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i=e.dataSync(),a=t.dataSync(),o=n.dataSync(),s=c.zeros(t.shape,r),u=s.dataSync(),l=0,p=0===e.rank||e.rank>1||1===t.rank?1:t.shape[1],h=0;h<i.length;h++)for(var d=0;d<p;d++)1===i[h]?u[l++]=a[h]:u[l++]=o[h];return s},e.prototype.topKValues=function(e,t){return this.topK(e,t).values},e.prototype.topKIndices=function(e,t){return this.topK(e,t).indices},e.prototype.topK=function(e,t){for(var n=e.dataSync(),r=[],i=0;i<n.length;i++)r.push({value:n[i],index:i});r.sort(function(e,t){return t.value-e.value});for(var a=g.getTypedArrayFromDType(e.dtype,t),o=new Int32Array(t),i=0;i<t;i++)a[i]=r[i].value,o[i]=r[i].index;return{values:c.tensor1d(a,e.dtype),indices:c.tensor1d(o,"int32")}},e.prototype.min=function(e,t){s.assertAxesAreInnerMostDims("min",t,e.rank);for(var n=s.computeOutAndReduceShapes(e.shape,t),r=n[0],i=n[1],a=c.zeros(r,e.dtype),o=g.sizeFromShape(i),u=a.dataSync(),l=e.dataSync(),p=0;p<u.length;++p){for(var h=p*o,d=l[0],f=0;f<o;++f){var m=l[h+f];if(isNaN(m)){d=Number.NaN;break}m<d&&(d=m)}u[p]=d}return a},e.prototype.minimum=function(e,t){return this.broadcastedBinaryOp(e,t,e.dtype,function(e,t){return Math.min(e,t)})},e.prototype.mod=function(e,t){return this.broadcastedBinaryOp(e,t,e.dtype,function(e,t){var n=e%t;return e<0&&t<0||e>=0&&t>=0?n:(n+t)%t})},e.prototype.max=function(e,t){s.assertAxesAreInnerMostDims("max",t,e.rank);for(var n=s.computeOutAndReduceShapes(e.shape,t),r=n[0],i=n[1],a=c.zeros(r,e.dtype),o=g.sizeFromShape(i),u=a.dataSync(),l=e.dataSync(),p=0;p<u.length;++p){for(var h=p*o,d=l[h],f=0;f<o;++f){var m=l[h+f];if(isNaN(m)){d=Number.NaN;break}m>d&&(d=m)}u[p]=d}return a},e.prototype.maximum=function(e,t){return this.broadcastedBinaryOp(e,t,e.dtype,function(e,t){return Math.max(e,t)})},e.prototype.squaredDifference=function(e,t){return this.broadcastedBinaryOp(e,t,e.dtype,function(e,t){var n=e-t;return n*n})},e.prototype.ceil=function(e){for(var t=e.dataSync(),n=new 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d.Tensor.make(e.shape,{values:n})},e.prototype.log=function(e){for(var t=e.dataSync(),n=new Float32Array(t.length),r=0;r<t.length;++r){var i=t[r];n[r]=Math.log(i)}return d.Tensor.make(e.shape,{values:n})},e.prototype.log1p=function(e){for(var t=e.dataSync(),n=new Float32Array(t.length),r=0;r<t.length;++r){var i=t[r];n[r]=Math.log1p(i)}return d.Tensor.make(e.shape,{values:n})},e.prototype.sqrt=function(e){for(var t=e.dataSync(),n=new Float32Array(t.length),r=0;r<t.length;++r){var i=t[r];n[r]=Math.sqrt(i)}return d.Tensor.make(e.shape,{values:n})},e.prototype.rsqrt=function(e){for(var t=e.dataSync(),n=new Float32Array(t.length),r=0;r<t.length;++r){var i=t[r];n[r]=1/Math.sqrt(i)}return d.Tensor.make(e.shape,{values:n})},e.prototype.square=function(e){for(var t=e.dataSync(),n=new Float32Array(t.length),r=0;r<t.length;++r){var i=t[r];n[r]=i*i}return d.Tensor.make(e.shape,{values:n})},e.prototype.reciprocal=function(e){for(var t=e.dataSync(),n=new 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Float32Array(e.size),r=e.dataSync(),i=0;i<r.length;i++){var a=r[i];n[i]=a>=0?a:t*a}return d.Tensor.make(e.shape,{values:n})},e.prototype.prelu=function(e,t){for(var n=new Float32Array(e.size),r=e.dataSync(),i=t.dataSync(),a=0;a<r.length;a++){var o=r[a];n[a]=o>=0?o:i[a]*o}return d.Tensor.make(e.shape,{values:n})},e.prototype.preluDer=function(e,t){for(var n=new Float32Array(e.size),r=e.dataSync(),i=t.dataSync(),a=0;a<r.length;a++){var o=r[a];n[a]=o>0?1:o<0?i[a]:o}return d.Tensor.make(e.shape,{values:n})},e.prototype.clip=function(e,t,n){for(var r=new Float32Array(e.size),i=e.dataSync(),a=0;a<i.length;++a)r[a]=Math.min(n,Math.max(t,i[a]));return d.Tensor.make(e.shape,{values:r})},e.prototype.abs=function(e){for(var t=new Float32Array(e.size),n=e.dataSync(),r=0;r<n.length;++r)t[r]=Math.abs(n[r]);return d.Tensor.make(e.shape,{values:t})},e.prototype.int=function(e){for(var t=new Int32Array(e.size),n=e.dataSync(),r=0;r<n.length;++r)t[r]=n[r];return d.Tensor.make(e.shape,{values:t},"int32")},e.prototype.sigmoid=function(e){for(var t=new Float32Array(e.size),n=e.dataSync(),r=0;r<n.length;++r)t[r]=1/(1+Math.exp(-n[r]));return d.Tensor.make(e.shape,{values:t})},e.prototype.sin=function(e){for(var t=new Float32Array(e.size),n=e.dataSync(),r=0;r<n.length;++r)t[r]=Math.sin(n[r]);return d.Tensor.make(e.shape,{values:t})},e.prototype.cos=function(e){for(var t=new Float32Array(e.size),n=e.dataSync(),r=0;r<n.length;++r)t[r]=Math.cos(n[r]);return d.Tensor.make(e.shape,{values:t})},e.prototype.tan=function(e){for(var t=new Float32Array(e.size),n=e.dataSync(),r=0;r<n.length;++r)t[r]=Math.tan(n[r]);return d.Tensor.make(e.shape,{values:t})},e.prototype.asin=function(e){for(var t=new Float32Array(e.size),n=e.dataSync(),r=0;r<n.length;++r)t[r]=Math.asin(n[r]);return d.Tensor.make(e.shape,{values:t})},e.prototype.acos=function(e){for(var t=new Float32Array(e.size),n=e.dataSync(),r=0;r<n.length;++r)t[r]=Math.acos(n[r]);return d.Tensor.make(e.shape,{values:t})},e.prototype.atan=function(e){for(var t=new Float32Array(e.size),n=e.dataSync(),r=0;r<n.length;++r)t[r]=Math.atan(n[r]);return d.Tensor.make(e.shape,{values:t})},e.prototype.atan2=function(e,t){return this.broadcastedBinaryOp(e,t,e.dtype,function(e,t){return Math.atan2(e,t)})},e.prototype.sinh=function(e){for(var t=new Float32Array(e.size),n=e.dataSync(),r=0;r<n.length;++r)t[r]=Math.sinh(n[r]);return d.Tensor.make(e.shape,{values:t})},e.prototype.cosh=function(e){for(var t=new Float32Array(e.size),n=e.dataSync(),r=0;r<n.length;++r)t[r]=Math.cosh(n[r]);return d.Tensor.make(e.shape,{values:t})},e.prototype.tanh=function(e){for(var t=new Float32Array(e.size),n=e.dataSync(),r=0;r<n.length;++r)t[r]=g.tanh(n[r]);return d.Tensor.make(e.shape,{values:t})},e.prototype.asinh=function(e){for(var t=new Float32Array(e.size),n=e.dataSync(),r=0;r<n.length;++r)t[r]=Math.asinh(n[r]);return d.Tensor.make(e.shape,{values:t})},e.prototype.acosh=function(e){for(var t=new Float32Array(e.size),n=e.dataSync(),r=0;r<n.length;++r)t[r]=Math.acosh(n[r]);return d.Tensor.make(e.shape,{values:t})},e.prototype.atanh=function(e){for(var t=new Float32Array(e.size),n=e.dataSync(),r=0;r<n.length;++r)t[r]=Math.atanh(n[r]);return d.Tensor.make(e.shape,{values:t})},e.prototype.step=function(e,t){void 0===t&&(t=0);for(var n=new Float32Array(e.size),r=e.dataSync(),i=0;i<r.length;++i){var a=r[i];g.isValNaN(a,e.dtype)?n[i]=g.getNaN(e.dtype):n[i]=a>0?1:t}return d.Tensor.make(e.shape,{values:n})},e.prototype.conv2d=function(e,t,n){for(var r=n.filterHeight,i=n.filterWidth,a=n.dilationHeight,o=n.dilationWidth,s=n.padInfo.left,u=n.padInfo.top,l=c.buffer(n.outShape,e.dtype),p=0;p<n.batchSize;++p)for(var h=0;h<n.outChannels;++h)for(var d=0;d<n.outHeight;++d)for(var f=d*n.strideHeight-s,g=0;g<n.outWidth;++g){for(var m=g*n.strideWidth-u,v=0,y=0;y<r;y++){var b=f+y*a;if(!(b<0||b>=n.inHeight))for(var w=0;w<i;w++){var x=m+w*o;if(!(x<0||x>=n.inWidth))for(var E=0;E<n.inChannels;++E)v+=e.get(p,b,x,E)*t.get(y,w,E,h)}}l.set(v,p,d,g,h)}return l.toTensor()},e.prototype.conv2dDerInput=function(e,t,n){for(var r=n.filterHeight,i=n.filterWidth,a=r-1-n.padInfo.top,o=i-1-n.padInfo.left,s=n.strideHeight,u=n.strideWidth,l=c.buffer(n.inShape,"float32"),p=0;p<n.batchSize;++p)for(var h=0;h<n.inChannels;++h)for(var d=0;d<n.inHeight;++d)for(var f=d-o,g=Math.max(0,Math.ceil(f/s)),m=Math.min(n.outHeight,(r+f)/s),v=0;v<n.inWidth;++v){for(var y=v-a,b=Math.max(0,Math.ceil(y/u)),w=Math.min(n.outWidth,(i+y)/u),x=0,E=g;E<m;++E)for(var _=E*s-f,A=b;A<w;++A)for(var S=A*u-y,O=0;O<n.outChannels;++O)x+=e.get(p,E,A,O)*t.get(r-1-_,i-1-S,h,O);l.set(x,p,d,v,h)}return l.toTensor()},e.prototype.conv2dDerFilter=function(e,t,n){for(var r=n.strideHeight,i=n.strideWidth,a=n.filterHeight,o=n.filterWidth,s=c.buffer(n.filterShape,"float32"),u=n.padInfo.left,l=n.padInfo.top,p=0;p<a;++p)for(var h=Math.max(0,Math.ceil((l-p)/r)),d=Math.min(n.outHeight,(n.inHeight+l-p)/r),f=0;f<o;++f)for(var g=Math.max(0,Math.ceil((u-f)/i)),m=Math.min(n.outWidth,(n.inWidth+u-f)/i),v=0;v<n.inChannels;++v)for(var y=0;y<n.outChannels;++y){for(var b=0,w=0;w<n.batchSize;++w)for(var x=h;x<d;++x)for(var E=p+x*r-l,_=g;_<m;++_){var A=f+_*i-u;b+=e.get(w,E,A,v)*t.get(w,x,_,y)}s.set(b,p,f,v,y)}return s.toTensor()},e.prototype.depthwiseConv2D=function(e,t,n){for(var r=n.filterHeight,i=n.filterWidth,a=n.dilationHeight,o=n.dilationWidth,s=n.padInfo.left,u=n.padInfo.top,l=n.outChannels/n.inChannels,p=c.buffer(n.outShape,e.dtype),h=0;h<n.batchSize;++h)for(var d=0;d<n.inChannels;++d)for(var f=0;f<n.outHeight;++f)for(var g=f*n.strideHeight-s,m=0;m<n.outWidth;++m)for(var v=m*n.strideWidth-u,y=0;y<l;++y){for(var b=0,w=0;w<r;++w){var x=g+w*a;if(!(x<0||x>=n.inHeight))for(var E=0;E<i;++E){var _=v+E*o;_<0||_>=n.inWidth||(b+=e.get(h,x,_,d)*t.get(w,E,d,y))}}p.set(b,h,f,m,d*l+y)}return p.toTensor()},e.prototype.tile=function(e,t){for(var n=new Array(e.rank),r=0;r<n.length;r++)n[r]=e.shape[r]*t[r];for(var i=c.buffer(n,e.dtype),a=e.buffer(),r=0;r<i.values.length;++r){for(var o=i.indexToLoc(r),s=new Array(e.rank),u=0;u<s.length;u++)s[u]=o[u]%e.shape[u];var l=a.locToIndex(s);i.values[r]=a.values[l]}return i.toTensor()},e.prototype.pad=function(e,t,n){var r=t.map(function(t,n){return t[0]+e.shape[n]+t[1]}),i=t.map(function(e){return e[0]}),a=e.buffer(),o=c.buffer(r,e.dtype);0!==n&&o.values.fill(n);for(var s=0;s<e.size;s++){var u=a.indexToLoc(s),l=u.map(function(e,t){return e+i[t]});o.set.apply(o,[e.get.apply(e,u)].concat(l))}return o.toTensor()},e.prototype.transpose=function(e,t){for(var n=new Array(e.rank),r=0;r<n.length;r++)n[r]=e.shape[t[r]];for(var i=e.dataSync(),a=p.buffer(n,e.dtype),o=e.buffer(),r=0;r<e.size;++r){for(var s=o.indexToLoc(r),u=new Array(s.length),l=0;l<u.length;l++)u[l]=s[t[l]];var c=a.locToIndex(u);a.values[c]=i[r]}return 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this.compileAndRun(t,[e])},e.prototype.sin=function(e){var t=new q.UnaryOpProgram(e.shape,W.SIN);return this.compileAndRun(t,[e])},e.prototype.cos=function(e){var t=new q.UnaryOpProgram(e.shape,W.COS);return this.compileAndRun(t,[e])},e.prototype.tan=function(e){var t=new q.UnaryOpProgram(e.shape,W.TAN);return this.compileAndRun(t,[e])},e.prototype.asin=function(e){var t=new q.UnaryOpProgram(e.shape,W.ASIN);return this.compileAndRun(t,[e])},e.prototype.acos=function(e){var t=new q.UnaryOpProgram(e.shape,W.ACOS);return this.compileAndRun(t,[e])},e.prototype.atan=function(e){var t=new q.UnaryOpProgram(e.shape,W.ATAN);return this.compileAndRun(t,[e])},e.prototype.atan2=function(e,t){var n=new y.BinaryOpProgram(v.ATAN2,e.shape,t.shape);return this.compileAndRun(n,[e,t])},e.prototype.sinh=function(e){var t=new q.UnaryOpProgram(e.shape,W.SINH);return this.compileAndRun(t,[e])},e.prototype.cosh=function(e){var t=new q.UnaryOpProgram(e.shape,W.COSH);return this.compileAndRun(t,[e])},e.prototype.tanh=function(e){var t=new q.UnaryOpProgram(e.shape,W.TANH);return this.compileAndRun(t,[e])},e.prototype.asinh=function(e){var t=new q.UnaryOpProgram(e.shape,W.ASINH);return this.compileAndRun(t,[e])},e.prototype.acosh=function(e){var t=new q.UnaryOpProgram(e.shape,W.ACOSH);return this.compileAndRun(t,[e])},e.prototype.atanh=function(e){var t=new q.UnaryOpProgram(e.shape,W.ATANH);return this.compileAndRun(t,[e])},e.prototype.step=function(e,t){var n=new q.UnaryOpProgram(e.shape,W.STEP(t));return this.compileAndRun(n,[e])},e.prototype.conv2d=function(e,t,n){var r=new E.Conv2DProgram(n);return this.compileAndRun(r,[e,t])},e.prototype.conv2dDerInput=function(e,t,n){var r=new x.Conv2DDerInputProgram(n);return this.compileAndRun(r,[e,t])},e.prototype.conv2dDerFilter=function(e,t,n){var r=new x.Conv2DDerFilterProgram(n);return this.compileAndRun(r,[e,t])},e.prototype.depthwiseConv2D=function(e,t,n){var r=new _.DepthwiseConv2DProgram(n);return this.compileAndRun(r,[e,t])},e.prototype.maxPool=function(e,t){var n=new D.Pool2DProgram(t,"max",!1),r=this.makeOutputArray(n.outputShape,e.dtype);return this.compileAndRun(n,[e],r)},e.prototype.minPool=function(e,t){var n=new D.Pool2DProgram(t,"min",!1),r=this.makeOutputArray(n.outputShape,e.dtype);return this.compileAndRun(n,[e],r)},e.prototype.avgPool=function(e,t){var n=new D.Pool2DProgram(t,"avg",!1),r=this.makeOutputArray(n.outputShape,"float32");return this.compileAndRun(n,[e],r)},e.prototype.maxPoolBackprop=function(e,t,n){var r=new D.Pool2DProgram(n,"max",!0),i=this.compileAndRun(r,[t]),a=new N.MaxPool2DBackpropProgram(n),o=this.makeOutputArray(a.outputShape,t.dtype),s=this.compileAndRun(a,[e,i],o);return i.dispose(),s},e.prototype.avgPoolBackprop=function(e,t,n){var r=new g.AvgPool2DBackpropProgram(n),i=this.makeOutputArray(r.outputShape,t.dtype);return this.compileAndRun(r,[e],i)},e.prototype.cast=function(e,t){return d.castTensor(e,t,this)},e.prototype.reshape=function(e,t){return d.reshapeTensor(e,t)},e.prototype.resizeBilinear=function(e,t,n,r){var i=new P.ResizeBilinearProgram(e.shape,t,n,r);return this.compileAndRun(i,[e])},e.prototype.multinomial=function(e,t,n){var r=e.shape[0],i=e.shape[1],a=new I.MultinomialProgram(r,i,t),o=this.makeOutputArray(a.outputShape,"int32"),s=a.getCustomSetupFunc(n);return this.compileAndRun(a,[e],o,s)},e.prototype.oneHot=function(e,t,n,r){var i=new z.OneHotProgram(e.size,t,n,r);return this.compileAndRun(i,[e])},e.prototype.makeOutputArray=function(e,t){return c.Tensor.make(e,{},t)},e.prototype.compileAndRun=function(e,t,n,r){var i=this;null==n&&(n=this.makeOutputArray(e.outputShape,t[0].dtype));var a=t.map(function(e){return i.uploadToGPU(e.dataId),{tensor:e,texData:i.texData.get(e.dataId)}});this.uploadToGPU(n.dataId);var o,s={tensor:n,texData:this.texData.get(n.dataId)},u=T.makeShaderKey(e,a,s),l=this.getAndSaveBinary(u,function(){return T.compileProgram(i.gpgpu,e,a,s)}),c=null!=this.activeTimers;return c&&(o=this.startTimer()),T.runProgram(l,a,s,r),c&&(o=this.endTimer(o),this.activeTimers.push(this.getQueryTime(o))),n},e.prototype.getAndSaveBinary=function(e,t){return e in this.binaryCache||(this.binaryCache[e]=t()),this.binaryCache[e]},e.prototype.getTextureManager=function(){return this.textureManager},e.prototype.dispose=function(){if(!this.disposed){for(var e in this.binaryCache)this.gpgpu.deleteProgram(this.binaryCache[e].webGLProgram);this.textureManager.dispose(),this.canvas.remove(),this.gpgpuCreatedLocally&&this.gpgpu.dispose(),this.disposed=!0}},e.prototype.throwIfNoData=function(e){if(!this.texData.has(e))throw new Error("WebGL backend: No data found for this tensor. Did you change your backend in the middle of the program? New backends can't use Tensors created with previous backends")},e.prototype.uploadToGPU=function(e){this.throwIfNoData(e);var t=this.texData.get(e),n=t.shape,r=t.values,a=t.texture,o=t.dtype,s=t.texType;if(null==a){var u,l=null!=this.activeTimers;l&&(u=performance.now());var c=K.getTextureShapeFromLogicalShape(this.gpgpu.gl,n);t.texShape=c;var p=this.textureManager.acquireTexture(c,s);t.texture=p,null!=r&&(this.gpgpu.uploadMatrixToTexture(p,c[0],c[1],i(r,o)),t.values=null,l&&(this.uploadWaitMs+=performance.now()-u))}},e.prototype.cacheOnCPU=function(e,t){var n=this.delayedStorage,i=this.texData.get(e),a=i.texture,o=i.texShape,s=i.dtype,u=i.texType;n&&null!=a&&(this.textureManager.releaseTexture(a,o,u),i.texture=null,i.texShape=null),null!=t&&(i.values=r(t,s))},e}();n.MathBackendWebGL=H,s.ENV.registerBackend("webgl",function(){return new H})},{"../environment":5,"../ops/axis_util":46,"../ops/reduce_util":66,"../tensor":86,"../types":91,"../util":92,"./backend_util":10,"./webgl/argminmax_gpu":12,"./webgl/avg_pool_backprop_gpu":13,"./webgl/batchnorm_gpu":14,"./webgl/binaryop_gpu":15,"./webgl/clip_gpu":16,"./webgl/concat_gpu":17,"./webgl/conv_backprop_gpu":18,"./webgl/conv_gpu":19,"./webgl/conv_gpu_depthwise":20,"./webgl/from_pixels_gpu":21,"./webgl/gather_gpu":22,"./webgl/gpgpu_context":23,"./webgl/gpgpu_math":24,"./webgl/logical_gpu":26,"./webgl/lrn_gpu":27,"./webgl/max_pool_backprop_gpu":28,"./webgl/mulmat_gpu":29,"./webgl/multinomial_gpu":30,"./webgl/onehot_gpu":31,"./webgl/pad_gpu":32,"./webgl/pool_gpu":33,"./webgl/reduce_gpu":34,"./webgl/resize_bilinear_gpu":35,"./webgl/reverse_gpu":36,"./webgl/slice_gpu":38,"./webgl/tex_util":39,"./webgl/texture_manager":40,"./webgl/tile_gpu":41,"./webgl/transpose_gpu":42,"./webgl/unaryop_gpu":43,"./webgl/webgl_util":44}],12:[function(e,t,n){"use strict";Object.defineProperty(n,"__esModule",{value:!0});var r=function(){return function(e,t,n){this.variableNames=["A"];var r=e.windowSize,i=e.batchSize,a=e.inSize,o=Math.ceil(a/r);n||this.variableNames.push("bestIndicesA"),this.outputShape=[i,o];var s="max"===t?">":"<",u=n?"inOffset + i;":"round(getBestIndicesA(batch, inOffset + i));";this.userCode="\n      void main() {\n        ivec2 coords = getOutputCoords();\n        int batch = coords[0];\n        int outIdx = coords[1];\n        int inOffset = outIdx * "+r+";\n\n        int bestIndex = 0;\n        float bestValue = getA(batch, inOffset);\n\n        for (int i = 0; i < "+r+"; i++) {\n          int inIdx = "+u+";\n          float candidate = getA(batch, inIdx);\n          if (isNaN(candidate)) {\n            setOutput(candidate);\n            return;\n          }\n          if (candidate "+s+" bestValue) {\n            bestValue = candidate;\n            bestIndex = inIdx;\n          }\n        }\n        setOutput(float(bestIndex));\n      }\n    "}}();n.ArgMinMaxProgram=r},{}],13:[function(e,t,n){"use strict";Object.defineProperty(n,"__esModule",{value:!0});var r=function(){return function(e){this.variableNames=["dy"],this.outputShape=e.inShape;var t=e.filterHeight,n=e.filterWidth,r=e.strideHeight,i=e.strideWidth,a=t-1-e.padInfo.top,o=n-1-e.padInfo.left,s=1/(t*n);this.userCode="\n      const ivec2 pads = ivec2("+a+", "+o+");\n      const float avgMultiplier = float("+s+");\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n\n        ivec2 dyRCCorner = coords.yz - pads;\n        int dyRCorner = dyRCCorner.x;\n        int dyCCorner = dyRCCorner.y;\n\n        // Convolve dy(?, ?, d) with pos mask(:, :, d) to get dx(xR, xC, d).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n        for (int wR = 0; wR < "+t+"; wR++) {\n          float dyR = float(dyRCorner + wR) / "+r+".0;\n\n          if (dyR < 0.0 || dyR >= "+e.outHeight+".0 || fract(dyR) > 0.0) {\n            continue;\n          }\n          int idyR = int(dyR);\n\n          for (int wC = 0; wC < "+n+"; wC++) {\n            float dyC = float(dyCCorner + wC) / "+i+".0;\n\n            if (dyC < 0.0 || dyC >= "+e.outWidth+".0 ||\n                fract(dyC) > 0.0) {\n              continue;\n            }\n            int idyC = int(dyC);\n\n            float dyValue = getDy(b, idyR, idyC, d);\n\n            dotProd += dyValue * avgMultiplier;\n          }\n        }\n        setOutput(dotProd);\n      }\n    "}}();n.AvgPool2DBackpropProgram=r},{}],14:[function(e,t,n){"use strict";Object.defineProperty(n,"__esModule",{value:!0});var r=e("../../ops/broadcast_util"),i=function(){return function(e,t,n,i,a,o){this.outputShape=[],this.supportsBroadcasting=!0,this.variableNames=["x","mean","variance"],r.assertAndGetBroadcastShape(e,t),r.assertAndGetBroadcastShape(e,n);var s="0.0";null!=i&&(r.assertAndGetBroadcastShape(e,i),this.variableNames.push("offset"),s="getOffsetAtOutCoords()");var u="1.0";null!=a&&(r.assertAndGetBroadcastShape(e,a),this.variableNames.push("scale"),u="getScaleAtOutCoords()"),this.outputShape=e,this.userCode="\n      void main() {\n        float x = getXAtOutCoords();\n        float mean = getMeanAtOutCoords();\n        float variance = getVarianceAtOutCoords();\n        float offset = "+s+";\n        float scale = "+u+";\n        float inv = scale / sqrt(variance + float("+o+"));\n        setOutput((x - mean) * inv + offset);\n      }\n    "}}();n.BatchNormProgram=i},{"../../ops/broadcast_util":49}],15:[function(e,t,n){"use strict";Object.defineProperty(n,"__esModule",{value:!0});var r=e("../../ops/broadcast_util"),i="\n  if (isNaN(a)) return a;\n  if (isNaN(b)) return b;\n";n.ADD="return a + b;",n.SUB="return a - b;",n.MUL="return a * b;",n.DIV="return a / b;",n.POW="\n  return (round(mod(b, 2.0)) == 0 || round(mod(b, 2.0)) == 2) ?\n      pow(abs(a), b) : sign(a) * pow(abs(a), b);\n",n.SQUARED_DIFFERENCE="return (a - b) * (a - b);",n.EQUAL=i+"\n  return float(a == b);\n",n.NOT_EQUAL=i+"\n  return float(a != b);\n",n.LESS=i+"\n  return float(a < b);\n",n.LESS_EQUAL=i+"\n  return float(a <= b);\n",n.GREATER=i+"\n  return float(a > b);\n",n.GREATER_EQUAL=i+"\n  return float(a >= b);\n",n.LOGICAL_AND=i+"\n  return float(a >= 1.0 && b >= 1.0);\n",n.LOGICAL_OR=i+"\n  return float(a >= 1.0 || b >= 1.0);\n",n.LOGICAL_XOR=i+"\n  return float(a >= 1.0 ^^ b >= 1.0);\n",n.PRELU="\n  return (a >= 0.0) ? a : b * a;\n",n.PRELU_DER="\n  return (a > 0.0) ? 1.0 : ((a < 0.0) ? b : a);\n",n.MAX=i+"\n  return max(a, b);\n",n.MIN=i+"\n  return min(a, b);\n",n.MOD=i+"\n  return mod(a, b);\n",n.ATAN2=i+"\n  return atan(a, b);\n";var a=function(){return function(e,t,n){this.variableNames=["A","B"],this.supportsBroadcasting=!0,this.outputShape=r.assertAndGetBroadcastShape(t,n),this.userCode="\n      float binaryOperation(float a, float b) {\n        "+e+"\n      }\n\n      void main() {\n        float a = getAAtOutCoords();\n        float b = getBAtOutCoords();\n        setOutput(binaryOperation(a, b));\n      }\n    "}}();n.BinaryOpProgram=a},{"../../ops/broadcast_util":49}],16:[function(e,t,n){"use strict";Object.defineProperty(n,"__esModule",{value:!0});var r=function(){return function(e,t,n){this.variableNames=["A"],this.outputShape=e;var r=t.toFixed(20),i=n.toFixed(20);this.userCode="\n      void main() {\n        float value = getAAtOutCoords();\n        if (isNaN(value)) {\n          setOutput(value);\n          return;\n        }\n\n        setOutput(clamp(value, "+r+", "+i+"));\n      }\n    "}}();n.ClipProgram=r},{}],17:[function(e,t,n){"use strict";Object.defineProperty(n,"__esModule",{value:!0});var r=e("../../ops/concat_util"),i=function(){return function(e,t){this.variableNames=["A","B"],this.outputShape=[],this.outputShape=r.computeOutShape(e,t,1),this.userCode="\n      void main() {\n        ivec2 coords = getOutputCoords();\n        int yR = coords.x;\n        int yC = coords.y;\n\n        float value = 0.0;\n        if (yC < "+e[1]+") {\n          value = getA(yR, yC);\n        } else {\n          yC -= "+e[1]+";\n          value = getB(yR, yC);\n        }\n\n        setOutput(value);\n      }\n    "}}();n.ConcatProgram=i},{"../../ops/concat_util":52}],18:[function(e,t,n){"use strict";Object.defineProperty(n,"__esModule",{value:!0});var r=function(){return function(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;var t=e.strideHeight,n=e.strideWidth,r=e.padInfo.top,i=e.padInfo.left;this.userCode="\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int wR = coords.x;\n        int wC = coords.y;\n        int d1 = coords.z;\n        int d2 = coords.w;\n\n        // Convolve x(?, ?, d1) with dy(:, :, d2) to get dw(wR, wC, d1, d2).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n\n        for (int b = 0; b < "+e.batchSize+"; b++) {\n          for (int yR = 0; yR < "+e.outHeight+"; yR++) {\n            int xR = wR + yR * "+t+" - "+r+";\n\n            if (xR < 0 || xR >= "+e.inHeight+") {\n              continue;\n            }\n\n            for (int yC = 0; yC < "+e.outWidth+"; yC++) {\n              int xC = wC + yC * "+n+" - "+i+";\n\n              if (xC < 0 || xC >= "+e.inWidth+") {\n                continue;\n              }\n\n              float dyValue = getDy(b, yR, yC, d2);\n              float xValue = getX(b, xR, xC, d1);\n              dotProd += (xValue * dyValue);\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    "}}();n.Conv2DDerFilterProgram=r;var i=function(){return function(e){this.variableNames=["dy","W"],this.outputShape=e.inShape;var t=e.filterHeight,n=e.filterWidth,r=e.strideHeight,i=e.strideWidth,a=t-1-e.padInfo.top,o=n-1-e.padInfo.left;this.userCode="\n      const ivec2 pads = ivec2("+a+", "+o+");\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int batch = coords[0];\n        int d1 = coords[3];\n\n        ivec2 dyCorner = coords.yz - pads;\n        int dyRCorner = dyCorner.x;\n        int dyCCorner = dyCorner.y;\n\n        // Convolve dy(?, ?, d2) with w(:, :, d1, d2) to compute dx(xR, xC, d1).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n        for (int wR = 0; wR < "+t+"; wR++) {\n          float dyR = float(dyRCorner + wR) / "+r+".0;\n\n          if (dyR < 0.0 || dyR >= "+e.outHeight+".0 || fract(dyR) > 0.0) {\n            continue;\n          }\n          int idyR = int(dyR);\n\n          int wRPerm = "+t+" - 1 - wR;\n\n          for (int wC = 0; wC < "+n+"; wC++) {\n            float dyC = float(dyCCorner + wC) / "+i+".0;\n\n            if (dyC < 0.0 || dyC >= "+e.outWidth+".0 ||\n                fract(dyC) > 0.0) {\n              continue;\n            }\n            int idyC = int(dyC);\n\n            int wCPerm = "+n+" - 1 - wC;\n\n            for (int d2 = 0; d2 < "+e.outChannels+"; d2++) {\n              float xValue = getDy(batch, idyR, idyC, d2);\n              float wValue = getW(wRPerm, wCPerm, d1, d2);\n              dotProd += xValue * wValue;\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    "}}();n.Conv2DDerInputProgram=i},{}],19:[function(e,t,n){"use strict";Object.defineProperty(n,"__esModule",{value:!0});var r=function(){return function(e){this.variableNames=["x","W"],this.outputShape=e.outShape;var t=e.padInfo.top,n=e.padInfo.left,r=e.strideHeight,i=e.strideWidth,a=e.dilationHeight,o=e.dilationWidth,s=e.filterHeight,u=e.filterWidth,l=4*Math.floor(e.inChannels/4),c=e.inChannels%4;this.userCode="\n      const ivec2 strides = ivec2("+r+", "+i+");\n      const ivec2 pads = ivec2("+t+", "+n+");\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int batch = coords[0];\n        int d2 = coords[3];\n\n        ivec2 xRCCorner = coords.yz * strides - pads;\n        int xRCorner = xRCCorner.x;\n        int xCCorner = xRCCorner.y;\n\n        // Convolve x(?, ?, d1) with w(:, :, d1, d2) to get y(yR, yC, d2).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n        for (int wR = 0; wR < "+s+"; wR++) {\n          int xR = xRCorner + wR * "+a+";\n\n          if (xR < 0 || xR >= "+e.inHeight+") {\n            continue;\n          }\n\n          for (int wC = 0; wC < "+u+"; wC++) {\n            int xC = xCCorner + wC * "+o+";\n\n            if (xC < 0 || xC >= "+e.inWidth+") {\n              continue;\n            }\n\n            for (int d1 = 0; d1 < "+l+"; d1 += 4) {\n              vec4 xValues = vec4(\n                getX(batch, xR, xC, d1),\n                getX(batch, xR, xC, d1 + 1),\n                getX(batch, xR, xC, d1 + 2),\n                getX(batch, xR, xC, d1 + 3)\n              );\n              vec4 wValues = vec4(\n                getW(wR, wC, d1, d2),\n                getW(wR, wC, d1 + 1, d2),\n                getW(wR, wC, d1 + 2, d2),\n                getW(wR, wC, d1 + 3, d2)\n              );\n\n              dotProd += dot(xValues, wValues);\n            }\n\n            if ("+(1===c)+") {\n              dotProd +=\n                getX(batch, xR, xC, "+l+") *\n                getW(wR, wC, "+l+", d2);\n            } else if ("+(2===c)+") {\n              vec2 xValues = vec2(\n                getX(batch, xR, xC, "+l+"),\n                getX(batch, xR, xC, "+l+" + 1)\n              );\n              vec2 wValues = vec2(\n                getW(wR, wC, "+l+", d2),\n                getW(wR, wC, "+l+" + 1, d2)\n              );\n              dotProd += dot(xValues, wValues);\n            } else if ("+(3===c)+") {\n              vec3 xValues = vec3(\n                getX(batch, xR, xC, "+l+"),\n                getX(batch, xR, xC, "+l+" + 1),\n                getX(batch, xR, xC, "+l+" + 2)\n              );\n              vec3 wValues = vec3(\n                getW(wR, wC, "+l+", d2),\n                getW(wR, wC, "+l+" + 1, d2),\n                getW(wR, wC, "+l+" + 2, d2)\n              );\n              dotProd += dot(xValues, wValues);\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    "}}();n.Conv2DProgram=r},{}],20:[function(e,t,n){"use strict";Object.defineProperty(n,"__esModule",{value:!0});var r=function(){return function(e){this.variableNames=["x","W"],this.outputShape=e.outShape;var t=e.inHeight,n=e.inWidth,r=e.padInfo.top,i=e.padInfo.left,a=e.strideHeight,o=e.strideWidth,s=e.dilationHeight,u=e.dilationWidth,l=e.filterHeight,c=e.filterWidth,p=e.outChannels/e.inChannels;this.userCode="\n      const ivec2 strides = ivec2("+a+", "+o+");\n      const ivec2 pads = ivec2("+r+", "+i+");\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int batch = coords.x;\n        ivec2 xRCCorner = coords.yz * strides - pads;\n        int d2 = coords.w;\n        int d1 = d2 / "+p+";\n        int q = d2 - d1 * "+p+";\n\n        int xRCorner = xRCCorner.x;\n        int xCCorner = xRCCorner.y;\n\n        // Convolve x(?, ?, d1) with w(:, :, d1, q) to get y(yR, yC, d2).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n        // TODO(dsmilkov): Flatten the two for loops and vec4 the operations.\n        for (int wR = 0; wR < "+l+"; wR++) {\n          int xR = xRCorner + wR * "+s+";\n\n          if (xR < 0 || xR >= "+t+") {\n            continue;\n          }\n\n          for (int wC = 0; wC < "+c+"; wC++) {\n            int xC = xCCorner + wC * "+u+";\n\n            if (xC < 0 || xC >= "+n+") {\n              continue;\n            }\n\n            float xVal = getX(batch, xR, xC, d1);\n            float wVal = getW(wR, wC, d1, q);\n            dotProd += xVal * wVal;\n          }\n        }\n        setOutput(dotProd);\n      }\n    "}}();n.DepthwiseConv2DProgram=r},{}],21:[function(e,t,n){"use strict";Object.defineProperty(n,"__esModule",{value:!0});var r=function(){return function(e){this.variableNames=["A"];var t=e[0],n=e[1];this.outputShape=e,this.userCode="\n      void main() {\n        ivec3 coords = getOutputCoords();\n        int texR = coords[0];\n        int texC = coords[1];\n        int depth = coords[2];\n        vec2 uv = (vec2(texC, texR) + halfCR) / vec2("+n+".0, "+t+".0);\n\n        vec4 values = texture2D(A, uv);\n        float value;\n        if (depth == 0) {\n          value = values.r;\n        } else if (depth == 1) {\n          value = values.g;\n        } else if (depth == 2) {\n          value = values.b;\n        } else if (depth == 3) {\n          value = values.a;\n        }\n\n        setOutput(floor(value * 255.0 + 0.5));\n      }\n    "}}();n.FromPixelsProgram=r},{}],22:[function(e,t,n){"use strict";function r(e,t){var n=e.length;if(n>4)throw Error("Gather for rank "+n+" is not yet supported");if(1===n)return"int(getIndices(resRC))";for(var r=["resRC.x","resRC.y","resRC.z","resRC.w"],i=[],a=0;a<e.length;a++)a===t?i.push("int(getIndices("+r[a]+"))"):i.push(""+r[a]);return i.join()}Object.defineProperty(n,"__esModule",{value:!0});var i=e("./shader_compiler"),a=function(){return function(e,t,n){this.variableNames=["A","indices"];var a=e.slice();a[n]=t,this.outputShape=a,this.rank=a.length;var o=i.getCoordsDataType(this.rank),s=r(e,n);this.userCode="\n      void main() {\n        "+o+" resRC = getOutputCoords();\n        setOutput(getA("+s+"));\n      }\n    "}}();n.GatherProgram=a},{"./shader_compiler":37}],23:[function(e,t,n){"use strict";var r=this&&this.__awaiter||function(e,t,n,r){return new(n||(n=Promise))(function(i,a){function o(e){try{u(r.next(e))}catch(e){a(e)}}function s(e){try{u(r.throw(e))}catch(e){a(e)}}function u(e){e.done?i(e.value):new n(function(t){t(e.value)}).then(o,s)}u((r=r.apply(e,t||[])).next())})},i=this&&this.__generator||function(e,t){function n(e){return function(t){return r([e,t])}}function r(n){if(i)throw new TypeError("Generator is already executing.");for(;u;)try{if(i=1,a&&(o=a[2&n[0]?"return":n[0]?"throw":"next"])&&!(o=o.call(a,n[1])).done)return o;switch(a=0,o&&(n=[0,o.value]),n[0]){case 0:case 1:o=n;break;case 4:return u.label++,{value:n[1],done:!1};case 5:u.label++,a=n[1],n=[0];continue;case 7:n=u.ops.pop(),u.trys.pop();continue;default:if(o=u.trys,!(o=o.length>0&&o[o.length-1])&&(6===n[0]||2===n[0])){u=0;continue}if(3===n[0]&&(!o||n[1]>o[0]&&n[1]<o[3])){u.label=n[1];break}if(6===n[0]&&u.label<o[1]){u.label=o[1],o=n;break}if(o&&u.label<o[2]){u.label=o[2],u.ops.push(n);break}o[2]&&u.ops.pop(),u.trys.pop();continue}n=t.call(e,u)}catch(e){n=[6,e],a=0}finally{i=o=0}if(5&n[0])throw n[1];return{value:n[0]?n[1]:void 0,done:!0}}var i,a,o,s,u={label:0,sent:function(){if(1&o[0])throw o[1];return o[1]},trys:[],ops:[]};return s={next:n(0),throw:n(1),return:n(2)},"function"==typeof Symbol&&(s[Symbol.iterator]=function(){return this}),s};Object.defineProperty(n,"__esModule",{value:!0});var a=e("../../environment"),o=e("../../util"),s=e("./gpgpu_util"),u=e("./tex_util"),l=e("./webgl_util"),c=function(){function e(e){this.outputTexture=null,this.program=null,this.disposed=!1,this.autoDebugValidate=!1,this.firstProgram=!0,this.gl=null!=e?e:s.createWebGLContext(),1===a.ENV.get("WEBGL_VERSION")?(this.textureFloatExtension=l.getExtensionOrThrow(this.gl,"OES_texture_float"),this.colorBufferFloatExtension=this.gl.getExtension("WEBGL_color_buffer_float")):this.colorBufferFloatExtension=l.getExtensionOrThrow(this.gl,"EXT_color_buffer_float"),this.loseContextExtension=l.getExtensionOrThrow(this.gl,"WEBGL_lose_context"),a.ENV.get("WEBGL_GET_BUFFER_SUB_DATA_ASYNC_EXTENSION_ENABLED")&&(this.getBufferSubDataAsyncExtension=this.gl.getExtension("WEBGL_get_buffer_sub_data_async")),this.vertexBuffer=s.createVertexBuffer(this.gl),this.indexBuffer=s.createIndexBuffer(this.gl),this.framebuffer=l.createFramebuffer(this.gl)}return e.prototype.dispose=function(){var e=this;if(!this.disposed){null!=this.program&&console.warn("Disposing a GPGPUContext that still has a bound WebGLProgram. 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This is probably a resource leak, delete the output matrix texture with GPGPUContext.deleteMatrixTexture before disposing.");var t=this.gl;l.callAndCheck(t,function(){return t.finish()}),l.callAndCheck(t,function(){return t.bindFramebuffer(t.FRAMEBUFFER,null)}),l.callAndCheck(t,function(){return t.deleteFramebuffer(e.framebuffer)}),l.callAndCheck(t,function(){return t.bindBuffer(t.ARRAY_BUFFER,null)}),l.callAndCheck(t,function(){return t.deleteBuffer(e.vertexBuffer)}),l.callAndCheck(t,function(){return t.bindBuffer(t.ELEMENT_ARRAY_BUFFER,null)}),l.callAndCheck(t,function(){return t.deleteBuffer(e.indexBuffer)}),this.loseContextExtension.loseContext(),this.disposed=!0}},e.prototype.enableAutomaticDebugValidation=function(e){this.autoDebugValidate=e,l.enableDebugWebGLErrorChecking(e)},e.prototype.createMatrixTexture=function(e,t){return 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e=this.getQueryTimerExtensionWebGL1();e.endQueryEXT(e.TIME_ELAPSED_EXT)}else{var t=this.gl,n=this.getQueryTimerExtensionWebGL2();t.endQuery(n.TIME_ELAPSED_EXT)}},e.prototype.isQueryAvailable=function(e,t){if(0===t)return!0;if(2===t){var n=this.gl,r=this.getQueryTimerExtensionWebGL2(),i=n.getQueryParameter(e,n.QUERY_RESULT_AVAILABLE),a=this.gl.getParameter(r.GPU_DISJOINT_EXT);return i&&!a}var i=(r=this.getQueryTimerExtensionWebGL1()).getQueryObjectEXT(e,r.QUERY_RESULT_AVAILABLE_EXT),a=this.gl.getParameter(r.GPU_DISJOINT_EXT);return i&&!a},e.prototype.pollQueryTime=function(e){var t=this;return new Promise(function(n,r){var i=a.ENV.get("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION");o.repeatedTry(function(){return t.isQueryAvailable(e,i)}).then(function(){return n(t.getQueryTime(e,i))}).catch(function(){console.warn("Disjoint query timer never available."),n(-1)})})},e.prototype.getQueryTime=function(e,t){if(0===t)return null;if(2===t){var 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r=f.getPackedMatrixTextureShapeWidthHeight(t,n),i=r[0],a=r[1],s=new Float32Array(f.getPackedRGBAArraySizeFromMatrixShape(t,n));g.callAndCheck(e,function(){return e.readPixels(0,0,i,a,e.RGBA,o(e),s)});var u=new Float32Array(t*n);return f.decodeMatrixFromPackedRGBA(s,t,n,u)}},{"../../environment":5,"./tex_util":39,"./webgl_util":44}],26:[function(e,t,n){"use strict";Object.defineProperty(n,"__esModule",{value:!0});var r=e("./shader_compiler"),i=function(){return function(e,t,n){this.variableNames=["c","a","b"],this.outputShape=t;var i,a;if(n>4)throw Error("Where for rank "+n+" is not yet supported");if(1===n)a="resRC",i="resRC";else{for(var o=["resRC.x","resRC.y","resRC.z","resRC.w"],s=[],u=[],l=0;l<t.length;l++)u.push(""+o[l]),l<e&&s.push(""+o[l]);i=s.join(),a=u.join()}var c=r.getCoordsDataType(n);this.userCode="\n      void main() {\n        "+c+" resRC = getOutputCoords();\n        float cVal = getC("+i+");\n        if (cVal >= 1.0) {\n          setOutput(getA("+a+"));\n        } else {\n          setOutput(getB("+a+"));\n        }\n      }\n    "}}();n.WhereProgram=i},{"./shader_compiler":37}],27:[function(e,t,n){"use strict";Object.defineProperty(n,"__esModule",{value:!0});var r=function(){return function(e,t,n,r,i,a){this.variableNames=["x"],this.outputShape=[];var o=t,s=e[1]-1,u=e[2]-1,l=e[3]-1;this.outputShape=e;var c,p="float("+n+") + float("+r+") * sum";c=.5===i?"inversesqrt("+p+")":1===i?"1.0/("+p+")":"exp(log("+p+") * float(-"+i+"));",this.userCode="withinChannel"===a?"\n        void main() {\n          ivec4 coords = getOutputCoords();\n          int b = coords[0];\n          int r = coords[1];\n          int c = coords[2];\n          int d = coords[3];\n          float x = getX(b, r, c, d);\n          float sum = 0.0;\n          for (int u = -"+o+"; u <= "+o+"; u++) {\n            for (int v = -"+o+"; v <= "+o+"; v++) {\n              int idx = r + u;\n              int idy = c + v;\n              if (idx >= 0 && idx <= "+s+" && idy >= 0 && idy <= "+u+") {\n                float z = getX(b, idx, idy, d);\n                sum += z * z;\n              }\n            }\n          }\n          float val = x * "+c+";\n          setOutput(val);\n        }\n      ":"\n        void main() {\n          ivec4 coords = getOutputCoords();\n          int b = coords[0];\n          int r = coords[1];\n          int c = coords[2];\n          int d = coords[3];\n          float x = getX(b, r, c, d);\n          float sum = 0.0;\n          for (int j = -"+o+"; j <= "+o+"; j++) {\n            int idx = d + j;\n            if (idx >= 0 && idx <=  "+l+") {\n              float z = getX(b, r, c, idx);\n              sum += z * z;\n            }\n          }\n          float val = x * "+c+";\n          setOutput(val);\n        }\n      "}}();n.LRNProgram=r},{}],28:[function(e,t,n){"use strict";Object.defineProperty(n,"__esModule",{value:!0});var r=function(){return function(e){this.variableNames=["dy","maxPos"],this.outputShape=e.inShape;var t=e.filterHeight,n=e.filterWidth,r=e.strideHeight,i=e.strideWidth,a=t-1-e.padInfo.top,o=n-1-e.padInfo.left,s=t*n-1;this.userCode="\n      const ivec2 pads = ivec2("+a+", "+o+");\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n\n        ivec2 dyRCCorner = coords.yz - pads;\n        int dyRCorner = dyRCCorner.x;\n        int dyCCorner = dyRCCorner.y;\n\n        // Convolve dy(?, ?, d) with pos mask(:, :, d) to get dx(xR, xC, d).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n        for (int wR = 0; wR < "+t+"; wR++) {\n          float dyR = float(dyRCorner + wR) / "+r+".0;\n\n          if (dyR < 0.0 || dyR >= "+e.outHeight+".0 || fract(dyR) > 0.0) {\n            continue;\n          }\n          int idyR = int(dyR);\n\n          for (int wC = 0; wC < "+n+"; wC++) {\n            float dyC = float(dyCCorner + wC) / "+i+".0;\n\n            if (dyC < 0.0 || dyC >= "+e.outWidth+".0 ||\n                fract(dyC) > 0.0) {\n              continue;\n            }\n            int idyC = int(dyC);\n\n            float dyValue = getDy(b, idyR, idyC, d);\n            int maxPosValue = "+s+" - int(getMaxPos(b, idyR, idyC, d));\n\n            // Get the current value, check it against the value from the\n            // position matrix.\n            int curPosValue = wR * "+n+" + wC;\n            float mask = float(maxPosValue == curPosValue ? 1.0 : 0.0);\n\n            dotProd += dyValue * mask;\n          }\n        }\n        setOutput(dotProd);\n      }\n    "}}();n.MaxPool2DBackpropProgram=r},{}],29:[function(e,t,n){"use strict";Object.defineProperty(n,"__esModule",{value:!0});var r=function(){return function(e,t,n,r){void 0===n&&(n=!1),void 0===r&&(r=!1),this.variableNames=["matrixA","matrixB"];var i=n?e[1]:e[0],a=r?t[0]:t[1],o=n?e[0]:e[1];this.outputShape=[i,a];var s=function(e,t){return n?t+" + "+e+", aRow":"aRow, "+t+" + "+e},u=function(e,t){return r?"bCol, "+t+" + "+e:t+" + "+e+", bCol"},l=4*Math.floor(o/4),c=o%4;this.userCode=" float dotARowBCol(int aRow, int bCol) {\n      float result = 0.0;\n      for (int i = 0; i < "+l+"; i += 4) {\n        vec4 a = vec4(\n          getMatrixA("+s(0,"i")+"),\n          getMatrixA("+s(1,"i")+"),\n          getMatrixA("+s(2,"i")+"),\n          getMatrixA("+s(3,"i")+")\n        );\n        vec4 b = vec4(\n          getMatrixB("+u(0,"i")+"),\n          getMatrixB("+u(1,"i")+"),\n          getMatrixB("+u(2,"i")+"),\n          getMatrixB("+u(3,"i")+")\n        );\n\n        result += dot(a, b);\n      }\n\n      if ("+(1===c)+") {\n        result += getMatrixA("+s(0,l)+") *\n          getMatrixB("+u(0,l)+");\n      } else if ("+(2===c)+") {\n        vec2 a = vec2(\n          getMatrixA("+s(0,l)+"),\n          getMatrixA("+s(1,l)+")\n        );\n        vec2 b = vec2(\n          getMatrixB("+u(0,l)+"),\n          getMatrixB("+u(1,l)+")\n        );\n        result += dot(a, b);\n      } else if ("+(3===c)+") {\n        vec3 a = vec3(\n          getMatrixA("+s(0,l)+"),\n          getMatrixA("+s(1,l)+"),\n          getMatrixA("+s(2,l)+")\n        );\n        vec3 b = vec3(\n          getMatrixB("+u(0,l)+"),\n          getMatrixB("+u(1,l)+"),\n          getMatrixB("+u(2,l)+")\n        );\n        result += dot(a, b);\n      }\n\n      return result;\n    }\n\n    void main() {\n      ivec2 resRC = getOutputCoords();\n      setOutput(dotARowBCol(resRC.x, resRC.y));\n    }\n    "}}();n.MatMulProgram=r},{}],30:[function(e,t,n){"use strict";Object.defineProperty(n,"__esModule",{value:!0});var r=function(){function e(e,t,n){this.variableNames=["probs"],this.outputShape=[e,n],this.userCode="\n      uniform float seed;\n\n      void main() {\n        ivec2 coords = getOutputCoords();\n        int batch = coords[0];\n\n        float r = random(seed);\n        float cdf = 0.0;\n\n        for (int i = 0; i < "+(t-1)+"; i++) {\n          cdf += getProbs(batch, i);\n\n          if (r < cdf) {\n            setOutput(float(i));\n            return;\n          }\n        }\n\n        // If no other event happened, last event happened.\n        setOutput(float("+(t-1)+"));\n      }\n    "}return e.prototype.getCustomSetupFunc=function(e){var t=this;return function(n,r){null==t.seedLoc&&(t.seedLoc=n.getUniformLocation(r,"seed")),n.gl.uniform1f(t.seedLoc,e)}},e}();n.MultinomialProgram=r},{}],31:[function(e,t,n){"use strict";Object.defineProperty(n,"__esModule",{value:!0});var r=function(){return function(e,t,n,r){this.variableNames=["indices"],this.outputShape=[e,t],this.userCode="\n      void main() {\n        ivec2 coords = getOutputCoords();\n        int index = round(getIndices(coords.x));\n        setOutput(mix(float("+r+"), float("+n+"),\n                      float(index == coords.y)));\n      }\n    "}}();n.OneHotProgram=r},{}],32:[function(e,t,n){"use strict";Object.defineProperty(n,"__esModule",{value:!0});var r=e("./shader_compiler"),i=function(){return function(e,t,n){this.variableNames=["x"],this.outputShape=t.map(function(t,n){return t[0]+e[n]+t[1]});var i=e.length,a=r.getCoordsDataType(i),o=t.map(function(e){return e[0]}).join(","),s=t.map(function(t,n){return t[0]+e[n]}).join(","),u=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,i);this.userCode=1!==i?"\n      "+a+" start = "+a+"("+o+");\n      "+a+" end = "+a+"("+s+");\n\n      void main() {\n        "+a+" outC = getOutputCoords();\n        if (any(lessThan(outC, start)) || any(greaterThanEqual(outC, end))) {\n          setOutput(float("+n+"));\n        } else {\n          "+a+" coords = outC - start;\n          setOutput(getX("+u+"));\n        }\n      }\n    ":"\n        int start = "+o+";\n        int end = "+s+";\n\n        void main() {\n          int outC = getOutputCoords();\n          if (outC < start || outC >= end) {\n            setOutput(float("+n+"));\n          } else {\n            setOutput(getX(outC - start));\n          }\n        }\n      "}}();n.PadProgram=i},{"./shader_compiler":37}],33:[function(e,t,n){"use strict";Object.defineProperty(n,"__esModule",{value:!0});var r=function(){return function(e,t,n){if(this.variableNames=["x"],"avg"===t&&n)throw new Error("Cannot compute positions for average pool.");var r=e.filterHeight,i=e.filterWidth,a=e.strideHeight,o=e.strideWidth,s=e.padInfo.top,u=e.padInfo.left;this.outputShape=e.outShape;var l="avg"===t,c="0.0";if(l||(c="min"===t?"1.0 / 0.0":"-1.0 / 0.0"),n){var p="min"===t?"<=":">=";this.userCode="\n        const ivec2 strides = ivec2("+a+", "+o+");\n        const ivec2 pads = ivec2("+s+", "+u+");\n\n        void main() {\n          ivec4 coords = getOutputCoords();\n          int batch = coords[0];\n          int d = coords[3];\n\n          ivec2 xRCCorner = coords.yz * strides - pads;\n          int xRCorner = xRCCorner.x;\n          int xCCorner = xRCCorner.y;\n\n          // max/min x(?, ?, d) to get y(yR, yC, d).\n          // ? = to be determined\n          float minMaxValue = 0.0;\n          float minMaxValueFound = 0.0;\n          int minMaxPosition = 0;\n          float avgValue = 0.0;\n\n          for (int wR = 0; wR < "+r+"; wR++) {\n            int xR = xRCorner + wR;\n\n            if (xR < 0 || xR >= "+e.inHeight+") {\n              continue;\n            }\n\n            for (int wC = 0; wC < "+i+"; wC++) {\n              int xC = xCCorner + wC;\n\n              if (xC < 0 || xC >= "+e.inWidth+") {\n                continue;\n              }\n\n              float value = getX(batch, xR, xC, d);\n\n              if (isNaN(value)) {\n                setOutput(value);\n                return;\n              }\n\n              // If a min / max value has already been found, use it. If not,\n              // use the current value.\n              float currMinMaxValue = mix(\n                  value, minMaxValue, minMaxValueFound);\n              if (value "+p+" currMinMaxValue) {\n                minMaxValue = value;\n                minMaxValueFound = 1.0;\n                minMaxPosition = wR * "+i+" + wC;\n              }\n            }\n          }\n          setOutput(float(minMaxPosition));\n        }\n      "}else{var h="min"===t?"min":"max",d=t+"("+t+"("+t+"(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])";"avg"===t&&(d="avgValue / "+r*i+".0");var f=4*Math.floor(i/4),g=i%4,m="\n      if (hasNaN(values)) {\n        setOutput(getNaN(values));\n        return;\n      }\n      if ("+l+") {\n        avgValue += dot(values, ones);\n      } else {\n        minMaxValue = "+h+"(values, minMaxValue);\n      }\n    ";this.userCode="\n      const ivec2 strides = ivec2("+a+", "+o+");\n      const ivec2 pads = ivec2("+s+", "+u+");\n      const float initializationValue = "+c+";\n      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);\n\n      float getValue(int batch, int xR, int xC, int d) {\n        if (xC < 0 || xC >= "+e.inWidth+") {\n          return initializationValue;\n        }\n        return getX(batch, xR, xC, d);\n      }\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int batch = coords[0];\n        int d = coords[3];\n\n        ivec2 xRCCorner = coords.yz * strides - pads;\n        int xRCorner = xRCCorner.x;\n        int xCCorner = xRCCorner.y;\n\n        // max/min x(?, ?, d) to get y(yR, yC, d).\n        // ? = to be determined\n        vec4 minMaxValue = vec4("+c+");\n        float avgValue = 0.0;\n\n        for (int wR = 0; wR < "+r+"; wR++) {\n          int xR = xRCorner + wR;\n\n          if (xR < 0 || xR >= "+e.inHeight+") {\n            continue;\n          }\n\n          for (int wC = 0; wC < "+f+"; wC += 4) {\n            int xC = xCCorner + wC;\n\n            vec4 values = vec4(\n              getValue(batch, xR, xC, d),\n              getValue(batch, xR, xC + 1, d),\n              getValue(batch, xR, xC + 2, d),\n              getValue(batch, xR, xC + 3, d)\n            );\n\n            "+m+"\n          }\n\n          int xC = xCCorner + "+f+";\n          if ("+(1===g)+") {\n            vec4 values = vec4(\n              getValue(batch, xR, xC, d),\n              initializationValue,\n              initializationValue,\n              initializationValue\n            );\n            "+m+"\n          } else if ("+(2===g)+") {\n            vec4 values = vec4(\n              getValue(batch, xR, xC, d),\n              getValue(batch, xR, xC + 1, d),\n              initializationValue,\n              initializationValue\n            );\n\n            "+m+"\n          } else if ("+(3===g)+") {\n            vec4 values = vec4(\n              getValue(batch, xR, xC, d),\n              getValue(batch, xR, xC + 1, d),\n              getValue(batch, xR, xC + 2, d),\n              initializationValue\n            );\n\n            "+m+"\n          }\n        }\n        setOutput("+d+");\n      }\n    "}}}();n.Pool2DProgram=r},{}],34:[function(e,t,n){"use strict";Object.defineProperty(n,"__esModule",{value:!0});var r=function(){return function(e,t){this.variableNames=["x"];var n=e.windowSize,r=e.batchSize,i=e.inSize,a=Math.ceil(i/n);this.outputShape=[r,a];var o="sum"===t,s="0.0";o||(s="min"===t?"1.0 / 0.0":"-1.0 / 0.0");var u="min"===t?"min":"max",l=t+"("+t+"("+t+"(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])";"sum"===t&&(l="sumValue");var c=4*Math.floor(n/4),p=n%4,h="\n      if ("+o+") {\n        sumValue += dot(values, ones);\n      } else {\n        if (hasNaN(values)) {\n          setOutput(getNaN(values));\n          return;\n        }\n        minMaxValue = "+u+"(values, minMaxValue);\n      }\n    ",d="";i%n>0&&(d="\n        if (inIdx < 0 || inIdx >= "+i+") {\n          return initializationValue;\n        }\n      "),this.userCode="\n      const float initializationValue = "+s+";\n      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);\n\n      float getValue(int batch, int inIdx) {\n        "+d+"\n        return getX(batch, inIdx);\n      }\n\n      void main() {\n        ivec2 coords = getOutputCoords();\n        int batch = coords[0];\n        int outIdx = coords[1];\n        int inOffset = outIdx * "+n+";\n\n        vec4 minMaxValue = vec4("+s+");\n        float sumValue = 0.0;\n\n        for (int i = 0; i < "+c+"; i += 4) {\n          int inIdx = inOffset + i;\n          vec4 values = vec4(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1),\n            getValue(batch, inIdx + 2),\n            getValue(batch, inIdx + 3)\n          );\n\n          "+h+"\n        }\n\n        int inIdx = inOffset + "+c+";\n        if ("+(1===p)+") {\n          vec4 values = vec4(\n            getValue(batch, inIdx),\n            initializationValue,\n            initializationValue,\n            initializationValue\n          );\n          "+h+"\n        } else if ("+(2===p)+") {\n          vec4 values = vec4(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1),\n            initializationValue,\n            initializationValue\n          );\n          "+h+"\n        } else if ("+(3===p)+") {\n          vec4 values = vec4(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1),\n            getValue(batch, inIdx + 2),\n            initializationValue\n          );\n          "+h+"\n        }\n        setOutput("+l+");\n      }\n    "}}();n.ReduceProgram=r},{}],35:[function(e,t,n){"use strict";Object.defineProperty(n,"__esModule",{value:!0});var r=function(){return function(e,t,n,r){this.variableNames=["A"],this.outputShape=[];var i=e[0],a=e[1],o=e[2],s=e[3];this.outputShape=[i,t,n,s];var u=r?[a-1,o-1]:[a,o],l=r?[t-1,n-1]:[t,n];this.userCode="\n      const vec2 effectiveInputOverOutputRatioRC = vec2(\n          "+u[0]/l[0]+",\n          "+u[1]/l[1]+");\n      const vec2 inputShapeRC = vec2("+a+".0, "+o+".0);\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n        ivec2 yRC = coords.yz;\n\n        // Fractional source index.\n        vec2 sourceFracIndexRC = vec2(yRC) * effectiveInputOverOutputRatioRC;\n\n        // Compute the four integer indices.\n        ivec2 sourceFloorRC = ivec2(sourceFracIndexRC);\n        ivec2 sourceCeilRC = ivec2(\n          min(inputShapeRC - 1.0, ceil(sourceFracIndexRC)));\n\n        float topLeft = getA(b, sourceFloorRC.x, sourceFloorRC.y, d);\n        float bottomLeft = getA(b, sourceCeilRC.x, sourceFloorRC.y, d);\n        float topRight = getA(b, sourceFloorRC.x, sourceCeilRC.y, d);\n        float bottomRight = getA(b, sourceCeilRC.x, sourceCeilRC.y, d);\n\n        vec2 fracRC = sourceFracIndexRC - vec2(sourceFloorRC);\n\n        float top = topLeft + (topRight - topLeft) * fracRC.y;\n        float bottom = bottomLeft + (bottomRight - bottomLeft) * fracRC.y;\n        float newValue = top + (bottom - top) * fracRC.x;\n\n        setOutput(newValue);\n      }\n    "}}();n.ResizeBilinearProgram=r},{}],36:[function(e,t,n){"use strict";Object.defineProperty(n,"__esModule",{value:!0});var r=e("./shader_compiler"),i=function(){return function(e,t){this.variableNames=["x"];var n=e.length;if(n>4)throw new Error("WebGL backend: Reverse of rank-"+n+" tensor is not yet supported");if(this.outputShape=e,1!==n){var i=function(n){return-1!==t.indexOf(n)&&1!==e[n]?e[n]+" - coords["+n+"] - 1":"coords["+n+"]"},a=e.map(function(e,t){return i(t)}).join(","),o=r.getCoordsDataType(n);this.userCode="\n      void main() {\n        "+o+" coords = getOutputCoords();\n        setOutput(getX("+a+"));\n      }\n    "}else this.userCode="\n        void main() {\n          int coord = getOutputCoords();\n          setOutput(getX("+e[0]+" - coord - 1));\n        }\n      "}}();n.ReverseProgram=i},{"./shader_compiler":37}],37:[function(e,t,n){"use strict";function r(){return E.ENV.get("WEBGL_FLOAT_TEXTURE_ENABLED")?k:O}function i(){return E.ENV.get("WEBGL_FLOAT_TEXTURE_ENABLED")?C:T}function a(e){var t=e.shapeInfo.logicalShape;switch(t.length){case 0:return h(e);case 1:return d(e);case 2:return f(e);case 3:return g(e);case 4:return m(e);default:throw new Error(t.length+"-D input sampling is not yet supported")}}function o(e,t,n){var r=v(e);return r+=a(e),(n||_.arraysEqual(e.shapeInfo.logicalShape,t.logicalShape))&&(r+=b(e,t,n)),r}function s(e,t){switch(e.length){case 0:return"\n    int getOutputCoords() {\n      return 0;\n    }\n  ";case 1:return u(e,t);case 2:return p(e,t);case 3:return l(e,t);case 4:return c(e,t);default:throw new Error(e.length+"-D output sampling is not yet supported")}}function u(e,t){return 1===t[0]?"\n      int getOutputCoords() {\n        return int(resultUV.x * "+t[1]+".0);\n      }\n    ":1===t[1]?"\n      int getOutputCoords() {\n        return int(resultUV.y * "+t[0]+".0);\n      }\n    ":"\n    int getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2("+t[0]+", "+t[1]+"));\n      return resTexRC.x * "+t[1]+" + resTexRC.y;\n    }\n  "}function l(e,t){var n=e[1]*e[2],r=e[2];return"\n    ivec3 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2("+t[0]+", "+t[1]+"));\n      int index = resTexRC.x * "+t[1]+" + resTexRC.y;\n      int r = index / "+n+";\n      index -= r * "+n+";\n      int c = index / "+r+";\n      int d = index - c * "+r+";\n      return ivec3(r, c, d);\n    }\n  "}function c(e,t){var n=e[3],r=e[2]*n,i=e[1]*r;return"\n    ivec4 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n        vec2("+t[0]+", "+t[1]+"));\n      int index = resTexRC.x * "+t[1]+" + resTexRC.y;\n\n      int r = index / "+i+";\n      index -= r * "+i+";\n\n      int c = index / "+r+";\n      index -= c * "+r+";\n\n      int d = index / "+n+";\n      int d2 = index - d * "+n+";\n\n      return ivec4(r, c, d, d2);\n    }\n  "}function p(e,t){return _.arraysEqual(e,t)?"\n      ivec2 getOutputCoords() {\n        return ivec2(resultUV.yx * vec2("+t[0]+", "+t[1]+"));\n      }\n    ":1===e[1]?"\n      ivec2 getOutputCoords() {\n        ivec2 resTexRC = ivec2(resultUV.yx *\n                               vec2("+t[0]+", "+t[1]+"));\n        int index = resTexRC.x * "+t[1]+" + resTexRC.y;\n        return ivec2(index, 0);\n      }\n    ":1===e[0]?"\n      ivec2 getOutputCoords() {\n        ivec2 resTexRC = ivec2(resultUV.yx *\n                               vec2("+t[0]+", "+t[1]+"));\n        int index = resTexRC.x * "+t[1]+" + resTexRC.y;\n        return ivec2(0, index);\n      }\n    ":"\n    ivec2 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2("+t[0]+", "+t[1]+"));\n      int index = resTexRC.x * "+t[1]+" + resTexRC.y;\n      int r = index / "+e[1]+";\n      int c = index - r * "+e[1]+";\n      return ivec2(r, c);\n    }\n  "}function h(e){var t=e.name;return"\n    float "+("get"+t.charAt(0).toUpperCase()+t.slice(1))+"() {\n      return sampleTexture("+t+", halfCR);\n    }\n  "}function d(e){var t=e.name,n="get"+t.charAt(0).toUpperCase()+t.slice(1);return"\n    float "+n+"(int index) {\n      return "+n+"Flat(index);\n    }\n  "}function f(e){var t=e.shapeInfo.logicalShape,n=e.shapeInfo.texShape,r=e.name,i="get"+r.charAt(0).toUpperCase()+r.slice(1),o=n[0],s=n[1];if(_.arraysEqual(t,n))return"\n    float "+i+"(int row, int col) {\n      vec2 uv = (vec2(col, row) + halfCR) / vec2("+s+".0, "+o+".0);\n      return sampleTexture("+r+", uv);\n    }\n  ";var u=_.squeezeShape(t),l=u.newShape,c=u.keptDims,p=l;if(p.length<t.length){var h=["row","col"];return"\n      "+a(w(e,p))+"\n      float "+i+"(int row, int col) {\n        return "+i+"("+x(h,c)+");\n      }\n    "}return 1===s?"\n    float "+i+"(int row, int col) {\n      int index = row * "+t[1]+" + col;\n      vec2 uv = vec2(0.5, (float(index) + 0.5) / "+o+".0);\n      return sampleTexture("+r+", uv);\n    }\n  ":1===o?"\n    float "+i+"(int row, int col) {\n      int index = row * "+t[1]+" + col;\n      vec2 uv = vec2((float(index) + 0.5) / "+s+".0, 0.5);\n      return sampleTexture("+r+", uv);\n    }\n  ":"\n  float "+i+"(int row, int col) {\n    vec2 uv = UVfrom2D("+o+", "+s+", "+t[1]+", row, col);\n    return sampleTexture("+r+", uv);\n  }\n"}function g(e){var t=e.shapeInfo.texShape,n=e.shapeInfo.logicalShape,r=e.name,i="get"+r.charAt(0).toUpperCase()+r.slice(1),o=t[0],s=t[1],u=n[1]*n[2],l=n[2],c=_.squeezeShape(n),p=c.newShape,h=c.keptDims,d=p;if(d.length<n.length){var f=["row","col","depth"];return"\n        "+a(w(e,d))+"\n        float "+i+"(int row, int col, int depth) {\n          return "+i+"("+x(f,h)+");\n        }\n      "}return s===u?"\n        float "+i+"(int row, int col, int depth) {\n          int texR = row;\n          int texC = col * "+l+" + depth;\n          vec2 uv = (vec2(texC, texR) + halfCR) /\n                     vec2("+s+".0, "+o+".0);\n          return sampleTexture("+r+", uv);\n        }\n      ":s===l?"\n    float "+i+"(int row, int col, int depth) {\n      int texR = row * "+n[1]+" + col;\n      int texC = depth;\n      vec2 uv = (vec2(texC, texR) + halfCR) / vec2("+s+".0, "+o+".0);\n      return sampleTexture("+r+", uv);\n    }\n  ":"\n      float "+i+"(int row, int col, int depth) {\n        vec2 uv = UVfrom3D(\n            "+o+", "+s+", "+u+", "+l+", row, col, depth);\n        return sampleTexture("+r+", uv);\n      }\n  "}function m(e){var t=e.shapeInfo.logicalShape,n=e.shapeInfo.texShape,r=e.name,i="get"+r.charAt(0).toUpperCase()+r.slice(1),o=n[0],s=n[1],u=t[3],l=t[2]*u,c=t[1]*l,p=_.squeezeShape(t),h=p.newShape,d=p.keptDims;if(h.length<t.length){var f=["row","col","depth","depth2"];return"\n      "+a(w(e,h))+"\n      float "+i+"(int row, int col, int depth, int depth2) {\n        return "+i+"("+x(f,d)+");\n      }\n    "}return s===c?"\n      float "+i+"(int row, int col, int depth, int depth2) {\n        int texR = row;\n        int texC = col * "+l+" + depth * "+u+" + depth2;\n        vec2 uv = (vec2(texC, texR) + halfCR) /\n                   vec2("+s+".0, "+o+".0);\n        return sampleTexture("+r+", uv);\n      }\n    ":s===u?"\n      float "+i+"(int row, int col, int depth, int depth2) {\n        int texR = row * "+t[1]*t[2]+" + col * "+t[2]+" + depth;\n        int texC = depth2;\n        vec2 uv = (vec2(texC, texR) + halfCR) /\n                  vec2("+s+".0, "+o+".0);\n        return sampleTexture("+r+", uv);\n      }\n    ":"\n    float "+i+"(int row, int col, int depth, int depth2) {\n      vec2 uv = UVfrom4D("+o+", "+s+", "+c+", "+l+",\n          "+u+", row, col, depth, depth2);\n      return sampleTexture("+r+", uv);\n    }\n  "}function v(e){var t=e.name,n=e.shapeInfo.texShape,r="get"+t.charAt(0).toUpperCase()+t.slice(1)+"Flat",i=n[0],a=n[1];return 1===a&&1===i?"\n      float "+r+"(int index) {\n        return sampleTexture("+t+", halfCR);\n      }\n    ":1===a?"\n      float "+r+"(int index) {\n        vec2 uv = vec2(0.5, (float(index) + 0.5) / "+i+".0);\n        return sampleTexture("+t+", uv);\n      }\n    ":1===i?"\n      float "+r+"(int index) {\n        vec2 uv = vec2((float(index) + 0.5) / "+a+".0, 0.5);\n        return sampleTexture("+t+", uv);\n      }\n    ":"\n    float "+r+"(int index) {\n      vec2 uv = UVfrom1D("+i+", "+a+", index);\n      return sampleTexture("+t+", uv);\n    }\n  "}function y(e,t,n,r){var i=e.shapeInfo.logicalShape.length,a=t.logicalShape.length,o="int";2===a?o="ivec2":3===a?o="ivec3":4===a&&(o="ivec4");var s,u=A.getBroadcastDims(e.shapeInfo.logicalShape,t.logicalShape),l=a-i;s=0===i?"":a<2&&u.length>=1?"coords = 0;":u.map(function(e){return"coords["+(e+l)+"] = 0;"}).join("\n");var c="";return c=a<2&&i>0?"coords":e.shapeInfo.logicalShape.map(function(e,t){return"coords["+(t+l)+"]"}).join(", "),"\n    float "+r+"() {\n      "+o+" coords = getOutputCoords();\n      "+s+"\n      return get"+n+"("+c+");\n    }\n  "}function b(e,t,n){var r=e.shapeInfo.texShape,i=e.name,a=i.charAt(0).toUpperCase()+i.slice(1),o="get"+a+"AtOutCoords",s=A.getBroadcastDims(e.shapeInfo.logicalShape,t.logicalShape),u=e.shapeInfo.logicalShape.length,l=t.logicalShape.length,c=n&&(l>u||s.length>0),p=A.broadcastDimsAreOuter(s);if(c&&!p)return y(e,t,a,o);var h=t.texShape;if(_.arraysEqual(r,h))return"\n      float "+o+"() {\n        return sampleTexture("+i+", resultUV);\n      }\n    ";var d=_.sizeFromShape(r),f="";return c&&p&&(f="\n        int mainPart = index / "+d+";\n        index -= mainPart * "+d+";\n      "),"\n    float "+o+"() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2("+h[0]+", "+h[1]+"));\n      int index = resTexRC.x * "+h[1]+" + resTexRC.y;\n      "+f+"\n      int texR = index / "+r[1]+";\n      int texC = index - texR * "+r[1]+";\n      vec2 uv = (vec2(texC, texR) + halfCR) /\n                 vec2("+r[1]+".0, "+r[0]+".0);\n\n      return sampleTexture("+i+", uv);\n    }\n  "}function w(e,t){var n=JSON.parse(JSON.stringify(e));return n.shapeInfo.logicalShape=t,n}function x(e,t){return t.map(function(t){return e[t]}).join(", ")}Object.defineProperty(n,"__esModule",{value:!0});var E=e("../../environment"),_=e("../../util"),A=e("../../ops/broadcast_util"),S=e("./tex_util");n.makeShader=function(e,t,n,a){var u=r(),l=i(),c=e.map(function(e){return"uniform sampler2D "+e.name+";"}).join("\n"),p=e.map(function(e){return o(e,t,a)}).join("\n"),h=t.texShape,d=s(t.logicalShape,h);return[N,u,l,c,d,p,n].join("\n")};var O="\n  uniform float NaN;\n\n  const vec4 floatDeltas = vec4(\n      1.0,\n      1.0 / 255.0,\n      1.0 / (255.0 * 255.0),\n      1.0 / (255.0 * 255.0 * 255.0)\n  );\n  const float minValue = "+S.FLOAT_MIN+".0;\n  const float maxValue = "+S.FLOAT_MAX+".0;\n  const float range = (maxValue - minValue) / 255.0;\n  const vec2 dotRange = vec2(1.0, range);\n\n  float sampleTexture(sampler2D textureSampler, vec2 uv) {\n    vec4 sampleValue = texture2D(textureSampler, uv);\n    if (all(equal(sampleValue, vec4("+S.BYTE_NAN_VALUE+")))) {\n      return NaN;\n    }\n\n    vec4 encValue = floor(sampleValue * 255.0 + 0.5);\n    float decodedValue = dot(encValue, floatDeltas);\n    return dot(vec2(minValue, decodedValue), dotRange);\n  }\n",T="\n  const vec4 floatPowers = vec4(\n    1.0,\n    255.0,\n    255.0 * 255.0,\n    255.0 * 255.0 * 255.0\n  );\n  const vec2 recipRange = vec2(1.0/range);\n  const vec2 recipRange255 = vec2(1.0/(maxValue - minValue));\n\n  void setOutput(float decodedValue) {\n    if (isNaN(decodedValue)) {\n      gl_FragColor = vec4("+S.BYTE_NAN_VALUE+");\n      return;\n    }\n\n    float a = dot(vec2(decodedValue, -minValue), recipRange);\n    float b = fract(a) * 255.0;\n    float c = fract(b) * 255.0;\n    float d = fract(c) * 255.0;\n    gl_FragColor = floor(vec4(a, b, c, d)) / 255.0;\n\n    // TODO(dsmilkov): Version above gets better accuracy but probably slower\n    // than the version below. Benchmark to determine if the accuracy is worth\n    // the cost.\n\n    // float normValue = dot(vec2(decodedValue, -minValue), recipRange255);\n    // vec4 f = normValue * floatPowers;\n    // gl_FragColor = floor(fract(f) * 255.0) / 255.0;\n  }\n",k="\n  float sampleTexture(sampler2D textureSampler, vec2 uv) {\n    return texture2D(textureSampler, uv).r;\n  }\n",C="\n  void setOutput(float val) {\n    gl_FragColor = vec4(val, 0, 0, 0);\n  }\n",N="\n  precision highp float;\n  precision highp int;\n  varying vec2 resultUV;\n  const vec2 halfCR = vec2(0.5, 0.5);\n\n  bool isNaN(float val) {\n    float v1 = val * val;\n    float v2 = val * val;\n    return v1 == v2 ? false : true;\n  }\n\n  bool hasNaN(vec4 values) {\n    vec4 v1 = values * values;\n    vec4 v2 = values * values;\n    return any(notEqual(v1, v2));\n  }\n\n  float getNaN(vec4 values) {\n    return dot(vec4(1), values);\n  }\n\n  int round(float value) {\n    return int(floor(value + 0.5));\n  }\n\n  int imod(int x, int y) {\n    return x - y * (x / y);\n  }\n\n  const vec2 randomConst = vec2(\n    23.14069263277926, // e^pi (Gelfond's constant)\n     2.665144142690225 // 2^sqrt(2) (Gelfond–Schneider constant)\n  );\n\n  float random(float seed) {\n      return fract(cos(dot(resultUV * seed, randomConst)) * 12345.6789);\n  }\n\n  \nvec2 UVfrom1D(int texNumR, int texNumC, int index) {\n  int texR = index / texNumC;\n  int texC = index - texR * texNumC;\n  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);\n}\n\n  \nvec2 UVfrom2D(int texNumR, int texNumC, int numC, int row, int col) {\n  int index = row * numC + col;\n  int texR = index / texNumC;\n  int texC = index - texR * texNumC;\n  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);\n}\n\n  \nvec2 UVfrom3D(int texNumR, int texNumC, int stride0,\n    int stride1, int row, int col, int depth) {\n  // Explicitly use integer operations as dot() only works on floats.\n  int index = row * stride0 + col * stride1 + depth;\n  int texR = index / texNumC;\n  int texC = index - texR * texNumC;\n  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);\n}\n\n  \nvec2 UVfrom4D(int texNumR, int texNumC, int stride0,\n    int stride1, int stride2, int row, int col, int depth,\n    int depth2) {\n  // Explicitly use integer operations as dot() only works on floats.\n  int index = row * stride0 + col * stride1 + depth * stride2 + depth2;\n  int texR = index / texNumC;\n  int texC = index - texR * texNumC;\n  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);\n}\n\n";n.getCoordsDataType=function(e){if(e<=1)return"int";if(2===e)return"ivec2";if(3===e)return"ivec3";if(4===e)return"ivec4";throw Error("GPU for rank "+e+" is not yet supported")}},{"../../environment":5,"../../ops/broadcast_util":49,"../../util":92,"./tex_util":39}],38:[function(e,t,n){"use strict";function r(e){if(1===e)return"sourceLoc";if(2===e)return"sourceLoc.x, sourceLoc.y";if(3===e)return"sourceLoc.x, sourceLoc.y, sourceLoc.z";if(4===e)return"sourceLoc.x, sourceLoc.y, sourceLoc.z, sourceLoc.w";throw Error("Slicing for rank "+e+" is not yet supported")}Object.defineProperty(n,"__esModule",{value:!0});var i=e("./shader_compiler"),a=function(){function e(e){this.variableNames=["source"],this.outputShape=e,this.rank=e.length;var t=i.getCoordsDataType(this.rank),n=r(this.rank);this.userCode="\n      uniform "+t+" start;\n\n      void main() {\n        "+t+" sourceLoc = start + getOutputCoords();\n        setOutput(getSource("+n+"));\n      }\n    "}return e.prototype.getCustomSetupFunc=function(e){var t=this;if(e.length!==this.rank)throw Error("The rank ("+this.rank+") of the program must match the length of start ("+e.length+")");return function(n,r){if(null!=t.startLoc||(t.startLoc=n.getUniformLocationNoThrow(r,"start"),null!=t.startLoc))if(1===t.rank)n.gl.uniform1i(t.startLoc,e[0]);else if(2===t.rank)n.gl.uniform2i(t.startLoc,e[0],e[1]);else if(3===t.rank)n.gl.uniform3i(t.startLoc,e[0],e[1],e[2]);else{if(4!==t.rank)throw Error("Slicing for rank "+t.rank+" is not yet supported");n.gl.uniform4i(t.startLoc,e[0],e[1],e[2],e[3])}}},e}();n.SliceProgram=a},{"./shader_compiler":37}],39:[function(e,t,n){"use strict";function r(e,t){return e*t}function i(e,t){if(e%t!=0)throw new Error("unpackedSize ("+e+") must be a multiple of "+t);return e/t}function a(e,t){return[Math.ceil(t/2),Math.ceil(e/2)]}function o(e,t){var n=a(e,t);return n[0]*n[1]*4}Object.defineProperty(n,"__esModule",{value:!0});!function(e){e[e.FLOAT=0]="FLOAT",e[e.UNSIGNED_BYTE=1]="UNSIGNED_BYTE"}(n.TextureType||(n.TextureType={})),n.getUnpackedMatrixTextureShapeWidthHeight=function(e,t){return[t,e]},n.getUnpackedArraySizeFromMatrixSize=r,n.getColorMatrixTextureShapeWidthHeight=function(e,t){return[4*t,e]},n.getMatrixSizeFromUnpackedArraySize=i,n.encodeMatrixToUnpackedArray=function(e,t,n){var i=r(e.length,n);if(t.length<i)throw new Error("unpackedArray length ("+t.length+") must be >= "+i);for(var a=0,o=0;o<e.length;++o)t[a]=e[o],a+=n},n.FLOAT_MAX=2e4,n.FLOAT_MIN=-n.FLOAT_MAX;var s=(n.FLOAT_MAX-n.FLOAT_MIN)/255,u=[1,1/255,1/65025,1/16581375],l=[1,255,65025];n.BYTE_NAN_VALUE=0,n.encodeFloatArray=function(e){for(var t=new Uint8Array(4*e.length),r=0;r<t.length;r+=4)!function(r){var i=e[r/4];if(isNaN(i))return t[r]=n.BYTE_NAN_VALUE,t[r+1]=n.BYTE_NAN_VALUE,t[r+2]=n.BYTE_NAN_VALUE,t[r+3]=n.BYTE_NAN_VALUE,"continue";var a=(i-n.FLOAT_MIN)/s,o=l.map(function(e){return e*a}).map(function(e){return Math.floor(e%1*255)});t[r]=Math.floor(a),t[r+1]=o[0],t[r+2]=o[1],t[r+3]=o[2]}(r);return t},n.decodeToFloatArray=function(e){for(var t=new Float32Array(e.length/4),r=0;r<e.length;r+=4)!function(r){if(e[r]===n.BYTE_NAN_VALUE&&e[r+1]===n.BYTE_NAN_VALUE&&e[r+2]===n.BYTE_NAN_VALUE&&e[r+3]===n.BYTE_NAN_VALUE)return t[r/4]=NaN,"continue";var i=0;u.forEach(function(t,n){i+=t*e[r+n]});var a=i*s+n.FLOAT_MIN;t[r/4]=a}(r);return t},n.decodeMatrixFromUnpackedArray=function(e,t,n){var r=i(e.length,n);if(t.length<r)throw new Error("matrix length ("+t.length+") must be >= "+r);for(var a=0,o=0;o<e.length;o+=n)t[a++]=e[o]},n.decodeMatrixFromUnpackedColorRGBAArray=function(e,t,n){var r=e.length*n/4;if(t.length<r)throw new Error("matrix length ("+t.length+") must be >= "+r);for(var i=0,a=0;a<e.length;a+=4)for(var o=0;o<n;o++)t[i++]=e[a+o]},n.getPackedMatrixTextureShapeWidthHeight=a,n.getPackedRGBAArraySizeFromMatrixShape=o,n.encodeMatrixToPackedRGBA=function(e,t,n,r){var i=o(t,n);if(r.length<i)throw new Error("packedRGBA length ("+r.length+") must be >= "+i);for(var s=a(t,n),u=s[0],l=s[1],c=n%2==1,p=t%2==1,h=Math.floor(n/2),d=Math.floor(t/2),f=c?4:0,g=n,m=0,v=0;v<d;++v){for(var y=2*v*n,b=0;b<h;++b)w=y+2*b,r[m]=e[w],r[m+1]=e[w+1],r[m+2]=e[w+g],r[m+3]=e[w+g+1],m+=4;m+=f}if(c)for(var w=n-1,m=4*(u-1),x=2*n,f=4*u,v=0;v<d;++v)r[m]=e[w],r[m+2]=e[w+n],w+=x,m+=f;if(p)for(var 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h=p[c],i=h.outboundLayer;if(!d.contains(this.inputLayers.map(function(e){return e.id}),i.id)){for(var f=[],m=0;m<h.inboundLayers.length;m++){var v=h.inboundLayers[m],b=h.nodeIndices[m],w=h.tensorIndices[m],x=n[T=v.name+"_"+b+"_"+w];f.push(x)}for(var E=i.computeOutputShape(y.singletonOrArray(f)),_=y.normalizeShapeList(E),A=i.inboundNodes.indexOf(h),m=0;m<_.length;m++)n[T=i.name+"_"+A+"_"+m]=_[m]}}for(var S=[],O=[],r=0;r<this.outputLayers.length;r++){var i=this.outputLayers[r],A=this.outputLayersNodeIndices[r],w=this.outputLayersTensorIndices[r],T=i.name+"_"+A+"_"+w;O.push(T)}for(r=0;r<O.length;r++){var k=O[r];y.assert(k in n),S.push(n[k])}return y.singletonOrArray(S)},t.prototype.runInternalGraph=function(e,t){null==t&&(t=y.pyListRepeat(null,e.length));for(var n={},r=0,i=d.zip(this.inputs,e,t);r<i.length;r++){var a=i[r],o=a[0],s=a[1],u=a[2];n[o.id]=[s,u]}for(var l=0,c=Object.keys(this.nodesByDepth).map(function(e){return parseInt(e,10)}).sort(y.reverseNumberCompare);l<c.length;l++)for(var p=c[l],h=0,f=this.nodesByDepth[p];h<f.length;h++){for(var m=f[h],v=m.outboundLayer,b=m.inputTensors,w=m.outputTensors,x=new Array,E=0,_=b;E<_.length;E++)(o=_[E]).id in n&&x.push(n[o.id]);if(x.length===b.length){var A={},S=void 0,O=void 0,T=void 0,k=void 0;if(null!=m.callArgs&&(A=m.callArgs),1===x.length){var C=x[0],N=C[0],R=C[1];null==A.mask&&(A.mask=R),T=y.toList(v.call(N,A)),k=y.toList(v.computeMask(N,R)),S=[N],O=[R]}else S=x.map(function(e){return e[0]}),O=x.map(function(e){return e[1]}),null==A.mask&&(A.mask=O),T=y.toList(v.call(S,A)),k=y.toList(v.computeMask(S,O));if(v.activityRegularizer)throw new g.NotImplementedError("Model invocation with concrete Tensor value(s) in the presence of activity regularizer(s) is not supported yet.");for(var I=0,z=d.zip(w,T,k);I<z.length;I++){var M=z[I],o=M[0],s=M[1],u=M[2];n[o.id]=[s,u]}}}for(var D=[],L=[],P=[],F=0,V=this.outputs;F<V.length;F++){o=V[F];y.assert(o.id in n,"Could not compute output "+o.name+" : "+o.id);var B=n[o.id],j=B[0],u=B[1];P.push(j.shape),D.push(j),L.push(u)}return[D,L,P]},t.prototype.buildNodeConversionMap=function(e){for(var n,r={},i=0,a=this.layers;i<a.length;i++){var o=a[i];n=o instanceof t?1:0;for(var s=0;s<o.inboundNodes.length;s++){var u=t.nodeKey(o,s);u in this.containerNodes&&(r[u]=n,n+=1)}}return r},t.prototype.getLayer=function(e,t){if(null!=t){if(this.layers.length<=t)throw new g.ValueError("Was asked to retrieve layer at index "+t+", but model only has "+this.layers.length+" layer(s).");return this.layers[t]}if(null==e)throw new g.ValueError("Provide either a layer name or layer index");for(var n=0,r=this.layers;n<r.length;n++){var i=r[n];if(i.name===e)return i}throw new g.ValueError("No such layer: "+e)},t.prototype.calculateLosses=function(){var e=this;return h.tidy(function(){for(var n=[],r=0,i=e.layers;r<i.length;r++)for(var a=i[r],o=0;o<a.inboundNodes.length;++o){var s=t.nodeKey(a,o);e.containerNodes.has(s)&&n.push.apply(n,a.calculateLosses())}return n})},t.prototype.getConfig=function(){for(var e={name:this.name},n=this.buildNodeConversionMap(this.layers),r=[],i=0,a=this.layers;i<a.length;i++){for(var o=(b=a[i]).constructor.name,s=b.getConfig(),u=[],l=0;l<b.inboundNodes.length;l++){var c=b.inboundNodes[l],p=t.nodeKey(b,l),h={};if(this.containerNodes.has(p)&&(c.callArgs&&(-1===JSON.stringify(c.callArgs).indexOf("undefined")?h=c.callArgs:(console.warn("Layer "+b.name+" was passed non-serializable keyword arguments: "+c.callArgs+". They will not be included in the serialized model (and thus will be missing at deserialization time)."),h={})),c.inboundLayers.length>0)){for(var d=[],f=0;f<c.inboundLayers.length;f++){var g=c.inboundLayers[f],m=c.nodeIndices[f],v=c.tensorIndices[f];null!==(x=n[t.nodeKey(g,m)])&&void 0!==x||(x=0),d.push([g.name,x,v,h])}u.push(d)}}r.push({name:b.name,className:o,config:s,inboundNodes:u})}e.layers=r;for(var y=[],f=0;f<this.inputLayers.length;f++){var b=this.inputLayers[f],m=this.inputLayersNodeIndices[f],p=t.nodeKey(b,m);if(this.containerNodes.has(p)){null!==(x=n[p])&&void 0!==x||(x=0);v=this.inputLayersTensorIndices[f];y.push([b.name,x,v])}}e.inputLayers=y;for(var w=[],f=0;f<this.outputLayers.length;f++){var b=this.outputLayers[f],m=this.outputLayersNodeIndices[f],p=t.nodeKey(b,m);if(this.containerNodes.has(p)){var x=n[p];null!==x&&void 0!==x||(x=0);v=this.outputLayersTensorIndices[f];w.push([b.name,x,v])}}return e.outputLayers=w,e},t.fromConfig=function(e,t){function n(e,t){e.name in i?i[e.name].push(t):i[e.name]=[t]}for(var r={},i={},a=t.name,o=t.layers,s=0,u=o;s<u.length;s++)!function(e){var i=e.name,a=m.deserialize(e,null!=t.customObjects?t.customObjects:{});r[i]=a;for(var o=0,s=e.inboundNodes;o<s.length;o++){var u=s[o];if(!(u instanceof Array))throw new g.ValueError("Corrupted configuration, expected array for nodeData: "+u);n(a,u)}}(p=u[s]);for(;!d.isEmpty(i);)for(var l=0,c=o;l<c.length;l++){var p=c[l];if((T=r[p.name]).name in i){for(var h=0,f=i[T.name];h<f.length;h++)!function(e,t){for(var i,a=[],o=0,s=t;o<s.length;o++){var u=s[o],l=u[0],c=u[1],p=u[2];if(3===u.length)i={};else{if(4!==u.length)throw new g.ValueError("Improperly formatted model config for layer "+JSON.stringify(e)+": "+JSON.stringify(u));i=u[3]}if(!(l in r))return void n(e,t);var h=r[l];if(h.inboundNodes.length<=c)return void n(e,t);var f=h.inboundNodes[c];a.push(f.outputTensors[p])}d.isEmpty(a)||e.apply(y.singletonOrArray(a),i)}(T,f[h]);delete i[T.name]}}for(var v=[],b=[],w=0,x=t.inputLayers;w<x.length;w++){var E=(p=x[w])[0],_=p[1],A=p[2];y.assert(E in r);k=(T=r[E]).inboundNodes[_].outputTensors;v.push(k[A])}for(var S=0,O=t.outputLayers;S<O.length;S++){var E=(p=O[S])[0],_=p[1],A=p[2];y.assert(E in r);var T=r[E],k=T.inboundNodes[_].outputTensors;b.push(k[A])}return new e({inputs:v,outputs:b,name:a})},Object.defineProperty(t.prototype,"stateful",{get:function(){if(this._stateful)throw new g.ValueError("Container instance unexpectedly has _stateful = true. 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i.shape[1]>n[1]&&(i=i.slice([0,0],n)),e[0]<e[1]&&(i=i.transpose()),p.scalarTimesArray(p.getScalar(this.gain),i)},t.prototype.getConfig=function(){return{gain:this.gain,seed:this.seed}},t}(v);n.Orthogonal=N,g.ClassNameMap.register("Orthogonal",N),n.INITIALIZER_IDENTIFIER_REGISTRY_SYMBOL_MAP={constant:"Constant",glorotNormal:"GlorotNormal",glorotUniform:"GlorotUniform",heNormal:"HeNormal",identity:"Identity",leCunNormal:"LeCunNormal",ones:"Ones",orthogonal:"Orthogonal",randomNormal:"RandomNormal",randomUniform:"RandomUniform",truncatedNormal:"TruncatedNormal",varianceScaling:"VarianceScaling",zeros:"Zeros"},n.serializeInitializer=function(e){return g.serializeKerasObject(e)},n.getInitializer=function(e){return"string"==typeof e?o({className:e in n.INITIALIZER_IDENTIFIER_REGISTRY_SYMBOL_MAP?n.INITIALIZER_IDENTIFIER_REGISTRY_SYMBOL_MAP[e]:e,config:{}}):e instanceof v?e:o(e)}},{"./backend/tfjs_backend":97,"./common":99,"./errors":104,"./types":125,"./utils/generic_utils":127,"./utils/math_utils":128,"@tensorflow/tfjs-core":8,underscore:140}],108:[function(e,t,n){"use strict";var r=this&&this.__extends||function(){var e=Object.setPrototypeOf||{__proto__:[]}instanceof Array&&function(e,t){e.__proto__=t}||function(e,t){for(var n in t)t.hasOwnProperty(n)&&(e[n]=t[n])};return function(t,n){function r(){this.constructor=t}e(t,n),t.prototype=null===n?Object.create(n):(r.prototype=n.prototype,new r)}}();Object.defineProperty(n,"__esModule",{value:!0});var i=e("@tensorflow/tfjs-core"),a=e("../activations"),o=e("../backend/tfjs_backend"),s=e("../backend/tfjs_backend"),u=e("../engine/topology"),l=e("../errors"),c=e("../types"),p=e("../utils/generic_utils"),h=function(e){function t(t){var n=e.call(this,null==t?{}:t)||this;return n.DEFAULT_ALPHA=.3,null==t&&(t={}),n.alpha=null==t.alpha?n.DEFAULT_ALPHA:t.alpha,n}return r(t,e),t.prototype.call=function(e,t){var n=p.getExactlyOneTensor(e);return i.leakyRelu(n,this.alpha)},t.prototype.computeOutputShape=function(e){return e},t.prototype.getConfig=function(){var t={alpha:this.alpha},n=e.prototype.getConfig.call(this);return Object.assign(t,n),t},t}(u.Layer);n.LeakyReLU=h,p.ClassNameMap.register("LeakyReLU",h);var d=function(e){function t(t){var n=e.call(this,null==t?{}:t)||this;if(n.DEFAULT_ALPHA=1,null==t&&(t={}),null!=t.alpha&&t.alpha!==n.DEFAULT_ALPHA)throw new l.NotImplementedError("Non-default alpha value ("+t.alpha+") is not supported by the ELU layer yet.");return n.alpha=null==t.alpha?n.DEFAULT_ALPHA:t.alpha,n}return r(t,e),t.prototype.call=function(e,t){var n=p.getExactlyOneTensor(e);return i.elu(n)},t.prototype.computeOutputShape=function(e){return e},t.prototype.getConfig=function(){var t={alpha:this.alpha},n=e.prototype.getConfig.call(this);return Object.assign(t,n),t},t}(u.Layer);n.ELU=d,p.ClassNameMap.register("ELU",d);var f=function(e){function t(t){var n=e.call(this,null==t?{}:t)||this;return n.DEFAULT_THETA=1,null==t&&(t={}),n.theta=null==t.theta?n.DEFAULT_THETA:t.theta,n.thetaTensor=s.getScalar(n.theta),n}return r(t,e),t.prototype.call=function(e,t){var n=p.getExactlyOneTensor(e);return n.mul(o.cast(n.greater(this.thetaTensor),c.DType.float32))},t.prototype.computeOutputShape=function(e){return e},t.prototype.getConfig=function(){var t={theta:this.theta},n=e.prototype.getConfig.call(this);return Object.assign(t,n),t},t}(u.Layer);n.ThresholdedReLU=f,p.ClassNameMap.register("ThresholdedReLU",f);var g=function(e){function t(t){var n=e.call(this,null==t?{}:t)||this;return n.DEFAULT_AXIS=1,null==t&&(t={}),n.axis=null==t.theta?n.DEFAULT_AXIS:t.theta,n}return r(t,e),t.prototype.call=function(e,t){var n=p.getExactlyOneTensor(e);return a.softmax(n,this.axis)},t.prototype.computeOutputShape=function(e){return e},t.prototype.getConfig=function(){var t={axis:this.axis},n=e.prototype.getConfig.call(this);return Object.assign(t,n),t},t}(u.Layer);n.Softmax=g,p.ClassNameMap.register("Softmax",g)},{"../activations":95,"../backend/tfjs_backend":97,"../engine/topology":102,"../errors":104,"../types":125,"../utils/generic_utils":127,"@tensorflow/tfjs-core":8}],109:[function(e,t,n){"use strict";var r=this&&this.__extends||function(){var e=Object.setPrototypeOf||{__proto__:[]}instanceof Array&&function(e,t){e.__proto__=t}||function(e,t){for(var n in t)t.hasOwnProperty(n)&&(e[n]=t[n])};return function(t,n){function r(){this.constructor=t}e(t,n),t.prototype=null===n?Object.create(n):(r.prototype=n.prototype,new r)}}();Object.defineProperty(n,"__esModule",{value:!0});var i=e("@tensorflow/tfjs-core"),a=e("../activations"),o=e("../backend/tfjs_backend"),s=e("../common"),u=e("../constraints"),l=e("../engine/topology"),c=e("../errors"),p=e("../initializers"),h=e("../regularizers"),d=e("../types"),f=e("../utils/conv_utils"),g=e("../utils/generic_utils"),m=function(e){function t(t,n){var r=e.call(this,n)||this;if(r.kernel=null,r.bias=null,r.DEFAULT_KERNEL_INITIALIZER="glorotNormal",r.DEFAULT_BIAS_INITIALIZER="zeros",r.rank=t,1!==r.rank&&2!==r.rank)throw new c.NotImplementedError("Convolution layer for rank other than 1 or 2 ("+r.rank+") is not implemented yet.");if(r.filters=n.filters,r.kernelSize=f.normalizeArray(n.kernelSize,t,"kernelSize"),r.strides=f.normalizeArray(null==n.strides?1:n.strides,t,"strides"),r.padding=null==n.padding?"valid":n.padding,s.checkPaddingMode(r.padding),r.dataFormat=null==n.dataFormat?"channelsLast":n.dataFormat,s.checkDataFormat(r.dataFormat),r.dilationRate=null==n.dilationRate?1:n.dilationRate,1===r.rank&&Array.isArray(r.dilationRate))throw new c.ValueError("dilationRate must be a number for 1D convolution, but received "+JSON.stringify(r.dilationRate));if(2===r.rank)if("number"==typeof r.dilationRate)r.dilationRate=[r.dilationRate,r.dilationRate];else if(2!==r.dilationRate.length)throw new c.ValueError("dilationRate must be a number or array of two numbers for 2D convolution, but received "+JSON.stringify(r.dilationRate));return r.activation=a.getActivation(n.activation),r.useBias=null==n.useBias||n.useBias,r.kernelInitializer=p.getInitializer(n.kernelInitializer||r.DEFAULT_KERNEL_INITIALIZER),r.biasInitializer=p.getInitializer(n.biasInitializer||r.DEFAULT_BIAS_INITIALIZER),r.kernelConstraint=u.getConstraint(n.kernelConstraint),r.biasConstraint=u.getConstraint(n.biasConstraint),r.kernelRegularizer=h.getRegularizer(n.kernelRegularizer),r.biasRegularizer=h.getRegularizer(n.biasRegularizer),r.activityRegularizer=h.getRegularizer(n.activityRegularizer),r}return r(t,e),t.prototype.build=function(e){e=g.getExactlyOneShape(e);var t="channelsFirst"===this.dataFormat?1:e.length-1;if(null==e[t])throw new c.ValueError("The channel dimension of the input should be defined. Found "+e[t]);var n=e[t],r=this.kernelSize.concat([n,this.filters]);this.kernel=this.addWeight("kernel",r,null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[{ndim:this.rank+2,axes:(i={},i[t]=n,i)}],this.built=!0;var i},t.prototype.call=function(e,t){e=g.getExactlyOneTensor(e);var n,r=null==this.bias?null:this.bias.read();if(1===this.rank)n=o.conv1dWithBias(e,this.kernel.read(),r,this.strides[0],this.padding,this.dataFormat,this.dilationRate);else if(2===this.rank)n=o.conv2dWithBias(e,this.kernel.read(),r,this.strides,this.padding,this.dataFormat,this.dilationRate);else if(3===this.rank)throw new c.NotImplementedError("3D convolution is not implemented yet.");return null!=this.activation&&(n=this.activation(n)),n},t.prototype.computeOutputShape=function(e){e=g.getExactlyOneShape(e);for(var t=[],n="channelsLast"===this.dataFormat?e.slice(1,e.length-1):e.slice(2),r=0;r<n.length;++r){var i=f.convOutputLength(n[r],this.kernelSize[r],this.padding,this.strides[r],"number"==typeof this.dilationRate?this.dilationRate:this.dilationRate[r]);t.push(i)}var a=[e[0]];return"channelsLast"===this.dataFormat?(a=a.concat(t)).push(this.filters):(a.push(this.filters),a=a.concat(t)),a},t.prototype.getConfig=function(){var t={rank:this.rank,filters:this.filters,kernelSize:this.kernelSize,strides:this.strides,padding:this.padding,dataFormat:this.dataFormat,dilationRate:this.dilationRate,activation:a.serializeActivation(this.activation),useBias:this.useBias,kernelInitializer:p.serializeInitializer(this.kernelInitializer),biasInitializer:p.serializeInitializer(this.biasInitializer),kernelRegularizer:h.serializeRegularizer(this.kernelRegularizer),biasRegularizer:h.serializeRegularizer(this.biasRegularizer),activityRegularizer:h.serializeRegularizer(this.activityRegularizer),kernelConstraint:u.serializeConstraint(this.kernelConstraint),biasConstraint:u.serializeConstraint(this.biasConstraint)},n=e.prototype.getConfig.call(this);return Object.assign(t,n),t},t}(l.Layer);n.Conv=m;var v=function(e){function t(t){return e.call(this,2,t)||this}return r(t,e),t.prototype.getConfig=function(){var t=e.prototype.getConfig.call(this);return delete t.rank,t},t}(m);n.Conv2D=v,g.ClassNameMap.register("Conv2D",v);var y=function(e){function t(t){var n=e.call(this,t)||this;if(n.inputSpec=[new l.InputSpec({ndim:4})],"same"!==n.padding&&"valid"!==n.padding)throw new c.ValueError("Conv2DTranspose currently supports only padding modes 'same' and 'valid', but received padding mode "+n.padding);return n}return r(t,e),t.prototype.build=function(e){if(4!==(e=g.getExactlyOneShape(e)).length)throw new c.ValueError("Input should have rank 4; Received input shape: "+JSON.stringify(e));var t="channelsFirst"===this.dataFormat?1:e.length-1;if(null==e[t])throw new c.ValueError("The channel dimension of the inputs should be defined. Found `None`.");var n=e[t],r=this.kernelSize.concat([this.filters,n]);this.kernel=this.addWeight("kernel",r,d.DType.float32,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],d.DType.float32,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[new l.InputSpec({ndim:4,axes:(i={},i[t]=n,i)})],this.built=!0;var i},t.prototype.call=function(e,t){var n=this;return i.tidy(function(){var t=g.getExactlyOneTensor(e);if(4!==t.shape.length)throw new c.ValueError("Conv2DTranspose.call() expects input tensor to be rank-4, but received a tensor of rank-"+t.shape.length);var r,a,s=t.shape,u=s[0];"channelsFirst"===n.dataFormat?(r=2,a=3):(r=1,a=2);var l=s[r],p=s[a],h=n.kernelSize[0],d=n.kernelSize[1],m=n.strides[0],v=n.strides[1],y=[u,f.deconvLength(l,m,h,n.padding),f.deconvLength(p,v,d,n.padding),n.filters];"channelsLast"!==n.dataFormat&&(t=o.transpose(t,[0,2,3,1]));var b=i.conv2dTranspose(t,n.kernel.read(),y,n.strides,n.padding);return"channelsLast"!==n.dataFormat&&(b=o.transpose(b,[0,3,1,2])),null!=n.bias&&(b=o.biasAdd(b,n.bias.read(),n.dataFormat)),null!=n.activation&&(b=n.activation(b)),b})},t.prototype.computeOutputShape=function(e){var t,n,r,i=(e=g.getExactlyOneShape(e)).slice();"channelsFirst"===this.dataFormat?(t=1,n=2,r=3):(t=3,n=1,r=2);var a=this.kernelSize[0],o=this.kernelSize[1],s=this.strides[0],u=this.strides[1];return i[t]=this.filters,i[n]=f.deconvLength(i[n],s,a,this.padding),i[r]=f.deconvLength(i[r],u,o,this.padding),i},t.prototype.getConfig=function(){var t=e.prototype.getConfig.call(this);return delete t.dilationRate,t},t}(v);n.Conv2DTranspose=y,g.ClassNameMap.register("Conv2DTranspose",y);var b=function(e){function t(t,n){var r=e.call(this,t,n)||this;if(r.DEFAULT_DEPTHWISE_INITIALIZER="glorotUniform",r.DEFAULT_POINTWISE_INITIALIZER="glorotUniform",r.depthwiseKernel=null,r.pointwiseKernel=null,null==n.filters)throw new c.ValueError("The `filters` configuration field is required by SeparableConv, but is unspecified.");if(null!=n.kernelInitializer||null!=n.kernelRegularizer||null!=n.kernelConstraint)throw new c.ValueError("Fields kernelInitializer, kernelRegularizer and kernelConstraint are invalid for SeparableConv2D. Use depthwiseInitializer, depthwiseRegularizer, depthwiseConstraint, pointwiseInitializer, pointwiseRegularizer and pointwiseConstraint instead.");if(null!=n.padding&&"same"!==n.padding&&"valid"!==n.padding)throw new c.ValueError("SeparableConv"+r.rank+"D supports only padding modes: 'same' and 'valid', but received "+JSON.stringify(n.padding));return r.depthMultiplier=null==n.depthMultiplier?1:n.depthMultiplier,r.depthwiseInitializer=p.getInitializer(n.depthwiseInitializer||r.DEFAULT_DEPTHWISE_INITIALIZER),r.depthwiseRegularizer=h.getRegularizer(n.depthwiseRegularizer),r.depthwiseConstraint=u.getConstraint(n.depthwiseConstraint),r.pointwiseInitializer=p.getInitializer(n.depthwiseInitializer||r.DEFAULT_POINTWISE_INITIALIZER),r.pointwiseRegularizer=h.getRegularizer(n.pointwiseRegularizer),r.pointwiseConstraint=u.getConstraint(n.pointwiseConstraint),r}return r(t,e),t.prototype.build=function(e){if((e=g.getExactlyOneShape(e)).length<this.rank+2)throw new c.ValueError("Inputs to SeparableConv"+this.rank+"D should have rank "+(this.rank+2)+", but received input shape: "+JSON.stringify(e));var t="channelsFirst"===this.dataFormat?1:e.length-1;if(null==e[t]||e[t]<0)throw new c.ValueError("The channel dimension of the inputs should be defined, but found "+JSON.stringify(e[t]));for(var n=e[t],r=this.kernelSize.concat([n,this.depthMultiplier]),i=[],a=0;a<this.rank;++a)i.push(1);i.push(n*this.depthMultiplier,this.filters);this.depthwiseKernel=this.addWeight("depthwise_kernel",r,d.DType.float32,this.depthwiseInitializer,this.depthwiseRegularizer,!0,this.depthwiseConstraint),this.pointwiseKernel=this.addWeight("pointwise_kernel",i,d.DType.float32,this.pointwiseInitializer,this.pointwiseRegularizer,!0,this.pointwiseConstraint),this.useBias?this.bias=this.addWeight("bias",[this.filters],d.DType.float32,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint):this.bias=null,this.inputSpec=[new l.InputSpec({ndim:this.rank+2,axes:(o={},o[t]=n,o)})],this.built=!0;var o},t.prototype.call=function(e,t){e=g.getExactlyOneTensor(e);var n;if(1===this.rank)throw new c.NotImplementedError("1D separable convolution is not implemented yet.");return 2===this.rank&&("channelsFirst"===this.dataFormat&&(e=o.transpose(e,[0,2,3,1])),n=i.separableConv2d(e,this.depthwiseKernel.read(),this.pointwiseKernel.read(),this.strides,this.padding,this.dilationRate,"NHWC")),this.useBias&&(n=o.biasAdd(n,this.bias.read(),this.dataFormat)),null!=this.activation&&(n=this.activation(n)),"channelsFirst"===this.dataFormat&&(n=o.transpose(n,[0,3,1,2])),n},t.prototype.getConfig=function(){var t=e.prototype.getConfig.call(this);return delete t.rank,delete t.kernelInitializer,delete t.kernelRegularizer,delete t.kernelConstraint,t.depthwiseInitializer=p.serializeInitializer(this.depthwiseInitializer),t.pointwiseInitializer=p.serializeInitializer(this.pointwiseInitializer),t.depthwiseRegularizer=h.serializeRegularizer(this.depthwiseRegularizer),t.pointwiseRegularizer=h.serializeRegularizer(this.pointwiseRegularizer),t.depthwiseConstraint=u.serializeConstraint(this.depthwiseConstraint),t.pointwiseConstraint=u.serializeConstraint(this.pointwiseConstraint),t},t}(m);n.SeparableConv=b;var w=function(e){function t(t){return e.call(this,2,t)||this}return r(t,e),t}(b);n.SeparableConv2D=w,g.ClassNameMap.register("SeparableConv2D",w);var x=function(e){function t(t){var n=e.call(this,1,t)||this;return n.inputSpec=[{ndim:3}],n}return r(t,e),t.prototype.getConfig=function(){var t=e.prototype.getConfig.call(this);return delete t.rank,delete t.dataFormat,t},t}(m);n.Conv1D=x,g.ClassNameMap.register("Conv1D",x)},{"../activations":95,"../backend/tfjs_backend":97,"../common":99,"../constraints":100,"../engine/topology":102,"../errors":104,"../initializers":107,"../regularizers":124,"../types":125,"../utils/conv_utils":126,"../utils/generic_utils":127,"@tensorflow/tfjs-core":8}],110:[function(e,t,n){"use strict";var r=this&&this.__extends||function(){var e=Object.setPrototypeOf||{__proto__:[]}instanceof Array&&function(e,t){e.__proto__=t}||function(e,t){for(var n in t)t.hasOwnProperty(n)&&(e[n]=t[n])};return function(t,n){function r(){this.constructor=t}e(t,n),t.prototype=null===n?Object.create(n):(r.prototype=n.prototype,new r)}}();Object.defineProperty(n,"__esModule",{value:!0});var i=e("../backend/tfjs_backend"),a=e("../constraints"),o=e("../errors"),s=e("../initializers"),u=e("../regularizers"),l=e("../utils/conv_utils"),c=e("../utils/generic_utils"),p=e("../utils/generic_utils"),h=function(e){function t(t){var n=e.call(this,t)||this;return n.depthwiseKernel=null,n.depthMultiplier=null==t.depthMultiplier?1:t.depthMultiplier,n.depthwiseInitializer=s.getInitializer(t.depthwiseInitializer||n.DEFAULT_KERNEL_INITIALIZER),n.depthwiseConstraint=a.getConstraint(t.depthwiseConstraint),n.depthwiseRegularizer=u.getRegularizer(t.depthwiseRegularizer),n}return r(t,e),t.prototype.build=function(e){if((e=p.getExactlyOneShape(e)).length<4)throw new o.ValueError("Inputs to DepthwiseConv2D should have rank 4. Received input shape: "+JSON.stringify(e)+".");var t="channelsFirst"===this.dataFormat?1:3;if(null==e[t]||e[t]<0)throw new o.ValueError("The channel dimension of the inputs to DepthwiseConv2D should be defined, but is not ("+e[t]+").");var n=e[t],r=[this.kernelSize[0],this.kernelSize[1],n,this.depthMultiplier];this.depthwiseKernel=this.addWeight("depthwise_kernel",r,null,this.depthwiseInitializer,this.depthwiseRegularizer,!0,this.depthwiseConstraint),this.useBias?this.bias=this.addWeight("bias",[n*this.depthMultiplier],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint):this.bias=null,this.built=!0},t.prototype.call=function(e,t){e=p.getExactlyOneTensor(e);var n=i.depthwiseConv2d(e,this.depthwiseKernel.read(),this.strides,this.padding,this.dataFormat,null);return this.useBias&&(n=i.biasAdd(n,this.bias.read(),this.dataFormat)),null!=this.activation&&(n=this.activation(n)),n},t.prototype.computeOutputShape=function(e){e=p.getExactlyOneShape(e);var t="channelsFirst"===this.dataFormat?e[2]:e[1],n="channelsFirst"===this.dataFormat?e[3]:e[2],r="channelsFirst"===this.dataFormat?e[1]*this.depthMultiplier:e[3]*this.depthMultiplier,i=l.convOutputLength(t,this.kernelSize[0],this.padding,this.strides[0]),a=l.convOutputLength(n,this.kernelSize[1],this.padding,this.strides[1]);return"channelsFirst"===this.dataFormat?[e[0],r,i,a]:[e[0],i,a,r]},t}(e("./convolutional").Conv2D);n.DepthwiseConv2D=h,c.ClassNameMap.register("DepthwiseConv2D",h)},{"../backend/tfjs_backend":97,"../constraints":100,"../errors":104,"../initializers":107,"../regularizers":124,"../utils/conv_utils":126,"../utils/generic_utils":127,"./convolutional":109}],111:[function(e,t,n){"use strict";var r=this&&this.__extends||function(){var e=Object.setPrototypeOf||{__proto__:[]}instanceof Array&&function(e,t){e.__proto__=t}||function(e,t){for(var n in t)t.hasOwnProperty(n)&&(e[n]=t[n])};return function(t,n){function r(){this.constructor=t}e(t,n),t.prototype=null===n?Object.create(n):(r.prototype=n.prototype,new r)}}();Object.defineProperty(n,"__esModule",{value:!0});var i=e("underscore"),a=e("../activations"),o=e("../backend/tfjs_backend"),s=e("../constraints"),u=e("../engine/topology"),l=e("../errors"),c=e("../initializers"),p=e("../regularizers"),h=e("../utils/generic_utils"),d=e("../utils/generic_utils"),f=e("../utils/math_utils"),g=function(e){function t(t){var n=e.call(this,t)||this;if(n.rate=Math.max(Math.min(t.rate,1),0),n.rateScalar=o.getScalar(n.rate),n.noiseShape=t.noiseShape,n.seed=t.seed,null!=n.seed)throw new l.NotImplementedError("Non-default seed is not implemented in Dropout layer yet: "+n.seed);return n.supportsMasking=!0,n}return r(t,e),t.prototype.getNoiseShape=function(e){if(null==this.noiseShape)return this.noiseShape;for(var t=e.shape,n=[],r=0;r<this.noiseShape.length;++r)n.push(null==this.noiseShape[r]?t[r]:this.noiseShape[r]);return n},t.prototype.call=function(e,t){var n=this;this.invokeCallHook(e,t);var r=h.getExactlyOneTensor(e);if(null!=this.noiseShape&&!i.isEqual(r.shape,this.noiseShape))throw new l.NotImplementedError("Non-default noise shape is not implemented in Dropout layer yet: "+JSON.stringify(this.noiseShape));if(0<this.rate&&this.rate<1){var a=null!=t.training&&t.training,s=this.getNoiseShape(r);return o.inTrainPhase(function(){return o.dropout(r,n.rateScalar,s,n.seed)},function(){return r},a)}return e},t.prototype.getConfig=function(){var t={rate:this.rate,noiseShape:this.noiseShape,seed:this.seed},n=e.prototype.getConfig.call(this);return Object.assign(t,n),t},t}(u.Layer);n.Dropout=g,h.ClassNameMap.register("Dropout",g);var m=function(e){function t(t){var n=e.call(this,t)||this;if(n.activation=null,n.useBias=!0,n.kernel=null,n.bias=null,n.DEFAULT_KERNEL_INITIALIZER="glorotNormal",n.DEFAULT_BIAS_INITIALIZER="zeros",null==t.batchInputShape&&null==t.inputShape&&null!=t.inputDim){var r=null;null!=t.batchSize&&(r=t.batchSize),n.batchInputShape=[r,t.inputDim]}return n.units=t.units,n.activation=a.getActivation(t.activation),null!=t.useBias&&(n.useBias=t.useBias),n.kernelInitializer=c.getInitializer(t.kernelInitializer||n.DEFAULT_KERNEL_INITIALIZER),n.biasInitializer=c.getInitializer(t.biasInitializer||n.DEFAULT_BIAS_INITIALIZER),n.kernelConstraint=s.getConstraint(t.kernelConstraint),n.biasConstraint=s.getConstraint(t.biasConstraint),n.kernelRegularizer=p.getRegularizer(t.kernelRegularizer),n.biasRegularizer=p.getRegularizer(t.biasRegularizer),n.activityRegularizer=p.getRegularizer(t.activityRegularizer),n.inputSpec=[{minNDim:2}],n}return r(t,e),t.prototype.build=function(e){var t=(e=h.getExactlyOneShape(e))[e.length-1];null==this.kernel&&(this.kernel=this.addWeight("kernel",[t,this.units],null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.units],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint))),this.inputSpec=[{minNDim:2,axes:(n={},n[-1]=t,n)}],this.built=!0;var n},t.prototype.computeOutputShape=function(e){var t=(e=h.getExactlyOneShape(e)).slice();return t[t.length-1]=this.units,t},t.prototype.call=function(e,t){this.invokeCallHook(e,t);var n=h.getExactlyOneTensor(e),r=o.dot(n,this.kernel.read());return null!=this.bias&&(r=o.biasAdd(r,this.bias.read())),null!=this.activation&&(r=this.activation(r)),r},t.prototype.getConfig=function(){var t={units:this.units,activation:a.serializeActivation(this.activation),useBias:this.useBias,kernelInitializer:c.serializeInitializer(this.kernelInitializer),biasInitializer:c.serializeInitializer(this.biasInitializer),kernelRegularizer:p.serializeRegularizer(this.kernelRegularizer),biasRegularizer:p.serializeRegularizer(this.biasRegularizer),activityRegularizer:p.serializeRegularizer(this.activityRegularizer),kernelConstraint:s.serializeConstraint(this.kernelConstraint),biasConstraint:s.serializeConstraint(this.biasConstraint)},n=e.prototype.getConfig.call(this);return Object.assign(t,n),t},t}(u.Layer);n.Dense=m,h.ClassNameMap.register("Dense",m);var v=function(e){function t(t){var n=e.call(this,t||{})||this;return n.inputSpec=[{minNDim:3}],n}return r(t,e),t.prototype.computeOutputShape=function(e){for(var t=0,n=(e=h.getExactlyOneShape(e)).slice(1);t<n.length;t++)if(null==n[t])throw new l.ValueError('The shape of the input to "Flatten" is not fully defined (got '+e.slice(1)+'). Make sure to pass a complete "input_shape" or "batch_input_shape" argument to the first layer in your model.');return[e[0],f.arrayProd(e,1)]},t.prototype.call=function(e,t){return this.invokeCallHook(e,t),o.batchFlatten(h.getExactlyOneTensor(e))},t}(u.Layer);n.Flatten=v,h.ClassNameMap.register("Flatten",v);var y=function(e){function t(t){var n=e.call(this,t)||this;return n.supportsMasking=!0,n.activation=a.getActivation(t.activation),n}return r(t,e),t.prototype.call=function(e,t){this.invokeCallHook(e,t);var n=h.getExactlyOneTensor(e);return this.activation(n)},t}(u.Layer);n.Activation=y,h.ClassNameMap.register("Activation",y);var b=function(e){function t(t){var n=e.call(this,t)||this;return n.n=t.n,n.inputSpec=[{ndim:2}],n}return r(t,e),t.prototype.computeOutputShape=function(e){return[e[0],this.n,e[1]]},t.prototype.call=function(e,t){return e=d.getExactlyOneTensor(e),o.repeat(e,this.n)},t.prototype.getConfig=function(){var t={n:this.n},n=e.prototype.getConfig.call(this);return Object.assign(t,n),t},t}(u.Layer);n.RepeatVector=b,h.ClassNameMap.register("RepeatVector",b);var w=function(e){function t(t){var n=e.call(this,t)||this;n.targetShape=t.targetShape;for(var r=0;r<n.targetShape.length;++r)n.isUnknown(n.targetShape[r])&&(n.targetShape[r]=null);return n}return r(t,e),t.prototype.isUnknown=function(e){return e<0||null==e},t.prototype.fixUnknownDimension=function(e,t){for(var n="Total size of new array must be unchanged.",r=t.slice(),i=1,a=null,o=0;o<r.length;++o){var s=r[o];if(this.isUnknown(s)){if(null!==a)throw new l.ValueError("Can only specifiy one unknown dimension.");a=o}else i*=s}var u=f.arrayProd(e);if(null!==a){if(0===i||u%i!=0)throw new l.ValueError(n);r[a]=u/i}else if(u!==i)throw new l.ValueError(n);return r},t.prototype.computeOutputShape=function(e){for(var t=!1,n=0;n<e.length;++n)if(this.isUnknown(e[n])){t=!0;break}return t?e.slice(0,1).concat(this.targetShape):e.slice(0,1).concat(this.fixUnknownDimension(e.slice(1),this.targetShape))},t.prototype.call=function(e,t){this.invokeCallHook(e,t);var n=h.getExactlyOneTensor(e),r=o.shape(n),i=r.slice(0,1).concat(this.fixUnknownDimension(r.slice(1),this.targetShape));return o.reshape(n,i)},t}(u.Layer);n.Reshape=w,h.ClassNameMap.register("Reshape",w)},{"../activations":95,"../backend/tfjs_backend":97,"../constraints":100,"../engine/topology":102,"../errors":104,"../initializers":107,"../regularizers":124,"../utils/generic_utils":127,"../utils/math_utils":128,underscore:140}],112:[function(e,t,n){"use strict";var r=this&&this.__extends||function(){var e=Object.setPrototypeOf||{__proto__:[]}instanceof Array&&function(e,t){e.__proto__=t}||function(e,t){for(var n in t)t.hasOwnProperty(n)&&(e[n]=t[n])};return function(t,n){function r(){this.constructor=t}e(t,n),t.prototype=null===n?Object.create(n):(r.prototype=n.prototype,new 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r(t,e),t.prototype.build=function(e){this.embeddings=this.addWeight("embeddings",[this.inputDim,this.outputDim],this.dtype,this.embeddingsInitializer,this.embeddingsRegularizer,!0,this.embeddingsConstraint),this.built=!0},t.prototype.computeMask=function(e,t){throw new u.NotImplementedError("computeMask has not been implemented for Embedding yet")},t.prototype.computeOutputShape=function(e){if(e=p.getExactlyOneShape(e),null==this.inputLength)return e.concat([this.outputDim]);var t=p.toList(this.inputLength);if(t.length!==e.length-1)throw new u.ValueError('"inputLength" is '+this.inputLength+", but received input shape has shape "+e);for(var n=0,r=0,a=i.zip(t,e.slice(1));r<a.length;r++){var o=a[r],s=o[0],l=o[1];if(null!=s&&null!=l&&s!==l)throw new u.ValueError('"inputLength" is '+this.inputLength+", but received input shape has shape "+e);null==s&&(t[n]=l),n++}return[e[0]].concat(t,[this.outputDim])},t.prototype.call=function(e,t){this.invokeCallHook(e,t);var n=p.getExactlyOneTensor(e);"int32"!==a.dtype(n)&&(n=a.cast(n,"int32"));var r=a.gather(this.embeddings.read(),n.as1D());return a.reshape(r,h.getExactlyOneShape(this.computeOutputShape(n.shape)))},t.prototype.getConfig=function(){var t={inputDim:this.inputDim,outputDim:this.outputDim,embeddingsInitializer:l.serializeInitializer(this.embeddingsInitializer),embeddingsRegularizer:c.serializeRegularizer(this.embeddingsRegularizer),activityRegularizer:c.serializeRegularizer(this.activityRegularizer),embeddingsConstraint:o.serializeConstraint(this.embeddingsConstraint),maskZero:this.maskZero,inputLength:this.inputLength},n=e.prototype.getConfig.call(this);return Object.assign(t,n),t},t}(s.Layer);n.Embedding=d,p.ClassNameMap.register("Embedding",d)},{"../backend/tfjs_backend":97,"../constraints":100,"../engine/topology":102,"../errors":104,"../initializers":107,"../regularizers":124,"../utils/generic_utils":127,underscore:140}],113:[function(e,t,n){"use strict";var r=this&&this.__extends||function(){var e=Object.setPrototypeOf||{__proto__:[]}instanceof Array&&function(e,t){e.__proto__=t}||function(e,t){for(var n in t)t.hasOwnProperty(n)&&(e[n]=t[n])};return function(t,n){function r(){this.constructor=t}e(t,n),t.prototype=null===n?Object.create(n):(r.prototype=n.prototype,new r)}}();Object.defineProperty(n,"__esModule",{value:!0});var i=e("underscore"),a=e("../backend/tfjs_backend"),o=e("../engine/topology"),s=e("../errors"),u=e("../utils/generic_utils"),l=e("../utils/math_utils"),c=function(e){function t(t){var n=e.call(this,t||{})||this;return n.supportsMasking=!0,n}return r(t,e),t.prototype.mergeFunction=function(e){throw new s.NotImplementedError},t.prototype.computeElementwiseOpOutputShape=function(e,t){if(null==e||null==t)return null;if(e.length<t.length)return this.computeElementwiseOpOutputShape(t,e);if(0===t.length)return e;for(var n=e.slice(0,e.length-t.length),r=0;r<t.length;++r){var i=e[e.length-t.length+r],a=t[r];if(null==i||null==a||i<0||a<0)n.push(null);else if(1===i)n.push(a);else if(1===a)n.push(i);else{if(i!==a)throw new s.ValueError("Operands could not be broadcast together with shapes "+JSON.stringify(e)+" "+JSON.stringify(t));n.push(i)}}return n},t.prototype.build=function(e){if(Array.isArray(e)&&!Array.isArray(e[0])&&(e=[u.getExactlyOneShape(e)]),(e=e).length<2)throw new s.ValueError("A merge layer should be called on an Array of at least 2 inputs. Got "+e.length+" input(s).");for(var t=[],n=0,r=e;n<r.length;n++)null!=(l=r[n])&&null!==l[0]&&t.push(l[0]);if((t=i.uniq(t)).length>1)throw new s.ValueError("Can not merge tensors with different batch sizes. Got tensors with shapes: "+JSON.stringify(e)+".");for(var a=null==e[0]?null:e[0].slice(1),o=1;o<e.length;++o){var l=null==e[o]?null:e[o].slice(1);a=this.computeElementwiseOpOutputShape(a,l)}var c=e.map(function(e){return e.length});i.contains(e,null)||1!==i.uniq(c).length?this.reshapeRequired=!0:this.reshapeRequired=!1},t.prototype.call=function(e,t){if(e=e,this.reshapeRequired){var n=[],r=e.map(function(e){return a.ndim(e)});if(i.contains(r,null)){for(var o=!1,s=0,u=e;s<u.length;s++){x=u[s];if(null==(E=a.ndim(x))){var c=a.shape(x),p=c[0],h=c.slice(1).concat([p]),d=a.reshape(x,[p].concat(l.arrayProd(c.slice(1))));d=a.permuteDimensions(d,[1,0]),d=a.reshape(d,h),n.push(d),o=!0}else if(E>1){v=i.range(1,E).concat([0]);n.push(a.permuteDimensions(x,v)),o=!0}else n.push(x)}var f=this.mergeFunction(n),g=a.ndim(f);if(o)if(null==g){var m=a.shape(f),h=[p=m[m.length-1]].concat(m.slice(0,m.length-1));f=a.reshape(a.permuteDimensions(a.reshape(f,[-1,p]),[1,0]),h)}else if(g>1){var v=[g-1].concat(i.range(0,g-1));f=a.permuteDimensions(f,v)}return f}for(var y=i.max(r),b=0,w=e;b<w.length;b++){for(var x=w[b],E=a.ndim(x),_=0;_<y-E;++_)x=a.expandDims(x,1);n.push(x)}return this.mergeFunction(n)}return this.mergeFunction(e)},t.prototype.computeOutputShape=function(e){var t;t=null==(e=e)[0]?null:e[0].slice(1);for(var n=1;n<e.length;++n){var r=null==e[n]?null:e[n].slice(1);t=this.computeElementwiseOpOutputShape(t,r)}for(var a=[],o=0,s=e;o<s.length;o++)null!=(r=s[o])&&null!==r[0]&&a.push(r[0]);return a=i.uniq(a),t=1===a.length?a.concat(t):[null].concat(t)},t}(o.Layer);n.Merge=c;var p=function(e){function t(t){return e.call(this,t)||this}return r(t,e),t.prototype.mergeFunction=function(e){for(var t=a.zeros(e[0].shape),n=0,r=e;n<r.length;n++){var i=r[n];t=a.add(t,i)}return t},t}(c);n.Add=p,u.ClassNameMap.register("Add",p),n.add=function(e){return Array.isArray(e)?new p({}).apply(e):new p(e)};var h=function(e){function t(t){return e.call(this,t)||this}return r(t,e),t.prototype.mergeFunction=function(e){for(var t=a.ones(e[0].shape),n=0,r=e;n<r.length;n++){var i=r[n];t=a.multiply(t,i)}return t},t}(c);n.Multiply=h,u.ClassNameMap.register("Multiply",h),n.multiply=function(e){return Array.isArray(e)?new h({}).apply(e):new h(e)};var d=function(e){function t(t){return e.call(this,t)||this}return r(t,e),t.prototype.mergeFunction=function(e){for(var t=a.zeros(e[0].shape),n=0,r=e;n<r.length;n++){var i=r[n];t=a.add(t,i)}return a.scalarTimesArray(a.getScalar(1/e.length),t)},t}(c);n.Average=d,u.ClassNameMap.register("Average",d),n.average=function(e){return Array.isArray(e)?new d({}).apply(e):new d(e)};var f=function(e){function t(t){return e.call(this,t)||this}return r(t,e),t.prototype.mergeFunction=function(e){for(var t=e[0],n=1;n<e.length;++n)t=a.maximum(t,e[n]);return t},t}(c);n.Maximum=f,u.ClassNameMap.register("Maximum",f),n.maximum=function(e){return Array.isArray(e)?new f({}).apply(e):new f(e)};var g=function(e){function t(t){return e.call(this,t)||this}return r(t,e),t.prototype.mergeFunction=function(e){for(var t=e[0],n=1;n<e.length;++n)t=a.minimum(t,e[n]);return t},t}(c);n.Minimum=g,u.ClassNameMap.register("Minimum",g),n.minimum=function(e){return Array.isArray(e)?new g({}).apply(e):new g(e)};var m=function(e){function t(t){var n=e.call(this,t)||this;return n.DEFAULT_AXIS=-1,null==t&&(t={}),n.axis=null==t.axis?n.DEFAULT_AXIS:t.axis,n.supportsMasking=!0,n.reshapeRequired=!1,n}return r(t,e),t.prototype.build=function(e){if(!Array.isArray(e)||!Array.isArray(e[0])||1===e.length)throw new s.ValueError("A `Concatenate` layer should be called on a list of at least 2 inputs");for(var t=!0,n=0,r=e=e;n<r.length;n++)if(null!=(h=r[n])){t=!1;break}if(!t){for(var a=[],o=0;o<e.length;++o){var u=e[o].slice();u.splice(this.axis,1);for(var l=!1,c=0,p=a;c<p.length;c++){var h=p[c];if(i.isEqual(h,u)){l=!0;break}}l||a.push(u)}if(a.length>1)throw new s.ValueError("A `Concatenate` layer requires inputs with matching shapes except for the concat axis. Got input shapes: "+JSON.stringify(e))}},t.prototype.mergeFunction=function(e){return a.concatenate(e,this.axis)},t.prototype.computeOutputShape=function(e){if(!Array.isArray(e)||!Array.isArray(e[0]))throw new s.ValueError("A `Concatenate` layer should be called on a list of inputs.");for(var t=e,n=t[0].slice(),r=this.axis<0?n.length+this.axis:this.axis,i=0,a=t.slice(1);i<a.length;i++){var o=a[i];if(null==n[r]||null==o[r]){n[r]=null;break}n[r]+=o[r]}return n},t}(c);n.Concatenate=m,u.ClassNameMap.register("Concatenate",m),n.concatenate=function(e){return Array.isArray(e)?new m({}).apply(e):new m(e)}},{"../backend/tfjs_backend":97,"../engine/topology":102,"../errors":104,"../utils/generic_utils":127,"../utils/math_utils":128,underscore:140}],114:[function(e,t,n){"use strict";var r=this&&this.__extends||function(){var e=Object.setPrototypeOf||{__proto__:[]}instanceof Array&&function(e,t){e.__proto__=t}||function(e,t){for(var n in t)t.hasOwnProperty(n)&&(e[n]=t[n])};return function(t,n){function r(){this.constructor=t}e(t,n),t.prototype=null===n?Object.create(n):(r.prototype=n.prototype,new r)}}();Object.defineProperty(n,"__esModule",{value:!0});var i=e("underscore"),a=e("../backend/tfjs_backend"),o=e("../constraints"),s=e("../engine/topology"),u=e("../errors"),l=e("../initializers"),c=e("../regularizers"),p=e("../utils/generic_utils"),h=function(e){function t(t){var n=e.call(this,t)||this;return n.supportsMasking=!0,n.axis=null==t.axis?-1:t.axis,n.momentum=null==t.momentum?.99:t.momentum,n.epsilon=null==t.epsilon?.001:t.epsilon,n.center=null==t.center||t.center,n.scale=null==t.scale||t.scale,n.betaInitializer=l.getInitializer(t.betaInitializer||"zeros"),n.gammaInitializer=l.getInitializer(t.gammaInitializer||"ones"),n.movingMeanInitializer=l.getInitializer(t.movingMeanInitializer||"zeros"),n.movingVarianceInitializer=l.getInitializer(t.movingVarianceInitializer||"ones"),n.betaConstraint=o.getConstraint(t.betaConstraint),n.gammaConstraint=o.getConstraint(t.gammaConstraint),n.betaRegularizer=c.getRegularizer(t.betaRegularizer),n.gammaRegularizer=c.getRegularizer(t.gammaRegularizer),n}return r(t,e),t.prototype.build=function(e){e=p.getExactlyOneShape(e);var t=this.axis>=0?this.axis:this.axis+e.length,n=e[t];if(null==n)throw new u.ValueError("Axis "+t+" of input tensor should have a defined dimension but the layer received an input with shape "+JSON.stringify(e)+".");this.inputSpec=[new s.InputSpec({ndim:e.length,axes:(i={},i[t]=n,i)})];var r=[n];this.scale&&(this.gamma=this.addWeight("gamma",r,null,this.gammaInitializer,this.gammaRegularizer,!0,this.gammaConstraint)),this.center&&(this.beta=this.addWeight("beta",r,null,this.betaInitializer,this.betaRegularizer,!0,this.betaConstraint)),this.movingMean=this.addWeight("moving_mean",r,null,this.movingMeanInitializer,null,!1),this.movingVariance=this.addWeight("moving_variance",r,null,this.movingVarianceInitializer,null,!1),this.built=!0;var i},t.prototype.call=function(e,t){var n=this,r=null!=t.training&&t.training,o=p.getExactlyOneTensor(e),s=a.shape(o),l=s.length,c=i.range(l),h=this.axis>=0?this.axis:this.axis+l;c.splice(h,1);var d=p.pyListRepeat(1,l);d[h]=s[h];var f=c.slice();f.sort();var g=!i.isEqual(f,i.range(l).slice(0,l-1));if(!r)return function(){if(g){var e=a.reshape(n.movingMean.read(),d),t=a.reshape(n.movingVariance.read(),d),r=n.center?a.reshape(n.beta.read(),d):null,i=n.scale?a.reshape(n.gamma.read(),d):null;return a.batchNormalization(o,e,t,r,i,n.epsilon)}return a.batchNormalization(o,n.movingMean.read(),n.movingVariance.read(),null==n.beta?null:n.beta.read(),null==n.gamma?null:n.gamma.read(),n.epsilon)}();throw new u.NotImplementedError("BatchNormalization.call() has not been implemented for training mode yet.")},t.prototype.getConfig=function(){var t={axis:this.axis,momentum:this.momentum,epsilon:this.epsilon,center:this.center,scale:this.scale,betaInitializer:l.serializeInitializer(this.betaInitializer),gammaInitializer:l.serializeInitializer(this.gammaInitializer),movingMeanInitializer:l.serializeInitializer(this.movingMeanInitializer),movingVarianceInitializer:l.serializeInitializer(this.movingVarianceInitializer),betaRegularizer:c.serializeRegularizer(this.betaRegularizer),gammaRegularizer:c.serializeRegularizer(this.gammaRegularizer),betaConstraint:o.serializeConstraint(this.betaConstraint),gammaConstraint:o.serializeConstraint(this.gammaConstraint)},n=e.prototype.getConfig.call(this);return Object.assign(t,n),t},t}(s.Layer);n.BatchNormalization=h,p.ClassNameMap.register("BatchNormalization",h)},{"../backend/tfjs_backend":97,"../constraints":100,"../engine/topology":102,"../errors":104,"../initializers":107,"../regularizers":124,"../utils/generic_utils":127,underscore:140}],115:[function(e,t,n){"use strict";var r=this&&this.__extends||function(){var e=Object.setPrototypeOf||{__proto__:[]}instanceof Array&&function(e,t){e.__proto__=t}||function(e,t){for(var n in t)t.hasOwnProperty(n)&&(e[n]=t[n])};return function(t,n){function r(){this.constructor=t}e(t,n),t.prototype=null===n?Object.create(n):(r.prototype=n.prototype,new r)}}();Object.defineProperty(n,"__esModule",{value:!0});var i=e("../backend/common"),a=e("../backend/tfjs_backend"),o=e("../engine/topology"),s=e("../errors"),u=e("../utils/generic_utils"),l=function(e){function t(t){var n=this;if(null==t&&(t={}),n=e.call(this,t)||this,n.dataFormat=null==t.dataFormat?i.imageDataFormat():t.dataFormat,null==t.padding)n.padding=[[1,1],[1,1]];else if("number"==typeof t.padding)n.padding=[[t.padding,t.padding],[t.padding,t.padding]];else{if(t.padding=t.padding,2!==t.padding.length)throw new s.ValueError("ZeroPadding2D expects padding to be a length-2 array, but received a length-"+t.padding.length+" array.");var r=void 0,a=void 0;if("number"==typeof t.padding[0])r=[t.padding[0],t.padding[0]],a=[t.padding[1],t.padding[1]];else{if(t.padding=t.padding,2!==t.padding[0].length)throw new s.ValueError("ZeroPadding2D expects height padding to be a length-2 array, but received a length-"+t.padding[0].length+" array.");if(r=t.padding[0],2!==t.padding[1].length)throw new s.ValueError("ZeroPadding2D expects width padding to be a length-2 array, but received a length-"+t.padding[1].length+" array.");a=t.padding[1]}n.padding=[r,a]}return n.inputSpec=[new o.InputSpec({ndim:4})],n}return r(t,e),t.prototype.computeOutputShape=function(e){e=u.getExactlyOneShape(e);var t,n;return"channelsFirst"===this.dataFormat?(t=null!=e[2]&&e[2]>=0?e[2]+this.padding[0][0]+this.padding[0][1]:null,n=null!=e[3]&&e[3]>=0?e[3]+this.padding[1][0]+this.padding[1][1]:null,[e[0],e[1],t,n]):(t=null!=e[1]&&e[1]>=0?e[1]+this.padding[0][0]+this.padding[0][1]:null,n=null!=e[2]&&e[2]>=0?e[2]+this.padding[1][0]+this.padding[1][1]:null,[e[0],t,n,e[3]])},t.prototype.call=function(e,t){return a.spatial2dPadding(u.getExactlyOneTensor(e),this.padding,this.dataFormat)},t.prototype.getConfig=function(){var t={padding:this.padding,dataFormat:this.dataFormat},n=e.prototype.getConfig.call(this);return Object.assign(t,n),t},t}(o.Layer);n.ZeroPadding2D=l,u.ClassNameMap.register("ZeroPadding2D",l)},{"../backend/common":96,"../backend/tfjs_backend":97,"../engine/topology":102,"../errors":104,"../utils/generic_utils":127}],116:[function(e,t,n){"use strict";var r=this&&this.__extends||function(){var e=Object.setPrototypeOf||{__proto__:[]}instanceof Array&&function(e,t){e.__proto__=t}||function(e,t){for(var n in t)t.hasOwnProperty(n)&&(e[n]=t[n])};return function(t,n){function r(){this.constructor=t}e(t,n),t.prototype=null===n?Object.create(n):(r.prototype=n.prototype,new r)}}();Object.defineProperty(n,"__esModule",{value:!0});var i=e("../backend/tfjs_backend"),a=e("../common"),o=e("../engine/topology"),s=e("../engine/topology"),u=e("../errors"),l=e("../utils/conv_utils"),c=e("../utils/generic_utils"),p=function(e){function t(t){var n=this;return null==t.poolSize&&(t.poolSize=2),n=e.call(this,t)||this,n.poolSize=[t.poolSize],n.strides=null==t.strides?n.poolSize:[t.strides],n.padding=null==t.padding?"valid":t.padding,a.checkPaddingMode(n.padding),n.inputSpec=[new o.InputSpec({ndim:3})],n}return r(t,e),t.prototype.computeOutputShape=function(e){return e=c.getExactlyOneShape(e),length=l.convOutputLength(e[1],this.poolSize[0],this.padding,this.strides[0]),[e[0],length,e[2]]},t.prototype.call=function(e,t){this.invokeCallHook(e,t),e=i.expandDims(c.getExactlyOneTensor(e),2);var n=this.poolingFunction(c.getExactlyOneTensor(e),[this.poolSize[0],1],[this.strides[0],1],this.padding,"channelsLast");return i.squeeze(n,2)},t.prototype.getConfig=function(){var t={poolSize:this.poolSize,padding:this.padding,strides:this.strides},n=e.prototype.getConfig.call(this);return Object.assign(t,n),t},t}(s.Layer);n.Pooling1D=p;var h=function(e){function t(t){return e.call(this,t)||this}return r(t,e),t.prototype.poolingFunction=function(e,t,n,r,o){return a.checkDataFormat(o),a.checkPaddingMode(r),i.pool2d(e,t,n,r,o,"max")},t}(p);n.MaxPooling1D=h,c.ClassNameMap.register("MaxPooling1D",h);var d=function(e){function t(t){return e.call(this,t)||this}return r(t,e),t.prototype.poolingFunction=function(e,t,n,r,o){return 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t=l.convOutputLength(t,this.poolSize[0],this.padding,this.strides[0]),n=l.convOutputLength(n,this.poolSize[1],this.padding,this.strides[1]),"channelsFirst"===this.dataFormat?[e[0],e[1],t,n]:[e[0],t,n,e[3]]},t.prototype.call=function(e,t){return this.invokeCallHook(e,t),this.poolingFunction(c.getExactlyOneTensor(e),this.poolSize,this.strides,this.padding,this.dataFormat)},t.prototype.getConfig=function(){var t={poolSize:this.poolSize,padding:this.padding,strides:this.strides,dataFormat:this.dataFormat},n=e.prototype.getConfig.call(this);return Object.assign(t,n),t},t}(s.Layer);n.Pooling2D=f;var g=function(e){function t(t){return e.call(this,t)||this}return r(t,e),t.prototype.poolingFunction=function(e,t,n,r,o){return a.checkDataFormat(o),a.checkPaddingMode(r),i.pool2d(e,t,n,r,o,"max")},t}(f);n.MaxPooling2D=g,c.ClassNameMap.register("MaxPooling2D",g);var m=function(e){function t(t){return e.call(this,t)||this}return r(t,e),t.prototype.poolingFunction=function(e,t,n,r,o){return a.checkDataFormat(o),a.checkPaddingMode(r),i.pool2d(e,t,n,r,o,"avg")},t}(f);n.AveragePooling2D=m,c.ClassNameMap.register("AveragePooling2D",m);var v=function(e){function t(t){var n=e.call(this,t)||this;return n.inputSpec=[new o.InputSpec({ndim:3})],n}return r(t,e),t.prototype.computeOutputShape=function(e){return[e[0],e[2]]},t.prototype.call=function(e,t){throw new u.NotImplementedError},t}(s.Layer);n.GlobalPooling1D=v;var y=function(e){function t(t){return e.call(this,t)||this}return r(t,e),t.prototype.call=function(e,t){var n=c.getExactlyOneTensor(e);return i.mean(n,1)},t}(v);n.GlobalAveragePooling1D=y,c.ClassNameMap.register("GlobalAveragePooling1D",y);var b=function(e){function t(t){return e.call(this,t)||this}return r(t,e),t.prototype.call=function(e,t){var n=c.getExactlyOneTensor(e);return i.max(n,1)},t}(v);n.GlobalMaxPooling1D=b,c.ClassNameMap.register("GlobalMaxPooling1D",b);var w=function(e){function t(t){var n=e.call(this,t)||this;return n.dataFormat=null==t.dataFormat?"channelsLast":t.dataFormat,a.checkDataFormat(n.dataFormat),n.inputSpec=[new o.InputSpec({ndim:4})],n}return r(t,e),t.prototype.computeOutputShape=function(e){return e=e,"channelsLast"===this.dataFormat?[e[0],e[3]]:[e[0],e[1]]},t.prototype.call=function(e,t){throw new u.NotImplementedError},t.prototype.getConfig=function(){var t={dataFormat:this.dataFormat},n=e.prototype.getConfig.call(this);return Object.assign(t,n),t},t}(s.Layer);n.GlobalPooling2D=w;var x=function(e){function t(){return null!==e&&e.apply(this,arguments)||this}return r(t,e),t.prototype.call=function(e,t){var n=c.getExactlyOneTensor(e);return"channelsLast"===this.dataFormat?i.mean(n,[1,2]):i.mean(n,[2,3])},t}(w);n.GlobalAveragePooling2D=x,c.ClassNameMap.register("GlobalAveragePooling2D",x);var E=function(e){function t(){return null!==e&&e.apply(this,arguments)||this}return r(t,e),t.prototype.call=function(e,t){var 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r.cell=n,r.returnSequences=null!=t.returnSequences&&t.returnSequences,r.returnState=null!=t.returnState&&t.returnState,r.goBackwards=null!=t.goBackwards&&t.goBackwards,r._stateful=null!=t.stateful&&t.stateful,r.unroll=null!=t.unroll&&t.unroll,r.supportsMasking=!0,r.inputSpec=[new c.InputSpec({ndim:3})],r.stateSpec=null,r.states=null,r.numConstants=null,r}return r(t,e),t.prototype.getStates=function(){if(null==this.states){var e=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1;return o.range(e).map(function(e){return null})}return this.states},t.prototype.setStates=function(e){this.states=e},t.prototype.computeOutputShape=function(e){m.isArrayOfShapes(e)&&(e=e[0]),e=e;var t=this.cell.stateSize;Array.isArray(t)||(t=[t]);var n,r=t[0];if(n=this.returnSequences?[e[0],e[1],r]:[e[0],r],this.returnState){for(var i=[],a=0,o=t;a<o.length;a++){var s=o[a];i.push([e[0],s])}return[n].concat(i)}return n},t.prototype.computeMask=function(e,t){throw new h.NotImplementedError("computeMask 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Received stateSpec="+this.stateSpec+"; However cell.stateSize is "+this.cell.stateSize)}else this.stateSpec=i.map(function(e){return new c.InputSpec({shape:[null,e]})});if(this.stateful)throw new h.NotImplementedError("stateful RNN layer is not implemented yet")},t.prototype.resetStates=function(e){if(!this.stateful)throw new h.AttributeError("Cannot call resetState() on an RNN Layer that is not stateful.");var t=this.inputSpec[0].shape[0];if(null==t)throw new h.ValueError("If an RNN is stateful, it needs to know its batch size. Specify the batch size of your input tensors: \n- If using a Sequential model, specify the batch size by passing a `batchInputShape` option to your first layer.\n- If using the functional API, specify the batch size by passing a `batchShape` option to your Input layer.");if(null==this.states)Array.isArray(this.cell.stateSize)?this.states=this.cell.stateSize.map(function(e){return u.zeros([t,e])}):this.states=[u.zeros([t,this.cell.stateSize])];else if(null==e)Array.isArray(this.cell.stateSize)?this.states=this.cell.stateSize.map(function(e){return u.zeros([t,e])}):this.states[0]=u.zeros([t,this.cell.stateSize]);else{if(Array.isArray(e)||(e=[e]),e.length!==this.states.length)throw new h.ValueError("Layer "+this.name+" expects "+this.states.length+" state(s), but it received "+e.length+" state value(s). 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o=[],s=[];if(null!=r){n.initialState=r,o=o.concat(r),this.stateSpec=[];for(var u=0,l=r;u<l.length;u++){var p=l[u];this.stateSpec.push(new c.InputSpec({shape:p.shape}))}s=s.concat(this.stateSpec)}if(null!=i&&(n.constants=i,o=o.concat(i),this.numConstants=i.length),o[0]instanceof g.SymbolicTensor){var h=[t].concat(o),d=this.inputSpec.concat(s),f=this.inputSpec;this.inputSpec=d;var m=e.prototype.apply.call(this,h,n);return this.inputSpec=f,m}return e.prototype.apply.call(this,t,n)},t.prototype.call=function(e,t){var n=this,r=null==t?null:t.mask,i=null==t?null:t.training,a=null==t?null:t.initialState;if(e=m.getExactlyOneTensor(e),null==a){if(this.stateful)throw new h.NotImplementedError("stateful RNN layer is not implemented yet.");a=this.getInitialState(e)}if(null!=r)throw new h.NotImplementedError("Masking is not implemented for RNN yet");var o=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1;if(a.length!==o)throw new h.ValueError("RNN Layer has "+o+" state(s) but was 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this.trainable?this.cell.nonTrainableWeights:this.cell.weights},enumerable:!0,configurable:!0}),t.prototype.getConfig=function(){var t={returnSequences:this.returnSequences,returnState:this.returnState,goBackwards:this.goBackwards,stateful:this.stateful,unroll:this.unroll};null!=this.numConstants&&(t.numConstants=this.numConstants);var n=this.cell.getConfig();t.cell={className:this.cell.constructor.name,config:n};var r=e.prototype.getConfig.call(this);return Object.assign(t,r),t},t}(p.Layer);n.RNN=b,m.ClassNameMap.register("RNN",b);var w=function(e){function t(){return null!==e&&e.apply(this,arguments)||this}return r(t,e),t=i([a.doc({heading:"Layers",subheading:"Classes"})],t)}(p.Layer);n.RNNCell=w;var x=function(e){function t(t){var n=e.call(this,t)||this;return n.DEFAULT_ACTIVATION="tanh",n.DEFAULT_KERNEL_INITIALIZER="glorotNormal",n.DEFAULT_RECURRENT_INITIALIZER="orthogonal",n.DEFAULT_BIAS_INITIALIZER="zeros",n.units=t.units,n.activation=s.getActivation(null==t.activation?n.DEFAULT_ACTIVATION:t.activation),n.useBias=null==t.useBias||t.useBias,n.kernelInitializer=d.getInitializer(t.kernelInitializer||n.DEFAULT_KERNEL_INITIALIZER),n.recurrentInitializer=d.getInitializer(t.recurrentInitializer||n.DEFAULT_RECURRENT_INITIALIZER),n.biasInitializer=d.getInitializer(t.biasInitializer||n.DEFAULT_BIAS_INITIALIZER),n.kernelRegularizer=f.getRegularizer(t.kernelRegularizer),n.recurrentRegularizer=f.getRegularizer(t.recurrentRegularizer),n.biasRegularizer=f.getRegularizer(t.biasRegularizer),n.kernelConstraint=l.getConstraint(t.kernelConstraint),n.recurrentConstraint=l.getConstraint(t.recurrentConstraint),n.biasConstraint=l.getConstraint(t.biasConstraint),n.dropout=v.min([1,v.max([0,null==t.dropout?0:t.dropout])]),n.recurrentDropout=v.min([1,v.max([0,null==t.recurrentDropout?0:t.recurrentDropout])]),n.stateSize=n.units,n}return r(t,e),t.prototype.build=function(e){e=m.getExactlyOneShape(e),this.kernel=this.addWeight("kernel",[e[e.length-1],this.units],null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.recurrentKernel=this.addWeight("recurrent_kernel",[this.units,this.units],null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint),this.useBias?this.bias=this.addWeight("bias",[this.units],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint):this.bias=null,this.built=!0},t.prototype.call=function(e,t){if(2!==(e=e).length)throw new h.ValueError("SimpleRNNCell expects 2 input Tensors, got "+e.length+".");var n=e[1];if(e=e[0],0!==this.dropout||0!==this.recurrentDropout)throw new h.NotImplementedError("Dropout is not implemented for SimpleRNNCell yet");var r=u.dot(e,this.kernel.read());null!=this.bias&&(r=u.biasAdd(r,this.bias.read()));var i=u.add(r,u.dot(n,this.recurrentKernel.read()));return null!=this.activation&&(i=this.activation(i)),[i,i]},t.prototype.getConfig=function(){var t={units:this.units,activation:s.serializeActivation(this.activation),useBias:this.useBias,kernelInitializer:d.serializeInitializer(this.kernelInitializer),recurrentInitializer:d.serializeInitializer(this.recurrentInitializer),biasInitializer:d.serializeInitializer(this.biasInitializer),kernelRegularizer:f.serializeRegularizer(this.kernelRegularizer),recurrentRegularizer:f.serializeRegularizer(this.recurrentRegularizer),biasRegularizer:f.serializeRegularizer(this.biasRegularizer),activityRegularizer:f.serializeRegularizer(this.activityRegularizer),kernelConstraint:l.serializeConstraint(this.kernelConstraint),recurrentConstraint:l.serializeConstraint(this.recurrentConstraint),biasConstraint:l.serializeConstraint(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout},n=e.prototype.getConfig.call(this);return Object.assign(t,n),t},t}(w);n.SimpleRNNCell=x,m.ClassNameMap.register("SimpleRNNCell",x);var E=function(e){function t(t){return t.cell=new x(t),e.call(this,t)||this}return r(t,e),t.prototype.call=function(t,n){var r=null==n?null:n.mask,i=null==n?null:n.training,a=null==n?null:n.initialState;return e.prototype.call.call(this,t,{mask:r,training:i,initialState:a})},Object.defineProperty(t.prototype,"units",{get:function(){return this.cell.units},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"activation",{get:function(){return this.cell.activation},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"useBias",{get:function(){return this.cell.useBias},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"kernelInitializer",{get:function(){return this.cell.kernelInitializer},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"recurrentInitializer",{get:function(){return this.cell.recurrentInitializer},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"biasInitializer",{get:function(){return this.cell.biasInitializer},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"kernelRegularizer",{get:function(){return this.cell.kernelRegularizer},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"recurrentRegularizer",{get:function(){return this.cell.recurrentRegularizer},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"biasRegularizer",{get:function(){return this.cell.biasRegularizer},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"kernelConstraint",{get:function(){return this.cell.kernelConstraint},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"recurrentConstraint",{get:function(){return this.cell.recurrentConstraint},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"biasConstraint",{get:function(){return this.cell.biasConstraint},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"dropout",{get:function(){return this.cell.dropout},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"recurrentDropout",{get:function(){return this.cell.recurrentDropout},enumerable:!0,configurable:!0}),t.prototype.getConfig=function(){var t={units:this.units,activation:s.serializeActivation(this.activation),useBias:this.useBias,kernelInitializer:d.serializeInitializer(this.kernelInitializer),recurrentInitializer:d.serializeInitializer(this.recurrentInitializer),biasInitializer:d.serializeInitializer(this.biasInitializer),kernelRegularizer:f.serializeRegularizer(this.kernelRegularizer),recurrentRegularizer:f.serializeRegularizer(this.recurrentRegularizer),biasRegularizer:f.serializeRegularizer(this.biasRegularizer),activityRegularizer:f.serializeRegularizer(this.activityRegularizer),kernelConstraint:l.serializeConstraint(this.kernelConstraint),recurrentConstraint:l.serializeConstraint(this.recurrentConstraint),biasConstraint:l.serializeConstraint(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout},n=e.prototype.getConfig.call(this);return Object.assign(t,n),t},t}(b);n.SimpleRNN=E,m.ClassNameMap.register("SimpleRNN",E);var _=function(e){function t(t){var n=e.call(this,t)||this;return n.DEFAULT_ACTIVATION="tanh",n.DEFAULT_RECURRENT_ACTIVATION="hardSigmoid",n.DEFAULT_KERNEL_INITIALIZER="glorotNormal",n.DEFAULT_RECURRENT_INITIALIZER="orthogonal",n.DEFAULT_BIAS_INITIALIZER="zeros",n.units=t.units,n.activation=s.getActivation(void 0===t.activation?n.DEFAULT_ACTIVATION:t.activation),n.recurrentActivation=s.getActivation(void 0===t.activation?n.DEFAULT_RECURRENT_ACTIVATION:t.recurrentActivation),n.useBias=null==t.useBias||t.useBias,n.kernelInitializer=d.getInitializer(t.kernelInitializer||n.DEFAULT_KERNEL_INITIALIZER),n.recurrentInitializer=d.getInitializer(t.recurrentInitializer||n.DEFAULT_RECURRENT_INITIALIZER),n.biasInitializer=d.getInitializer(t.biasInitializer||n.DEFAULT_BIAS_INITIALIZER),n.kernelRegularizer=f.getRegularizer(t.kernelRegularizer),n.recurrentRegularizer=f.getRegularizer(t.recurrentRegularizer),n.biasRegularizer=f.getRegularizer(t.biasRegularizer),n.kernelConstraint=l.getConstraint(t.kernelConstraint),n.recurrentConstraint=l.getConstraint(t.recurrentConstraint),n.biasConstraint=l.getConstraint(t.biasConstraint),n.dropout=v.min([1,v.max([0,null==t.dropout?0:t.dropout])]),n.recurrentDropout=v.min([1,v.max([0,null==t.recurrentDropout?0:t.recurrentDropout])]),n.implementation=t.implementation,n.stateSize=n.units,n}return r(t,e),t.prototype.build=function(e){var t=(e=m.getExactlyOneShape(e))[e.length-1];this.kernel=this.addWeight("kernel",[t,3*this.units],null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.recurrentKernel=this.addWeight("recurrent_kernel",[this.units,3*this.units],null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint),this.useBias?this.bias=this.addWeight("bias",[3*this.units],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint):this.bias=null,this.built=!0},t.prototype.call=function(e,t){if(0!==this.dropout||0!==this.recurrentDropout)throw new h.NotImplementedError("Dropout is not implemented for GRUCell yet");if(2!==(e=e).length)throw new h.ValueError("GRUCell expects 2 input Tensors (inputs, h, c), got "+e.length+".");var n=e[1];e=e[0];var r,i,a;if(1===this.implementation){var o=u.sliceAlongLastAxis(this.kernel.read(),0,this.units),s=u.sliceAlongLastAxis(this.kernel.read(),this.units,this.units),l=u.sliceAlongLastAxis(this.kernel.read(),2*this.units,this.units),c=u.sliceAlongLastAxis(this.recurrentKernel.read(),0,this.units),p=u.sliceAlongLastAxis(this.recurrentKernel.read(),this.units,this.units),d=u.sliceAlongLastAxis(this.recurrentKernel.read(),2*this.units,this.units),f=e,g=e,m=e,v=u.dot(f,o),y=u.dot(g,s),b=u.dot(m,l);if(this.useBias){var w=u.sliceAlongFirstAxis(this.bias.read(),0,this.units),x=u.sliceAlongFirstAxis(this.bias.read(),this.units,this.units),E=u.sliceAlongFirstAxis(this.bias.read(),2*this.units,this.units);v=u.biasAdd(v,w),y=u.biasAdd(y,x),b=u.biasAdd(b,E)}var _=n,A=n,S=n;r=this.recurrentActivation(u.add(v,u.dot(_,c))),i=this.recurrentActivation(u.add(y,u.dot(A,p))),a=this.activation(u.add(b,u.dot(u.multiply(i,S),d)))}else{var O=u.dot(e,this.kernel.read());this.useBias&&(O=u.biasAdd(O,this.bias.read()));var T=u.dot(n,u.sliceAlongLastAxis(this.recurrentKernel.read(),0,2*this.units)),v=u.sliceAlongLastAxis(O,0,this.units),y=u.sliceAlongLastAxis(O,this.units,this.units),k=u.sliceAlongLastAxis(T,0,this.units),C=u.sliceAlongLastAxis(T,this.units,this.units);r=this.recurrentActivation(u.add(v,k)),i=this.recurrentActivation(u.add(y,C));var b=u.sliceAlongLastAxis(O,2*this.units,this.units),N=u.dot(u.multiply(i,n),u.sliceAlongLastAxis(this.recurrentKernel.read(),2*this.units,this.units));a=this.activation(u.add(b,N))}var R=u.add(u.multiply(r,n),u.multiply(u.scalarPlusArray(u.getScalar(1),u.neg(r)),a));return[R,R]},t.prototype.getConfig=function(){var t={units:this.units,activation:s.serializeActivation(this.activation),useBias:this.useBias,kernelInitializer:d.serializeInitializer(this.kernelInitializer),recurrentInitializer:d.serializeInitializer(this.recurrentInitializer),biasInitializer:d.serializeInitializer(this.biasInitializer),kernelRegularizer:f.serializeRegularizer(this.kernelRegularizer),recurrentRegularizer:f.serializeRegularizer(this.recurrentRegularizer),biasRegularizer:f.serializeRegularizer(this.biasRegularizer),activityRegularizer:f.serializeRegularizer(this.activityRegularizer),kernelConstraint:l.serializeConstraint(this.kernelConstraint),recurrentConstraint:l.serializeConstraint(this.recurrentConstraint),biasConstraint:l.serializeConstraint(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation},n=e.prototype.getConfig.call(this);return Object.assign(t,n),t},t}(w);n.GRUCell=_,m.ClassNameMap.register("GRUCell",_);var A=function(e){function t(t){return 0===t.implementation&&console.warn("`implementation=0` has been deprecated, and now defaults to `implementation=1`. Please update your layer call."),t.cell=new _(t),e.call(this,t)||this}return r(t,e),t.prototype.call=function(t,n){var r=null==n?null:n.mask,i=null==n?null:n.training,a=null==n?null:n.initialState;return e.prototype.call.call(this,t,{mask:r,training:i,initialState:a})},Object.defineProperty(t.prototype,"units",{get:function(){return this.cell.units},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"activation",{get:function(){return this.cell.activation},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"useBias",{get:function(){return this.cell.useBias},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"kernelInitializer",{get:function(){return this.cell.kernelInitializer},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"recurrentInitializer",{get:function(){return this.cell.recurrentInitializer},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"biasInitializer",{get:function(){return this.cell.biasInitializer},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"kernelRegularizer",{get:function(){return this.cell.kernelRegularizer},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"recurrentRegularizer",{get:function(){return this.cell.recurrentRegularizer},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"biasRegularizer",{get:function(){return this.cell.biasRegularizer},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"kernelConstraint",{get:function(){return this.cell.kernelConstraint},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"recurrentConstraint",{get:function(){return this.cell.recurrentConstraint},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"biasConstraint",{get:function(){return this.cell.biasConstraint},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"dropout",{get:function(){return this.cell.dropout},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"recurrentDropout",{get:function(){return this.cell.recurrentDropout},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"implementation",{get:function(){return this.cell.implementation},enumerable:!0,configurable:!0}),t.prototype.getConfig=function(){var t={units:this.units,activation:s.serializeActivation(this.activation),useBias:this.useBias,kernelInitializer:d.serializeInitializer(this.kernelInitializer),recurrentInitializer:d.serializeInitializer(this.recurrentInitializer),biasInitializer:d.serializeInitializer(this.biasInitializer),kernelRegularizer:f.serializeRegularizer(this.kernelRegularizer),recurrentRegularizer:f.serializeRegularizer(this.recurrentRegularizer),biasRegularizer:f.serializeRegularizer(this.biasRegularizer),activityRegularizer:f.serializeRegularizer(this.activityRegularizer),kernelConstraint:l.serializeConstraint(this.kernelConstraint),recurrentConstraint:l.serializeConstraint(this.recurrentConstraint),biasConstraint:l.serializeConstraint(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation},n=e.prototype.getConfig.call(this);return Object.assign(t,n),t},t.fromConfig=function(e,t){return 0===t.implmentation&&(t.implementation=1),new e(t)},t}(b);n.GRU=A,m.ClassNameMap.register("GRU",A);var S=function(e){function t(t){var n=e.call(this,t)||this;return n.DEFAULT_ACTIVATION="tanh",n.DEFAULT_RECURRENT_ACTIVATION="hardSigmoid",n.DEFAULT_KERNEL_INITIALIZER="glorotNormal",n.DEFAULT_RECURRENT_INITIALIZER="orthogonal",n.DEFAULT_BIAS_INITIALIZER="zeros",n.units=t.units,n.activation=s.getActivation(void 0===t.activation?n.DEFAULT_ACTIVATION:t.activation),n.recurrentActivation=s.getActivation(void 0===t.activation?n.DEFAULT_RECURRENT_ACTIVATION:t.recurrentActivation),n.useBias=null==t.useBias||t.useBias,n.kernelInitializer=d.getInitializer(t.kernelInitializer||n.DEFAULT_KERNEL_INITIALIZER),n.recurrentInitializer=d.getInitializer(t.recurrentInitializer||n.DEFAULT_RECURRENT_INITIALIZER),n.biasInitializer=d.getInitializer(t.biasInitializer||n.DEFAULT_BIAS_INITIALIZER),n.unitForgetBias=t.unitForgetBias,n.kernelRegularizer=f.getRegularizer(t.kernelRegularizer),n.recurrentRegularizer=f.getRegularizer(t.recurrentRegularizer),n.biasRegularizer=f.getRegularizer(t.biasRegularizer),n.kernelConstraint=l.getConstraint(t.kernelConstraint),n.recurrentConstraint=l.getConstraint(t.recurrentConstraint),n.biasConstraint=l.getConstraint(t.biasConstraint),n.dropout=v.min([1,v.max([0,null==t.dropout?0:t.dropout])]),n.recurrentDropout=v.min([1,v.max([0,null==t.recurrentDropout?0:t.recurrentDropout])]),n.implementation=t.implementation,n.stateSize=[n.units,n.units],n}return r(t,e),t.prototype.build=function(e){var t=(e=m.getExactlyOneShape(e))[e.length-1];this.kernel=this.addWeight("kernel",[t,4*this.units],null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.recurrentKernel=this.addWeight("recurrent_kernel",[this.units,4*this.units],null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint);var n;if(this.useBias){if(this.unitForgetBias){var i=this.biasInitializer,a=this.units;n=new(function(e){function t(){return null!==e&&e.apply(this,arguments)||this}return r(t,e),t.prototype.apply=function(e,t){var n=i.apply([a]),r=(new d.Ones).apply([a]),o=i.apply([2*a]);return u.concatAlongFirstAxis(u.concatAlongFirstAxis(n,r),o)},t}(d.Initializer))}else n=this.biasInitializer;this.bias=this.addWeight("bias",[4*this.units],null,n,this.biasRegularizer,!0,this.biasConstraint)}else this.bias=null;this.built=!0},t.prototype.call=function(e,t){if(0!==this.dropout||0!==this.recurrentDropout)throw new h.NotImplementedError("Dropout is not implemented for LSTMCell yet");if(3!==(e=e).length)throw new h.ValueError("LSTMCell expects 3 input Tensors (inputs, h, c), got "+e.length+".");var n=e[1],r=e[2];e=e[0];var i,a,o,s;if(1===this.implementation){var l=u.sliceAlongLastAxis(this.kernel.read(),0,this.units),c=u.sliceAlongLastAxis(this.kernel.read(),this.units,this.units),p=u.sliceAlongLastAxis(this.kernel.read(),2*this.units,this.units),d=u.sliceAlongLastAxis(this.kernel.read(),3*this.units,this.units),f=u.sliceAlongLastAxis(this.recurrentKernel.read(),0,this.units),g=u.sliceAlongLastAxis(this.recurrentKernel.read(),this.units,this.units),m=u.sliceAlongLastAxis(this.recurrentKernel.read(),2*this.units,this.units),v=u.sliceAlongLastAxis(this.recurrentKernel.read(),3*this.units,this.units),y=e,b=e,w=e,x=e,E=u.dot(y,l),_=u.dot(b,c),A=u.dot(w,p),S=u.dot(x,d);if(this.useBias){var O=u.sliceAlongFirstAxis(this.bias.read(),0,this.units),T=u.sliceAlongFirstAxis(this.bias.read(),this.units,this.units),k=u.sliceAlongFirstAxis(this.bias.read(),2*this.units,this.units),C=u.sliceAlongFirstAxis(this.bias.read(),3*this.units,this.units);E=u.biasAdd(E,O),_=u.biasAdd(_,T),A=u.biasAdd(A,k),S=u.biasAdd(S,C)}var N=n,R=n,I=n,z=n;i=this.recurrentActivation(u.add(E,u.dot(N,f))),a=this.recurrentActivation(u.add(_,u.dot(R,g))),o=u.add(u.multiply(a,r),u.multiply(i,this.activation(u.add(A,u.dot(I,m))))),s=this.recurrentActivation(u.add(S,u.dot(z,v)))}else{var M=u.dot(e,this.kernel.read());M=u.add(M,u.dot(n,this.recurrentKernel.read())),this.useBias&&(M=u.biasAdd(M,this.bias.read()));var D=u.sliceAlongLastAxis(M,0,this.units),L=u.sliceAlongLastAxis(M,this.units,this.units),P=u.sliceAlongLastAxis(M,2*this.units,this.units),F=u.sliceAlongLastAxis(M,3*this.units,this.units);i=this.recurrentActivation(D),a=this.recurrentActivation(L),o=u.add(u.multiply(a,r),u.multiply(i,this.activation(P))),s=this.recurrentActivation(F)}var V=u.multiply(s,this.activation(o));return[V,V,o]},t.prototype.getConfig=function(){var t={units:this.units,activation:s.serializeActivation(this.activation),useBias:this.useBias,kernelInitializer:d.serializeInitializer(this.kernelInitializer),recurrentInitializer:d.serializeInitializer(this.recurrentInitializer),biasInitializer:d.serializeInitializer(this.biasInitializer),unitForgetBias:this.unitForgetBias,kernelRegularizer:f.serializeRegularizer(this.kernelRegularizer),recurrentRegularizer:f.serializeRegularizer(this.recurrentRegularizer),biasRegularizer:f.serializeRegularizer(this.biasRegularizer),activityRegularizer:f.serializeRegularizer(this.activityRegularizer),kernelConstraint:l.serializeConstraint(this.kernelConstraint),recurrentConstraint:l.serializeConstraint(this.recurrentConstraint),biasConstraint:l.serializeConstraint(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation},n=e.prototype.getConfig.call(this);return Object.assign(t,n),t},t}(w);n.LSTMCell=S,m.ClassNameMap.register("LSTMCell",S);var O=function(e){function t(t){return 0===t.implementation&&console.warn("`implementation=0` has been deprecated, and now defaults to `implementation=1`. Please update your layer call."),t.cell=new S(t),e.call(this,t)||this}return r(t,e),t.prototype.call=function(t,n){var r=null==n?null:n.mask,i=null==n?null:n.training,a=null==n?null:n.initialState;return e.prototype.call.call(this,t,{mask:r,training:i,initialState:a})},Object.defineProperty(t.prototype,"units",{get:function(){return this.cell.units},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"activation",{get:function(){return this.cell.activation},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"useBias",{get:function(){return this.cell.useBias},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"kernelInitializer",{get:function(){return this.cell.kernelInitializer},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"recurrentInitializer",{get:function(){return this.cell.recurrentInitializer},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"biasInitializer",{get:function(){return this.cell.biasInitializer},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"unitForgetBias",{get:function(){return this.cell.unitForgetBias},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"kernelRegularizer",{get:function(){return this.cell.kernelRegularizer},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"recurrentRegularizer",{get:function(){return this.cell.recurrentRegularizer},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"biasRegularizer",{get:function(){return this.cell.biasRegularizer},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"kernelConstraint",{get:function(){return this.cell.kernelConstraint},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"recurrentConstraint",{get:function(){return this.cell.recurrentConstraint},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"biasConstraint",{get:function(){return this.cell.biasConstraint},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"dropout",{get:function(){return this.cell.dropout},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"recurrentDropout",{get:function(){return this.cell.recurrentDropout},enumerable:!0,configurable:!0}),Object.defineProperty(t.prototype,"implementation",{get:function(){return this.cell.implementation},enumerable:!0,configurable:!0}),t.prototype.getConfig=function(){var t={units:this.units,activation:s.serializeActivation(this.activation),useBias:this.useBias,kernelInitializer:d.serializeInitializer(this.kernelInitializer),recurrentInitializer:d.serializeInitializer(this.recurrentInitializer),biasInitializer:d.serializeInitializer(this.biasInitializer),unitForgetBias:this.unitForgetBias,kernelRegularizer:f.serializeRegularizer(this.kernelRegularizer),recurrentRegularizer:f.serializeRegularizer(this.recurrentRegularizer),biasRegularizer:f.serializeRegularizer(this.biasRegularizer),activityRegularizer:f.serializeRegularizer(this.activityRegularizer),kernelConstraint:l.serializeConstraint(this.kernelConstraint),recurrentConstraint:l.serializeConstraint(this.recurrentConstraint),biasConstraint:l.serializeConstraint(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation},n=e.prototype.getConfig.call(this);return Object.assign(t,n),t},t.fromConfig=function(e,t){return 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