW(wRPerm, wCPerm, d1, d2); dotProd += xValue * wValue; } } } } setOutput(dotProd); } `}}class l{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;const t=e.strideDepth,r=e.strideHeight,n=e.strideWidth,s=e.padInfo.front,a=e.padInfo.top,o=e.padInfo.left;this.userCode=` void main() { ivec5 coords = getOutputCoords(); int wF = coords.x; int wR = coords.y; int wC = coords.z; int d1 = coords.w; int d2 = coords.u; float dotProd = 0.0; for (int b = 0; b < ${e.batchSize}; b++) { for (int yF = 0; yF < ${e.outDepth}; yF++) { int xF = wF + yF * ${t} - ${s}; if (xF < 0 || xF >= ${e.inDepth}) { continue; } for (int yR = 0; yR< ${e.outHeight}; yR++) { int xR = wR + yR * ${r} - ${a}; if (xR < 0 || xR >= ${e.inHeight}) { continue; } for (int yC = 0; yC< ${e.outWidth}; yC++) { int xC = wC + yC * ${n} - ${o}; if (xC < 0 || xC >= ${e.inWidth}) { continue; } float dyValue = getDy(b, yF, yR, yC, d2); float xValue = getX(b, xF, xR, xC, d1); dotProd += (xValue * dyValue); } } } } setOutput(dotProd); } `}}class i{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;const t=e.filterDepth,r=e.filterHeight,n=e.filterWidth,s=e.strideDepth,a=e.strideHeight,o=e.strideWidth,l=t-1-e.padInfo.front,i=r-1-e.padInfo.top,p=n-1-e.padInfo.left;this.userCode=` const ivec3 pads = ivec3(${l}, ${i}, ${p}); void main() { ivec5 coords = getOutputCoords(); int batch = coords.x; int d1 = coords.u; ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads; int dyFCorner = dyCorner.x; int dyRCorner = dyCorner.y; int dyCCorner = dyCorner.z; float dotProd = 0.0; for (int wF = 0; wF< ${t}; wF++) { float dyF = float(dyFCorner + wF) / ${s}.0; if (dyF < 0.0 || dyF >= ${e.outDepth}.0 || fract(dyF) > 0.0) { continue; } int idyF = int(dyF); int wFPerm = ${t} - 1 - wF; for (int wR = 0; wR< ${r}; wR++) { float dyR = float(dyRCorner + wR) / ${a}.0; if (dyR < 0.0 || dyR >= ${e.outHeight}.0 || fract(dyR) > 0.0) { continue; } int idyR = int(dyR); int wRPerm = ${r} - 1 - wR; for (int wC = 0; wC< ${n}; wC++) { float dyC = float(dyCCorner + wC) / ${o}.0; if (dyC < 0.0 || dyC >= ${e.outWidth}.0 || fract(dyC) > 0.0) { continue; } int idyC = int(dyC); int wCPerm = ${n} - 1 - wC; for (int d2 = 0; d2< ${e.outChannels}; d2++) { float xValue = getDy(batch, idyF, idyR, idyC, d2); float wValue = getW(wFPerm, wRPerm, wCPerm, d1, d2); dotProd += xValue * wValue; } } } } setOutput(dotProd); } `}}},{"@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],dAZKp:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"conv2DBackpropInput",()=>i),s.export(r,"conv2DBackpropInputConfig",()=>p);var a=e("@tensorflow/tfjs-core"),o=e("../conv_backprop_gpu"),l=e("../conv_backprop_packed_gpu");function i(e){let{inputs:t,backend:r,attrs:n}=e,{dy:s,filter:i}=t,{inputShape:p,strides:u,pad:c,dataFormat:d,dimRoundingMode:f}=n,m=a.backend_util.convertConv2DDataFormat(d),h=a.backend_util.computeConv2DInfo(p,i.shape,u,1,c,f,!1,m);if((0,a.env)().getBool("WEBGL_PACK_CONV2DTRANSPOSE")&&"channelsLast"===m){let e=[[h.strideHeight,h.strideWidth]],t=new(0,l.Conv2DDerInputPackedProgram)(h);return r.runWebGLProgram(t,[s,i],"float32",e)}{let e=new(0,o.Conv2DDerInputProgram)(h);return r.runWebGLProgram(e,[s,i],"float32")}}let p={kernelName:a.Conv2DBackpropInput,backendName:"webgl",kernelFunc:i}},{"@tensorflow/tfjs-core":"2Gtps","../conv_backprop_gpu":"e8lti","../conv_backprop_packed_gpu":"jg0dj","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],jg0dj:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"Conv2DDerInputPackedProgram",()=>o);var a=e("./gpgpu_math");class o{constructor(e){this.variableNames=["dy","W"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"strides",type:"vec2"}],this.outputShape=e.inShape,this.enableShapeUniforms=(0,a.useShapeUniforms)(this.outputShape.length);const t=e.filterHeight,r=e.filterWidth,n=t-1-e.padInfo.top,s=r-1-e.padInfo.left;this.userCode=` const ivec2 pads = ivec2(${n}, ${s}); void main() { ivec4 coords = getOutputCoords(); int batch = coords[0]; int d1 = coords[3]; ivec2 dyCorner = ivec2(coords[1], coords[2]) - pads; int dyRCorner = dyCorner.x; int dyCCorner = dyCorner.y; vec4 result = vec4(0.); for (int wR = 0; wR< ${t}; wR++) { float dyR = float(dyRCorner + wR) / strides[0]; if (dyR < 0.0 || dyR >= ${e.outHeight}.0 || fract(dyR) > 0.0) { continue; } int idyR = int(dyR); int wRPerm = ${t} - 1 - wR; for (int wC = 0; wC< ${r}; wC++) { int wCPerm = ${r} - 1 - wC; float dyC = float(dyCCorner + wC) / strides[1]; bool idyCVal = (dyC >= 0.0) && (dyC< ${e.outWidth}.0) && (fract(dyC) == 0.0); int idyC = int(dyC); float dyC2 = float(dyCCorner + wC + 1) / strides[1]; bool idyCVal2 = (dyC2 >= 0.0) && (dyC2< ${e.outWidth}.0) && (fract(dyC2) == 0.0); int idyC2 = int(dyC2); if (idyCVal && idyCVal2) { for (int d2 = 0; d2 < ${e.outChannels}; d2 += 2) { vec4 wValue = getW(wRPerm, wCPerm, d1, d2); vec4 dySample = getDy(batch, idyR, idyC, d2); vec4 dySample2 = (idyC / 2 == idyC2 / 2) ? dySample : getDy(batch, idyR, idyC2, d2); 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int end = ${u(s,"coords",this.op)}; float val = ${i}; int pow2 = int(pow(2.0, index)); if (${d}) { int idx = ${f}; ${u(s,"coords",this.op)} = idx; val ${this.op}= getX(${p(s,"coords",this.op)}); } setOutput(val); } `}}function p(e,t,r){if(1===e)return`${t}`;if(2===e)return`${t}.x, ${t}.y`;if(3===e)return`${t}.x, ${t}.y, ${t}.z`;if(4===e)return`${t}.x, ${t}.y, ${t}.z, ${t}.w`;throw Error(`Cumulative ${r} for rank ${e} is not yet supported`)}function u(e,t,r){if(1===e)return`${t}`;if(2===e)return`${t}.y`;if(3===e)return`${t}.z`;if(4===e)return`${t}.w`;throw Error(`Cumulative ${r} for rank ${e} is not yet supported`)}},{"./shader_compiler":"gZjZZ","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],l4dmJ:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"cumImpl",()=>p);var a=e("@tensorflow/tfjs-core"),o=e("../cum_gpu"),l=e("./Identity"),i=e("./Transpose");function p(e,t,r,n,s,p){let u=t.shape.length,c=a.backend_util.getAxesPermutation([n],u),d=t;null!=c&&(d=(0,i.transpose)({inputs:{x:t},backend:r,attrs:{perm:c}}));let f=a.backend_util.getInnerMostAxes(1,u)[0];if(f!==u-1)throw Error(`WebGL cumprod shader expects an inner-most axis=${t.shape.length-1} but got axis=${n}`);let m=d.shape[f],h=(0,l.identity)({inputs:{x:d},backend:r});for(let t=0;t<=Math.ceil(Math.log2(m))-1;t++){let n=new(0,o.CumProgram)(e,d.shape,!1,p),s=[[t]],a=h;h=r.runWebGLProgram(n,[h],h.dtype,s),r.disposeIntermediateTensorInfo(a)}if(s){let t=new(0,o.CumProgram)(e,d.shape,s,p),n=h;h=r.runWebGLProgram(t,[h],h.dtype),r.disposeIntermediateTensorInfo(n)}if(null!=c){let e=a.backend_util.getUndoAxesPermutation(c),t=(0,i.transpose)({inputs:{x:h},backend:r,attrs:{perm:e}});return r.disposeIntermediateTensorInfo(h),r.disposeIntermediateTensorInfo(d),t}return h}},{"@tensorflow/tfjs-core":"2Gtps","../cum_gpu":"2DlyG","./Identity":"97wVJ","./Transpose":"lqCy7","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],jJsSs:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"cumsum",()=>i),s.export(r,"cumsumConfig",()=>p);var a=e("@tensorflow/tfjs-core"),o=e("../cum_gpu"),l=e("./Cum_impl");function i(e){let{inputs:t,backend:r,attrs:n}=e,{x:s}=t,{axis:a,exclusive:i,reverse:p}=n;return(0,l.cumImpl)(o.CumOpType.Sum,s,r,a,i,p)}let p={kernelName:a.Cumsum,backendName:"webgl",kernelFunc:i}},{"@tensorflow/tfjs-core":"2Gtps","../cum_gpu":"2DlyG","./Cum_impl":"l4dmJ","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],"5RBVO":[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"denseBincount",()=>l),s.export(r,"denseBincountConfig",()=>i);var a=e("@tensorflow/tfjs-core"),o=e("../kernel_utils/shared");function l(e){let{inputs:t,backend:r,attrs:n}=e,{x:s,weights:a}=t,{size:l,binaryOutput:i}=n;if(1===s.shape.length){let e=r.readSync(s.dataId),t=r.readSync(a.dataId),n=(0,o.bincountImplCPU)(e,t,a.dtype,a.shape,l);return r.makeTensorInfo([l],a.dtype,n)}if(2===s.shape.length){let e=r.bufferSync(s),t=r.bufferSync(a),n=(0,o.bincountReduceImplCPU)(e,t,l,i);return r.makeTensorInfo(n.shape,a.dtype,n.values)}throw Error(`Error in denseBincount: input must be at most rank 2, but got rank${s.shape.length}.`)}let i={kernelName:a.DenseBincount,backendName:"webgl",kernelFunc:l}},{"@tensorflow/tfjs-core":"2Gtps","../kernel_utils/shared":"6ruDg","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],"9LXR4":[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"depthToSpace",()=>l),s.export(r,"depthToSpaceConfig",()=>i);var a=e("@tensorflow/tfjs-core"),o=e("../depth_to_space_gpu");function l(e){let{inputs:t,backend:r,attrs:n}=e,{x:s}=t,{blockSize:a,dataFormat:l}=n,i=s.shape[0],p="NHWC"===l?s.shape[1]:s.shape[2],u="NHWC"===l?s.shape[2]:s.shape[3],c="NHWC"===l?s.shape[3]:s.shape[1],d=p*a,f=u*a,m=c/(a*a),h=new(0,o.DepthToSpaceProgram)("NHWC"===l?[i,d,f,m]:[i,m,d,f],a,l);return r.runWebGLProgram(h,[s],s.dtype)}let i={kernelName:a.DepthToSpace,backendName:"webgl",kernelFunc:l}},{"@tensorflow/tfjs-core":"2Gtps","../depth_to_space_gpu":"RB4TH","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],RB4TH:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"DepthToSpaceProgram",()=>a);class a{constructor(e,t,r){this.variableNames=["x"],this.outputShape=[],this.outputShape=e,this.blockSize=t,this.dataFormat=r,this.userCode=` void main() { ivec4 coords = getOutputCoords(); int b = coords[0]; int h = ${this.getHeightCoordString()}; int w = ${this.getWidthCoordString()}; int d = ${this.getDepthCoordString()}; int in_h = h / ${t}; int offset_h = imod(h, ${t}); int in_w = w / ${t}; int offset_w = imod(w, ${t}); int offset_d = (offset_h * ${t} + offset_w) * ${this.getOutputDepthSize()}; int in_d = d + offset_d; float result = ${this.getInputSamplingString()}; setOutput(result); } `}getHeightCoordString(){return"NHWC"===this.dataFormat?"coords[1]":"coords[2]"}getWidthCoordString(){return"NHWC"===this.dataFormat?"coords[2]":"coords[3]"}getDepthCoordString(){return"NHWC"===this.dataFormat?"coords[3]":"coords[1]"}getOutputDepthSize(){return"NHWC"===this.dataFormat?this.outputShape[3]:this.outputShape[1]}getInputSamplingString(){return"NHWC"===this.dataFormat?"getX(b, in_h, in_w, in_d)":"getX(b, in_d, in_h, in_w)"}}},{"@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],"36o00":[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"depthwiseConv2dNative",()=>i),s.export(r,"depthwiseConv2dNativeConfig",()=>p);var a=e("@tensorflow/tfjs-core"),o=e("../conv_gpu_depthwise"),l=e("../conv_packed_gpu_depthwise");function i(e){let t,{inputs:r,backend:n,attrs:s}=e,{x:i,filter:p}=r,{strides:u,pad:c,dilations:d,dimRoundingMode:f}=s,m=d;null==m&&(m=[1,1]),a.util.assert(a.backend_util.eitherStridesOrDilationsAreOne(u,m),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${u} and dilations '${m}'`);let h=a.backend_util.computeConv2DInfo(i.shape,p.shape,u,m,c,f,!0);t=(0,a.env)().getBool("WEBGL_PACK_DEPTHWISECONV")&&h.strideWidth<=2&&h.outChannels/h.inChannels==1?new(0,l.DepthwiseConvPacked2DProgram)(h):new(0,o.DepthwiseConv2DProgram)(h);let g=[[h.padInfo.top,h.padInfo.left],[h.strideHeight,h.strideWidth],[h.dilationHeight,h.dilationWidth],[h.inHeight,h.inWidth]];return n.runWebGLProgram(t,[i,p],"float32",g)}let p={kernelName:a.DepthwiseConv2dNative,backendName:"webgl",kernelFunc:i}},{"@tensorflow/tfjs-core":"2Gtps","../conv_gpu_depthwise":"jUzNG","../conv_packed_gpu_depthwise":"60T3v","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],jUzNG:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"DepthwiseConv2DProgram",()=>o);var a=e("./gpgpu_math");class o{constructor(e,t=!1,r=null,n=!1,s=!1){this.variableNames=["x","W"],this.customUniforms=[{name:"pads",type:"ivec2"},{name:"strides",type:"ivec2"},{name:"dilations",type:"ivec2"},{name:"inDims",type:"ivec2"}],this.outputShape=e.outShape,this.enableShapeUniforms=(0,a.useShapeUniforms)(this.outputShape.length);const o=e.filterHeight,l=e.filterWidth,i=e.outChannels/e.inChannels;let p="",u="";r&&(p=n?`float activation(float a) { float b = getPreluActivationWeightsAtOutCoords(); ${r} }`:s?`float activation(float a) { float b = getLeakyreluAlphaAtOutCoords(); ${r} }`:` float activation(float x) { ${r} } `,u="result = activation(result);"),t&&this.variableNames.push("bias"),n&&this.variableNames.push("preluActivationWeights"),s&&this.variableNames.push("leakyreluAlpha"),this.userCode=` ${p} void main() { ivec4 coords = getOutputCoords(); int batch = coords.x; ivec2 xRCCorner = coords.yz * strides - pads; int d2 = coords.w; int d1 = d2 / ${i}; int q = d2 - d1 * ${i}; int xRCorner = xRCCorner.x; int xCCorner = xRCCorner.y; // 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< ${o}; wR++) { int xR = xRCorner + wR * dilations[0]; if (xR < 0 || xR >= inDims[0]) { continue; } for (int wC = 0; wC< ${l}; wC++) { int xC = xCCorner + wC * dilations[1]; if (xC < 0 || xC >= inDims[1]) { continue; } float xVal = getX(batch, xR, xC, d1); float wVal = getW(wR, wC, d1, q); dotProd += xVal * wVal; } } float result = dotProd; ${t?"result += getBiasAtOutCoords();":""} ${u} setOutput(result); } `}}},{"./gpgpu_math":"6rFox","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],"60T3v":[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"DepthwiseConvPacked2DProgram",()=>l);var a=e("@tensorflow/tfjs-core"),o=e("./gpgpu_math");class l{constructor(e,t=!1,r=null,n=!1,s=!1){this.variableNames=["x","W"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"pads",type:"ivec2"},{name:"strides",type:"ivec2"},{name:"dilations",type:"ivec2"},{name:"inDims",type:"ivec2"}],this.outputShape=e.outShape,this.enableShapeUniforms=(0,o.useShapeUniforms)(this.outputShape.length);const l=e.outChannels/e.inChannels,i=e.padInfo.left,p=e.strideWidth,u=e.dilationWidth,c=e.filterHeight,d=e.filterWidth;let f=` int xR; int xC; int xCOffset; vec4 wTexel; vec4 previous; vec4 final;`;for(let e=0;e<d;e++)f+=` vec4 xTexelC${2*e}; int xTexelC${2*e}Ready; vec4 xTexelC${2*e+1}; int xTexelC${2*e+1}Ready; vec4 xC${e};`;f+=` for (int r = 0; r < ${c}; r++) { `;for(let e=0;e<d;e++)f+=` xTexelC${2*e} = vec4(0.0); xTexelC${2*e}Ready = 0; xTexelC${2*e+1} = vec4(0.0); xTexelC${2*e+1}Ready = 0; xC${e} = vec4(0.0);`;f+=` xR = xRCorner + r * dilations[0]; if (xR >=0 && xR< inDims[0]) { `;for(let e=0;e<(d+1)/2;e++){const t=2*e;if(f+=` xC = xCCorner + ${t*u}; `,1===p){if(t<d&&(i%2==1?(f+=` xCOffset = xC + 1; if (xCOffset >= 0 && xCOffset< inDims[1] && xTexelC${t}Ready == 0) { xTexelC${t} = getX(batch, xR, xCOffset, d1); // Need to manually clear unused channels in case // we're reading from recycled texture. if (xCOffset + 1 >= inDims[1]) { xTexelC${t}.zw = vec2(0.0); } xTexelC${t}Ready = 1; } `,1===u&&t>0?f+=` xC${t} = vec4(xTexelC${t-2}.zw, xTexelC${t}.xy); `:f+=` xCOffset = xC + 1 - 2; if (xCOffset >= 0 && xCOffset< inDims[1]) { previous = getX(batch, xR, xCOffset, d1); // Need to manually clear unused channels in case // we're reading from recycled texture. if (xCOffset + 1 >= inDims[1]) { previous.zw = vec2(0.0); } xC${t} = vec4(previous.zw, xTexelC${t}.xy); } else { xC${t} = vec4(0.0, 0.0, xTexelC${t}.xy); } `):f+=` if (xC >= 0 && xC< inDims[1] && xTexelC${t}Ready == 0) { xTexelC${t} = getX(batch, xR, xC, d1); if (xC + 1 >= inDims[1]) { xTexelC${t}.zw = vec2(0.0); } xTexelC${t}Ready = 1; } xC${t} = xTexelC${t}; `,t+1<d)){const e=i%2==0?a.util.nearestLargerEven(u):u;u%2==0&&i%2==1||u%2!=0&&i%2!=1?(f+=` xCOffset = xC + imod(pads[1], 2) + ${e}; if (xCOffset >= 0 && xCOffset< inDims[1] && xTexelC${t+1}Ready == 0) { xTexelC${t+1} = getX(batch, xR, xCOffset, d1); // Need to manually clear unused channels in case // we're reading from recycled texture. if (xCOffset + 1 >= inDims[1]) { xTexelC${t+1}.zw = vec2(0.0); } xTexelC${t+1}Ready = 1; } `,u>1?f+=` xCOffset -= 2; if (xCOffset >= 0 && xCOffset< inDims[1]) { previous = getX(batch, xR, xCOffset, d1); xC${t+1} = vec4(previous.zw, xTexelC${t+1}.xy); } else { xC${t+1} = vec4(0.0, 0.0, xTexelC${t+1}.xy); } `:f+=` xC${t+1} = vec4(xTexelC${t}.zw, xTexelC${t+1}.xy); `):1===e?f+=` xC${t+1} = xTexelC${t}; `:f+=` xCOffset = xC + ${e}; if (xCOffset >= 0 && xCOffset< inDims[1] && xTexelC${t+1}Ready == 0) { xTexelC${t+1} = getX(batch, xR, xCOffset, d1); if (xCOffset + 1 >= inDims[1]) { xTexelC${t+1}.zw = vec2(0.0); } xTexelC${t+1}Ready = 1; } xC${t+1} = xTexelC${t+1}; `}}else t<d&&(i%2==1?(f+=` xCOffset = xC + 1 - strides[1]; if(xCOffset >= 0 && xCOffset< inDims[1] && xTexelC${t}Ready == 0) { xTexelC${t} = getX(batch, xR, xCOffset, d1); // Need to manually clear unused channels in case // we're reading from recycled texture. if (xCOffset + 1 >= inDims[1]) { xTexelC${t}.zw = vec2(0.0); } xTexelC${t}Ready = 1; } if(xC + 1 >= 0 && xC + 1< inDims[1] && xTexelC${t+1}Ready == 0) { xTexelC${t+1} = getX(batch, xR, xC + 1, d1); // Need to manually clear unused channels in case // we're reading from recycled texture. if (xC + 2 >= inDims[1]) { xTexelC${t+1}.zw = vec2(0.0); } xTexelC${t+1}Ready = 1; } xC${t} = vec4(xTexelC${t}.zw, xTexelC${t+1}.zw); `,t+1<d&&(f+=` final = vec4(0.0); xCOffset = xC + 1 + strides[1]; if(xCOffset >= 0 && xCOffset< inDims[1]) { final = getX(batch, xR, xCOffset, d1); } xC${t+1} = vec4(xTexelC${t+1}.xy, final.xy); `)):(f+=` if(xC >= 0 && xC< inDims[1] && xTexelC${t}Ready == 0) { xTexelC${t} = getX(batch, xR, xC, d1); if (xC + 1 >= inDims[1]) { xTexelC${t}.zw = vec2(0.0); } xTexelC${t}Ready = 1; } xCOffset = xC + strides[1]; if(xCOffset >= 0 && xCOffset< inDims[1] && xTexelC${t+1}Ready == 0) { xTexelC${t+1} = getX(batch, xR, xCOffset, d1); if (xCOffset + 1 >= inDims[1]) { xTexelC${t+1}.zw = vec2(0.); } xTexelC${t+1}Ready = 1; } xC${t} = vec4( xTexelC${t}.xy, xTexelC${t+1}.xy); `,t+1<d&&(f+=` xC${t+1} = vec4(xTexelC${t}.zw, xTexelC${t+1}.zw); `)));t<d&&(f+=` wTexel = getW(r, ${t}, d1, q); dotProd += xC${t} * vec4(wTexel.xz, wTexel.xz); `,t+1<d&&(f+=` wTexel = getW(r, ${t+1}, d1, q); dotProd += xC${t+1} * vec4(wTexel.xz, wTexel.xz); `))}f+=` } } `;let m="",h="";r&&(m=n?`vec4 activation(vec4 a) { vec4 b = getPreluActivationWeightsAtOutCoords(); ${r} }`:s?`vec4 activation(vec4 a) { vec4 b = getLeakyreluAlphaAtOutCoords(); ${r} }`:`vec4 activation(vec4 x) { ${r} }`,h="result = activation(result);"),t&&this.variableNames.push("bias"),n&&this.variableNames.push("preluActivationWeights"),s&&this.variableNames.push("leakyreluAlpha"),this.userCode=` ${m} void main() { ivec4 coords = getOutputCoords(); int batch = coords.x; ivec2 xRCCorner = coords.yz * strides - pads; int d2 = coords.w; int d1 = d2 / ${l}; int q = d2 - d1 * ${l}; int xRCorner = xRCCorner.x; int xCCorner = xRCCorner.y; //intialize dotProd with a small epsilon seems to reduce GPU accuracy loss. vec4 dotProd = vec4(0.000000000000001); ${f} vec4 result = dotProd - vec4(0.000000000000001); ${t?"result += getBiasAtOutCoords();":""} ${h} setOutput(result); } `}}},{"@tensorflow/tfjs-core":"2Gtps","./gpgpu_math":"6rFox","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],"12xnA":[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"depthwiseConv2dNativeBackpropFilter",()=>l),s.export(r,"depthwiseConv2dNativeBackpropFilterConfig",()=>i);var a=e("@tensorflow/tfjs-core"),o=e("../conv_backprop_gpu_depthwise");function l(e){let{inputs:t,backend:r,attrs:n}=e,{x:s,dy:l}=t,{strides:i,dilations:p,pad:u,dimRoundingMode:c,filterShape:d}=n,f=a.backend_util.computeConv2DInfo(s.shape,d,i,p,u,c,!0),m=new(0,o.DepthwiseConv2DDerFilterProgram)(f);return r.runWebGLProgram(m,[s,l],"float32")}let i={kernelName:a.DepthwiseConv2dNativeBackpropFilter,backendName:"webgl",kernelFunc:l}},{"@tensorflow/tfjs-core":"2Gtps","../conv_backprop_gpu_depthwise":"4GYwp","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],"4GYwp":[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"DepthwiseConv2DDerFilterProgram",()=>a),s.export(r,"DepthwiseConv2DDerInputProgram",()=>o);class a{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;const t=e.strideHeight,r=e.strideWidth,n=e.padInfo.top,s=e.padInfo.left,a=e.outChannels/e.inChannels;this.userCode=` void main() { ivec4 coords = getOutputCoords(); int wR = coords.x; int wC = coords.y; int d1 = coords.z; int dm = coords.w; int d2 = d1 * ${a} + dm; float dotProd = 0.0; // TO DO: Vec4 over the batch size for (int b = 0; b< ${e.batchSize}; b++) { for (int yR = 0; yR < ${e.outHeight}; yR++) { int xR = wR + yR * ${t} - ${n}; if (xR < 0 || xR >= ${e.inHeight}) { continue; } for (int yC = 0; yC< ${e.outWidth}; yC++) { int xC = wC + yC * ${r} - ${s}; if (xC < 0 || xC >= ${e.inWidth}) { continue; } float dyValue = getDy(b, yR, yC, d2); float xValue = getX(b, xR, xC, d1); dotProd += (xValue * dyValue); } } } setOutput(dotProd); } `}}class o{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;const t=e.filterHeight,r=e.filterWidth,n=e.strideHeight,s=e.strideWidth,a=t-1-e.padInfo.top,o=r-1-e.padInfo.left,l=e.outChannels/e.inChannels;this.userCode=` const ivec2 pads = ivec2(${a}, ${o}); void main() { ivec4 coords = getOutputCoords(); int batch = coords[0]; int d1 = coords[3]; ivec2 dyCorner = coords.yz - pads; int dyRCorner = dyCorner.x; 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`,i=(0,o.binaryKernelFunc)({opSnippet:"return float(a >= 1.0 || b >= 1.0);",packedOpSnippet:l,dtype:"bool"}),p={kernelName:a.LogicalOr,backendName:"webgl",kernelFunc:i}},{"@tensorflow/tfjs-core":"2Gtps","../kernel_utils/kernel_funcs_utils":"5oexO","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],gm5j4:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"lrn",()=>i),s.export(r,"LRNConfig",()=>p);var a=e("@tensorflow/tfjs-core"),o=e("../lrn_gpu"),l=e("../lrn_packed_gpu");let i=e=>{let{inputs:t,backend:r,attrs:n}=e,{x:s}=t,{depthRadius:i,bias:p,alpha:u,beta:c}=n,d=(0,a.env)().getBool("WEBGL_PACK_NORMALIZATION")?new(0,l.LRNPackedProgram)(s.shape,i,p,u,c):new(0,o.LRNProgram)(s.shape,i,p,u,c);return r.runWebGLProgram(d,[s],s.dtype)},p={kernelName:a.LRN,backendName:"webgl",kernelFunc:i}},{"@tensorflow/tfjs-core":"2Gtps","../lrn_gpu":"1Uwrr","../lrn_packed_gpu":"cxp6G","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],"1Uwrr":[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"LRNProgram",()=>a);class a{constructor(e,t,r,n,s){let a;this.variableNames=["x"],this.outputShape=[];const o=e[3]-1;this.outputShape=e;const l=`float(${r}) + float(${n}) * sum`;a=.5===s?`inversesqrt(${l})`:1===s?`1.0/(${l})`:`exp(log(${l}) * float(-${s}));`,this.userCode=` void main() { ivec4 coords = getOutputCoords(); int b = coords[0]; int r = coords[1]; int c = coords[2]; int d = coords[3]; float x = getX(b, r, c, d); float sum = 0.0; for (int j = -${t}; j<= ${t}; j++) { int idx = d + j; if (idx >= 0 && idx<= ${o}) { float z = getX(b, r, c, idx); sum += z * z; } } float val = x * ${a}; setOutput(val); } `}}},{"@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],cxp6G:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"LRNPackedProgram",()=>a);class a{constructor(e,t,r,n,s){let a;this.variableNames=["x"],this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0;const o=e[3]-1;this.outputShape=e;const l=`float(${r}) + float(${n}) * sum`;a=.5===s?`inversesqrt(${l})`:1===s?`1.0/(${l})`:`exp(log(${l}) * float(-${s}));`,this.userCode=` void main() { ivec4 coords = getOutputCoords(); int b = coords.x; int r = coords.y; int c = coords.z; int d = coords.w; bool hasNextCol = d< ${this.outputShape[3]}; bool hasNextRow = c < ${this.outputShape[2]}; vec4 sum = vec4(0.); vec4 xFragAtOutputCoords = getX(b, r, c, d); vec4 xAtOutputCoords = vec4( getChannel(xFragAtOutputCoords, vec2(c, d)), hasNextCol ? getChannel(xFragAtOutputCoords, vec2(c, d + 1)) : 0.0, hasNextRow ? getChannel(xFragAtOutputCoords , vec2(c + 1, d)) : 0.0, (hasNextRow && hasNextCol) ? getChannel(xFragAtOutputCoords, vec2(c + 1, d + 1)) : 0.0 ); int firstChannel = d - ${t}; 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 = - ${t}; j<= ${t}; j++) { ivec2 idx = depth + j; bvec2 aboveLowerBound = greaterThanEqual(idx, ivec2(0)); bvec2 belowUpperBound = lessThanEqual(idx, ivec2(${o})); bool depthInRange = aboveLowerBound.x && belowUpperBound.x; bool depthPlusOneInRange = aboveLowerBound.y && belowUpperBound.y; if(depthInRange || depthPlusOneInRange){ vec4 z = vec4(0.); vec4 xFragAtCurrentDepth; z.xz = cache.xy; if(depthPlusOneInRange && hasNextCol){ xFragAtCurrentDepth = idx.y != d ? getX(b, r, c, idx.y) : xFragAtOutputCoords; z.y = getChannel(xFragAtCurrentDepth, vec2(c, idx.y)); if(hasNextRow){ z.w = getChannel(xFragAtCurrentDepth, vec2(c + 1, idx.y)); } } cache.xy = z.yw; sum += z * z; } } vec4 result = xAtOutputCoords * ${a}; setOutput(result); } `}}},{"@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],lcb03:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"lrnGrad",()=>l),s.export(r,"LRNGradConfig",()=>i);var a=e("@tensorflow/tfjs-core"),o=e("../lrn_grad_gpu");let l=e=>{let{inputs:t,backend:r,attrs:n}=e,{x:s,y:a,dy:l}=t,{depthRadius:i,bias:p,alpha:u,beta:c}=n,d=new(0,o.LRNGradProgram)(s.shape,i,p,u,c);return r.runWebGLProgram(d,[s,a,l],s.dtype)},i={kernelName:a.LRNGrad,backendName:"webgl",kernelFunc:l}},{"@tensorflow/tfjs-core":"2Gtps","../lrn_grad_gpu":"kS8Sp","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],kS8Sp:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"LRNGradProgram",()=>a);class a{constructor(e,t,r,n,s){this.variableNames=["inputImage","outputImage","dy"],this.outputShape=[],this.outputShape=e,this.depth=e[3],this.depthRadius=t,this.bias=r,this.alpha=n,this.beta=s,this.userCode=` void main() { ivec4 coords = getOutputCoords(); int b = coords[0]; int r = coords[1]; int c = coords[2]; float result = 0.0; for (int d = 0; d< ${this.depth}; ++d) { int depthBegin = int(max(0.0, float(d - ${t}))); int depthEnd = int(min(float(${this.depth}), float(d + ${t} + 1))); const int MIN_DEPTH_BEGIN = 0; const int MAX_DEPTH_END = ${this.depth}; float norm = 0.0; for (int k = MIN_DEPTH_BEGIN; k < MAX_DEPTH_END; ++k) { if (k < depthBegin){ continue; } else if (k >= depthBegin && k< depthEnd) { norm += getInputImage(b, r, c, k) * getInputImage(b, r, c, k); } else { break; } } norm = float(${n}) * norm + float(${r}); for(int k = MIN_DEPTH_BEGIN; k < MAX_DEPTH_END; ++k){ if (k < depthBegin){ continue; } else if (k >= depthBegin && k< depthEnd){ float dyi = -2.0 * float(${n}) * float(${s}) * getInputImage(b, r, c, k) * getOutputImage(b, r, c, d) / norm; if (k == d) { dyi += pow(norm, -1.0 * ${s}); } if (k == coords[3]) { dyi *= getDy(b, r, c, d); result += dyi; } } else { break; } } } setOutput(result); } `}}},{"@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],afHh0:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"max",()=>p),s.export(r,"maxConfig",()=>u);var a=e("@tensorflow/tfjs-core"),o=e("../kernel_utils/shared"),l=e("./Max_impl"),i=e("./Transpose_impl");function p(e){let t,{inputs:r,backend:n,attrs:s}=e,{x:p}=r,{reductionIndices:u,keepDims:c}=s,d=p.shape.length,f=a.util.parseAxisParam(u,p.shape),m=f,h=a.backend_util.getAxesPermutation(m,d),g=null!=h,x=n.shouldExecuteOnCPU([p]),y=p;if(g){if(x){let e=n.texData.get(y.dataId).values,t=Array(d);for(let e=0;e<t.length;e++)t[e]=p.shape[h[e]];let r=(0,i.transposeImplCPU)(e,p.shape,p.dtype,h,t);y=n.makeTensorInfo(t,p.dtype),n.texData.get(y.dataId).values=r}else y=(0,i.transposeImpl)(p,h,n);m=a.backend_util.getInnerMostAxes(m.length,d)}a.backend_util.assertAxesAreInnerMostDims("max",m,d);let[v,b]=a.backend_util.computeOutAndReduceShapes(y.shape,m),k=v;if(c&&(k=a.backend_util.expandShapeToKeepDim(v,f)),x){let e=n.texData.get(y.dataId).values,r=(0,o.maxImplCPU)(e,a.util.sizeFromShape(b),k,p.dtype);t=n.makeTensorInfo(k,p.dtype),n.texData.get(t.dataId).values=r}else t=(0,l.maxImpl)(y,b,k,n);return g&&n.disposeIntermediateTensorInfo(y),t}let u={kernelName:a.Max,backendName:"webgl",kernelFunc:p}},{"@tensorflow/tfjs-core":"2Gtps","../kernel_utils/shared":"6ruDg","./Max_impl":"5vcnJ","./Transpose_impl":[["transposeImpl","3ouoc"],["transposeImplCPU","6ruDg"]],"@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],"5vcnJ":[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"maxImpl",()=>i);var a=e("@tensorflow/tfjs-core"),o=e("../kernel_utils/reduce"),l=e("../kernels/Reshape");function i(e,t,r,n){let s=a.util.sizeFromShape(t),i=a.util.sizeFromShape(e.shape),p=(0,l.reshape)({inputs:{x:e},attrs:{shape:[i/s,s]},backend:n}),u=(0,o.reduce)(p,e.dtype,"max",n),c=(0,l.reshape)({inputs:{x:u},attrs:{shape:r},backend:n});return n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(u),c}},{"@tensorflow/tfjs-core":"2Gtps","../kernel_utils/reduce":"gwlbf","../kernels/Reshape":"aOEE6","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],"94OQw":[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"maximum",()=>d),s.export(r,"maximumConfig",()=>f);var a=e("@tensorflow/tfjs-core"),o=e("../binaryop_gpu"),l=e("../binaryop_packed_gpu"),i=e("../kernel_utils/kernel_funcs_utils"),p=e("../kernel_utils/shared");let u=o.CHECK_NAN_SNIPPET+` return max(a, b); 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Got strides ${u} and dilations '1'`);let f=a.backend_util.computePool2DInfo(s.shape,p,u,1,c,d);if(1===f.filterWidth&&1===f.filterHeight&&a.util.arraysEqual(f.inShape,f.outShape))return(0,i.identity)({inputs:{x:s},backend:r});let m=new(0,o.Pool2DProgram)(f,"max",!1);return r.runWebGLProgram(m,[s],s.dtype)}let u={kernelName:a.MaxPool,backendName:"webgl",kernelFunc:p}},{"@tensorflow/tfjs-core":"2Gtps","../pool_gpu":"1JUNb","../webgl_util":"kBGlX","./Identity":"97wVJ","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],"2yDQt":[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"maxPool3d",()=>l),s.export(r,"maxPool3DConfig",()=>i);var a=e("@tensorflow/tfjs-core"),o=e("../pool_gpu");function l(e){let{inputs:t,backend:r,attrs:n}=e,{x:s}=t,{filterSize:l,strides:i,pad:p,dataFormat:u,dimRoundingMode:c}=n,d=a.backend_util.computePool3DInfo(s.shape,l,i,[1,1,1],p,c,u),f=new(0,o.Pool3DProgram)(d,"max",!1);return r.runWebGLProgram(f,[s],s.dtype)}let i={kernelName:a.MaxPool3D,backendName:"webgl",kernelFunc:l}},{"@tensorflow/tfjs-core":"2Gtps","../pool_gpu":"1JUNb","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],"5foYE":[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"maxPool3DGrad",()=>i),s.export(r,"maxPool3DGradConfig",()=>p);var a=e("@tensorflow/tfjs-core"),o=e("../max_pool_backprop_gpu"),l=e("../pool_gpu");function i(e){let{inputs:t,backend:r,attrs:n}=e,{dy:s,input:i}=t,{filterSize:p,strides:u,pad:c,dimRoundingMode:d}=n,f=a.backend_util.computePool3DInfo(i.shape,p,u,[1,1,1],c,d),m=new(0,l.Pool3DProgram)(f,"max",!0),h=r.runWebGLProgram(m,[i],i.dtype),g=new(0,o.MaxPool3DBackpropProgram)(f),x=r.runWebGLProgram(g,[s,h],i.dtype);return r.disposeIntermediateTensorInfo(h),x}let p={kernelName:a.MaxPool3DGrad,backendName:"webgl",kernelFunc:i}},{"@tensorflow/tfjs-core":"2Gtps","../max_pool_backprop_gpu":"QmnTE","../pool_gpu":"1JUNb","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],QmnTE:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"MaxPool2DBackpropProgram",()=>a),s.export(r,"MaxPool3DBackpropProgram",()=>o);class a{constructor(e){this.variableNames=["dy","maxPos"],this.outputShape=e.inShape;const t=e.strideHeight,r=e.strideWidth,n=e.dilationHeight,s=e.effectiveFilterHeight,a=e.effectiveFilterWidth,o=s-1-e.padInfo.top,l=a-1-e.padInfo.left;this.userCode=` const ivec2 pads = ivec2(${o}, ${l}); void main() { ivec4 coords = getOutputCoords(); int b = coords[0]; int d = coords[3]; ivec2 dyRCCorner = coords.yz - pads; int dyRCorner = dyRCCorner.x; int dyCCorner = dyRCCorner.y; // Convolve dy(?, ?, d) with pos mask(:, :, d) to get dx(xR, xC, d). // ? = to be determined. : = across all values in that axis. float dotProd = 0.0; for (int wR = 0; wR< ${s}; wR += ${n}) { float dyR = float(dyRCorner + wR) / ${t}.0; if (dyR < 0.0 || dyR >= ${e.outHeight}.0 || fract(dyR) > 0.0) { continue; } int idyR = int(dyR); for (int wC = 0; wC< ${a}; wC++) { float dyC = float(dyCCorner + wC) / ${r}.0; if (dyC < 0.0 || dyC >= ${e.outWidth}.0 || fract(dyC) > 0.0) { continue; } int idyC = int(dyC); float dyValue = getDy(b, idyR, idyC, d); int maxPosValue = ${s*a-1} - int(getMaxPos(b, idyR, idyC, d)); // Get the current value, check it against the value from the // position matrix. int curPosValue = wR * ${a} + wC; float mask = float(maxPosValue == curPosValue ? 1.0 : 0.0); dotProd += dyValue * mask; } } setOutput(dotProd); } `}}class o{constructor(e){this.variableNames=["dy","maxPos"],this.outputShape=e.inShape;const t=e.strideDepth,r=e.strideHeight,n=e.strideWidth,s=e.dilationDepth,a=e.dilationHeight,o=e.dilationWidth,l=e.effectiveFilterDepth,i=e.effectiveFilterHeight,p=e.effectiveFilterWidth,u=l-1-e.padInfo.front,c=i-1-e.padInfo.top,d=p-1-e.padInfo.left;this.userCode=` const ivec3 pads = ivec3(${u}, ${c}, ${d}); 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< ${l}; wD += ${s}) { float dyD = float(dyDCorner + wD) / ${t}.0; if (dyD < 0.0 || dyD >= ${e.outDepth}.0 || fract(dyD) > 0.0) { continue; } int idyD = int(dyD); for (int wR = 0; wR< ${i}; wR += ${a}) { float dyR = float(dyRCorner + wR) / ${r}.0; if (dyR < 0.0 || dyR >= ${e.outHeight}.0 || fract(dyR) > 0.0) { continue; } int idyR = int(dyR); for (int wC = 0; wC< ${p}; wC += ${o}) { float dyC = float(dyCCorner + wC) / ${n}.0; if (dyC < 0.0 || dyC >= ${e.outWidth}.0 || fract(dyC) > 0.0) { continue; } int idyC = int(dyC); float dyValue = getDy(batch, idyD, idyR, idyC, ch); int maxPosValue = ${l*i*p-1} - int(getMaxPos(batch, idyD, idyR, idyC, ch)); // Get the current value, check it against the value from the // position matrix. int curPosValue = wD * ${i} * ${p} + wR * ${p} + wC; float mask = float(maxPosValue == curPosValue ? 1.0 : 0.0); dotProd += dyValue * mask; } } } setOutput(dotProd); } `}}},{"@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],fOmt4:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"maxPoolGrad",()=>p),s.export(r,"maxPoolGradConfig",()=>u);var a=e("@tensorflow/tfjs-core"),o=e("../max_pool_backprop_gpu"),l=e("../pool_gpu"),i=e("../webgl_util");function p(e){let{inputs:t,backend:r,attrs:n}=e,{dy:s,input:p,output:u}=t;(0,i.assertNotComplex)([p,u],"maxPoolGrad");let{filterSize:c,strides:d,pad:f,dimRoundingMode:m}=n,h=a.backend_util.computePool2DInfo(p.shape,c,d,1,f,m),g=new(0,l.Pool2DProgram)(h,"max",!0),x=r.runWebGLProgram(g,[p],p.dtype),y=new(0,o.MaxPool2DBackpropProgram)(h),v=r.runWebGLProgram(y,[s,x],p.dtype);return r.disposeIntermediateTensorInfo(x),v}let u={kernelName:a.MaxPoolGrad,backendName:"webgl",kernelFunc:p}},{"@tensorflow/tfjs-core":"2Gtps","../max_pool_backprop_gpu":"QmnTE","../pool_gpu":"1JUNb","../webgl_util":"kBGlX","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],"1bzUD":[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"maxPoolWithArgmaxConfig",()=>l);var a=e("@tensorflow/tfjs-core"),o=e("./MaxPoolWithArgmax_impl");let l={kernelName:a.MaxPoolWithArgmax,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:r})=>{let{x:n}=e,{filterSize:s,strides:l,pad:i,includeBatchInIndex:p}=t;a.util.assert(4===n.shape.length,()=>`Error in maxPool: input must be rank 4 but got rank ${n.shape.length}.`);let u=[1,1];a.util.assert(a.backend_util.eitherStridesOrDilationsAreOne(l,u),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${l} and dilations '${u}'`);let c=a.backend_util.computePool2DInfo(n.shape,s,l,u,i),[d,f]=(0,o.maxPoolWithArgmaxImpl)(n,p,c,r);return[d,f]}}},{"@tensorflow/tfjs-core":"2Gtps","./MaxPoolWithArgmax_impl":"aMj9m","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],aMj9m:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"maxPoolWithArgmaxImpl",()=>o);var a=e("../pool_gpu");function o(e,t,r,n){let s=new(0,a.Pool2DProgram)(r,"max",!1),o=n.runWebGLProgram(s,[e],"float32");return s=new(0,a.Pool2DProgram)(r,"max",!0,!0,t),[o,n.runWebGLProgram(s,[e],"float32")]}},{"../pool_gpu":"1JUNb","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],"76W3Z":[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"meanConfig",()=>i);var a=e("@tensorflow/tfjs-core"),o=e("./Mean_impl"),l=e("./Transpose_impl");let i={kernelName:a.Mean,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:r})=>{let{x:n}=e,{keepDims:s,axis:i}=t,p=n.shape.length,u=a.util.parseAxisParam(i,n.shape),c=u,d=a.backend_util.getAxesPermutation(c,p),f=null!=d,m=r.shouldExecuteOnCPU([n]),h=[],g=n;if(f){if(m){let e=r.texData.get(g.dataId).values,t=Array(p);for(let e=0;e<t.length;e++)t[e]=n.shape[d[e]];let s=(0,l.transposeImplCPU)(e,n.shape,n.dtype,d,t);g=r.makeTensorInfo(t,n.dtype),r.texData.get(g.dataId).values=s}else g=(0,l.transposeImpl)(n,d,r);h.push(g),c=a.backend_util.getInnerMostAxes(c.length,p)}a.backend_util.assertAxesAreInnerMostDims("sum",c,p);let[x,y]=a.backend_util.computeOutAndReduceShapes(g.shape,c),v=x;s&&(v=a.backend_util.expandShapeToKeepDim(x,u));let b=(0,o.meanImpl)(g,y,v,r);for(let e of h)r.disposeIntermediateTensorInfo(e);return b}}},{"@tensorflow/tfjs-core":"2Gtps","./Mean_impl":"apcOt","./Transpose_impl":[["transposeImpl","3ouoc"],["transposeImplCPU","6ruDg"]],"@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],apcOt:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"meanImpl",()=>i);var a=e("@tensorflow/tfjs-core"),o=e("../kernel_utils/reduce"),l=e("../kernels/Reshape");function i(e,t,r,n){let s=a.util.sizeFromShape(t),i=a.util.sizeFromShape(e.shape),p=(0,l.reshape)({inputs:{x:e},attrs:{shape:[i/s,s]},backend:n}),u=(0,o.reduce)(p,"float32","mean",n),c=(0,l.reshape)({inputs:{x:u},attrs:{shape:r},backend:n});return n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(u),c}},{"@tensorflow/tfjs-core":"2Gtps","../kernel_utils/reduce":"gwlbf","../kernels/Reshape":"aOEE6","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],"1XKVy":[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"min",()=>p),s.export(r,"minConfig",()=>u);var a=e("@tensorflow/tfjs-core"),o=e("../kernel_utils/reduce"),l=e("./Reshape"),i=e("./Transpose");function p(e){let t,{inputs:r,backend:n,attrs:s}=e,{x:p}=r,{axis:u,keepDims:c}=s,d=p.shape.length,f=a.util.parseAxisParam(u,p.shape),m=f,h=a.backend_util.getAxesPermutation(m,d),g=p;null!=h&&(g=(0,i.transpose)({inputs:{x:p},backend:n,attrs:{perm:h}}),m=a.backend_util.getInnerMostAxes(m.length,p.shape.length)),a.backend_util.assertAxesAreInnerMostDims("min",m,d);let[x,y]=a.backend_util.computeOutAndReduceShapes(g.shape,m),v=a.util.sizeFromShape(y),b=(0,l.reshape)({inputs:{x:g},backend:n,attrs:{shape:[-1,v]}}),k=(0,o.reduce)(b,b.dtype,"min",n);if(c){let e=a.backend_util.expandShapeToKeepDim(x,f);t=(0,l.reshape)({inputs:{x:k},backend:n,attrs:{shape:e}})}else t=(0,l.reshape)({inputs:{x:k},backend:n,attrs:{shape:x}});return n.disposeIntermediateTensorInfo(b),n.disposeIntermediateTensorInfo(k),null!=h&&n.disposeIntermediateTensorInfo(g),t}let u={kernelName:a.Min,backendName:"webgl",kernelFunc:p}},{"@tensorflow/tfjs-core":"2Gtps","../kernel_utils/reduce":"gwlbf","./Reshape":"aOEE6","./Transpose":"lqCy7","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],jZlPa:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"minimum",()=>d),s.export(r,"minimumConfig",()=>f);var a=e("@tensorflow/tfjs-core"),o=e("../binaryop_gpu"),l=e("../binaryop_packed_gpu"),i=e("../kernel_utils/kernel_funcs_utils"),p=e("../kernel_utils/shared");let u=o.CHECK_NAN_SNIPPET+` return min(a, b); `,c=` vec4 result = vec4(min(a, b)); bvec4 isNaNA = isnan(a); bvec4 isNaNB = isnan(b); bvec4 isNaN = bvec4(isNaNA.x || isNaNB.x, isNaNA.y || isNaNB.y, isNaNA.z || isNaNB.z, isNaNA.w || isNaNB.w); `+l.CHECK_NAN_SNIPPET_PACKED+` return result; `,d=(0,i.binaryKernelFunc)({opSnippet:u,packedOpSnippet:c,cpuKernelImpl:p.minimumImplCPU}),f={kernelName:a.Minimum,backendName:"webgl",kernelFunc:d}},{"@tensorflow/tfjs-core":"2Gtps","../binaryop_gpu":"mK7ON","../binaryop_packed_gpu":"hyPKl","../kernel_utils/kernel_funcs_utils":"5oexO","../kernel_utils/shared":"6ruDg","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],akMJ7:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"mirrorPadKernelFunc",()=>i),s.export(r,"mirrorPadConfig",()=>p);var a=e("@tensorflow/tfjs-core"),o=e("../mirror_pad_gpu"),l=e("../mirror_pad_packed_gpu");let i=({inputs:e,backend:t,attrs:r})=>{let{x:n}=e,{paddings:s,mode:i}=r,p=(0,a.env)().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new(0,l.MirrorPadPackedProgram)(n.shape,s,i):new(0,o.MirrorPadProgram)(n.shape,s,i);return t.runWebGLProgram(p,[n],n.dtype)},p={kernelName:a.MirrorPad,backendName:"webgl",kernelFunc:i}},{"@tensorflow/tfjs-core":"2Gtps","../mirror_pad_gpu":"aE5py","../mirror_pad_packed_gpu":"58hA8","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],aE5py:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"MirrorPadProgram",()=>o);var a=e("./shader_compiler");class o{constructor(e,t,r){this.variableNames=["x"],this.outputShape=t.map((t,r)=>t[0]+e[r]+t[1]);const n=e.length,s=(0,a.getCoordsDataType)(n),o=t.map(e=>e[0]).join(","),l=t.map((t,r)=>t[0]+e[r]).join(","),i=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,n),p=+("reflect"!==r);if(1===n){this.userCode=` int start = ${o}; int end = ${l}; void main() { int outC = getOutputCoords(); if (outC< start) { outC = start * 2 - outC - ${p}; } else if(outC >= end) { outC = (end - 1) * 2 - outC + ${p}; } setOutput(getX(outC - start)); } `;return}this.userCode=` ${s} start = ${s}(${o}); ${s} end = ${s}(${l}); void main() { ${s} outC = getOutputCoords(); for (int i = 0; i< ${n}; i++) { if (outC[i] < start[i]) { outC[i] = start[i] * 2 - outC[i] - ${p}; } else if(outC[i] >= end[i]) { outC[i] = (end[i] - 1) * 2 - outC[i] + ${p}; } } ${s} coords = outC - start; setOutput(getX(${i})); } `}}},{"./shader_compiler":"gZjZZ","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],"58hA8":[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"MirrorPadPackedProgram",()=>l);var a=e("./packing_util"),o=e("./shader_compiler");class l{constructor(e,t,r){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=t.map((t,r)=>t[0]+e[r]+t[1]);const n=e.length,s=(0,o.getCoordsDataType)(n),l=t.map(e=>e[0]).join(","),i=t.map((t,r)=>t[0]+e[r]).join(","),p=(0,a.getChannels)("rc",n),u=(0,a.getChannels)("source",n),c=`${p[n-1]}< ${this.outputShape[n-1]}`,d=1===n?"source":`vec2(${u.slice(-2).join()})`,f=+("reflect"!==r);let m="";if(1===n){const e=` ${s} source = rc; 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c=(0,a.env)().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new(0,l.PadPackedProgram)(s.shape,p,u):new(0,o.PadProgram)(s.shape,p,u),d=[[u]];return r.runWebGLProgram(c,[s],s.dtype,d)},u={kernelName:a.PadV2,backendName:"webgl",kernelFunc:p}},{"@tensorflow/tfjs-core":"2Gtps","../pad_gpu":"hRZTO","../pad_packed_gpu":"aq7Wf","./Fill":"9ryy3","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],hRZTO:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"PadProgram",()=>o);var a=e("./shader_compiler");class o{constructor(e,t,r){this.variableNames=["x"],this.customUniforms=[{name:"value",type:"float"}],this.outputShape=t.map((t,r)=>t[0]+e[r]+t[1]);const n=e.length,s=(0,a.getCoordsDataType)(n),o=t.map(e=>e[0]).join(","),l=t.map((t,r)=>t[0]+e[r]).join(","),i=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,n);if(1===n){this.userCode=` int start = ${o}; int end = ${l}; void main() { int outC = getOutputCoords(); if (outC< start || 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result.b = isExpZero.b ? 1.0 : result.b; result.a = isExpZero.a ? 1.0 : result.a; bvec4 isNaN1 = lessThan(a, vec4(0.0)); bvec4 isNaN2 = lessThan(floor(b), b); bvec4 isNaN = bvec4(isNaN1.x && isNaN2.x, isNaN1.y && isNaN2.y, isNaN1.z && isNaN2.z, isNaN1.w && isNaN2.w); `+o.CHECK_NAN_SNIPPET_PACKED+` return result; `,u=(0,l.binaryKernelFunc)({opSnippet:i,packedOpSnippet:p}),c={kernelName:a.Pow,backendName:"webgl",kernelFunc:u}},{"@tensorflow/tfjs-core":"2Gtps","../binaryop_packed_gpu":"hyPKl","../kernel_utils/kernel_funcs_utils":"5oexO","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],i8gle:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"prod",()=>u),s.export(r,"prodConfig",()=>c);var a=e("@tensorflow/tfjs-core"),o=e("../kernel_utils/reduce"),l=e("../kernel_utils/shared"),i=e("./Reshape"),p=e("./Transpose");function u(e){let t,{inputs:r,backend:n,attrs:s}=e,{x:u}=r,{axis:c,keepDims:d}=s,f=u.shape.length,m=[],h=a.util.parseAxisParam(c,u.shape),g=h,x=a.backend_util.getAxesPermutation(g,f),y=u;if(null!=x&&(y=(0,p.transpose)({inputs:{x:u},backend:n,attrs:{perm:x}}),g=a.backend_util.getInnerMostAxes(g.length,f),m.push(y)),a.backend_util.assertAxesAreInnerMostDims("prod",g,f),n.shouldExecuteOnCPU([y])){let e=n.texData.get(y.dataId).values,{outVals:r,outShape:s,outDtype:a}=(0,l.prodImplCPU)(y.shape,y.dtype,e,g);t=n.makeTensorInfo(s,a,r)}else{let[e,r]=a.backend_util.computeOutAndReduceShapes(y.shape,g),s=a.util.sizeFromShape(r),l=(0,i.reshape)({inputs:{x:y},backend:n,attrs:{shape:[-1,s]}}),p=(0,a.sumOutType)(u.dtype),c=(0,o.reduce)(l,p,"prod",n);t=(0,i.reshape)({inputs:{x:c},backend:n,attrs:{shape:e}}),m.push(l),m.push(c)}if(d){m.push(t);let e=a.backend_util.expandShapeToKeepDim(t.shape,h);t=(0,i.reshape)({inputs:{x:t},backend:n,attrs:{shape:e}})}return m.forEach(e=>n.disposeIntermediateTensorInfo(e)),t}let c={kernelName:a.Prod,backendName:"webgl",kernelFunc:u}},{"@tensorflow/tfjs-core":"2Gtps","../kernel_utils/reduce":"gwlbf","../kernel_utils/shared":"6ruDg","./Reshape":"aOEE6","./Transpose":"lqCy7","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],"9WlaC":[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"raggedGather",()=>l),s.export(r,"raggedGatherConfig",()=>i);var a=e("@tensorflow/tfjs-core"),o=e("../kernel_utils/shared");function l(e){let{inputs:t,backend:r,attrs:n}=e,{paramsNestedSplits:s,paramsDenseValues:a,indices:l}=t,{outputRaggedRank:i}=n,p=s.map(e=>r.readSync(e.dataId)),u=s.map(e=>e.shape),c=r.readSync(a.dataId),d=r.readSync(l.dataId),[f,m,h]=(0,o.raggedGatherImplCPU)(p,u,c,a.shape,a.dtype,d,l.shape,i),g=f.map(e=>r.makeTensorInfo([e.length],"int32",e)),x=r.makeTensorInfo(h,a.dtype,m);return g.concat([x])}let i={kernelName:a.RaggedGather,backendName:"webgl",kernelFunc:l}},{"@tensorflow/tfjs-core":"2Gtps","../kernel_utils/shared":"6ruDg","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],"6frqk":[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"raggedRange",()=>l),s.export(r,"raggedRangeConfig",()=>i);var a=e("@tensorflow/tfjs-core"),o=e("../kernel_utils/shared");function l(e){let{inputs:t,backend:r}=e,{starts:n,limits:s,deltas:a}=t,l=r.readSync(n.dataId),i=r.readSync(s.dataId),p=r.readSync(a.dataId),[u,c]=(0,o.raggedRangeImplCPU)(l,n.shape,n.dtype,i,s.shape,p,a.shape);return[r.makeTensorInfo([u.length],"int32",u),r.makeTensorInfo([c.length],n.dtype,c)]}let i={kernelName:a.RaggedRange,backendName:"webgl",kernelFunc:l}},{"@tensorflow/tfjs-core":"2Gtps","../kernel_utils/shared":"6ruDg","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],"9QHo7":[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"raggedTensorToTensor",()=>l),s.export(r,"raggedTensorToTensorConfig",()=>i);var a=e("@tensorflow/tfjs-core"),o=e("../kernel_utils/shared");function l(e){let{inputs:t,backend:r,attrs:n}=e,{shape:s,values:a,defaultValue:l,rowPartitionTensors:i}=t,{rowPartitionTypes:p}=n,u=r.readSync(s.dataId),c=r.readSync(a.dataId),d=r.readSync(l.dataId),f=i.map(e=>r.readSync(e.dataId)),m=i.map(e=>e.shape),[h,g]=(0,o.raggedTensorToTensorImplCPU)(u,s.shape,c,a.shape,a.dtype,d,l.shape,f,m,p);return r.makeTensorInfo(h,a.dtype,g)}let i={kernelName:a.RaggedTensorToTensor,backendName:"webgl",kernelFunc:l}},{"@tensorflow/tfjs-core":"2Gtps","../kernel_utils/shared":"6ruDg","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],h4DwD:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"range",()=>l),s.export(r,"rangeConfig",()=>i);var a=e("@tensorflow/tfjs-core"),o=e("../kernel_utils/shared");let l=e=>{let{backend:t,attrs:r}=e,{start:n,stop:s,step:a,dtype:l}=r,i=(0,o.rangeImplCPU)(n,s,a,l);return t.makeTensorInfo([i.length],l,i)},i={kernelName:a.Range,backendName:"webgl",kernelFunc:l}},{"@tensorflow/tfjs-core":"2Gtps","../kernel_utils/shared":"6ruDg","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],cW4of:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"reciprocal",()=>o),s.export(r,"reciprocalConfig",()=>l);var a=e("@tensorflow/tfjs-core");let o=(0,e("../kernel_utils/kernel_funcs_utils").unaryKernelFunc)({opSnippet:"return 1.0 / x;"}),l={kernelName:a.Reciprocal,backendName:"webgl",kernelFunc:o}},{"@tensorflow/tfjs-core":"2Gtps","../kernel_utils/kernel_funcs_utils":"5oexO","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],fD5Nl:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"relu",()=>p),s.export(r,"reluConfig",()=>u);var a=e("@tensorflow/tfjs-core"),o=e("../kernel_utils/kernel_funcs_utils");let l=e("../unaryop_gpu").CHECK_NAN_SNIPPET+` return (x< 0.0) ? 0.0 : x; `,i=` 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; `,p=(0,o.unaryKernelFunc)({opSnippet:l,packedOpSnippet:i}),u={kernelName:a.Relu,backendName:"webgl",kernelFunc:p}},{"@tensorflow/tfjs-core":"2Gtps","../kernel_utils/kernel_funcs_utils":"5oexO","../unaryop_gpu":"byMKQ","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],fJ8FQ:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"relu6",()=>p),s.export(r,"relu6Config",()=>u);var a=e("@tensorflow/tfjs-core"),o=e("../kernel_utils/kernel_funcs_utils");let l=e("../unaryop_gpu").CHECK_NAN_SNIPPET+` return (x< 0.0) ? 0.0 : min(6.0, x); `,i=` 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; `,p=(0,o.unaryKernelFunc)({opSnippet:l,packedOpSnippet:i}),u={kernelName:a.Relu6,backendName:"webgl",kernelFunc:p}},{"@tensorflow/tfjs-core":"2Gtps","../kernel_utils/kernel_funcs_utils":"5oexO","../unaryop_gpu":"byMKQ","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],"50UZz":[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"resizeBilinear",()=>i),s.export(r,"resizeBilinearConfig",()=>p);var a=e("@tensorflow/tfjs-core"),o=e("../resize_bilinear_gpu"),l=e("../resize_bilinear_packed_gpu");function i(e){let{inputs:t,backend:r,attrs:n}=e,{images:s}=t,{alignCorners:i,halfPixelCenters:p,size:u}=n,[c,d]=u,f=(0,a.env)().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new(0,l.ResizeBilinearPackedProgram)(s.shape,c,d,i,p):new(0,o.ResizeBilinearProgram)(s.shape,c,d,i,p);return r.runWebGLProgram(f,[s],"float32")}let p={kernelName:a.ResizeBilinear,backendName:"webgl",kernelFunc:i}},{"@tensorflow/tfjs-core":"2Gtps","../resize_bilinear_gpu":"alDcg","../resize_bilinear_packed_gpu":"f4ege","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],alDcg:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"ResizeBilinearProgram",()=>a);class a{constructor(e,t,r,n,s){this.variableNames=["A"],this.outputShape=[];const[a,o,l,i]=e;this.outputShape=[a,t,r,i];const p=[n&&t>1?o-1:o,n&&r>1?l-1:l],u=[n&&t>1?t-1:t,n&&r>1?r-1:r];this.userCode=` const vec2 effectiveInputOverOutputRatioRC = vec2( ${p[0]/u[0]}, ${p[1]/u[1]}); const vec2 inputShapeRC = vec2(${o}.0, ${l}.0); void main() { ivec4 coords = getOutputCoords(); int b = coords[0]; int d = coords[3]; ivec2 yRC = coords.yz; // Fractional source index. vec2 sourceFracIndexRC = ${s?"(vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC - vec2(0.5)":"vec2(yRC) * effectiveInputOverOutputRatioRC"}; // 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); } `}}},{"@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],f4ege:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"ResizeBilinearPackedProgram",()=>a);class a{constructor(e,t,r,n,s){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[];const[a,o,l,i]=e;this.outputShape=[a,t,r,i];const p=[n&&t>1?o-1:o,n&&r>1?l-1:l],u=[n&&t>1?t-1:t,n&&r>1?r-1:r];this.userCode=` const vec3 effectiveInputOverOutputRatioRC = vec3( ${p[0]/u[0]}, ${p[1]/u[1]}, ${p[1]/u[1]}); const vec3 inputShapeRC = vec3(${o}.0, ${l}.0, ${l}.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 = ${s?"(vec3(yRC) + vec3(0.5)) * effectiveInputOverOutputRatioRC - vec3(0.5)":"vec3(yRC) * effectiveInputOverOutputRatioRC"}; // 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< ${i-1}; bool hasNextRow = coords.z < ${r-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); } `}}},{"@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],"9CnrH":[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"resizeBilinearGrad",()=>l),s.export(r,"resizeBilinearGradConfig",()=>i);var a=e("@tensorflow/tfjs-core"),o=e("../resize_bilinear_backprop_gpu");function l(e){let{inputs:t,backend:r,attrs:n}=e,{images:s,dy:a}=t,{alignCorners:l}=n,i=new(0,o.ResizeBilinearBackpropProgram)(a.shape,s.shape,l);return r.runWebGLProgram(i,[a],a.dtype)}let i={kernelName:a.ResizeBilinearGrad,backendName:"webgl",kernelFunc:l}},{"@tensorflow/tfjs-core":"2Gtps","../resize_bilinear_backprop_gpu":"ddFJt","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],ddFJt:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"ResizeBilinearBackpropProgram",()=>a);class a{constructor(e,t,r){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t;const[,n,s]=t,[,a,o]=e,l=[r&&a>1?n-1:n,r&&o>1?s-1:s],i=[r&&a>1?a-1:a,r&&o>1?o-1:o],p=l[0]/i[0],u=l[1]/i[1],c=1/p,d=1/u,f=2*Math.ceil(c)+2,m=2*Math.ceil(d)+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(${p}); const float widthScale = float(${u}); const float invHeightScale = float(${c}); const float invWidthScale = float(${d}); const int winHeight = int(${f}); const int winWidth = int(${m}); // Compute bounds for where in dy we will look float startRLerp = floor(float(r) * invHeightScale); int startDyR = int(startRLerp - float(winHeight / 2)); float startCLerp = floor(float(c) * invWidthScale); int startDyC = int(startCLerp - float(winWidth / 2)); // Loop over dy for (int dyROffset = 0; dyROffset< winHeight; dyROffset++) { int dyR = dyROffset + startDyR; // Guard against the window exceeding the bounds of dy if (dyR < 0 || dyR >= ${a}) { continue; } for (int dyCOffset = 0; dyCOffset< winWidth; dyCOffset++) { int dyC = dyCOffset + startDyC; // Guard against the window exceeding the bounds of dy if (dyC < 0 || dyC >= ${o}) { continue; } float dxR = float(dyR) * heightScale; int topDxRIndex = int(floor(dxR)); int bottomDxRIndex = int(min(ceil(dxR), ${n-1}.0)); float dxRLerp = dxR - float(topDxRIndex); float inverseDxRLerp = 1.0 - dxRLerp; float dxC = float(dyC) * widthScale; int leftDxCIndex = int(floor(dxC)); int rightDxCIndex = int(min(ceil(dxC), ${s-1}.0)); float dxCLerp = dxC - float(leftDxCIndex); float inverseDxCLerp = 1.0 - dxCLerp; if (r == topDxRIndex && c == leftDxCIndex) { // topLeft accumulator += getDy(b, dyR, dyC, d) * inverseDxRLerp * inverseDxCLerp; } if (r == topDxRIndex && c == rightDxCIndex) { // topRight accumulator += getDy(b, dyR, dyC, d) * inverseDxRLerp * dxCLerp; } if (r == bottomDxRIndex && c == leftDxCIndex) { // bottomLeft accumulator += getDy(b, dyR, dyC, d) * dxRLerp * inverseDxCLerp; } if (r == bottomDxRIndex && c == rightDxCIndex) { // bottomRight accumulator += getDy(b, dyR, dyC, d) * dxRLerp * dxCLerp; } } } // End loop over dy setOutput(accumulator); } `}}},{"@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],g9ks1:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"resizeNearestNeighbor",()=>i),s.export(r,"resizeNearestNeighborConfig",()=>p);var a=e("@tensorflow/tfjs-core"),o=e("../resize_nearest_neighbor_gpu"),l=e("../resize_nearest_neighbor_packed_gpu");function i(e){let{inputs:t,backend:r,attrs:n}=e,{images:s}=t,{alignCorners:i,halfPixelCenters:p,size:u}=n,[c,d]=u,f=(0,a.env)().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new(0,l.ResizeNearestNeighborPackedProgram)(s.shape,c,d,i,p):new(0,o.ResizeNearestNeighborProgram)(s.shape,c,d,i,p);return r.runWebGLProgram(f,[s],s.dtype)}let p={kernelName:a.ResizeNearestNeighbor,backendName:"webgl",kernelFunc:i}},{"@tensorflow/tfjs-core":"2Gtps","../resize_nearest_neighbor_gpu":"iOaTB","../resize_nearest_neighbor_packed_gpu":"8Lhcl","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],iOaTB:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"ResizeNearestNeighborProgram",()=>a);class a{constructor(e,t,r,n,s){this.variableNames=["A"],this.outputShape=[];const[a,o,l,i]=e;this.outputShape=[a,t,r,i];const p=[n&&t>1?o-1:o,n&&r>1?l-1:l],u=[n&&t>1?t-1:t,n&&r>1?r-1:r];this.userCode=` const vec2 effectiveInputOverOutputRatioRC = vec2( ${p[0]/u[0]}, ${p[1]/u[1]}); const vec2 inputShapeRC = vec2(${o}.0, ${l}.0); void main() { ivec4 coords = getOutputCoords(); int b = coords[0]; int d = coords[3]; ivec2 yRC = coords.yz; // Fractional source index. vec2 sourceFracIndexRC = ${s?"max((vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC, vec2(0.0))":"vec2(yRC) * effectiveInputOverOutputRatioRC"}; // Compute the coordinators of nearest neighbor point. ivec2 sourceNearestRC = ivec2( min(inputShapeRC - 1.0, floor(sourceFracIndexRC + ${n?"0.5":"0.0"}))); float newValue = getA(b, sourceNearestRC.x, sourceNearestRC.y, d); setOutput(newValue); } `}}},{"@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],"8Lhcl":[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"ResizeNearestNeighborPackedProgram",()=>a);class a{constructor(e,t,r,n,s){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[];const[a,o,l,i]=e;this.outputShape=[a,t,r,i];const p=[n&&t>1?o-1:o,n&&r>1?l-1:l],u=[n&&t>1?t-1:t,n&&r>1?r-1:r];this.userCode=` const vec3 effectiveInputOverOutputRatioRC = vec3( ${p[0]/u[0]}, ${p[1]/u[1]}, ${p[1]/u[1]}); const vec3 inputShapeRC = vec3(${o}.0, ${l}.0, ${l}.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 = ${s?"max((vec3(yRC) + vec3(0.5)) * effectiveInputOverOutputRatioRC, vec3(0.0))":"vec3(yRC) * effectiveInputOverOutputRatioRC"}; // Compute the coordinators of nearest neighbor point. ivec3 sourceNearestRC = ivec3( min(inputShapeRC - 1.0, floor(sourceFracIndexRC + ${n?"0.5":"0.0"}))); // Should we calculate next column and row elements in 2x2 packed cell. bool hasNextCol = d< ${i-1}; bool hasNextRow = coords.z < ${r-1}; vec4 newValue = vec4( getAValue(b, sourceNearestRC.x, sourceNearestRC.y, d), hasNextCol ? getAValue(b, sourceNearestRC.x, sourceNearestRC.y, d + 1) : 0.0, hasNextRow ? getAValue(b, sourceNearestRC.x, sourceNearestRC.z, d) : 0.0, (hasNextRow && hasNextCol) ? getAValue(b, sourceNearestRC.x, sourceNearestRC.z, d + 1) : 0.0); setOutput(newValue); } `}}},{"@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],bi2fw:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"resizeNearestNeighborGrad",()=>l),s.export(r,"resizeNearestNeighborGradConfig",()=>i);var a=e("@tensorflow/tfjs-core"),o=e("../resize_nearest_neighbor_backprop_gpu");function l(e){let{inputs:t,backend:r,attrs:n}=e,{images:s,dy:a}=t,{alignCorners:l}=n,i=new(0,o.ResizeNearestNeigborBackpropProgram)(a.shape,s.shape,l);return r.runWebGLProgram(i,[a],a.dtype)}let i={kernelName:a.ResizeNearestNeighborGrad,backendName:"webgl",kernelFunc:l}},{"@tensorflow/tfjs-core":"2Gtps","../resize_nearest_neighbor_backprop_gpu":"13qX0","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],"13qX0":[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"ResizeNearestNeigborBackpropProgram",()=>a);class a{constructor(e,t,r){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t;const[,n,s]=t,[,a,o]=e,l=[r&&a>1?n-1:n,r&&o>1?s-1:s],i=[r&&a>1?a-1:a,r&&o>1?o-1:o],p=l[0]/i[0],u=l[1]/i[1],c=1/p,d=1/u,f=2*Math.ceil(c)+2,m=2*Math.ceil(d)+2;this.userCode=` void main() { ivec4 coords = getOutputCoords(); int b = coords[0]; int d = coords[3]; int r = coords[1]; int c = coords[2]; float accumulator = 0.0; const float heightScale = float(${p}); const float widthScale = float(${u}); const float invHeightScale = float(${c}); const float invWidthScale = float(${d}); const int winHeight = int(${f}); const int winWidth = int(${m}); // Compute bounds for where in dy we will look float startRLerp = floor(float(r) * invHeightScale); int startDyR = int(floor(startRLerp - float(winHeight / 2))); float startCLerp = floor(float(c) * invWidthScale); int startDyC = int(floor(startCLerp - float(winWidth / 2))); // Loop over dy for (int dyROffset = 0; dyROffset< winHeight; dyROffset++) { int dyR = dyROffset + startDyR; // Guard against the window exceeding the bounds of dy if (dyR < 0 || dyR >= ${a}) { continue; } for (int dyCOffset = 0; dyCOffset< winWidth; dyCOffset++) { int dyC = dyCOffset + startDyC; // Guard against the window exceeding the bounds of dy if (dyC < 0 || dyC >= ${o}) { continue; } float sourceFracRow = float(${l[0]}) * (float(dyR) / float(${i[0]})); float sourceFracCol = float(${l[1]}) * (float(dyC) / float(${i[1]})); int sourceNearestRow = int(min( float(int(${n}) - 1), ${r} ? float(round(sourceFracRow)) : float(floor(sourceFracRow)))); int sourceNearestCol = int(min( float(int(${s}) - 1), ${r} ? float(round(sourceFracCol)) : float(floor(sourceFracCol)))); if (r == sourceNearestRow && c == sourceNearestCol) { accumulator += getDy(b, dyR, dyC, d); } } } // End loop over dy setOutput(accumulator); } `}}},{"@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],ltUYd:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"reverse",()=>p),s.export(r,"reverseConfig",()=>u);var a=e("@tensorflow/tfjs-core"),o=e("../reverse_gpu"),l=e("../reverse_packed_gpu"),i=e("./Identity");function p(e){let{inputs:t,backend:r,attrs:n}=e,{x:s}=t,{dims:p}=n,u=s.shape.length,c=a.util.parseAxisParam(p,s.shape);if(0===u)return(0,i.identity)({inputs:{x:s},backend:r});let d=(0,a.env)().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new(0,l.ReversePackedProgram)(s.shape,c):new(0,o.ReverseProgram)(s.shape,c);return r.runWebGLProgram(d,[s],s.dtype)}let u={kernelName:a.Reverse,backendName:"webgl",kernelFunc:p}},{"@tensorflow/tfjs-core":"2Gtps","../reverse_gpu":"43jwk","../reverse_packed_gpu":"k8Am5","./Identity":"97wVJ","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],"43jwk":[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"ReverseProgram",()=>o);var a=e("./shader_compiler");class o{constructor(e,t){this.variableNames=["x"];const r=e.length;if(r>4)throw Error(`WebGL backend: Reverse of rank-${r} tensor is not yet supported`);if(this.outputShape=e,1===r){this.userCode=` void main() { int coord = getOutputCoords(); setOutput(getX(${e[0]} - coord - 1)); } `;return}const n=e.map((r,n)=>-1!==t.indexOf(n)&&1!==e[n]?`${e[n]} - coords[${n}] - 1`:`coords[${n}]`).join(","),s=(0,a.getCoordsDataType)(r);this.userCode=` void main() { ${s} coords = getOutputCoords(); setOutput(getX(${n})); } `}}},{"./shader_compiler":"gZjZZ","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],k8Am5:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"ReversePackedProgram",()=>l);var a=e("./packing_util"),o=e("./shader_compiler");class l{constructor(e,t){this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0;const r=e.length;if(r>4)throw Error(`WebGL backend: Reverse of rank-${r} tensor is not yet supported`);this.outputShape=e;const n=(0,a.getChannels)("rc",r),s=`${n[r-1]} + 1< ${this.outputShape[r-1]}`,l=`${n[r-2]} + 1 < ${this.outputShape[r-2]}`,i=(0,o.getCoordsDataType)(r);function p(r){let n=e.map((n,s)=>{var a,o;return a=s,o=r,-1!==t.indexOf(a)&&1!==e[a]?`${e[a]} - ${o[a]} - 1`:`${o[a]}`}),s=n.join(","),a=n.slice(-2).join(",");return`getChannel(getX(${s}), vec2(${a}))`}1===r?this.userCode=` void main(){ int rc = getOutputCoords(); vec4 result = vec4(0.); result.r = getChannel(getX(${e[0]} - rc - 1), ${e[0]} - rc - 1); if(${s}){ result.g = getChannel(getX(${e[0]} - (rc + 1) - 1), ${e[0]} - (rc + 1) - 1); } setOutput(result); } `:this.userCode=` void main() { ${i} rc = getOutputCoords(); vec4 result = vec4(0.); result.r = ${p(n.slice())}; if(${s}){ result.g = ${function(e){return e[r-1]="("+e[r-1]+" + 1)",p(e)}(n.slice())}; } if(${l}) { result.b = ${function(e){return e[r-2]="("+e[r-2]+" + 1)",p(e)}(n.slice())}; if(${s}) { result.a = ${function(e){return e[r-1]="("+e[r-1]+" + 1)",e[r-2]="("+e[r-2]+" + 1)",p(e)}(n.slice())}; } } setOutput(result); } `}}},{"./packing_util":"esmZC","./shader_compiler":"gZjZZ","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],ct6xT:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"rotateWithOffsetConfig",()=>l);var a=e("@tensorflow/tfjs-core"),o=e("../rotate_gpu");let l={kernelName:a.RotateWithOffset,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:r})=>{let{image:n}=e,{radians:s,fillValue:l,center:i}=t,p=new(0,o.RotateProgram)(n.shape,l),[u,c]=a.backend_util.getImageCenter(i,n.shape[1],n.shape[2]),d=[[u,c,Math.sin(s),Math.cos(s)]];return r.runWebGLProgram(p,[n],n.dtype,d)}}},{"@tensorflow/tfjs-core":"2Gtps","../rotate_gpu":"9ECEy","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],"9ECEy":[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"RotateProgram",()=>a);class a{constructor(e,t){this.variableNames=["Image"],this.outputShape=[],this.customUniforms=[{name:"params",type:"vec4"}];const r=e[1],n=e[2];this.outputShape=e;let s="";s="number"==typeof t?`float outputValue = ${t.toFixed(2)};`:` vec3 fill = vec3(${t.join(",")}); float outputValue = fill[coords[3]];`,this.userCode=` void main() { ivec4 coords = getOutputCoords(); int x = coords[2]; int y = coords[1]; float coordXFloat = (float(x) - params[0]) * params[3] - (float(y) - params[1]) * params[2]; float coordYFloat = (float(x) - params[0]) * params[2] + (float(y) - params[1]) * params[3]; int coordX = int(round(coordXFloat + params[0])); int coordY = int(round(coordYFloat + params[1])); ${s} if(coordX >= 0 && coordX< ${n} && coordY >= 0 && coordY< ${r}) { outputValue = getImage(coords[0], coordY, coordX, coords[3]); } setOutput(outputValue); } `}}},{"@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],guuD3:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"round",()=>i),s.export(r,"roundConfig",()=>p);var a=e("@tensorflow/tfjs-core"),o=e("../kernel_utils/kernel_funcs_utils");let l=` // 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; } } `,i=(0,o.unaryKernelFunc)({opSnippet:l}),p={kernelName:a.Round,backendName:"webgl",kernelFunc:i}},{"@tensorflow/tfjs-core":"2Gtps","../kernel_utils/kernel_funcs_utils":"5oexO","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],cEMqB:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"rsqrt",()=>i),s.export(r,"rsqrtConfig",()=>p);var a=e("@tensorflow/tfjs-core"),o=e("../kernel_utils/kernel_funcs_utils"),l=e("../kernel_utils/shared");let i=(0,o.unaryKernelFunc)({opSnippet:"return inversesqrt(x);",cpuKernelImpl:l.rsqrtImplCPU}),p={kernelName:a.Rsqrt,backendName:"webgl",kernelFunc:i}},{"@tensorflow/tfjs-core":"2Gtps","../kernel_utils/kernel_funcs_utils":"5oexO","../kernel_utils/shared":"6ruDg","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],"71HHv":[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"scatterNd",()=>p),s.export(r,"scatterNdConfig",()=>u);var a=e("@tensorflow/tfjs-core"),o=e("../scatter_gpu"),l=e("../scatter_packed_gpu"),i=e("./Reshape");function p(e){let t,{inputs:r,backend:n,attrs:s}=e,{indices:p,updates:u}=r,{shape:c}=s,{sliceRank:d,numUpdates:f,sliceSize:m,strides:h,outputSize:g}=a.backend_util.calculateShapes(u,p,c),x=[g/m,m];if(0===g)return n.makeTensorInfo(c,p.dtype);let y=(0,i.reshape)({inputs:{x:p},backend:n,attrs:{shape:[f,d]}}),v=(0,i.reshape)({inputs:{x:u},backend:n,attrs:{shape:[f,m]}}),b=n.makeTensorInfo([],"float32",new Float32Array([0]));t=(0,a.env)().getBool("WEBGL_PACK")?new(0,l.ScatterPackedProgram)(f,d,y.shape.length,v.shape.length,h,x):new(0,o.ScatterProgram)(f,d,y.shape.length,v.shape.length,h,x);let k=n.runWebGLProgram(t,[v,y,b],v.dtype),_=(0,i.reshape)({inputs:{x:k},backend:n,attrs:{shape:c}});return n.disposeIntermediateTensorInfo(y),n.disposeIntermediateTensorInfo(v),n.disposeIntermediateTensorInfo(k),n.disposeIntermediateTensorInfo(b),_}let u={kernelName:a.ScatterNd,backendName:"webgl",kernelFunc:p}},{"@tensorflow/tfjs-core":"2Gtps","../scatter_gpu":"axeQc","../scatter_packed_gpu":"18Lp3","./Reshape":"aOEE6","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],axeQc:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"ScatterProgram",()=>o);var 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s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"ScatterPackedProgram",()=>o);var a=e("./shader_compiler");class o{constructor(e,t,r,n,s,o,l=!0,i=!1){this.variableNames=["updates","indices","defaultValue"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=o;const p=(0,a.getCoordsDataType)(s.length),u=(0,a.getCoordsDataType)(o.length);let c="";1===r?c="i":2===r&&(c="i, j");const d=`getIndices(${c})`;let f="";1===n?f="i":2===n&&(f="i, coords[1]");const m=`getUpdates(${f})`;let h="";i&&(h="coords[0], coords[1]");const g=`getDefaultValue(${h})`;this.userCode=` ${p} strides = ${p}(${s}); void main() { ${u} coords = getOutputCoords(); vec4 sum = vec4(0.); vec4 found = vec4(0.); for (int i = 0; i< ${e}; i+=2) { ivec2 flattenedIndex = ivec2(0); for (int j = 0; j < ${t}; j+=2) { ivec4 index = round(${d}); flattenedIndex += index.xz * ${t>1?"strides[j]":"strides"}; if (j + 1< ${t}) { flattenedIndex += index.yw * ${t>1?"strides[j + 1]":"strides"}; 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i={kernelName:a.StringSplit,backendName:"webgl",kernelFunc:l}},{"@tensorflow/tfjs-core":"2Gtps","../kernel_utils/shared":"6ruDg","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],dp2Po:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"stringToHashBucketFast",()=>l),s.export(r,"stringToHashBucketFastConfig",()=>i);var a=e("@tensorflow/tfjs-core"),o=e("../kernel_utils/shared");function l(e){let{inputs:t,backend:r,attrs:n}=e,{numBuckets:s}=n,{input:a}=t;if("string"!==a.dtype)throw Error("Input must be of datatype string");if(s<=0)throw Error("Number of buckets must be at least 1");let l=r.readSync(a.dataId),i=(0,o.stringToHashBucketFastImplCPU)(l,s);return r.makeTensorInfo(a.shape,"int32",i)}let i={kernelName:a.StringToHashBucketFast,backendName:"webgl",kernelFunc:l}},{"@tensorflow/tfjs-core":"2Gtps","../kernel_utils/shared":"6ruDg","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],jW0aV:[function(e,t,r,n){var 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i(e){let{inputs:t,backend:r,attrs:n}=e,{x:s}=t,{reps:i}=n;if("string"===s.dtype||s.shape.length>5){let e=r.readSync(s.dataId),t="string"===s.dtype?e.map(e=>a.util.decodeString(e)):e,n=(0,a.buffer)(s.shape,s.dtype,t),l=(0,o.tileImplCPU)(n,i);return r.makeTensorInfo(l.shape,l.dtype,l.values)}let p=new(0,l.TileProgram)(s.shape,i);return r.runWebGLProgram(p,[s],s.dtype)}let p={kernelName:a.Tile,backendName:"webgl",kernelFunc:i}},{"@tensorflow/tfjs-core":"2Gtps","../kernel_utils/shared":"6ruDg","../tile_gpu":"hjZSH","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],hjZSH:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"TileProgram",()=>o);var a=e("./shader_compiler");class o{constructor(e,t){this.variableNames=["A"];const r=Array(e.length);for(let n=0;n<r.length;n++)r[n]=e[n]*t[n];this.outputShape=r,this.rank=r.length;const n=(0,a.getCoordsDataType)(this.rank),s=function(e){let t=e.length;if(t>5)throw Error(`Tile for 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s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"SwapProgram",()=>a),s.export(r,"MergeProgram",()=>o);class a{constructor(e){this.variableNames=["x","indices"],this.customUniforms=[{name:"n",type:"int"},{name:"firstPass",type:"int"},{name:"negativeInf",type:"float"},{name:"dir",type:"int"},{name:"inc",type:"int"}],this.outputShape=e,this.userCode=` void main() { ivec2 coords = getOutputCoords(); int batch = coords[0]; int elemIdx = coords[1]; // We compare elements pair-wise within a group of size 2 * inc. // The comparing rule for each group alternates between ascending // and descending. Within each group, we compare each pair at // positions i and i+inc. To decide whether an element at position i // is x0 or x1, we mod it by 2 * inc, if the result is smaller than // inc, it is in the first half of the group, we denote it as x0, // otherwise we denote it as x1. // For example, as shown in the Bitonic top K paper referenced above, // Figure5(a) shows that element[1] is in the // second half of the group when group size is 2, but it is in the // first half of the group when group size is 4. bool isFirstInPair = imod(elemIdx, 2 * inc)< inc; int i = isFirstInPair ? elemIdx : elemIdx - inc; int i0 = firstPass == 1 ? i : int(getIndices(batch, i)); int i1 = firstPass == 1 ? i + inc : int(getIndices(batch, i + inc)); float x0 = i0 < n ? getX(batch, i0) : negativeInf; float x1 = i1 < n ? getX(batch, i1) : negativeInf; // Denotes which direction indices are in (ascending or descending). bool reverse = imod(elemIdx, 2 * dir) >= dir; bool isGreater = x0 > x1 || (x0 == x1 && i1 > i0); if (reverse == isGreater) { // Elements in opposite order of direction int iTemp = i0; i0 = i1; i1 = iTemp; } if (isFirstInPair) { setOutput(float(i0)); } else { setOutput(float(i1)); } } `}}class o{constructor(e){this.variableNames=["x","indices"],this.customUniforms=[{name:"n",type:"int"},{name:"firstPass",type:"int"},{name:"k",type:"int"}],this.outputShape=e,this.userCode=` void main() { // Takes max of indices (0, k), (1, k + 1), (2, k + 2) ... ivec2 coords = getOutputCoords(); int batch = coords[0]; int elemIdx = coords[1]; // The output size is half of the previous size. // If the previous sequence is | | | | _ _ _ _ | | | | _ _ _ _ (k=4), // we only need to output the indices at positions |, the indices at // positions _ can be thrown away, see Figure5(b) After Phase 2 // (Merge phase) in the Bitonic Top K paper referenced above. // For example, the paper shows we only need to output the orange bars. // The output sequence should look like this | | | | | | | |. // Because the sequence is halved, to map the output index back // to the previous sequence to find the corresponding value, // we need to double the index. When we double the index, // we basically interpolate a position, so 2i looks like // | _ | _ | _ | _ | _ | _ | _. We move the | to the first k position // of each 2k positions by - elemIdx % k. E.g. for output at // index 4,5,6,7, we want to get the corresponding element at // original index 8,9,10,11, for output at index 8,9,10,11, // we want to get the corresponding element at original index // 16,17,18,19, so on and so forth. int i = elemIdx< k ? elemIdx : (elemIdx * 2 - imod(elemIdx, k)); int i0 = firstPass == 1 ? i : int(getIndices(batch, i)); int i1 = firstPass == 1 ? i + k : int(getIndices(batch, i + k)); float x0 = getX(batch, i0); float x1 = i1 < n ? getX(batch, i1) : x0; setOutput(x0 >= x1 ? float(i0) : float(i1)); } `}}},{"@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],"2YDLy":[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"transform",()=>l),s.export(r,"transformConfig",()=>i);var a=e("@tensorflow/tfjs-core"),o=e("../transform_gpu");function l(e){let{inputs:t,backend:r,attrs:n}=e,{image:s,transforms:a}=t,{interpolation:l,fillMode:i,fillValue:p,outputShape:u}=n,[c,d,f,m]=s.shape,[h,g]=null!=u?u:[d,f],x=new(0,o.TransformProgram)(d,f,l,i,p,[c,h,g,m]);return r.runWebGLProgram(x,[s,a],"float32")}let i={kernelName:a.Transform,backendName:"webgl",kernelFunc:l}},{"@tensorflow/tfjs-core":"2Gtps","../transform_gpu":"4yTiU","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],"4yTiU":[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"TransformProgram",()=>a);class a{constructor(e,t,r,n,s,a){let o;switch(this.variableNames=["Image","Transforms"],this.outputShape=a,n){case"constant":default:o=1;break;case"reflect":o=2;break;case"wrap":o=3;break;case"nearest":o=4}this.userCode=` float mapCoord(float outCoord, float len) { float inCoord = outCoord; if(${o} == 2) { if (inCoord< 0.0) { if (len <= 1.0) { inCoord = 0.0; } else { float sz2 = 2.0 * len; if (inCoord < sz2) { inCoord = sz2 * float(int(float(-inCoord / sz2))) + inCoord; } inCoord = inCoord < -len ? inCoord + sz2 : -inCoord - 1.0; } } else if (inCoord >len - 1.0) { if (len<= 1.0) { inCoord = 0.0; } else { float sz2 = 2.0 * len; inCoord -= sz2 * float(int(float(inCoord / sz2))); if (inCoord >= len) { inCoord = sz2 - inCoord - 1.0; } } } return clamp(inCoord, 0.0, len - 1.0); } else if (${o} == 3) { if (inCoord< 0.0) { if (len <= 1.0) { inCoord = 0.0; } else { float sz = len - 1.0; inCoord += len * (float(int(float(-inCoord / sz))) + 1.0); } } else if (inCoord >len - 1.0) { if (len<= 1.0) { inCoord = 0.0; } else { float sz = len - 1.0; inCoord -= len * float(int(float(inCoord / sz))); } } return clamp(inCoord, 0.0, len - 1.0); } else if (${o} == 4) { return clamp(outCoord, 0.0, len - 1.0); } else { return outCoord; } } float readWithFillValue(int batch, int coordY, int coordX, int channel) { float outputValue; if (0 <= coordY && coordY < ${e} && 0 <= coordX && coordX < ${t}) { outputValue = getImage(batch, coordY, coordX, channel); } else { outputValue = float(${s}); } return outputValue; } void main() { ivec4 coords = getOutputCoords(); float outputValue; int batch = coords[0]; int x = coords[2]; int y = coords[1]; int channel = coords[3]; float xf = float(x); float yf = float(y); float a1 = getTransforms(batch, 0); float a2 = getTransforms(batch, 1); float a3 = getTransforms(batch, 2); float b1 = getTransforms(batch, 3); float b2 = getTransforms(batch, 4); float b3 = getTransforms(batch, 5); float c1 = getTransforms(batch, 6); float c2 = getTransforms(batch, 7); float projection = c1 * xf + c2 * yf + 1.0; if (projection == 0.0) { outputValue = float(${s}); } else { float inX = (a1 * xf + a2 * yf + a3) / projection; float inY = (b1 * xf + b2 * yf + b3) / projection; float mapX = mapCoord(inX, float(${t})); float mapY = mapCoord(inY, float(${e})); if (${"nearest"===r?1:2} == 1) { int coordY = int(round(mapY)); int coordX = int(round(mapX)); outputValue = readWithFillValue(batch, coordY, coordX, channel); } else { float yFloor = floor(mapY); float xFloor = floor(mapX); float yCeil = yFloor + 1.0; float xCeil = xFloor + 1.0; float valueYFloor = (xCeil - mapX) * readWithFillValue(batch, int(yFloor), int(xFloor), channel) + (mapX - xFloor) * readWithFillValue(batch, int(yFloor), int(xCeil), channel); float valueYCeil = (xCeil - mapX) * readWithFillValue(batch, int(yCeil), int(xFloor), channel) + (mapX - xFloor) * readWithFillValue(batch, int(yCeil), int(xCeil), channel); outputValue = (yCeil - mapY) * valueYFloor + (mapY - yFloor) * valueYCeil; } } setOutput(outputValue); } `}}},{"@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],hBsG3:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"unique",()=>i),s.export(r,"uniqueConfig",()=>p);var a=e("@tensorflow/tfjs-core"),o=e("../kernel_utils/shared"),l=e("../webgl_util");function i(e){let{inputs:t,attrs:r,backend:n}=e,{axis:s}=r,{x:a}=t;(0,l.assertNotComplex)(a,"unique"),console.warn("WARNING: ","UI might be locked temporarily as data is being downloaded");let i=n.readSync(a.dataId),{outputValues:p,outputShape:u,indices:c}=(0,o.uniqueImplCPU)(i,s,a.shape,a.dtype);return[n.makeTensorInfo(u,a.dtype,p),n.makeTensorInfo([c.length],"int32",c)]}let p={kernelName:a.Unique,backendName:"webgl",kernelFunc:i}},{"@tensorflow/tfjs-core":"2Gtps","../kernel_utils/shared":"6ruDg","../webgl_util":"kBGlX","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],eP6TK:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"unpack",()=>i),s.export(r,"unpackConfig",()=>p);var a=e("@tensorflow/tfjs-core"),o=e("./Reshape"),l=e("./Slice");function i(e){let{inputs:t,backend:r,attrs:n}=e,{value:s}=t,{axis:a}=n;a<0&&(a+=s.shape.length);let i=s.shape.length,p=s.shape[a],u=Array(i-1),c=0;for(let e=0;e<i;e++)e!==a&&(u[c++]=s.shape[e]);let d=[],f=Array(i).fill(0),m=s.shape.slice();m[a]=1;let h=Array(p);for(let e=0;e<h.length;e++){f[a]=e;let t=(0,l.slice)({inputs:{x:s},backend:r,attrs:{begin:f,size:m}}),n=(0,o.reshape)({inputs:{x:t},backend:r,attrs:{shape:u}});h[e]=n,d.push(t)}return d.forEach(e=>r.disposeIntermediateTensorInfo(e)),h}let p={kernelName:a.Unpack,backendName:"webgl",kernelFunc:i}},{"@tensorflow/tfjs-core":"2Gtps","./Reshape":"aOEE6","./Slice":"io5JZ","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],"1Qhxo":[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"unsortedSegmentSum",()=>c),s.export(r,"unsortedSegmentSumConfig",()=>d);var a=e("@tensorflow/tfjs-core"),o=e("../segment_gpu"),l=e("./Range"),i=e("./Reshape"),p=e("./Tile"),u=e("./Transpose");function c(e){let{inputs:t,backend:r,attrs:n}=e,{x:s,segmentIds:c}=t,{numSegments:d}=n,f=s.shape.length,m=[],h=0,g=a.backend_util.getAxesPermutation([h],f),x=s;null!=g&&(x=(0,u.transpose)({inputs:{x:s},backend:r,attrs:{perm:g}}),m.push(x),h=a.backend_util.getInnerMostAxes(1,f)[0]);let y=a.backend_util.segment_util.computeOutShape(x.shape,h,d),v=a.util.sizeFromShape([x.shape[h]]),b=(0,i.reshape)({inputs:{x:x},backend:r,attrs:{shape:[-1,v]}});m.push(b);let k=(0,a.sumOutType)(s.dtype),_=(e,t,n,s,i)=>{let u=e.shape[0],c=e.shape[1],d=a.backend_util.segment_util.segOpComputeOptimalWindowSize(c,i),f=new(0,o.SegmentOpProgram)({windowSize:d,inSize:c,batchSize:u,numSegments:i},t),h=r.compileAndRun(f,[e,n],s);if(m.push(h),h.shape[1]===i)return h;let g=(0,l.range)({backend:r,attrs:{start:0,stop:i,step:1,dtype:"float32"}}),x=(0,p.tile)({inputs:{x:g},backend:r,attrs:{reps:[c/d]}});return m.push(g),m.push(x),_(h,t,x,s,i)},I=_(b,"unsortedSegmentSum",c,k,d),j=(0,i.reshape)({inputs:{x:I},backend:r,attrs:{shape:y}}),w=j;if(null!=g){m.push(j);let e=a.backend_util.getUndoAxesPermutation(g);w=(0,u.transpose)({inputs:{x:w},backend:r,attrs:{perm:e}})}return m.forEach(e=>r.disposeIntermediateTensorInfo(e)),w}let d={kernelName:a.UnsortedSegmentSum,backendName:"webgl",kernelFunc:c}},{"@tensorflow/tfjs-core":"2Gtps","../segment_gpu":"fEqD0","./Range":"h4DwD","./Reshape":"aOEE6","./Tile":"2BktY","./Transpose":"lqCy7","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],fEqD0:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"SegmentOpProgram",()=>a);class a{constructor(e,t){this.variableNames=["x","segmentIds"];const r=e.windowSize,n=e.batchSize,s=e.inSize,a=e.numSegments,o=a*Math.ceil(s/r);this.outputShape=[n,o];const l=4*Math.floor(r/4),i=r%4,p=` sumValue += dot(values, segFilter); `;let u="";s%r>0&&(u=` if (inIdx< 0 || inIdx >= ${s}) { return initializationValue; } `);let c="";s%r>0&&(c=` if (inIdx< 0 || inIdx >= ${s}) { return -1.0; } `),this.userCode=` const float initializationValue = 0.0; float getValue(int batch, int inIdx) { ${u} return getX(batch, inIdx); } float getSegmentIdAtIndex(int inIdx) { ${c} return getSegmentIds(inIdx); } void main() { ivec2 coords = getOutputCoords(); int batch = coords[0]; int outIdx = coords[1]; int inOffset = int(floor(float(outIdx) / float( ${a})) * float(${r})); int currentSeg = int(mod(float(outIdx), float(${a}))); float sumValue = 0.0; for (int i = 0; i< ${l}; 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 ); ${p} } int inIdx = inOffset + ${l}; if (${1===i}) { 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 ); ${p} } else if (${2===i}) { 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 ); ${p} } else if (${3===i}) { 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 ); ${p} } setOutput(sumValue); } `}}},{"@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],b4yJT:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r);var a=e("./base");s.exportAll(a,r),e("./register_all_kernels")},{"./base":"bmQG8","./register_all_kernels":"62E5G","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],bmQG8:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"MathBackendCPU",()=>o.MathBackendCPU),s.export(r,"version_cpu",()=>i.version),s.export(r,"shared",()=>l);var a=e("@tensorflow/tfjs-core"),o=e("./backend_cpu"),l=e("./shared"),i=e("./version");(0,a.registerBackend)("cpu",()=>new(0,o.MathBackendCPU),1)},{"@tensorflow/tfjs-core":"2Gtps","./backend_cpu":"b4BSc","./shared":"jEP2j","./version":"dKDSI","@parcel/transformer-js/src/esmodule-helpers.js":"6ykb1"}],b4BSc:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"MathBackendCPU",()=>i);var a=e("@tensorflow/tfjs-core"),o=e("./cpu_util");let l=a.kernel_impls.whereImpl;class i extends a.KernelBackend{nextDataId(){return i.nextDataId++}constructor(){super(),this.blockSize=48,this.firstUse=!0,this.data=new(0,a.DataStorage)(this,(0,a.engine)())}write(e,t,r){this.firstUse&&(this.firstUse=!1,(0,a.env)().get("IS_NODE")&&a.backend_util.warn("\n============================\nHi, looks like you are running TensorFlow.js in Node.js. 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Equal":"6vsbD","./kernels/Erf":"7xSpz","./kernels/Exp":"9ub2a","./kernels/ExpandDims":"fRg5Q","./kernels/Expm1":"la325","./kernels/FFT":"i9oI8","./kernels/Fill":"8zGrw","./kernels/FlipLeftRight":"3COuK","./kernels/Floor":"ggI8q","./kernels/FloorDiv":"4CGo3","./kernels/FusedConv2D":"2tKGZ","./kernels/FusedDepthwiseConv2D":"3Effs","./kernels/GatherNd":"fbTOY","./kernels/GatherV2":"4V15q","./kernels/Greater":"8VCX5","./kernels/GreaterEqual":"6dCtd","./kernels/Identity":"ew2a3","./kernels/IFFT":"2Mfch","./kernels/Imag":"4Od8v","./kernels/IsFinite":"bzcHc","./kernels/IsInf":"aTLYv","./kernels/IsNaN":"gHpOo","./kernels/LeakyRelu":"3XDq5","./kernels/Less":"amDj6","./kernels/LessEqual":"2l63t","./kernels/LinSpace":"9m7fp","./kernels/Log":"6pnuq","./kernels/Log1p":"ixzUq","./kernels/LogicalAnd":"OUTi1","./kernels/LogicalNot":"2si92","./kernels/LogicalOr":"hO7A3","./kernels/LRN":"zdv2n","./kernels/LRNGrad":"ePwSb","./kernels/Max":"19KxN","./kernels/Maximum":"3mucZ","./kernels/MaxPool":"kUIKv","./kernels/MaxPool3D":"21jus","./kernels/MaxPool3DGrad":"f4E9l","./kernels/MaxPoolGrad":"koGS6","./kernels/MaxPoolWithArgmax":"dTuNm","./kernels/Mean":"fmev5","./kernels/Min":"9osZy","./kernels/Minimum":"h5VzA","./kernels/MirrorPad":"1lNW2","./kernels/Mod":"hMMNZ","./kernels/Multinomial":"iaROS","./kernels/Multiply":"blR5P","./kernels/Neg":"8cO7T","./kernels/NonMaxSuppressionV3":"h85ni","./kernels/NonMaxSuppressionV4":"faKbd","./kernels/NonMaxSuppressionV5":"hCHZZ","./kernels/NotEqual":"bhFpO","./kernels/OneHot":"9plCE","./kernels/OnesLike":"kpDJA","./kernels/Pack":"1fNim","./kernels/PadV2":"2Tf5D","./kernels/Pow":"kLar1","./kernels/Prelu":"jLNHQ","./kernels/Prod":"1vdcs","./kernels/RaggedGather":"gzFNc","./kernels/RaggedRange":"j4Jmi","./kernels/RaggedTensorToTensor":"7ZkQK","./kernels/Range":"j30dI","./kernels/Real":"fBBrK","./kernels/RealDiv":"l0XIp","./kernels/Reciprocal":"jw3Jp","./kernels/Relu":"9mB5U","./kernels/Relu6":"6AGG5","./kernels/Reshape":"94cVf","./kernels/ResizeBilinear":"aqDSc","./kernels/ResizeBilinearGrad":"4vVD1","./kernels/ResizeNearestNeighbor":"7TDMp","./kernels/ResizeNearestNeighborGrad":"arXoN","./kernels/Reverse":"g4sF4","./kernels/RotateWithOffset":"buBka","./kernels/Round":"fiSlE","./kernels/Rsqrt":"anhkm","./kernels/ScatterNd":"1TDdU","./kernels/SearchSorted":"5qRls","./kernels/Select":"lCXpt","./kernels/Selu":"7b5Ai","./kernels/Sigmoid":"dgIMK","./kernels/Sign":"fjTv4","./kernels/Sin":"96Ts1","./kernels/Sinh":"7TNAI","./kernels/Slice":"aVrpO","./kernels/Softmax":"3QD6z","./kernels/Softplus":"hXZZ0","./kernels/SpaceToBatchND":"HGFyQ","./kernels/SparseFillEmptyRows":"9KREA","./kernels/SparseReshape":"lWpFB","./kernels/SparseSegmentMean":"jt9ak","./kernels/SparseSegmentSum":"fzkPQ","./kernels/SparseToDense":"4Dlhe","./kernels/SplitV":"27QZB","./kernels/Sqrt":"b2SF0","./kernels/Square":"6RKDU","./kernels/SquaredDifference":"5czoa","./kernels/StaticRegexReplace":"hBYHB","./kernels/Step":"gLD1g","./kernels/StridedSlice":"634M0","./kernels/StringNGrams":"4s5vv","./kernels/StringSplit":"j9Qom","./kernels/StringToHashBucketFast":"ikODx","./kernels/Sub":"kDL1v","./kernels/Sum":"9Vc6r","./kernels/Tan":"1n2Cy","./kernels/Tanh":"6duST","./kernels/TensorScatterUpdate":"4T45m","./kernels/Tile":"5fOHa","./kernels/TopK":"kxEVO","./kernels/Transform":"fYCMo","./kernels/Transpose":"j4ys5","./kernels/Unique":"d9zwP","./kernels/Unpack":"9obkn","./kernels/UnsortedSegmentSum":"4TMs1","./kernels/ZerosLike":"fmLIH"}],eS3My:[function(e,t,r,n){var 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