ArtPlayer/docs/compiled/artplayer-plugin-danmuku-mask.mjs

/*!
 * 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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ea={architecture:"MobileNetV1",outputStride:16,quantBytes:4,multiplier:.75},eo=["MobileNetV1","ResNet50"],el={MobileNetV1:[8,16,32],ResNet50:[32,16]},ei={MobileNetV1:[.5,.75,1],ResNet50:[1]},eu=[1,2,4],ep={flipHorizontal:!1,internalResolution:"medium",segmentationThreshold:.7,maxDetections:10,scoreThreshold:.4,nmsRadius:20},ec={flipHorizontal:!1,internalResolution:"medium",segmentationThreshold:.7,maxDetections:10,scoreThreshold:.4,nmsRadius:20,minKeypointScore:.3,refineSteps:10};function ed(e){var t=e.segmentationThreshold,r=e.maxDetections,n=e.scoreThreshold,s=e.nmsRadius;if(t<0||t>1)throw Error("segmentationThreshold "+t+". 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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=J(e),a=s[0],l=s[1],i=ee(t,this.baseModel.outputStride,[a,l]),u=er(e,i),p=u.resized,c=u.padding,d=(0,o.tidy)(function(){var e=n.predictForPersonSegmentation(p),t=e.segmentLogits,s=e.heatmapScores,i=e.offsets,u=e.displacementFwd,d=e.displacementBwd,f=p.shape,h=et(t,[a,l],[f[0],f[1]],[[c.top,c.bottom],[c.left,c.right]],!0);return{segmentation:k((0,o.squeeze)(h),r),heatmapScores:s,offsets:i,displacementFwd:u,displacementBwd:d}}),f=d.segmentation,h=d.heatmapScores,m=d.offsets,g=d.displacementFwd,x=d.displacementBwd;return p.dispose(),{segmentation:f,heatmapScores:h,offsets:m,displacementFwd:g,displacementBwd:x,padding:c,internalResolutionHeightAndWidth:i}},e.prototype.segmentPerson=function(e,t){return void 0===t&&(t=ep),d(this,void 0,void 0,function(){var r,n,s,a,o,l,i,u,p,d,h,m,g,x,v,y;return f(this,function(f){switch(f.label){case 0:return ed(t=c(c({},ep),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,u=r.internalResolutionHeightAndWidth,d=(p=n.shape)[0],h=p[1],[4,n.data()];case 1:return m=f.sent(),n.dispose(),[4,en([s,a,o,l])];case 2:return x=(g=f.sent())[0],v=g[1],y=es(y=z(x,v,g[2],g[3],this.baseModel.outputStride,t.maxDetections,t.scoreThreshold,t.nmsRadius),[d,h],u,i,!1),s.dispose(),a.dispose(),o.dispose(),l.dispose(),[2,{height:d,width:h,data:m,allPoses:y}]}})})},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,u,p,h,m,g,x,v,y,_,b,T,w,I,j=this;return f(this,function(C){switch(C.label){case 0:return ef(t=c(c({},ec),t)),n=(r=J(e))[0],s=r[1],i=(l=er(e,a=ee(t.internalResolution,this.baseModel.outputStride,[n,s]))).resized,u=l.padding,h=(p=(0,o.tidy)(function(){var e=j.predictForMultiPersonInstanceSegmentationAndPart(i),r=e.segmentLogits,l=e.longOffsets,p=e.heatmapScores,c=e.offsets,d=e.displacementFwd,f=e.displacementBwd,h=et(r,[n,s],a,[[u.top,u.bottom],[u.left,u.right]],!0);return{segmentation:k((0,o.squeeze)(h),t.segmentationThreshold),longOffsets:l,heatmapScoresRaw:p,offsetsRaw:c,displacementFwdRaw:d,displacementBwdRaw:f}})).segmentation,m=p.longOffsets,g=p.heatmapScoresRaw,x=p.offsetsRaw,v=p.displacementFwdRaw,y=p.displacementBwdRaw,[4,en([g,x,v,y])];case 1:return b=(_=C.sent())[0],T=_[1],w=es(w=z(b,T,_[2],_[3],this.baseModel.outputStride,t.maxDetections,t.scoreThreshold,t.nmsRadius),[n,s],a,u,!1),[4,function(e,t,r,n,s,a,l,i,u,p,c,h){var m=l[0],g=l[1];return void 0===u&&(u=.2),void 0===p&&(p=8),void 0===c&&(c=.3),void 0===h&&(h=10),d(this,void 0,void 0,function(){var l,d,x,v,y;return f(this,function(f){switch(f.label){case 0:return l=r.filter(function(e){return e.score>=u}),P()?[4,Promise.all((x=(0,o.tidy)(function(){var r=D(e,t,l,n,s,a,[m,g],i,p,c,h),u=(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)(u,(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 v=f.sent(),[4,t.data()];case 4:y=f.sent(),d=function(e,t,r,n,s,a,o,l,i,u){var p=o[0],c=o[1];void 0===u&&(u=5);for(var d=r.map(function(e){return new Uint8Array(n*s).fill(0)}),f=l.top,h=l.left,m=N([n,s],[p,c],l),g=m[0],x=m[1],v=R([p,c],a)[0],y=0;y<n;y+=1)for(var _=0;_<s;_+=1){var b=y*s+_;if(1===e[b]){var k=F({x:_,y:y},t,r,u,[f,h],[g,x],v,[n,s],a,i);k>=0&&(d[k][b]=1)}}return d}(v,y,l,n,s,a,[m,g],i,p),f.label=5;case 5:return[2,d.map(function(e,t){return{data:e,pose:l[t],width:s,height:n}})]}})})}(h,m,w,n,s,this.baseModel.outputStride,a,u,t.scoreThreshold,t.refineSteps,t.minKeypointScore,t.maxDetections)];case 2:return I=C.sent(),i.dispose(),h.dispose(),m.dispose(),g.dispose(),x.dispose(),v.dispose(),y.dispose(),[2,I]}})})},e.prototype.segmentPersonPartsActivation=function(e,t,r){var n=this;void 0===r&&(r=.5);var s=J(e),a=s[0],l=s[1],i=ee(t,this.baseModel.outputStride,[a,l]),u=er(e,i),p=u.resized,c=u.padding,d=(0,o.tidy)(function(){var e,t,s,i,u,d=n.predictForPersonSegmentationAndPart(p),f=d.segmentLogits,h=d.partHeatmapLogits,m=d.heatmapScores,g=d.offsets,x=d.displacementFwd,v=d.displacementBwd,y=p.shape,_=y[0],T=y[1],w=et(f,[a,l],[_,T],[[c.top,c.bottom],[c.left,c.right]],!0),I=et(h,[a,l],[_,T],[[c.top,c.bottom],[c.left,c.right]],!0);return{partSegmentation:(e=k((0,o.squeeze)(w),r),s=(t=I.shape)[0],i=t[1],u=t[2],(0,o.tidy)(function(){var t=b(I),r=(0,o.expandDims)((0,o.range)(0,u,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:m,offsets:g,displacementFwd:x,displacementBwd:v}}),f=d.partSegmentation,h=d.heatmapScores,m=d.offsets,g=d.displacementFwd,x=d.displacementBwd;return p.dispose(),{partSegmentation:f,heatmapScores:h,offsets:m,displacementFwd:g,displacementBwd:x,padding:c,internalResolutionHeightAndWidth:i}},e.prototype.segmentPersonParts=function(e,t){return void 0===t&&(t=ep),d(this,void 0,void 0,function(){var r,n,s,a,o,l,i,u,p,d,h,m,g,x,v,y;return f(this,function(f){switch(f.label){case 0:return ed(t=c(c({},ep),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,u=r.internalResolutionHeightAndWidth,d=(p=n.shape)[0],h=p[1],[4,n.data()];case 1:return m=f.sent(),n.dispose(),[4,en([s,a,o,l])];case 2:return x=(g=f.sent())[0],v=g[1],y=es(y=z(x,v,g[2],g[3],this.baseModel.outputStride,t.maxDetections,t.scoreThreshold,t.nmsRadius),[d,h],u,i,!1),s.dispose(),a.dispose(),o.dispose(),l.dispose(),[2,{height:d,width:h,data:m,allPoses:y}]}})})},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,u,p,h,m,g,x,v,y,_,T,w,I,j,C,S=this;return f(this,function(E){switch(E.label){case 0:return ef(t=c(c({},ec),t)),n=(r=J(e))[0],s=r[1],i=(l=er(e,a=ee(t.internalResolution,this.baseModel.outputStride,[n,s]))).resized,u=l.padding,h=(p=(0,o.tidy)(function(){var e,r,l,p,c=S.predictForMultiPersonInstanceSegmentationAndPart(i),d=c.segmentLogits,f=c.longOffsets,h=c.heatmapScores,m=c.offsets,g=c.displacementFwd,x=c.displacementBwd,v=c.partHeatmaps,y=et(d,[n,s],a,[[u.top,u.bottom],[u.left,u.right]],!0),_=et(v,[n,s],a,[[u.top,u.bottom],[u.left,u.right]],!0);return{segmentation:k((0,o.squeeze)(y),t.segmentationThreshold),longOffsets:f,heatmapScoresRaw:h,offsetsRaw:m,displacementFwdRaw:g,displacementBwdRaw:x,partSegmentation:(r=(e=_.shape)[0],l=e[1],p=e[2],(0,o.tidy)(function(){var e=b(_),t=(0,o.expandDims)((0,o.range)(0,p,1,"int32"),1),n=(0,o.cast)((0,o.matMul)(e,t),"int32");return(0,o.reshape)(n,[r,l])}))}})).segmentation,m=p.longOffsets,g=p.heatmapScoresRaw,x=p.offsetsRaw,v=p.displacementFwdRaw,y=p.displacementBwdRaw,_=p.partSegmentation,[4,en([g,x,v,y])];case 1:return w=(T=E.sent())[0],I=T[1],j=es(j=z(w,I,T[2],T[3],this.baseModel.outputStride,t.maxDetections,t.scoreThreshold,t.nmsRadius),[n,s],a,u,!1),[4,function(e,t,r,n,s,a,l,i,u,p,c,h,m){var g=i[0],x=i[1];return void 0===p&&(p=.2),void 0===c&&(c=8),void 0===h&&(h=.3),void 0===m&&(m=10),d(this,void 0,void 0,function(){var i,d,v,y,_,b;return f(this,function(f){switch(f.label){case 0:return i=n.filter(function(e){return e.score>=p}),P()?[4,Promise.all((v=(0,o.tidy)(function(){var n=D(e,t,i,s,a,l,[g,x],u,c,h,m),p=(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)(p,(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(),v.forEach(function(e){return e.dispose()}),[3,6];case 2:return[4,e.data()];case 3:return y=f.sent(),[4,t.data()];case 4:return _=f.sent(),[4,r.data()];case 5:b=f.sent(),d=function(e,t,r,n,s,a,o,l,i,u,p){var c=l[0],d=l[1];void 0===p&&(p=5);for(var f=n.map(function(e){return new Int32Array(s*a).fill(-1)}),h=i.top,m=i.left,g=N([s,a],[c,d],i),x=g[0],v=g[1],y=R([c,d],o)[0],_=0;_<s;_+=1)for(var b=0;b<a;b+=1){var k=_*a+b;if(1===e[k]){var T=F({x:b,y:_},t,n,p,[h,m],[x,v],y,[s,a],o,u);T>=0&&(f[T][k]=r[k])}}return f}(y,_,b,i,s,a,l,[g,x],u,c),f.label=6;case 6:return[2,d.map(function(e,t){return{pose:i[t],data:e,height:s,width:a}})]}})})}(h,m,_,j,n,s,this.baseModel.outputStride,a,u,t.scoreThreshold,t.refineSteps,t.minKeypointScore,t.maxDetections)];case 2:return C=E.sent(),i.dispose(),h.dispose(),m.dispose(),g.dispose(),x.dispose(),v.dispose(),y.dispose(),_.dispose(),[2,C]}})})},e.prototype.dispose=function(){this.baseModel.dispose()},e}(),em=["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,m(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(v(e),255!==e)throw Error("Foreground id must be 255 but got "+e);return"person"}function ev(e){if(v(e),e>=em.length)throw Error("Invalid body part value "+e);return em[e]}var ey=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]=em.length,s[4*t+3]=0):(s[4*t]=e,s[4*t+3]=255)}),{maskValueToLabel:ev,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}(),e_={runtime:"mediapipe",modelType:"general"},eb=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 ek(e){return v(e),"person"}var eT=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:ek,mask:new eb(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 ew(e){return e instanceof o.Tensor?{height:e.shape[0],width:e.shape[1]}:{height:e.height,width:e.width}}function eI(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 ej={runtime:"tfjs",modelType:"general",modelUrl:"https://tfhub.dev/mediapipe/tfjs-model/selfie_segmentation/general/1"},eC={flipHorizontal:!1},eN={outputTensorSize:{width:256,height:256},keepAspectRatio:!1,borderMode:"zero",outputTensorFloatRange:[0,1]},eS={outputTensorSize:{width:256,height:144},keepAspectRatio:!1,borderMode:"zero",outputTensorFloatRange:[0,1]},eE={activation:"none"},eA=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,m(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 eF(e){return v(e),"person"}var eR,eD=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({},eC);var t=c({},e);return null==t.flipHorizontal&&(t.flipHorizontal=eC.flipHorizontal),t}(t),null==e?(this.reset(),[2,[]]):[2,[{maskValueToLabel:eF,mask:new eA((0,o.tidy)(function(){var t,n,s,a,l,i,u,p,c,d,f,h,m,g,x,v,y,_,b,k,T,w,I=(x=(t="general"===r.modelType?eN:eS).outputTensorSize,v=t.keepAspectRatio,y=t.borderMode,_=t.outputTensorFloatRange,T=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;eI(t,"targetSize"),eI(e,"roi");var a,o,l=n/s,i=e.height/e.width,u=0,p=0;return l>i?(a=e.width,o=e.width*l,p=(1-i/l)/2):(a=e.height/l,o=e.height,u=(1-l/i)/2),e.width=a,e.height=o,{top:p,left:u,right:u,bottom:p}}((n=b=ew(e),k={xCenter:.5*n.width,yCenter:.5*n.height,width:n.width,height:n.height,rotation:0}),x,v),s=b.width,a=b.height,l=k.width,i=k.height,u=1,p=Math.cos(k.rotation),c=Math.sin(k.rotation),d=k.xCenter,f=k.yCenter,h=1/s,m=1/a,(g=Array(16))[0]=l*p*u*h,g[1]=-i*c*h,g[2]=0,g[3]=(-.5*l*p*u+.5*i*c+d)*h,g[4]=l*c*u*m,g[5]=i*p*m,g[6]=0,g[7]=(-.5*i*p-.5*l*c*u+f)*m,g[8]=0,g[9]=0,g[10]=l*h,g[11]=0,g[12]=0,g[13]=0,g[14]=0,g[15]=1,w=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)((eI(x,"inputResolution"),[1/x.width*w[0][0]*b.width,1/x.height*w[0][1]*b.width,w[0][3]*b.width,1/x.width*w[1][0]*b.height,1/x.height*w[1][1]*b.height,w[1][3]*b.height,0,0]),[1,8]),s=o.image.transform((0,o.expandDims)((0,o.cast)(r,"float32")),n,"bilinear","zero"===y?"constant":"nearest",0,[x.height,x.width]);return null!=_?(t=function(e,t,r,n){!1;var s=(n-r)/255;return{scale:s,offset:r-0*s}}(0,0,_[0],_[1]),(0,o.tidy)(function(){return(0,o.add)((0,o.mul)(s,t.scale),t.offset)})):s}),padding:T,transformationMatrix:w}).imageTensor,j=(0,o.slice)(r.model.predict(I),[0,0,0,1],-1),C=ew(e),N=(0,o.tidy)(function(){var e=(0,o.squeeze)(j,[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=C?o.image.resizeBilinear(r,[C.height,C.width]):r;return(0,o.squeeze)(n,[2])}throw Error("Unsupported number of tensor channels "+t)}),S=(0,o.expandDims)(N,2),E=(0,o.pad)(S,[[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 eP(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({},ej);var t=c({},e);if(t.runtime="tfjs",null==t.modelType&&(t.modelType=ej.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 eD(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 eT(function(e){if(null==e)return c({},e_);var t=c({},e);return t.runtime="mediapipe",null==t.modelType&&(t.modelType=e_.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>eu.indexOf(e.quantBytes))throw Error("Invalid quantBytes "+e.quantBytes+". Should be one of "+eu+" 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?H+"float/"+a:H+"quant"+r+"/"+a,[4,(0,l.loadGraphModel)(e.modelUrl||n)];case 1:return[2,new eh(new W(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,u;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"},u="model-stride"+t+".json",s=4===r?K+"float/"+i[n]+"/"+u:K+"quant"+r+"/"+i[n]+"/"+u,[4,(0,l.loadGraphModel)(e.modelUrl||s)];case 1:return[2,new eh(new w(a.sent(),t))]}})})}(e)]:[2,null]})})})(e).then(function(e){return new ey(e)})]})})}(n=t)];default:throw Error(e+" is not a supported model name.")}})})}(s=eR||(eR={})).BodyPix="BodyPix",s.MediaPipeSelfieSegmentation="MediaPipeSelfieSegmentation";var e$="blurred",eM="blurred-mask",eO="mask",eB={};function eq(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 eL(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 eV(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 eG(e,t){var r=eV(t);return r.width=e.width,r.height=e.height,r.getContext("2d").putImageData(e,0,0),r}function ez(e,t,r,n,s,a){return d(this,void 0,void 0,function(){var l,i,u;return f(this,function(p){switch(p.label){case 0:return t instanceof o.Tensor?[4,o.browser.toPixels(t)]:[3,2];case 1:l=p.sent(),u=(i=eL(t))[0],t=new ImageData(l,i[1],u),p.label=2;case 2:return t instanceof ImageData&&(t=eG(t,"draw-image")),null==s||null==a?e.drawImage(t,r,n):e.drawImage(t,r,n,s,a),[2]}})})}function eU(e){var t=e.getContext("2d");t.scale(-1,1),t.translate(-e.width,0)}function eX(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,ez(e,t,0,0)];case 1:return n.sent(),[2]}})})}function eW(e,t,r){return d(this,void 0,void 0,function(){var n;return f(this,function(s){switch(s.label){case 0:return n=eV(r),0!==t?[3,2]:[4,function(e,t){return d(this,void 0,void 0,function(){var r,n,s;return f(this,function(a){switch(a.label){case 0:return n=(r=eL(e))[0],t.width=s=r[1],t.height=n,[4,ez(t.getContext("2d"),e,0,0,s,n)];case 1:return a.sent(),[2]}})})}(e,n)];case 1:return s.sent(),[3,4];case 2:return[4,function(e,t,r){return d(this,void 0,void 0,function(){var n,s,a,o;return f(this,function(l){switch(l.label){case 0:return s=(n=eL(e))[0],a=n[1],o=r.getContext("2d"),r.width=a,r.height=s,o.clearRect(0,0,a,s),o.save(),/^((?!chrome|android).)*safari/i.test(navigator.userAgent)?[4,function(e,t,r){return d(this,void 0,void 0,function(){var n,s,a,o,l,i,u,p;return f(this,function(c){switch(c.label){case 0:for(n=e.getContext("2d"),s=0,o=1/(2*Math.PI*(a=5)*a),l=r<3?1:2,u=-r;u<=r;u+=l)for(p=-r;p<=r;p+=l)i=o*Math.exp(-(p*p+u*u)/(2*a*a)),s+=i;u=-r,c.label=1;case 1:if(!(u<=r))return[3,6];p=-r,c.label=2;case 2:return p<=r?(n.globalAlpha=o*Math.exp(-(p*p+u*u)/(2*a*a))/s*r,[4,ez(n,t,p,u)]):[3,5];case 3:c.sent(),c.label=4;case 4:return p+=l,[3,2];case 5:return u+=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,ez(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 eH(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,u,p,c,d,h,m,g,x,v,y,_;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((u=(i=(l=f.sent())[0]).width)*(p=i.height)*4),d=Math.round(255*s),h=Array(256).fill(!1),a.forEach(function(e){return 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f(this,function(f){switch(f.label){case 0:return i=(l=eL(t))[0],eq({width:l[1],height:i},r,"image","mask"),[4,eW(eG(r,eO),s,eM)];case 1:for(e.width=(u=f.sent()).width,e.height=u.height,(p=e.getContext("2d")).save(),a&&eU(e),d=(c=eV("lowres-part-mask")).getContext("2d"),c.width=u.width*(1/o),c.height=u.height*(1/o),d.drawImage(u,0,0,u.width,u.height,0,0,c.width,c.height),p.imageSmoothingEnabled=!1,p.drawImage(c,0,0,c.width,c.height,0,0,e.width,e.height),h=0;h<c.width;h++)p.beginPath(),p.strokeStyle="#ffffff",p.moveTo(o*h,0),p.lineTo(o*h,e.height),p.stroke();for(h=0;h<c.height;h++)p.beginPath(),p.strokeStyle="#ffffff",p.moveTo(0,o*h),p.lineTo(e.width,o*h),p.stroke();return p.globalAlpha=1-n,[4,ez(p,t,0,0,u.width,u.height)];case 2:return f.sent(),p.restore(),[2]}})})}function eZ(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,u,p,c,h;return f(this,function(m){switch(m.label){case 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e.width=(i=g.sent()).width,e.height=i.height,u=e.getContext("2d"),Array.isArray(r)&&0===r.length?(u.drawImage(i,0,0),[2]):[4,function(e,t,r,n){return d(this,void 0,void 0,function(){var s;return f(this,function(a){switch(a.label){case 0:return[4,eH(e,{r:0,g:0,b:0,a:0},{r:0,g:0,b:0,a:255},!0,r,t)];case 1:return s=eG(a.sent(),eO),0===n?[2,s]:[2,eW(s,n,eM)]}})})}(r,n,s,o)];case 2:return p=g.sent(),u.save(),l&&eU(e),h=(c=eL(t))[0],m=c[1],[4,ez(u,t,0,0,m,h)];case 3:return g.sent(),[4,eX(u,p,"destination-in")];case 4:return g.sent(),[4,eX(u,i,"destination-over")];case 5:return g.sent(),u.restore(),[2]}})})}},{"@tensorflow/tfjs-core":"hADTC","@tensorflow/tfjs-converter":"7lxVT","@mediapipe/selfie_segmentation":"3OB47","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],hADTC:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),e("./base_side_effects");var 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s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"Engine",()=>v),s.export(r,"getOrMakeEngine",()=>y),s.export(r,"ENGINE",()=>_),s.export(r,"add",()=>b);var a=e("./backends/backend"),o=e("./environment"),l=e("./global_util"),i=e("./kernel_names"),u=e("./kernel_registry"),p=e("./log"),c=e("./profiler"),d=e("./tape"),f=e("./tensor"),h=e("./tensor_util"),m=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 v{constructor(e){this.ENV=e,this.registry={},this.registryFactory={},this.pendingBackendInitId=0,this.state=new x}async ready(){if(null!=this.pendingBackendInit)return this.pendingBackendInit.then(()=>{});if(null!=this.backendInstance)return;let e=this.getSortedBackends();for(let t=0;t<e.length;t++){let r=e[t];if(await this.initializeBackend(r).success)return void await this.setBackend(r)}throw Error("Could not initialize any backends, all backend initializations failed.")}get backend(){if(null!=this.pendingBackendInit)throw Error(`Backend '${this.backendName}' has not yet been initialized. 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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,p.warn(`Initialization of backend ${e} failed`),p.warn(r.stack||r.message),!1));return this.pendingBackendInit=n,{success:n,asyncInit:!0}}}catch(t){return p.warn(`Initialization of backend ${e} failed`),p.warn(t.stack||t.message),{success:!1,asyncInit:!1}}}removeBackend(e){if(!(e in this.registryFactory))throw Error(`${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 '${e}'`)}runKernelFunc(e){let t,r,n,s,a=[],o=this.isTapeOn(),l=this.state.numBytes,i=this.state.numTensors;this.shouldCheckForMemLeaks()&&this.state.numDataMovesStack.push(0),null==this.backendName&&this.backend;let p=g(e)?e.kernelName:null!=this.state.activeScope?this.state.activeScope.name:"";if(g(e)){let{kernelName:t,inputs:s,attrs:l}=e;null==this.backendName&&this.backend;let i=(0,u.getKernel)(t,this.backendName);m.assert(null!=i,()=>`Cannot find registered kernel '${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 u=r.map(e=>null!=e.rank?e:this.makeTensorFromTensorInfo(e));if(o){let e=this.getTensorsForGradient(t,s,u);a=this.saveTensorsForBackwardMode(e)}return u}}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(p,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(p,c,()=>r()),this.ENV.getBool("DEBUG")&&this.profiler.logKernelProfile(s),t=s.outputs):t=r()}),o&&this.addTapeNode(p,c,t,f,a,d),this.state.profiling&&this.state.activeProfile.kernels.push({name:p,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,u.getGradient)(e);if(null!=n){let e,s=n.inputsToSave||[],a=n.outputsToSave||[];n.saveAllInputs?(m.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"),u=e("../ops/scalar"),p=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,u.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,p.zerosLike)(n).variable(!1))});let s=this.accumulations[r].variable,u=Array.isArray(e)?e[r].tensor:e[t];null!=u&&(0,o.tidy)(()=>{let 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e(t.learningRate,t.momentum,t.useNesterov)}}},{"../engine":"gtimw","../globals":"6oj2G","../ops/add":"hFQoV","../ops/mul":"1OlNG","../ops/scalar":"forpx","../ops/zeros_like":"bDxUb","./sgd_optimizer":"2FFC7","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],"2FFC7":[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"),u=e("../ops/scalar"),p=e("./optimizer");class c extends p.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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null!=s&&(u=(0,a.convertToTensor)(s,"scale","batchNorm")),null!=n&&(p=(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!=u&&o.assert(4===u.rank||1===u.rank,()=>`Error in batchNorm4D: scale must be rank 4 or rank 1 but got rank ${u.rank}.`),null!=p&&o.assert(4===p.rank||1===p.rank,()=>`Error in batchNorm4D: offset must be rank 4 or rank 1 but got rank ${p.rank}.`),(0,l.batchNorm)(c,d,f,p,u,i)}})},{"../tensor_util_env":"4hoNq","../util":"lLzfH","./batchnorm":"a14hO","./operation":"hyTBr","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],"2K5KM":[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"bincount",()=>u);var a=e("../engine"),o=e("../kernel_names"),l=e("../tensor_util_env"),i=e("../util");let u=(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":"gtimw","../kernel_names":"agfs7","../tensor_util_env":"4hoNq","../util":"lLzfH","./operation":"hyTBr","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],dLkHl:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"bitwiseAnd",()=>u);var a=e("../engine"),o=e("../kernel_names"),l=e("../tensor_util_env"),i=e("../util_base");let u=(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":"gtimw","../kernel_names":"agfs7","../tensor_util_env":"4hoNq","../util_base":"2IDj3","./operation":"hyTBr","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],hnbiR:[function(e,t,r,n){var 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Has rank ${r.rank}`);if(1!==n.rank)throw Error(`broadcastArgs(): second input must be a vector (rank=1). Has rank ${n.rank}`);return a.ENGINE.runKernel(o.BroadcastArgs,{s0:r,s1:n})}})},{"../engine":"gtimw","../kernel_names":"agfs7","../tensor_util_env":"4hoNq","./operation":"hyTBr","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],"2sLNU":[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"broadcastTo",()=>d);var a=e("../engine"),o=e("../kernel_names"),l=e("../tensor_util_env"),i=e("../util_base"),u=e("./clone"),p=e("./operation"),c=e("./reshape");let d=(0,p.op)({broadcastTo_:function(e,t){let r=(0,l.convertToTensor)(e,"broadcastTo","x"),n=r.shape;if((0,i.assertNonNegativeIntegerDimensions)(t),t.length<r.rank)throw Error(`broadcastTo(): shape.length=${t.length} < input.rank=${r.rank}.`);if(t.length>r.rank){let e=r.shape.slice();for(;e.length<t.length;)e.unshift(1);r=(0,c.reshape)(r,e)}let s=r.shape,p=Array.from(t);for(let e=t.length-1;e>=0;e--)if(s[e]===t[e])p[e]=1;else if(1!==r.shape[e])throw Error(`broadcastTo(): [${n}] cannot be broadcast to [${t}].`);if(0===p.map((e,t)=>e>1?t:-1).filter(e=>e>=0).length)return(0,u.clone)(r);let d={x:r};return a.ENGINE.runKernel(o.Tile,d,{reps:p})}})},{"../engine":"gtimw","../kernel_names":"agfs7","../tensor_util_env":"4hoNq","../util_base":"2IDj3","./clone":"etnty","./operation":"hyTBr","./reshape":"aTsgx","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],"3cRYj":[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"ceil",()=>i);var a=e("../engine"),o=e("../kernel_names"),l=e("../tensor_util_env");let i=(0,e("./operation").op)({ceil_:function(e){let t=(0,l.convertToTensor)(e,"x","ceil","float32");return a.ENGINE.runKernel(o.Ceil,{x:t})}})},{"../engine":"gtimw","../kernel_names":"agfs7","../tensor_util_env":"4hoNq","./operation":"hyTBr","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],eJlYk:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"clipByValue",()=>p);var a=e("../engine"),o=e("../kernel_names"),l=e("../tensor_util_env"),i=e("../util"),u=e("./fill");let p=(0,e("./operation").op)({clipByValue_:function(e,t,r){let n=(0,l.convertToTensor)(e,"x","clipByValue");return(i.assert(t<=r,()=>`Error in clip: min (${t}) must be less than or equal to max (${r}).`),t===r)?(0,u.fill)(n.shape,t,n.dtype):a.ENGINE.runKernel(o.ClipByValue,{x:n},{clipValueMin:t,clipValueMax:r})}})},{"../engine":"gtimw","../kernel_names":"agfs7","../tensor_util_env":"4hoNq","../util":"lLzfH","./fill":"8mmbD","./operation":"hyTBr","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],kVnPe:[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":"gMgmG","./operation":"hyTBr","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],dmtGN:[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":"gMgmG","./operation":"hyTBr","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],ceEsl:[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":"gMgmG","./operation":"hyTBr","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],kxLEJ:[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":"gMgmG","./operation":"hyTBr","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],co9ZC:[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"),u=e("./operation"),p=e("./reshape");let c=(0,u.op)({conv1d_:function(e,t,r,n,s="NWC",u=1,c){let d=(0,a.convertToTensor)(e,"x","conv1d"),f=(0,a.convertToTensor)(t,"filter","conv1d"),h=d,m=!1;2===d.rank&&(m=!0,h=(0,p.reshape)(d,[1,d.shape[0],d.shape[1]])),o.assert(3===h.rank,()=>`Error in conv1d: input must be rank 3, but got rank ${h.rank}.`),o.assert(3===f.rank,()=>`Error in conv1d: filter must be rank 3, but got rank ${f.rank}.`),i.checkPadOnDimRoundingMode("conv1d",n,c),o.assert(h.shape[2]===f.shape[1],()=>`Error in conv1d: depth of input (${h.shape[2]}) must match input depth for filter ${f.shape[1]}.`),o.assert(i.eitherStridesOrDilationsAreOne(r,u),()=>`Error in conv1D: Either stride or dilation must be 1. 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Got strides ${r} and dilations '${p}'`),i.assert("NDHWC"===s,()=>`Error in conv3d: got dataFormat of ${s} but only NDHWC is currently supported.`),i.assert((0,u.stridesOrDilationsArePositive)(p),()=>"Error in conv3D: Dilated rates should be larger than 0."),i.assert((0,u.stridesOrDilationsArePositive)(r),()=>"Error in conv3D: Strides should be larger than 0.");let g={x:h,filter:f},x=a.ENGINE.runKernel(o.Conv3D,g,{strides:r,pad:n,dataFormat:s,dilations:p});return m?(0,c.reshape)(x,[x.shape[1],x.shape[2],x.shape[3],x.shape[4]]):x}})},{"../engine":"gtimw","../kernel_names":"agfs7","../tensor_util_env":"4hoNq","../util":"lLzfH","./conv_util":"i0dk6","./operation":"hyTBr","./reshape":"aTsgx","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],jxCMI:[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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a=e("../../engine"),o=e("../../gradients"),l=e("../../kernel_names"),i=e("../../tensor_util"),u=e("../../tensor_util_env"),p=e("../../util"),c=e("../add"),d=e("../broadcast_util"),f=e("../conv2d"),h=e("../conv2d_backprop_filter"),m=e("../conv2d_backprop_input"),g=e("../conv_util"),x=e("../fused_util"),v=e("../operation"),y=e("../reshape");let _=(0,v.op)({fusedConv2d_:function({x:e,filter:t,strides:r,pad:n,dataFormat:s="NHWC",dilations:v=[1,1],dimRoundingMode:_,bias:b,activation:k="linear",preluActivationWeights:T,leakyreluAlpha:w}){let I,j;if(k=k||"linear",!1===(0,x.shouldFuse)(a.ENGINE.state.gradientDepth,k)){p.assert("NHWC"===s,()=>`Error in fused conv2d: got dataFormat of ${s} but only NHWC is currently supported for the case of gradient depth is 0 and the activation is not linear.`);let a=(0,f.conv2d)(e,t,r,n,s,v,_);return null!=b&&(a=(0,c.add)(a,b)),(0,x.applyActivation)(a,k,T,w)}let C=(0,u.convertToTensor)(e,"x","conv2d","float32"),N=(0,u.convertToTensor)(t,"filter","conv2d","float32"),S=C,E=!1;3===C.rank&&(E=!0,S=(0,y.reshape)(C,[1,C.shape[0],C.shape[1],C.shape[2]])),p.assert(4===S.rank,()=>`Error in fused conv2d: input must be rank 4, but got rank ${S.rank}.`),p.assert(4===N.rank,()=>`Error in fused conv2d: filter must be rank 4, but got rank ${N.rank}.`),g.checkPadOnDimRoundingMode("fused conv2d",n,_);let A="NHWC"===s?S.shape[3]:S.shape[1];p.assert(N.shape[2]===A,()=>`Error in conv2d: depth of input (${A}) must match input depth for filter ${N.shape[2]}.`),p.assert(g.eitherStridesOrDilationsAreOne(r,v),()=>`Error in conv2D: Either strides or dilations must be 1. Got strides ${r} and dilations '${v}'`);let F=g.computeConv2DInfo(S.shape,N.shape,r,v,n,_);if(null!=b&&(I=(0,u.convertToTensor)(b,"bias","fused conv2d"),[I]=(0,i.makeTypesMatch)(I,C),"NHWC"===s?d.assertAndGetBroadcastShape(F.outShape,I.shape):(p.assert(I.shape.length<=1,()=>`Error in fused conv2d: only supports scalar or 1-D Tensor bias for NCHW format but got the bias of rank-${I.shape.length}.`),p.assert(0===I.shape.length||I.shape[0]===F.outChannels||1===I.shape[0],()=>`Error in fused conv2d: bias shape (${I.shape}) is not compatible with the number of output channels (${F.outChannels})`))),null!=T){let e=T.shape;if(p.assert(e.length<=1||3===e.length,()=>`Error in fused conv2d: only supports scalar, 1-D Tensor or 3-D Tensor PReLU activation weights but got a tensor of rank-${e.length}.`),1===e.length)p.assert(1===e[0]||e[0]===F.outChannels,()=>`Error in fused conv2d: PReLU activation weights (${e}) is not compatible with the number of output channels (${F.outChannels}).`);else if(3===e.length)try{d.assertAndGetBroadcastShape(e,F.outShape)}catch(t){throw Error(`Error in fused conv2d: PReLU activation weights (${e}) is not compatible with the output shape of the conv2d (${F.outShape}).`)}j=(0,u.convertToTensor)(T,"prelu weights","fused conv2d")}let R=(e,t)=>{p.assert("NHWC"===s,()=>`Error in gradient of fused conv2D: got dataFormat of ${s} but only NHWC is currently supported.`);let[a,o,l,i]=t,u=(0,x.getFusedDyActivation)(e,l,k);p.assert(g.tupleValuesAreOne(v),()=>`Error in gradient of fused conv2D: dilation rates greater than 1 are not yet supported in gradients. 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f=t;3===f.rank&&(f=(0,p.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 h="NHWC"===u?d.shape[3]:d.shape[1],m="NHWC"===u?f.shape[3]:f.shape[1];l.assert(h===r[2],()=>`Error in conv2dDerFilter: depth of input ${h}) must match input depth in filter (${r[2]}.`),l.assert(m===r[3],()=>`Error in conv2dDerFilter: depth of dy (${m}) must match output depth for filter (${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:u,dimRoundingMode:c,filterShape:r})}})},{"../engine":"gtimw","../kernel_names":"agfs7","../util":"lLzfH","./conv_util":"i0dk6","./operation":"hyTBr","./reshape":"aTsgx","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],dJmcU:[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",()=>v),s.export(r,"shouldFuse",()=>y);var a=e("./broadcast_util"),o=e("./elu"),l=e("./leaky_relu"),i=e("./mul"),u=e("./prelu"),p=e("./relu"),c=e("./relu6"),d=e("./reshape"),f=e("./sigmoid"),h=e("./step"),m=e("./sum");function g(e,t,r){if(null==r||"linear"===r)return e;if("relu"===r)return(0,i.mul)(e,(0,h.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,m.sum)(r,n)),(0,d.reshape)(r,e.shape)}function v(e,t,r,n){if("linear"===t)return e;if("relu"===t)return(0,p.relu)(e);if("elu"===t)return(0,o.elu)(e);if("relu6"===t)return(0,c.relu6)(e);if("prelu"===t)return(0,u.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 y=(e,t)=>!(e>0)||"linear"===t},{"./broadcast_util":"5OjHc","./elu":"dBwXu","./leaky_relu":"cbLfe","./mul":"1OlNG","./prelu":"3aTLU","./relu":"lnyoN","./relu6":"hKBJU","./reshape":"aTsgx","./sigmoid":"1G17C","./step":"elPQj","./sum":"gHwwi","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],"7GmMh":[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"depthwiseConv2d",()=>_);var a=e("../../engine"),o=e("../../gradients"),l=e("../../kernel_names"),i=e("../../tensor_util"),u=e("../../tensor_util_env"),p=e("../../util"),c=e("../add"),d=e("../broadcast_util"),f=e("../conv_util"),h=e("../depthwise_conv2d"),m=e("../depthwise_conv2d_native_backprop_filter"),g=e("../depthwise_conv2d_native_backprop_input"),x=e("../fused_util"),v=e("../operation"),y=e("../reshape");let _=(0,v.op)({fusedDepthwiseConv2d_:function({x:e,filter:t,strides:r,pad:n,dataFormat:s="NHWC",dilations:v=[1,1],dimRoundingMode:_,bias:b,activation:k="linear",preluActivationWeights:T,leakyreluAlpha:w}){let I,j;if(!1===(0,x.shouldFuse)(a.ENGINE.state.gradientDepth,k)){let a=(0,h.depthwiseConv2d)(e,t,r,n,s,v,_);return null!=b&&(a=(0,c.add)(a,b)),(0,x.applyActivation)(a,k,T,w)}let C=(0,u.convertToTensor)(e,"x","depthwiseConv2d","float32"),N=(0,u.convertToTensor)(t,"filter","depthwiseConv2d","float32"),S=C,E=!1;3===C.rank&&(E=!0,S=(0,y.reshape)(C,[1,C.shape[0],C.shape[1],C.shape[2]])),p.assert(4===S.rank,()=>`Error in fused depthwiseConv2d: input must be rank 4, but got rank ${S.rank}.`),p.assert(4===N.rank,()=>`Error in fused depthwiseConv2d: filter must be rank 4, but got rank ${N.rank}.`),p.assert(S.shape[3]===N.shape[2],()=>`Error in fused depthwiseConv2d: number of input channels (${S.shape[3]}) must match the inChannels dimension in filter ${N.shape[2]}.`),null==v&&(v=[1,1]),p.assert(f.eitherStridesOrDilationsAreOne(r,v),()=>`Error in fused depthwiseConv2d: Either strides or dilations must be 1. Got strides ${r} and dilations '${v}'`),f.checkPadOnDimRoundingMode("fused depthwiseConv2d",n,_);let A=f.computeConv2DInfo(S.shape,N.shape,r,v,n,_,!0);null!=b&&(I=(0,u.convertToTensor)(b,"bias","fused conv2d"),[I]=(0,i.makeTypesMatch)(I,C),d.assertAndGetBroadcastShape(A.outShape,I.shape)),null!=T&&(j=(0,u.convertToTensor)(T,"prelu weights","fused depthwiseConv2d"));let F=(e,t)=>{p.assert(f.tupleValuesAreOne(v),()=>`Error in gradient of fused depthwiseConv2d: dilation rates greater than 1 are not yet supported. Got dilations '${v}'`);let[s,a,o,l]=t,i=(0,x.getFusedDyActivation)(e,o,k),u=(0,g.depthwiseConv2dNativeBackpropInput)(a.shape,i,s,r,n,v,_),c=(0,m.depthwiseConv2dNativeBackpropFilter)(a,i,s.shape,r,n,v,_);return null!=l?[u,c,(0,x.getFusedBiasGradient)(I,i)]:[u,c]},R={x:S,filter:N,bias:I,preluActivationWeights:j},D={strides:r,pad:n,dataFormat:s,dilations:v,dimRoundingMode:_,activation:k,leakyreluAlpha:w};return null==b?(0,o.customGrad)((e,t,r)=>{let n=a.ENGINE.runKernel(l.FusedDepthwiseConv2D,R,D);return r([t,e,n]),E&&(n=(0,y.reshape)(n,[n.shape[1],n.shape[2],n.shape[3]])),{value:n,gradFunc:F}})(S,N):(0,o.customGrad)((e,t,r,n)=>{let s=a.ENGINE.runKernel(l.FusedDepthwiseConv2D,R,D);return n([t,e,s,r]),E&&(s=(0,y.reshape)(s,[s.shape[1],s.shape[2],s.shape[3]])),{value:s,gradFunc:F}})(S,N,I)}})},{"../../engine":"gtimw","../../gradients":"3aQK6","../../kernel_names":"agfs7","../../tensor_util":"j3qzf","../../tensor_util_env":"4hoNq","../../util":"lLzfH","../add":"hFQoV","../broadcast_util":"5OjHc","../conv_util":"i0dk6","../depthwise_conv2d":"gd3xg","../depthwise_conv2d_native_backprop_filter":"2SM9P","../depthwise_conv2d_native_backprop_input":"bmRr0","../fused_util":"dJmcU","../operation":"hyTBr","../reshape":"aTsgx","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],"2SM9P":[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"depthwiseConv2dNativeBackpropFilter",()=>u);var a=e("../engine"),o=e("../kernel_names"),l=e("./operation"),i=e("./reshape");let u=(0,l.op)({depthwiseConv2dNativeBackpropFilter_:function(e,t,r,n,s,l=[1,1],u){let p=e;3===e.rank&&(p=(0,i.reshape)(e,[1,e.shape[0],e.shape[1],e.shape[2]]));let c=t;3===c.rank&&(c=(0,i.reshape)(t,[1,t.shape[0],t.shape[1],t.shape[2]]));let d={x:p,dy:c};return a.ENGINE.runKernel(o.DepthwiseConv2dNativeBackpropFilter,d,{strides:n,pad:s,dimRoundingMode:u,dilations:l,filterShape:r})}})},{"../engine":"gtimw","../kernel_names":"agfs7","./operation":"hyTBr","./reshape":"aTsgx","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],bmRr0:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"depthwiseConv2dNativeBackpropInput",()=>u);var a=e("../engine"),o=e("../kernel_names"),l=e("./operation"),i=e("./reshape");let u=(0,l.op)({depthwiseConv2dNativeBackpropInput_:function(e,t,r,n,s,l=[1,1],u){let p=t,c=!1;3===t.rank&&(c=!0,p=(0,i.reshape)(t,[1,t.shape[0],t.shape[1],t.shape[2]]));let d={dy:p,filter:r},f=a.ENGINE.runKernel(o.DepthwiseConv2dNativeBackpropInput,d,{strides:n,pad:s,dimRoundingMode:u,dilations:l,inputShape:e});return c?(0,i.reshape)(f,[f.shape[1],f.shape[2],f.shape[3]]):f}})},{"../engine":"gtimw","../kernel_names":"agfs7","./operation":"hyTBr","./reshape":"aTsgx","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],"1gjNc":[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"matMul",()=>x);var a=e("../../engine"),o=e("../../gradients"),l=e("../../kernel_names"),i=e("../../tensor_util"),u=e("../../tensor_util_env"),p=e("../../util"),c=e("../add"),d=e("../broadcast_util"),f=e("../fused_util"),h=e("../mat_mul"),m=e("../operation"),g=e("../reshape");let x=(0,m.op)({fusedMatMul_:function({a:e,b:t,transposeA:r=!1,transposeB:n=!1,bias:s,activation:m="linear",preluActivationWeights:x,leakyreluAlpha:v=.2}){let y,_;if(!1===(0,f.shouldFuse)(a.ENGINE.state.gradientDepth,m)){let 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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":"loqXi"}],"3dEn3":[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":"loqXi"}],c3DS0:[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":"loqXi"}],"5Yh4i":[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"GraphExecutor",()=>p);var a=e("@tensorflow/tfjs-core"),o=e("../operations/executors/utils"),l=e("../operations/operation_executor"),i=e("./execution_context"),u=e("./model_analysis");class p{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}:${e.defaultOutput}`:t})}get functions(){return Object.keys(this._functions).reduce((e,t)=>(e[t]=this._functions[t].signature,e),{})}constructor(e,t){this.graph=e,this.parent=t,this.compiledMap=new Map,this.parseNodeNameCache=new Map,this._weightMap={},this.SEPARATOR=",",this._functions={},this._functionExecutorMap={},this.keepIntermediateTensors=!1,this._outputs=e.outputs,this._inputs=e.inputs,this._initNodes=e.initNodes,this._signature=e.signature,this._functions=e.functions,null!=e.functions&&Object.keys(e.functions).forEach(t=>{this._functionExecutorMap[t]=new p(e.functions[t],this)})}getCompilationKey(e,t){let r=e.map(e=>e.name).sort(),n=t.map(e=>e.name).sort();return r.join(this.SEPARATOR)+"--"+n.join(this.SEPARATOR)}compile(e,t){let r=(0,u.getExecutionSubgraph)(e,t,this.weightMap,this._initNodes),{missingInputs:n,dynamicNode:s,syncInputs:a}=r;if(null!=s)throw Error(`This execution contains the node '${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: [${n}]`)}let o=(0,u.getNodesInTopologicalOrder)(this.graph,r),l=(0,u.getNodeLiveUntilMap)(o);return{orderedNodes:o,nodeLiveUntilMap:l}}cloneAndKeepTensor(e){if(null==e)return null;let t=e.clone();return(0,a.keep)(t),t}cloneTensorList(e){return e?e.map(e=>this.cloneAndKeepTensor(e)):null}cloneTensorMap(e){return Object.fromEntries(Object.entries(e).map(([e,t])=>[e,this.cloneTensorList(t)]))}execute(e,t){this.disposeIntermediateTensors();let r=Object.keys(e=this.mapInputs(e)).sort();this.checkInputs(e),this.checkInputShapeAndType(e),t=this.mapOutputs(t),this.checkOutputs(t);let n=r.map(e=>this.graph.nodes[(0,o.parseNodeName)(e)[0]]),s=t.map(e=>(0,o.parseNodeName)(e)[0]),u=new Set(s),p=s.map(e=>this.graph.nodes[e]);0===p.length&&(p=this._outputs);let c=this.getCompilationKey(n,p),d=this.compiledMap.get(c);null==d&&(d=this.compile(e,p),this.compiledMap.set(c,d));try{this.keepIntermediateTensors=(0,a.env)().getBool("KEEP_INTERMEDIATE_TENSORS")}catch(e){this.keepIntermediateTensors=!1,console.warn(e.message)}let f={},h={};return(0,a.tidy)(()=>{let r=new(0,i.ExecutionContext)(this.weightMap,f,h,this.functionExecutorMap,this.parseNodeNameCache),n=Object.assign({},this.weightMap);this.keepIntermediateTensors&&(this.clonedTensorsMap=this.cloneTensorMap(this.weightMap)),Object.keys(e).forEach(t=>{let[s,a]=(0,o.parseNodeName)(t,r),l=[];l[a]=e[t],n[s]=l,this.keepIntermediateTensors&&(this.clonedTensorsMap[s]=this.cloneTensorList(l))});let s=this.getFrozenTensorIds(n),{orderedNodes:p,nodeLiveUntilMap:c}=d;for(let e of p){if(n[e.name])continue;let t=(0,l.executeOp)(e,n,r,this._resourceManager);if(a.util.isPromise(t))throw Error(`The execution of the op '${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,u,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,u.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,u.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,u.isControlFlow)(e)&&null!=a){for(let e of a)if(!((0,u.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 u=await this.executeWithControlFlow(e,l,t,r),p=t.map(e=>(0,o.getTensor)(e,u,l)),c=new Set([...p.map(e=>e.id),...Object.keys(e).map(t=>e[t].id),...this.weightIds]);return Object.values(u).forEach(e=>{e.forEach(e=>{!e||e.isDisposed||c.has(e.id)||e.dispose()})}),null==this.parent&&l.dispose(c),p}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),p=l.map(e=>this.graph.nodes[e]);0===p.length&&(p=this._outputs);let{usedNodes:c,missingInputs:d,dynamicNode:f,syncInputs:h}=(0,u.getExecutionSubgraph)(e,p,this.weightMap,this._initNodes),m=[...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={},v=this.getFrozenTensorIds(g),y={};for(;m.length>0;){let e=this.processStack(a,m,t,g,y,v,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 _=p.filter(e=>!(0,u.isControlFlow)(e)&&!(0,o.getTensor)(e.name,g,t)).map(e=>e.name);if(_.length>0){let e="";throw null!=f&&(e=`Alternatively, to avoid the dynamic ops, use model.execute() and specify the inputs [${h}]`),Error(`Cannot compute the outputs [${_}] from the provided inputs [${s}]. Consider providing the following inputs: [${d}]. ${e}`)}return g}processStack(e,t,r,n,s,i,u,p,c){let d=[];for(;t.length>0;){let e=t.pop();r.currentContext=e.contexts;let f="";if("Enter"===e.node.op&&(0,o.getParamValue)("isConstant",e.node,n,r)&&([f]=(0,o.getNodeNameAndIndex)(e.node.name,r)),null==n[e.node.name]){let h=(0,l.executeOp)(e.node,n,r,this._resourceManager);f||([f]=(0,o.getNodeNameAndIndex)(e.node.name,r));let m=r.currentContext;a.util.isPromise(h)?d.push(h.then(a=>(n[f]=a,this.keepIntermediateTensors&&(this.clonedTensorsMap[f]=this.cloneTensorList(a)),r.currentContext=m,this.checkTensorForDisposal(f,e.node,n,r,i,u,p),this.processChildNodes(e.node,t,r,n,s,c),a))):(n[f]=h,this.keepIntermediateTensors&&(this.clonedTensorsMap[f]=this.cloneTensorList(h)),this.checkTensorForDisposal(f,e.node,n,r,i,u,p),this.processChildNodes(e.node,t,r,n,s,c))}else this.processChildNodes(e.node,t,r,n,s,c)}return d}processChildNodes(e,t,r,n,s,a){e.children.forEach(e=>{let[l]=(0,o.getNodeNameAndIndex)(e.name,r);!s[l]&&a.has(e.name)&&("Merge"===e.op?e.inputNames.some(e=>!!(0,o.getTensor)(e,n,r))&&(s[l]=!0,t.push({contexts:r.currentContext,node:e})):e.inputNames.every(e=>!!(0,o.getTensor)(e,n,r))&&(s[l]=!0,t.push({contexts:r.currentContext,node:e})))})}dispose(){Object.keys(this.weightMap).forEach(e=>this.weightMap[e].forEach(e=>e.dispose()))}checkInputShapeAndType(e){Object.keys(e).forEach(t=>{let r=e[t],[n]=(0,o.parseNodeName)(t),s=this.graph.nodes[n];if(s.attrParams.shape&&s.attrParams.shape.value){let e=s.attrParams.shape.value,t=e.length===r.shape.length&&r.shape.every((t,r)=>-1===e[r]||e[r]===t);a.util.assert(t,()=>`The shape of dict['${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":"hADTC","../operations/executors/utils":"5HlwR","../operations/operation_executor":"jQwBO","./execution_context":"RqD6m","./model_analysis":"kqHTr","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],jQwBO:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"executeOp",()=>N);var a=e("@tensorflow/tfjs-core"),o=e("./custom_op/node_value_impl"),l=e("./custom_op/register"),i=e("./executors/arithmetic_executor"),u=e("./executors/basic_math_executor"),p=e("./executors/control_executor"),c=e("./executors/convolution_executor"),d=e("./executors/creation_executor"),f=e("./executors/dynamic_executor"),h=e("./executors/evaluation_executor"),m=e("./executors/graph_executor"),g=e("./executors/hash_table_executor"),x=e("./executors/image_executor"),v=e("./executors/logical_executor"),y=e("./executors/matrices_executor"),_=e("./executors/normalization_executor"),b=e("./executors/ragged_executor"),k=e("./executors/reduction_executor"),T=e("./executors/slice_join_executor"),w=e("./executors/sparse_executor"),I=e("./executors/spectral_executor"),j=e("./executors/string_executor"),C=e("./executors/transformation_executor");function N(e,t,r,n,s=a.tidy){let S=((e,t,r)=>{switch(e.category){case"arithmetic":return s(()=>i.executeOp(e,t,r));case"basic_math":return s(()=>u.executeOp(e,t,r));case"control":return p.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(()=>h.executeOp(e,t,r));case"image":return s(()=>x.executeOp(e,t,r));case"graph":return s(()=>m.executeOp(e,t,r));case"logical":return s(()=>v.executeOp(e,t,r));case"matrices":return s(()=>y.executeOp(e,t,r));case"normalization":return s(()=>_.executeOp(e,t,r));case"ragged":return s(()=>b.executeOp(e,t,r));case"reduction":return s(()=>k.executeOp(e,t,r));case"slice_join":return s(()=>T.executeOp(e,t,r));case"sparse":return s(()=>w.executeOp(e,t,r));case"spectral":return s(()=>I.executeOp(e,t,r));case"string":return s(()=>j.executeOp(e,t,r));case"transformation":return s(()=>C.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(S)?S.then(e=>[].concat(e)):[].concat(S)}},{"@tensorflow/tfjs-core":"hADTC","./custom_op/node_value_impl":"eybSd","./custom_op/register":"3biEy","./executors/arithmetic_executor":"aRYK5","./executors/basic_math_executor":"13Nub","./executors/control_executor":"cORBu","./executors/convolution_executor":"8v2C7","./executors/creation_executor":"iZBgV","./executors/dynamic_executor":"boeiz","./executors/evaluation_executor":"2Wwvd","./executors/graph_executor":"7NhkA","./executors/hash_table_executor":"8aJJs","./executors/image_executor":"bjBkW","./executors/logical_executor":"bLfko","./executors/matrices_executor":"9dcJo","./executors/normalization_executor":"ijF4h","./executors/ragged_executor":"2NxHF","./executors/reduction_executor":"aPxOS","./executors/slice_join_executor":"jugxk","./executors/sparse_executor":"bo1UF","./executors/spectral_executor":"a9k3w","./executors/string_executor":"iQDRL","./executors/transformation_executor":"lGcIS","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],eybSd:[function(e,t,r,n){var 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u={forceHalfFloat:i.forceHalfFloat}},{"@tensorflow/tfjs-core":"hADTC","./backend_webgl":"kocjS","./version":"4j4u9","./webgl":"2uHRt","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],kocjS:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"EPSILON_FLOAT32",()=>I),s.export(r,"EPSILON_FLOAT16",()=>j),s.export(r,"getBinaryCache",()=>N),s.export(r,"MathBackendWebGL",()=>E),e("./flags_webgl");var a=e("@tensorflow/tfjs-core"),o=e("./canvas_util"),l=e("./decode_matrix_gpu"),i=e("./decode_matrix_packed_gpu"),u=e("./encode_float_gpu"),p=e("./encode_float_packed_gpu"),c=e("./encode_matrix_gpu"),d=e("./encode_matrix_packed_gpu"),f=e("./gpgpu_context"),h=e("./gpgpu_math"),m=e("./kernel_utils/shared"),g=e("./pack_gpu"),x=e("./reshape_packed_gpu"),v=e("./tex_util"),y=e("./texture_manager"),_=e("./unaryop_gpu"),b=e("./unaryop_packed_gpu"),k=e("./unpack_gpu"),T=e("./webgl_util");let 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e=(0,o.getWebGLContext)((0,a.env)().getNumber("WEBGL_VERSION"));t=new(0,f.GPGPUContext)(e),this.binaryCache=N((0,a.env)().getNumber("WEBGL_VERSION")),this.gpgpuCreatedLocally=!0}this.gpgpu=t,this.canvas=this.gpgpu.gl.canvas,this.textureManager=new(0,y.TextureManager)(this.gpgpu),this.numMBBeforeWarning=null==(0,a.env)().global.screen?1024:(0,a.env)().global.screen.height*(0,a.env)().global.screen.width*window.devicePixelRatio*600/1024/1024,this.texData=new(0,a.DataStorage)(this,(0,a.engine)())}numDataIds(){return this.texData.numDataIds()-this.pendingDeletes}writeTexture(e,t,r,n,s,a){let o=this.makeTensorInfo(t,r),l=this.texData.get(o.dataId);l.isPacked=!1,l.texture={texture:e,texShape:[n,s]},l.texShape=[n,s];let i=T.getShapeAs3D(t),u=new(0,c.EncodeMatrixProgram)(i,!1,a),p=this.runWebGLProgram(u,[o],r,[[n,s]]);return p.shape=t,l.texture=null,this.disposeIntermediateTensorInfo(o),p.dataId}write(e,t,r){if(((0,a.env)().getBool("WEBGL_CHECK_NUMERICAL_PROBLEMS")||(0,a.env)().getBool("DEBUG"))&&this.checkNumericalProblems(e),"complex64"===r&&null!=e)throw Error("Cannot write to a complex64 dtype. 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Consider enabling float32 rendering: 'tf.env().set('WEBGL_RENDER_FLOAT32_ENABLED', true);'`);throw Error(`The value ${r} cannot be represented on this device.`)}}}getValuesFromTexture(e){let{shape:t,dtype:r,isPacked:n}=this.texData.get(e),s=a.util.sizeFromShape(t);if((0,a.env)().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")){let r=this.decode(e),n=this.texData.get(r.dataId),a=this.gpgpu.downloadMatrixFromPackedTexture(n.texture.texture,...v.getDenseTexShape(t)).subarray(0,s);return this.disposeIntermediateTensorInfo(r),a}let o=(0,a.env)().getBool("WEBGL_PACK")&&!0===n,l=o?T.getShapeAs3D(t):t,i=o?new(0,p.EncodeFloatPackedProgram)(l):new(0,u.EncodeFloatProgram)(l),c=this.runWebGLProgram(i,[{shape:l,dtype:r,dataId:e}],"float32"),d=this.texData.get(c.dataId),f=this.gpgpu.downloadByteEncodedFloatMatrixFromOutputTexture(d.texture.texture,d.texShape[0],d.texShape[1]).subarray(0,s);return this.disposeIntermediateTensorInfo(c),f}timerAvailable(){return(0,a.env)().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0}time(e){let t=this.activeTimers,r=[],n=!1;null==this.programTimersStack?(this.programTimersStack=r,n=!0):this.activeTimers.push(r),this.activeTimers=r,e();let s=a.util.flatten(this.activeTimers.map(e=>e.query)).filter(e=>null!=e),o=a.util.flatten(this.activeTimers.map(e=>e.name)).filter(e=>null!=e);this.activeTimers=t,n&&(this.programTimersStack=null);let l={uploadWaitMs:this.uploadWaitMs,downloadWaitMs:this.downloadWaitMs,kernelMs:null,wallMs:null};return(async()=>{if((0,a.env)().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0){let e=await Promise.all(s);l.kernelMs=a.util.sum(e),l.getExtraProfileInfo=()=>e.map((e,t)=>({name:o[t],ms:e})).map(e=>`${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 u=this.texData.get(e);u.texture=null,u.texShape=null,u.isPacked=!1,u.slice=null}getTexture(e){return this.uploadToGPU(e),this.texData.get(e).texture.texture}getDataInfo(e){return this.texData.get(e)}shouldExecuteOnCPU(e,t=S){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:u,isUniform:!1},f=h.makeShaderKey(e,c,d),m=this.getAndSaveBinary(f,()=>h.compileProgram(this.gpgpu,e,c,d)),g=null!=this.activeTimers;g&&(l=this.startTimer()),(0,a.env)().get("ENGINE_COMPILE_ONLY")||h.runProgram(this.gpgpu,m,c,d,n),p.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")&&u.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()?I:j}uploadToGPU(e){let t,r=this.texData.get(e),{shape:n,dtype:s,values:o,texture:l,usage:i,isPacked:u}=r;if(null!=l)return;let 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1:w.push(`uniform int ${e.name}Shape;`);break;case 2:w.push(`uniform ivec2 ${e.name}Shape;`);break;case 3:w.push(`uniform ivec3 ${e.name}Shape;`);break;case 4:w.push(`uniform ivec4 ${e.name}Shape;`)}w.push(`uniform ivec2 ${e.name}TexShape;`)}}),r.enableShapeUniforms){switch(t.logicalShape.length){case 1:w.push("uniform int outShape;");break;case 2:w.push("uniform ivec2 outShape;"),w.push("uniform int outShapeStrides;");break;case 3:w.push("uniform ivec3 outShape;"),w.push("uniform ivec2 outShapeStrides;");break;case 4:w.push("uniform ivec4 outShape;"),w.push("uniform ivec3 outShapeStrides;")}w.push("uniform ivec2 outTexShape;")}r.customUniforms&&r.customUniforms.forEach(e=>{w.push(`uniform ${e.type} ${e.name}${e.arrayIndex?`[${e.arrayIndex}]`:""};`)});let I=w.join("\n"),j=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 ${s}() { return ${l.texture2D}(${n}, halfCR); } `;case 1:return function(e,t){let r=e.name,n="get"+r.charAt(0).toUpperCase()+r.slice(1),s=e.shapeInfo.texShape,a=(0,o.getGlslDifferences)();if(t)return` vec4 ${n}(int index) { ivec2 packedTexShape = ivec2(ceil(float(${r}TexShape[0]) / 2.0), ceil(float(${r}TexShape[1]) / 2.0)); vec2 uv = packedUVfrom1D( packedTexShape[0], packedTexShape[1], index); return ${a.texture2D}(${r}, uv); } `;let l=[Math.ceil(s[0]/2),Math.ceil(s[1]/2)];return` vec4 ${n}(int index) { vec2 uv = packedUVfrom1D( ${l[0]}, ${l[1]}, index); return ${a.texture2D}(${r}, uv); } `}(t,r);case 2:return function(e,t){let r=e.shapeInfo.logicalShape,n=e.name,s="get"+n.charAt(0).toUpperCase()+n.slice(1),l=e.shapeInfo.texShape,i=l[0],u=l[1],p=(0,o.getGlslDifferences)();if(null!=l&&a.util.arraysEqual(r,l))return t?` vec4 ${s}(int row, int col) { vec2 uv = (vec2(col, row) + halfCR) / vec2(${n}TexShape[1], ${n}TexShape[0]); return ${p.texture2D}(${n}, uv); } `:` vec4 ${s}(int row, int col) { vec2 uv = (vec2(col, row) + halfCR) / vec2(${u}.0, ${i}.0); return ${p.texture2D}(${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 ${p.texture2D}(${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 ${p.texture2D}(${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=y(t,n.slice(1));return` ${e(s,r)} vec4 ${a}(int b, int row, int col) { return ${a}(${_(["b","row","col"],[1,2])}); } `}let u=(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 ${u.texture2D}(${s}, uv); } `;let p=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( ${p}, ${c}, ${f}, ${d}, b, row, col); return ${u.texture2D}(${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,u=[Math.ceil(i[0]/2),Math.ceil(i[1]/2)],p=u[0],c=u[1],d=Math.ceil(a[l-1]/2),f=d*Math.ceil(a[l-2]/2),h="int b, int row, int col",m=`b * ${f} + (row / 2) * ${d} + (col / 2)`;for(let e=2;e<l-1;e++)h=`int b${e}, `+h,f*=a[l-e-1],m=`b${e} * ${f} + `+m;return` vec4 ${n}(${h}) { int index = ${m}; int texR = index / ${c}; int texC = index - texR * ${c}; vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${c}, ${p}); 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=m(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=m(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:u}=a.util.squeezeShape(n);if(i.length<n.length){let n=y(t,i);return` ${e(n,r)} float ${o}(int row, int col) { return ${o}(${_(["row","col"],u)}); } `}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 p=l[0],c=l[1],d=m(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) / ${p}.0); return sampleTexture(${s}, uv); } `:1===p?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 + ${d}; vec2 uv = uvFromFlat(${p}, ${c}, index); return sampleTexture(${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:u,keptDims:p}=a.util.squeezeShape(n);if(u.length<n.length){let n=y(t,u);return` ${e(n,r)} float ${o}(int row, int col, int depth) { return ${o}(${_(["row","col","depth"],p)}); } `}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],h=t.shapeInfo.flatOffset;if(f===l&&null==h)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==h)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=m(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,u=n[1]*i,{newShape:p,keptDims:c}=a.util.squeezeShape(n);if(p.length<n.length){let n=y(t,p);return` ${e(n,r)} float ${o}(int row, int col, int depth, int depth2) { return ${o}(${_(["row","col","depth","depth2"],c)}); } `}if(t.shapeInfo.isUniform)return` float ${o}(int row, int col, int depth, int depth2) { int index = round(dot(vec4(row, col, depth, depth2), vec4(${u}, ${i}, ${l}, 1))); ${g(t)} } `;let d=t.shapeInfo.flatOffset,f=t.shapeInfo.texShape,h=f[0],x=f[1],v=`int stride2 = ${s}Shape[3];`,b=`int stride1 = ${s}Shape[2] * stride2;`,k=`int stride0 = ${s}Shape[1] * stride1;`;if(x===u&&null==d)return r?` float ${o}(int row, int col, int depth, int depth2) { ${v} ${b} float texR = float(row); float texC = dot(vec3(col, depth, depth2), vec3(stride1, stride2, 1)); vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${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, ${h}.0); return sampleTexture(${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, ${h}.0); return sampleTexture(${s}, uv); } `;let T=m(s);return r?` float ${o}(int row, int col, int depth, int depth2) { // Explicitly use integer operations as dot() only works on floats. ${v} ${b} ${k} int index = row * stride0 + col * stride1 + depth * stride2 + depth2; vec2 uv = uvFromFlat(${s}TexShape[0], ${s}TexShape[1], index + ${T}); return sampleTexture(${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 * ${u} + col * ${i} + depth * ${l} + depth2; vec2 uv = uvFromFlat(${h}, ${x}, index + ${T}); return sampleTexture(${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,u=r[1]*i,{newShape:p,keptDims:c}=a.util.squeezeShape(r);if(p.length<r.length){let r=y(t,p);return` ${e(r)} float ${s}(int row, int col, int depth, int depth2, int depth3) { return ${s}(${_(["row","col","depth","depth2","depth3"],c)}); } `}if(t.shapeInfo.isUniform)return` float ${s}(int row, int col, int depth, int depth2, int depth3) { float index = dot( vec4(row, col, depth, depth2), vec4(${u}, ${i}, ${l}, ${o})) + depth3; ${g(t)} } `;let d=t.shapeInfo.flatOffset,f=t.shapeInfo.texShape,h=f[0],x=f[1];if(x===u&&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, ${h}.0); return sampleTexture(${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, ${h}.0); return sampleTexture(${n}, uv); } `;let v=m(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 * ${u} + col * ${i} + depth * ${l} + depth2 * ${o} + depth3 + ${v}; vec2 uv = uvFromFlat(${h}, ${x}, index); return sampleTexture(${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=y(t,o);return` ${e(r)} float ${s}(int row, int col, int depth, int depth2, int depth3, int depth4) { return ${s}(${_(["row","col","depth","depth2","depth3","depth4"],l)}); } `}let i=r[5],u=r[4]*i,p=r[3]*u,c=r[2]*p,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}, ${p}, ${u})) + dot( vec2(depth3, depth4), vec2(${i}, 1))); ${g(t)} } `;let f=t.shapeInfo.flatOffset,h=t.shapeInfo.texShape,x=h[0],v=h[1];if(v===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}, ${p}, ${u}, ${i})) + float(depth4); vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${v}.0, ${x}.0); return sampleTexture(${n}, uv); } `;if(v===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]}, ${r[4]})) + float(depth3); int texC = depth4; vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${v}.0, ${x}.0); return sampleTexture(${n}, uv); } `;let b=m(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 * ${p} + depth2 * ${u} + depth3 * ${i} + depth4 + ${b}; vec2 uv = uvFromFlat(${x}, ${v}, index); return sampleTexture(${n}, uv); } `}(t);default:throw Error(`${n.length}-D input sampling is not yet supported`)}}(e,n);let l=e.shapeInfo.logicalShape,u=t.logicalShape;return l.length<=u.length&&(r?s+=function(e,t){let r,n=e.name,s=n.charAt(0).toUpperCase()+n.slice(1),o=e.shapeInfo.logicalShape.length,l=t.logicalShape.length,u=i(e.shapeInfo.logicalShape,t.logicalShape),p=x(l),c=l-o,d=["x","y","z","w","u","v"];r=0===o?"":l<2&&u.length>=1?"coords = 0;":u.map(e=>`coords.${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 h="return outputValue;",m=1===a.util.sizeFromShape(e.shapeInfo.logicalShape),g=1===a.util.sizeFromShape(t.logicalShape);if(1!==o||m||g){if(m&&!g)h=1===l?` return vec4(outputValue.x, outputValue.x, 0., 0.); `:` return vec4(outputValue.x); `;else if(u.length){let e=o-2,t=o-1;u.indexOf(e)>-1&&u.indexOf(t)>-1?h="return vec4(outputValue.x);":u.indexOf(e)>-1?h="return vec4(outputValue.x, outputValue.y, outputValue.x, outputValue.y);":u.indexOf(t)>-1&&(h="return vec4(outputValue.xx, outputValue.zz);")}}else h=` return vec4(outputValue.xy, outputValue.xy); `;return` vec4 ${"get"+s+"AtOutCoords"}() { ${p} coords = getOutputCoords(); ${r} vec4 outputValue = get${s}(${f}); ${h} } `}(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,u=e.shapeInfo.texShape,p=e.shapeInfo.logicalShape.length,c=t.logicalShape.length;if(!e.shapeInfo.isUniform&&p===c&&null==e.shapeInfo.flatOffset&&a.util.arraysEqual(u,l))return` float ${o}() { return sampleTexture(${n}, resultUV); } `;let d=x(c),f=i(e.shapeInfo.logicalShape,t.logicalShape),h=c-p,m=["x","y","z","w","u","v"];r=0===p?"":c<2&&f.length>=1?"coords = 0;":f.map(e=>`coords.${m[e+h]} = 0;`).join("\n");let g="";return g=c<2&&p>0?"coords":e.shapeInfo.logicalShape.map((e,t)=>`coords.${m[t+h]}`).join(", "),` float ${o}() { ${d} coords = getOutputCoords(); ${r} return get${s}(${g}); } `}(e,t)),s})(e,t,r.packedInputs,r.enableShapeUniforms)).join("\n"),C=t.texShape,N=(0,o.getGlslDifferences)(),S=(n=N,` float sampleTexture(sampler2D textureSampler, vec2 uv) { return ${n.texture2D}(textureSampler, uv).r; } `),E=(s=N,`${s.version} precision highp float; precision highp int; precision highp sampler2D; ${s.varyingFs} vec2 resultUV; ${s.defineOutput} const vec2 halfCR = vec2(0.5, 0.5); struct ivec5 { int x; int y; int z; int w; int u; }; struct ivec6 { int x; int y; int z; int w; int u; int v; }; uniform float NAN; ${s.defineSpecialNaN} ${s.defineSpecialInf} ${s.defineRound} int imod(int x, int y) { return x - y * (x / y); } int idiv(int a, int b, float sign) { int res = a / b; int mod = imod(a, b); if (sign< 0. && mod != 0) { res -= 1; } return res; } //Based on the work of Dave Hoskins //https://www.shadertoy.com/view/4djSRW #define HASHSCALE1 443.8975 float random(float seed){ vec2 p = resultUV * seed; vec3 p3 = fract(vec3(p.xyx) * HASHSCALE1); p3 += dot(p3, p3.yzx + 19.19); return fract((p3.x + p3.y) * p3.z); } ${p} ${c} ${d} `);return t.isPacked?(k=function(e,t,r){switch(e.length){case 0:return h();case 1:var n,s;let o;return n=t,s=r,1===(o=[Math.ceil(n[0]/2),Math.ceil(n[1]/2)])[0]?s?` 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 * ${o[1]} + resTexRC.y); } `;case 2:var l=e,i=t,u=r;let p=[Math.ceil(i[0]/2),Math.ceil(i[1]/2)];if(a.util.arraysEqual(l,i))return u?` ivec2 getOutputCoords() { ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0)); return 2 * ivec2(resultUV.yx * vec2(packedTexShape[0], packedTexShape[1])); } `:` ivec2 getOutputCoords() { return 2 * ivec2(resultUV.yx * vec2(${p[0]}, ${p[1]})); } `;let c=Math.ceil(l[1]/2);return u?` ivec2 getOutputCoords() { ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0)); int texelsInLogicalRow = int(ceil(float(outShape[1]) / 2.0)); ivec2 resTexRC = ivec2(resultUV.yx * vec2(packedTexShape[0], packedTexShape[1])); int index = resTexRC.x * packedTexShape[1] + resTexRC.y; int r = 2 * (index / texelsInLogicalRow); int c = imod(index, texelsInLogicalRow) * 2; return ivec2(r, c); } `:` ivec2 getOutputCoords() { ivec2 resTexRC = ivec2(resultUV.yx * vec2(${p[0]}, ${p[1]})); int index = resTexRC.x * ${p[1]} + resTexRC.y; int r = 2 * (index / ${c}); int c = imod(index, ${c}) * 2; return ivec2(r, c); } `;case 3:var d=e,f=t,m=r;if(m)return` ivec3 getOutputCoords() { ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0)); int texelsInLogicalRow = int(ceil(float(outShape[2]) / 2.0)); int texelsInBatch = texelsInLogicalRow * int(ceil(float(outShape[1]) / 2.0)); ivec2 resTexRC = ivec2(resultUV.yx * vec2(packedTexShape[0], packedTexShape[1])); int index = resTexRC.x * packedTexShape[1] + resTexRC.y; int b = index / texelsInBatch; index -= b * texelsInBatch; int r = 2 * (index / texelsInLogicalRow); int c = imod(index, texelsInLogicalRow) * 2; return ivec3(b, r, c); } `;let g=[Math.ceil(f[0]/2),Math.ceil(f[1]/2)],x=Math.ceil(d[2]/2),v=x*Math.ceil(d[1]/2);return` ivec3 getOutputCoords() { ivec2 resTexRC = ivec2(resultUV.yx * vec2(${g[0]}, ${g[1]})); int index = resTexRC.x * ${g[1]} + resTexRC.y; int b = index / ${v}; index -= b * ${v}; int r = 2 * (index / ${x}); int c = imod(index, ${x}) * 2; return ivec3(b, r, c); } `;default:return function(e,t,r){if(r)return` ivec4 getOutputCoords() { ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0)); ivec2 resTexRC = ivec2(resultUV.yx * vec2(packedTexShape[0], packedTexShape[1])); int index = resTexRC.x * packedTexShape[1] + resTexRC.y; int texelsInLogicalRow = int(ceil(float(outShape[3]) / 2.0)); int texelsInBatch = texelsInLogicalRow * int(ceil(float(outShape[2]) / 2.0)); int texelsInBatchN = texelsInBatch * outShape[1]; int b2 = index / texelsInBatchN; index -= b2 * texelsInBatchN; int b = index / texelsInBatch; index -= b * texelsInBatch; int r = 2 * (index / texelsInLogicalRow); int c = imod(index, texelsInLogicalRow) * 2; return ivec4(b2, b, r, c); } `;let n=[Math.ceil(t[0]/2),Math.ceil(t[1]/2)],s=Math.ceil(e[e.length-1]/2),a=s*Math.ceil(e[e.length-2]/2),o=a,l="",i="b, r, c";for(let t=2;t<e.length-1;t++)o*=e[e.length-t-1],l=` int b${t} = index / ${o}; index -= b${t} * ${o}; `+l,i=`b${t}, `+i;return` ivec${e.length} getOutputCoords() { ivec2 resTexRC = ivec2(resultUV.yx * vec2(${n[0]}, ${n[1]})); int index = resTexRC.x * ${n[1]} + resTexRC.y; ${l} int b = index / ${a}; index -= b * ${a}; int r = 2 * (index / ${s}); int c = imod(index, ${s}) * 2; return ivec${e.length}(${i}); } `}(e,t,r)}}(t.logicalShape,C,r.enableShapeUniforms),u=N,T=` void setOutput(vec4 val) { ${u.output} = val; } `):(k=function(e,t,r){switch(e.length){case 0:return h();case 1:return n=t,s=r,1===n[0]?s?` int getOutputCoords() { return int(resultUV.x * float(outTexShape[1])); } `:` int getOutputCoords() { return int(resultUV.x * ${n[1]}.0); } `:1===n[1]?s?` int getOutputCoords() { return int(resultUV.y * float(outTexShape[0])); } `:` int getOutputCoords() { return int(resultUV.y * ${n[0]}.0); } `:s?` int getOutputCoords() { ivec2 resTexRC = ivec2(resultUV.yx * vec2(outTexShape[0], outTexShape[1])); return resTexRC.x * outTexShape[1] + resTexRC.y; } `:` int getOutputCoords() { ivec2 resTexRC = ivec2(resultUV.yx * vec2(${n[0]}, ${n[1]})); return resTexRC.x * ${n[1]} + resTexRC.y; } `;case 2:return o=e,i=t,u=r,a.util.arraysEqual(o,i)?u?` ivec2 getOutputCoords() { return ivec2(resultUV.yx * vec2(outTexShape[0], outTexShape[1])); } `:` ivec2 getOutputCoords() { return ivec2(resultUV.yx * vec2(${i[0]}, ${i[1]})); } `:1===o[1]?u?` ivec2 getOutputCoords() { ivec2 resTexRC = ivec2(resultUV.yx * vec2(outTexShape[0], outTexShape[1])); int index = resTexRC.x * outTexShape[1] + resTexRC.y; return ivec2(index, 0); } `:` ivec2 getOutputCoords() { ivec2 resTexRC = ivec2(resultUV.yx * vec2(${i[0]}, ${i[1]})); int index = resTexRC.x * ${i[1]} + resTexRC.y; return ivec2(index, 0); } `:1===o[0]?u?` ivec2 getOutputCoords() { ivec2 resTexRC = ivec2(resultUV.yx * vec2(outTexShape[0], outTexShape[1])); int index = resTexRC.x * outTexShape[1] + resTexRC.y; return ivec2(0, index); } `:` ivec2 getOutputCoords() { ivec2 resTexRC = ivec2(resultUV.yx * vec2(${i[0]}, ${i[1]})); int index = resTexRC.x * ${i[1]} + resTexRC.y; return ivec2(0, index); } `:u?` ivec2 getOutputCoords() { ivec2 resTexRC = ivec2(resultUV.yx * vec2(outTexShape[0], outTexShape[1])); int index = resTexRC.x * outTexShape[1] + resTexRC.y; int r = index / outShape[1]; int c = index - r * outShape[1]; return ivec2(r, c); } `:` ivec2 getOutputCoords() { ivec2 resTexRC = ivec2(resultUV.yx * vec2(${i[0]}, ${i[1]})); int index = resTexRC.x * ${i[1]} + resTexRC.y; int r = index / ${o[1]}; int c = index - r * ${o[1]}; return ivec2(r, c); } `;case 3:var n,s,o,i,u,p,c,d,f,m=e,g=t,x=r;if(x){let e=l.getOutputLogicalCoordinatesFromFlatIndexByUniform(["r","c","d"],m);return` ivec3 getOutputCoords() { ivec2 resTexRC = ivec2(resultUV.yx * vec2(outTexShape[0], outTexShape[1])); int index = resTexRC.x * outTexShape[1] + resTexRC.y; ${e} return ivec3(r, c, d); } `}let v=l.getLogicalCoordinatesFromFlatIndex(["r","c","d"],m);return` ivec3 getOutputCoords() { ivec2 resTexRC = ivec2(resultUV.yx * vec2(${g[0]}, ${g[1]})); int index = resTexRC.x * ${g[1]} + resTexRC.y; ${v} return ivec3(r, c, d); } `;case 4:var y=e,_=t,b=r;if(b){let e=l.getOutputLogicalCoordinatesFromFlatIndexByUniform(["r","c","d","d2"],y);return` ivec4 getOutputCoords() { ivec2 resTexRC = ivec2(resultUV.yx * vec2(outTexShape[0], outTexShape[1])); int index = resTexRC.x * outTexShape[1] + resTexRC.y; ${e} return ivec4(r, c, d, d2); } `}let k=l.getLogicalCoordinatesFromFlatIndex(["r","c","d","d2"],y);return` ivec4 getOutputCoords() { ivec2 resTexRC = ivec2(resultUV.yx * vec2(${_[0]}, ${_[1]})); int index = resTexRC.x * ${_[1]} + resTexRC.y; ${k} return ivec4(r, c, d, d2); } `;case 5:let T;return p=e,c=t,T=l.getLogicalCoordinatesFromFlatIndex(["r","c","d","d2","d3"],p),` ivec5 getOutputCoords() { ivec2 resTexRC = ivec2(resultUV.yx * vec2(${c[0]}, ${c[1]})); int index = resTexRC.x * ${c[1]} + resTexRC.y; ${T} ivec5 outShape = ivec5(r, c, d, d2, d3); return outShape; } `;case 6:let w;return d=e,f=t,w=l.getLogicalCoordinatesFromFlatIndex(["r","c","d","d2","d3","d4"],d),` ivec6 getOutputCoords() { ivec2 resTexRC = ivec2(resultUV.yx * vec2(${f[0]}, 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${o};`}).join("")}function l(e,t,r="index"){let n=a.util.computeStrides(t);return n.map((t,s)=>{let a=`int ${e[s]} = ${r} / outShapeStrides[${s}]`,o=s===n.length-1?`int ${e[s+1]} = ${r} - ${e[s]} * outShapeStrides[${s}]`:`index -= ${e[s]} * outShapeStrides[${s}]`;return`${a}; ${o};`}).join("")}function i(e,t,r="index"){let n=function(e,t){let r=e.length,n=e.map(e=>`${t}[${e}]`),s=Array(r-1);s[r-2]=n[r-1];for(let e=r-3;e>=0;--e)s[e]=`(${s[e+1]} * ${n[e+1]})`;return s}(e.map((e,t)=>t),t);return n.map((t,s)=>{let a=`int ${e[s]} = ${r} / ${n[s]}`,o=s===n.length-1?`int ${e[s+1]} = ${r} - ${e[s]} * ${n[s]}`:`index -= ${e[s]} * ${n[s]}`;return`${a}; ${o};`}).join("")}function u(e){return 1===e.length?`${e[0]}`:`vec${e.length}(${e.join(",")})`}function p(e,t){if(e.length!==t.length)throw Error(`Vectors to be dotted must be of the same length -got ${e.length} and ${t.length}`);let r=[],n=Math.floor(e.length/4),s=e.length%4;for(let s=0;s<n;s++){let n=e.slice(4*s,4*s+4),a=t.slice(4*s,4*s+4);r.push(`${u(n)}, ${u(a)}`)}if(0!==s){let s=e.slice(4*n),a=t.slice(4*n);1===s.length&&(s=s.map(e=>`float(${e})`),a=a.map(e=>`float(${e})`)),r.push(`${u(s)}, ${u(a)}`)}return r.map((e,t)=>`dot(${e})`).join("+")}function c(e){let t=a.util.computeStrides(e).map(e=>e.toString());return` int getFlatIndex(ivec3 coords) { return coords.x * ${t[0]} + coords.y * ${t[1]} + coords.z; } `}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":"hADTC","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],"1hjAY":[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"DecodeMatrixPackedProgram",()=>u);var a=e("./glsl_version"),o=e("./gpgpu_math"),l=e("./shader_compiler_util"),i=e("./tex_util");class u{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outPackingScheme=i.PackingScheme.DENSE,this.customUniforms=[{name:"texShape",type:"ivec2"}];let 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); } void main() { ivec2 resTexRC = ivec2(resultUV.yx * vec2(texShape[0], texShape[1])); int index = 4 * (resTexRC.x * texShape[1] + resTexRC.y); vec4 result = vec4(0.); for (int i=0; i<4; i++) { int flatIndex = index + i; ivec3 rc = outCoordsFromFlatIndex(flatIndex); result[i] = getChannel(getA(rc.x, rc.y, rc.z), vec2(rc.y, rc.z)); } ${t.output} = result; } `}}},{"./glsl_version":"5v0d7","./gpgpu_math":"aCqaC","./shader_compiler_util":"ll5XN","./tex_util":"kxvAY","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],atnH0:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"EncodeFloatProgram",()=>i);var a=e("./glsl_version"),o=e("./shader_compiler_util"),l=e("./tex_util");class i{constructor(e){this.variableNames=["A"],this.outTexUsage=l.TextureUsage.DOWNLOAD;let t=(0,a.getGlslDifferences)();this.outputShape=e,this.userCode=` ${o.ENCODE_FLOAT_SNIPPET} void main() { float x = getAAtOutCoords(); ${t.output} = encode_float(x); } `}}},{"./glsl_version":"5v0d7","./shader_compiler_util":"ll5XN","./tex_util":"kxvAY","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],fY0wW:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"EncodeFloatPackedProgram",()=>i);var a=e("./glsl_version"),o=e("./shader_compiler_util"),l=e("./tex_util");class i{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!1,this.outTexUsage=l.TextureUsage.DOWNLOAD;let t=(0,a.getGlslDifferences)();this.outputShape=e,this.userCode=` ${o.ENCODE_FLOAT_SNIPPET} void main() { ivec3 coords = getOutputCoords(); float x = getChannel(getAAtOutCoords(), vec2(coords.y, coords.z)); ${t.output} = encode_float(x); } `}}},{"./glsl_version":"5v0d7","./shader_compiler_util":"ll5XN","./tex_util":"kxvAY","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],llrtn:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"EncodeMatrixProgram",()=>u);var a=e("./glsl_version"),o=e("./gpgpu_math"),l=e("./shader_compiler_util");let i={R:0,G:1,B:2,A:3};class u{constructor(e,t=!1,r="RGBA"){this.variableNames=["A"],this.customUniforms=[{name:"texShape",type:"ivec2"}];let n=(0,a.getGlslDifferences)();this.outputShape=e,this.enableShapeUniforms=(0,o.useShapeUniforms)(this.outputShape.length);let s="result";t&&(s="floor(result * 255. + 0.5)");let u="";for(let e=0;e<r.length;e++){let t=r[e];u+=` if(offset == ${e}) { result = values[${i[t]}]; }`}this.userCode=` ${this.enableShapeUniforms?l.getFlatIndexFrom3DOutput():l.getFlatIndexFrom3D(e)} void main() { ivec3 coords = getOutputCoords(); int flatIndex = getFlatIndex(coords); float result = 0.; int offset = imod(flatIndex, ${r.length}); flatIndex = idiv(flatIndex, ${r.length}, 1.); int r = flatIndex / texShape[1]; if (r < texShape[0]) { int c = imod(flatIndex, texShape[1]); vec2 uv = (vec2(c, r) + halfCR) / vec2(texShape[1], texShape[0]); vec4 values = ${n.texture2D}(A, uv); ${u} } ${n.output} = vec4(${s}, 0., 0., 0.); } `}}},{"./glsl_version":"5v0d7","./gpgpu_math":"aCqaC","./shader_compiler_util":"ll5XN","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],hMhmd:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"EncodeMatrixPackedProgram",()=>i);var a=e("./glsl_version"),o=e("./gpgpu_math"),l=e("./shader_compiler_util");class i{constructor(e,t=!1){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.customUniforms=[{name:"texShape",type:"ivec2"}];let r=(0,a.getGlslDifferences)();this.outputShape=e,this.enableShapeUniforms=(0,o.useShapeUniforms)(this.outputShape.length);let n="",s="result";t&&(s="floor(result * 255. + 0.5)");for(let t=0;t<=1;t++)for(let s=0;s<=1;s++){let a=2*t+s;n+=` localCoords = coords; 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":"5v0d7","./gpgpu_math":"aCqaC","./shader_compiler_util":"ll5XN","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],hJTBE:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"GPGPUContext",()=>p),s.export(r,"linearSearchLastTrue",()=>c);var a=e("@tensorflow/tfjs-core"),o=e("./canvas_util"),l=e("./gpgpu_util"),i=e("./tex_util"),u=e("./webgl_util");class p{constructor(e){this.outputTexture=null,this.program=null,this.disposed=!1,this.itemsToPoll=[];let 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")){let t=e;this.createVertexArray=()=>u.callAndCheck(t,()=>t.createVertexArray()),this.bindVertexArray=e=>u.callAndCheck(t,()=>t.bindVertexArray(e)),this.deleteVertexArray=e=>u.callAndCheck(t,()=>t.deleteVertexArray(e)),this.getVertexArray=()=>u.callAndCheck(t,()=>t.getParameter(t.VERTEX_ARRAY_BINDING))}else if(null!=e){let 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=()=>u.callAndCheck(e,()=>t.createVertexArrayOES()),this.bindVertexArray=r=>u.callAndCheck(e,()=>t.bindVertexArrayOES(r)),this.deleteVertexArray=r=>u.callAndCheck(e,()=>t.deleteVertexArrayOES(r)),this.getVertexArray=()=>u.callAndCheck(e,()=>e.getParameter(t.VERTEX_ARRAY_BINDING_OES))}let r="WEBGL_color_buffer_float",n="EXT_color_buffer_half_float";if(this.parallelCompilationExtension=this.gl.getExtension("KHR_parallel_shader_compile"),1===(0,a.env)().getNumber("WEBGL_VERSION")){let e="OES_texture_half_float";if(this.textureFloatExtension=u.getExtensionOrThrow(this.gl,"OES_texture_float"),u.hasExtension(this.gl,e))this.textureHalfFloatExtension=u.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),u.hasExtension(this.gl,n))this.colorBufferHalfFloatExtension=u.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",u.hasExtension(this.gl,r))this.colorBufferFloatExtension=this.gl.getExtension(r);else if(u.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=u.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;u.callAndCheck(e,()=>e.finish()),u.callAndCheck(e,()=>e.bindFramebuffer(e.FRAMEBUFFER,null)),u.callAndCheck(e,()=>e.deleteFramebuffer(this.framebuffer)),u.callAndCheck(e,()=>e.bindBuffer(e.ARRAY_BUFFER,null)),u.callAndCheck(e,()=>e.bindBuffer(e.ELEMENT_ARRAY_BUFFER,null)),u.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&&(u.unbindColorTextureFromFramebuffer(this.gl,this.framebuffer),this.outputTexture=null),u.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=u.createProgram(t);u.callAndCheck(t,()=>t.attachShader(r,this.vertexShader)),u.callAndCheck(t,()=>t.attachShader(r,e)),u.linkProgram(t,r);let n=Object.assign(r,{vao:this.createVertexArray()});return this.debug&&u.validateProgram(t,n),n}buildVao(e){this.setProgram(e),this.bindVertexArray(e.vao);let t=this.gl;u.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&&(u.callAndCheck(this.gl,()=>this.gl.deleteProgram(e)),this.deleteVertexArray(e.vao))}setProgram(e){this.throwIfDisposed(),this.program=e,null!=this.program&&this.debug&&u.validateProgram(this.gl,this.program),u.callAndCheck(this.gl,()=>this.gl.useProgram(e))}getUniformLocation(e,t,r=!0){return(this.throwIfDisposed(),r)?u.getProgramUniformLocationOrThrow(this.gl,e,t):u.getProgramUniformLocation(this.gl,e,t)}getAttributeLocation(e,t){return this.throwIfDisposed(),u.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(),u.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&&u.validateProgram(this.gl,this.program),u.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()),u.callAndCheck(e,()=>e.drawElements(e.TRIANGLES,6,e.UNSIGNED_SHORT,0))}blockUntilAllProgramsCompleted(){this.throwIfDisposed(),u.callAndCheck(this.gl,()=>this.gl.finish())}getQueryTimerExtension(){return null==this.disjointQueryTimerExtension&&(this.disjointQueryTimerExtension=u.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(),u.bindColorTextureToFramebuffer(this.gl,e,this.framebuffer),this.debug&&u.validateFramebuffer(this.gl)}unbindTextureToFrameBuffer(){null!=this.outputTexture?(u.bindColorTextureToFramebuffer(this.gl,this.outputTexture,this.framebuffer),this.debug&&u.validateFramebuffer(this.gl)):u.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;u.bindColorTextureToFramebuffer(n,e,this.framebuffer),this.debug&&u.validateFramebuffer(n),this.outputTexture=e,u.callAndCheck(n,()=>n.viewport(0,0,t,r)),u.callAndCheck(n,()=>n.scissor(0,0,t,r))}setOutputMatrixWriteRegionDriver(e,t,r,n){this.throwIfDisposed(),u.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":"hADTC","./canvas_util":"45XFH","./gpgpu_util":"ae4xK","./tex_util":"kxvAY","./webgl_util":"hSqB7","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],ae4xK:[function(e,t,r,n){var 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ls/FlipLeftRight":"kJm6F","./kernels/Floor":"lQvGn","./kernels/FloorDiv":"9gJF4","./kernels/FromPixels":"7o6pu","./kernels/FusedConv2D":"bX0bx","./kernels/FusedDepthwiseConv2D":"fLpvm","./kernels/GatherNd":"3zja3","./kernels/GatherV2":"aCEdT","./kernels/Greater":"1Xjbf","./kernels/GreaterEqual":"kJPfU","./kernels/Identity":"eH68D","./kernels/IFFT":"5tF5H","./kernels/Imag":"lIWnW","./kernels/IsFinite":"2sUBb","./kernels/IsInf":"gDSDP","./kernels/IsNaN":"cBR9s","./kernels/LeakyRelu":"9THSD","./kernels/Less":"hcdH8","./kernels/LessEqual":"kYw7M","./kernels/LinSpace":"9wq53","./kernels/Log":"k5eu0","./kernels/Log1p":"iTdfZ","./kernels/LogicalAnd":"cs5BO","./kernels/LogicalNot":"2CzzD","./kernels/LogicalOr":"3NoAJ","./kernels/LRN":"hDfav","./kernels/LRNGrad":"1QDvH","./kernels/Max":"15AIZ","./kernels/Maximum":"apiBX","./kernels/MaxPool":"bLGeN","./kernels/MaxPool3D":"88kSn","./kernels/MaxPool3DGrad":"lj8jK","./kernels/MaxPoolGrad":"e2UoK","./kernels/MaxPoolWithArgmax":"eue0R","./kernels/Mean":"eyzN2","./kernels/Min":"dIWud","./kernels/Minimum":"dkrAD","./kernels/MirrorPad":"hiTbr","./kernels/Mod":"HrpnP","./kernels/Multinomial":"023g2","./kernels/Multiply":"exqRf","./kernels/Neg":"8Dggw","./kernels/NonMaxSuppressionV3":"cAAs8","./kernels/NonMaxSuppressionV4":"2rIMJ","./kernels/NonMaxSuppressionV5":"kQF6C","./kernels/NotEqual":"fcGpz","./kernels/OneHot":"fI3HW","./kernels/OnesLike":"dZiwf","./kernels/Pack":"lEeEU","./kernels/PadV2":"6Katd","./kernels/Pow":"dN6YC","./kernels/Prelu":"3ZqQw","./kernels/Prod":"7pkku","./kernels/RaggedGather":"lNiXX","./kernels/RaggedRange":"4g5B2","./kernels/RaggedTensorToTensor":"2ARTj","./kernels/Range":"1qqQJ","./kernels/Real":"hXKZs","./kernels/RealDiv":"iTd5N","./kernels/Reciprocal":"3U322","./kernels/Relu":"bWdfN","./kernels/Relu6":"4vqNA","./kernels/Reshape":"6JJRX","./kernels/ResizeBilinear":"cEb6n","./kernels/ResizeBilinearGrad":"d9Mfx","./kernels/ResizeNearestNeighbor":"bmwc8","./kernels/ResizeNearestNeighborGrad":"fKCQq","./kernels/Reverse":"iCykH","./kernels/RotateWithOffset":"iNfzI","./kernels/Round":"dfB9N","./kernels/Rsqrt":"l8Us1","./kernels/ScatterNd":"eM9xS","./kernels/SearchSorted":"a5air","./kernels/Select":"kGIjr","./kernels/Selu":"jZ73b","./kernels/Sigmoid":"j3au9","./kernels/Sign":"kv0Rb","./kernels/Sin":"fA8xk","./kernels/Sinh":"cGJA0","./kernels/Slice":"1rG2n","./kernels/Softmax":"cDakL","./kernels/Softplus":"2JM9U","./kernels/SpaceToBatchND":"6fRfC","./kernels/SparseFillEmptyRows":"eum8a","./kernels/SparseReshape":"3RE2p","./kernels/SparseSegmentMean":"kCBJu","./kernels/SparseSegmentSum":"apllm","./kernels/SparseToDense":"6aFw3","./kernels/SplitV":"fWOc9","./kernels/Sqrt":"O6srq","./kernels/Square":"coIP7","./kernels/SquaredDifference":"1YoVr","./kernels/StaticRegexReplace":"jo3Rv","./kernels/Step":"3RjTY","./kernels/StridedSlice":"725nD","./kernels/StringNGrams":"8Pm3f","./kernels/StringSplit":"g8CU1","./kernels/StringToHashBucketFast":"6PYfa","./kernels/Sub":"eCliL","./kernels/Sum":"6yTIe","./kernels/Tan":"lAEh4","./kernels/Tanh":"2aYdz","./kernels/TensorScatterUpdate":"1J1EG","./kernels/Tile":"kIunT","./kernels/TopK":"4sTNd","./kernels/Transform":"kaMdV","./kernels/Transpose":"6x6Ts","./kernels/Unique":"a99la","./kernels/Unpack":"c9jMA","./kernels/UnsortedSegmentSum":"794cJ","./kernels/ZerosLike":"9lTC1"}],dbpcl:[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:u,transposeB:p,activation:c,leakyreluAlpha:d}=n;return(0,o.batchMatMulImpl)({a:s,b:a,transposeA:u,transposeB:p,backend:r,bias:l,preluActivationWeights:i,leakyreluAlpha:d,activation:c})}let i={kernelName:a._FusedMatMul,backendName:"webgl",kernelFunc:l}},{"@tensorflow/tfjs-core":"hADTC","./BatchMatMul_impl":"11rB3","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],"11rB3":[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"),u=e("./Reshape"),p=e("./Sum"),c=e("./Transpose");let d=1e3;function f({a:e,b:t,transposeA:r,transposeB:n,backend:s,bias:f=null,preluActivationWeights:h=null,leakyreluAlpha:m=0,activation:g=null}){let x,v=e.shape.length,y=t.shape.length,_=r?e.shape[v-2]:e.shape[v-1],b=n?t.shape[y-1]:t.shape[y-2],k=r?e.shape[v-1]:e.shape[v-2],T=n?t.shape[y-2]:t.shape[y-1],w=e.shape.slice(0,-2),I=t.shape.slice(0,-2),j=a.util.sizeFromShape(w),C=a.util.sizeFromShape(I),N=a.broadcast_util.assertAndGetBroadcastShape(e.shape.slice(0,-2),t.shape.slice(0,-2)).concat([k,T]);a.util.assert(_===b,()=>`Error in matMul: inner shapes (${_}) and (${b}) of Tensors with shapes ${e.shape} and ${t.shape} and transposeA=${r} and transposeB=${n} must match.`);let 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u={kernelName:a.ArgMax,backendName:"webgl",kernelFunc:i}},{"@tensorflow/tfjs-core":"hADTC","../kernel_utils/arg_min_max":"4W0ve","./Transpose":"6x6Ts","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],"4W0ve":[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"argMinMaxReduce",()=>u);var a=e("@tensorflow/tfjs-core"),o=e("../argminmax_gpu"),l=e("../argminmax_packed_gpu"),i=e("../kernels/Reshape");function u(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),u=null!==l&&l.isPacked,p=t;u&&r.push(p=e.unpackTensor(t));let[c,d]=a.backend_util.computeOutAndReduceShapes(p.shape,s),f=a.util.sizeFromShape(d),h=(0,i.reshape)({inputs:{x:p},backend:e,attrs:{shape:[-1,f]}});r.push(h);let m=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 u=a.backend_util.computeOptimalWindowSize(i),p={windowSize:u,inSize:i,batchSize:l,outSize:Math.ceil(i/u)},c=new(0,o.ArgMinMaxProgram)(p,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 h=e(t,r,n,f);return t.disposeIntermediateTensorInfo(f),h}(e,h,n);r.push(m);let g=(0,i.reshape)({inputs:{x:m},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],u=a.backend_util.computeOptimalWindowSize(i),p=new(0,l.ArgMinMaxPackedProgram)(o,u,n,null==s),c=null==s?[r]:[r,s],d=t.runWebGLProgram(p,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":"hADTC","../argminmax_gpu":"7YiW2","../argminmax_packed_gpu":"bQj26","../kernels/Reshape":"6JJRX","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],"7YiW2":[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"];let{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 ${"max"===t?">":"<"} bestValue) { bestValue = candidate; bestIndex = inIdx; } } setOutput(float(bestIndex)); } `}}},{"@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],bQj26:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"ArgMinMaxPackedProgram",()=>i);var a=e("@tensorflow/tfjs-core"),o=e("./packing_util"),l=e("./shader_compiler");class i{constructor(e,t,r,n){let s,i;this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,a.util.assert(e.length>2,()=>`Packed arg${r.charAt(0).toUpperCase()+r.slice(1)} supports only inputs with rank above 2.`);let u=Math.ceil(e[e.length-1]/t);this.outputShape=e.slice(0,-1),u>1&&this.outputShape.push(u),n||this.variableNames.push("bestIndicesA");let p=this.outputShape,c=p.length,d=(0,l.getCoordsDataType)(c),f=(0,o.getChannels)("coords",c);if(1===u){i=c+1;let 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]};`;let h=["x","y","z","w","u","v"].slice(0,i),m="."+h[i-1],g=h.map(e=>"int "+e),x=(0,o.getChannels)("sourceLocR",i-1).concat("inIdx.r"),v=(0,o.getChannels)("sourceLocG",i-1).concat("inIdx.g"),y=(0,o.getChannels)("sourceLocB",i-1).concat("inIdx.b"),_=(0,o.getChannels)("sourceLocA",i-1).concat("inIdx.a"),b="max"===r?"greaterThan":"lessThan",k=n?"":` inIdx = round(vec4(getBestIndicesAChannel(${x.join()}), getBestIndicesAChannel(${v.join()}), getBestIndicesAChannel(${y.join()}), getBestIndicesAChannel(${_.join()})));`,T=`vec4( getAChannel(${x.join()}), hasNextCol ? getAChannel(${v.join()}) : 0., hasNextRow ? getAChannel(${y.join()}) : 0., hasNextRow && hasNextCol ? getAChannel(${_.join()}) : 0.)`,w=n?"":` float getBestIndicesAChannel(${g.join()}) { return getChannel(getBestIndicesA(${h.join()}), vec2(${h.slice(-2).join()})); }`;this.userCode=` float getAChannel(${g.join()}) { return getChannel(getA(${h.join()}), vec2(${h.slice(-2).join()})); } ${w} void main() { ${d} coords = getOutputCoords(); bool hasNextCol = ${f[c-1]}< ${p[c-1]-1}; bool hasNextRow = ${f[c-2]} < ${p[c-2]-1}; ${s} ivec4 srcIdx = ivec4(sourceLocR${m}, sourceLocG${m}, sourceLocB${m}, sourceLocA${m}) * ${t}; ivec4 inIdx = srcIdx; vec4 bestIndex = vec4(inIdx); vec4 bestValue = ${T}; for (int i = 0; i < ${t}; i++) { inIdx = srcIdx; ${k} vec4 candidate = ${T}; bvec4 nan = isnan(candidate); bvec4 replace = bvec4( vec4(${b}(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":"hADTC","./packing_util":"gX790","./shader_compiler":"2b0aL","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],"2w91t":[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",()=>u);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,u=a.util.parseAxisParam(i,s.shape),p=a.backend_util.getAxesPermutation(u,s.shape.length),c=s,d=[];null!=p&&(d.push(c=(0,l.transpose)({inputs:{x:s},backend:r,attrs:{perm:p}})),u=a.backend_util.getInnerMostAxes(u.length,c.shape.length)),a.backend_util.assertAxesAreInnerMostDims("argMin",[u[0]],c.shape.length);let f=(0,o.argMinMaxReduce)(r,c,u[0],"min");return d.forEach(e=>r.disposeIntermediateTensorInfo(e)),f}let u={kernelName:a.ArgMin,backendName:"webgl",kernelFunc:i}},{"@tensorflow/tfjs-core":"hADTC","../kernel_utils/arg_min_max":"4W0ve","./Transpose":"6x6Ts","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],"4gYKq":[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",()=>u);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}),u={kernelName:a.Asin,backendName:"webgl",kernelFunc:i}},{"@tensorflow/tfjs-core":"hADTC","../kernel_utils/kernel_funcs_utils":"eRfJh","../unaryop_gpu":"dKkzg","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],"5NnHk":[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",()=>u);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}),u={kernelName:a.Asinh,backendName:"webgl",kernelFunc:i}},{"@tensorflow/tfjs-core":"hADTC","../kernel_utils/kernel_funcs_utils":"eRfJh","../unaryop_gpu":"dKkzg","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],iCFXP:[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",()=>u);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}),u={kernelName:a.Atan,backendName:"webgl",kernelFunc:i}},{"@tensorflow/tfjs-core":"hADTC","../kernel_utils/kernel_funcs_utils":"eRfJh","../unaryop_gpu":"dKkzg","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],APiHf:[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 u=o.CHECK_NAN_SNIPPET+` return atan(a, b); `,p=` 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:u,packedOpSnippet:p}),d={kernelName:a.Atan2,backendName:"webgl",kernelFunc:c}},{"@tensorflow/tfjs-core":"hADTC","../binaryop_gpu":"a2Mj7","../binaryop_packed_gpu":"fwruC","../kernel_utils/kernel_funcs_utils":"eRfJh","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],iDemk:[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",()=>u);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}),u={kernelName:a.Atanh,backendName:"webgl",kernelFunc:i}},{"@tensorflow/tfjs-core":"hADTC","../kernel_utils/kernel_funcs_utils":"eRfJh","../unaryop_gpu":"dKkzg","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],k7gqw:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"avgPool",()=>u),s.export(r,"avgPoolConfig",()=>p);var a=e("@tensorflow/tfjs-core"),o=e("../pool_gpu"),l=e("../webgl_util"),i=e("./Identity");function u(e){let{inputs:t,backend:r,attrs:n}=e,{x:s}=t;(0,l.assertNotComplex)(s,"avgPool");let{filterSize:u,strides:p,pad:c,dimRoundingMode:d}=n;a.util.assert(a.backend_util.eitherStridesOrDilationsAreOne(p,1),()=>`Error in avgPool: Either strides or dilations must be 1. Got strides ${p} and dilations '1'`);let f=a.backend_util.computePool2DInfo(s.shape,u,p,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 h=new(0,o.Pool2DProgram)(f,"avg",!1);return r.runWebGLProgram(h,[s],"float32")}let p={kernelName:a.AvgPool,backendName:"webgl",kernelFunc:u}},{"@tensorflow/tfjs-core":"hADTC","../pool_gpu":"6Iq2c","../webgl_util":"hSqB7","./Identity":"eH68D","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],"6Iq2c":[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.");let a=e.filterWidth,o=e.strideHeight,l=e.strideWidth,i=e.dilationHeight,u=e.dilationWidth,p=e.effectiveFilterHeight,c=e.effectiveFilterWidth,d=e.padInfo.top,f=e.padInfo.left;this.outputShape=e.outShape;let h="avg"===t,m=`((batch * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + d`,g=`(xR * ${e.inWidth} + xC) * ${e.inChannels} + d`,x="0.0";if(h||(x="-1.0 / 1e-20"),r){this.userCode=` const ivec2 strides = ivec2(${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< ${p}; wR += ${i}) { int xR = xRCorner + wR; if (xR < 0 || xR >= ${e.inHeight}) { continue; } for (int wC = 0; wC< ${c}; wC += ${u}) { int xC = xCCorner + wC; if (xC < 0 || xC >= ${e.inWidth}) { continue; } float value = getX(batch, xR, xC, d); // If a min / max value has already been found, use it. If not, // use the current value. float currMinMaxValue = mix( value, minMaxValue, minMaxValueFound); if (value >= currMinMaxValue) { minMaxValue = value; minMaxValueFound = 1.0; minMaxPosition = ${n?s?m:g:`wR * ${c} + wC`}; } } } setOutput(float(minMaxPosition)); } `;return}let v=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;"avg"===t&&(v="avgValue / max(count, 1.0)");let y=4*Math.floor(a/4),_=a%4,b=` if (${h}) { avgValue += dot(values, ones); } else { minMaxValue = max(values, minMaxValue); } `;this.userCode=` const ivec2 strides = ivec2(${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< ${p}; wR += ${i}) { int xR = xRCorner + wR; if (xR < 0 || xR >= ${e.inHeight}) { continue; } for (int wC = 0; wC< ${y}; wC += 4) { int xC = xCCorner + wC * ${u}; vec4 values = vec4( getValue(batch, xR, xC, d), getValue(batch, xR, xC + ${u}, d), getValue(batch, xR, xC + 2 * ${u}, d), getValue(batch, xR, xC + 3 * ${u}, d) ); ${b} } int xC = xCCorner + ${y}; if (${1===_}) { vec4 values = vec4( getValue(batch, xR, xC, d), initializationValue, initializationValue, initializationValue ); ${b} } else if (${2===_}) { vec4 values = vec4( getValue(batch, xR, xC, d), getValue(batch, xR, xC + ${u}, d), initializationValue, initializationValue ); ${b} } else if (${3===_}) { vec4 values = vec4( getValue(batch, xR, xC, d), getValue(batch, xR, xC + ${u}, d), getValue(batch, xR, xC + 2 * ${u}, d), initializationValue ); ${b} } } setOutput(${v}); } `}}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.");let a=e.filterWidth,o=e.strideDepth,l=e.strideHeight,i=e.strideWidth,u=e.dilationDepth,p=e.dilationHeight,c=e.dilationWidth,d=e.effectiveFilterDepth,f=e.effectiveFilterHeight,h=e.effectiveFilterWidth,m=e.padInfo.front,g=e.padInfo.top,x=e.padInfo.left;this.outputShape=e.outShape;let v="avg"===t,y="0.0";if(v||(y="-1.0 / 1e-20"),r){this.userCode=` const ivec3 strides = ivec3(${o}, ${l}, ${i}); const ivec3 pads = ivec3(${m}, ${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 += ${u}) { int xD = xDCorner + wD; if (xD < 0 || xD >= ${e.inDepth}) { continue; } for (int wR = 0; wR< ${f}; wR += ${p}) { int xR = xRCorner + wR; if (xR < 0 || xR >= ${e.inHeight}) { continue; } for (int wC = 0; wC< ${h}; 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} * ${h} + wR * ${h} + wC`}; } } } } setOutput(float(minMaxPosition)); } `;return}let _=`${t}(${t}(${t}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;"avg"===t&&(_="avgValue / max(count, 1.0)");let b=4*Math.floor(a/4),k=a%4,T=` if (${v}) { avgValue += dot(values, ones); } else { minMaxValue = max(values, minMaxValue); } `;this.userCode=` const ivec3 strides = ivec3(${o}, ${l}, ${i}); const ivec3 pads = ivec3(${m}, ${g}, ${x}); const float initializationValue = ${y}; 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 >= ${e.inWidth}) { return initializationValue; } count += 1.0; return getX(batch, xD, xR, xC, ch); } void main() { ivec5 coords = getOutputCoords(); int batch = coords.x; int ch = coords.u; ivec3 xCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads; int xDCorner = xCorner.x; int xRCorner = xCorner.y; int xCCorner = xCorner.z; // max/min x(?, ?, ?, d) to get y(yD, yR, yC, ch). // ? = to be determined vec4 minMaxValue = vec4(${y}); float avgValue = 0.0; count = 0.0; for (int wD = 0; wD< ${d}; wD += ${u}) { int xD = xDCorner + wD; if (xD < 0 || xD >= ${e.inDepth}) { continue; } for (int wR = 0; wR< ${f}; wR += ${p}) { int xR = xRCorner + wR; if (xR < 0 || xR >= ${e.inHeight}) { continue; } for (int wC = 0; wC< ${b}; 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) ); ${T} } int xC = xCCorner + ${b}; if (${1===k}) { vec4 values = vec4( getValue(batch, xD, xR, xC, ch), initializationValue, initializationValue, initializationValue ); ${T} } else if (${2===k}) { vec4 values = vec4( getValue(batch, xD, xR, xC, ch), getValue(batch, xD, xR, xC + ${c}, ch), initializationValue, initializationValue ); ${T} } else if (${3===k}) { 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 ); ${T} } } } setOutput(${_}); } `}}},{"@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],VrUzp:[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:u,dimRoundingMode:p,dataFormat:c}=n,d=a.backend_util.computePool3DInfo(s.shape,l,i,[1,1,1],u,p,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":"hADTC","../pool_gpu":"6Iq2c","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],iwWTr:[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:u,pad:p,dimRoundingMode:c}=n,d=a.backend_util.computePool3DInfo(l.shape,i,u,[1,1,1],p,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":"hADTC","../avg_pool_backprop_gpu":"lP4g7","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],lP4g7:[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;let t=e.filterHeight,r=e.filterWidth,n=e.strideHeight,s=e.strideWidth,a=e.dilationHeight,o=e.dilationWidth,l=e.effectiveFilterHeight,i=e.effectiveFilterWidth,u=l-1-e.padInfo.top,p=i-1-e.padInfo.left;this.userCode=` const ivec2 pads = ivec2(${u}, ${p}); const float avgMultiplier = float(${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 >= ${e.outWidth}.0 || fract(dyC) > 0.0) { continue; } int idyC = int(dyC); float dyValue = getDy(b, idyR, idyC, d); dotProd += dyValue * avgMultiplier; } } setOutput(dotProd); } `}}class o{constructor(e){this.variableNames=["dy"],this.outputShape=e.inShape;let t=e.filterDepth,r=e.filterHeight,n=e.filterWidth,s=e.strideDepth,a=e.strideHeight,o=e.strideWidth,l=e.dilationDepth,i=e.dilationHeight,u=e.dilationWidth,p=e.effectiveFilterDepth,c=e.effectiveFilterHeight,d=e.effectiveFilterWidth,f=p-1-e.padInfo.front,h=c-1-e.padInfo.top,m=d-1-e.padInfo.left;this.userCode=` const ivec3 pads = ivec3(${f}, ${h}, ${m}); const float avgMultiplier = float(${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< ${p}; 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 += ${u}) { float dyC = float(dyCCorner + wC) / ${o}.0; if (dyC < 0.0 || dyC >= ${e.outWidth}.0 || fract(dyC) > 0.0) { continue; } int idyC = int(dyC); float dyValue = getDy(batch, idyD, idyR, idyC, ch); dotProd += dyValue * avgMultiplier; } } } setOutput(dotProd); } `}}},{"@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],"6Ox0Z":[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",()=>u);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:u,strides:p,pad:c}=n,d=a.backend_util.computePool2DInfo(i.shape,u,p,1,c),f=new(0,o.AvgPool2DBackpropProgram)(d);return r.runWebGLProgram(f,[s],i.dtype)}let u={kernelName:a.AvgPoolGrad,backendName:"webgl",kernelFunc:i}},{"@tensorflow/tfjs-core":"hADTC","../avg_pool_backprop_gpu":"lP4g7","../webgl_util":"hSqB7","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],"5xFjy":[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":"hADTC","./BatchMatMul_impl":"11rB3","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],"26EfT":[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",()=>u);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:u,scale:p}=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==u||s.shape.length===u.shape.length,()=>"Batch normalization gradient requires mean and offset to have equal ranks."),a.util.assert(null==p||s.shape.length===p.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!=u&&(f=u.shape,d.push(u));let h=null;null!=p&&(h=p.shape,d.push(p));let m=(0,a.env)().getBool("WEBGL_PACK_NORMALIZATION")?new(0,l.BatchNormPackedProgram)(n.shape,s.shape,i.shape,f,h,c):new(0,o.BatchNormProgram)(n.shape,s.shape,i.shape,f,h,c);return t.runWebGLProgram(m,d,d[0].dtype)},u={kernelName:a.FusedBatchNorm,backendName:"webgl",kernelFunc:i}},{"@tensorflow/tfjs-core":"hADTC","../batchnorm_gpu":"40xQV","../batchnorm_packed_gpu":"cWuEj","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],"40xQV":[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":"hADTC","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],cWuEj:[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":"hADTC","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],fOvcB:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"batchToSpaceND",()=>u),s.export(r,"batchToSpaceNDConfig",()=>p);var a=e("@tensorflow/tfjs-core"),o=e("./Reshape"),l=e("./Slice"),i=e("./Transpose");let u=e=>{let{inputs:t,backend:r,attrs:n}=e,{x:s}=t,{blockShape:u,crops:p}=n;a.util.assert(s.shape.length<=4,()=>"batchToSpaceND for rank > 4 with a WebGL backend not implemented yet");let c=u.reduce((e,t)=>e*t),d=a.backend_util.getReshaped(s.shape,u,c),f=a.backend_util.getPermuted(d.length,u.length),h=a.backend_util.getReshapedPermuted(s.shape,u,c),m=a.backend_util.getSliceBeginCoords(p,u.length),g=a.backend_util.getSliceSize(h,p,u.length),x=[],v=(0,o.reshape)({inputs:{x:s},backend:r,attrs:{shape:d}}),y=(0,i.transpose)({inputs:{x:v},backend:r,attrs:{perm:f}}),_=(0,o.reshape)({inputs:{x:y},backend:r,attrs:{shape:h}}),b=(0,l.slice)({inputs:{x:_},backend:r,attrs:{begin:m,size:g}});return x.push(v),x.push(y),x.push(_),x.forEach(e=>r.disposeIntermediateTensorInfo(e)),b},p={kernelName:a.BatchToSpaceND,backendName:"webgl",kernelFunc:u}},{"@tensorflow/tfjs-core":"hADTC","./Reshape":"6JJRX","./Slice":"1rG2n","./Transpose":"6x6Ts","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],"1rG2n":[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"slice",()=>u),s.export(r,"sliceConfig",()=>p);var a=e("@tensorflow/tfjs-core"),o=e("../kernel_utils/shared"),l=e("../slice_gpu"),i=e("../slice_packed_gpu");function u(e){let t,r,n,s,u,{inputs:p,backend:c,attrs:d}=e,{x:f}=p,{begin:h,size:m}=d,[g,x]=a.slice_util.parseSliceParams(f,h,m);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:v}=c.texData.get(f.dataId),y=a.slice_util.isSliceContinous(f.shape,g,x);if(v||!y){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 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r=(0,a.getCoordsDataType)(this.rank);this.customUniforms=[{name:"start",arrayIndex:this.rank,type:"int"}];let 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":"2b0aL","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],"7UT3d":[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":"hADTC","./Identity":"eH68D","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],"6FBp4":[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":"dKkzg","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],"2zhjk":[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"ceil",()=>u),s.export(r,"ceilConfig",()=>p);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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e=1;e<t.length;e++){let n=t[e-1];r.push(`else if (yC < ${t[e]}) setOutput(getT${e}(yR, yC-${n}));`)}let n=t.length,s=t[t.length-1];r.push(`else setOutput(getT${n}(yR, yC-${s}));`),this.userCode=` void main() { ivec2 coords = getOutputCoords(); int yR = coords.x; int yC = coords.y; ${r.join("\n ")} } `}}},{"@tensorflow/tfjs-core":"hADTC","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],"4vhSy":[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"ConcatPackedProgram",()=>i);var a=e("@tensorflow/tfjs-core"),o=e("./packing_util"),l=e("./shader_compiler");class i{constructor(e,t){this.packedInputs=!0,this.packedOutput=!0,this.outputShape=[],this.outputShape=a.backend_util.computeOutShape(e,t);let r=this.outputShape,n=r.length,s=(0,l.getCoordsDataType)(n),i=(0,o.getChannels)("coords",n),p=["x","y","z","w","u","v"].slice(0,n);this.variableNames=e.map((e,t)=>`T${t}`);let 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];let d=p[t],f=p.slice(-2),h=p.join(),m=`if (${d} < ${c[0]}) { return getChannel( getT0(${h}), vec2(${f.join()})); }`;for(let e=1;e<c.length;e++){let t=c[e-1];m+=` if (${d} < ${c[e]} && ${d} >= ${c[e-1]}) { return getChannel( getT${e}(${u(p,d,t)}), vec2(${u(f,d,t)})); }`}let g=c.length,x=c[c.length-1];m+=` return getChannel( getT${g}(${u(p,d,x)}), vec2(${u(f,d,x)}));`,this.userCode=` float getValue(${p.map(e=>"int "+e)}) { ${m} } 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 u(e,t,r){let n=e.indexOf(t);return e.map((e,t)=>t===n?`${e} - ${r}`:e).join()}},{"@tensorflow/tfjs-core":"hADTC","./packing_util":"gX790","./shader_compiler":"2b0aL","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],lIWnW:[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":"hADTC","./Identity":"eH68D","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],"7OelL":[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"conv2d",()=>p),s.export(r,"conv2DConfig",()=>c);var a=e("@tensorflow/tfjs-core"),o=e("../conv_gpu"),l=e("../conv_packed_gpu"),i=e("./Conv2D_impl"),u=e("./Reshape");function p(e){let t,{inputs:r,backend:n,attrs:s}=e,{x:p,filter:c}=r,{strides:d,pad:f,dataFormat:h,dilations:m,dimRoundingMode:g}=s,x=a.backend_util.convertConv2DDataFormat(h),v=a.backend_util.computeConv2DInfo(p.shape,c.shape,d,m,f,g,!1,x);if(1===v.filterHeight&&1===v.filterWidth&&1===v.dilationHeight&&1===v.dilationWidth&&1===v.strideHeight&&1===v.strideWidth&&("SAME"===v.padInfo.type||"VALID"===v.padInfo.type))t=(0,i.conv2dByMatMul)({x:p,filter:c,convInfo:v,backend:n});else if(v.strideWidth<=2&&"channelsLast"===x&&(0,a.env)().getBool("WEBGL_EXP_CONV")){let e=new(0,l.Conv2DPackedProgram)(v),r=[[v.padInfo.top,v.padInfo.left],[v.strideHeight,v.strideWidth],[v.dilationHeight,v.dilationWidth],[v.inHeight,v.inWidth]];t=n.runWebGLProgram(e,[p,c],"float32",r)}else if((0,a.env)().getBool("WEBGL_CONV_IM2COL"))t=(0,i.conv2dWithIm2Row)({x:p,filter:c,convInfo:v,backend:n});else{let e=new(0,o.Conv2DProgram)(v);t=n.runWebGLProgram(e,[p,c],"float32")}let y=(0,u.reshape)({inputs:{x:t},backend:n,attrs:{shape:v.outShape}});return n.disposeIntermediateTensorInfo(t),y}let c={kernelName:a.Conv2D,backendName:"webgl",kernelFunc:p}},{"@tensorflow/tfjs-core":"hADTC","../conv_gpu":"e94Ho","../conv_packed_gpu":"crrN0","./Conv2D_impl":"3YhXn","./Reshape":"6JJRX","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],e94Ho:[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;let a=e.padInfo.top,o=e.padInfo.left,l=e.strideHeight,i=e.strideWidth,u=e.dilationHeight,p=e.dilationWidth,c=e.filterHeight,d=e.filterWidth,f=4*Math.floor(e.inChannels/4),h=e.inChannels%4,m="channelsLast"===e.dataFormat,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}, ${o}); void main() { ivec4 coords = getOutputCoords(); int batch = coords[0]; int d2 = coords[${m?3:1}]; ivec2 xRCCorner = ivec2(coords[${m?1:2}], coords[${m?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 * ${u}; 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< ${f}; d1 += 4) { vec4 wValues = vec4( getW(wR, wC, d1, d2), getW(wR, wC, d1 + 1, d2), getW(wR, wC, d1 + 2, d2), getW(wR, wC, d1 + 3, d2) ); if (${m}) { 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 (${1===h}) { if (${m}) { 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===h}) { vec2 wValues = vec2( getW(wR, wC, ${f}, d2), getW(wR, wC, ${f} + 1, d2) ); if (${m}) { 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===h}) { vec3 wValues = vec3( getW(wR, wC, ${f}, d2), getW(wR, wC, ${f} + 1, d2), getW(wR, wC, ${f} + 2, d2) ); if (${m}) { 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();":""} ${x} setOutput(result); } `}}class o{constructor(e){this.variableNames=["x","W"],this.outputShape=e.outShape;let t=e.padInfo.front,r=e.padInfo.top,n=e.padInfo.left,s=e.strideDepth,a=e.strideHeight,o=e.strideWidth,l=e.dilationDepth,i=e.dilationHeight,u=e.dilationWidth,p=e.filterDepth,c=e.filterHeight,d=e.filterWidth,f=4*Math.floor(e.inChannels/4),h=e.inChannels%4;this.userCode=` const ivec3 strides = ivec3(${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 < ${p}; 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 * ${u}; 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===h}) { dotProd += getX(batch, xF, xR, xC, ${f}) * getW(wF, wR, wC, ${f}, d2); } else if (${2===h}) { 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===h}) { 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, ${f} + 2, d2) ); dotProd += dot(xValues, wValues); } } } } setOutput(dotProd); } `}}},{"@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],crrN0:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"Conv2DPackedProgram",()=>l);var a=e("@tensorflow/tfjs-core"),o=e("./gpgpu_math");class l{constructor(e,t=!1,r=null,n=!1,s=!1){this.variableNames=["x","W"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"pads",type:"ivec2"},{name:"strides",type:"ivec2"},{name:"dilations",type:"ivec2"},{name:"inDims",type:"ivec2"}],this.outputShape=e.outShape,this.enableShapeUniforms=(0,o.useShapeUniforms)(this.outputShape.length);let l=e.padInfo.left,i=e.strideWidth,u=e.dilationWidth,p=e.filterHeight,c=e.filterWidth,d=` int xR; int xC; int xCOffset; vec4 wTexel; vec4 previous; vec4 final;`;for(let e=0;e<c;e++)d+=` vec4 xTexelC${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 < ${p}; 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++){let r=2*t;if(d+=` xC = xCCorner + ${r*u}; `,1===i){if(r<c&&(l%2==1?(d+=` xCOffset = xC + 1; if (xCOffset >= 0 && xCOffset< inDims[1] && xTexelC${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${r}Ready = 1; } `,1===u&&r>0?d+=` xC${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)){let e=l%2==0?a.util.nearestLargerEven(u):u;u%2==0&&l%2==1||u%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${r+1}Ready = 1; } `,u>1?d+=` xCOffset -= 2; if (xCOffset >= 0 && xCOffset< inDims[1]) { previous = getX(batch, xR, xCOffset, d1); xC${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="",h="";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} }`,h="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();":""} ${h} setOutput(result); } `}}},{"@tensorflow/tfjs-core":"hADTC","./gpgpu_math":"aCqaC","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],"3YhXn":[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"conv2dByMatMul",()=>h),s.export(r,"conv2dWithIm2Row",()=>m);var a=e("@tensorflow/tfjs-core"),o=e("../im2col_packed_gpu"),l=e("../kernel_utils/kernel_funcs_utils"),i=e("../mulmat_packed_gpu"),u=e("../webgl_util"),p=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 h({x:e,filter:t,convInfo:r,backend:n,bias:s=null,preluActivationWeights:o=null,leakyreluAlpha:l=0,activation:i=null}){let h,m=e.shape,g=n.texData.get(e.dataId),x=r.inChannels,v=m[0]*m[1]*m[2],y=r.outChannels,_="channelsLast"===r.dataFormat,b=[];if(null!=o){let e=f(o.shape,_);null!=e&&(o=(0,d.reshape)({inputs:{x:o},backend:n,attrs:{shape:e}}),b.push(o))}if(null!=s){let e=f(s.shape,_);null!=e&&(s=(0,d.reshape)({inputs:{x:s},backend:n,attrs:{shape:e}}),b.push(s))}if(!((1===v||1===y)&&x>p.MATMUL_SHARED_DIM_THRESHOLD)&&g.isPacked&&_&&null!=g.texture&&m[2]%2!=0&&a.util.arraysEqual(g.shape.slice(-3),m.slice(-3))){let f=m[0]*m[1]*(m[2]+1),x={dataId:e.dataId,shape:[1,f,r.inChannels],dtype:e.dtype},v=g.shape;g.shape=g.shape.slice(),g.shape[g.shape.length-2]++,a.util.assert(u.isReshapeFree(g.shape,x.shape),()=>`packed reshape ${g.shape} to ${x.shape} isn't free`);let y=(0,d.reshape)({inputs:{x:t},backend:n,attrs:{shape:[1,r.inChannels,r.outChannels]}});b.push(y);let _=(0,p.batchMatMulImpl)({a:x,b:y,backend:n,transposeA:!1,transposeB:!1,bias:s,activation:i,preluActivationWeights:o,leakyreluAlpha:l}),k=n.texData.get(_.dataId);a.util.assert(k.isPacked,()=>"batchMatMul result is expected to be packed"),g.shape=v,k.shape=r.outShape,(h=(0,c.identity)({inputs:{x:_},backend:n})).shape=r.outShape,b.push(_)}else{let a=r.outHeight*r.outWidth,u=(0,d.reshape)({inputs:{x:e},backend:n,attrs:{shape:_?[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,p.batchMatMulImpl)({a:_?u:c,b:_?c:u,transposeA:!_,transposeB:!1,backend:n,bias:s,activation:i,preluActivationWeights:o,leakyreluAlpha:l});h=(0,d.reshape)({inputs:{x:f},backend:n,attrs:{shape:r.outShape}}),b.push(u),b.push(c),b.push(f)}for(let e of b)n.disposeIntermediateTensorInfo(e);return h}function m({x:e,filter:t,convInfo:r,backend:n,bias:s=null,preluActivationWeights:u=null,leakyreluAlpha:p=0,activation:c=null}){let{filterWidth:h,filterHeight:m,inChannels:g,outWidth:x,outHeight:v,dataFormat:y}=r,_="channelsLast"===y,b=h*m*g,k=v*x,T=[r.batchSize,b,k],w=[];if(null!=u){let e=f(u.shape,_);null!=e&&(u=(0,d.reshape)({inputs:{x:u},backend:n,attrs:{shape:e}}),w.push(u))}if(null!=s){let e=f(s.shape,_);null!=e&&(s=(0,d.reshape)({inputs:{x:s},backend:n,attrs:{shape:e}}),w.push(s))}let I=(0,d.reshape)({inputs:{x:t},backend:n,attrs:{shape:[1,b,a.util.sizeFromShape(t.shape)/b]}});w.push(I);let j=new(0,o.Im2ColPackedProgram)(T,r),C=[e.shape,[r.padInfo.top,r.padInfo.left],[r.strideHeight,r.strideWidth],[r.dilationHeight,r.dilationWidth],[r.inChannels],[r.filterWidth*r.inChannels],[r.outWidth]],N=n.runWebGLProgram(j,[e],"float32",C),S=(0,d.reshape)({inputs:{x:N},backend:n,attrs:{shape:T}});w.push(N),w.push(S);let E=null!=s,A=null!=u,F="leakyrelu"===c,R=c?(0,l.mapActivationToShaderProgram)(c,!0):null,D=new(0,i.MatMulPackedProgram)(_?S.shape:I.shape,_?I.shape:S.shape,_?[r.batchSize,k,r.outChannels]:[r.batchSize,r.outChannels,k],!0,!1,E,R,A,F),P=_?[S,I]:[I,S];if(s&&P.push(s),A&&P.push(u),F){let e=n.makeTensorInfo([],"float32",a.util.createScalarValue(p,"float32"));P.push(e),w.push(e)}let $=n.runWebGLProgram(D,P,"float32"),M=(0,d.reshape)({inputs:{x:$},backend:n,attrs:{shape:r.outShape}});for(let e of(w.push($),w))n.disposeIntermediateTensorInfo(e);return M}},{"@tensorflow/tfjs-core":"hADTC","../im2col_packed_gpu":"5yoWf","../kernel_utils/kernel_funcs_utils":"eRfJh","../mulmat_packed_gpu":"dESVa","../webgl_util":"hSqB7","./BatchMatMul_impl":"11rB3","./Identity":"eH68D","./Reshape":"6JJRX","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],"5yoWf":[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);let{dataFormat:r}=t,n=(0,a.getGlslDifferences)(),s="channelsLast"===r,l=s?1:2,i=s?2:3,u=this.enableShapeUniforms?"if(blockIndex< outShape[2] && pos < outShape[1]) {":`if(blockIndex < ${e[2]} && pos < ${e[1]}) {`,p="";for(let e=0;e<=1;e++)for(let t=0;t<=1;t++)p+=` blockIndex = rc.z + ${t}; pos = rc.y + ${e}; ${u} offsetY = int(blockIndex / outWidth) * stride[0] - pad[0]; d0 = offsetY + dilation[0] * (pos / itemsPerBlockRow); if(d0 < inputShape[${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; ${p} ${n.output} = result; } `}}},{"./glsl_version":"5v0d7","./gpgpu_math":"aCqaC","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],icoxO:[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:u,dataFormat:p,dimRoundingMode:c,filterShape:d}=n,f=a.backend_util.convertConv2DDataFormat(p),h=a.backend_util.computeConv2DInfo(s.shape,d,i,1,u,c,!1,f),m=new(0,o.Conv2DDerFilterProgram)(h);return r.runWebGLProgram(m,[s,l],"float32")}let i={kernelName:a.Conv2DBackpropFilter,backendName:"webgl",kernelFunc:l}},{"@tensorflow/tfjs-core":"hADTC","../conv_backprop_gpu":"e7iMB","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],e7iMB:[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;let 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; } ${a?`float dyValue = getDy(b, yR, yC, d2); float xValue = getX(b, xR, xC, d1); dotProd += (xValue * dyValue);`:`float dyValue = getDy(b, d2, yR, yC); float xValue = getX(b, d1, xR, xC); dotProd += (xValue * dyValue);`} } } } setOutput(dotProd); } `}}class o{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterHeight,r=e.filterWidth,n=e.strideHeight,s=e.strideWidth,a="channelsLast"===e.dataFormat,o=t-1-e.padInfo.top,l=r-1-e.padInfo.left;this.userCode=` const ivec2 pads = ivec2(${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;let 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 >= ${e.inWidth}) { continue; } float dyValue = getDy(b, yF, yR, yC, d2); float xValue = getX(b, xF, xR, xC, d1); dotProd += (xValue * dyValue); } } } } setOutput(dotProd); } `}}class i{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterDepth,r=e.filterHeight,n=e.filterWidth,s=e.strideDepth,a=e.strideHeight,o=e.strideWidth,l=t-1-e.padInfo.front,i=r-1-e.padInfo.top,u=n-1-e.padInfo.left;this.userCode=` const ivec3 pads = ivec3(${l}, ${i}, ${u}); void main() { ivec5 coords = getOutputCoords(); int batch = coords.x; int d1 = coords.u; ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads; int dyFCorner = dyCorner.x; int dyRCorner = dyCorner.y; int dyCCorner = dyCorner.z; float dotProd = 0.0; for (int wF = 0; wF< ${t}; wF++) { float dyF = float(dyFCorner + wF) / ${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< ${e.outChannels}; d2++) { float xValue = getDy(batch, idyF, idyR, idyC, d2); float wValue = getW(wFPerm, wRPerm, wCPerm, d1, d2); dotProd += xValue * wValue; } } } } setOutput(dotProd); } `}}},{"@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],cuDGO:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"conv2DBackpropInput",()=>i),s.export(r,"conv2DBackpropInputConfig",()=>u);var a=e("@tensorflow/tfjs-core"),o=e("../conv_backprop_gpu"),l=e("../conv_backprop_packed_gpu");function i(e){let{inputs:t,backend:r,attrs:n}=e,{dy:s,filter:i}=t,{inputShape:u,strides:p,pad:c,dataFormat:d,dimRoundingMode:f}=n,h=a.backend_util.convertConv2DDataFormat(d),m=a.backend_util.computeConv2DInfo(u,i.shape,p,1,c,f,!1,h);if((0,a.env)().getBool("WEBGL_PACK_CONV2DTRANSPOSE")&&"channelsLast"===h){let e=[[m.strideHeight,m.strideWidth]],t=new(0,l.Conv2DDerInputPackedProgram)(m);return r.runWebGLProgram(t,[s,i],"float32",e)}{let e=new(0,o.Conv2DDerInputProgram)(m);return r.runWebGLProgram(e,[s,i],"float32")}}let u={kernelName:a.Conv2DBackpropInput,backendName:"webgl",kernelFunc:i}},{"@tensorflow/tfjs-core":"hADTC","../conv_backprop_gpu":"e7iMB","../conv_backprop_packed_gpu":"5Aqjf","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],"5Aqjf":[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"Conv2DDerInputPackedProgram",()=>o);var a=e("./gpgpu_math");class o{constructor(e){this.variableNames=["dy","W"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"strides",type:"vec2"}],this.outputShape=e.inShape,this.enableShapeUniforms=(0,a.useShapeUniforms)(this.outputShape.length);let t=e.filterHeight,r=e.filterWidth,n=t-1-e.padInfo.top,s=r-1-e.padInfo.left;this.userCode=` const ivec2 pads = ivec2(${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 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":"loqXi"}],"9L8uJ":[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",()=>u);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:u}=r,{strides:p,pad:c,dilations:d,dimRoundingMode:f}=s,h=d;null==h&&(h=[1,1]),a.util.assert(a.backend_util.eitherStridesOrDilationsAreOne(p,h),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${p} and dilations '${h}'`);let m=a.backend_util.computeConv2DInfo(i.shape,u.shape,p,h,c,f,!0);t=(0,a.env)().getBool("WEBGL_PACK_DEPTHWISECONV")&&m.strideWidth<=2&&m.outChannels/m.inChannels==1?new(0,l.DepthwiseConvPacked2DProgram)(m):new(0,o.DepthwiseConv2DProgram)(m);let g=[[m.padInfo.top,m.padInfo.left],[m.strideHeight,m.strideWidth],[m.dilationHeight,m.dilationWidth],[m.inHeight,m.inWidth]];return n.runWebGLProgram(t,[i,u],"float32",g)}let u={kernelName:a.DepthwiseConv2dNative,backendName:"webgl",kernelFunc:i}},{"@tensorflow/tfjs-core":"hADTC","../conv_gpu_depthwise":"hZW35","../conv_packed_gpu_depthwise":"f0bET","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],hZW35:[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);let o=e.filterHeight,l=e.filterWidth,i=e.outChannels/e.inChannels,u="",p="";r&&(u=n?`float activation(float a) { float b = getPreluActivationWeightsAtOutCoords(); ${r} }`:s?`float activation(float a) { float b = getLeakyreluAlphaAtOutCoords(); ${r} }`:` float activation(float x) { ${r} } `,p="result = activation(result);"),t&&this.variableNames.push("bias"),n&&this.variableNames.push("preluActivationWeights"),s&&this.variableNames.push("leakyreluAlpha"),this.userCode=` ${u} 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();":""} ${p} setOutput(result); } `}}},{"./gpgpu_math":"aCqaC","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],f0bET:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"DepthwiseConvPacked2DProgram",()=>l);var a=e("@tensorflow/tfjs-core"),o=e("./gpgpu_math");class l{constructor(e,t=!1,r=null,n=!1,s=!1){this.variableNames=["x","W"],this.packedInputs=!0,this.packedOutput=!0,this.customUniforms=[{name:"pads",type:"ivec2"},{name:"strides",type:"ivec2"},{name:"dilations",type:"ivec2"},{name:"inDims",type:"ivec2"}],this.outputShape=e.outShape,this.enableShapeUniforms=(0,o.useShapeUniforms)(this.outputShape.length);let l=e.outChannels/e.inChannels,i=e.padInfo.left,u=e.strideWidth,p=e.dilationWidth,c=e.filterHeight,d=e.filterWidth,f=` int xR; int xC; int xCOffset; vec4 wTexel; vec4 previous; vec4 final;`;for(let e=0;e<d;e++)f+=` vec4 xTexelC${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++){let t=2*e;if(f+=` xC = xCCorner + ${t*p}; `,1===u){if(t<d&&(i%2==1?(f+=` xCOffset = xC + 1; if (xCOffset >= 0 && xCOffset< inDims[1] && xTexelC${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${t}Ready = 1; } `,1===p&&t>0?f+=` xC${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)){let e=i%2==0?a.util.nearestLargerEven(p):p;p%2==0&&i%2==1||p%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${t+1}Ready = 1; } `,p>1?f+=` xCOffset -= 2; if (xCOffset >= 0 && xCOffset< inDims[1]) { previous = getX(batch, xR, xCOffset, d1); xC${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 h="",m="";r&&(h=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=` ${h} 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();":""} ${m} setOutput(result); } `}}},{"@tensorflow/tfjs-core":"hADTC","./gpgpu_math":"aCqaC","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],"91Gmp":[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:u,pad:p,dimRoundingMode:c,filterShape:d}=n,f=a.backend_util.computeConv2DInfo(s.shape,d,i,u,p,c,!0),h=new(0,o.DepthwiseConv2DDerFilterProgram)(f);return r.runWebGLProgram(h,[s,l],"float32")}let i={kernelName:a.DepthwiseConv2dNativeBackpropFilter,backendName:"webgl",kernelFunc:l}},{"@tensorflow/tfjs-core":"hADTC","../conv_backprop_gpu_depthwise":"3CkF8","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],"3CkF8":[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;let 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 >= ${e.inWidth}) { continue; } float dyValue = getDy(b, yR, yC, d2); float xValue = getX(b, xR, xC, d1); dotProd += (xValue * dyValue); } } } setOutput(dotProd); } `}}class o{constructor(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;let t=e.filterHeight,r=e.filterWidth,n=e.strideHeight,s=e.strideWidth,a=t-1-e.padInfo.top,o=r-1-e.padInfo.left,l=e.outChannels/e.inChannels;this.userCode=` const ivec2 pads = ivec2(${a}, ${o}); void main() { ivec4 coords = getOutputCoords(); int batch = coords[0]; int d1 = coords[3]; ivec2 dyCorner = coords.yz - pads; int dyRCorner = dyCorner.x; 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int b = coords[0]; int r = coords[1]; int c = coords[2]; int d = coords[3]; float x = getX(b, r, c, d); float sum = 0.0; for (int j = -${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 * ${a}; setOutput(val); } `}}},{"@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],ae9ST:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"LRNPackedProgram",()=>a);class a{constructor(e,t,r,n,s){let a;this.variableNames=["x"],this.outputShape=[],this.packedInputs=!0,this.packedOutput=!0;let o=e[3]-1;this.outputShape=e;let l=`float(${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":"loqXi"}],"1QDvH":[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:u,alpha:p,beta:c}=n,d=new(0,o.LRNGradProgram)(s.shape,i,u,p,c);return r.runWebGLProgram(d,[s,a,l],s.dtype)},i={kernelName:a.LRNGrad,backendName:"webgl",kernelFunc:l}},{"@tensorflow/tfjs-core":"hADTC","../lrn_grad_gpu":"jps1r","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],jps1r:[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(); 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= 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 * ${a} + wC; float mask = float(maxPosValue == curPosValue ? 1.0 : 0.0); dotProd += dyValue * mask; } } setOutput(dotProd); } `}}class o{constructor(e){this.variableNames=["dy","maxPos"],this.outputShape=e.inShape;let t=e.strideDepth,r=e.strideHeight,n=e.strideWidth,s=e.dilationDepth,a=e.dilationHeight,o=e.dilationWidth,l=e.effectiveFilterDepth,i=e.effectiveFilterHeight,u=e.effectiveFilterWidth,p=l-1-e.padInfo.front,c=i-1-e.padInfo.top,d=u-1-e.padInfo.left;this.userCode=` const ivec3 pads = ivec3(${p}, ${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< ${u}; 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*u-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} * ${u} + wR * ${u} + wC; float mask = float(maxPosValue == curPosValue ? 1.0 : 0.0); dotProd += dyValue * mask; } } } setOutput(dotProd); } `}}},{"@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],e2UoK:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"maxPoolGrad",()=>u),s.export(r,"maxPoolGradConfig",()=>p);var a=e("@tensorflow/tfjs-core"),o=e("../max_pool_backprop_gpu"),l=e("../pool_gpu"),i=e("../webgl_util");function u(e){let{inputs:t,backend:r,attrs:n}=e,{dy:s,input:u,output:p}=t;(0,i.assertNotComplex)([u,p],"maxPoolGrad");let{filterSize:c,strides:d,pad:f,dimRoundingMode:h}=n,m=a.backend_util.computePool2DInfo(u.shape,c,d,1,f,h),g=new(0,l.Pool2DProgram)(m,"max",!0),x=r.runWebGLProgram(g,[u],u.dtype),v=new(0,o.MaxPool2DBackpropProgram)(m),y=r.runWebGLProgram(v,[s,x],u.dtype);return r.disposeIntermediateTensorInfo(x),y}let p={kernelName:a.MaxPoolGrad,backendName:"webgl",kernelFunc:u}},{"@tensorflow/tfjs-core":"hADTC","../max_pool_backprop_gpu":"3Mg5I","../pool_gpu":"6Iq2c","../webgl_util":"hSqB7","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],eue0R:[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:u}=t;a.util.assert(4===n.shape.length,()=>`Error in maxPool: input must be rank 4 but got rank ${n.shape.length}.`);let p=[1,1];a.util.assert(a.backend_util.eitherStridesOrDilationsAreOne(l,p),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${l} and dilations '${p}'`);let c=a.backend_util.computePool2DInfo(n.shape,s,l,p,i),[d,f]=(0,o.maxPoolWithArgmaxImpl)(n,u,c,r);return[d,f]}}},{"@tensorflow/tfjs-core":"hADTC","./MaxPoolWithArgmax_impl":"kNWzJ","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],kNWzJ:[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":"6Iq2c","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],eyzN2:[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,u=n.shape.length,p=a.util.parseAxisParam(i,n.shape),c=p,d=a.backend_util.getAxesPermutation(c,u),f=null!=d,h=r.shouldExecuteOnCPU([n]),m=[],g=n;if(f){if(h){let e=r.texData.get(g.dataId).values,t=Array(u);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);m.push(g),c=a.backend_util.getInnerMostAxes(c.length,u)}a.backend_util.assertAxesAreInnerMostDims("sum",c,u);let[x,v]=a.backend_util.computeOutAndReduceShapes(g.shape,c),y=x;s&&(y=a.backend_util.expandShapeToKeepDim(x,p));let _=(0,o.meanImpl)(g,v,y,r);for(let e of m)r.disposeIntermediateTensorInfo(e);return _}}},{"@tensorflow/tfjs-core":"hADTC","./Mean_impl":"iriUo","./Transpose_impl":[["transposeImpl","iUCh6"],["transposeImplCPU","awGPZ"]],"@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],iriUo:[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),u=(0,l.reshape)({inputs:{x:e},attrs:{shape:[i/s,s]},backend:n}),p=(0,o.reduce)(u,"float32","mean",n),c=(0,l.reshape)({inputs:{x:p},attrs:{shape:r},backend:n});return n.disposeIntermediateTensorInfo(u),n.disposeIntermediateTensorInfo(p),c}},{"@tensorflow/tfjs-core":"hADTC","../kernel_utils/reduce":"ghhUV","../kernels/Reshape":"6JJRX","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],dIWud:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"min",()=>u),s.export(r,"minConfig",()=>p);var a=e("@tensorflow/tfjs-core"),o=e("../kernel_utils/reduce"),l=e("./Reshape"),i=e("./Transpose");function u(e){let t,{inputs:r,backend:n,attrs:s}=e,{x:u}=r,{axis:p,keepDims:c}=s,d=u.shape.length,f=a.util.parseAxisParam(p,u.shape),h=f,m=a.backend_util.getAxesPermutation(h,d),g=u;null!=m&&(g=(0,i.transpose)({inputs:{x:u},backend:n,attrs:{perm:m}}),h=a.backend_util.getInnerMostAxes(h.length,u.shape.length)),a.backend_util.assertAxesAreInnerMostDims("min",h,d);let[x,v]=a.backend_util.computeOutAndReduceShapes(g.shape,h),y=a.util.sizeFromShape(v),_=(0,l.reshape)({inputs:{x:g},backend:n,attrs:{shape:[-1,y]}}),b=(0,o.reduce)(_,_.dtype,"min",n);if(c){let e=a.backend_util.expandShapeToKeepDim(x,f);t=(0,l.reshape)({inputs:{x:b},backend:n,attrs:{shape:e}})}else t=(0,l.reshape)({inputs:{x:b},backend:n,attrs:{shape:x}});return n.disposeIntermediateTensorInfo(_),n.disposeIntermediateTensorInfo(b),null!=m&&n.disposeIntermediateTensorInfo(g),t}let p={kernelName:a.Min,backendName:"webgl",kernelFunc:u}},{"@tensorflow/tfjs-core":"hADTC","../kernel_utils/reduce":"ghhUV","./Reshape":"6JJRX","./Transpose":"6x6Ts","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],dkrAD:[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"),u=e("../kernel_utils/shared");let p=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:p,packedOpSnippet:c,cpuKernelImpl:u.minimumImplCPU}),f={kernelName:a.Minimum,backendName:"webgl",kernelFunc:d}},{"@tensorflow/tfjs-core":"hADTC","../binaryop_gpu":"a2Mj7","../binaryop_packed_gpu":"fwruC","../kernel_utils/kernel_funcs_utils":"eRfJh","../kernel_utils/shared":"awGPZ","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],hiTbr:[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",()=>u);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,u=(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(u,[n],n.dtype)},u={kernelName:a.MirrorPad,backendName:"webgl",kernelFunc:i}},{"@tensorflow/tfjs-core":"hADTC","../mirror_pad_gpu":"k1Kdk","../mirror_pad_packed_gpu":"4mdW8","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],k1Kdk:[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]);let 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),u=+("reflect"!==r);if(1===n){this.userCode=` int start = ${o}; 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const ${s} end = ${s}(${i}); void main() { ${s} outputLoc = getOutputCoords(); vec4 result = vec4(0.); ${h} setOutput(result); } `}}},{"./packing_util":"gX790","./shader_compiler":"2b0aL","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],HrpnP:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"mod",()=>p),s.export(r,"modConfig",()=>c);var a=e("@tensorflow/tfjs-core"),o=e("../binaryop_packed_gpu"),l=e("../kernel_utils/kernel_funcs_utils");let i=`if (b == 0.0) return NAN; return mod(a, b);`,u=` vec4 result = mod(a, b); bvec4 isNaN = equal(b, vec4(0.0)); `+o.CHECK_NAN_SNIPPET_PACKED+` return result; `,p=(0,l.binaryKernelFunc)({opSnippet:i,packedOpSnippet:u}),c={kernelName:a.Mod,backendName:"webgl",kernelFunc:p}},{"@tensorflow/tfjs-core":"hADTC","../binaryop_packed_gpu":"fwruC","../kernel_utils/kernel_funcs_utils":"eRfJh","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],"023g2":[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"multinomial",()=>i),s.export(r,"multinomialConfig",()=>u);var a=e("@tensorflow/tfjs-core"),o=e("../multinomial_gpu"),l=e("./Softmax");function i(e){let{inputs:t,backend:r,attrs:n}=e,{logits:s}=t,{numSamples:a,seed:i,normalized:u}=n,p=u?s:(0,l.softmax)({inputs:{logits:s},backend:r,attrs:{dim:s.shape.length-1}}),c=p.shape[0],d=p.shape[1],f=new(0,o.MultinomialProgram)(c,d,a),h=r.runWebGLProgram(f,[p],"int32",[[i]]);return u||r.disposeIntermediateTensorInfo(p),h}let u={kernelName:a.Multinomial,backendName:"webgl",kernelFunc:i}},{"@tensorflow/tfjs-core":"hADTC","../multinomial_gpu":"1tJSb","./Softmax":"cDakL","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],"1tJSb":[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"MultinomialProgram",()=>a);class a{constructor(e,t,r){this.variableNames=["probs"],this.customUniforms=[{name:"seed",type:"float"}],this.outputShape=[e,r],this.userCode=` void main() { ivec2 coords = getOutputCoords(); 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i={kernelName:a.RaggedGather,backendName:"webgl",kernelFunc:l}},{"@tensorflow/tfjs-core":"hADTC","../kernel_utils/shared":"awGPZ","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],"4g5B2":[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),u=r.readSync(a.dataId),[p,c]=(0,o.raggedRangeImplCPU)(l,n.shape,n.dtype,i,s.shape,u,a.shape);return[r.makeTensorInfo([p.length],"int32",p),r.makeTensorInfo([c.length],n.dtype,c)]}let i={kernelName:a.RaggedRange,backendName:"webgl",kernelFunc:l}},{"@tensorflow/tfjs-core":"hADTC","../kernel_utils/shared":"awGPZ","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],"2ARTj":[function(e,t,r,n){var 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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":"hADTC","../kernel_utils/shared":"awGPZ","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],"3U322":[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":"hADTC","../kernel_utils/kernel_funcs_utils":"eRfJh","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],bWdfN:[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"relu",()=>u),s.export(r,"reluConfig",()=>p);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; `,u=(0,o.unaryKernelFunc)({opSnippet:l,packedOpSnippet:i}),p={kernelName:a.Relu,backendName:"webgl",kernelFunc:u}},{"@tensorflow/tfjs-core":"hADTC","../kernel_utils/kernel_funcs_utils":"eRfJh","../unaryop_gpu":"dKkzg","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],"4vqNA":[function(e,t,r,n){var s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"relu6",()=>u),s.export(r,"relu6Config",()=>p);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; `,u=(0,o.unaryKernelFunc)({opSnippet:l,packedOpSnippet:i}),p={kernelName:a.Relu6,backendName:"webgl",kernelFunc:u}},{"@tensorflow/tfjs-core":"hADTC","../kernel_utils/kernel_funcs_utils":"eRfJh","../unaryop_gpu":"dKkzg","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],cEb6n:[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",()=>u);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:u,size:p}=n,[c,d]=p,f=(0,a.env)().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new(0,l.ResizeBilinearPackedProgram)(s.shape,c,d,i,u):new(0,o.ResizeBilinearProgram)(s.shape,c,d,i,u);return r.runWebGLProgram(f,[s],"float32")}let u={kernelName:a.ResizeBilinear,backendName:"webgl",kernelFunc:i}},{"@tensorflow/tfjs-core":"hADTC","../resize_bilinear_gpu":"7ZFAw","../resize_bilinear_packed_gpu":"2OnKZ","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],"7ZFAw":[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=[];let[a,o,l,i]=e;this.outputShape=[a,t,r,i];let u=[n&&t>1?o-1:o,n&&r>1?l-1:l],p=[n&&t>1?t-1:t,n&&r>1?r-1:r];this.userCode=` const vec2 effectiveInputOverOutputRatioRC = vec2( ${u[0]/p[0]}, ${u[1]/p[1]}); const vec2 inputShapeRC = vec2(${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":"loqXi"}],"2OnKZ":[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=[];let[a,o,l,i]=e;this.outputShape=[a,t,r,i];let u=[n&&t>1?o-1:o,n&&r>1?l-1:l],p=[n&&t>1?t-1:t,n&&r>1?r-1:r];this.userCode=` const vec3 effectiveInputOverOutputRatioRC = vec3( ${u[0]/p[0]}, ${u[1]/p[1]}, ${u[1]/p[1]}); const vec3 inputShapeRC = vec3(${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":"loqXi"}],d9Mfx:[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":"hADTC","../resize_bilinear_backprop_gpu":"aBvtN","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],aBvtN:[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;let[,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],u=l[0]/i[0],p=l[1]/i[1],c=1/u,d=1/p,f=2*Math.ceil(c)+2,h=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(${u}); const float widthScale = float(${p}); const float invHeightScale = float(${c}); const float invWidthScale = float(${d}); const int winHeight = int(${f}); const int winWidth = int(${h}); // Compute bounds for where in dy we will look float startRLerp = floor(float(r) * invHeightScale); int startDyR = int(startRLerp - float(winHeight / 2)); float startCLerp = floor(float(c) * invWidthScale); int startDyC = int(startCLerp - float(winWidth / 2)); // Loop over dy for (int dyROffset = 0; dyROffset< winHeight; dyROffset++) { int dyR = dyROffset + startDyR; // Guard against the window exceeding the bounds of dy if (dyR < 0 || dyR >= ${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":"loqXi"}],bmwc8:[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",()=>u);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:u,size:p}=n,[c,d]=p,f=(0,a.env)().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new(0,l.ResizeNearestNeighborPackedProgram)(s.shape,c,d,i,u):new(0,o.ResizeNearestNeighborProgram)(s.shape,c,d,i,u);return r.runWebGLProgram(f,[s],s.dtype)}let u={kernelName:a.ResizeNearestNeighbor,backendName:"webgl",kernelFunc:i}},{"@tensorflow/tfjs-core":"hADTC","../resize_nearest_neighbor_gpu":"wVl0D","../resize_nearest_neighbor_packed_gpu":"3V7Ml","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],wVl0D:[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=[];let[a,o,l,i]=e;this.outputShape=[a,t,r,i];let u=[n&&t>1?o-1:o,n&&r>1?l-1:l],p=[n&&t>1?t-1:t,n&&r>1?r-1:r];this.userCode=` const vec2 effectiveInputOverOutputRatioRC = vec2( ${u[0]/p[0]}, ${u[1]/p[1]}); const vec2 inputShapeRC = vec2(${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":"loqXi"}],"3V7Ml":[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=[];let[a,o,l,i]=e;this.outputShape=[a,t,r,i];let u=[n&&t>1?o-1:o,n&&r>1?l-1:l],p=[n&&t>1?t-1:t,n&&r>1?r-1:r];this.userCode=` const vec3 effectiveInputOverOutputRatioRC = vec3( ${u[0]/p[0]}, ${u[1]/p[1]}, ${u[1]/p[1]}); const vec3 inputShapeRC = vec3(${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 < ${r-1}; vec4 newValue = vec4( getAValue(b, sourceNearestRC.x, sourceNearestRC.y, d), hasNextCol ? getAValue(b, sourceNearestRC.x, sourceNearestRC.y, d + 1) : 0.0, hasNextRow ? getAValue(b, sourceNearestRC.x, sourceNearestRC.z, d) : 0.0, (hasNextRow && hasNextCol) ? getAValue(b, sourceNearestRC.x, sourceNearestRC.z, d + 1) : 0.0); setOutput(newValue); } 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o{constructor(e,t){this.variableNames=["x"];let r=e.length;if(r>4)throw Error(`WebGL backend: Reverse of rank-${r} tensor is not yet supported`);if(this.outputShape=e,1===r){this.userCode=` void main() { int coord = getOutputCoords(); setOutput(getX(${e[0]} - coord - 1)); } `;return}let n=e.map((r,n)=>-1!==t.indexOf(n)&&1!==e[n]?`${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":"2b0aL","@parcel/transformer-js/src/esmodule-helpers.js":"loqXi"}],"1BHMm":[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){var r,n,s;this.variableNames=["x"],this.packedInputs=!0,this.packedOutput=!0;let l=e.length;if(l>4)throw Error(`WebGL backend: Reverse of rank-${l} tensor is not yet 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s=e("@parcel/transformer-js/src/esmodule-helpers.js");s.defineInteropFlag(r),s.export(r,"ScatterPackedProgram",()=>o);var a=e("./shader_compiler");class o{constructor(e,t,r,n,s,o,l=!0,i=!1){this.variableNames=["updates","indices","defaultValue"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=o;let u=(0,a.getCoordsDataType)(s.length),p=(0,a.getCoordsDataType)(o.length),c="";1===r?c="i":2===r&&(c="i, j");let d=`getIndices(${c})`,f="";1===n?f="i":2===n&&(f="i, coords[1]");let h=`getUpdates(${f})`,m="";i&&(m="coords[0], coords[1]");let g=`getDefaultValue(${m})`;this.userCode=` ${u} strides = ${u}(${s}); void main() { ${p} 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"}; } } if 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Equal":"hOgtZ","./kernels/Erf":"i3HT8","./kernels/Exp":"hPUQx","./kernels/ExpandDims":"YQiG0","./kernels/Expm1":"a5XSW","./kernels/FFT":"jnh5f","./kernels/Fill":"gLwZV","./kernels/FlipLeftRight":"3crkN","./kernels/Floor":"l7WfX","./kernels/FloorDiv":"bq9X7","./kernels/FusedConv2D":"jmgT6","./kernels/FusedDepthwiseConv2D":"cWEPO","./kernels/GatherNd":"gDqkt","./kernels/GatherV2":"qS03f","./kernels/Greater":"fMRwP","./kernels/GreaterEqual":"l1SE7","./kernels/Identity":"lz9gJ","./kernels/IFFT":"5rlbe","./kernels/Imag":"1YWkw","./kernels/IsFinite":"3kl64","./kernels/IsInf":"1xLXC","./kernels/IsNaN":"5p8Qz","./kernels/LeakyRelu":"BPSQp","./kernels/Less":"evneQ","./kernels/LessEqual":"5IGAH","./kernels/LinSpace":"3r1AE","./kernels/Log":"bwxVX","./kernels/Log1p":"fwrvQ","./kernels/LogicalAnd":"kol4r","./kernels/LogicalNot":"gcKA4","./kernels/LogicalOr":"bgaRE","./kernels/LRN":"2sRzy","./kernels/LRNGrad":"hFjiL","./kernels/Max":"dzwTK","./kernels/Maximum":"1Q4kc","./kernels/MaxPool":"kMXNT","./kernels/MaxPool3D":"d1dZ0","./kernels/MaxPool3DGrad":"hjBDV","./kernels/MaxPoolGrad":"hXQ5i","./kernels/MaxPoolWithArgmax":"ciK98","./kernels/Mean":"1EiRF","./kernels/Min":"fBfk7","./kernels/Minimum":"faufz","./kernels/MirrorPad":"799ir","./kernels/Mod":"3aUwW","./kernels/Multinomial":"gNpUi","./kernels/Multiply":"7NGDi","./kernels/Neg":"70PGK","./kernels/NonMaxSuppressionV3":"R7rVY","./kernels/NonMaxSuppressionV4":"aIhbu","./kernels/NonMaxSuppressionV5":"eJQKu","./kernels/NotEqual":"jrWXP","./kernels/OneHot":"hdgvU","./kernels/OnesLike":"7VQel","./kernels/Pack":"hEwG7","./kernels/PadV2":"9Z490","./kernels/Pow":"qmrVH","./kernels/Prelu":"6U1tC","./kernels/Prod":"9ym2m","./kernels/RaggedGather":"4fPuR","./kernels/RaggedRange":"crR9B","./kernels/RaggedTensorToTensor":"bZRl3","./kernels/Range":"jRkfN","./kernels/Real":"2dRsO","./kernels/RealDiv":"NXJyr","./kernels/Reciprocal":"958ZW","./kernels/Relu":"8pfPa","./kernels/Relu6":"8KuoG","./kernels/Reshape":"eIo6C","./kernels/ResizeBilinear":"6xOvz","./kernels/ResizeBilinearGrad":"dEg4d","./kernels/ResizeNearestNeighbor":"eBhqi","./kernels/ResizeNearestNeighborGrad":"7oB9R","./kernels/Reverse":"1htKV","./kernels/RotateWithOffset":"lnxXS","./kernels/Round":"lsMjQ","./kernels/Rsqrt":"bv39b","./kernels/ScatterNd":"b1Yfi","./kernels/SearchSorted":"1POT8","./kernels/Select":"9R6op","./kernels/Selu":"3nqxN","./kernels/Sigmoid":"feZfA","./kernels/Sign":"eTlOQ","./kernels/Sin":"5g8fH","./kernels/Sinh":"gGAnN","./kernels/Slice":"6zAVh","./kernels/Softmax":"H1bvB","./kernels/Softplus":"klSvI","./kernels/SpaceToBatchND":"8aAJV","./kernels/SparseFillEmptyRows":"kQn4a","./kernels/SparseReshape":"dckEc","./kernels/SparseSegmentMean":"au78P","./kernels/SparseSegmentSum":"dwoxZ","./kernels/SparseToDense":"loRNl","./kernels/SplitV":"7gid4","./kernels/Sqrt":"1aPpb","./kernels/Square":"ELl6R","./kernels/SquaredDifference":"JN6BO","./kernels/StaticRegexReplace":"7kidZ","./kernels/Step":"aKEGV","./kernels/StridedSlice":"2g4do","./kernels/StringNGrams":"c0QuG","./kernels/StringSplit":"jpuMv","./kernels/StringToHashBucketFast":"1eq9a","./kernels/Sub":"lwW2V","./kernels/Sum":"2o1Uw","./kernels/Tan":"bnQEx","./kernels/Tanh":"a59xI","./kernels/TensorScatterUpdate":"bPp5D","./kernels/Tile":"4DF5i","./kernels/TopK":"679kb","./kernels/Transform":"85hQ3","./kernels/Transpose":"jCE2o","./kernels/Unique":"8DrHh","./kernels/Unpack":"11UmK","./kernels/UnsortedSegmentSum":"2E5hY","./kernels/ZerosLike":"17IqM"}],"6Gn3Q":[function(e,t,r,n){var 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